def plot_u(u, x, xv, y, yv, t, n):
if t[n] == 0:
time.sleep(2)
if plot_method == 1:
plt.mesh(x, y, u, title='t=%g' % t[n], zlim=[-1,1],
caxis=[-1,1])
elif plot_method == 2:
surfc(xv, yv, u, title='t=%g' % t[n], zlim=[-1, 1],
colorbar=True, colormap=hot(), caxis=[-1,1],
shading='flat')
elif plot_method == 3:
print ('Experimental 3D matplotlib...under development...')
#plt.clf()
ax = fig.add_subplot(111, projection='3d')
u_surf = ax.plot_surface(xv, yv, u, alpha=0.3)
#ax.contourf(xv, yv, u, zdir='z', offset=-100, cmap=cm.coolwarm)
#ax.set_zlim(-1, 1)
# Remove old surface before drawing
if u_surf is not None:
ax.collections.remove(u_surf)
plt.draw()
time.sleep(1)
if plot_method > 0:
time.sleep(0) # pause between frames
if save_plot:
filename = 'tmp_%04d.png' % n
plt.savefig(filename) # time consuming!
def makeplots( domain, geom, Lx, Lz, value, name, title, ndigits=0, index=None, clim=None, lineOn=False, imgtype=None,):
points, colors = domain.elem_eval( [ geom, value ], ischeme='bezier3', separate=True )
with plot.PyPlot( name, ndigits=ndigits, figsize=(5,6), index=index, imgtype=imgtype ) as plt:
plt.mesh( points, colors, triangulate='bezier', edgecolors='none' )
plt.title(title)
plt.xlabel('x [m]')
plt.ylabel('z [m]')
plt.xticks( [0, Lx/2.0, Lx], ['0', '300', '600'] )
plt.yticks( [-0, -0.4*Lz, -0.8*Lz, -Lz], ['0', '400', '800', '1000'] )
if clim is not None:
plt.clim(*clim)
plt.colorbar()
if lineOn:
# Only for wedge problem in 2D
plt.plot( [0, 600],[-400, -500],'k' )
plt.plot( [0, 600],[-800, -600],'k' )
def makeplots( domain, geom, verts_x, verts_z, value, name, title, ndigits=0, index=None, imgtype=None):
points, colors = domain.elem_eval( [ geom, value ], ischeme='bezier3', separate=True )
with plot.PyPlot( name, ndigits=ndigits, index=index, imgtype=imgtype ) as plt:
plt.mesh( points, colors, triangulate='bezier', edgecolors='none' )
plt.title(title)
plt.xlabel('x [m]', fontsize=10)
plt.xticks([0, max(verts_x)/2.0, max(verts_x)], ['0', '2000', '4000'], fontsize=10)
plt.ylabel('z [m]', fontsize=10)
plt.yticks([max(verts_z), min(verts_z)], ['0', '1850'], fontsize=10)
plt.ylim
ax = plt.gca()
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="5%", pad=0.05)
cb = plt.colorbar(cax=cax)
cb.ax.tick_params(labelsize=10)
def makeplots(
domain,
geom,
Lx,
Lz,
value,
name,
title,
ndigits=0,
index=None,
clim=None,
lineOn=False,
imgtype=None,
):
points, colors = domain.elem_eval([geom, value],
ischeme='bezier3',
separate=True)
with plot.PyPlot(name,
ndigits=ndigits,
figsize=(5, 6),
index=index,
imgtype=imgtype) as plt:
plt.mesh(points, colors, triangulate='bezier', edgecolors='none')
plt.title(title)
plt.xlabel('x [m]')
plt.ylabel('z [m]')
plt.xticks([0, Lx / 2.0, Lx], ['0', '300', '600'])
plt.yticks([-0, -0.4 * Lz, -0.8 * Lz, -Lz],
['0', '400', '800', '1000'])
if clim is not None:
plt.clim(*clim)
plt.colorbar()
if lineOn:
# Only for wedge problem in 2D
plt.plot([0, 600], [-400, -500], 'k')
plt.plot([0, 600], [-800, -600], 'k')
geom = refgeom + disp
E = mu['ymod1']
NU = mu['prat']
MU = E / (1 + NU)
LAMBDA = E * NU / (1 + NU) / (1 - 2 * NU)
stressfunc = -MU * disp.symgrad(refgeom) + LAMBDA * disp.div(
refgeom) * fn.eye(disp.shape[0])
if geom.shape == (2, ):
stressfunc = stressfunc[tuple('xyz'.index(c) for c in stress)]
mesh, stressdata = case.domain.elem_eval([geom, 1],
separate=True,
ischeme='bezier3')
with _plot('u', name=name, **kwargs) as plt:
plt.mesh(mesh, stressdata)
_colorbar(plt, **kwargs)
elif geom.shape == (3, ):
nutils.plot.writevtu(name,
case.domain,
geom,
pointdata={
'stress-xx': stressfunc[0, 0],
'stress-xy': stressfunc[0, 1],
'stress-xz': stressfunc[0, 2],
'stress-yy': stressfunc[1, 1],
'stress-yz': stressfunc[1, 2],
'stress-zz': stressfunc[2, 2],
'disp-x': disp[0],
'disp-y': disp[1],
import numpy as np import matplotlib.pyplot as plt y0 = 0 yn = 1 x0 = -2 xn = 2 x = np.linspace(x0,xn,61) y = np.linspace(y0,yn,21) X,Y = np.meshgrid(x,y) plt.mesh([X,Y],[0]) plt.show()
def cmatplot(cmat, ux=None, uy=None, method=1, clevels=None):
"""
CMATPLOT Plots a cycle matrix, e.g. a rainflow matrix.
CALL: cmatplot(F)
cmatplot(F,method)
cmatplot(ux,uy,F)
cmatplot(ux,uy,F,method)
F = Cycle matrix (e.g. rainflow matrix) [nxm]
method = 1: mesh-plot (default)
2: surf-plot
3: pcolor-plot [axis('square')]
4: contour-plot [axis('square')]
5: TechMath-plot [axis('square')]
11: From-To, mesh-plot
12: From-To, surf-plot
13: From-To, pcolor-plot [axis('square')]
14: From-To, contour-plot [axis('square')]
15: From-To, TechMath-plot [axis('square')]
ux = x-axis (default: 1:m)
uy = y-axis (default: 1:n)
Examples:
param = [-1 1 64]; u=levels(param);
F = mktestmat(param,[-0.2 0.2],0.25,1/2);
cmatplot(F,method=1);
cmatplot(u,u,F,method=2); colorbar;
cmatplot(u,u,F,method=3); colorbar;
cmatplot(u,u,F,method=4);
close all;
See also
--------
cocc, plotcc
"""
F = cmat
shape = np.shape(F)
if ux is None:
ux = np.arange(shape[1]) # Antalet kolumner
if uy is None:
uy = np.arange(shape[0]) # Antalet rader
if clevels is None:
Fmax = np.max(F)
if method in [5, 15]:
clevels = Fmax * np.r_[0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1.0]
else: # 4, 14
clevels = Fmax * np.r_[0.005,
0.01,
0.02,
0.05,
0.1,
0.2,
0.4,
0.6,
0.8]
# Make sure ux and uy are row vectors
ux = ux.ravel()
uy = uy.ravel()
n = len(F)
from matplotlib import pyplot as plt
if method == 1: # mesh
F = np.flipud(F.T) # Vrid cykelmatrisen for att plotta rett
plt.mesh(ux, np.fliplr(uy), F)
plt.xlabel('min')
plt.ylabel('Max')
# view(-37.5-90,30);
# v = axis;
# plt.axis([min(ux) max(ux) min(uy) max(uy) v[5:6]]);
elif method == 2: # surf
F = np.flipud(F.T) # Vrid cykelmatrisen for att plotta rett
plt.surf(ux, np.fliplr(uy), F)
plt.xlabel('min')
plt.ylabel('Max')