I've got these two lists which are x,y points to be plotted:
microns = [38, 45, 53, 63, 75, 90, 106, 125, 150, 180]
cumulative_dist = [25.037, 32.577, 38.34, 43.427, 51.57,56.99, 62.41,69.537,74.85, 81.927]
The thing is I need to plot them following the scale showed in the image below (more info here), which is a log-normal plot.
How can I get this scale using matplotlib?
I guess I'll need to use matplotlib.scale.FuncScale, but I'm not quite sure how to get there.
After David's insightful comment I've read this page and managed to plot the Figure the way I wanted.
from matplotlib.ticker import ScalarFormatter, AutoLocator
from matplotlib import pyplot
import pandas as pd
import probscale
fig, ax = pyplot.subplots(figsize=(9, 6))
microns = [38, 45, 53, 63, 75, 90, 106, 125, 150, 180]
cumulative_dist = [25.037, 32.577, 38.34, 43.427, 51.57,56.99, 62.41,69.537,74.85, 81.927]
probscale.probplot(pd.Series(microns, index=cumulative_dist), ax=ax, plottype='prob', probax='y', datascale='log',
problabel='Cumulative Distribution (%)',datalabel='Particle Size (μm)',
scatter_kws=dict(marker='.', linestyle='none', markersize=15))
ax.set_xlim(left=28, right=210)
ax.set_ylim(bottom=1, top=99)
ax.set_title('Log Normal Plot')
ax.grid(True, axis='both', which='major')
formatter = ScalarFormatter()
formatter.set_scientific(False)
ax.xaxis.set_major_formatter(formatter)
ax.xaxis.set_minor_formatter(formatter)
ax.xaxis.set_major_locator(AutoLocator())
ax.set_xticks([]) # for major ticks
ax.set_xticks([], minor=True) # for minor ticks
ax.set_xticks(microns)
fig.show()
probplot? matplotlib.org/mpl-probscale/tutorial/…