def plot_XYZ(self, cmap="Blues", plot="image", **kwargs):
"""
This is 8 million times faster than pseudocolor I guess, but it won't handle unevenly spaced stuff.
You need to generate X, Y and Z first, probably using get_XYZ.
cmap Name of the matplotlib cmap to use
plot Type of plot, "image" for fast colorplot, "mountains" for slow 3d plot
"""
# if we don't have the data, tell the user
if self.X == None or self.Y == None or self.Z == None:
print "You haven't assembled the surface data yet. Use get_XYZ first!"
return
# try the user's colormap
try:
colormap = eval("_pylab.cm."+cmap)
except:
print "ERROR: Invalid colormap, using default."
colormap = _pylab.cm.Blues
# at this point we have X, Y, Z and a colormap, so plot the mf.
f=_pylab.gcf()
f.clear()
if plot.lower() == "mountains":
X, Y = meshgrid(self.X, self.Y)
a = Axes3D(f)
a.plot_surface(X, Y, self.Z, rstride=2, cstride=2, cmap=colormap, **kwargs)
else:
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(self.X[-1] - self.X[0])/(len(self.X)-1))
y_width = abs(float(self.Y[-1] - self.Y[0])/(len(self.Y)-1))
# do whatever transformation is required
X = self.X
Y = self.Y
Z = self.Z
# reverse the Z's
Z = list(Z); Z.reverse(); Z = array(Z)
_pylab.imshow(Z, cmap=colormap,
extent=[X[0]-x_width/2.0, X[-1]+x_width/2.0,
Y[0]+y_width/2.0, Y[-1]-y_width/2.0], **kwargs)
_pylab.colorbar()
_pt.image_set_aspect(1.0)
# set the title and labels
self.title = self.path
a = _pylab.gca()
a.set_title(self.title)
a.set_xlabel(self.xlabel)
a.set_ylabel(self.ylabel)
def image_data(Z, X=[0,1.0], Y=[0,1.0], aspect=1.0, zmin=None, zmax=None, clear=1, **kwargs):
"""
Generates an image or 3d plot
X 1-d array of x-values
Y 1-d array of y-values
Z 2-d array of z-values
X and Y can be something like [0,2] or an array of X-values
"""
fig = _pylab.gcf()
if clear:
fig.clear()
_pylab.axes()
# generate the 3d axes
X = _numpy.array(X)
Y = _numpy.array(Y)
Z = _numpy.array(Z)
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(X[-1] - X[0])/(len(Z[0])-1))
y_width = abs(float(Y[-1] - Y[0])/(len(Z)-1))
# reverse the Z's
Z = Z[-1::-1]
# get rid of the label and title kwargs
xlabel=''
ylabel=''
title =''
if kwargs.has_key('xlabel'): xlabel = kwargs.pop('xlabel')
if kwargs.has_key('ylabel'): ylabel = kwargs.pop('ylabel')
if kwargs.has_key('title'): title = kwargs.pop('title')
_pylab.imshow(Z, extent=[X[0]-x_width/2.0, X[-1]+x_width/2.0,
Y[0]-y_width/2.0, Y[-1]+y_width/2.0], **kwargs)
_pylab.colorbar()
_pt.image_set_clim(zmin,zmax)
_pt.image_set_aspect(aspect)
a = _pylab.gca()
a.set_title(title)
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
_pt.close_sliders()
_pt.image_sliders()
_pt.raise_figure_window()
_pt.raise_pyshell()
_pylab.draw()
return _pylab.gca()
def image_data(Z,
X=[0, 1.0],
Y=[0, 1.0],
aspect=1.0,
zmin=None,
zmax=None,
clear=1,
title='',
clabel='z',
autoformat=True,
colormap="Last Used",
shell_history=1,
**kwargs):
"""
Generates an image or 3d plot
X 1-d array of x-values
Y 1-d array of y-values
Z 2-d array of z-values
X and Y can be something like [0,2] or an array of X-values
kwargs are sent to pylab.imshow()
"""
global _colormap
_pylab.ioff()
fig = _pylab.gcf()
if clear:
fig.clear()
_pylab.axes()
# generate the 3d axes
X = _n.array(X)
Y = _n.array(Y)
Z = _n.array(Z)
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(X[-1] - X[0]) / (len(Z[0]) - 1))
y_width = abs(float(Y[-1] - Y[0]) / (len(Z) - 1))
# reverse the Z's
Z = Z[-1::-1]
# get rid of the label and title kwargs
xlabel = ''
ylabel = ''
title = ''
if kwargs.has_key('xlabel'): xlabel = kwargs.pop('xlabel')
if kwargs.has_key('ylabel'): ylabel = kwargs.pop('ylabel')
if kwargs.has_key('title'): title = kwargs.pop('title')
_pylab.imshow(Z,
extent=[
X[0] - x_width / 2.0, X[-1] + x_width / 2.0,
Y[0] - y_width / 2.0, Y[-1] + y_width / 2.0
],
**kwargs)
cb = _pylab.colorbar()
_pt.image_set_clim(zmin, zmax)
_pt.image_set_aspect(aspect)
cb.set_label(clabel)
a = _pylab.gca()
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
#_pt.close_sliders()
#_pt.image_sliders()
# title
history = _fun.get_shell_history()
for n in range(0, min(shell_history, len(history))):
title = title + "\n" + history[n].split('\n')[0].strip()
title = title + '\nPlot created ' + _time.asctime()
a.set_title(title.strip())
if autoformat: _pt.image_format_figure(fig)
_pylab.ion()
_pylab.show()
#_pt.raise_figure_window()
#_pt.raise_pyshell()
_pylab.draw()
# add the color sliders
if colormap:
if _colormap: _colormap.close()
_colormap = _pt.image_colormap(colormap, image=a.images[0])
def image_data(Z, X=[0,1.0], Y=[0,1.0], aspect=1.0, zmin=None, zmax=None, clear=1, clabel='z', autoformat=True, colormap="Last Used", shell_history=1, **kwargs):
"""
Generates an image or 3d plot
X 1-d array of x-values
Y 1-d array of y-values
Z 2-d array of z-values
X and Y can be something like [0,2] or an array of X-values
kwargs are sent to pylab.imshow()
"""
global _colormap
_pylab.ioff()
fig = _pylab.gcf()
if clear:
fig.clear()
_pylab.axes()
# generate the 3d axes
X = _n.array(X)
Y = _n.array(Y)
Z = _n.array(Z)
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(X[-1] - X[0])/(len(Z[0])-1))
y_width = abs(float(Y[-1] - Y[0])/(len(Z)-1))
# reverse the Z's
Z = Z[-1::-1]
# get rid of the label and title kwargs
xlabel=''
ylabel=''
title =''
if kwargs.has_key('xlabel'): xlabel = kwargs.pop('xlabel')
if kwargs.has_key('ylabel'): ylabel = kwargs.pop('ylabel')
if kwargs.has_key('title'): title = kwargs.pop('title')
_pylab.imshow(Z, extent=[X[0]-x_width/2.0, X[-1]+x_width/2.0,
Y[0]-y_width/2.0, Y[-1]+y_width/2.0], **kwargs)
cb = _pylab.colorbar()
_pt.image_set_clim(zmin,zmax)
_pt.image_set_aspect(aspect)
cb.set_label(clabel)
a = _pylab.gca()
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
#_pt.close_sliders()
#_pt.image_sliders()
# title
history = _fun.get_shell_history()
for n in range(0, min(shell_history, len(history))):
title = title + "\n" + history[n].split('\n')[0].strip()
title = title + '\nPlot created ' + _time.asctime()
a.set_title(title.strip())
if autoformat: _pt.image_format_figure(fig)
_pylab.ion()
_pylab.show()
#_pt.raise_figure_window()
#_pt.raise_pyshell()
_pylab.draw()
# add the color sliders
if colormap:
if _colormap: _colormap.close()
_colormap = _pt.image_colormap(colormap, image=a.images[0])
def image_data(Z, X=[0,1.0], Y=[0,1.0], aspect=1.0, zmin=None, zmax=None, clear=1, clabel='z', autoformat=True, colormap="Last Used", shell_history=0, **kwargs):
"""
Generates an image plot.
Parameters
----------
Z
2-d array of z-values
X=[0,1.0], Y=[0,1.0]
1-d array of x-values (only the first and last element are used)
See matplotlib's imshow() for additional optional arguments.
"""
global _colormap
# Set interpolation to something more relevant for every day science
if not 'interpolation' in kwargs.keys(): kwargs['interpolation'] = 'nearest'
_pylab.ioff()
fig = _pylab.gcf()
if clear:
fig.clear()
_pylab.axes()
# generate the 3d axes
X = _n.array(X)
Y = _n.array(Y)
Z = _n.array(Z)
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(X[-1] - X[0])/(len(Z[0])-1))
y_width = abs(float(Y[-1] - Y[0])/(len(Z)-1))
# reverse the Z's
# Transpose and reverse
Z = Z.transpose()
Z = Z[-1::-1]
# get rid of the label and title kwargs
xlabel=''
ylabel=''
title =''
if 'xlabel' in kwargs: xlabel = kwargs.pop('xlabel')
if 'ylabel' in kwargs: ylabel = kwargs.pop('ylabel')
if 'title' in kwargs: title = kwargs.pop('title')
_pylab.imshow(Z, extent=[X[0]-x_width/2.0, X[-1]+x_width/2.0,
Y[0]-y_width/2.0, Y[-1]+y_width/2.0], **kwargs)
cb = _pylab.colorbar()
_pt.image_set_clim(zmin,zmax)
_pt.image_set_aspect(aspect)
cb.set_label(clabel)
a = _pylab.gca()
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
#_pt.close_sliders()
#_pt.image_sliders()
# title
history = _fun.get_shell_history()
for n in range(0, min(shell_history, len(history))):
title = title + "\n" + history[n].split('\n')[0].strip()
title = title + '\nPlot created ' + _time.asctime()
a.set_title(title.strip())
if autoformat: _pt.image_format_figure(fig)
_pylab.ion()
_pylab.show()
#_pt.raise_figure_window()
#_pt.raise_pyshell()
_pylab.draw()
# add the color sliders
if colormap:
if _colormap: _colormap.close()
_colormap = _pt.image_colormap(colormap, image=a.images[0])
def image_data(Z, X=[0,1.0], Y=[0,1.0], aspect=1.0, zmin=None, zmax=None, clear=1, clabel='z', autoformat=True, colormap="Last Used", shell_history=0, **kwargs):
"""
Generates an image plot.
Parameters
----------
Z
2-d array of z-values
X=[0,1.0], Y=[0,1.0]
1-d array of x-values (only the first and last element are used)
See matplotlib's imshow() for additional optional arguments.
"""
global _colormap
# Set interpolation to something more relevant for every day science
if not 'interpolation' in kwargs.keys(): kwargs['interpolation'] = 'nearest'
_pylab.ioff()
fig = _pylab.gcf()
if clear:
fig.clear()
_pylab.axes()
# generate the 3d axes
X = _n.array(X)
Y = _n.array(Y)
Z = _n.array(Z)
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(X[-1] - X[0])/(len(Z[0])-1))
y_width = abs(float(Y[-1] - Y[0])/(len(Z)-1))
# reverse the Z's
# Transpose and reverse
Z = Z.transpose()
Z = Z[-1::-1]
# get rid of the label and title kwargs
xlabel=''
ylabel=''
title =''
if 'xlabel' in kwargs: xlabel = kwargs.pop('xlabel')
if 'ylabel' in kwargs: ylabel = kwargs.pop('ylabel')
if 'title' in kwargs: title = kwargs.pop('title')
_pylab.imshow(Z, extent=[X[0]-x_width/2.0, X[-1]+x_width/2.0,
Y[0]-y_width/2.0, Y[-1]+y_width/2.0], **kwargs)
cb = _pylab.colorbar()
_pt.image_set_clim(zmin,zmax)
_pt.image_set_aspect(aspect)
cb.set_label(clabel)
a = _pylab.gca()
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
#_pt.close_sliders()
#_pt.image_sliders()
# title
history = _fun.get_shell_history()
for n in range(0, min(shell_history, len(history))):
title = title + "\n" + history[n].split('\n')[0].strip()
title = title + '\nPlot created ' + _time.asctime()
a.set_title(title.strip())
if autoformat: _pt.image_format_figure(fig)
_pylab.ion()
_pylab.show()
#_pt.raise_figure_window()
#_pt.raise_pyshell()
_pylab.draw()
# add the color sliders
if colormap:
if _colormap: _colormap.close()
_colormap = _pt.image_colormap(colormap, image=a.images[0])
def image_data(Z,
X=[0, 1.0],
Y=[0, 1.0],
aspect=1.0,
zmin=None,
zmax=None,
clear=1,
**kwargs):
"""
Generates an image or 3d plot
X 1-d array of x-values
Y 1-d array of y-values
Z 2-d array of z-values
X and Y can be something like [0,2] or an array of X-values
"""
fig = _pylab.gcf()
if clear:
fig.clear()
_pylab.axes()
# generate the 3d axes
X = _numpy.array(X)
Y = _numpy.array(Y)
Z = _numpy.array(Z)
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(X[-1] - X[0]) / (len(Z[0]) - 1))
y_width = abs(float(Y[-1] - Y[0]) / (len(Z) - 1))
# reverse the Z's
Z = Z[-1::-1]
# get rid of the label and title kwargs
xlabel = ''
ylabel = ''
title = ''
if kwargs.has_key('xlabel'): xlabel = kwargs.pop('xlabel')
if kwargs.has_key('ylabel'): ylabel = kwargs.pop('ylabel')
if kwargs.has_key('title'): title = kwargs.pop('title')
_pylab.imshow(Z,
extent=[
X[0] - x_width / 2.0, X[-1] + x_width / 2.0,
Y[0] - y_width / 2.0, Y[-1] + y_width / 2.0
],
**kwargs)
_pylab.colorbar()
_pt.image_set_clim(zmin, zmax)
_pt.image_set_aspect(aspect)
a = _pylab.gca()
a.set_title(title)
a.set_xlabel(xlabel)
a.set_ylabel(ylabel)
_pt.close_sliders()
_pt.image_sliders()
_pt.raise_figure_window()
_pt.raise_pyshell()
_pylab.draw()
return _pylab.gca()
def plot_XYZ(self, cmap="Blues", plot="image", **kwargs):
"""
This is 8 million times faster than pseudocolor I guess, but it won't handle unevenly spaced stuff.
You need to generate X, Y and Z first, probably using get_XYZ.
cmap Name of the matplotlib cmap to use
plot Type of plot, "image" for fast colorplot, "mountains" for slow 3d plot
"""
# if we don't have the data, tell the user
if self.X == None or self.Y == None or self.Z == None:
print "You haven't assembled the surface data yet. Use get_XYZ first!"
return
# try the user's colormap
try:
colormap = eval("_pylab.cm." + cmap)
except:
print "ERROR: Invalid colormap, using default."
colormap = _pylab.cm.Blues
# at this point we have X, Y, Z and a colormap, so plot the mf.
f = _pylab.gcf()
f.clear()
if plot.lower() == "mountains":
X, Y = meshgrid(self.X, self.Y)
a = Axes3D(f)
a.plot_surface(X,
Y,
self.Z,
rstride=2,
cstride=2,
cmap=colormap,
**kwargs)
else:
# assume X and Y are the bin centers and figure out the bin widths
x_width = abs(float(self.X[-1] - self.X[0]) / (len(self.X) - 1))
y_width = abs(float(self.Y[-1] - self.Y[0]) / (len(self.Y) - 1))
# do whatever transformation is required
X = self.X
Y = self.Y
Z = self.Z
# reverse the Z's
Z = list(Z)
Z.reverse()
Z = array(Z)
_pylab.imshow(Z,
cmap=colormap,
extent=[
X[0] - x_width / 2.0, X[-1] + x_width / 2.0,
Y[0] + y_width / 2.0, Y[-1] - y_width / 2.0
],
**kwargs)
_pylab.colorbar()
_pt.image_set_aspect(1.0)
# set the title and labels
self.title = self.path
a = _pylab.gca()
a.set_title(self.title)
a.set_xlabel(self.xlabel)
a.set_ylabel(self.ylabel)
