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import core.modules
import core.modules.module_registry
from core.modules.vistrails_module import Module, ModuleError
from core.modules.basic_modules import PythonSource
from Array import *
from Matrix import *
import pylab
import matplotlib
import urllib
import random
class ArrayPlot(object):
namespace = 'numpy|array|plotting'
def get_label(self, ar, i):
lab = ar.get_name(i)
if lab == None:
return 'Array ' + str(i)
else:
return lab
def is_cacheable(self):
return False
def get_color(self, colors, i, randomcolor):
if randomcolor:
return (random.random(), random.random(), random.random())
if self.color_dict == None:
self.color_dict = {}
for (k,r,g,b) in colors:
self.color_dict[k] = (r,g,b)
if self.color_dict.has_key(i):
return self.color_dict[i]
else:
return None
def get_marker(self, markers, i):
if markers == None:
return None
if self.marker_dict == None:
self.marker_dict = {}
for (k,m) in markers:
self.marker_dict[k] = m
if self.marker_dict.has_key(i):
return self.marker_dict[i]
else:
return None
def get_alpha(self, alphas, i):
return None
class ArrayImage(ArrayPlot, Module):
'''
Display the 2D input Data Array as a color-mapped image.
Independent control of the aspect ratio, colormap, presence of the
colorbar and presented axis values are provided through the
appropriate input ports: Aspect Ratio, Colormap, Colorbar,
Extents. To change the colormap being used, it must be one of the
pre-made maps provided by matplotlib.cm. Only 1 2D array can be
viewed at a time.
'''
def compute(self):
data = self.getInputFromPort("Data Array")
da_ar = data.get_array().squeeze()
if da_ar.ndim != 2:
raise ModuleError("Input Data Array must have dimension = 2")
aspect_ratio = self.forceGetInputFromPort("Aspect Ratio")
colormap = self.forceGetInputFromPort("Colormap")
colorbar = self.forceGetInputFromPort("Colorbar")
extents = self.forceGetInputFromPort("Extents")
# Quickly check the assigned colormap to make sure it's valid
if colormap == None:
colormap = "jet"
if not hasattr(pylab, colormap):
colormap = "jet"
bg_color = self.forceGetInputFromPort("Background")
array_x_t = self.forceGetInputFromPort("Use X Title")
array_y_t = self.forceGetInputFromPort("Use Y Title")
p_title = self.forceGetInputFromPort("Title")
x_label = self.forceGetInputFromPort("X Title")
y_label = self.forceGetInputFromPort("Y Title")
s = urllib.unquote(str(self.forceGetInputFromPort("source", '')))
s = 'from pylab import *\n' +\
'from numpy import *\n' +\
'import numpy\n'
if bg_color == None:
bg_color = 'w'
if type(bg_color) == type(''):
s += 'figure(facecolor=\'' + bg_color + '\')\n'
else:
s += 'figure(facecolor=' + str(bg_color) + ')\n'
s += 'imshow(da_ar, interpolation=\'bicubic\''
if aspect_ratio != None:
s += ', aspect=' + str(aspect_ratio)
if extents != None:
s += ', extent=['+str(extents[0])+','+str(extents[1])+','+str(extents[2])+','+str(extents[3])+']'
s += ')\n'
s += colormap + '()\n'
if colorbar:
s += 'colorbar()\n'
if array_x_t:
s += 'xlabel(\'' + data.get_domain_name() + '\')\n'
elif x_label:
s += 'xlabel(\'' + x_label + '\')\n'
if array_y_t:
s += 'ylabel(\'' + data.get_range_name() + '\')\n'
elif y_label:
s += 'ylabel(\'' + y_label + '\')\n'
if p_title:
s += 'title(\'' + p_title + '\')\n'
exec s
self.setResult('source', s)
@classmethod
def register(cls, reg, basic):
reg.add_module(cls, namespace=cls.namespace)
@classmethod
def register_ports(cls, reg, basic):
reg.add_input_port(cls, "source", (basic.String, 'source'), True)
reg.add_input_port(cls, "Data Array", (NDArray, 'Array to Plot'))
reg.add_input_port(cls, "Aspect Ratio", (basic.Float, 'Aspect Ratio'))
reg.add_input_port(cls, "Colormap", (basic.String, 'Colormap'))
reg.add_input_port(cls, "Colorbar", (basic.Boolean, 'Show Colorbar'), True)
reg.add_input_port(cls, "Extents", [basic.Float, basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Background", [basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Use X Title", (basic.Boolean, 'Apply X-axis Label'))
reg.add_input_port(cls, "Use Y Title", (basic.Boolean, 'Apply Y-axis Label'))
reg.add_input_port(cls, "Title", (basic.String, 'Figure Title'))
reg.add_input_port(cls, "X Title", (basic.String, 'X-axis label'), True)
reg.add_input_port(cls, "Y Title", (basic.String, 'Y-axis label'), True)
reg.add_output_port(cls, "source", (basic.String, 'source'))
class Histogram(ArrayPlot, Module):
'''
Plot a histogram of the data values. Multiple datasets can be
presented by providing multiple connections to the Data Array
port. These data are then differentiated by assigned colors and
labels. By default, 10 bins are used to histogram the data.
Additionally, recapturing the PDF of the data is possible by
enabling the Normalize option.
'''
def compute(self):
data = self.getInputListFromPort("Data Array")
self.label_dict = None
self.color_dict = None
use_legend = self.forceGetInputFromPort("Legend")
randomcolors = self.forceGetInputFromPort("Random Colors")
colors = self.forceGetInputListFromPort("Colors")
bg_color = self.forceGetInputFromPort("Background")
array_x_t = self.forceGetInputFromPort("Use X Title")
array_y_t = self.forceGetInputFromPort("Use Y Title")
p_title = self.forceGetInputFromPort("Title")
x_label = self.forceGetInputFromPort("X Title")
nbins = self.forceGetInputFromPort("Bins")
if nbins == None:
nbins = 10
normed = self.forceGetInputFromPort("Normalize")
if normed == None:
normed = False
s = urllib.unquote(str(self.forceGetInputFromPort("source", '')))
self.source = ''
s = 'from pylab import *\n' +\
'from numpy import *\n' +\
'import numpy\n'
if bg_color == None:
bg_color = 'w'
if type(bg_color) == type(''):
s += 'figure(facecolor=\'' + bg_color + '\')\n'
else:
s += 'figure(facecolor=' + str(bg_color) + ')\n'
data_list = []
for i in data:
data_list.append(i.get_array().squeeze())
da_ar = None
try:
da_ar = numpy.array(data_list)
except:
raise ModuleException("Not all Data Array inputs are the same size!")
for i in range(da_ar.shape[0]):
lab = self.get_label(data[i], i)
col = self.get_color(colors, i, randomcolors)
s += 'hist(da_ar['+str(i)+',:], bins=' + str(nbins)
if lab != None:
s += ', label=\'' + lab + '\''
if col != None:
s += ', facecolor=' + str(col)
s += ', normed='+str(normed)
s += ')\n'
if use_legend:
s += 'legend()\n'
if array_x_t:
s += 'xlabel(\'' + data[0].get_domain_name() + '\')\n'
elif x_label:
s += 'xlabel(\'' + x_label + '\')\n'
if array_y_t:
s += 'ylabel(\'Histogram Value\')\n'
if p_title:
s += 'title(\'' + p_title + '\')\n'
exec s
self.setResult("source", s)
@classmethod
def register(cls, reg, basic):
reg.add_module(cls, namespace=cls.namespace)
@classmethod
def register_ports(cls, reg, basic):
reg.add_input_port(cls, "source", (basic.String, 'source'), True)
reg.add_input_port(cls, "Data Array", (NDArray, 'Data Array to Plot'))
reg.add_input_port(cls, "Legend", (basic.Boolean, 'Use Legend'), True)
reg.add_input_port(cls, "Random Colors", (basic.Boolean, 'Assign Random Colors'), True)
reg.add_input_port(cls, "Colors", [basic.Integer, basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Background", [basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Use X Title", (basic.Boolean, 'Apply X-axis Label'))
reg.add_input_port(cls, "Use Y Title", (basic.Boolean, 'Apply Y-axis Label'))
reg.add_input_port(cls, "Title", (basic.String, 'Figure Title'))
reg.add_input_port(cls, "X Title", (basic.String, 'X-axis label'), True)
reg.add_input_port(cls, "Bins", (basic.Integer, 'Number of Bins'))
reg.add_input_port(cls, "Normalize", (basic.Boolean, 'Normalize to PDF'), True)
reg.add_output_port(cls, "source", (basic.String, 'source'))
class BarChart(ArrayPlot, Module):
'''
Create a bar chart of the input data. Different datasets can be
used simultaneously by connecting to the Data input port multiple
times. Each successive data connection will be rendered on top of
the previous dataset. This creates a stacked bar chart. Error
bars are drawn with the errors for each of the datasets connected
to the Error Bars input port.
'''
def get_ticks(self, num):
a = []
for i in range(num):
a.append('')
for i in self.tick_dict.keys():
a[i] = self.tick_dict[i]
return a
def compute(self):
data = self.getInputListFromPort("Data")
errs = self.forceGetInputListFromPort("Error Bars")
if len(errs) == 0:
errs = None
self.label_dict = None
self.color_dict = None
use_legend = self.forceGetInputFromPort("Legend")
randomcolors = self.forceGetInputFromPort("Random Colors")
colors = self.forceGetInputListFromPort("Colors")
bg_color = self.forceGetInputFromPort("Background")
array_x_t = self.forceGetInputFromPort("Use X Title")
array_y_t = self.forceGetInputFromPort("Use Y Title")
ticks = self.forceGetInputListFromPort("Bar Labels")
self.tick_dict = {}
for (k,v) in ticks:
self.tick_dict[k] = v
p_title = self.forceGetInputFromPort("Title")
x_label = self.forceGetInputFromPort("X Title")
y_label = self.forceGetInputFromPort("Y Title")
width = self.forceGetInputFromPort("Bar Width")
if width == None:
width = 0.5
if errs != None:
if len(data) != len(errs):
raise ModuleError("Number of data does not match number of error bar data")
s = urllib.unquote(str(self.forceGetInputFromPort("source", '')))
self.source = ''
s = 'from pylab import *\n' +\
'from numpy import *\n' +\
'import numpy\n'
if bg_color == None:
bg_color = 'w'
if type(bg_color) == type(''):
s += 'figure(facecolor=\'' + bg_color + '\')\n'
else:
s += 'figure(facecolor=' + str(bg_color) + ')\n'
numpts = None
ind = None
prev = None
ind = numpy.arange(data[0].get_array().flatten().shape[0])
t = self.get_ticks(data[0].get_array().flatten().shape[0])
ag_ar = numpy.zeros((len(data), data[0].get_array().flatten().shape[0]))
for i in range(len(data)):
da_ar = data[i].get_array().flatten()
ag_ar[i,:] = da_ar
er_ar = numpy.zeros((len(data), data[0].get_array().flatten().shape[0]))
if errs != None:
for i in range(len(data)):
er_ar[i,:] = errs[i].get_array().flatten()
for i in range(ag_ar.shape[0]):
s += 'bar(ind, ag_ar[' + str(i) + ',:], width'
lab = self.get_label(data[i], i)
col = self.get_color(colors, i, randomcolors)
if lab != None:
s += ', label=\'' + lab + '\''
if col != None:
s += ', color=' + str(col)
if errs != None:
s += ', yerr=er_ar[' + str(i) + ',:]'
if prev != None:
s += ', bottom=ag_ar[' + str(i-1) + ',:]'
s += ')\n'
prev = ag_ar[i]
if use_legend:
s += 'legend()\n'
if array_x_t:
s += 'xlabel(\'' + data[0].get_domain_name() + '\')\n'
elif x_label:
s += 'xlabel(\'' + x_label + '\')\n'
if array_y_t:
s += 'ylabel(\'' + data[0].get_range_name() + '\')\n'
elif y_label:
s += 'ylabel(\'' + y_label + '\')\n'
if p_title:
s += 'title(\'' + p_title + '\')\n'
s += 'xticks(ind + width/2., t)\n'
exec s
self.setResult("source", s)
@classmethod
def register(cls, reg, basic):
reg.add_module(cls, namespace=cls.namespace)
@classmethod
def register_ports(cls, reg, basic):
reg.add_input_port(cls, "source", (basic.String, 'source'), True)
reg.add_input_port(cls, "Data", (NDArray, 'Data Array to Plot'))
reg.add_input_port(cls, "Error Bars", (NDArray, 'Error Array to Plot'))
reg.add_input_port(cls, "Legend", (basic.Boolean, 'Use Legend'), True)
reg.add_input_port(cls, "Random Colors", (basic.Boolean, 'Assign Random Colors'), True)
reg.add_input_port(cls, "Colors", [basic.Integer, basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Background", [basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Bar Labels", [basic.Integer, basic.String], True)
reg.add_input_port(cls, "Use X Title", (basic.Boolean, 'Apply X-axis Label'))
reg.add_input_port(cls, "Use Y Title", (basic.Boolean, 'Apply Y-axis Label'))
reg.add_input_port(cls, "X Title", (basic.String, 'X-axis label'), True)
reg.add_input_port(cls, "Y Title", (basic.String, 'Y-axis label'), True)
reg.add_input_port(cls, "Title", (basic.String, 'Figure Title'))
reg.add_input_port(cls, "Bar Width", (basic.Float, 'Bar Width'), True)
reg.add_output_port(cls, "source", (basic.String, 'source'))
class ScatterPlot(ArrayPlot, Module):
'''
Create a scatter plot from X and Y positions defined by the X
Array and Y Array ports, respectively. Datasets can be added by
connecting multiple arrays to the appropriate input ports.
Symbols representing each dataset can be defined by using the
Markers input assigning a valid pylab symbol to a dataset.
'''
def compute(self):
xdata = self.getInputListFromPort("X Array")
ydata = self.getInputListFromPort("Y Array")
self.label_dict = None
use_legend = self.forceGetInputFromPort("Legend")
randomcolors = self.forceGetInputFromPort("Random Colors")
colors = self.forceGetInputListFromPort("Colors")
self.color_dict = None
bg_color = self.forceGetInputFromPort("Background")
markers = self.forceGetInputListFromPort("Markers")
self.marker_dict = None
ps = self.forceGetInputFromPort("Point Size")
array_x_t = self.forceGetInputFromPort("Use X Title")
array_y_t = self.forceGetInputFromPort("Use Y Title")
p_title = self.forceGetInputFromPort("Title")
x_label = self.forceGetInputFromPort("X Title")
y_label = self.forceGetInputFromPort("Y Title")
s = urllib.unquote(str(self.forceGetInputFromPort("source", '')))
self.source = ''
if len(xdata) != len(ydata):
raise ModuleError("Cannot create scatter plot for different number of X and Y datasets.")
s = 'from pylab import *\n' +\
'from numpy import *\n' +\
'import numpy\n'
if bg_color == None:
bg_color = 'w'
if type(bg_color) == type(''):
s += 'figure(facecolor=\'' + bg_color + '\')\n'
else:
s += 'figure(facecolor=' + str(bg_color) + ')\n'
xdata_ar = numpy.zeros((len(xdata), xdata[0].get_array().flatten().shape[0]))
ydata_ar = numpy.zeros((len(xdata), xdata[0].get_array().flatten().shape[0]))
for i in range(len(xdata)):
xd = xdata[i]
yd = ydata[i]
xdata_ar[i,:] = xd.get_array().flatten()
ydata_ar[i,:] = yd.get_array().flatten()
for i in range(len(xdata)):
xar = xdata[i]
yar = ydata[i]
lab = self.get_label(xar, i)
col = self.get_color(colors, i, randomcolors)
mar = self.get_marker(markers, i)
s += 'scatter(xdata_ar[' + str(i) +',:], ydata_ar[' + str(i) + ',:]'
if lab != None:
s += ', label=\'' + lab +'\''
if col != None:
s += ', color=' + str(col)
if mar != None:
s += ', marker=\'' + mar + '\''
if ps != None:
s += ', size=' + str(ps)
s += ')\n'
if use_legend:
s += 'legend()\n'
if array_x_t:
s += 'xlabel(\'' + xar.get_domain_name() + '\')\n'
elif x_label:
s += 'xlabel(\'' + x_label + '\')\n'
if array_y_t:
s += 'ylabel(\'' + yar.get_domain_name() + '\')\n'
elif y_label:
s += 'ylabel(\'' + y_label + '\')\n'
if p_title:
s += 'title(\'' + p_title + '\')\n'
print s
exec s
self.setResult("source", s)
@classmethod
def register(cls, reg, basic):
reg.add_module(cls, namespace=cls.namespace)
@classmethod
def register_ports(cls, reg, basic):
reg.add_input_port(cls, "source", (basic.String, 'source'), True)
reg.add_input_port(cls, "X Array", (NDArray, 'X Array to Plot'))
reg.add_input_port(cls, "Y Array", (NDArray, 'Y Array to Plot'))
reg.add_input_port(cls, "Legend", (basic.Boolean, 'Use Legend'), True)
reg.add_input_port(cls, "Random Colors", (basic.Boolean, 'Assign Random Colors'), True)
reg.add_input_port(cls, "Colors", [basic.Integer, basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Background", [basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Markers", [basic.Integer, basic.String], True)
reg.add_input_port(cls, "Use X Title", (basic.Boolean, 'Apply X-axis Label'))
reg.add_input_port(cls, "Use Y Title", (basic.Boolean, 'Apply Y-axis Label'))
reg.add_input_port(cls, "X Title", (basic.String, 'X-axis label'), True)
reg.add_input_port(cls, "Y Title", (basic.String, 'Y-axis label'), True)
reg.add_input_port(cls, "Title", (basic.String, 'Figure Title'))
reg.add_input_port(cls, "Point Size", (basic.Float, 'Point Size'), True)
reg.add_output_port(cls, "source", (basic.String, 'source'))
class LinePlot(ArrayPlot, Module):
'''
Create a standard line plot from a 1 or 2-dimensional Input Array.
If the Input Array is 2-dimensional, each row will be plotted as a
new line.
'''
def compute(self):
data = self.getInputFromPort("Input Array")
indexes = self.forceGetInputFromPort("Indexes")
self.label_dict = None
use_legend = self.forceGetInputFromPort("Legend")
randomcolors = self.forceGetInputFromPort("Random Colors")
colors = self.forceGetInputListFromPort("Colors")
self.color_dict = None
markers = self.forceGetInputListFromPort("Markers")
self.marker_dict = None
x_label = self.forceGetInputFromPort("X Title")
y_label = self.forceGetInputFromPort("Y Title")
p_title = self.forceGetInputFromPort("Title")
bg_color = self.forceGetInputFromPort("Background")
array_x_t = self.forceGetInputFromPort("Use X Title")
array_y_t = self.forceGetInputFromPort("Use Y Title")
s = urllib.unquote(str(self.forceGetInputFromPort("source", '')))
self.source = ''
da_ar = data.get_array()
if da_ar.ndim > 2:
raise ModuleError("Cannot plot data with dimensions > 2")
s = 'from pylab import *\n' +\
'from numpy import *\n' +\
'import numpy\n'
if bg_color == None:
bg_color = 'w'
if type(bg_color) == type(''):
s += 'figure(facecolor=\'' + bg_color + '\')\n'
else:
s += 'figure(facecolor=' + str(bg_color) + ')\n'
if da_ar.ndim == 1:
da_ar.shape = (1, da_ar.shape[0])
xar = self.forceGetInputFromPort("X Values")
sf = self.forceGetInputFromPort("Scaling Factor")
if sf == None:
sf = 1.
if xar == None:
start_i = None
end_i = None
if indexes == None:
start_i = 0
end_i = da_ar.shape[1]
else:
start_i = indexes[0]
end_i = indexes[1]
xar = numpy.arange(start_i, end_i)
xar = xar * sf
else:
xar = xar.get_array()
print da_ar.shape
print xar.shape
for i in range(da_ar.shape[0]):
lab = self.get_label(data, i)
col = self.get_color(colors, i, randomcolors)
mar = self.get_marker(markers, i)
if indexes == None:
s += 'plot(xar, da_ar[' + str(i) + ',:]'
else:
s += 'plot(xar, da_ar[' + str(i) + ',' + str(indexes[0]) + ':' + str(indexes[1]) + ']'
if lab != None:
s += ', label=\'' + lab +'\''
if col != None:
s += ', color=' + str(col)
if mar != None:
s += ', marker=\'' + mar + '\''
s += ')\n'
if use_legend:
s += 'legend()\n'
if array_x_t:
s += 'xlabel(\'' + data.get_domain_name() + '\')\n'
elif x_label:
s += 'xlabel(\'' + x_label + '\')\n'
if array_y_t:
s += 'ylabel(\'' + data.get_range_name() + '\')\n'
elif y_label:
s += 'ylabel(\'' + y_label + '\')\n'
if p_title:
s += 'title(\'' + p_title + '\')\n'
exec s
self.setResult("source", s)
@classmethod
def register(cls, reg, basic):
reg.add_module(cls, namespace=cls.namespace)
@classmethod
def register_ports(cls, reg, basic):
reg.add_input_port(cls, "source", (basic.String, 'source'), True)
reg.add_input_port(cls, "Input Array", (NDArray, 'Array to Plot'))
reg.add_input_port(cls, "X Values", (NDArray, 'Domain Values'))
reg.add_input_port(cls, "Legend", (basic.Boolean, 'Use Legend'), True)
reg.add_input_port(cls, "Random Colors", (basic.Boolean, 'Assign Random Colors'), True)
reg.add_input_port(cls, "Colors", [basic.Integer, basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Markers", [basic.Integer, basic.String], True)
reg.add_input_port(cls, "Use X Title", (basic.Boolean, 'Apply X-axis Label'))
reg.add_input_port(cls, "Use Y Title", (basic.Boolean, 'Apply Y-axis Label'))
reg.add_input_port(cls, "X Title", (basic.String, 'X-axis label'), True)
reg.add_input_port(cls, "Y Title", (basic.String, 'Y-axis label'), True)
reg.add_input_port(cls, "Title", (basic.String, 'Figure Title'))
reg.add_input_port(cls, "Background", [basic.Float, basic.Float, basic.Float], True)
reg.add_input_port(cls, "Indexes", [basic.Integer, basic.Integer], True)
reg.add_input_port(cls, "Scaling Factor", (basic.Float, 'Scaling Factor'), True)
reg.add_output_port(cls, "source", (basic.String, 'source'))
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