def setup_plot():
global rate_slider, delta_slider, fig, ax, l, radio
fig, ax = plt.subplots()
ax.grid('on')
plt.subplots_adjust(left=0.25, bottom=0.25)
moneyFmt = FuncFormatter(money)
ax.yaxis.set_major_formatter(moneyFmt)
s = calc_compounding( rate, periods, principal, contribution, delta,inflation)
t = np.arange(2014, (2014+periods))
l, = plt.plot(t,s, lw=2, color='red')
plt.ylabel("Investment Loss (FV)")
plt.axis([2014, (2014+periods), 0, principal])
plt.axis('tight')
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
axamp = plt.axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
rate_slider = Slider(axfreq, 'Avg.Returns', 4, 8, valinit=rate)
delta_slider = Slider(axamp, 'Delta', 0.1, 1, valinit=delta)
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
rate_slider.on_changed(update)
delta_slider.on_changed(update)
button.on_clicked(reset)
rax = plt.axes([0.015, 0.15, 0.15, 0.15], axisbg=axcolor)
radio = RadioButtons(rax, ('0','3000', '6000', '9000'), active=0)
radio.on_clicked(contribution_update)
plt.show()
return rate_slider,delta_slider,fig,ax,l,radio
def _create_controls(self):
self._freq_ax = plt.axes([0.2, 0.19, 0.2, 0.03])
self._freq_slider = Slider(self._freq_ax,
'Frequency',
0,
self.samplerate / 2.0,
valinit = self.frequency)
self._freq_slider.on_changed(self.set_signal_frequency)
self._ampl_ax = plt.axes([0.2, 0.1, 0.2, 0.03])
self._ampl_slider = Slider(self._ampl_ax,
'Amplitude',
-100,
0,
valinit = dcv.lin2db(self.amplitude))
self._ampl_slider.on_changed(self.set_signal_amplitude)
self._signaltype_ax = plt.axes([0.5, 0.05, 0.15, 0.20])
self._signaltype_radio = RadioButtons(self._signaltype_ax,
('Sine', 'Square', 'Sawtooth',
'Triangle', 'Noise', 'Constant'))
self._signaltype_radio.on_clicked(self.set_signal_type)
self._windowtype_ax = plt.axes([0.7, 0.05, 0.15, 0.20])
self._windowtype_radio = RadioButtons(self._windowtype_ax,
('Flat', 'Hanning', 'Hamming', 'Blackman'))
self._windowtype_radio.on_clicked(self.set_window_type)
def slide_ddg(args):
global new_df, radio, color_by, picked
global scat, ax, sliders, sc_df, fig, cm, cbar
sc_df = Rf.score_file2df(args['sc'], args['names'])
args['logger'].log('score file has %i entries' % len(sc_df))
if args['pc'] is not None:
pc_df = get_rmsds_from_table(args['pc'])
args['logger'].log('pc file had %i entries' % len(pc_df))
a = sc_df.merge(pc_df, on='description')
args['logger'].log('combined there are %i entries' % len(a))
sc_df = a.copy()
if args['percent'] != 100:
threshold = np.percentile(sc_df[args['y']], args['percent'])
sc_df = sc_df[ sc_df[args['y']] < threshold ]
color_by = args['y']
picked = False
new_df = sc_df.copy()
fig, ax = plt.subplots()
plt.subplots_adjust(left=0.25, bottom=0.25)
cm = plt.cm.get_cmap('RdYlBu')
scat = ax.scatter(sc_df[args['x']].values, sc_df[args['y']].values, s=40, cmap=cm, c=sc_df[color_by], picker=True)
cbar = plt.colorbar(scat)
sliders = {}
for i, term in enumerate(args['terms']):
slider_ax = plt.axes([0.25, 0.01+i*0.035, 0.65, 0.03])
sliders[term] = Slider(slider_ax, term, np.min(sc_df[term].values), np.max(sc_df[term].values), 0)
sliders[term].on_changed(update)
ax.set_xlim(np.min(new_df[args['x']].values)-1, np.max(new_df[args['x']].values)+1)
ax.set_ylim(np.min(new_df[args['y']].values)-1, np.max(new_df[args['y']].values)+1)
ax.set_xlabel(args['x'])
ax.set_ylabel(args['y'])
resetax = plt.axes([0.025, 0.7, 0.15, 0.15]) #[0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color='lightgoldenrodyellow', hovercolor='0.975')
button.on_clicked(reset)
printax = plt.axes([0.025, 0.3, 0.15, 0.15])
printbutton = Button(printax, 'Print', color='green', hovercolor='red')
printbutton.on_clicked(print_table)
logax = plt.axes([0.025, 0.1, 0.15, 0.15])
logbutton = Button(logax, 'log table', color='blue', hovercolor='red')
logbutton.on_clicked(log_table)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], axisbg='white')
radio = RadioButtons(rax, args['terms'], active=0)
radio.on_clicked(colorfunc)
# cbar = plt.colorbar(scat)
pl = PointLabel(new_df, ax, fig, args['x'], args['y'], ['description', 'a_sasa', 'a_res_solv', 'a_pack', 'a_span_topo', 'a_ddg', 'fa_elec'], args['logger'])
fig.canvas.mpl_connect('pick_event', pl.onpick)
plt.show()
class WidgetsBasic(WidgetsSimple):
def __init__(self, canvas=None, active_prop=None):
super(WidgetsBasic, self).__init__(canvas, active_prop)
self.colors_ifs = {}
@property
def prop_ifs(self):
return self.active_prop
def update_show_components(self, label):
super(WidgetsBasic, self).update_show_components(label)
if label == "hide ifs":
if self.holder_actives[label]:
self.prop_ifs.holder.set_linestyle(" ")
self.prop_ifs.holder.set_visible(False)
self.prop_ifs.set_visible_annotations(False)
self.prop_ifs.topo_const.set_visible(False)
else:
self.prop_ifs.holder.set_linestyle(" ")
self.prop_ifs.holder.set_visible(True)
self.prop_ifs.set_visible_annotations(True)
self.prop_ifs.topo_const.set_visible(True)
# here is updated the active prop_ifs
def recreate_widgets(self, idx_active, props, active_prop):
super(WidgetsBasic, self).recreate_widgets_(active_prop)
self._recreate_active_ifs_radiobutton(idx_active, props)
def _recreate_active_ifs_radiobutton(self, idx_active, props):
self.props = props
axcolor = "lightgoldenrodyellow"
if hasattr(self, "rax_activeifs"):
self.rax_activeifs.cla()
self.rax_activeifs = plt.axes(
[0.2 + self.button_length__ + 0.01, 0.05, self.button_length__, self.button_height__], axisbg=axcolor
)
activecolor = self.active_prop.get_color()
self.w_rad_active_ifs = RadioButtons(
self.rax_activeifs, sorted(self.colors_ifs.keys()), active=idx_active, activecolor=activecolor
)
self.w_rad_active_ifs.on_clicked(self.colorfunc)
return self.w_rad_active_ifs
def colorfunc(self, label):
idx = int(label)
self.active_prop = self.props[idx]
self.w_rad_active_ifs.activecolor = self.prop_ifs.get_color()
self._recreate_radius_slider()
self._recreate_show_lines_check_button()
self._recreate_alpha_slider()
self._recreate_textsize_slider()
if self.canvas is None:
self.canvas.draw()
def run_main(A,B,C,dA,dB,dC):
plt.close()
plt.figure()
int_writer()
var_writer_uncert(A,B,C)
run_SPCAT()
data = cat_reader()
t = []
s = []
for x in data:
s.append(0.0)
s.append(str(10**float(x[1])))
s.append(0.0)
t.append(float(x[0])-0.0001)
t.append(x[0])
t.append(float(x[0])+0.0001)
ax = plt.subplot(111)
plt.subplots_adjust(left=0.25, bottom=0.25)
a0 = 5
f0 = 3
global l
l, = plt.plot(t,s, lw=2, color='red')
#plt.axis([0, 1, -10, 10])
axcolor = 'lightgoldenrodyellow'
axA = plt.axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
axB = plt.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
axC = plt.axes([0.25, 0.05, 0.65, 0.03], axisbg=axcolor)
global A_slider
global B_slider
global C_slider
A_slider = Slider(axA, 'A', A-dA, A+dA, valinit=A)
B_slider = Slider(axB, 'B', B-dB, B+dB, valinit=B)
C_slider = Slider(axC, 'C', C-dC, C+dC, valinit=C)
A_slider.on_changed(update)
B_slider.on_changed(update)
C_slider.on_changed(update)
global button
global radio
resetax = plt.axes([0.1, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
button.on_clicked(reset)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
radio.on_clicked(colorfunc)
plt.show()
def _create_plot_controls(self):
self._dbrax = plt.axes([0.12, 0.05, 0.10, 0.10])
self._dbradio = RadioButtons(self._dbrax, ('Amplitude', 'Phase'))
self._dbradio.on_clicked(self.set_plot_style)
self._rax = plt.axes([0.25, 0.03, 0.15, 0.20])
self._radio = RadioButtons(self._rax, ('Low Pass', 'High Pass'))
self._radio.on_clicked(self.set_biquad_type)
self._sfax = plt.axes([0.6, 0.19, 0.2, 0.03])
self._fcslider = Slider(self._sfax, 'Cut-off frequency', 0, self._bq_fs/2, valinit = self._bq_fc)
self._fcslider.on_changed(self.set_biquad_frequency_cutoff)
def _GUI_display(self,redshift_est,ztest,corr_val,wave,flux_sc):
'''Display the spectrum and reference lines.'''
self.fig = plt.figure(figsize=(10, 8))
gs = gridspec.GridSpec(2, 1, height_ratios=[2, 1])
ax2 = plt.subplot(gs[0])
ax = plt.subplot(gs[1])
plt.subplots_adjust(right=0.8)
ax.plot(ztest,corr_val,'b')
ax.axvline(redshift_est,color='k',ls='--')
ax.fill_between(self.ztest,np.zeros(self.ztest.size),self.corr_prior,facecolor='grey',alpha=0.6)
ax.set_xlabel('Redshift')
ax.set_ylabel('Correlation')
self.pspec, = ax2.plot(wave,flux_sc)
ax2.axvline(3725.0*(1+redshift_est),ls='--',alpha=0.7,c='blue')
ax2.axvline(3968.5*(1+redshift_est),ls='--',alpha=0.7,c='red')
ax2.axvline(3933.7*(1+redshift_est),ls='--',alpha=0.7,c='red')
ax2.axvline(4102.9*(1+redshift_est),ls='--',alpha=0.7,c='orange')
ax2.axvline(4304.0*(1+redshift_est),ls='--',alpha=0.7,c='orange')
ax2.axvline(4862.0*(1+redshift_est),ls='--',alpha=0.7,c='orange')
ax2.axvline(4959.0*(1+redshift_est),ls='--',alpha=0.7,c='blue')
ax2.axvline(5007.0*(1+redshift_est),ls='--',alpha=0.7,c='blue')
ax2.axvline(5175.0*(1+redshift_est),ls='--',alpha=0.7,c='orange')
if self.first_pass:
self.line_est = Estimateline(self.pspec,ax2,self.uline_n)
rax = plt.axes([0.85, 0.5, 0.1, 0.2])
if self.qualityval == 0:
radio = RadioButtons(rax, ('Unclear', 'Clear'))
else:
radio = RadioButtons(rax, ('Unclear', 'Clear'),active=1)
def qualfunc(label):
if label == 'Clear':
self.qualityval = 1
else:
self.qualityval = 0
radio.on_clicked(qualfunc)
closeax = plt.axes([0.83, 0.3, 0.15, 0.1])
button = Button(closeax, 'Accept & Close', hovercolor='0.975')
def closeplot(event):
plt.close()
button.on_clicked(closeplot)
ax2.set_xlim(self.lower_w,self.upper_w)
ax2.set_xlabel('Wavelength (A)')
ax2.set_ylabel('Counts')
if not self.first_pass:
self.spectra2 = DragSpectra(self.pspec,flux_sc,ax2,self.fig)
self.fig.canvas.mpl_connect('motion_notify_event',self.spectra2.on_motion)
self.fig.canvas.mpl_connect('button_press_event',self.spectra2.on_press)
self.fig.canvas.mpl_connect('button_release_event',self.spectra2.on_release)
plt.show()
def _create_plot_controls(self):
self._dbrax = plt.axes([0.12, 0.05, 0.15, 0.15])
self._dbradio = RadioButtons(self._dbrax, ('Amplitude', 'Phase'))
self._dbradio.on_clicked(self.set_plot_style)
self._rax = plt.axes([0.30, 0.03, 0.15, 0.20])
self._radio = RadioButtons(self._rax, ('feedback', 'feedforward', 'allpass'))
self._radio.on_clicked(self.set_comb_type)
self._sfax = plt.axes([0.6, 0.19, 0.2, 0.03])
self._dlyslider = Slider(self._sfax, 'delay (ms)', 0, (self._size/2.0) * 1000.0 / self._fs, valinit = self._delay)
self._dlyslider.on_changed(self.set_comb_delay)
self._sfax = plt.axes([0.6, 0.10, 0.2, 0.03])
self._gainslider = Slider(self._sfax, 'gain', -1, 1, valinit = self._gain)
self._gainslider.on_changed(self.set_comb_gain)
def ReadFluxLC(self,fluxLC):
self.fluxes = fluxLC.fluxes
self.errors = array(fluxLC.fluxErrors)
self.tBins = fluxLC.tBins
self.models = fluxLC.modelNames
self.flcFlag =True
axcolor = 'lightgoldenrodyellow'
# self.radioFig = plt.figure(2)
#
ax = plt.axes([.01, 0.7, 0.2, 0.32], axisbg=axcolor)
self.data = self.fluxes['total']
if self.radio:
del self.radio
self.radioAx.cla()
self.radio = RadioButtons(self.radioAx,tuple(self.fluxes.keys()))
self.radio.on_clicked(self.Selector)
self.PlotData()
def __init__(self, image, low, high):
self.image_name = image
self.low = low
self.high = high
self.filter = None
self.output = None
self.filter_type = None
self.padRows = None
self.padCols = None
original_input = cv2.imread(image,0)
rows, cols = original_input.shape
if(rows < cols):
original_input = cv2.transpose(original_input)
self.transposed = True
else:
self.transposed = False
rows, cols = original_input.shape
optimalRows = cv2.getOptimalDFTSize(rows)
optimalCols = cv2.getOptimalDFTSize(cols)
self.padRows = optimalRows - rows
self.padCols = optimalCols - cols
self.input = np.zeros((optimalRows,optimalCols))
self.input[:rows,:cols] = original_input
self.dftshift = get_dft_shift(self.input)
plt.subplots_adjust(left=0, bottom=0.05, right=1, top=1, wspace=0, hspace=0)
plt.subplot(131)
plt.axis('off')
plt.title('original image')
plt.imshow(self.input, cmap = 'gray',interpolation='nearest')
self.axslow = plt.axes([0.05, 0.01, 0.5, 0.02])
self.slow = Slider(self.axslow, 'low', 0.01, 1, valinit=self.low)
self.slow.on_changed(self.updateLow)
self.axhigh = plt.axes([0.05, 0.03, 0.5, 0.02])
self.shigh = Slider(self.axhigh, 'high', 0.01, 1, valinit=self.high)
self.shigh.on_changed(self.updateHigh)
self.slow.slidermax=self.shigh
self.shigh.slidermin=self.slow
self.axfilter = plt.axes([0.62, 0.01, 0.15, 0.04])
self.rfilter = RadioButtons(self.axfilter, ('Gaussian Filter', 'Ideal Filter'))
self.rfilter.on_clicked(self.updateFilterType)
self.filter_type = self.rfilter.value_selected
self.axprocess = plt.axes([0.8, 0.01, 0.08, 0.04])
self.bprocess = Button(self.axprocess, 'Process')
self.bprocess.on_clicked(self.process)
self.axsave = plt.axes([0.88, 0.01, 0.08, 0.04])
self.bsave = Button(self.axsave, 'Save')
self.bsave.on_clicked(self.save)
def __init__(self,image=None,imginfo={},verbosity=0,cmap=None,**kwargs):
"""
image ... (opt) 2D Array
imginfo... (opt) dictionary with parameters of the image
verbosity. (opt) quiet (0), verbose (3), debug (4)
futher options are passed to the imshow method of matplotlib
"""
self.kwargs = kwargs;
self.verbosity=verbosity;
# open new figure and draw image
self.fig = plt.figure();
self.axis = self.fig.add_subplot(111);
self.fig.subplots_adjust(right=0.85);
self.AxesImage=None;
# add Switches and Buttons
axStyle = self.fig.add_axes([0.85, 0.1, 0.12, 0.12]);
self.rbStyle = RadioButtons(axStyle,["linear","log","contour"]);
self.rbStyle.on_clicked(self.set_style);
self.currentstyle = "linear";
axLine = self.fig.add_axes([0.85, 0.3, 0.12, 0.05]);
self.bLine = Button(axLine,'Line Profile');
self.bLine.on_clicked(self._toggle_line_profile);
self.LineProfile=None;
self.bLine.color_activated='red';
# key pressed
self.fig.canvas.mpl_connect('key_press_event', self._key_press_callback)
# draw image if given
self.set_cmap(cmap);
if image is not None:
self.set_image(image,imginfo);
def LoadEFlux(self,fileName):
flux = pickle.load(open(fileName))
self.fluxes = flux['energy fluxes']
self.fluxErrors = flux['errors']
self.tBins = flux['tBins']
axcolor = 'lightgoldenrodyellow'
# self.radioFig = plt.figure(2)
if self.radio:
#del self.radio
self.radioAx.cla()
#
self.radioAx = plt.axes([.01, 0.7, 0.2, 0.32], axisbg=axcolor)
self.data = self.fluxes['total']
self.errors = self.fluxErrors['total']
self.radio = RadioButtons(self.radioAx,tuple(self.fluxes.keys()))
self.radio.on_clicked(self.Selector)
self.PlotData()
def slider_radio():
def update(val):
amp = samp.val
freq = sfreq.val
l.set_ydata(amp*np.sin(2*np.pi*freq*t))
fig.canvas.draw_idle()
def reset(event):
sfreq.reset()
samp.reset()
def colorfunc(label):
l.set_color(label)
fig.canvas.draw_idle()
fig = figure()
ax = fig.subplots()
fig.subplots_adjust(left=0.25, bottom=0.25)
t = np.arange(0.0, 1.0, 0.001)
a0 = 5
f0 = 3
s = a0*np.sin(2*np.pi*f0*t)
l, = ax.plot(t, s, lw=2, color='red')
ax.axis([0, 1, -10, 10])
# %% plot axes
axcolor = 'lightgoldenrodyellow'
axfreq = fig.add_axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
axamp = fig.add_axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)
# %% freq slide
sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0)
samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
sfreq.on_changed(update)
samp.on_changed(update)
# %% reset button
resetax = fig.add_axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
button.on_clicked(reset)
# %% color buttons
rax = fig.add_axes([0.025, 0.5, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
radio.on_clicked(colorfunc)
# %% scoping
axw = [axfreq, axamp, sfreq, samp, button, radio] # place to hold all the axesWidgets to keep in scope
return axw # MUST return ax or GUI will be non-responsive!
def plot_mapqs(folder):
"""Plots the Distribution of MAPQ Scores for the Inversion Regions in the respective species
folder : input folder to look for the files
"""
mapqs_counts = defaultdict(list)
mapqs_labels = defaultdict(list)
strain_matcher = re.compile('(.*) \(.*\)') ## regex to get strain name from radio button click
## Parse the information from the mapq count files and store the information in a dictionary of lists
for mapq_file in glob.glob(folder+"*.count.txt"):
strain = mapq_file.split("/")[-1].split(".")[0]
TEMP_HANDLE = open(mapq_file,'r')
for line in TEMP_HANDLE:
line = line.strip('\n')
mapqs_counts[strain].append(int(line.split(' ')[0]))
mapqs_labels[strain].append(line.split(' ')[1])
fig, ax = plt.subplots()
indexes = np.arange(len(mapqs_counts[S]))
rects = plt.bar(indexes,mapqs_counts[S],0.5)
ax.set_xticks(indexes+1*0.2)
ax.set_xticklabels(mapqs_labels[S],rotation=30)
rax1 = plt.axes([0.92, 0.1, 0.08, 0.8])
radio1 = RadioButtons(rax1, ('MC (Sand)','CL (Sand)','CM (Sand)','CN (Sand)','TI (Sand)','DC (Sand)','MS (Sand)','CV (Sand)','PN (Rock)','AC (Rock)','LF (Rock)','MP (Rock)','MZ (Rock)'), active=0)
def update1(strain):
match = re.match(strain_matcher,strain)
strain = match.group(1)
#indexes = np.arange(len(mapqs_counts[S]))
for rect,h in zip(rects,mapqs_counts[strain]):
rect.set_height(h)
ax.set_xticks(indexes+1*0.2)
ax.set_xticklabels(mapqs_labels[strain],rotation=30)
ax.relim()
ax.autoscale()
fig.canvas.draw_idle()
#global S
#print S
#S = strain
radio1.on_clicked(update1)
plt.show()
def _init_radio(self):
"""
Add radio buttons to the radio ax for color scale.
self._make_radio_axes() needs to have been called.
"""
self.radio = RadioButtons(
self.radio_ax,
labels=['log', 'linear'],
active=1)
def Slider():
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button, RadioButtons
fig, ax = plt.subplots()
plt.subplots_adjust(left=0.25, bottom=0.25)
t = np.arange(0.0, 1.0, 0.001)
a0 = 5
f0 = 3
s = a0*np.sin(2*np.pi*f0*t)
l, = plt.plot(t,s, lw=2, color='red')
plt.axis([0, 1, -10, 10])
axcolor = 'lightgoldenrodyellow'
axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], axisbg=axcolor)
axamp = plt.axes([0.25, 0.15, 0.65, 0.03], axisbg=axcolor)
sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0)
samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
def update(val):
amp = samp.val
freq = sfreq.val
l.set_ydata(amp*np.sin(2*np.pi*freq*t))
fig.canvas.draw_idle()
sfreq.on_changed(update)
samp.on_changed(update)
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
sfreq.reset()
samp.reset()
button.on_clicked(reset)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
def colorfunc(label):
l.set_color(label)
fig.canvas.draw_idle()
radio.on_clicked(colorfunc)
plt.show()
class AnalyzeFrame(object):
"""
A slider representing a floating point range
"""
def __init__(self, fname, n=10, intraday=False):
""" """
self.fig = plt.figure(facecolor='white')
self.fig.canvas.set_window_title(u'期货数据分析')
self.nbar = n
self.cursors = []
self.data, = load_datas(n, intraday, fname)
self.axes = []
self.rax = plt.axes([0, 0.5, 0.08, 0.15])
self.radio = RadioButtons(self.rax, ('scatter', 'summary', 'summary2', 'entry', 'exit', 'simple'), active=0)
self.axes, self.cursors = scatter_analyze(self.fig, self.data)
self.radio.on_clicked(self.update)
def update(self, op):
for ax in self.axes:
self.fig.delaxes(ax)
for c in self.cursors:
del c
if op == "scatter":
print "scatter_analyze"
self.axes, self.cursors = scatter_analyze(self.fig, self.data)
elif op == "summary":
print "summary_analyze"
self.axes, self.cursors = summary_analyze(self.fig, self.data, self.nbar, 1)
elif op == "summary2":
print "summary2_analyze"
self.axes, self.cursors = summary_analyze(self.fig, self.data, self.nbar, 2)
elif op == "entry":
print "entry_analyze"
self.axes, self.cursors = entry_analyze(self.fig, self.data, self.nbar)
elif op == "exit":
print "exit_analyze"
self.axes, self.cursors = exit_analyze(self.fig, self.data, self.nbar)
elif op == "simple":
self.axes, self.cursors = simple_entry_analyze(self.fig, self.data, self.nbar)
#elif op == "hm":
#axes, cursors = follow_entry_analyze(fig, data)
#print "hm"
self.fig.canvas.draw()
def setup_canvas(self):
"""Create the figure and the axes for the plot and buttons."""
# Initialise the figure.
self.currentFigure = plt.figure()
self.axes = self.currentFigure.add_subplot(1, 1, 1)
# Create the image.
self.start_plotting(self.originalDataset)
# Create the class radio button.
classAxesLoc = plt.axes([0.05, 0.05, 0.07, 0.1 * round(len(self.classToColorMapping) / 3)], axisbg='0.85')
classAxesLoc.set_title('Class Options')
classRadio = RadioButtons(classAxesLoc, active=0, activecolor='black', labels=[i for i in sorted(self.classToColorMapping)])
classRadio.on_clicked(self.on_class_change)
# Create the reset button.
resetAxesLoc = plt.axes([0.05, 0.44, 0.07, 0.075], axisbg='white')
resetButton = Button(resetAxesLoc, 'Reset')
resetButton.on_clicked(self.on_reset)
# Create the recompute boundaries button.
recomputeAxesLoc = plt.axes([0.05, 0.54, 0.07, 0.075], axisbg='white')
recomputeButton = Button(recomputeAxesLoc, 'Recompute')
recomputeButton.on_clicked(self.on_recompute)
# Create the k choice button.
kAxesLoc = plt.axes([0.05, 0.65, 0.07, 0.15], axisbg='0.85')
kAxesLoc.set_title('K Options')
kRadio = RadioButtons(kAxesLoc, active=0, activecolor='black', labels=[1, 3, 5, 7])
kRadio.on_clicked(self.on_k_change)
# Create the add/delete radio button.
addDeleteAxesLoc = plt.axes([0.05, 0.85, 0.07, 0.1], axisbg='0.85')
addDeleteAxesLoc.set_title('Add/Delete Points')
addDeleteRadio = RadioButtons(addDeleteAxesLoc, active=1, activecolor='black', labels=['Add', 'Delete'])
addDeleteRadio.on_clicked(self.on_delete_change)
# Attach the mouse click event.
cid = self.currentFigure.canvas.mpl_connect('button_press_event', self.on_click)
# Display the figure maximised. These commands to maximise the figure are for the Qt4Agg backend. If a different backend is being used, then
# the maximisation command will likely need to be changed.
figManager = plt.get_current_fig_manager()
figManager.window.showMaximized()
plt.show()
# Disconnect the mouse click event.
self.currentFigure.canvas.mpl_disconnect(cid)
def _add_normalise_power_selector(self):
"""
Add a radio button to chose whether or not the power of all spectra
should be normalized to 1.
"""
pos_shp = [CONTOLS_START_X, 0.5, CONTROLS_WIDTH, CONTROLS_HEIGHT]
rax = self.figure.add_axes(pos_shp, axisbg=AXCOLOUR, title="Normalise")
np_tuple = ("yes", "no")
self.normalise_power_selector = RadioButtons(rax, np_tuple, active=np_tuple.index(self.normalise_power))
self.normalise_power_selector.on_clicked(self._update_normalise_power)
def filter_connect(self):
# user to change default parameters
self.cidSelectFreq = self.filterAxs['amVfreq'].get_figure().canvas.mpl_connect('button_press_event', self.getBandpassFreq)
# get order
self.bnorder = RadioButtons(self.filterAxs['ordr'], (1,2,3,4,5), active=1)
self.cidorder = self.bnorder.on_clicked(self.getButterOrder)
# get type of filter to use
self.bnband = RadioButtons(self.filterAxs['band'], ('bandpass','lowpass','highpass'))
self.cidband = self.bnband.on_clicked(self.getBandtype)
#add apply button. causes the filtered data to be applied
self.bnapply = Button(self.filterAxs['apply'], 'Apply')
self.cidapply = self.bnapply.on_clicked(self.applyFilter)
#add unapply button. causes the filtered data to be applied
self.bnunapply = Button(self.filterAxs['unapply'], 'Unapply')
self.cidunapply = self.bnunapply.on_clicked(self.unapplyFilter)
def _add_xscale_selector(self):
"""
Add a radio button to the figure for selecting which scaling the x-axes
should use.
"""
pos_shp = [CONTOLS_START_X, 0.8, CONTROLS_WIDTH, CONTROLS_HEIGHT]
rax = self.figure.add_axes(pos_shp, axisbg=AXCOLOUR, title="X Scale")
xscale_tuple = ("log", "linear")
self.xscale_selector = RadioButtons(rax, xscale_tuple, active=xscale_tuple.index(self.xscale))
self.xscale_selector.on_clicked(self._update_xscale)
def _add_mode_selector(self):
"""
Add a radio button to the figure for selecting which mode of the model
should be displayed.
"""
pos_shp = [CONTOLS_START_X, 0.07, CONTROLS_WIDTH, 0.1 + 0.002 * self.input_data.read_data_shape()[3]]
rax = self.figure.add_axes(pos_shp, axisbg=AXCOLOUR, title="Mode")
mode_tuple = tuple(range(self.input_data.read_data_shape()[3]))
self.mode_selector = RadioButtons(rax, mode_tuple, active=mode_tuple.index(self.mode))
self.mode_selector.on_clicked(self._update_mode)
def _create_plot_controls(self):
self._dbrax = plt.axes([0.12, 0.05, 0.13, 0.10])
self._dbradio = RadioButtons(self._dbrax, ('Amplitude', 'Phase'))
self._dbradio.on_clicked(self.set_plot_style)
self._rax = plt.axes([0.27, 0.03, 0.15, 0.20])
self._radio = RadioButtons(self._rax, ('Low Pass', 'High Pass', 'Band Pass', 'All Pass', 'Notch', 'Peak', 'Low Shelf', 'High Shelf'))
self._radio.on_clicked(self.set_biquad_type)
self._sfax = plt.axes([0.6, 0.19, 0.2, 0.03])
self._sqax = plt.axes([0.6, 0.12, 0.2, 0.03])
self._sdbax = plt.axes([0.6, 0.05, 0.2, 0.03])
self._fcslider = Slider(self._sfax, 'Cut-off frequency', 0, self._bq_fs/2, valinit = self._bq_fc)
self._qslider = Slider(self._sqax, 'Q factor', 0.01, 10.0, valinit = self._bq_q)
self._dbslider = Slider(self._sdbax, 'dB gain', -20.0, 20.0, valinit = self._bq_dbgain)
self._fcslider.on_changed(self.set_biquad_frequency_cutoff)
self._qslider.on_changed(self.set_biquad_q_factor)
self._dbslider.on_changed(self.set_biquad_dbgain)
def _add_mode_selector(self):
"""
Add a radio button to the figure for selecting which mode of the model
should be displayed.
"""
pos_shp = [0.02, 0.07, 0.04, 0.1 + 0.002 * self.model.number_of_modes]
rax = self.ipp_fig.add_axes(pos_shp, axisbg=AXCOLOUR, title="Mode")
mode_tuple = tuple(range(self.model.number_of_modes))
self.mode_selector = RadioButtons(rax, mode_tuple, active=0)
self.mode_selector.on_clicked(self._update_mode)
def _add_state_variable_selector(self):
"""
Generate radio selector buttons to set which state variable is
displayed on the x and y axis of the phase-plane plot.
"""
svx_ind = self.model.state_variables.index(self.svx)
svy_ind = self.model.state_variables.index(self.svy)
#State variable for the x axis
pos_shp = [0.08, 0.07, 0.065, 0.12 + 0.006 * self.model.nvar]
rax = self.ipp_fig.add_axes(pos_shp, axisbg=AXCOLOUR, title="x-axis")
self.state_variable_x = RadioButtons(rax, tuple(self.model.state_variables), active=svx_ind)
self.state_variable_x.on_clicked(self._update_svx)
#State variable for the y axis
pos_shp = [0.16, 0.07, 0.065, 0.12 + 0.006 * self.model.nvar]
rax = self.ipp_fig.add_axes(pos_shp, axisbg=AXCOLOUR, title="y-axis")
self.state_variable_y = RadioButtons(rax, tuple(self.model.state_variables), active=svy_ind)
self.state_variable_y.on_clicked(self._update_svy)
def plot(Z):
ax = plt.subplot(111)
plt.subplots_adjust(bottom=0.25)
ax.contour(flatperm2.pd(Z, 1, 1).T)
ax1 = plt.axes([0.125, 0.15, 0.775, 0.03])
ax2 = plt.axes([0.125, 0.05, 0.775, 0.03])
s1 = Slider(ax1, r'$\omega_1$', 0.1, 30.0, valinit=1)
s2 = Slider(ax2, r'$\omega_2$', 0.1, 10.0, valinit=1)
plt.show()
def update(val):
w1 = s1.val
w2 = s2.val
print((w1, w2))
ax.clear()
ax.contour(flatperm2.pd(Z, w1, w2).T)
# l.set_ydata(amp*sin(2*pi*freq*t))
plt.draw()
s1.on_changed(update)
s2.on_changed(update)
return
resetax = axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
sfreq.reset()
samp.reset()
button.on_clicked(reset)
rax = axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
def colorfunc(label):
l.set_color(label)
draw()
radio.on_clicked(colorfunc)
show()
def setFigure(self):
fig = py.figure(figsize=(5,5))
axs = self.addAxes(fig)
self.bntext = py.Button(axs['text'], 'Text')
self.bnchange= py.Button(axs['change'], 'Change')
self.bnband = RadioButtons(axs['band'], ('low','high','double'))
self.bnBandLabel = py.Button(axs['band_label'], 'low')
return fig, axs
def make_buttons(self):
axcolor = 'lightgoldenrodyellow'
rax = plt.axes([0.05, 0.05, 0.15, 0.15], axisbg=axcolor)
radio = RadioButtons(rax, ('x1', 'x5', 'x10'))
radio.on_clicked(self.set_multiplier)
axprev = plt.axes([0.7, 0.05, 0.1, 0.075])
axnext = plt.axes([0.81, 0.05, 0.1, 0.075])
axup = plt.axes([0.59, 0.05, 0.1, 0.075])
axdown = plt.axes([0.48, 0.05, 0.1, 0.075])
axdone = plt.axes([0.30, 0.05, 0.1, 0.075])
bnext = Button(axnext, 'Right')
bnext.on_clicked(self.next)
bprev = Button(axprev, 'Left')
bprev.on_clicked(self.prev)
bup = Button(axup, 'Up')
bup.on_clicked(self.up)
bdown = Button(axdown, 'Down')
bdown.on_clicked(self.down)
bdone = Button(axdone, 'Done')
bdone.on_clicked(self.done)
def _add_variable_selector(self):
"""
Generate radio selector buttons to set which state variable is
displayed.
"""
noc = self.input_data.read_data_shape()[1] # number of choices
#State variable for the x axis
pos_shp = [CONTOLS_START_X, 0.22, CONTROLS_WIDTH, 0.12 + 0.008 * noc]
rax = self.figure.add_axes(pos_shp, axisbg=AXCOLOUR, title="State Variable")
self.variable_selector = RadioButtons(rax, tuple(range(noc)), active=0)
self.variable_selector.on_clicked(self._update_variable)
def _add_spectrum_mode_selector(self):
"""
Add a radio button to the figure for selecting which part of the spectrum
should be displayed: 0:real, 1:imag, 2:abs
"""
pos_shp = [CONTOLS_START_X, 0.07, CONTROLS_WIDTH, 0.1 + 0.002 * 3]
rax = self.figure.add_axes(pos_shp, axisbg=AXCOLOUR, title="Spectrum Mode")
spectrum_mode_tuple = ("Re", "Imag", "Abs")
self.spectrum_mode_selector = RadioButtons(rax, spectrum_mode_tuple,
active=spectrum_mode_tuple.index(self.spectrum))
self.spectrum_mode_selector.on_clicked(self._update_spectrum_mode)
class DoS():
"""
Definition of the density of state class
"""
def __init__(self,
bandarrays=None,
energies=None,
evals=None,
units='eV',
label='1',
sigma=0.2,
npts=2500,
fermi_level=None,
norm=1.0,
sdos=None,
e_min=None,
e_max=None):
"""
Extract a quantity which is associated to the DoS, that can be plotted
"""
import numpy as np
self.ens = []
self.labels = []
self.ef = None
# self.norms=[]
self.npts = npts
if e_min is not None:
self.e_min = e_min
else:
self.e_min = 1.e100
if e_max is not None:
self.e_max = e_max
else:
self.e_max = -1.e100
if bandarrays is not None:
self.append_from_bandarray(bandarrays, label)
if evals is not None:
self.append_from_dict(evals, label)
if energies is not None:
self.append(
np.array([energies]),
label=label,
units=units,
norm=(np.array([norm]) if isinstance(norm, float) else norm))
self.sigma = sigma
self.fermi_level(fermi_level, units=units)
if sdos is not None:
self._embed_sdos(sdos)
def _embed_sdos(self, sdos):
self.sdos = []
for i, xdos in enumerate(sdos):
self.sdos.append({'coord': xdos['coord']})
jdos = 0
for subspin in xdos['dos']:
if len(subspin[0]) == 0:
continue
d = {'doslist': subspin}
try:
self.ens[jdos]['sdos'].append(d)
except KeyError:
self.ens[jdos]['sdos'] = [d]
jdos += 1
def append_from_bandarray(self, bandarrays, label):
"""
Add a new band array to the previous DoS. Important for kpoints DOS
"""
import numpy as np
for jspin in range(2):
kptlists, lbl = _bandarray_to_data(jspin, bandarrays)
self.append(np.array(kptlists[0]),
label=label + lbl,
units='AU',
norm=np.array(kptlists[1]))
def append_from_dict(self, evals, label):
import numpy as np
"Get the energies from the different flavours given by the dict"
evs = [[], []]
ef = None
for ev in evals:
occ = self.get_ev(ev, ['e_occ', 'e_occupied'])
if occ:
ef = max(occ)
vrt = self.get_ev(ev, ['e_vrt', 'e_virt'])
eigen = False
if occ:
eigen = occ
if vrt:
eigen = vrt
if not eigen:
eigen = self.get_ev(ev)
if not occ and not vrt and eigen:
ef = max(eigen)
if not eigen:
continue
for i, e in enumerate(eigen):
if e:
evs[i].append(e)
for i, energs in enumerate(evs):
if len(energs) == 0:
continue
self.append(np.array(energs),
label=label,
units='AU',
norm=1.0 - 2.0 * i)
if ef:
self.fermi_level(ef, units='AU')
def get_ev(self, ev, keys=None):
"Get the correct list of the energies for this eigenvalue"
res = False
if keys is None:
ener = ev.get('e')
spin = ev.get('s')
if ener and spin == 1:
res = [ener]
elif ener and spin == -1:
res = [None, ener]
else:
for k in keys:
if k in ev:
res = ev[k]
if not isinstance(res, list):
res = [res]
break
return res
def append(self, energies, label=None, units='eV', norm=1.0):
if not isinstance(norm, float) and len(norm) == 0:
return
dos = self.conversion_factor(units) * energies
self.ens.append({'dos': DiracSuperposition(dos, wgts=norm)})
lbl = label if label is not None else str(len(self.labels) + 1)
self.labels.append(lbl)
# self.norms.append(norm)
self.range = self._set_range()
def conversion_factor(self, units):
if units == 'AU':
fac = AU_eV
elif units == 'eV':
fac = 1.0
else:
raise ValueError('Unrecognized units (' + units + ')')
return fac
def fermi_level(self, fermi_level, units='eV'):
if fermi_level is not None:
self.ef = fermi_level * self.conversion_factor(units)
def _set_range(self, npts=None, e_min=None, e_max=None):
import numpy as np
if npts is None:
npts = self.npts
if e_min is None:
e_min = self.e_min
if e_max is None:
e_max = self.e_max
for dos in self.ens:
mn, mx = dos['dos'].xlim
e_min = min(e_min, mn)
e_max = max(e_max, mx)
return np.arange(e_min, e_max, (e_max - e_min) / npts)
def curve(self, dos, norm, sigma=None):
import numpy as np
if sigma is None:
sigma = self.sigma
nrm = np.sqrt(2.0 * np.pi) * sigma / norm
dos_g = []
for e_i in self.range:
if len(dos.shape) == 2:
nkpt = dos.shape[0]
value = 0.0
for ikpt in range(nkpt):
value += np.sum(
np.exp(-(e_i - dos[ikpt, :])**2 / (2.0 * sigma**2)) /
nrm[ikpt])
else:
value = np.sum(
np.exp(-(e_i - dos[:])**2 / (2.0 * sigma**2)) / nrm)
# Append data corresponding to each energy grid
dos_g.append(value)
return np.array(dos_g)
def dump(self, sigma=None):
"For Gnuplot"
if sigma is None:
sigma = self.sigma
# data=[self.curve(dos,norm=self.norms[i],sigma=sigma)
# for i,dos in enumerate(self.ens)]
data = [
dos['dos'].curve(self.range, sigma=sigma)[1] for dos in self.ens
]
for i, e in enumerate(self.range):
safe_print(e, ' '.join(map(str, [d[i] for d in data])))
def plot(self,
sigma=None,
legend=True,
xlmin=None,
xlmax=None,
ylmin=None,
ylmax=None,
width=6.4,
height=4.8):
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider # , Button, RadioButtons
if sigma is None:
sigma = self.sigma
self.fig, self.ax1 = plt.subplots(figsize=(width, height))
self.plotl = []
for i, dos in enumerate(self.ens):
# self.plotl.append(self.ax1.plot(self.range,self.curve(dos,norm=self.norms[i],sigma=sigma),label=self.labels[i]))
self.plotl.append(
self.ax1.plot(*dos['dos'].curve(self.range, sigma=sigma),
label=self.labels[i]))
if xlmax is not None:
plt.xlim(xmax=xlmax)
if xlmin is not None:
plt.xlim(xmin=xlmin)
if ylmax is not None:
plt.ylim(ymax=ylmax)
if ylmin is not None:
plt.ylim(ymin=ylmin)
plt.xlabel('Energy [eV]', fontsize=18)
plt.ylabel('DoS', fontsize=18)
if self.ef is not None:
plt.axvline(self.ef, color='k', linestyle='--')
# self.ax1.annotate('Fermi level', xy=(self.ef,2),
# xytext=(self.ef, 10),
# arrowprops=dict(facecolor='white', shrink=0.05),
# )
if len(self.labels) > 1 and legend:
plt.legend(loc='best')
axcolor = 'lightgoldenrodyellow'
try:
axsigma = plt.axes([0.2, 0.93, 0.65, 0.03], facecolor=axcolor)
except AttributeError:
axsigma = plt.axes([0.2, 0.93, 0.65, 0.03], axisbg=axcolor)
self.ssig = Slider(axsigma, 'Smearing', 0.0, 0.4, valinit=sigma)
self.ssig.on_changed(self.update)
if hasattr(self, 'sdos') and self.sdos:
self._set_sdos_selector()
self._set_sdos()
plt.show()
def _set_sdos_selector(self):
import matplotlib.pyplot as plt
from matplotlib.widgets import RadioButtons
self.sdos_selector = RadioButtons(plt.axes(
[0.93, 0.05, 0.04, 0.11], axisbg='lightgoldenrodyellow'),
('x', 'y', 'z'),
active=1)
self.isdos = 1
self.sdos_selector.on_clicked(self._update_sdos)
def _set_sdos(self):
import numpy
xs = self.sdos[self.isdos]['coord']
self._set_sdos_sliders(numpy.min(xs), numpy.max(xs))
self._update_sdos(0.0) # fake value as it is unused
def _sdos_curve(self, sdos, vmin, vmax):
import numpy
xs = self.sdos[self.isdos]['coord']
imin = numpy.argmin(numpy.abs(xs - vmin))
imax = numpy.argmin(numpy.abs(xs - vmax))
doslist = sdos[self.isdos]['doslist']
# norms=self.sdos[self.isdos]['norms'][ispin]
tocurve = [0.0 for i in doslist[imin]]
for d in doslist[imin:imax + 1]:
tocurve = [t + dd for t, dd in zip(tocurve, d)]
# tocurve=numpy.sum([ d[ispin] for d in doslist[imin:imax+1]],axis=0)
return tocurve
# float(len(xs))/float(imax+1-imin)*tocurve,norms
def _update_sdos(self, val):
isdos = self.isdos
if val == 'x':
isdos = 0
elif val == 'y':
isdos = 1
elif val == 'z':
isdos = 2
if isdos != self.isdos:
self.isdos = isdos
self._set_sdos()
vmin, vmax = (s.val for s in self.ssdos)
if vmax < vmin:
self.ssdos[1].set_val(vmin)
vmax = vmin
if vmin > vmax:
self.ssdos[0].set_val(vmax)
vmin = vmax
# now plot the sdos curve associated to the given value
sig = self.ssig.val
curves = []
for dos in self.ens:
if 'sdos' not in dos:
continue
renorms = self._sdos_curve(dos['sdos'], vmin, vmax)
curve = dos['dos'].curve(self.range, sigma=sig, wgts=renorms)
curves.append(curve)
if hasattr(self, '_sdos_plots'):
for pl, curve in zip(self._sdos_plots, curves):
pl[0].set_ydata(curve[1])
else:
self._sdos_plots = []
for c in curves:
self._sdos_plots.append(self.ax1.plot(*c, label='sdos'))
self.ax1.relim()
self.ax1.autoscale_view()
self.fig.canvas.draw_idle()
def _set_sdos_sliders(self, cmin, cmax):
import matplotlib.pyplot as plt
from futile.Figures import VertSlider
if hasattr(self, 'ssdos'):
self.ssdos[0].ax.clear()
self.ssdos[0].__init__(self.ssdos[0].ax,
'SDos',
cmin,
cmax,
valinit=cmin)
self.ssdos[1].ax.clear()
self.ssdos[1].__init__(self.ssdos[1].ax,
'',
cmin,
cmax,
valinit=cmax)
else:
axcolor = 'red'
axmin = plt.axes([0.93, 0.2, 0.02, 0.65], axisbg=axcolor)
axmax = plt.axes([0.95, 0.2, 0.02, 0.65], axisbg=axcolor)
self.ssdos = [
VertSlider(axmin, 'SDos', cmin, cmax, valinit=cmin),
VertSlider(axmax, '', cmin, cmax, valinit=cmax)
]
self.ssdos[0].valtext.set_ha('right')
self.ssdos[1].valtext.set_ha('left')
self.ssdos[0].on_changed(self._update_sdos)
self.ssdos[1].on_changed(self._update_sdos)
def update(self, val):
sig = self.ssig.val
for i, dos in enumerate(self.ens):
self.plotl[i][0].set_ydata(dos['dos'].curve(self.range,
sigma=sig)[1])
# self.plotl[i][0].set_ydata(self.curve(dos,norm=self.norms[i],sigma=sig))
self.ax1.relim()
self.ax1.autoscale_view()
self.fig.canvas.draw_idle()
states[0] = (x+1j*y)*k0 + z*k1
arrows[0] = update_arrow(states[0],arrows[0])
update_final_state()
return True
fig.canvas.mpl_connect('button_press_event',on_click_handler)
axA = fig.add_axes([.2,.9,.6,.05])
slA = Slider(axA,'Angle',-180,180,valinit=360*gate[1])
def update_angle(value):
gate[1] = value/360.
update_final_state()
slA.on_changed(update_angle)
axR = fig.add_axes([.01,.88,.1,.1])
gate_dict = odict([('X',GateX),('Y',GateY),('Z',GateZ)])
rbR = RadioButtons(axR,tuple(gate_dict),active=2)
def update_gate(value):
gate[0] = gate_dict[value]
update_final_state()
rbR.on_clicked(update_gate)
axI = fig.add_axes([.01,.6,.1,.25])
sq2 = .5*np.sqrt(2.)
vectors_dict = odict([('0',(ax0,0,1)),('1',(ax1,0,1)),\
('+',(ax0,0,sq2)),('-',(ax0,0,-sq2)),\
('0+i1',(ax0,sq2,0)),('0-i1',(ax0,-sq2,0))])
# ('0+i1',(ax1,-sq2,0)),('0-i1',(ax1,sq2,0))])
rbI = RadioButtons(axI,tuple(vectors_dict),active=0)
def update_initial(value):
ax,xd,yd=vectors_dict[value]
update_initial_state(axes=ax,button=3,xdata=xd,ydata=yd)
plt.rcParams["figure.figsize"] = 16, 2
f2 = plt.figure(2)
f2.canvas.set_window_title('Harmonograph Controls')
ax2 = f2.add_subplot(111)
plt.axis('off')
plt.subplots_adjust(left=0.0, right=1.0, top=1.0, bottom=0.0)
def xprint(name, value): # convenience function to print params.
print(name + ' '.join(['%.3f' % x for x in value]))
# Radio buttons for pendulum selector
pend = plt.axes([0.0, 0.0, 0.1, 0.8])
radio = RadioButtons(pend, ('1', '2', '3', '4'))
p = 0
update = True
def pensel(label): # Pendulum selector callback
global p, update
pendict = {'1': 0, '2': 1, '3': 2, '4': 3}
p = pendict[label]
update = False
Xsa.set_val(ax[p])
Xsf.set_val(fx[p])
Xsp.set_val(px[p])
Ysa.set_val(ay[p])
Ysf.set_val(fy[p])
fig.canvas.draw_idle()
sdist.on_changed(update)
sangle.on_changed(update)
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
sdist.reset()
sangle.reset()
button.on_clicked(reset)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], axisbg=axcolor)
radio = RadioButtons(rax, (0, 1, 2, 3), active=0)
def colorfunc(label):
global currentLDR
currentLDR = int(label)
update(0)
radio.on_clicked(colorfunc)
plt.show()
plt.close(fig)
def evaluateError(angle, distance, m1, m2, m3, m4):
offset = 45.
angle += offset
stemp.set_val(temp)
l.set_ydata((331 + 0.6 * temp) / t)
fig.canvas.draw_idle()
sspeed.on_changed(updateSpeed)
stemp.on_changed(updateTemp)
resetax = plt.axes([0.0, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
sspeed.reset()
stemp.reset()
button.on_clicked(reset)
rax = plt.axes([0.01, 0.7, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('yellow', 'pink', 'green'), active=0)
def colorfunc(label):
l.set_color(label)
fig.canvas.draw_idle()
radio.on_clicked(colorfunc)
plt.show()
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
global pwm, freq, activeButton
pwm = a0
freq = f0
activeButton = 0
ESP8266_send()
sfreq.reset()
srpm.reset()
button.on_clicked(reset)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('BUZZER', 'LED'), active=0)
def colorfunc(label):
global activeButton
if label == "BUZZER":
activeButton = 0
else:
activeButton = 1
ESP8266_send()
radio.on_clicked(colorfunc)
plt.show()
def reset(event):
for i in np.arange(nbeads):
slvec[i].reset()
savec[i].reset()
swvec[i].reset()
button.on_clicked(reset)
rax = axes([0.025, 0.3, 0.12, 0.50], axisbg=axcolor, aspect='equal')
blabs = []
for i in np.arange(1, ncases + 1):
blabs.append('Case {0}'.format(i))
#radio = RadioButtons(rax, ['Case 1', 'Case 2', 'Case 3'], active=0)
radio = RadioButtons(rax, blabs, active=0)
def colorfunc(label):
datakey = int(label[-2:])
per0, dp0 = test_data(datakey - 1)
l0.set_xdata(per0)
l0.set_ydata(dp0)
#l.set_color(label)
draw()
radio.on_clicked(colorfunc)
show()
def poly_plots(snrs):
for snr in snrs:
print "Fitting polygons and sources to " + snr.name
white = fits.open("white/" + snr.name + ".fits")
red = fits.open("red/rpj/" + snr.name + ".fits")
green = fits.open("green/rpj/" + snr.name + ".fits")
blue = fits.open("blue/rpj/" + snr.name + ".fits")
white_data = white[0].data
red_data = red[0].data
green_data = green[0].data
blue_data = blue[0].data
# rgb = np.dstack([red_data,green_data,blue_data])
xmax = white[0].header["NAXIS1"]
ymax = white[0].header["NAXIS2"]
w = wcs.WCS(white[0].header)
try:
pix2deg = white[0].header["CD2_2"]
except KeyError:
pix2deg = white[0].header["CDELT2"]
# Divide by maximum value to normalise
# rgb = normalize(rgb, np.nanmin(rgb), np.nanmax(rgb))
# Percentile interval for image normalisation
pct = 97.0
interval = PercentileInterval(pct)
# vmin, vmax = interval.get_limits(data)
# stretch = AsinhStretch(a=0.1)
i = interval.get_limits(red_data)
r = normalize(red_data, *i)
i = interval.get_limits(green_data)
g = normalize(green_data, *i)
i = interval.get_limits(blue_data)
b = normalize(blue_data, *i)
rgb = np.dstack([r, g, b])
rgb[np.isnan(rgb)] = 0.0
def update(val):
vmin = svmin.val
vmax = svmax.val
img_white.set_clim([svmin.val, svmax.val])
fig.canvas.draw()
fig = newfigure(figsize=(10, 5))
ax_white = fig.add_axes([0.05, 0.15, 0.4, 0.8])
ax_rgb = fig.add_axes([0.55, 0.15, 0.4, 0.8])
img_rgb = ax_rgb.imshow(rgb)
img_white = ax_white.imshow(white_data, cmap="gray")
cbaxes = fig.add_axes([0.45, 0.1, 0.03, 0.85])
cb = plt.colorbar(img_white, cax=cbaxes, orientation="vertical")
axcolor = 'white'
axmin = fig.add_axes([0.05, 0.05, 0.1, 0.02], axisbg=axcolor)
axmax = fig.add_axes([0.24, 0.05, 0.1, 0.02], axisbg=axcolor)
# vmin0 = np.min(white_data)
# vmax0 = np.max(white_data)
vmin0, vmax0 = interval.get_limits(white_data)
# include the slider: cribbed from https://stackoverflow.com/questions/5611805/using-matplotlib-slider-widget-to-change-clim-in-image
svmin = Slider(axmin, "vmin", 2 * vmin0, -2 * vmin0, valinit=vmin0)
svmax = Slider(axmax, "vmax", -2 * vmax0, 2 * vmax0, valinit=vmax0)
svmin.on_changed(update)
svmax.on_changed(update)
fig.suptitle(
'Left-click = select source, middle-click = source subtract, right-click = select region to exclude from background calculation'
)
centerx, centery = w.wcs_world2pix(snr.loc.fk5.ra.value,
snr.loc.fk5.dec.value, 0)
print centerx, centery
major, minor = snr.maj / (2 * pix2deg), snr.min / (2 * pix2deg)
for ax in ax_white, ax_rgb:
# If you don't do this, it automatically zooms out when you first click on the plot
ax.set_xlim(0, xmax)
ax.set_ylim(0, ymax)
# Plot rough size of SNR -- DAG doesn't include pa information so neither can I
ax.plot([centerx, centerx], [centery - major, centery + major],
**reticsnr)
ax.plot([centerx - minor, centerx + minor], [centery, centery],
**reticsnr)
polypick = PolyPick(ax_white)
rax = fig.add_axes([0.6, 0.0, 0.15, 0.10])
radio = RadioButtons(rax, ("white", "rgb"), active=0)
def changeax(axl):
if axl == "white":
polypick.ax = ax_white
plt.sca(ax_white)
elif axl == "rgb":
polypick.ax = ax_rgb
plt.sca(ax_rgb)
fig.canvas.draw_idle()
radio.on_clicked(changeax)
plt.show()
# Export pixel co-ordinates as WCS co-ordinates in order to use on any arbitrary image, and save for later
polygon = Coords()
sources = Coords()
exclude = Coords()
if len(polypick.coords.x):
polygon.x, polygon.y = w.wcs_pix2world(
zip(polypick.coords.x, polypick.coords.y), 0).transpose()
else:
# User has got bored of picking polygons and wants to exit this loop
print "No polygon detected; leaving polygon-drawing mode."
break
if len(polypick.points.x):
sources.x, sources.y = w.wcs_pix2world(
zip(polypick.points.x, polypick.points.y), 0).transpose()
if len(polypick.exclude.x):
exclude.x, exclude.y = w.wcs_pix2world(
zip(polypick.exclude.x, polypick.exclude.y), 0).transpose()
# NB: overwrites data for any old measurements for this live object
snr.polygon = polygon
snr.sources = sources
snr.exclude = exclude
return snrs
def plot_setup(self, pre_fig=None):
# Setting the figure and unpacking the different subplots to variables
if not self.parent.show_second:
self.fig, ((self.pendulum_plot, self.angle_plot),
(self.phase_plot, self.vel_plot)) = subplots(
2, 2, gridspec_kw={'width_ratios': [1, 2.5]})
else:
self.fig = figure()
self.gs = gridspec.GridSpec(ncols=5 * 4, nrows=3, figure=self.fig)
self.pendulum_plot = self.fig.add_subplot(self.gs[0, 0:2 * 4])
self.angle_plot = self.fig.add_subplot(self.gs[0, 2 * 4 + 1:])
self.phase_plot = self.fig.add_subplot(self.gs[1, 0:2 * 4])
self.vel_plot = self.fig.add_subplot(self.gs[1, 2 * 4 + 1:])
self.angle_plot_diff = self.fig.add_subplot(self.gs[2, 1:10])
self.vel_plot_diff = self.fig.add_subplot(self.gs[2, 11:])
subplots_adjust(left=p_left,
right=p_right,
top=p_top,
bottom=p_bot,
hspace=h_space,
wspace=w_space)
self.fig.set_facecolor(Color.BACKGROUND)
self.pendulum_plot.set(aspect='equal')
self.phase_plot.set(aspect='equal')
# Setting axes for the sliders and buttons
self.ax_rod_length = axes([
0.815 + slider_pad, 0.73, slider_w - 0.005, p_top - p_bot -
(0.75 - 0.10)
],
facecolor=Color.SLIDER_INACTIVE)
self.ax_bob_mass = axes([
0.815 + slider_pad * 2 + slider_w - 0.005, 0.73, slider_w - 0.005,
p_top - p_bot - (0.75 - 0.10)
],
facecolor=Color.SLIDER_INACTIVE)
self.ax_dt = axes([
0.815 + slider_pad * 3 + 2 * (slider_w - 0.005), 0.73,
slider_w - 0.005, p_top - p_bot - (0.75 - 0.10)
],
facecolor=Color.SLIDER_INACTIVE)
self.ax_Fd = axes([
0.815 + slider_pad * 4 + 3 * (slider_w - 0.005), 0.73,
slider_w - 0.005, p_top - p_bot - (0.75 - 0.10)
],
facecolor=Color.SLIDER_INACTIVE)
self.ax_Om_d = axes([
0.815 + slider_pad * 5 + 4 * (slider_w - 0.005), 0.73,
slider_w - 0.005, p_top - p_bot - (0.75 - 0.10)
],
facecolor=Color.SLIDER_INACTIVE)
self.ax_dampening = axes(
[0.82 + slider_pad, p_bot + 0.315 + button_w, button_w, button_w],
facecolor=Color.RADIO_BACKGROUND,
title="Dampening type")
self.ax_second_calc = axes(
[0.82 + slider_pad, p_bot + 0.34, button_w, button_w - 0.065],
facecolor=Color.RADIO_BACKGROUND,
title="Second trajectory")
self.ax_Dtheta = axes(
[0.835 + slider_pad, p_bot + 0.30, button_w - 0.055, slider_w],
facecolor=Color.SLIDER_INACTIVE)
self.ax_anim_params = axes(
[0.82 + slider_pad, p_bot + 0.105, button_w, button_w],
facecolor=Color.RADIO_BACKGROUND,
title="Animation speed")
self.ax_apply_run = axes(
[0.82 + slider_pad, p_bot + 0.05, button_w, slider_w * 2])
self.ax_reset = axes(
[0.82 + slider_pad, p_bot, button_w, slider_w * 2])
self.slider_rod_length = Slider(self.ax_rod_length,
"l",
5,
15,
color=Color.SLIDER_ACTIVE,
valinit=self.parent.rod_length,
valstep=0.1,
orientation="vertical")
self.slider_bob_mass = Slider(self.ax_bob_mass,
"m",
0.1,
10.0,
color=Color.SLIDER_ACTIVE,
valinit=self.parent.bob_mass,
valstep=0.1,
orientation="vertical")
self.slider_dt = Slider(self.ax_dt,
"dt",
0.001,
0.3,
color=Color.SLIDER_ACTIVE,
valinit=self.parent.dt,
valstep=0.001,
orientation="vertical",
valfmt="%1.3f")
self.slider_Fd = Slider(self.ax_Fd,
"$F_D$",
0.0,
2,
color=Color.SLIDER_ACTIVE,
valinit=self.parent.F_d,
valstep=0.1,
orientation="vertical",
valfmt="%1.1f")
self.slider_Om_d = Slider(self.ax_Om_d,
"$\Omega_D$",
0.0,
2 * np.pi,
color=Color.SLIDER_ACTIVE,
valinit=self.parent.Om_d,
valstep=0.01,
orientation="vertical",
valfmt="%1.2f")
self.radio_damping = RadioButtons(
self.ax_dampening,
["underdamped", "overdamped", "critical damping", "none"],
active=self.parent.dampening_index,
activecolor=Color.RADIO_SELECTED)
for i in self.radio_damping.labels:
i.set_fontsize("small")
self.radio_second_calc = RadioButtons(self.ax_second_calc,
["No", "Yes"],
active=self.parent.show_second,
activecolor=Color.RADIO_SELECTED)
for i in self.radio_second_calc.labels:
i.set_fontsize("small")
self.slider_Dtheta = Slider(self.ax_Dtheta,
"$\Delta\\theta$",
0.0,
0.01,
color=Color.SLIDER_ACTIVE,
valinit=self.parent.init_Dtheta,
valstep=0.0001,
orientation="horizontal",
valfmt="%1.4f")
self.radio_anim_params = RadioButtons(
self.ax_anim_params, ["$1/2$x", "1x", "4x", "10x", "No animation"],
active=self.parent.speed_index,
activecolor=Color.RADIO_SELECTED)
for i in self.radio_anim_params.labels:
i.set_fontsize("small")
self.button_apply_run = Button(self.ax_apply_run,
"Apply and run..",
color=Color.BUTTON_OFF_HOVER,
hovercolor=Color.BUTTON_ON_HOVER)
self.button_reset_apply = Button(self.ax_reset,
"Reset and run..",
color=Color.BUTTON_OFF_HOVER,
hovercolor=Color.BUTTON_ON_HOVER)
def _GUI_display(self, redshift_est, ztest, corr_val, test_waveform,
template_waveform):
wave = test_waveform.masked_wave
flux_sci = test_waveform.masked_flux
'''Display the spectrum and reference lines.'''
self.fig = plt.figure(figsize=(10, 8))
gs = gridspec.GridSpec(2, 1, height_ratios=[2, 1])
ax2 = plt.subplot(gs[0])
ax = plt.subplot(gs[1])
plt.subplots_adjust(top=0.96, bottom=0.04, left=0.04, right=0.92)
figManager = plt.get_current_fig_manager()
figManager.window.showMaximized()
ax.plot(ztest, corr_val, 'b')
pspec_corr = ax.axvline(redshift_est, color='k', ls='--')
ax.set_xlabel('Redshift')
ax.set_ylabel('Correlation')
self.pspec, = ax2.plot(wave, flux_sci)
ax2.set_ylim(np.min(flux_sci), np.max(flux_sci))
ax2.set_xlim(wave[0], wave[-1])
ax2.plot()
# Plot sky lines:
# Red = HK
# Purple = OII, Halpha
# Black = sky
# Blue = Emission
# Orange = Absorption
vlin_pspecs = plot_skylines(ax2, redshift_est)
# Include information in plot
self.fig.text(0.923,
0.9,
'%s' % template_waveform.name,
bbox=dict(facecolor='white', alpha=1.),
fontsize=18)
self.fig.text(0.922,
0.8,
'Blue/ = Emission\nPurple Lines',
bbox=dict(facecolor='white', alpha=1.))
self.fig.text(0.922,
0.78,
'Red/ = Absorption\nOrange Lines',
bbox=dict(facecolor='white', alpha=1.))
self.fig.text(0.922,
0.74,
'Black = Sky\n Lines',
bbox=dict(facecolor='white', alpha=1.))
# from left, from bottom, width, height
rax = plt.axes([0.925, 0.43, 0.07, 0.22])
# Setup User input box on plot
if self.qualityval == 1:
radio = RadioButtons(
rax, ('1 - No Clue ', '2 - Slight\n Chance',
'3 - Maybe', '4 - Probably', '5 - Clear'))
else:
radio = RadioButtons(
rax, ('1 - No Clue ', '2 - Slight\n Chance',
'3 - Maybe', '4 - Probably', '5 - Clear'),
active=1)
def qualfunc(label):
if label == '5 - Clear':
self.qualityval = 5
elif label == '4 - Probably':
self.qualityval = 4
elif label == '3 - Maybe':
self.qualityval = 3
elif label == '2 - Slight\n Chance':
self.qualityval = 2
else:
self.qualityval = 1
radio.on_clicked(qualfunc)
# from left, from bottom, width, height
closeax = plt.axes([0.93, 0.18, 0.06, 0.08])
button = Button(closeax, 'Accept & Close', hovercolor='0.975')
def closeplot(event):
plt.close()
button.on_clicked(closeplot)
skip_spec_ax = plt.axes([0.93, 0.94, 0.06, 0.04])
skip_button = Button(skip_spec_ax, 'skip spectra', hovercolor='0.975')
def skip_spec(event):
plt.close()
self.qualityval = 0
skip_button.on_clicked(skip_spec)
#ax2.set_xlim(self.lower_w,self.upper_w)
ax2.set_xlabel('Wavelength (A)')
ax2.set_ylabel('Counts')
# Setup the classification
if self.first_pass:
line_est = Estimateline(self.pspec, ax2, self.uline_n)
else:
spectra2 = DragSpectra(vlin_pspecs, pspec_corr, redshift_est, ax2)
self.fig.canvas.mpl_connect('motion_notify_event',
spectra2.on_motion)
self.fig.canvas.mpl_connect('button_press_event',
spectra2.on_press)
self.fig.canvas.mpl_connect('button_release_event',
spectra2.on_release)
plt.show()
if self.qualityval == 0:
return None
elif self.first_pass:
if line_est.lam == 0:
return None
else:
return line_est.lam / self.uline - 1.0
else:
return spectra2.finalz
class AlignmentInterface(BaseReviewInterface):
"""Custom interface for rating the quality of alignment between two 3d MR images"""
def __init__(self,
fig,
rating_list=cfg.default_rating_list,
next_button_callback=None,
quit_button_callback=None,
change_vis_type_callback=None,
toggle_animation_callback=None,
show_first_image_callback=None,
show_second_image_callback=None,
alpha_seg=cfg.default_alpha_seg):
"""Constructor"""
super().__init__(fig, None, next_button_callback, quit_button_callback)
self.rating_list = rating_list
self.latest_alpha_seg = alpha_seg
self.prev_axis = None
self.prev_ax_pos = None
self.zoomed_in = False
self.next_button_callback = next_button_callback
self.quit_button_callback = quit_button_callback
self.change_vis_type_callback = change_vis_type_callback
self.toggle_animation_callback = toggle_animation_callback
self.show_first_image_callback = show_first_image_callback
self.show_second_image_callback = show_second_image_callback
self.add_radio_buttons_rating()
self.add_radio_buttons_comparison_method()
# this list of artists to be populated later
# makes to handy to clean them all
self.data_handles = list()
self.unzoomable_axes = [
self.radio_bt_rating.ax,
self.radio_bt_vis_type.ax,
self.text_box.ax,
self.bt_next.ax,
self.bt_quit.ax,
]
def add_radio_buttons_comparison_method(self):
ax_radio = plt.axes(cfg.position_alignment_radio_button_method,
facecolor=cfg.color_rating_axis,
aspect='equal')
self.radio_bt_vis_type = RadioButtons(ax_radio,
cfg.choices_alignment_comparison,
active=None,
activecolor='orange')
self.radio_bt_vis_type.on_clicked(self.change_vis_type_callback)
for txt_lbl in self.radio_bt_vis_type.labels:
txt_lbl.set(color=cfg.text_option_color, fontweight='normal')
for circ in self.radio_bt_vis_type.circles:
circ.set(radius=0.06)
def add_radio_buttons_rating(self):
ax_radio = plt.axes(cfg.position_alignment_radio_button_rating,
facecolor=cfg.color_rating_axis,
aspect='equal')
self.radio_bt_rating = RadioButtons(ax_radio,
self.rating_list,
active=None,
activecolor='orange')
self.radio_bt_rating.on_clicked(self.save_rating)
for txt_lbl in self.radio_bt_rating.labels:
txt_lbl.set(color=cfg.text_option_color, fontweight='normal')
for circ in self.radio_bt_rating.circles:
circ.set(radius=0.06)
def save_rating(self, label):
"""Update the rating"""
# print(' rating {}'.format(label))
self.user_rating = label
def get_ratings(self):
"""Returns the final set of checked ratings"""
return self.user_rating
def allowed_to_advance(self):
"""
Method to ensure work is done for current iteration,
before allowing the user to advance to next subject.
Returns False if atleast one of the following conditions are not met:
Atleast Checkbox is checked
"""
return self.radio_bt_rating.value_selected is not None
def reset_figure(self):
"Resets the figure to prepare it for display of next subject."
self.clear_data()
self.clear_radio_buttons()
self.clear_notes_annot()
def clear_data(self):
"""clearing all data/image handles"""
if self.data_handles:
for artist in self.data_handles:
artist.remove()
# resetting it
self.data_handles = list()
def clear_radio_buttons(self):
"""Clears the radio button"""
# enabling default rating encourages lazy advancing without review
# self.radio_bt_rating.set_active(cfg.index_freesurfer_default_rating)
for index, label in enumerate(self.radio_bt_rating.labels):
if label.get_text() == self.radio_bt_rating.value_selected:
self.radio_bt_rating.circles[index].set_facecolor(
cfg.color_rating_axis)
break
self.radio_bt_rating.value_selected = None
def clear_notes_annot(self):
"""clearing notes and annotations"""
self.text_box.set_val(cfg.textbox_initial_text)
# text is matplotlib artist
self.annot_text.remove()
def on_mouse(self, event):
"""Callback for mouse events."""
if self.prev_axis is not None:
# include all the non-data axes here (so they wont be zoomed-in)
if event.inaxes not in self.unzoomable_axes:
self.prev_axis.set_position(self.prev_ax_pos)
self.prev_axis.set_zorder(0)
self.prev_axis.patch.set_alpha(0.5)
self.zoomed_in = False
# right click undefined
if event.button in [3]:
pass
# double click to zoom in to any axis
elif event.dblclick and event.inaxes is not None and \
event.inaxes not in self.unzoomable_axes:
# zoom axes full-screen
self.prev_ax_pos = event.inaxes.get_position()
event.inaxes.set_position(cfg.zoomed_position)
event.inaxes.set_zorder(1) # bring forth
event.inaxes.set_facecolor('black') # black
event.inaxes.patch.set_alpha(1.0) # opaque
self.zoomed_in = True
self.prev_axis = event.inaxes
else:
pass
plt.draw()
def on_keyboard(self, key_in):
"""Callback to handle keyboard shortcuts to rate and advance."""
# ignore keyboard key_in when mouse within Notes textbox
if key_in.inaxes == self.text_box.ax or key_in.key is None:
return
key_pressed = key_in.key.lower()
# print(key_pressed)
if key_pressed in [
'right',
]:
self.next_button_callback()
elif key_pressed in ['ctrl+q', 'q+ctrl']:
self.quit_button_callback()
elif key_pressed in [' ', 'space']:
self.toggle_animation_callback()
elif key_pressed in ['alt+1', '1+alt']:
self.show_first_image_callback()
elif key_pressed in ['alt+2', '2+alt']:
self.show_second_image_callback()
else:
if key_pressed in cfg.default_rating_list_shortform:
self.user_rating = cfg.map_short_rating[key_pressed]
index_to_set = cfg.default_rating_list.index(self.user_rating)
self.radio_bt_rating.set_active(index_to_set)
else:
pass
plt.draw()
class guiMenu:
fig = None
gauss_params = [33, 7]
logTextLabels = []
logText = []
axMisc = None
axAlgorithm = None
axSaveOptions = None
axGauss = None
axLog = None
axRadio = None
axLogLabels = None
line_gaussian = None
ax_window_size = None
slider_window_size = None
ax_sigma = None
slider_sigma = None
originalStdOut = None
#------------------------------------------------------------------------------
# Class initialization
#
def __init__(self):
self.strTitle = 'Gesture Analysis Configuration - ' + settings.appVersion
self.fig = plt.figure()
self.fig.canvas.set_window_title(self.strTitle)
self.fig.set_size_inches((settings.screen_cx * 0.49) / self.fig.dpi,
(settings.screen_cy * 0.465) / self.fig.dpi)
self.fig.canvas.mpl_connect('resize_event', self.onresize)
self.fig.canvas.mpl_connect('close_event', self.onclose)
self.fig.edgecolor = 'blue'
self.fig.set_facecolor('0.90')
left = 0.03 # the left side of the subplots of the figure
right = 0.97 # the right side of the subplots of the figure
bottom = 0.04 # the bottom of the subplots of the figure
top = 0.92 # the top of the subplots of the figure
wspace = 0.3 # the amount of width reserved for blank space between subplots
hspace = 0.7 # the amount of height reserved for white space between subplots
plt.subplots_adjust(left=left,
top=top,
right=right,
bottom=bottom,
wspace=wspace,
hspace=hspace)
self.axMisc = plt.subplot2grid((6, 4), (0, 0),
rowspan=1,
colspan=1,
aspect='auto',
anchor='NW')
self.axAlgorithm = plt.subplot2grid((6, 4), (1, 0),
rowspan=2,
colspan=1,
aspect='auto',
anchor='NW')
self.axSaveOptions = plt.subplot2grid((6, 4), (3, 0),
rowspan=3,
colspan=1,
aspect='equal',
anchor='NW')
self.axGauss = plt.subplot2grid((6, 4), (0, 1), rowspan=4, colspan=3)
self.axLog = plt.subplot2grid((6, 4), (5, 1),
rowspan=1,
colspan=3,
aspect='auto',
anchor='NW')
# create the various groups of UI controls
self.createUIMiscellaneous()
self.createUILog()
self.createUIAlgorithm()
self.createUIGaussianFilterControls()
self.createUIMiscellaneousControls()
# set settings.tkGuiCanvas for use for modal dialogs
try:
if (self.fig is not None) and (self.fig.canvas is not None) and (
self.fig.canvas._tkcanvas is not None):
settings.tkGuiCanvas = self.fig.canvas._tkcanvas
except Exception as e:
pass
#------------------------------------------------------------------------------
#
def get_aspect(self, ax):
# Total figure size
figW, figH = ax.get_figure().get_size_inches()
# Axis size on figure
_, _, w, h = ax.get_position().bounds
# Ratio of display units
disp_ratio = (figH * h) / (figW * w)
# Ratio of data units
# Negative over negative because of the order of subtraction
data_ratio = sub(*ax.get_ylim()) / sub(*ax.get_xlim())
return disp_ratio / data_ratio
#------------------------------------------------------------------------------
#
def createUIAlgorithm(self):
algorithm = settings.application.algorithm.lower()
defaultAlgoritmIdx = 0
if (algorithm == 'total'):
defaultAlgoritmIdx = 0
elif (algorithm == 'parallel'):
defaultAlgoritmIdx = 1
elif (algorithm == 'naive'):
defaultAlgoritmIdx = 2
self.axAlgorithm.set_title('Algorithm',
x=0,
horizontalalignment='left')
# create an axis to host to radio buttons. make its aspect ratio
# equal so the radiobuttons stay round
aspect = self.get_aspect(self.axAlgorithm)
rect = [0, 0, 1.0 * aspect, 1.0]
ip = InsetPosition(self.axAlgorithm, rect)
self.axRadio = plt.axes(rect)
self.axRadio.set_axes_locator(ip)
self.axRadio.axis('off')
self.radioAlgorithm = RadioButtons(
self.axRadio,
('Total Energy', 'Parallel Energy', 'Naive (no filter)'),
active=defaultAlgoritmIdx)
self.radioAlgorithm.on_clicked(self.onClickAlgorithm)
#------------------------------------------------------------------------------
#
def createUIGaussianFilterControls(self):
axcolor = 'lightgoldenrodyellow'
rect = [0.82, -0.158, 0.14, 0.07]
ax_btnapply = plt.axes(rect)
ip = InsetPosition(self.axGauss, rect) #posx, posy, width, height
ax_btnapply.set_axes_locator(ip)
self.btnApply = Button(ax_btnapply, 'Apply')
self.btnApply.on_clicked(self.onclickApply)
rect = [0.82, -0.245, 0.14, 0.07]
ax_btnreset = plt.axes(rect)
ip = InsetPosition(self.axGauss, rect) #posx, posy, width, height
ax_btnreset.set_axes_locator(ip)
self.btnReset = Button(ax_btnreset,
'Reset',
color='0.950',
hovercolor='0.975')
self.btnReset.on_clicked(self.onclickReset)
rect = [0.1, -0.155, 0.55, 0.04]
self.ax_window_size = plt.axes(rect, facecolor=axcolor)
ip = InsetPosition(self.axGauss, rect) #posx, posy, width, height
self.ax_window_size.set_axes_locator(ip)
self.slider_window_size = Slider(self.ax_window_size,
'Window Size',
1, (self.gauss_params[0] + 1) * 2 + 1,
valinit=self.gauss_params[0],
valstep=2)
self.slider_window_size.on_changed(self.updateGaussianFilter)
rect = [0.1, -0.235, 0.55, 0.04]
self.ax_sigma = plt.axes(rect, facecolor=axcolor)
ip = InsetPosition(self.axGauss, rect) #posx, posy, width, height
self.ax_sigma.set_axes_locator(ip)
self.slider_sigma = Slider(self.ax_sigma,
'Sigma',
1, (self.gauss_params[1] + 1) * 2,
valinit=self.gauss_params[1],
valstep=1)
self.slider_sigma.on_changed(self.updateGaussianFilter)
self.updateGaussianFilter()
#------------------------------------------------------------------------------
#
def createUIMiscellaneous(self):
self.axMisc.set_title('', x=0, horizontalalignment='left')
# removing top and right borders
self.axMisc.xaxis.set_visible(False)
self.axMisc.yaxis.set_visible(False)
# remove ticks
self.axSaveOptions.set_xticks([])
self.axSaveOptions.set_yticks([])
# remove ticks
self.axAlgorithm.set_xticks([])
self.axAlgorithm.set_yticks([])
bbox = self.axMisc.get_window_extent()
self.axMisc.set_xlim(0, bbox.width)
self.axMisc.set_ylim(0, bbox.height)
#------------------------------------------------------------------------------
#
def createUILog(self):
self.axLog.set_title('Console Log', x=0, horizontalalignment='left')
# removing top and right borders
self.axLog.xaxis.set_visible(False)
self.axLog.yaxis.set_visible(False)
self.resetLogLabels()
# redirect console messages to gui's log
self.originalStdOut = sys.stdout
sys.stdout = CaptureOutput()
# -----------------------------------------------------------------------------
#
def resetLogLabels(self):
cnt = len(self.logTextLabels)
for i in range(0, cnt):
self.logTextLabels[i].remove()
self.logTextLabels = []
bbox = self.axLog.get_window_extent()
self.axLog.set_xlim(0, bbox.width)
self.axLog.set_ylim(0, bbox.height)
aspect = self.get_aspect(self.axLog)
rect = [0, 0, 1.0 * aspect, 1.0]
ip = InsetPosition(self.axLog, rect)
if (self.axLogLabels is None):
self.axLogLabels = plt.axes(rect)
else:
self.axLogLabels.set_position(rect)
self.axLogLabels.set_axes_locator(ip)
self.axLogLabels.axis('off')
aspectLog = 1.0 / self.get_aspect(self.axLog)
strText = 'Tyg'
tmp, self.logTextHeight = settings.getTextExtent(self.axLog, strText)
self.logTextHeight = self.logTextHeight * aspectLog # * self.fig.dpi
# pre-create empty log label placeholders
self.logTextLabels = []
y = (self.logTextHeight / 4.0)
cy = bbox.height
idx = len(self.logText) - 1
while (y < cy):
str = self.logText[idx] if (idx >= 0) else ''
idx = idx - 1
lbl = self.axLogLabels.text(
8.0,
y,
str,
horizontalalignment='left',
verticalalignment='bottom',
color='dimgray',
clip_on=True,
transform=self.axLog.transData
) #, bbox={'facecolor':'lightgray', 'alpha':0.7, 'pad':0.0})
self.logTextLabels.append(lbl)
y += self.logTextHeight
# -----------------------------------------------------------------------------
#
def createUIMiscellaneousControls(self):
rect = [0.06, 0.30, 0.70, 0.40]
ip = InsetPosition(self.axMisc, rect) #posx, posy, width, height
ax_btnbrowse = plt.axes(rect)
ax_btnbrowse.set_axes_locator(ip)
self.btnBrowse = Button(ax_btnbrowse, 'Input File')
self.btnBrowse.on_clicked(self.onclickBrowse)
self.axSaveOptions.set_title('Output Files',
x=0,
horizontalalignment='left')
x = 0.06
dx = 0.70 # 0.80
dy = 0.10 # 0.17
cy = 0.14 # 0.24
y = 0.80
rect = [x, y, dx, dy]
ip = InsetPosition(self.axSaveOptions,
rect) #posx, posy, width, height
ax_btn = plt.axes(rect)
ax_btn.set_axes_locator(ip)
self.btnSaveJSON = Button(ax_btn, 'JSON')
self.btnSaveJSON.on_clicked(self.onclickSaveJSON)
rect = [x, y - 1 * cy, dx, dy]
ip = InsetPosition(self.axSaveOptions,
rect) #posx, posy, width, height
ax_btn = plt.axes(rect)
ax_btn.set_axes_locator(ip)
self.btnSaveTXT = Button(ax_btn, 'Text')
self.btnSaveTXT.on_clicked(self.onclickSaveTXT)
rect = [x, y - 2 * cy, dx, dy]
ip = InsetPosition(self.axSaveOptions,
rect) #posx, posy, width, height
ax_btn = plt.axes(rect)
ax_btn.set_axes_locator(ip)
self.btnSaveFilterView = Button(ax_btn, 'Filter Graph')
self.btnSaveFilterView.on_clicked(self.onclickSaveFilterView)
rect = [x, y - 3 * cy, dx, dy]
ip = InsetPosition(self.axSaveOptions,
rect) #posx, posy, width, height
ax_btn = plt.axes(rect)
ax_btn.set_axes_locator(ip)
self.btnSaveSkeletonView = Button(ax_btn, '3D Joint Data')
self.btnSaveSkeletonView.on_clicked(self.onclickSaveSkeletonView)
rect = [x, y - 4 * cy, dx, dy]
ip = InsetPosition(self.axSaveOptions,
rect) #posx, posy, width, height
ax_btn = plt.axes(rect)
ax_btn.set_axes_locator(ip)
self.btnSaveScoreView = Button(ax_btn, 'Score View')
self.btnSaveScoreView.on_clicked(self.onclickSaveScoreView)
rect = [x, y - 5 * cy, dx, dy]
ip = InsetPosition(self.axSaveOptions,
rect) #posx, posy, width, height
ax_btn = plt.axes(rect)
ax_btn.set_axes_locator(ip)
self.btnSavePNG = Button(ax_btn, 'Full Score')
self.btnSavePNG.on_clicked(self.onclickSaveImage)
#------------------------------------------------------------------------------
# canvas resize event
#
def onresize(self, event):
# plt.tight_layout()
# keep tha radio buttons round...
if (self.axRadio is not None) and (self.axAlgorithm is not None):
aspect = self.get_aspect(self.axAlgorithm)
rect = [0, 0, 1.0 * aspect, 1.0]
ip = InsetPosition(self.axAlgorithm, rect)
self.axRadio.set_axes_locator(ip)
self.axRadio.set_position(rect)
self.resetLogLabels()
# -----------------------------------------------------------------------------
# canvas close event
#
def onclose(self, event):
self.fig = None
# if user closes this figure, let the main application know and to exit
settings.application.close()
# -----------------------------------------------------------------------------
#
def updateUIControls(self, algorithm):
algorithm = algorithm.lower()
fEnable = False if (algorithm == 'naive') else True
alpha = 0.2 if (algorithm == 'naive') else 1.0
self.btnApply.set_active(fEnable)
self.btnReset.set_active(fEnable)
self.btnApply.label.set_alpha(alpha)
self.btnReset.label.set_alpha(alpha)
fUpdateGaussianPlot = False
if (self.gauss_params[0] != self.slider_window_size.val):
self.ax_window_size.clear()
self.slider_window_size.__init__(
self.ax_window_size,
'Window Size',
valmin=1,
valmax=(self.gauss_params[0] + 1) * 2 + 1,
valinit=self.gauss_params[0],
valstep=2)
self.slider_window_size.on_changed(self.updateGaussianFilter)
fUpdateGaussianPlot = True
if (self.gauss_params[1] != self.slider_sigma.val):
self.ax_sigma.clear()
self.slider_sigma.__init__(self.ax_sigma,
'Sigma',
valmin=1,
valmax=(self.gauss_params[1] + 1) * 2,
valinit=self.gauss_params[1],
valstep=1)
self.slider_sigma.on_changed(self.updateGaussianFilter)
fUpdateGaussianPlot = True
if (fUpdateGaussianPlot):
self.updateGaussianFilter()
self.line_gaussian.set_alpha(alpha)
self.ax_window_size.patch.set_alpha(alpha)
if (self.slider_window_size.poly):
self.slider_window_size.poly.set_alpha(alpha)
self.slider_window_size.set_active(fEnable)
for r in self.slider_window_size.ax.texts:
r.set_alpha(alpha)
self.ax_sigma.patch.set_alpha(alpha)
if (self.slider_sigma.poly):
self.slider_sigma.poly.set_alpha(alpha)
self.slider_sigma.set_active(fEnable)
for r in self.slider_sigma.ax.texts:
r.set_alpha(alpha)
self.fig.canvas.draw_idle()
# -----------------------------------------------------------------------------
#
def updateInputName(self):
self.fig.canvas.set_window_title(
self.strTitle + ' - [' +
settings.application.strBeautifiedInputFile + ']')
# -----------------------------------------------------------------------------
#
def getAlgorithmSelection(self):
if (self.radioAlgorithm.value_selected == 'Total Energy'):
return 'Total'
elif (self.radioAlgorithm.value_selected == 'Parallel Energy'):
return 'Parallel'
return 'Naive'
# -----------------------------------------------------------------------------
#
def onClickAlgorithm(self, label):
algorithm = self.getAlgorithmSelection()
if (settings.application.labanotation is not None):
self.gauss_params = settings.application.labanotation.getGaussianParameters(
algorithm)
self.updateUIControls(algorithm)
settings.application.applyAlgoritm(algorithm)
#------------------------------------------------------------------------------
# updateGaussianFilter() has an unused parameter, though needs it because the
# sliders use this function as their update callback...
def updateGaussianFilter(self, val=0):
# remove current gaussian lines
if (self.line_gaussian is not None):
self.line_gaussian.remove()
del self.line_gaussian
self.line_gaussian = None
gauss_params = (int(self.slider_window_size.val),
int(self.slider_sigma.val))
self._t = np.arange(-gauss_params[0] / 2.0 + 0.5,
gauss_params[0] / 2.0 + 0.5, 1.0)
s = wf.gaussFilter(gauss_params[0], gauss_params[1])
self.line_gaussian, = self.axGauss.plot(self._t,
s,
marker="o",
linestyle='-',
color='red',
lw=1)
# for i, txt in enumerate(s):
# self.axGauss.annotate("{:0.2f}".format(txt), (self._t[i], s[i]))
wnd = int(gauss_params[0] / 2) + 1
self.axGauss.set_xlim(-wnd, wnd)
self.axGauss.set_ylim(0, 0.42) # np.max(s))
self.fig.canvas.draw_idle()
#------------------------------------------------------------------------------
#
def onclickApply(self, event):
algorithm = self.getAlgorithmSelection()
self.gauss_params = (int(self.slider_window_size.val),
int(self.slider_sigma.val))
if (settings.application.labanotation is not None):
settings.application.labanotation.setGaussianParameters(
algorithm, self.gauss_params)
settings.application.applyAlgoritm(algorithm)
#------------------------------------------------------------------------------
#
def onclickSaveJSON(self, event):
settings.application.saveJSON()
#------------------------------------------------------------------------------
#
def onclickSaveTXT(self, event):
settings.application.saveTXT()
#------------------------------------------------------------------------------
#
def onclickSaveImage(self, event):
settings.application.saveImage()
#------------------------------------------------------------------------------
#
def onclickSaveFilterView(self, event):
settings.application.saveFilterView()
#------------------------------------------------------------------------------
#
def onclickSaveSkeletonView(self, event):
settings.application.saveSkeletonView()
#------------------------------------------------------------------------------
#
def onclickSaveScoreView(self, event):
settings.application.saveScoreView()
#------------------------------------------------------------------------------
#
def onclickReset(self, event):
self.slider_window_size.reset()
self.slider_sigma.reset()
#------------------------------------------------------------------------------
#
def onclickBrowse(self, event):
file = self.selectInputFile()
if (file is None):
return
settings.application.openAndProcessInputfile(file)
#------------------------------------------------------------------------------
#
def selectInputFile(self):
fTyp = [("Kinect Joint Data File", "*.csv")]
splitInput = os.path.split(
os.path.abspath(settings.application.inputFilePath))
options = {}
options['filetypes'] = fTyp
options['initialdir'] = splitInput[0].replace('/', os.sep)
if (settings.tkGuiCanvas is not None):
options['parent'] = settings.tkGuiCanvas
file = tkFileDialog.askopenfilename(**options)
if not file:
return None
return file
#------------------------------------------------------------------------------
#
def logMessage(self, str, ioRedirect=False):
# also write message to console
if (self.originalStdOut is not None):
extra = "\r\n" if (ioRedirect is False) else ""
self.originalStdOut.write(str + extra)
self.logText.append(str)
cnt = len(self.logTextLabels)
if (cnt > 0):
for i in range(cnt - 1, 0, -1):
self.logTextLabels[i].set_text(
self.logTextLabels[i - 1].get_text())
self.logTextLabels[0].set_text(str)
self.fig.canvas.draw_idle()
def slide_ddg(args):
global new_df, radio, color_by, picked
global scat, ax, sliders, sc_df, fig, cm, cbar
sc_df = Rf.score_file2df(args['sc'], args['names'])
args['logger'].log('score file has %i entries' % len(sc_df))
if args['pc'] is not None:
pc_df = get_rmsds_from_table(args['pc'])
args['logger'].log('pc file had %i entries' % len(pc_df))
a = sc_df.merge(pc_df, on='description')
args['logger'].log('combined there are %i entries' % len(a))
sc_df = a.copy()
if args['percent'] != 100:
threshold = np.percentile(sc_df[args['y']], args['percent'])
sc_df = sc_df[sc_df[args['y']] < threshold]
color_by = args['y']
picked = False
new_df = sc_df.copy()
fig, ax = plt.subplots()
plt.subplots_adjust(left=0.25, bottom=0.25)
cm = plt.cm.get_cmap('RdYlBu')
scat = ax.scatter(sc_df[args['x']].values,
sc_df[args['y']].values,
s=40,
cmap=cm,
c=sc_df[color_by],
picker=True)
cbar = plt.colorbar(scat)
sliders = {}
for i, term in enumerate(args['terms']):
slider_ax = plt.axes([0.25, 0.01 + i * 0.035, 0.65, 0.03])
sliders[term] = Slider(slider_ax, term, np.min(sc_df[term].values),
np.max(sc_df[term].values), 0)
sliders[term].on_changed(update)
ax.set_xlim(
np.min(new_df[args['x']].values) - 1,
np.max(new_df[args['x']].values) + 1)
ax.set_ylim(
np.min(new_df[args['y']].values) - 1,
np.max(new_df[args['y']].values) + 1)
ax.set_xlabel(args['x'])
ax.set_ylabel(args['y'])
resetax = plt.axes([0.025, 0.7, 0.15, 0.15]) #[0.8, 0.025, 0.1, 0.04])
button = Button(resetax,
'Reset',
color='lightgoldenrodyellow',
hovercolor='0.975')
button.on_clicked(reset)
printax = plt.axes([0.025, 0.3, 0.15, 0.15])
printbutton = Button(printax, 'Print', color='green', hovercolor='red')
printbutton.on_clicked(print_table)
logax = plt.axes([0.025, 0.1, 0.15, 0.15])
logbutton = Button(logax, 'log table', color='blue', hovercolor='red')
logbutton.on_clicked(log_table)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], axisbg='white')
radio = RadioButtons(rax, args['terms'], active=0)
radio.on_clicked(colorfunc)
# cbar = plt.colorbar(scat)
pl = PointLabel(new_df, ax, fig, args['x'], args['y'], [
'description', 'a_sasa', 'a_res_solv', 'a_pack', 'a_span_topo',
'a_ddg', 'fa_elec'
], args['logger'])
fig.canvas.mpl_connect('pick_event', pl.onpick)
plt.show()
z0_slider.on_changed(update)
# angle slider
angle_valinit = 0
angax = axes([0.25, 0.035, 0.5, 0.025], axisbg='slategray')
angslider = Slider(angax, 'theta', 0, pi, valinit=0)
def upangle(val):
global theta
theta = angslider.val
plot1d()
angslider.on_changed(upangle)
# radio buttons
ffax = axes([0.01, 0.1, 0.04, 0.2], axisbg='slategray')
ffbutt = RadioButtons(ffax, ('.1', '.2', '.3', '.4', '.5'), active=2)
def updateff(label):
global ff
ff = float(label)
make_plots()
ffbutt.on_clicked(updateff)
show()
class PickPhaseMenuMore:
""" Pick phase for multiple seismograms and array stack
Button: Sync
"""
def __init__(self, gsac, opts, axs):
self.gsac = gsac
self.opts = opts
self.axs = axs
self.axstk = self.axs['Fstk']
if not 'stkdh' in gsac.__dict__:
if opts.filemode == 'sac' and os.path.isfile(opts.fstack):
gsac.stkdh = SacDataHdrs(opts.fstack, opts.delta)
else:
hdrini, hdrmed, hdrfin = opts.qcpara.ichdrs
self.cchdrs = [hdrini, hdrmed]
self.twcorr = opts.ccpara.twcorr
# check data coverage
opts.ipick = hdrini
opts.twcorr = opts.ccpara.twcorr
checkCoverage(gsac, opts)
gsac.selist = gsac.saclist
self.ccStack()
self.initPlot()
self.plotStack()
self.addEarthquakeInfo()
self.setLabels()
self.connect()
def initPlot(self):
""" Plot waveforms """
gsac = self.gsac
opts = self.opts
sortSeis(gsac, opts)
self.ppm = PickPhaseMenu(gsac, opts, self.axs)
# make the legend box invisible
if self.opts.pick_on:
self.ppm.axpp.get_legend().set_visible(False)
def addEarthquakeInfo(self):
""" Set Earthquake Info
* Magnitude
* Location (Lat and Long)
* Depth
"""
gsac = self.gsac
# get required parameters
locationLat = round(gsac.event[6],2)
locationLon = round(gsac.event[7],2)
depth = round(gsac.event[8],2)
magnitude = round(gsac.event[9],2)
all_gcarc = []
[all_gcarc.append(hdr.gcarc) for hdr in gsac.selist ]
avg_gcarc = round(np.mean(all_gcarc),2)
infoaxis = self.axs['Info']
# remove axes markings
infoaxis.axes.get_xaxis().set_ticks([])
infoaxis.axes.get_yaxis().set_visible(False)
# write the info into the axis plot
infoaxis.text(0.1,0.85,'Magnitude: '+str(magnitude))
infoaxis.text(0.1,0.65,'Lat: '+str(locationLat))
infoaxis.text(0.1,0.45,'Lon: '+str(locationLon))
infoaxis.text(0.1,0.25,'Depth: '+str(depth))
infoaxis.text(0.1,0.05,'Gcarc: '+str(avg_gcarc))
def setLabels(self):
""" Set plot attributes """
self.ppm.axpp.set_title('Seismograms')
if self.opts.filemode == 'pkl':
axstk = self.axstk
trans = transforms.blended_transform_factory(axstk.transAxes, axstk.transAxes)
axstk.text(1,1.01,self.opts.pklfile,transform=trans, va='bottom', ha='right',color='k')
axpp = self.ppm.axpp
trans = transforms.blended_transform_factory(axpp.transAxes, axpp.transData)
font = FontProperties()
font.set_family('monospace')
axpp.text(1.025, 0, ' '*8+'qual= CCC/SNR/COH', transform=trans, va='center',
color='k', fontproperties=font)
def plotStack(self):
""" Plot array stack and span """
colorwave = self.opts.pppara.colorwave
stkybase = 0
ppstk = PickPhase(self.gsac.stkdh, self.opts, self.axstk, stkybase, colorwave, 1)
ppstk.plotPicks()
ppstk.disconnectPick()
self.ppstk = ppstk
self.axstk.set_title('Array Stack')
self.ppstk.stalabel.set_visible(False)
if self.opts.ynorm == 1.0:
self.axstk.set_ylim(stkybase-0.5, stkybase+0.5)
self.axstk.set_yticks([stkybase])
self.axstk.set_yticklabels([])
self.axstk.axvline(x=0, color='k', ls=':')
# plot legend
pppara = self.opts.pppara
pickLegend(self.axstk, pppara.npick, pppara.pickcolors, pppara.pickstyles, False)
self.plotSpan()
def plotSpan(self):
""" Span for array stack """
axstk = self.axstk
self.xzoom = [axstk.get_xlim(),]
def on_select(xmin, xmax):
""" Mouse event: select span. """
if self.span.visible:
print('span selected: %6.1f %6.1f ' % (xmin, xmax))
xxlim = (xmin, xmax)
axstk.set_xlim(xxlim)
self.xzoom.append(xxlim)
if self.opts.upylim_on:
print ('upylim')
self.ppstk.updateY(xxlim) ##
axstk.figure.canvas.draw()
pppara = self.opts.pppara
a, col = pppara.alphatwsele, pppara.colortwsele
mspan = pppara.minspan * self.opts.delta
self.span = TimeSelector(axstk, on_select, 'horizontal', minspan=mspan, useblit=False,
rectprops=dict(alpha=a, facecolor=col))
#self.replot()
#self.ppm.axpp.figure.canvas.draw()
# -------------------------------- SORTING ---------------------------------- #
# Sort seismograms by
# --------------
# * | file indices |
# --------------
# ----- ----- ----- -----
# * quality factor | all | ccc | snr | coh |
# ----- ----- ----- -----
# ---- ----- ------
# * given header | az | baz | dist | ...
# ---- ----- ------
def sorting(self, event):
""" Sort the seismograms in particular order """
self.getSortAxes()
self.summarize_sort()
self.sort_connect()
plt.show()
def getSortAxes(self):
figsort = plt.figure('SortSeismograms',figsize=(15, 12))
x0 = 0.05
xx = 0.10
yy = 0.04
#xm = 0.02
dy = 0.15
dx = 0.12
y0 = 0.90
"""Allocating size of buttons"""
# file indices (filenames)
rectfile = [x0, y0-dy*1, xx, yy]
# quality
rectqall = [x0+dx*0, y0-2*dy, xx, yy]
rectqccc = [x0+dx*1, y0-2*dy, xx, yy]
rectqsnr = [x0+dx*2, y0-2*dy, xx, yy]
rectqcoh = [x0+dx*3, y0-2*dy, xx, yy]
# headers
recthnpts = [x0+dx*0, y0-3*dy, xx, yy]
recthb = [x0+dx*1, y0-3*dy, xx, yy]
recthe = [x0+dx*2, y0-3*dy, xx, yy]
recthdelta = [x0+dx*3, y0-3*dy, xx, yy]
recthstla = [x0+dx*0, y0-3.5*dy, xx, yy]
recthstlo = [x0+dx*1, y0-3.5*dy, xx, yy]
recthdist = [x0+dx*2, y0-3.5*dy, xx, yy]
recthaz = [x0+dx*3, y0-3.5*dy, xx, yy]
recthbaz = [x0+dx*0, y0-4*dy, xx, yy]
recthgcarc = [x0+dx*1, y0-4*dy, xx, yy]
# quit
rectquit = [0.2, y0-5*dy, 0.2, yy]
"""writing buttons to axis"""
sortAxs = {}
figsort.text(0.1,y0-dy*0.5,'Sort by file Index Name: ')
sortAxs['file'] = figsort.add_axes(rectfile)
figsort.text(0.1,y0-dy*1.5,'Sort by Quality: ')
sortAxs['qall'] = figsort.add_axes(rectqall)
sortAxs['qccc'] = figsort.add_axes(rectqccc)
sortAxs['qsnr'] = figsort.add_axes(rectqsnr)
sortAxs['qcoh'] = figsort.add_axes(rectqcoh)
figsort.text(0.1,y0-dy*2.5,'Sort by Header: ')
sortAxs['hnpts'] = figsort.add_axes(recthnpts)
sortAxs['hb'] = figsort.add_axes(recthb)
sortAxs['he'] = figsort.add_axes(recthe)
sortAxs['hdelta'] = figsort.add_axes(recthdelta)
sortAxs['hstla'] = figsort.add_axes(recthstla)
sortAxs['hstlo'] = figsort.add_axes(recthstlo)
sortAxs['hdist'] = figsort.add_axes(recthdist)
sortAxs['haz'] = figsort.add_axes(recthaz)
sortAxs['hbaz'] = figsort.add_axes(recthbaz)
sortAxs['hgcarc'] = figsort.add_axes(recthgcarc)
sortAxs['quit'] = figsort.add_axes(rectquit)
""" size of text summary box """
rectsumm = [0.55, 0.05, 0.40, 0.90]
sortAxs['summary'] = figsort.add_axes(rectsumm)
# remove axes markings on summary field
sortAxs['summary'].get_xaxis().set_ticks([])
sortAxs['summary'].get_yaxis().set_visible([])
self.sortAxs = sortAxs
self.figsort = figsort
def summarize_sort(self):
sortAxs = self.sortAxs
# define constants
x0 = 0.03
x1 = 0.20
y0 = 0.95
dy = 0.03
# explain what the summaries are
sortAxs['summary'].text(x0,y0-dy*0,'FILENAMES')
sortAxs['summary'].text(x0,y0-dy*1,'File: ')
sortAxs['summary'].text(x1,y0-dy*1,'Sort in alphabetical order by filename')
sortAxs['summary'].text(x0,y0-dy*3,'QUALITY:')
sortAxs['summary'].text(x0,y0-dy*4,'All: ')
sortAxs['summary'].text(x1,y0-dy*4,'Weighted Ratio of all quality measures')
sortAxs['summary'].text(x0,y0-dy*5,'CCC: ')
sortAxs['summary'].text(x1,y0-dy*5,'Cross-coefficient Coefficient')
sortAxs['summary'].text(x0,y0-dy*6,'SNR: ')
sortAxs['summary'].text(x1,y0-dy*6,'Signal-to-noise Ratio')
sortAxs['summary'].text(x0,y0-dy*7,'COH: ')
sortAxs['summary'].text(x1,y0-dy*7,'time domain coherence')
sortAxs['summary'].text(x0,y0-dy*9,'OTHER HEADERS:')
sortAxs['summary'].text(x0,y0-dy*10,'NPTS: ')
sortAxs['summary'].text(x1,y0-dy*10,'Number of points per data component')
sortAxs['summary'].text(x0,y0-dy*11,'B: ')
sortAxs['summary'].text(x1,y0-dy*11,'Beginning value of the independent variable')
sortAxs['summary'].text(x0,y0-dy*12,'E: ')
sortAxs['summary'].text(x1,y0-dy*12,'Ending value of the independent variable')
sortAxs['summary'].text(x0,y0-dy*13,'Delta: ')
sortAxs['summary'].text(x1,y0-dy*13,'Increment between evenly spaced samples')
sortAxs['summary'].text(x0,y0-dy*14,'STLA: ')
sortAxs['summary'].text(x1,y0-dy*14,'Station latitude (deg, north positive)')
sortAxs['summary'].text(x0,y0-dy*15,'STLO: ')
sortAxs['summary'].text(x1,y0-dy*15,'Station longitude (deg, east positive)')
sortAxs['summary'].text(x0,y0-dy*16,'DIST: ')
sortAxs['summary'].text(x1,y0-dy*16,'Station to event distance (km)')
sortAxs['summary'].text(x0,y0-dy*17,'AZ: ')
sortAxs['summary'].text(x1,y0-dy*17,'Event to station azimuth (deg)')
sortAxs['summary'].text(x0,y0-dy*18,'BAZ: ')
sortAxs['summary'].text(x1,y0-dy*18,'Station to event azimuth (deg)')
sortAxs['summary'].text(x0,y0-dy*19,'GCARC: ')
sortAxs['summary'].text(x1,y0-dy*19,'Station to event great circle arc length (deg)')
""" Connect button events. """
def sort_connect(self):
"""write the position for the buttons into self"""
self.axfile = self.sortAxs['file']
self.axqall = self.sortAxs['qall']
self.axqccc = self.sortAxs['qccc']
self.axqsnr = self.sortAxs['qsnr']
self.axqcoh = self.sortAxs['qcoh']
self.axqcoh = self.sortAxs['qcoh']
self.axhnpts = self.sortAxs['hnpts']
self.axhb = self.sortAxs['hb']
self.axhe = self.sortAxs['he']
self.axhdelta = self.sortAxs['hdelta']
self.axhstla = self.sortAxs['hstla']
self.axhstlo = self.sortAxs['hstlo']
self.axhdist = self.sortAxs['hdist']
self.axhaz = self.sortAxs['haz']
self.axhbaz = self.sortAxs['hbaz']
self.axhgcarc = self.sortAxs['hgcarc']
self.axquit = self.sortAxs['quit']
"""add a button to the correct place as defined by the axes
Also label the buttons here, as seen in the GUI
"""
self.bnfile = Button(self.axfile, 'File')
self.bnqall = Button(self.axqall, 'All')
self.bnqccc = Button(self.axqccc, 'CCC')
self.bnqsnr = Button(self.axqsnr, 'SNR')
self.bnqcoh = Button(self.axqcoh, 'COH')
self.bnhnpts = Button(self.axhnpts, 'NPTS')
self.bnhb = Button(self.axhb, 'B')
self.bnhe = Button(self.axhe, 'E')
self.bnhdelta = Button(self.axhdelta, 'Delta')
self.bnhstla = Button(self.axhstla, 'STLA')
self.bnhstlo = Button(self.axhstlo, 'STLO')
self.bnhdist = Button(self.axhdist, 'Dist')
self.bnhaz = Button(self.axhaz, 'AZ')
self.bnhbaz = Button(self.axhbaz, 'BAZ')
self.bnhgcarc = Button(self.axhgcarc, 'GCARC')
self.bnquit = Button(self.axquit, 'Waiting for User input')
""" each button changes the way the seismograms are sorted """
self.cidfile = self.bnfile.on_clicked(self.sort_file)
self.cidqall = self.bnqall.on_clicked(self.sort_qall)
self.cidqccc = self.bnqccc.on_clicked(self.sort_qccc)
self.cidqsnr = self.bnqsnr.on_clicked(self.sort_qsnr)
self.cidqcoh = self.bnqcoh.on_clicked(self.sort_qcoh)
self.cidhnpts = self.bnhnpts.on_clicked(self.sort_hnpts)
self.cidhb = self.bnhb.on_clicked(self.sort_hb)
self.cidhe = self.bnhe.on_clicked(self.sort_he)
self.cidhdelta = self.bnhdelta.on_clicked(self.sort_hdelta)
self.cidhstla = self.bnhstla.on_clicked(self.sort_hstla)
self.cidhstlo = self.bnhstlo.on_clicked(self.sort_hstlo)
self.cidhdist = self.bnhdist.on_clicked(self.sort_hdist)
self.cidhaz = self.bnhaz.on_clicked(self.sort_haz)
self.cidhbaz = self.bnhbaz.on_clicked(self.sort_hbaz)
self.cidhgcarc = self.bnhgcarc.on_clicked(self.sort_hgcarc)
# dismiss window when done
self.bnquit.on_clicked(self.dismiss_sort)
def sort_disconnect(self):
self.bnfile.disconnect(self.cidfile)
self.bnqall.disconnect(self.cidqall)
self.bnqccc.disconnect(self.cidqccc)
self.bnqsnr.disconnect(self.cidqsnr)
self.bnqcoh.disconnect(self.cidqcoh)
self.bnhnpts.disconnect(self.cidhnpts)
self.bnhb.disconnect(self.cidhb)
self.bnhe.disconnect(self.cidhe)
self.bnhdelta.disconnect(self.cidhdelta)
self.bnhstla.disconnect(self.cidhstla)
self.bnhstlo.disconnect(self.cidhstlo)
self.bnhdist.disconnect(self.cidhdist)
self.bnhaz.disconnect(self.cidhaz)
self.bnhbaz.disconnect(self.cidhbaz)
self.bnhgcarc.disconnect(self.cidhgcarc)
def sort_file(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'i';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_qall(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'all';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_qccc(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = '1';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_qsnr(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = '2';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_qcoh(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = '3';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hnpts(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'npts';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hb(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'b';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_he(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'e';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hdelta(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'delta';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hkstnm(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'kstnm';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hstla(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'stla';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hstlo(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'stlo';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hdist(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'dist';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_haz(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'az';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hbaz(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'baz';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def sort_hgcarc(self, event):
self.bnquit.label.set_text('Processing...')
event.canvas.draw()
self.opts.sortby = 'gcarc';
self.replot_seismograms()
self.ppm.axpp.figure.canvas.draw()
self.bnquit.label.set_text('Done! Click to Exit.')
event.canvas.draw()
return
def dismiss_sort(self, event):
"""Dismiss the sorting selection popup Window"""
self.sort_disconnect()
close()
# -------------------------------- SORTING ---------------------------------- #
# --------------------------------- Filtering ------------------------------- #
# Implement Butterworth filter
#
def filtering(self,event):
filterAxes = self.getFilterAxes()
self.spreadButter()
self.filter_connect()
plt.show()
def filter_connect(self):
# user to change default parameters
self.cidSelectFreq = self.filterAxs['amVfreq'].get_figure().canvas.mpl_connect('button_press_event', self.getBandpassFreq)
# get order
self.bnorder = RadioButtons(self.filterAxs['ordr'], (1,2,3,4), active=1)
self.cidorder = self.bnorder.on_clicked(self.getButterOrder)
# get type of filter to use
self.bnband = RadioButtons(self.filterAxs['band'], ('bandpass','lowpass','highpass'))
self.cidband = self.bnband.on_clicked(self.getBandtype)
# get reverse pass option
self.bnreversepass = RadioButtons(self.filterAxs['reversepass'], ('yes', 'no'), active=1)
self.cidreversepass = self.bnreversepass.on_clicked(self.getReversePassOption)
#add apply button. causes the filtered data to be applied
self.bnapply = Button(self.filterAxs['apply'], 'Apply')
self.cidapply = self.bnapply.on_clicked(self.applyFilter)
#add unapply button. causes the filtered data to be applied
self.bnunapply = Button(self.filterAxs['unapply'], 'Unapply')
self.cidunapply = self.bnunapply.on_clicked(self.unapplyFilter)
def getReversePassOption(self, event):
if event == 'yes':
self.opts.filterParameters['reversepass'] = True
else:
self.opts.filterParameters['reversepass'] = False
self.spreadButter()
def getBandtype(self, event):
self.opts.filterParameters['band'] = event
if event=='bandpass':
self.filterAxs['amVfreq'].figure.canvas.mpl_disconnect(self.cidSelectFreq)
# set defaults
self.opts.filterParameters['lowFreq'] = 0.05
self.opts.filterParameters['highFreq'] = 0.25
self.opts.filterParameters['advance'] = False
self.spreadButter()
#execute
self.cidSelectFreq = self.filterAxs['amVfreq'].get_figure().canvas.mpl_connect('button_press_event', self.getBandpassFreq)
elif event=='lowpass':
self.filterAxs['amVfreq'].figure.canvas.mpl_disconnect(self.cidSelectFreq)
# set defaults
self.opts.filterParameters['lowFreq'] = 0.05
self.opts.filterParameters['highFreq'] = np.nan
self.opts.filterParameters['advance'] = False
self.spreadButter()
#execute
self.cidSelectFreq = self.filterAxs['amVfreq'].get_figure().canvas.mpl_connect('button_press_event', self.getLowFreq)
elif event=='highpass':
self.filterAxs['amVfreq'].figure.canvas.mpl_disconnect(self.cidSelectFreq)
# set defaults
self.opts.filterParameters['lowFreq'] = np.nan
self.opts.filterParameters['highFreq'] = 0.25
self.opts.filterParameters['advance'] = False
self.spreadButter()
#execute
self.cidSelectFreq = self.filterAxs['amVfreq'].get_figure().canvas.mpl_connect('button_press_event', self.getHighFreq)
def getLowFreq(self, event):
if event.inaxes == self.filterAxs['amVfreq']:
self.opts.filterParameters['lowFreq'] = event.xdata
self.spreadButter()
def getHighFreq(self, event):
if event.inaxes == self.filterAxs['amVfreq']:
self.opts.filterParameters['highFreq'] = event.xdata
self.spreadButter()
def getButterOrder(self, event):
self.opts.filterParameters['order'] = int(event)
self.spreadButter()
def getBandpassFreq(self,event):
if event.inaxes == self.filterAxs['amVfreq']:
if self.opts.filterParameters['advance']: # low and high frequencies recorded
self.opts.filterParameters['highFreq'] = event.xdata
if self.opts.filterParameters['lowFreq']<self.opts.filterParameters['highFreq']:
self.opts.filterParameters['advance'] = False
self.spreadButter()
else:
print('Value chose must be higher than lower frequency of %f' % self.opts.filterParameters['lowFreq'])
else:
self.opts.filterParameters['lowFreq'] = event.xdata
self.opts.filterParameters['advance'] = True
def modifyFilterTextLabels(self):
self.filterAxs['Info'].clear()
self.filterAxs['Info'].text(0.1,0.7,'Low Freq: '+str(self.opts.filterParameters['lowFreq']))
self.filterAxs['Info'].text(0.1,0.4,'High Freq: '+str(self.opts.filterParameters['highFreq']))
self.filterAxs['Info'].text(0.1,0.1,'Order: '+str(self.opts.filterParameters['order']))
"""Apply the butterworth filter to the data """
def spreadButter(self):
# clear axes
self.filterAxs['amVtime'].clear()
self.filterAxs['amVfreq'].clear()
#set axes limit
self.filterAxs['amVtime'].set_xlim(-30,30)
self.filterAxs['amVfreq'].set_xlim(0,1.50)
self.modifyFilterTextLabels()
originalTime = self.ppstk.time - self.ppstk.sacdh.reftime
originalSignalTime = self.ppstk.sacdh.data
originalFreq, originalSignalFreq = ftr.time_to_freq(originalTime, originalSignalTime, self.opts.delta)
filteredSignalTime, filteredSignalFreq, adjusted_w, adjusted_h = ftr.filtering_time_freq(originalTime, originalSignalTime, self.opts.delta, self.opts.filterParameters['band'], self.opts.filterParameters['highFreq'], self.opts.filterParameters['lowFreq'], self.opts.filterParameters['order'], self.opts.filterParameters['reversepass'])
# PLOT TIME
self.filterAxs['amVtime'].plot(originalTime, originalSignalTime, label='Original')
self.filterAxs['amVtime'].plot(originalTime, filteredSignalTime, label='Filtered')
self.filterAxs['amVtime'].legend(loc="upper right")
self.filterAxs['amVtime'].set_title('Signal vs Time')
self.filterAxs['amVtime'].set_xlabel('Time (s)', fontsize = 12)
self.filterAxs['amVtime'].set_ylabel('Signal', fontsize = 12)
# PLOT FREQUENCY
self.filterAxs['amVfreq'].plot(originalFreq, np.abs(originalSignalFreq), label='Original')
self.filterAxs['amVfreq'].plot(originalFreq, np.abs(filteredSignalFreq), label='Filtered')
self.filterAxs['amVfreq'].plot(adjusted_w, adjusted_h, label='Butterworth Filter')
self.filterAxs['amVfreq'].legend(loc="upper right")
self.filterAxs['amVfreq'].set_title('Amplitude vs frequency')
self.filterAxs['amVfreq'].set_xlabel('Frequency (Hz)', fontsize = 12)
self.filterAxs['amVfreq'].set_ylabel('Amplitude Signal', fontsize = 12)
# redraw the plots on the popup window
self.figfilter.canvas.draw()
def applyFilter(self, event):
#should we write filtered data for individual seismograms
self.opts.filterParameters['apply'] = True
# replot filtered stuff
self.axstk.clear()
self.ppm.axpp.clear()
self.axs['Fron'].clear()
self.axs['Prev'].clear()
self.axs['Next'].clear()
self.axs['Last'].clear()
self.axs['Zoba'].clear()
self.axs['Shdo'].clear()
self.axs['Shfp'].clear()
self.axs['Shod'].clear()
self.axs['Quit'].clear()
self.ppm = PickPhaseMenu(self.gsac, self.opts, self.axs)
# make the legend box invisible
if self.opts.pick_on:
self.ppm.axpp.get_legend().set_visible(False)
self.plotStack()
# redraw figures
self.ppm.axpp.figure.canvas.draw()
self.axstk.figure.canvas.draw()
# disconnect
self.bnorder.disconnect(self.cidorder)
self.bnunapply.disconnect(self.cidunapply)
self.bnband.disconnect(self.cidband)
self.filterAxs['amVfreq'].figure.canvas.mpl_disconnect(self.cidSelectFreq)
plt.close()
def unapplyFilter(self, event):
# do not write filtered data for individual seismograms
self.opts.filterParameters['apply'] = False
#reset back to original defaults
self.opts.filterParameters['band'] = 'bandpass'
self.opts.filterParameters['lowFreq'] = 0.05
self.opts.filterParameters['highFreq'] = 0.25
self.opts.filterParameters['order'] = 2
# replot filtered stuff
self.axstk.clear()
self.ppm.axpp.clear()
self.axs['Fron'].clear()
self.axs['Prev'].clear()
self.axs['Next'].clear()
self.axs['Last'].clear()
self.axs['Zoba'].clear()
self.axs['Shdo'].clear()
self.axs['Shfp'].clear()
self.axs['Shod'].clear()
self.axs['Quit'].clear()
self.initPlot()
self.plotStack()
# redraw figures
self.ppm.axpp.figure.canvas.draw()
self.axstk.figure.canvas.draw()
# disconnect
self.bnorder.disconnect(self.cidorder)
self.bnapply.disconnect(self.cidapply)
self.bnband.disconnect(self.cidband)
self.filterAxs['amVfreq'].figure.canvas.mpl_disconnect(self.cidSelectFreq)
plt.close()
def getFilterAxes(self):
figfilter = plt.figure(figsize=(15, 12))
self.figfilter = figfilter
rect_amVtime = [0.10, 0.50, 0.80, 0.35]
rect_amVfreq = [0.10, 0.07, 0.80, 0.35]
rectinfo = [0.8, 0.86, 0.15, 0.10]
rectordr = [0.3, 0.86, 0.10, 0.10]
rectunapply = [0.42, 0.90, 0.07, 0.04]
rectapply = [0.5, 0.90, 0.05, 0.04]
rectband = [0.6, 0.86, 0.10, 0.10]
rectreversepass = [0.72, 0.86, 0.07, 0.10]
filterAxs = {}
self.figfilter.text(0.03,0.95,'Butterworth Filter', {'weight':'bold', 'size':21})
filterAxs['amVtime'] = figfilter.add_axes(rect_amVtime)
filterAxs['amVfreq'] = figfilter.add_axes(rect_amVfreq)
filterAxs['ordr'] = figfilter.add_axes(rectordr)
filterAxs['unapply'] = figfilter.add_axes(rectunapply)
filterAxs['apply'] = figfilter.add_axes(rectapply)
filterAxs['band'] = figfilter.add_axes(rectband)
filterAxs['reversepass'] = figfilter.add_axes(rectreversepass)
self.figfilter.text(0.3, 0.97, 'Order:')
self.figfilter.text(0.6, 0.97, 'Filter Type:')
self.figfilter.text(0.72, 0.97, 'Run Reverse:')
# frequencies used to compute butterworth filter displayed here
filterAxs['Info'] = figfilter.add_axes(rectinfo)
filterAxs['Info'].axes.get_xaxis().set_visible(False)
filterAxs['Info'].axes.get_yaxis().set_visible(False)
self.filterAxs = filterAxs
# --------------------------------- Filtering ------------------------------- #
def plot_stations(self, event):
event_name = 'event'
if hasattr(self.opts, 'pklfile'):
event_name = self.opts.pklfile
PlotStations(event_name, self.gsac)
def on_zoom(self, event):
""" Zoom back to previous xlim when event is in event.inaxes.
"""
evkey = event.key
axstk = self.axstk
if not axstk.contains(event)[0] or evkey is None: return
xzoom = self.xzoom
if evkey.lower() == 'z' and len(xzoom) > 1:
del xzoom[-1]
axstk.set_xlim(xzoom[-1])
print('Zoom back to: %6.1f %6.1f ' % tuple(xzoom[-1]))
if self.opts.upylim_on:
for pp in self.pps:
del pp.ynorm[-1]
plt.setp(pp.lines[0], ydata=pp.ybase+pp.sacdh.data*pp.ynorm[-1])
axstk.figure.canvas.draw()
def replot_seismograms(self):
""" Replot seismograms and array stack after running iccs.
"""
sortSeis(self.gsac, self.opts)
self.ppm.initIndex()
self.ppm.replot(0)
self.setLabels()
def replot(self):
""" Replot seismograms and array stack after running iccs.
"""
self.ppstk.disconnect()
self.ppstk.axpp.cla()
self.plotStack()
sortSeis(self.gsac, self.opts)
self.ppm.initIndex()
self.ppm.replot(0)
self.setLabels()
def connect(self):
""" Connect button events. """
# write the position for the buttons into self
self.axccim = self.axs['CCIM']
self.axccff = self.axs['CCFF']
self.axsync = self.axs['Sync']
self.axmccc = self.axs['MCCC']
self.axsac2 = self.axs['SAC2']
self.axsort = self.axs['Sort']
self.axfilter = self.axs['Filter']
self.axplotsta = self.axs['plotsta']
# name the buttons
self.bnccim = Button(self.axccim, 'Align')
self.bnccff = Button(self.axccff, 'Refine')
self.bnsync = Button(self.axsync, 'Sync')
self.bnmccc = Button(self.axmccc, 'Finalize')
self.bnsac2 = Button(self.axsac2, 'SAC P2')
self.bnsort = Button(self.axsort, 'Sort')
self.bnfilter = Button(self.axfilter, 'Filter')
self.bnplotsta = Button(self.axplotsta, 'Map of\n stations')
self.cidccim = self.bnccim.on_clicked(self.ccim)
self.cidccff = self.bnccff.on_clicked(self.ccff)
self.cidsync = self.bnsync.on_clicked(self.sync)
self.cidmccc = self.bnmccc.on_clicked(self.mccc)
self.cidsac2 = self.bnsac2.on_clicked(self.plot2)
self.cidsort = self.bnsort.on_clicked(self.sorting)
self.cidfilter = self.bnfilter.on_clicked(self.filtering)
self.cidplotsta = self.bnplotsta.on_clicked(self.plot_stations)
self.cidpress = self.axstk.figure.canvas.mpl_connect('key_press_event', self.on_zoom)
def disconnect(self):
""" Disconnect button events. """
self.bnccim.disconnect(self.cidccim)
self.bnccff.disconnect(self.cidccff)
self.bnsync.disconnect(self.cidsync)
self.bnmccc.disconnect(self.cidmccc)
self.bnsac2.disconnect(self.cidsac2)
self.bnsort.disconnect(self.cidsort)
self.bnfilter.disconnect(self.cidfilter)
self.axccim.cla()
self.axccff.cla()
self.axsync.cla()
self.axmccc.cla()
self.axsac2.cla()
self.axsort.cla()
self.axfilter.cla()
def syncPick(self):
""" Sync final time pick hdrfin from array stack to all traces.
"""
self.getPicks()
tshift = self.tfin - self.tmed
hdrini, hdrmed, hdrfin = self.opts.qcpara.ichdrs
for sacdh in self.gsac.saclist:
tfin = sacdh.gethdr(hdrmed) + tshift
sacdh.sethdr(hdrfin, tfin)
def syncWind(self):
""" Sync time window relative to hdrfin from array stack to all traces.
Times saved to twhdrs are alway absolute.
"""
wh0, wh1 = self.opts.qcpara.twhdrs
hdrini, hdrmed, hdrfin = self.opts.qcpara.ichdrs
self.getWindow(hdrfin)
twfin = self.twcorr
for sacdh in self.gsac.saclist:
tfin = sacdh.gethdr(hdrfin)
th0 = tfin + twfin[0]
th1 = tfin + twfin[1]
sacdh.sethdr(wh0, th0)
sacdh.sethdr(wh1, th1)
def sync(self, event):
""" Sync final time pick and time window from array stack to each trace and update current page.
"""
hdrini, hdrmed, hdrfin = self.opts.qcpara.ichdrs
wh0, wh1 = self.opts.qcpara.twhdrs
if self.ppstk.sacdh.gethdr(hdrfin) == -12345.:
print('*** hfinal %s is not defined. Pick at array stack first! ***' % hdrfin)
return
self.syncPick()
self.syncWind()
twfin = self.twcorr
for pp in self.ppm.pps:
sacdh = pp.sacdh
tfin = sacdh.gethdr(hdrfin)
ipk = int(hdrfin[1])
tpk = tfin - sacdh.reftime
pp.timepicks[ipk].set_xdata(tpk)
th0 = tfin + twfin[0]
th1 = tfin + twfin[1]
pp.twindow = [th0, th1]
pp.resetWindow()
print('--> Sync final time picks and time window... You can now run CCFF to refine final picks.')
def getWindow(self, hdr):
""" Get time window twcorr (relative to hdr) from array stack, which is from last run.
"""
ppstk = self.ppstk
tw0, tw1 = ppstk.twindow
t0 = ppstk.sacdh.gethdr(hdr)
if t0 == -12345.:
print(('Header {0:s} not defined'.format(hdr)))
return
twcorr = [tw0-t0, tw1-t0]
self.twcorr = twcorr
def getPicks(self):
""" Get time picks of stack
"""
hdrini, hdrmed, hdrfin = self.opts.qcpara.ichdrs
self.tini = self.gsac.stkdh.gethdr(hdrini)
self.tmed = self.gsac.stkdh.gethdr(hdrmed)
self.tfin = self.gsac.stkdh.gethdr(hdrfin)
def ccim(self, event):
# running ICCS-A will erase everything you did. Make sure the user did not hit it by mistake
shouldRun = tkinter.messagebox.askokcancel("Will Erase Work!","This will erase any picks past t1. \nAre you sure?")
if shouldRun:
""" Run iccs with time window from final stack. Time picks: hdrini, hdrmed.
"""
hdrini, hdrmed, hdrfin = self.opts.qcpara.ichdrs
self.cchdrs = hdrini, hdrmed
self.getWindow(self.cchdrs[0])
self.ccStack()
self.getPicks()
self.replot()
def ccff(self, event):
""" Run iccs with time window from final stack. Time picks: hdrfin, hdrfin.
"""
hdrini, hdrmed, hdrfin = self.opts.qcpara.ichdrs
if self.gsac.stkdh.gethdr(hdrfin) == -12345.:
print('*** hfinal %s is not defined. Sync first! ***' % hdrfin)
return
"""running ICCS-B will erase everything you did. Make sure the user did not hit it by mistake"""
shouldRun = tkinter.messagebox.askokcancel("Will Erase Work!","This will erase any picks past t2 and will recalculate all t2 values. \nAre you sure?")
if shouldRun:
self.cchdrs = hdrfin, hdrfin
self.getWindow(self.cchdrs[0])
self.getPicks()
self.ccStack()
stkdh = self.gsac.stkdh
stkdh.sethdr(hdrini, self.tini)
stkdh.sethdr(hdrmed, self.tmed)
self.replot()
def ccStack(self):
"""
Call iccs.ccWeightStack.
Change reference time pick to the input pick before ICCS and to the output pick afterwards.
"""
opts = self.opts
ccpara = opts.ccpara
opts.ccpara.twcorr = self.twcorr
ccpara.cchdrs = self.cchdrs
hdr0, hdr1 = int(ccpara.cchdrs[0][1]), int(ccpara.cchdrs[1][1])
stkdh, stkdata, quas = ccWeightStack(self.gsac.selist, self.opts)
stkdh.selected = True
stkdh.sethdr(opts.qcpara.hdrsel, b'True ')
self.gsac.stkdh = stkdh
if opts.reltime != hdr1:
out = '\n--> change opts.reltime from %i to %i'
print(out % (opts.reltime, hdr1))
opts.reltime = hdr1
def mccc(self, event):
""" Run mccc.py """
gsac = self.gsac
mcpara = self.opts.mcpara
#rcfile = mcpara.rcfile
ipick = mcpara.ipick
wpick = mcpara.wpick
self.getWindow(ipick)
timewindow = self.twcorr
#tw = timewindow[1]-timewindow[0]
taperwindow = taperWindow(timewindow, mcpara.taperwidth)
mcpara.timewindow = timewindow
mcpara.taperwindow = taperwindow
evline, mcname = eventListName(gsac.event, mcpara.phase)
mcpara.evline = evline
mcpara.mcname = mcname
mcpara.kevnm = gsac.kevnm
solution, solist_LonLat, delay_times = mccc(gsac, mcpara)
self.gsac.solist_LonLat = solist_LonLat
self.gsac.delay_times = delay_times
wpk = int(wpick[1])
if self.opts.reltime != wpk:
out = '\n--> change opts.reltime from %i to %i'
print(out % (self.opts.reltime, wpk))
self.opts.reltime = wpk
self.replot()
def plot2(self, event):
""" Plot P2 stack of seismograms for defined time picks (ichdrs + wpick).
"""
opts = copy.copy(self.opts)
twin_on = opts.twin_on
pick_on = opts.pick_on
reltime = opts.reltime
ynorm = opts.ynorm
fill = opts.fill
selist = self.gsac.selist
tpicks = opts.qcpara.ichdrs + [opts.mcpara.wpick,]
npick = len(tpicks)
tlabs = 'ABCDE'
fig2 = plt.figure(figsize=(9,12))
fig2.clf()
plt.subplots_adjust(bottom=.05, top=0.96, left=.1, right=.97, wspace=.5, hspace=.24)
opts.twin_on = False
opts.pick_on = False
ax0 = fig2.add_subplot(npick,1,1)
axsacs = [ ax0 ] + [ fig2.add_subplot(npick,1,i+1, sharex=ax0) for i in list(range(1, npick)) ]
for i in list(range(npick)):
opts.reltime = int(tpicks[i][1])
ax = axsacs[i]
sacp2(selist, opts, ax)
tt = '(' + tlabs[i] + ')'
trans = transforms.blended_transform_factory(ax.transAxes, ax.transAxes)
ax.text(-.05, 1, tt, transform=trans, va='center', ha='right', size=16)
opts.ynorm = ynorm
opts.twin_on = twin_on
opts.pick_on = pick_on
opts.reltime = reltime
opts.fill = fill
opts.zero_on = False
plt.show()
def __init__(self, fileDir):
self.damage_Tag = ''
self.lines = [] # 生成的成果list
self.log = las.LASReader(fileDir, null_subs=np.nan)
self.fig1 = plt.figure('MIT油套管快速评价系统', figsize=(12, 8))
xls = xlrd.open_workbook(".\\casing_data.xls")
table = xls.sheet_by_name('Sheet1')
# 注意下面几个的类型为excel单元格对象
self.outer_diameter = table.cell(0, 2)
self.inner_diameter = table.cell(0, 3)
self.thickness = table.cell(0, 4)
self.scale_left = float(self.inner_diameter.value) / 2 - 20
self.scale_right = float(self.inner_diameter.value) / 2 + 120
self.scale_left_min = float(self.inner_diameter.value) - 30
self.scale_right_max = float(self.inner_diameter.value) + 30
# 定义RadioButtons
axcolor = 'lightgoldenrodyellow'
rax = plt.axes([0.75, 0.05, 0.12, 0.07], facecolor=axcolor)
radio = RadioButtons(rax, (u'Penetration', u'Projection', u'Transformation'), active=-1, activecolor='purple')
plt.subplots_adjust(bottom=0.15, top=0.95, right=0.9, left=0.10, wspace=0.60)
radio.on_clicked(self.actionfunc)
#####################################################################################
# 坐标轴1
self.ax1 = plt.subplot(141)
# 下面赋值加逗号是为了使得type(self.line1)为matplotlib.lines.Line2D对象，而不是list
self.line1, = self.ax1.plot(self.log.data['D01'], self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D02'] + 2.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D03'] + 5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D04'] + 7.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D05'] + 10, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax1.plot(self.log.data['D06'] + 12.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D07'] + 15, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D08'] + 17.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D09'] + 20, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D10'] + 22.5, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax1.plot(self.log.data['D11'] + 25, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D12'] + 27.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D13'] + 30, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D14'] + 32.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D15'] + 35, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax1.plot(self.log.data['D16'] + 37.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D17'] + 40, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D18'] + 42.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D19'] + 45, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D20'] + 47.5, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax1.plot(self.log.data['D21'] + 50, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D22'] + 52.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D23'] + 55, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.plot(self.log.data['D24'] + 57.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax1.set_xlim(self.scale_left, self.scale_right)
self.ax1.set_ylim(self.log.start, self.log.stop)
self.ax1.invert_yaxis()
span1 = SpanSelector(self.ax1, self.onselect1, 'vertical', useblit=False,
rectprops=dict(alpha=0.5, facecolor='yellow'), span_stays=True)
# plt.ylabel(self.log.curves.DEPT.descr + " (%s)" % self.log.curves.DEPT.units)
# plt.xlabel(self.log.curves.D01.descr + " (%s)" % self.log.curves.D01.units)
# plt.title(self.log.well.WELL.data)
plt.ylabel('Measured Depth(m)')
plt.title('Original')
plt.gca().spines['bottom'].set_position(('data', 0))
plt.gca().spines['top'].set_position(('data', 0))
plt.grid()
#####################################################################################
# 坐标轴2
self.ax2 = plt.subplot(142)
self.line2, = self.ax2.plot(self.log.data['D01'], self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D02'] + 2.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D03'] + 5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D04'] + 7.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D05'] + 10, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax2.plot(self.log.data['D06'] + 12.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D07'] + 15, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D08'] + 17.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D09'] + 20, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D10'] + 22.5, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax2.plot(self.log.data['D11'] + 25, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D12'] + 27.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D13'] + 30, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D14'] + 32.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D15'] + 35, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax2.plot(self.log.data['D16'] + 37.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D17'] + 40, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D18'] + 42.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D19'] + 45, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D20'] + 47.5, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax2.plot(self.log.data['D21'] + 50, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D22'] + 52.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D23'] + 55, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.plot(self.log.data['D24'] + 57.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax2.set_xlim(self.scale_left, self.scale_right)
self.ax2.set_ylim(self.log.start, self.log.stop)
self.ax2.invert_yaxis()
span2 = SpanSelector(self.ax2, self.onselect2, 'vertical', useblit=False,
rectprops=dict(alpha=0.5, facecolor='yellow'), span_stays=True)
plt.title('Middle')
plt.gca().spines['bottom'].set_position(('data', 0))
plt.gca().spines['top'].set_position(('data', 0))
self.ax2.grid()
#####################################################################################
# 坐标轴3
self.ax3 = plt.subplot(143)
self.line3, = self.ax3.plot(self.log.data['D01'], self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D02'] + 2.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D03'] + 5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D04'] + 7.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D05'] + 10, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax3.plot(self.log.data['D06'] + 12.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D07'] + 15, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D08'] + 17.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D09'] + 20, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D10'] + 22.5, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax3.plot(self.log.data['D11'] + 25, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D12'] + 27.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D13'] + 30, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D14'] + 32.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D15'] + 35, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax3.plot(self.log.data['D16'] + 37.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D17'] + 40, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D18'] + 42.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D19'] + 45, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D20'] + 47.5, self.log.data['DEPT'], 'r-', lw=0.3)
self.ax3.plot(self.log.data['D21'] + 50, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D22'] + 52.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D23'] + 55, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.plot(self.log.data['D24'] + 57.5, self.log.data['DEPT'], 'g-', lw=0.3)
self.ax3.set_xlim(self.scale_left, self.scale_right)
self.ax3.set_ylim(self.log.start, self.log.stop)
self.ax3.invert_yaxis()
# self.span3_cyan = SpanSelector(self.ax3, self.onselect3, 'vertical', useblit=True,
# rectprops=dict(alpha=0.5, facecolor='cyan'), span_stays=True)
plt.title('Large')
plt.gca().spines['bottom'].set_position(('data', 0))
plt.gca().spines['top'].set_position(('data', 0))
self.ax3.grid()
#####################################################################################
# 坐标轴4
self.ax4 = plt.subplot(144)
self.ax4.plot(self.log.data['IDMX'], self.log.data['DEPT'], 'r--', lw=0.3)
self.ax4.plot(self.log.data['IDMN'], self.log.data['DEPT'], 'b-', lw=0.3)
self.ax4.plot(self.log.data['IDAV'], self.log.data['DEPT'], 'k--', lw=0.3)
self.ax4.set_xlim(self.scale_left_min, self.scale_right_max)
self.ax4.set_ylim(self.log.start, self.log.stop)
self.ax4.invert_yaxis()
plt.title('Min-Max')
plt.gca().spines['bottom'].set_position(('data', 0))
plt.gca().spines['top'].set_position(('data', 0))
self.ax4.grid()
multi = MultiCursor(plt.gcf().canvas, (self.ax1, self.ax2, self.ax3, self.ax4), color='r', lw=1,
horizOn=True, vertOn=False)
#########################
plt.show()
def _setup_browser_selection(raw, kind, selector=True):
"""Organize browser selections."""
import matplotlib.pyplot as plt
from matplotlib.widgets import RadioButtons
from ..selection import (read_selection, _SELECTIONS, _EEG_SELECTIONS,
_divide_to_regions)
from ..utils import _get_stim_channel
_check_option('group_by', kind, ('position, selection'))
if kind == 'position':
order = _divide_to_regions(raw.info)
keys = _SELECTIONS[1:] # no 'Vertex'
kind = 'position'
else: # kind == 'selection'
from ..io import RawFIF, RawArray
if not isinstance(raw, (RawFIF, RawArray)):
raise ValueError("order='selection' only works for Neuromag data. "
"Use order='position' instead.")
order = dict()
try:
stim_ch = _get_stim_channel(None, raw.info)
except ValueError:
stim_ch = ['']
keys = np.concatenate([_SELECTIONS, _EEG_SELECTIONS])
stim_ch = pick_channels(raw.ch_names, stim_ch)
for key in keys:
channels = read_selection(key, info=raw.info)
picks = pick_channels(raw.ch_names, channels)
if len(picks) == 0:
continue # omit empty selections
order[key] = np.concatenate([picks, stim_ch])
misc = pick_types(raw.info,
meg=False,
eeg=False,
stim=True,
eog=True,
ecg=True,
emg=True,
ref_meg=False,
misc=True,
resp=True,
chpi=True,
exci=True,
ias=True,
syst=True,
seeg=False,
bio=True,
ecog=False,
fnirs=False,
exclude=())
if len(misc) > 0:
order['Misc'] = misc
keys = np.concatenate([keys, ['Misc']])
if not selector:
return order
fig_selection = figure_nobar(figsize=(2, 6), dpi=80)
fig_selection.canvas.set_window_title('Selection')
rax = plt.subplot2grid((6, 1), (2, 0), rowspan=4, colspan=1)
topo_ax = plt.subplot2grid((6, 1), (0, 0), rowspan=2, colspan=1)
keys = np.concatenate([keys, ['Custom']])
order.update({'Custom': list()}) # custom selection with lasso
plot_sensors(raw.info,
kind='select',
ch_type='all',
axes=topo_ax,
ch_groups=kind,
title='',
show=False)
fig_selection.radio = RadioButtons(
rax, [key for key in keys if key in order.keys()])
for circle in fig_selection.radio.circles:
circle.set_radius(0.02) # make them smaller to prevent overlap
circle.set_edgecolor('gray') # make sure the buttons are visible
return order, fig_selection
def __init__(self):
''' The constructor creates instances of the walker, biker, and driver
objects from the 'modes' module, sets a default distance and trip
number, and then calculates the time, cost, calories,
and CO2 emissions for all modes of tranit. Then it sets up graphs
for displaying the information, as well as sliders, buttons, and
RadioButtons for gathering user input. The functions that those
buttons execute are defined internally.
'''
# Create instances of the driver, biker, and walker objects
# Whose instance variables will be used heavily in calculations.
self.d = Driver()
self.b = Biker()
self.w = Walker()
# Default vaulues
self.dist = 1
self.trips = 1
# Do initial calculations (calcualte returns calcDict)
self.calcDict = self.calculate()
# Create figure object which we will place everything on
# of dimensions 14" by 10"
self.fig = plt.figure(figsize=(14, 10))
# Create 4 axes objects evenly spaced in a column. These will
# hold the four graphs/figures (time, cost, calories, and CO2.)
self.ax1 = self.fig.add_subplot(411)
self.ax2 = self.fig.add_subplot(412)
self.ax3 = self.fig.add_subplot(413)
self.ax4 = self.fig.add_subplot(414)
# Adjust the location of subplots (the axes holding graphs)
self.fig.subplots_adjust(left=.74,
right=.94,
bottom=.18,
top=.98,
hspace=.25)
### Set up Buttons, RadioButtons, Sliders and their fcns! ###
# The structure of setting up the temporary rax axes, then making
# the RadioButton, then defining it's function, then adding the
# on_clicked statement is taken from this example:
# http://matplotlib.org/examples/widgets/radio_buttons.html
axcolor = 'lightgoldenrodyellow'
def getRadioPosList(ax):
''' This function is simply for positioning the 4 radio buttons
used to change units approporatiely, vertically centered in
relation to the adjacent graph. '''
# Width and height are the same for each radio button
widthRax = 0.12
heightRax = 0.10
# Find the lower (left) x value of adjacent graph
# And construct appropriate x value for radio axes
x0Ax = ax.get_position().get_points()[0, 0]
xRax = x0Ax - (widthRax * 1.8)
# Find lower and upper y values of the adjacent graph,
# average them, and add half the height of the radiobutton axes
# to determine a y value that will vertically center the radiobutton
y0Ax = ax.get_position().get_points()[0, 1]
y1Ax = ax.get_position().get_points()[1, 1]
yRax = ((y0Ax + y1Ax) / 2) - (heightRax / 2)
return [xRax, yRax, widthRax, heightRax]
# Unit Change RadioButton 1: Change Time Units
rax = plt.axes(getRadioPosList(self.ax1), axisbg=axcolor)
self.radioTime = RadioButtons(rax, ('Hours', 'Minutes', 'Audiobooks'))
def timeChange(label):
self.updateGraph()
plt.draw()
self.radioTime.on_clicked(timeChange)
# Unit Change RadioButton 2: Change Money Units
rax = plt.axes(getRadioPosList(self.ax2), axisbg=axcolor)
self.radioCost = RadioButtons(rax, ('Dollars', 'Coffees'))
def costChange(label):
self.updateGraph()
plt.draw()
self.radioCost.on_clicked(costChange)
# Unit Change RadioButton 3: Change calorie burn units
rax = plt.axes(getRadioPosList(self.ax3), axisbg=axcolor)
self.radioCal = RadioButtons(rax, ('Cal (total)', 'Cal (/hour)'))
def calChange(label):
self.updateGraph()
plt.draw()
self.radioCal.on_clicked(calChange)
# Unit Change RadioButton 4: Change CO2 Emissions Units
rax = plt.axes(getRadioPosList(self.ax4), axisbg=axcolor)
self.radioCO2 = RadioButtons(rax, ('CO2 (lbs)', 'CO2 (trees)'))
def CO2Change(label):
self.updateGraph()
plt.draw()
self.radioCO2.on_clicked(CO2Change)
# Sliders 1 and 2: Distnace and Number of Trips
# Axes and instance of slider for distance control
axslideDist = plt.axes([0.17, 0.10, 0.77, 0.03], axisbg=axcolor)
self.slideDist = Slider(axslideDist,
'Distance (miles)',
0.0,
100.0,
valinit=self.dist,
valfmt='%4.2f')
# Axes and instance of slider for number of trips control
axslideTrip = plt.axes([0.17, 0.05, 0.77, 0.03], axisbg=axcolor)
self.slideTrip = Slider(axslideTrip,
'Trips',
0.0,
100.0,
valinit=self.trips,
valfmt='%4.2f')
# Function for updating values after either slider is moved.
def sliderUpdate(val):
self.trips = self.slideTrip.val
self.dist = self.slideDist.val
self.calcDict = self.calculate()
self.updateGraph()
self.slideTrip.on_changed(sliderUpdate)
self.slideDist.on_changed(sliderUpdate)
axcolor = 'gold'
# Customization RadioButton 1: Car - Car Type
rax = plt.axes([.06, .72, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Driving Info", fontsize=11)
rax.text(0, 1.05, "Car Type", fontsize=11)
self.radioCarType = RadioButtons(
rax, ('Average', 'Small Sedan', 'Medium Sedan', 'Large Sedan',
'4WD/Sport', 'Minivan'))
def carTypeChange(label):
''' Adjusts instance of driver object based on the category selected
using the driver object's setCat function.'''
if label == 'Average':
self.d.setCat('average')
elif label == 'Small Sedan':
self.d.setCat('smallSedan')
elif label == ('Medium Sedan'):
self.d.setCat('mediumSedan')
elif label == 'Large Sedan':
self.d.setCat('largeSedan')
elif label == '4WD/Sport':
self.d.setCat('4wdSport')
elif label == 'Minivan':
self.d.setCat('minivan')
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioCarType.on_clicked(carTypeChange)
# Customization RadioButton 2: Bike - Spend on Bike
rax = plt.axes([.26, .72, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Biking Info:", fontsize=11)
rax.text(0, 1.05, "Spend on parts/maintenance ($/year)", fontsize=11)
self.radioBikeSpend = RadioButtons(
rax,
('$0-25', '$25-50', '$50-100', '$100-150', '$150-200', '>$200'),
active=2)
def bikeSpendChange(label):
''' Adjusts instance of biker object based on selected spending,
using the biker object's setSpend fcn. Then updates graph.'''
if label == '$0-25':
self.b.setSpend(12.5)
elif label == '$25-50':
self.b.setSpend(37.5)
elif label == '$50-100':
self.b.setSpend(75)
elif label == ('$100-150'):
self.b.setSpend(125)
elif label == '$150-200':
self.b.setSpend(175)
elif label == '>$200':
self.b.setSpend(250)
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioBikeSpend.on_clicked(bikeSpendChange)
# Customization RadioButton 3: Walk - Spend on Shoes
rax = plt.axes([.06, .424, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Walking Info:", fontsize=11)
rax.text(0, 1.05, "Spend on a new pair of shoes", fontsize=11)
self.radioWalkSpend = RadioButtons(
rax,
('$0-25', '$25-50', '$50-100', '$100-150', '$150-200', '>$200'),
active=1)
def walkSpendChange(label):
''' Changes instance of walker object based on spending.'''
if label == '$0-25':
self.w.setSpend(12.5)
elif label == '$25-50':
self.w.setSpend(37.5)
elif label == '$50-100':
self.w.setSpend(75)
elif label == ('$100-150'):
self.w.setSpend(125)
elif label == '$150-200':
self.w.setSpend(175)
elif label == '>$200':
self.w.setSpend(250)
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioWalkSpend.on_clicked(walkSpendChange)
# Customization RadioButton 4: Person - Sex
rax = plt.axes([.26, .424, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Calorie Burn Info:", fontsize=11)
rax.text(0, 1.05, "Sex", fontsize=11)
self.radioPersonSex = RadioButtons(rax, ('Male', 'Female'), active=0)
def personSexChange(label):
''' Changes the sex of the person instance of the current instnace
of the driver, biker, and walker objects. So much OOP!!!!'''
if label == 'Male':
self.d.person.setSex('M', True)
self.b.person.setSex('M', True)
self.w.person.setSex('M', True)
elif label == 'Female':
self.d.person.setSex('F', True)
self.b.person.setSex('F', True)
self.w.person.setSex('F', True)
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioPersonSex.on_clicked(personSexChange)
# Reset Button
axReset = plt.axes([0.17, 0.25, 0.15, 0.10])
bReset = Button(axReset, 'Reset Defaults')
def resetDefaults(event):
''' Resets all buttons/sliders to their default position,
which triggers recalculations and redrawing of the
graphs. This function is a little slow.'''
self.slideDist.set_val(1)
self.slideTrip.set_val(1)
self.radioTime.set_active(0)
self.radioCost.set_active(0)
self.radioCal.set_active(0)
self.radioCO2.set_active(0)
self.radioCarType.set_active(0)
self.radioBikeSpend.set_active(2)
self.radioWalkSpend.set_active(1)
self.radioPersonSex.set_active(0)
plt.draw()
bReset.on_clicked(resetDefaults)
# These keep the current drawing current.
self.updateGraph()
plt.show()
button.label.set_fontsize(8)
def reset(event):
s0.reset()
s1.reset()
s2.reset()
s3.reset()
button.on_clicked(reset)
rax = plt.axes([
0.025, 0.5 - 0.01 * num_tasks_sampled, 0.18,
0.03 * num_tasks_sampled
],
facecolor=axcolor)
radio = RadioButtons(rax, sample_task_ids, active=0)
def update_y_test(label):
# Update the target_data:
(X_train, y_train), (X_test, y_test) = task_dict[label]
l_button.set_ydata(y_train.data.numpy())
l_button.set_xdata(X_train.data.numpy())
l_button_test.set_ydata(y_test.data.numpy())
l_button_test.set_xdata(X_test.data.numpy())
# Update the fitted data:
if is_VAE:
statistics = statistics_Net(torch.cat([X_train, y_train],
1))[0][0]
else:
statistics = statistics_Net(torch.cat([X_train, y_train],
class RunSim:
''' This class is the core of the program. It uses matplotlib to gather
user input and dispaly results, and also preforms requisite calculations.'''
def __init__(self):
''' The constructor creates instances of the walker, biker, and driver
objects from the 'modes' module, sets a default distance and trip
number, and then calculates the time, cost, calories,
and CO2 emissions for all modes of tranit. Then it sets up graphs
for displaying the information, as well as sliders, buttons, and
RadioButtons for gathering user input. The functions that those
buttons execute are defined internally.
'''
# Create instances of the driver, biker, and walker objects
# Whose instance variables will be used heavily in calculations.
self.d = Driver()
self.b = Biker()
self.w = Walker()
# Default vaulues
self.dist = 1
self.trips = 1
# Do initial calculations (calcualte returns calcDict)
self.calcDict = self.calculate()
# Create figure object which we will place everything on
# of dimensions 14" by 10"
self.fig = plt.figure(figsize=(14, 10))
# Create 4 axes objects evenly spaced in a column. These will
# hold the four graphs/figures (time, cost, calories, and CO2.)
self.ax1 = self.fig.add_subplot(411)
self.ax2 = self.fig.add_subplot(412)
self.ax3 = self.fig.add_subplot(413)
self.ax4 = self.fig.add_subplot(414)
# Adjust the location of subplots (the axes holding graphs)
self.fig.subplots_adjust(left=.74,
right=.94,
bottom=.18,
top=.98,
hspace=.25)
### Set up Buttons, RadioButtons, Sliders and their fcns! ###
# The structure of setting up the temporary rax axes, then making
# the RadioButton, then defining it's function, then adding the
# on_clicked statement is taken from this example:
# http://matplotlib.org/examples/widgets/radio_buttons.html
axcolor = 'lightgoldenrodyellow'
def getRadioPosList(ax):
''' This function is simply for positioning the 4 radio buttons
used to change units approporatiely, vertically centered in
relation to the adjacent graph. '''
# Width and height are the same for each radio button
widthRax = 0.12
heightRax = 0.10
# Find the lower (left) x value of adjacent graph
# And construct appropriate x value for radio axes
x0Ax = ax.get_position().get_points()[0, 0]
xRax = x0Ax - (widthRax * 1.8)
# Find lower and upper y values of the adjacent graph,
# average them, and add half the height of the radiobutton axes
# to determine a y value that will vertically center the radiobutton
y0Ax = ax.get_position().get_points()[0, 1]
y1Ax = ax.get_position().get_points()[1, 1]
yRax = ((y0Ax + y1Ax) / 2) - (heightRax / 2)
return [xRax, yRax, widthRax, heightRax]
# Unit Change RadioButton 1: Change Time Units
rax = plt.axes(getRadioPosList(self.ax1), axisbg=axcolor)
self.radioTime = RadioButtons(rax, ('Hours', 'Minutes', 'Audiobooks'))
def timeChange(label):
self.updateGraph()
plt.draw()
self.radioTime.on_clicked(timeChange)
# Unit Change RadioButton 2: Change Money Units
rax = plt.axes(getRadioPosList(self.ax2), axisbg=axcolor)
self.radioCost = RadioButtons(rax, ('Dollars', 'Coffees'))
def costChange(label):
self.updateGraph()
plt.draw()
self.radioCost.on_clicked(costChange)
# Unit Change RadioButton 3: Change calorie burn units
rax = plt.axes(getRadioPosList(self.ax3), axisbg=axcolor)
self.radioCal = RadioButtons(rax, ('Cal (total)', 'Cal (/hour)'))
def calChange(label):
self.updateGraph()
plt.draw()
self.radioCal.on_clicked(calChange)
# Unit Change RadioButton 4: Change CO2 Emissions Units
rax = plt.axes(getRadioPosList(self.ax4), axisbg=axcolor)
self.radioCO2 = RadioButtons(rax, ('CO2 (lbs)', 'CO2 (trees)'))
def CO2Change(label):
self.updateGraph()
plt.draw()
self.radioCO2.on_clicked(CO2Change)
# Sliders 1 and 2: Distnace and Number of Trips
# Axes and instance of slider for distance control
axslideDist = plt.axes([0.17, 0.10, 0.77, 0.03], axisbg=axcolor)
self.slideDist = Slider(axslideDist,
'Distance (miles)',
0.0,
100.0,
valinit=self.dist,
valfmt='%4.2f')
# Axes and instance of slider for number of trips control
axslideTrip = plt.axes([0.17, 0.05, 0.77, 0.03], axisbg=axcolor)
self.slideTrip = Slider(axslideTrip,
'Trips',
0.0,
100.0,
valinit=self.trips,
valfmt='%4.2f')
# Function for updating values after either slider is moved.
def sliderUpdate(val):
self.trips = self.slideTrip.val
self.dist = self.slideDist.val
self.calcDict = self.calculate()
self.updateGraph()
self.slideTrip.on_changed(sliderUpdate)
self.slideDist.on_changed(sliderUpdate)
axcolor = 'gold'
# Customization RadioButton 1: Car - Car Type
rax = plt.axes([.06, .72, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Driving Info", fontsize=11)
rax.text(0, 1.05, "Car Type", fontsize=11)
self.radioCarType = RadioButtons(
rax, ('Average', 'Small Sedan', 'Medium Sedan', 'Large Sedan',
'4WD/Sport', 'Minivan'))
def carTypeChange(label):
''' Adjusts instance of driver object based on the category selected
using the driver object's setCat function.'''
if label == 'Average':
self.d.setCat('average')
elif label == 'Small Sedan':
self.d.setCat('smallSedan')
elif label == ('Medium Sedan'):
self.d.setCat('mediumSedan')
elif label == 'Large Sedan':
self.d.setCat('largeSedan')
elif label == '4WD/Sport':
self.d.setCat('4wdSport')
elif label == 'Minivan':
self.d.setCat('minivan')
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioCarType.on_clicked(carTypeChange)
# Customization RadioButton 2: Bike - Spend on Bike
rax = plt.axes([.26, .72, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Biking Info:", fontsize=11)
rax.text(0, 1.05, "Spend on parts/maintenance ($/year)", fontsize=11)
self.radioBikeSpend = RadioButtons(
rax,
('$0-25', '$25-50', '$50-100', '$100-150', '$150-200', '>$200'),
active=2)
def bikeSpendChange(label):
''' Adjusts instance of biker object based on selected spending,
using the biker object's setSpend fcn. Then updates graph.'''
if label == '$0-25':
self.b.setSpend(12.5)
elif label == '$25-50':
self.b.setSpend(37.5)
elif label == '$50-100':
self.b.setSpend(75)
elif label == ('$100-150'):
self.b.setSpend(125)
elif label == '$150-200':
self.b.setSpend(175)
elif label == '>$200':
self.b.setSpend(250)
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioBikeSpend.on_clicked(bikeSpendChange)
# Customization RadioButton 3: Walk - Spend on Shoes
rax = plt.axes([.06, .424, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Walking Info:", fontsize=11)
rax.text(0, 1.05, "Spend on a new pair of shoes", fontsize=11)
self.radioWalkSpend = RadioButtons(
rax,
('$0-25', '$25-50', '$50-100', '$100-150', '$150-200', '>$200'),
active=1)
def walkSpendChange(label):
''' Changes instance of walker object based on spending.'''
if label == '$0-25':
self.w.setSpend(12.5)
elif label == '$25-50':
self.w.setSpend(37.5)
elif label == '$50-100':
self.w.setSpend(75)
elif label == ('$100-150'):
self.w.setSpend(125)
elif label == '$150-200':
self.w.setSpend(175)
elif label == '>$200':
self.w.setSpend(250)
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioWalkSpend.on_clicked(walkSpendChange)
# Customization RadioButton 4: Person - Sex
rax = plt.axes([.26, .424, .15, 0.2], axisbg=axcolor)
rax.text(0, 1.15, "Customize Calorie Burn Info:", fontsize=11)
rax.text(0, 1.05, "Sex", fontsize=11)
self.radioPersonSex = RadioButtons(rax, ('Male', 'Female'), active=0)
def personSexChange(label):
''' Changes the sex of the person instance of the current instnace
of the driver, biker, and walker objects. So much OOP!!!!'''
if label == 'Male':
self.d.person.setSex('M', True)
self.b.person.setSex('M', True)
self.w.person.setSex('M', True)
elif label == 'Female':
self.d.person.setSex('F', True)
self.b.person.setSex('F', True)
self.w.person.setSex('F', True)
else:
print('Error!')
self.updateGraph()
plt.draw()
self.radioPersonSex.on_clicked(personSexChange)
# Reset Button
axReset = plt.axes([0.17, 0.25, 0.15, 0.10])
bReset = Button(axReset, 'Reset Defaults')
def resetDefaults(event):
''' Resets all buttons/sliders to their default position,
which triggers recalculations and redrawing of the
graphs. This function is a little slow.'''
self.slideDist.set_val(1)
self.slideTrip.set_val(1)
self.radioTime.set_active(0)
self.radioCost.set_active(0)
self.radioCal.set_active(0)
self.radioCO2.set_active(0)
self.radioCarType.set_active(0)
self.radioBikeSpend.set_active(2)
self.radioWalkSpend.set_active(1)
self.radioPersonSex.set_active(0)
plt.draw()
bReset.on_clicked(resetDefaults)
# These keep the current drawing current.
self.updateGraph()
plt.show()
def calculate(self):
''' This function does all the calculating behind the program. It uses
attributes of the driver, walker, and biker object's to calculate
values for time, cost, calorie burn, and CO2 emitted in various units.
This information is stored in the handy-dandy dictionary: calcDict.'''
# Dictionary that holds calculations for different categories in the form
# of lists, where [0]=driver, [1]=biker, [2]=walker
calcDict = {
'time': [],
'cost': [],
'cal': [],
'time-mins': [],
'time-audio': [],
'cost-coffee': [],
'cal-hour': [],
'cal-sansBMR': [],
'CO2': 0.0,
'CO2-tree': 0.0
}
# Time in hours
calcDict['time'].append(self.dist * self.trips / self.d.getMPH())
calcDict['time'].append(self.dist * self.trips / self.b.getMPH())
calcDict['time'].append(self.dist * self.trips / self.w.getMPH())
# Cost in US dollars
calcDict['cost'].append(self.d.getCost() * self.dist * self.trips)
calcDict['cost'].append(self.b.getCost() * self.dist * self.trips)
calcDict['cost'].append(self.w.getCost() * self.dist * self.trips)
# Total calories burned
calcDict['cal'].append(self.d.person.getCal() * calcDict['time'][0])
calcDict['cal'].append(self.b.person.getCal() * calcDict['time'][1])
calcDict['cal'].append(self.w.person.getCal() * calcDict['time'][2])
## Alternative units for above categories
# Time in audiobooks (based on avg len of 12.59 hours)
# Note: avg length determined from sample of 25 bestsellers on Audible.com
calcDict['time-mins'].append(calcDict['time'][0] * 60)
calcDict['time-mins'].append(calcDict['time'][1] * 60)
calcDict['time-mins'].append(calcDict['time'][2] * 60)
# Time in audiobooks (based on avg len of 12.59 hours)
# Note: avg length determined from sample of 25 bestsellers on Audible.com
calcDict['time-audio'].append(calcDict['time'][0] / 12.59)
calcDict['time-audio'].append(calcDict['time'][1] / 12.59)
calcDict['time-audio'].append(calcDict['time'][2] / 12.59)
#Cost in terms of coffee at blue Mondays burned per hour
calcDict['cost-coffee'].append(calcDict['cost'][0] / 2.60)
calcDict['cost-coffee'].append(calcDict['cost'][1] / 2.60)
calcDict['cost-coffee'].append(calcDict['cost'][2] / 2.60)
#Cal burned per hour
calcDict['cal-hour'].append(self.d.person.getCal())
calcDict['cal-hour'].append(self.b.person.getCal())
calcDict['cal-hour'].append(self.w.person.getCal())
# CO2 emissions in lbs
calcDict['CO2'] = self.d.getCO2() * (self.dist * self.trips)
# CO2 emissions in terms of trees planted
# A single tree planted thru americanforests.org sequesters 911 pounds of CO2
# This value reflects the number of trees one should plant to sequester the carbon
# emitted by driving
calcDict['CO2-tree'] = (calcDict['CO2'] / 911)
return calcDict
def makeGraph(self, ax, data, ylab):
''' makeGraph is called by updateGraph and redraws the 3 graphs
every time it is called. The x labels are always the same but the
y values are passed in as 'data'. '''
ax.clear()
N = 3 # 3 divisions of x axis
maxNum = max(data) # determine max y value
ind = np.arange(N) # the x locations for the groups
width = 0.5 # the width of the bars
## the bars
rects1 = ax.bar(ind, data, width, color=['cyan', 'yellow', 'magenta'])
# axes and labels
ax.set_xlim(-.1, len(ind) - .4)
ax.set_ylim(0, maxNum + (maxNum / 10) * 2)
xTickMarks = ['Drive', 'Bike', 'Walk']
ax.set_xticks(ind + (width / 2))
xtickNames = ax.set_xticklabels(xTickMarks)
ax.set_ylabel(ylab)
def autolabel(rects):
''' Adds labels above bars. Code adapted from matplotlib demo code:
http://matplotlib.org/examples/api/barchart_demo.html'''
# attach some text labels
for rect in rects:
height = rect.get_height()
ax.text(rect.get_x() + rect.get_width() / 2.,
1.05 * height,
'%4.2f' % (height),
fontsize=11,
ha='center',
va='bottom')
autolabel(rects1)
def showInfo(self, ax, data, msg):
''' The forth subplot (axes) holds text instead of a bar plot
and it gets updated using this function.'''
# Erase any existing information to avoid redrawing
ax.clear()
# Remove labels
ax.set_xticklabels('')
ax.set_yticklabels('')
ax.text(.08, .70, "By not driving...", fontsize=11)
ax.text(.4,
.45,
'%4.2f' % (data),
style='italic',
bbox={
'facecolor': 'lightgreen',
'alpha': 0.65,
'pad': 10
})
ax.text(.08, .20, msg, fontsize=11)
def updateGraph(self):
''' This is called whenever the graph needs to be updated. It calls
self.calculate to make sure self.calcDate is up to date and it uses
the values of the radio buttons and sliders as well as the values stored
in calcDict to determine which y values to pass into makeGraph to
make the 3 graphs and which values to pass to showInfo.'''
self.calcDict = self.calculate()
if self.radioTime.value_selected == 'Hours':
self.makeGraph(self.ax1, self.calcDict['time'], 'Time (Hours)')
elif self.radioTime.value_selected == 'Minutes':
self.makeGraph(self.ax1, self.calcDict['time-mins'],
'Time (Minutes)')
elif self.radioTime.value_selected == 'Audiobooks':
self.makeGraph(self.ax1, self.calcDict['time-audio'],
'Time (Audiobooks)')
if self.radioCost.value_selected == 'Dollars':
self.makeGraph(self.ax2, self.calcDict['cost'], 'Cost ($)')
elif self.radioCost.value_selected == 'Coffees':
self.makeGraph(self.ax2, self.calcDict['cost-coffee'],
'Cost (Coffees)')
else:
print('Error!')
if self.radioCal.value_selected == 'Cal (total)':
self.makeGraph(self.ax3, self.calcDict['cal'], 'Calories (total)')
elif self.radioCal.value_selected == 'Cal (/hour)':
self.makeGraph(self.ax3, self.calcDict['cal-hour'],
'Calories (/hour)')
else:
print('Error!')
if self.radioCO2.value_selected == 'CO2 (lbs)':
self.showInfo(self.ax4, self.calcDict['CO2'],
'Pounds of CO2 not emitted')
elif self.radioCO2.value_selected == 'CO2 (trees)':
self.showInfo(self.ax4, self.calcDict['CO2-tree'],
'Trees planted!')
else:
print('Error!')
dust_slider = Slider(ax_dust, 'Dust', -1, 2.5, valinit=0)
hot_gas_slider = Slider(ax_hot_gas, 'Hot Gas', -1, 2.5, valinit=0)
cold_gas_slider = Slider(ax_cold_gas, 'Cold Gas', -1, 2.5, valinit=0)
###############################################################################
#### Radio Buttons ####
radio_length = 0.10
radio_height = 0.10
radio_separation = 0.12
ax_y = plot.axes([
0.05, slider_y + slider_height - radio_height, radio_length, radio_height
])
radio_y = RadioButtons(ax_y, ('linear', 'log'), active=0)
ax_norm = plot.axes([
0.05, slider_y + slider_height - radio_height - radio_separation,
radio_length + 0.10, radio_height
])
radio_norm = RadioButtons(ax_norm, ('normalize blue', 'normalize red'),
active=0)
###############################################################################
### Slider Listeners ###
def update(val):
num_b = b_slider.val
def change_capa(event):
amplifier.set_cap_neut_enable(True, 0)
amplifier.set_cap_neut_level(capa_button.val, 0)
def change_gain(event):
amplifier.set_loop_gain(gain_button.val, 1)
def change_lag(event):
amplifier.set_loop_lag(lag_button.val, 1)
ax_mode = plt.axes([0.05, 0.025, 0.2, 0.125], frameon=False)
mode_button = RadioButtons(ax_mode, ['CC', 'TEVC'])
mode_button.on_clicked(change_mode)
ax_bridge = plt.axes([0.5, 0.025, 0.3, 0.05])
bridge_button = Slider(ax_bridge, 'Bridge', 0, 100, 0)
bridge_button.on_changed(change_bridge)
range = amplifier.get_cap_neut_range(0)
ax_capa = plt.axes([0.5, 0.075, 0.3, 0.05])
capa_button = Slider(ax_capa, 'Capacitance', range.dValMin, range.dValMax, 0)
capa_button.on_changed(change_capa)
ax_gain = plt.axes([0.5, 0.125, 0.3, 0.05])
gain_button = Slider(ax_gain, 'Gain', 20, 500, 20)
gain_button.on_changed(change_gain)
global mask, visibility
if visibility:
mask = mask_base
visibility = False
else:
mask = mask_vel
visibility = True
check.on_clicked(func)
#%% Radio buttom for velocity selection
axrad_vel = pv.add_axes([0.01, 0.65, 0.1, 0.1])
if cumfile2:
radio_vel = RadioButtons(axrad_vel, ('vel', 'vel2'))
mapdict_vel = {'vel': vel, 'vel2': vel2}
else:
radio_vel = RadioButtons(axrad_vel, ('vel', ))
mapdict_vel = {'vel': vel}
def show_vel(val):
global vmin, vmax
data = mapdict_vel[val] * mask
data = data - np.nanmean(data[refy1:refy2, refx1:refx2])
if vlimauto: ## auto
vmin = np.nanpercentile(data * mask, 100 - auto_crange)
vmax = np.nanpercentile(data * mask, auto_crange)
cax.set_data(data)
fig, axSimPlot = plt.subplots(1, 1, figsize=(8, 7))
# レーダの検知可能範囲を描画
axSimPlot.plot(simObject.leftScanBoundary[0,:]/1000, simObject.leftScanBoundary[1,:]/1000, c='#212121')
axSimPlot.plot(simObject.rightScanBoundary[0,:]/1000, simObject.rightScanBoundary[1,:]/1000, c='#212121')
axSimPlot.set_xlabel('X [m]')
axSimPlot.set_ylabel('Y [m]')
axSimPlot.set_xlim([0, 140])
axSimPlot.set_ylim([-80, 80])
axSimPlot.grid()
axSimPlot.axis('equal')
fig.tight_layout()
fig.subplots_adjust(left=0.25, bottom=0.2, right=None, top=None)
# シミュレーションを終了させるラジオボタンオブジェクト
axQuitBttn = plt.axes([0.05, 0.7, 0.1, 0.1], facecolor=radioButtonColor)
quitBttnObj = RadioButtons(axQuitBttn, ('Run', 'Quit'))
# 動作フラグを定義
global simRunFlag
simRunFlag = True
# ボタンが押された時の動作を制御する関数
def SwitchSimRunOrQuit(label):
global simRunFlag
if label == 'Run':
simRunFlag = True
elif label == 'Quit':
simRunFlag = False
else:
simRunFlag = True
# ボタンが押されたら関数を呼び出す
quitBttnObj.on_clicked(SwitchSimRunOrQuit)
sxamp = Slider(xamp, 'A', 0, 3, valinit=A)
syamp = Slider(yamp, 'B', 0, 3, valinit=B)
sxfreq = Slider(xfreq, 'a', 0, 4, valinit=a)
syfreq = Slider(yfreq, 'c', 0, 4, valinit=c)
sxphase = Slider(xphase, 'b', 0, 7, valinit=b)
syphase = Slider(yphase, 'd', 0, 7, valinit=d)
sphase_diff = Slider(phase_diff, 'Rotate', 0, 1, valinit=r)
#Text in window
plt.text(0.40, -0.90, 'controlers', fontsize=14)
#Radio button for graphs
radio = RadioButtons(
rax, ('(0,0)', 'y=0', 'x=0', 'y=x(/)', 'y=-x(\)', 'y=x^2(∪)', 'y=-x^2(∩)',
'x=y^2(⊂)', 'x=-y^2(⊃)', 'x^2+y^2=1(o)', 'Eight(8)', 'Infinity(∞)',
'N', 'И', 'Z', 'S', 'Alpha(∝)', 'Mirror of ∝', 'Gujarati four',
'Mirror of Gujarati four', 'Rotation(∪,∩)3D', 'Rotation(⊂,⊃)3D',
'Rotation(N,И)3D', 'Rotation(Z,S)3D', 'Bangles_X', 'Bangles_Y',
'Crown_X', 'Crown_Y', 'Atom'),
active=3)
#animation function
def animate(i):
#not creating exctra variable using global variables
global A
global B
global a
global b
global c
global d
global r
regularization_strenght = (np.exp(val) - 1) / 40000
if regularized and init:
update_graph(1)
def change_reg_type(label):
global reg_type
reg_type = label
btn_axes = plt.axes([0.75, 0.20, 0.2, 0.06])
fit_button = Button(btn_axes, 'fit')
radio_axes = plt.axes([0.75, 0.68, 0.2, 0.2])
radio_axes.set_title('basis function')
radio_buttons = RadioButtons(radio_axes, ('polynomial', 'gaussian'))
radio_buttons.on_clicked(change_basis_function)
reg_radio_axes = plt.axes([0.75, 0.5, 0.2, 0.15])
reg_button = RadioButtons(reg_radio_axes,
('no regularization', 'regularization'))
reg_button.on_clicked(reg_button_click)
reg_type_axes = plt.axes([0.75, 0.32, 0.2, 0.15])
reg_type_button = RadioButtons(reg_type_axes,
('regularization', 'curvature penalty'))
reg_type_button.on_clicked(change_reg_type)
slider_axes = plt.axes([0.2, 0.08, 0.65, 0.04])
reg_slider = Slider(slider_axes,
'regularization stenght',
class ObjFindGUI(object):
"""
GUI to interactively identify object traces. The GUI can be run within
PypeIt during data reduction, or as a standalone script outside of
PypeIt. To initialise the GUI, call the initialise() function in this
file.
"""
def __init__(self,
canvas,
image,
frame,
det,
sobjs,
trace_dict,
axes,
profdict,
slit_ids=None,
printout=False,
runtime=False):
"""Controls for the interactive Object ID tasks in PypeIt.
The main goal of this routine is to interactively add/delete/modify
object apertures.
Args:
canvas (Matploltib figure canvas): The canvas on which all axes are contained
image (AxesImage): The image plotted to screen
frame (ndarray): The image data
det (int): Detector to add a slit on
sobjs (SpecObjs, None): An instance of the SpecObjs class
trace_dict (dict): A dictionary containing information about the object traces
axes (dict): Dictionary of four Matplotlib axes instances (Main spectrum panel, two for residuals, one for information)
profdict (dict): Dictionary containing profile information (profile data, and the left/right lines displayinf the FWHM)
slit_ids (list, None): List of slit ID numbers
printout (bool): Should the results be printed to screen
runtime (bool): Is the GUI being launched during data reduction?
"""
# Store the axes
self._det = det
self.image = image
self.frame = frame
self.nspec, self.nspat = frame.shape[0], frame.shape[1]
self._spectrace = np.arange(self.nspec)
self.profile = profdict
self._printout = printout
self._runtime = runtime
self._slit_ids = slit_ids
self._trcdict = trace_dict
self.axes = axes
self.specobjs = sobjs
self.objtraces = []
self._object_traces = ObjectTraces()
self.anchors = []
self._obj_idx = -1
self._spatpos = np.arange(frame.shape[1])[np.newaxis, :].repeat(
frame.shape[0], axis=0) # Spatial coordinate (as the frame shape)
self.empty_mantrace()
if sobjs is None:
self._object_traces.from_dict(self._trcdict['objtrc'], det)
else:
self._object_traces.from_specobj(sobjs, det)
# Unset some of the matplotlib keymaps
matplotlib.pyplot.rcParams[
'keymap.fullscreen'] = '' # toggling fullscreen (Default: f, ctrl+f)
#matplotlib.pyplot.rcParams['keymap.home'] = '' # home or reset mnemonic (Default: h, r, home)
matplotlib.pyplot.rcParams[
'keymap.back'] = '' # forward / backward keys to enable (Default: left, c, backspace)
matplotlib.pyplot.rcParams[
'keymap.forward'] = '' # left handed quick navigation (Default: right, v)
#matplotlib.pyplot.rcParams['keymap.pan'] = '' # pan mnemonic (Default: p)
matplotlib.pyplot.rcParams[
'keymap.zoom'] = '' # zoom mnemonic (Default: o)
matplotlib.pyplot.rcParams[
'keymap.save'] = '' # saving current figure (Default: s)
matplotlib.pyplot.rcParams[
'keymap.quit'] = '' # close the current figure (Default: ctrl+w, cmd+w)
matplotlib.pyplot.rcParams[
'keymap.grid'] = '' # switching on/off a grid in current axes (Default: g)
matplotlib.pyplot.rcParams[
'keymap.yscale'] = '' # toggle scaling of y-axes ('log'/'linear') (Default: l)
matplotlib.pyplot.rcParams[
'keymap.xscale'] = '' # toggle scaling of x-axes ('log'/'linear') (Default: L, k)
matplotlib.pyplot.rcParams[
'keymap.all_axes'] = '' # enable all axes (Default: a)
# Initialise the main canvas tools
canvas.mpl_connect('draw_event', self.draw_callback)
canvas.mpl_connect('button_press_event', self.button_press_callback)
canvas.mpl_connect('key_press_event', self.key_press_callback)
canvas.mpl_connect('button_release_event',
self.button_release_callback)
canvas.mpl_connect('motion_notify_event', self.mouse_move_callback)
self.canvas = canvas
# Interaction variables
self._respreq = [
False, None
] # Does the user need to provide a response before any other operation will be permitted? Once the user responds, the second element of this array provides the action to be performed.
self._qconf = False # Confirm quit message
self._changes = False
self._use_updates = True
self._trcmthd = 'object'
self.mmx, self.mmy = 0, 0
self._inslit = 0 # Which slit is the mouse in
# Draw the spectrum
self.canvas.draw()
# Initialise buttons and menu options
self._ax_meth_default = 'Object'
self._methdict = dict({
'Object': [0, 'object'],
'Standard Star': [1, 'std'],
'Slit Edges': [2, 'slit']
})
# 'Manual': [3, 'manual']
self.initialise_menu()
def print_help(self):
"""Print the keys and descriptions that can be used for Identification
"""
keys = operations.keys()
print(
"===============================================================")
print(
"Add/remove object traces until you are happy with the resulting")
print("traces. When you've finished, click one of the exit buttons on")
print(
"the right side of the page. If you click 'Continue (and save changes)'"
)
print(
"the object traces will be printed to the terminal, where you can")
print("copy them into your .pypeit file.")
print("")
print("thick coloured dashed lines = object traces")
print("thick coloured solid line = currently selected object trace")
print("thin green/blue lines = slit edges")
print("")
print("Meanings of the different coloured dashed lines:")
print(" green = user-defined object trace")
print(" blue = trace automatically generated with PypeIt")
print(" red = trace automatically generated with PypeIt (deleted)")
print(
"===============================================================")
print(" OBJECT ID OPERATIONS")
for key in keys:
print("{0:6s} : {1:s}".format(key, operations[key]))
print(
"---------------------------------------------------------------")
def initialise_menu(self):
"""Initialise the menu buttons
"""
axcolor = 'lightgoldenrodyellow'
# Continue with reduction (using updated specobjs)
ax_cont = plt.axes([0.82, 0.85, 0.15, 0.05])
self._ax_cont = Button(ax_cont,
"Continue (and save changes)",
color=axcolor,
hovercolor='y')
self._ax_cont.on_clicked(self.button_cont)
# Continue with reduction (using original specobjs)
ax_exit = plt.axes([0.82, 0.79, 0.15, 0.05])
self._ax_exit = Button(ax_exit,
"Continue (don't save changes)",
color=axcolor,
hovercolor='y')
self._ax_exit.on_clicked(self.button_exit)
# Button to select trace method
rax = plt.axes([0.82, 0.59, 0.15, 0.15], facecolor=axcolor)
rax.set_title("Select trace method:")
self._ax_meth = RadioButtons(
rax, ('Object', 'Standard Star', 'Slit Edges')) #, 'Manual'))
self._ax_meth.on_clicked(self.radio_meth)
# Determine the best default to use:
if self._trcdict["trace_model"]["object"]["trace_model"] is not None:
self._ax_meth_default = 'Object'
elif self._trcdict["trace_model"]["std"]["trace_model"] is not None:
self._ax_meth_default = 'Standard Star'
elif self._trcdict["trace_model"]["slit"]["trace_model"] is not None:
self._ax_meth_default = 'Slit Edges'
# elif self._trcdict["trace_model"]["manual"]["trace_model"] is not None:
# self._ax_meth_default = 'Manual'
# Set the active method
self._ax_meth.set_active(self._methdict[self._ax_meth_default][0])
def radio_meth(self, label, infobox=True):
"""Tell the code what to do when a different trace method is selected
Args:
label (str): The label of the radio button that was clicked
"""
# Update the radio button
if self._methdict[label][1]:
self._trcmthd = self._methdict[label][1]
# Check if the method is available, if not, change to the default (manual is always allowed)
if self._trcmthd != "manual":
if self._trcdict["trace_model"][
self._trcmthd]["trace_model"] is None:
self.update_infobox(
message=
"That option is not available - changing to default",
yesno=False)
self._ax_meth.set_active(
self._methdict[self._ax_meth_default][0])
self._trcmthd = self._methdict[self._ax_meth_default][1]
else:
if infobox:
self.update_infobox(
message="Trace method set to: {0:s}".format(label),
yesno=False)
else:
if infobox:
self.update_infobox(
message="Trace method set to: {0:s}".format(label),
yesno=False)
def button_cont(self, event):
"""What to do when the 'exit and save' button is clicked
"""
self._respreq = [True, "exit_update"]
self.update_infobox(
message=
"Are you sure you want to exit and use the updated object traces?",
yesno=True)
def button_exit(self, event):
"""What to do when the 'exit and do not save changes' button is clicked
"""
self._respreq = [True, "exit_restore"]
self.update_infobox(
message=
"Are you sure you want to exit and use the original object traces?",
yesno=True)
def replot(self):
"""Redraw the entire canvas
"""
self.canvas.restore_region(self.background)
self.draw_objtraces()
self.draw_anchors()
self.canvas.draw()
def draw_objtraces(self):
"""Draw the object traces
"""
for i in self.objtraces:
i.pop(0).remove()
self.objtraces = []
# Plot the object traces
allcols = ['DodgerBlue', 'LimeGreen',
'r'] # colors mean: [original, added, deleted]
for iobj in range(self._object_traces.nobj):
color = allcols[self._object_traces._add_rm[iobj]]
if iobj == self._obj_idx:
self.objtraces.append(self.axes['main'].plot(
self._object_traces._trace_spat[iobj],
self._object_traces._trace_spec[iobj],
color=color,
linestyle='-',
linewidth=4,
alpha=0.5))
else:
self.objtraces.append(self.axes['main'].plot(
self._object_traces._trace_spat[iobj],
self._object_traces._trace_spec[iobj],
color=color,
linestyle='--',
linewidth=3,
alpha=0.5))
def draw_anchors(self):
"""Draw the anchors for manual tracing
"""
for i in self.anchors:
i.pop(0).remove()
self.anchors = []
# Plot the best fitting trace, if it exists
if self._mantrace["spat_trc"] is not None:
self.anchors.append(self.axes['main'].plot(
self._mantrace["spat_trc"],
self._mantrace["spec_trc"],
'g-',
linewidth=3,
alpha=0.5))
# Plot the anchor points on top
self.anchors.append(self.axes['main'].plot(self._mantrace["spat_a"],
self._mantrace["spec_a"],
'ro',
alpha=0.5))
def draw_profile(self):
"""Draw the object profile
"""
if self._obj_idx == -1:
sz = self.profile['profile'].get_xdata.size
self.profile['profile'].set_ydata(np.zeros(sz))
else:
# Plot the extent of the FWHM
self.profile['fwhm'][0].set_xdata(
-self._object_traces._fwhm[self._obj_idx] / 2.0)
self.profile['fwhm'][1].set_xdata(
+self._object_traces._fwhm[self._obj_idx] / 2.0)
# Update the data shown
objprof = self.make_objprofile()
self.profile['profile'].set_ydata(objprof)
self.axes['profile'].set_xlim([
-self._object_traces._fwhm[self._obj_idx],
+self._object_traces._fwhm[self._obj_idx]
])
omin, omax = objprof.min(), objprof.max()
self.axes['profile'].set_ylim(
[omin - 0.1 * (omax - omin), omax + 0.1 * (omax - omin)])
def draw_callback(self, event):
"""Draw callback (i.e. everytime the canvas is being drawn/updated)
Args:
event (Event): A matplotlib event instance
"""
# Get the background
self.background = self.canvas.copy_from_bbox(self.axes['main'].bbox)
self.draw_objtraces()
def get_ind_under_point(self, event):
"""Get the index of the object trace closest to the cursor
Args:
event (Event): Matplotlib event instance containing information about the event
"""
mindist = self._spatpos.shape[0]**2
self._obj_idx = -1
for iobj in range(self._object_traces.nobj):
dist = (event.xdata-self._object_traces._trace_spat[iobj])**2 +\
(event.ydata-self._object_traces._trace_spec[iobj])**2
if np.min(dist) < mindist:
mindist = np.min(dist)
self._obj_idx = iobj
if self._obj_idx != -1:
self.draw_profile()
return
def get_axisID(self, event):
"""Get the ID of the axis where an event has occurred
Args:
event (Event): Matplotlib event instance containing information about the event
Returns:
int, None: Axis where the event has occurred
"""
if event.inaxes == self.axes['main']:
return 0
elif event.inaxes == self.axes['info']:
return 1
elif event.inaxes == self.axes['profile']:
return 2
return None
def mouse_move_callback(self, event):
"""Store the locations of mouse as it moves across the canvas
"""
if event.inaxes is None:
return
axisID = self.get_axisID(event)
if event.inaxes == self.axes['main']:
self.mmx, self.mmy = event.xdata, event.ydata
def button_press_callback(self, event):
"""What to do when the mouse button is pressed
Args:
event (Event): Matplotlib event instance containing information about the event
"""
if event.inaxes is None:
return
if self.canvas.toolbar.mode != "":
return
if event.button == 1:
self._addsub = 1
elif event.button == 3:
self._addsub = 0
if event.inaxes == self.axes['main']:
self._start = [event.x, event.y]
elif event.inaxes == self.axes['profile']:
self._start = [event.x, event.y]
def button_release_callback(self, event):
"""What to do when the mouse button is released
Args:
event (Event): Matplotlib event instance containing information about the event
"""
if event.inaxes is None:
return
if event.inaxes == self.axes['info']:
if (event.xdata > 0.8) and (event.xdata < 0.9):
answer = "y"
elif event.xdata >= 0.9:
answer = "n"
else:
return
self.operations(answer, -1)
self.update_infobox(default=True)
return
elif event.inaxes == self.axes['profile']:
if (event.x == self._start[0]) and (event.y == self._start[1]):
self.set_fwhm(event.xdata)
self.update_infobox(
message="FWHM updated for the selected object",
yesno=False)
return
elif self._respreq[0]:
# The user is trying to do something before they have responded to a question
return
if self.canvas.toolbar.mode != "":
return
# Draw an actor
axisID = self.get_axisID(event)
if axisID is not None:
if axisID <= 2:
self._end = [event.x, event.y]
if (self._end[0] == self._start[0]) and (self._end[1]
== self._start[1]):
# The mouse button was pressed (not dragged)
self.get_ind_under_point(event)
self.update_infobox(message="Object selected", yesno=False)
pass
elif self._end != self._start:
# The mouse button was dragged
if axisID == 0:
if self._start > self._end:
tmp = self._start
self._start = self._end
self._end = tmp
# Now do something
pass
# Now plot
self.canvas.restore_region(self.background)
self.draw_objtraces()
self.canvas.draw()
def key_press_callback(self, event):
"""What to do when a key is pressed
Args:
event (Event): Matplotlib event instance containing information about the event
"""
# Check that the event is in an axis...
if not event.inaxes:
return
# ... but not the information box!
if event.inaxes == self.axes['info']:
return
axisID = self.get_axisID(event)
self.operations(event.key, axisID)
def operations(self, key, axisID):
"""Canvas operations
Args:
key (str): Which key has been pressed
axisID (int): The index of the axis where the key has been pressed (see get_axisID)
"""
# Check if the user really wants to quit
if key == 'q' and self._qconf:
if self._changes:
self.update_infobox(
message=
"WARNING: There are unsaved changes!!\nPress q again to exit",
yesno=False)
self._qconf = True
else:
msgs.bug(
"Need to change this to kill and return the results to PypeIt"
)
plt.close()
elif self._qconf:
self.update_infobox(default=True)
self._qconf = False
# Manage responses from questions posed to the user.
if self._respreq[0]:
if key != "y" and key != "n":
return
else:
# Switch off the required response
self._respreq[0] = False
# Deal with the response
if self._respreq[1] == "delete_object" and key == "y":
self.delete_object()
elif self._respreq[1] == "clear_anchors" and key == "y":
self.empty_mantrace()
self.replot()
elif self._respreq[1] == "exit_update" and key == "y":
self._use_updates = True
self.print_pypeit_info()
self.operations("qu", None)
elif self._respreq[1] == "exit_restore" and key == "y":
self._use_updates = False
self.operations("qr", None)
else:
return
# Reset the info box
self.update_infobox(default=True)
return
if key == '?':
self.print_help()
elif key == 'a':
self.add_object()
elif key == 'c':
if axisID == 0:
# If this is pressed on the main window
self.recenter()
# elif key == 'c':
# self._respreq = [True, "clear_anchors"]
# self.update_infobox(message="Are you sure you want to clear the anchors", yesno=True)
elif key == 'd':
if self._obj_idx != -1:
self._respreq = [True, "delete_object"]
self.update_infobox(
message="Are you sure you want to delete this object trace",
yesno=True)
# elif key == 'm':
# if self._trcmthd != 'manual':
# self.update_infobox(message="To add an anchor point, set the 'manual' trace method", yesno=False)
# else:
# self.add_anchor()
# elif key == 'n':
# self.remove_anchor()
elif key == 'qu' or key == 'qr':
if self._changes:
self.update_infobox(
message=
"WARNING: There are unsaved changes!!\nPress q again to exit",
yesno=False)
self._qconf = True
else:
plt.close()
# elif key == '+':
# if self._mantrace["polyorder"] < 10:
# self._mantrace["polyorder"] += 1
# self.update_infobox(message="Polynomial order = {0:d}".format(self._mantrace["polyorder"]), yesno=False)
# self.fit_anchors()
# else:
# self.update_infobox(message="Polynomial order must be <= 10", yesno=False)
# elif key == '-':
# if self._mantrace["polyorder"] > 1:
# self._mantrace["polyorder"] -= 1
# self.update_infobox(message="Polynomial order = {0:d}".format(self._mantrace["polyorder"]), yesno=False)
# self.fit_anchors()
# else:
# self.update_infobox(message="Polynomial order must be >= 1", yesno=False)
self.replot()
def add_anchor(self):
"""Add a manual anchor point
"""
self._mantrace['spat_a'].append(self.mmx)
self._mantrace['spec_a'].append(self.mmy)
self.fit_anchors()
def remove_anchor(self):
"""Remove a manual anchor point
"""
# Find the anchor closest to the mouse position
if len(self._mantrace['spat_a']) != 0:
mindist = (self._mantrace['spat_a'][0] - self.mmx)**2 + (
self._mantrace['spec_a'][0] - self.mmy)**2
minidx = 0
for ianc in range(1, len(self._mantrace['spat_a'])):
dist = (self._mantrace['spat_a'][ianc] - self.mmx)**2 + (
self._mantrace['spec_a'][ianc] - self.mmy)**2
if dist < mindist:
mindist = dist
minidx = ianc
del self._mantrace['spat_a'][minidx]
del self._mantrace['spec_a'][minidx]
self.fit_anchors()
def fit_anchors(self):
"""Fit the manual anchor points
"""
if len(self._mantrace['spat_a']) <= self._mantrace['polyorder']:
self.update_infobox(
message=
"You need to select more trace points before manually adding\n"
+ "a manual object trace. To do this, use the 'm' key",
yesno=False)
else:
# Fit a polynomial to the anchor points
coeff = np.polyfit(self._mantrace['spec_a'],
self._mantrace['spat_a'],
self._mantrace['polyorder'])
self._mantrace['spat_trc'] = np.polyval(coeff,
self._mantrace['spec_trc'])
# Replot, regardless of whether a fit is done (a point might have been added/removed)
self.replot()
def get_slit(self):
"""Find the slit that the mouse is currently in
"""
ypos = int(self.mmy)
for sl in range(self._trcdict['slit_left'].shape[1]):
if (self.mmx > self._trcdict['slit_left'][ypos, sl]) and (
self.mmx < self._trcdict['slit_righ'][ypos, sl]):
self._inslit = sl
return
def add_object(self):
if self._trcmthd == 'manual' and len(
self._mantrace['spat_a']) <= self._mantrace['polyorder']:
self.update_infobox(
message=
"You need to select more trace points before manually adding\n"
+ "a manual object trace. To do this, use the 'm' key",
yesno=False)
return
# Add an object trace
spec_vec = self._mantrace['spec_trc']
if self._trcmthd == 'manual':
trace_model = self._mantrace['spat_trc'].copy()
# Now empty the manual tracing
self.empty_mantrace()
else:
if self._trcmthd == 'slit':
self.get_slit()
trace_model = self._trcdict["trace_model"][
self._trcmthd]["trace_model"][:, self._inslit].copy()
else:
trace_model = self._trcdict["trace_model"][
self._trcmthd]["trace_model"].copy()
spat_0 = np.interp(self.mmy, spec_vec, trace_model)
shift = self.mmx - spat_0
trace_model += shift
# Determine the FWHM
if self._object_traces.nobj != 0:
fwhm = self._object_traces._fwhm[0]
else: # Otherwise just use the fwhm parameter input to the code (or the default value)
fwhm = 2
# Finally, add this object to the list
self._object_traces.add_object(self._det, self.mmx,
self.mmy, trace_model,
self._spectrace.copy(), fwhm)
def add_object_sobj(self):
"""Add an object to specobjs
"""
if self._trcmthd == 'manual' and len(
self._mantrace['spat_a']) <= self._mantrace['polyorder']:
self.update_infobox(
message=
"You need to select more trace points before manually adding\n"
+ "a manual object trace. To do this, use the 'm' key",
yesno=False)
return
# Add an object trace
spec_vec = self._mantrace['spec_trc']
if self._trcmthd == 'manual':
trace_model = self._mantrace['spat_trc'].copy()
# Now empty the manual tracing
self.empty_mantrace()
else:
trace_model = self._trcdict["trace_model"][
self._trcmthd]["trace_model"].copy()
spat_0 = np.interp(self.mmy, spec_vec, trace_model)
shift = self.mmx - spat_0
trace_model += shift
xsize = self._trcdict["slit_righ"] - self._trcdict["slit_left"]
nsamp = np.ceil(xsize.max())
# Extract the SpecObj parameters
par = self._trcdict['sobj_par']
# Create a SpecObj
thisobj = specobjs.SpecObj(par['frameshape'],
par['slit_spat_pos'],
par['slit_spec_pos'],
det=par['det'],
setup=par['setup'],
slitid=par['slitid'],
orderindx=par['orderindx'],
objtype=par['objtype'])
thisobj.hand_extract_spat = self.mmx
thisobj.hand_extract_spec = self.mmy
thisobj.hand_extract_det = par['det']
thisobj.hand_extract_fwhm = None
thisobj.hand_extract_flag = True
f_ximg = RectBivariateSpline(spec_vec, np.arange(self.nspat),
par["ximg"])
thisobj.spat_fracpos = f_ximg(thisobj.hand_extract_spec,
thisobj.hand_extract_spat,
grid=False) # interpolate from ximg
thisobj.smash_peakflux = np.interp(
thisobj.spat_fracpos * nsamp, np.arange(nsamp),
self._trcdict['profile']) # interpolate from fluxconv
# assign the trace
thisobj.trace_spat = trace_model
thisobj.trace_spec = spec_vec
thisobj.spat_pixpos = thisobj.trace_spat[self.nspec // 2]
thisobj.set_idx()
if self._object_traces.nobj != 0:
thisobj.fwhm = self._object_traces._fwhm[0]
else: # Otherwise just use the fwhm parameter input to the code (or the default value)
thisobj.fwhm = 2
# Finally, add new object
self.specobjs.add_sobj(thisobj)
def delete_object(self):
"""Delete an object trace
"""
self._object_traces.delete_object(self._obj_idx)
self._obj_idx = -1
self.replot()
def delete_object_sobj(self):
"""Delete a specobj
"""
self.specobjs.remove_sobj(self._obj_idx)
self._obj_idx = -1
def print_pypeit_info(self):
"""print text that the user should insert into their .pypeit file
"""
if 1 in self._object_traces._add_rm:
msgs.info(
"Include the following info in the manual_extract column in your .pypeit file:\n"
)
print(self._object_traces.get_pypeit_string())
def recenter(self):
xlim = self.axes['main'].get_xlim()
ylim = self.axes['main'].get_ylim()
xmin = self.mmx - 0.5 * (xlim[1] - xlim[0])
xmax = self.mmx + 0.5 * (xlim[1] - xlim[0])
ymin = self.mmy - 0.5 * (ylim[1] - ylim[0])
ymax = self.mmy + 0.5 * (ylim[1] - ylim[0])
self.axes['main'].set_xlim([xmin, xmax])
self.axes['main'].set_ylim([ymin, ymax])
def make_objprofile(self):
"""Generate an object profile from the traces
"""
coords = self._spatpos - self._object_traces._trace_spat[
self._obj_idx][:, np.newaxis]
ww = np.where(
np.abs(coords) < 4 * self._object_traces._fwhm[self._obj_idx])
bincent = self.profile['profile'].get_xdata()
offs = 0.5 * (bincent[1] - bincent[0])
edges = np.append(bincent[0] - offs, bincent + offs)
prof, _ = np.histogram(coords[ww], bins=edges, weights=self.frame[ww])
return prof / ww[0].size
def set_fwhm(self, xdata):
"""Set the FWHM using the available panel
Args:
xdata (float): The x coordinate selected by the user
"""
self._object_traces._fwhm[self._obj_idx] = 2.0 * np.abs(xdata)
self.draw_profile()
self.replot()
return
def get_specobjs(self):
"""Get the updated version of SpecObjs
Returns:
SpecObjs: SpecObjs Class
"""
if self._use_updates:
msgs.work("Have not updated SpecObjs yet")
return self.specobjs
else:
return None
def update_infobox(self,
message="Press '?' to list the available options",
yesno=True,
default=False):
"""Send a new message to the information window at the top of the canvas
Args:
message (str): Message to be displayed
"""
self.axes['info'].clear()
if default:
self.axes['info'].text(0.5,
0.5,
"Press '?' to list the available options",
transform=self.axes['info'].transAxes,
horizontalalignment='center',
verticalalignment='center')
self.canvas.draw()
return
# Display the message
self.axes['info'].text(0.5,
0.5,
message,
transform=self.axes['info'].transAxes,
horizontalalignment='center',
verticalalignment='center')
if yesno:
self.axes['info'].fill_between(
[0.8, 0.9],
0,
1,
facecolor='green',
alpha=0.5,
transform=self.axes['info'].transAxes)
self.axes['info'].fill_between(
[0.9, 1.0],
0,
1,
facecolor='red',
alpha=0.5,
transform=self.axes['info'].transAxes)
self.axes['info'].text(0.85,
0.5,
"YES",
transform=self.axes['info'].transAxes,
horizontalalignment='center',
verticalalignment='center')
self.axes['info'].text(0.95,
0.5,
"NO",
transform=self.axes['info'].transAxes,
horizontalalignment='center',
verticalalignment='center')
self.axes['info'].set_xlim((0, 1))
self.axes['info'].set_ylim((0, 1))
self.canvas.draw()
def empty_mantrace(self):
"""Generate an empty dictionary for the manual tracing
"""
self._mantrace = dict(spat_a=[],
spec_a=[],
spat_trc=None,
spec_trc=np.arange(self.nspec),
polyorder=0)
return
"Leapfrog": Leapfrog
}
if plot_animation is None:
plot_animation = animation.FuncAnimation(fig,
animate,
init_func=init,
interval=animation_interval,
blit=False)
method_scheme = d[label](init_temp, s, r)
plt.draw()
rax = plt.axes([0.05, 0.7, 0.15, 0.15])
radio = RadioButtons(rax,
("Explicit Downstream", "Explicit Upstream",
"Implicit Downstream", "Implicit Upstream", "Leapfrog"))
def make_temp_sliders(index, ax, label, valmin, valmax):
def slider_on_change(val):
init_temp[index] = val
t_slider = Slider(ax, label, valmin, valmax, valinit=init_temp[index])
t_slider.on_changed(slider_on_change)
return t_slider
left_t_slider = make_temp_sliders(0, plt.axes([0.05, 0.5, 0.15, 0.03]),
"Left temp", -2, 2)
right_t_slider = make_temp_sliders(-1, plt.axes([0.05, 0.6, 0.15, 0.03]),
# In[62]:
fig = plt.figure(figsize=(20, 10))
main = plt.axes([0.1, 0.1, 0.8, 0.8])
ax1 = plt.axes([0.125, 0.05, 0.75, 0.03])
ax2 = plt.axes([0, 0.125, 0.08, 0.75])
slider1 = MyRadioButtons(ax1, [
'pop', 'old_proportion', 'poverty_rate', 'white', 'black', 'hispanic',
'asian', 'house_owner_rate', 'internet', 'gsp', 'household_with_baby',
'unemployment', 'tax', 'democratic_party'
],
orientation="horizontal")
slider2 = RadioButtons(ax2, [
'pop', 'old_proportion', 'poverty_rate', 'white', 'black', 'hispanic',
'asian', 'house_owner_rate', 'internet', 'gsp', 'household_with_baby',
'unemployment', 'tax', 'democratic_party'
])
dot, = main.plot(state[slider1.value_selected], state[slider2.value_selected],
'o')
def updata1(label):
dot.set_data(state[label], state[slider2.value_selected])
lab = np.max(state[label]) - np.min(state[label])
main.set_xlim(
np.min(state[label]) - 0.1 * lab,
np.max(state[label]) + 0.1 * lab)
fig.canvas.draw_idle()
l.set_ydata(amp * np.sin(2 * np.pi * freq * t))
fig.canvas.draw_idle()
sfreq.on_changed(update)
samp.on_changed(update)
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
def reset(event):
sfreq.reset()
samp.reset()
button.on_clicked(reset)
rax = plt.axes([0.025, 0.5, 0.15, 0.15], facecolor=axcolor)
radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
def colorfunc(label):
l.set_color(label)
fig.canvas.draw_idle()
radio.on_clicked(colorfunc)
plt.show()
