fontsize can be assigned inside dictionary fontdict which provides additional parameters fontweight, verticalalignment , horizontalalignment The below snippet should work plt.title(‘Temperature \n Humidity’, fontdict = {‘fontsize’ : 100})
Alternatively, if you want to simply set the number of ticks while allowing matplotlib to position them (currently only with MaxNLocator), there is pyplot.locator_params, You can specify specific axis in this method as mentioned below, default is both:
Convert your x-axis data from text to datetime.datetime, use datetime.strptime: This is an example of how to plot data once you have an array of datetimes:
It could be a problem with the backend. What is the output of python -c ‘import matplotlib; import matplotlib.pyplot; print(matplotlib.backends.backend)’? If it is the ‘agg’ backend, what you see is the expected behaviour as it is a non-interactive backend that does not show anything to the screen, but work with plt.savefig(…). You should switch to, e.g., … Read more
There is an illustrative example of how to create custom colormaps here. The docstring is essential for understanding the meaning of cdict. Once you get that under your belt, you might use a cdict like this: Although the cdict format gives you a lot of flexibility, I find for simple gradients its format is rather unintuitive. Here is a utility function … Read more
If I understand your question right, you want to plot two things on the same axes with no shared axis. There is probably a better way to do this, but you can stack twinx (doc) and twiny (doc) as such Which will give you tick marks on all sides of the plot. ax will plot against the bottom and left, ax_new will plot against the top and right.
The following code will load an image from a file image.png and will display it as grayscale. If you want to display the inverse grayscale, switch the cmap to cmap=’gray_r’.
When making colormaps with LinearSegmentedColormap.from_list, you can supply a list of tuples of the form (value, color) (as opposed to simply a list of colors) where the values correspond to the relative positions of colors. The values must range from 0 to 1 so you will have to supply an intermediate color. In your case I might try this, and … Read more
You just have the wrong order of your commands. A backend should be set before importing pyplot in jupyter. Or in other words, after changing the backend, pyplot needs to be imported again. Therefore call %matplotlib … prior to importing pyplot. In first cell: In second cell:
How about doing it with Pillow: If an alpha (transparency) channel is present in the input image and should be preserved, use mode LA: Using matplotlib and the formula you could do: