matplotlib

Creating a smooth surface plot from topographic data using matplotlib

由 夙愿已清 提交于 2021-02-04 11:41:27
问题 I have a code that creates a 3d topographic surface from lat, lon and elev data. I'm using ax.plot_surface , which creates a topographic surface that looks like this: I would like to smooth the data to create a picture that looks more like this: Is there a better way to smooth out the interpolation done by mesh grid? my_data is sorted by [lat,lon,elev] size(912,3) Code below import os import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt from scipy

Python - matplotlib - differences between subplot() and subplots()

由 时光毁灭记忆、已成空白 提交于 2021-02-04 11:40:33
问题 I'm kind of new in coding and thus in python so this may sound quite dumb, but what are the main differences between .subplot() and .subplots() methods from matplotlib in python? I didn't find this explanation anywhere else and after reading the documentation from https://matplotlib.org/ I inferred that with both methods you can create as many figures and plots as you want...so for me both of them seem to be quite the same thing and they just differ the way you can handle plots, axes, etc..

Point in polygon using shapely?

由 ぃ、小莉子 提交于 2021-02-04 08:21:39
问题 I am running the following script which I believe should be returning TRUE for the point being in the polygon but it is returning FALSE. from shapely import geometry polygon = [(-1571236.8349707182, 8989180.222117377), (1599362.9654156454, 8924317.946336618), (-1653179.0745812152, 8922145.163675062), (-1626237.6614402141, 8986445.107619021)] Point_X = -1627875.474 Point_Y = 8955472.968 line = geometry.LineString(polygon) point = geometry.Point(Point_X, Point_Y) print(line.contains(point))

Measurement length for X and Y-axis

由 自古美人都是妖i 提交于 2021-02-04 08:09:50
问题 I wonder if it's possible to change the measurement milestones for graphs created by pandas. In my code the X-axis stands for time and is measured by month, but the measurement milestones are all over the place. In the image below, the milestones for the X-axis are 2012M01 , 2012M06 , 2012M11 , 2013M04 and 2013M09 . Is there any way I can choose how long the distance should be between every milestone? For example, to make it so it shows every year or every half year? This is the code I used

Measurement length for X and Y-axis

由 南笙酒味 提交于 2021-02-04 08:09:02
问题 I wonder if it's possible to change the measurement milestones for graphs created by pandas. In my code the X-axis stands for time and is measured by month, but the measurement milestones are all over the place. In the image below, the milestones for the X-axis are 2012M01 , 2012M06 , 2012M11 , 2013M04 and 2013M09 . Is there any way I can choose how long the distance should be between every milestone? For example, to make it so it shows every year or every half year? This is the code I used

Measurement length for X and Y-axis

由 笑着哭i 提交于 2021-02-04 08:08:22
问题 I wonder if it's possible to change the measurement milestones for graphs created by pandas. In my code the X-axis stands for time and is measured by month, but the measurement milestones are all over the place. In the image below, the milestones for the X-axis are 2012M01 , 2012M06 , 2012M11 , 2013M04 and 2013M09 . Is there any way I can choose how long the distance should be between every milestone? For example, to make it so it shows every year or every half year? This is the code I used

How to scale the x and y axis equally by log in Seaborn?

由 人走茶凉 提交于 2021-02-04 07:53:01
问题 I want to create a regplot with a linear regression in Seaborn and scale both axes equally by log, such that the regression stays a straight line. An example: import matplotlib.pyplot as plt import seaborn as sns some_x=[0,1,2,3,4,5,6,7] some_y=[3,5,4,7,7,9,9,10] ax = sns.regplot(x=some_x, y=some_y, order=1) plt.ylim(0, 12) plt.xlim(0, 12) plt.show() What I get: If I scale the x and y axis by log, I would expect the regression to stay a straight line. What I tried: import matplotlib.pyplot as

Python package to plot two heatmaps in one (split each square into two triangles)

由 狂风中的少年 提交于 2021-02-04 06:57:51
问题 I've been searching around but couldn't find an easy solution to plot two heatmaps in one graphic by having each square in the heatmap split into two triangles (similar to the attached graphic I saw in a paper). Does anybody know a Python package that is able to do this? I tried seaborn but I don't think it has an easy way to achieve this. Thank you for your time! -Peter 回答1: plt.tripcolor colors a mesh of triangles similar to how plt.pcolormesh colors a rectangular mesh. Also similar to

Python package to plot two heatmaps in one (split each square into two triangles)

由 陌路散爱 提交于 2021-02-04 06:53:24
问题 I've been searching around but couldn't find an easy solution to plot two heatmaps in one graphic by having each square in the heatmap split into two triangles (similar to the attached graphic I saw in a paper). Does anybody know a Python package that is able to do this? I tried seaborn but I don't think it has an easy way to achieve this. Thank you for your time! -Peter 回答1: plt.tripcolor colors a mesh of triangles similar to how plt.pcolormesh colors a rectangular mesh. Also similar to

[Python图像处理] 三十六.OpenCV图像几何变换万字详解（平移缩放旋转、镜像仿射透视）

由 北慕城南 提交于 2021-02-02 08:22:22
该系列文章是讲解Python OpenCV图像处理知识，前期主要讲解图像入门、OpenCV基础用法，中期讲解图像处理的各种算法，包括图像锐化算子、图像增强技术、图像分割等，后期结合深度学习研究图像识别、图像分类应用。希望文章对您有所帮助，如果有不足之处，还请海涵~ 前面一篇文章介绍了OpenCV图像处理入门知识、算数逻辑运算与图像融合。这篇文章将介绍图像几何变换，包括：图像平移变换、图像缩放变换、图像旋转变换、图像镜像变换、图像仿射变换和图像透视变换，万字长文整理，希望对您有所帮助。 同时，该部分知识均为作者查阅资料撰写总结，并且开设成了收费专栏，为小宝赚点奶粉钱，感谢您的抬爱。当然如果您是在读学生或经济拮据，可以私聊我给你每篇文章开白名单，或者转发原文给你，更希望您能进步，一起加油喔~ https://github.com/eastmountyxz/ImageProcessing-Python 文章目录 一.图像几何变换概述 二.图像平移变换 三.图像缩放变换 四.图像旋转变换 五.图像镜像变换 六.图像仿射变换 七.图像透视变换 八.总结 前文参考： [Python图像处理] 一.图像处理基础知识及OpenCV入门函数 [Python图像处理] 二.OpenCV+Numpy库读取与修改像素 [Python图像处理] 三.获取图像属性、兴趣ROI区域及通道处理
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