Question

我正在创建两个Python脚本来为技术报告生成一些图表。在第一个脚本中，我定义了从硬盘上的原始数据生成绘图的函数。每个函数都会生成一个我需要的特定类型的图。第二个脚本更像是一个批处理文件，它应该绕过这些函数并将生成的图存储在我的硬盘上。

我需要的是一种在Python中返回绘图的方法。所以基本上我想这样做：

fig = some_function_that_returns_a_plot(args)
fig.savefig('plot_name')

但我不知道的是如何将情节作为我可以返回的变量。这可能吗？是这样，怎么样？

Answer 1

您可以定义绘图功能，如

import numpy as np
import matplotlib.pyplot as plt

# an example graph type
def fig_barh(ylabels, xvalues, title=''):
    # create a new figure
    fig = plt.figure()

    # plot to it
    yvalues = 0.1 + np.arange(len(ylabels))
    plt.barh(yvalues, xvalues, figure=fig)
    yvalues += 0.4
    plt.yticks(yvalues, ylabels, figure=fig)
    if title:
        plt.title(title, figure=fig)

    # return it
    return fig

然后像

一样使用它们

from matplotlib.backends.backend_pdf import PdfPages

def write_pdf(fname, figures):
    doc = PdfPages(fname)
    for fig in figures:
        fig.savefig(doc, format='pdf')
    doc.close()

def main():
    a = fig_barh(['a','b','c'], [1, 2, 3], 'Test #1')
    b = fig_barh(['x','y','z'], [5, 3, 1], 'Test #2')
    write_pdf('test.pdf', [a, b])

if __name__=="__main__":
    main()

Answer 2

由于我正在使用scipy.stats.probplot()进行绘制，因此当前接受的答案对我而言并不起作用。我改用matplotlib.pyplot.gca()直接访问an Axes instance：

"""
For my plotting ideas, see:
https://pythonfordatascience.org/independent-t-test-python/
For the dataset, see:
https://github.com/Opensourcefordatascience/Data-sets
"""

# Import modules.
from scipy import stats
import matplotlib.pyplot as plt
import pandas as pd
from tempfile import gettempdir
from os import path
from slugify import slugify

# Define plot func.
def get_plots(df):

    # plt.figure(): Create a new P-P plot. If we're inside a loop, and want
    #               a new plot for every iteration, this is important!
    plt.figure()
    stats.probplot(diff, plot=plt)
    plt.title('Sepal Width P-P Plot')
    pp_p = plt.gca() # Assign an Axes instance of the plot.

    # Plot histogram. This uses pandas.DataFrame.plot(), which returns
    # an instance of the Axes directly.
    hist_p = df.plot(kind = 'hist', title = 'Sepal Width Histogram Plot',
                            figure=plt.figure()) # Create a new plot again.

    return pp_p, hist_p    

# Import raw data.
df = pd.read_csv('https://raw.githubusercontent.com/'
                 'Opensourcefordatascience/Data-sets/master//Iris_Data.csv')

# Subset the dataset.
setosa = df[(df['species'] == 'Iris-setosa')]
setosa.reset_index(inplace= True)
versicolor = df[(df['species'] == 'Iris-versicolor')]
versicolor.reset_index(inplace= True)

# Calculate a variable for analysis.
diff = setosa['sepal_width'] - versicolor['sepal_width']

# Create plots, save each of them to a temp file, and show them afterwards.
# As they're just Axes instances, we need to call get_figure() at first.
for plot in get_plots(diff):
    outfn = path.join(gettempdir(), slugify(plot.title.get_text()) + '.png')
    print('Saving a plot to "' + outfn + '".')
    plot.get_figure().savefig(outfn)
    plot.get_figure().show()

Answer 3

如果您不想显示图片而只获得一个变量作为回报，那么您可以尝试以下操作（使用一些额外的东西来删除轴）：

def myplot(t,x):        
    fig = Figure(figsize=(2,1), dpi=80)    
    canvas = FigureCanvasAgg(fig)
    ax = fig.add_subplot()
    ax.fill_between(t,x)
    ax.autoscale(tight=True)
    ax.axis('off')
    canvas.draw()
    buf = canvas.buffer_rgba()
    X = np.asarray(buf)    
    return X

返回的变量 X 可以与 OpenCV 一起使用，例如做一个

cv2.imshow('',X)

必须包含这些导入：

from matplotlib.figure import Figure
from matplotlib.backends.backend_agg import FigureCanvasAgg

如何为变量分配绘图并将该变量用作Python函数中的返回值

3 个答案: