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【科研绘图】琴图 +箱型图混合 matplotlib库和seabsorn库的使用

2022-08-10 03:21:00 【九久呀】

文章目录

绘图结果

请添加图片描述

上面这张图是琴图+箱型图

Tips:
箱型图是用于看数据分布情况。琴图+箱型图的组合也越来越多的应用于论文绘图中。

更多的图片和代码请参考：
链接：https://pan.baidu.com/s/1olkdo0NFbPOWL4JIxZcAAw?pwd=vvj1
提取码：vvj1
–来自百度网盘超级会员V5的分享

绘制箱型图+琴图

导入相关库函数

这里使用matplotlib库

import matplotlib.pyplot as plt
import scipy.stats as st
import pandas as pd
import seaborn as sns
import numpy as np
from scipy import stats
import logging
import os
from matplotlib.pyplot import MultipleLocator
import matplotlib.ticker as ticker

数据导入和图片存储名称：

newROIs = ['Amygdala', 'Caudate', 'Putamen', 'Hippocampus', 'ParaHippocampal', 'Cingulate', 'Precuneus',
           'Angular', 'SupraMarginal', 'Temporal_INF', 'Temporal_MID', 'Frontal']

figName = {
    'Amygdala':'Amygdala', 'Caudate':'Caudate', 'Putamen':'Putamen', 'Hippocampus':'Hippocampus',
           'ParaHippocampal':'Parahippocampal gyrus', 'Cingulate':'Posterior cingulate gyrus', 'Precuneus':'Precuneus',
            'Angular':'Angular gyrus', 'SupraMarginal':'Supramarginal gyrus', 'Temporal_INF':'Inferior temporal gyrus',
          'Temporal_MID':'Middle temporal gyrus', 'Frontal':'Superior frontal gyrus'}
dst = 't1'
if os.path.exists(dst) == False:
    os.makedirs(dst)
roi = newROIs[0]


if not os.path.exists('logging'):
    os.mkdir('logging')
hi2 = pd.read_csv('C:/Users/28411/python/limpid/Data_XM_BL&FU/test_0414/{0}/{1}.csv'.format(dst, roi), sep=',')

logging进行写入日志


logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s [%(filename)s:%(lineno)d]',
                        filename='logging/'+'{0}.log'.format(dst), datefmt='%Y-%m-%d %H:%M:%S')

logging.info("\nStart!Reading {0}.csv".format(roi))

设置图形颜色

emci_color = '#8dbada'
lmci_color = '#ffbf81'


emciEdgeColor = '#1a71af'
lmciEdgeColor = '#f57e09'


emciBoxFaceColor = '#5298c7'
lmciBoxFaceColor = '#ff9f40'


for i in range(4):
    edgeColor.append(emciEdgeColor)
    seaborn_color2.append(emci_color)
    whiskers_color2.append(emciEdgeColor)
    whiskers_color2.append(emciEdgeColor)
    boxFaceColor.append(emciBoxFaceColor)
for i in range(4):
    edgeColor.append(lmciEdgeColor)
    seaborn_color2.append(lmci_color)
    whiskers_color2.append(lmciEdgeColor)
    whiskers_color2.append(lmciEdgeColor)
    boxFaceColor.append(lmciBoxFaceColor)
inx2 = ['non-carriers', 'heterozygotes', 'homozygotes', 'carriers']
index2 = inx2 * 2

BG_WHITE = "#fbf9f4"
GREY_LIGHT = "#b4aea9"
GREY50 = "#7F7F7F"
BLUE_DARK = "#1B2838"
BLUE = "#2a475e"
BLACK = "#282724"
GREY_DARK = "#747473"
RED_DARK = "#850e00"

将数据进行转化

y_data = []
for i in range(hi2.shape[1]):
    da = []
    x = hi2.iloc[:, i].values
    for xi in x:
        if(str(xi)) == 'nan':
            continue
        da.append(xi.astype(float))
    y_data.append(da)

设置位置下标

POSITIONS = [1,1.5,2,2.5,  3.2,3.7,4.2,4.7]
posi = np.array([1,1.5,2,2.5,  3.2,3.7,4.2,4.7])

开始画图

plt.rc('font', family='Times New Roman') # 设置字体
fig, ax = plt.subplots(figsize=(12, 10), dpi=600) # 使用subplot进行画图
ax.spines['right'].set_visible(False) # 设置坐标轴是否可见
# ax.spines['left'].set_visible(False)
violins = ax.violinplot( # 绘制小提琴图
    y_data,
    positions=POSITIONS,
    # bw_method="silverman",
    # showmeans=False,
    # showmedians=,
    showextrema=False
)

for i in range(8): # 上色
    ax.get_children()[i].set_color(seaborn_color2[i])

for pc in violins["bodies"]:
    pc.set_alpha(1)
    pc.set_linewidth(1.4)

violins["bodies"][0].set_edgecolors(emciEdgeColor) # 因为小提琴图是以字典形式返回的，所以这里也使用字典形式进行添加绘制信息
violins["bodies"][1].set_edgecolors(emciEdgeColor) 
violins["bodies"][2].set_edgecolors(emciEdgeColor)
violins["bodies"][3].set_edgecolors(emciEdgeColor)

violins["bodies"][4].set_edgecolors(lmciEdgeColor)
violins["bodies"][5].set_edgecolors(lmciEdgeColor)
violins["bodies"][6].set_edgecolors(lmciEdgeColor)
violins["bodies"][7].set_edgecolors(lmciEdgeColor)

medianprops = dict(
    linewidth=1,
    # color='',
    solid_capstyle="butt"
)
whiskerprops = dict(
    linewidth=1
)

boxprops = dict(
    linewidth=1,
    # color=seaborn_color2,
)

flierprops = dict(marker='o')

bplot = ax.boxplot( # 绘制箱型图
    y_data,
    widths=0.15,
    positions=POSITIONS,
    flierprops=flierprops,

    showfliers=True,
    labels=index2,
    # labels=['EMCI','MCI', 'LMCI','EMCI','MCI', 'LMCI','EMCI','MCI', 'LMCI'],
    # medianprops= medianprops,
    # whiskerprops = whiskerprops,
    # boxprops = boxprops,
    showmeans=True,
    patch_artist=True,
    meanline=True,
    showcaps=False

)

for patch, c in zip(bplot['boxes'], edgeColor):
    patch.set_color(c)

for patch, c in zip(bplot['boxes'], boxFaceColor):
    patch.set(facecolor=c)

for patch, c in zip(bplot['whiskers'], whiskers_color2):
    patch.set_color(c)
    patch.set_linewidth(3)
for patch, c in zip(bplot['medians'], edgeColor):
    patch.set_color(c)
    patch.set_linewidth(3)

for patch, c in zip(bplot['means'], edgeColor):
    patch.set_color(c)
    patch.set_linewidth(3)
    patch.set_linestyle(':')

for patch, c in zip(bplot['fliers'], edgeColor):
    patch.set_markeredgecolor(c)
    patch.set_markerfacecolor(c)

y_t = ax.get_yticks()

plt.gca().yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))

plt.tick_params(labelsize=32)
if dst == 'av45':
    ax.set_ylabel('${^1}$${^8}$F-AV45 PET SUVR', fontsize=26)
if dst == 'fdg':
    ax.set_ylabel('${^1}$${^8}$F-FDG PET SUVR', fontsize=26)
if dst == 't1':
    ax.set_ylabel('Gray matter density', fontsize=32)
y_major_locator = MultipleLocator(0.2)
ax.yaxis.set_major_locator(y_major_locator)

ax.set_title('{0}'.format(figName[roi]), fontsize=32, pad=20)
ax.set_xticklabels(index2, rotation=30, horizontalalignment='right')

ax.set_ylim(0, 0.8)


plt.tight_layout() # 这行代码很重要，进行图片大小调整

升级版

请添加图片描述

画图代码


import matplotlib.pyplot as plt
import scipy.stats as st
import pandas as pd
import seaborn as sns
import numpy as np
from scipy import stats
import logging
import os
from matplotlib.pyplot import MultipleLocator
import matplotlib.ticker as ticker


newROIs = ['Amygdala', 'Caudate', 'Putamen', 'Hippocampus', 'ParaHippocampal', 'Cingulate', 'Precuneus',
           'Angular', 'SupraMarginal', 'Temporal_INF', 'Temporal_MID', 'Frontal']

figName = {
    'Amygdala':'Amygdala', 'Caudate':'Caudate', 'Putamen':'Putamen', 'Hippocampus':'Hippocampus',
           'ParaHippocampal':'Parahippocampal gyrus', 'Cingulate':'Posterior cingulate gyrus', 'Precuneus':'Precuneus',
            'Angular':'Angular gyrus', 'SupraMarginal':'Supramarginal gyrus', 'Temporal_INF':'Inferior temporal gyrus',
          'Temporal_MID':'Middle temporal gyrus', 'Frontal':'Superior frontal gyrus'}
dst = 'fdg'
if os.path.exists(dst) == False:
    os.makedirs(dst)
roi = newROIs[8]


if not os.path.exists('logging'):
    os.mkdir('logging')
hi2 = pd.read_csv('C:/Users/28411/Desktop/limpid/Data_XM/ROIs/BaseLineROIs/{0}/{1}.csv'.format(dst, roi), sep=',')

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s [%(filename)s:%(lineno)d]',
                        filename='logging/'+'{0}.log'.format(dst), datefmt='%Y-%m-%d %H:%M:%S')

logging.info("\nStart!Reading {0}.csv".format(roi))

seaborn_color2 = []
whiskers_color2 = []
edgeColor = []
boxFaceColor = []

emci_color = '#8dbada'
mci_color = '#ffbf81'
lmci_color = '#93d094'

emciEdgeColor = '#1a71af'
mciEdgeColor = '#f57e09'
lmciEdgeColor = '#279824'

emciBoxFaceColor = '#5298c7'
mciBoxFaceColor = '#ff9f40'
lmciBoxFaceColor = '#5db85b'

for i in range(3):
    edgeColor.append(emciEdgeColor)
    seaborn_color2.append(emci_color)
    whiskers_color2.append(emciEdgeColor)
    whiskers_color2.append(emciEdgeColor)
    boxFaceColor.append(emciBoxFaceColor)

for i in range(3):
    edgeColor.append(mciEdgeColor)
    seaborn_color2.append(mci_color)
    whiskers_color2.append(mciEdgeColor)
    whiskers_color2.append(mciEdgeColor)
    boxFaceColor.append(mciBoxFaceColor)

for i in range(3):
    edgeColor.append(lmciEdgeColor)
    seaborn_color2.append(lmci_color)
    whiskers_color2.append(lmciEdgeColor)
    whiskers_color2.append(lmciEdgeColor)
    boxFaceColor.append(lmciBoxFaceColor)
inx2 = ['non-carriers', 'heterozygotes', 'homozygotes']
index2 = inx2 * 3

y_data = []
for i in range(hi2.shape[1]):
    da = []
    x = hi2.iloc[:, i].values
    for xi in x:
        if(str(xi)) == 'nan':
            continue
        da.append(xi.astype(float))
    y_data.append(da)

POSITIONS = [1,1.5,2, 2.7,3.2,3.7, 4.4,4.9,5.4]
BG_WHITE = "#fbf9f4"
GREY_LIGHT = "#b4aea9"
GREY50 = "#7F7F7F"
BLUE_DARK = "#1B2838"
BLUE = "#2a475e"
BLACK = "#282724"
GREY_DARK = "#747473"
RED_DARK = "#850e00"

posi = np.array([1,1.5,2,  2.7,3.2,3.7,  4.4,4.9,5.4])

plt.rc('font', family='Times New Roman')
fig, ax = plt.subplots(figsize=(12, 10), dpi=600)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
violins = ax.violinplot(
    y_data,
    positions=POSITIONS,
    # bw_method="silverman",
    # showmeans=False,
    # showmedians=,
    showextrema=False
)

for i in range(9):
    ax.get_children()[i].set_color(seaborn_color2[i])

for pc in violins["bodies"]:
    pc.set_alpha(1)
    pc.set_linewidth(1.4)

# violins["bodies"][0].set_label('EMCI')
# violins["bodies"][3].set_label('MCI')
# violins["bodies"][6].set_label('LMCI')

violins["bodies"][0].set_edgecolors(emciEdgeColor)
violins["bodies"][1].set_edgecolors(emciEdgeColor)
violins["bodies"][2].set_edgecolors(emciEdgeColor)

violins["bodies"][3].set_edgecolors(mciEdgeColor)
violins["bodies"][4].set_edgecolors(mciEdgeColor)
violins["bodies"][5].set_edgecolors(mciEdgeColor)

violins["bodies"][6].set_edgecolors(lmciEdgeColor)
violins["bodies"][7].set_edgecolors(lmciEdgeColor)
violins["bodies"][8].set_edgecolors(lmciEdgeColor)

medianprops = dict(
    linewidth=1,
    # color='',
    solid_capstyle="butt"
)
whiskerprops = dict(
    linewidth=1
)

boxprops = dict(
    linewidth=1,
    # color=seaborn_color2,
)

flierprops = dict(marker='o')

bplot = ax.boxplot(
    y_data,
    widths=0.15,
    positions=POSITIONS,
    flierprops=flierprops,

    showfliers=True,
    labels=index2,
    # labels=['EMCI','MCI', 'LMCI','EMCI','MCI', 'LMCI','EMCI','MCI', 'LMCI'],
    # medianprops= medianprops,
    # whiskerprops = whiskerprops,
    # boxprops = boxprops,
    showmeans=True,
    patch_artist=True,
    meanline=True,
    showcaps=False

)

for patch, c in zip(bplot['boxes'], edgeColor):
    patch.set_color(c)

for patch, c in zip(bplot['boxes'], boxFaceColor):
    patch.set(facecolor=c)

for patch, c in zip(bplot['whiskers'], whiskers_color2):
    patch.set_color(c)
    patch.set_linewidth(3)
for patch, c in zip(bplot['medians'], edgeColor):
    patch.set_color(c)
    patch.set_linewidth(3)

for patch, c in zip(bplot['means'], edgeColor):
    patch.set_color(c)
    patch.set_linewidth(3)
    patch.set_linestyle(':')

for patch, c in zip(bplot['fliers'], edgeColor):
    patch.set_markeredgecolor(c)
    patch.set_markerfacecolor(c)

y_t = ax.get_yticks()


plt.gca().yaxis.set_major_formatter(ticker.FormatStrFormatter('%.2f'))


plt.tick_params(labelsize=32)
# if dst == 'av45':
# ax.set_ylabel('${^1}$${^8}$F-AV45 PET SUVR', fontsize=26)
# if dst == 'fdg':
# ax.set_ylabel('${^1}$${^8}$F-FDG PET SUVR', fontsize=26)
# if dst == 't1':
# ax.set_ylabel('Gray matter volume', fontsize=26)
y_major_locator = MultipleLocator(0.4)
ax.yaxis.set_major_locator(y_major_locator)

ax.set_title('{0}'.format(figName[roi]), fontsize=32, pad=20)
ax.set_xticklabels(index2, rotation=30, horizontalalignment='right')

ax.set_ylim(0, 2.4+0.3)

highhh = 2.3

# y_labels = np.linspace(0, highhh, 6)
#
# ax.set_yticklabels(y_labels, fontsize=16)
# plt.legend()

plt.tight_layout()



def plotLine(num, posiOne, posiTwo, pValue):

    if pValue<0.001:
        labelp = '${^*}$${^*}$${^*}$'
    elif pValue <0.01:
        labelp = '${^*}$${^*}$'
    elif pValue<0.05:
        labelp = '${^*}$'

    # inner group
    if posiTwo - posiOne == 0.5 or posiTwo - posiOne == 1:

        if posiTwo <= 2:
            if posiOne == 1.0 and posiTwo == 2.0:
                ax.plot([1.0, 1.0, 2.0, 2.0], [highhh+0.12, highhh+0.12, highhh+0.12, highhh+0.12], c=emci_color)
                ax.text(1.5, highhh+0.07, labelp, fontsize=16, va="bottom", ha="center", c=emci_color)
            if posiOne == 1 and posiTwo == 1.5:
                ax.plot([1.0, 1.0, 1.5, 1.5], [highhh+0.08, highhh+0.08, highhh+0.08, highhh+0.08], c=emci_color)
                ax.text(1.25, highhh+0.03, labelp, fontsize=16, va="bottom", ha="center", c=emci_color)
            if posiOne == 1.5 and posiTwo == 2.0:
                ax.plot([1.5, 1.5, 2.0, 2.0], [highhh+0.04, highhh+0.04, highhh+0.04, highhh+0.04], c=emci_color)
                ax.text(1.75, highhh-0.01, labelp, fontsize=16, va="bottom", ha="center", c=emci_color)

        elif posiTwo <= 3.7:
            if posiOne == 2.7 and posiTwo == 3.7:
                ax.plot([2.7, 2.7, 3.7, 3.7], [highhh+0.12, highhh+0.12, highhh+0.12, highhh+0.12], c=mci_color)
                ax.text(3.2, highhh+0.07, labelp, fontsize=16, va="bottom", ha="center", c=mci_color)
            if posiOne == 2.7 and posiTwo == 3.2:
                ax.plot([2.7, 2.7, 3.2, 3.2], [highhh+0.08, highhh+0.08, highhh+0.08, highhh+0.08], c=mci_color)
                ax.text(2.95, highhh+0.03, labelp, fontsize=16, va="bottom", ha="center", c=mci_color)
            if posiOne == 3.2 and posiTwo == 3.7:
                ax.plot([3.2, 3.2, 3.7, 3.7], [highhh+0.04, highhh+0.04, highhh+0.04, highhh+0.04], c=mci_color)
                ax.text(3.45, highhh-0.01, labelp, fontsize=16, va="bottom", ha="center", c=mci_color)

        elif posiTwo <= 5.4:
            if posiOne == 4.4 and posiTwo == 5.4:
                ax.plot([4.4, 4.4, 5.4, 5.4], [highhh+0.12, highhh+0.12, highhh+0.12, highhh+0.12], c=lmci_color)
                ax.text(4.9, highhh+0.07, labelp, fontsize=16, va="bottom", ha="center", c=lmci_color)
            if posiOne == 4.4 and posiTwo == 4.9:
                ax.plot([4.4, 4.4, 4.9, 4.9], [highhh+0.08, highhh+0.08, highhh+0.08, highhh+0.08], c=lmci_color)
                ax.text(4.65, highhh+0.03, labelp, fontsize=16, va="bottom", ha="center", c=lmci_color)
            if posiOne == 4.9 and posiTwo == 5.4:
                ax.plot([4.9, 4.9, 5.4, 5.4], [highhh+0.04, highhh+0.04, highhh+0.04, highhh+0.04], c=lmci_color)
                ax.text(5.15, highhh-0.01, labelp, fontsize=16, va="bottom", ha="center", c=lmci_color)
    else:
        up = num * 0.07

        if up == 0.07:
            up += 0.09

        # print('plotLine from {0} to {1}'.format(posiOne, posiTwo))

        ax.plot([posiOne + 0.1, posiOne + 0.1, posiTwo - 0.1, posiTwo - 0.1],
                [highhh + up, highhh + up, highhh + up, highhh + up],
                c="black")
        x_label = (posiOne+posiTwo-0.2)/2
        y_label = highhh+up-0.04
        print(num, labelp)
        ax.text(x_label, y_label, labelp, fontsize=16, va="bottom", ha="center", c='k')
        # print(x_label, y_label)

    return

y = y_data
emci_0 = y[0]
emci_1 = y[1]
emci_2 = y[2]

mci_0 = y[3]
mci_1 = y[4]
mci_2 = y[5]

lmci_0 = y[6]
lmci_1 = y[7]
lmci_2 = y[8]

nine={
    'emci_0': emci_0, 'emci_1': emci_1,'emci_2': emci_2, 'mci_0': mci_0, 'mci_1': mci_1, 'mci_2': mci_2,
      'lmci_0': lmci_0, 'lmci_1': lmci_1, 'lmci_2': lmci_2}
nine_name = ['emci_0', 'emci_1', 'emci_2', 'mci_0', 'mci_1', 'mci_2', 'lmci_0', 'lmci_1', 'lmci_2']

原网站

版权声明
本文为[九久呀]所创，转载请带上原文链接，感谢
https://blog.csdn.net/qq_38851184/article/details/126192647

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