from pylab import *
from plot_utils import plot_2x1
# Must Define
# data2plot
# EH
# EL
#ylims = (2,0.92,1.0)
# Title = r'$SNR = -9$'
plot_2x1(shiftStreams, peakStreams,
['Signal Level', 'Signal Level'], 'Time steps')
fig = gcf()
# dashed lines
fig.axes[0].axvline(x = 300, ls = '--', c = 'k')
fig.axes[0].axvline(x = 600, ls = '--', c = 'k')
fig.axes[1].axvline(x = 300, ls = '--', c = 'k')
fig.axes[1].axvline(x = 600, ls = '--', c = 'k')
#fig.axes[1].axhline(y=EH, ls = '--')
#fig.axes[1].axhline(y=EL, ls = '--')
fig.show()
# Save figure as eps
from pylab import *
from plot_utils import plot_2x1
# Run this script interactively:
# Must first Define
# data2plot
# EH
# EL
ylims = (2, 0.91, 1.0)
Title = ''
plot_2x1(F.res['ht'],
F.res['e_ratio'], ['Hidden Variables', 'Energy Ratio'],
'Time Steps',
Title,
ylims=ylims)
fig = gcf()
# dashed lines
fig.axes[0].axvline(x=300, ls='--', c='k')
fig.axes[0].axvline(x=600, ls='--', c='k')
fig.axes[1].axvline(x=300, ls='--', c='k')
fig.axes[1].axvline(x=600, ls='--', c='k')
fig.axes[1].axhline(y=EH, ls='--')
fig.axes[1].axhline(y=EL, ls='--')
fig.show()
from pylab import *
from plot_utils import plot_2x1
# Run this script interactively:
# Must first Define
# data2plot
# EH
# EL
ylims = (2,0.91,1.0)
Title = ''
plot_2x1(F.res['ht'], F.res['e_ratio'],
['Hidden Variables', 'Energy Ratio'], 'Time Steps',Title, ylims= ylims)
fig = gcf()
# dashed lines
fig.axes[0].axvline(x = 300, ls = '--', c = 'k')
fig.axes[0].axvline(x = 600, ls = '--', c = 'k')
fig.axes[1].axvline(x = 300, ls = '--', c = 'k')
fig.axes[1].axvline(x = 600, ls = '--', c = 'k')
fig.axes[1].axhline(y=EH, ls = '--')
fig.axes[1].axhline(y=EL, ls = '--')
fig.show()
# Save figure as eps
def plot_res(self, var, xname="time steps", ynames=None, title=None, hline=1, anom=1):
if ynames is None:
ynames = [""] * 4
if title is None:
title = self.p["version"]
# Preprocessing
if "exp_ht" in var:
res["exp_ht"][res["exp_ht"] == 0.0] = np.nan
if "S" in self.A_version:
thresh = self.p["t_thresh"]
elif "T" in self.A_version:
thresh = self.p["x_thresh"]
elif "eng" in self.A_version:
thresh = (self.p["e_high"] - self.p["e_low"]) / 2
num_plots = len(var)
for i, v in enumerate(var):
if type(v) == str:
var[i] = getattr(self, "res")[v]
if num_plots == 1:
plt.figure()
plt.plot(var[0])
plt.title(title)
if anom == 1:
for x in self.res["anomalies"]:
plt.axvline(x, ymin=0.25, color="r")
elif num_plots == 2:
plot_2x1(var[0], var[1], ynames[:2], xname, main_title=title)
if hline == 1:
plt.hlines(-thresh, 0, self.res["ht"].shape[0], linestyles="dashed")
plt.hlines(+thresh, 0, self.res["ht"].shape[0], linestyles="dashed")
plt.ylim(-2 * thresh, 2 * thresh)
if anom == 1:
f = plt.gcf()
for ax in f.axes[:-1]:
for x in self.res["anomalies"]:
ax.axvline(x, ymin=0.25, color="r")
elif num_plots == 3:
plot_3x1(var[0], var[1], var[2], ynames[:3], xname, main_title=title)
if hline == 1:
plt.hlines(-thresh, 0, self.res["ht"].shape[0], linestyles="dashed")
plt.hlines(+thresh, 0, self.res["ht"].shape[0], linestyles="dashed")
plt.ylim(-2 * thresh, 2 * thresh)
if anom == 1:
f = plt.gcf()
for ax in f.axes[:-1]:
for x in self.res["anomalies"]:
ax.axvline(x, ymin=0.25, color="r")
elif num_plots == 4:
plot_4x1(var[0], var[1], var[2], var[3], ynames[:4], xname, main_title=title)
plt.title(title)
if hline == 1:
plt.hlines(-thresh, 0, self.res["ht"].shape[0], linestyles="dashed")
plt.hlines(+thresh, 0, self.res["ht"].shape[0], linestyles="dashed")
plt.ylim(-2 * thresh, 2 * thresh)
if anom == 1:
f = plt.gcf()
for ax in f.axes[:-1]:
for x in self.res["anomalies"]:
ax.axvline(x, ymin=0.25, color="r")
def plot_res(self, var, xname = 'Time Steps', ynames = None, title = None, hline= 1, anom = 1):
"""Plots each of the elements given in var.
var = list of variables. Maximum = 4. if string, will look for them in self.res structure
hline = whether to plot threshold values on final plot.
anom = whether to plot anomalous time ticks.
"""
if ynames is None:
ynames = ['']*4
if title is None:
title = (self.p['version'])
if 'SRE' in self.A_version:
thresh = self.p['t_thresh']
num_plots = len(var)
for i, v in enumerate(var):
if type(v) == str :
var[i] = getattr(self, 'res')[v]
if num_plots == 1:
plt.figure()
plt.plot(var[0])
plt.title(title)
if anom == 1:
for x in self.res['anomalies']:
plt.axvline(x, ymin=0.9, color='r')
elif num_plots == 2:
plot_2x1(var[0], var[1], ynames[:2], xname, main_title = title)
if hline == 1:
plt.hlines(-thresh, 0, self.res['ht'].shape[0], linestyles = 'dashed')
plt.hlines(+thresh, 0, self.res['ht'].shape[0], linestyles = 'dashed')
plt.ylim(-3*thresh,3*thresh)
if anom == 1:
f = plt.gcf()
for ax in f.axes[:-1]:
for x in self.res['anomalies']:
ax.axvline(x, ymin=0.9, color='r')
elif num_plots == 3:
plot_3x1(var[0], var[1], var[2], ynames[:3] , xname, main_title = title)
if hline == 1:
plt.hlines(-thresh, 0, self.res['ht'].shape[0], linestyles = 'dashed')
plt.hlines(+thresh, 0, self.res['ht'].shape[0], linestyles = 'dashed')
plt.ylim(-3*thresh,3*thresh)
if anom == 1:
f = plt.gcf()
for ax in f.axes[:-1]:
for x in self.res['anomalies']:
ax.axvline(x, ymin=0.9, color='r')
elif num_plots == 4:
plot_4x1(var[0], var[1], var[2], var[3], ynames[:4], xname, main_title = title)
plt.title(title)
if hline == 1:
plt.hlines(-thresh, 0, self.res['ht'].shape[0], linestyles = 'dashed')
plt.hlines(+thresh, 0, self.res['ht'].shape[0], linestyles = 'dashed')
plt.ylim(-3*thresh,3*thresh)
if anom == 1:
f = plt.gcf()
for ax in f.axes[:-1]:
for x in self.res['anomalies']:
ax.axvline(x, ymin=0.9, color='r')
plt.draw()
from pylab import *
from plot_utils import plot_2x1
# Must Define
# data2plot
# EH
# EL
#ylims = (2,0.92,1.0)
# Title = r'$SNR = -9$'
plot_2x1(shiftStreams, peakStreams, ['Signal Level', 'Signal Level'],
'Time steps')
fig = gcf()
# dashed lines
fig.axes[0].axvline(x=300, ls='--', c='k')
fig.axes[0].axvline(x=600, ls='--', c='k')
fig.axes[1].axvline(x=300, ls='--', c='k')
fig.axes[1].axvline(x=600, ls='--', c='k')
#fig.axes[1].axhline(y=EH, ls = '--')
#fig.axes[1].axhline(y=EL, ls = '--')
fig.show()
# Save figure as eps
filename = 'Peak and shift inputs'