scipy

python: plotting a histogram with a function line on top

由 落爺英雄遲暮 提交于 2021-01-20 16:30:43
问题 I'm trying to do a little bit of distribution plotting and fitting in Python using SciPy for stats and matplotlib for the plotting. I'm having good luck with some things like creating a histogram: seed(2) alpha=5 loc=100 beta=22 data=ss.gamma.rvs(alpha,loc=loc,scale=beta,size=5000) myHist = hist(data, 100, normed=True) Brilliant! I can even take the same gamma parameters and plot the line function of the probability distribution function (after some googling): rv = ss.gamma(5,100,22) x = np

How to solve the polynomial eigenvalue in python?

由 萝らか妹 提交于 2021-01-18 16:09:33
问题 In my python code, I would like to solve the polynomial eigenvalue problem: A0 + lambda*A1 + lambda^2*A2 + lambda^3*A3 + .... = 0 where An are dense matrices, and lambda is a constant. In matlab it is possible to solve this problem using the polyeig function. It seems that there is no equivalent functionality in scipy. So far the only way I can think to do it is to form the corresponding companion matrix. This creates an equivalent linear eigenvalue problem which can be given to existing

How to solve the polynomial eigenvalue in python?

由 梦想与她 提交于 2021-01-18 16:08:50
问题 In my python code, I would like to solve the polynomial eigenvalue problem: A0 + lambda*A1 + lambda^2*A2 + lambda^3*A3 + .... = 0 where An are dense matrices, and lambda is a constant. In matlab it is possible to solve this problem using the polyeig function. It seems that there is no equivalent functionality in scipy. So far the only way I can think to do it is to form the corresponding companion matrix. This creates an equivalent linear eigenvalue problem which can be given to existing

How to solve the polynomial eigenvalue in python?

由 别说谁变了你拦得住时间么 提交于 2021-01-18 16:05:46
问题 In my python code, I would like to solve the polynomial eigenvalue problem: A0 + lambda*A1 + lambda^2*A2 + lambda^3*A3 + .... = 0 where An are dense matrices, and lambda is a constant. In matlab it is possible to solve this problem using the polyeig function. It seems that there is no equivalent functionality in scipy. So far the only way I can think to do it is to form the corresponding companion matrix. This creates an equivalent linear eigenvalue problem which can be given to existing

How to solve the polynomial eigenvalue in python?

由 落花浮王杯 提交于 2021-01-18 16:04:42
问题 In my python code, I would like to solve the polynomial eigenvalue problem: A0 + lambda*A1 + lambda^2*A2 + lambda^3*A3 + .... = 0 where An are dense matrices, and lambda is a constant. In matlab it is possible to solve this problem using the polyeig function. It seems that there is no equivalent functionality in scipy. So far the only way I can think to do it is to form the corresponding companion matrix. This creates an equivalent linear eigenvalue problem which can be given to existing

How to read .npy files in Matlab

由 房东的猫 提交于 2021-01-18 07:46:25
问题 I was wondering if there is way to read .npy files in Matlab? I know I can convert those to Matlab-style .mat files using scipy.io.savemat in Python; however I'm more interested in a native or plugin support for .npy files in Matlab. 回答1: There is a c++ library available https://github.com/rogersce/cnpy You could write a mex function to read the data. I would prefer to store everything in hdf5 回答2: This did the job for me, I used it to read npy files. https://github.com/kwikteam/npy-matlab If

Python实现语音识别和语音合成

由 狂风中的少年 提交于 2021-01-13 07:37:08
声音的本质是震动，震动的本质是位移关于时间的函数，波形文件(.wav)中记录了不同采样时刻的位移。 通过傅里叶变换，可以将时间域的声音函数分解为一系列不同频率的正弦函数的叠加，通过频率谱线的特殊分布，建立音频内容和文本的对应关系，以此作为模型训练的基础。 案例：画出语音信号的波形和频率分布，（ freq.wav数据地址 ） # -*- encoding:utf-8 -*- import numpy as np import numpy.fft as nf import scipy.io.wavfile as wf import matplotlib.pyplot as plt sample_rate, sigs = wf.read( ' ../machine_learning_date/freq.wav ' ) print (sample_rate) # 8000采样率 print (sigs.shape) # (3251,) sigs = sigs / (2 ** 15) # 归一化 times = np.arange(len(sigs)) / sample_rate freqs = nf.fftfreq(sigs.size, 1 / sample_rate) ffts = nf.fft(sigs) pows = np.abs(ffts) plt.figure( ' Audio

python实现爬取指定bilibili视频的弹幕并制作词云

由 匆匆过客 提交于 2021-01-12 20:01:30
先看下最终实现的效果 具体实现思路是 1.爬取带有弹幕信息的网页 2.处理爬取得到的内容并提取所需要的弹幕信息，然后写入文本中 3.通过词云库将文本处理成想要的图片 所需要用到的库 import requests from bs4 import BeautifulSoup import pandas as pd import re import jieba from wordcloud import WordCloud from scipy.misc import imread import matplotlib.pyplot as plt 首先爬取想要的信息 ps（哔哩哔哩的弹幕全部保存在 http://comment.bilibili.com/ 122512779 .xml 中，红色字体为该视频的cid，可以在当前视频页通过：查看网页源代码—ctrl+f查找cid-出现的第一个9位cid，来获取） url = ' http://comment.bilibili.com/.xml ' # 对方的url header = { ' User-Agent ' : ' Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari

numpy.ndarray类型的数组元素输出时，保留小数点后4位

由 孤街浪徒 提交于 2021-01-09 02:23:04
因为计算结果数组中每个值都是很长的一串小数，看起来比较乱，想格式化一下输出方式。 这是个看起来很简单的问题，但是方法找了很久。 方法也是看起来很简单，用 numpy.set_printoptions(precision=4) 代码： 1 import numpy as np 2 aa=np.random.rand(2,3 ) 3 print (aa) 4 np.set_printoptions(precision=4 ) 5 print (aa) 输出： reference: https://docs.scipy.org/doc/numpy/reference/generated/numpy.set_printoptions.html 来源： oschina 链接： https://my.oschina.net/u/4374968/blog/3899474

Python 十大图像处理工具

由 北城余情 提交于 2021-01-08 18:53:32
作者：Parul Pandey 编译：大数据文摘 本文主要介绍了一些简单易懂最常用的Python图像处理库 当今世界充满了各种数据，而图像是其中高的重要组成部分。然而，若想其有所应用，我们需要对这些图像进行处理。图像处理是分析和操纵数字图像的过程，旨在提高其质量或从中提取一些信息，然后将其用于某些方面。 图像处理中的常见任务包括显示图像，基本操作（如裁剪、翻转、旋转等），图像分割，分类和特征提取，图像恢复和图像识别等。Python之成为图像处理任务的最佳选择，是因为这一科学编程语言日益普及，并且其自身免费提供许多最先进的图像处理工具。 让我们看一下用于图像处理任务的一些常用Python库。 1. scikit Image scikit-image是一个基于numpy数组的开源Python包。 它实现了用于研究、教育和工业应用的算法和实用程序。 即使是对于那些刚接触Python的人，它也是一个相当简单的库。 此库代码质量非常高并已经过同行评审，是由一个活跃的志愿者社区编写的。 使用说明文档： https://scikit-image.org/docs/stable/user_guide.html 用法举例： 图像过滤、 模版匹配 可使用“skimage”来导入该库。大多数功能都能在子模块中找到。 import matplotlib.pyplot as plt %matplotlib
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