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Python科学绘图
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Python科学绘图

Python科学绘图

常见python主流绘图工具库

matplotlib

seraborn

proplot

SciencePlots

matplotlib

安装

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import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
from matplotlib.ticker import ScalarFormatter
import pandas as pd

散点图

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# 输入文件位置，红点坐标，输出图
def sandian1(file_path: str,
             red_point_por: float,
             red_point_K: float,
             red_point_name: str,
             ):
    df = pd.read_csv(file_path, header=None, names=['img_name', 'por', 'K'])

    df['por'] = pd.to_numeric(df['por'], errors='coerce')
    df['por'] = df['por'] * 100
    df['K'] = pd.to_numeric(df['K'], errors='coerce')
    por = df['por']
    K = df['K']
    por2 = red_point_por
    K2 = red_point_K
    name2 = red_point_name

    # 创建图形和坐标轴 1in=2.54 figsize=(宽度, 高度) 10 , 7
    fig, ax = plt.subplots(figsize=(3.9, 2.7), dpi=300)

    # 设置全局字体为 Times New Roman
    plt.rcParams['font.family'] = 'serif'
    plt.rcParams['font.serif'] = ['Times New Roman'] + plt.rcParams['font.serif']

    # 绘制数据组1（黑色方块）
    ax.scatter(por, K, marker='s', color='black', facecolors='none', s=50, label=img_name)
    # 绘制数据组2（红色圆点）
    ax.scatter(por2, K2, marker='o', color='red', s=80, label=name2)

    # 设置为对数y轴
    ax.set_yscale('log')
    # 取消 y 轴的科学计数法
    formatter = ScalarFormatter(useOffset=False, useMathText=False)
    ax.yaxis.set_major_formatter(formatter)
    # 设置坐标轴范围
    ax.set_xlim(10, 30)
    ax.set_ylim(1, 1000)
    # 设置主刻度和次刻度的位置和格式
    ax.xaxis.set_major_locator(ticker.MultipleLocator(5))  # 主刻度间隔为5
    #ax.xaxis.set_minor_locator(ticker.MultipleLocator(1))  # 次刻度间隔为1

    # 分别设置 x 轴和 y 轴的刻度标签大小
    ax.tick_params(axis='x', labelsize=10)  # 设置 x 轴刻度标签大小
    ax.tick_params(axis='y', labelsize=10)  # 设置 y 轴刻度标签大小
    # 获取当前刻度标签
    x_labels = ax.get_xticklabels()
    y_labels = ax.get_yticklabels()
    # 设置字体属性
    for label in x_labels:
        label.set_fontname('Times New Roman')  # 设置字体
        label.set_fontweight('bold')           # 设置粗体
    for label in y_labels:
        label.set_fontname('Times New Roman')            # 设置字体
        label.set_fontweight('bold')           # 设置粗体

    # 设置刻度长度和宽度方向
    ax.tick_params(axis='x', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='x', which='minor', length=3, width=1, direction='in')
    ax.tick_params(axis='y', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='y', which='minor', length=3, width=1, direction='in')

    # 设置坐标轴线条样式
    ax.spines['bottom'].set_linewidth(1)  # 底部轴线宽度
    ax.spines['left'].set_linewidth(1)    # 左侧轴线宽度
    ax.spines['top'].set_linewidth(1)     # 顶部轴线宽度
    ax.spines['right'].set_linewidth(1)   # 右侧轴线宽度

    # 坐标轴标题
    ax.set_xlabel('POR(%)', fontsize=11, fontname='Times New Roman', fontweight='bold')
    ax.set_ylabel('Permeability(mD)', fontsize=11, fontname='Times New Roman', fontweight='bold')

    # 添加图例
    legend = ax.legend(fontsize=8)
    # 去掉框线和背景
    legend.get_frame().set_linewidth(0.0)  # 设置框线宽度为0
    legend.get_frame().set_facecolor('none')  # 设置背景为透明

    # 添加网格
    ax.grid(True, which='both', linestyle='-', linewidth=0.5, alpha=0.5)

    # 调整布局
    plt.tight_layout()

    return plt

箱线图

Boxplots

Box plots with custom fill colors

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def xiangxiantu_one_por(file_path: str,
                        img_name:  str,
                        key_point_value: float
                        ):
    df = pd.read_csv(file_path, header=None, names=['img_name', 'por', 'K'])

    df['por'] = pd.to_numeric(df['por'], errors='coerce')
    df['por'] = df['por'] * 100
    por = df['por'].dropna()

    # 创建图形和坐标轴 1in=2.54 figsize=(宽度, 高度) 5 , 7
    fig, ax = plt.subplots(figsize=(3, 2.7), dpi=300)

    # 设置全局字体为 Times New Roman
    plt.rcParams['font.family'] = 'serif'
    plt.rcParams['font.serif'] = ['Times New Roman'] + plt.rcParams['font.serif']

    # 基础框体
    data = [por]
    labels = [img_name]
    boxplot = ax.boxplot(data, notch=True, patch_artist=True, tick_labels=labels)

    # y轴范围
    ax.set_ylim(10, 30)

    # 设置箱体颜色
    colors = ['lightgreen']
    for box, color in zip(boxplot['boxes'], colors):
        box.set(facecolor=color)

    # 在第一组数据上标记点
    ax.scatter(1, key_point_value, color='red', s=50, zorder=5, marker='o')

    # 添加网格
    ax.grid(True, which='both', linestyle='-', linewidth=0.5, alpha=0.5)

    # 设置主刻度和次刻度的位置和格式
    ax.yaxis.set_major_locator(ticker.MultipleLocator(5))  # 主刻度间隔为5
    # ax.xaxis.set_minor_locator(ticker.MultipleLocator(1))  # 次刻度间隔为1

    # 分别设置 x 轴和 y 轴的刻度标签大小
    ax.tick_params(axis='x', labelsize=7)  # 设置 x 轴刻度标签大小
    ax.tick_params(axis='y', labelsize=8)  # 设置 y 轴刻度标签大小

    # 设置刻度长度和宽度方向
    ax.tick_params(axis='x', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='x', which='minor', length=3, width=1, direction='in')
    ax.tick_params(axis='y', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='y', which='minor', length=3, width=1, direction='in')

    # 设置坐标轴线条样式
    ax.spines['bottom'].set_linewidth(1)  # 底部轴线宽度
    ax.spines['left'].set_linewidth(1)    # 左侧轴线宽度
    ax.spines['top'].set_linewidth(1)     # 顶部轴线宽度
    ax.spines['right'].set_linewidth(1)   # 右侧轴线宽度

    # 坐标轴标题
    ax.set_ylabel('POR(%)', fontsize=10, fontname='Times New Roman', fontweight='bold')

    plt.tight_layout()
    return plt

def xiangxiantu_one_K(file_path:    str,
                        img_name:   str,
                        key_point_value:    float
                        ):
    df = pd.read_csv(file_path, header=None, names=['img_name', 'por', 'K'])
    df['K'] = pd.to_numeric(df['K'], errors='coerce')
    K = df['K'].dropna()

    # 创建图形和坐标轴 1in=2.54 figsize=(宽度, 高度) 5 , 7
    fig, ax = plt.subplots(figsize=(3, 2.7), dpi=300)

    # 设置全局字体为 Times New Roman
    plt.rcParams['font.family'] = 'serif'
    plt.rcParams['font.serif'] = ['Times New Roman'] + plt.rcParams['font.serif']

    # 基础框体
    data = [K]
    labels = [img_name]
    boxplot = ax.boxplot(data, notch=True, patch_artist=True, tick_labels=labels)

    # 设置箱体颜色
    colors = ['lightgreen']
    for box, color in zip(boxplot['boxes'], colors):
        box.set(facecolor=color)

    # 在第一组数据上标记点
    ax.scatter(1, key_point_value, color='red', s=50, zorder=5, marker='o')

    # 添加网格
    ax.grid(True, which='both', linestyle='-', linewidth=0.5, alpha=0.5)

    # 设置为对数y轴
    ax.set_yscale('log')
    # 取消 y 轴的科学计数法
    formatter = ScalarFormatter(useOffset=False, useMathText=False)
    ax.yaxis.set_major_formatter(formatter)
    # 设置坐标轴范围
    ax.set_ylim(1, 1000)

    # 分别设置 x 轴和 y 轴的刻度标签大小
    ax.tick_params(axis='x', labelsize=7)  # 设置 x 轴刻度标签大小
    ax.tick_params(axis='y', labelsize=8)  # 设置 y 轴刻度标签大小

    # 设置刻度长度和宽度方向
    ax.tick_params(axis='x', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='x', which='minor', length=3, width=1, direction='in')
    ax.tick_params(axis='y', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='y', which='minor', length=3, width=1, direction='in')

    # 设置坐标轴线条样式
    ax.spines['bottom'].set_linewidth(1)  # 底部轴线宽度
    ax.spines['left'].set_linewidth(1)    # 左侧轴线宽度
    ax.spines['top'].set_linewidth(1)     # 顶部轴线宽度
    ax.spines['right'].set_linewidth(1)   # 右侧轴线宽度

    # 坐标轴标题
    ax.set_ylabel('Permeability(mD)', fontsize=10, fontname='Times New Roman', fontweight='bold')

    plt.tight_layout()
    return plt

小提琴图

Box plot vs. violin plot comparison

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def xiaotiqintu_one_por(file_path: str,
                        img_name:  str,
                        key_point_value: float
                        ):
    df = pd.read_csv(file_path, header=None, names=['img_name', 'por', 'K'])

    df['por'] = pd.to_numeric(df['por'], errors='coerce')
    df['por'] = df['por'] * 100
    por = df['por'].dropna()

    # 创建图形和坐标轴 1in=2.54 figsize=(宽度, 高度) 5 , 7
    fig, ax = plt.subplots(figsize=(3, 2.7), dpi=300)

    # 设置全局字体为 Times New Roman
    plt.rcParams['font.family'] = 'serif'
    plt.rcParams['font.serif'] = ['Times New Roman'] + plt.rcParams['font.serif']

    # 基础框体
    data = [por]
    labels = [img_name]
    boxplot = ax.violinplot(data, showmeans=False, showmedians=True)

    # 设置填充区域颜色
    for pc in boxplot['bodies']:
        pc.set_facecolor('lightblue')  # 设置填充颜色
        pc.set_edgecolor('lightblue')  # 设置边缘线颜色
        pc.set_alpha(0.5)  # 设置透明度

    # 设置其他线条颜色
    boxplot['cmedians'].set_color('black')  # 设置中位数线颜色
    boxplot['cmins'].set_color('black')  # 设置小提琴下届线颜色
    boxplot['cmaxes'].set_color('black')  # 设置小提琴上届线颜色
    boxplot['cbars'].set_color('black')  # 设置小提琴竖线颜色

    # y轴范围
    ax.set_xlim(0, 2)
    ax.set_ylim(10, 30)

    # X轴标记
    ax.set_xticks([1])
    ax.set_xticklabels(labels)

    # 在第一组数据上标记点
    ax.scatter(1, key_point_value, color='red', s=50, zorder=5, marker='o')

    # 添加网格
    ax.grid(True, which='both', linestyle='-', linewidth=0.5, alpha=0.5)

    # 设置主刻度和次刻度的位置和格式
    ax.yaxis.set_major_locator(ticker.MultipleLocator(5))  # 主刻度间隔为5
    ax.xaxis.set_minor_locator(ticker.MultipleLocator(1))  # 次刻度间隔为1

    # 分别设置 x 轴和 y 轴的刻度标签大小
    ax.tick_params(axis='x', labelsize=7)  # 设置 x 轴刻度标签大小
    ax.tick_params(axis='y', labelsize=8)  # 设置 y 轴刻度标签大小

    # 设置刻度长度和宽度方向
    ax.tick_params(axis='x', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='x', which='minor', length=3, width=1, direction='in')
    ax.tick_params(axis='y', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='y', which='minor', length=3, width=1, direction='in')

    # 设置坐标轴线条样式
    ax.spines['bottom'].set_linewidth(1)  # 底部轴线宽度
    ax.spines['left'].set_linewidth(1)    # 左侧轴线宽度
    ax.spines['top'].set_linewidth(1)     # 顶部轴线宽度
    ax.spines['right'].set_linewidth(1)   # 右侧轴线宽度

    # 坐标轴标题
    ax.set_ylabel('POR(%)', fontsize=10, fontname='Times New Roman', fontweight='bold')

    plt.tight_layout()
    return plt

# 小提琴图
def xiaotiqintu_one_K(file_path: str,
                        img_name:  str,
                        key_point_value: float
                        ):
    df = pd.read_csv(file_path, header=None, names=['img_name', 'por', 'K'])
    df['K'] = pd.to_numeric(df['K'], errors='coerce')
    K = df['K'].dropna()

    # 创建图形和坐标轴 1in=2.54 figsize=(宽度, 高度) 5 , 7
    fig, ax = plt.subplots(figsize=(3, 2.7), dpi=300)

    # 设置全局字体为 Times New Roman
    plt.rcParams['font.family'] = 'serif'
    plt.rcParams['font.serif'] = ['Times New Roman'] + plt.rcParams['font.serif']

    # 基础框体
    data = [K]
    labels = [img_name]
    boxplot = ax.violinplot(data, showmeans=False, showmedians=True)

    # 设置填充区域颜色
    for pc in boxplot['bodies']:
        pc.set_facecolor('lightgreen')  # 设置填充颜色
        pc.set_edgecolor('lightgreen')  # 设置边缘线颜色
        pc.set_alpha(0.5)  # 设置透明度

    # 设置其他线条颜色
    boxplot['cmedians'].set_color('black')  # 设置中位数线颜色
    boxplot['cmins'].set_color('black')  # 设置小提琴下届线颜色
    boxplot['cmaxes'].set_color('black')  # 设置小提琴上届线颜色
    boxplot['cbars'].set_color('black')  # 设置小提琴竖线颜色

    # X轴标记
    ax.set_xlim(0, 2)
    ax.set_xticks([1])
    ax.set_xticklabels(labels)

    # 设置为对数y轴
    ax.set_yscale('log')
    # 取消 y 轴的科学计数法
    formatter = ScalarFormatter(useOffset=False, useMathText=False)
    ax.yaxis.set_major_formatter(formatter)
    # 设置坐标轴范围
    ax.set_ylim(1, 1000)

    # 在第一组数据上标记点
    ax.scatter(1, key_point_value, color='red', s=50, zorder=5, marker='o')

    # 添加网格
    ax.grid(True, which='both', linestyle='-', linewidth=0.5, alpha=0.5)

    # 设置主刻度和次刻度的位置和格式
    #ax.yaxis.set_major_locator(ticker.MultipleLocator(5))  # 主刻度间隔为5
    ax.xaxis.set_minor_locator(ticker.MultipleLocator(1))  # 次刻度间隔为1

    # 分别设置 x 轴和 y 轴的刻度标签大小
    ax.tick_params(axis='x', labelsize=7)  # 设置 x 轴刻度标签大小
    ax.tick_params(axis='y', labelsize=8)  # 设置 y 轴刻度标签大小

    # 设置刻度长度和宽度方向
    ax.tick_params(axis='x', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='x', which='minor', length=3, width=1, direction='in')
    ax.tick_params(axis='y', which='major', length=4, width=1, direction='in')
    ax.tick_params(axis='y', which='minor', length=3, width=1, direction='in')

    # 设置坐标轴线条样式
    ax.spines['bottom'].set_linewidth(1)  # 底部轴线宽度
    ax.spines['left'].set_linewidth(1)    # 左侧轴线宽度
    ax.spines['top'].set_linewidth(1)     # 顶部轴线宽度
    ax.spines['right'].set_linewidth(1)   # 右侧轴线宽度

    # 坐标轴标题
    ax.set_ylabel('Permeability(mD)', fontsize=10, fontname='Times New Roman', fontweight='bold')

    plt.tight_layout()
    return plt
文章作者: HibisciDai
文章链接: http://hibiscidai.com/2025/02/28/Python科学绘图/
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