def xy_data(xdata, ydata, eydata=None, exdata=None, label=None, xlabel='', ylabel='', \
title='', shell_history=1, xshift=0, yshift=0, xshift_every=1, yshift_every=1, \
coarsen=0, style=None, clear=True, axes=None, xscale='linear', yscale='linear', grid=False, \
legend='best', legend_max=20, autoformat=True, tall=False, draw=True, **kwargs):
"""
Plots specified data.
xdata, ydata Arrays (or arrays of arrays) of data to plot
eydata, exdata Arrays of x and y errorbar values
label string or array of strings for the line labels
xlabel='' label for the x-axis
ylabel='' label for the y-axis
title='' title for the axes; set to None to have nothing.
shell_history=1 how many commands from the pyshell history to include
with the title
xshift=0, yshift=0 progressive shifts on the data, to make waterfall plots
xshift_every=1 perform the progressive shift every 1 or n'th line.
yshift_every=1 perform the progressive shift every 1 or n'th line.
style style cycle object.
clear=True if no axes are specified, clear the figure, otherwise
clear just the axes.
axes=None which axes to use, or "gca" for the current axes
xscale,yscale 'linear' by default. Set either to 'log' for log axes
grid=False Should we draw a grid on the axes?
legend='best' where to place the legend (see pylab.legend())
Set this to None to ignore the legend.
legend_max=20 number of legend entries before it's truncated with '...'
autoformat=True Should we format the figure for printing?
False Should the format be tall?
draw=True whether or not to draw the plot after plotting
**kwargs are sent to pylab.errorbar()
"""
_pylab.ioff()
# make sure everything is at least iterable.
if not _fun.is_iterable(xdata): xdata = [xdata]
if not _fun.is_iterable(exdata): exdata = [exdata]
if not _fun.is_iterable(ydata): ydata = [ydata]
if not _fun.is_iterable(eydata): eydata = [eydata]
# make sure at least xdata and ydata are 2-D
if _fun.is_a_number(xdata[0]): xdata = [xdata]
if _fun.is_a_number(ydata[0]): ydata = [ydata]
# make sure the number of data sets agrees
N = max(len(xdata), len(ydata))
for n in range(N - len(xdata)):
xdata.append(xdata[0])
for n in range(N - len(ydata)):
ydata.append(ydata[0])
for n in range(N - len(exdata)):
exdata.append(exdata[0])
for n in range(N - len(eydata)):
eydata.append(eydata[0])
# loop over each x and y data set, making sure None's are all converted
# to counting arrays
for n in range(N):
# clean up the [None]'s
if _fun.is_iterable(xdata[n]) and xdata[n][0] == None: xdata[n] = None
if _fun.is_iterable(ydata[n]) and ydata[n][0] == None: ydata[n] = None
if xdata[n] == None and ydata[n] == None:
print "ERROR: " + str(n) + "'th data set is (None, None)."
return
if xdata[n] == None: xdata[n] = _n.arange(len(ydata[n]))
if ydata[n] == None: ydata[n] = _n.arange(len(xdata[n]))
# check that the labels is a list of strings of the same length
if not _fun.is_iterable(label): label = [label] * N
while len(label) < len(ydata):
label.append(label[0])
# concatenate if necessary
if len(label) > legend_max:
label[legend_max - 2] = '...'
for n in range(legend_max - 1, len(label) - 1):
label[n] = "_nolegend_"
# clear the figure?
if clear and not axes: _pylab.gcf().clear() # axes cleared later
# setup axes
if axes == "gca" or axes == None: axes = _pylab.gca()
# if we're clearing the axes
if clear: axes.clear()
# set the current axes
_pylab.axes(axes)
# now loop over the list of data in xdata and ydata
for n in range(0, len(xdata)):
# get the label
if label: l = str(label[n])
else: l = str(n)
# calculate the x an y progressive shifts
dx = xshift * (n / xshift_every)
dy = yshift * (n / yshift_every)
# if we're supposed to coarsen the data, do so.
x = _fun.coarsen_array(xdata[n], coarsen)
y = _fun.coarsen_array(ydata[n], coarsen)
ey = _fun.coarsen_array(eydata[n], coarsen, 'quadrature')
ex = _fun.coarsen_array(exdata[n], coarsen, 'quadrature')
# update the style
if not style == None: kwargs.update(style.next())
axes.errorbar(x + dx, y + dy, label=l, yerr=ey, xerr=ex, **kwargs)
_pylab.xscale(xscale)
_pylab.yscale(yscale)
if legend: axes.legend(loc=legend)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
# for some arguments there should be no title.
if title in [None, False, 0]:
axes.set_title('')
# add the commands to the title
else:
title = str(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()
axes.set_title(title)
if grid: _pylab.grid(True)
if autoformat:
_pt.format_figure(draw=False)
_pt.auto_zoom(axes=axes, draw=False)
# update the canvas
if draw:
_pylab.ion()
_pylab.draw()
_pylab.show()
return axes
def xy_data(xdata, ydata, eydata=None, exdata=None, label=None, xlabel='', ylabel='', \
title='', shell_history=1, xshift=0, yshift=0, xshift_every=1, yshift_every=1, \
coarsen=0, style=None, clear=True, axes=None, xscale='linear', yscale='linear', grid=False, \
legend='best', legend_max=20, autoformat=True, tall=False, draw=True, **kwargs):
"""
Plots specified data.
xdata, ydata Arrays (or arrays of arrays) of data to plot
eydata, exdata Arrays of x and y errorbar values
label string or array of strings for the line labels
xlabel='' label for the x-axis
ylabel='' label for the y-axis
title='' title for the axes; set to None to have nothing.
shell_history=1 how many commands from the pyshell history to include
with the title
xshift=0, yshift=0 progressive shifts on the data, to make waterfall plots
xshift_every=1 perform the progressive shift every 1 or n'th line.
yshift_every=1 perform the progressive shift every 1 or n'th line.
style style cycle object.
clear=True if no axes are specified, clear the figure, otherwise
clear just the axes.
axes=None which axes to use, or "gca" for the current axes
xscale,yscale 'linear' by default. Set either to 'log' for log axes
grid=False Should we draw a grid on the axes?
legend='best' where to place the legend (see pylab.legend())
Set this to None to ignore the legend.
legend_max=20 number of legend entries before it's truncated with '...'
autoformat=True Should we format the figure for printing?
False Should the format be tall?
draw=True whether or not to draw the plot after plotting
**kwargs are sent to pylab.errorbar()
"""
_pylab.ioff()
# make sure everything is at least iterable.
if not _fun.is_iterable(xdata): xdata = [xdata]
if not _fun.is_iterable(exdata): exdata = [exdata]
if not _fun.is_iterable(ydata): ydata = [ydata]
if not _fun.is_iterable(eydata): eydata = [eydata]
# make sure at least xdata and ydata are 2-D
if _fun.is_a_number(xdata[0]): xdata = [xdata]
if _fun.is_a_number(ydata[0]): ydata = [ydata]
# make sure the number of data sets agrees
N = max(len(xdata),len(ydata))
for n in range(N-len( xdata)): xdata.append( xdata[0])
for n in range(N-len( ydata)): ydata.append( ydata[0])
for n in range(N-len(exdata)): exdata.append(exdata[0])
for n in range(N-len(eydata)): eydata.append(eydata[0])
# loop over each x and y data set, making sure None's are all converted
# to counting arrays
for n in range(N):
# clean up the [None]'s
if _fun.is_iterable(xdata[n]) and xdata[n][0] is None: xdata[n] = None
if _fun.is_iterable(ydata[n]) and ydata[n][0] is None: ydata[n] = None
if xdata[n] is None and ydata[n] is None:
print "ERROR: "+str(n)+"'th data set is (None, None)."
return
if xdata[n] is None: xdata[n] = _n.arange(len(ydata[n]))
if ydata[n] is None: ydata[n] = _n.arange(len(xdata[n]))
# check that the labels is a list of strings of the same length
if not _fun.is_iterable(label): label = [label]*N
while len(label) < len(ydata): label.append(label[0])
# concatenate if necessary
if len(label) > legend_max:
label[legend_max-2] = '...'
for n in range(legend_max-1,len(label)-1): label[n] = "_nolegend_"
# clear the figure?
if clear and not axes: _pylab.gcf().clear() # axes cleared later
# setup axes
if axes=="gca" or axes is None: axes = _pylab.gca()
# if we're clearing the axes
if clear: axes.clear()
# set the current axes
_pylab.axes(axes)
# now loop over the list of data in xdata and ydata
for n in range(0,len(xdata)):
# get the label
if label: l = str(label[n])
else: l = str(n)
# calculate the x an y progressive shifts
dx = xshift*(n/xshift_every)
dy = yshift*(n/yshift_every)
# if we're supposed to coarsen the data, do so.
x = _fun.coarsen_array(xdata[n], coarsen)
y = _fun.coarsen_array(ydata[n], coarsen)
ey = _fun.coarsen_array(eydata[n], coarsen, 'quadrature')
ex = _fun.coarsen_array(exdata[n], coarsen, 'quadrature')
# update the style
if not style is None: kwargs.update(style.next())
axes.errorbar(x+dx, y+dy, label=l, yerr=ey, xerr=ex, **kwargs)
_pylab.xscale(xscale)
_pylab.yscale(yscale)
if legend: axes.legend(loc=legend)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
# for some arguments there should be no title.
if title in [None, False, 0]:
axes.set_title('')
# add the commands to the title
else:
title = str(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()
axes.set_title(title)
if grid: _pylab.grid(True)
if autoformat:
_pt.format_figure(draw=False)
_pt.auto_zoom(axes=axes, draw=False)
# update the canvas
if draw:
_pylab.ion()
_pylab.draw()
_pylab.show()
return axes
def xy_data(xdata, ydata, eydata=None, exdata=None, label=None, xlabel='', ylabel='', \
title='', shell_history=0, xshift=0, yshift=0, xshift_every=1, yshift_every=1, \
coarsen=0, style=None, clear=True, axes=None, xscale='linear', yscale='linear', grid=False, \
legend='best', legend_max=20, autoformat=True, autoformat_window=True, tall=False, draw=True, **kwargs):
"""
Plots specified data.
Parameters
----------
xdata, ydata
Arrays (or arrays of arrays) of data to plot
eydata=None, exdata=None
Arrays of x and y errorbar values
label=None
String or array of strings for the line labels
xlabel=''
Label for the x-axis
ylabel=''
Label for the y-axis
title=''
Title for the axes; set to None to have nothing.
shell_history=0
How many commands from the pyshell history to include with the title
xshift=0, yshift=0
Progressive shifts on the data, to make waterfall plots
xshift_every=1
Perform the progressive shift every 1 or n'th line.
yshift_every=1
perform the progressive shift every 1 or n'th line.
style=None
style cycle object.
clear=True
If no axes are specified (see below), clear the figure, otherwise clear just the axes.
axes=None
Which matplotlib axes to use, or "gca" for the current axes
xscale='linear', yscale='linear'
'linear' or 'log' x and y axis scales.
grid=False
Should we draw a grid on the axes?
legend='best'
Where to place the legend (see pylab.legend() for options)
Set this to None to ignore the legend.
legend_max=20
Number of legend entries before it's truncated with '...'
autoformat=True
Should we format the figure for printing?
autoformat_window=True
Should we resize and reposition the window when autoformatting?
tall=False
Should the format be tall?
draw=True
Whether or not to draw the plot after plotting.
See matplotlib's errorbar() function for additional optional keyword arguments.
"""
_pylab.ioff()
# Make sure the dimensionality of the data sets matches
xdata, ydata = _match_data_sets(xdata, ydata)
exdata = _match_error_to_data_set(xdata, exdata)
eydata = _match_error_to_data_set(ydata, eydata)
# check that the labels is a list of strings of the same length
if not _fun.is_iterable(label): label = [label] * len(xdata)
while len(label) < len(ydata):
label.append(label[0])
# concatenate if necessary
if len(label) > legend_max:
label[legend_max - 2] = '...'
for n in range(legend_max - 1, len(label) - 1):
label[n] = "_nolegend_"
# clear the figure?
if clear and not axes: _pylab.gcf().clear() # axes cleared later
# setup axes
if axes == "gca" or axes is None: axes = _pylab.gca()
# if we're clearing the axes
if clear: axes.clear()
# set the current axes
_pylab.axes(axes)
# now loop over the list of data in xdata and ydata
for n in range(0, len(xdata)):
# get the label
l = str(n) + ": " + str(label[n])
# calculate the x an y progressive shifts
dx = xshift * (n / xshift_every)
dy = yshift * (n / yshift_every)
# if we're supposed to coarsen the data, do so.
x = _fun.coarsen_array(xdata[n], coarsen)
y = _fun.coarsen_array(ydata[n], coarsen)
ey = _fun.coarsen_array(eydata[n], coarsen, 'quadrature')
ex = _fun.coarsen_array(exdata[n], coarsen, 'quadrature')
# update the style
if not style is None: kwargs.update(next(style))
axes.errorbar(x + dx, y + dy, label=l, yerr=ey, xerr=ex, **kwargs)
_pylab.xscale(xscale)
_pylab.yscale(yscale)
if legend: axes.legend(loc=legend)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
# for some arguments there should be no title.
if title in [None, False, 0]:
axes.set_title('')
# add the commands to the title
else:
title = str(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()
axes.set_title(title)
if grid: _pylab.grid(True)
if autoformat:
_pt.format_figure(draw=False, modify_geometry=autoformat_window)
_pt.auto_zoom(axes=axes, draw=False)
# update the canvas
if draw:
_pylab.ion()
_pylab.draw()
_pylab.show()
return axes
def get_XYZ(self, xaxis=None, yaxis=None, xlabel=None, ylabel=None, xcoarsen=0, ycoarsen=0):
"""
This will assemble the X, Y, Z data for a 2d colorplot or surface.
yaxis=None What values to use for the y-axis data. "first" means take the first column
yaxis=None means just use bin number
xaxis=None What values to use for the x-axis data, can be a header array
xaxis="first" means pop off the first row of the data
xcoarsen, ycoarsen How much to coarsen the columns or rows
"""
# next we assemble the 2-d array for the colorplot
Z=[]
for c in self.ckeys:
# transform so the image plotting has the same orientation as the data
# in the file itself.
col = list(self.columns[c])
col.reverse()
Z.append(col)
# initialize the axis labels
X=[]
for n in range(len(Z)): X.append(n)
self.xlabel = "x-step number"
Y=[]
for n in range(len(Z[0])): Y.append(n)
self.ylabel = "y-step number"
Y.reverse()
# now if we're supposed to, pop off the first column as Y labels
if yaxis=="first":
# just pop off the first column (Z columns are already reversed)
Y = Z.pop(0)
self.ylabel = "y-values"
# pop the first element of the X-data
X.pop(0)
# otherwise, it's a column value
elif not yaxis==None:
Y = list(self.c(yaxis))
Y.reverse()
self.ylabel = yaxis
# if we're supposed to, pop off the top row for the x-axis values
if xaxis == "first":
X = []
for n in range(len(Z)):
X.append(Z[n].pop(-1))
self.xlabel = "x-values"
# pop the first element of the Y-data
Y.pop(-1)
# otherwise, if we specified a row from the header, use that
elif not xaxis==None:
X = array(self.h(xaxis))
# trim X down to the length of the Zd.ZX row
X.resize(len(Z[:])-1)
self.xlabel = xaxis
# now if we're supposed to coarsen, do so (produces a numpy array)
self.X = _fun.coarsen_array(X, xcoarsen)
self.Y = _fun.coarsen_array(Y, ycoarsen)
# Z has to be transposed to make the data file look like the plot
self.Z = _fun.coarsen_matrix(Z, xcoarsen, ycoarsen).transpose()
# if we specified labels, they trump everything
if xlabel: self.xlabel = xlabel
if ylabel: self.ylabel = ylabel
return
def xy_data(xdata, ydata, eydata=None, exdata=None, label=None, xlabel='', ylabel='', \
title='', shell_history=0, xshift=0, yshift=0, xshift_every=1, yshift_every=1, \
coarsen=0, style=None, clear=True, axes=None, xscale='linear', yscale='linear', grid=False, \
legend='best', legend_max=20, autoformat=True, autoformat_window=True, tall=False, draw=True, **kwargs):
"""
Plots specified data.
Parameters
----------
xdata, ydata
Arrays (or arrays of arrays) of data to plot
eydata=None, exdata=None
Arrays of x and y errorbar values
label=None
String or array of strings for the line labels
xlabel=''
Label for the x-axis
ylabel=''
Label for the y-axis
title=''
Title for the axes; set to None to have nothing.
shell_history=0
How many commands from the pyshell history to include with the title
xshift=0, yshift=0
Progressive shifts on the data, to make waterfall plots
xshift_every=1
Perform the progressive shift every 1 or n'th line.
yshift_every=1
perform the progressive shift every 1 or n'th line.
style=None
style cycle object.
clear=True
If no axes are specified (see below), clear the figure, otherwise clear just the axes.
axes=None
Which matplotlib axes to use, or "gca" for the current axes
xscale='linear', yscale='linear'
'linear' or 'log' x and y axis scales.
grid=False
Should we draw a grid on the axes?
legend='best'
Where to place the legend (see pylab.legend() for options)
Set this to None to ignore the legend.
legend_max=20
Number of legend entries before it's truncated with '...'
autoformat=True
Should we format the figure for printing?
autoformat_window=True
Should we resize and reposition the window when autoformatting?
tall=False
Should the format be tall?
draw=True
Whether or not to draw the plot after plotting.
See matplotlib's errorbar() function for additional optional keyword arguments.
"""
_pylab.ioff()
# Make sure the dimensionality of the data sets matches
xdata, ydata = _match_data_sets(xdata, ydata)
exdata = _match_error_to_data_set(xdata, exdata)
eydata = _match_error_to_data_set(ydata, eydata)
# check that the labels is a list of strings of the same length
if not _fun.is_iterable(label): label = [label]*len(xdata)
while len(label) < len(ydata): label.append(label[0])
# concatenate if necessary
if len(label) > legend_max:
label[legend_max-2] = '...'
for n in range(legend_max-1,len(label)-1): label[n] = "_nolegend_"
# clear the figure?
if clear and not axes: _pylab.gcf().clear() # axes cleared later
# setup axes
if axes=="gca" or axes is None: axes = _pylab.gca()
# if we're clearing the axes
if clear: axes.clear()
# set the current axes
_pylab.axes(axes)
# now loop over the list of data in xdata and ydata
for n in range(0,len(xdata)):
# get the label
if label[n]=='_nolegend_':
l = '_nolegend_'
else:
l = str(n)+": "+str(label[n])
# calculate the x an y progressive shifts
dx = xshift*(n/xshift_every)
dy = yshift*(n/yshift_every)
# if we're supposed to coarsen the data, do so.
x = _fun.coarsen_array(xdata[n], coarsen)
y = _fun.coarsen_array(ydata[n], coarsen)
ey = _fun.coarsen_array(eydata[n], coarsen, 'quadrature')
ex = _fun.coarsen_array(exdata[n], coarsen, 'quadrature')
# update the style
if not style is None: kwargs.update(next(style))
axes.errorbar(x+dx, y+dy, label=l, yerr=ey, xerr=ex, **kwargs)
_pylab.xscale(xscale)
_pylab.yscale(yscale)
if legend: axes.legend(loc=legend)
axes.set_xlabel(xlabel)
axes.set_ylabel(ylabel)
# for some arguments there should be no title.
if title in [None, False, 0]:
axes.set_title('')
# add the commands to the title
else:
title = str(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()
axes.set_title(title)
if grid: _pylab.grid(True)
if autoformat:
_pt.format_figure(draw=False, modify_geometry=autoformat_window)
_pt.auto_zoom(axes=axes, draw=False)
# update the canvas
if draw:
_pylab.ion()
_pylab.draw()
_pylab.show()
return axes
def get_XYZ(self,
xaxis=None,
yaxis=None,
xlabel=None,
ylabel=None,
xcoarsen=0,
ycoarsen=0):
"""
This will assemble the X, Y, Z data for a 2d colorplot or surface.
yaxis=None What values to use for the y-axis data. "first" means take the first column
yaxis=None means just use bin number
xaxis=None What values to use for the x-axis data, can be a header array
xaxis="first" means pop off the first row of the data
xcoarsen, ycoarsen How much to coarsen the columns or rows
"""
# next we assemble the 2-d array for the colorplot
Z = []
for c in self.ckeys:
# transform so the image plotting has the same orientation as the data
# in the file itself.
col = list(self.columns[c])
col.reverse()
Z.append(col)
# initialize the axis labels
X = []
for n in range(len(Z)):
X.append(n)
self.xlabel = "x-step number"
Y = []
for n in range(len(Z[0])):
Y.append(n)
self.ylabel = "y-step number"
Y.reverse()
# now if we're supposed to, pop off the first column as Y labels
if yaxis == "first":
# just pop off the first column (Z columns are already reversed)
Y = Z.pop(0)
self.ylabel = "y-values"
# pop the first element of the X-data
X.pop(0)
# otherwise, it's a column value
elif not yaxis == None:
Y = list(self.c(yaxis))
Y.reverse()
self.ylabel = yaxis
# if we're supposed to, pop off the top row for the x-axis values
if xaxis == "first":
X = []
for n in range(len(Z)):
X.append(Z[n].pop(-1))
self.xlabel = "x-values"
# pop the first element of the Y-data
Y.pop(-1)
# otherwise, if we specified a row from the header, use that
elif not xaxis == None:
X = array(self.h(xaxis))
# trim X down to the length of the Zd.ZX row
X.resize(len(Z[:]) - 1)
self.xlabel = xaxis
# now if we're supposed to coarsen, do so (produces a numpy array)
self.X = _fun.coarsen_array(X, xcoarsen)
self.Y = _fun.coarsen_array(Y, ycoarsen)
# Z has to be transposed to make the data file look like the plot
self.Z = _fun.coarsen_matrix(Z, xcoarsen, ycoarsen).transpose()
# if we specified labels, they trump everything
if xlabel: self.xlabel = xlabel
if ylabel: self.ylabel = ylabel
return
