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change ProgressBar from Toplevel to the gui / remove ScrollbarFrame /…
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… change update_baseline() for apply_baseline_settings() entirely revisited / revisit auto_eval() / add eval_baseline()
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@patquem
patquem committed Aug 12, 2024
1 parent 2bafe0a commit 0b46cee
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Showing 7 changed files with 237 additions and 284 deletions.
3 changes: 2 additions & 1 deletion examples/ex_nogui_auto_decomposition.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,8 @@ def auto_decomposition(verbosity=True, show_plots=False):
spectrum = Spectrum()
spectrum.load_profile(fname)
spectrum.apply_range(range_min=55)
spectrum.auto_baseline()
spectrum.baseline.mode = 'Semi-Auto'
spectrum.eval_baseline()
spectrum.subtract_baseline()
spectrum.auto_peaks(model_name="Lorentzian")
# spectrum.fit() # fit is already performed during auto_peaks processing
Expand Down
211 changes: 135 additions & 76 deletions fitspy/app/callbacks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
"""
import os
import warnings
from types import LambdaType
from tkinter import END
from tkinter.messagebox import askyesno, showerror
from tkinter import filedialog as fd
Expand Down Expand Up @@ -234,7 +235,7 @@ def apply_model(self, model_dict=None, fnames=None, selection=False):
args = (model_dict, fnames, ncpus)
thread = Thread(target=self.spectra.apply_model, args=args)
thread.start()
self.progressbar.show(self.spectra, nfiles)
self.progressbar.update(self.spectra, nfiles, ncpus)
thread.join()
self.colorize_from_fit_status(fnames)
self.reassign_current_spectrum(self.current_spectrum.fname)
Expand Down Expand Up @@ -376,7 +377,7 @@ def plot(self):
x, y = spectrum.x, None
if baseline.attached or baseline.mode == 'Semi-Auto':
y = spectrum.y
baseline.plot(self.ax, x=x, y=y)
baseline.plot(self.ax, x, y, attached=baseline.attached)

self.ax.legend()
self.tmp = None
Expand Down Expand Up @@ -498,11 +499,11 @@ def on_press_baseline_peaks(self, event):
self.fr_fit.disable()
self.selected_frame = None

def baseline_subtract_message(self):
def baseline_is_subtracted_message(self):
""" Show an error message associated with the baseline """
msg = "A baseline has already been subtracted to the spectrum."
msg += "\nFurther action requires to reinitialize the spectrum."
msg += "\n\nContinue ?"
msg = "A baseline has already been subtracted to the spectrum.\n"
msg += "Further action requires to reinitialize the spectrum.\n\n"
msg += 'Continue ?'
return askyesno(message=msg)

def add_baseline_point(self, x, y):
Expand All @@ -511,7 +512,7 @@ def add_baseline_point(self, x, y):
return

if self.current_spectrum.baseline.is_subtracted:
if not self.baseline_subtract_message():
if not self.baseline_is_subtracted_message():
return
self.current_spectrum.load_profile(self.current_spectrum.fname)
self.current_spectrum.apply_range()
Expand All @@ -534,66 +535,99 @@ def del_baseline_point(self, x, _):
self.current_spectrum.baseline.points[1].pop(ind_min)
self.plot()

def update_baseline(self, key):
""" Update a baseline attribute"""
def apply_baseline_settings(self, fnames=None):
""" Apply baseline settings """
if self.current_spectrum.baseline.is_subtracted:
if not self.baseline_subtract_message():
if not self.baseline_is_subtracted_message():
self.set_baseline_settings()
return

val = eval(f"self.baseline_{key}").get()
setattr(self.current_spectrum.baseline, key, val)
if fnames is None:
fnames = self.fileselector.filenames
fnames = [fnames[i] for i in self.fileselector.lbox.curselection()]

has_previous_results = False
for fname in fnames:
spectrum, _ = self.spectra.get_objects(fname)
if (spectrum.baseline.is_subtracted
or not isinstance(spectrum.result_fit, LambdaType)):
has_previous_results = True
break

msg = 'Changing baseline settings will remove the previous results.\n'
msg += 'Continue ?'
if has_previous_results and not askyesno('', msg):
self.set_range()
return

keys = ['mode', 'coef', 'order_max', 'sigma', 'attached']
for key in keys:
val = eval(f"self.baseline_{key}").get()
setattr(self.current_spectrum.baseline, key, val)

# keep main values before reinitialization
range_min = self.current_spectrum.range_min
range_max = self.current_spectrum.range_max
vars_baseline = vars(self.current_spectrum.baseline).copy()

self.reinit(fnames)

for fname in fnames:
spectrum, _ = self.spectra.get_objects(fname)
spectrum.range_min = range_min
spectrum.range_max = range_max
for key, value in vars_baseline.items():
setattr(spectrum.baseline, key, value)

spectrum = self.current_spectrum
spectrum.apply_range()
spectrum.baseline.eval(spectrum.x, spectrum.y,
attached=spectrum.baseline.attached)

self.current_spectrum.preprocess()
self.set_range()
self.set_baseline_settings()
self.paramsview.delete()
self.statsview.delete()
self.plot()

def set_baseline(self):
""" Set baseline properties from the baseline to the appli """
spectrum = self.current_spectrum # pylint:disable=unused-variable
attrs = ['mode', 'coef', 'order_max', 'sigma', 'attached']
for attr in attrs:
eval(f'self.baseline_{attr}.set(spectrum.baseline.{attr})')
def apply_baseline_settings_to_all(self):
""" Apply baseline settings to all the spectra """
self.apply_baseline_settings(fnames=self.spectra.fnames)

def set_baseline_settings(self):
""" Set baseline settings from the baseline to the appli """
for x in ['mode', 'coef', 'order_max', 'sigma', 'attached']:
eval(f'self.baseline_{x}.set(self.current_spectrum.baseline.{x})')

def load_baseline(self, fname=None):
""" Load a baseline from a row-column .txt file """
if self.current_spectrum.baseline.is_subtracted:
if not self.baseline_subtract_message():
if not self.baseline_is_subtracted_message():
return

if fname is None:
fname = fd.askopenfilename(title='Select file')

if os.path.isfile(fname):
self.current_spectrum.baseline.load_baseline(fname)
self.current_spectrum.preprocess()
self.plot()

def subtract_baseline(self, fnames=None):
""" Subtract the current baseline """
baseline = self.current_spectrum.baseline
if baseline.mode is None:
return
if baseline.mode != 'Semi-Auto' and len(baseline.points[0]) == 0:
return
""" Subtract baseline to the current spectrum """

self.apply_baseline_settings(fnames=fnames)

if fnames is None:
fnames = self.fileselector.filenames
fnames = [fnames[i] for i in self.fileselector.lbox.curselection()]
fnames = [fnames[i] for i in
self.fileselector.lbox.curselection()]

for fname in fnames:
spectrum, _ = self.spectra.get_objects(fname)
for key, value in vars(baseline).items():
setattr(spectrum.baseline, key, value)
spectrum.preprocess()
spectrum.subtract_baseline()

self.paramsview.delete()
self.statsview.delete()
self.ax.clear()
self.plot()

def delete_baseline(self):
""" Delete the current baseline """
self.current_spectrum.baseline.points = [[], []]
self.current_spectrum.baseline.mode = None
self.plot()

def load_user_model(self, model):
Expand Down Expand Up @@ -701,7 +735,7 @@ def fit(self, fnames=None, selection=True):
fit_params['xtol'] = params['xtol'].get()

model_dict = self.current_spectrum.save()
model_dict.pop('baseline') # to not affect previous works on baseline
# model_dict.pop('baseline') # to not affect previous works on baseline
self.apply_model(model_dict=model_dict, fnames=fnames,
selection=selection)

Expand All @@ -714,37 +748,59 @@ def set_range(self):
self.range_min.set(self.current_spectrum.range_min or "")
self.range_max.set(self.current_spectrum.range_max or "")

def apply_range(self, delete_tabview=True):
""" Set range to the current spectrum """
if is_convertible_to_float(self.range_min.get()):
self.current_spectrum.range_min = float(self.range_min.get())
def apply_range(self, fnames=None):
""" Set an apply range to the spectrum/spectra """

if is_convertible_to_float(self.range_max.get()):
self.current_spectrum.range_max = float(self.range_max.get())
def get_from_name(self, name): # pylint:disable=unused-variable
try:
return float(eval(f"self.{name}.get()"))
except:
return None

self.remove(delete_tabview=delete_tabview)
self.current_spectrum.preprocess()
self.plot()
range_min = get_from_name(self, 'range_min')
range_max = get_from_name(self, 'range_max')

def apply_range_to_all(self):
""" Apply the appli range to all the spectra """
if range_min is not None and range_max is not None:
if range_min >= range_max:
showerror("incorrect values for X-range (min >= max)")
self.set_range()
return

if is_convertible_to_float(self.range_min.get()):
range_min = float(self.range_min.get())
for spectrum in self.spectra.all:
spectrum.range_min = range_min
if fnames is None:
fnames = self.fileselector.filenames
fnames = [fnames[i] for i in self.fileselector.lbox.curselection()]

if is_convertible_to_float(self.range_max.get()):
range_max = float(self.range_max.get())
for spectrum in self.spectra.all:
spectrum.range_max = range_max
has_previous_results = False
for fname in fnames:
spectrum, _ = self.spectra.get_objects(fname)
if (spectrum.baseline.y_eval is not None
or not isinstance(spectrum.result_fit, LambdaType)):
has_previous_results = True
break

msg = 'Changing X-range will remove the previous results.\n'
msg += 'Continue ?'
if has_previous_results and not askyesno('', msg):
self.set_range()
return

self.current_spectrum.preprocess()
self.paramsview.delete()
self.statsview.delete()
self.reinit(fnames)

for fname in fnames:
spectrum, _ = self.spectra.get_objects(fname)
spectrum.range_min = range_min
spectrum.range_max = range_max
spectrum.apply_range()

self.set_range()
# self.remove(delete_tabview=delete_tabview)
self.ax.clear()
self.plot()

def apply_range_to_all(self):
""" Set and apply range to all the spectra """
self.apply_range(fnames=self.spectra.fnames)

def update_normalize_status(self):
""" Update 'normalize_status' to all the spectra """
for spectrum in self.spectra.all:
Expand All @@ -754,7 +810,6 @@ def update_normalize_status(self):
self.current_spectrum.preprocess()
self.paramsview.delete()
self.statsview.delete()
self.ax.clear()
self.plot()

def update_normalize_range(self):
Expand Down Expand Up @@ -791,14 +846,14 @@ def reinit(self, fnames=None):
spectrum.norm_mode = None
spectrum.result_fit = lambda: None
spectrum.remove_models()
spectrum.baseline.mode = None
spectrum.baseline.points = [[], []]
spectrum.baseline.is_subtracted = False

self.colorize_from_fit_status(fnames=fnames)
self.paramsview.delete()
self.statsview.delete()
self.set_range()
self.ax.clear()
self.plot()

def reinit_all(self):
Expand All @@ -810,6 +865,8 @@ def reassign_current_spectrum(self, fname):
ind = self.fileselector.filenames.index(fname)
self.fileselector.select_item(ind)
self.current_spectrum, _ = self.spectra.get_objects(fname)
self.set_range()
self.set_baseline_settings()
self.ax.clear()
self.plot()

Expand All @@ -827,23 +884,26 @@ def remove(self, delete_tabview=True):
def auto_eval(self, model_name=None, fnames=None):
""" Fit spectrum after evaluating baseline and peaks automatically """
if fnames is None:
fnames = [self.current_spectrum.fname]
self.current_spectrum.baseline.mode = 'Semi-Auto'
self.subtract_baseline(fnames=fnames)
self.auto_peaks(model_name=model_name)
self.fit(fnames=fnames)
fnames = self.fileselector.filenames
fnames = [fnames[i] for i in self.fileselector.lbox.curselection()]

def auto_eval_all(self, model_name=None):
""" Apply automatic fitting on all spectra """
self.show_plot = False
current_fname = self.current_spectrum.fname
for spectrum in self.spectra.all:
self.current_spectrum = spectrum
self.auto_eval(model_name=model_name)
self.colorize_from_fit_status(self.spectra.fnames)
for fname in fnames:
self.current_spectrum, _ = self.spectra.get_objects(fname)
self.current_spectrum.apply_range()
self.current_spectrum.baseline.mode = 'Semi-Auto'
self.current_spectrum.eval_baseline()
self.current_spectrum.subtract_baseline()
self.auto_peaks(model_name=model_name)
self.colorize_from_fit_status([fname])
self.show_plot = True
self.reassign_current_spectrum(current_fname)

def auto_eval_all(self, model_name=None):
""" Apply automatic fitting on all spectra """
self.auto_eval(model_name=model_name, fnames=self.spectra.fnames)

def delete_all(self, _):
""" Delete all spectra """
self.ax.clear()
Expand Down Expand Up @@ -964,11 +1024,10 @@ def update(self, fname=None):
self.update_markers(fname)

self.current_spectrum, _ = self.spectra.get_objects(fname)
self.current_spectrum.preprocess()

self.show_plot = False
self.set_range()
self.set_baseline()
self.set_baseline_settings()
self.paramsview.spectrum = self.current_spectrum
self.paramsview.bkg_name = self.bkg_name
self.paramsview.plot = self.plot
Expand Down
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