def plotScatterNorm_ds2_bserr(data_aggPF, name, fullName):
x = data_aggPF['sm_norm_diff_signals_2']['median']
y = data_aggPF['sm_norm_diff_signals_2']['bserr'].apply(lambda x: float(x.split(',')[1][:-1]) - float(x.split(',')[0][1:]))
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=True)
plotlib.setproperties(xlabel='Normalized differential signals',
ylabel='Bootstrapped error',
title=fullName,
labelfontsize=25, tickfontsize=25, equal=True)
plt.savefig(figureDir+'/'+name+'_scatterNorm_ds2_bserr.png')
def plotScatterNorm_QO_ds2(data_aggPF, name, fullName):
x = data_aggPF['QO_norm_signals']['median']
y = data_aggPF['sm_norm_diff_signals_2']['median']
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=True)
plotlib.setproperties(xlim=(-0.09, 1), ylim=(-0.09, 1),
xlabel='Normalized quenched signals',
ylabel='Normalized differential signals 2',
title=fullName,
labelfontsize=25, tickfontsize=25, equal=True)
plt.savefig(figureDir+'/'+name+'_scatterNorm_QO_ds2.png')
def plotScatterNorm_ds2_fbserr(data_aggPF, name, fullName):
x = data_aggPF['sm_norm_diff_signals_2']['median']
y = data_aggPF['sm_norm_diff_signals_2']['bserr'].apply(lambda x: float(x.split(',')[1][:-1]) - float(x.split(',')[0][1:]))
df = pd.concat([x, y / x], axis=1).replace([np.inf, -np.inf], np.nan).dropna()
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(df[0], df[1], alpha=0.7, log=True)
plotlib.setproperties(xlabel='Normalized differential signals',
ylabel='Fractional bootstrapped error',
title=fullName,
labelfontsize=25, tickfontsize=25, equal=True)
plt.savefig(figureDir+'/'+name+'_scatterNorm_ds2_fbserr.png')
def plotScatterNorm_QO_sm_linear(data_aggPF, name, fullName):
x = data_aggPF['quenched_norm']['median']
y = data_aggPF['switch2_norm']['median']
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=False)
plotlib.setproperties(xlim=(-0.09, 1), ylim=(-0.09, 1),
xlabel='Normalized quenched signals',
ylabel='Normalized switching signals',
title=fullName,
labelfontsize=25, tickfontsize=25, equal=True)
plt.savefig(figureDir+'/'+name+'_scatterNorm_QO_sm_linear.png')
def plotScatter_QO_sm(data_aggPF, name, fullName):
x = data_aggPF['QO_signals']['median']
y = data_aggPF['sm_signals']['median']
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=True)
ub = max(np.percentile(x, 99.9), np.percentile(y, 99.9)) * 1.1
plotlib.setproperties(xlim=(0, ub), ylim=(0, ub),
xlabel='Quenched signals',
ylabel='Switching signals',
title=fullName,
labelfontsize=25, tickfontsize=25, equal=True)
plt.savefig(figureDir+'/'+name+'_scatter_QO_sm.png')
def plotScatterNorm_ds2_bserr(data_aggPF, name, fullName):
x = data_aggPF['sm_norm_diff_signals_2']['median']
y = data_aggPF['sm_norm_diff_signals_2']['bserr'].apply(
lambda x: float(x.split(',')[1][:-1]) - float(x.split(',')[0][1:]))
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=True)
plotlib.setproperties(xlabel='Normalized differential signals',
ylabel='Bootstrapped error',
title=fullName,
labelfontsize=25,
tickfontsize=25,
equal=True)
plt.savefig(figureDir + '/' + name + '_scatterNorm_ds2_bserr.png')
def plotScatterNorm_QO_ds1(data_aggPF, name, fullName):
x = data_aggPF['QO_norm_signals']['median']
y = data_aggPF['sm_norm_diff_signals_1']['median']
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=True)
plotlib.setproperties(xlim=(-0.09, 1),
ylim=(-0.09, 1),
xlabel='Normalized quenched signals',
ylabel='Normalized differential signals 1',
title=fullName,
labelfontsize=25,
tickfontsize=25,
equal=True)
plt.savefig(figureDir + '/' + name + '_scatterNorm_QO_ds1.png')
def plotScatter_QO_sm(data_aggPF, name, fullName):
x = data_aggPF['QO_signals']['median']
y = data_aggPF['sm_signals']['median']
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(x, y, alpha=0.7, log=True)
ub = max(np.percentile(x, 99.9), np.percentile(y, 99.9)) * 1.1
plotlib.setproperties(xlim=(0, ub),
ylim=(0, ub),
xlabel='Quenched signals',
ylabel='Switching signals',
title=fullName,
labelfontsize=25,
tickfontsize=25,
equal=True)
plt.savefig(figureDir + '/' + name + '_scatter_QO_sm.png')
def plotScatterNorm_ds2_fbserr(data_aggPF, name, fullName):
x = data_aggPF['sm_norm_diff_signals_2']['median']
y = data_aggPF['sm_norm_diff_signals_2']['bserr'].apply(
lambda x: float(x.split(',')[1][:-1]) - float(x.split(',')[0][1:]))
df = pd.concat([x, y / x], axis=1).replace([np.inf, -np.inf],
np.nan).dropna()
plt.figure(figsize=(7, 7))
plotlib.scatterDensity(df[0], df[1], alpha=0.7, log=True)
plotlib.setproperties(xlabel='Normalized differential signals',
ylabel='Fractional bootstrapped error',
title=fullName,
labelfontsize=25,
tickfontsize=25,
equal=True)
plt.savefig(figureDir + '/' + name + '_scatterNorm_ds2_fbserr.png')