area

问题 Closed. This question is not reproducible or was caused by typos. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 1 year ago . Improve this question Suppose we have a=60 and B=60 . I am trying to calculate this area: when I try this: W = ((u^2)* cot(B) + (v^2 * cot(a))/8; I get this error: Incorrect dimensions for raising a matrix to a power. Check that the matrix is square and the power is a scalar. To

问题 I've been struggling to find a solution to find the area of overlap between two curves. I'm not dealing with probability density functions with known parameters but curves obtained from smoothing of empirical data points. The only hint I found is to calculate the area that is not over-lapping as in this code (from here): x <- seq(-6,6,by = 0.01) y1 <- dnorm(x,0,1) y2 <- pnorm(x,1,1.1) f1 <- approxfun(x, y1-y2) f2 <- function(z) abs(f1(z)) dif <- integrate(f2, min(x), max(x)) plot(x,y1,type="l

问题 SO far I have been able to perform medianBlur and Edge Detection, Now I want to o further remove noise from the image, Matlabs region **property functions ** was used to remove all white regions that had a total pixel area of less than the mean pixel area value. How can I implement this on python import matplotlib.image as mpimg import numpy as np import cv2 import os import math from collections import defaultdict from matplotlib import pyplot as plt import imutils #import generalized_hough

来源： https://stackoverflow.com/questions/59754658/voronoi-regions

来源： https://stackoverflow.com/questions/59754658/voronoi-regions

来源： https://stackoverflow.com/questions/59754658/voronoi-regions

问题 Sorry to my noob question, but how can I add a shadow area/color between the upper and lower lines in a seaborn chart? The primary code I've working on is the following: plt.figure(figsize=(18,10)) sns.set(style="darkgrid") palette = sns.color_palette("mako_r", 3) sns.lineplot(x="Date", y="Value", hue='Std_Type', style='Value_Type', sizes=(.25, 2.5), palette = palette, data=tbl4) The idea is to get some effect like below (the example from seaborn website): But I could not replicate the effect

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 2 months ago . Improve this question Can someone explain what is happening at every step? I know the final output is 140.5, but I am unsure why that is. What is happening at each line that is resulting in 140.5? #define PI 3.1 #define calcCircleArea(r) (PI * (r) * (r)) #define calcCylinderArea

问题 I am following the example here and successfully created convex hulls. But I have a question on how to calculate the shared areas between each convex hull in the following figure: Thanks! 回答1: Here's an example to get the intersection of Manhattan and the Bronx. You could use pd.concat() before .overlay() if you want to combine boroughs. import geopandas as gpd nybb_path = gpd.datasets.get_path('nybb') boros = gpd.read_file(nybb_path) boros.set_index('BoroCode', inplace=True) boros.sort_index

问题 The sample project named "color-blob-detection" that comes with the openCV SDK for android can be used to identify an area of a particular color. What I require is to extract that area and save it into the phone memory as a bitmap. This is what I have understood so far: There is a list of contours: List<MatOfPoint> contours = new ArrayList<MatOfPoint>(); Contours are found using: Imgproc.findContours(mDilatedMask, contours, mHierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); This