From the documentation for scatter: Optional kwargs control the Collection properties; in particular: edgecolors: The string ‘none’ to plot faces with no outlines facecolors: The string ‘none’ to plot unfilled outlines Try the following: import matplotlib.pyplot as plt import numpy as np x = np.random.randn(60) y = np.random.randn(60) plt.scatter(x, y, s=80, facecolors=”none”, edgecolors=”r”) plt.show() Note: … Read more
Translate from user data coordinate system to display coordinate system. and use edgecolors=”none” to plot faces with no outlines. import numpy as np fig = figure() ax = fig.add_subplot(111) dx_in_points = np.diff(ax.transData.transform(zip([0]*len(dx), dx))) scatter(x,y,c=z,s=dx_in_points**2,marker=”s”, edgecolors=”none”)
This works for me, using matplotlib 1.1: import numpy as np import matplotlib.pyplot as plt x = np.arange(10) y = np.sin(x) plt.scatter(x, y, marker=”+”, s=150, linewidths=4, c=y, cmap=plt.cm.coolwarm) plt.show() Result: Alternatively, for n points, make an array of RGB color values with shape (n, 3), and assign it to the edgecolors keyword argument of scatter(): … Read more
What you’ve got is pretty much “best practice”; it’s just a bit confusing until you get used to it. Two things, though: First, be careful with this: sizeof(MPI_CHAR) is, I assume, 4 bytes, not 1. MPI_CHAR is an (integer) constant that describes (to the MPI library) a character. You probably want sizeof(char), or SIZE/2*sizeof(char), or … Read more
The problem is that marker can only be a single value and not a list of markers, as the color parmeter. You can either do a grouping by marker value so you have the x and y lists that have the same marker and plot them: xs = [[1, 2, 3], [4, 5, 6]] ys … Read more
Using Circles An easy option is to replace the scatter by a PatchCollection consisting of Circles of radius 0.5. circles = [plt.Circle((xi,yi), radius=0.5, linewidth=0) for xi,yi in zip(x,y)] c = matplotlib.collections.PatchCollection(circles) ax.add_collection(c) Using scatter with markers of size in data units The alternative, if a scatter plot is desired, would be to update the markersize … Read more
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])
There’s no need to manually set the colors. Instead, specify a grayscale colormap… import numpy as np import matplotlib.pyplot as plt # Generate data… x = np.random.random(10) y = np.random.random(10) # Plot… plt.scatter(x, y, c=y, s=500) plt.gray() plt.show() Or, if you’d prefer a wider range of colormaps, you can also specify the cmap kwarg to … Read more
This can be a somewhat confusing way of defining the size but you are basically specifying the area of the marker. This means, to double the width (or height) of the marker you need to increase s by a factor of 4. [because A = WH => (2W)(2H)=4A] There is a reason, however, that the … Read more
plot does not have any parameter name type To plot the scatter use plt.scatter(x,y)