![]() set_minor_formatter ( NullFormatter ()) # Adjust the subplot layout, because the logit one may take more space # than usual, due to y-tick labels like "1 - 10^" plt. Scatter Demo2 Scatter plot with histograms Scatter Masked Marker examples Scatter plots with a legend Simple Plot Shade regions defined by a logical mask using fillbetween Spectrum representations Stackplots and streamgraphs Stairs Demo Stem Plot Step Demo Creating a timeline with lines, dates, and text hlines and vlines Cross. ![]() grid ( True ) # Format the minor tick labels of the y-axis into empty strings with # `NullFormatter`, to avoid cumbering the axis with too many labels. By default, a linear scaling is used, mapping the lowest value to 0 and the highest to 1. yscale ( 'symlog', linthreshy = 0.01 ) plt. The normalization method used to scale scalar data to the 0, 1 range before mapping to colors using cmap. arange ( len ( y )) # plot with various axes scales plt. seed ( 19680801 ) # make up some data in the interval ]0, 1 y. I think it might be good to plot both on a log scale. Both the quantities on the x and y axes have very different scales, and one of the variables has a huge dynamic range (nearly 0 to 12 million roughly) while the other is between nearly 0 and 2. The answer to the question below would help (this seems to be a duplicate question though) Matplotlib also has a dedicated section for colormap normalization For your question, you would want to use stored value like following pcm plt.pcolor (self.data, norm colors.LogNorm ()) plt. Needs to have z/colour axis on a log scale, so we see. import matplotlib.pyplot as plt import numpy as np from numpy import ma from matplotlib import cm, ticker N 100 x np.linspace(-3.0, 3.0, N) y np.linspace(-2.0, 2.0, N) X, Y np.meshgrid(x, y) A low hump with a spike coming out. Import numpy as np import matplotlib.pyplot as plt from matplotlib.ticker import NullFormatter # useful for `logit` scale # Fixing random state for reproducibility np. I am trying to plot the following numbers on a log scale as a scatter plot in matplotlib. Demonstrate use of a log color scale in contourf. import matplotlib.pyplot as plt import numpy as np Data for plotting t np.
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