Caveat: Unless the ticklabels are already set to a string (as is usually the case in e.g. a boxplot), this will not work with any version of matplotlib newer than 1.1.0. If you’re working from the current github master, this won’t work. I’m not sure what the problem is yet… It may be an unintended … Read more
You can adjust the subplot geometry in the very tight_layout call as follows: fig.tight_layout(rect=[0, 0.03, 1, 0.95]) As it’s stated in the documentation (https://matplotlib.org/users/tight_layout_guide.html): tight_layout() only considers ticklabels, axis labels, and titles. Thus, other artists may be clipped and also may overlap.
Use matplotlib‘s calls that won’t block: Using draw(): from matplotlib.pyplot import plot, draw, show plot([1,2,3]) draw() print(‘continue computation’) # at the end call show to ensure window won’t close. show() Using interactive mode: from matplotlib.pyplot import plot, ion, show ion() # enables interactive mode plot([1,2,3]) # result shows immediatelly (implicit draw()) print(‘continue computation’) # at … Read more
The following code will load an image from a file image.png and will display it as grayscale. import numpy as np import matplotlib.pyplot as plt from PIL import Image fname=”image.png” image = Image.open(fname).convert(“L”) arr = np.asarray(image) plt.imshow(arr, cmap=’gray’, vmin=0, vmax=255) plt.show() If you want to display the inverse grayscale, switch the cmap to cmap=’gray_r’.
First, what happens when T0 is not None? I would test that, then I would adjust the values I pass to plt.subplot(); maybe try values 131, 132, and 133, or values that depend whether or not T0 exists. Second, after plt.show() is called, a new figure is created. To deal with this, you can Call … Read more
Just place the colorbar in its own axis and use subplots_adjust to make room for it. As a quick example: import numpy as np import matplotlib.pyplot as plt fig, axes = plt.subplots(nrows=2, ncols=2) for ax in axes.flat: im = ax.imshow(np.random.random((10,10)), vmin=0, vmax=1) fig.subplots_adjust(right=0.8) cbar_ax = fig.add_axes([0.85, 0.15, 0.05, 0.7]) fig.colorbar(im, cax=cbar_ax) plt.show() Note that the … Read more
You can use pyplot.matshow() from matplotlib: import matplotlib.pyplot as plt plt.matshow(dataframe.corr()) plt.show() Edit: In the comments was a request for how to change the axis tick labels. Here’s a deluxe version that is drawn on a bigger figure size, has axis labels to match the dataframe, and a colorbar legend to interpret the color scale. … Read more
I constantly forget the names of the colors I want to use and keep coming back to this question =) The previous answers are great, but I find it a bit difficult to get an overview of the available colors from the posted image. I prefer the colors to be grouped with similar colors, so … Read more
Use pyplot.suptitle or Figure.suptitle: import matplotlib.pyplot as plt import numpy as np fig=plt.figure() data=np.arange(900).reshape((30,30)) for i in range(1,5): ax=fig.add_subplot(2,2,i) ax.imshow(data) fig.suptitle(‘Main title’) # or plt.suptitle(‘Main title’) plt.show()
Here’s the working version of the code in question (requires at least version Matplotlib 1.1.0 from 2011-11-14): import numpy as np import matplotlib.pyplot as plt plt.axis([0, 10, 0, 1]) for i in range(10): y = np.random.random() plt.scatter(i, y) plt.pause(0.05) plt.show() Note the call to plt.pause(0.05), which both draws the new data and runs the GUI’s … Read more