我该如何遍历一个文件列表并将它们作为子图绘制在一个图形上？

Question

我试着把文件打印到8个子图上。我使用for循环和枚举运算符以及axarray来完成此操作。 我几乎完成了最后一步（使用axarray），但需要指导如何完成它。 我的代码是：

'import matplotlib.pyplot as plt
import parse_gctoo
import glob
f, ax1 = plt.subplots()

def histo_plotter(file, plot_title, ax):
    # read in file as string
    GCT_object = parse_gctoo.parse(file)
    # for c in range(9):
    #     print type(GCT_object.data_df.iloc[0][c])
    # computing median of rows in data_df
    # gene_medians = GCT_object.data_df.quantile(q=0.5,axis=1)
    # plot_title = "Gene expression levels for {}".format(cell)
    if plot_title == "ZSPCQNORM":
        gene_means = GCT_object.data_df.mean(axis=1)
        #making histogram of means
        ax.hist(gene_means)
        plt.title("MeanGeneExpressionZSPCQNORM")
        plt.xlabel("MedianGeneExpression")
        plt.ylabel("Count")
    elif plot_title == "QNORM":
        gene_medians = GCT_object.data_df.median(axis=1)
        #making histogram of medians
        ax.hist(gene_medians)
        plt.title("MedianGeneExpressionQNORM")
        plt.xlabel("MedianGeneExpression")
        plt.ylabel("Count")
plt.show()
f.savefig("hist_example1.png")



# plt.ylim(-1, 1)
# plt.xlim(-1,1)

# histo_plotter("/Users/eibelman/Desktop/ZSCOREDATA-    CXA061_SKL_48H_X1_B29_ZSPCQNORM_n372x978.gct.txt", "ZSPCQNORM", ax1)
#     histo_plotter("/Users/eibelman/Desktop/NewLJP005_A375_24H_X2_B19_QNORM_n373x978.gct.txt", "QNORM", ax1)
#########



# Create list of x2 LJP005 cell line files

z_list = glob.glob("/Volumes/cmap_obelix/pod/custom/LJP/roast/LJP005_[A375, A549, BT20, HA1E, HC515, HEPG2, HS578T, HT29]*X2*/zs/*ZSPCQNORM*.gct")
q_list = glob.glob("/Volumes/cmap_obelix/pod/custom/LJP/roast/LJP005_[A375, A549, BT20, HA1E, HC515, HEPG2, HS578T, HT29]*_X2_*/*_QNORM_*.gct")



# for loop which allows plotting multiple files in a single figure

f, axarray = plt.subplots(2, 4)
for n, single_q in enumerate(q_list):
     # axarray = plt.subplot(len(q_list), 1, n+1)
     axarray = histo_plotter(n, "QNORM", ax1)
    # axarray[n].plot()
plt.show()

# f, axarray = plt.subplots(2, 4)
# for n, single_z in enumerate(z_list):
#     # ax = plt.subplot(len(z_list), 1, n+1)
#     histo_plotter(single_z, "ZSPCQNORM", ax1)'

Answer 1

首先，在循环开始时调用plt.figure()一次就足够了。在

其次，您需要正确使用subplot。以下是subplot函数的文档：

Typical call signature:

subplot(nrows, ncols, plot_number) Where nrows and ncols are used to notionally split the figure into nrows * ncols sub-axes, and plot_number is used to identify the particular subplot that this function is to create within the notional grid. plot_number starts at 1, increments across rows first and has a maximum of nrows * ncols.

EDIT

如果您希望每个文件都有一个新的图形，那么在每次迭代中，您应该不带参数地调用plt.figure()。在

Answer 2

你可以试试这个：

import matplotlib.pyplot as plt

plt.figure()

for n, single_q in enumerate(q_list):
    ax = plt.subplot(len(q_list), 1, n+1)
    GCT_object = parse_gctoo.parse(single_q)
    gene_medians = GCT_object.data_df.median(axis=1)
    plt.hist(gene_medians)
    # tweak title, labels, etc.

plt.show()

解释：

• enumerate迭代项目（s），同时返回它们的索引（n）
• 函数subplot(size, column, row)需要这些参数：size是图中子图的总数，row和{}决定当前绘图的位置。n+1是将绘图沿绘图网格放置在正确位置所必需的
• 我用你自己的数据编辑了剩下的代码