def _save_xls_data_table(self, root, ias, step_heat_title, fusion_title, spectrometer,
summary_sheet=False,
auto_view=False):
ext = '.xls'
app = 'Microsoft Office 2011/Microsoft Excel'
shgroups, fgroups = self._assemble_groups(ias)
if shgroups:
w = StepHeatTableXLSWriter()
name = '{}_{}_step_heat_data'.format(self.name, spectrometer)
p, _ = unique_path(root, name, extension=ext)
iagroups, shgroups = zip(*shgroups)
w.build(p, iagroups, shgroups, use_summary_sheet=summary_sheet,
title=step_heat_title)
if auto_view:
view_file(p, application=app)
if fgroups:
w = FusionTableXLSWriter()
name = '{}_{}_fusion_data'.format(self.name, spectrometer)
p, _ = unique_path(root, name, extension=ext)
iagroups, fgroups = zip(*fgroups)
w.build(p, iagroups, fgroups, use_summary_sheet=summary_sheet,
title=fusion_title)
if auto_view:
view_file(p, application=app)
def _new_frame_path(self,
path=None,
directory='scans',
offset=0,
base_frame_name=None,
verbose=True):
"""
"""
if base_frame_name is None:
base_frame_name = 'scan'
'''
if directory is an absolute path paths.data_dir is not joined
'''
base = os.path.join(paths.data_dir, directory)
if not os.path.isdir(base):
os.mkdir(base)
if path is None:
path, _cnt = unique_path(base,
base_frame_name,
extension=self._extension)
if verbose:
self.info('New frame {}'.format(path))
return path
def _save(self, editor, root, pathname, name, project, lns):
if self._save_pdf_figure:
p, _ = unique_path(root, pathname, extension='.pdf')
editor.save_file(p, dest_box=(1.5, 1, 6, 9))
if self._save_db_figure:
editor.save_figure('EasyFigure {}'.format(name), project, lns)
def _start_recording(self, path, basename):
self.info('start video recording {}'.format(path))
d = os.path.dirname(path)
if not os.path.isdir(d):
self.warning('invalid directory {}'.format(d))
self.warning('using default directory')
path, _ = unique_path(paths.video_dir, basename, extension='avi')
self.info('saving recording to path {}'.format(path))
# if self.use_db:
# db = self.get_video_database()
# db.connect()
#
# v = db.add_video_record(rid=basename)
# db.add_path(v, path)
# self.info('saving {} to database'.format(basename))
# db.commit()
video = self.video
def renderer(p):
cw, ch = self.get_frame_size()
frame = video.get_cached_frame()
frame = video.crop(frame, 0, 0, cw, ch)
if frame is not None:
pil_save(frame, p)
if self.render_with_markup:
renderer = self._render_snapshot
self.video.start_recording(path, renderer)
def snapshot(self, path=None, name=None, auto=False, inform=True):
"""
path: abs path to use
name: base name to use if auto saving in default dir
auto: force auto save
returns:
path: local abs path
upath: remote abs path
"""
if path is None:
if self.auto_save_snapshot or auto:
if name is None:
name = 'snapshot'
path, _cnt = unique_path(root=paths.snapshot_dir, base=name,
extension='jpg')
else:
path = self.save_file_dialog()
if path:
self.info('saving snapshot {}'.format(path))
# play camera shutter sound
play_sound('shutter')
self._render_snapshot(path)
upath = self._upload(path)
if inform:
self.information_dialog('Snapshot save to {}. Uploaded to'.format(path, upath))
return path, upath
def snapshot(self, path=None, name=None, auto=False, inform=True):
"""
path: abs path to use
name: base name to use if auto saving in default dir
auto: force auto save
returns:
path: local abs path
upath: remote abs path
"""
if path is None:
if self.auto_save_snapshot or auto:
if name is None:
name = 'snapshot'
path, _cnt = unique_path(root=paths.snapshot_dir,
base=name,
extension='jpg')
else:
path = self.save_file_dialog()
if path:
self.info('saving snapshot {}'.format(path))
# play camera shutter sound
play_sound('shutter')
self._render_snapshot(path)
upath = self._upload(path)
if inform:
self.information_dialog(
'Snapshot save to {}. Uploaded to'.format(path, upath))
return path, upath
def _dump_scan(self):
root = os.path.join(paths.data_dir, 'mass_calibration_scans')
if not os.path.isdir(root):
os.mkdir(root)
p, _ = unique_path(root, 'scan')
d = self._get_coarse_data()
savetxt(p, d)
def _dump_scan(self):
root = os.path.join(paths.data_dir, 'mass_calibration_scans')
if not os.path.isdir(root):
os.mkdir(root)
p, _ = unique_path(root, 'scan')
d = self._get_coarse_data()
savetxt(p, d)
def export_csv(self):
ans = self._get_analyses('export_apis')
ans = self.make_analyses(ans, unpack=True)
root = os.path.join(paths.data_dir, 'apis')
p, _ = unique_path(root, 'data', extension='.csv')
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
for ai in ans:
self._write_analysis(ai, writer)
def export_csv(self):
ans = self._get_analyses('export_apis')
ans = self.make_analyses(ans, unpack=True)
root = os.path.join(paths.data_dir, 'apis')
p, _ = unique_path(root, 'data', extension='.csv')
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
for ai in ans:
self._write_analysis(ai, writer)
def __clear(self):
'''
'''
# make a backup copy
p, _cnt = unique_path(paths.root, 'laser_shot_history', 'bak')
shutil.copy(self.pickle_path, p)
os.remove(self.pickle_path)
self.history = []
def import_irradiation(self,
dest,
name,
progress,
include_analyses=False,
include_blanks=False,
include_airs=False,
include_cocktails=False,
include_list=None,
dry_run=True):
self.connect()
p, c = unique_path(paths.data_dir, 'import')
self.import_err_file = open(p, 'w')
# with dest.session_ctx(commit=not dry_run) as sess:
self.dbimport = dest.add_import(source=self.db.name,
source_host=self.db.host)
# is irrad already in dest
dbirrad = dest.get_irradiation(name)
added_to_db = False
if dbirrad is None:
# add chronology
dbchron = self._add_chronology(dest, name)
# # add production
# dbpr = self._add_production_ratios(dest, name)
# add irradiation
dbirrad = dest.add_irradiation(name, chronology=dbchron)
added_to_db = True
dest.sess.flush()
if dbirrad:
# add all the levels and positions for this irradiation
added_to_db = self._add_levels(dest,
progress,
dbirrad,
include_analyses,
include_blanks,
include_airs,
include_cocktails,
include_list,
dry_run=dry_run)
else:
self.warning(
'no irradiation found or created for {}. not adding levels'.
format(name))
self.debug('irradiation import dry_run={}'.format(dry_run))
#if not dry_run:
# dest.sess.commit()
self.import_err_file.close()
return ImportName(name=name, skipped=not added_to_db)
def _save_table(self, editor, root, ident, tag):
ft = ('pdf', 'xls', 'csv')
sft = ', '.join(ft[:-1])
sft = '{} or {}'.format(sft, ft[-1])
for ext in self._file_types:
if ext not in ft:
self.warning('Invalid file type "{}". Use "{}"'.format(ext, sft))
p, _ = unique_path(root, '{}_{}_table'.format(tag, ident), extension='.{}'.format(ext))
editor.save_file(p, title='Ar/Ar Step heat data')
def compress(self, base='archive'):
up, _cnt = unique_path(os.path.dirname(self.root), base, extension='zip')
name = os.path.basename(up)
with ZipFile(up, 'w', compression=ZIP_DEFLATED) as af:
for p in os.listdir(self.root):
if p.startswith('.'):
continue
if p == name:
continue
af.write(os.path.join(self.root, p), p)
return name
def _make(self, ep):
opt = ep.doc(0)
db = self.db
with db.session_ctx():
ids = opt['identifiers']
progress = self.open_progress(n=len(ids), close_at_end=False)
editor = InverseIsochronEditor(processor=self)
editor.plotter_options_manager.set_plotter_options('Default')
p, _ = unique_path(
os.path.join(paths.dissertation, 'data', 'minnabluff'),
'compare_iso_spec')
wfile = open(p, 'w')
for i in ids:
hist = db.get_interpreted_age_histories((i, ))[-1]
li = db.get_labnumber(i)
ans = self._get_analyses(li)
if ans:
progress.change_message(
'Calculating isochron for {}'.format(i))
unks = self.make_analyses(ans,
use_progress=False,
use_cache=False)
age, reg, _ = calculate_isochron(unks)
# print self._calculate_intercept(reg)
iaage = hist.interpreted_age.age
iaerr = hist.interpreted_age.age_err
ii, ee = self._calculate_intercept(reg)
ee2 = 2 * ee * (reg.mswd**0.5 if reg.mswd > 1 else 1)
comp = 'EQ'
if ii - ee2 > 295.5:
comp = 'GT'
elif ii + ee2 < 295.5:
comp = 'LT'
t0 = 'Identifier: {}'.format(li.identifier)
t00 = 'Sample: {}'.format(li.sample.name)
t1 = 'InterpretedAge: {}+/-{}'.format(iaage, iaerr)
t2 = 'IsochronAge: {}'.format(age)
t3 = 'Dev: {} ({:0.2f}%)'.format(
age - iaage, (age - iaage) / iaage * 100)
t4 = 'TrappedComponent: {:0.2f}+/-{:0.3f}'.format(ii, ee)
t5 = 'TrappedComparison: {}'.format(comp)
t = '\n'.join((t0, t00, t1, t2, t3, t4, t5))
# print t
wfile.write(t + '\n---\n')
# editor.set_items(unks)
# editor.rebuild()
# print 'exception', editor.get_trapped_component()
wfile.close()
progress.close()
def save_summary_table(self, root, auto_view=False):
name = '{}_summary'.format(self.name)
w = SummaryPDFTableWriter()
items = self.interpreted_ages
title = self.get_title()
opt = self.pdf_table_options
p, _ = unique_path(root, name, extension='.pdf')
w.options = opt
w.build(p, items, title)
if auto_view:
view_file(p)
def _start_recording(
self,
path=None,
basename='vm_recording',
use_dialog=False,
user='******',
):
if path is None:
if use_dialog:
path = self.save_file_dialog()
else:
vd = self.video_archiver.root
self.debug('video archiver root {}'.format(vd))
if vd is None:
vd = paths.video_dir
path, _ = unique_path(vd, basename, extension='avi')
self.info('start video recording {}'.format(path))
d = os.path.dirname(path)
if not os.path.isdir(d):
self.warning('invalid directory {}'.format(d))
self.warning('using default directory')
path, _ = unique_path(paths.video_dir, basename, extension='avi')
self.info('saving recording to path {}'.format(path))
# if self.use_db:
# db = self.get_video_database()
# db.connect()
#
# v = db.add_video_record(rid=basename)
# db.add_path(v, path)
# self.info('saving {} to database'.format(basename))
# db.commit()
renderer = None
if self.render_with_markup:
renderer = self._render_snapshot
self.video.start_recording(path, renderer)
def compress(self, base='archive'):
up, _cnt = unique_path(os.path.dirname(self.root),
base,
extension='zip')
name = os.path.basename(up)
with ZipFile(up, 'w', compression=ZIP_DEFLATED) as af:
for p in os.listdir(self.root):
if p.startswith('.'):
continue
if p == name:
continue
af.write(os.path.join(self.root, p), p)
return name
def import_irradiation(self, dest, name,
progress,
include_analyses=False,
include_blanks=False,
include_airs=False,
include_cocktails=False,
include_list=None,
dry_run=True):
self.connect()
p, c = unique_path(paths.data_dir, 'import')
self.import_err_file = open(p, 'w')
# with dest.session_ctx(commit=not dry_run) as sess:
self.dbimport = dest.add_import(
source=self.db.name,
source_host=self.db.host)
# is irrad already in dest
dbirrad = dest.get_irradiation(name)
added_to_db = False
if dbirrad is None:
# add chronology
dbchron = self._add_chronology(dest, name)
# # add production
# dbpr = self._add_production_ratios(dest, name)
# add irradiation
dbirrad = dest.add_irradiation(name, chronology=dbchron)
added_to_db = True
dest.sess.flush()
if dbirrad:
# add all the levels and positions for this irradiation
added_to_db = self._add_levels(dest, progress, dbirrad,
include_analyses,
include_blanks,
include_airs,
include_cocktails,
include_list,
dry_run=dry_run)
else:
self.warning('no irradiation found or created for {}. not adding levels'.format(name))
self.debug('irradiation import dry_run={}'.format(dry_run))
#if not dry_run:
# dest.sess.commit()
self.import_err_file.close()
return ImportName(name=name, skipped=not added_to_db)
def _make(self, ep):
opt = ep.doc(0)
db = self.db
with db.session_ctx():
ids = opt['identifiers']
progress = self.open_progress(n=len(ids), close_at_end=False)
editor = InverseIsochronEditor(processor=self)
editor.plotter_options_manager.set_plotter_options('Default')
p, _ = unique_path(os.path.join(paths.dissertation, 'data', 'minnabluff'),
'compare_iso_spec')
fp = open(p, 'w')
for i in ids:
hist = db.get_interpreted_age_histories((i,))[-1]
li = db.get_labnumber(i)
ans = self._get_analyses(li)
if ans:
progress.change_message('Calculating isochron for {}'.format(i))
unks = self.make_analyses(ans,
use_progress=False,
use_cache=False)
age, reg, _ = calculate_isochron(unks)
# print self._calculate_intercept(reg)
iaage = hist.interpreted_age.age
iaerr = hist.interpreted_age.age_err
ii, ee = self._calculate_intercept(reg)
ee2 = 2 * ee * (reg.mswd ** 0.5 if reg.mswd > 1 else 1)
comp = 'EQ'
if ii - ee2 > 295.5:
comp = 'GT'
elif ii + ee2 < 295.5:
comp = 'LT'
t0 = 'Identifier: {}'.format(li.identifier)
t00 = 'Sample: {}'.format(li.sample.name)
t1 = 'InterpretedAge: {}+/-{}'.format(iaage, iaerr)
t2 = 'IsochronAge: {}'.format(age)
t3 = 'Dev: {} ({:0.2f}%)'.format(age - iaage, (age - iaage) / iaage * 100)
t4 = 'TrappedComponent: {:0.2f}+/-{:0.3f}'.format(ii, ee)
t5 = 'TrappedComparison: {}'.format(comp)
t = '\n'.join((t0, t00, t1, t2, t3, t4, t5))
# print t
fp.write(t + '\n---\n')
# editor.set_items(unks)
# editor.rebuild()
# print editor.get_trapped_component()
fp.close()
progress.close()
def write(self, db, ias):
data = self._assemble_data(db, ias)
root = os.path.join(paths.dissertation, 'data', 'minnabluff', 'interpreted_ages')
p, _ = unique_path(root, 'tas.csv')
with open(p, 'w') as fp:
writer = csv.writer(fp)
header = ['sample', 'sio2', 'total_alk', 'age']
writer.writerow(header)
for b, rs in groupby(data, key=lambda x: int(x[-1])):
writer.writerows(rs)
writer.writerow([])
def write(self, db, ias):
data = self._assemble_data(db, ias)
root = os.path.join(paths.dissertation, 'data', 'minnabluff',
'interpreted_ages')
p, _ = unique_path(root, 'tas.csv')
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
header = ['sample', 'sio2', 'total_alk', 'age']
writer.writerow(header)
for b, rs in groupby(data, key=lambda x: int(x[-1])):
writer.writerows(rs)
writer.writerow([])
def _start_recording(self, path=None, basename='vm_recording',
use_dialog=False, user='******', ):
if path is None:
if use_dialog:
path = self.save_file_dialog()
else:
vd = self.video_archiver.root
self.debug('video archiver root {}'.format(vd))
if vd is None:
vd = paths.video_dir
path, _ = unique_path(vd, basename, extension='avi')
self.info('start video recording {}'.format(path))
d = os.path.dirname(path)
if not os.path.isdir(d):
self.warning('invalid directory {}'.format(d))
self.warning('using default directory')
path, _ = unique_path(paths.video_dir, basename,
extension='avi')
self.info('saving recording to path {}'.format(path))
# if self.use_db:
# db = self.get_video_database()
# db.connect()
#
# v = db.add_video_record(rid=basename)
# db.add_path(v, path)
# self.info('saving {} to database'.format(basename))
# db.commit()
renderer = None
if self.render_with_markup:
renderer = self._render_snapshot
self.video.start_recording(path, renderer)
def _save_pdf_data_table(self, root, ias, step_heat_title, fusion_title, spectrometer, auto_view=False):
shgroups, fgroups = self._assemble_groups(ias)
ext = '.pdf'
if shgroups:
w = StepHeatPDFTableWriter()
# name = '{}_{}_step_heatdata'.format(self.name, spectrometer)
name = '{}stepheatdata'.format(spectrometer)
p, _ = unique_path(root, name, extension=ext)
iagroups, shgroups = zip(*shgroups)
w.build(p, shgroups, title=step_heat_title)
if auto_view:
view_file(p)
if fgroups:
w = FusionPDFTableWriter()
# name = '{}_{}_fusion_data'.format(self.name, spectrometer)
name = '{}fusiondata'.format(spectrometer)
p, _ = unique_path(root, name, extension=ext)
iagroups, fgroups = zip(*fgroups)
w.build(p, fgroups, title=fusion_title)
if auto_view:
view_file(p)
def start_recording(self, path=None, use_dialog=False):
'''
'''
self.info('start video recording ')
if path is None:
if use_dialog:
path = self.save_file_dialog()
else:
path, _ = unique_path(paths.video_dir,
'vm_recording',
extension='avi')
self.info('saving recording to path {}'.format(path))
# self.start()
self.video.start_recording(path)
def start_recording(self, path=None, use_dialog=False):
'''
'''
self.info('start video recording ')
if path is None:
if use_dialog:
path = self.save_file_dialog()
else:
path, _ = unique_path(paths.video_dir,
'vm_recording',
extension='avi')
self.info('saving recording to path {}'.format(path))
# self.start()
self.video.start_recording(path)
def generate_results(self):
self.debug('generate results')
dvc = self.dvc
db = dvc.db
positions = sorted([pp for p in self.positions for pp in p.positions])
wb = Workbook()
sh = wb.add_sheet('Results')
for i, attr in enumerate(
('Analysis', 'Position', 'Age', 'Error', 'Weight', 'Note')):
wb.sheet(0, i, attr)
wb.nrows = 1
def func(x, prog, i, n):
dbmps = db.get_measured_positions(self.load_name, x)
dbpos = db.get_load_position(self.load_name, x)
weight, note = dbpos.weight, dbpos.note
for dbmp in dbmps:
rid = dbmp.analysis.record_id
# rid = 1
if prog:
prog.change_message('Write results for {},{}'.format(
rid, x))
# ai = dvc.make_analyses((rid,))
age, error = 0, 0
sh.write(wb.nrows, 0, rid)
sh.write(wb.nrows, 1, x)
sh.write(wb.nrows, 2, age)
sh.write(wb.nrows, 3, error)
sh.write(wb.nrows, 4, weight)
sh.write(wb.nrows, 5, note)
wb.nrows += 1
with db.session_ctx():
progress_iterator(positions, func, threshold=1)
path, _ = unique_path(paths.load_results_dir,
self.load_name,
extension='.xls')
wb.save(path)
def generate_results(self):
self.debug('generate results')
dvc = self.dvc
db = dvc.db
positions = sorted([pp for p in self.positions
for pp in p.positions])
wb = Workbook()
sh = wb.add_sheet('Results')
for i, attr in enumerate(('Analysis', 'Position', 'Age',
'Error', 'Weight', 'Note')):
wb.sheet(0, i, attr)
wb.nrows = 1
def func(x, prog, i, n):
dbmps = db.get_measured_positions(self.load_name, x)
dbpos = db.get_load_position(self.load_name, x)
weight, note = dbpos.weight, dbpos.note
for dbmp in dbmps:
rid = dbmp.analysis.record_id
# rid = 1
if prog:
prog.change_message('Write results for {},{}'.format(rid, x))
# ai = dvc.make_analyses((rid,))
age, error = 0, 0
sh.write(wb.nrows, 0, rid)
sh.write(wb.nrows, 1, x)
sh.write(wb.nrows, 2, age)
sh.write(wb.nrows, 3, error)
sh.write(wb.nrows, 4, weight)
sh.write(wb.nrows, 5, note)
wb.nrows += 1
with db.session_ctx():
progress_iterator(positions, func, threshold=1)
path, _ = unique_path(paths.load_results_dir, self.load_name, extension='.xls')
wb.save(path)
def _do_fit_blanks(self, gs, fits, atype, root, save_figure, with_table):
'''
fit this block of analyses
'''
start, end = gs[0].analysis_timestamp, gs[-1].analysis_timestamp
ds = timedelta(minutes=59)
atypes = ('blank_{}'.format(atype), )
blanks = self._get_analysis_date_range(start - ds, end + ds, atypes)
if blanks:
man = self.processor
blanks = man.make_analyses(blanks)
gs = man.make_analyses(gs)
man.load_analyses(gs, show_progress=False)
man.load_analyses(blanks, show_progress=False)
refiso = gs[0]
ae = self.editor
ae.tool.load_fits(refiso.isotope_keys, refiso.isotope_fits)
fkeys = fits.keys()
for fi in ae.tool.fits:
if fi.name in fkeys:
fi.trait_set(show=True,
fit=fits[fi.name],
trait_change_notify=False)
ae.unknowns = gs
ae.references = blanks
ae.rebuild_graph()
if save_figure:
p, _ = unique_path(root,
base=refiso.record_id,
extension='.pdf')
if with_table:
writer = BlanksPDFWrtier()
writer.build(p, ae.component, gs, blanks)
else:
ae.graph.save_pdf(p)
def _do_fit_blanks(self, gs, fits, atype, root,
save_figure, with_table):
'''
fit this block of analyses
'''
start, end = gs[0].analysis_timestamp, gs[-1].analysis_timestamp
ds = timedelta(minutes=59)
atypes = ('blank_{}'.format(atype),)
blanks = self._get_analysis_date_range(start - ds, end + ds, atypes)
if blanks:
man = self.processor
blanks = man.make_analyses(blanks)
gs = man.make_analyses(gs)
man.load_analyses(gs, show_progress=False)
man.load_analyses(blanks, show_progress=False)
refiso = gs[0]
ae = self.editor
ae.tool.load_fits(refiso.isotope_keys,
refiso.isotope_fits
)
fkeys = fits.keys()
for fi in ae.tool.fits:
if fi.name in fkeys:
fi.trait_set(show=True, fit=fits[fi.name], trait_change_notify=False)
ae.unknowns = gs
ae.references = blanks
ae.rebuild_graph()
if save_figure:
p, _ = unique_path(root, base=refiso.record_id,
extension='.pdf')
if with_table:
writer = BlanksPDFWrtier()
writer.build(p, ae.component, gs, blanks)
else:
ae.graph.save_pdf(p)
def _do_detector_intercalibration(self, gs, fit, reftype, root,
save_figure, with_table):
start, end = gs[0].analysis_timestamp, gs[-1].analysis_timestamp
ds = timedelta(hours=3)
refs = self._get_analysis_date_range(start - ds, end + ds, (reftype, ))
if refs:
man = self.processor
refs = man.make_analyses(refs)
gs = man.make_analyses(gs)
man.load_analyses(gs, show_progress=False)
man.load_analyses(refs, show_progress=False)
refiso = gs[0]
ae = self.editor
# ae.tool.load_fits(ks, fs)
ae.tool.load_fits(['Ar40/Ar36'], [fit])
ae.tool.fits[0].show = True
# fkeys = fits.keys()
# for fi in ae.tool.fits:
# if fi.name in fkeys:
# fi.trait_set(show=True, fit=fits[fi.name], trait_change_notify=False)
ae.unknowns = gs
ae.references = refs
ae.rebuild_graph()
if save_figure:
p, _ = unique_path(root,
base=refiso.record_id,
extension='.pdf')
if with_table:
writer = DetectorIntercalibrationPDFWriter()
writer.build(p, ae.component, gs, refs)
else:
ae.graph.save_pdf(p)
def _do_detector_intercalibration(self, gs, fit, reftype, root,
save_figure, with_table):
start, end = gs[0].analysis_timestamp, gs[-1].analysis_timestamp
ds = timedelta(hours=3)
refs = self._get_analysis_date_range(start - ds, end + ds, (reftype,))
if refs:
man = self.processor
refs = man.make_analyses(refs)
gs = man.make_analyses(gs)
man.load_analyses(gs, show_progress=False)
man.load_analyses(refs, show_progress=False)
refiso = gs[0]
ae = self.editor
# ae.tool.load_fits(ks, fs)
ae.tool.load_fits(['Ar40/Ar36'], [fit])
ae.tool.fits[0].show = True
# fkeys = fits.keys()
# for fi in ae.tool.fits:
# if fi.name in fkeys:
# fi.trait_set(show=True, fit=fits[fi.name], trait_change_notify=False)
ae.unknowns = gs
ae.references = refs
ae.rebuild_graph()
if save_figure:
p, _ = unique_path(root, base=refiso.record_id,
extension='.pdf')
if with_table:
writer = DetectorIntercalibrationPDFWriter()
writer.build(p, ae.component, gs, refs)
else:
ae.graph.save_pdf(p)
def _new_frame_path(self, path=None, directory='scans',
offset=0,
base_frame_name=None, verbose=True):
"""
"""
if base_frame_name is None:
base_frame_name = 'scan'
'''
if directory is an absolute path paths.data_dir is not joined
'''
base = os.path.join(paths.data_dir, directory)
if not os.path.isdir(base):
os.mkdir(base)
if path is None:
path, _cnt = unique_path(base, base_frame_name,
extension=self._extension)
if verbose:
self.info('New frame {}'.format(path))
return path
def _start_recording(self, path, basename):
self.info('start video recording {}'.format(path))
d = os.path.dirname(path)
if not os.path.isdir(d):
self.warning('invalid directory {}'.format(d))
self.warning('using default directory')
path, _ = unique_path(paths.video_dir, basename, extension='avi')
self.info('saving recording to path {}'.format(path))
# if self.use_db:
# db = self.get_video_database()
# db.connect()
#
# v = db.add_video_record(rid=basename)
# db.add_path(v, path)
# self.info('saving {} to database'.format(basename))
# db.commit()
video = self.video
crop_to_hole = True
dim = self.stage_map.g_dimension
cropdim = dim * 8 * self.pxpermm
color = self.canvas.crosshairs_color.getRgb()[:3]
r = int(self.canvas.get_crosshairs_radius() * self.pxpermm)
# offx, offy = self.canvas.get_screen_offset()
def renderer(p):
# cw, ch = self.get_frame_size()
frame = video.get_cached_frame()
if frame is not None:
if not len(frame.shape):
return
frame = copy(frame)
# ch, cw, _ = frame.shape
# ch, cw = int(ch), int(cw)
if crop_to_hole:
frame = video.crop(frame, 0, 0, cropdim, cropdim)
if self.render_with_markup:
# draw crosshairs
if len(frame.shape) == 2:
frame = gray2rgb(frame)
ch, cw, _ = frame.shape
ch, cw = int(ch), int(cw)
y = ch // 2
x = cw // 2
cp = circle_perimeter(y, x, r, shape=(ch, cw))
frame[cp] = color
frame[line(y, 0, y, x - r)] = color # left
frame[line(y, x + r, y, int(cw) - 1)] = color # right
frame[line(0, x, y - r, x)] = color # bottom
frame[line(y + r, x, int(ch) - 1, x)] = color # top
if frame is not None:
pil_save(frame, p)
self.video.start_recording(path, renderer)
import gc
import sys
import cPickle
from itertools import groupby
import psutil
from pychron.core.helpers.filetools import unique_path
# import objgraph
USE_MEM_LOG = False
if USE_MEM_LOG:
root = os.path.join(os.path.expanduser('~'), 'Desktop', 'memtest')
if not os.path.isdir(root):
os.mkdir(root)
p, _ = unique_path(root, 'mem')
def write_mem(msg, m, verbose):
with open(os.path.join(root, p), 'a') as wfile:
msg = '{:<50s}:{}\n'.format(msg, m)
wfile.write(msg)
if verbose:
print msg.strip()
PID = None
def mem_break():
write_mem('#' + '=' * 49, '')
def _execute_calibration(self):
name = os.path.join(paths.scripts_dir, '{}_calibration_scan.yaml'.format(self.name))
import csv
d = os.path.join(paths.data_dir, 'diode_scans')
p, _cnt = unique_path(d, 'calibration', extension='csv')
# st = None
#
# py = self.laser_manager.pyrometer
# tc = self.laser_manager.get_device('temperature_monitor')
g = StreamStackedGraph()
g.clear()
g.new_plot(scan_delay=1)
g.new_series(x=[], y=[])
g.new_plot(scan_delay=1)
g.new_series(x=[], y=[], plotid=1)
open_view(g)
record = False
if record:
self.laser_manager.stage_manager.start_recording()
time.sleep(1)
# def gfunc(t, v1, v2):
# g.add_datum((t, v1))
# g.add_datum((t, v2), plotid=1)
def gfunc(v1, v2):
g.record(v1)
g.record(v2, plotid=1)
yd = yaml.load(open(name).read())
start = yd['start']
end = yd['end']
step = yd['step']
mean_tol = yd['mean_tol']
std = yd['std']
n = (end - start) / step + 1
# nn = 30
#
# py = self.laser_manager.pyrometer
# tc = self.laser_manager.get_device('temperature_monitor')
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
st = time.time()
for ti in linspace(start, end, n):
if self._cancel:
break
args = self._equilibrate_temp(ti, gfunc, st, mean_tol, std)
if args:
self.info('{} equilibrated'.format(ti))
py_t, tc_t = args
writer.writerow((ti, py_t, tc_t))
else:
break
self.laser_manager.set_laser_temperature(0)
if record:
self.laser_manager.stage_manager.stop_recording()
self._executing = False
def _execute_scan(self):
name = os.path.join(paths.scripts_dir, '{}_scan.yaml'.format(self.name))
import csv
d = os.path.join(paths.data_dir, 'diode_scans')
p, _cnt = unique_path(d, 'scan', extension='csv')
st = None
py = self.laser_manager.pyrometer
tc = self.laser_manager.get_device('temperature_monitor')
yd = yaml.load(open(name).read())
power = yd['power']
duration = yd['duration']
power_on = yd['power_on']
power_off = yd['power_off']
period = yd['period']
if 'temp' in yd:
temp = yd['temp']
else:
temp = None
g = StreamStackedGraph()
g.new_plot(scan_delay=1, )
g.new_series(x=[], y=[])
g.new_plot(scan_delay=1, )
g.new_series(x=[], y=[], plotid=1)
open_view(g)
self.laser_manager.stage_manager.start_recording()
time.sleep(1)
def gfunc(v1, v2):
g.record(v1)
g.record(v2, plotid=1)
pi = 0
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
t = 0
ti = 0
while ti <= duration:
if self._cancel:
break
# print ti, power_off, pi, ti >= power_off, (ti >= power_off and pi)
if ti == power_on:
# turn on set laser to power
if temp:
self.laser_manager.set_laser_temperature(temp)
pi = temp
else:
pi = power
self.laser_manager.set_laser_power(power)
elif ti >= power_off and pi:
print 'setting power off'
if temp:
self.laser_manager.set_laser_temperature(0)
else:
self.laser_manager.set_laser_power(0)
pi = 0
if st is None:
st = time.time()
t = time.time() - st
py_t = py.read_temperature(verbose=False)
tc_t = tc.read_temperature(verbose=False)
gfunc(py_t, tc_t)
writer.writerow((ti, pi, t, py_t, tc_t))
ti += 1
time.sleep(period)
if temp:
self.laser_manager.set_laser_temperature(0)
else:
self.laser_manager.set_laser_power(0)
self.laser_manager.stage_manager.stop_recording()
self._executing = False
def __init__(self, *args, **kw):
super(StageVisualizer, self).__init__(*args, **kw)
# p = os.path.join(data_dir, 'stage_visualizer')
self.path, _ = unique_path(paths.stage_visualizer_dir, 'vis',
extension='')
def make_strat_canvas_file(self):
identifiers = ['57735',
'57742',
'57734',
'57737',
'57736',
'57744',
'57743',
'57725',
'58627']
identifiers = ['57731',
'58612',
'58620']
identifiers = ['58616',
'57719',
'58767']
db = self.db
root = os.path.join(paths.dissertation,
'data', 'minnabluff', 'strat_sequences')
seqname = 'seq4'
p, _ = unique_path(root, seqname, extension='.yaml')
with db.session_ctx():
items = []
for i in identifiers:
strat = {}
ln = db.get_labnumber(i)
sample = ln.sample
ia = ln.selected_interpreted_age.interpreted_age
if ia.age_kind != 'Integrated':
strat['elevation'] = sample.elevation
mat = sample.material.name
strat['label'] = '{}({}) {}+/-{} ({})'.format(sample.name,
mat,
ia.age, ia.age_err,
ia.age_kind)
strat['age'] = ia.age
strat['age_err'] = ia.age_err
strat['mswd'] = ia.mswd
items.append(strat)
syd = sorted(items, key=lambda x: x['elevation'])
for i, yi in enumerate(syd[:-1]):
# print i, yi['elevation'], yi['age']
# ee2=2*yi['age_err']*yi['mswd']**0.5
if not strat_ok(yi, syd[i + 1]):
yi['color'] = 'red'
yd = dict(options={},
items=items)
import yaml
with open(p, 'w') as wfile:
yaml.dump(yd, wfile, default_flow_style=False)
from pychron.canvas.canvas2D.strat_canvas import StratCanvas
s = StratCanvas()
s.load_scene(yd)
p, _ = unique_path(root, seqname, extension='.pdf')
from chaco.pdf_graphics_context import PdfPlotGraphicsContext
g = PdfPlotGraphicsContext(
filename=p)
s.do_layout(size=(500, 700),
force=True)
g.render_component(s)
g.save()
def path(self):
p, _ = unique_path(paths.report_dir, 'report', extension='.pdf')
return p
def make_strat_canvas_file(self):
identifiers = [
'57735', '57742', '57734', '57737', '57736', '57744', '57743',
'57725', '58627'
]
identifiers = ['57731', '58612', '58620']
identifiers = ['58616', '57719', '58767']
db = self.db
root = os.path.join(paths.dissertation, 'data', 'minnabluff',
'strat_sequences')
seqname = 'seq4'
p, _ = unique_path(root, seqname, extension='.yaml')
with db.session_ctx():
items = []
for i in identifiers:
strat = {}
ln = db.get_labnumber(i)
sample = ln.sample
ia = ln.selected_interpreted_age.interpreted_age
if ia.age_kind != 'Integrated':
strat['elevation'] = sample.elevation
mat = sample.material.name
strat['label'] = '{}({}) {}+/-{} ({})'.format(
sample.name, mat, ia.age, ia.age_err, ia.age_kind)
strat['age'] = ia.age
strat['age_err'] = ia.age_err
strat['mswd'] = ia.mswd
items.append(strat)
syd = sorted(items, key=lambda x: x['elevation'])
for i, yi in enumerate(syd[:-1]):
# print i, yi['elevation'], yi['age']
# ee2=2*yi['age_err']*yi['mswd']**0.5
if not strat_ok(yi, syd[i + 1]):
yi['color'] = 'red'
yd = dict(options={}, items=items)
import yaml
with open(p, 'w') as wfile:
yaml.dump(yd, wfile, default_flow_style=False)
from pychron.canvas.canvas2D.strat_canvas import StratCanvas
s = StratCanvas()
s.load_scene(yd)
p, _ = unique_path(root, seqname, extension='.pdf')
from chaco.pdf_graphics_context import PdfPlotGraphicsContext
g = PdfPlotGraphicsContext(filename=p)
s.do_layout(size=(500, 700), force=True)
g.render_component(s)
g.save()
def _execute_scan(self):
name = os.path.join(paths.scripts_dir, '{}_scan.yaml'.format(self.name))
import csv
d = os.path.join(paths.data_dir, 'diode_scans')
p, _cnt = unique_path(d, 'scan', extension='csv')
st = None
py = self.laser_manager.pyrometer
tc = self.laser_manager.get_device('temperature_monitor')
yd = yaml.load(open(name).read())
power = yd['power']
duration = yd['duration']
power_on = yd['power_on']
power_off = yd['power_off']
period = yd['period']
if yd.has_key('temp'):
temp = yd['temp']
else:
temp = None
g = StreamStackedGraph()
g.new_plot(scan_delay=1,)
g.new_series(x=[], y=[])
g.new_plot(scan_delay=1,)
g.new_series(x=[], y=[], plotid=1)
self.laser_manager.open_view(g)
self.laser_manager.stage_manager.start_recording()
time.sleep(1)
def gfunc(v1, v2):
g.record(v1)
g.record(v2, plotid=1)
pi = 0
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
t = 0
ti = 0
while ti <= duration:
if self._cancel:
break
# print ti, power_off, pi, ti >= power_off, (ti >= power_off and pi)
if ti == power_on:
# turn on set laser to power
if temp:
self.laser_manager.set_laser_temperature(temp)
pi = temp
else:
pi = power
self.laser_manager.set_laser_power(power)
elif ti >= power_off and pi:
print 'setting power off'
if temp:
self.laser_manager.set_laser_temperature(0)
else:
self.laser_manager.set_laser_power(0)
pi = 0
if st is None:
st = time.time()
t = time.time() - st
py_t = py.read_temperature(verbose=False)
tc_t = tc.read_temperature(verbose=False)
gfunc(py_t, tc_t)
writer.writerow((ti, pi, t, py_t, tc_t))
ti += 1
time.sleep(period)
if temp:
self.laser_manager.set_laser_temperature(0)
else:
self.laser_manager.set_laser_power(0)
self.laser_manager.stage_manager.stop_recording()
self._executing = False
def _execute_calibration(self):
name = os.path.join(paths.scripts_dir, '{}_calibration_scan.yaml'.format(self.name))
import csv
d = os.path.join(paths.data_dir, 'diode_scans')
p, _cnt = unique_path(d, 'calibration', extension='csv')
# st = None
#
# py = self.laser_manager.pyrometer
# tc = self.laser_manager.get_device('temperature_monitor')
g = StreamStackedGraph()
g.clear()
g.new_plot(scan_delay=1)
g.new_series(x=[], y=[])
g.new_plot(scan_delay=1)
g.new_series(x=[], y=[], plotid=1)
self.laser_manager.open_view(g)
record = False
if record:
self.laser_manager.stage_manager.start_recording()
time.sleep(1)
# def gfunc(t, v1, v2):
# g.add_datum((t, v1))
# g.add_datum((t, v2), plotid=1)
def gfunc(v1, v2):
g.record(v1)
g.record(v2, plotid=1)
yd = yaml.load(open(name).read())
start = yd['start']
end = yd['end']
step = yd['step']
mean_tol = yd['mean_tol']
std = yd['std']
n = (end - start) / step + 1
# nn = 30
#
# py = self.laser_manager.pyrometer
# tc = self.laser_manager.get_device('temperature_monitor')
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
st = time.time()
for ti in linspace(start, end, n):
if self._cancel:
break
args = self._equilibrate_temp(ti, gfunc, st, mean_tol, std)
if args:
self.info('{} equilibrated'.format(ti))
py_t, tc_t = args
writer.writerow((ti, py_t, tc_t))
else:
break
self.laser_manager.set_laser_temperature(0)
if record:
self.laser_manager.stage_manager.stop_recording()
self._executing = False
def _save(self, editor, root, pathname, name, project, lns):
p, _ = unique_path(root, pathname, extension='.pdf')
editor.save_file(p)
if self._save_db_figure:
editor.save_figure('EasyFigure {}'.format(name),
project, lns)
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ===============================================================================
# ============= enthought library imports =======================
from __future__ import absolute_import
import os
from pychron.core.helpers.filetools import unique_path
# ============= standard library imports ========================
# ============= local library imports ==========================
root = os.path.join(os.path.expanduser('~'), 'Desktop', 'filelog')
if not os.path.isdir(root):
os.mkdir(root)
p, _ = unique_path(root, 'mem')
def file_log(msg):
with open(os.path.join(root, p), 'a') as wfile:
wfile.write('{}\n'.format(msg))
# ============= EOF =============================================
def __init__(self, *args, **kw):
super(StageVisualizer, self).__init__(*args, **kw)
# p = os.path.join(data_dir, 'stage_visualizer')
self.path, _ = unique_path(paths.stage_visualizer_dir,
'vis',
extension='')
