def update_plot(self):
"""
Replots the entire spectrum canvas
with a new maximal power.
"""
# remove the old plot
self.wCanvas.fig.clf()
# retrieve new pmax value
text = self.pmax_edit.text()
text = text.replace(",", ".")
pmax = float(text) # pmax_edit has a positive float validator
if self.DEBUG:
print(f"new pmax value {pmax}")
# creates the ax and attaches it to the widget figure
axs = pl.mk_signal_modulus_ax(self.time_unit, fig=self.wCanvas.fig)
pl.plot_signal_modulus(
axs,
time_vector=self.tvec,
signal=self.signal,
modulus=self.modulus,
periods=self.periods,
p_max=pmax,
)
# redraw COI if checkbox is checked
self.draw_coi()
# re-draw ridge
if self._has_ridge:
self.draw_ridge()
# refresh the canvas
self.wCanvas.draw()
self.wCanvas.show()
def compute_spectrum(self,
raw_signal,
sinc_detrend=True,
norm_amplitude=False,
do_plot=True,
draw_coi=False):
"""
Computes the Wavelet spectrum for a given *signal* for the given *periods*
signal : a sequence, the time-series to be analyzed
sinc_detrend : boolean, if True sinc-filter detrending
will be done with the set T_cut_off parameter
norm_amplitude : boolean, if True sliding window amplitude envelope
estimation is performed, and normalisation with
1/envelope
do_plot : boolean, set to False if no plot is desired,
good for for batch processing
draw_coi: boolean, set to True if cone of influence
shall be drawn on the wavelet power spectrum
After a successful analysis, the analyser instance updates
self.wlet
self.modulus
with the results.
"""
if sinc_detrend:
detrended = self.sinc_detrend(raw_signal)
ana_signal = detrended
else:
ana_signal = raw_signal
# only after potential detrending!
if norm_amplitude:
ana_signal = self.normalize_amplitude(ana_signal)
self.ana_signal = ana_signal
modulus, wlet = core.compute_spectrum(ana_signal, self.dt,
self.periods)
if do_plot:
tvec = np.arange(len(ana_signal)) * self.dt
axs = pl.mk_signal_modulus_ax(self.time_unit_label)
pl.plot_signal_modulus(
axs,
time_vector=tvec,
signal=ana_signal,
modulus=modulus,
periods=self.periods,
p_max=self.p_max,
)
fig = ppl.gcf()
fig.tight_layout()
self.ax_spec = axs[1]
if draw_coi:
coi_m = core.Morlet_COI()
pl.draw_COI(axs[1], time_vector=tvec)
self.wlet = wlet
self.modulus = modulus
self._has_spec = True
def compute_spectrum(self,
raw_signal,
T_c=None,
window_size=None,
do_plot=True,
draw_coi=False):
"""
Computes the Wavelet spectrum for a given *raw_signal*.
Parameters
----------
signal : a sequence, the time-series to be analyzed
T_c : float, optional
Cut off period for the sinc-filter detrending, all periods
larger than that one are removed from the signal. If not given,
no sinc-detending will be done.
window_size : float, optional
Length of the sliding window for amplitude
envelope estimation in real time units, e.g. 17 minutes.
If not given no amplitude normalization will be done.
do_plot : boolean, set to False if no plot is desired,
good for batch processing
draw_coi: boolean, set to True if cone of influence
shall be drawn on the wavelet power spectrum
Returns
-------
modulus : 2d ndarray
the real Wavelet power spectrum normalized by signal
variance, has shape len(periods) x len(signal). Is set to None
before any analysis is done.
transform : 2d ndarray
the complex results of the Wavelet transform with
shape len(periods) x len(signal). Is set to None
before any analysis is done.
After a successful analysis, the analyzer instance updates
self.transform
self.modulus
with the results. If do_plot was set to True, the attributes
self.ax_spec_signal
self.ax_spec
allow to access the created subplots directly.
"""
if T_c:
detrended = self.sinc_detrend(raw_signal, T_c)
ana_signal = detrended
else:
ana_signal = raw_signal
# only after potential detrending!
if window_size:
ana_signal = self.normalize_amplitude(ana_signal, window_size)
self.ana_signal = ana_signal
modulus, transform = core.compute_spectrum(ana_signal, self.dt, self.periods)
if do_plot:
tvec = np.arange(len(ana_signal)) * self.dt
axs = pl.mk_signal_modulus_ax(self.time_unit_label)
pl.plot_signal_modulus(
axs,
time_vector=tvec,
signal=ana_signal,
modulus=modulus,
periods=self.periods,
p_max=self.p_max,
)
fig = ppl.gcf()
fig.tight_layout()
# some space for a title
fig.subplots_adjust(top=0.95)
self.ax_spec_signal = axs[0]
self.ax_spec = axs[1]
if draw_coi:
pl.draw_COI(axs[1], time_vector=tvec)
self.transform = transform
self.modulus = modulus
# return also directly
return modulus, transform
def initUI(self, position):
self.setWindowTitle("Wavelet Spectrum - " + str(self.signal_id))
self.setGeometry(510 + position, 80 + position, 620, 750)
main_widget = QWidget()
self.statusBar()
# Wavelet and signal plot
self.wCanvas = mkWaveletCanvas()
main_frame = QWidget()
self.wCanvas.setParent(main_frame)
ntb = NavigationToolbar(self.wCanvas, main_frame) # full toolbar
# -------------plot the wavelet power spectrum---------------------------
# creates the ax and attaches it to the widget figure
axs = pl.mk_signal_modulus_ax(self.time_unit, fig=self.wCanvas.fig)
pl.plot_signal_modulus(
axs,
time_vector=self.tvec,
signal=self.signal,
modulus=self.modulus,
periods=self.periods,
p_max=self.pow_max,
)
self.wCanvas.fig.subplots_adjust(bottom=0.11,
right=0.95,
left=0.13,
top=0.95)
self.wCanvas.fig.tight_layout()
# --- Spectrum plotting options ---
spectrum_opt_box = QGroupBox("Spectrum Plotting Options")
spectrum_opt_box.setSizePolicy(QSizePolicy.Maximum,
QSizePolicy.Maximum)
spectrum_opt_layout = QHBoxLayout()
spectrum_opt_layout.setSpacing(10)
spectrum_opt_box.setLayout(spectrum_opt_layout)
# uppler limit of the colormap <-> imshow(...,vmax = pmax)
pmax_label = QLabel("Maximal Power:")
self.pmax_edit = QLineEdit()
self.pmax_edit.setStatusTip("Sets upper power limit of the spectrum")
self.pmax_edit.setMaximumWidth(80)
self.pmax_edit.setValidator(posfloatV)
# retrieve initial power value, axs[1] is the spectrum
pmin, pmax = axs[1].images[0].get_clim()
self.pmax_edit.insert(f"{pmax:.0f}")
RePlotButton = QPushButton("Update Plot", self)
RePlotButton.setStatusTip(
"Rescales the color map of the spectrum with the new max value")
RePlotButton.clicked.connect(self.update_plot)
self.cb_coi = QCheckBox("COI", self)
self.cb_coi.setStatusTip(
"Draws the cone of influence onto the spectrum")
self.cb_coi.stateChanged.connect(self.draw_coi)
# ridge_opt_layout.addWidget(drawRidgeButton,1,3) # not needed anymore?!
spectrum_opt_layout.addWidget(pmax_label)
spectrum_opt_layout.addWidget(self.pmax_edit)
spectrum_opt_layout.addStretch(0)
spectrum_opt_layout.addWidget(RePlotButton)
spectrum_opt_layout.addStretch(0)
spectrum_opt_layout.addWidget(self.cb_coi)
# --- Time average -> asymptotic Fourier ---
time_av_box = QGroupBox("Time Averaging")
estimFourierButton = QPushButton("Estimate Fourier", self)
estimFourierButton.clicked.connect(self.ini_average_spec)
estimFourierButton.setStatusTip(
"Shows time averaged Wavelet power spectrum")
time_av_layout = QHBoxLayout()
# time_av_layout.addStretch()
time_av_layout.addWidget(estimFourierButton)
# time_av_layout.addStretch()
time_av_box.setLayout(time_av_layout)
# --- Ridge detection and options --
ridge_opt_box = QGroupBox("Ridge Detection")
ridge_opt_box.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.Maximum)
ridge_opt_layout = QGridLayout()
ridge_opt_box.setLayout(ridge_opt_layout)
# Start ridge detection
maxRidgeButton = QPushButton("Detect Maximum Ridge", self)
maxRidgeButton.setStatusTip("Finds the time-consecutive power maxima")
maxRidgeButton.setSizePolicy(QSizePolicy.Minimum, QSizePolicy.Fixed)
maxRidgeButton.clicked.connect(self.do_maxRidge_detection)
# remove annealing, too slow.. not well implemented
# annealRidgeButton = QPushButton('Set up ridge\nfrom annealing', self)
# annealRidgeButton.clicked.connect(self.set_up_anneal)
power_label = QLabel("Ridge Threshold:")
power_label.setSizePolicy(QSizePolicy.Minimum, QSizePolicy.Fixed)
power_thresh_edit = QLineEdit()
power_thresh_edit.setStatusTip(
"Sets the minimal power value required to be considered part of the ridge"
)
power_thresh_edit.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
power_thresh_edit.setMinimumSize(60, 0)
power_thresh_edit.setValidator(posfloatV)
smooth_label = QLabel("Ridge Smoothing:")
ridge_smooth_edit = QLineEdit()
ridge_smooth_edit.setStatusTip(
"Savitzky-Golay smoothing (k=3) of the ridge in time")
ridge_smooth_edit.setMinimumSize(60, 0)
ridge_smooth_edit.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
ridge_smooth_edit.setValidator(
QIntValidator(bottom=3, top=len(self.signal)))
# Plot Results
plotResultsButton = QPushButton("Plot Ridge Readout", self)
plotResultsButton.setStatusTip(
"Shows instantaneous period, phase, power and amplitude along the ridge"
)
# plotResultsButton.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
plotResultsButton.clicked.connect(self.ini_plot_readout)
ridge_opt_layout.addWidget(maxRidgeButton, 0, 0, 1, 1)
ridge_opt_layout.addWidget(plotResultsButton, 1, 0, 1, 1)
# ridge_opt_layout.addWidget(annealRidgeButton,1,0)
ridge_opt_layout.addWidget(power_label, 0, 1)
ridge_opt_layout.addWidget(power_thresh_edit, 0, 2)
ridge_opt_layout.addWidget(smooth_label, 1, 1)
ridge_opt_layout.addWidget(ridge_smooth_edit, 1, 2)
# for spacing
rtool_box = QWidget()
rtool_layout = QHBoxLayout()
rtool_box.setLayout(rtool_layout)
rtool_layout.addWidget(ridge_opt_box)
rtool_layout.addStretch(0)
# --- put everything together ---
main_layout = QGridLayout()
# main_layout.setSpacing(0)
main_layout.addWidget(self.wCanvas, 0, 0, 4, 5)
main_layout.addWidget(ntb, 5, 0, 1, 5)
main_layout.addWidget(spectrum_opt_box, 6, 0, 1, 3)
main_layout.addWidget(time_av_box, 6, 3, 1, 1)
main_layout.addItem(QSpacerItem(2, 15), 6, 5)
main_layout.addWidget(ridge_opt_box, 7, 0, 1, 5)
# set stretching (resizing) behavior
main_layout.setRowStretch(0, 1) # plot should stretch
main_layout.setRowMinimumHeight(
0, 300) # plot should not get squeezed too much
main_layout.setRowStretch(5, 0) # options shouldn't stretch
main_layout.setRowStretch(6, 0) # options shouldn't stretch
main_layout.setRowStretch(7, 0) # options shouldn't stretch
# initialize line edits
power_thresh_edit.textChanged[str].connect(self.qset_power_thresh)
power_thresh_edit.insert("0.0") # initialize with 0
ridge_smooth_edit.textChanged[str].connect(self.qset_ridge_smooth)
ridge_smooth_edit.insert("0") # initialize with 0
main_widget.setLayout(main_layout)
self.setCentralWidget(main_widget)
self.show()
# plot the signal/trend tvec = np.arange(len(signal)) * dt ax = pl.mk_signal_ax(time_unit='s') pl.draw_signal(ax, tvec, signal) # pl.draw_detrended(ax, tvec, signal) pl.draw_trend(ax, tvec, trend) ppl.legend(ncol=2) ppl.tight_layout() # --- compute spectrum on the original signal --- modulus, wlet = pyboat.compute_spectrum(signal, dt, periods) # plot spectrum and ridge ax_sig, ax_spec = pl.mk_signal_modulus_ax(time_unit) pl.plot_signal_modulus((ax_sig, ax_spec), tvec, signal, modulus, periods) # --- compute spectrum on the detrended signal --- modulus, wlet = pyboat.compute_spectrum(detr_signal, dt, periods) # get maximum ridge ridge_ys = pyboat.get_maxRidge_ys(modulus) # evaluate along the ridge ridge_results = pyboat.eval_ridge(ridge_ys, wlet, signal, periods, tvec) # plot spectrum and ridge ax_sig2, ax_spec2 = pl.mk_signal_modulus_ax(time_unit) pl.plot_signal_modulus((ax_sig2, ax_spec2), tvec, signal, modulus, periods) pl.draw_Wavelet_ridge(ax_spec2, ridge_results)
def do_the_loop(self):
'''
Uses the explicitly parsed self.wlet_pars
to control signal analysis settings.
Takes general analysis Parameters
self.parentDV.dt
self.parentDV.time_unit
and the DataFrame
self.parentDV.df
from the parent DataViewer.
Reads additional settings from this Batch Process Window.
'''
if self.export_options.isChecked():
OutPath = self.get_OutPath()
if OutPath is None:
return
periods = np.linspace(self.wlet_pars['T_min'], self.wlet_pars['T_max'],
self.wlet_pars['step_num'])
# retrieve batch settings
power_thresh = self.get_thresh()
rsmooth = self.get_ridge_smooth()
ridge_results = {}
for i, signal_id in enumerate(self.parentDV.df):
# log to terminal
print(f"processing {signal_id}..")
# sets parentDV.raw_signal and parentDV.tvec
succ = self.parentDV.vector_prep(signal_id)
# ui silently passes over..
if not succ:
print(f"Can't process signal {signal_id}..")
continue
# detrend?!
if self.parentDV.cb_use_detrended.isChecked():
trend = self.parentDV.calc_trend()
signal = self.parentDV.raw_signal - trend
else:
signal = self.parentDV.raw_signal
# amplitude normalization?
if self.parentDV.cb_use_envelope.isChecked():
if self.debug:
print('Calculating envelope with L=', self.wlet_pars['L'])
signal = pyboat.normalize_with_envelope(
signal, self.wlet_pars['L'], self.parentDV.dt)
# compute the spectrum
modulus, wlet = pyboat.compute_spectrum(signal, self.parentDV.dt,
periods)
# get maximum ridge
ridge = pyboat.get_maxRidge_ys(modulus)
# generate time vector
tvec = np.arange(len(signal)) * self.parentDV.dt
# evaluate along the ridge
ridge_data = pyboat.eval_ridge(ridge,
wlet,
signal,
periods,
tvec,
power_thresh,
smoothing_wsize=rsmooth)
ridge_results[signal_id] = (ridge_data)
# -- Save out individual results --
if self.cb_specs.isChecked():
# plot spectrum and ridge
ax_sig, ax_spec = pl.mk_signal_modulus_ax(
self.parentDV.time_unit)
pl.plot_signal_modulus((ax_sig, ax_spec),
tvec,
signal,
modulus,
periods,
p_max=self.wlet_pars['p_max'])
pl.draw_Wavelet_ridge(ax_spec, ridge_data)
plt.tight_layout()
fname = f'{OutPath}/{signal_id}_wspec.png'
if self.debug:
print(f'Plotting and saving {signal_id} to {fname}')
plt.savefig(fname)
plt.close()
if self.cb_readout_plots.isChecked():
pl.plot_readout(ridge_data)
fname = f'{OutPath}/{signal_id}_readout.png'
if self.debug:
print(f'Plotting and saving {signal_id} to {fname}')
plt.savefig(fname)
plt.close()
if self.cb_readout.isChecked():
fname = f'{OutPath}/{signal_id}_readout.csv'
if self.debug:
print(f'Saving ridge reatout to {fname}')
ridge_data.to_csv(fname,
sep=',',
float_format='%.3f',
index=False)
self.progress.setValue(i)
return ridge_results
def do_the_loop(self):
'''
Uses the explicitly parsed self.wlet_pars
to control signal analysis settings.
Takes general analysis Parameters
self.parentDV.dt
self.parentDV.time_unit
and the DataFrame
self.parentDV.df
from the parent DataViewer.
Reads additional settings from this Batch Process Window.
'''
EmptyRidge = 0
if self.export_options.isChecked():
OutPath = self.get_OutPath()
if OutPath is None:
return
periods = np.linspace(self.wlet_pars['T_min'], self.wlet_pars['T_max'],
self.wlet_pars['step_num'])
# retrieve batch settings
power_thresh = self.get_thresh()
rsmooth = self.get_ridge_smooth()
# results get stored here
ridge_results = {}
df_fouriers = pd.DataFrame(index=periods)
df_fouriers.index.name = 'period'
for i, signal_id in enumerate(self.parentDV.df):
# log to terminal
print(f"processing {signal_id}..")
# sets parentDV.raw_signal and parentDV.tvec
succ = self.parentDV.vector_prep(signal_id)
# ui silently passes over..
if not succ:
print(f"Can't process signal {signal_id}..")
continue
# detrend?!
if self.parentDV.cb_use_detrended.isChecked():
trend = self.parentDV.calc_trend()
signal = self.parentDV.raw_signal - trend
else:
signal = self.parentDV.raw_signal
# amplitude normalization?
if self.parentDV.cb_use_envelope.isChecked():
if self.debug:
print('Calculating envelope with L=', self.wlet_pars['L'])
signal = pyboat.normalize_with_envelope(
signal, self.wlet_pars['L'], self.parentDV.dt)
# compute the spectrum
modulus, wlet = pyboat.compute_spectrum(signal, self.parentDV.dt,
periods)
# get maximum ridge
ridge = pyboat.get_maxRidge_ys(modulus)
# generate time vector
tvec = np.arange(len(signal)) * self.parentDV.dt
# evaluate along the ridge
ridge_data = pyboat.eval_ridge(ridge,
wlet,
signal,
periods,
tvec,
power_thresh,
smoothing_wsize=rsmooth)
# from ridge thresholding..
if ridge_data.empty:
EmptyRidge += 1
else:
ridge_results[signal_id] = ridge_data
# time average the spectrum, all have shape len(periods)!
averaged_Wspec = np.mean(modulus, axis=1)
df_fouriers[signal_id] = averaged_Wspec
# -- Save out individual results --
if self.cb_specs.isChecked():
# plot spectrum and ridge
ax_sig, ax_spec = pl.mk_signal_modulus_ax(
self.parentDV.time_unit)
pl.plot_signal_modulus((ax_sig, ax_spec),
tvec,
signal,
modulus,
periods,
p_max=self.wlet_pars['p_max'])
pl.draw_Wavelet_ridge(ax_spec, ridge_data)
plt.tight_layout()
fname = os.path.join(OutPath, f'{signal_id}_wspec.png')
if self.debug:
print(
f'Plotting and saving spectrum {signal_id} to {fname}')
plt.savefig(fname, dpi=DPI)
plt.close()
if self.cb_specs_noridge.isChecked():
# plot spectrum without ridge
ax_sig, ax_spec = pl.mk_signal_modulus_ax(
self.parentDV.time_unit)
pl.plot_signal_modulus((ax_sig, ax_spec),
tvec,
signal,
modulus,
periods,
p_max=self.wlet_pars['p_max'])
plt.tight_layout()
fname = os.path.join(OutPath, f'{signal_id}_wspecNR.png')
if self.debug:
print(
f'Plotting and saving spectrum {signal_id} to {fname}')
plt.savefig(fname, dpi=DPI)
plt.close()
if self.cb_readout_plots.isChecked() and not ridge_data.empty:
pl.plot_readout(ridge_data)
fname = os.path.join(OutPath, f'{signal_id}_readout.png')
if self.debug:
print(f'Plotting and saving {signal_id} to {fname}')
plt.savefig(fname, dpi=DPI)
plt.close()
if self.cb_readout.isChecked() and not ridge_data.empty:
fname = os.path.join(OutPath, f'{signal_id}_readout.csv')
if self.debug:
print(f'Saving ridge reatout to {fname}')
ridge_data.to_csv(fname,
sep=',',
float_format='%.3f',
index=False)
self.progress.setValue(i)
if EmptyRidge > 0:
self.NoRidges = MessageWindow(
f'{EmptyRidge} ridge readouts entirely below threshold..',
'Discarded ridges')
return ridge_results, df_fouriers
def do_the_loop(self):
"""
Uses the explicitly parsed self.wlet_pars
to control signal analysis settings.
Takes general analysis Parameters
self.parentDV.dt
self.parentDV.time_unit
and the DataFrame
self.parentDV.df
from the parent DataViewer.
Reads additional settings from this Batch Process Window.
"""
EmptyRidge = 0
if self.export_options.isChecked():
OutPath = self.get_OutPath()
if OutPath is None:
return
periods = np.linspace(self.wlet_pars["Tmin"], self.wlet_pars["Tmax"],
self.wlet_pars["step_num"])
# retrieve batch settings
power_thresh = self.get_thresh()
rsmooth = self.get_ridge_smooth()
# results get stored here
ridge_results = {}
df_fouriers = pd.DataFrame(index=periods)
df_fouriers.index.name = "period"
for i, signal_id in enumerate(self.parentDV.df):
# log to terminal
print(f"processing {signal_id}..")
# sets parentDV.raw_signal and parentDV.tvec
succ = self.parentDV.vector_prep(signal_id)
# ui silently passes over..
if not succ:
print(f"Warning, can't process signal {signal_id}..")
continue
# detrend?!
if self.parentDV.cb_use_detrended.isChecked():
trend = self.parentDV.calc_trend()
signal = self.parentDV.raw_signal - trend
else:
signal = self.parentDV.raw_signal
# amplitude normalization?
if self.parentDV.cb_use_envelope.isChecked():
if self.debug:
print("Calculating envelope with L=",
self.wlet_pars["window_size"])
signal = pyboat.normalize_with_envelope(
signal, self.wlet_pars["window_size"], self.parentDV.dt)
# compute the spectrum
modulus, wlet = pyboat.compute_spectrum(signal, self.parentDV.dt,
periods)
# get maximum ridge
ridge = pyboat.get_maxRidge_ys(modulus)
# generate time vector
tvec = np.arange(len(signal)) * self.parentDV.dt
# evaluate along the ridge
ridge_data = pyboat.eval_ridge(
ridge,
wlet,
signal,
periods,
tvec,
power_thresh,
smoothing_wsize=rsmooth,
)
# from ridge thresholding..
if ridge_data.empty:
EmptyRidge += 1
else:
ridge_results[signal_id] = ridge_data
# time average the spectrum, all have shape len(periods)!
averaged_Wspec = np.mean(modulus, axis=1)
df_fouriers[signal_id] = averaged_Wspec
# -- Save out individual results --
settings = QSettings()
float_format = settings.value('float_format', '%.3f')
graphics_format = settings.value('graphics_format', 'png')
exbox_checked = self.export_options.isChecked()
if exbox_checked and self.cb_filtered_sigs.isChecked():
signal_df = pd.DataFrame()
signal_df['signal'] = signal
signal_df.index = tvec
signal_df.index.name = 'time'
fname = os.path.join(OutPath, f"{signal_id}_filtered.csv")
if self.debug:
print(f"Saving filtered signal to {fname}")
signal_df.to_csv(fname,
sep=",",
float_format=float_format,
index=True,
header=True)
if exbox_checked and self.cb_specs.isChecked():
# plot spectrum and ridge
ax_sig, ax_spec = pl.mk_signal_modulus_ax(
self.parentDV.time_unit)
pl.plot_signal_modulus(
(ax_sig, ax_spec),
tvec,
signal,
modulus,
periods,
p_max=self.wlet_pars["pow_max"],
)
pl.draw_Wavelet_ridge(ax_spec, ridge_data)
plt.tight_layout()
fname = os.path.join(OutPath,
f"{signal_id}_wspec.{graphics_format}")
if self.debug:
print(
f"Plotting and saving spectrum {signal_id} to {fname}")
plt.savefig(fname, dpi=DPI)
plt.close()
if exbox_checked and self.cb_specs_noridge.isChecked():
# plot spectrum without ridge
ax_sig, ax_spec = pl.mk_signal_modulus_ax(
self.parentDV.time_unit)
pl.plot_signal_modulus(
(ax_sig, ax_spec),
tvec,
signal,
modulus,
periods,
p_max=self.wlet_pars["pow_max"],
)
plt.tight_layout()
fname = os.path.join(OutPath,
f"{signal_id}_wspecNR.{graphics_format}")
if self.debug:
print(
f"Plotting and saving spectrum {signal_id} to {fname}")
plt.savefig(fname, dpi=DPI)
plt.close()
if exbox_checked and self.cb_readout_plots.isChecked(
) and not ridge_data.empty:
pl.plot_readout(ridge_data)
fname = os.path.join(OutPath,
f"{signal_id}_readout.{graphics_format}")
if self.debug:
print(f"Plotting and saving {signal_id} to {fname}")
plt.savefig(fname, dpi=DPI)
plt.close()
if exbox_checked and self.cb_readout.isChecked(
) and not ridge_data.empty:
fname = os.path.join(OutPath, f"{signal_id}_readout.csv")
if self.debug:
print(f"Saving ridge readout to {fname}")
ridge_data.to_csv(fname,
sep=",",
float_format=float_format,
index=False)
self.progress.setValue(i)
if EmptyRidge > 0:
msg = f"{EmptyRidge} ridge readouts entirely below threshold.."
msgBox = QMessageBox()
msgBox.setWindowTitle("Discarded Ridges")
msgBox.setText(msg)
msgBox.exec()
return ridge_results, df_fouriers
def initUI(self, position):
self.setWindowTitle('Wavelet Spectrum - ' + str(self.signal_id))
self.setGeometry(510 + position, 80 + position, 620, 750)
# Wavelet and signal plot
self.wCanvas = mkWaveletCanvas()
main_frame = QWidget()
self.wCanvas.setParent(main_frame)
ntb = NavigationToolbar(self.wCanvas, main_frame) # full toolbar
#-------------plot the wavelet power spectrum---------------------------
# creates the ax and attaches it to the widget figure
axs = pl.mk_signal_modulus_ax(self.time_unit, fig=self.wCanvas.fig)
pl.plot_signal_modulus(axs,
time_vector=self.tvec,
signal=self.signal,
modulus=self.modulus,
periods=self.periods,
p_max=self.p_max)
self.wCanvas.fig.subplots_adjust(bottom=0.11,
right=0.95,
left=0.13,
top=0.95)
self.wCanvas.fig.tight_layout()
# --- Spectrum plotting options ---
spectrum_opt_box = QGroupBox("Plotting Options")
spectrum_opt_box.setSizePolicy(QSizePolicy.Maximum,
QSizePolicy.Maximum)
spectrum_opt_layout = QHBoxLayout()
spectrum_opt_layout.setSpacing(10)
spectrum_opt_box.setLayout(spectrum_opt_layout)
# uppler limit of the colormap <-> imshow(...,vmax = pmax)
pmax_label = QLabel("Maximal Power:")
self.pmax_edit = QLineEdit()
self.pmax_edit.setToolTip('Rescales the color map of the spectrum')
self.pmax_edit.setMaximumWidth(60)
self.pmax_edit.setValidator(posfloatV)
# retrieve initial power value, axs[1] is the spectrum
pmin, pmax = axs[1].images[0].get_clim()
self.pmax_edit.insert(f'{pmax:.0f}')
RePlotButton = QPushButton('Update Plot', self)
RePlotButton.setToolTip(
'Redraws the spectrum with the new upper power limit')
RePlotButton.clicked.connect(self.update_plot)
self.cb_coi = QCheckBox('COI', self)
self.cb_coi.setToolTip('Draws the cone of influence onto the spectrum')
self.cb_coi.stateChanged.connect(self.draw_coi)
# ridge_opt_layout.addWidget(drawRidgeButton,1,3) # not needed anymore?!
spectrum_opt_layout.addWidget(pmax_label)
spectrum_opt_layout.addWidget(self.pmax_edit)
spectrum_opt_layout.addStretch(0)
spectrum_opt_layout.addWidget(RePlotButton)
spectrum_opt_layout.addStretch(0)
spectrum_opt_layout.addWidget(self.cb_coi)
# --- Ridge detection and options --
ridge_opt_box = QGroupBox("Ridge Detection")
ridge_opt_box.setSizePolicy(QSizePolicy.Maximum, QSizePolicy.Maximum)
ridge_opt_layout = QGridLayout()
ridge_opt_box.setLayout(ridge_opt_layout)
#Start ridge detection
maxRidgeButton = QPushButton('Detect Maximum Ridge', self)
maxRidgeButton.setSizePolicy(QSizePolicy.Minimum, QSizePolicy.Fixed)
maxRidgeButton.clicked.connect(self.do_maxRidge_detection)
# remove annealing, too slow.. not well implemented
# annealRidgeButton = QPushButton('Set up ridge\nfrom annealing', self)
# annealRidgeButton.clicked.connect(self.set_up_anneal)
power_label = QLabel("Ridge Threshold:")
power_label.setSizePolicy(QSizePolicy.Minimum, QSizePolicy.Fixed)
power_thresh_edit = QLineEdit()
power_thresh_edit.setToolTip(
'Sets the minimal power value required to be part of the ridge')
power_thresh_edit.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
power_thresh_edit.setMinimumSize(50, 0)
power_thresh_edit.setValidator(posfloatV)
smooth_label = QLabel("Ridge Smoothing:")
ridge_smooth_edit = QLineEdit()
ridge_smooth_edit.setMinimumSize(50, 0)
ridge_smooth_edit.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
ridge_smooth_edit.setValidator(
QIntValidator(bottom=3, top=len(self.signal)))
# Plot Results
plotResultsButton = QPushButton('Plot Ridge Readout', self)
plotResultsButton.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
plotResultsButton.clicked.connect(self.ini_plot_readout)
ridge_opt_layout.addWidget(maxRidgeButton, 0, 0, 1, 1)
ridge_opt_layout.addWidget(plotResultsButton, 1, 0, 1, 1)
# ridge_opt_layout.addWidget(annealRidgeButton,1,0)
ridge_opt_layout.addWidget(power_label, 0, 1)
ridge_opt_layout.addWidget(power_thresh_edit, 0, 2)
ridge_opt_layout.addWidget(smooth_label, 1, 1)
ridge_opt_layout.addWidget(ridge_smooth_edit, 1, 2)
# for spacing
rtool_box = QWidget()
rtool_layout = QHBoxLayout()
rtool_box.setLayout(rtool_layout)
rtool_layout.addWidget(ridge_opt_box)
rtool_layout.addStretch(0)
# put everything together
main_layout = QVBoxLayout()
main_layout.setSpacing(0)
main_layout.addWidget(self.wCanvas)
main_layout.addWidget(ntb)
main_layout.addWidget(spectrum_opt_box)
main_layout.addWidget(ridge_opt_box)
self.setLayout(main_layout)
# initialize line edits
power_thresh_edit.textChanged[str].connect(self.qset_power_thresh)
power_thresh_edit.insert('0.0') # initialize with 0
ridge_smooth_edit.textChanged[str].connect(self.qset_ridge_smooth)
ridge_smooth_edit.insert('0') # initialize with 0
self.show()
