python背景颜色函数 python设置颜色的函数
python matplotlib.pyplot.imshow 函数画二维颜色图
matplotlib.pyplot.imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, *, filternorm=True, filterrad=4.0, resample=None, url=None, data=None, **kwargs)
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From:
改以下参数可以对图片效果进行调整:
举个栗子:
python使用pil获取图层中出现次数最多的颜色值
这里分享下python,使用pil获取图层中出现次数最多颜色值的方法。
设备:magicbook
系统:Windows 11
软件:python2014
1、首先打开pycharm开发工具,创建python项目,然后新建python文件。
2、定义函数countNum,传入参数amn;然后使用字典,获取字符串中的字符,统计出现的次数。
3、定义一个字符串变量cmn,然后调用函数countNum,传入cmn,然后将返回的值给变量bmn,并打印。
4、保存代码并运行python文件,查看控制台打印结果,如下图所示就完成了。
python已知rgb,如何转为颜色
转为16进制就是分别把红绿蓝三种颜色的色值转为十六进制,前面加个井号
科学可视化:Python + Matplotlib(英文翻译)
by Nicolas P. Rougier, Bordeaux, November 2021.
PDF地址:
原文:
The Python scientific visualisation landscape is huge. It is composed of a myriad of tools, ranging from the most versatile and widely used down to the more specialised and confidential. Some of these tools are community based while others are developed by companies. Some are made specifically for the web, others are for the desktop only, some deal with 3D and large data, while others target flawless 2D rendering.
翻译:
Python 科学可视化领域是巨大的(见下图)。它由无数工具组成,从最通用和最有广泛性的工具到更专业和达到机密级的工具。其中一些工具是基于社区的,而另一些则是由公司开发的。有些是专门为 Web 制作的,有些仅适用于桌面,有些用于处理 3D 和大数据,而有些则针对完美的 2D 渲染。
原文:
Figure : The most important element of a figure is the figure itself. It is created when you call the figure method and we’ve already seen you can specify its size but you can also specify a background color (facecolor) as well as a title (suptitle). It is important to know that the background color won’t be used when you save the figure because the savefig function has also a facecolor argument (that is white by default) that will override your figure background color. If you don’t want any background you can specify transparent=True when you save the figure.
Axes : This is the second most important element that corresponds to the actual area where your data will be rendered. It is also called a subplot. You can have have one to many axes per figure and each is usually surrounded by four edges (left, top, right and bottom) that are called spines. Each of these spines can be decorated with major and minor ticks (that can point inward or outward), tick labels and a label. By default, matplotlib decorates only the left and bottom spines.
Axis : The decorated spines are called axis. The horizontal one is the xaxis and the vertical one is the yaxis. Each of them are made of a spine, major and minor ticks, major and minor ticks labels and an axis label.
Spines : Spines are the lines connecting the axis tick marks and noting the boundaries of the data area. They can be placed at arbitrary positions and may be visible or invisible.
Artist : Everything on the figure, including Figure, Axes, and Axis objects, is an artist. This includes Text objects, Line2D objects, collection objects, Patch objects. When the figure is rendered, all of the artists are drawn to the canvas. A given artist can only be in one Axes.
翻译:
Figure(图形):图形中最重要的元素是Figure本身。它是在你调用 figure 方法时创建的,我们已经看到你可以指定它的大小,但你也可以指定背景颜色 (facecolor) 和标题 (suptitle)。重要的是保存图形时不会使用背景颜色,因为 savefig 函数也有一个 facecolor 参数(默认为白色),它将覆盖图形背景颜色。如果您不想要任何背景,您可以在保存图形时指定 transparent=True。
Axes(轴域) :这是第二个最重要的元素,对应于将呈现数据的实际区域。它也被称为子图。每个图形可以有一个到多个Axes ,每个轴通常被称为spines的四个边缘(左、上、右和下)包围。这些spines中的每一个都可以装饰有主要和次要刻度(可以指向内或向外)、刻度标签和标签。默认情况下,matplotlib 只装饰左侧和底部的Spines。
Axis(轴):轴上的刻度称为Axis。水平轴是 x 轴,垂直轴是 y 轴。它们中的每一个都由Spines、主要和次要刻度、刻度标签以及轴标签组成。
Spines(图脊):Spines 是连接轴刻度线和关注数据区域边界的线。它们可以放置在任意位置并且可以是可见的或不可见的。
Artist(艺术家):图形上的所有内容,包括图形、轴和轴对象,都是 Artist 。这包括 Text 对象、Line2D 对象、集合对象、Patch 对象。当图形被渲染时,所有的 Artist 都被绘制到画布上。给定的 Artist 只能在一个 Axes 中。
原文:
Given the definition above, problems arise when how a visual is perceived differs significantly from the intent of the conveyer. Consequently, it is important to identify, as early as possible in the design process, the audience and the message the visual is to convey. The graphical design of the visual should be informed by this intent.
Only after identifying the message will it be worth the time to develop your figure, just as you would take the time to craft your words and sentences when writing an article only after deciding on the main points of the text.
A figure can be displayed on a variety of media, such as a poster, a computer monitor, a projection screen (as in an oral presentation), or a simple sheet of paper (as in a printed article). Each of these media represents different physical sizes for the figure, but more importantly, each of them also implies different ways of viewing and interacting with the figure.
Whether describing an experimental setup, introducing a new model, or presenting new results, you cannot explain everything within the figure itself—a figure should be accompanied by a caption. The caption explains how to read the figure and provides additional precision for what cannot be graphically represented.
All plots require at least some manual tuning of the different settings to better express the message, be it for making a precise plot more salient to a broad audience, or to choose the best colormap for the nature of the data.
Color is an important dimension in human vision and is consequently equally important in the design of a scientific figure.
What distinguishes a scientific figure from other graphical artwork is the presence of data that needs to be shown as objectively as possible.
Chartjunk refers to all the unnecessary or confusing visual elements found in a figure that do not improve the message (in the best case) or add confusion (in the worst case).
Remember, in science, message and readability of the figure is the most important aspect while beauty is only an option.
There exist many tools that can make your life easier when creating figures, and knowing a few of them can save you a lot of time.
翻译:
如上所述,当视觉所展示的与表达者的意图明显出现偏差时,就会出现问题。 因此,在设计过程中尽早确定受众和视觉传达的信息非常重要。 视觉的图形设计应以此意图为依据。
只有在确定了信息之后,才值得花时间开发你的图形,就像你在写一篇文章时,只有在确定了文本的要点之后,才会花时间精心制作你的单词和句子。
图形可以显示在各种媒介上,例如海报、计算机显示器、投影屏幕(如宣讲会)或简单的纸(如印刷品)。每一个媒介都代表了图形的不同物理尺寸,但更重要的是,每一个还提示了观看者和与图形互动的不同方式。
无论是说明如何设置实验、引入新模型还是展示新结果,图形都无法解释本身的所有内容——图形应附有备注。备注解释了如何阅读该图并为无法用图形表示的内容提供更精确的说明。
所有的图形都至少需要对不同的缺省值进行一些手动调整,以更好地表达信息,不仅是为了使图形对广大观众更加突出精确,还需要对数据的性质选择最佳颜色图。
颜色是人类视觉中的一个重要维度,因此在科学人物的设计中同样重要。
科学图形与其他图形艺术作品的区别在于,数据的展现需要尽可能客观地显示。
“无用图形”是指在图中存在的所有不必要或令人困惑的视觉元素,这些元素不会改善信息(在最好的情况下)或增加混乱(在最坏的情况下)。
请记住,在科学中,图形的信息和可读性是最重要的方面,而美化只是一种选择。
有许多工具可以让您在创建图形时更轻松,了解其中的一些工具可以为您节省大量时间。
python如何设置rgb颜色
通过代码来设置颜色。
可以使用语句,turtlecolor("red")通过这一句代码,画笔的颜色就被设置为红色,以此类推。
Python由荷兰数学和计算机科学研究学会的于1990年代初设计。
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