python图片画不出来

Question

为什么运行不出来，哪里有错误呢？一直提示这个错误，我是复制的论文代码，应该没问题啊

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sympy.solvers import solve
from sympy import Symbol
from matplotlib import patches
import matplotlib.patches as mpatches
import scipy.io as sio

plotting configuration

ratio = 1.5
figure_len, figure_width = 15ratio, 12ratio
font_size_1, font_size_2 = 36ratio, 36ratio
legend_size = 18ratio
line_width, tick_len = 3ratio, 10ratio
marker_size = 15ratio
plot_line_width = 5*ratio
hfont = {'fontname': 'Arial'}

simulation setup

dt = 0.0001
T = int(9/dt)

neuronal parameters

tau_e, tau_i = 0.020, 0.010
alpha_e, alpha_i = 2, 2

network connectivity

```Jee = 0.5
Jei = 0.45
Jie = 1.0
Jii = 1.5

l_g_e = [1, 2, 3]
l_g_i = [2, 3, 4]

for g_e_idx in range(len(l_g_e)):

```

g_e_temp = l_g_e[g_e_idx]
g_i_temp = l_g_i[g_e_idx]

r_e, r_i = 0, 0
z_e, z_i = 0, 0

l_r_e, l_r_i = [], []

for i in range(T):
    if 50000 <= i < 70000:
        g_e, g_i = g_e_temp, g_i_temp
    else:
        g_e, g_i = 0.5, 1.5

    g_e = g_e * (g_e > 0)
    g_i = g_i * (g_i > 0)

    # SSN part
    z_e = Jee * r_e - Jei * r_i + g_e
    z_i = Jie * r_e - Jii * r_i + g_i

    z_e = z_e * (z_e > 0)
    z_i = z_i * (z_i > 0)

    r_e = r_e + (-r_e + np.power(z_e, alpha_e)) / tau_e * dt
    r_i = r_i + (-r_i + np.power(z_i, alpha_i)) / tau_i * dt

    r_e = r_e * (r_e > 0)
    r_i = r_i * (r_i > 0)

    l_r_e.append(r_e)
    l_r_i.append(r_i)

l_r_e = np.asarray(l_r_e)
l_r_i = np.asarray(l_r_i)

# plotting
plt.figure(figsize=(figure_len, figure_width))
ax = plt.gca()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(True)
ax.spines['left'].set_visible(True)
for axis in ['top', 'bottom', 'left', 'right']:
    ax.spines[axis].set_linewidth(line_width)
plt.tick_params(width=line_width, length=tick_len)
plt.yscale('symlog', linthreshy=0.1)

plt.plot(l_r_e, color='blue', linewidth=plot_line_width)
plt.plot(l_r_i, color='red', linewidth=plot_line_width)

plt.xticks(np.arange(30000, 90000 + 5000, 20000), np.arange(0, 6 + 0.5, 2), fontsize=font_size_1, **hfont)
plt.yticks([0, 1, 100, 10000], fontsize=font_size_1, **hfont)
plt.xlabel('Time (s)', fontsize=font_size_1, **hfont)
plt.ylabel('Firing rate (Hz)', fontsize=font_size_1, **hfont)
plt.xlim([30000, 90000])
plt.ylim([0, 10000])
plt.legend(['Exc', 'Inh'], prop={"family": "Arial", 'size': font_size_1}, loc='upper right')
plt.savefig('paper_figures/png/Fig_1S_Supralinear_network_2D_weak_Jee_g_e_' + str(g_e_temp) + '_g_i_' + str(g_i_temp) + '.png')
plt.savefig('paper_figures/pdf/Fig_1S_Supralinear_network_2D_weak_Jee_g_e_' + str(g_e_temp) + '_g_i_' + str(g_i_temp) + '.pdf')

Answer 1

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代码中有几个问题导致无法运行，并且报错信息中的 'libchreshy' 是一个拼写错误。

1. 缺少注释符号：在代码中没有正确标记注释符号，这可能导致Python解释器无法理解代码中的注释内容。你可以使用 '#' 添加注释符号。

2. 缺少变量 ratio 的定义：在代码中使用了变量 ratio，但是没有定义它的值。你可以为 ratio 设置一个数值，例如 ratio = 1.5。

3. 缺少引号：在代码中出现了一行没有正确加引号的注释。你可以在 'plotting configuration' 这行代码前面添加引号。

4. 缺少引号：在代码的最后一行，plt.savefig() 函数中的文件路径没有正确加引号。你可以在文件路径的两端添加引号。

以下是修改后的代码：

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sympy.solvers import solve
from sympy import Symbol
from matplotlib import patches
import matplotlib.patches as mpatches
import scipy.io as sio

# plotting configuration
ratio = 1.5
figure_len, figure_width = 15*ratio, 12*ratio
font_size_1, font_size_2 = 36*ratio, 36*ratio
legend_size = 18*ratio
line_width, tick_len = 3*ratio, 10*ratio
marker_size = 15*ratio
plot_line_width = 5*ratio
hfont = {'fontname': 'Arial'}

# simulation setup
dt = 0.0001
T = int(9/dt)

# neuronal parameters
tau_e, tau_i = 0.020, 0.010
alpha_e, alpha_i = 2, 2

# network connectivity
Jee = 0.5
Jei = 0.45
Jie = 1.0
Jii = 1.5

l_g_e = [1, 2, 3]
l_g_i = [2, 3, 4]

for g_e_idx in range(len(l_g_e)):
    g_e_temp = l_g_e[g_e_idx]
    g_i_temp = l_g_i[g_e_idx]
    r_e, r_i = 0, 0
    z_e, z_i = 0, 0
    l_r_e, l_r_i = [], []
    for i in range(T):
        if 50000 <= i < 70000:
            g_e, g_i = g_e_temp, g_i_temp
        else:
            g_e, g_i = 0.5, 1.5
        g_e = g_e * (g_e > 0)
        g_i = g_i * (g_i > 0)
        # SSN part
        z_e = Jee * r_e - Jei * r_i + g_e
        z_i = Jie * r_e - Jii * r_i + g_i
        z_e = z_e * (z_e > 0)
        z_i = z_i * (z_i > 0)
        r_e = r_e + (-r_e + np.power(z_e, alpha_e)) / tau_e * dt
        r_i = r_i + (-r_i + np.power(z_i, alpha_i)) / tau_i * dt
        r_e = r_e * (r_e > 0)
        r_i = r_i * (r_i > 0)
        l_r_e.append(r_e)
        l_r_i.append(r_i)
    l_r_e = np.asarray(l_r_e)
    l_r_i = np.asarray(l_r_i)
    
    # plotting
    plt.figure(figsize=(figure_len, figure_width))
    ax = plt.gca()
    ax.spines['top'].set_visible(False)
    ax.spines['right'].set_visible(False)
    ax.spines['bottom'].set_visible(True)
    ax.spines['left'].set_visible(True)
    for axis in ['top', 'bottom', 'left', 'right']:
        ax.spines[axis].set_linewidth(line_width)
    plt.tick_params(width=line_width, length=tick_len)
    plt.yscale('symlog', linthreshy=0.1)
    plt.plot(l_r_e, color='blue', linewidth=plot_line_width)
    plt.plot(l_r_i, color='red', linewidth=plot_line_width)
    plt.xticks(np.arange(30000, 90000 + 5000, 20000), np.arange(0, 6 + 0.5, 2), fontsize=font_size_1, **hfont)
    plt.yticks([0, 1, 100, 10000], fontsize=font_size_1, **hfont)
    plt.xlabel('Time (s)', fontsize=font_size_1, **hfont)
    plt.ylabel('Firing rate (Hz)', fontsize=font_size_1, **hfont)
    plt.xlim([30000, 90000])
    plt.ylim([0, 10000])
    plt.legend(['Exc', 'Inh'], prop={"family": "Arial", 'size': font_size_1}, loc='upper right')
    plt.savefig('paper_figures/png/Fig_1S_Supralinear_network_2D_weak_Jee_g_e_' + str(g_e_temp) + '_g_i_' + str(g_i_temp) + '.png')
    plt.savefig('paper_figures/pdf/Fig_1S_Supralinear_network_2D_weak_Jee_g_e_' + str(g_e_temp) + '_g_i_' + str(g_i_temp) + '.pdf')

请注意，以上只是根据你提供的代码进行了简单的修复，可能还有其他问题。如果还有错误，请提供完整的代码和错误信息，以便我们更好地帮助你。