c++的eigen矩阵保存的复数如何在python中用numpy导入加载

东方耀 · 发表于 2023-11-10 16:39:45

c++的eigen矩阵保存的复数如何在python中用numpy导入加载

用这个np.genfromtxt  而不是 np.loadtxt

for i in range(antenna_tx_num * antenna_rx_num):
      # 每列的转换器
      converters = convert

// 保存输入的数据方便分析

      Eigen::VectorXcf tx, rx;

      tx.resize(ninput_items[0]);

      rx.resize(ninput_items[1]);

      memcpy(&tx(0), in_tx, sizeof(gr_complex) * ninput_items[0]);

      memcpy(&rx(0), in_rx, sizeof(gr_complex) * ninput_items[1]);

      /*写文件**/

      ofstream f_out_tx("tx.txt", ios::out);

      f_out_tx << tx << endl;

      f_out_tx.flush();

      /*写文件**/

      ofstream f_out_rx("rx.txt", ios::out);

      f_out_rx << rx << endl;

      f_out_rx.flush();
复制代码

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

__author__ = u'东方耀微信：dfy_88888'

__date__ = '2023/11/10 下午3:47'

__product__ = 'PyCharm'

__filename__ = '19_sfcw的发射信号与回波信号分析'

from scipy.fftpack import fft, ifft, fftshift

from scipy.signal import lfilter

import scipy.io as scio

import math

import cmath

from sklearn.cluster import KMeans

import time

from matplotlib import cm

import numpy as np

import random

import os

import struct

import shutil

from scipy import signal

from collections import Counter, OrderedDict

import io

from PIL import Image

import cv2

import json

from tqdm import tqdm

import csv

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D    # ValueError: Unknown projection '3d' 必须加这一行才行

from matplotlib import transforms

import matplotlib.ticker as mticker

from matplotlib.font_manager import FontProperties

font_fname = "/usr/share/fonts/wps-office/simfang.ttf"

# font_fname = "C:\Windows\Fonts\simfang.ttf"

font = FontProperties(fname=font_fname)

# plt.rcParams['font.sans-serif']=['simfang']#设置作图中文显示

random.seed(888)

def randomcolor():

colorArr = ['1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E', 'F']

color = ""

for i in range(6):

      color += colorArr[random.randint(0, 14)]

return "#" + color

my_color = []

for _ in range(1000):

# 每帧不同的颜色

my_color.append(randomcolor())

tx_file = "/home/jiang/jjj_grc_works/jiang_KGD_projects/18/tx.txt"

rx_file = "/home/jiang/jjj_grc_works/jiang_KGD_projects/18/rx.txt"

# x是字符串  x = (real,imag)

convert = (lambda x: float(x[1:-1].split(b',')[0]) +

                  float(x[1:-1].split(b',')[1]) * 1j)

converters = {}

for i in range(1):

# 每列的转换器

converters[i] = convert

# tx = np.loadtxt(tx_file, dtype=np.complex64)

tx = np.genfromtxt(tx_file, dtype=np.complex64, converters=converters, autostrip=True)

# rx = np.loadtxt(rx_file, dtype=np.complex64)

rx = np.genfromtxt(rx_file, dtype=np.complex64, converters=converters, autostrip=True)

print("tx_len = ", tx.shape)

print("rx_len = ", rx.shape)

look_one_echo_wave_dat = tx

fig = plt.figure(figsize=(18, 20))  # H=2000  W=1800像素

plt.figure(1)

plt.subplots_adjust(wspace=0, hspace=0.6)

plt.subplot(4, 1, 1)

plt.xlabel("点数", fontproperties=font, fontsize=15)

plt.ylabel("value", fontproperties=font, fontsize=15)

plt.title("Rx_IQ路_时域波形_len=%d" % len(look_one_echo_wave_dat), fontproperties=font, fontsize=16)

plt.plot(look_one_echo_wave_dat.real, marker="o", markersize=4, markerfacecolor=my_color[0], color=my_color[0], label="real")

plt.plot(look_one_echo_wave_dat.imag, marker="o", markersize=4, markerfacecolor=my_color[1], color=my_color[1], label="imag")

plt.legend(loc="best")

plt.subplot(4, 1, 2)

plt.xlabel("点数_频率(M)", fontproperties=font, fontsize=15)

plt.ylabel("幅值", fontproperties=font, fontsize=15)

plt.title("Rx_幅度谱", fontproperties=font, fontsize=16)

plt.plot(np.abs(fftshift(fft(look_one_echo_wave_dat))), marker="o", markersize=4, markerfacecolor=my_color[3], color=my_color[3])

# plt.legend(loc="best")

plt.subplot(4, 1, 3)

plt.xlabel("点数", fontproperties=font, fontsize=15)

plt.ylabel("相位", fontproperties=font, fontsize=15)

plt.title("Rx_时域的相位角", fontproperties=font, fontsize=16)

# plt.plot(np.angle(fftshift(fft(echo_wave_data_mat[:, look_echo_wave_index]))), marker="o", markersize=4, markerfacecolor=my_color[4], color=my_color[4])

plt.plot(np.angle(look_one_echo_wave_dat), marker="o", markersize=4, markerfacecolor=my_color[4], color=my_color[4])

# plt.legend(loc="best")

plt.subplot(4, 1, 4)

plt.xlabel("点数", fontproperties=font, fontsize=15)

plt.ylabel("value", fontproperties=font, fontsize=15)

plt.title("Rx_IQ路_时域的幅值", fontproperties=font, fontsize=16)

plt.plot(np.abs(look_one_echo_wave_dat), marker="o", markersize=4, markerfacecolor=my_color[4], color=my_color[4])

plt.show()

复制代码

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[C/C++] c++的eigen矩阵保存的复数如何在python中用numpy导入加载