def plot_points_3D( filenames, show = True, fignum = 1,
axislabels = None ):
"""
Plot a set of points specified by coordinates contained within filename
The input file should contain the x1, x2 and x3 coordinates of each point
in csv format. E.g. A file with 4 points may look like
0.5,0.5,0.5, 0.5
0.5,1.0,0.5, 0.0
0.5,0.0,0.5, 0.0
"""
if ( not type(filenames ) == type([]) ):
filenames = [filenames]
colors = ['k','r','b','g']
markers = ['o','^','8','s']
fig = pylab.figure( fignum )
ax = p3.Axes3D( fig )
i = 0
for filename in filenames:
data = file_utils.read_csv_floats( filename )
assert data.shape[0] == 3
ax.scatter3D( data[0,:], data[1,:], data[2,:], c = colors[i],
marker = markers[0] )
i += 1
if ( axislabels is not None ):
ax.set_xlabel( axislabels[0] )
ax.set_ylabel( axislabels[1] )
ax.set_zlabel( axislabels[2] )
if ( show ):
pylab.show()
def plot_sub_space_indices( filename,show = True,fignum = 1,
otherfilename = None,
title = None ):
pylab.figure( fignum )
data = file_utils.read_csv_floats( filename )
assert data.shape[1] == 2
#pylab.plot(data[:,0],data[:,1],'ok')
xMax = numpy.max( data[:,0] )
yMax = numpy.max( data[:,1] )
for i in range(data.shape[0]):
box = numpy.array( [[data[i,0]-1,data[i,1]-1],
[data[i,0],data[i,1]-1],
[data[i,0],data[i,1]],
[data[i,0]-1,data[i,1]],
[data[i,0]-1,data[i,1]-1]] ) + 0.5
p1 = pylab.plot( box[:,0], box[:,1], '-k' )
#pylab.legend((p1),("sparse grid indices"),loc=0)
if ( otherfilename is not None ):
data = file_utils.read_csv_floats( otherfilename )
if (data.shape[0] > 0 ):
for i in range( data.shape[0] ):
box = numpy.array( [[data[i,0]-1,data[i,1]-1],
[data[i,0],data[i,1]-1],
[data[i,0],data[i,1]],
[data[i,0]-1,data[i,1]],
[data[i,0]-1,data[i,1]-1]] ) + 0.5
p2 = pylab.plot( box[:,0], box[:,1], '-r' )
xMaxNew = numpy.max( data[:,0] )
xMax = max( xMax, xMaxNew )
yMaxNew = numpy.max( data[:,1] )
yMax = max( yMax, yMaxNew )
pylab.legend( (p1,p2), ('sparse grid indices',
'active sparse grid indices'), loc = 0 )
lim = max( xMax, yMax )
pylab.xticks( numpy.arange( 0, lim + 1 ) )
pylab.yticks( numpy.arange( 0, lim + 1) )
pylab.xlim( -0.5, lim + 1 )
pylab.ylim( -0.5, lim + 1 )
if ( title is not None ):
pylab.title( title )
if ( show ):
pylab.show()
def plot_points( filenames, show = True, fignum = 1,
axislabels = None, title = None, fontsize = 12,
markersize = 2 ):
"""
Plot a set of points specified by coordinates contained within filename
The input file should contain the x1 and x2 coordinates of each point in
csv format. E.g.
0.5,0.5,0.5
0.5,1.0,0.0
"""
params = { 'lines.markersize': markersize,
'font.size': fontsize }
pylab.rcParams.update( params )
if ( not type(filenames) == type([]) ):
filenames = [filenames]
pylab.figure( fignum )
colors = ['k','r','b','g','m','y','c']
i = 0
for filename in filenames:
data = file_utils.read_csv_floats( filename )
if ( len( data ) > 0 ):
assert data.shape[0] == 2
pylab.plot( data[0,:], data[1,:], marker='o',
color = colors[i],
linestyle = "" )
i += 1
if ( i > 6 ):
break
if ( axislabels is not None ):
pylab.xlabel( axislabels[0] )
pylab.ylabel( axislabels[1], rotation='horizontal' )
if ( title is not None ):
pylab.title( title )
if ( show ):
pylab.show()
def plot_surface_from_file_function_values( filename, numPts1D,
degreeOfFreedom = 0,
transposeData = False,
domain = None,
show = True,
fignum = 1,
axislabels = None,
title = None ):
"""
File must be a ( nDOF x nPts ) matrix
"""
data = file_utils.read_csv_floats( filename )
if ( transposeData ):
data = numpy.transpose( data );
data = data[degreeOfFreedom,:]
plot_surface_from_function_values( data,
domain = domain,
numPts1D = numPts1D,
show = show,
fignum = fignum,
axislabels = axislabels,
title = title )
def plotPointClasses( basename, show = True, colors = None ):
assert type( basename ) == type("")
filename = addExtension( basename,".csv" )
data = file_utils.read_csv_floats( filename )
assert data.shape[1] == 4
k = 0
classSets = []
classNumbers = {}
classNumbers[int(data[0,3])] = k
classSets.append( [data[0,:2]] )
for i in range ( 1, data.shape[0] ):
if ( classNumbers.has_key( int(data[i,3]) ) ):
classSets[classNumbers[int(data[i,3])]].append( data[i,:2] )
else:
k += 1
classNumbers[int(data[i,3])] = k
classSets.append( [data[i,:2]] )
if colors is not None:
if len( colors ) != len( classSets ):
colors = None
msg = "Warning: (PlotPointClasses) The number of colors specified does not match the number of classes. Reverting to default colors."
print msg
pylab.figure()
for i in range( len( classSets ) ):
points = numpy.array( classSets[i] )
if colors is None:
pylab.plot( points[:,0], points[:,1], 'o' )
else:
pylab.plot( points[:,0], points[:,1], marker = 'o',
color = colors[i], linestyle = 'None')
if ( show ):
pylab.show()
