If you only need an image as the result, you can get the canvas buffer as a numpy array, and then do the blending, here is an example: from matplotlib import pyplot as plt import numpy as np fig, ax = plt.subplots() ax.scatter(x1,y1,c=”b”,edgecolors=”none”) ax.set_xlim(-4, 4) ax.set_ylim(-4, 4) ax.patch.set_facecolor(“none”) ax.patch.set_edgecolor(“none”) fig.canvas.draw() w, h = fig.canvas.get_width_height() img … Read more
You can set the alpha argument in your imshow command. In your example, img3 = plt.imshow(zvals2, interpolation=’nearest’, cmap=cmap2, origin=’lower’, alpha=0.6) EDIT: Thanks for the clarification. Here is a description of what you can do: First, choose a matplotlib colormap object (in your case, for white and black, you can take the ‘binary’ colormap). Or create … Read more
If you don’t want to use a for loop (which can be very slow for large lists) You can use the scatter command as is with an RGB color list, but you need to specify the colors as a vector of RGB (or RGBA) values between 0 and 1 X = [0, 1, 2] Y … Read more
It’s easiest to use a “symlog” plot for this purpose. The interval near 0 will be on a linear scale, so 0 can be displayed. import matplotlib.pyplot as plt fig, ax = plt.subplots() ax.plot([0,1,2],[10,10,100],marker=”o”,linestyle=”-“) ax.set_yscale(‘symlog’) ax.set_xscale(‘symlog’) plt.show() Symlog sets a small interval near zero (both above and below) to use a linear scale. This allows … Read more
I think @Evert has the right answer: plt.scatter(dates,values) plt.plot(dates, values) plt.show() Which is pretty much the same as plt.plot(dates, values, ‘-o’) plt.show() You can replace -o with another suitable format string as described in the documentation. You can also split the choices of line and marker styles using the linestyle= and marker= keyword arguments.
If you don’t want to change the spacing globally (by editing your rcParams), and want a cleaner approach, try this: ax.tick_params(axis=”both”, which=”major”, pad=15) or for just x axis ax.tick_params(axis=”x”, which=”major”, pad=15) or the y axis ax.tick_params(axis=”y”, which=”major”, pad=15)
Given li in the question: li = list(zip(range(1, 14), range(14, 27))) To unpack the data from pairs into lists use zip: x, y = zip(*li) x → (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13) y → (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26) … Read more
Updated: Now includes handling the data sample and uses mpl dates functionality. import matplotlib.pyplot as plt from matplotlib.dates import DateFormatter, MinuteLocator, SecondLocator import numpy as np from StringIO import StringIO import datetime as dt ### The example data a=StringIO(“””a 10:15:22 10:15:30 OK b 10:15:23 10:15:28 OK c 10:16:00 10:17:10 FAILED b 10:16:30 10:16:50 OK “””) … Read more
I found the solution through the help of this SO post, which links to this free sample chapter of a book I’m probably gonna need to buy. As sort of mentioned in a number of other posts, one needs to “Promote” the blank QtWidget to a MplWidget using the header mplwidget. After doing this, and … Read more
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