def mplot(sage_plot, equal_scale=False, edit_res=False):
"""
This function convert sage_plot, created at sage, in matplotlib graph.
"""
plt.clf()
fig = plt.figure()
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
L = sage_plot.matplotlib().gca().lines
for t in L:
data = t.get_data()
ax.add_line(mpl.lines.Line2D(data[0], data[1]))
ax.autoscale_view()
if equal_scale:
ax.axis('equal')
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>", size=2)
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
ax.axis["yzero"].set_axis_direction("left")
ax.minorticks_on()
ax.grid()
if edit_res:
return (fig)
else:
plt.savefig('')
plt.show()
plt.close()
def run(self, results):
par = self.getValueOfParameter("parameter")
i = int(self.getValueOfParameter("iteration number"))
title = self.getValueOfParameter("title")
if(par==""):
return False
if(i >= results.__len__()):
return False
dialogform = Dialog(QApplication.activeWindow())
fig = Figure((5.0, 4.0), dpi=100)
ax = SubplotZero(fig, 1, 1, 1)
fig.add_subplot(ax)
for n in ["top", "right"]:
ax.axis[n].set_visible(False)
for n in ["bottom", "left"]:
ax.axis[n].set_visible(True)
x = results[i].getResults(par)
if(not(x.__len__())):
return False
ax.hist(x, 100, normed=1)
ax.set_xlabel('Error')
ax.set_ylabel('Probability')
ax.grid(True)
ax.set_title(title)
dialogform.showFigure(fig)
return True
fig.add_subplot(ax2)
#
for direction in ["xzero", "yzero"]:
ax2.axis[direction].set_axisline_style("-|>")
ax2.axis[direction].set_visible(True)
#
for direction in ["left", "right", "bottom", "top"]:
ax2.axis[direction].set_visible(False)
ax2.set_aspect('equal')
ax2.set_xlim(Sig_min, Sig_max)
ax2.set_ylim(-(Sig_max-Sig_min)/2, (Sig_max-Sig_min)/2)
ax2.text(0., 1.05, '$\sigma_{nt}$',size=20, transform=BlendedGenericTransform(ax2.transData, ax2.transAxes))
ax2.text(1.05, -0.15, '$\sigma_{nn}$',size=20, transform=BlendedGenericTransform(ax2.transAxes, ax2.transData))
ax2.grid()
mohr_circle, = ax2.plot([], [], '.r',label='Etat de contrainte', markersize=2)
ax2.legend()
# ########################
def Snn_Snt_decomposition (Sigma, n) :
# Check that norm of n is one
n=n/np.linalg.norm(n)
# Flux stress vectir
phi=np.dot(Sigma,n)
# Normal stress component
from numpy import *
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid.axislines import SubplotZero
x = linspace(-5 * pi, 5 * pi, 500)
y = (sin(x) / x)**2
fig = plt.figure(figsize=(8, 4))
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
ax.grid(True)
ax.set_xticks([
-5 * pi, -4 * pi, -3 * pi, -2 * pi, -pi, 0, pi, 2 * pi, 3 * pi, 4 * pi,
5 * pi
])
ax.set_xticklabels([
"$-5 \pi$", "$-4 \pi$", "$-3 \pi$", "$-2 \pi$", "$- \pi$", "0", "$\pi$",
"$2 \pi$", "$3 \pi$", "$4 \pi$", "$5 \pi$"
])
ax.set_ylim((-.3, 1.2))
ax.set_yticklabels([])
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("->")
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
ax.plot(x, y, label=r"$sinc^{2} \ x$", color="k", linewidth=3, alpha=0.8)
ax.text(5.5 * pi, 0., "x")
ax.text(0.1, 1, "1")
ax.legend()
plt.tight_layout()
plt.savefig("sinc.png")
