C++/Qt中调用Python模块_qt调用python

C++/Qt中调用Python模块

开发环境搭建

作为一种胶水语言，Python 能够很容易地调用 C 、 C++ 等语言，也能够通过其他语言调用 Python 的模块。Python 提供了 C++ 库，使得开发者能很方便地从 C++ 程序中调用 Python 模块。

值得注意的是，Windows平台下的Python提供的静态库接口只支持MSVC编译器。

参考的资料：

• C调用Python（传递数字、字符串、list数组（一维、二维），结构体）
• 浅析 C++ 调用 Python 模块
• Embedding Python in Another Application

开发Python模块

Python 模块的源码示例：

# -*- coding: utf-8 -*-

' a module for alwhales data fit project '

__author__ = 'Dog Tao'

import sys

# 根据不同的开发环境设置对应的外部模块的路径
sys.path.append('E:\\Working\\PythonDev\\DataFitting\\venv\Lib\\site-packages')

import numpy as np
import matplotlib.pyplot as plt

from pylab import mpl
from scipy import interpolate
from scipy.optimize import curve_fit

mpl.rcParams['font.sans-serif'] = ['SimHei']  # 指定默认字体
plt.rcParams['axes.unicode_minus'] = False  # 解决负数坐标显示问题

def polynomial_fitting(x_series, y_series, deg=3):
    """
    多项式拟合方法
    :param x_series: x series of data point
    :param y_series: y series of data point
    :param deg: order of polynomial
    :return: list type of polynomial fit parameters
    """
    return np.polyfit(x_series, y_series, deg)

def interpolate_linear(x_series, y_series, x_fit_series):
    """
    线性插值拟合
    :param x_series: x series of data point
    :param y_series: y series of data point
    :param x_fit_series: new series of x to fit b_spline
    :return: list type of linear fit callable object
    """
    f_linear = interpolate.interp1d(x_series, y_series)
    return f_linear(x_fit_series)

def interpolate_b_spline(x_series, y_series, x_fit_series):
    """
    B样条曲线插值
    :param x_series: x series of data point
    :param y_series: y series of data point
    :param x_fit_series: new series of x to fit b_spline
    :return: y series of fit data
    """
    tck = interpolate.splrep(x_series, y_series)
    return interpolate.splev(x_fit_series, tck, 0)

def func_4PL(x, a, b, c, d):
    """
    四参数模式为Y=(a-d)/[1+(x/c)^b]+d, 目前最常用与免疫检测领域，用于描述吸光度随抗原浓度变化的规律
    :param x: value
    :param a: 曲线上渐近线估值
    :param b: 曲线下渐近线估值
    :param c: 曲线的斜率
    :param d: 最大结合一半时对应的剂量
    :return: y value
    ""
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