python
复制代码
import matplotlib.pyplot as plt
import numpy as np
# plt.rcParams['font.family'] = 'SimHei' # 指定使用中文字体，例如宋体（SimHei）
def Curve_Fitting(x, y, deg):
parameter = np.polyfit(x, y, deg) #拟合deg次多项式
p = np.poly1d(parameter) #拟合deg次多项式
aa='' #方程拼接 ------------------------------------------------------
for i in range(deg+1):
bb=round(parameter[i], 2)
if bb>0:
if i==0:
bb=str(bb)
else:
bb='+'+str(bb)
else:
bb=str(bb)
if deg==i:
aa=aa+bb
else:
aa=aa+bb+'x^'+str(deg-i) #方程拼接 ------------------------------------------------------
# 利用相关系数矩阵计算R方
r2 = round(np.corrcoef(y, p(x))[0,1]**2,2)
plt.scatter(x, y, label="Comparison", color='b', marker='o') #原始数据散点图
plt.plot(x, p(x), color='r') # 画拟合曲线
# plt.text(-1,0,aa,fontdict={'size':'10','color':'b'})
plt.legend([f"R^2: {r2}", f"Fitting Equation: {aa}"]) #拼接好的方程和R方放到图例
# 添加标签和标题
plt.xlabel("Old Normalized_TMB Values")
plt.ylabel("New Normalized_TMB Values")
plt.title("Comparison of Normalized_TMB")
plt.savefig('./tmp.jpg')
plt.show()
print('曲线方程为：',aa)
print(' r^2为：', r2)
def plot_scatter(old_list, new_list):
# 示例数据：相同样本的两次运行结果
# sample_names = ["Sample 1", "Sample 2", "Sample 3", "Sample 4"]
run1_values = old_list # 第一次运行的数据
run2_values = new_list # 第二次运行的数据
# 创建散点图
plt.scatter(run1_values, run2_values, label="Comparison", color='b', marker='o')
# 添加标签和标题
plt.xlabel("Old Normalized_TMB Values")
plt.ylabel("New Normalized_TMB Values")
plt.title("Comparison of Normalized_TMB")
# 添加数据点的标签
# for i, sample_name in enumerate(sample_names):
# plt.annotate(sample_name, (run1_values[i], run2_values[i]))
# 添加一条线表示一对一的关系
plt.plot([min(run1_values), max(run1_values)], [min(run1_values), max(run1_values)], linestyle='--', color='r', label="1:1 Line")
# 显示图例
plt.legend()
plt.savefig('./tmp.jpg')
# 显示散点图
plt.show()
normalzed_tmb_compare_file = 'normalzed_tmb.txt'
old_FFPE_list, new_FFPE_list = [], []
old_CF_list, new_CF_list = [], []
with open(normalzed_tmb_compare_file) as f:
next(f)
for line in f:
line_list = line.strip('\n').split('\t')
# if float(line_list[0]) > 20:
# continue
old, type_, new = line_list
if type_ == 'FFPE':
old_FFPE_list.append(float(line_list[0]))
new_FFPE_list.append(float(line_list[-1]))
if type_ == 'CF':
old_CF_list.append(float(line_list[0]))
new_CF_list.append(float(line_list[-1]))
# Curve_Fitting(old_FFPE_list, new_FFPE_list, 1)
# Curve_Fitting(old_CF_list, new_CF_list, 1)
Curve_Fitting(old_CF_list+old_FFPE_list, new_CF_list+new_FFPE_list, 1)
# plot_scatter(old_list, new_list)