def test_altitude_plot():
pytplot.netcdf_to_tplot(current_directory +
"/testfiles/g15_xrs_2s_20170619_20170619.nc",
time='time_tag')
pytplot.store_data(
'altitude',
data={
'x':
pytplot.data_quants['A_COUNT'].coords['time'].values,
'y':
np.arange(
0,
len(pytplot.data_quants['A_COUNT'].coords['time'].values),
step=1)
})
pytplot.link('A_COUNT', 'altitude')
pytplot.xlim('2017-06-19 02:00:00', '2017-06-19 04:00:00')
pytplot.ylim("A_COUNT", 17000, 18000)
pytplot.timebar('2017-06-19 03:00:00',
"A_COUNT",
color=(100, 255, 0),
thick=3)
pytplot.timebar('2017-06-19 03:30:00', "A_COUNT", color='g')
pytplot.options("A_COUNT", 'alt', 1)
pytplot.tplot(2, testing=True)
pytplot.tplot(2, testing=True, bokeh=True)
def load_data(filenames=None,
instruments=None,
level='l2',
type=None,
insitu=True,
iuvs=False,
start_date='2014-01-01',
end_date='2020-01-01',
update_prefs=False,
only_update_prefs=False,
local_dir=None,
list_files=False,
new_files=True,
exclude_orbit_file=False,
download_only=False,
varformat=None,
varnames=[],
prefix='',
suffix='',
get_support_data=False,
auto_yes=False):
"""
This function downloads MAVEN data loads it into tplot variables, if applicable.
"""
if not isinstance(instruments, list) and instruments is not None:
instruments = [instruments]
if not isinstance(type, list) and type is not None:
type = [type]
if not isinstance(filenames, list) and filenames is not None:
filenames = [filenames]
# 1. Get a list of MAVEN files queries from the above seach parameters
maven_files = maven_filenames(filenames, instruments, level, insitu, iuvs,
start_date, end_date, update_prefs,
only_update_prefs, local_dir)
# If we are not asking for KP data, this flag ensures only ancillary data is loaded in from the KP files
if level != 'kp':
ancillary_only = True
else:
ancillary_only = False
# Convert to list
if not isinstance(type, list):
type = [type]
# Keep track of what files are downloaded
files_to_load = []
# Loop through all instruments, download files locally if needed
for instr in maven_files.keys():
bn_files_to_load = []
if maven_files[instr]:
s = maven_files[instr][0]
data_dir = maven_files[instr][1]
public = maven_files[instr][2]
# Add to list of files to load
for f in s:
# Filter by type
if type != [None] and instr != 'kp':
file_type_match = False
desc = l2_regex.match(f).group("description")
for t in type:
if t in desc:
file_type_match = True
if not file_type_match:
continue
# Check if the files are KP data
if instr == 'kp':
full_path = create_dir_if_needed(f, data_dir, 'insitu')
else:
full_path = create_dir_if_needed(f, data_dir, level)
bn_files_to_load.append(f)
files_to_load.append(os.path.join(full_path, f))
if list_files:
for f in s:
print(f)
return
if new_files:
if instr == 'kp':
s = get_new_files(bn_files_to_load, data_dir, instr,
'insitu')
else:
s = get_new_files(bn_files_to_load, data_dir, instr, level)
if len(s) == 0:
continue
print("Your request will download a total of: " + str(len(s)) +
" files for instrument " + str(instr))
print('Would you like to proceed with the download? ')
valid_response = False
cancel = False
if auto_yes:
valid_response = True
while not valid_response:
response = (input('(y/n) > '))
if response == 'y' or response == 'Y':
valid_response = True
cancel = False
elif response == 'n' or response == 'N':
print('Cancelled download. Returning...')
valid_response = True
cancel = True
else:
print('Invalid input. Please answer with y or n.')
if cancel:
continue
i = 0
display_progress(i, len(s))
for f in s:
i = i + 1
if instr == 'kp':
full_path = create_dir_if_needed(f, data_dir, 'insitu')
else:
full_path = create_dir_if_needed(f, data_dir, level)
get_file_from_site(f, public, full_path)
display_progress(i, len(s))
# 2. Load files into tplot
if files_to_load:
# Flatten out downloaded files from list of lists of filenames
if isinstance(files_to_load[0], list):
files_to_load = [
item for sublist in files_to_load for item in sublist
]
# Only load in files into tplot if we actually downloaded CDF files
cdf_files = [f for f in files_to_load if '.cdf' in f]
sts_files = [f for f in files_to_load if '.sts' in f]
kp_files = [f for f in files_to_load if '.tab' in f]
loaded_tplot_vars = []
if not download_only:
for f in cdf_files:
# Loop through CDF files
desc = l2_regex.match(os.path.basename(f)).group("description")
if desc != '' and suffix == '':
created_vars = pytplot.cdf_to_tplot(
f,
varformat=varformat,
varnames=varnames,
string_encoding='utf-8',
get_support_data=get_support_data,
prefix=prefix,
suffix=desc,
merge=True)
else:
created_vars = pytplot.cdf_to_tplot(
f,
varformat=varformat,
varnames=varnames,
string_encoding='utf-8',
get_support_data=get_support_data,
prefix=prefix,
suffix=suffix,
merge=True)
# Specifically for SWIA and SWEA data, make sure the plots have log axes and are spectrograms
instr = l2_regex.match(os.path.basename(f)).group("instrument")
if instr in ["swi", "swe"]:
pytplot.options(created_vars, 'spec', 1)
loaded_tplot_vars.append(created_vars)
for f in sts_files:
# Loop through STS (Mag) files
desc = l2_regex.match(os.path.basename(f)).group("description")
if desc != '' and suffix == '':
loaded_tplot_vars.append(
pytplot.sts_to_tplot(f,
prefix=prefix,
suffix=desc,
merge=True))
else:
loaded_tplot_vars.append(
pytplot.sts_to_tplot(f,
prefix=prefix,
suffix=suffix,
merge=True))
# Remove the Decimal Day column, not really useful
for tvar in loaded_tplot_vars:
if "DDAY_" in tvar:
pytplot.del_data(tvar)
del tvar
# Flatten out the list and only grab the unique tplot variables
flat_list = list(
set([
item for sublist in loaded_tplot_vars for item in sublist
]))
# Load in KP data specifically for all of the Ancillary data (position, attitude, Ls, etc)
if kp_files != []:
kp_data_loaded = maven_kp_to_tplot(
filename=kp_files,
ancillary_only=ancillary_only,
instruments=instruments)
# Link all created KP data to the ancillary KP data
for tvar in kp_data_loaded:
pytplot.link(tvar,
"mvn_kp::spacecraft::altitude",
link_type='alt')
pytplot.link(tvar,
"mvn_kp::spacecraft::mso_x",
link_type='x')
pytplot.link(tvar,
"mvn_kp::spacecraft::mso_y",
link_type='y')
pytplot.link(tvar,
"mvn_kp::spacecraft::mso_z",
link_type='z')
pytplot.link(tvar,
"mvn_kp::spacecraft::geo_x",
link_type='geo_x')
pytplot.link(tvar,
"mvn_kp::spacecraft::geo_y",
link_type='geo_y')
pytplot.link(tvar,
"mvn_kp::spacecraft::geo_z",
link_type='geo_z')
pytplot.link(tvar,
"mvn_kp::spacecraft::sub_sc_longitude",
link_type='lon')
pytplot.link(tvar,
"mvn_kp::spacecraft::sub_sc_latitude",
link_type='lat')
# Link all created tplot variables to the corresponding KP data
for tvar in flat_list:
pytplot.link(tvar,
"mvn_kp::spacecraft::altitude",
link_type='alt')
pytplot.link(tvar, "mvn_kp::spacecraft::mso_x", link_type='x')
pytplot.link(tvar, "mvn_kp::spacecraft::mso_y", link_type='y')
pytplot.link(tvar, "mvn_kp::spacecraft::mso_z", link_type='z')
pytplot.link(tvar,
"mvn_kp::spacecraft::geo_x",
link_type='geo_x')
pytplot.link(tvar,
"mvn_kp::spacecraft::geo_y",
link_type='geo_y')
pytplot.link(tvar,
"mvn_kp::spacecraft::geo_z",
link_type='geo_z')
pytplot.link(tvar,
"mvn_kp::spacecraft::sub_sc_longitude",
link_type='lon')
pytplot.link(tvar,
"mvn_kp::spacecraft::sub_sc_latitude",
link_type='lat')
# Return list of unique KP data
return flat_list
def plot(kp,
parameter=None,
time=None,
errors=None,
sameplot=True,
list=False,
title='',
qt=True,
exec_qt=True,
log=False):
'''
Plot time-series data from insitu data structure.
Parameters:
kp : dict
insitu kp data structure/dictionary read from file(s)
parameter : list of str/int
The parameter(s) to be plotted. Can be provided as
integers (by index) or strings (by name: inst.obs). If a
single parameter is provided, it must be an int or str. If
several are provided it must be a list. A list may contain
a mixture of data types.
time : list of str
Two-element list of strings or integers indicating the
range of Time to be plotted. At present, there are no
checks on whether provided Times are within provided data
sameplot : bool
if True, put all curves on same axes
if False, generate new axes for each plot
list : bool
Lists all Key Parameters instead of plotting
title : str
The Title to give the plot
qt : bool
If true, plots with qt. Else creates an HTML page with bokeh.
exec_qt : bool
If False, does not run the event loop for pyqtgraph.
Returns :
None
Examples:
>>> # Plot SWIA H+ density.
>>> pydivide.plot(insitu,parameter='swia.hplus_density')
>>> # Plot SWIA H+ density and altitude in the same window.
>>> pydivide.plot(insitu,parameter=['swia.hplus_density', 'spacecraft.altitude'],sameplot=True)
'''
if list:
x = param_list(kp)
for param in x:
print(param)
return
# Check for orbit num rather than time string
if isinstance(time, builtins.list):
if isinstance(time[0], int):
time = orbit_time(time[0], time[1])
elif isinstance(time, int):
time = orbit_time(time)
# Check existence of parameter
if parameter is None:
print("Must provide an index (or name) for param to be plotted.")
return
# Store instrument and observation of parameter(s) in lists
inst = []
obs = []
if type(parameter) is int or type(parameter) is str:
a, b = get_inst_obs_labels(kp, parameter)
inst.append(a.upper())
obs.append(b.upper())
nparam = 1
else:
nparam = len(parameter)
for param in parameter:
a, b = get_inst_obs_labels(kp, param)
inst.append(a.upper())
obs.append(b.upper())
inst_obs = builtins.list(zip(inst, obs))
# Cycle through the parameters, plotting each according to
# the given keywords
#
iplot = 1 # subplot indexes on 1
legend_names = []
y_list = pydivide.tplot_varcreate(kp, instruments=inst, observations=obs)
for inst_temp, obs_temp in inst_obs:
legend_names.append(obs_temp)
iplot += 1
if time is not None:
pytplot.xlim(time[0], time[1])
if sameplot:
pytplot_name = ''.join(legend_names)
pytplot.store_data(pytplot_name, data=y_list)
pytplot.options(pytplot_name, 'legend_names', legend_names)
pytplot.options(pytplot_name, 'ylog', log)
pytplot.link(pytplot_name,
"mvn_kp::spacecraft::altitude",
link_type='alt')
pytplot.link(pytplot_name, "mvn_kp::spacecraft::mso_x", link_type='x')
pytplot.link(pytplot_name, "mvn_kp::spacecraft::mso_y", link_type='y')
pytplot.link(pytplot_name, "mvn_kp::spacecraft::mso_z", link_type='z')
pytplot.link(pytplot_name,
"mvn_kp::spacecraft::geo_x",
link_type='geo_x')
pytplot.link(pytplot_name,
"mvn_kp::spacecraft::geo_y",
link_type='geo_y')
pytplot.link(pytplot_name,
"mvn_kp::spacecraft::geo_z",
link_type='geo_z')
pytplot.link(pytplot_name,
"mvn_kp::spacecraft::sub_sc_longitude",
link_type='lon')
pytplot.link(pytplot_name,
"mvn_kp::spacecraft::sub_sc_latitude",
link_type='lat')
pytplot.tplot_options('title', title)
pytplot.tplot_options('wsize', [1000, 300])
pytplot.tplot(pytplot_name,
bokeh=not qt,
exec_qt=exec_qt,
window_name='PYDIVIDE_PLOT')
else:
pytplot.tplot_options('title', title)
pytplot.tplot_options('wsize', [1000, 300 * (iplot - 1)])
pytplot.tplot(y_list,
bokeh=not qt,
exec_qt=exec_qt,
window_name='PYDIVIDE_PLOT')
return
def options(name, option, value):
"""
This function allows the user to set a large variety of options for individual plots.
Parameters:
name : str
Name of the tplot variable
option : str
The name of the option. See section below
value : str/int/float/list
The value of the option. See section below.
Options:
=================== ========== =====
Options Value type Notes
=================== ========== =====
Color str/list Red, Orange, Yellow, Green, Blue, etc.
Colormap str/list https://matplotlib.org/examples/color/colormaps_reference.html.
Spec int 1 sets the Tplot Variable to spectrogram mode, 0 reverts.
Alt int 1 sets the Tplot Variable to altitude plot mode, 0 reverts.
Map int 1 sets the Tplot Variable to latitude/longitude mode, 0 reverts.
link list Allows a user to reference one tplot variable to another.
ylog int 1 sets the y axis to log scale, 0 reverts.
zlog int 1 sets the z axis to log scale, 0 reverts (spectrograms only).
legend_names list A list of strings that will be used to identify the lines.
xlog_interactive bool Sets x axis on interactive plot to log scale if True.
ylog bool Set y axis on main plot window to log scale if True.
ylog_interactive bool Sets y axis on interactive plot to log scale if True.
zlog bool Sets z axis on main plot window to log scale if True.
line_style str scatter (to make scatter plots), or solid_line, dot, dash, dash_dot, dash_dot_dot_dot, long_dash.
char_size int Defines character size for plot labels, etc.
name str The title of the plot.
panel_size flt Number between (0,1], representing the percent size of the plot.
basemap str Full path and name of a background image for "Map" plots.
alpha flt Number between [0,1], gives the transparancy of the plot lines.
thick flt Sets plot line width.
yrange flt list Two numbers that give the y axis range of the plot.
zrange flt list Two numbers that give the z axis range of the plot.
xrange_interactive flt list Two numberes that give the x axis range of interactive plots.
yrange_interactive flt list Two numberes that give the y axis range of interactive plots.
ytitle str Title shown on the y axis.
ztitle str Title shown on the z axis. Spec plots only.
plotter str Allows a user to implement their own plotting script in place of the ones
herein.
crosshair_x str Title for x-axis crosshair.
crosshair_y str Title for y-axis crosshair.
crosshair_z str Title for z-axis crosshair.
static str Datetime string that gives desired time to plot y and z values from a spec
plot.
static_tavg str Datetime string that gives desired time-averaged y and z values to plot
from a spec plot.
t_average int Seconds around which the cursor is averaged when hovering over spectrogram
plots.
=================== ========== =====
Returns:
None
Examples:
>>> # Change the y range of Variable1
>>> import pytplot
>>> x_data = [1,2,3,4,5]
>>> y_data = [1,2,3,4,5]
>>> pytplot.store_data("Variable1", data={'x':x_data, 'y':y_data})
>>> pytplot.options('Variable1', 'yrange', [2,4])
>>> # Change Variable1 to use a log scale
>>> pytplot.options('Variable1', 'ylog', 1)
"""
if not isinstance(name, list):
name = [name]
option = option.lower()
for i in name:
if i not in data_quants.keys():
print(str(i) + " is currently not in pytplot.")
return
if option == 'color':
if isinstance(value, list):
data_quants[i].attrs['plot_options']['extras']['line_color'] = value
else:
data_quants[i].attrs['plot_options']['extras']['line_color'] = [value]
if option == 'link':
if isinstance(value, list):
pytplot.link(i, value[1], value[0])
if option == 'colormap':
if isinstance(value, list):
data_quants[i].attrs['plot_options']['extras']['colormap'] = value
else:
data_quants[i].attrs['plot_options']['extras']['colormap'] = [value]
if option == 'spec':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras']['spec'] = value
if option == 'alt':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras']['alt'] = value
if option == 'map':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras']['map'] = value
if option == 'legend_names':
data_quants[i].attrs['plot_options']['yaxis_opt']['legend_names'] = value
if option == 'xlog_interactive':
if value:
data_quants[i].attrs['plot_options']['interactive_xaxis_opt']['xi_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['interactive_xaxis_opt']['xi_axis_type'] = 'linear'
if option == 'ylog':
negflag = 0 # _ylog_check(data_quants, value, i)
if negflag == 0 and value:
data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'linear'
if option == 'ylog_interactive':
if value:
data_quants[i].attrs['plot_options']['interactive_yaxis_opt']['yi_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['interactive_yaxis_opt']['yi_axis_type'] = 'linear'
if option == 'zlog':
negflag = _zlog_check(data_quants, value, i)
if negflag == 0:
data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'linear'
if option == 'nodata':
data_quants[i].attrs['plot_options']['line_opt']['visible'] = value
if option == 'line_style':
to_be = []
if value == 0 or value == 'solid_line':
to_be = []
elif value == 1 or value == 'dot':
to_be = [2, 4]
elif value == 2 or value == 'dash':
to_be = [6]
elif value == 3 or value == 'dash_dot':
to_be = [6, 4, 2, 4]
elif value == 4 or value == 'dash_dot_dot_dot':
to_be = [6, 4, 2, 4, 2, 4, 2, 4]
elif value == 5 or value == 'long_dash':
to_be = [10]
else:
to_be=value
data_quants[i].attrs['plot_options']['line_opt']['line_style'] = to_be
if(value == 6 or value == 'none'):
data_quants[i].attrs['plot_options']['line_opt']['visible'] = False
if option == 'char_size':
data_quants[i].attrs['plot_options']['extras']['char_size'] = value
if option == 'name':
data_quants[i].attrs['plot_options']['line_opt']['name'] = value
if option == "panel_size":
if value > 1 or value <= 0:
print("Invalid value. Should be (0, 1]")
return
data_quants[i].attrs['plot_options']['extras']['panel_size'] = value
if option == 'basemap':
data_quants[i].attrs['plot_options']['extras']['basemap'] = value
if option == 'alpha':
if value > 1 or value < 0:
print("Invalid value. Should be [0, 1]")
return
data_quants[i].attrs['plot_options']['extras']['alpha'] = value
if option == 'thick':
data_quants[i].attrs['plot_options']['line_opt']['line_width'] = value
if option == ('yrange' or 'y_range'):
data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = [value[0], value[1]]
if option == ('zrange' or 'z_range'):
data_quants[i].attrs['plot_options']['zaxis_opt']['z_range'] = [value[0], value[1]]
if option == 'xrange_interactive':
data_quants[i].attrs['plot_options']['interactive_xaxis_opt']['xi_range'] = [value[0], value[1]]
if option == 'yrange_interactive':
data_quants[i].attrs['plot_options']['interactive_yaxis_opt']['yi_range'] = [value[0], value[1]]
if option == 'xtitle':
data_quants[i].attrs['plot_options']['xaxis_opt']['axis_label'] = value
if option == 'ytitle':
data_quants[i].attrs['plot_options']['yaxis_opt']['axis_label'] = value
if option == 'ztitle':
data_quants[i].attrs['plot_options']['zaxis_opt']['axis_label'] = value
if option == 'plotter':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras']['plotter'] = value
if option == 'crosshair_x':
data_quants[i].attrs['plot_options']['xaxis_opt']['crosshair'] = value
if option == 'crosshair_y':
data_quants[i].attrs['plot_options']['yaxis_opt']['crosshair'] = value
if option == 'crosshair_z':
data_quants[i].attrs['plot_options']['zaxis_opt']['crosshair'] = value
if option == 'static':
data_quants[i].attrs['plot_options']['extras']['static'] = value
if option == 'static_tavg':
data_quants[i].attrs['plot_options']['extras']['static_tavg'] = [value[0], value[1]]
if option == 't_average':
data_quants[i].attrs['plot_options']['extras']['t_average'] = value
return
def tplot_varcreate(insitu):
"""Creates tplot variables from the insitu variable
"""
# initialize each instrument
created_vars = []
for obs in insitu["SPACECRAFT"]:
obs_specific = "mvn_kp::spacecraft::" + obs.lower()
try:
pytplot.store_data(obs_specific,
data={
'x': insitu['Time'],
'y': insitu["SPACECRAFT"][obs]
})
created_vars.append(obs_specific)
except:
pass
# Join together the matricies and remove the individual points
pytplot.join_vec([
'mvn_kp::spacecraft::t11', 'mvn_kp::spacecraft::t12',
'mvn_kp::spacecraft::t13', 'mvn_kp::spacecraft::t21',
'mvn_kp::spacecraft::t22', 'mvn_kp::spacecraft::t23',
'mvn_kp::spacecraft::t31', 'mvn_kp::spacecraft::t32',
'mvn_kp::spacecraft::t33'
], 'mvn_kp::geo_to_mso_matrix')
pytplot.del_data([
'mvn_kp::spacecraft::t11', 'mvn_kp::spacecraft::t12',
'mvn_kp::spacecraft::t13', 'mvn_kp::spacecraft::t21',
'mvn_kp::spacecraft::t22', 'mvn_kp::spacecraft::t23',
'mvn_kp::spacecraft::t31', 'mvn_kp::spacecraft::t32',
'mvn_kp::spacecraft::t33'
])
pytplot.join_vec([
'mvn_kp::spacecraft::spacecraft_t11',
'mvn_kp::spacecraft::spacecraft_t12',
'mvn_kp::spacecraft::spacecraft_t13',
'mvn_kp::spacecraft::spacecraft_t21',
'mvn_kp::spacecraft::spacecraft_t22',
'mvn_kp::spacecraft::spacecraft_t23',
'mvn_kp::spacecraft::spacecraft_t31',
'mvn_kp::spacecraft::spacecraft_t32',
'mvn_kp::spacecraft::spacecraft_t33'
], 'mvn_kp::spacecraft_to_mso_matrix')
pytplot.del_data([
'mvn_kp::spacecraft::spacecraft_t11',
'mvn_kp::spacecraft::spacecraft_t12',
'mvn_kp::spacecraft::spacecraft_t13',
'mvn_kp::spacecraft::spacecraft_t21',
'mvn_kp::spacecraft::spacecraft_t22',
'mvn_kp::spacecraft::spacecraft_t23',
'mvn_kp::spacecraft::spacecraft_t31',
'mvn_kp::spacecraft::spacecraft_t32',
'mvn_kp::spacecraft::spacecraft_t33'
])
created_vars.remove('mvn_kp::spacecraft::t11')
created_vars.remove('mvn_kp::spacecraft::t12')
created_vars.remove('mvn_kp::spacecraft::t13')
created_vars.remove('mvn_kp::spacecraft::t21')
created_vars.remove('mvn_kp::spacecraft::t22')
created_vars.remove('mvn_kp::spacecraft::t23')
created_vars.remove('mvn_kp::spacecraft::t31')
created_vars.remove('mvn_kp::spacecraft::t32')
created_vars.remove('mvn_kp::spacecraft::t33')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t11')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t12')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t13')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t21')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t22')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t23')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t31')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t32')
created_vars.remove('mvn_kp::spacecraft::spacecraft_t33')
inst_list = ["EUV", "LPW", "STATIC", "SWEA", "SWIA", "MAG", "SEP", "NGIMS"]
for instrument in inst_list:
# for each observation for each instrument
if instrument in insitu:
if insitu[instrument] is not None:
for obs in insitu[instrument]:
# create variable name
obs_specific = "mvn_kp::" + instrument.lower(
) + "::" + obs.lower()
try:
# store data in tplot variable
pytplot.store_data(obs_specific,
data={
'x': insitu['Time'],
'y': insitu[instrument][obs]
})
created_vars.append(obs_specific)
pytplot.link(obs_specific,
"mvn_kp::spacecraft::altitude",
link_type='alt')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::mso_x",
link_type='x')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::mso_y",
link_type='y')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::mso_z",
link_type='z')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::geo_x",
link_type='geo_x')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::geo_y",
link_type='geo_y')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::geo_z",
link_type='geo_z')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::sub_sc_longitude",
link_type='lon')
pytplot.link(obs_specific,
"mvn_kp::spacecraft::sub_sc_latitude",
link_type='lat')
except:
pass
return created_vars
def options(name, option=None, value=None, opt_dict=None):
"""
This function allows the user to set a large variety of options for individual plots.
Parameters:
name : str
Name or number of the tplot variable
option : str
The name of the option. See section below.
value : str/int/float/list
The value of the option. See section below.
dict : dict
This can be a dictionary of option:value pairs. Option and value
will not be needed if this dictionary item is supplied.
Options:
=================== ========== =====
Options Value type Notes
=================== ========== =====
Color str/list red, green, blue, etc. Also takes in RGB tuples, i.e. (0,255,0) for green
Colormap str/list https://matplotlib.org/examples/color/colormaps_reference.html.
Spec int 1 sets the Tplot Variable to spectrogram mode, 0 reverts.
Alt int 1 sets the Tplot Variable to altitude plot mode, 0 reverts.
Map int 1 sets the Tplot Variable to latitude/longitude mode, 0 reverts.
link list Allows a user to reference one tplot variable to another.
ylog int 1 sets the y axis to log scale, 0 reverts.
zlog int 1 sets the z axis to log scale, 0 reverts (spectrograms only).
legend_names list A list of strings that will be used to identify the lines.
xlog_slice bool Sets x axis on slice plot to log scale if True.
ylog bool Set y axis on main plot window to log scale if True.
ylog_slice bool Sets y axis on slice plot to log scale if True.
zlog bool Sets z axis on main plot window to log scale if True.
line_style str scatter (to make scatter plots), or solid_line, dot, dash, dash_dot, dash_dot_dot_dot, long_dash.
char_size int Defines character size for plot labels, etc.
name str The title of the plot.
panel_size flt Number between (0,1], representing the percent size of the plot.
basemap str Full path and name of a background image for "Map" plots.
alpha flt Number between [0,1], gives the transparancy of the plot lines.
thick flt Sets plot line width.
yrange flt list Two numbers that give the y axis range of the plot.
zrange flt list Two numbers that give the z axis range of the plot.
xrange_slice flt list Two numbers that give the x axis range of spectrogram slicing plots.
yrange_slice flt list Two numbers that give the y axis range of spectrogram slicing plots.
ytitle str Title shown on the y axis.
ztitle str Title shown on the z axis. Spec plots only.
ysubtitle str Subtitle shown on the y axis.
zsubtitle str Subtitle shown on the z axis. Spec plots only.
plotter str Allows a user to implement their own plotting script in place of the ones
herein.
crosshair_x str Title for x-axis crosshair.
crosshair_y str Title for y-axis crosshair.
crosshair_z str Title for z-axis crosshair.
static str Datetime string that gives desired time to plot y and z values from a spec
plot.
static_tavg str Datetime string that gives desired time-averaged y and z values to plot
from a spec plot.
t_average int Seconds around which the cursor is averaged when hovering over spectrogram
plots.
'spec_plot_dim' int If variable two dimensions, this sets which dimension the variable will have on
on the y axis. All other dimensions are summed into this one.
=================== ========== =====
Returns:
None
Examples:
>>> # Change the y range of Variable1
>>> import pytplot
>>> x_data = [1,2,3,4,5]
>>> y_data = [1,2,3,4,5]
>>> pytplot.store_data("Variable1", data={'x':x_data, 'y':y_data})
>>> pytplot.options('Variable1', 'yrange', [2,4])
>>> # Change Variable1 to use a log scale
>>> pytplot.options('Variable1', 'ylog', 1)
"""
if isinstance(name, int):
name = list(pytplot.data_quants.keys())[name]
if opt_dict is None:
opt_dict = {option: value}
else:
if not isinstance(opt_dict, dict):
print("dict must be a dictionary object. Returning.")
return
if not isinstance(name, list):
name = [name]
for i in name:
for option, value in opt_dict.items():
# Lower case option for consistency
option = option.lower()
if i not in data_quants.keys():
print(str(i) + " is currently not in pytplot.")
return
if option == 'color':
if isinstance(value, list):
data_quants[i].attrs['plot_options']['extras'][
'line_color'] = value
else:
data_quants[i].attrs['plot_options']['extras'][
'line_color'] = [value]
if option == 'link':
if isinstance(value, list):
pytplot.link(i, value[1], value[0])
if option == 'colormap':
if isinstance(value, list):
data_quants[i].attrs['plot_options']['extras'][
'colormap'] = value
else:
data_quants[i].attrs['plot_options']['extras'][
'colormap'] = [value]
if option == 'spec':
_reset_plots(i)
if value:
if 'spec_bins' not in data_quants[i].coords:
print(
f"{i} does not contain coordinates for spectrogram plotting. Continuing..."
)
else:
data_quants[i].attrs['plot_options']['extras'][
'spec'] = value
data_quants[i].attrs['plot_options']['yaxis_opt'][
'y_range'] = utilities.get_y_range(data_quants[i])
else:
data_quants[i].attrs['plot_options']['extras'][
'spec'] = value
data_quants[i].attrs['plot_options']['yaxis_opt'][
'y_range'] = utilities.get_y_range(data_quants[i])
if option == 'alt':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras']['alt'] = value
if option == 'map':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras']['map'] = value
if option == 'legend_names':
data_quants[i].attrs['plot_options']['yaxis_opt'][
'legend_names'] = value
if option == 'xlog_slice':
if value:
data_quants[i].attrs['plot_options']['slice_xaxis_opt'][
'xi_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['slice_xaxis_opt'][
'xi_axis_type'] = 'linear'
if option == 'ylog':
negflag = 0 # _ylog_check(data_quants, value, i)
if negflag == 0 and value:
data_quants[i].attrs['plot_options']['yaxis_opt'][
'y_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['yaxis_opt'][
'y_axis_type'] = 'linear'
if option == 'ylog_slice':
if value:
data_quants[i].attrs['plot_options']['slice_yaxis_opt'][
'yi_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['slice_yaxis_opt'][
'yi_axis_type'] = 'linear'
if option == 'zlog':
negflag = _zlog_check(data_quants, value, i)
if negflag == 0:
data_quants[i].attrs['plot_options']['zaxis_opt'][
'z_axis_type'] = 'log'
else:
data_quants[i].attrs['plot_options']['zaxis_opt'][
'z_axis_type'] = 'linear'
if option == 'nodata':
data_quants[i].attrs['plot_options']['line_opt'][
'visible'] = value
if option == 'line_style':
to_be = []
if value == 0 or value == 'solid_line':
to_be = []
elif value == 1 or value == 'dot':
to_be = [2, 4]
elif value == 2 or value == 'dash':
to_be = [6]
elif value == 3 or value == 'dash_dot':
to_be = [6, 4, 2, 4]
elif value == 4 or value == 'dash_dot_dot_dot':
to_be = [6, 4, 2, 4, 2, 4, 2, 4]
elif value == 5 or value == 'long_dash':
to_be = [10]
else:
to_be = value
data_quants[i].attrs['plot_options']['line_opt'][
'line_style'] = to_be
if (value == 6 or value == 'none'):
data_quants[i].attrs['plot_options']['line_opt'][
'visible'] = False
if option == 'char_size':
data_quants[i].attrs['plot_options']['extras'][
'char_size'] = value
if option == 'name':
data_quants[i].attrs['plot_options']['line_opt'][
'name'] = value
if option == "panel_size":
if value > 1 or value <= 0:
print("Invalid value. Should be (0, 1]")
return
data_quants[i].attrs['plot_options']['extras'][
'panel_size'] = value
if option == 'basemap':
data_quants[i].attrs['plot_options']['extras'][
'basemap'] = value
if option == 'alpha':
if value > 1 or value < 0:
print("Invalid value. Should be [0, 1]")
return
data_quants[i].attrs['plot_options']['extras']['alpha'] = value
if option == 'thick':
data_quants[i].attrs['plot_options']['line_opt'][
'line_width'] = value
if option == 'yrange' or option == 'y_range':
data_quants[i].attrs['plot_options']['yaxis_opt'][
'y_range'] = [value[0], value[1]]
if option == 'zrange' or option == 'z_range':
data_quants[i].attrs['plot_options']['zaxis_opt'][
'z_range'] = [value[0], value[1]]
if option == 'xrange_slice':
data_quants[i].attrs['plot_options']['slice_xaxis_opt'][
'xi_range'] = [value[0], value[1]]
if option == 'yrange_slice':
data_quants[i].attrs['plot_options']['slice_yaxis_opt'][
'yi_range'] = [value[0], value[1]]
if option == 'xtitle':
data_quants[i].attrs['plot_options']['xaxis_opt'][
'axis_label'] = value
if option == 'ytitle':
data_quants[i].attrs['plot_options']['yaxis_opt'][
'axis_label'] = value
if option == 'ztitle':
data_quants[i].attrs['plot_options']['zaxis_opt'][
'axis_label'] = value
if option == 'xsubtitle':
data_quants[i].attrs['plot_options']['xaxis_opt'][
'axis_subtitle'] = value
if option == 'ysubtitle':
data_quants[i].attrs['plot_options']['yaxis_opt'][
'axis_subtitle'] = value
if option == 'zsubtitle':
data_quants[i].attrs['plot_options']['zaxis_opt'][
'axis_subtitle'] = value
if option == 'ybar':
data_quants[i].attrs['plot_options']['extras']['ybar'] = value
if option == 'ybar_color':
data_quants[i].attrs['plot_options']['extras']['ybar'] = value
if option == 'ybar_size':
data_quants[i].attrs['plot_options']['extras']['ysize'] = value
if option == 'plotter':
_reset_plots(i)
data_quants[i].attrs['plot_options']['extras'][
'plotter'] = value
if option == 'crosshair_x':
data_quants[i].attrs['plot_options']['xaxis_opt'][
'crosshair'] = value
if option == 'crosshair_y':
data_quants[i].attrs['plot_options']['yaxis_opt'][
'crosshair'] = value
if option == 'crosshair_z':
data_quants[i].attrs['plot_options']['zaxis_opt'][
'crosshair'] = value
if option == 'static':
data_quants[i].attrs['plot_options']['extras'][
'static'] = value
if option == 'static_tavg':
data_quants[i].attrs['plot_options']['extras'][
'static_tavg'] = [value[0], value[1]]
if option == 't_average':
data_quants[i].attrs['plot_options']['extras'][
't_average'] = value
if option == 'spec_plot_dim':
attr_dict = deepcopy(data_quants[i].attrs)
data_dict = {}
data_dict['x'] = data_quants[i].coords['time'].values
data_values = data_quants[i].values
if len(data_values.shape) <= 2:
pass
else:
data_dict['y'] = np.swapaxes(data_values, 2, value)
for c in data_quants[i].coords:
if c == 'time' or c == 'spec_bins':
continue
data_dict[c] = data_quants[i].coords[c].values
v2_values = data_quants[i].coords["v2"].values
data_dict['v2'] = data_dict['v' + str(value)]
data_dict['v' + str(value)] = v2_values
pytplot.store_data(i, data=data_dict)
data_quants[i].attrs = attr_dict
data_quants[i].attrs['plot_options']['yaxis_opt'][
'y_range'] = utilities.get_y_range(data_quants[i])
return
def options(name, option=None, value=None, opt_dict=None):
"""
This function allows the user to set a large variety of options for individual plots.
Parameters:
name : str
Name or number of the tplot variable
option : str
The name of the option. See section below.
value : str/int/float/list
The value of the option. See section below.
dict : dict
This can be a dictionary of option:value pairs. Option and value
will not be needed if this dictionary item is supplied.
Options:
=================== ========== =====
Options Value type Notes
=================== ========== =====
Color str/list red, green, blue, etc. Also takes in RGB tuples, i.e. (0,255,0) for green
Colormap str/list https://matplotlib.org/examples/color/colormaps_reference.html.
Spec int 1 sets the Tplot Variable to spectrogram mode, 0 reverts.
Alt int 1 sets the Tplot Variable to altitude plot mode, 0 reverts.
Map int 1 sets the Tplot Variable to latitude/longitude mode, 0 reverts.
link list Allows a user to reference one tplot variable to another.
ylog int 1 sets the y axis to log scale, 0 reverts.
zlog int 1 sets the z axis to log scale, 0 reverts (spectrograms only).
legend_names list A list of strings that will be used to identify the lines.
xlog_slice bool Sets x axis on slice plot to log scale if True.
ylog bool Set y axis on main plot window to log scale if True.
ylog_slice bool Sets y axis on slice plot to log scale if True.
zlog bool Sets z axis on main plot window to log scale if True.
line_style str scatter (to make scatter plots), or solid_line, dot, dash, dash_dot, dash_dot_dot_dot, long_dash.
char_size int Defines character size for plot labels, etc.
name str The title of the plot.
panel_size flt Number between (0,1], representing the percent size of the plot.
basemap str Full path and name of a background image for "Map" plots.
alpha flt Number between [0,1], gives the transparency of the plot lines.
thick flt Sets plot line width.
yrange flt list Two numbers that give the y axis range of the plot.
zrange flt list Two numbers that give the z axis range of the plot.
xrange_slice flt list Two numbers that give the x axis range of spectrogram slicing plots.
yrange_slice flt list Two numbers that give the y axis range of spectrogram slicing plots.
ytitle str Title shown on the y axis. Use backslash for new lines.
ztitle str Title shown on the z axis. Spec plots only. Use backslash for new lines.
ysubtitle str Subtitle shown on the y axis.
zsubtitle str Subtitle shown on the z axis. Spec plots only.
plotter str Allows a user to implement their own plotting script in place of the ones
herein.
crosshair_x str Title for x-axis crosshair.
crosshair_y str Title for y-axis crosshair.
crosshair_z str Title for z-axis crosshair.
static str Datetime string that gives desired time to plot y and z values from a spec
plot.
static_tavg str Datetime string that gives desired time-averaged y and z values to plot
from a spec plot.
t_average int Seconds around which the cursor is averaged when hovering over spectrogram
plots.
spec_plot_dim int/str If variable has more than two dimensions, this sets which dimension the v
variable will display on the y axis in spectrogram plots.
All other dimensions are summed into this one, unless "spec_slices_to_use"
is also set for this variable.
spec_dim_to_plot int/str Same as spec_plot_dim, just with a slightly more descriptive name
spec_slices_to_use str Must be a dictionary of coordinate:values. If a variable has more than two
dimensions, spectrogram plots will plot values at that particular slice of
that dimension. See examples for how it works.
border bool Turns on or off the top/right axes that would create a box around the plot
var_label_ticks int Sets the number of ticks if this variable is displayed as an alternative x axis
=================== ========== =====
Returns:
None
Examples:
>>> # Change the y range of Variable1
>>> import pytplot
>>> x_data = [1,2,3,4,5]
>>> y_data = [1,2,3,4,5]
>>> pytplot.store_data("Variable1", data={'x':x_data, 'y':y_data})
>>> pytplot.options('Variable1', 'yrange', [2,4])
>>> # Change Variable1 to use a log scale
>>> pytplot.options('Variable1', 'ylog', 1)
>>> # Set the spectrogram plots to show dimension 'v2' at slice 'v1' = 0
>>> pytplot.options("Variable2", "spec_dim_to_plot", 'v2')
>>> pytplot.options("Variable2", "spec_slices_to_use", {'v1': 0})
"""
if isinstance(name, int):
name = list(pytplot.data_quants.keys())[name]
if opt_dict is None:
opt_dict = {option: value}
else:
if not isinstance(opt_dict,dict):
print("dict must be a dictionary object. Returning.")
return
if not isinstance(name, list):
name = [name]
for i in name:
for option, value in opt_dict.items():
# Lower case option for consistency
option = option.lower()
if i not in pytplot.data_quants.keys():
print(str(i) + " is currently not in pytplot.")
return
if option == 'color':
if isinstance(value, list):
pytplot.data_quants[i].attrs['plot_options']['extras']['line_color'] = value
else:
pytplot.data_quants[i].attrs['plot_options']['extras']['line_color'] = [value]
if option == 'link':
if isinstance(value, list):
pytplot.link(i, value[1], value[0])
if option == 'colormap':
if isinstance(value, list):
pytplot.data_quants[i].attrs['plot_options']['extras']['colormap'] = value
else:
pytplot.data_quants[i].attrs['plot_options']['extras']['colormap'] = [value]
if option == 'spec':
_reset_plots(i)
if value:
if 'spec_bins' not in pytplot.data_quants[i].coords:
print(f"{i} does not contain coordinates for spectrogram plotting. Continuing...")
continue
else:
pytplot.data_quants[i].attrs['plot_options']['extras']['spec'] = value
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = utilities.get_y_range(pytplot.data_quants[i])
else:
pytplot.data_quants[i].attrs['plot_options']['extras']['spec'] = value
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = utilities.get_y_range(pytplot.data_quants[i])
# Set the default dimension to plot by. All others will be summed over.
if 'spec_dim_to_plot' not in pytplot.data_quants[i].attrs['plot_options']['extras']:
if 'v' in pytplot.data_quants[i].coords:
pytplot.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = 'v'
elif 'v2' in pytplot.data_quants[i].coords:
pytplot.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = 'v2'
else:
pytplot.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = 'v1'
if option == 'alt':
_reset_plots(i)
pytplot.data_quants[i].attrs['plot_options']['extras']['alt'] = value
if option == 'map':
_reset_plots(i)
pytplot.data_quants[i].attrs['plot_options']['extras']['map'] = value
if option == 'legend_names':
if isinstance(value, list):
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_names'] = value
else:
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['legend_names'] = [value]
if option == 'xlog_slice':
if value:
pytplot.data_quants[i].attrs['plot_options']['slice_xaxis_opt']['xi_axis_type'] = 'log'
else:
pytplot.data_quants[i].attrs['plot_options']['slice_xaxis_opt']['xi_axis_type'] = 'linear'
if option == 'ylog':
negflag = 0 # _ylog_check(data_quants, value, i)
if negflag == 0 and value:
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'log'
else:
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['y_axis_type'] = 'linear'
if option == 'ylog_slice':
if value:
pytplot.data_quants[i].attrs['plot_options']['slice_yaxis_opt']['yi_axis_type'] = 'log'
else:
pytplot.data_quants[i].attrs['plot_options']['slice_yaxis_opt']['yi_axis_type'] = 'linear'
if option == 'zlog':
# check for negative values and warn the user that they will be ignored
negflag = _zlog_check(pytplot.data_quants, value, i)
if negflag != 0 and value:
print(str(i) + ' contains negative values; setting the z-axis to log scale will cause the negative values to be ignored on figures.')
if value:
pytplot.data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'log'
else:
pytplot.data_quants[i].attrs['plot_options']['zaxis_opt']['z_axis_type'] = 'linear'
if option == 'nodata':
pytplot.data_quants[i].attrs['plot_options']['line_opt']['visible'] = value
if option == 'line_style':
if value == 0 or value == 'solid_line':
to_be = []
elif value == 1 or value == 'dot':
to_be = [2, 4]
elif value == 2 or value == 'dash':
to_be = [6]
elif value == 3 or value == 'dash_dot':
to_be = [6, 4, 2, 4]
elif value == 4 or value == 'dash_dot_dot_dot':
to_be = [6, 4, 2, 4, 2, 4, 2, 4]
elif value == 5 or value == 'long_dash':
to_be = [10]
else:
to_be=value
pytplot.data_quants[i].attrs['plot_options']['line_opt']['line_style'] = to_be
if(value == 6 or value == 'none'):
pytplot.data_quants[i].attrs['plot_options']['line_opt']['visible'] = False
if option == 'char_size':
pytplot.data_quants[i].attrs['plot_options']['extras']['char_size'] = value
if option == 'name':
pytplot.data_quants[i].attrs['plot_options']['line_opt']['name'] = value
if option == "panel_size":
if value > 1 or value <= 0:
print("Invalid value. Should be (0, 1]")
return
pytplot.data_quants[i].attrs['plot_options']['extras']['panel_size'] = value
if option == 'basemap':
pytplot.data_quants[i].attrs['plot_options']['extras']['basemap'] = value
if option == 'alpha':
if value > 1 or value < 0:
print("Invalid value. Should be [0, 1]")
return
pytplot.data_quants[i].attrs['plot_options']['extras']['alpha'] = value
if option == 'thick':
pytplot.data_quants[i].attrs['plot_options']['line_opt']['line_width'] = value
if option == 'yrange' or option == 'y_range':
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = [value[0], value[1]]
if option == 'zrange' or option == 'z_range':
pytplot.data_quants[i].attrs['plot_options']['zaxis_opt']['z_range'] = [value[0], value[1]]
if option == 'xrange_slice':
pytplot.data_quants[i].attrs['plot_options']['slice_xaxis_opt']['xi_range'] = [value[0], value[1]]
if option == 'yrange_slice':
pytplot.data_quants[i].attrs['plot_options']['slice_yaxis_opt']['yi_range'] = [value[0], value[1]]
if option == 'xtitle':
pytplot.data_quants[i].attrs['plot_options']['xaxis_opt']['axis_label'] = value
if option == 'ytitle':
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['axis_label'] = value
if option == 'ztitle':
pytplot.data_quants[i].attrs['plot_options']['zaxis_opt']['axis_label'] = value
if option == 'xsubtitle':
pytplot.data_quants[i].attrs['plot_options']['xaxis_opt']['axis_subtitle'] = value
if option == 'ysubtitle':
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['axis_subtitle'] = value
if option == 'zsubtitle':
pytplot.data_quants[i].attrs['plot_options']['zaxis_opt']['axis_subtitle'] = value
if option == 'ybar':
pytplot.data_quants[i].attrs['plot_options']['extras']['ybar'] = value
if option == 'ybar_color':
pytplot.data_quants[i].attrs['plot_options']['extras']['ybar'] = value
if option == 'ybar_size':
pytplot.data_quants[i].attrs['plot_options']['extras']['ysize'] = value
if option == 'plotter':
_reset_plots(i)
pytplot.data_quants[i].attrs['plot_options']['extras']['plotter'] = value
if option == 'crosshair_x':
pytplot.data_quants[i].attrs['plot_options']['xaxis_opt']['crosshair'] = value
if option == 'crosshair_y':
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['crosshair'] = value
if option == 'crosshair_z':
pytplot.data_quants[i].attrs['plot_options']['zaxis_opt']['crosshair'] = value
if option == 'static':
pytplot.data_quants[i].attrs['plot_options']['extras']['static'] = value
if option == 'static_tavg':
pytplot.data_quants[i].attrs['plot_options']['extras']['static_tavg'] = [value[0], value[1]]
if option == 't_average':
pytplot.data_quants[i].attrs['plot_options']['extras']['t_average'] = value
if option == 'spec_dim_to_plot' or option == 'spec_plot_dim':
if len(pytplot.data_quants[i].values.shape) <= 2:
print(f"Must have more than 2 coordinate dimensions to set spec_coord_to_plot for {pytplot.data_quants[i].name}")
continue
# Set the 'spec_dim_to_plot' value to either 'v' or 'v1', 'v2', 'v3', etc.
if isinstance(value, int):
coord_to_plot = "v" + str(value)
if coord_to_plot not in pytplot.data_quants[i].coords:
if value == 1:
coord_to_plot = "v"
if coord_to_plot not in pytplot.data_quants[i].coords:
print(f"Dimension {value} not found in {pytplot.data_quants[i].name}")
continue
else:
print(f"Dimension {value} not found in {pytplot.data_quants[i].name}")
continue
pytplot.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = coord_to_plot
elif isinstance(value, str):
coord_to_plot = value
if coord_to_plot not in pytplot.data_quants[i].coords:
print(f"Dimension {value} not found in {pytplot.data_quants[i].name}")
continue
else:
pytplot.data_quants[i].attrs['plot_options']['extras']['spec_dim_to_plot'] = value
# If we're plotting against different coordinates, we need to change what we consider the "spec_bins"
pytplot.data_quants[i].coords['spec_bins'] = pytplot.data_quants[i].coords[coord_to_plot]
pytplot.data_quants[i].attrs['plot_options']['yaxis_opt']['y_range'] = utilities.get_y_range(pytplot.data_quants[i])
if option == 'spec_slices_to_use':
if not isinstance(value, dict):
print("Must be a dictionary object in the format {'v2':15, 'v3':7}")
return
else:
for coord in value:
if coord not in pytplot.data_quants[i].coords:
print(f"Dimension {coord} not found in {pytplot.data_quants[i].name}")
continue
pytplot.data_quants[i].attrs['plot_options']['extras']['spec_slices_to_use'] = value
if option == 'border':
pytplot.data_quants[i].attrs['plot_options']['extras']['border'] = value
if option == 'var_label_ticks':
pytplot.data_quants[i].attrs['plot_options']['var_label_ticks'] = value
return