Bar color became white when plotting many bins in catplot-CodePudding

I am trying to plot a histogram of exponential distribution ranging from 0 to 20 with mean value 2.2 and bin width 0.05. However, the bar color became white as I am plotting it. The following is my code:

bins = np.linspace(0, 20, 401)

x = np.random.exponential(2.2, 3000)
counts, _ = np.histogram(x, bins)

df = pd.DataFrame({'bin': bins[:-1], 'count': counts})
p = sns.catplot(data = df, x = 'bin', y = 'count', yerr = [i**(1/2) for i in counts], kind = 'bar', height = 4, aspect = 2, palette = 'Dark2_r')
p.set(xlabel = 'Muon decay times ($\mu s$)', ylabel = 'Count', title = 'Distribution for muon decay times')

for ax in p.axes.flat:
    labels = ax.get_xticklabels()
    for i,l in enumerate(labels):
        if (i@ != 0):
            labels[i] = ""
    ax.set_xticklabels(labels, rotation=30)

I believe that this is caused by the number of bins. If the first line of the codes are set to bins = np.linspace(0, 20, 11), the plot would be:

But I have no idea how to resolve this.

CodePudding user response：

As @JohanC points out, if you're trying to draw elements that are close to or smaller than the resolution of your raster graphic, you have to expect some artifacts. But it also seems like you'd have an easier time making this plot directly in matplotlib, since catplot is not designed to make histograms:

f, ax = plt.subplots(figsize=(8, 4), dpi=96)
ax.bar(
    bins[:-1], counts,
    yerr=[i**(1/2) for i in counts],
    width=(bins[1] - bins[0]), align="edge",
    linewidth=0, error_kw=dict(linewidth=1),
)
ax.set(
    xmargin=.01,
    xlabel='Muon decay times ($\mu s$)',
    ylabel='Count',
    title='Distribution for muon decay times'
)

CodePudding user response：

Matplotlib doesn't have a good way to deal with bars that are thinner than one pixel. If you save to an image file, you can increase the dpi and/or the figsize.

Some white space is due to the bars being 0.8 wide, leaving a gap of 0.2. Seaborn's barplot doesn't let you set the bar widths, but you could iterate through the generated bars and change their width (also updating their x-value to keep them centered around the tick position).

The edges of the bars get a fixed color (default 'none', or fully transparent). While iterating through the generated bars, you could set the edge color equal to the face color.

from matplotlib import pyplot as plt
from matplotlib.ticker import MultipleLocator
import seaborn as sns
import pandas as pd
import numpy as np

bins = np.linspace(0, 20, 401)

x = np.random.exponential(2.2, 3000)
counts, _ = np.histogram(x, bins)

df = pd.DataFrame({'bin': bins[:-1], 'count': counts})
g = sns.catplot(data=df, x='bin', y='count', yerr=[i ** (1 / 2) for i in counts], kind='bar',
                height=4, aspect=2, palette='Dark2_r', lw=0.5)
g.set(xlabel='Muon decay times ($\mu s$)', ylabel='Count', title='Distribution for muon decay times')

for ax in g.axes.flat:
    ax.xaxis.set_major_locator(MultipleLocator(40))
    ax.tick_params(axis='x', labelrotation=30)
    for bar in ax.patches:
        bar.set_edgecolor(bar.get_facecolor())
        bar.set_x(bar.get_x() - (1 - bar.get_width()) / 2)
        bar.set_width(1)
plt.tight_layout()
plt.show()