def test_close(self):
""" Various tests for mlab.close().
"""
f = mlab.figure()
self.assert_(f.running)
mlab.close(f)
self.assertFalse(f.running)
f = mlab.figure(314)
self.assert_(f.running)
mlab.close(314)
self.assertFalse(f.running)
f = mlab.figure('test_figure')
self.assert_(f.running)
mlab.close('test_figure')
self.assertFalse(f.running)
f = mlab.figure()
self.assert_(f.running)
mlab.close()
self.assertFalse(f.running)
figs = [mlab.figure() for i in range(5)]
for f in figs:
self.assert_(f.running)
mlab.close(all=True)
for f in figs:
self.assertFalse(f.running)
def generate_file_rst(fname, target_dir, src_dir, plot_gallery):
""" Generate the rst file for a given example.
"""
image_name = fname[:-2] + 'png'
global rst_template, plot_rst_template
this_template = rst_template
last_dir = os.path.split(src_dir)[-1]
# to avoid leading . in file names
if last_dir == '.': last_dir = ''
else: last_dir += '_'
short_fname = last_dir + fname
src_file = os.path.join(src_dir, fname)
example_file = os.path.join(target_dir, fname)
shutil.copyfile(src_file, example_file)
if plot_gallery and fname.startswith('plot'):
# generate the plot as png image if file name
# starts with plot and if it is more recent than an
# existing image.
if not os.path.exists(os.path.join(target_dir, 'images')):
os.makedirs(os.path.join(target_dir, 'images'))
image_file = os.path.join(target_dir, 'images', image_name)
if (not os.path.exists(image_file) or
os.stat(image_file).st_mtime <= os.stat(src_file).st_mtime):
print 'plotting %s' % fname
import matplotlib.pyplot as plt
plt.close('all')
try:
from enthought.mayavi import mlab
mlab.close(all=True)
except:
pass
try:
execfile(example_file, {'pl' : plt})
facecolor = plt.gcf().get_facecolor() # hack to keep black bg
if facecolor == (0.0, 0.0, 0.0, 1.0):
plt.savefig(image_file, facecolor='black')
else:
plt.savefig(image_file)
try:
from enthought.mayavi import mlab
e = mlab.get_engine()
if len(e.scenes) > 0:
mlab.savefig(image_file)
except:
pass
except:
print 80*'_'
print '%s is not compiling:' % fname
traceback.print_exc()
print 80*'_'
this_template = plot_rst_template
docstring, short_desc, end_row = extract_docstring(example_file)
f = open(os.path.join(target_dir, fname[:-2] + 'rst'), 'w')
f.write(this_template % locals())
f.flush()
def test_close(self):
""" Various tests for mlab.close().
"""
f = mlab.figure()
self.assert_(f.running)
mlab.close(f)
self.assertFalse(f.running)
f = mlab.figure(314)
self.assert_(f.running)
mlab.close(314)
self.assertFalse(f.running)
f = mlab.figure('test_figure')
self.assert_(f.running)
mlab.close('test_figure')
self.assertFalse(f.running)
f = mlab.figure()
self.assert_(f.running)
mlab.close()
self.assertFalse(f.running)
figs = [mlab.figure() for i in range(5)]
for f in figs:
self.assert_(f.running)
mlab.close(all=True)
for f in figs:
self.assertFalse(f.running)
(decmax-decmean)*3600.:
(limy[1]-limy[0]+1)*1j,
vmin:vmax+0.1:dv]
'''
# ------------------------------------------------------------------------------
# Re-order the VLA array to have the dimensions in the good direction !
# (z = v, x= R.A.), etc ...
# Also flip the velocity axis to be in the good direction
HI_cube = scidata[slice_min:slice_max + 1, limy[0]:limy[1] + 1,
limx[0]:limx[1] + 1]
HI_cube = np.transpose(HI_cube, (2, 1, 0))[::-1, :, ::-1]
# Start the plotting
mlab.close(1)
fig = mlab.figure(1, size=(1100, 1100))
# What contours levels do I want ? Can be chosen by defaults, or scripted.
isolevels = [1.3, 2.5, 3.5, 6.0]
# --- !!! ---
# MAYAVI BUG & WORK-AROUND (#1)
# Currently, the x3d export function from Mayavi ignores the "vmin" and "vmax"
# parameters in the plotting function, and only uses the min and max of the
# datasets. Hence, to export the "exact same" color for the different plot
# elements shown in the interactive Mayavi window, the data itself MUST be
# modified; i.e. all values outside the [vmin->vmax] range must be replaced.
# This is NOT elegant, and will hopefully be fixed in future releases of Mayavi.
color_scale = [0.8, 6.1]
mlab.clf()
mlab.points3d(center.T[0],
center.T[1],
center.T[2],
colors_,
scale_factor=0.05,
scale_mode='none',
colormap='RdBu',
vmin=colors_.min(),
vmax=colors_.max())
#mlab.quiver3d(center.T[0],center.T[1],center.T[2],normal.T[0],normal.T[1],normal.T[2],colormap='spectral',scale_mode='none')
mlab.colorbar()
if i >= 1:
vx,vy,vz = center.T[0]-old_center.T[0],\
center.T[1]-old_center.T[1],\
center.T[2]-old_center.T[2]
v = np.sqrt(vx**2 + vy**2 + vz**2)
mlab.quiver3d(center.T[0],center.T[1],center.T[2],\
vx,vy,vz,scalars=v,colormap='spectral',scale_mode='scalar')
#mlab.show()
old_center = center.copy()
mlab.view(distance=5, azimuth=-90, elevation=90)
mlab.savefig('pulsation_lm%d%d_k%03d_%03d.png' %
(l, m, k, i))
mlab.close()
multimedia.make_movie(
'pulsation_lm%d%d_k%03d_*.png' % (l, m, k),
output='pulsation_lm%d%d_k%03d.avi' % (l, m, k))
span+=1
for j in range(skip,cnt-1):
if j%span!=0 and j!=0:
continue
print "TimeStep: %d" % (times[j])
xx=xs[j]
yy=ys[j]
zz=zs[j]
tt=ts[j]
mlab.clf(fig1)
mlab.clf(fig2)
mlab.points3d(xx,yy,zz,tt,colormap="gist_heat",scale_factor=0.2,figure=fig1)
mlab.mesh(xdummy,ydummy,pairdistro[j],figure=fig2)
mlab.show(stop=True)
mlab.close(all=True)
#Bond lengths
"""
print "Calculating histogram of bond lengths corresponding to the minimum energy."
n=pes.index(min(pes))
xs=xs[n][:N]
ys=ys[n][:N]
zs=zs[n][:N]
radii=list()
for i in range(N):
for j in range(i+1,N):
radii.append(((xs[i]-xs[j])**2+(ys[i]-ys[j])**2+(zs[i]-zs[j])**2)**0.5)
bins=pl.array(range(1000))/1000.0*rcut*1.5
pl.hist(radii,bins)
def close(self):
"""Close the figure and cleanup data structure."""
from enthought.mayavi import mlab
mlab.close(self._f)
(limy[1]-limy[0]+1)*1j,
vmin:vmax+0.1:dv]
'''
# ------------------------------------------------------------------------------
# Re-order the VLA array to have the dimensions in the good direction !
# (z = v, x= R.A.), etc ...
# Also flip the velocity axis to be in the good direction
HI_cube = scidata[slice_min:slice_max+1,limy[0]:limy[1]+1,limx[0]:limx[1]+1 ]
HI_cube = np.transpose(HI_cube, (2,1,0))[::-1,:,::-1]
# Start the plotting
mlab.close(1)
fig = mlab.figure(1, size=(1100,1100))
# What contours levels do I want ? Can be chosen by defaults, or scripted.
isolevels = [1.3,2.5,3.5,6.0]
# --- !!! ---
# MAYAVI BUG & WORK-AROUND (#1)
# Currently, the x3d export function from Mayavi ignores the "vmin" and "vmax"
# parameters in the plotting function, and only uses the min and max of the
# datasets. Hence, to export the "exact same" color for the different plot
# elements shown in the interactive Mayavi window, the data itself MUST be
# modified; i.e. all values outside the [vmin->vmax] range must be replaced.
# This is NOT elegant, and will hopefully be fixed in future releases of Mayavi.
color_scale = [0.8,6.1]
@author: R. Bourquin
@copyright: Copyright (C) 2010, 2011 R. Bourquin
@license: Modified BSD License
"""
import numpy as np
from enthought.mayavi import mlab
from WaveBlocks.Plot import surfcf
x, y = np.mgrid[0:5*np.pi:0.05, 0:5*np.pi:0.05]
# Plane waves:
k = 1
l = 0
z = np.exp(1.0j*k*x)*np.exp(1.0j*l*y)
surfcf(x, y, np.angle(z), np.real(z))
mlab.savefig("planewave_real_surfplot.png")
mlab.close()
surfcf(x, y, np.angle(z), np.imag(z))
mlab.savefig("planewave_imag_surfplot.png")
mlab.close()
surfcf(x, y, np.angle(z), np.conj(z)*z)
mlab.savefig("planewave_abs_surfplot.png")
mlab.close()
figsize = (1200, 900)
# make a spatial_set object
a = 0.0
b = 10.0
nz = 100
hz = .6
hv = .35
# function for testing
fun = lambda z: sp.exp(-(z-a))
domain = Domain(a,b,hz, hv)
mlab.close(0)
f = mlab.figure(0,
bgcolor=bgcolor,
fgcolor=fgcolor, size=figsize)
# plot the figure
# mlab.clf(0)
# plot a funciton in space
domain.plot_function(fun, tube_radius=.1)
# plot quivers
names = ['incoming', 'outgoing', 'domain']
colors = [(0,0,1), (1,0,0), (0,1,0)]
scale_factors = [.3, .3, .2]
def cleanUp(self):
from enthought.mayavi import mlab
mlab.close()
def cleanUp(self):
from enthought.mayavi import mlab
mlab.close()
