def main():
figure = Plot.new_figure(figsize=(5,10))
data_path = lambda x: os.path.join('json', 'fig_4d_difference_' + x + '_lifetime.json')
fits = [ Fit(data_path(fig)) for fig in ['large', 'larger'] ]
for fit in fits:
fit.maps['value_transforms']['τ'] = lambda x: '%.2E' % round(x, 2)
fit.meta['contact_type'] = 'transparent'
plots = []
for idx, fit in enumerate(fits):
n, m = 2, 1
options = {}
if idx != 0: options['sharex'] = plots[idx - 1].plt
plot = Plot(fit, figure.add_subplot(n, m, (m * idx + 1), **options))
plot.id = 'd.' + str(idx + 1)
plots.append(plot)
for plot in plots:
plot.plot_data()
plot.plot_fit()
plot.add_ylabel()
plot.add_parameter_overlay()
plots[-1].add_xlabel()
matplotlib.pyplot.setp(plots[0].plt.get_xticklabels(), visible=False)
figure.savefig(os.path.join('build', 'plot_fits_large_lifetime.eps'), transparent=True)
plots[0].fit.save_info('build/plot_fits_large_lifetime_info.tex', 'plotFitsLargeLifetimeInfo')
Plot.close_figure(figure)
def main():
figure = Plot.new_figure(figsize=(5,10))
fit_ids = ['a', 'b', 'c', 'd']
def data_path(fit_id):
if fit_id == 'c':
fit_type = 'parallel'
else:
fit_type = 'difference'
return os.path.join('json', 'fig_4' + fit_id + '_' + fit_type + '.json')
fits = [ Fit(data_path(fig)) for fig in fit_ids ]
for fit in fits[0:3]:
fit.maps['value_transforms']['Ω_C'] = lambda x: '%.2E' % round(x, 2)
for i in (0, 1): fits[i].meta['contact_type'] = 'tunneling'
fits[2].meta['contact_type'] = 'pinhole'
fits[3].meta['contact_type'] = 'transparent'
plots = []
for idx, fit in enumerate(fits):
n, m = 4, 1
options = {}
if idx != 0: options['sharex'] = plots[idx - 1].plt
plot = Plot(fit, figure.add_subplot(n, m, (m * idx + 1), **options))
plot.id = fit_ids[idx]
plots.append(plot)
for idx, plot in enumerate(plots):
plot.plot_data()
plot.plot_fit()
if idx == 2:
plot.add_ylabel(False)
else:
plot.add_ylabel(True)
plot.add_parameter_overlay()
plots[-1].add_xlabel()
matplotlib.pyplot.setp([ p.plt.get_xticklabels() for p in plots[0:3] ], visible=False)
figure.savefig(os.path.join('build', 'plot_fits.eps'), transparent=True)
plots[0].fit.save_info('build/plot_fits_info.tex', 'plotFitsInfo')
Plot.close_figure(figure)