Matplotlib - label each bin

问题

I\'m currently using Matplotlib to create a histogram:

import matplotlib
matplotlib.use(\'Agg\')
import matplotlib.pyplot as pyplot
...
fig = pyplot.figure()
ax = fig.add_subplot(1,1,1,)
n, bins, patches = ax.hist(measurements, bins=50, range=(graph_minimum, graph_maximum), histtype=\'bar\')

#ax.set_xticklabels([n], rotation=\'vertical\')

for patch in patches:
    patch.set_facecolor(\'r\')

pyplot.title(\'Spam and Ham\')
pyplot.xlabel(\'Time (in seconds)\')
pyplot.ylabel(\'Bits of Ham\')
pyplot.savefig(output_filename)

I\'d like to make the x-axis labels a bit more meaningful.

Firstly, the x-axis ticks here seem to be limited to five ticks. No matter what I do, I can\'t seem to change this - even if I add more xticklabels, it only uses the first five. I\'m not sure how Matplotlib calculates this, but I assume it\'s auto-calculated from the range/data?

Is there some way I can increase the resolution of x-tick labels - even to the point of one for each bar/bin?

(Ideally, I\'d also like the seconds to be reformatted in micro-seconds/milli-seconds, but that\'s a question for another day).

Secondly, I\'d like each individual bar labeled - with the actual number in that bin, as well as the percentage of the total of all bins.

The final output might look something like this:

Is something like that possible with Matplotlib?

Cheers, Victor

回答1:

Sure! To set the ticks, just, well... Set the ticks (see matplotlib.pyplot.xticks or ax.set_xticks). (Also, you don't need to manually set the facecolor of the patches. You can just pass in a keyword argument.)

For the rest, you'll need to do some slightly more fancy things with the labeling, but matplotlib makes it fairly easy.

As an example:

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FormatStrFormatter

data = np.random.randn(82)
fig, ax = plt.subplots()
counts, bins, patches = ax.hist(data, facecolor='yellow', edgecolor='gray')

# Set the ticks to be at the edges of the bins.
ax.set_xticks(bins)
# Set the xaxis's tick labels to be formatted with 1 decimal place...
ax.xaxis.set_major_formatter(FormatStrFormatter('%0.1f'))

# Change the colors of bars at the edges...
twentyfifth, seventyfifth = np.percentile(data, [25, 75])
for patch, rightside, leftside in zip(patches, bins[1:], bins[:-1]):
    if rightside < twentyfifth:
        patch.set_facecolor('green')
    elif leftside > seventyfifth:
        patch.set_facecolor('red')

# Label the raw counts and the percentages below the x-axis...
bin_centers = 0.5 * np.diff(bins) + bins[:-1]
for count, x in zip(counts, bin_centers):
    # Label the raw counts
    ax.annotate(str(count), xy=(x, 0), xycoords=('data', 'axes fraction'),
        xytext=(0, -18), textcoords='offset points', va='top', ha='center')

    # Label the percentages
    percent = '%0.0f%%' % (100 * float(count) / counts.sum())
    ax.annotate(percent, xy=(x, 0), xycoords=('data', 'axes fraction'),
        xytext=(0, -32), textcoords='offset points', va='top', ha='center')


# Give ourselves some more room at the bottom of the plot
plt.subplots_adjust(bottom=0.15)
plt.show()

回答2:

To add SI prefixes to your axis labels you want to use QuantiPhy. In fact, in its documentation it has an example that shows how to do this exact thing: MatPlotLib Example.

I think you would add something like this to your code:

from matplotlib.ticker import FuncFormatter
from quantiphy import Quantity

time_fmtr = FuncFormatter(lambda v, p: Quantity(v, 's').render(prec=2))
ax.xaxis.set_major_formatter(time_fmtr)

来源：https://stackoverflow.com/questions/6352740/matplotlib-label-each-bin