scatter

I have a set of data that I want to show as a scatter plot. I want each point to be plotted as a square of size dx . x = [0.5,0.1,0.3] y = [0.2,0.7,0.8] z = [10.,15.,12.] dx = [0.05,0.2,0.1] scatter(x,y,c=z,s=dx,marker='s') The problem is that the size s that the scatter function read is in points^2. What I'd like is having each point represented by a square of area dx^2, where this area is in 'real' units, the plot units. I hope you can get this point. I also have another question. The scatter function plots the markers with a black border, how can I drop this option and have no border at all

How could I add trendline to a dot graph drawn using matplotlib.scatter? martinenzinger as explained here With help from numpy one can calculate for example a linear fitting. # plot the data itself pylab.plot(x,y,'o') # calc the trendline z = numpy.polyfit(x, y, 1) p = numpy.poly1d(z) pylab.plot(x,p(x),"r--") # the line equation: print "y=%.6fx+(%.6f)"%(z[0],z[1]) 来源： https://stackoverflow.com/questions/26447191/how-to-add-trendline-in-python-matplotlib-dot-scatter-graphs

I would like to know how to make matplotlib's scatter function colour points by a third variable. Questions gnuplot linecolor variable in matplotlib? and Matplotlib scatterplot; colour as a function of a third variable posed similar queries, however, the answers to those questions don't address my issue: the use of c=arraywhichspecifiespointcolour in the scatter function only sets the fill colour, not the edge colour. This means that the use of c=arr... fails when using markersymbol='+' , for instance (because that marker has no fill, only edges). I want points to be coloured by a third

I want to partition matrix into blocks (not stripes) and then distribute this blocks using MPI_Scatter. I came up with solution which works, but I think it is far from "best practice". I have 8x8 matrix, filled with numbers from 0 to 63. Then I divide it into 4 4x4 blocks, using MPI_Type_vector and distribute it via MPI_Send, but this require some extra computation since i have to compute offsets for each block in big matrix. If I use scatter, first (top left) block is transfered OK, but other blocks are not (wrong offset for start of block). So is it possible to transfer blocks of matrix

I would like to scale the markersize of matplotlib.pyplot.Axes.scatter plot based on the number of points on the x/y-axis. import matplotlib.pyplot as plt import numpy as np vmin = 1 vmax = 11 x = np.random.randint(vmin, vmax, 5) y = np.random.randint(vmin, vmax, 5) fig, ax = plt.subplots() for v in np.arange(vmin, vmax): ax.axvline(v - 0.5) ax.axvline(v + 0.5) ax.axhline(v - 0.5) ax.axhline(v + 0.5) ax.set_xlim(vmin - 0.5, vmax + 0.5) ax.set_ylim(vmin - 0.5, vmax + 0.5) ax.scatter(x, y) ax.set_aspect(1) plt.show() ax is always using an equal aspect ratio and both axes have the same lim values