def main():
"""
NAME
pmag_results_extract.py
DESCRIPTION
make a tab delimited output file from pmag_results table
SYNTAX
pmag_results_extract.py [command line options]
OPTIONS
-h prints help message and quits
-f RFILE, specify pmag_results table; default is pmag_results.txt
-fa AFILE, specify er_ages table; default is NONE
-fsp SFILE, specify pmag_specimens table, default is NONE
-fcr CFILE, specify pmag_criteria table, default is NONE
-g include specimen_grade in table - only works for PmagPy generated pmag_specimen formatted files.
-tex, output in LaTeX format
"""
do_help = pmag.get_flag_arg_from_sys('-h')
if do_help:
print(main.__doc__)
return False
res_file = pmag.get_named_arg_from_sys('-f', 'pmag_results.txt')
crit_file = pmag.get_named_arg_from_sys('-fcr', '')
spec_file = pmag.get_named_arg_from_sys('-fsp', '')
age_file = pmag.get_named_arg_from_sys('-fa', '')
grade = pmag.get_flag_arg_from_sys('-g')
latex = pmag.get_flag_arg_from_sys('-tex')
WD = pmag.get_named_arg_from_sys('-WD', os.getcwd())
ipmag.pmag_results_extract(res_file, crit_file, spec_file, age_file, latex, grade, WD)
def main():
"""
NAME
pmag_results_extract.py
DESCRIPTION
make a tab delimited output file from pmag_results table
SYNTAX
pmag_results_extract.py [command line options]
OPTIONS
-h prints help message and quits
-f RFILE, specify pmag_results table; default is pmag_results.txt
-fa AFILE, specify er_ages table; default is NONE
-fsp SFILE, specify pmag_specimens table, default is NONE
-fcr CFILE, specify pmag_criteria table, default is NONE
-g include specimen_grade in table - only works for PmagPy generated pmag_specimen formatted files.
-tex, output in LaTeX format
"""
do_help = pmag.get_flag_arg_from_sys('-h')
if do_help:
print main.__doc__
return False
res_file = pmag.get_named_arg_from_sys('-f', 'pmag_results.txt')
crit_file = pmag.get_named_arg_from_sys('-fcr', '')
spec_file = pmag.get_named_arg_from_sys('-fsp', '')
age_file = pmag.get_named_arg_from_sys('-fa', '')
grade = pmag.get_flag_arg_from_sys('-g')
latex = pmag.get_flag_arg_from_sys('-tex')
WD = pmag.get_named_arg_from_sys('-WD', os.getcwd())
ipmag.pmag_results_extract(res_file, crit_file, spec_file, age_file, latex,
grade, WD)
def __init__(self, WD=None, DM=None, dmodel=None):
"""
Input working directory, data model number (2.5 or 3),
and data model (optional).
"""
wx.Frame.__init__(self,
None,
wx.ID_ANY,
self.title,
name='pmag_gui mainframe')
#set icon
self.icon = wx.Icon()
icon_path = os.path.join(PMAGPY_DIRECTORY, 'programs', 'images',
'PmagPy.ico')
if os.path.isfile(icon_path):
self.icon.CopyFromBitmap(wx.Bitmap(icon_path, wx.BITMAP_TYPE_ANY))
self.SetIcon(self.icon)
else:
print("-I- PmagPy icon file not found -- skipping")
# if DM was provided:
if DM:
self.data_model_num = int(float(DM))
# try to get DM from command line args
if not DM:
self.data_model_num = int(
float(pmag.get_named_arg_from_sys("-DM", 0)))
DM = self.data_model_num
# if WD was provided:
if WD:
self.WD = WD
else:
WD = pmag.get_named_arg_from_sys("-WD", '')
self.WD = WD
self.data_model = dmodel
self.FIRST_RUN = True
self.panel = wx.Panel(self, name='pmag_gui main panel')
self.InitUI()
if WD and DM:
self.set_dm(self.data_model_num)
if WD:
self.dir_path.SetValue(self.WD)
# for use as module:
self.resource_dir = os.getcwd()
# set some things
self.HtmlIsOpen = False
self.Bind(wx.EVT_CLOSE, self.on_menu_exit)
# if not specified on the command line,
# make the user choose data model num (2 or 3)
# and working directory
wx.CallAfter(self.get_dm_and_wd, DM, WD)
def __init__(self, WD=None, DM=None, dmodel=None):
"""
Input working directory, data model number (2.5 or 3),
and data model (optional).
"""
wx.Frame.__init__(self, None, wx.ID_ANY, self.title, name='pmag_gui mainframe')
#set icon
self.icon = wx.Icon()
icon_path = os.path.join(PMAGPY_DIRECTORY, 'programs', 'images', 'PmagPy.ico')
if os.path.isfile(icon_path):
self.icon.CopyFromBitmap(wx.Bitmap(icon_path, wx.BITMAP_TYPE_ANY))
self.SetIcon(self.icon)
else:
print("-I- PmagPy icon file not found -- skipping")
# if DM was provided:
if DM:
self.data_model_num = int(float(DM))
# try to get DM from command line args
if not DM:
self.data_model_num = int(float(pmag.get_named_arg_from_sys("-DM", 0)))
DM = self.data_model_num
# if WD was provided:
if WD:
self.WD = WD
else:
WD = pmag.get_named_arg_from_sys("-WD", '')
self.WD = WD
self.WD = os.path.realpath(self.WD)
self.data_model = dmodel
self.FIRST_RUN = True
self.panel = wx.Panel(self, name='pmag_gui main panel')
self.InitUI()
if WD and DM:
self.set_dm(self.data_model_num)
if WD:
self.dir_path.SetValue(self.WD)
# for use as module:
self.resource_dir = os.getcwd()
# set some things
self.HtmlIsOpen = False
self.Bind(wx.EVT_CLOSE, self.on_menu_exit)
# if not specified on the command line,
# make the user choose data model num (2 or 3)
# and working directory
wx.CallAfter(self.get_dm_and_wd, DM, WD)
def main():
try:
from mpl_toolkits.basemap import basemap_datadir
except:
print "-E- Could not import the basemap module..."
else:
# allow user to specify what directory to find the data_files in
custom_dir = pmag.get_named_arg_from_sys('-source-dir', default_val="")
if os.path.isdir(custom_dir):
data_dir = custom_dir
# if user didn't specify a directory, find the etopo20 directory
else:
# if installed by pip, etopo20 is in sys.prefix
pip_data_dir = os.path.join(sys.prefix, 'data_files', 'etopo20')
if os.path.isdir(pip_data_dir):
data_dir = pip_data_dir
else:
# if not installed by pip, etopo20 is in the local PmagPy directory
from pmagpy import find_pmag_dir
pmag_dir = find_pmag_dir.get_pmag_dir()
data_dir = os.path.join(pmag_dir, 'data_files', 'etopo20')
# if none of those options worked, warn the user:
if not os.path.isdir(data_dir):
print "-W- Could not find data_files to copy in {}".format(
data_dir)
print "-I- You can run this program with the command line flag -source-dir to specify the location of the etopo20 directory."
print "-I- For example: 'install_etopo.py -source-dir ~/Python/PmagPy/data_files/etopo20'"
return
print "installing etopo20 files from ", path.join(data_dir, 'etopo20*')
print "to the basemap data directory: ", basemap_datadir
command = 'cp ' + path.join(data_dir,
'etopo20*') + " " + basemap_datadir
os.system(command)
def main():
if '-h' in sys.argv:
print "See https://earthref.org/PmagPy/cookbook/#magic_gui.py for a complete tutorial"
sys.exit()
print '-I- Starting MagIC GUI - please be patient'
# if redirect is true, wxpython makes its own output window for stdout/stderr
#app = wx.App(redirect=True)
# this sends stdout to terminal:
app = wx.App(redirect=False)
# this sends stdout to wxPython:
#app = wx.App(redirect=True)
working_dir = pmag.get_named_arg_from_sys('-WD', '.')
app.frame = MainFrame(working_dir)
## this causes an error with Canopy Python
## (it works with brew Python)
## need to use these lines for Py2app
#if working_dir == '.':
# app.frame.on_change_dir_button(None)
app.frame.Show()
app.frame.Center()
## use for debugging:
#if '-i' in sys.argv:
# import wx.lib.inspection
# wx.lib.inspection.InspectionTool().Show()
app.MainLoop()
def main():
if '-h' in sys.argv:
help_msg = """
Runs Pmag GUI for uploading, downloading, analyzing and visualizing
data.
SYNTAX
pmag_gui.py [command line options]
# or, for Anaconda users:
pmag_gui_anaconda [command line options]
INFORMATION
See https://earthref.org/PmagPy/cookbook/#pmag_gui.py for a complete tutorial
"""
print(help_msg)
sys.exit()
print('-I- Starting Pmag GUI - please be patient')
# if redirect is true, wxpython makes its own output window for stdout/stderr
if 'darwin' in sys.platform:
app = wx.App(redirect=False)
else:
app = wx.App(redirect=True)
app.frame = MagMainFrame()
working_dir = pmag.get_named_arg_from_sys('-WD', '.')
app.frame.Show()
app.frame.Center()
## use for debugging:
#if '-i' in sys.argv:
# import wx.lib.inspection
# wx.lib.inspection.InspectionTool().Show()
app.MainLoop()
def main():
if '-h' in sys.argv:
print(
"See https://earthref.org/PmagPy/cookbook/#magic_gui.py for a complete tutorial"
)
sys.exit()
print('-I- Starting MagIC GUI - please be patient')
# if redirect is true, wxpython makes its own output window for stdout/stderr
if 'darwin' in sys.platform:
app = wx.App(redirect=False)
else:
app = wx.App(redirect=True)
working_dir = pmag.get_named_arg_from_sys('-WD', '')
app.frame = MainFrame(working_dir)
## this causes an error with Canopy Python
## (it works with brew Python)
## need to use these lines for Py2app
#if working_dir == '.':
# app.frame.on_change_dir_button(None)
app.frame.Show()
app.frame.Center()
## use for debugging:
#if '-i' in sys.argv:
# import wx.lib.inspection
# wx.lib.inspection.InspectionTool().Show()
app.MainLoop()
def main():
if '-h' in sys.argv:
help_msg = """
Runs Pmag GUI for uploading, downloading, analyzing and visualizing
data.
SYNTAX
pmag_gui.py [command line options]
# or, for Anaconda users:
pmag_gui_anaconda [command line options]
INFORMATION
See https://earthref.org/PmagPy/cookbook/#pmag_gui.py for a complete tutorial
"""
print(help_msg)
sys.exit()
print('-I- Starting Pmag GUI - please be patient')
# if redirect is true, wxpython makes its own output window for stdout/stderr
if 'darwin' in sys.platform:
app = wx.App(redirect=False)
else:
app = wx.App(redirect=True)
app.frame = MagMainFrame()
working_dir = pmag.get_named_arg_from_sys('-WD', '.')
app.frame.Show()
app.frame.Center()
## use for debugging:
#if '-i' in sys.argv:
# import wx.lib.inspection
# wx.lib.inspection.InspectionTool().Show()
app.MainLoop()
def main():
try:
from mpl_toolkits.basemap import basemap_datadir
except:
print("-E- Could not import the basemap module...")
else:
# allow user to specify what directory to find the data_files in
custom_dir = pmag.get_named_arg_from_sys('-source-dir', default_val="")
if os.path.isdir(custom_dir):
data_dir = custom_dir
# if user didn't specify a directory, find the etopo20 directory
else:
# if installed by pip, etopo20 is in sys.prefix
pip_data_dir = os.path.join(sys.prefix, 'data_files', 'etopo20')
if os.path.isdir(pip_data_dir):
data_dir = pip_data_dir
else:
# if not installed by pip, etopo20 is in the local PmagPy directory
from pmagpy import find_pmag_dir
pmag_dir = find_pmag_dir.get_pmag_dir()
data_dir = os.path.join(pmag_dir, 'data_files', 'etopo20')
# if none of those options worked, warn the user:
if not os.path.isdir(data_dir):
print("-W- Could not find data_files to copy in {}".format(data_dir))
print("-I- You can run this program with the command line flag -source-dir to specify the location of the etopo20 directory.")
print("-I- For example: 'install_etopo.py -source-dir ~/Python/PmagPy/data_files/etopo20'")
return
print("installing etopo20 files from ", path.join(data_dir, 'etopo20*'))
print("to the basemap data directory: ",basemap_datadir)
command = 'cp ' + path.join(data_dir, 'etopo20*') + " "+ basemap_datadir
os.system(command)
def main():
if '-h' in sys.argv:
help_msg = """
MagIC GUI is for creating and uploading contributions to the MagIC database.
Note: if you are starting with a measurement file, it is better to use
Pmag GUI instead.
MagIC GUI is mainly meant for contributions with specimen-level data and higher.
SYNTAX
magic_gui.py [command line options]
# or, for Anaconda users:
magic_gui_anaconda [command line options]
INFORMATION
See https://earthref.org/PmagPy/cookbook/#magic_gui.py for a complete tutorial
"""
print(help_msg)
sys.exit()
print('-I- Starting MagIC GUI - please be patient')
# if redirect is true, wxpython makes its own output window for stdout/stderr
if 'darwin' in sys.platform:
app = wx.App(redirect=False)
else:
app = wx.App(redirect=True)
working_dir = pmag.get_named_arg_from_sys('-WD', '')
app.frame = MainFrame(working_dir)
app.frame.Show()
app.frame.Center()
## use for debugging:
#if '-i' in sys.argv:
# import wx.lib.inspection
# wx.lib.inspection.InspectionTool().Show()
app.MainLoop()
def __init__(self, WD=None, DM=None, dmodel=None):
"""
Input working directory, data model number (2.5 or 3),
and data model (optional).
"""
if not DM:
self.data_model_num = int(pmag.get_named_arg_from_sys("-DM", 2.5))
else:
self.data_model_num = int(DM)
self.data_model = dmodel
self.FIRST_RUN = True
wx.Frame.__init__(self, None, wx.ID_ANY, self.title, name='pmag_gui mainframe')
self.panel = wx.Panel(self, name='pmag_gui main panel')
self.InitUI()
# for use as module:
self.resource_dir = os.getcwd()
if not WD:
self.get_DIR() # choose directory dialog
else:
self.WD = WD
self.HtmlIsOpen = False
self.Bind(wx.EVT_CLOSE, self.on_menu_exit)
if self.data_model_num == 2:
self.er_magic = builder.ErMagicBuilder(self.WD, data_model=self.data_model)
elif self.data_model_num == 3:
wx.CallAfter(self.get_wd_data)
def main():
if '-h' in sys.argv:
print "Choose the folder where you want the PmagPy data files to be."
print "Navigate to that folder, and use the command: 'move_data_files.py -d .'"
print "Alternatively, you may use the full path to the directory of your choice from anywhere in the file system: 'move_data_files.py -d /Users/***/Desktop' where *** is your username"
sys.exit()
dest = pmag.get_named_arg_from_sys('-d', None, True)
data_files = path.join(sys.prefix, 'data_files')
copy_directory(data_files, dest)
def main():
if '-h' in sys.argv:
print("Choose the folder where you want the PmagPy data files to be.")
print("Navigate to that folder, and use the command: 'move_data_files.py -d .'")
print("Alternatively, you may use the full path to the directory of your choice from anywhere in the file system: 'move_data_files.py -d /Users/***/Desktop' where *** is your username")
sys.exit()
dest = pmag.get_named_arg_from_sys('-d', None, True)
data_files = path.join(sys.prefix, 'data_files')
copy_directory(data_files, dest)
def main():
"""
Take out dos problem characters from any file
"""
filename = pmag.get_named_arg_from_sys('-f')
if not filename:
return
with open(filename, 'rb+') as f:
content = f.read()
f.seek(0)
f.write(content.replace(b'\r', b''))
f.truncate()
def main():
"""
Take out dos problem characters from any file
"""
filename = pmag.get_named_arg_from_sys('-f')
if not filename:
return
with open(filename, 'rb+') as f:
content = f.read()
f.seek(0)
f.write(content.replace(b'\r', b''))
f.truncate()
def __init__(self, WD=None, DM=None, dmodel=None):
"""
Input working directory, data model number (2.5 or 3),
and data model (optional).
"""
wx.Frame.__init__(self,
None,
wx.ID_ANY,
self.title,
name='pmag_gui mainframe')
# if DM was provided:
if DM:
self.data_model_num = int(DM)
# try to get DM from command line args
if not DM:
self.data_model_num = int(pmag.get_named_arg_from_sys("-DM", 0))
DM = self.data_model_num
# if you still don't have DM, make the user choose
if not DM:
from dialogs import demag_dialogs
ui_dialog = demag_dialogs.user_input(
self, ['data_model'],
parse_funcs=[float],
heading=
"Please input prefered data model (2.5,3.0). Note: 2.5 is for legacy projects only, if you are have new data please use 3.0.",
values=[3])
res = ui_dialog.ShowModal()
vals = ui_dialog.get_values()
self.data_model_num = int(vals[1]['data_model'])
self.data_model = dmodel
self.FIRST_RUN = True
self.panel = wx.Panel(self, name='pmag_gui main panel')
self.InitUI()
# for use as module:
self.resource_dir = os.getcwd()
if not WD:
self.get_DIR() # choose directory dialog
else:
self.WD = WD
self.HtmlIsOpen = False
self.Bind(wx.EVT_CLOSE, self.on_menu_exit)
if self.data_model_num == 2:
self.er_magic = builder.ErMagicBuilder(self.WD,
data_model=self.data_model)
elif self.data_model_num == 3:
wx.CallAfter(self.get_wd_data)
def main():
if '-h' in sys.argv:
print(
"Some mapping utilities use the Etopo package for topography and these data sets do not come standard with the Python installation of Basemap. To install these additional files, use: 'install_etopo.py'."
)
return
try:
from mpl_toolkits.basemap import basemap_datadir
except:
print("-E- Could not import the basemap module...")
else:
# allow user to specify what directory to find the data_files in
custom_dir = pmag.get_named_arg_from_sys('-source-dir', default_val="")
if os.path.isdir(custom_dir):
data_dir = custom_dir
# if user didn't specify a directory, find the etopo20 directory
else:
# if installed by pip, etopo20 is in sys.prefix
pip_data_dir = os.path.join(sys.prefix, 'data_files', 'etopo20')
if os.path.isdir(pip_data_dir):
data_dir = pip_data_dir
else:
# if not installed by pip, etopo20 is in the local PmagPy directory
from pmagpy import find_pmag_dir
pmag_dir = find_pmag_dir.get_pmag_dir()
data_dir = os.path.join(pmag_dir, 'data_files', 'etopo20')
# if none of those options worked, warn the user:
if not os.path.isdir(data_dir):
print(
"-W- Could not find data_files to copy in {}".format(data_dir))
print(
"-I- You can run this program with the command line flag -source-dir to specify the location of the etopo20 directory."
)
print(
"-I- For example: 'install_etopo.py -source-dir ~/Python/PmagPy/data_files/etopo20'"
)
return
print("installing etopo20 files from ",
path.join(data_dir, 'etopo20*'))
print("to the basemap data directory: ", basemap_datadir)
if sys.platform in ['win32', 'win64']:
command = 'copy ' + path.join(data_dir,
'etopo20*') + " " + basemap_datadir
else:
command = 'cp ' + path.join(data_dir,
'etopo20*') + " " + basemap_datadir
os.system(command)
def main():
"""
NAME
download_magic.py
DESCRIPTION
unpacks a magic formatted smartbook .txt file from the MagIC database into the
tab delimited MagIC format txt files for use with the MagIC-Py programs.
SYNTAX
download_magic.py command line options]
INPUT
takes either the upload.txt file created by upload_magic.py or the file
exported by the MagIC v2.2 console software (downloaded from the MagIC database
or output by the Console on your PC).
OPTIONS
-h prints help message and quits
-i allows interactive entry of filename
-f FILE specifies input file name
-O do not overwrite duplicate Location_* directories while downloading
"""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
# interactive entry
if '-i' in sys.argv:
infile = raw_input("Magic txt file for unpacking? ")
dir_path = '.'
input_dir_path = '.'
# non-interactive
else:
dataframe = extractor.command_line_dataframe([['O', False, True]])
checked_args = extractor.extract_and_check_args(sys.argv, dataframe)
infile, dir_path, input_dir_path, overwrite = extractor.get_vars(
['f', 'WD', 'ID', 'O'], checked_args)
data_model = float(pmag.get_named_arg_from_sys("-DM", 2.5))
ipmag.download_magic(infile, dir_path, input_dir_path, overwrite,
data_model)
def __init__(self, WD=None):
self.data_model_num = int(pmag.get_named_arg_from_sys("-DM", 2.5))
self.FIRST_RUN = True
wx.Frame.__init__(self, None, wx.ID_ANY, self.title, name='pmag_gui mainframe')
self.panel = wx.Panel(self, name='pmag_gui main panel')
self.InitUI()
# for use as module:
self.resource_dir = os.getcwd()
if not WD:
self.get_DIR() # choose directory dialog
else:
self.WD = WD
self.HtmlIsOpen = False
self.Bind(wx.EVT_CLOSE, self.on_menu_exit)
if self.data_model_num == 2:
self.er_magic = builder.ErMagicBuilder(self.WD)
elif self.data_model_num == 3:
self.contribution = nb.Contribution(self.WD)
def main():
"""
NAME
download_magic.py
DESCRIPTION
unpacks a magic formatted smartbook .txt file from the MagIC database into the
tab delimited MagIC format txt files for use with the MagIC-Py programs.
SYNTAX
download_magic.py command line options]
INPUT
takes either the upload.txt file created by upload_magic.py or the file
exported by the MagIC v2.2 console software (downloaded from the MagIC database
or output by the Console on your PC).
OPTIONS
-h prints help message and quits
-i allows interactive entry of filename
-f FILE specifies input file name
-O do not overwrite duplicate Location_* directories while downloading
"""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-WD' in sys.argv:
ind=sys.argv.index('-WD')
dir_path=sys.argv[ind+1]
# interactive entry
if '-i' in sys.argv:
infile=raw_input("Magic txt file for unpacking? ")
dir_path = '.'
input_dir_path = '.'
# non-interactive
else:
dataframe = extractor.command_line_dataframe([['O', False, True]])
checked_args = extractor.extract_and_check_args(sys.argv, dataframe)
infile, dir_path, input_dir_path, overwrite = extractor.get_vars(['f', 'WD', 'ID', 'O'], checked_args)
data_model = float(pmag.get_named_arg_from_sys("-DM", 2.5))
ipmag.download_magic(infile, dir_path, input_dir_path, overwrite, data_model)
def main():
if '-h' in sys.argv:
print "See https://earthref.org/PmagPy/cookbook/#pmag_gui.py for a complete tutorial"
sys.exit()
from programs import pmag_gui
from pmagpy import pmag
print '-I- Starting Pmag GUI 3 - please be patient'
# if redirect is true, wxpython makes its own output window for stdout/stderr
app = wx.App(redirect=True)
app.frame = pmag_gui.MagMainFrame(DM=3)
working_dir = pmag.get_named_arg_from_sys('-WD', '.')
## this causes an error with Canopy Python
## (it works with brew Python)
## need to use these lines for Py2app
if working_dir == '.':
app.frame.on_change_dir_button(None)
app.frame.Show()
app.frame.Center()
## use for debugging:
#if '-i' in sys.argv:
# import wx.lib.inspection
# wx.lib.inspection.InspectionTool().Show()
app.MainLoop()
def main():
"""
NAME
upload_magic.py
DESCRIPTION
This program will prepare your PMAG text files created by the programs nfo_magic.py,
zeq_magic.py, thellier_magic.py, mag_magic, specimens_results_magic.py and so on.
it will check for all the MagIC text files and skip the missing ones
SYNTAX
upload_magic.py
INPUT
MagIC txt files
OPTIONS
-h prints help message and quits
-all include all the measurement data, default is only those used in interpretations
-DM specify which MagIC data model number to use (2 or 3). Default is 3.
OUTPUT
upload.txt: file for uploading to MagIC database
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
else:
data_model_num = pmag.get_named_arg_from_sys("-DM", 3)
dataframe = extractor.command_line_dataframe([['cat', False, 0], ['F', False, ''], ['f', False, '']])
checked_args = extractor.extract_and_check_args(sys.argv, dataframe)
dir_path, concat = extractor.get_vars(['WD', 'cat'], checked_args)
if data_model_num == 2:
ipmag.upload_magic(concat, dir_path)
else:
ipmag.upload_magic3(concat, dir_path)
def main():
"""
NAME
thellier_magic.py
DESCRIPTION
plots Thellier-Thellier data in version 3.0 format
Reads saved interpretations from a specimen formatted table, default: specimens.txt
SYNTAX
thellier_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEAS, set measurements input file, default is 'measurements.txt'
-fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
-fcr CRIT, set criteria file for grading. # not yet implemented
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out review (in format specified by -fmt key or default)
-spc SPEC, plots single specimen SPEC, saves plot with specified format
with optional -b bounds and quits
-b BEG END: sets bounds for calculation
BEG: starting step number for slope calculation
END: ending step number for slope calculation
-z use only z component difference for pTRM calculation
OUTPUT
figures:
ALL: numbers refer to temperature steps in command line window
1) Arai plot: closed circles are zero-field first/infield
open circles are infield first/zero-field
triangles are pTRM checks
squares are pTRM tail checks
VDS is vector difference sum
diamonds are bounds for interpretation
2) Zijderveld plot: closed (open) symbols are X-Y (X-Z) planes
X rotated to NRM direction
3) (De/Re)Magnetization diagram:
circles are NRM remaining
squares are pTRM gained
4) equal area projections:
green triangles are pTRM gained direction
red (purple) circles are lower(upper) hemisphere of ZI step directions
blue (cyan) squares are lower(upper) hemisphere IZ step directions
5) Optional: TRM acquisition
6) Optional: TDS normalization
command line window:
list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of measuements)
list of possible commands: type letter followed by return to select option
saving of plots creates image files with specimen, plot type as name
"""
#
# initializations
#
version_num=pmag.get_version()
verbose=pmagplotlib.verbose
#
# default acceptance criteria
#
accept=pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
plots,fmt,Zdiff=0,'svg',0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg_from_sys("-f", default_val="measurements.txt")
spec_file=pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
crit_file=pmag.get_named_arg_from_sys("-fcr", default_val="criteria.txt")
spec_file=os.path.join(dir_path,spec_file)
meas_file=os.path.join(dir_path,meas_file)
crit_file=os.path.join(dir_path,crit_file)
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
if '-sav' in sys.argv: plots,verbose=1,0
if '-z' in sys.argv: Zdiff=1
specimen=pmag.get_named_arg_from_sys("-spc",default_val="")
if '-b' in sys.argv:
ind=sys.argv.index('-b')
start=int(sys.argv[ind+1])
end=int(sys.argv[ind+2])
else:
start,end="",""
fnames = {'measurements': meas_file, 'specimens': spec_file, 'criteria': crit_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames, read_tables=['measurements', 'specimens', 'criteria'])
#
# import prior interpretations from specimen file
#
specimen_cols = ['analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s', 'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma', 'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1', 'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95', 'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements', 'dir_tilt_correction', 'experiments', 'geologic_classes', 'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment', 'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma', 'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma', 'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q', 'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max', 'meas_step_min', 'meas_step_unit', 'method_codes', 'sample', 'software_packages', 'specimen']
if 'specimens' in contribution.tables:
spec_container = contribution.tables['specimens']
prior_spec_data=spec_container.get_records_for_code('LP-PI-TRM',strict_match=False) # look up all prior intensity interpretations
else:
spec_container, prior_spec_data = None, []
backup=0
#
Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
#
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data['method_codes']=meas_data['method_codes'].str.replace(" ","") # get rid of nasty spaces
meas_data= meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM|LP-TRM|LP-TRM-TD')==True] # fish out zero field steps for plotting
intensity_types = [col_name for col_name in meas_data.columns if col_name in Mkeys]
int_key = intensity_types[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
meas_data = meas_data[meas_data[int_key].notnull()] # get all the non-null intensity records of the same type
if 'flag' not in meas_data.columns: meas_data['flag'] = 'g' # set the default flag to good
meas_data = meas_data[meas_data['flag'].str.contains('g')==True] # only the 'good' measurements
thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')==True] # get all the Thellier data
trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM')==True] # get all the TRM acquisition data
td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD')==True] # get all the TD data
anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN')==True] # get all the anisotropy data
#
# get list of unique specimen names from measurement data
#
specimen_names= meas_data.specimen.unique() # this is a Series of all the specimen names
specimen_names= specimen_names.tolist() # turns it into a list
specimen_names.sort() # sorts by specimen name
#
# set up new DataFrame for this sessions specimen interpretations
#
spec_container = nb.MagicDataFrame(dtype='specimens', columns=specimen_cols)
current_spec_data = spec_container.df # this is for interpretations from this session
if specimen=="": # do all specimens
k = 0
else:
k=specimen_names.index(specimen) # just do this one
# define figure numbers for arai, zijderveld and
# de-,re-magnetization diagrams
AZD={}
AZD['deremag'], AZD['zijd'],AZD['arai'],AZD['eqarea']=1,2,3,4
pmagplotlib.plot_init(AZD['arai'],5,5)
pmagplotlib.plot_init(AZD['zijd'],5,5)
pmagplotlib.plot_init(AZD['deremag'],5,5)
pmagplotlib.plot_init(AZD['eqarea'],5,5)
if len(trm_data)>0:
AZD['TRM']=5
pmagplotlib.plot_init(AZD['TRM'],5,5)
if len(td_data)>0:
AZD['TDS']=6
pmagplotlib.plot_init(AZD['TDS'],5,5)
#
while k < len(specimen_names):
this_specimen=specimen_names[k] # set the current specimen for plotting
if verbose and this_specimen!="":print(this_specimen, k+1 , 'out of ',len(specimen_names))
#
# set up datablocks
#
thelblock= thel_data[thel_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
trmblock= trm_data[trm_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
tdsrecs= td_data[td_data['specimen'].str.contains(this_specimen)==True] # fish out this specimen
anisblock= anis_data[anis_data['specimen'].str.contains(this_specimen)==True] # fish out the anisotropy data
prior_specimen_interpretations= prior_spec_data[prior_spec_data['specimen'].str.contains(this_specimen)==True] # fish out prior interpretation
#
# sort data into types
#
araiblock,field=pmag.sortarai(thelblock,this_specimen,Zdiff,version=3)
first_Z=araiblock[0]
GammaChecks=araiblock[5]
if len(first_Z)<3:
if backup==0:
k+=1
if verbose:
print('skipping specimen - moving forward ', this_specimen)
else:
k-=1
if verbose:
print('skipping specimen - moving backward ', this_specimen)
else:
backup=0
zijdblock,units=pmag.find_dmag_rec(this_specimen,thelblock,version=3)
if start=="" and len(prior_specimen_interpretations)>0:
if verbose: print('Looking up saved interpretation....')
#
# get prior interpretation steps
#
beg_int=pd.to_numeric(prior_specimen_interpretations.meas_step_min.values).tolist()[0]
end_int=pd.to_numeric(prior_specimen_interpretations.meas_step_max.values).tolist()[0]
else: beg_int,end_int="",""
recnum=0
if verbose: print("index step Dec Inc Int Gamma")
for plotrec in zijdblock:
if plotrec[0]==beg_int:start=recnum # while we are at it, collect these bounds
if plotrec[0]==end_int:end=recnum
if verbose:
if GammaChecks!="":
gamma=""
for g in GammaChecks:
if g[0]==plotrec[0]-273:
gamma=g[1]
break
if gamma!="":
print('%i %i %7.1f %7.1f %8.3e %7.1f' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3],gamma))
else:
print('%i %i %7.1f %7.1f %8.3e ' % (recnum,plotrec[0]-273,plotrec[1],plotrec[2],plotrec[3]))
recnum += 1
for fig in list(AZD.keys()):pmagplotlib.clearFIG(AZD[fig]) # clear all figures
pmagplotlib.plotAZ(AZD,araiblock,zijdblock,this_specimen,units[0])
if verbose:pmagplotlib.drawFIGS(AZD)
pars,errcode=pmag.PintPars(thelblock,araiblock,zijdblock,start,end,accept,version=3)
pars['measurement_step_unit']="K"
pars['experiment_type']='LP-PI-TRM'
#
# work on saving interpretations stuff later
#
if errcode!=1: # no problem in PintPars
pars["specimen_lab_field_dc"]=field
pars["specimen_int"]=-1*field*pars["specimen_b"]
pars["er_specimen_name"]=this_specimen
#pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose) # deal with this later
pars["specimen_grade"]='None'
pars['measurement_step_min']=pars['meas_step_min']
pars['measurement_step_max']=pars['meas_step_max']
if pars['measurement_step_unit']=='K':
outstr= "specimen Tmin Tmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma Gamma_max \n"
pars_out= (this_specimen,(pars["meas_step_min"]-273),(pars["meas_step_max"]-273),(pars["specimen_int_n"]),1e6*(pars["specimen_lab_field_dc"]),1e6*(pars["specimen_int"]),pars["specimen_b"],pars["specimen_q"],pars["specimen_f"],pars["specimen_fvds"],pars["specimen_b_beta"],pars["int_mad_free"],pars["int_dang"],pars["int_drats"],pars["int_n_ptrm"],pars["specimen_grade"],np.sqrt(pars["specimen_rsc"]),int(pars["int_md"]), pars["specimen_b_sigma"],pars['specimen_gamma'])
outstring= '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out +'\n'
elif pars['measurement_step_unit']=='J':
outstr= "specimen Wmin Wmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma ThetaMax DeltaMax GammaMax\n"
pars_out= (this_specimen,(pars["meas_step_min"]),(pars["meas_step_max"]),(pars["specimen_int_n"]),1e6*(pars["specimen_lab_field_dc"]),1e6*(pars["specimen_int"]),pars["specimen_b"],pars["specimen_q"],pars["specimen_f"],pars["specimen_fvds"],pars["specimen_b_beta"],pars["specimen_int_mad"],pars["specimen_int_dang"],pars["specimen_drats"],pars["specimen_int_ptrm_n"],pars["specimen_grade"],np.sqrt(pars["specimen_rsc"]),int(pars["specimen_md"]), pars["specimen_b_sigma"],pars["specimen_theta"],pars["specimen_delta"],pars["specimen_gamma"])
outstring= '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out +'\n'
print(outstr)
print(outstring)
pmagplotlib.plotB(AZD,araiblock,zijdblock,pars)
mpars=pmag.domean(araiblock[1],start,end,'DE-BFL')
if verbose:
pmagplotlib.drawFIGS(AZD)
print('pTRM direction= ','%7.1f'%(mpars['specimen_dec']),' %7.1f'%(mpars['specimen_inc']),' MAD:','%7.1f'%(mpars['specimen_mad']))
if len(anisblock)>0: # this specimen has anisotropy data
if verbose: print('Found anisotropy record... but ignoring for now ')
if plots==1:
if fmt != "pmag":
files={}
for key in list(AZD.keys()):
files[key]='SP:_'+this_specimen+'_TY:_'+key+'_'+'.'+fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['deremag']='DeReMag Plot'
titles['zijd']='Zijderveld Plot'
titles['arai']='Arai Plot'
titles['TRM']='TRM Acquisition data'
AZD = pmagplotlib.addBorders(AZD,titles,black,purple)
pmagplotlib.saveP(AZD,files)
else: # save in pmag format
print('pmag format no longer supported')
#script="grep "+this_specimen+" output.mag | thellier -mfsi"
#script=script+' %8.4e'%(field)
#min='%i'%((pars["measurement_step_min"]-273))
#Max='%i'%((pars["measurement_step_max"]-273))
#script=script+" "+min+" "+Max
#script=script+" |plotxy;cat mypost >>thellier.ps\n"
#pltf.write(script)
#pmag.domagicmag(outf,MeasRecs)
if specimen!="": sys.exit() # syonara
if verbose:
ans=input('Return for next specimen, q to quit: ')
if ans=='q':sys.exit()
k+=1 # moving on
def main():
"""
NAME
atrm_magic.py
DESCRIPTION
Converts ATRM data to best-fit tensor (6 elements plus sigma)
Original program ARMcrunch written to accomodate ARM anisotropy data
collected from 6 axial directions (+X,+Y,+Z,-X,-Y,-Z) using the
off-axis remanence terms to construct the tensor. A better way to
do the anisotropy of ARMs is to use 9,12 or 15 measurements in
the Hext rotational scheme.
SYNTAX
atrm_magic.py [-h][command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f FILE: specify input file, default is atrm_measurements.txt
-Fa FILE: specify anisotropy output file, default is trm_anisotropy.txt (MagIC 2.5 only)
-Fr FILE: specify results output file, default is atrm_results.txt (MagIC 2.5 only)
-Fsi FILE: specify output file, default is specimens.txt (MagIC 3 only)
-DM DATA_MODEL: specify MagIC 2 or MagIC 3, default is 3
INPUT
Input for the present program is a TRM acquisition data with an optional baseline.
The order of the measurements is:
Decs=[0,90,0,180,270,0,0,90,0]
Incs=[0,0,90,0,0,-90,0,0,90]
The last two measurements are optional
"""
# initialize some parameters
args = sys.argv
user = ""
meas_file = "atrm_measurements.txt"
rmag_anis = "trm_anisotropy.txt"
rmag_res = "atrm_results.txt"
dir_path = '.'
#
# get name of file from command line
#
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind + 1]
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = sys.argv[ind + 1]
if "-f" in args:
ind = args.index("-f")
meas_file = sys.argv[ind + 1]
if "-Fa" in args:
ind = args.index("-Fa")
rmag_anis = args[ind + 1]
if "-Fr" in args:
ind = args.index("-Fr")
rmag_res = args[ind + 1]
data_model_num = int(pmag.get_named_arg_from_sys("-DM", 3))
spec_file = pmag.get_named_arg_from_sys("-Fsi", "specimens.txt")
spec_file = os.path.join(dir_path, spec_file)
meas_file = dir_path + '/' + meas_file
rmag_anis = dir_path + '/' + rmag_anis
rmag_res = dir_path + '/' + rmag_res
# read in data
if data_model_num == 3:
meas_data = []
meas_data3, file_type = pmag.magic_read(meas_file)
if file_type != 'measurements':
print(file_type, "This is not a valid measurements file ")
sys.exit()
# convert meas_data to 2.5
for rec in meas_data3:
meas_map = map_magic.meas_magic3_2_magic2_map
meas_data.append(map_magic.mapping(rec, meas_map))
else:
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(file_type, "This is not a valid magic_measurements file ")
sys.exit()
meas_data = pmag.get_dictitem(
meas_data, 'magic_method_codes', 'LP-AN-TRM', 'has')
#
#
# get sorted list of unique specimen names
ssort = []
for rec in meas_data:
spec = rec["er_specimen_name"]
if spec not in ssort:
ssort.append(spec)
sids = sorted(ssort)
#
#
# work on each specimen
#
specimen, npos = 0, 6
RmagSpecRecs, RmagResRecs = [], []
SpecRecs, SpecRecs3 = [], []
while specimen < len(sids):
nmeas = 0
s = sids[specimen]
RmagSpecRec = {}
RmagResRec = {}
BX, X = [], []
method_codes = []
Spec0 = ""
#
# find the data from the meas_data file for this sample
# and get dec, inc, int and convert to x,y,z
#
# fish out data for this specimen name
data = pmag.get_dictitem(meas_data, 'er_specimen_name', s, 'T')
if len(data) > 5:
RmagSpecRec["rmag_anisotropy_name"] = data[0]["er_specimen_name"]
RmagSpecRec["er_location_name"] = data[0].get("er_location_name", "")
RmagSpecRec["er_specimen_name"] = data[0]["er_specimen_name"]
RmagSpecRec["er_sample_name"] = data[0].get("er_sample_name", "")
RmagSpecRec["er_site_name"] = data[0].get("er_site_name", "")
RmagSpecRec["magic_experiment_names"] = RmagSpecRec["rmag_anisotropy_name"] + ":ATRM"
RmagSpecRec["er_citation_names"] = "This study"
RmagResRec["rmag_result_name"] = data[0]["er_specimen_name"] + ":ATRM"
RmagResRec["er_location_names"] = data[0].get("er_location_names", "")
RmagResRec["er_specimen_names"] = data[0]["er_specimen_name"]
RmagResRec["er_sample_names"] = data[0].get("er_sample_name", "")
RmagResRec["er_site_names"] = data[0].get("er_site_name", "")
RmagResRec["magic_experiment_names"] = RmagSpecRec["rmag_anisotropy_name"] + ":ATRM"
RmagResRec["er_citation_names"] = "This study"
RmagSpecRec["anisotropy_type"] = "ATRM"
if "magic_instrument_codes" in list(data[0].keys()):
RmagSpecRec["magic_instrument_codes"] = data[0]["magic_instrument_codes"]
else:
RmagSpecRec["magic_instrument_codes"] = ""
RmagSpecRec["anisotropy_description"] = "Hext statistics adapted to ATRM"
for rec in data:
meths = rec['magic_method_codes'].strip().split(':')
Dir = []
Dir.append(float(rec["measurement_dec"]))
Dir.append(float(rec["measurement_inc"]))
Dir.append(float(rec["measurement_magn_moment"]))
if "LT-T-Z" in meths:
BX.append(pmag.dir2cart(Dir)) # append baseline steps
elif "LT-T-I" in meths:
X.append(pmag.dir2cart(Dir))
nmeas += 1
#
if len(BX) == 1:
for i in range(len(X) - 1):
BX.append(BX[0]) # assume first 0 field step as baseline
elif len(BX) == 0: # assume baseline is zero
for i in range(len(X)):
BX.append([0., 0., 0.]) # assume baseline of 0
elif len(BX) != len(X): # if BX isn't just one measurement or one in between every infield step, just assume it is zero
print('something odd about the baselines - just assuming zero')
for i in range(len(X)):
BX.append([0., 0., 0.]) # assume baseline of 0
if nmeas < 6: # must have at least 6 measurements right now -
print('skipping specimen ', s, ' too few measurements')
specimen += 1
else:
# B matrix made from design matrix for positions
B, H, tmpH = pmag.designATRM(npos)
#
# subtract optional baseline and put in a work array
#
work = numpy.zeros((nmeas, 3), 'f')
for i in range(nmeas):
for j in range(3):
# subtract baseline, if available
work[i][j] = X[i][j] - BX[i][j]
#
# calculate tensor elements
# first put ARM components in w vector
#
w = numpy.zeros((npos * 3), 'f')
index = 0
for i in range(npos):
for j in range(3):
w[index] = work[i][j]
index += 1
s = numpy.zeros((6), 'f') # initialize the s matrix
for i in range(6):
for j in range(len(w)):
s[i] += B[i][j] * w[j]
trace = s[0] + s[1] + s[2] # normalize by the trace
for i in range(6):
s[i] = old_div(s[i], trace)
a = pmag.s2a(s)
#------------------------------------------------------------
# Calculating dels is different than in the Kappabridge
# routine. Use trace normalized tensor (a) and the applied
# unit field directions (tmpH) to generate model X,Y,Z
# components. Then compare these with the measured values.
#------------------------------------------------------------
S = 0.
comp = numpy.zeros((npos * 3), 'f')
for i in range(npos):
for j in range(3):
index = i * 3 + j
compare = a[j][0] * tmpH[i][0] + a[j][1] * \
tmpH[i][1] + a[j][2] * tmpH[i][2]
comp[index] = compare
for i in range(npos * 3):
d = old_div(w[i], trace) - comp[i] # del values
S += d * d
nf = float(npos * 3. - 6.) # number of degrees of freedom
if S > 0:
sigma = numpy.sqrt(old_div(S, nf))
else:
sigma = 0
hpars = pmag.dohext(nf, sigma, s)
#
# prepare for output
#
RmagSpecRec["anisotropy_s1"] = '%8.6f' % (s[0])
RmagSpecRec["anisotropy_s2"] = '%8.6f' % (s[1])
RmagSpecRec["anisotropy_s3"] = '%8.6f' % (s[2])
RmagSpecRec["anisotropy_s4"] = '%8.6f' % (s[3])
RmagSpecRec["anisotropy_s5"] = '%8.6f' % (s[4])
RmagSpecRec["anisotropy_s6"] = '%8.6f' % (s[5])
RmagSpecRec["anisotropy_mean"] = '%8.3e' % (old_div(trace, 3))
RmagSpecRec["anisotropy_sigma"] = '%8.6f' % (sigma)
RmagSpecRec["anisotropy_unit"] = "Am^2"
RmagSpecRec["anisotropy_n"] = '%i' % (npos)
RmagSpecRec["anisotropy_tilt_correction"] = '-1'
# used by thellier_gui - must be taken out for uploading
RmagSpecRec["anisotropy_F"] = '%7.1f ' % (hpars["F"])
# used by thellier_gui - must be taken out for uploading
RmagSpecRec["anisotropy_F_crit"] = hpars["F_crit"]
RmagResRec["anisotropy_t1"] = '%8.6f ' % (hpars["t1"])
RmagResRec["anisotropy_t2"] = '%8.6f ' % (hpars["t2"])
RmagResRec["anisotropy_t3"] = '%8.6f ' % (hpars["t3"])
RmagResRec["anisotropy_v1_dec"] = '%7.1f ' % (hpars["v1_dec"])
RmagResRec["anisotropy_v2_dec"] = '%7.1f ' % (hpars["v2_dec"])
RmagResRec["anisotropy_v3_dec"] = '%7.1f ' % (hpars["v3_dec"])
RmagResRec["anisotropy_v1_inc"] = '%7.1f ' % (hpars["v1_inc"])
RmagResRec["anisotropy_v2_inc"] = '%7.1f ' % (hpars["v2_inc"])
RmagResRec["anisotropy_v3_inc"] = '%7.1f ' % (hpars["v3_inc"])
RmagResRec["anisotropy_ftest"] = '%7.1f ' % (hpars["F"])
RmagResRec["anisotropy_ftest12"] = '%7.1f ' % (hpars["F12"])
RmagResRec["anisotropy_ftest23"] = '%7.1f ' % (hpars["F23"])
RmagResRec["result_description"] = 'Critical F: ' + \
hpars["F_crit"] + ';Critical F12/F13: ' + hpars["F12_crit"]
if hpars["e12"] > hpars["e13"]:
RmagResRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
else:
RmagResRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
if hpars["e23"] > hpars['e12']:
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
else:
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["tilt_correction"] = '-1'
RmagResRec["anisotropy_type"] = 'ATRM'
RmagResRec["magic_method_codes"] = 'LP-AN-TRM:AE-H'
RmagSpecRec["magic_method_codes"] = 'LP-AN-TRM:AE-H'
RmagResRec["magic_software_packages"] = pmag.get_version()
RmagSpecRec["magic_software_packages"] = pmag.get_version()
RmagSpecRecs.append(RmagSpecRec)
RmagResRecs.append(RmagResRec)
specimen += 1
if data_model_num == 3:
SpecRec = RmagResRec.copy()
SpecRec.update(RmagSpecRec)
SpecRecs.append(SpecRec)
# finished iterating through specimens,
# now we need to write out the data to files
if data_model_num == 3:
# translate records
for rec in SpecRecs:
rec3 = map_magic.convert_aniso('magic3', rec)
SpecRecs3.append(rec3)
# write output to 3.0 specimens file
pmag.magic_write(spec_file, SpecRecs3, 'specimens')
print("specimen data stored in {}".format(spec_file))
else:
# write output to 2.5 rmag_ files
pmag.magic_write(rmag_anis, RmagSpecRecs, 'rmag_anisotropy')
print("specimen tensor elements stored in ", rmag_anis)
pmag.magic_write(rmag_res, RmagResRecs, 'rmag_results')
print("specimen statistics and eigenparameters stored in ", rmag_res)
def main():
"""
NAME
hysteresis_magic.py
DESCRIPTION
calculates hystereis parameters and saves them in 3.0 specimen format file
makes plots if option selected
SYNTAX
hysteresis_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input file, default is agm_measurements.txt
-F: specify specimens.txt output file
-P: do not make the plots
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
PLT = 1
plots = 0
fmt = pmag.get_named_arg_from_sys('-fmt', 'svg')
dir_path = pmag.get_named_arg_from_sys('-WD', '.')
dir_path = os.path.realpath(dir_path)
verbose = pmagplotlib.verbose
version_num = pmag.get_version()
user = pmag.get_named_arg_from_sys('-usr', '')
if "-h" in args:
print(main.__doc__)
sys.exit()
meas_file = pmag.get_named_arg_from_sys('-f', 'agm_measurements.txt')
spec_file = pmag.get_named_arg_from_sys('-F', 'specimens.txt')
if '-P' in args:
PLT = 0
irm_init, imag_init = -1, -1
if '-sav' in args:
verbose = 0
plots = 1
pltspec = pmag.get_named_arg_from_sys('-spc', 0)
if pltspec:
#pltspec= args[ind+1]
verbose = 0
plots = 1
spec_file = dir_path + '/' + spec_file
meas_file = dir_path + '/' + meas_file
SpecRecs = []
#
#
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'measurements':
print(main.__doc__)
print('bad file')
sys.exit()
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs, RemRecs = [], []
HDD = {}
if verbose:
if verbose and PLT:
print("Plots may be on top of each other - use mouse to place ")
if PLT:
HDD['hyst'], HDD['deltaM'], HDD['DdeltaM'] = 1, 2, 3
pmagplotlib.plot_init(HDD['DdeltaM'], 5, 5)
pmagplotlib.plot_init(HDD['deltaM'], 5, 5)
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
imag_init = 0
irm_init = 0
else:
HDD['hyst'], HDD['deltaM'], HDD['DdeltaM'], HDD['irm'], HDD[
'imag'] = 0, 0, 0, 0, 0
#
if spec_file: prior_data, file_type = pmag.magic_read(spec_file)
#
# get list of unique experiment names and specimen names
#
experiment_names, sids = [], []
hys_data = pmag.get_dictitem(meas_data, 'method_codes', 'LP-HYS', 'has')
dcd_data = pmag.get_dictitem(meas_data, 'method_codes', 'LP-IRM-DCD',
'has')
imag_data = pmag.get_dictitem(meas_data, 'method_codes', 'LP-IMAG', 'has')
for rec in hys_data:
if rec['experiment'] not in experiment_names:
experiment_names.append(rec['experiment'])
if rec['specimen'] not in sids: sids.append(rec['specimen'])
#
k = 0
if pltspec:
k = sids.index(pltspec)
print(sids[k])
while k < len(sids):
specimen = sids[k]
HystRec = {
'specimen': specimen,
'experiment': ""
} # initialize a new specimen hysteresis record
if verbose and PLT: print(specimen, k + 1, 'out of ', len(sids))
#
#
B, M, Bdcd, Mdcd = [], [], [], [
] #B,M for hysteresis, Bdcd,Mdcd for irm-dcd data
Bimag, Mimag = [], [] #Bimag,Mimag for initial magnetization curves
spec_data = pmag.get_dictitem(
hys_data, 'specimen', specimen,
'T') # fish out all the LP-HYS data for this specimen
if len(spec_data) > 0:
meths = spec_data[0]['method_codes'].split(':')
e = spec_data[0]['experiment']
HystRec['experiment'] = spec_data[0]['experiment']
for rec in spec_data:
B.append(float(rec['meas_field_dc']))
M.append(float(rec['magn_moment']))
spec_data = pmag.get_dictitem(
dcd_data, 'specimen', specimen,
'T') # fish out all the data for this specimen
if len(spec_data) > 0:
HystRec['experiment'] = HystRec['experiment'] + ':' + spec_data[0][
'experiment']
irm_exp = spec_data[0]['experiment']
for rec in spec_data:
Bdcd.append(float(rec['treat_dc_field']))
Mdcd.append(float(rec['magn_moment']))
spec_data = pmag.get_dictitem(
imag_data, 'specimen', specimen,
'T') # fish out all the data for this specimen
if len(spec_data) > 0:
imag_exp = spec_data[0]['experiment']
for rec in spec_data:
Bimag.append(float(rec['meas_field_dc']))
Mimag.append(float(rec['magn_moment']))
#
# now plot the hysteresis curve
#
if len(B) > 0:
hmeths = []
for meth in meths:
hmeths.append(meth)
hpars = pmagplotlib.plotHDD(HDD, B, M, e)
if verbose and PLT: pmagplotlib.drawFIGS(HDD)
#
if verbose: pmagplotlib.plotHPARS(HDD, hpars, 'bs')
HystRec['hyst_mr_moment'] = hpars['hysteresis_mr_moment']
HystRec['hyst_ms_moment'] = hpars['hysteresis_ms_moment']
HystRec['hyst_bc'] = hpars['hysteresis_bc']
HystRec['hyst_bcr'] = hpars['hysteresis_bcr']
HystRec['hyst_xhf'] = hpars['hysteresis_xhf']
HystRec['experiments'] = e
HystRec['software_packages'] = version_num
if hpars["magic_method_codes"] not in hmeths:
hmeths.append(hpars["magic_method_codes"])
methods = ""
for meth in hmeths:
methods = methods + meth.strip() + ":"
HystRec["method_codes"] = methods[:-1]
HystRec["citations"] = "This study"
#
if len(Bdcd) > 0:
rmeths = []
for meth in meths:
rmeths.append(meth)
if verbose and PLT: print('plotting IRM')
if irm_init == 0:
HDD['irm'] = 5
pmagplotlib.plot_init(HDD['irm'], 5, 5)
irm_init = 1
rpars = pmagplotlib.plotIRM(HDD['irm'], Bdcd, Mdcd, irm_exp)
HystRec['rem_mr_moment'] = rpars['remanence_mr_moment']
HystRec['rem_bcr'] = rpars['remanence_bcr']
HystRec['experiments'] = specimen + ':' + irm_exp
if rpars["magic_method_codes"] not in meths:
meths.append(rpars["magic_method_codes"])
methods = ""
for meth in rmeths:
methods = methods + meth.strip() + ":"
HystRec[
"method_codes"] = HystRec['method_codes'] + ':' + methods[:-1]
HystRec["citations"] = "This study"
else:
if irm_init: pmagplotlib.clearFIG(HDD['irm'])
if len(Bimag) > 0:
if verbose and PLT: print('plotting initial magnetization curve')
# first normalize by Ms
Mnorm = []
for m in Mimag:
Mnorm.append(old_div(m, float(hpars['hysteresis_ms_moment'])))
if imag_init == 0:
HDD['imag'] = 4
pmagplotlib.plot_init(HDD['imag'], 5, 5)
imag_init = 1
pmagplotlib.plotIMAG(HDD['imag'], Bimag, Mnorm, imag_exp)
else:
if imag_init: pmagplotlib.clearFIG(HDD['imag'])
if len(list(HystRec.keys())) > 0: HystRecs.append(HystRec)
#
files = {}
if plots:
if pltspec:
s = pltspec
else:
s = specimen
files = {}
for key in list(HDD.keys()):
files[key] = s + '_' + key + '.' + fmt
pmagplotlib.saveP(HDD, files)
if pltspec: sys.exit()
if verbose and PLT:
pmagplotlib.drawFIGS(HDD)
ans = input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n "
)
if ans == "a":
files = {}
for key in list(HDD.keys()):
files[key] = specimen + '_' + key + '.' + fmt
pmagplotlib.saveP(HDD, files)
if ans == '': k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]: tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0 and len(Bdcd) == 0:
if verbose: print('skipping this one - no hysteresis data')
k += 1
if len(HystRecs) > 0:
# go through prior_data, clean out prior results and save combined file as spec_file
SpecRecs, keys = [], list(HystRecs[0].keys())
if len(prior_data) > 0:
prior_keys = list(prior_data[0].keys())
else:
prior_keys = []
for rec in prior_data:
for key in keys:
if key not in list(rec.keys()): rec[key] = ""
if 'LP-HYS' not in rec['method_codes']:
SpecRecs.append(rec)
for rec in HystRecs:
for key in prior_keys:
if key not in list(rec.keys()): rec[key] = ""
prior = pmag.get_dictitem(prior_data, 'specimen', rec['specimen'],
'T')
if len(prior) > 0 and 'sample' in list(prior[0].keys()):
rec['sample'] = prior[0][
'sample'] # pull sample name from prior specimens table
SpecRecs.append(rec)
# drop unnecessary/duplicate rows
dir_path = os.path.split(spec_file)[0]
con = nb.Contribution(dir_path, read_tables=[])
con.add_magic_table_from_data('specimens', SpecRecs)
con.tables['specimens'].drop_duplicate_rows(ignore_cols=[
'specimen', 'sample', 'citations', 'software_packages'
])
con.tables['specimens'].df = con.tables[
'specimens'].df.drop_duplicates()
con.write_table_to_file('specimens', custom_name=spec_file)
# old way:
##pmag.magic_write(spec_file,SpecRecs,"specimens")
if verbose: print("hysteresis parameters saved in ", spec_file)
def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input file, default is measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
plots = 0
pltspec = ""
verbose = pmagplotlib.verbose
#version_num = pmag.get_version()
dir_path = pmag.get_named_arg_from_sys('-WD', '.')
dir_path = os.path.realpath(dir_path)
meas_file = pmag.get_named_arg_from_sys('-f', 'measurements.txt')
fmt = pmag.get_named_arg_from_sys('-fmt', 'png')
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind + 1]
verbose = 0
plots = 1
#
con = nb.Contribution(dir_path,
read_tables=['measurements'],
custom_filenames={'measurements': meas_file})
# get as much name data as possible (used for naming plots)
if not 'measurements' in con.tables:
print("-W- No measurement file found")
return
con.propagate_location_to_measurements()
if 'measurements' not in con.tables:
print(main.__doc__)
print('bad file')
sys.exit()
meas_container = con.tables['measurements']
#meas_df = meas_container.df
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs = []
HDD = {}
HDD['hyst'] = 1
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
#
# get list of unique experiment names and specimen names
#
sids = []
hyst_data = meas_container.get_records_for_code('LP-HYS')
#experiment_names = hyst_data['experiment_name'].unique()
if not len(hyst_data):
print("-W- No hysteresis data found")
return
sids = hyst_data['specimen'].unique()
# if 'treat_temp' is provided, use that value, otherwise assume 300
hyst_data['treat_temp'].where(hyst_data['treat_temp'].notnull(),
'300',
inplace=True)
# start at first specimen, or at provided specimen ('-spc')
k = 0
if pltspec != "":
try:
print(sids)
k = list(sids).index(pltspec)
except ValueError:
print('-W- No specimen named: {}.'.format(pltspec))
print('-W- Please provide a valid specimen name')
return
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
while k < len(sids):
locname, site, sample, synth = '', '', '', ''
s = sids[k]
if verbose:
print(s, k + 1, 'out of ', len(sids))
# B, M for hysteresis, Bdcd,Mdcd for irm-dcd data
B, M = [], []
# get all measurements for this specimen
spec = hyst_data[hyst_data['specimen'] == s]
# get names
if 'location' in spec:
locname = spec['location'][0]
if 'site' in spec:
site = spec['sample'][0]
if 'sample' in spec:
sample = spec['sample'][0]
# get all records with non-blank values in any intlist column
# find intensity data
for int_column in intlist:
if int_column in spec.columns:
int_col = int_column
break
meas_data = spec[spec[int_column].notnull()]
if len(meas_data) == 0:
break
#
c = ['k-', 'b-', 'c-', 'g-', 'm-', 'r-', 'y-']
cnum = 0
Temps = []
xlab, ylab, title = '', '', ''
Temps = meas_data['treat_temp'].unique()
for t in Temps:
print('working on t: ', t)
t_data = meas_data[meas_data['treat_temp'] == t]
m = int_col
B = t_data['meas_field_dc'].astype(float).values
M = t_data[m].astype(float).values
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = 'Field (T)'
ylab = m
title = 'Hysteresis: ' + s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD['hyst'])
pmagplotlib.plotXY(HDD['hyst'],
B,
M,
sym=c[cnum],
xlab=xlab,
ylab=ylab,
title=title)
pmagplotlib.plotXY(HDD['hyst'], [1.1 * B.min(), 1.1 * B.max()],
[0, 0],
sym='k-',
xlab=xlab,
ylab=ylab,
title=title)
pmagplotlib.plotXY(HDD['hyst'], [0, 0],
[1.1 * M.min(), 1.1 * M.max()],
sym='k-',
xlab=xlab,
ylab=ylab,
title=title)
if verbose:
pmagplotlib.drawFIGS(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
for key in list(HDD.keys()):
if pmagplotlib.isServer:
if synth == '':
files[
key] = "LO:_" + locname + '_SI:_' + site + '_SA:_' + sample + '_SP:_' + s + '_TY:_' + key + '_.' + fmt
else:
files[
key] = 'SY:_' + synth + '_TY:_' + key + '_.' + fmt
else:
if synth == '':
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
else:
files[key] = "{}_{}.{}".format(synth, key, fmt)
pmagplotlib.saveP(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.drawFIGS(HDD)
ans = input(
"S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n "
)
if ans == "a":
files = {}
for key in list(HDD.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[
key] = "LO:_" + locname + '_SI:_' + site + '_SA:_' + sample + '_SP:_' + s + '_TY:_' + key + '_.' + fmt
else: # use more readable plot naming convention
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
pmagplotlib.saveP(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = input(
'Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file [and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored. ] Bracketed part not yet implemented
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets measurements format input file, default: measurements.txt
-fsp SPECFILE: sets specimens format file with prior interpreations, default: specimens.txt
-fsa SAMPFILE: sets samples format file sample=>site information, default: samples.txt
-fsi SITEFILE: sets sites format file with site=>location informationprior interpreations, default: samples.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave, e, b = 1, 0, 0 # average replicates, initial end and beginning step
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
plots, coord = 0, 's'
noorient = 0
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
calculation_type, fmt = "", "svg"
user, spec_keys, locname = "", [], ''
geo, tilt, ask = 0, 0, 0
PriorRecs = [] # empty list for prior interpretations
backup = 0
specimen = "" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg_from_sys("-f",
default_val="measurements.txt")
spec_file = pmag.get_named_arg_from_sys("-fsp",
default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
#meas_file = os.path.join(dir_path, meas_file)
#spec_file = os.path.join(dir_path, spec_file)
#samp_file = os.path.join(dir_path, samp_file)
#site_file = os.path.join(dir_path, site_file)
plot_file = pmag.get_named_arg_from_sys("-Fp", default_val="")
crd = pmag.get_named_arg_from_sys("-crd", default_val="s")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
beg_pca, end_pca = "", ""
if '-dir' in sys.argv:
ind = sys.argv.index('-dir')
direction_type = sys.argv[ind + 1]
beg_pca = int(sys.argv[ind + 2])
end_pca = int(sys.argv[ind + 3])
if direction_type == 'L':
calculation_type = 'DE-BFL'
if direction_type == 'P':
calculation_type = 'DE-BFP'
if direction_type == 'F':
calculation_type = 'DE-FM'
if '-A' in sys.argv:
doave = 0
if '-sav' in sys.argv:
plots, verbose = 1, 0
#
first_save = 1
fnames = {
'measurements': meas_file,
'specimens': spec_file,
'samples': samp_file,
'sites': site_file
}
contribution = nb.Contribution(
dir_path,
custom_filenames=fnames,
read_tables=['measurements', 'specimens', 'samples', 'sites'])
#
# import specimens
specimen_cols = [
'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s',
'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma',
'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1',
'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95',
'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements',
'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment',
'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma',
'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma',
'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q',
'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max',
'meas_step_min', 'meas_step_unit', 'method_codes', 'sample',
'software_packages', 'specimen'
]
if 'specimens' in contribution.tables:
# contribution.propagate_name_down('sample','measurements')
spec_container = contribution.tables['specimens']
prior_spec_data = spec_container.get_records_for_code(
'LP-DIR', strict_match=False
) # look up all prior directional interpretations
#
# tie sample names to measurement data
#
else:
spec_container, prior_spec_data = None, []
#
# import samples for orientation info
#
if 'samples' in contribution.tables:
# contribution.propagate_name_down('site','measurements')
contribution.propagate_cols(
col_names=['azimuth', 'dip', 'orientation_flag'],
target_df_name='measurements',
source_df_name='samples')
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
#
ZED = {}
ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3
pmagplotlib.plot_init(ZED['eqarea'], 6, 6)
pmagplotlib.plot_init(ZED['zijd'], 6, 6)
pmagplotlib.plot_init(ZED['demag'], 6, 6)
# save_pca=0
angle, direction_type, setangle = "", "", 0
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LT-NO|LT-AF-Z|LT-T-Z|LT-M-Z') == True] # fish out steps for plotting
meas_data = meas_data[meas_data['method_codes'].str.contains(
'AN|ARM|LP-TRM|LP-PI-ARM') == False] # strip out unwanted experiments
intensity_types = [
col_name for col_name in meas_data.columns if col_name in intlist
]
# plot first intensity method found - normalized to initial value anyway -
# doesn't matter which used
int_key = intensity_types[0]
# get all the non-null intensity records of the same type
meas_data = meas_data[meas_data[int_key].notnull()]
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
# need to treat LP-NO specially for af data, treatment should be zero,
# otherwise 273.
meas_data['treatment'] = meas_data['treat_ac_field'].where(
cond=meas_data['treat_ac_field'] != '0', other=meas_data['treat_temp'])
meas_data['ZI'] = 1 # initialize these to one
meas_data['instrument_codes'] = "" # initialize these to blank
# for unusual case of microwave power....
if 'treat_mw_power' in meas_data.columns:
meas_data.loc[
meas_data.treat_mw_power != 0,
'treatment'] = meas_data.treat_mw_power * meas_data.treat_mw_time
#
# get list of unique specimen names from measurement data
#
# this is a list of all the specimen names
specimen_names = meas_data.specimen.unique()
specimen_names = specimen_names.tolist()
specimen_names.sort()
#
# set up new DataFrame for this sessions specimen interpretations
#
data_container = nb.MagicDataFrame(dtype='specimens',
columns=specimen_cols)
# this is for interpretations from this session
current_spec_data = data_container.df
locname = 'LookItUp'
if specimen == "":
k = 0
else:
k = specimen_names.index(specimen)
# let's look at the data now
while k < len(specimen_names):
# set the current specimen for plotting
this_specimen = specimen_names[k]
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
if setangle == 0:
angle = ""
this_specimen_measurements = meas_data[
meas_data['specimen'].str.contains(
this_specimen) == True] # fish out this specimen
this_specimen_measurements = this_specimen_measurements[
this_specimen_measurements['flag'].str.contains(
'g') == True] # fish out this specimen
if len(this_specimen_measurements) != 0: # if there are measurements
#
# set up datablock [[treatment,dec, inc, int, direction_type],[....]]
#
#
# figure out the method codes
#
units, methods, title = "", "", this_specimen
# this is a list of all the specimen method codes`
meas_meths = this_specimen_measurements.method_codes.unique()
tr = pd.to_numeric(this_specimen_measurements.treatment).tolist()
if set(tr) == set([0]):
k += 1
continue
for m in meas_meths:
if 'LT-AF-Z' in m:
units = 'T' # units include tesla
tr[0] = 0
if 'LT-T-Z' in m:
units = units + ":K" # units include kelvin
if 'LT-M-Z' in m:
units = units + ':J' # units include joules
tr[0] = 0
units = units.strip(':') # strip off extra colons
if 'LP-' in m:
methods = methods + ":" + m
decs = pd.to_numeric(this_specimen_measurements.dir_dec).tolist()
incs = pd.to_numeric(this_specimen_measurements.dir_inc).tolist()
#
# fix the coordinate system
#
if coord != '-1': # need to transform coordinates to geographic
azimuths = pd.to_numeric(this_specimen_measurements.azimuth
).tolist() # get the azimuths
# get the azimuths
dips = pd.to_numeric(this_specimen_measurements.dip).tolist()
dirs = [decs, incs, azimuths, dips]
# this transposes the columns and rows of the list of lists
dirs_geo = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dogeo_V(dirs_geo)
if coord == '100': # need to do tilt correction too
bed_dip_dirs = pd.to_numeric(
this_specimen_measurements.bed_dip_dir).tolist(
) # get the azimuths
bed_dips = pd.to_numeric(this_specimen_measurements.bed_dip
).tolist() # get the azimuths
dirs = [decs, incs, bed_dip_dirs, bed_dips]
# this transposes the columns and rows of the list of lists
dirs_tilt = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dotilt_V(dirs_tilt)
title = title + '_t'
else:
title = title + '_g'
if angle == "":
angle = decs[0]
ints = pd.to_numeric(this_specimen_measurements[int_key]).tolist()
ZI = this_specimen_measurements.ZI.tolist()
flags = this_specimen_measurements.flag.tolist()
codes = this_specimen_measurements.instrument_codes.tolist()
datalist = [tr, decs, incs, ints, ZI, flags, codes]
# this transposes the columns and rows of the list of lists
datablock = list(map(list, list(zip(*datalist))))
pmagplotlib.plotZED(ZED, datablock, angle, title, units)
if verbose:
pmagplotlib.drawFIGS(ZED)
#
# collect info for current_specimen_interpretation dictionary
#
if beg_pca == "" and len(prior_spec_data) != 0:
#
# find prior interpretation
#
prior_specimen_interpretations = prior_spec_data[
prior_spec_data['specimen'].str.contains(
this_specimen) == True]
beg_pcas = pd.to_numeric(prior_specimen_interpretations.
meas_step_min.values).tolist()
end_pcas = pd.to_numeric(prior_specimen_interpretations.
meas_step_max.values).tolist()
spec_methods = prior_specimen_interpretations.method_codes.tolist(
)
# step through all prior interpretations and plot them
for ind in range(len(beg_pcas)):
spec_meths = spec_methods[ind].split(':')
for m in spec_meths:
if 'DE-BFL' in m:
calculation_type = 'DE-BFL' # best fit line
if 'DE-BFP' in m:
calculation_type = 'DE-BFP' # best fit plane
if 'DE-FM' in m:
calculation_type = 'DE-FM' # fisher mean
if 'DE-BFL-A' in m:
calculation_type = 'DE-BFL-A' # anchored best fit line
start, end = tr.index(beg_pcas[ind]), tr.index(
end_pcas[ind]
) # getting the starting and ending points
# calculate direction/plane
mpars = pmag.domean(datablock, start, end,
calculation_type)
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
else:
start, end = int(beg_pca), int(end_pca)
# calculate direction/plane
mpars = pmag.domean(datablock, start, end, calculation_type)
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
if plots == 1 or specimen != "":
if plot_file == "":
basename = title
else:
basename = plot_file
files = {}
for key in list(ZED.keys()):
files[key] = basename + '_' + key + '.' + fmt
pmagplotlib.saveP(ZED, files)
if specimen != "":
sys.exit()
if verbose:
recnum = 0
for plotrec in datablock:
if units == 'T':
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] * 1e3, " mT",
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "K":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] - 273, ' C',
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "J":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0], ' J',
plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if 'K' in units and 'T' in units:
if plotrec[0] >= 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] - 273, ' C',
plotrec[3], plotrec[1], plotrec[2],
plotrec[6]))
if plotrec[0] < 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' %
(plotrec[5], recnum, plotrec[0] * 1e3, " mT",
plotrec[3], plotrec[1], plotrec[2],
plotrec[6]))
recnum += 1
# we have a current interpretation
elif mpars["specimen_direction_type"] != "Error":
#
# create a new specimen record for the interpreation for this
# specimen
this_specimen_interpretation = {
col: ""
for col in specimen_cols
}
# this_specimen_interpretation["analysts"]=user
this_specimen_interpretation['software_packages'] = version_num
this_specimen_interpretation['specimen'] = this_specimen
this_specimen_interpretation["method_codes"] = calculation_type
this_specimen_interpretation["meas_step_unit"] = units
this_specimen_interpretation["meas_step_min"] = tr[start]
this_specimen_interpretation["meas_step_max"] = tr[end]
this_specimen_interpretation["dir_dec"] = '%7.1f' % (
mpars['specimen_dec'])
this_specimen_interpretation["dir_inc"] = '%7.1f' % (
mpars['specimen_inc'])
this_specimen_interpretation["dir_dang"] = '%7.1f' % (
mpars['specimen_dang'])
this_specimen_interpretation["dir_n_measurements"] = '%i' % (
mpars['specimen_n'])
this_specimen_interpretation["dir_tilt_correction"] = coord
methods = methods.replace(" ", "")
if "T" in units:
methods = methods + ":LP-DIR-AF"
if "K" in units:
methods = methods + ":LP-DIR-T"
if "J" in units:
methods = methods + ":LP-DIR-M"
this_specimen_interpretation["method_codes"] = methods.strip(
':')
this_specimen_interpretation[
"experiments"] = this_specimen_measurements.experiment.unique(
)[0]
#
# print some stuff
#
if calculation_type != 'DE-FM':
this_specimen_interpretation["dir_mad_free"] = '%7.1f' % (
mpars['specimen_mad'])
this_specimen_interpretation["dir_alpha95"] = ''
if verbose:
if units == 'K':
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) - 273,
float(this_specimen_interpretation[
"meas_step_max"]) - 273,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif units == 'T':
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) * 1e3,
float(this_specimen_interpretation[
"meas_step_max"]) * 1e3,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation[
'meas_step_min']) < 1.0:
min = float(this_specimen_interpretation[
'meas_step_min']) * 1e3
else:
min = float(this_specimen_interpretation[
'meas_step_min']) - 273
if float(this_specimen_interpretation[
'meas_step_max']) < 1.0:
max = float(this_specimen_interpretation[
'meas_step_max']) * 1e3
else:
max = float(this_specimen_interpretation[
'meas_step_max']) - 273
print(
'%s %i %7.1f %i %i %7.1f %7.1f %7.1f %s \n' %
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
min, max,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]),
float(this_specimen_interpretation[
"meas_step_max"]),
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
this_specimen_interpretation["dir_alpha95"] = '%7.1f' % (
mpars['specimen_alpha95'])
this_specimen_interpretation["dir_mad_free"] = ''
if verbose:
if 'K' in units:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurments"]),
float(this_specimen_interpretation[
"dir_mad_free"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) - 273,
float(this_specimen_interpretation[
"meas_step_max"]) - 273,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n'
%
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_alpha95"]),
float(
this_specimen_interpretation["dir_dang"]),
float(this_specimen_interpretation[
"meas_step_min"]) * 1e3,
float(this_specimen_interpretation[
"meas_step_max"]) * 1e3,
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation[
'meas_step_min']) < 1.0:
min = float(this_specimen_interpretation[
'meas_step_min']) * 1e3
else:
min = float(this_specimen_interpretation[
'meas_step_min']) - 273
if float(this_specimen_interpretation[
'meas_step_max']) < 1.0:
max = float(this_specimen_interpretation[
'meas_step_max']) * 1e3
else:
max = float(this_specimen_interpretation[
'meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %s \n' % (
this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(
this_specimen_interpretation["dir_alpha95"]
), min, max,
float(this_specimen_interpretation["dir_dec"]),
float(this_specimen_interpretation["dir_inc"]),
calculation_type))
else:
print(
'%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' %
(this_specimen_interpretation["specimen"],
int(this_specimen_interpretation[
"dir_n_measurements"]),
float(this_specimen_interpretation[
"dir_alpha95"]),
float(this_specimen_interpretation[
"meas_step_min"]),
float(this_specimen_interpretation[
"meas_step_max"]),
float(
this_specimen_interpretation["dir_dec"]),
float(
this_specimen_interpretation["dir_inc"]),
calculation_type))
if verbose:
saveit = input("Save this interpretation? [y]/n \n")
# START HERE
#
# if len(current_spec_data)==0: # no interpretations yet for this session
# print "no current interpretation"
# beg_pca,end_pca="",""
# calculation_type=""
# get the ones that meet the current coordinate system
else:
print("no data")
if verbose:
input('Ready for next specimen ')
k += 1
def main():
"""
NAME
dayplot_magic.py
DESCRIPTION
makes 'day plots' (Day et al. 1977) and squareness/coercivity,
plots 'linear mixing' curve from Dunlop and Carter-Stiglitz (2006).
squareness coercivity of remanence (Neel, 1955) plots after
Tauxe et al. (2002)
SYNTAX
dayplot_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input hysteresis file, default is specimens.txt
-fmt [svg,png,jpg] format for output plots
-sav saves plots and quits quietly
"""
args = sys.argv
if "-h" in args:
print main.__doc__
sys.exit()
verbose = pmagplotlib.verbose
dir_path = pmag.get_named_arg_from_sys('-WD', '.')
fmt = pmag.get_named_arg_from_sys('-fmt', 'svg')
if '-sav' in sys.argv:
plots = 1
verbose = False
else:
plots = 0
infile = pmag.get_named_arg_from_sys("-f", "specimens.txt")
fnames = {'specimens': infile}
con = nb.Contribution(dir_path,
read_tables=['specimens'],
custom_filenames=fnames)
spec_container = con.tables['specimens']
spec_df = spec_container.df
#
# initialize some variables
# define figure numbers for Day,S-Bc,S-Bcr
DSC = {}
DSC['day'], DSC['S-Bc'], DSC['S-Bcr'], DSC['bcr1-bcr2'] = 1, 2, 3, 4
pmagplotlib.plot_init(DSC['day'], 5, 5)
pmagplotlib.plot_init(DSC['S-Bc'], 5, 5)
pmagplotlib.plot_init(DSC['S-Bcr'], 5, 5)
pmagplotlib.plot_init(DSC['bcr1-bcr2'], 5, 5)
S, BcrBc, Bcr2, Bc, hsids, Bcr = [], [], [], [], [], []
Bcr1, Bcr1Bc, S1 = [], [], []
locations = ''
if 'location' in spec_df.columns:
locations = spec_df['location'].unique()
do_rem = bool('rem_bcr' in spec_df.columns)
for ind, row in spec_df.iterrows():
if row['hyst_bcr'] and row['hyst_mr_moment']:
S.append(
float(row['hyst_mr_moment']) / float(row['hyst_ms_moment']))
Bcr.append(float(row['hyst_bcr']))
Bc.append(float(row['hyst_bc']))
BcrBc.append(Bcr[-1] / Bc[-1])
hsids.append(row['specimen'])
if do_rem:
if row['rem_bcr'] and float(row['rem_bcr']) > 0:
try:
Bcr1.append(float(row['rem_bcr']))
Bcr1Bc.append(Bcr1[-1] / Bc[-1])
S1.append(S[-1])
Bcr2.append(Bcr[-1])
except ValueError:
if verbose:
print 'hysteresis data for ', row['specimen'],
print ' not found'
#
# now plot the day and S-Bc, S-Bcr plots
#
if len(Bcr1) > 0:
pmagplotlib.plotDay(DSC['day'], Bcr1Bc, S1, 'ro')
pmagplotlib.plotSBcr(DSC['S-Bcr'], Bcr1, S1, 'ro')
pmagplotlib.plot_init(DSC['bcr1-bcr2'], 5, 5)
pmagplotlib.plotBcr(DSC['bcr1-bcr2'], Bcr1, Bcr2)
else:
del DSC['bcr1-bcr2']
pmagplotlib.plotDay(DSC['day'], BcrBc, S, 'bs')
pmagplotlib.plotSBcr(DSC['S-Bcr'], Bcr, S, 'bs')
pmagplotlib.plotSBc(DSC['S-Bc'], Bc, S, 'bs')
files = {}
if len(locations) > 0:
locations = locations[:-1]
for key in DSC.keys():
files[
key] = 'LO:_' + locations + '_' + 'SI:__SA:__SP:__TY:_' + key + '_.' + fmt
if verbose:
pmagplotlib.drawFIGS(DSC)
ans = raw_input(" S[a]ve to save plots, return to quit: ")
if ans == "a":
pmagplotlib.saveP(DSC, files)
else:
sys.exit()
if plots:
pmagplotlib.saveP(DSC, files)
def main():
"""
NAME
dayplot_magic.py
DESCRIPTION
makes 'day plots' (Day et al. 1977) and squareness/coercivity,
plots 'linear mixing' curve from Dunlop and Carter-Stiglitz (2006).
squareness coercivity of remanence (Neel, 1955) plots after
Tauxe et al. (2002)
SYNTAX
dayplot_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input hysteresis file, default is specimens.txt
-fmt [svg,png,jpg] format for output plots
-sav saves plots and quits quietly
"""
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
verbose = pmagplotlib.verbose
dir_path = pmag.get_named_arg_from_sys('-WD', '.')
fmt = pmag.get_named_arg_from_sys('-fmt', 'svg')
if '-sav' in sys.argv:
plots = 1
verbose = False
else:
plots = 0
infile = pmag.get_named_arg_from_sys("-f", "specimens.txt")
fnames = {'specimens': infile}
con = nb.Contribution(dir_path, read_tables=['specimens'],
custom_filenames=fnames)
spec_container = con.tables['specimens']
spec_df = spec_container.df
#
# initialize some variables
# define figure numbers for Day,S-Bc,S-Bcr
DSC = {}
DSC['day'], DSC['S-Bc'], DSC['S-Bcr'], DSC['bcr1-bcr2'] = 1, 2, 3, 4
pmagplotlib.plot_init(DSC['day'], 5, 5)
pmagplotlib.plot_init(DSC['S-Bc'], 5, 5)
pmagplotlib.plot_init(DSC['S-Bcr'], 5, 5)
pmagplotlib.plot_init(DSC['bcr1-bcr2'], 5, 5)
S, BcrBc, Bcr2, Bc, hsids, Bcr = [], [], [], [], [], []
Bcr1, Bcr1Bc, S1 = [], [], []
locations = ''
if 'location' in spec_df.columns:
locations = spec_df['location'].unique()
do_rem = bool('rem_bcr' in spec_df.columns)
for ind, row in spec_df.iterrows():
if row['hyst_bcr'] and row['hyst_mr_moment']:
S.append(old_div(float(row['hyst_mr_moment']), float(row['hyst_ms_moment'])))
Bcr.append(float(row['hyst_bcr']))
Bc.append(float(row['hyst_bc']))
BcrBc.append(old_div(Bcr[-1], Bc[-1]))
hsids.append(row['specimen'])
if do_rem:
if row['rem_bcr'] and float(row['rem_bcr']) > 0:
try:
Bcr1.append(float(row['rem_bcr']))
Bcr1Bc.append(old_div(Bcr1[-1], Bc[-1]))
S1.append(S[-1])
Bcr2.append(Bcr[-1])
except ValueError:
if verbose:
print('hysteresis data for ', row['specimen'], end=' ')
print(' not found')
#
# now plot the day and S-Bc, S-Bcr plots
#
if len(Bcr1) > 0:
pmagplotlib.plotDay(DSC['day'], Bcr1Bc, S1, 'ro')
pmagplotlib.plotSBcr(DSC['S-Bcr'], Bcr1, S1, 'ro')
pmagplotlib.plot_init(DSC['bcr1-bcr2'], 5, 5)
pmagplotlib.plotBcr(DSC['bcr1-bcr2'], Bcr1, Bcr2)
else:
del DSC['bcr1-bcr2']
pmagplotlib.plotDay(DSC['day'], BcrBc, S, 'bs')
pmagplotlib.plotSBcr(DSC['S-Bcr'], Bcr, S, 'bs')
pmagplotlib.plotSBc(DSC['S-Bc'], Bc, S, 'bs')
files = {}
if len(locations) > 0:
locations = locations[:-1]
for key in list(DSC.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_' + locations + '_' + 'SI:__SA:__SP:__TY:_' + key + '_.' + fmt
else: # use more readable plot naming convention
files[key] = '{}_{}.{}'.format(locations, key, fmt)
if verbose:
pmagplotlib.drawFIGS(DSC)
ans = input(" S[a]ve to save plots, return to quit: ")
if ans == "a":
pmagplotlib.saveP(DSC, files)
else:
sys.exit()
if plots:
pmagplotlib.saveP(DSC, files)
def main():
"""
NAME
plotXY.py
DESCRIPTION
Makes simple X,Y plots
INPUT FORMAT
X,Y data in columns
SYNTAX
plotxy.py [command line options]
OPTIONS
-h prints this help message
-f FILE to set file name on command line
-c col1 col2 specify columns to plot
-xsig col3 specify xsigma if desired
-ysig col4 specify xsigma if desired
-b xmin xmax ymin ymax, sets bounds
-sym SYM SIZE specify symbol to plot: default is red dots, 10 pt
-S don't plot the symbols
-xlab XLAB
-ylab YLAB
-l connect symbols with lines
-fmt [svg,png,pdf,eps] specify output format, default is svg
-sav saves plot and quits
-poly X plot a degree X polynomial through the data
-skip n Number of lines to skip before reading in data
"""
fmt, plot = 'svg', 0
col1, col2 = 0, 1
sym, size = 'ro', 50
xlab, ylab = '', ''
lines = 0
if '-h' in sys.argv:
print main.__doc__
sys.exit()
if '-f' in sys.argv:
ind = sys.argv.index('-f')
file = sys.argv[ind + 1]
if '-fmt' in sys.argv:
ind = sys.argv.index('-fmt')
fmt = sys.argv[ind + 1]
if '-sav' in sys.argv: plot = 1
if '-c' in sys.argv:
ind = sys.argv.index('-c')
col1 = int(sys.argv[ind + 1]) - 1
col2 = int(sys.argv[ind + 2]) - 1
if '-xsig' in sys.argv:
ind = sys.argv.index('-xsig')
col3 = int(sys.argv[ind + 1]) - 1
if '-ysig' in sys.argv:
ind = sys.argv.index('-ysig')
col4 = int(sys.argv[ind + 1]) - 1
if '-xlab' in sys.argv:
ind = sys.argv.index('-xlab')
xlab = sys.argv[ind + 1]
if '-ylab' in sys.argv:
ind = sys.argv.index('-ylab')
ylab = sys.argv[ind + 1]
if '-b' in sys.argv:
ind = sys.argv.index('-b')
xmin = float(sys.argv[ind + 1])
xmax = float(sys.argv[ind + 2])
ymin = float(sys.argv[ind + 3])
ymax = float(sys.argv[ind + 4])
if '-poly' in sys.argv:
ind = sys.argv.index('-poly')
degr = sys.argv[ind + 1]
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = sys.argv[ind + 1]
size = int(sys.argv[ind + 2])
if '-l' in sys.argv: lines = 1
if '-S' in sys.argv: sym = ''
skip = int(pmag.get_named_arg_from_sys('-skip', default_val=0))
X, Y = [], []
Xerrs, Yerrs = [], []
f = open(file, 'rU')
for num in range(skip):
f.readline()
data = f.readlines()
for line in data:
line.replace('\n', '')
line.replace('\t', ' ')
rec = line.split()
X.append(float(rec[col1]))
Y.append(float(rec[col2]))
if '-xsig' in sys.argv: Xerrs.append(float(rec[col3]))
if '-ysig' in sys.argv: Yerrs.append(float(rec[col4]))
if '-poly' in sys.argv:
pylab.plot(xs, ys)
coeffs = numpy.polyfit(X, Y, degr)
correl = numpy.corrcoef(X, Y)**2
polynomial = numpy.poly1d(coeffs)
xs = numpy.linspace(numpy.min(X), numpy.max(X), 10)
ys = polynomial(xs)
pylab.plot(xs, ys)
print polynomial
if degr == '1': print 'R-square value =', '%5.4f' % (correl[0, 1])
if sym != '':
pylab.scatter(X, Y, marker=sym[1], c=sym[0], s=size)
else:
pylab.plot(X, Y)
if '-xsig' in sys.argv and '-ysig' in sys.argv:
pylab.errorbar(X, Y, xerr=Xerrs, yerr=Yerrs, fmt=None)
if '-xsig' in sys.argv and '-ysig' not in sys.argv:
pylab.errorbar(X, Y, xerr=Xerrs, fmt=None)
if '-xsig' not in sys.argv and '-ysig' in sys.argv:
pylab.errorbar(X, Y, yerr=Yerrs, fmt=None)
if xlab != '': pylab.xlabel(xlab)
if ylab != '': pylab.ylabel(ylab)
if lines == 1: pylab.plot(X, Y, 'k-')
if '-b' in sys.argv: pylab.axis([xmin, xmax, ymin, ymax])
if plot == 0:
pylab.show()
else:
pylab.savefig('plotXY.' + fmt)
print 'Figure saved as ', 'plotXY.' + fmt
sys.exit()
def main():
"""
NAME
aniso_magic.py
DESCRIPTION
plots anisotropy data with either bootstrap or hext ellipses
SYNTAX
aniso_magic.py [-h] [command line options]
OPTIONS
-h plots help message and quits
-usr USER: set the user name
-f AFILE, specify specimens.txt formatted file for input
-fsa SAMPFILE, specify samples.txt file (required to plot by site)
-fsi SITEFILE, specify site file (required to include location information)
-x Hext [1963] and bootstrap
-B DON'T do bootstrap, do Hext
-par Tauxe [1998] parametric bootstrap
-v plot bootstrap eigenvectors instead of ellipses
-sit plot by site instead of entire file
-crd [s,g,t] coordinate system, default is specimen (g=geographic, t=tilt corrected)
-P don't make any plots - just fill in the specimens, samples, sites tables
-sav don't make the tables - just save all the plots
-fmt [svg, jpg, eps] format for output images, pdf default
-gtc DEC INC dec,inc of pole to great circle [down(up) in green (cyan)
-d Vi DEC INC; Vi (1,2,3) to compare to direction DEC INC
-nb N; specifies the number of bootstraps - default is 1000
DEFAULTS
AFILE: specimens.txt
plot bootstrap ellipses of Constable & Tauxe [1987]
NOTES
minor axis: circles
major axis: triangles
principal axis: squares
directions are plotted on the lower hemisphere
for bootstrapped eigenvector components: Xs: blue, Ys: red, Zs: black
"""
args = sys.argv
if "-h" in args:
print main.__doc__
sys.exit()
#version_num = pmag.get_version()
verbose = pmagplotlib.verbose
dir_path = pmag.get_named_arg_from_sys("-WD", ".")
num_bootstraps = pmag.get_named_arg_from_sys("-nb", 1000)
#user = pmag.get_named_arg_from_sys("-usr", "")
ipar = pmag.get_flag_arg_from_sys("-par", true=1, false=0)
ihext = pmag.get_flag_arg_from_sys("-x", true=1, false=0)
ivec = pmag.get_flag_arg_from_sys("-v", true=1, false=0)
iplot = pmag.get_flag_arg_from_sys("-P", true=0, false=1)
isite = pmag.get_flag_arg_from_sys("-sit", true=1, false=0)
iboot, vec = 1, 0
infile = pmag.get_named_arg_from_sys('-f', 'specimens.txt')
samp_file = pmag.get_named_arg_from_sys('-fsa', 'samples.txt')
site_file = pmag.get_named_arg_from_sys('-fsi', 'sites.txt')
#outfile = pmag.get_named_arg_from_sys("-F", "rmag_results.txt")
fmt = pmag.get_named_arg_from_sys("-fmt", "pdf")
hpars, bpars = [], []
CS, crd = -1, 's'
ResRecs = []
comp, Dir, PDir = 0, [], []
if '-B' in args:
iboot, ihext = 0, 1
if '-crd' in sys.argv:
ind = sys.argv.index('-crd')
crd = sys.argv[ind+1]
if crd == 'g':
CS = 0
if crd == 't':
CS = 100
if '-sav' in args:
plots = 1
verbose = 0
else:
plots = 0
if '-gtc' in args:
ind = args.index('-gtc')
d, i = float(args[ind+1]), float(args[ind+2])
PDir.append(d)
PDir.append(i)
if '-d' in args:
comp = 1
ind = args.index('-d')
vec = int(args[ind+1])-1
Dir = [float(args[ind+2]), float(args[ind+3])]
#
# set up plots
#
ANIS = {}
initcdf, inittcdf = 0, 0
ANIS['data'], ANIS['conf'] = 1, 2
if iboot == 1:
ANIS['tcdf'] = 3
if iplot == 1:
inittcdf = 1
pmagplotlib.plot_init(ANIS['tcdf'], 5, 5)
if comp == 1 and iplot == 1:
initcdf = 1
ANIS['vxcdf'], ANIS['vycdf'], ANIS['vzcdf'] = 4, 5, 6
pmagplotlib.plot_init(ANIS['vxcdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vycdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vzcdf'], 5, 5)
if iplot == 1:
pmagplotlib.plot_init(ANIS['conf'], 5, 5)
pmagplotlib.plot_init(ANIS['data'], 5, 5)
# read in the data
fnames = {'specimens': infile, 'samples': samp_file, 'sites': site_file}
con = nb.Contribution(dir_path, read_tables=['specimens', 'samples', 'sites'],
custom_filenames=fnames)
spec_container = con.tables['specimens']
spec_df = con.propagate_name_down('location', 'specimens')
# get only anisotropy records
spec_df = spec_container.get_records_for_code('AE-', strict_match=False)
if 'aniso_tilt_correction' not in spec_df.columns:
spec_df['aniso_tilt_correction'] = None
orlist = spec_df['aniso_tilt_correction'].dropna().unique()
if CS not in orlist:
if len(orlist) > 0:
CS = orlist[0]
else:
CS = -1
if CS == -1:
crd = 's'
if CS == 0:
crd = 'g'
if CS == 100:
crd = 't'
if verbose:
print "desired coordinate system not available, using available: ", crd
if isite == 1:
sitelist = spec_df['site'].unique()
sitelist.sort()
plt = len(sitelist)
else:
plt = 1
k = 0
while k < plt:
site = ""
loc_name = ""
sdata, Ss = [], [] # list of S format data
if isite == 0:
sdata = spec_df
if 'location' in sdata.columns:
loc_name = ':'.join(sdata['location'].unique())
else:
site = sitelist[k]
sdata = spec_df[spec_df['site'] == site]
if 'location' in sdata.columns:
loc_name = sdata['location'][0]
csrecs = sdata[sdata['aniso_tilt_correction'] == CS]
#anitypes = csrecs['aniso_type'].unique()
for name in ['citations', 'location', 'site', 'sample']:
if name not in csrecs:
csrecs[name] = ""
Locs = csrecs['location'].unique()
#Sites = csrecs['site'].unique()
#Samples = csrecs['sample'].unique()
#Specimens = csrecs['specimen'].unique()
#Cits = csrecs['citations'].unique()
for ind, rec in csrecs.iterrows():
s = [float(i.strip()) for i in rec['aniso_s'].split(':')]
if s[0] <= 1.0:
Ss.append(s) # protect against crap
# tau,Vdirs=pmag.doseigs(s)
# do we need fpars somewhere???
# fpars = pmag.dohext(int(rec["aniso_s_n_measurements"]) -6, float(rec["aniso_s_sigma"]), s)
# fill in ResRecs (ignoring this for now, grab it from aniso_magic if needed)
if len(Ss) > 1:
title = "LO:_" + loc_name + '_SI:_' + site + '_SA:__SP:__CO:_' + crd
bpars, hpars = pmagplotlib.plotANIS(ANIS, Ss, iboot, ihext, ivec, ipar,
title, iplot, comp, vec, Dir, num_bootstraps)
if len(PDir) > 0:
pmagplotlib.plotC(ANIS['data'], PDir, 90., 'g')
pmagplotlib.plotC(ANIS['conf'], PDir, 90., 'g')
if verbose and plots == 0:
pmagplotlib.drawFIGS(ANIS)
if plots == 1:
save(ANIS,fmt,title)
if hpars != [] and ihext == 1:
HextRec = {}
#for key in ResRec.keys():HextRec[key]=ResRec[key] # copy over stuff
HextRec["anisotropy_v1_dec"] = '%7.1f'%(hpars["v1_dec"])
HextRec["anisotropy_v2_dec"] = '%7.1f'%(hpars["v2_dec"])
HextRec["anisotropy_v3_dec"] = '%7.1f'%(hpars["v3_dec"])
HextRec["anisotropy_v1_inc"] = '%7.1f'%(hpars["v1_inc"])
HextRec["anisotropy_v2_inc"] = '%7.1f'%(hpars["v2_inc"])
HextRec["anisotropy_v3_inc"] = '%7.1f'%(hpars["v3_inc"])
HextRec["anisotropy_t1"] = '%10.8f'%(hpars["t1"])
HextRec["anisotropy_t2"] = '%10.8f'%(hpars["t2"])
HextRec["anisotropy_t3"] = '%10.8f'%(hpars["t3"])
HextRec["anisotropy_hext_F"] = '%7.1f '%(hpars["F"])
HextRec["anisotropy_hext_F12"] = '%7.1f '%(hpars["F12"])
HextRec["anisotropy_hext_F23"] = '%7.1f '%(hpars["F23"])
HextRec["anisotropy_v1_eta_semi_angle"] = '%7.1f '%(hpars["e12"])
HextRec["anisotropy_v1_eta_dec"] = '%7.1f '%(hpars["v2_dec"])
HextRec["anisotropy_v1_eta_inc"] = '%7.1f '%(hpars["v2_inc"])
HextRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f '%(hpars["e13"])
HextRec["anisotropy_v1_zeta_dec"] = '%7.1f '%(hpars["v3_dec"])
HextRec["anisotropy_v1_zeta_inc"] = '%7.1f '%(hpars["v3_inc"])
HextRec["anisotropy_v2_eta_semi_angle"] = '%7.1f '%(hpars["e12"])
HextRec["anisotropy_v2_eta_dec"] = '%7.1f '%(hpars["v1_dec"])
HextRec["anisotropy_v2_eta_inc"] = '%7.1f '%(hpars["v1_inc"])
HextRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f '%(hpars["e23"])
HextRec["anisotropy_v2_zeta_dec"] = '%7.1f '%(hpars["v3_dec"])
HextRec["anisotropy_v2_zeta_inc"] = '%7.1f '%(hpars["v3_inc"])
HextRec["anisotropy_v3_eta_semi_angle"] = '%7.1f '%(hpars["e12"])
HextRec["anisotropy_v3_eta_dec"] = '%7.1f '%(hpars["v1_dec"])
HextRec["anisotropy_v3_eta_inc"] = '%7.1f '%(hpars["v1_inc"])
HextRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f '%(hpars["e23"])
HextRec["anisotropy_v3_zeta_dec"] = '%7.1f '%(hpars["v2_dec"])
HextRec["anisotropy_v3_zeta_inc"] = '%7.1f '%(hpars["v2_inc"])
HextRec["magic_method_codes"] = 'LP-AN:AE-H'
if verbose:
print "Hext Statistics: "
print " tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I"
print HextRec["anisotropy_t1"], HextRec["anisotropy_v1_dec"],
print HextRec["anisotropy_v1_inc"], HextRec["anisotropy_v1_eta_semi_angle"],
print HextRec["anisotropy_v1_eta_dec"], HextRec["anisotropy_v1_eta_inc"],
print HextRec["anisotropy_v1_zeta_semi_angle"], HextRec["anisotropy_v1_zeta_dec"],
print HextRec["anisotropy_v1_zeta_inc"]
#
print HextRec["anisotropy_t2"],HextRec["anisotropy_v2_dec"],
print HextRec["anisotropy_v2_inc"], HextRec["anisotropy_v2_eta_semi_angle"],
print HextRec["anisotropy_v2_eta_dec"], HextRec["anisotropy_v2_eta_inc"],
print HextRec["anisotropy_v2_zeta_semi_angle"], HextRec["anisotropy_v2_zeta_dec"],
print HextRec["anisotropy_v2_zeta_inc"]
#
print HextRec["anisotropy_t3"], HextRec["anisotropy_v3_dec"],
print HextRec["anisotropy_v3_inc"], HextRec["anisotropy_v3_eta_semi_angle"],
print HextRec["anisotropy_v3_eta_dec"], HextRec["anisotropy_v3_eta_inc"],
print HextRec["anisotropy_v3_zeta_semi_angle"], HextRec["anisotropy_v3_zeta_dec"],
print HextRec["anisotropy_v3_zeta_inc"]
#HextRec['magic_software_packages']=version_num
#ResRecs.append(HextRec)
if bpars != []:
BootRec = {}
#for key in ResRec.keys():BootRec[key]=ResRec[key] # copy over stuff
BootRec["anisotropy_v1_dec"] = '%7.1f'%(bpars["v1_dec"])
BootRec["anisotropy_v2_dec"] = '%7.1f'%(bpars["v2_dec"])
BootRec["anisotropy_v3_dec"] = '%7.1f'%(bpars["v3_dec"])
BootRec["anisotropy_v1_inc"] = '%7.1f'%(bpars["v1_inc"])
BootRec["anisotropy_v2_inc"] = '%7.1f'%(bpars["v2_inc"])
BootRec["anisotropy_v3_inc"] = '%7.1f'%(bpars["v3_inc"])
BootRec["anisotropy_t1"] = '%10.8f'%(bpars["t1"])
BootRec["anisotropy_t2"] = '%10.8f'%(bpars["t2"])
BootRec["anisotropy_t3"] = '%10.8f'%(bpars["t3"])
BootRec["anisotropy_v1_eta_inc"] = '%7.1f '%(bpars["v1_eta_inc"])
BootRec["anisotropy_v1_eta_dec"] = '%7.1f '%(bpars["v1_eta_dec"])
BootRec["anisotropy_v1_eta_semi_angle"] = '%7.1f '%(bpars["v1_eta"])
BootRec["anisotropy_v1_zeta_inc"] = '%7.1f '%(bpars["v1_zeta_inc"])
BootRec["anisotropy_v1_zeta_dec"] = '%7.1f '%(bpars["v1_zeta_dec"])
BootRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f '%(bpars["v1_zeta"])
BootRec["anisotropy_v2_eta_inc"] = '%7.1f '%(bpars["v2_eta_inc"])
BootRec["anisotropy_v2_eta_dec"] = '%7.1f '%(bpars["v2_eta_dec"])
BootRec["anisotropy_v2_eta_semi_angle"] = '%7.1f '%(bpars["v2_eta"])
BootRec["anisotropy_v2_zeta_inc"] = '%7.1f '%(bpars["v2_zeta_inc"])
BootRec["anisotropy_v2_zeta_dec"] = '%7.1f '%(bpars["v2_zeta_dec"])
BootRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f '%(bpars["v2_zeta"])
BootRec["anisotropy_v3_eta_inc"] = '%7.1f '%(bpars["v3_eta_inc"])
BootRec["anisotropy_v3_eta_dec"] = '%7.1f '%(bpars["v3_eta_dec"])
BootRec["anisotropy_v3_eta_semi_angle"] = '%7.1f '%(bpars["v3_eta"])
BootRec["anisotropy_v3_zeta_inc"] = '%7.1f '%(bpars["v3_zeta_inc"])
BootRec["anisotropy_v3_zeta_dec"] = '%7.1f '%(bpars["v3_zeta_dec"])
BootRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f '%(bpars["v3_zeta"])
BootRec["anisotropy_hext_F"] = ''
BootRec["anisotropy_hext_F12"] = ''
BootRec["anisotropy_hext_F23"] = ''
BootRec["magic_method_codes"] = 'LP-AN:AE-H:AE-BS' # regular bootstrap
if ipar == 1:
BootRec["magic_method_codes"] = 'LP-AN:AE-H:AE-BS-P' # parametric bootstrap
if verbose:
print "Boostrap Statistics: "
print " tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I"
print BootRec["anisotropy_t1"], BootRec["anisotropy_v1_dec"],
print BootRec["anisotropy_v1_inc"], BootRec["anisotropy_v1_eta_semi_angle"],
print BootRec["anisotropy_v1_eta_dec"], BootRec["anisotropy_v1_eta_inc"],
print BootRec["anisotropy_v1_zeta_semi_angle"], BootRec["anisotropy_v1_zeta_dec"],
print BootRec["anisotropy_v1_zeta_inc"]
#
print BootRec["anisotropy_t2"], BootRec["anisotropy_v2_dec"], BootRec["anisotropy_v2_inc"],
print BootRec["anisotropy_v2_eta_semi_angle"], BootRec["anisotropy_v2_eta_dec"],
print BootRec["anisotropy_v2_eta_inc"], BootRec["anisotropy_v2_zeta_semi_angle"],
print BootRec["anisotropy_v2_zeta_dec"], BootRec["anisotropy_v2_zeta_inc"]
#
print BootRec["anisotropy_t3"], BootRec["anisotropy_v3_dec"], BootRec["anisotropy_v3_inc"],
print BootRec["anisotropy_v3_eta_semi_angle"], BootRec["anisotropy_v3_eta_dec"],
print BootRec["anisotropy_v3_eta_inc"], BootRec["anisotropy_v3_zeta_semi_angle"],
print BootRec["anisotropy_v3_zeta_dec"], BootRec["anisotropy_v3_zeta_inc"]
#BootRec['magic_software_packages'] = version_num
ResRecs.append(BootRec)
k += 1
goon = 1
while goon == 1 and iplot == 1 and verbose:
if iboot == 1:
print "compare with [d]irection "
print " plot [g]reat circle, change [c]oord. system, change [e]llipse calculation, s[a]ve plots, [q]uit "
if isite == 1:
print " [p]revious, [s]ite, [q]uit, <return> for next "
ans = raw_input("")
if ans == "q":
sys.exit()
if ans == "e":
iboot, ipar, ihext, ivec = 1, 0, 0, 0
e = raw_input("Do Hext Statistics 1/[0]: ")
if e == "1":
ihext = 1
e = raw_input("Suppress bootstrap 1/[0]: ")
if e == "1":
iboot = 0
if iboot == 1:
e = raw_input("Parametric bootstrap 1/[0]: ")
if e == "1":
ipar = 1
e = raw_input("Plot bootstrap eigenvectors: 1/[0]: ")
if e == "1":
ivec=1
if iplot == 1:
if inittcdf == 0:
ANIS['tcdf'] = 3
pmagplotlib.plot_init(ANIS['tcdf'], 5, 5)
inittcdf = 1
bpars, hpars = pmagplotlib.plotANIS(ANIS, Ss, iboot, ihext, ivec, ipar, title, iplot,
comp, vec, Dir, num_bootstraps)
if verbose and plots == 0:
pmagplotlib.drawFIGS(ANIS)
if ans == "c":
print "Current Coordinate system is: "
if CS == -1:
print " Specimen"
if CS == 0:
print " Geographic"
if CS == 100:
print " Tilt corrected"
key = raw_input(" Enter desired coordinate system: [s]pecimen, [g]eographic, [t]ilt corrected ")
if key == 's':
CS = -1
if key == 'g':
CS = 0
if key == 't':
CS = 100
if CS not in orlist:
if len(orlist) > 0:
CS = orlist[0]
else:
CS = -1
if CS == -1:
crd = 's'
if CS == 0:
crd = 'g'
if CS == 100:
crd = 't'
print "desired coordinate system not available, using available: ", crd
k -= 1
goon = 0
if ans == "":
if isite == 1:
goon = 0
else:
print "Good bye "
sys.exit()
if ans == 'd':
if initcdf == 0:
initcdf = 1
ANIS['vxcdf'], ANIS['vycdf'], ANIS['vzcdf'] = 4, 5, 6
pmagplotlib.plot_init(ANIS['vxcdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vycdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vzcdf'], 5, 5)
Dir, comp = [], 1
print """
Input: Vi D I to compare eigenvector Vi with direction D/I
where Vi=1: principal
Vi=2: major
Vi=3: minor
D= declination of comparison direction
I= inclination of comparison direction"""
con = 1
while con == 1:
try:
vdi = raw_input("Vi D I: ").split()
vec = int(vdi[0])-1
Dir = [float(vdi[1]), float(vdi[2])]
con = 0
except IndexError:
print " Incorrect entry, try again "
bpars, hpars = pmagplotlib.plotANIS(ANIS, Ss, iboot, ihext, ivec, ipar, title,
iplot, comp, vec, Dir, num_bootstraps)
Dir, comp = [], 0
if ans == 'g':
con, cnt = 1, 0
while con == 1:
try:
print " Input: input pole to great circle ( D I) to plot a great circle: "
di = raw_input(" D I: ").split()
PDir.append(float(di[0]))
PDir.append(float(di[1]))
con=0
except:
cnt += 1
if cnt < 10:
print " enter the dec and inc of the pole on one line "
else:
print "ummm - you are doing something wrong - i give up"
sys.exit()
pmagplotlib.plotC(ANIS['data'], PDir, 90., 'g')
pmagplotlib.plotC(ANIS['conf'], PDir, 90., 'g')
if verbose and plots == 0:
pmagplotlib.drawFIGS(ANIS)
if ans == "p":
k -= 2
goon = 0
if ans == "q":
k = plt
goon = 0
if ans == "s":
keepon = 1
site = raw_input(" print site or part of site desired: ")
while keepon == 1:
try:
k = sitelist.index(site)
keepon = 0
except:
tmplist = []
for qq in range(len(sitelist)):
if site in sitelist[qq]:
tmplist.append(sitelist[qq])
print site, " not found, but this was: "
print tmplist
site = raw_input('Select one or try again\n ')
k = sitelist.index(site)
goon, ans = 0, ""
if ans == "a":
locs = pmag.makelist(Locs)
site_name = "_"
if isite:
site_name = site
title = "LO:_" + locs + '_SI:_' + site_name + '_SA:__SP:__CO:_' + crd
save(ANIS, fmt, title)
goon = 0
else:
if verbose:
print 'skipping plot - not enough data points'
k += 1
# put rmag_results stuff here
#if len(ResRecs)>0:
# ResOut,keylist=pmag.fillkeys(ResRecs)
# pmag.magic_write(outfile,ResOut,'rmag_results')
if verbose:
print " Good bye "
def main():
"""
NAME
thellier_magic.py
DESCRIPTION
plots Thellier-Thellier data in version 3.0 format
Reads saved interpretations from a specimen formatted table, default: specimens.txt
SYNTAX
thellier_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEAS, set measurements input file, default is 'measurements.txt'
-fsp PRIOR, set specimens.txt prior interpretations file, default is 'specimens.txt'
-fcr CRIT, set criteria file for grading. # not yet implemented
-fmt [svg,png,jpg], format for images - default is svg
-sav, saves plots with out review (in format specified by -fmt key or default)
-spc SPEC, plots single specimen SPEC, saves plot with specified format
with optional -b bounds and quits
-b BEG END: sets bounds for calculation
BEG: starting step number for slope calculation
END: ending step number for slope calculation
-z use only z component difference for pTRM calculation
OUTPUT
figures:
ALL: numbers refer to temperature steps in command line window
1) Arai plot: closed circles are zero-field first/infield
open circles are infield first/zero-field
triangles are pTRM checks
squares are pTRM tail checks
VDS is vector difference sum
diamonds are bounds for interpretation
2) Zijderveld plot: closed (open) symbols are X-Y (X-Z) planes
X rotated to NRM direction
3) (De/Re)Magnetization diagram:
circles are NRM remaining
squares are pTRM gained
4) equal area projections:
green triangles are pTRM gained direction
red (purple) circles are lower(upper) hemisphere of ZI step directions
blue (cyan) squares are lower(upper) hemisphere IZ step directions
5) Optional: TRM acquisition
6) Optional: TDS normalization
command line window:
list is: temperature step numbers, temperatures (C), Dec, Inc, Int (units of measuements)
list of possible commands: type letter followed by return to select option
saving of plots creates image files with specimen, plot type as name
"""
#
# initializations
#
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
#
# default acceptance criteria
#
accept = pmag.default_criteria(0)[0] # set the default criteria
#
# parse command line options
#
plots, fmt, Zdiff = 0, 'svg', 0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg_from_sys("-f",
default_val="measurements.txt")
spec_file = pmag.get_named_arg_from_sys("-fsp",
default_val="specimens.txt")
crit_file = pmag.get_named_arg_from_sys("-fcr", default_val="criteria.txt")
spec_file = os.path.join(dir_path, spec_file)
meas_file = os.path.join(dir_path, meas_file)
crit_file = os.path.join(dir_path, crit_file)
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
if '-sav' in sys.argv: plots, verbose = 1, 0
if '-z' in sys.argv: Zdiff = 1
specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
if '-b' in sys.argv:
ind = sys.argv.index('-b')
start = int(sys.argv[ind + 1])
end = int(sys.argv[ind + 2])
else:
start, end = "", ""
fnames = {
'measurements': meas_file,
'specimens': spec_file,
'criteria': crit_file
}
contribution = nb.Contribution(
dir_path,
custom_filenames=fnames,
read_tables=['measurements', 'specimens', 'criteria'])
#
# import prior interpretations from specimen file
#
specimen_cols = [
'analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s',
'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma',
'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1',
'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95',
'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements',
'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment',
'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma',
'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma',
'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q',
'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max',
'meas_step_min', 'meas_step_unit', 'method_codes', 'sample',
'software_packages', 'specimen'
]
if 'specimens' in contribution.tables:
spec_container = contribution.tables['specimens']
prior_spec_data = spec_container.get_records_for_code(
'LP-PI-TRM',
strict_match=False) # look up all prior intensity interpretations
else:
spec_container, prior_spec_data = None, []
backup = 0
#
Mkeys = ['magn_moment', 'magn_volume', 'magn_mass']
#
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data['method_codes'] = meas_data['method_codes'].str.replace(
" ", "") # get rid of nasty spaces
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LP-PI-TRM|LP-TRM|LP-TRM-TD') ==
True] # fish out zero field steps for plotting
intensity_types = [
col_name for col_name in meas_data.columns if col_name in Mkeys
]
int_key = intensity_types[
0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
meas_data = meas_data[meas_data[int_key].notnull(
)] # get all the non-null intensity records of the same type
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
meas_data = meas_data[meas_data['flag'].str.contains('g') ==
True] # only the 'good' measurements
thel_data = meas_data[meas_data['method_codes'].str.contains('LP-PI-TRM')
== True] # get all the Thellier data
trm_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM') ==
True] # get all the TRM acquisition data
td_data = meas_data[meas_data['method_codes'].str.contains('LP-TRM-TD') ==
True] # get all the TD data
anis_data = meas_data[meas_data['method_codes'].str.contains('LP-AN') ==
True] # get all the anisotropy data
#
# get list of unique specimen names from measurement data
#
specimen_names = meas_data.specimen.unique(
) # this is a Series of all the specimen names
specimen_names = specimen_names.tolist() # turns it into a list
specimen_names.sort() # sorts by specimen name
#
# set up new DataFrame for this sessions specimen interpretations
#
spec_container = nb.MagicDataFrame(dtype='specimens',
columns=specimen_cols)
current_spec_data = spec_container.df # this is for interpretations from this session
if specimen == "": # do all specimens
k = 0
else:
k = specimen_names.index(specimen) # just do this one
# define figure numbers for arai, zijderveld and
# de-,re-magnetization diagrams
AZD = {}
AZD['deremag'], AZD['zijd'], AZD['arai'], AZD['eqarea'] = 1, 2, 3, 4
pmagplotlib.plot_init(AZD['arai'], 5, 5)
pmagplotlib.plot_init(AZD['zijd'], 5, 5)
pmagplotlib.plot_init(AZD['deremag'], 5, 5)
pmagplotlib.plot_init(AZD['eqarea'], 5, 5)
if len(trm_data) > 0:
AZD['TRM'] = 5
pmagplotlib.plot_init(AZD['TRM'], 5, 5)
if len(td_data) > 0:
AZD['TDS'] = 6
pmagplotlib.plot_init(AZD['TDS'], 5, 5)
#
while k < len(specimen_names):
this_specimen = specimen_names[
k] # set the current specimen for plotting
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
#
# set up datablocks
#
thelblock = thel_data[thel_data['specimen'].str.contains(this_specimen)
== True] # fish out this specimen
trmblock = trm_data[trm_data['specimen'].str.contains(this_specimen) ==
True] # fish out this specimen
tdsrecs = td_data[td_data['specimen'].str.contains(this_specimen) ==
True] # fish out this specimen
anisblock = anis_data[anis_data['specimen'].str.contains(this_specimen)
== True] # fish out the anisotropy data
prior_specimen_interpretations = prior_spec_data[
prior_spec_data['specimen'].str.contains(
this_specimen) == True] # fish out prior interpretation
#
# sort data into types
#
araiblock, field = pmag.sortarai(thelblock,
this_specimen,
Zdiff,
version=3)
first_Z = araiblock[0]
GammaChecks = araiblock[5]
if len(first_Z) < 3:
if backup == 0:
k += 1
if verbose:
print('skipping specimen - moving forward ', this_specimen)
else:
k -= 1
if verbose:
print('skipping specimen - moving backward ',
this_specimen)
else:
backup = 0
zijdblock, units = pmag.find_dmag_rec(this_specimen,
thelblock,
version=3)
if start == "" and len(prior_specimen_interpretations) > 0:
if verbose: print('Looking up saved interpretation....')
#
# get prior interpretation steps
#
beg_int = pd.to_numeric(prior_specimen_interpretations.
meas_step_min.values).tolist()[0]
end_int = pd.to_numeric(prior_specimen_interpretations.
meas_step_max.values).tolist()[0]
else:
beg_int, end_int = "", ""
recnum = 0
if verbose: print("index step Dec Inc Int Gamma")
for plotrec in zijdblock:
if plotrec[0] == beg_int:
start = recnum # while we are at it, collect these bounds
if plotrec[0] == end_int: end = recnum
if verbose:
if GammaChecks != "":
gamma = ""
for g in GammaChecks:
if g[0] == plotrec[0] - 273:
gamma = g[1]
break
if gamma != "":
print('%i %i %7.1f %7.1f %8.3e %7.1f' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3], gamma))
else:
print('%i %i %7.1f %7.1f %8.3e ' %
(recnum, plotrec[0] - 273, plotrec[1],
plotrec[2], plotrec[3]))
recnum += 1
for fig in list(AZD.keys()):
pmagplotlib.clearFIG(AZD[fig]) # clear all figures
pmagplotlib.plotAZ(AZD, araiblock, zijdblock, this_specimen,
units[0])
if verbose: pmagplotlib.drawFIGS(AZD)
pars, errcode = pmag.PintPars(thelblock,
araiblock,
zijdblock,
start,
end,
accept,
version=3)
pars['measurement_step_unit'] = "K"
pars['experiment_type'] = 'LP-PI-TRM'
#
# work on saving interpretations stuff later
#
if errcode != 1: # no problem in PintPars
pars["specimen_lab_field_dc"] = field
pars["specimen_int"] = -1 * field * pars["specimen_b"]
pars["er_specimen_name"] = this_specimen
#pars,kill=pmag.scoreit(pars,this_specimen_interpretation,accept,'',verbose) # deal with this later
pars["specimen_grade"] = 'None'
pars['measurement_step_min'] = pars['meas_step_min']
pars['measurement_step_max'] = pars['meas_step_max']
if pars['measurement_step_unit'] == 'K':
outstr = "specimen Tmin Tmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma Gamma_max \n"
pars_out = (this_specimen, (pars["meas_step_min"] - 273),
(pars["meas_step_max"] -
273), (pars["specimen_int_n"]),
1e6 * (pars["specimen_lab_field_dc"]),
1e6 * (pars["specimen_int"]),
pars["specimen_b"], pars["specimen_q"],
pars["specimen_f"], pars["specimen_fvds"],
pars["specimen_b_beta"], pars["int_mad_free"],
pars["int_dang"], pars["int_drats"],
pars["int_n_ptrm"], pars["specimen_grade"],
np.sqrt(pars["specimen_rsc"]),
int(pars["int_md"]), pars["specimen_b_sigma"],
pars['specimen_gamma'])
outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f' % pars_out + '\n'
elif pars['measurement_step_unit'] == 'J':
outstr = "specimen Wmin Wmax N lab_field B_anc b q f(coe) Fvds beta MAD Dang Drats Nptrm Grade R MD% sigma ThetaMax DeltaMax GammaMax\n"
pars_out = (
this_specimen, (pars["meas_step_min"]),
(pars["meas_step_max"]), (pars["specimen_int_n"]),
1e6 * (pars["specimen_lab_field_dc"]),
1e6 * (pars["specimen_int"]), pars["specimen_b"],
pars["specimen_q"], pars["specimen_f"],
pars["specimen_fvds"], pars["specimen_b_beta"],
pars["specimen_int_mad"], pars["specimen_int_dang"],
pars["specimen_drats"], pars["specimen_int_ptrm_n"],
pars["specimen_grade"], np.sqrt(pars["specimen_rsc"]),
int(pars["specimen_md"]), pars["specimen_b_sigma"],
pars["specimen_theta"], pars["specimen_delta"],
pars["specimen_gamma"])
outstring = '%s %4.0f %4.0f %i %4.1f %4.1f %5.3f %5.1f %5.3f %5.3f %5.3f %7.1f %7.1f %7.1f %s %s %6.3f %i %5.3f %7.1f %7.1f %7.1f' % pars_out + '\n'
print(outstr)
print(outstring)
pmagplotlib.plotB(AZD, araiblock, zijdblock, pars)
mpars = pmag.domean(araiblock[1], start, end, 'DE-BFL')
if verbose:
pmagplotlib.drawFIGS(AZD)
print('pTRM direction= ',
'%7.1f' % (mpars['specimen_dec']),
' %7.1f' % (mpars['specimen_inc']), ' MAD:',
'%7.1f' % (mpars['specimen_mad']))
if len(anisblock) > 0: # this specimen has anisotropy data
if verbose:
print('Found anisotropy record... but ignoring for now ')
if plots == 1:
if fmt != "pmag":
files = {}
for key in list(AZD.keys()):
files[
key] = 'SP:_' + this_specimen + '_TY:_' + key + '_' + '.' + fmt
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['deremag'] = 'DeReMag Plot'
titles['zijd'] = 'Zijderveld Plot'
titles['arai'] = 'Arai Plot'
titles['TRM'] = 'TRM Acquisition data'
AZD = pmagplotlib.addBorders(AZD, titles, black,
purple)
pmagplotlib.saveP(AZD, files)
else: # save in pmag format
print('pmag format no longer supported')
#script="grep "+this_specimen+" output.mag | thellier -mfsi"
#script=script+' %8.4e'%(field)
#min='%i'%((pars["measurement_step_min"]-273))
#Max='%i'%((pars["measurement_step_max"]-273))
#script=script+" "+min+" "+Max
#script=script+" |plotxy;cat mypost >>thellier.ps\n"
#pltf.write(script)
#pmag.domagicmag(outf,MeasRecs)
if specimen != "": sys.exit() # syonara
if verbose:
ans = input('Return for next specimen, q to quit: ')
if ans == 'q': sys.exit()
k += 1 # moving on
def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input file, default is measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
plots = 0
pltspec = ""
verbose = pmagplotlib.verbose
#version_num = pmag.get_version()
dir_path = pmag.get_named_arg_from_sys('-WD', '.')
dir_path = os.path.realpath(dir_path)
meas_file = pmag.get_named_arg_from_sys('-f', 'measurements.txt')
fmt = pmag.get_named_arg_from_sys('-fmt', 'png')
if '-sav' in args:
verbose = 0
plots = 1
if '-spc' in args:
ind = args.index("-spc")
pltspec = args[ind+1]
verbose = 0
plots = 1
#
con = nb.Contribution(dir_path, read_tables=['measurements'],
custom_filenames={'measurements': meas_file})
# get as much name data as possible (used for naming plots)
if not 'measurements' in con.tables:
print("-W- No measurement file found")
return
con.propagate_location_to_measurements()
if 'measurements' not in con.tables:
print(main.__doc__)
print('bad file')
sys.exit()
meas_container = con.tables['measurements']
#meas_df = meas_container.df
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs = []
HDD = {}
HDD['hyst'] = 1
pmagplotlib.plot_init(HDD['hyst'], 5, 5)
#
# get list of unique experiment names and specimen names
#
sids = []
hyst_data = meas_container.get_records_for_code('LP-HYS')
#experiment_names = hyst_data['experiment_name'].unique()
if not len(hyst_data):
print("-W- No hysteresis data found")
return
sids = hyst_data['specimen'].unique()
# if 'treat_temp' is provided, use that value, otherwise assume 300
hyst_data['treat_temp'].where(hyst_data['treat_temp'].notnull(), '300', inplace=True)
# start at first specimen, or at provided specimen ('-spc')
k = 0
if pltspec != "":
try:
print(sids)
k = list(sids).index(pltspec)
except ValueError:
print('-W- No specimen named: {}.'.format(pltspec))
print('-W- Please provide a valid specimen name')
return
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
while k < len(sids):
locname, site, sample, synth = '', '', '', ''
s = sids[k]
if verbose:
print(s, k + 1, 'out of ', len(sids))
# B, M for hysteresis, Bdcd,Mdcd for irm-dcd data
B, M = [], []
# get all measurements for this specimen
spec = hyst_data[hyst_data['specimen'] == s]
# get names
if 'location' in spec:
locname = spec['location'][0]
if 'site' in spec:
site = spec['sample'][0]
if 'sample' in spec:
sample = spec['sample'][0]
# get all records with non-blank values in any intlist column
# find intensity data
for int_column in intlist:
if int_column in spec.columns:
int_col = int_column
break
meas_data = spec[spec[int_column].notnull()]
if len(meas_data) == 0:
break
#
c = ['k-', 'b-', 'c-', 'g-', 'm-', 'r-', 'y-']
cnum = 0
Temps = []
xlab, ylab, title = '', '', ''
Temps = meas_data['treat_temp'].unique()
for t in Temps:
print('working on t: ', t)
t_data = meas_data[meas_data['treat_temp'] == t]
m = int_col
B = t_data['meas_field_dc'].astype(float).values
M = t_data[m].astype(float).values
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = 'Field (T)'
ylab = m
title = 'Hysteresis: ' + s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD['hyst'])
pmagplotlib.plotXY(HDD['hyst'],B,M,sym=c[cnum],xlab=xlab,ylab=ylab,title=title)
pmagplotlib.plotXY(HDD['hyst'],[1.1*B.min(),1.1*B.max()],[0,0],sym='k-',xlab=xlab,ylab=ylab,title=title)
pmagplotlib.plotXY(HDD['hyst'],[0,0],[1.1*M.min(),1.1*M.max()],sym='k-',xlab=xlab,ylab=ylab,title=title)
if verbose:
pmagplotlib.drawFIGS(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
for key in list(HDD.keys()):
if pmagplotlib.isServer:
if synth == '':
files[key] = "LO:_"+locname+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else:
files[key] = 'SY:_'+synth+'_TY:_'+key+'_.'+fmt
else:
if synth == '':
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
else:
files[key] = "{}_{}.{}".format(synth, key, fmt)
pmagplotlib.saveP(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.drawFIGS(HDD)
ans = input("S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans == "a":
files = {}
for key in list(HDD.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[key] = "LO:_"+locname+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+s+'_TY:_'+key+'_.'+fmt
else: # use more readable plot naming convention
filename = ''
for item in [locname, site, sample, s, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key] = filename
pmagplotlib.saveP(HDD, files)
if ans == '':
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == 'q':
print("Good bye")
sys.exit()
if ans == 's':
keepon = 1
specimen = input('Enter desired specimen name (or first part there of): ')
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print(specimen, " not found, but this was: ")
print(tmplist)
specimen = input('Select one or try again\n ')
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print('skipping this one - no hysteresis data')
k += 1
def main():
"""
NAME
aniso_magic.py
DESCRIPTION
plots anisotropy data with either bootstrap or hext ellipses
SYNTAX
aniso_magic.py [-h] [command line options]
OPTIONS
-h plots help message and quits
-usr USER: set the user name
-f AFILE, specify specimens.txt formatted file for input
-fsa SAMPFILE, specify samples.txt file (required to plot by site)
-fsi SITEFILE, specify site file (required to include location information)
-x Hext [1963] and bootstrap
-B DON'T do bootstrap, do Hext
-par Tauxe [1998] parametric bootstrap
-v plot bootstrap eigenvectors instead of ellipses
-sit plot by site instead of entire file
-crd [s,g,t] coordinate system, default is specimen (g=geographic, t=tilt corrected)
-P don't make any plots - just fill in the specimens, samples, sites tables
-sav don't make the tables - just save all the plots
-fmt [svg, jpg, eps] format for output images, pdf default
-gtc DEC INC dec,inc of pole to great circle [down(up) in green (cyan)
-d Vi DEC INC; Vi (1,2,3) to compare to direction DEC INC
-nb N; specifies the number of bootstraps - default is 1000
DEFAULTS
AFILE: specimens.txt
plot bootstrap ellipses of Constable & Tauxe [1987]
NOTES
minor axis: circles
major axis: triangles
principal axis: squares
directions are plotted on the lower hemisphere
for bootstrapped eigenvector components: Xs: blue, Ys: red, Zs: black
"""
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
#version_num = pmag.get_version()
verbose = pmagplotlib.verbose
dir_path = pmag.get_named_arg_from_sys("-WD", ".")
num_bootstraps = pmag.get_named_arg_from_sys("-nb", 1000)
#user = pmag.get_named_arg_from_sys("-usr", "")
ipar = pmag.get_flag_arg_from_sys("-par", true=1, false=0)
ihext = pmag.get_flag_arg_from_sys("-x", true=1, false=0)
ivec = pmag.get_flag_arg_from_sys("-v", true=1, false=0)
iplot = pmag.get_flag_arg_from_sys("-P", true=0, false=1)
isite = pmag.get_flag_arg_from_sys("-sit", true=1, false=0)
iboot, vec = 1, 0
infile = pmag.get_named_arg_from_sys('-f', 'specimens.txt')
samp_file = pmag.get_named_arg_from_sys('-fsa', 'samples.txt')
site_file = pmag.get_named_arg_from_sys('-fsi', 'sites.txt')
#outfile = pmag.get_named_arg_from_sys("-F", "rmag_results.txt")
fmt = pmag.get_named_arg_from_sys("-fmt", "pdf")
hpars, bpars = [], []
CS, crd = -1, 's'
ResRecs = []
comp, Dir, PDir = 0, [], []
if '-B' in args:
iboot, ihext = 0, 1
if '-crd' in sys.argv:
ind = sys.argv.index('-crd')
crd = sys.argv[ind + 1]
if crd == 'g':
CS = 0
if crd == 't':
CS = 100
if '-sav' in args:
plots = 1
verbose = 0
else:
plots = 0
if '-gtc' in args:
ind = args.index('-gtc')
d, i = float(args[ind + 1]), float(args[ind + 2])
PDir.append(d)
PDir.append(i)
if '-d' in args:
comp = 1
ind = args.index('-d')
vec = int(args[ind + 1]) - 1
Dir = [float(args[ind + 2]), float(args[ind + 3])]
#
# set up plots
#
ANIS = {}
initcdf, inittcdf = 0, 0
ANIS['data'], ANIS['conf'] = 1, 2
if iboot == 1:
ANIS['tcdf'] = 3
if iplot == 1:
inittcdf = 1
pmagplotlib.plot_init(ANIS['tcdf'], 5, 5)
if comp == 1 and iplot == 1:
initcdf = 1
ANIS['vxcdf'], ANIS['vycdf'], ANIS['vzcdf'] = 4, 5, 6
pmagplotlib.plot_init(ANIS['vxcdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vycdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vzcdf'], 5, 5)
if iplot == 1:
pmagplotlib.plot_init(ANIS['conf'], 5, 5)
pmagplotlib.plot_init(ANIS['data'], 5, 5)
# read in the data
fnames = {'specimens': infile, 'samples': samp_file, 'sites': site_file}
con = nb.Contribution(dir_path,
read_tables=['specimens', 'samples', 'sites'],
custom_filenames=fnames)
con.propagate_location_to_specimens()
spec_container = con.tables['specimens']
# get only anisotropy records
spec_df = spec_container.get_records_for_code('AE-', strict_match=False)
if 'aniso_tilt_correction' not in spec_df.columns:
spec_df['aniso_tilt_correction'] = None
orlist = spec_df['aniso_tilt_correction'].dropna().unique()
if CS not in orlist:
if len(orlist) > 0:
CS = orlist[0]
else:
CS = -1
if CS == -1:
crd = 's'
if CS == 0:
crd = 'g'
if CS == 100:
crd = 't'
if verbose:
print("desired coordinate system not available, using available: ",
crd)
if isite == 1:
sitelist = spec_df['site'].unique()
sitelist.sort()
plt = len(sitelist)
else:
plt = 1
k = 0
while k < plt:
site = ""
loc_name = ""
sdata, Ss = [], [] # list of S format data
if isite == 0:
sdata = spec_df
if 'location' in sdata.columns:
loc_name = ':'.join(sdata['location'].unique())
else:
site = sitelist[k]
sdata = spec_df[spec_df['site'] == site]
if 'location' in sdata.columns:
loc_name = sdata['location'][0]
csrecs = sdata[sdata['aniso_tilt_correction'] == CS]
#anitypes = csrecs['aniso_type'].unique()
for name in ['citations', 'location', 'site', 'sample']:
if name not in csrecs:
csrecs[name] = ""
Locs = csrecs['location'].unique()
#Sites = csrecs['site'].unique()
#Samples = csrecs['sample'].unique()
#Specimens = csrecs['specimen'].unique()
#Cits = csrecs['citations'].unique()
for ind, rec in csrecs.iterrows():
s = [float(i.strip()) for i in rec['aniso_s'].split(':')]
if s[0] <= 1.0:
Ss.append(s) # protect against crap
# tau,Vdirs=pmag.doseigs(s)
# do we need fpars somewhere???
# fpars = pmag.dohext(int(rec["aniso_s_n_measurements"]) -6, float(rec["aniso_s_sigma"]), s)
# fill in ResRecs (ignoring this for now, grab it from aniso_magic if needed)
if len(Ss) > 1:
if pmagplotlib.isServer: # use server plot naming convention
title = "LO:_" + loc_name + '_SI:_' + site + '_SA:__SP:__CO:_' + crd
else: # use more readable plot naming convention
title = "{}_{}_{}".format(loc_name, site, crd)
bpars, hpars = pmagplotlib.plotANIS(ANIS, Ss, iboot, ihext, ivec,
ipar, title, iplot, comp, vec,
Dir, num_bootstraps)
if len(PDir) > 0:
pmagplotlib.plotC(ANIS['data'], PDir, 90., 'g')
pmagplotlib.plotC(ANIS['conf'], PDir, 90., 'g')
if verbose and plots == 0:
pmagplotlib.drawFIGS(ANIS)
if plots == 1:
save(ANIS, fmt, title)
if hpars != [] and ihext == 1:
HextRec = {}
#for key in ResRec.keys():HextRec[key]=ResRec[key] # copy over stuff
HextRec["anisotropy_v1_dec"] = '%7.1f' % (hpars["v1_dec"])
HextRec["anisotropy_v2_dec"] = '%7.1f' % (hpars["v2_dec"])
HextRec["anisotropy_v3_dec"] = '%7.1f' % (hpars["v3_dec"])
HextRec["anisotropy_v1_inc"] = '%7.1f' % (hpars["v1_inc"])
HextRec["anisotropy_v2_inc"] = '%7.1f' % (hpars["v2_inc"])
HextRec["anisotropy_v3_inc"] = '%7.1f' % (hpars["v3_inc"])
HextRec["anisotropy_t1"] = '%10.8f' % (hpars["t1"])
HextRec["anisotropy_t2"] = '%10.8f' % (hpars["t2"])
HextRec["anisotropy_t3"] = '%10.8f' % (hpars["t3"])
HextRec["anisotropy_hext_F"] = '%7.1f ' % (hpars["F"])
HextRec["anisotropy_hext_F12"] = '%7.1f ' % (hpars["F12"])
HextRec["anisotropy_hext_F23"] = '%7.1f ' % (hpars["F23"])
HextRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars["e12"])
HextRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (hpars["v2_dec"])
HextRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (hpars["v2_inc"])
HextRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars["e13"])
HextRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars["v3_dec"])
HextRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars["v3_inc"])
HextRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars["e12"])
HextRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (hpars["v1_dec"])
HextRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (hpars["v1_inc"])
HextRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars["e23"])
HextRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars["v3_dec"])
HextRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars["v3_inc"])
HextRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars["e12"])
HextRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (hpars["v1_dec"])
HextRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (hpars["v1_inc"])
HextRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars["e23"])
HextRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars["v2_dec"])
HextRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars["v2_inc"])
HextRec["magic_method_codes"] = 'LP-AN:AE-H'
if verbose:
print("Hext Statistics: ")
print(
" tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I"
)
print(HextRec["anisotropy_t1"],
HextRec["anisotropy_v1_dec"],
end=' ')
print(HextRec["anisotropy_v1_inc"],
HextRec["anisotropy_v1_eta_semi_angle"],
end=' ')
print(HextRec["anisotropy_v1_eta_dec"],
HextRec["anisotropy_v1_eta_inc"],
end=' ')
print(HextRec["anisotropy_v1_zeta_semi_angle"],
HextRec["anisotropy_v1_zeta_dec"],
end=' ')
print(HextRec["anisotropy_v1_zeta_inc"])
#
print(HextRec["anisotropy_t2"],
HextRec["anisotropy_v2_dec"],
end=' ')
print(HextRec["anisotropy_v2_inc"],
HextRec["anisotropy_v2_eta_semi_angle"],
end=' ')
print(HextRec["anisotropy_v2_eta_dec"],
HextRec["anisotropy_v2_eta_inc"],
end=' ')
print(HextRec["anisotropy_v2_zeta_semi_angle"],
HextRec["anisotropy_v2_zeta_dec"],
end=' ')
print(HextRec["anisotropy_v2_zeta_inc"])
#
print(HextRec["anisotropy_t3"],
HextRec["anisotropy_v3_dec"],
end=' ')
print(HextRec["anisotropy_v3_inc"],
HextRec["anisotropy_v3_eta_semi_angle"],
end=' ')
print(HextRec["anisotropy_v3_eta_dec"],
HextRec["anisotropy_v3_eta_inc"],
end=' ')
print(HextRec["anisotropy_v3_zeta_semi_angle"],
HextRec["anisotropy_v3_zeta_dec"],
end=' ')
print(HextRec["anisotropy_v3_zeta_inc"])
#HextRec['magic_software_packages']=version_num
#ResRecs.append(HextRec)
if bpars != []:
BootRec = {}
#for key in ResRec.keys():BootRec[key]=ResRec[key] # copy over stuff
BootRec["anisotropy_v1_dec"] = '%7.1f' % (bpars["v1_dec"])
BootRec["anisotropy_v2_dec"] = '%7.1f' % (bpars["v2_dec"])
BootRec["anisotropy_v3_dec"] = '%7.1f' % (bpars["v3_dec"])
BootRec["anisotropy_v1_inc"] = '%7.1f' % (bpars["v1_inc"])
BootRec["anisotropy_v2_inc"] = '%7.1f' % (bpars["v2_inc"])
BootRec["anisotropy_v3_inc"] = '%7.1f' % (bpars["v3_inc"])
BootRec["anisotropy_t1"] = '%10.8f' % (bpars["t1"])
BootRec["anisotropy_t2"] = '%10.8f' % (bpars["t2"])
BootRec["anisotropy_t3"] = '%10.8f' % (bpars["t3"])
BootRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
bpars["v1_eta_inc"])
BootRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
bpars["v1_eta_dec"])
BootRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
bpars["v1_eta"])
BootRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
bpars["v1_zeta_inc"])
BootRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
bpars["v1_zeta_dec"])
BootRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
bpars["v1_zeta"])
BootRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
bpars["v2_eta_inc"])
BootRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
bpars["v2_eta_dec"])
BootRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
bpars["v2_eta"])
BootRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
bpars["v2_zeta_inc"])
BootRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
bpars["v2_zeta_dec"])
BootRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
bpars["v2_zeta"])
BootRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
bpars["v3_eta_inc"])
BootRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
bpars["v3_eta_dec"])
BootRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
bpars["v3_eta"])
BootRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
bpars["v3_zeta_inc"])
BootRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
bpars["v3_zeta_dec"])
BootRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
bpars["v3_zeta"])
BootRec["anisotropy_hext_F"] = ''
BootRec["anisotropy_hext_F12"] = ''
BootRec["anisotropy_hext_F23"] = ''
BootRec[
"magic_method_codes"] = 'LP-AN:AE-H:AE-BS' # regular bootstrap
if ipar == 1:
BootRec[
"magic_method_codes"] = 'LP-AN:AE-H:AE-BS-P' # parametric bootstrap
if verbose:
print("Boostrap Statistics: ")
print(
" tau_i, V_i_D, V_i_I, V_i_zeta, V_i_zeta_D, V_i_zeta_I, V_i_eta, V_i_eta_D, V_i_eta_I"
)
print(BootRec["anisotropy_t1"],
BootRec["anisotropy_v1_dec"],
end=' ')
print(BootRec["anisotropy_v1_inc"],
BootRec["anisotropy_v1_eta_semi_angle"],
end=' ')
print(BootRec["anisotropy_v1_eta_dec"],
BootRec["anisotropy_v1_eta_inc"],
end=' ')
print(BootRec["anisotropy_v1_zeta_semi_angle"],
BootRec["anisotropy_v1_zeta_dec"],
end=' ')
print(BootRec["anisotropy_v1_zeta_inc"])
#
print(BootRec["anisotropy_t2"],
BootRec["anisotropy_v2_dec"],
BootRec["anisotropy_v2_inc"],
end=' ')
print(BootRec["anisotropy_v2_eta_semi_angle"],
BootRec["anisotropy_v2_eta_dec"],
end=' ')
print(BootRec["anisotropy_v2_eta_inc"],
BootRec["anisotropy_v2_zeta_semi_angle"],
end=' ')
print(BootRec["anisotropy_v2_zeta_dec"],
BootRec["anisotropy_v2_zeta_inc"])
#
print(BootRec["anisotropy_t3"],
BootRec["anisotropy_v3_dec"],
BootRec["anisotropy_v3_inc"],
end=' ')
print(BootRec["anisotropy_v3_eta_semi_angle"],
BootRec["anisotropy_v3_eta_dec"],
end=' ')
print(BootRec["anisotropy_v3_eta_inc"],
BootRec["anisotropy_v3_zeta_semi_angle"],
end=' ')
print(BootRec["anisotropy_v3_zeta_dec"],
BootRec["anisotropy_v3_zeta_inc"])
#BootRec['magic_software_packages'] = version_num
ResRecs.append(BootRec)
k += 1
goon = 1
while goon == 1 and iplot == 1 and verbose:
if iboot == 1:
print("compare with [d]irection ")
print(
" plot [g]reat circle, change [c]oord. system, change [e]llipse calculation, s[a]ve plots, [q]uit "
)
if isite == 1:
print(" [p]revious, [s]ite, [q]uit, <return> for next ")
ans = input("")
if ans == "q":
sys.exit()
if ans == "e":
iboot, ipar, ihext, ivec = 1, 0, 0, 0
e = input("Do Hext Statistics 1/[0]: ")
if e == "1":
ihext = 1
e = input("Suppress bootstrap 1/[0]: ")
if e == "1":
iboot = 0
if iboot == 1:
e = input("Parametric bootstrap 1/[0]: ")
if e == "1":
ipar = 1
e = input("Plot bootstrap eigenvectors: 1/[0]: ")
if e == "1":
ivec = 1
if iplot == 1:
if inittcdf == 0:
ANIS['tcdf'] = 3
pmagplotlib.plot_init(ANIS['tcdf'], 5, 5)
inittcdf = 1
bpars, hpars = pmagplotlib.plotANIS(
ANIS, Ss, iboot, ihext, ivec, ipar, title, iplot, comp,
vec, Dir, num_bootstraps)
if verbose and plots == 0:
pmagplotlib.drawFIGS(ANIS)
if ans == "c":
print("Current Coordinate system is: ")
if CS == -1:
print(" Specimen")
if CS == 0:
print(" Geographic")
if CS == 100:
print(" Tilt corrected")
key = input(
" Enter desired coordinate system: [s]pecimen, [g]eographic, [t]ilt corrected "
)
if key == 's':
CS = -1
if key == 'g':
CS = 0
if key == 't':
CS = 100
if CS not in orlist:
if len(orlist) > 0:
CS = orlist[0]
else:
CS = -1
if CS == -1:
crd = 's'
if CS == 0:
crd = 'g'
if CS == 100:
crd = 't'
print(
"desired coordinate system not available, using available: ",
crd)
k -= 1
goon = 0
if ans == "":
if isite == 1:
goon = 0
else:
print("Good bye ")
sys.exit()
if ans == 'd':
if initcdf == 0:
initcdf = 1
ANIS['vxcdf'], ANIS['vycdf'], ANIS['vzcdf'] = 4, 5, 6
pmagplotlib.plot_init(ANIS['vxcdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vycdf'], 5, 5)
pmagplotlib.plot_init(ANIS['vzcdf'], 5, 5)
Dir, comp = [], 1
print("""
Input: Vi D I to compare eigenvector Vi with direction D/I
where Vi=1: principal
Vi=2: major
Vi=3: minor
D= declination of comparison direction
I= inclination of comparison direction""")
con = 1
while con == 1:
try:
vdi = input("Vi D I: ").split()
vec = int(vdi[0]) - 1
Dir = [float(vdi[1]), float(vdi[2])]
con = 0
except IndexError:
print(" Incorrect entry, try again ")
bpars, hpars = pmagplotlib.plotANIS(
ANIS, Ss, iboot, ihext, ivec, ipar, title, iplot, comp,
vec, Dir, num_bootstraps)
Dir, comp = [], 0
if ans == 'g':
con, cnt = 1, 0
while con == 1:
try:
print(
" Input: input pole to great circle ( D I) to plot a great circle: "
)
di = input(" D I: ").split()
PDir.append(float(di[0]))
PDir.append(float(di[1]))
con = 0
except:
cnt += 1
if cnt < 10:
print(
" enter the dec and inc of the pole on one line "
)
else:
print(
"ummm - you are doing something wrong - i give up"
)
sys.exit()
pmagplotlib.plotC(ANIS['data'], PDir, 90., 'g')
pmagplotlib.plotC(ANIS['conf'], PDir, 90., 'g')
if verbose and plots == 0:
pmagplotlib.drawFIGS(ANIS)
if ans == "p":
k -= 2
goon = 0
if ans == "q":
k = plt
goon = 0
if ans == "s":
keepon = 1
site = input(" print site or part of site desired: ")
while keepon == 1:
try:
k = sitelist.index(site)
keepon = 0
except:
tmplist = []
for qq in range(len(sitelist)):
if site in sitelist[qq]:
tmplist.append(sitelist[qq])
print(site, " not found, but this was: ")
print(tmplist)
site = input('Select one or try again\n ')
k = sitelist.index(site)
goon, ans = 0, ""
if ans == "a":
locs = pmag.makelist(Locs)
site_name = "_"
if isite:
site_name = site
if pmagplotlib.isServer: # use server plot naming convention
title = "LO:_" + locs + '_SI:_' + site_name + '_SA:__SP:__CO:_' + crd
else: # use more readable plot naming convention
title = "{}_{}_{}".format(locs, site_name, crd)
save(ANIS, fmt, title)
goon = 0
else:
if verbose:
print('skipping plot - not enough data points')
k += 1
# put rmag_results stuff here
#if len(ResRecs)>0:
# ResOut,keylist=pmag.fillkeys(ResRecs)
# pmag.magic_write(outfile,ResOut,'rmag_results')
if verbose:
print(" Good bye ")
def main():
"""
NAME
eqarea_magic.py
DESCRIPTION
makes equal area projections from declination/inclination data
SYNTAX
eqarea_magic.py [command line options]
INPUT
takes magic formatted sites, samples, specimens, or measurements
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic, default='sites.txt'
supported types=[measurements, specimens, samples, sites]
-fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
default='specimens.txt'
-fsa FILE: specify sample file name, (required if you want to plot specimens by site)
default='samples.txt'
-fsi FILE: specify site file name, default='sites.txt'
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-sav save plot and quit quietly
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
# initialize some default variables
FIG = {} # plot dictionary
FIG["eqarea"] = 1 # eqarea is figure 1
plotE = 0
plt = 0 # default to not plotting
verbose = pmagplotlib.verbose
# extract arguments from sys.argv
if "-h" in sys.argv:
print main.__doc__
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
pmagplotlib.plot_init(FIG["eqarea"], 5, 5)
in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
full_in_file = os.path.join(dir_path, in_file)
plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
if plot_by == "all":
plot_key = "all"
elif plot_by == "sit":
plot_key = "site"
elif plot_by == "sam":
plot_key = "sample"
elif plot_by == "spc":
plot_key = "specimen"
else:
plot_key = "all"
if "-c" in sys.argv:
contour = 1
else:
contour = 0
if "-sav" in sys.argv:
plt = 1
verbose = 0
if "-ell" in sys.argv:
plotE = 1
ind = sys.argv.index("-ell")
ell_type = sys.argv[ind + 1]
ell_type = pmag.get_named_arg_from_sys("-ell", "F")
dist = ell_type.upper()
# if dist type is unrecognized, use Fisher
if dist not in ["F", "K", "B", "BE", "BV"]:
dist = "F"
if dist == "BV":
FIG["bdirs"] = 2
pmagplotlib.plot_init(FIG["bdirs"], 5, 5)
crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
dec_key = "dir_dec"
inc_key = "dir_inc"
tilt_key = "dir_tilt_correction"
# Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
#
fnames = {"specimens": spec_file, "samples": samp_file, "sites": site_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames, single_file=in_file)
# the object that contains the DataFrame + useful helper methods:
table_name = contribution.tables.keys()[0]
data_container = contribution.tables[table_name]
# the actual DataFrame:
data = data_container.df
# uses sample infile to add temporary site_name
# column to the specimen table
data_container = contribution.tables[table_name]
data = data_container.df
if (plot_key != "all") and (plot_key not in data.columns):
data = contribution.propagate_name_down(plot_key, table_name)
# add tilt key into DataFrame columns if it isn't there already
if tilt_key not in data.columns:
data.loc[:, tilt_key] = None
if verbose:
print len(data), " records read from ", in_file
# find desired dec,inc data:
dir_type_key = ""
#
# get plotlist if not plotting all records
#
plotlist = []
if plot_key != "all":
# return all where plot_key is not blank
if plot_key not in data.columns:
print 'Can\'t plot by "{}". That header is not in infile: {}'.format(plot_key, in_file)
return
plots = data[data[plot_key].notnull()]
plotlist = plots[plot_key].unique() # grab unique values
else:
plotlist.append("All")
for plot in plotlist:
if verbose:
print plot
if plot == "All":
# plot everything at once
plot_data = data
else:
# pull out only partial data
plot_data = data[data[plot_key] == plot]
DIblock = []
GCblock = []
# SLblock, SPblock = [], []
title = plot
mode = 1
k = 0
if dec_key not in plot_data.columns:
print "-W- No dec/inc data"
continue
# get all records where dec & inc values exist
plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
if plot_data.empty:
continue
# this sorting out is done in get_di_bock
# if coord == '0': # geographic, use records with no tilt key (or tilt_key 0)
# cond1 = plot_data[tilt_key].fillna('') == coord
# cond2 = plot_data[tilt_key].isnull()
# plot_data = plot_data[cond1 | cond2]
# else: # not geographic coordinates, use only records with correct tilt_key
# plot_data = plot_data[plot_data[tilt_key] == coord]
# get metadata for naming the plot file
locations = data_container.get_name("location", df_slice=plot_data)
site = data_container.get_name("site", df_slice=plot_data)
sample = data_container.get_name("sample", df_slice=plot_data)
specimen = data_container.get_name("specimen", df_slice=plot_data)
# make sure method_codes is in plot_data
if "method_codes" not in plot_data.columns:
plot_data["method_codes"] = ""
# get data blocks
DIblock = data_container.get_di_block(df_slice=plot_data, tilt_corr=coord, excl=["DE-BFP"])
# SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
# get great circles
great_circle_data = data_container.get_records_for_code("DE-BFP", incl=True, use_slice=True, sli=plot_data)
if len(great_circle_data) > 0:
gc_cond = great_circle_data[tilt_key] == coord
GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
# SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]
if len(DIblock) > 0:
if contour == 0:
pmagplotlib.plotEQ(FIG["eqarea"], DIblock, title)
else:
pmagplotlib.plotEQcont(FIG["eqarea"], DIblock)
else:
pmagplotlib.plotNET(FIG["eqarea"])
if len(GCblock) > 0:
for rec in GCblock:
pmagplotlib.plotC(FIG["eqarea"], rec, 90.0, "g")
if len(DIblock) == 0 and len(GCblock) == 0:
if verbose:
print "no records for plotting"
continue
# sys.exit()
if plotE == 1:
ppars = pmag.doprinc(DIblock) # get principal directions
nDIs, rDIs, npars, rpars = [], [], [], []
for rec in DIblock:
angle = pmag.angle([rec[0], rec[1]], [ppars["dec"], ppars["inc"]])
if angle > 90.0:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist == "B": # do on whole dataset
etitle = "Bingham confidence ellipse"
bpars = pmag.dobingham(DIblock)
for key in bpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (bpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (bpars[key])
npars.append(bpars["dec"])
npars.append(bpars["inc"])
npars.append(bpars["Zeta"])
npars.append(bpars["Zdec"])
npars.append(bpars["Zinc"])
npars.append(bpars["Eta"])
npars.append(bpars["Edec"])
npars.append(bpars["Einc"])
if dist == "F":
etitle = "Fisher confidence cone"
if len(nDIs) > 2:
fpars = pmag.fisher_mean(nDIs)
for key in fpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (fpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (fpars[key])
mode += 1
npars.append(fpars["dec"])
npars.append(fpars["inc"])
npars.append(fpars["alpha95"]) # Beta
npars.append(fpars["dec"])
isign = abs(fpars["inc"]) / fpars["inc"]
npars.append(fpars["inc"] - isign * 90.0) # Beta inc
npars.append(fpars["alpha95"]) # gamma
npars.append(fpars["dec"] + 90.0) # Beta dec
npars.append(0.0) # Beta inc
if len(rDIs) > 2:
fpars = pmag.fisher_mean(rDIs)
if verbose:
print "mode ", mode
for key in fpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (fpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (fpars[key])
mode += 1
rpars.append(fpars["dec"])
rpars.append(fpars["inc"])
rpars.append(fpars["alpha95"]) # Beta
rpars.append(fpars["dec"])
isign = abs(fpars["inc"]) / fpars["inc"]
rpars.append(fpars["inc"] - isign * 90.0) # Beta inc
rpars.append(fpars["alpha95"]) # gamma
rpars.append(fpars["dec"] + 90.0) # Beta dec
rpars.append(0.0) # Beta inc
if dist == "K":
etitle = "Kent confidence ellipse"
if len(nDIs) > 3:
kpars = pmag.dokent(nDIs, len(nDIs))
if verbose:
print "mode ", mode
for key in kpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (kpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (kpars[key])
mode += 1
npars.append(kpars["dec"])
npars.append(kpars["inc"])
npars.append(kpars["Zeta"])
npars.append(kpars["Zdec"])
npars.append(kpars["Zinc"])
npars.append(kpars["Eta"])
npars.append(kpars["Edec"])
npars.append(kpars["Einc"])
if len(rDIs) > 3:
kpars = pmag.dokent(rDIs, len(rDIs))
if verbose:
print "mode ", mode
for key in kpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (kpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (kpars[key])
mode += 1
rpars.append(kpars["dec"])
rpars.append(kpars["inc"])
rpars.append(kpars["Zeta"])
rpars.append(kpars["Zdec"])
rpars.append(kpars["Zinc"])
rpars.append(kpars["Eta"])
rpars.append(kpars["Edec"])
rpars.append(kpars["Einc"])
else: # assume bootstrap
if dist == "BE":
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
Bkpars = pmag.dokent(BnDIs, 1.0)
if verbose:
print "mode ", mode
for key in Bkpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (Bkpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (Bkpars[key])
mode += 1
npars.append(Bkpars["dec"])
npars.append(Bkpars["inc"])
npars.append(Bkpars["Zeta"])
npars.append(Bkpars["Zdec"])
npars.append(Bkpars["Zinc"])
npars.append(Bkpars["Eta"])
npars.append(Bkpars["Edec"])
npars.append(Bkpars["Einc"])
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
Bkpars = pmag.dokent(BrDIs, 1.0)
if verbose:
print "mode ", mode
for key in Bkpars.keys():
if key != "n" and verbose:
print " ", key, "%7.1f" % (Bkpars[key])
if key == "n" and verbose:
print " ", key, " %i" % (Bkpars[key])
mode += 1
rpars.append(Bkpars["dec"])
rpars.append(Bkpars["inc"])
rpars.append(Bkpars["Zeta"])
rpars.append(Bkpars["Zdec"])
rpars.append(Bkpars["Zinc"])
rpars.append(Bkpars["Eta"])
rpars.append(Bkpars["Edec"])
rpars.append(Bkpars["Einc"])
etitle = "Bootstrapped confidence ellipse"
elif dist == "BV":
sym = {"lower": ["o", "c"], "upper": ["o", "g"], "size": 3, "edgecolor": "face"}
if len(nDIs) > 5:
BnDIs = pmag.di_boot(nDIs)
pmagplotlib.plotEQsym(FIG["bdirs"], BnDIs, "Bootstrapped Eigenvectors", sym)
if len(rDIs) > 5:
BrDIs = pmag.di_boot(rDIs)
if len(nDIs) > 5: # plot on existing plots
pmagplotlib.plotDIsym(FIG["bdirs"], BrDIs, sym)
else:
pmagplotlib.plotEQ(FIG["bdirs"], BrDIs, "Bootstrapped Eigenvectors")
if dist == "B":
if len(nDIs) > 3 or len(rDIs) > 3:
pmagplotlib.plotCONF(FIG["eqarea"], etitle, [], npars, 0)
elif len(nDIs) > 3 and dist != "BV":
pmagplotlib.plotCONF(FIG["eqarea"], etitle, [], npars, 0)
if len(rDIs) > 3:
pmagplotlib.plotCONF(FIG["eqarea"], etitle, [], rpars, 0)
elif len(rDIs) > 3 and dist != "BV":
pmagplotlib.plotCONF(FIG["eqarea"], etitle, [], rpars, 0)
for key in FIG.keys():
files = {}
filename = pmag.get_named_arg_from_sys("-fname")
if filename:
filename += "." + fmt
else:
filename = (
"LO:_"
+ locations
+ "_SI:_"
+ site
+ "_SA:_"
+ sample
+ "_SP:_"
+ specimen
+ "_CO:_"
+ crd
+ "_TY:_"
+ key
+ "_."
+ fmt
)
files[key] = filename
if pmagplotlib.isServer:
black = "#000000"
purple = "#800080"
titles = {}
titles["eq"] = "Equal Area Plot"
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
if plt:
pmagplotlib.saveP(FIG, files)
continue
if verbose:
pmagplotlib.drawFIGS(FIG)
ans = raw_input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q":
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG, files)
continue
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg_from_sys("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg_from_sys("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg_from_sys("-f",
'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg_from_sys("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(
' By default, this information is not available in your measurement file.'
)
print(
' Trying to acquire this information from {}'.format(dir_path))
con = nb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(
plot_key))
con.write_table_to_file('measurements')
# read in data
data, file_type = pmag.magic_read(in_file)
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = [
'measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass'
]
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append(
[float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plotMT(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.drawFIGS(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
pmagplotlib.saveP(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
atrm_magic.py
DESCRIPTION
Converts ATRM data to best-fit tensor (6 elements plus sigma)
Original program ARMcrunch written to accomodate ARM anisotropy data
collected from 6 axial directions (+X,+Y,+Z,-X,-Y,-Z) using the
off-axis remanence terms to construct the tensor. A better way to
do the anisotropy of ARMs is to use 9,12 or 15 measurements in
the Hext rotational scheme.
SYNTAX
atrm_magic.py [-h][command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f FILE: specify input file, default is atrm_measurements.txt
-Fa FILE: specify anisotropy output file, default is trm_anisotropy.txt (MagIC 2.5 only)
-Fr FILE: specify results output file, default is atrm_results.txt (MagIC 2.5 only)
-Fsi FILE: specify output file, default is specimens.txt (MagIC 3 only)
-DM DATA_MODEL: specify MagIC 2 or MagIC 3, default is 3
INPUT
Input for the present program is a TRM acquisition data with an optional baseline.
The order of the measurements is:
Decs=[0,90,0,180,270,0,0,90,0]
Incs=[0,0,90,0,0,-90,0,0,90]
The last two measurements are optional
"""
# initialize some parameters
args = sys.argv
user = ""
meas_file = "atrm_measurements.txt"
rmag_anis = "trm_anisotropy.txt"
rmag_res = "atrm_results.txt"
dir_path = '.'
#
# get name of file from command line
#
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind + 1]
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-usr" in args:
ind = args.index("-usr")
user = sys.argv[ind + 1]
if "-f" in args:
ind = args.index("-f")
meas_file = sys.argv[ind + 1]
if "-Fa" in args:
ind = args.index("-Fa")
rmag_anis = args[ind + 1]
if "-Fr" in args:
ind = args.index("-Fr")
rmag_res = args[ind + 1]
data_model_num = int(pmag.get_named_arg_from_sys("-DM", 3))
spec_file = pmag.get_named_arg_from_sys("-Fsi", "specimens.txt")
spec_file = os.path.join(dir_path, spec_file)
meas_file = dir_path + '/' + meas_file
rmag_anis = dir_path + '/' + rmag_anis
rmag_res = dir_path + '/' + rmag_res
# read in data
if data_model_num == 3:
meas_data = []
meas_data3, file_type = pmag.magic_read(meas_file)
if file_type != 'measurements':
print(file_type, "This is not a valid measurements file ")
sys.exit()
# convert meas_data to 2.5
for rec in meas_data3:
meas_map = map_magic.meas_magic3_2_magic2_map
meas_data.append(map_magic.mapping(rec, meas_map))
else:
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(file_type, "This is not a valid magic_measurements file ")
sys.exit()
meas_data = pmag.get_dictitem(meas_data, 'magic_method_codes', 'LP-AN-TRM',
'has')
#
#
# get sorted list of unique specimen names
ssort = []
for rec in meas_data:
spec = rec["er_specimen_name"]
if spec not in ssort:
ssort.append(spec)
sids = sorted(ssort)
#
#
# work on each specimen
#
specimen, npos = 0, 6
RmagSpecRecs, RmagResRecs = [], []
SpecRecs, SpecRecs3 = [], []
while specimen < len(sids):
nmeas = 0
s = sids[specimen]
RmagSpecRec = {}
RmagResRec = {}
BX, X = [], []
method_codes = []
Spec0 = ""
#
# find the data from the meas_data file for this sample
# and get dec, inc, int and convert to x,y,z
#
# fish out data for this specimen name
data = pmag.get_dictitem(meas_data, 'er_specimen_name', s, 'T')
if len(data) > 5:
RmagSpecRec["rmag_anisotropy_name"] = data[0]["er_specimen_name"]
RmagSpecRec["er_location_name"] = data[0].get(
"er_location_name", "")
RmagSpecRec["er_specimen_name"] = data[0]["er_specimen_name"]
RmagSpecRec["er_sample_name"] = data[0].get("er_sample_name", "")
RmagSpecRec["er_site_name"] = data[0].get("er_site_name", "")
RmagSpecRec["magic_experiment_names"] = RmagSpecRec[
"rmag_anisotropy_name"] + ":ATRM"
RmagSpecRec["er_citation_names"] = "This study"
RmagResRec[
"rmag_result_name"] = data[0]["er_specimen_name"] + ":ATRM"
RmagResRec["er_location_names"] = data[0].get(
"er_location_names", "")
RmagResRec["er_specimen_names"] = data[0]["er_specimen_name"]
RmagResRec["er_sample_names"] = data[0].get("er_sample_name", "")
RmagResRec["er_site_names"] = data[0].get("er_site_name", "")
RmagResRec["magic_experiment_names"] = RmagSpecRec[
"rmag_anisotropy_name"] + ":ATRM"
RmagResRec["er_citation_names"] = "This study"
RmagSpecRec["anisotropy_type"] = "ATRM"
if "magic_instrument_codes" in list(data[0].keys()):
RmagSpecRec["magic_instrument_codes"] = data[0][
"magic_instrument_codes"]
else:
RmagSpecRec["magic_instrument_codes"] = ""
RmagSpecRec[
"anisotropy_description"] = "Hext statistics adapted to ATRM"
for rec in data:
meths = rec['magic_method_codes'].strip().split(':')
Dir = []
Dir.append(float(rec["measurement_dec"]))
Dir.append(float(rec["measurement_inc"]))
Dir.append(float(rec["measurement_magn_moment"]))
if "LT-T-Z" in meths:
BX.append(pmag.dir2cart(Dir)) # append baseline steps
elif "LT-T-I" in meths:
X.append(pmag.dir2cart(Dir))
nmeas += 1
#
if len(BX) == 1:
for i in range(len(X) - 1):
BX.append(BX[0]) # assume first 0 field step as baseline
elif len(BX) == 0: # assume baseline is zero
for i in range(len(X)):
BX.append([0., 0., 0.]) # assume baseline of 0
elif len(BX) != len(
X
): # if BX isn't just one measurement or one in between every infield step, just assume it is zero
print('something odd about the baselines - just assuming zero')
for i in range(len(X)):
BX.append([0., 0., 0.]) # assume baseline of 0
if nmeas < 6: # must have at least 6 measurements right now -
print('skipping specimen ', s, ' too few measurements')
specimen += 1
else:
# B matrix made from design matrix for positions
B, H, tmpH = pmag.designATRM(npos)
#
# subtract optional baseline and put in a work array
#
work = numpy.zeros((nmeas, 3), 'f')
for i in range(nmeas):
for j in range(3):
# subtract baseline, if available
work[i][j] = X[i][j] - BX[i][j]
#
# calculate tensor elements
# first put ARM components in w vector
#
w = numpy.zeros((npos * 3), 'f')
index = 0
for i in range(npos):
for j in range(3):
w[index] = work[i][j]
index += 1
s = numpy.zeros((6), 'f') # initialize the s matrix
for i in range(6):
for j in range(len(w)):
s[i] += B[i][j] * w[j]
trace = s[0] + s[1] + s[2] # normalize by the trace
for i in range(6):
s[i] = old_div(s[i], trace)
a = pmag.s2a(s)
#------------------------------------------------------------
# Calculating dels is different than in the Kappabridge
# routine. Use trace normalized tensor (a) and the applied
# unit field directions (tmpH) to generate model X,Y,Z
# components. Then compare these with the measured values.
#------------------------------------------------------------
S = 0.
comp = numpy.zeros((npos * 3), 'f')
for i in range(npos):
for j in range(3):
index = i * 3 + j
compare = a[j][0] * tmpH[i][0] + a[j][1] * \
tmpH[i][1] + a[j][2] * tmpH[i][2]
comp[index] = compare
for i in range(npos * 3):
d = old_div(w[i], trace) - comp[i] # del values
S += d * d
nf = float(npos * 3. - 6.) # number of degrees of freedom
if S > 0:
sigma = numpy.sqrt(old_div(S, nf))
else:
sigma = 0
hpars = pmag.dohext(nf, sigma, s)
#
# prepare for output
#
RmagSpecRec["anisotropy_s1"] = '%8.6f' % (s[0])
RmagSpecRec["anisotropy_s2"] = '%8.6f' % (s[1])
RmagSpecRec["anisotropy_s3"] = '%8.6f' % (s[2])
RmagSpecRec["anisotropy_s4"] = '%8.6f' % (s[3])
RmagSpecRec["anisotropy_s5"] = '%8.6f' % (s[4])
RmagSpecRec["anisotropy_s6"] = '%8.6f' % (s[5])
RmagSpecRec["anisotropy_mean"] = '%8.3e' % (old_div(trace, 3))
RmagSpecRec["anisotropy_sigma"] = '%8.6f' % (sigma)
RmagSpecRec["anisotropy_unit"] = "Am^2"
RmagSpecRec["anisotropy_n"] = '%i' % (npos)
RmagSpecRec["anisotropy_tilt_correction"] = '-1'
# used by thellier_gui - must be taken out for uploading
RmagSpecRec["anisotropy_F"] = '%7.1f ' % (hpars["F"])
# used by thellier_gui - must be taken out for uploading
RmagSpecRec["anisotropy_F_crit"] = hpars["F_crit"]
RmagResRec["anisotropy_t1"] = '%8.6f ' % (hpars["t1"])
RmagResRec["anisotropy_t2"] = '%8.6f ' % (hpars["t2"])
RmagResRec["anisotropy_t3"] = '%8.6f ' % (hpars["t3"])
RmagResRec["anisotropy_v1_dec"] = '%7.1f ' % (hpars["v1_dec"])
RmagResRec["anisotropy_v2_dec"] = '%7.1f ' % (hpars["v2_dec"])
RmagResRec["anisotropy_v3_dec"] = '%7.1f ' % (hpars["v3_dec"])
RmagResRec["anisotropy_v1_inc"] = '%7.1f ' % (hpars["v1_inc"])
RmagResRec["anisotropy_v2_inc"] = '%7.1f ' % (hpars["v2_inc"])
RmagResRec["anisotropy_v3_inc"] = '%7.1f ' % (hpars["v3_inc"])
RmagResRec["anisotropy_ftest"] = '%7.1f ' % (hpars["F"])
RmagResRec["anisotropy_ftest12"] = '%7.1f ' % (hpars["F12"])
RmagResRec["anisotropy_ftest23"] = '%7.1f ' % (hpars["F23"])
RmagResRec["result_description"] = 'Critical F: ' + \
hpars["F_crit"] + ';Critical F12/F13: ' + hpars["F12_crit"]
if hpars["e12"] > hpars["e13"]:
RmagResRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
else:
RmagResRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
if hpars["e23"] > hpars['e12']:
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
else:
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["tilt_correction"] = '-1'
RmagResRec["anisotropy_type"] = 'ATRM'
RmagResRec["magic_method_codes"] = 'LP-AN-TRM:AE-H'
RmagSpecRec["magic_method_codes"] = 'LP-AN-TRM:AE-H'
RmagResRec["magic_software_packages"] = pmag.get_version()
RmagSpecRec["magic_software_packages"] = pmag.get_version()
RmagSpecRecs.append(RmagSpecRec)
RmagResRecs.append(RmagResRec)
specimen += 1
if data_model_num == 3:
SpecRec = RmagResRec.copy()
SpecRec.update(RmagSpecRec)
SpecRecs.append(SpecRec)
# finished iterating through specimens,
# now we need to write out the data to files
if data_model_num == 3:
# translate records
for rec in SpecRecs:
rec3 = map_magic.convert_aniso('magic3', rec)
SpecRecs3.append(rec3)
# write output to 3.0 specimens file
pmag.magic_write(spec_file, SpecRecs3, 'specimens')
print("specimen data stored in {}".format(spec_file))
else:
# write output to 2.5 rmag_ files
pmag.magic_write(rmag_anis, RmagSpecRecs, 'rmag_anisotropy')
print("specimen tensor elements stored in ", rmag_anis)
pmag.magic_write(rmag_res, RmagResRecs, 'rmag_results')
print("specimen statistics and eigenparameters stored in ", rmag_res)
def main():
"""
NAME
aarm_magic.py
DESCRIPTION
Converts AARM data to best-fit tensor (6 elements plus sigma)
Original program ARMcrunch written to accomodate ARM anisotropy data
collected from 6 axial directions (+X,+Y,+Z,-X,-Y,-Z) using the
off-axis remanence terms to construct the tensor. A better way to
do the anisotropy of ARMs is to use 9,12 or 15 measurements in
the Hext rotational scheme.
SYNTAX
aarm_magic.py [-h][command line options]
OPTIONS
-h prints help message and quits
-usr USER: identify user, default is ""
-f FILE: specify input file, default is aarm_measurements.txt
-crd [s,g,t] specify coordinate system, requires samples file
-fsa FILE: specify er_samples.txt file, default is er_samples.txt (2.5) or samples.txt (3.0)
-Fa FILE: specify anisotropy output file, default is arm_anisotropy.txt (MagIC 2.5 only)
-Fr FILE: specify results output file, default is aarm_results.txt (MagIC 2.5 only)
-Fsi FILE: specify output file, default is specimens.txt (MagIC 3 only)
-DM DATA_MODEL: specify MagIC 2 or MagIC 3, default is 3
INPUT
Input for the present program is a series of baseline, ARM pairs.
The baseline should be the AF demagnetized state (3 axis demag is
preferable) for the following ARM acquisition. The order of the
measurements is:
positions 1,2,3, 6,7,8, 11,12,13 (for 9 positions)
positions 1,2,3,4, 6,7,8,9, 11,12,13,14 (for 12 positions)
positions 1-15 (for 15 positions)
"""
# initialize some parameters
args = sys.argv
if "-h" in args:
print(main.__doc__)
sys.exit()
user = ""
meas_file = "aarm_measurements.txt"
rmag_anis = "arm_anisotropy.txt"
rmag_res = "aarm_results.txt"
dir_path = '.'
#
# get name of file from command line
#
data_model_num = int(pmag.get_named_arg_from_sys("-DM", 3))
spec_file = pmag.get_named_arg_from_sys("-Fsi", "specimens.txt")
if data_model_num == 3:
samp_file = pmag.get_named_arg_from_sys("-fsa", "samples.txt")
else:
samp_file = pmag.get_named_arg_from_sys("-fsa", "er_samples.txt")
if '-WD' in args:
ind = args.index('-WD')
dir_path = args[ind + 1]
if "-usr" in args:
ind = args.index("-usr")
user = sys.argv[ind + 1]
if "-f" in args:
ind = args.index("-f")
meas_file = sys.argv[ind + 1]
coord = '-1'
if "-crd" in sys.argv:
ind = sys.argv.index("-crd")
coord = sys.argv[ind + 1]
if coord == 's':
coord = '-1'
if coord == 'g':
coord = '0'
if coord == 't':
coord = '100'
if "-Fa" in args:
ind = args.index("-Fa")
rmag_anis = args[ind + 1]
if "-Fr" in args:
ind = args.index("-Fr")
rmag_res = args[ind + 1]
meas_file = dir_path + '/' + meas_file
samp_file = dir_path + '/' + samp_file
rmag_anis = dir_path + '/' + rmag_anis
rmag_res = dir_path + '/' + rmag_res
spec_file = os.path.join(dir_path, spec_file)
# read in data
# read in data
if data_model_num == 3:
meas_data = []
meas_data3, file_type = pmag.magic_read(meas_file)
if file_type != 'measurements':
print(file_type,
"This is not a valid MagIC 3.0. measurements file ")
sys.exit()
# convert meas_data to 2.5
for rec in meas_data3:
meas_map = map_magic.meas_magic3_2_magic2_map
meas_data.append(map_magic.mapping(rec, meas_map))
else:
meas_data, file_type = pmag.magic_read(meas_file)
if file_type != 'magic_measurements':
print(file_type,
"This is not a valid MagIC 2.5 magic_measurements file ")
sys.exit()
# fish out relevant data
meas_data = pmag.get_dictitem(meas_data, 'magic_method_codes', 'LP-AN-ARM',
'has')
# figure out how to do this with 3 vs. 2.5
if coord != '-1': # need to read in sample data
if data_model_num == 3:
samp_data3, file_type = pmag.magic_read(samp_file)
if file_type != 'samples':
print(file_type, "This is not a valid er_samples file ")
print("Only specimen coordinates will be calculated")
coord = '-1'
else:
# translate to 2
samp_data = []
samp_map = map_magic.samp_magic3_2_magic2_map
for rec in samp_data3:
samp_data.append(map_magic.mapping(rec, samp_map))
else:
samp_data, file_type = pmag.magic_read(samp_file)
if file_type != 'er_samples':
print(file_type, "This is not a valid er_samples file ")
print("Only specimen coordinates will be calculated")
coord = '-1'
#
# sort the specimen names
#
ssort = []
for rec in meas_data:
spec = rec["er_specimen_name"]
if spec not in ssort:
ssort.append(spec)
if len(ssort) > 1:
sids = sorted(ssort)
else:
sids = ssort
#
# work on each specimen
#
specimen = 0
RmagSpecRecs, RmagResRecs = [], []
SpecRecs, SpecRecs3 = [], []
while specimen < len(sids):
s = sids[specimen]
data = []
RmagSpecRec = {}
RmagResRec = {}
method_codes = []
#
# find the data from the meas_data file for this sample
#
data = pmag.get_dictitem(meas_data, 'er_specimen_name', s, 'T')
#
# find out the number of measurements (9, 12 or 15)
#
npos = old_div(len(data), 2)
if npos == 9:
#
# get dec, inc, int and convert to x,y,z
#
# B matrix made from design matrix for positions
B, H, tmpH = pmag.designAARM(npos)
X = []
for rec in data:
Dir = []
Dir.append(float(rec["measurement_dec"]))
Dir.append(float(rec["measurement_inc"]))
Dir.append(float(rec["measurement_magn_moment"]))
X.append(pmag.dir2cart(Dir))
#
# subtract baseline and put in a work array
#
work = numpy.zeros((npos, 3), 'f')
for i in range(npos):
for j in range(3):
work[i][j] = X[2 * i + 1][j] - X[2 * i][j]
#
# calculate tensor elements
# first put ARM components in w vector
#
w = numpy.zeros((npos * 3), 'f')
index = 0
for i in range(npos):
for j in range(3):
w[index] = work[i][j]
index += 1
s = numpy.zeros((6), 'f') # initialize the s matrix
for i in range(6):
for j in range(len(w)):
s[i] += B[i][j] * w[j]
trace = s[0] + s[1] + s[2] # normalize by the trace
for i in range(6):
s[i] = old_div(s[i], trace)
a = pmag.s2a(s)
#------------------------------------------------------------
# Calculating dels is different than in the Kappabridge
# routine. Use trace normalized tensor (a) and the applied
# unit field directions (tmpH) to generate model X,Y,Z
# components. Then compare these with the measured values.
#------------------------------------------------------------
S = 0.
comp = numpy.zeros((npos * 3), 'f')
for i in range(npos):
for j in range(3):
index = i * 3 + j
compare = a[j][0] * tmpH[i][0] + a[j][1] * \
tmpH[i][1] + a[j][2] * tmpH[i][2]
comp[index] = compare
for i in range(npos * 3):
d = old_div(w[i], trace) - comp[i] # del values
S += d * d
nf = float(npos * 3 - 6) # number of degrees of freedom
if S > 0:
sigma = numpy.sqrt(old_div(S, nf))
else:
sigma = 0
RmagSpecRec["rmag_anisotropy_name"] = data[0]["er_specimen_name"]
RmagSpecRec["er_location_name"] = data[0].get(
"er_location_name", "")
RmagSpecRec["er_specimen_name"] = data[0]["er_specimen_name"]
RmagSpecRec["er_sample_name"] = data[0].get("er_sample_name", "")
RmagSpecRec["er_site_name"] = data[0].get("er_site_name", "")
RmagSpecRec["magic_experiment_names"] = RmagSpecRec[
"rmag_anisotropy_name"] + ":AARM"
RmagSpecRec["er_citation_names"] = "This study"
RmagResRec[
"rmag_result_name"] = data[0]["er_specimen_name"] + ":AARM"
RmagResRec["er_location_names"] = data[0].get(
"er_location_name", "")
RmagResRec["er_specimen_names"] = data[0]["er_specimen_name"]
RmagResRec["er_sample_names"] = data[0].get("er_sample_name", "")
RmagResRec["er_site_names"] = data[0].get("er_site_name", "")
RmagResRec["magic_experiment_names"] = RmagSpecRec[
"rmag_anisotropy_name"] + ":AARM"
RmagResRec["er_citation_names"] = "This study"
if "magic_instrument_codes" in list(data[0].keys()):
RmagSpecRec["magic_instrument_codes"] = data[0][
"magic_instrument_codes"]
else:
RmagSpecRec["magic_instrument_codes"] = ""
RmagSpecRec["anisotropy_type"] = "AARM"
RmagSpecRec[
"anisotropy_description"] = "Hext statistics adapted to AARM"
if coord != '-1': # need to rotate s
# set orientation priorities
SO_methods = []
for rec in samp_data:
if "magic_method_codes" not in rec:
rec['magic_method_codes'] = 'SO-NO'
if "magic_method_codes" in rec:
methlist = rec["magic_method_codes"]
for meth in methlist.split(":"):
if "SO" in meth and "SO-POM" not in meth.strip():
if meth.strip() not in SO_methods:
SO_methods.append(meth.strip())
SO_priorities = pmag.set_priorities(SO_methods, 0)
# continue here
redo, p = 1, 0
if len(SO_methods) <= 1:
az_type = SO_methods[0]
orient = pmag.find_samp_rec(RmagSpecRec["er_sample_name"],
samp_data, az_type)
if orient["sample_azimuth"] != "":
method_codes.append(az_type)
redo = 0
while redo == 1:
if p >= len(SO_priorities):
print("no orientation data for ", s)
orient["sample_azimuth"] = ""
orient["sample_dip"] = ""
method_codes.append("SO-NO")
redo = 0
else:
az_type = SO_methods[SO_methods.index(
SO_priorities[p])]
orient = pmag.find_samp_rec(
RmagSpecRec["er_sample_name"], samp_data, az_type)
if orient["sample_azimuth"] != "":
method_codes.append(az_type)
redo = 0
p += 1
az, pl = orient['sample_azimuth'], orient['sample_dip']
s = pmag.dosgeo(s, az, pl) # rotate to geographic coordinates
if coord == '100':
sample_bed_dir, sample_bed_dip = orient[
'sample_bed_dip_direction'], orient['sample_bed_dip']
# rotate to geographic coordinates
s = pmag.dostilt(s, sample_bed_dir, sample_bed_dip)
hpars = pmag.dohext(nf, sigma, s)
#
# prepare for output
#
RmagSpecRec["anisotropy_s1"] = '%8.6f' % (s[0])
RmagSpecRec["anisotropy_s2"] = '%8.6f' % (s[1])
RmagSpecRec["anisotropy_s3"] = '%8.6f' % (s[2])
RmagSpecRec["anisotropy_s4"] = '%8.6f' % (s[3])
RmagSpecRec["anisotropy_s5"] = '%8.6f' % (s[4])
RmagSpecRec["anisotropy_s6"] = '%8.6f' % (s[5])
RmagSpecRec["anisotropy_mean"] = '%8.3e' % (old_div(trace, 3))
RmagSpecRec["anisotropy_sigma"] = '%8.6f' % (sigma)
RmagSpecRec["anisotropy_unit"] = "Am^2"
RmagSpecRec["anisotropy_n"] = '%i' % (npos)
RmagSpecRec["anisotropy_tilt_correction"] = coord
# used by thellier_gui - must be taken out for uploading
RmagSpecRec["anisotropy_F"] = '%7.1f ' % (hpars["F"])
# used by thellier_gui - must be taken out for uploading
RmagSpecRec["anisotropy_F_crit"] = hpars["F_crit"]
RmagResRec["anisotropy_t1"] = '%8.6f ' % (hpars["t1"])
RmagResRec["anisotropy_t2"] = '%8.6f ' % (hpars["t2"])
RmagResRec["anisotropy_t3"] = '%8.6f ' % (hpars["t3"])
RmagResRec["anisotropy_v1_dec"] = '%7.1f ' % (hpars["v1_dec"])
RmagResRec["anisotropy_v2_dec"] = '%7.1f ' % (hpars["v2_dec"])
RmagResRec["anisotropy_v3_dec"] = '%7.1f ' % (hpars["v3_dec"])
RmagResRec["anisotropy_v1_inc"] = '%7.1f ' % (hpars["v1_inc"])
RmagResRec["anisotropy_v2_inc"] = '%7.1f ' % (hpars["v2_inc"])
RmagResRec["anisotropy_v3_inc"] = '%7.1f ' % (hpars["v3_inc"])
RmagResRec["anisotropy_ftest"] = '%7.1f ' % (hpars["F"])
RmagResRec["anisotropy_ftest12"] = '%7.1f ' % (hpars["F12"])
RmagResRec["anisotropy_ftest23"] = '%7.1f ' % (hpars["F23"])
RmagResRec["result_description"] = 'Critical F: ' + \
hpars["F_crit"] + ';Critical F12/F13: ' + hpars["F12_crit"]
if hpars["e12"] > hpars["e13"]:
RmagResRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
else:
RmagResRec["anisotropy_v1_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v1_zeta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v1_zeta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v1_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v1_eta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v1_eta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
if hpars["e23"] > hpars['e12']:
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
else:
RmagResRec["anisotropy_v2_zeta_semi_angle"] = '%7.1f ' % (
hpars['e12'])
RmagResRec["anisotropy_v2_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v2_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v3_eta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v3_eta_dec"] = '%7.1f ' % (
hpars['v2_dec'])
RmagResRec["anisotropy_v3_eta_inc"] = '%7.1f ' % (
hpars['v2_inc'])
RmagResRec["anisotropy_v3_zeta_semi_angle"] = '%7.1f ' % (
hpars['e13'])
RmagResRec["anisotropy_v3_zeta_dec"] = '%7.1f ' % (
hpars['v1_dec'])
RmagResRec["anisotropy_v3_zeta_inc"] = '%7.1f ' % (
hpars['v1_inc'])
RmagResRec["anisotropy_v2_eta_semi_angle"] = '%7.1f ' % (
hpars['e23'])
RmagResRec["anisotropy_v2_eta_dec"] = '%7.1f ' % (
hpars['v3_dec'])
RmagResRec["anisotropy_v2_eta_inc"] = '%7.1f ' % (
hpars['v3_inc'])
RmagResRec["tilt_correction"] = '-1'
RmagResRec["anisotropy_type"] = 'AARM'
RmagResRec["magic_method_codes"] = 'LP-AN-ARM:AE-H'
RmagSpecRec["magic_method_codes"] = 'LP-AN-ARM:AE-H'
RmagResRec["magic_software_packages"] = pmag.get_version()
RmagSpecRec["magic_software_packages"] = pmag.get_version()
specimen += 1
RmagSpecRecs.append(RmagSpecRec)
RmagResRecs.append(RmagResRec)
if data_model_num == 3:
SpecRec = RmagResRec.copy()
SpecRec.update(RmagSpecRec)
SpecRecs.append(SpecRec)
else:
print('skipping specimen ', s, ' only 9 positions supported',
'; this has ', npos)
specimen += 1
if data_model_num == 3:
# translate records
for rec in SpecRecs:
rec3 = map_magic.convert_aniso('magic3', rec)
SpecRecs3.append(rec3)
# write output to 3.0 specimens file
pmag.magic_write(spec_file, SpecRecs3, 'specimens')
print("specimen data stored in {}".format(spec_file))
else:
if rmag_anis == "":
rmag_anis = "rmag_anisotropy.txt"
pmag.magic_write(rmag_anis, RmagSpecRecs, 'rmag_anisotropy')
print("specimen tensor elements stored in ", rmag_anis)
if rmag_res == "":
rmag_res = "rmag_results.txt"
pmag.magic_write(rmag_res, RmagResRecs, 'rmag_results')
print("specimen statistics and eigenparameters stored in ", rmag_res)
def main():
"""
NAME
eqarea_magic.py
DESCRIPTION
makes equal area projections from declination/inclination data
SYNTAX
eqarea_magic.py [command line options]
INPUT
takes magic formatted sites, samples, specimens, or measurements
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic, default='sites.txt'
supported types=[measurements, specimens, samples, sites]
-fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
default='specimens.txt'
-fsa FILE: specify sample file name, (required if you want to plot specimens by site)
default='samples.txt'
-fsi FILE: specify site file name, default='sites.txt'
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-sav save plot and quit quietly
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
# initialize some default variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
plotE = 0
plt = 0 # default to not plotting
verbose = pmagplotlib.verbose
# extract arguments from sys.argv
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=".")
pmagplotlib.plot_init(FIG['eqarea'],5,5)
in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
in_file = pmag.resolve_file_name(in_file, dir_path)
if "-WD" not in sys.argv:
dir_path = os.path.split(in_file)[0]
#full_in_file = os.path.join(dir_path, in_file)
plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
if plot_by == 'all':
plot_key = 'all'
elif plot_by == 'sit':
plot_key = 'site'
elif plot_by == 'sam':
plot_key = 'sample'
elif plot_by == 'spc':
plot_key = 'specimen'
else:
plot_by = 'all'
plot_key = 'all'
if '-c' in sys.argv:
contour = 1
else:
contour = 0
if '-sav' in sys.argv:
plt = 1
verbose = 0
if '-ell' in sys.argv:
plotE = 1
ind = sys.argv.index('-ell')
ell_type = sys.argv[ind+1]
ell_type = pmag.get_named_arg_from_sys("-ell", "F")
dist = ell_type.upper()
# if dist type is unrecognized, use Fisher
if dist not in ['F', 'K', 'B', 'BE', 'BV']:
dist = 'F'
if dist == "BV":
FIG['bdirs'] = 2
pmagplotlib.plot_init(FIG['bdirs'],5,5)
crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
dec_key = 'dir_dec'
inc_key = 'dir_inc'
tilt_key = 'dir_tilt_correction'
#Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
#
fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames,
single_file=in_file)
try:
contribution.propagate_location_to_samples()
contribution.propagate_location_to_specimens()
contribution.propagate_location_to_measurements()
except KeyError as ex:
pass
# the object that contains the DataFrame + useful helper methods:
table_name = list(contribution.tables.keys())[0]
data_container = contribution.tables[table_name]
# the actual DataFrame:
data = data_container.df
if plot_key != "all" and plot_key not in data.columns:
print("-E- You can't plot by {} with the data provided".format(plot_key))
return
# add tilt key into DataFrame columns if it isn't there already
if tilt_key not in data.columns:
data.loc[:, tilt_key] = None
if verbose:
print(len(data), ' records read from ', in_file)
# find desired dec,inc data:
dir_type_key = ''
#
# get plotlist if not plotting all records
#
plotlist=[]
if plot_key != "all":
# return all where plot_key is not blank
if plot_key not in data.columns:
print('Can\'t plot by "{}". That header is not in infile: {}'.format(plot_key, in_file))
return
plots = data[data[plot_key].notnull()]
plotlist = plots[plot_key].unique() # grab unique values
else:
plotlist.append('All')
for plot in plotlist:
if verbose:
print(plot)
if plot == 'All':
# plot everything at once
plot_data = data
else:
# pull out only partial data
plot_data = data[data[plot_key] == plot]
DIblock = []
GCblock = []
# SLblock, SPblock = [], []
title = plot
mode = 1
k = 0
if dec_key not in plot_data.columns:
print("-W- No dec/inc data")
continue
# get all records where dec & inc values exist
plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
if plot_data.empty:
continue
# this sorting out is done in get_di_bock
#if coord == '0': # geographic, use records with no tilt key (or tilt_key 0)
# cond1 = plot_data[tilt_key].fillna('') == coord
# cond2 = plot_data[tilt_key].isnull()
# plot_data = plot_data[cond1 | cond2]
#else: # not geographic coordinates, use only records with correct tilt_key
# plot_data = plot_data[plot_data[tilt_key] == coord]
# get metadata for naming the plot file
locations = data_container.get_name('location', df_slice=plot_data)
site = data_container.get_name('site', df_slice=plot_data)
sample = data_container.get_name('sample', df_slice=plot_data)
specimen = data_container.get_name('specimen', df_slice=plot_data)
# make sure method_codes is in plot_data
if 'method_codes' not in plot_data.columns:
plot_data['method_codes'] = ''
# get data blocks
DIblock = data_container.get_di_block(df_slice=plot_data,
tilt_corr=coord, excl=['DE-BFP'])
#SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
# get great circles
great_circle_data = data_container.get_records_for_code('DE-BFP', incl=True,
use_slice=True, sli=plot_data)
if len(great_circle_data) > 0:
gc_cond = great_circle_data[tilt_key] == coord
GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
#SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]
if len(DIblock) > 0:
if contour == 0:
pmagplotlib.plotEQ(FIG['eqarea'], DIblock, title)
else:
pmagplotlib.plotEQcont(FIG['eqarea'], DIblock)
else:
pmagplotlib.plotNET(FIG['eqarea'])
if len(GCblock)>0:
for rec in GCblock:
pmagplotlib.plotC(FIG['eqarea'], rec, 90., 'g')
if len(DIblock) == 0 and len(GCblock) == 0:
if verbose:
print("no records for plotting")
continue
#sys.exit()
if plotE == 1:
ppars = pmag.doprinc(DIblock) # get principal directions
nDIs, rDIs, npars, rpars = [], [], [], []
for rec in DIblock:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist=='B': # do on whole dataset
etitle="Bingham confidence ellipse"
bpars=pmag.dobingham(DIblock)
for key in list(bpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(bpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist=='F':
etitle="Fisher confidence cone"
if len(nDIs)>2:
fpars=pmag.fisher_mean(nDIs)
for key in list(fpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(fpars[key]))
mode+=1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign=old_div(abs(fpars['inc']),fpars['inc'])
npars.append(fpars['inc']-isign*90.) #Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) #Beta inc
if len(rDIs)>2:
fpars=pmag.fisher_mean(rDIs)
if verbose: print("mode ",mode)
for key in list(fpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(fpars[key]))
mode+=1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign=old_div(abs(fpars['inc']),fpars['inc'])
rpars.append(fpars['inc']-isign*90.) #Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) #Beta inc
if dist=='K':
etitle="Kent confidence ellipse"
if len(nDIs)>3:
kpars=pmag.dokent(nDIs,len(nDIs))
if verbose: print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(kpars[key]))
mode+=1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs)>3:
kpars=pmag.dokent(rDIs,len(rDIs))
if verbose: print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(kpars[key]))
mode+=1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist=='BE':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
if verbose: print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
if verbose: print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
etitle="Bootstrapped confidence ellipse"
elif dist=='BV':
sym={'lower':['o','c'],'upper':['o','g'],'size':3,'edgecolor':'face'}
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plotEQsym(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors', sym)
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plotDIsym(FIG['bdirs'],BrDIs,sym)
else:
pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
if dist=='B':
if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],npars,0)
elif len(nDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],npars,0)
if len(rDIs)>3:
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],rpars,0)
elif len(rDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],rpars,0)
for key in list(FIG.keys()):
files = {}
filename = pmag.get_named_arg_from_sys('-fname')
if filename: # use provided filename
filename+= '.' + fmt
elif pmagplotlib.isServer: # use server plot naming convention
filename='LO:_'+locations+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
elif plot_key == 'all':
filename = 'all'
if 'location' in plot_data.columns:
locs = plot_data['location'].unique()
loc_string = "_".join([loc.replace(' ', '_') for loc in locs])
filename += "_" + loc_string
filename += "_" + crd + "_" + key
filename += ".{}".format(fmt)
else: # use more readable naming convention
filename = ''
# fix this if plot_by is location , for example
use_names = {'location': [locations], 'site': [locations, site],
'sample': [locations, site, sample],
'specimen': [locations, site, sample, specimen]}
use = use_names[plot_key]
use.extend([crd, key])
for item in use: #[locations, site, sample, specimen, crd, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key]=filename
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
if plt:
pmagplotlib.saveP(FIG,files)
continue
if verbose:
pmagplotlib.drawFIGS(FIG)
ans=input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q":
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG,files)
continue
def main():
"""
NAME
hysteresis_magic.py
DESCRIPTION
calculates hystereis parameters and saves them in 3.0 specimen format file
makes plots if option selected
SYNTAX
hysteresis_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input file, default is agm_measurements.txt
-F: specify specimens.txt output file
-P: do not make the plots
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args=sys.argv
PLT=1
plots=0
fmt=pmag.get_named_arg_from_sys('-fmt','svg')
dir_path=pmag.get_named_arg_from_sys('-WD','.')
dir_path=os.path.realpath(dir_path)
verbose=pmagplotlib.verbose
version_num=pmag.get_version()
user=pmag.get_named_arg_from_sys('-usr','')
if "-h" in args:
print(main.__doc__)
sys.exit()
meas_file=pmag.get_named_arg_from_sys('-f','agm_measurements.txt')
spec_file=pmag.get_named_arg_from_sys('-F','specimens.txt')
if '-P' in args:
PLT=0
irm_init,imag_init=-1,-1
if '-sav' in args:
verbose=0
plots=1
pltspec=pmag.get_named_arg_from_sys('-spc',0)
if pltspec:
#pltspec= args[ind+1]
verbose=0
plots=1
spec_file=dir_path+'/'+spec_file
meas_file=dir_path+'/'+meas_file
SpecRecs=[]
#
#
meas_data,file_type=pmag.magic_read(meas_file)
if file_type!='measurements':
print(main.__doc__)
print('bad file')
sys.exit()
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs,RemRecs=[],[]
HDD={}
if verbose:
if verbose and PLT:print("Plots may be on top of each other - use mouse to place ")
if PLT:
HDD['hyst'],HDD['deltaM'],HDD['DdeltaM']=1,2,3
pmagplotlib.plot_init(HDD['DdeltaM'],5,5)
pmagplotlib.plot_init(HDD['deltaM'],5,5)
pmagplotlib.plot_init(HDD['hyst'],5,5)
imag_init=0
irm_init=0
else:
HDD['hyst'],HDD['deltaM'],HDD['DdeltaM'],HDD['irm'],HDD['imag']=0,0,0,0,0
#
if spec_file: prior_data,file_type=pmag.magic_read(spec_file)
#
# get list of unique experiment names and specimen names
#
experiment_names,sids=[],[]
hys_data=pmag.get_dictitem(meas_data,'method_codes','LP-HYS','has')
dcd_data=pmag.get_dictitem(meas_data,'method_codes','LP-IRM-DCD','has')
imag_data=pmag.get_dictitem(meas_data,'method_codes','LP-IMAG','has')
for rec in hys_data:
if rec['experiment'] not in experiment_names:experiment_names.append(rec['experiment'])
if rec['specimen'] not in sids:sids.append(rec['specimen'])
#
k=0
if pltspec:
k=sids.index(pltspec)
print(sids[k])
while k < len(sids):
specimen=sids[k]
HystRec={'specimen':specimen,'experiment':""} # initialize a new specimen hysteresis record
if verbose and PLT:print(specimen, k+1 , 'out of ',len(sids))
#
#
B,M,Bdcd,Mdcd=[],[],[],[] #B,M for hysteresis, Bdcd,Mdcd for irm-dcd data
Bimag,Mimag=[],[] #Bimag,Mimag for initial magnetization curves
spec_data=pmag.get_dictitem(hys_data,'specimen',specimen,'T') # fish out all the LP-HYS data for this specimen
if len(spec_data)>0:
meths=spec_data[0]['method_codes'].split(':')
e=spec_data[0]['experiment']
HystRec['experiment']=spec_data[0]['experiment']
for rec in spec_data:
B.append(float(rec['meas_field_dc']))
M.append(float(rec['magn_moment']))
spec_data=pmag.get_dictitem(dcd_data,'specimen',specimen,'T') # fish out all the data for this specimen
if len(spec_data)>0:
HystRec['experiment']=HystRec['experiment']+':'+spec_data[0]['experiment']
irm_exp=spec_data[0]['experiment']
for rec in spec_data:
Bdcd.append(float(rec['treat_dc_field']))
Mdcd.append(float(rec['magn_moment']))
spec_data=pmag.get_dictitem(imag_data,'specimen',specimen,'T') # fish out all the data for this specimen
if len(spec_data)>0:
imag_exp=spec_data[0]['experiment']
for rec in spec_data:
Bimag.append(float(rec['meas_field_dc']))
Mimag.append(float(rec['magn_moment']))
#
# now plot the hysteresis curve
#
if len(B)>0:
hmeths=[]
for meth in meths: hmeths.append(meth)
hpars=pmagplotlib.plotHDD(HDD,B,M,e)
if verbose and PLT:pmagplotlib.drawFIGS(HDD)
#
if verbose:pmagplotlib.plotHPARS(HDD,hpars,'bs')
HystRec['hyst_mr_moment']=hpars['hysteresis_mr_moment']
HystRec['hyst_ms_moment']=hpars['hysteresis_ms_moment']
HystRec['hyst_bc']=hpars['hysteresis_bc']
HystRec['hyst_bcr']=hpars['hysteresis_bcr']
HystRec['susc_h']=hpars['hysteresis_xhf']
HystRec['experiments']=e
HystRec['software_packages']=version_num
if hpars["magic_method_codes"] not in hmeths:hmeths.append(hpars["magic_method_codes"])
methods=""
for meth in hmeths:
methods=methods+meth.strip()+":"
HystRec["method_codes"]=methods[:-1]
HystRec["citations"]="This study"
#
if len(Bdcd)>0:
rmeths=[]
for meth in meths: rmeths.append(meth)
if verbose and PLT:print('plotting IRM')
if irm_init==0:
HDD['irm']=5
pmagplotlib.plot_init(HDD['irm'],5,5)
irm_init=1
rpars=pmagplotlib.plotIRM(HDD['irm'],Bdcd,Mdcd,irm_exp)
HystRec['rem_mr_moment']=rpars['remanence_mr_moment']
HystRec['rem_bcr']=rpars['remanence_bcr']
HystRec['experiments']=specimen+':'+irm_exp
if rpars["magic_method_codes"] not in meths:meths.append(rpars["magic_method_codes"])
methods=""
for meth in rmeths:
methods=methods+meth.strip()+":"
HystRec["method_codes"]=HystRec['method_codes']+':'+methods[:-1]
HystRec["citations"]="This study"
else:
if irm_init:pmagplotlib.clearFIG(HDD['irm'])
if len(Bimag)>0:
if verbose and PLT:print('plotting initial magnetization curve')
# first normalize by Ms
Mnorm=[]
for m in Mimag: Mnorm.append(old_div(m,float(hpars['hysteresis_ms_moment'])))
if imag_init==0:
HDD['imag']=4
pmagplotlib.plot_init(HDD['imag'],5,5)
imag_init=1
pmagplotlib.plotIMAG(HDD['imag'],Bimag,Mnorm,imag_exp)
else:
if imag_init:pmagplotlib.clearFIG(HDD['imag'])
if len(list(HystRec.keys()))>0:HystRecs.append(HystRec)
#
files={}
if plots:
if pltspec:s=pltspec
files={}
for key in list(HDD.keys()):
files[key]=s+'_'+key+'.'+fmt
pmagplotlib.saveP(HDD,files)
if pltspec:sys.exit()
if verbose and PLT:
pmagplotlib.drawFIGS(HDD)
ans=input("S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans=="a":
files={}
for key in list(HDD.keys()):
files[key]=specimen+'_'+key+'.'+fmt
pmagplotlib.saveP(HDD,files)
if ans=='':k+=1
if ans=="p":
del HystRecs[-1]
k-=1
if ans=='q':
print("Good bye")
sys.exit()
if ans=='s':
keepon=1
specimen=input('Enter desired specimen name (or first part there of): ')
while keepon==1:
try:
k =sids.index(specimen)
keepon=0
except:
tmplist=[]
for qq in range(len(sids)):
if specimen in sids[qq]:tmplist.append(sids[qq])
print(specimen," not found, but this was: ")
print(tmplist)
specimen=input('Select one or try again\n ')
k =sids.index(specimen)
else:
k+=1
if len(B)==0 and len(Bdcd)==0:
if verbose:print('skipping this one - no hysteresis data')
k+=1
if len(HystRecs)>0:
# go through prior_data, clean out prior results and save combined file as spec_file
SpecRecs,keys=[],list(HystRecs[0].keys())
if len(prior_data)>0:
prior_keys=list(prior_data[0].keys())
else: prior_keys=[]
for rec in prior_data:
for key in keys:
if key not in list(rec.keys()):rec[key]=""
if 'LP-HYS' not in rec['method_codes']:
SpecRecs.append(rec)
for rec in HystRecs:
for key in prior_keys:
if key not in list(rec.keys()):rec[key]=""
prior=pmag.get_dictitem(prior_data,'specimen',rec['specimen'],'T')
if len(prior)>0 and 'sample' in list(prior[0].keys()):
rec['sample']=prior[0]['sample'] # pull sample name from prior specimens table
SpecRecs.append(rec)
pmag.magic_write(spec_file,SpecRecs,"specimens")
if verbose:print("hysteresis parameters saved in ",spec_file)
def main():
"""
NAME
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a sites table
SYNTAX
vgpmap_magic.py [command line options]
OPTIONS
-h prints help and quits
-eye ELAT ELON [specify eyeball location], default is 90., 0.
-f FILE sites format file, [default is sites.txt]
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-etp plot the etopo20 topographpy data (requires high resolution data set)
-prj PROJ, specify one of the following:
ortho = orthographic
lcc = lambert conformal
moll = molweide
merc = mercator
-sym SYM SIZE: choose a symbol and size, examples:
ro 5 : small red circles
bs 10 : intermediate blue squares
g^ 20 : large green triangles
-ell plot dp/dm or a95 ellipses
-rev RSYM RSIZE : flip reverse poles to normal antipode
-S: plot antipodes of all poles
-age : plot the ages next to the poles
-crd [g,t] : choose coordinate system, default is to plot all site VGPs
-fmt [pdf, png, eps...] specify output format, default is pdf
-sav save and quit
DEFAULTS
FILE: pmag_results.txt
res: c
prj: ortho
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", ".")
# plot: default is 0, if -sav in sys.argv should be 1
plot = pmag.get_flag_arg_from_sys("-sav", true=1, false=0)
fmt = pmag.get_named_arg_from_sys("-fmt", "pdf")
res = pmag.get_named_arg_from_sys("-res", "c")
proj = pmag.get_named_arg_from_sys("-prj", "ortho")
anti = pmag.get_flag_arg_from_sys("-S", true=1, false=0)
fancy = pmag.get_flag_arg_from_sys("-etp", true=1, false=0)
ell = pmag.get_flag_arg_from_sys("-ell", true=1, false=0)
ages = pmag.get_flag_arg_from_sys("-age", true=1, false=0)
if '-rev' in sys.argv:
flip = 1
ind = sys.argv.index('-rev')
rsym = (sys.argv[ind + 1])
rsize = int(sys.argv[ind + 2])
else:
flip, rsym, rsize = 0, "g^", 8
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = (sys.argv[ind + 1])
size = int(sys.argv[ind + 2])
else:
sym, size = 'ro', 8
if '-eye' in sys.argv:
ind = sys.argv.index('-eye')
lat_0 = float(sys.argv[ind + 1])
lon_0 = float(sys.argv[ind + 2])
else:
lat_0, lon_0 = 90., 0.
crd = pmag.get_named_arg_from_sys("-crd", "")
coord_dict = {'g': 0, 't': 100}
coord = coord_dict[crd] if crd else ""
results_file = pmag.get_named_arg_from_sys("-f", "sites.txt")
con = nb.Contribution(dir_path, single_file=results_file)
if not list(con.tables.keys()):
print("-W - Couldn't read in data")
return
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons = [], []
Pars = []
dates, rlats, rlons = [], [], []
site_container = con.tables['sites']
site_df = site_container.df
# use individual results
site_df = site_df[site_df['result_type'] == 'i']
# use records with vgp_lat and vgp_lon
cond1, cond2 = site_df['vgp_lat'].notnull(), site_df['vgp_lon'].notnull()
Results = site_df[cond1 & cond2]
# use tilt correction
if coord and 'dir_tilt_correction' in Results.columns:
Results = Results[Results['dir_tilt_correction'] == coord]
# get location name and average ages
location = ":".join(Results['location'].unique())
if 'average_age' in Results.columns and ages == 1:
dates = Results['average_age'].unique()
# go through rows and extract data
for ind, row in Results.iterrows():
lat, lon = float(row['vgp_lat']), float(row['vgp_lon'])
if anti == 1:
lats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360.
lons.append(lon)
elif flip == 0:
lats.append(lat)
lons.append(lon)
elif flip == 1:
if lat < 0:
rlats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360
rlons.append(lon)
else:
lats.append(lat)
lons.append(lon)
ppars = []
ppars.append(lon)
ppars.append(lat)
ell1, ell2 = "", ""
if 'vgp_dm' in list(row.keys()) and row['vgp_dm']:
ell1 = float(row['vgp_dm'])
if 'vgp_dp' in list(row.keys()) and row['vgp_dp']:
ell2 = float(row['vgp_dp'])
if 'vgp_alpha95' in list(row.keys()) and row['vgp_alpha95'].notnull():
ell1, ell2 = float(row['vgp_alpha95']), float(row['vgp_alpha95'])
if ell1 and ell2:
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
isign = old_div(abs(lats[-1]), lats[-1])
ppars.append(lats[-1] - isign * 90.)
ppars.append(ell2)
ppars.append(lons[-1] + 90.)
ppars.append(0.)
Pars.append(ppars)
location = location.strip(':')
Opts = {
'latmin': -90,
'latmax': 90,
'lonmin': 0.,
'lonmax': 360.,
'lat_0': lat_0,
'lon_0': lon_0,
'proj': proj,
'sym': 'bs',
'symsize': 3,
'pltgrid': 0,
'res': res,
'boundinglat': 0.
}
Opts['details'] = {
'coasts': 1,
'rivers': 0,
'states': 0,
'countries': 0,
'ocean': 1,
'fancy': fancy
}
# make the base map with a blue triangle at the pole
pmagplotlib.plotMAP(FIG['map'], [90.], [0.], Opts)
Opts['pltgrid'] = -1
Opts['sym'] = sym
Opts['symsize'] = size
if len(dates) > 0:
Opts['names'] = dates
if len(lats) > 0:
# add the lats and lons of the poles
pmagplotlib.plotMAP(FIG['map'], lats, lons, Opts)
Opts['names'] = []
if len(rlats) > 0:
Opts['sym'] = rsym
Opts['symsize'] = rsize
# add the lats and lons of the poles
pmagplotlib.plotMAP(FIG['map'], rlats, rlons, Opts)
if plot == 0:
pmagplotlib.drawFIGS(FIG)
if ell == 1: # add ellipses if desired.
Opts['details'] = {
'coasts': 0,
'rivers': 0,
'states': 0,
'countries': 0,
'ocean': 0,
'fancy': fancy
}
Opts['pltgrid'] = -1 # turn off meridian replotting
Opts['symsize'] = 2
Opts['sym'] = 'g-'
for ppars in Pars:
if ppars[2] != 0:
PTS = pmagplotlib.plotELL(FIG['map'], ppars, 'g.', 0, 0)
elats, elons = [], []
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
# make the base map with a blue triangle at the pole
pmagplotlib.plotMAP(FIG['map'], elats, elons, Opts)
if plot == 0:
pmagplotlib.drawFIGS(FIG)
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_' + location + '_VGP_map.' + fmt
else: # use more readable naming convention
files[key] = '{}_VGP_map.{}'.format(location, fmt)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'LO:_' + location + '_VGP_map'
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
elif plot == 0:
pmagplotlib.drawFIGS(FIG)
ans = input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
print("Good bye")
sys.exit()
else:
pmagplotlib.saveP(FIG, files)
def main():
"""
NAME
zeq_magic.py
DESCRIPTION
reads in magic_measurements formatted file, makes plots of remanence decay
during demagnetization experiments. Reads in prior interpretations saved in
a pmag_specimens formatted file [and allows re-interpretations of best-fit lines
and planes and saves (revised or new) interpretations in a pmag_specimens file.
interpretations are saved in the coordinate system used. Also allows judicious editting of
measurements to eliminate "bad" measurements. These are marked as such in the magic_measurements
input file. they are NOT deleted, just ignored. ] Bracketed part not yet implemented
SYNTAX
zeq_magic.py [command line options]
OPTIONS
-h prints help message and quits
-f MEASFILE: sets measurements format input file, default: measurements.txt
-fsp SPECFILE: sets specimens format file with prior interpreations, default: specimens.txt
-fsa SAMPFILE: sets samples format file sample=>site information, default: samples.txt
-fsi SITEFILE: sets sites format file with site=>location informationprior interpreations, default: samples.txt
-Fp PLTFILE: sets filename for saved plot, default is name_type.fmt (where type is zijd, eqarea or decay curve)
-crd [s,g,t]: sets coordinate system, g=geographic, t=tilt adjusted, default: specimen coordinate system
-spc SPEC plots single specimen SPEC, saves plot with specified format
with optional -dir settings and quits
-dir [L,P,F][beg][end]: sets calculation type for principal component analysis, default is none
beg: starting step for PCA calculation
end: ending step for PCA calculation
[L,P,F]: calculation type for line, plane or fisher mean
must be used with -spc option
-fmt FMT: set format of saved plot [png,svg,jpg]
-A: suppresses averaging of replicate measurements, default is to average
-sav: saves all plots without review
SCREEN OUTPUT:
Specimen, N, a95, StepMin, StepMax, Dec, Inc, calculation type
"""
# initialize some variables
doave, e, b = 1, 0, 0 # average replicates, initial end and beginning step
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
plots, coord = 0, 's'
noorient = 0
version_num = pmag.get_version()
verbose = pmagplotlib.verbose
calculation_type, fmt = "", "svg"
user, spec_keys, locname = "", [], ''
geo, tilt, ask = 0, 0, 0
PriorRecs = [] # empty list for prior interpretations
backup = 0
specimen = "" # can skip everything and just plot one specimen with bounds e,b
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
meas_file = pmag.get_named_arg_from_sys(
"-f", default_val="measurements.txt")
spec_file = pmag.get_named_arg_from_sys(
"-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
#meas_file = os.path.join(dir_path, meas_file)
#spec_file = os.path.join(dir_path, spec_file)
#samp_file = os.path.join(dir_path, samp_file)
#site_file = os.path.join(dir_path, site_file)
plot_file = pmag.get_named_arg_from_sys("-Fp", default_val="")
crd = pmag.get_named_arg_from_sys("-crd", default_val="s")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
specimen = pmag.get_named_arg_from_sys("-spc", default_val="")
beg_pca, end_pca = "", ""
if '-dir' in sys.argv:
ind = sys.argv.index('-dir')
direction_type = sys.argv[ind + 1]
beg_pca = int(sys.argv[ind + 2])
end_pca = int(sys.argv[ind + 3])
if direction_type == 'L':
calculation_type = 'DE-BFL'
if direction_type == 'P':
calculation_type = 'DE-BFP'
if direction_type == 'F':
calculation_type = 'DE-FM'
if '-A' in sys.argv:
doave = 0
if '-sav' in sys.argv:
plots, verbose = 1, 0
#
first_save = 1
fnames = {'measurements': meas_file, 'specimens': spec_file,
'samples': samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames, read_tables=[
'measurements', 'specimens', 'samples', 'sites'])
#
# import specimens
specimen_cols = ['analysts', 'aniso_ftest', 'aniso_ftest12', 'aniso_ftest23', 'aniso_s', 'aniso_s_mean', 'aniso_s_n_measurements', 'aniso_s_sigma', 'aniso_s_unit', 'aniso_tilt_correction', 'aniso_type', 'aniso_v1', 'aniso_v2', 'aniso_v3', 'citations', 'description', 'dir_alpha95', 'dir_comp', 'dir_dec', 'dir_inc', 'dir_mad_free', 'dir_n_measurements', 'dir_tilt_correction', 'experiments', 'geologic_classes',
'geologic_types', 'hyst_bc', 'hyst_bcr', 'hyst_mr_moment', 'hyst_ms_moment', 'int_abs', 'int_b', 'int_b_beta', 'int_b_sigma', 'int_corr', 'int_dang', 'int_drats', 'int_f', 'int_fvds', 'int_gamma', 'int_mad_free', 'int_md', 'int_n_measurements', 'int_n_ptrm', 'int_q', 'int_rsc', 'int_treat_dc_field', 'lithologies', 'meas_step_max', 'meas_step_min', 'meas_step_unit', 'method_codes', 'sample', 'software_packages', 'specimen']
if 'specimens' in contribution.tables:
# contribution.propagate_name_down('sample','measurements')
spec_container = contribution.tables['specimens']
if 'method_codes' not in spec_container.df.columns:
spec_container.df['method_codes'] = None
prior_spec_data = spec_container.get_records_for_code(
'LP-DIR', strict_match=False) # look up all prior directional interpretations
#
# tie sample names to measurement data
#
else:
spec_container, prior_spec_data = None, []
#
# import samples for orientation info
#
if ('samples' in contribution.tables) and ('specimens' in contribution.tables):
# contribution.propagate_name_down('site','measurements')
contribution.propagate_cols(col_names=[
'azimuth', 'dip', 'orientation_quality'], target_df_name='measurements', source_df_name='samples')
#
# define figure numbers for equal area, zijderveld,
# and intensity vs. demagnetiztion step respectively
#
ZED = {}
ZED['eqarea'], ZED['zijd'], ZED['demag'] = 1, 2, 3
pmagplotlib.plot_init(ZED['eqarea'], 6, 6)
pmagplotlib.plot_init(ZED['zijd'], 6, 6)
pmagplotlib.plot_init(ZED['demag'], 6, 6)
# save_pca=0
angle, direction_type, setangle = "", "", 0
# create measurement dataframe
#
meas_container = contribution.tables['measurements']
meas_data = meas_container.df
#
meas_data = meas_data[meas_data['method_codes'].str.contains(
'LT-NO|LT-AF-Z|LT-T-Z|LT-M-Z') == True] # fish out steps for plotting
meas_data = meas_data[meas_data['method_codes'].str.contains(
'AN|ARM|LP-TRM|LP-PI-ARM') == False] # strip out unwanted experiments
intensity_types = [
col_name for col_name in meas_data.columns if col_name in intlist]
intensity_types = [
col_name for col_name in intensity_types if any(meas_data[col_name])]
if not len(intensity_types):
print('-W- No intensity columns found')
return
# plot first non-empty intensity method found - normalized to initial value anyway -
# doesn't matter which used
int_key = intensity_types[0]
# get all the non-null intensity records of the same type
meas_data = meas_data[meas_data[int_key].notnull()]
if 'flag' not in meas_data.columns:
meas_data['flag'] = 'g' # set the default flag to good
# need to treat LP-NO specially for af data, treatment should be zero,
# otherwise 273.
meas_data['treatment'] = meas_data['treat_ac_field'].where(
cond=meas_data['treat_ac_field'] != 0, other=meas_data['treat_temp'])
meas_data['ZI'] = 1 # initialize these to one
meas_data['instrument_codes'] = "" # initialize these to blank
# for unusual case of microwave power....
if 'treat_mw_power' in meas_data.columns:
meas_data.loc[
(meas_data.treat_mw_power != 0) &
(meas_data.treat_mw_power) &
(meas_data.treat_mw_time),
'treatment'] = meas_data.treat_mw_power * meas_data.treat_mw_time
#
# get list of unique specimen names from measurement data
#
# this is a list of all the specimen names
specimen_names = meas_data.specimen.unique()
specimen_names = specimen_names.tolist()
specimen_names.sort()
#
# set up new DataFrame for this sessions specimen interpretations
#
data_container = nb.MagicDataFrame(
dtype='specimens', columns=specimen_cols)
# this is for interpretations from this session
current_spec_data = data_container.df
locname = 'LookItUp'
if specimen == "":
k = 0
else:
k = specimen_names.index(specimen)
# let's look at the data now
while k < len(specimen_names):
mpars = None
# set the current specimen for plotting
this_specimen = specimen_names[k]
# reset beginning/end pca if plotting more than one specimen
if not specimen:
beg_pca, end_pca = "", ""
if verbose and this_specimen != "":
print(this_specimen, k + 1, 'out of ', len(specimen_names))
if setangle == 0:
angle = ""
this_specimen_measurements = meas_data[meas_data['specimen'].str.contains(
this_specimen) == True] # fish out this specimen
this_specimen_measurements = this_specimen_measurements[this_specimen_measurements['flag'].str.contains(
'g') == True] # fish out this specimen
if len(this_specimen_measurements) != 0: # if there are measurements
#
# set up datablock [[treatment,dec, inc, int, direction_type],[....]]
#
#
# figure out the method codes
#
units, methods, title = "", "", this_specimen
# this is a list of all the specimen method codes`
meas_meths = this_specimen_measurements.method_codes.unique()
tr = pd.to_numeric(this_specimen_measurements.treatment).tolist()
if set(tr) == set([0]):
k += 1
continue
for m in meas_meths:
if 'LT-AF-Z' in m:
units = 'T' # units include tesla
tr[0] = 0
if 'LT-T-Z' in m:
units = units + ":K" # units include kelvin
if 'LT-M-Z' in m:
units = units + ':J' # units include joules
tr[0] = 0
units = units.strip(':') # strip off extra colons
if 'LP-' in m:
methods = methods + ":" + m
decs = pd.to_numeric(this_specimen_measurements.dir_dec).tolist()
incs = pd.to_numeric(this_specimen_measurements.dir_inc).tolist()
#
# fix the coordinate system
#
if coord != '-1': # need to transform coordinates to geographic
azimuths = pd.to_numeric(
this_specimen_measurements.azimuth).tolist() # get the azimuths
# get the azimuths
dips = pd.to_numeric(this_specimen_measurements.dip).tolist()
dirs = [decs, incs, azimuths, dips]
# this transposes the columns and rows of the list of lists
dirs_geo = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dogeo_V(dirs_geo)
if coord == '100': # need to do tilt correction too
bed_dip_dirs = pd.to_numeric(
this_specimen_measurements.bed_dip_dir).tolist() # get the azimuths
bed_dips = pd.to_numeric(
this_specimen_measurements.bed_dip).tolist() # get the azimuths
dirs = [decs, incs, bed_dip_dirs, bed_dips]
# this transposes the columns and rows of the list of lists
dirs_tilt = np.array(list(map(list, list(zip(*dirs)))))
decs, incs = pmag.dotilt_V(dirs_tilt)
title = title + '_t'
else:
title = title + '_g'
if angle == "":
angle = decs[0]
ints = pd.to_numeric(this_specimen_measurements[int_key]).tolist()
ZI = this_specimen_measurements.ZI.tolist()
flags = this_specimen_measurements.flag.tolist()
codes = this_specimen_measurements.instrument_codes.tolist()
datalist = [tr, decs, incs, ints, ZI, flags, codes]
# this transposes the columns and rows of the list of lists
datablock = list(map(list, list(zip(*datalist))))
pmagplotlib.plotZED(ZED, datablock, angle, title, units)
if verbose:
pmagplotlib.drawFIGS(ZED)
#
# collect info for current_specimen_interpretation dictionary
#
#
# find prior interpretation
#
prior_specimen_interpretations = prior_spec_data[prior_spec_data['specimen'].str.contains(this_specimen) == True]
if (beg_pca == "") and (len(prior_specimen_interpretations) != 0):
if len(prior_specimen_interpretations)>0:
beg_pcas = pd.to_numeric(
prior_specimen_interpretations.meas_step_min.values).tolist()
end_pcas = pd.to_numeric(
prior_specimen_interpretations.meas_step_max.values).tolist()
spec_methods = prior_specimen_interpretations.method_codes.tolist()
# step through all prior interpretations and plot them
for ind in range(len(beg_pcas)):
spec_meths = spec_methods[ind].split(':')
for m in spec_meths:
if 'DE-BFL' in m:
calculation_type = 'DE-BFL' # best fit line
if 'DE-BFP' in m:
calculation_type = 'DE-BFP' # best fit plane
if 'DE-FM' in m:
calculation_type = 'DE-FM' # fisher mean
if 'DE-BFL-A' in m:
calculation_type = 'DE-BFL-A' # anchored best fit line
start, end = tr.index(beg_pcas[ind]), tr.index(
end_pcas[ind]) # getting the starting and ending points
# calculate direction/plane
mpars = pmag.domean(
datablock, start, end, calculation_type)
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
else:
try:
start, end = int(beg_pca), int(end_pca)
except ValueError:
beg_pca = 0
end_pca = len(datablock) - 1
start, end = int(beg_pca), int(end_pca)
# calculate direction/plane
try:
mpars = pmag.domean(datablock, start, end, calculation_type)
except Exception as ex:
print('-I- Problem with {}'.format(this_specimen))
print(' ', ex)
print(' Skipping')
k += 1
continue
if mpars["specimen_direction_type"] != "Error":
# put it on the plot
pmagplotlib.plotDir(ZED, mpars, datablock, angle)
if verbose:
pmagplotlib.drawFIGS(ZED)
if plots == 1 or specimen != "":
if plot_file == "":
basename = title
else:
basename = plot_file
files = {}
for key in list(ZED.keys()):
files[key] = basename + '_' + key + '.' + fmt
pmagplotlib.saveP(ZED, files)
if specimen != "":
sys.exit()
if verbose:
recnum = 0
for plotrec in datablock:
if units == 'T':
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] * 1e3, " mT", plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "K":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] - 273, ' C', plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if units == "J":
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0], ' J', plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if 'K' in units and 'T' in units:
if plotrec[0] >= 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] - 273, ' C', plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
if plotrec[0] < 1.:
print('%s: %i %7.1f %s %8.3e %7.1f %7.1f %s' % (
plotrec[5], recnum, plotrec[0] * 1e3, " mT", plotrec[3], plotrec[1], plotrec[2], plotrec[6]))
recnum += 1
# we have a current interpretation
elif mpars["specimen_direction_type"] != "Error":
#
# create a new specimen record for the interpreation for this
# specimen
this_specimen_interpretation = {
col: "" for col in specimen_cols}
# this_specimen_interpretation["analysts"]=user
this_specimen_interpretation['software_packages'] = version_num
this_specimen_interpretation['specimen'] = this_specimen
this_specimen_interpretation["method_codes"] = calculation_type
this_specimen_interpretation["meas_step_unit"] = units
this_specimen_interpretation["meas_step_min"] = tr[start]
this_specimen_interpretation["meas_step_max"] = tr[end]
this_specimen_interpretation["dir_dec"] = '%7.1f' % (
mpars['specimen_dec'])
this_specimen_interpretation["dir_inc"] = '%7.1f' % (
mpars['specimen_inc'])
this_specimen_interpretation["dir_dang"] = '%7.1f' % (
mpars['specimen_dang'])
this_specimen_interpretation["dir_n_measurements"] = '%i' % (
mpars['specimen_n'])
this_specimen_interpretation["dir_tilt_correction"] = coord
methods = methods.replace(" ", "")
if "T" in units:
methods = methods + ":LP-DIR-AF"
if "K" in units:
methods = methods + ":LP-DIR-T"
if "J" in units:
methods = methods + ":LP-DIR-M"
this_specimen_interpretation["method_codes"] = methods.strip(
':')
this_specimen_interpretation["experiments"] = this_specimen_measurements.experiment.unique()[
0]
#
# print some stuff
#
if calculation_type != 'DE-FM':
this_specimen_interpretation["dir_mad_free"] = '%7.1f' % (
mpars['specimen_mad'])
this_specimen_interpretation["dir_alpha95"] = ''
if verbose:
if units == 'K':
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) - 273, float(this_specimen_interpretation["meas_step_max"]) - 273, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif units == 'T':
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) * 1e3, float(this_specimen_interpretation["meas_step_max"]) * 1e3, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation['meas_step_min']) < 1.0:
min = float(
this_specimen_interpretation['meas_step_min']) * 1e3
else:
min = float(
this_specimen_interpretation['meas_step_min']) - 273
if float(this_specimen_interpretation['meas_step_max']) < 1.0:
max = float(
this_specimen_interpretation['meas_step_max']) * 1e3
else:
max = float(
this_specimen_interpretation['meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(
this_specimen_interpretation["dir_dang"]), min, max, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
else:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]), float(this_specimen_interpretation["meas_step_max"]), float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
else:
this_specimen_interpretation["dir_alpha95"] = '%7.1f' % (
mpars['specimen_alpha95'])
this_specimen_interpretation["dir_mad_free"] = ''
if verbose:
if 'K' in units:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurments"]), float(this_specimen_interpretation["dir_mad_free"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) - 273, float(this_specimen_interpretation["meas_step_max"]) - 273, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif 'T' in units:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_alpha95"]), float(this_specimen_interpretation["dir_dang"]), float(
this_specimen_interpretation["meas_step_min"]) * 1e3, float(this_specimen_interpretation["meas_step_max"]) * 1e3, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
elif 'T' in units and 'K' in units:
if float(this_specimen_interpretation['meas_step_min']) < 1.0:
min = float(
this_specimen_interpretation['meas_step_min']) * 1e3
else:
min = float(
this_specimen_interpretation['meas_step_min']) - 273
if float(this_specimen_interpretation['meas_step_max']) < 1.0:
max = float(
this_specimen_interpretation['meas_step_max']) * 1e3
else:
max = float(
this_specimen_interpretation['meas_step_max']) - 273
print('%s %i %7.1f %i %i %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(
this_specimen_interpretation["dir_alpha95"]), min, max, float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
else:
print('%s %i %7.1f %7.1f %7.1f %7.1f %7.1f %s \n' % (this_specimen_interpretation["specimen"], int(this_specimen_interpretation["dir_n_measurements"]), float(this_specimen_interpretation["dir_alpha95"]), float(
this_specimen_interpretation["meas_step_min"]), float(this_specimen_interpretation["meas_step_max"]), float(this_specimen_interpretation["dir_dec"]), float(this_specimen_interpretation["dir_inc"]), calculation_type))
if verbose:
saveit = input("Save this interpretation? [y]/n \n")
# START HERE
#
# if len(current_spec_data)==0: # no interpretations yet for this session
# print "no current interpretation"
# beg_pca,end_pca="",""
# calculation_type=""
# get the ones that meet the current coordinate system
else:
print("no data")
if verbose:
res = input(' <return> for next specimen, [q]uit ')
if res == 'q':
return
k += 1
def main():
"""
NAME
dmag_magic.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot,
default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols,
(for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
# initialize variables from command line + defaults
FIG = {} # plot dictionary
FIG['demag'] = 1 # demag is figure 1
in_file = pmag.get_named_arg_from_sys("-f", default_val="measurements.txt")
plot_by = pmag.get_named_arg_from_sys("-obj", default_val="loc")
name_dict = {
'loc': 'location',
'sit': 'site',
'sam': 'sample',
'spc': 'specimen'
}
plot_key = name_dict[plot_by]
LT = "LT-" + pmag.get_named_arg_from_sys("-LT", "AF") + "-Z"
if LT == "LT-T-Z":
units, dmag_key = 'K', 'treat_temp'
elif LT == "LT-AF-Z":
units, dmag_key = 'T', 'treat_ac_field'
elif LT == 'LT-M-Z':
units, dmag_key = 'J', 'treat_mw_energy'
else:
units = 'U'
no_norm = pmag.get_flag_arg_from_sys("-N")
norm = 0 if no_norm else 1
no_plot = pmag.get_flag_arg_from_sys("-sav")
plot = 0 if no_plot else 1
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
XLP = pmag.get_named_arg_from_sys("-XLP", "")
dir_path = pmag.get_named_arg_from_sys("-WD", os.getcwd())
spec_file = pmag.get_named_arg_from_sys("-fsp",
default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
# create contribution and add required headers
fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path,
single_file=in_file,
custom_filenames=fnames)
file_type = list(contribution.tables.keys())[0]
print(len(contribution.tables['measurements'].df), ' records read from ',
in_file)
# add plot_key into measurements table
if plot_key not in contribution.tables['measurements'].df.columns:
#contribution.propagate_name_down(plot_key, 'measurements')
contribution.propagate_location_to_measurements()
data_container = contribution.tables[file_type]
# pare down to only records with useful data
# grab records that have the requested code
data_slice = data_container.get_records_for_code(LT)
# and don't have the offending code
data = data_container.get_records_for_code(XLP,
incl=False,
use_slice=True,
sli=data_slice,
strict_match=False)
# make sure quality is in the dataframe
if 'quality' not in data.columns:
data['quality'] = 'g'
# get intensity key and make sure intensity data is not blank
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
# get rid of any entirely blank intensity columns
for col_name in IntMeths:
if not data[col_name].any():
data.drop(col_name, axis=1, inplace=True)
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
if len(IntMeths) == 0:
print('No intensity headers found')
sys.exit()
int_key = IntMeths[
0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
data = data[data[int_key].notnull()]
# make list of individual plots
# by default, will be by location_name
plotlist = data[plot_key].unique()
plotlist.sort()
pmagplotlib.plot_init(FIG['demag'], 5, 5)
# iterate through and plot the data
for plt in plotlist:
plot_data = data[data[plot_key] == plt].copy()
if plot:
print(plt, 'plotting by: ', plot_key)
if len(plot_data) > 2:
title = plt
spcs = []
spcs = plot_data['specimen'].unique()
for spc in spcs:
INTblock = []
spec_data = plot_data[plot_data['specimen'] == spc]
for ind, rec in spec_data.iterrows():
INTblock.append([
float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, rec['quality']
])
if len(INTblock) > 2:
pmagplotlib.plotMT(FIG['demag'], INTblock, title, 0, units,
norm)
if not plot:
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LT + '.' + fmt
pmagplotlib.saveP(FIG, files)
#sys.exit()
else:
pmagplotlib.drawFIGS(FIG)
prompt = " S[a]ve to save plot, [q]uit, Return to continue: "
ans = input(prompt)
if ans == 'q':
sys.exit()
if ans == "a":
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LT + '.' + fmt
pmagplotlib.saveP(FIG, files)
pmagplotlib.clearFIG(FIG['demag'])
def main():
"""
NAME
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a sites table
SYNTAX
vgpmap_magic.py [command line options]
OPTIONS
-h prints help and quits
-eye ELAT ELON [specify eyeball location], default is 90., 0.
-f FILE sites format file, [default is sites.txt]
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-etp plot the etopo20 topographpy data (requires high resolution data set)
-prj PROJ, specify one of the following:
ortho = orthographic
lcc = lambert conformal
moll = molweide
merc = mercator
-sym SYM SIZE: choose a symbol and size, examples:
ro 5 : small red circles
bs 10 : intermediate blue squares
g^ 20 : large green triangles
-ell plot dp/dm or a95 ellipses
-rev RSYM RSIZE : flip reverse poles to normal antipode
-S: plot antipodes of all poles
-age : plot the ages next to the poles
-crd [g,t] : choose coordinate system, default is to plot all site VGPs
-fmt [pdf, png, eps...] specify output format, default is pdf
-sav save and quit
DEFAULTS
FILE: pmag_results.txt
res: c
prj: ortho
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", ".")
# plot: default is 0, if -sav in sys.argv should be 1
plot = pmag.get_flag_arg_from_sys("-sav", true=1, false=0)
fmt = pmag.get_named_arg_from_sys("-fmt", "pdf")
res = pmag.get_named_arg_from_sys("-res", "c")
proj = pmag.get_named_arg_from_sys("-prj", "ortho")
anti = pmag.get_flag_arg_from_sys("-S", true=1, false=0)
fancy = pmag.get_flag_arg_from_sys("-etp", true=1, false=0)
ell = pmag.get_flag_arg_from_sys("-ell", true=1, false=0)
ages = pmag.get_flag_arg_from_sys("-age", true=1, false=0)
if '-rev' in sys.argv:
flip = 1
ind = sys.argv.index('-rev')
rsym = (sys.argv[ind + 1])
rsize = int(sys.argv[ind + 2])
else:
flip, rsym, rsize = 0, "g^", 8
if '-sym' in sys.argv:
ind = sys.argv.index('-sym')
sym = (sys.argv[ind + 1])
size = int(sys.argv[ind + 2])
else:
sym, size = 'ro', 8
if '-eye' in sys.argv:
ind = sys.argv.index('-eye')
lat_0 = float(sys.argv[ind + 1])
lon_0 = float(sys.argv[ind + 2])
else:
lat_0, lon_0 = 90., 0.
crd = pmag.get_named_arg_from_sys("-crd", "")
coord_dict = {'g': 0, 't': 100}
coord = coord_dict[crd] if crd else ""
results_file = pmag.get_named_arg_from_sys("-f", "sites.txt")
con = nb.Contribution(dir_path, single_file=results_file)
if not list(con.tables.keys()):
print("-W - Couldn't read in data")
return
FIG = {'map': 1}
pmagplotlib.plot_init(FIG['map'], 6, 6)
# read in er_sites file
lats, lons = [], []
Pars = []
dates, rlats, rlons = [], [], []
site_container = con.tables['sites']
site_df = site_container.df
# use individual results
site_df = site_df[site_df['result_type'] == 'i']
# use records with vgp_lat and vgp_lon
cond1, cond2 = site_df['vgp_lat'].notnull(), site_df['vgp_lon'].notnull()
Results = site_df[cond1 & cond2]
# use tilt correction
if coord and 'dir_tilt_correction' in Results.columns:
Results = Results[Results['dir_tilt_correction'] == coord]
# get location name and average ages
location = ":".join(Results['location'].unique())
if 'average_age' in Results.columns and ages == 1:
dates = Results['average_age'].unique()
# go through rows and extract data
for ind, row in Results.iterrows():
lat, lon = float(row['vgp_lat']), float(row['vgp_lon'])
if anti == 1:
lats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360.
lons.append(lon)
elif flip == 0:
lats.append(lat)
lons.append(lon)
elif flip == 1:
if lat < 0:
rlats.append(-lat)
lon = lon + 180.
if lon > 360:
lon = lon - 360
rlons.append(lon)
else:
lats.append(lat)
lons.append(lon)
ppars = []
ppars.append(lon)
ppars.append(lat)
ell1, ell2 = "", ""
if 'vgp_dm' in list(row.keys()) and row['vgp_dm']:
ell1 = float(row['vgp_dm'])
if 'vgp_dp' in list(row.keys()) and row['vgp_dp']:
ell2 = float(row['vgp_dp'])
if 'vgp_alpha95' in list(row.keys()) and row['vgp_alpha95'].notnull():
ell1, ell2 = float(row['vgp_alpha95']), float(row['vgp_alpha95'])
if ell1 and ell2:
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
isign = old_div(abs(lats[-1]), lats[-1])
ppars.append(lats[-1] - isign * 90.)
ppars.append(ell2)
ppars.append(lons[-1] + 90.)
ppars.append(0.)
Pars.append(ppars)
location = location.strip(':')
Opts = {'latmin': -90, 'latmax': 90, 'lonmin': 0., 'lonmax': 360.,
'lat_0': lat_0, 'lon_0': lon_0, 'proj': proj, 'sym': 'bs',
'symsize': 3, 'pltgrid': 0, 'res': res, 'boundinglat': 0.}
Opts['details'] = {'coasts': 1, 'rivers': 0, 'states': 0,
'countries': 0, 'ocean': 1, 'fancy': fancy}
# make the base map with a blue triangle at the pole
pmagplotlib.plotMAP(FIG['map'], [90.], [0.], Opts)
Opts['pltgrid'] = -1
Opts['sym'] = sym
Opts['symsize'] = size
if len(dates) > 0:
Opts['names'] = dates
if len(lats) > 0:
# add the lats and lons of the poles
pmagplotlib.plotMAP(FIG['map'], lats, lons, Opts)
Opts['names'] = []
if len(rlats) > 0:
Opts['sym'] = rsym
Opts['symsize'] = rsize
# add the lats and lons of the poles
pmagplotlib.plotMAP(FIG['map'], rlats, rlons, Opts)
if plot == 0:
pmagplotlib.drawFIGS(FIG)
if ell == 1: # add ellipses if desired.
Opts['details'] = {'coasts': 0, 'rivers': 0, 'states': 0,
'countries': 0, 'ocean': 0, 'fancy': fancy}
Opts['pltgrid'] = -1 # turn off meridian replotting
Opts['symsize'] = 2
Opts['sym'] = 'g-'
for ppars in Pars:
if ppars[2] != 0:
PTS = pmagplotlib.plotELL(FIG['map'], ppars, 'g.', 0, 0)
elats, elons = [], []
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
# make the base map with a blue triangle at the pole
pmagplotlib.plotMAP(FIG['map'], elats, elons, Opts)
if plot == 0:
pmagplotlib.drawFIGS(FIG)
files = {}
for key in list(FIG.keys()):
if pmagplotlib.isServer: # use server plot naming convention
files[key] = 'LO:_' + location + '_VGP_map.' + fmt
else: # use more readable naming convention
files[key] = '{}_VGP_map.{}'.format(location, fmt)
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles = {}
titles['eq'] = 'LO:_' + location + '_VGP_map'
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
elif plot == 0:
pmagplotlib.drawFIGS(FIG)
ans = input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
print("Good bye")
sys.exit()
else:
pmagplotlib.saveP(FIG, files)
def main():
"""
NAME
plotXY.py
DESCRIPTION
Makes simple X,Y plots
INPUT FORMAT
X,Y data in columns
SYNTAX
plotxy.py [command line options]
OPTIONS
-h prints this help message
-f FILE to set file name on command line
-c col1 col2 specify columns to plot
-xsig col3 specify xsigma if desired
-ysig col4 specify xsigma if desired
-b xmin xmax ymin ymax, sets bounds
-sym SYM SIZE specify symbol to plot: default is red dots, 10 pt
-S don't plot the symbols
-xlab XLAB
-ylab YLAB
-l connect symbols with lines
-fmt [svg,png,pdf,eps] specify output format, default is svg
-sav saves plot and quits
-poly X plot a degree X polynomial through the data
-skip n Number of lines to skip before reading in data
"""
fmt,plot='svg',0
col1,col2=0,1
sym,size = 'ro',50
xlab,ylab='',''
lines=0
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
if '-f' in sys.argv:
ind=sys.argv.index('-f')
file=sys.argv[ind+1]
if '-fmt' in sys.argv:
ind=sys.argv.index('-fmt')
fmt=sys.argv[ind+1]
if '-sav' in sys.argv:plot=1
if '-c' in sys.argv:
ind=sys.argv.index('-c')
col1=int(sys.argv[ind+1])-1
col2=int(sys.argv[ind+2])-1
if '-xsig' in sys.argv:
ind=sys.argv.index('-xsig')
col3=int(sys.argv[ind+1])-1
if '-ysig' in sys.argv:
ind=sys.argv.index('-ysig')
col4=int(sys.argv[ind+1])-1
if '-xlab' in sys.argv:
ind=sys.argv.index('-xlab')
xlab=sys.argv[ind+1]
if '-ylab' in sys.argv:
ind=sys.argv.index('-ylab')
ylab=sys.argv[ind+1]
if '-b' in sys.argv:
ind=sys.argv.index('-b')
xmin=float(sys.argv[ind+1])
xmax=float(sys.argv[ind+2])
ymin=float(sys.argv[ind+3])
ymax=float(sys.argv[ind+4])
if '-poly' in sys.argv:
ind=sys.argv.index('-poly')
degr=sys.argv[ind+1]
if '-sym' in sys.argv:
ind=sys.argv.index('-sym')
sym=sys.argv[ind+1]
size=int(sys.argv[ind+2])
if '-l' in sys.argv: lines=1
if '-S' in sys.argv: sym=''
skip = int(pmag.get_named_arg_from_sys('-skip', default_val=0))
X,Y=[],[]
Xerrs,Yerrs=[],[]
f=open(file,'r')
for num in range(skip):
f.readline()
data=f.readlines()
for line in data:
line.replace('\n','')
line.replace('\t',' ')
rec=line.split()
X.append(float(rec[col1]))
Y.append(float(rec[col2]))
if '-xsig' in sys.argv:Xerrs.append(float(rec[col3]))
if '-ysig' in sys.argv:Yerrs.append(float(rec[col4]))
if '-poly' in sys.argv:
pylab.plot(xs,ys)
coeffs=numpy.polyfit(X,Y,degr)
correl=numpy.corrcoef(X,Y)**2
polynomial=numpy.poly1d(coeffs)
xs=numpy.linspace(numpy.min(X),numpy.max(X),10)
ys=polynomial(xs)
pylab.plot(xs,ys)
print(polynomial)
if degr=='1': print('R-square value =', '%5.4f'%(correl[0,1]))
if sym!='':
pylab.scatter(X,Y,marker=sym[1],c=sym[0],s=size)
else:
pylab.plot(X,Y)
if '-xsig' in sys.argv and '-ysig' in sys.argv:
pylab.errorbar(X,Y,xerr=Xerrs,yerr=Yerrs,fmt=None)
if '-xsig' in sys.argv and '-ysig' not in sys.argv:
pylab.errorbar(X,Y,xerr=Xerrs,fmt=None)
if '-xsig' not in sys.argv and '-ysig' in sys.argv:
pylab.errorbar(X,Y,yerr=Yerrs,fmt=None)
if xlab!='':pylab.xlabel(xlab)
if ylab!='':pylab.ylabel(ylab)
if lines==1:pylab.plot(X,Y,'k-')
if '-b' in sys.argv:pylab.axis([xmin,xmax,ymin,ymax])
if plot==0:
pylab.show()
else:
pylab.savefig('plotXY.'+fmt)
print('Figure saved as ','plotXY.'+fmt)
sys.exit()
def main():
"""
NAME
agm_magic.py
DESCRIPTION
converts Micromag agm files to magic format
SYNTAX
agm_magic.py [-h] [command line options]
OPTIONS
-usr USER: identify user, default is "" - put in quotation marks!
-bak: this is a IRM backfield curve
-f FILE, specify input file, required
-fsa SAMPFILE, specify er_samples.txt file relating samples, site and locations names,default is none
-F MFILE, specify magic measurements formatted output file, default is agm_measurements.txt
-spn SPEC, specimen name, default is base of input file name, e.g. SPECNAME.agm
-spc NUM, specify number of characters to designate a specimen, default = 0
-Fsp SPECFILE : name of er_specimens.txt file for appending data to
[default: er_specimens.txt]
-ncn NCON,: specify naming convention: default is #1 below
-syn SYN, synthetic specimen name
-loc LOCNAME : specify location/study name,
should have either LOCNAME or SAMPFILE (unless synthetic)
-ins INST : specify which instrument was used (e.g, SIO-Maud), default is ""
-u units: [cgs,SI], default is cgs
Sample naming convention:
[1] XXXXY: where XXXX is an arbitrary length site designation and Y
is the single character sample designation. e.g., TG001a is the
first sample from site TG001. [default]
[2] XXXX-YY: YY sample from site XXXX (XXX, YY of arbitary length)
[3] XXXX.YY: YY sample from site XXXX (XXX, YY of arbitary length)
[4-Z] XXXX[YYY]: YYY is sample designation with Z characters from site XXX
[5] site name same as sample
[6] site is entered under a separate column -- NOT CURRENTLY SUPPORTED
[7-Z] [XXXX]YYY: XXXX is site designation with Z characters with sample name XXXXYYYY
[8] specimen is a synthetic - it has no sample, site, location information
NB: all others you will have to customize your self
or e-mail [email protected] for help.
OUTPUT
MagIC format files: magic_measurements, er_specimens, er_sample, er_site
"""
citation='This study'
MeasRecs=[]
units='cgs'
meth="LP-HYS"
version_num=pmag.get_version()
args=sys.argv
fmt='old'
er_sample_name,er_site_name,er_location_name="","",""
inst=""
er_location_name="unknown"
er_synthetic_name=""
user=""
er_site_name=""
dir_path='.'
dm=3
if "-WD" in args:
ind=args.index("-WD")
dir_path=args[ind+1]
if "-ID" in args:
ind = args.index("-ID")
input_dir_path = args[ind+1]
else:
input_dir_path = dir_path
output_dir_path = dir_path
specfile = output_dir_path+'/er_specimens.txt'
output = output_dir_path+"/agm_measurements.txt"
if "-h" in args:
print(main.__doc__)
sys.exit()
if "-bak" in args:
meth="LP-IRM-DCD"
output = output_dir_path+"/irm_measurements.txt"
if "-new" in args: fmt='new'
if "-usr" in args:
ind=args.index("-usr")
user=args[ind+1]
if '-F' in args:
ind=args.index("-F")
output = output_dir_path+'/'+args[ind+1]
if '-f' in args:
ind=args.index("-f")
agm_file= input_dir_path+'/'+args[ind+1]
er_specimen_name=args[ind+1].split('.')[0]
else:
print("agm_file field is required option")
print(main.__doc__)
sys.exit()
if '-Fsp' in args:
ind=args.index("-Fsp")
specfile= output_dir_path+'/'+args[ind+1]
specnum,samp_con,Z=0,'1',1
if "-spc" in args:
ind=args.index("-spc")
specnum=int(args[ind+1])
if specnum!=0:specnum=-specnum
if "-spn" in args:
ind=args.index("-spn")
er_specimen_name=args[ind+1]
#elif "-syn" not in args:
# print "you must specify a specimen name"
# sys.exit()
if "-syn" in args:
ind=args.index("-syn")
er_synthetic_name=args[ind+1]
er_specimen_name=""
if "-loc" in args:
ind=args.index("-loc")
er_location_name=args[ind+1]
if "-fsa" in args:
ind=args.index("-fsa")
sampfile = input_dir_path+'/'+args[ind+1]
Samps,file_type=pmag.magic_read(sampfile)
print('sample_file successfully read in')
if "-ncn" in args:
ind=args.index("-ncn")
samp_con=sys.argv[ind+1]
if "4" in samp_con:
if "-" not in samp_con:
print("option [4] must be in form 4-Z where Z is an integer")
sys.exit()
else:
Z=samp_con.split("-")[1]
samp_con="4"
if "7" in samp_con:
if "-" not in samp_con:
print("option [7] must be in form 7-Z where Z is an integer")
sys.exit()
else:
Z=samp_con.split("-")[1]
samp_con="7"
if "-ins" in args:
ind=args.index("-ins")
inst=args[ind+1]
if "-u" in args:
ind=args.index("-u")
units=args[ind+1]
dm = pmag.get_named_arg_from_sys("-DM", 2)
ErSpecRecs,filetype=pmag.magic_read(specfile)
ErSpecRec,MeasRec={},{}
ErSpecRec['er_citation_names']="This study"
ErSpecRec['er_specimen_name']=er_specimen_name
ErSpecRec['er_synthetic_name']=er_synthetic_name
if specnum!=0:
ErSpecRec["er_sample_name"]=er_specimen_name[:specnum]
else:
ErSpecRec["er_sample_name"]=er_specimen_name
if "-fsa" in args and er_synthetic_name=="":
for samp in Samps:
if samp["er_sample_name"] == ErSpecRec["er_sample_name"]:
ErSpecRec["er_location_name"]=samp["er_location_name"]
ErSpecRec["er_site_name"]=samp["er_site_name"]
break
elif int(samp_con)!=6 and int(samp_con)!=8:
site=pmag.parse_site(ErSpecRec['er_sample_name'],samp_con,Z)
ErSpecRec["er_site_name"]=site
ErSpecRec["er_location_name"]=er_location_name
ErSpecRec['er_scientist_mail_names']=user.strip()
insert=1
for rec in ErSpecRecs:
if rec['er_specimen_name']==er_specimen_name:
insert=0
break
if insert==1:
ErSpecRecs.append(ErSpecRec)
ErSpecRecs,keylist=pmag.fillkeys(ErSpecRecs)
pmag.magic_write(specfile,ErSpecRecs,'er_specimens')
print("specimen name put in ",specfile)
f=open(agm_file,'r')
Data=f.readlines()
if "ASCII" not in Data[0]:fmt='new'
measnum,start=1,""
if fmt=='new': # new Micromag formatted file
end=2
for skip in range(len(Data)):
line=Data[skip]
rec=line.split()
if 'Units' in line:units=rec[-1]
if "Raw" in rec:
start=skip+2
if "Field" in rec and "Moment" in rec and start=="":
start=skip+2
break
else:
start = 2
end=1
for i in range(start,len(Data)-end): # skip header stuff
MeasRec={}
for key in list(ErSpecRec.keys()):
MeasRec[key]=ErSpecRec[key]
MeasRec['magic_instrument_codes']=inst
MeasRec['magic_method_codes']=meth
if 'er_synthetic_name' in list(MeasRec.keys()) and MeasRec['er_synthetic_name']!="":
MeasRec['magic_experiment_name']=er_synthetic_name+':'+meth
else:
MeasRec['magic_experiment_name']=er_specimen_name+':'+meth
line=Data[i]
rec=line.split(',') # data comma delimited
if rec[0]!='\n':
if units=='cgs':
field =float(rec[0])*1e-4 # convert from oe to tesla
else:
field =float(rec[0]) # field in tesla
if meth=="LP-HYS":
MeasRec['measurement_lab_field_dc']='%10.3e'%(field)
MeasRec['treatment_dc_field']=''
else:
MeasRec['measurement_lab_field_dc']=''
MeasRec['treatment_dc_field']='%10.3e'%(field)
if units=='cgs':
MeasRec['measurement_magn_moment']='%10.3e'%(float(rec[1])*1e-3) # convert from emu to Am^2
else:
MeasRec['measurement_magn_moment']='%10.3e'%(float(rec[1])) # Am^2
MeasRec['treatment_temp']='273' # temp in kelvin
MeasRec['measurement_temp']='273' # temp in kelvin
MeasRec['measurement_flag']='g'
MeasRec['measurement_standard']='u'
MeasRec['measurement_number']='%i'%(measnum)
measnum+=1
MeasRec['magic_software_packages']=version_num
MeasRecs.append(MeasRec)
# now we have to relabel LP-HYS method codes. initial loop is LP-IMT, minor loops are LP-M - do this in measurements_methods function
if meth=='LP-HYS':
recnum=0
while float(MeasRecs[recnum]['measurement_lab_field_dc'])<float(MeasRecs[recnum+1]['measurement_lab_field_dc']) and recnum+1<len(MeasRecs): # this is LP-IMAG
MeasRecs[recnum]['magic_method_codes']='LP-IMAG'
MeasRecs[recnum]['magic_experiment_name']=MeasRecs[recnum]['er_specimen_name']+":"+'LP-IMAG'
recnum+=1
#
if int(dm)==2:
pmag.magic_write(output,MeasRecs,'magic_measurements')
else:
print ('MagIC 3 is not supported yet')
sys.exit()
pmag.magic_write(output,MeasRecs,'measurements')
print("results put in ", output)
def main():
"""
NAME
mk_redo.py
DESCRIPTION
Makes thellier_redo and zeq_redo files from existing pmag_specimens format file
SYNTAX
mk_redo.py [-h] [command line options]
INPUT
takes specimens.txt formatted input file
OPTIONS
-h: prints help message and quits
-f FILE: specify input file, default is 'specimens.txt'
-F REDO: specify output file suffix, default is redo so that
output filenames are 'thellier_redo' for thellier data and 'zeq_redo' for direction only data
OUTPUT
makes a thellier_redo or a zeq_redo format file
"""
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
zfile, tfile = 'zeq_redo', 'thellier_redo'
zredo, tredo = "", ""
dir_path = pmag.get_named_arg_from_sys('-WD', '.')
inspec = pmag.get_named_arg_from_sys('-f', 'specimens.txt')
if '-F' in sys.argv:
ind = sys.argv.index('-F')
redo = sys.argv[ind + 1]
tfile = redo
zfile = redo
inspec = pmag.resolve_file_name(inspec, dir_path)
zfile = pmag.resolve_file_name(zfile, dir_path)
tfile = pmag.resolve_file_name(tfile, dir_path)
#
# read in data
#
specs = []
prior_spec_data, file_type = pmag.magic_read(inspec)
if file_type != 'specimens':
print(file_type, " this is not a valid pmag_specimens file")
sys.exit()
outstrings = []
for spec in prior_spec_data:
tmp = spec["method_codes"].split(":")
meths = []
for meth in tmp:
methods = meth.strip().split('-')
for m in methods:
if m not in meths:
meths.append(m)
if 'DIR' in meths: # DE-BFL, DE-BFP or DE-FM
specs.append(spec['specimen'])
if 'dir_comp' in list(spec.keys(
)) and spec['dir_comp'] != "" and spec['dir_comp'] != " ":
comp_name = spec['dir_comp']
else:
comp_name = string.ascii_uppercase[
specs.count(spec['specimen']) - 1]
calculation_type = "DE-BFL" # assume default calculation type is best-fit line
if "BFP" in meths:
calculation_type = 'DE-BFP'
elif "FM" in meths:
calculation_type = 'DE-FM'
if zredo == "":
zredo = open(zfile, "w")
outstring = '%s %s %s %s %s \n' % (
spec["specimen"], calculation_type, spec["meas_step_min"],
spec["meas_step_max"], comp_name)
if outstring not in outstrings:
zredo.write(outstring)
outstrings.append(outstring) # only writes unique interpretions
elif "PI" in meths and "TRM" in meths: # thellier record
if tredo == "":
tredo = open(tfile, "w")
outstring = '%s %i %i \n' % (spec["specimen"],
float(spec["meas_step_min"]),
float(spec["meas_step_max"]))
if outstring not in outstrings:
tredo.write(outstring)
outstrings.append(outstring) # only writes unique interpretions
print('Redo files saved to: ', zfile, tfile)
def main():
"""
NAME
quick_hyst.py
DESCRIPTION
makes plots of hysteresis data
SYNTAX
quick_hyst.py [command line options]
OPTIONS
-h prints help message and quits
-f: specify input file, default is measurements.txt
-spc SPEC: specify specimen name to plot and quit
-sav save all plots and quit
-fmt [png,svg,eps,jpg]
"""
args = sys.argv
if "-h" in args:
print main.__doc__
sys.exit()
plots = 0
pltspec = ""
verbose = pmagplotlib.verbose
# version_num = pmag.get_version()
dir_path = pmag.get_named_arg_from_sys("-WD", ".")
dir_path = os.path.realpath(dir_path)
meas_file = pmag.get_named_arg_from_sys("-f", "measurements.txt")
fmt = pmag.get_named_arg_from_sys("-fmt", "png")
if "-sav" in args:
verbose = 0
plots = 1
if "-spc" in args:
ind = args.index("-spc")
pltspec = args[ind + 1]
verbose = 0
plots = 1
#
con = nb.Contribution(dir_path, read_tables=["measurements"], custom_filenames={"measurements": meas_file})
# get as much name data as possible (used for naming plots)
if not "measurements" in con.tables:
print "-W- No measurement file found"
return
con.propagate_name_down("location", "measurements")
if "measurements" not in con.tables:
print main.__doc__
print "bad file"
sys.exit()
meas_container = con.tables["measurements"]
# meas_df = meas_container.df
#
# initialize some variables
# define figure numbers for hyst,deltaM,DdeltaM curves
HystRecs = []
HDD = {}
HDD["hyst"] = 1
pmagplotlib.plot_init(HDD["hyst"], 5, 5)
#
# get list of unique experiment names and specimen names
#
sids = []
hyst_data = meas_container.get_records_for_code("LP-HYS")
# experiment_names = hyst_data['experiment_name'].unique()
if not len(hyst_data):
print "-W- No hysteresis data found"
return
sids = hyst_data["specimen"].unique()
# if 'treat_temp' is provided, use that value, otherwise assume 300
hyst_data["treat_temp"].where(hyst_data["treat_temp"], "300", inplace=True)
# start at first specimen, or at provided specimen ('-spc')
k = 0
if pltspec != "":
try:
print sids
k = list(sids).index(pltspec)
except ValueError:
print "-W- No specimen named: {}.".format(pltspec)
print "-W- Please provide a valid specimen name"
return
intlist = ["magn_moment", "magn_volume", "magn_mass"]
while k < len(sids):
locname, site, sample, synth = "", "", "", ""
s = sids[k]
if verbose:
print s, k + 1, "out of ", len(sids)
# B, M for hysteresis, Bdcd,Mdcd for irm-dcd data
B, M = [], []
# get all measurements for this specimen
spec = hyst_data[hyst_data["specimen"] == s]
# get names
if "location" in spec:
locname = spec["location"][0]
if "site" in spec:
site = spec["sample"][0]
if "sample" in spec:
sample = spec["sample"][0]
# get all records with non-blank values in any intlist column
# find intensity data
for int_column in intlist:
if int_column in spec.columns:
int_col = int_column
break
meas_data = spec[spec[int_column].notnull()]
if len(meas_data) == 0:
break
#
c = ["k-", "b-", "c-", "g-", "m-", "r-", "y-"]
cnum = 0
Temps = []
xlab, ylab, title = "", "", ""
Temps = meas_data["treat_temp"].unique()
for t in Temps:
print "working on t: ", t
t_data = meas_data[meas_data["treat_temp"] == t]
m = int_col
B = t_data["meas_field_dc"].astype(float).values
M = t_data[m].astype(float).values
# now plot the hysteresis curve(s)
#
if len(B) > 0:
B = numpy.array(B)
M = numpy.array(M)
if t == Temps[-1]:
xlab = "Field (T)"
ylab = m
title = "Hysteresis: " + s
if t == Temps[0]:
pmagplotlib.clearFIG(HDD["hyst"])
pmagplotlib.plotXY(HDD["hyst"], B, M, sym=c[cnum], xlab=xlab, ylab=ylab, title=title)
pmagplotlib.plotXY(
HDD["hyst"], [1.1 * B.min(), 1.1 * B.max()], [0, 0], sym="k-", xlab=xlab, ylab=ylab, title=title
)
pmagplotlib.plotXY(
HDD["hyst"], [0, 0], [1.1 * M.min(), 1.1 * M.max()], sym="k-", xlab=xlab, ylab=ylab, title=title
)
if verbose:
pmagplotlib.drawFIGS(HDD)
cnum += 1
if cnum == len(c):
cnum = 0
#
files = {}
if plots:
if pltspec != "":
s = pltspec
for key in HDD.keys():
if synth == "":
files[key] = (
"LO:_" + locname + "_SI:_" + site + "_SA:_" + sample + "_SP:_" + s + "_TY:_" + key + "_." + fmt
)
else:
files[key] = "SY:_" + synth + "_TY:_" + key + "_." + fmt
pmagplotlib.saveP(HDD, files)
if pltspec != "":
sys.exit()
if verbose:
pmagplotlib.drawFIGS(HDD)
ans = raw_input("S[a]ve plots, [s]pecimen name, [q]uit, <return> to continue\n ")
if ans == "a":
files = {}
for key in HDD.keys():
files[key] = (
"LO:_" + locname + "_SI:_" + site + "_SA:_" + sample + "_SP:_" + s + "_TY:_" + key + "_." + fmt
)
pmagplotlib.saveP(HDD, files)
if ans == "":
k += 1
if ans == "p":
del HystRecs[-1]
k -= 1
if ans == "q":
print "Good bye"
sys.exit()
if ans == "s":
keepon = 1
specimen = raw_input("Enter desired specimen name (or first part there of): ")
while keepon == 1:
try:
k = sids.index(specimen)
keepon = 0
except:
tmplist = []
for qq in range(len(sids)):
if specimen in sids[qq]:
tmplist.append(sids[qq])
print specimen, " not found, but this was: "
print tmplist
specimen = raw_input("Select one or try again\n ")
k = sids.index(specimen)
else:
k += 1
if len(B) == 0:
if verbose:
print "skipping this one - no hysteresis data"
k += 1
def main():
"""
NAME
eqarea_magic.py
DESCRIPTION
makes equal area projections from declination/inclination data
SYNTAX
eqarea_magic.py [command line options]
INPUT
takes magic formatted sites, samples, specimens, or measurements
OPTIONS
-h prints help message and quits
-f FILE: specify input magic format file from magic, default='sites.txt'
supported types=[measurements, specimens, samples, sites]
-fsp FILE: specify specimen file name, (required if you want to plot measurements by sample)
default='specimens.txt'
-fsa FILE: specify sample file name, (required if you want to plot specimens by site)
default='samples.txt'
-fsi FILE: specify site file name, default='sites.txt'
-obj OBJ: specify level of plot [all, sit, sam, spc], default is all
-crd [s,g,t]: specify coordinate system, [s]pecimen, [g]eographic, [t]ilt adjusted
default is geographic, unspecified assumed geographic
-fmt [svg,png,jpg] format for output plots
-ell [F,K,B,Be,Bv] plot Fisher, Kent, Bingham, Bootstrap ellipses or Boostrap eigenvectors
-c plot as colour contour
-sav save plot and quit quietly
NOTE
all: entire file; sit: site; sam: sample; spc: specimen
"""
# initialize some default variables
FIG = {} # plot dictionary
FIG['eqarea'] = 1 # eqarea is figure 1
plotE = 0
plt = 0 # default to not plotting
verbose = pmagplotlib.verbose
# extract arguments from sys.argv
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", default_val=os.getcwd())
pmagplotlib.plot_init(FIG['eqarea'],5,5)
in_file = pmag.get_named_arg_from_sys("-f", default_val="sites.txt")
full_in_file = os.path.join(dir_path, in_file)
plot_by = pmag.get_named_arg_from_sys("-obj", default_val="all").lower()
spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
if plot_by == 'all':
plot_key = 'all'
elif plot_by == 'sit':
plot_key = 'site'
elif plot_by == 'sam':
plot_key = 'sample'
elif plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'all'
if '-c' in sys.argv:
contour = 1
else:
contour = 0
if '-sav' in sys.argv:
plt = 1
verbose = 0
if '-ell' in sys.argv:
plotE = 1
ind = sys.argv.index('-ell')
ell_type = sys.argv[ind+1]
ell_type = pmag.get_named_arg_from_sys("-ell", "F")
dist = ell_type.upper()
# if dist type is unrecognized, use Fisher
if dist not in ['F', 'K', 'B', 'BE', 'BV']:
dist = 'F'
if dist == "BV":
FIG['bdirs'] = 2
pmagplotlib.plot_init(FIG['bdirs'],5,5)
crd = pmag.get_named_arg_from_sys("-crd", default_val="g")
if crd == "s":
coord = "-1"
elif crd == "t":
coord = "100"
else:
coord = "0"
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
dec_key = 'dir_dec'
inc_key = 'dir_inc'
tilt_key = 'dir_tilt_correction'
#Dir_type_keys=['','site_direction_type','sample_direction_type','specimen_direction_type']
#
fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path, custom_filenames=fnames,
single_file=in_file)
# the object that contains the DataFrame + useful helper methods:
table_name = list(contribution.tables.keys())[0]
data_container = contribution.tables[table_name]
# the actual DataFrame:
data = data_container.df
# uses sample infile to add temporary site_name
# column to the specimen table
data_container = contribution.tables[table_name]
data = data_container.df
if (plot_key != "all") and (plot_key not in data.columns):
contribution.propagate_location_to_measurements()
contribution.propagate_location_to_specimens()
# add tilt key into DataFrame columns if it isn't there already
if tilt_key not in data.columns:
data.loc[:, tilt_key] = None
if verbose:
print(len(data), ' records read from ', in_file)
# find desired dec,inc data:
dir_type_key = ''
#
# get plotlist if not plotting all records
#
plotlist=[]
if plot_key != "all":
# return all where plot_key is not blank
if plot_key not in data.columns:
print('Can\'t plot by "{}". That header is not in infile: {}'.format(plot_key, in_file))
return
plots = data[data[plot_key].notnull()]
plotlist = plots[plot_key].unique() # grab unique values
else:
plotlist.append('All')
for plot in plotlist:
if verbose:
print(plot)
if plot == 'All':
# plot everything at once
plot_data = data
else:
# pull out only partial data
plot_data = data[data[plot_key] == plot]
DIblock = []
GCblock = []
# SLblock, SPblock = [], []
title = plot
mode = 1
k = 0
if dec_key not in plot_data.columns:
print("-W- No dec/inc data")
continue
# get all records where dec & inc values exist
plot_data = plot_data[plot_data[dec_key].notnull() & plot_data[inc_key].notnull()]
if plot_data.empty:
continue
# this sorting out is done in get_di_bock
#if coord == '0': # geographic, use records with no tilt key (or tilt_key 0)
# cond1 = plot_data[tilt_key].fillna('') == coord
# cond2 = plot_data[tilt_key].isnull()
# plot_data = plot_data[cond1 | cond2]
#else: # not geographic coordinates, use only records with correct tilt_key
# plot_data = plot_data[plot_data[tilt_key] == coord]
# get metadata for naming the plot file
locations = data_container.get_name('location', df_slice=plot_data)
site = data_container.get_name('site', df_slice=plot_data)
sample = data_container.get_name('sample', df_slice=plot_data)
specimen = data_container.get_name('specimen', df_slice=plot_data)
# make sure method_codes is in plot_data
if 'method_codes' not in plot_data.columns:
plot_data['method_codes'] = ''
# get data blocks
DIblock = data_container.get_di_block(df_slice=plot_data,
tilt_corr=coord, excl=['DE-BFP'])
#SLblock = [[ind, row['method_codes']] for ind, row in plot_data.iterrows()]
# get great circles
great_circle_data = data_container.get_records_for_code('DE-BFP', incl=True,
use_slice=True, sli=plot_data)
if len(great_circle_data) > 0:
gc_cond = great_circle_data[tilt_key] == coord
GCblock = [[float(row[dec_key]), float(row[inc_key])] for ind, row in great_circle_data[gc_cond].iterrows()]
#SPblock = [[ind, row['method_codes']] for ind, row in great_circle_data[gc_cond].iterrows()]
if len(DIblock) > 0:
if contour == 0:
pmagplotlib.plotEQ(FIG['eqarea'], DIblock, title)
else:
pmagplotlib.plotEQcont(FIG['eqarea'], DIblock)
else:
pmagplotlib.plotNET(FIG['eqarea'])
if len(GCblock)>0:
for rec in GCblock:
pmagplotlib.plotC(FIG['eqarea'], rec, 90., 'g')
if len(DIblock) == 0 and len(GCblock) == 0:
if verbose:
print("no records for plotting")
continue
#sys.exit()
if plotE == 1:
ppars = pmag.doprinc(DIblock) # get principal directions
nDIs, rDIs, npars, rpars = [], [], [], []
for rec in DIblock:
angle=pmag.angle([rec[0],rec[1]],[ppars['dec'],ppars['inc']])
if angle>90.:
rDIs.append(rec)
else:
nDIs.append(rec)
if dist=='B': # do on whole dataset
etitle="Bingham confidence ellipse"
bpars=pmag.dobingham(DIblock)
for key in list(bpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(bpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(bpars[key]))
npars.append(bpars['dec'])
npars.append(bpars['inc'])
npars.append(bpars['Zeta'])
npars.append(bpars['Zdec'])
npars.append(bpars['Zinc'])
npars.append(bpars['Eta'])
npars.append(bpars['Edec'])
npars.append(bpars['Einc'])
if dist=='F':
etitle="Fisher confidence cone"
if len(nDIs)>2:
fpars=pmag.fisher_mean(nDIs)
for key in list(fpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(fpars[key]))
mode+=1
npars.append(fpars['dec'])
npars.append(fpars['inc'])
npars.append(fpars['alpha95']) # Beta
npars.append(fpars['dec'])
isign=old_div(abs(fpars['inc']),fpars['inc'])
npars.append(fpars['inc']-isign*90.) #Beta inc
npars.append(fpars['alpha95']) # gamma
npars.append(fpars['dec']+90.) # Beta dec
npars.append(0.) #Beta inc
if len(rDIs)>2:
fpars=pmag.fisher_mean(rDIs)
if verbose: print("mode ",mode)
for key in list(fpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(fpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(fpars[key]))
mode+=1
rpars.append(fpars['dec'])
rpars.append(fpars['inc'])
rpars.append(fpars['alpha95']) # Beta
rpars.append(fpars['dec'])
isign=old_div(abs(fpars['inc']),fpars['inc'])
rpars.append(fpars['inc']-isign*90.) #Beta inc
rpars.append(fpars['alpha95']) # gamma
rpars.append(fpars['dec']+90.) # Beta dec
rpars.append(0.) #Beta inc
if dist=='K':
etitle="Kent confidence ellipse"
if len(nDIs)>3:
kpars=pmag.dokent(nDIs,len(nDIs))
if verbose: print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(kpars[key]))
mode+=1
npars.append(kpars['dec'])
npars.append(kpars['inc'])
npars.append(kpars['Zeta'])
npars.append(kpars['Zdec'])
npars.append(kpars['Zinc'])
npars.append(kpars['Eta'])
npars.append(kpars['Edec'])
npars.append(kpars['Einc'])
if len(rDIs)>3:
kpars=pmag.dokent(rDIs,len(rDIs))
if verbose: print("mode ",mode)
for key in list(kpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(kpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(kpars[key]))
mode+=1
rpars.append(kpars['dec'])
rpars.append(kpars['inc'])
rpars.append(kpars['Zeta'])
rpars.append(kpars['Zdec'])
rpars.append(kpars['Zinc'])
rpars.append(kpars['Eta'])
rpars.append(kpars['Edec'])
rpars.append(kpars['Einc'])
else: # assume bootstrap
if dist=='BE':
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
Bkpars=pmag.dokent(BnDIs,1.)
if verbose: print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
npars.append(Bkpars['dec'])
npars.append(Bkpars['inc'])
npars.append(Bkpars['Zeta'])
npars.append(Bkpars['Zdec'])
npars.append(Bkpars['Zinc'])
npars.append(Bkpars['Eta'])
npars.append(Bkpars['Edec'])
npars.append(Bkpars['Einc'])
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
Bkpars=pmag.dokent(BrDIs,1.)
if verbose: print("mode ",mode)
for key in list(Bkpars.keys()):
if key!='n' and verbose: print(" ",key, '%7.1f'%(Bkpars[key]))
if key=='n' and verbose: print(" ",key, ' %i'%(Bkpars[key]))
mode+=1
rpars.append(Bkpars['dec'])
rpars.append(Bkpars['inc'])
rpars.append(Bkpars['Zeta'])
rpars.append(Bkpars['Zdec'])
rpars.append(Bkpars['Zinc'])
rpars.append(Bkpars['Eta'])
rpars.append(Bkpars['Edec'])
rpars.append(Bkpars['Einc'])
etitle="Bootstrapped confidence ellipse"
elif dist=='BV':
sym={'lower':['o','c'],'upper':['o','g'],'size':3,'edgecolor':'face'}
if len(nDIs)>5:
BnDIs=pmag.di_boot(nDIs)
pmagplotlib.plotEQsym(FIG['bdirs'],BnDIs,'Bootstrapped Eigenvectors', sym)
if len(rDIs)>5:
BrDIs=pmag.di_boot(rDIs)
if len(nDIs)>5: # plot on existing plots
pmagplotlib.plotDIsym(FIG['bdirs'],BrDIs,sym)
else:
pmagplotlib.plotEQ(FIG['bdirs'],BrDIs,'Bootstrapped Eigenvectors')
if dist=='B':
if len(nDIs)> 3 or len(rDIs)>3: pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],npars,0)
elif len(nDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],npars,0)
if len(rDIs)>3:
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],rpars,0)
elif len(rDIs)>3 and dist!='BV':
pmagplotlib.plotCONF(FIG['eqarea'],etitle,[],rpars,0)
for key in list(FIG.keys()):
files = {}
filename = pmag.get_named_arg_from_sys('-fname')
if filename: # use provided filename
filename+= '.' + fmt
elif pmagplotlib.isServer: # use server plot naming convention
filename='LO:_'+locations+'_SI:_'+site+'_SA:_'+sample+'_SP:_'+specimen+'_CO:_'+crd+'_TY:_'+key+'_.'+fmt
else: # use more readable naming convention
filename = ''
for item in [locations, site, sample, specimen, crd, key]:
if item:
item = item.replace(' ', '_')
filename += item + '_'
if filename.endswith('_'):
filename = filename[:-1]
filename += ".{}".format(fmt)
files[key]=filename
if pmagplotlib.isServer:
black = '#000000'
purple = '#800080'
titles={}
titles['eq']='Equal Area Plot'
FIG = pmagplotlib.addBorders(FIG,titles,black,purple)
pmagplotlib.saveP(FIG,files)
if plt:
pmagplotlib.saveP(FIG,files)
continue
if verbose:
pmagplotlib.drawFIGS(FIG)
ans=input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == "q":
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG,files)
continue
def main():
"""
NAME
plotXY.py
DESCRIPTION
Makes simple X,Y plots
INPUT FORMAT
X,Y data in columns
SYNTAX
plotxy.py [command line options]
OPTIONS
-h prints this help message
-f FILE to set file name on command line
-c col1 col2 specify columns to plot
-xsig col3 specify xsigma if desired
-ysig col4 specify xsigma if desired
-b xmin xmax ymin ymax, sets bounds
-sym SYM SIZE specify symbol to plot: default is red dots, 10 pt
-S don't plot the symbols
-xlab XLAB
-ylab YLAB
-l connect symbols with lines
-fmt [svg,png,pdf,eps] specify output format, default is svg
-sav saves plot and quits
-poly X plot a degree X polynomial through the data
-skip n Number of lines to skip before reading in data
"""
fmt, plot = "svg", 0
col1, col2 = 0, 1
sym, size = "ro", 50
xlab, ylab = "", ""
lines = 0
if "-h" in sys.argv:
print main.__doc__
sys.exit()
if "-f" in sys.argv:
ind = sys.argv.index("-f")
file = sys.argv[ind + 1]
if "-fmt" in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if "-sav" in sys.argv:
plot = 1
if "-c" in sys.argv:
ind = sys.argv.index("-c")
col1 = int(sys.argv[ind + 1]) - 1
col2 = int(sys.argv[ind + 2]) - 1
if "-xsig" in sys.argv:
ind = sys.argv.index("-xsig")
col3 = int(sys.argv[ind + 1]) - 1
if "-ysig" in sys.argv:
ind = sys.argv.index("-ysig")
col4 = int(sys.argv[ind + 1]) - 1
if "-xlab" in sys.argv:
ind = sys.argv.index("-xlab")
xlab = sys.argv[ind + 1]
if "-ylab" in sys.argv:
ind = sys.argv.index("-ylab")
ylab = sys.argv[ind + 1]
if "-b" in sys.argv:
ind = sys.argv.index("-b")
xmin = float(sys.argv[ind + 1])
xmax = float(sys.argv[ind + 2])
ymin = float(sys.argv[ind + 3])
ymax = float(sys.argv[ind + 4])
if "-poly" in sys.argv:
ind = sys.argv.index("-poly")
degr = sys.argv[ind + 1]
if "-sym" in sys.argv:
ind = sys.argv.index("-sym")
sym = sys.argv[ind + 1]
size = int(sys.argv[ind + 2])
if "-l" in sys.argv:
lines = 1
if "-S" in sys.argv:
sym = ""
skip = int(pmag.get_named_arg_from_sys("-skip", default_val=0))
X, Y = [], []
Xerrs, Yerrs = [], []
f = open(file, "rU")
for num in range(skip):
f.readline()
data = f.readlines()
for line in data:
line.replace("\n", "")
line.replace("\t", " ")
rec = line.split()
X.append(float(rec[col1]))
Y.append(float(rec[col2]))
if "-xsig" in sys.argv:
Xerrs.append(float(rec[col3]))
if "-ysig" in sys.argv:
Yerrs.append(float(rec[col4]))
if "-poly" in sys.argv:
pylab.plot(xs, ys)
coeffs = numpy.polyfit(X, Y, degr)
correl = numpy.corrcoef(X, Y) ** 2
polynomial = numpy.poly1d(coeffs)
xs = numpy.linspace(numpy.min(X), numpy.max(X), 10)
ys = polynomial(xs)
pylab.plot(xs, ys)
print polynomial
if degr == "1":
print "R-square value =", "%5.4f" % (correl[0, 1])
if sym != "":
pylab.scatter(X, Y, marker=sym[1], c=sym[0], s=size)
else:
pylab.plot(X, Y)
if "-xsig" in sys.argv and "-ysig" in sys.argv:
pylab.errorbar(X, Y, xerr=Xerrs, yerr=Yerrs, fmt=None)
if "-xsig" in sys.argv and "-ysig" not in sys.argv:
pylab.errorbar(X, Y, xerr=Xerrs, fmt=None)
if "-xsig" not in sys.argv and "-ysig" in sys.argv:
pylab.errorbar(X, Y, yerr=Yerrs, fmt=None)
if xlab != "":
pylab.xlabel(xlab)
if ylab != "":
pylab.ylabel(ylab)
if lines == 1:
pylab.plot(X, Y, "k-")
if "-b" in sys.argv:
pylab.axis([xmin, xmax, ymin, ymax])
if plot == 0:
pylab.show()
else:
pylab.savefig("plotXY." + fmt)
print "Figure saved as ", "plotXY." + fmt
sys.exit()
def main():
"""
NAME
vgpmap_magic.py
DESCRIPTION
makes a map of vgps and a95/dp,dm for site means in a sites table
SYNTAX
vgpmap_magic.py [command line options]
OPTIONS
-h prints help and quits
-eye ELAT ELON [specify eyeball location], default is 90., 0.
-f FILE sites format file, [default is sites.txt]
-res [c,l,i,h] specify resolution (crude, low, intermediate, high]
-etp plot the etopo20 topographpy data (requires high resolution data set)
-prj PROJ, specify one of the following:
ortho = orthographic
lcc = lambert conformal
moll = molweide
merc = mercator
-sym SYM SIZE: choose a symbol and size, examples:
ro 5 : small red circles
bs 10 : intermediate blue squares
g^ 20 : large green triangles
-ell plot dp/dm or a95 ellipses
-rev RSYM RSIZE : flip reverse poles to normal antipode
-S: plot antipodes of all poles
-age : plot the ages next to the poles
-crd [g,t] : choose coordinate system, default is to plot all site VGPs
-fmt [pdf, png, eps...] specify output format, default is pdf
-sav save and quit
DEFAULTS
FILE: pmag_results.txt
res: c
prj: ortho
ELAT,ELON = 0,0
SYM SIZE: ro 8
RSYM RSIZE: g^ 8
"""
if "-h" in sys.argv:
print main.__doc__
sys.exit()
dir_path = pmag.get_named_arg_from_sys("-WD", ".")
# plot: default is 0, if -sav in sys.argv should be 1
plot = pmag.get_flag_arg_from_sys("-sav", true=1, false=0)
fmt = pmag.get_named_arg_from_sys("-fmt", "pdf")
res = pmag.get_named_arg_from_sys("-res", "c")
proj = pmag.get_named_arg_from_sys("-prj", "ortho")
anti = pmag.get_flag_arg_from_sys("-S", true=1, false=0)
fancy = pmag.get_flag_arg_from_sys("-etp", true=1, false=0)
ell = pmag.get_flag_arg_from_sys("-ell", true=1, false=0)
ages = pmag.get_flag_arg_from_sys("-age", true=1, false=0)
if "-rev" in sys.argv:
flip = 1
ind = sys.argv.index("-rev")
rsym = sys.argv[ind + 1]
rsize = int(sys.argv[ind + 2])
else:
flip, rsym, rsize = 0, "g^", 8
if "-sym" in sys.argv:
ind = sys.argv.index("-sym")
sym = sys.argv[ind + 1]
size = int(sys.argv[ind + 2])
else:
sym, size = "ro", 8
if "-eye" in sys.argv:
ind = sys.argv.index("-eye")
lat_0 = float(sys.argv[ind + 1])
lon_0 = float(sys.argv[ind + 2])
else:
lat_0, lon_0 = 90.0, 0.0
crd = pmag.get_named_arg_from_sys("-crd", "")
coord_dict = {"g": 0, "t": 100}
coord = coord_dict[crd] if crd else ""
results_file = pmag.get_named_arg_from_sys("-f", "sites.txt")
con = nb.Contribution(dir_path, single_file=results_file)
if not con.tables.keys():
print "-W - Couldn't read in data"
return
FIG = {"map": 1}
pmagplotlib.plot_init(FIG["map"], 6, 6)
# read in er_sites file
lats, lons = [], []
Pars = []
dates, rlats, rlons = [], [], []
site_container = con.tables["sites"]
site_df = site_container.df
# use individual results
site_df = site_df[site_df["result_type"] == "i"]
# use records with vgp_lat and vgp_lon
cond1, cond2 = site_df["vgp_lat"].notnull(), site_df["vgp_lon"].notnull()
Results = site_df[cond1 & cond2]
# use tilt correction
if coord and "dir_tilt_correction" in Results.columns:
Results = Results[Results["dir_tilt_correction"] == coord]
# get location name and average ages
location = ":".join(Results["location"].unique())
if "average_age" in Results.columns and ages == 1:
dates = Results["average_age"].unique()
# go through rows and extract data
for ind, row in Results.iterrows():
lat, lon = float(row["vgp_lat"]), float(row["vgp_lon"])
if anti == 1:
lats.append(-lat)
lon = lon + 180.0
if lon > 360:
lon = lon - 360.0
lons.append(lon)
elif flip == 0:
lats.append(lat)
lons.append(lon)
elif flip == 1:
if lat < 0:
rlats.append(-lat)
lon = lon + 180.0
if lon > 360:
lon = lon - 360
rlons.append(lon)
else:
lats.append(lat)
lons.append(lon)
ppars = []
ppars.append(lon)
ppars.append(lat)
ell1, ell2 = "", ""
if "vgp_dm" in row.keys() and row["vgp_dm"]:
ell1 = float(row["vgp_dm"])
if "vgp_dp" in row.keys() and row["vgp_dp"]:
ell2 = float(row["vgp_dp"])
if "vgp_alpha95" in row.keys() and row["vgp_alpha95"].notnull():
ell1, ell2 = float(row["vgp_alpha95"]), float(row["vgp_alpha95"])
if ell1 and ell2:
ppars = []
ppars.append(lons[-1])
ppars.append(lats[-1])
ppars.append(ell1)
ppars.append(lons[-1])
isign = abs(lats[-1]) / lats[-1]
ppars.append(lats[-1] - isign * 90.0)
ppars.append(ell2)
ppars.append(lons[-1] + 90.0)
ppars.append(0.0)
Pars.append(ppars)
location = location.strip(":")
Opts = {
"latmin": -90,
"latmax": 90,
"lonmin": 0.0,
"lonmax": 360.0,
"lat_0": lat_0,
"lon_0": lon_0,
"proj": proj,
"sym": "bs",
"symsize": 3,
"pltgrid": 0,
"res": res,
"boundinglat": 0.0,
}
Opts["details"] = {"coasts": 1, "rivers": 0, "states": 0, "countries": 0, "ocean": 1, "fancy": fancy}
# make the base map with a blue triangle at the pole
pmagplotlib.plotMAP(FIG["map"], [90.0], [0.0], Opts)
Opts["pltgrid"] = -1
Opts["sym"] = sym
Opts["symsize"] = size
if len(dates) > 0:
Opts["names"] = dates
if len(lats) > 0:
# add the lats and lons of the poles
pmagplotlib.plotMAP(FIG["map"], lats, lons, Opts)
Opts["names"] = []
if len(rlats) > 0:
Opts["sym"] = rsym
Opts["symsize"] = rsize
# add the lats and lons of the poles
pmagplotlib.plotMAP(FIG["map"], rlats, rlons, Opts)
if plot == 0:
pmagplotlib.drawFIGS(FIG)
if ell == 1: # add ellipses if desired.
Opts["details"] = {"coasts": 0, "rivers": 0, "states": 0, "countries": 0, "ocean": 0, "fancy": fancy}
Opts["pltgrid"] = -1 # turn off meridian replotting
Opts["symsize"] = 2
Opts["sym"] = "g-"
for ppars in Pars:
if ppars[2] != 0:
PTS = pmagplotlib.plotELL(FIG["map"], ppars, "g.", 0, 0)
elats, elons = [], []
for pt in PTS:
elons.append(pt[0])
elats.append(pt[1])
# make the base map with a blue triangle at the pole
pmagplotlib.plotMAP(FIG["map"], elats, elons, Opts)
if plot == 0:
pmagplotlib.drawFIGS(FIG)
files = {}
for key in FIG.keys():
files[key] = "LO:_" + location + "_VGP_map." + fmt
if pmagplotlib.isServer:
black = "#000000"
purple = "#800080"
titles = {}
titles["eq"] = "LO:_" + location + "_VGP_map"
FIG = pmagplotlib.addBorders(FIG, titles, black, purple)
pmagplotlib.saveP(FIG, files)
elif plot == 0:
pmagplotlib.drawFIGS(FIG)
ans = raw_input(" S[a]ve to save plot, Return to quit: ")
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
print "Good bye"
sys.exit()
else:
pmagplotlib.saveP(FIG, files)
def main():
"""
NAME
irmaq_magic.py
DESCRIPTION
plots IRM acquisition curves from measurements file
SYNTAX
irmaq_magic [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt/measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot, default is by location
-N ; do not normalize by last point - use original units
-fmt [png,jpg,eps,pdf] set plot file format [default is svg]
-sav save plot[s] and quit
-DM MagIC data model number, default is 3
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
FIG = {} # plot dictionary
FIG['exp'] = 1 # exp is figure 1
dir_path = './'
plot, fmt = 0, 'svg'
units = 'T',
XLP = []
norm = 1
LP = "LP-IRM"
if len(sys.argv) > 1:
if '-h' in sys.argv:
print(main.__doc__)
sys.exit()
data_model = int(pmag.get_named_arg_from_sys("-DM", 3))
if '-N' in sys.argv:
norm = 0
if '-sav' in sys.argv:
plot = 1
if '-fmt' in sys.argv:
ind = sys.argv.index("-fmt")
fmt = sys.argv[ind + 1]
if data_model == 3:
in_file = pmag.get_named_arg_from_sys("-f", 'measurements.txt')
else:
in_file = pmag.get_named_arg_from_sys("-f", 'magic_measurements.txt')
if '-WD' in sys.argv:
ind = sys.argv.index('-WD')
dir_path = sys.argv[ind + 1]
dir_path = os.path.realpath(dir_path)
in_file = pmag.resolve_file_name(in_file, dir_path)
if '-WD' not in sys.argv:
dir_path = os.path.split(in_file)[0]
plot_by = pmag.get_named_arg_from_sys("-obj", "loc")
if data_model == 3:
plot_key = 'location'
if plot_by == 'sit':
plot_key = 'site'
if plot_by == 'sam':
plot_key = 'sample'
if plot_by == 'spc':
plot_key = 'specimen'
else:
plot_key = 'er_location_name'
if plot_by == 'sit':
plot_key = 'er_site_name'
if plot_by == 'sam':
plot_key = 'er_sample_name'
if plot_by == 'spc':
plot_key = 'er_specimen_name'
# set defaults and get more information if needed
if data_model == 3:
dmag_key = 'treat_dc_field'
else:
dmag_key = 'treatment_dc_field'
#
if data_model == 3 and plot_key != 'specimen':
# gonna need to read in more files
print('-W- You are trying to plot measurements by {}'.format(plot_key))
print(' By default, this information is not available in your measurement file.')
print(' Trying to acquire this information from {}'.format(dir_path))
con = nb.Contribution(dir_path)
meas_df = con.propagate_location_to_measurements()
if plot_key not in meas_df.columns:
print('-W- Could not find required data.')
print(' Try a different plot key.')
return
else:
print('-I- Found {} information, continuing with plotting'.format(plot_key))
con.write_table_to_file('measurements')
# read in data
data, file_type = pmag.magic_read(in_file)
sids = pmag.get_specs(data)
pmagplotlib.plot_init(FIG['exp'], 6, 6)
#
#
# find desired intensity data
#
# get plotlist
#
plotlist = []
if data_model == 3:
intlist = ['magn_moment', 'magn_volume', 'magn_mass', 'magnitude']
else:
intlist = ['measurement_magnitude', 'measurement_magn_moment',
'measurement_magn_volume', 'measurement_magn_mass']
IntMeths = []
# get all the records with this lab protocol
#print('data', len(data))
#print('data[0]', data[0])
if data_model == 3:
data = pmag.get_dictitem(data, 'method_codes', LP, 'has')
else:
data = pmag.get_dictitem(data, 'magic_method_codes', LP, 'has')
Ints = {}
NoInts, int_key = 1, ""
for key in intlist:
# get all non-blank data for intensity type
Ints[key] = pmag.get_dictitem(data, key, '', 'F')
if len(Ints[key]) > 0:
NoInts = 0
if int_key == "":
int_key = key
if NoInts == 1:
print('No intensity information found')
sys.exit()
for rec in Ints[int_key]:
if rec[plot_key] not in plotlist:
plotlist.append(rec[plot_key])
plotlist.sort()
for plt in plotlist:
print(plt)
INTblock = []
# get data with right intensity info whose plot_key matches plot
data = pmag.get_dictitem(Ints[int_key], plot_key, plt, 'T')
# get a list of specimens with appropriate data
sids = pmag.get_specs(data)
if len(sids) > 0:
title = data[0][plot_key]
for s in sids:
INTblock = []
# get data for each specimen
if data_model == 3:
sdata = pmag.get_dictitem(data, 'specimen', s, 'T')
else:
sdata = pmag.get_dictitem(data, 'er_specimen_name', s, 'T')
for rec in sdata:
INTblock.append([float(rec[dmag_key]), 0, 0,
float(rec[int_key]), 1, 'g'])
pmagplotlib.plotMT(FIG['exp'], INTblock, title, 0, units, norm)
files = {}
for key in list(FIG.keys()):
files[key] = title + '_' + LP + '.' + fmt
if plot == 0:
pmagplotlib.drawFIGS(FIG)
ans = input(" S[a]ve to save plot, [q]uit, Return to continue: ")
if ans == 'q':
sys.exit()
if ans == "a":
pmagplotlib.saveP(FIG, files)
else:
pmagplotlib.saveP(FIG, files)
pmagplotlib.clearFIG(FIG['exp'])
def main():
"""
NAME
dmag_magic.py
DESCRIPTION
plots intensity decay curves for demagnetization experiments
SYNTAX
dmag_magic -h [command line options]
INPUT
takes magic formatted magic_measurements.txt files
OPTIONS
-h prints help message and quits
-f FILE: specify input file, default is: magic_measurements.txt
-obj OBJ: specify object [loc, sit, sam, spc] for plot,
default is by location
-LT [AF,T,M]: specify lab treatment type, default AF
-XLP [PI]: exclude specific lab protocols,
(for example, method codes like LP-PI)
-N do not normalize by NRM magnetization
-sav save plots silently and quit
-fmt [svg,jpg,png,pdf] set figure format [default is svg]
NOTE
loc: location (study); sit: site; sam: sample; spc: specimen
"""
if '-h' in sys.argv:
print main.__doc__
sys.exit()
# initialize variables from command line + defaults
FIG = {} # plot dictionary
FIG['demag'] = 1 # demag is figure 1
in_file = pmag.get_named_arg_from_sys("-f", default_val="measurements.txt")
plot_by = pmag.get_named_arg_from_sys("-obj", default_val="loc")
name_dict = {'loc': 'location', 'sit': 'site',
'sam': 'sample', 'spc': 'specimen'}
plot_key = name_dict[plot_by]
LT = "LT-" + pmag.get_named_arg_from_sys("-LT", "AF") + "-Z"
if LT == "LT-T-Z":
units, dmag_key = 'K', 'treat_temp'
elif LT == "LT-AF-Z":
units, dmag_key = 'T', 'treat_ac_field'
elif LT == 'LT-M-Z':
units, dmag_key = 'J', 'treat_mw_energy'
else:
units = 'U'
no_norm = pmag.get_flag_arg_from_sys("-N")
norm = 0 if no_norm else 1
no_plot = pmag.get_flag_arg_from_sys("-sav")
plot = 0 if no_plot else 1
fmt = pmag.get_named_arg_from_sys("-fmt", "svg")
XLP = pmag.get_named_arg_from_sys("-XLP", "")
dir_path = pmag.get_named_arg_from_sys("-WD", os.getcwd())
spec_file = pmag.get_named_arg_from_sys("-fsp", default_val="specimens.txt")
samp_file = pmag.get_named_arg_from_sys("-fsa", default_val="samples.txt")
site_file = pmag.get_named_arg_from_sys("-fsi", default_val="sites.txt")
# create contribution and add required headers
fnames = {"specimens": spec_file, "samples": samp_file, 'sites': site_file}
contribution = nb.Contribution(dir_path, single_file=in_file,
custom_filenames=fnames)
file_type = contribution.tables.keys()[0]
print len(contribution.tables['measurements'].df), ' records read from ', in_file
# add plot_key into measurements table
if plot_key not in contribution.tables['measurements'].df.columns:
contribution.propagate_name_down(plot_key, 'measurements')
data_container = contribution.tables[file_type]
# pare down to only records with useful data
# grab records that have the requested code
data_slice = data_container.get_records_for_code(LT)
# and don't have the offending code
data = data_container.get_records_for_code(XLP, incl=False, use_slice=True,
sli=data_slice, strict_match=False)
# make sure quality is in the dataframe
if 'quality' not in data.columns:
data['quality'] = 'g'
# get intensity key and make sure intensity data is not blank
intlist = ['magn_moment', 'magn_volume', 'magn_mass']
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
# get rid of any entirely blank intensity columns
for col_name in IntMeths:
if not data[col_name].any():
data.drop(col_name, axis=1, inplace=True)
IntMeths = [col_name for col_name in data.columns if col_name in intlist]
if len(IntMeths) == 0:
print 'No intensity headers found'
sys.exit()
int_key = IntMeths[0] # plot first intensity method found - normalized to initial value anyway - doesn't matter which used
data = data[data[int_key].notnull()]
# make list of individual plots
# by default, will be by location_name
plotlist = data[plot_key].unique()
plotlist.sort()
pmagplotlib.plot_init(FIG['demag'], 5, 5)
# iterate through and plot the data
for plt in plotlist:
plot_data = data[data[plot_key] == plt].copy()
if plot:
print plt, 'plotting by: ', plot_key
if len(plot_data) > 2:
title = plt
spcs = []
spcs = plot_data['specimen'].unique()
for spc in spcs:
INTblock = []
spec_data = plot_data[plot_data['specimen'] == spc]
for ind, rec in spec_data.iterrows():
INTblock.append([float(rec[dmag_key]), 0, 0, float(rec[int_key]), 1, rec['quality']])
if len(INTblock) > 2:
pmagplotlib.plotMT(FIG['demag'], INTblock,
title, 0, units, norm)
if not plot:
files = {}
for key in FIG.keys():
files[key] = title + '_' + LT + '.' + fmt
pmagplotlib.saveP(FIG, files)
#sys.exit()
else:
pmagplotlib.drawFIGS(FIG)
prompt = " S[a]ve to save plot, [q]uit, Return to continue: "
ans = raw_input(prompt)
if ans == 'q':
sys.exit()
if ans == "a":
files = {}
for key in FIG.keys():
files[key] = title + '_' + LT + '.' + fmt
pmagplotlib.saveP(FIG, files)
pmagplotlib.clearFIG(FIG['demag'])
