NAME:
scatterplot
PURPOSE:
make a ‘smart’ scatterplot that is a density plot in high-density regions and a regular scatterplot for outliers
INPUT:
x, y
xlabel - (raw string!) x-axis label, LaTeX math mode, no $s needed
ylabel - (raw string!) y-axis label, LaTeX math mode, no $s needed
xrange
yrange
bins - number of bins to use in each dimension
weights - data-weights
aspect - aspect ratio
contours - if False, don’t plot contours
cntrcolors - color of contours (can be array as for bovy_dens2d)
cntrlw, cntrls - linewidths and linestyles for contour
cntrSmooth - use ndimage.gaussian_filter to smooth before contouring
onedhists - if True, make one-d histograms on the sides
onedhistx - if True, make one-d histograms on the side of the x distribution
onedhisty - if True, make one-d histograms on the side of the y distribution
onedhistcolor, onedhistfc, onedhistec
onedhistxnormed, onedhistynormed - normed keyword for one-d histograms
onedhistxweights, onedhistyweights - weights keyword for one-d histograms
cmap= cmap for density plot
hist= and edges= - you can supply the histogram of the data yourself, this can be useful if you want to censor the data, both need to be set and calculated using scipy.histogramdd with the given range
retAxes= return all Axes instances
OUTPUT:
plot to output device, Axes instance(s) or not, depending on input
HISTORY:
2010-04-15 - Written - Bovy (NYU)
