SciencePlots: Python高质量科学绘图

2020-09-08
#Python

1.简介

SciencePlots: Matplotlib styles for scientific plotting. This repo has Matplotlib styles to format your plots for scientific papers, presentations and theses.

Python中的Matplotlib来绘制高质量的科学绘图，可用于科学论文，演讲和学位论文的制图。

Github地址为：garrettj403/SciencePlots: Matplotlib styles for scientific plotting。

2.代码

安装：

pip install SciencePlots

""" An example of the 'science' theme. """

import numpy as np 
import matplotlib.pyplot as plt 

def model(x, p):
    return x ** (2 * p + 1) / (1 + x ** (2 * p))

x = np.linspace(0.75, 1.25, 201)

2.1 science

with plt.style.context(['science']):
    fig, ax = plt.subplots()
    for p in [10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig1.pdf')
    fig.savefig('figures/fig1.jpg', dpi=300)

2.2 science + ieee

with plt.style.context(['science', 'ieee']):
    fig, ax = plt.subplots()
    for p in [10, 20, 50]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig2.pdf')
    fig.savefig('figures/fig2.jpg', dpi=300)

2.3 science + scatter

with plt.style.context(['science', 'scatter']):
    fig, ax = plt.subplots(figsize=(4,4))
    ax.plot([-2, 2], [-2, 2], 'k--')
    ax.fill_between([-2, 2], [-2.2, 1.8], [-1.8, 2.2], color='dodgerblue', alpha=0.2, lw=0)
    for i in range(7):
        x1 = np.random.normal(0, 0.5, 10)
        y1 = x1 + np.random.normal(0, 0.2, 10)
        ax.plot(x1, y1, label=r"$^\#${}".format(i+1))
    ax.legend(title='Sample', loc=2)
    ax.set_xlabel(r"$\log_{10}\left(\frac{L_\mathrm{IR}}{\mathrm{L}_\odot}\right)$")
    ax.set_ylabel(r"$\log_{10}\left(\frac{L_\mathrm{6.2}}{\mathrm{L}_\odot}\right)$")
    ax.set_xlim([-2, 2])
    ax.set_ylim([-2, 2])
    fig.savefig('figures/fig3.pdf')
    fig.savefig('figures/fig3.jpg', dpi=300)

2.4 science + high-vis

with plt.style.context(['science', 'high-vis']):
    fig, ax = plt.subplots()
    for p in [10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig4.pdf')
    fig.savefig('figures/fig4.jpg', dpi=300)

2.5 dark_background + science + high-vis:

with plt.style.context(['dark_background', 'science', 'high-vis']):
    fig, ax = plt.subplots()
    for p in [10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig5.pdf')
    fig.savefig('figures/fig5.jpg', dpi=300)

2.6 science + notebook

with plt.style.context(['science', 'notebook']):
    fig, ax = plt.subplots()
    for p in [10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig10.pdf')
    fig.savefig('figures/fig10.jpg', dpi=300)

2.7 science + bright

# Plot different color cycles 
with plt.style.context(['science', 'bright']):
    fig, ax = plt.subplots()
    for p in [5, 10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig6.pdf')
    fig.savefig('figures/fig6.jpg', dpi=300)

2.8 science + vibrant:

with plt.style.context(['science', 'vibrant']):
    fig, ax = plt.subplots()
    for p in [5, 10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig7.pdf')
    fig.savefig('figures/fig7.jpg', dpi=300)

2.9 science + muted

with plt.style.context(['science', 'muted']):
    fig, ax = plt.subplots()
    for p in [5, 7, 10, 15, 20, 30, 38, 50, 100, 500]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order', fontsize=7)
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig8.pdf')
    fig.savefig('figures/fig8.jpg', dpi=300)

2.10 science + retro

with plt.style.context(['science', 'retro']):
    fig, ax = plt.subplots()
    for p in [10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig9.pdf')
    fig.savefig('figures/fig9.jpg', dpi=300)

2.11 science + grid

with plt.style.context(['science', 'grid']):
    fig, ax = plt.subplots()
    for p in [10, 15, 20, 30, 50, 100]:
        ax.plot(x, model(x, p), label=p)
    ax.legend(title='Order')
    ax.set(xlabel='Voltage (mV)')
    ax.set(ylabel='Current ($\mu$A)')
    ax.autoscale(tight=True)
    fig.savefig('figures/fig11.pdf')
    fig.savefig('figures/fig11.jpg', dpi=300)

参考