matplotlib中matshow和imshow的区别

2023-10-25 08:40

本文主要是介绍matplotlib中matshow和imshow的区别,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!

matplotlib中matshow和imshow的区别

1.matshow

如下,即在一个图形窗口中将数组作为矩阵展示

def matshow(A, fignum=None, **kwargs):"""Display an array as a matrix in a new figure window.The origin is set at the upper left hand corner and rows (firstdimension of the array) are displayed horizontally.  The aspectratio of the figure window is that of the array, unless this wouldmake an excessively short or narrow figure.Tick labels for the xaxis are placed on top.Parameters----------A : array-like(M, N)The matrix to be displayed.fignum : None or int or FalseIf *None*, create a new figure window with automatic numbering.If a nonzero integer, draw into the figure with the given number(create it if it does not exist).If 0, use the current axes (or create one if it does not exist)... note::Because of how `.Axes.matshow` tries to set the figure aspectratio to be the one of the array, strange things may happen if youreuse an existing figure.Returns-------image : `~matplotlib.image.AxesImage`Other Parameters----------------**kwargs : `~matplotlib.axes.Axes.imshow` arguments"""

效果图如下:

2.imshow

展示图像数据在一个二维普通光栅中

    def imshow(self, X, cmap=None, norm=None, aspect=None,interpolation=None, alpha=None, vmin=None, vmax=None,origin=None, extent=None, shape=None, filternorm=1,filterrad=4.0, imlim=None, resample=None, url=None, **kwargs):"""Display an image, i.e. data on a 2D regular raster.Parameters----------X : array-like or PIL imageThe image data. Supported array shapes are:- (M, N): an image with scalar data. The data is visualizedusing a colormap.- (M, N, 3): an image with RGB values (0-1 float or 0-255 int).- (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),i.e. including transparency.The first two dimensions (M, N) define the rows and columns ofthe image.Out-of-range RGB(A) values are clipped.cmap : str or `~matplotlib.colors.Colormap`, optionalThe Colormap instance or registered colormap name used to mapscalar data to colors. This parameter is ignored for RGB(A) data.Defaults to :rc:`image.cmap`.norm : `~matplotlib.colors.Normalize`, optionalThe `Normalize` instance used to scale scalar data to the [0, 1]range before mapping to colors using *cmap*. By default, a linearscaling mapping the lowest value to 0 and the highest to 1 is used.This parameter is ignored for RGB(A) data.aspect : {'equal', 'auto'} or float, optionalControls the aspect ratio of the axes. The aspect is of particularrelevance for images since it may distort the image, i.e. pixelwill not be square.This parameter is a shortcut for explicitly calling`.Axes.set_aspect`. See there for further details.- 'equal': Ensures an aspect ratio of 1. Pixels will be square(unless pixel sizes are explicitly made non-square in datacoordinates using *extent*).- 'auto': The axes is kept fixed and the aspect is adjusted sothat the data fit in the axes. In general, this will result innon-square pixels.If not given, use :rc:`image.aspect` (default: 'equal').interpolation : str, optionalThe interpolation method used. If *None*:rc:`image.interpolation` is used, which defaults to 'nearest'.Supported values are 'none', 'nearest', 'bilinear', 'bicubic','spline16', 'spline36', 'hanning', 'hamming', 'hermite', 'kaiser','quadric', 'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc','lanczos'.If *interpolation* is 'none', then no interpolation is performedon the Agg, ps, pdf and svg backends. Other backends will fall backto 'nearest'. Note that most SVG renders perform interpolation atrendering and that the default interpolation method they implementmay differ.See:doc:`/gallery/images_contours_and_fields/interpolation_methods`for an overview of the supported interpolation methods.Some interpolation methods require an additional radius parameter,which can be set by *filterrad*. Additionally, the antigrain imageresize filter is controlled by the parameter *filternorm*.alpha : scalar, optionalThe alpha blending value, between 0 (transparent) and 1 (opaque).This parameter is ignored for RGBA input data.vmin, vmax : scalar, optionalWhen using scalar data and no explicit *norm*, *vmin* and *vmax*define the data range that the colormap covers. By default,the colormap covers the complete value range of the supplieddata. *vmin*, *vmax* are ignored if the *norm* parameter is used.origin : {'upper', 'lower'}, optionalPlace the [0,0] index of the array in the upper left or lower leftcorner of the axes. The convention 'upper' is typically used formatrices and images.If not given, :rc:`image.origin` is used, defaulting to 'upper'.Note that the vertical axes points upward for 'lower'but downward for 'upper'.extent : scalars (left, right, bottom, top), optionalThe bounding box in data coordinates that the image will fill.The image is stretched individually along x and y to fill the box.The default extent is determined by the following conditions.Pixels have unit size in data coordinates. Their centers are oninteger coordinates, and their center coordinates range from 0 tocolumns-1 horizontally and from 0 to rows-1 vertically.Note that the direction of the vertical axis and thus the defaultvalues for top and bottom depend on *origin*:- For ``origin == 'upper'`` the default is``(-0.5, numcols-0.5, numrows-0.5, -0.5)``.- For ``origin == 'lower'`` the default is``(-0.5, numcols-0.5, -0.5, numrows-0.5)``.See the example :doc:`/tutorials/intermediate/imshow_extent` for amore detailed description.filternorm : bool, optional, default: TrueA parameter for the antigrain image resize filter (see theantigrain documentation).  If *filternorm* is set, the filternormalizes integer values and corrects the rounding errors. Itdoesn't do anything with the source floating point values, itcorrects only integers according to the rule of 1.0 which meansthat any sum of pixel weights must be equal to 1.0.  So, thefilter function must produce a graph of the proper shape.filterrad : float > 0, optional, default: 4.0The filter radius for filters that have a radius parameter, i.e.when interpolation is one of: 'sinc', 'lanczos' or 'blackman'.resample : bool, optionalWhen *True*, use a full resampling method.  When *False*, onlyresample when the output image is larger than the input image.url : str, optionalSet the url of the created `.AxesImage`. See `.Artist.set_url`.Returns-------image : `~matplotlib.image.AxesImage`Other Parameters----------------**kwargs : `~matplotlib.artist.Artist` propertiesThese parameters are passed on to the constructor of the`.AxesImage` artist.See also--------matshow : Plot a matrix or an array as an image.Notes-----Unless *extent* is used, pixel centers will be located at integercoordinates. In other words: the origin will coincide with the centerof pixel (0, 0).There are two common representations for RGB images with an alphachannel:-   Straight (unassociated) alpha: R, G, and B channels represent thecolor of the pixel, disregarding its opacity.-   Premultiplied (associated) alpha: R, G, and B channels representthe color of the pixel, adjusted for its opacity by multiplication.`~matplotlib.pyplot.imshow` expects RGB images adopting the straight(unassociated) alpha representation."""

同一个矩阵展示效果如下:

与上面对比我们可以看到图像的坐标默认是不同的。

 

详细可参阅官方文档。

https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.matshow.html#matplotlib.axes.Axes.matshow

https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.imshow.html#matplotlib.axes.Axes.imshow

 

 

这篇关于matplotlib中matshow和imshow的区别的文章就介绍到这儿,希望我们推荐的文章对编程师们有所帮助!



http://www.chinasem.cn/article/281380

相关文章

Java中ArrayList和LinkedList有什么区别举例详解

《Java中ArrayList和LinkedList有什么区别举例详解》:本文主要介绍Java中ArrayList和LinkedList区别的相关资料,包括数据结构特性、核心操作性能、内存与GC影... 目录一、底层数据结构二、核心操作性能对比三、内存与 GC 影响四、扩容机制五、线程安全与并发方案六、工程

java中不同版本JSONObject区别小结

《java中不同版本JSONObject区别小结》本文主要介绍了java中不同版本JSONObject区别小结,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们... 目录1. FastjsON2. Jackson3. Gson4. org.json6. 总结在Jav

数据库使用之union、union all、各种join的用法区别解析

《数据库使用之union、unionall、各种join的用法区别解析》:本文主要介绍SQL中的Union和UnionAll的区别,包括去重与否以及使用时的注意事项,还详细解释了Join关键字,... 目录一、Union 和Union All1、区别:2、注意点:3、具体举例二、Join关键字的区别&php

java中的HashSet与 == 和 equals的区别示例解析

《java中的HashSet与==和equals的区别示例解析》HashSet是Java中基于哈希表实现的集合类,特点包括:元素唯一、无序和可包含null,本文给大家介绍java中的HashSe... 目录什么是HashSetHashSet 的主要特点是HashSet 的常用方法hasSet存储为啥是无序的

2.1/5.1和7.1声道系统有什么区别? 音频声道的专业知识科普

《2.1/5.1和7.1声道系统有什么区别?音频声道的专业知识科普》当设置环绕声系统时,会遇到2.1、5.1、7.1、7.1.2、9.1等数字,当一遍又一遍地看到它们时,可能想知道它们是什... 想要把智能电视自带的音响升级成专业级的家庭影院系统吗?那么你将面临一个重要的选择——使用 2.1、5.1 还是

Python中@classmethod和@staticmethod的区别

《Python中@classmethod和@staticmethod的区别》本文主要介绍了Python中@classmethod和@staticmethod的区别,文中通过示例代码介绍的非常详细,对大... 目录1.@classmethod2.@staticmethod3.例子1.@classmethod

Golan中 new() 、 make() 和简短声明符的区别和使用

《Golan中new()、make()和简短声明符的区别和使用》Go语言中的new()、make()和简短声明符的区别和使用,new()用于分配内存并返回指针,make()用于初始化切片、映射... 详细介绍golang的new() 、 make() 和简短声明符的区别和使用。文章目录 `new()`

Python中json文件和jsonl文件的区别小结

《Python中json文件和jsonl文件的区别小结》本文主要介绍了JSON和JSONL两种文件格式的区别,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下... 众所周知,jsON 文件是使用php JSON(JavaScripythonpt Object No

结构体和联合体的区别及说明

《结构体和联合体的区别及说明》文章主要介绍了C语言中的结构体和联合体,结构体是一种自定义的复合数据类型,可以包含多个成员,每个成员可以是不同的数据类型,联合体是一种特殊的数据结构,可以在内存中共享同一... 目录结构体和联合体的区别1. 结构体(Struct)2. 联合体(Union)3. 联合体与结构体的

什么是 Ubuntu LTS?Ubuntu LTS和普通版本区别对比

《什么是UbuntuLTS?UbuntuLTS和普通版本区别对比》UbuntuLTS是Ubuntu操作系统的一个特殊版本,旨在提供更长时间的支持和稳定性,与常规的Ubuntu版本相比,LTS版... 如果你正打算安装 Ubuntu 系统,可能会被「LTS 版本」和「普通版本」给搞得一头雾水吧?尤其是对于刚入