1
我正在将一组R可视化翻译成Python。我有以下的目标R的多个情节直方图：MatPlotlib Seaborn多重格式化
使用Matplotlib和Seaborn结合，以一种StackOverflow的成员的帮助下（见链接：Python Seaborn Distplot Y value corresponding to a given X value），我是能够创建以下Python的阴谋：
我很满意它的外观，只是，我不知道如何把在该地块的报头信息。这里是我创建Python图表的Python代码
""" Program to draw the sampling histogram distributions """
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
import seaborn as sns
def main():
""" Main routine for the sampling histogram program """
sns.set_style('whitegrid')
markers_list = ["s", "o", "*", "^", "+"]
# create the data dataframe as df_orig
df_orig = pd.read_csv('lab_samples.csv')
df_orig = df_orig.loc[df_orig.hra != -9999]
hra_list_unique = df_orig.hra.unique().tolist()
# create and subset df_hra_colors to match the actual hra colors in df_orig
df_hra_colors = pd.read_csv('hra_lookup.csv')
df_hra_colors['hex'] = np.vectorize(rgb_to_hex)(df_hra_colors['red'], df_hra_colors['green'], df_hra_colors['blue'])
df_hra_colors.drop(labels=['red', 'green', 'blue'], axis=1, inplace=True)
df_hra_colors = df_hra_colors.loc[df_hra_colors['hra'].isin(hra_list_unique)]
# hard coding the current_component to pc1 here, we will extend it by looping
# through the list of components
current_component = 'pc1'
num_tests = 5
df_columns = df_orig.columns.tolist()
start_index = 5
for test in range(num_tests):
current_tests_list = df_columns[start_index:(start_index + num_tests)]
# now create the sns distplots for each HRA color and overlay the tests
i = 1
for _, row in df_hra_colors.iterrows():
plt.subplot(3, 3, i)
select_columns = ['hra', current_component] + current_tests_list
df_current_color = df_orig.loc[df_orig['hra'] == row['hra'], select_columns]
y_data = df_current_color.loc[df_current_color[current_component] != -9999, current_component]
axs = sns.distplot(y_data, color=row['hex'],
hist_kws={"ec":"k"},
kde_kws={"color": "k", "lw": 0.5})
data_x, data_y = axs.lines[0].get_data()
axs.text(0.0, 1.0, row['hra'], horizontalalignment="left", fontsize='x-small',
verticalalignment="top", transform=axs.transAxes)
for current_test_index, current_test in enumerate(current_tests_list):
# this_x defines the series of current_component(pc1,pc2,rhob) for this test
# indicated by 1, corresponding R program calls this test_vector
x_series = df_current_color.loc[df_current_color[current_test] == 1, current_component].tolist()
for this_x in x_series:
this_y = np.interp(this_x, data_x, data_y)
axs.plot([this_x], [this_y - current_test_index * 0.05],
markers_list[current_test_index], markersize = 3, color='black')
axs.xaxis.label.set_visible(False)
axs.xaxis.set_tick_params(labelsize=4)
axs.yaxis.set_tick_params(labelsize=4)
i = i + 1
start_index = start_index + num_tests
# plt.show()
pp = PdfPages('plots.pdf')
pp.savefig()
pp.close()
def rgb_to_hex(red, green, blue):
"""Return color as #rrggbb for the given color values."""
return '#%02x%02x%02x' % (red, green, blue)
if __name__ == "__main__":
main()
熊猫代码工作正常，它正在做它应该做的。这是我缺乏在Matplotlib中使用'PdfPages'的知识和经验，这是瓶颈。如何在Python/Matplotlib/Seaborn中显示头文件信息，以便在相应的可视化中显示。通过标题信息，我的意思是什么R可视化具有在直方图之前的顶部，即'pc1'，MRP，XRD ......
我可以很容易地从我的程序中获取它们的值，例如，current_component是'pc1'等，但我不知道如何使用Header格式化绘图。有人可以提供一些指导吗？