def visualize_test_between_class(test, human, non_human):
fig = plt.figure("Trajectories for Test, Human, and Non-Human")
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
line_style = ['r.-', 'gx-', 'bo-']
# plotting test data
x = [i.pose.position.x for i in test]
y = [i.pose.position.y for i in test]
ax.plot(x, y, line_style[0], label="Test")
# plotting human data
x = [i.pose.position.x for i in human]
y = [i.pose.position.y for i in human]
ax.plot(x, y, line_style[1], label="Human")
# plotting non-human data
x = [i.pose.position.x for i in non_human]
y = [i.pose.position.y for i in non_human]
ax.plot(x, y, line_style[2], label="Non-human")
ax.margins(0.05)
ax.legend(loc="lower right", fontsize=10)
plt.title("Chunks of Trajectories")
plt.xlabel("Axis")
plt.ylabel("Ordinate")
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)
pylab.grid()
plt.show()
def test_m_n_computation(obj_img, theta, Nx, Ny, dx, dy, Nt, Nr, dr):
bx = -Nx/2 * dx
by = -Ny/2 * dy
xmin = -(Nx-1)/2.0*dx
ymin = -(Ny-1)/2.0*dy
legend_list = []
fig = plt.figure(figsize=(8,8))
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
plt.imshow(obj_img, cmap=plt.cm.gray, interpolation='none', \
extent=[bx,-bx, by, -by], alpha=0.5)
for t in np.arange(Nr):
if np.sin(theta) < 1.0/np.sqrt(2):
data = test_n_computation(theta, t, Nx, Ny, dx, dy, Nt, Nr, dr)
else:
data = test_m_computation(theta, t, Nx, Ny, dx, dy, Nt, Nr, dr)
#rdata = np.round(data)
plt.plot(data[0,:]*dx+xmin, data[1,:]*dy+ymin,'*-', linewidth = 3 )
legend_list.append('(t=' + str(t) + ')')
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
ax.xaxis.set_ticks(np.arange(-Nx,Nx,2))
ax.yaxis.set_ticks(np.arange(-Ny,Ny,2))
plt.axis('equal')
plt.grid(True)
plt.legend(legend_list)
plt.title('Angle: ' + str(theta*180/np.pi))
def setup_two_axes_subplot(fig, m, n, curr_plot_num, invisible=["bottom", "top", "right"]):
ax = SubplotZero(fig, m, n, curr_plot_num)
fig.add_subplot(ax)
ax.axis["xzero"].set_visible(True)
for n in invisible:
ax.axis[n].set_visible(False)
return ax
def plot_func(a, b, c, out_putline):
'''Plot the line function in a coordinate axis
Parameters:
a -- The coefficient for y in the standard for Ay + Bx = C
b -- The coefficient for x in the standard for Ay + Bx = C
c -- The constanct C in the standard for Ay + Bx = C
out_putline -- The string of the standard form Ay + Bx = C
'''
# Unable to plot if the coefficient of x or y equals to 0
if b == 0:
sys.stderr.write('Unable to plot a vertical line!!!\n')
sys.exit(1)
if a == 0:
sys.stderr.write('Unable to plot a horizontal line!!!\n')
sys.exit(1)
# General steps to generate an axis
try:
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
except Exception, e:
sys.stderr.write('Unable to use matplotlib!!!\n')
sys.exit(1)
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 _blank_plot(domain, ran):
# make the plot
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
# thicken the axis lines
ax.axhline(linewidth=1.7, color="k")
ax.axvline(linewidth=1.7, color="k")
x_lower, x_upper = int(domain.left), int(
domain.right) # needs to be changed, is just a temporary type changer
y_lower, y_upper = int(ran.left), int(ran.right)
# remove tick lines on the axes
plt.xticks([])
plt.yticks([])
plt.ylim(y_lower, y_upper)
plt.xlim(x_lower, x_upper)
# add axes labels
ax.text(1.05,
0,
r'$x$',
transform=BlendedGenericTransform(ax.transAxes, ax.transData),
va='center')
ax.text(0,
1.05,
r'$y$',
transform=BlendedGenericTransform(ax.transData, ax.transAxes),
ha='center')
# end-of-axis arrows
x_width = (abs(plt.xlim()[0]) + abs(plt.xlim()[1]))
y_width = (abs(plt.ylim()[0]) + abs(plt.ylim()[1]))
plt.arrow(plt.xlim()[1],
-0.003,
0.00000000001,
0,
width=x_width * 0.0015 * 0.5,
color="k",
clip_on=False,
head_width=y_width * 0.12 / 7,
head_length=x_width * 0.024 * 0.5)
plt.arrow(0.003,
plt.ylim()[1],
0,
0.00000000001,
width=y_width * 0.0015 * 0.5,
color="k",
clip_on=False,
head_width=x_width * 0.12 / 7,
head_length=y_width * 0.024 * 0.5)
# only show cartesian axes
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
def plot_L(self):
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
for el in self.L:
self.plot_box(X=el, index=0, this_color='blue', canvas=ax)
ax.set_xlim(-15., 15.)
ax.set_ylim(-15., 15.)
ax.axis('equal')
plt.show()
def subplots():
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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)
return fig, ax
def __init__(self):
self.fig = plt.figure(1)
self.ax = SubplotZero(self.fig,111)
self.fig.add_subplot(self.ax)
for direction in ["xzero","yzero"]:
self.ax.axis[direction].set_axisline_style("-|>")
self.ax.axis[direction].set_visible(True)
for direction in ["left","right","bottom","top"]:
self.ax.axis[direction].set_visible(False)
def renderGraph(self): # pylint: disable=R0914
assert len(self._oData.aoSeries) == 1
oSeries = self._oData.aoSeries[0]
# hacking
#self.setWidth(512);
#self.setHeight(128);
# end
oFigure = self._createFigure()
from mpl_toolkits.axes_grid.axislines import SubplotZero
# pylint: disable=E0401
oAxis = SubplotZero(oFigure, 111)
oFigure.add_subplot(oAxis)
# Disable all the normal axis.
oAxis.axis['right'].set_visible(False)
oAxis.axis['top'].set_visible(False)
oAxis.axis['bottom'].set_visible(False)
oAxis.axis['left'].set_visible(False)
# Use the zero axis instead.
oAxis.axis['yzero'].set_axisline_style('-|>')
oAxis.axis['yzero'].set_visible(True)
oAxis.axis['xzero'].set_axisline_style('-|>')
oAxis.axis['xzero'].set_visible(True)
if oSeries.aoYValues[-1] == 100:
sColor = 'green'
elif oSeries.aoYValues[-1] > 75:
sColor = 'yellow'
else:
sColor = 'red'
oAxis.plot(oSeries.aoXValues,
oSeries.aoYValues,
'.-',
color=sColor,
linewidth=3)
oAxis.fill_between(oSeries.aoXValues,
oSeries.aoYValues,
facecolor=sColor,
alpha=0.5)
oAxis.set_xlim(left=-0.01)
oAxis.set_xticklabels([])
oAxis.set_xmargin(1)
oAxis.set_ylim(bottom=0, top=100)
oAxis.set_yticks([0, 50, 100])
oAxis.set_ylabel('%')
#oAxis.set_yticklabels([]);
oAxis.set_yticklabels(['', '%', ''])
return self._produceSvg(oFigure, False)
def plot(points):
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
plt.ylim([-10, 10])
plt.xlim([-10, 10])
ax.plot(*zip(*points), marker='o', color='r', ls='')
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)
plt.show()
def plot_subpaving(self):
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
for el in self.outside:
self.plot_box(X=el, index=0, this_color='red', canvas=ax)
for el in self.boundary:
self.plot_box(X=el, index=0, this_color='yellow', canvas=ax)
for el in self.inside:
self.plot_box(X=el, index=0, this_color='green', canvas=ax)
ax.set_xlim(-12., 12.)
ax.set_ylim(-12., 12.)
ax.axis('equal')
plt.show()
return
def setup_two_axes(fig, labelpad=1, invisible=["bottom", "top", "right"]):
plt.rcParams['xtick.major.pad'] = 0.1
plt.rcParams['xtick.minor.pad'] = 0.1
plt.rcParams['ytick.major.pad'] = 2
plt.rcParams['ytick.minor.pad'] = 2
ax = SubplotZero(fig, 1, 1, 1)
ax.yaxis.labelpad = labelpad
fig.add_subplot(ax)
# make xzero axis (horizontal axis line through y=0) visible.
ax.axis["xzero"].set_visible(True)
ax.xaxis.labelpad = labelpad
# make other axis (bottom, top, right) invisible.
for n in invisible:
ax.axis[n].set_visible(False)
return ax
def initplot(size):
"""
Inicializa o desenho de gráficos.
"""
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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.set_xlim(-10, size)
ax.set_ylim(-10, size)
return (fig, ax)
def test():
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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)
x = np.linspace(-0.5, 1., 100)
ax.plot(x, np.sin(x * np.pi))
plt.show()
def open_window_and_show_results(points, curve, bezier_points):
# Generate the curve
curve_begin = min(points, key=lambda p: p.x)
curve_end = max(points, key=lambda p: p.x)
curve_begin = floor(curve_begin.x)
curve_end = ceil(curve_end.x)
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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)
curve_points = []
if (len(curve) == 3):
curve_points = generate_curve_points_quadratic(
[x * 0.1 for x in range(curve_begin * 10, curve_end * 10)],
curve[0], curve[1], curve[2]) # values for x²
elif (len(curve) == 4):
curve_points = generate_curve_points_cubic(
[x * 0.1 for x in range(curve_begin * 10, curve_end * 10)],
curve[0], curve[1], curve[2], curve[3]) # values for x²
else:
raise "Length of curve has to be 3 or 4"
# plot_points(plt, curve_points, 'blue')
# plot_points(plt, points, 'ro')
plot_points(plt, points, 'red')
plot_points(plt, bezier_points, 'go')
plot_points(
plt,
draw_bezier_curve(bezier_points[0], bezier_points[1], bezier_points[2],
bezier_points[3]), 'orange')
plt.show()
def test_min_max_plane_indices(obj_img, Nx, Ny, dx, dy, Nt, Nr, dr):
bx = -Nx / 2 * dx
by = -Ny / 2 * dy
fovx = Nx * dx
fovy = Ny * dy
r = np.ceil(np.sqrt((fovx)**2 + (fovy)**2))
xc = dx / 2
yc = -dy / 2
sdd = 2 * r
p1x = np.zeros(Nt, dtype=TYPE)
p1y = np.zeros(Nt, dtype=TYPE)
p2x = np.zeros(Nt, dtype=TYPE)
p2y = np.zeros(Nt, dtype=TYPE)
for angle in np.arange(Nt):
text = ''
legend_list = []
fig = plt.figure(figsize=(8, 8))
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
plt.imshow(obj_img, cmap=plt.cm.gray, interpolation='none', \
extent=[bx,-bx, by, -by], alpha=0.5)
for t in np.arange(-Nr / 2, Nr / 2):
# find p1-detector and p2-source coordinates
p1x[angle], p1y[angle] = get_p1(angle * np.pi / Nt, t, r, xc, yc,
dr)
p2x[angle], p2y[angle] = get_p2(angle*np.pi/Nt, sdd, p1x[angle], \
p1y[angle])
plt.plot( [p1x[angle], p2x[angle]] ,[p1y[angle], p2y[angle]], ':',\
linewidth = 3 )
imin, imax, jmin, jmax = min_max_plane_indices(Nx, Ny, \
p1x[angle], p1y[angle], p2x[angle], p2y[angle], bx, by, dx, dy)
text += '(t=' + str(t) + ') imin:' + str(imin) + ', imax:' + \
str(imax) + ' ,jmin:' + str(jmin) + ' ,jmax:' + \
str(jmax) + '\n'
legend_list.append('(t=' + str(t) + ')')
for direction in ["xzero", "yzero"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
ax.xaxis.set_ticks(np.arange(-Nx, Nx, 2))
ax.yaxis.set_ticks(np.arange(-Ny, Ny, 2))
plt.axis('equal')
plt.grid(True)
plt.legend(legend_list)
plt.title(text, fontsize=10)
def make_zerocross_axes(figsize, loc):
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid.axislines import SubplotZero
fig = plt.figure(figsize=figsize)
ax = SubplotZero(fig, loc)
ax.set_aspect("equal")
fig.add_subplot(ax)
for direction in ["xzero", "yzero"]:
axis = ax.axis[direction]
axis.set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
return ax
def make_plot_ax():
fig = figure(figsize=(6, 5))
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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)
xlim(-0.1, 2.1)
ylim(xlim())
ticks = [0.5 * i for i in range(1, 5)]
labels = [str(i) if i == int(i) else "" for i in ticks]
ax.set_xticks(ticks)
ax.set_yticks(ticks)
ax.set_xticklabels(labels)
ax.set_yticklabels(labels)
ax.axis["yzero"].set_axis_direction("left")
return ax
def plot_points_helper(x, y, x_poly, y_poly, scale_plot=True):
figure = plt.figure(figsize=(12, 8))
ax = SubplotZero(figure, 111)
figure.add_subplot(ax)
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)
scale = np.mean(x[x > 0]) + np.mean(y[y > 0]) if scale_plot else 0
plt.xlim([min(x) - scale, max(x) + scale])
plt.ylim([min(y) - scale, max(y) + scale])
plt.scatter(x, y)
plt.plot(x_poly, y_poly, color='r')
plt.show()
def plotUnitCircle(p):
""" plot some 2D vectors with p-norm < 1 """
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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)
x = np.linspace(-1.0, 1.0, 1000)
y = np.linspace(-1.0, 1.0, 1000)
X, Y = np.meshgrid(x, y)
F = (((abs(X) ** p + abs(Y) ** p) ** (1.0 / p)) - 1)
ax.contour(X, Y, F, [0])
plt.savefig('UnitCircle.pdf', facecolor='w', edgecolor='w',
papertype=None, format='pdf', transparent=False,
bbox_inches='tight', pad_inches=0.1)
plt.show()
def create_plot(self, scale, y_bounds, points=None, file_name=None):
"""
Using matplotlib, graphs the given points on a Cartesian plane.
Adapted from the matplotlib documentation:
https://matplotlib.org/examples/axes_grid/demo_axisline_style.html.
args:
scale: Numpy array of increments for the x-axis.
points: Numpy array of points' Y-values to be plotted.
y_bounds: integer determining scale of y axis
file_name: name for plot to be serialized under.
"""
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
fig = plt.figure(1)
subplot = SubplotZero(fig, 111)
fig.add_subplot(subplot)
for direction in ['xzero', 'yzero']:
subplot.axis[direction].set_axisline_style('-|>')
subplot.axis[direction].set_visible(True)
for direction in ['left', 'right', 'bottom', 'top']:
subplot.axis[direction].set_visible(False)
subplot.set_ylim([-y_bounds, y_bounds])
if points is not None:
subplot.plot(scale, points)
if file_name:
plt.savefig(file_name)
else:
plt.show()
ax0.axis('off')
ax0.set_title('extracellular potential')
ax1 = fig.add_subplot(gs[:6, 1], aspect='equal') # dipole moment ill.
ax1.axis('off')
ax1.set_title('extracellular potential')
ax2 = fig.add_subplot(gs[:6, 2], aspect='equal') # dipole moment ill.
ax2.axis('off')
ax2.set_title('magnetic field')
# ax3 = fig.add_subplot(gs[0, 3], aspect='equal') # spherical shell model ill.
# ax3.set_title('4-sphere volume conductor')
# ax4 = fig.add_subplot(gs[1, 3],
# aspect='equal'
# ) # MEG/EEG forward model ill.
# ax4.set_title('EEG and MEG signal detection')
ax3 = SubplotZero(fig, gs[7:, 0])
fig.add_subplot(ax3)
ax3.set_title('4-sphere volume conductor', verticalalignment='bottom')
ax4 = fig.add_subplot(gs[7:, 1]) # EEG
ax4.set_title('scalp electric potential $\phi_\mathbf{p}(\mathbf{r})$')
ax5 = fig.add_subplot(gs[7:, 2], sharey=ax4) # MEG
# ax5.set_title('scalp magnetic field')
#morphology - line sources for panels A and B
zips = []
xz = cell.get_idx_polygons()
for x, z in xz:
zips.append(zip(x, z))
for ax in [ax0]:
polycol = PolyCollection(zips,
linewidths=(0.5),
alphabet[4],
horizontalalignment='center',
verticalalignment='center',
fontsize=16,
fontweight='demibold',
transform=ax.transAxes)
plotting.remove_axis_junk(ax)
t = np.arange(p_net.shape[1]) * PSET.dt * PSET.decimate_q
inds = (t >= T[0]) & (t <= T[1])
ax.plot(t[inds], p_net[i, inds], 'k', lw=1)
ax.set_ylabel(ylabel)
ax.set_xticklabels([])
# panel F. Illustration of 4-sphere volume conductor model geometry
ax = SubplotZero(fig, gs[2, 1])
fig.add_subplot(ax)
ax.set_title('four-sphere volume conductor model')
for direction in ["xzero"]:
ax.axis[direction].set_visible(True)
for direction in ["left", "right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
theta = np.linspace(0, np.pi, 31)
# draw some circles:
for i, r, label in zip(range(4), PSET.foursphereParams['radii'],
['brain', 'CSF', 'skull', 'scalp']):
ax.plot(np.cos(theta) * r,
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 15 23:07:24 2017
@author: Lenovo-Y430p
"""
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid.axislines import SubplotZero
import numpy as np
width = 1 # 两条柱之间的距离
num = 5 #柱的个数
ind = np.arange(num)
fig = plt.figure(figsize=(15, 4))
ax = SubplotZero(fig, 1, 3, 1)
ax1 = fig.add_subplot(ax)
means = [0.6481, 0.6215, 0.58, 0.56, 0.442]
stds = [0.0129, 0.0119, 0.01, 0.009, 0.003]
plt.bar(0.2 + ind,
means,
0.6 * width,
color=['k', 'r', 'c', 'y', 'r'],
linewidth=0.1,
yerr=stds,
error_kw=dict(elinewidth=1.5, ecolor='green'))
plt.axis([0, 5, 0, 1])
plt.ylabel(u'wPrecision')
plt.grid()
plt.xticks([])
#!/usr/bin/env python3
from mpl_toolkits.axes_grid.axislines import SubplotZero
from matplotlib.transforms import BlendedGenericTransform
import matplotlib.patches as mpatches
import matplotlib.pyplot as plt
import numpy as np
if __name__ == '__main__':
fig = plt.figure(1)
ax = SubplotZero(fig, 1, 1, 1)
# fig.autofmt_xdate(bottom=0.2, rotation=30, ha='right')
fig.add_subplot(ax)
ax.text(-1.15, 0.99, 'y', transform=BlendedGenericTransform(ax.transData, ax.transAxes), ha='center')
ax.text(1., -0.25, 'x', transform=BlendedGenericTransform(ax.transAxes, ax.transData), va='center')
#
for direction in ["xzero", "left"]:
ax.axis[direction].set_axisline_style("-|>")
ax.axis[direction].set_visible(True)
for direction in ["right", "bottom", "top"]:
ax.axis[direction].set_visible(False)
x = np.linspace(-1., +1., 1000) # x < 0
# print(x)
# ########################
Sigma=np.array([[S11,S12,S13],[S12,S22, S23 ],[S13,S23, S33 ]],float)
print("Sigma=", Sigma)
VP=np.linalg.eigvals(Sigma)
Sig_max= np.max((VP)) + 5
Sig_min= np.min((VP)) - 5
# ########################
# Set up the figure, the axis, and the plot element we want to animate
# ########################
fig = plt.figure(1)
# Espace x,y
# Espace Snn,Snt
ax2 = SubplotZero(fig, 111)
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))
"""
Created on Fri Jun 23 10:19:29 2017
@author: Lenovo-Y430p
"""
from pylab import mpl
mpl.rcParams['font.sans-serif'] = ['SimHei']
#from numpy import *
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import math
from mpl_toolkits.axes_grid.axislines import SubplotZero
fig = plt.figure()
ax = SubplotZero(fig, 2, 2, 1)
ax1 = fig.add_subplot(ax)
#rect=[0.1,0.1,0.8,0.8]
#axprops = dict(xticks=[], yticks=[])
#ax0=fig.add_axes(rect, label='ax0',**axprops)
imgP = plt.imread("面积11.jpg")
ax1.imshow(imgP / 256)
#ax1=fig.add_axes(rect, label='ax1',frameon=False)
#x = np.linspace(0,10,100)
#y = math.sin(x)
#ax1.plot(x,y)
ax1.set_title(" 10mm2 in 0.5h")
#ax1.set_ylim([-5,12])
ax = SubplotZero(fig, 2, 2, 2)
ax2 = fig.add_subplot(ax)
#!/bin/env python
from mpl_toolkits.axes_grid.axislines import SubplotZero
import matplotlib.pyplot as plt
import numpy as np
if 1:
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
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)
x = np.linspace(-0.5, 1., 100)
ax.plot(x, np.sin(x * np.pi))
plt.show()
plt.savefig("foo.png")
plt.savefig("foo.eps")
plt.savefig("foo.pdf")
##Input : the stress tensor
##Output : anmiation
# ########################
# INPUT : Stress tensor ! must be a plan stress state !
# ########################
Sigma = np.array([[400, 100, 0], [100, -200, 0], [0, 0, 0]], float)
print("Sigma=", Sigma)
# ########################
# Set up the figure, the axis, and the plot element we want to animate
# ########################
fig = plt.figure(1)
Sig_max = 500.0
# Espace x,y
ax1 = SubplotZero(fig, 121)
fig.add_subplot(ax1)
#
for direction in ["xzero", "yzero"]:
ax1.axis[direction].set_axisline_style("-|>")
ax1.axis[direction].set_visible(True)
#
for direction in ["left", "right", "bottom", "top"]:
ax1.axis[direction].set_visible(False)
ax1.set_aspect('equal')
ax1.set_xlim(-Sig_max, Sig_max)
ax1.set_ylim(-Sig_max, Sig_max)
ax1.text(0.,
1.05,
