Python Matplotlib rectangular binning
I realize that there is a patch submitted to matplotlib, but I adopted the code from the other example to acommodate a few needs that I had.
now the histogram is plotted from the lower left corner, as in conventional math (not computing)
also, values outside the binning range are ignored and I use a 2d numpy array for the twodimensional array
I changed the data input from pairs to two 1D arrays since this is how data is supplied to scatter(x,y) and alike functions
def histBin(x,y,x_range=(0.0,1.0),y_range=(0.0,1.0),xbins=10,ybins=None):
""" Helper function to do 2D histogram binning
x, y are lists / 2D arrays
x_range and yrange define the range of the plot similar to the hist(range=...)
xbins,ybins are the number of bins within this range.
"""
pairsData = zip(x,y)
if (ybins == None):
ybins = xbins
xdata, ydata = zip(*pairsData)
xmin,xmax = x_range
xmin = float(xmin)
xmax = float(xmax)
xwidth = xmax-xmin
ymin,ymax = y_range
ymin = float(ymin)
ymax = float(ymax)
ywidth = ymax-ymin
def xbin(xval):
return floor(xbins*(xval-xmin)/xwidth) if xmin <= xval < xmax else xbins-1 if xval ==xmax else None
def ybin(yval):
return floor(ybins*(yval-ymin)/ywidth) if ymin <= yval < ymax else ybins-1 if yval ==ymax else None
hist = numpy.zeros((xbins,ybins))
for x,y in pairsData:
i_x,i_y = xbin(x),ybin(ymax-y)
if i_x is not None and i_y is not None:
hist[i_y,i_x] += 1
extent = (xmin,xmax,ymin,ymax)
return hist,extent
Numpy has a function called histogram2d, whose docstring also shows you how to visualize it using Matplotlib. Add interpolation=nearest
to the imshow call to disable the interpolation.