mask

This question already has an answer here: Plot only on continent in matplotlib 5 answers I am trying to plot 1x1 degree data on a matplotlib.Basemap , and I want to fill the ocean with white. However, in order for the boundaries of the ocean to follow the coastlines drawn by matplotlib , the resolution of the white ocean mask should be much higher than the resolution of my data. After searching around for a long time I tried the two possible solutions: (1) maskoceans() and is_land() functions, but since my data is lower resolution than the map drawn by basemap it does not look good on the

Hi Everyone (this is my first post), I am trying to figure a way of cropping a polygon out of an image. I have been reading other similar code. It seems that most code is based around the following process: Resize the image to fit the width and height of the polygon shape, Create a blank image of an unusual colour the same size, Overlay transparent pixels in the shape of the polygon, Overlay that on to the resized image Set the unusual colour to be transparent... My problem is I do not want the code to be reliant on the unusual colour not being in the original image. Does anyone have a better

Here is a simplified description: Imagine that I'm given a View class that draws a picture of a wall and I want to draw it with a window cut out. Assume that I extend that View class and override its dispatchDraw() method to do the following. First draw the background if any to be seen through the window. Next I want to mask out the rectangular window region somehow and then call super.dispatchDraw(). Finally I want to remove the mask and draw a person standing at the window so that they are painted over both the background and the wall. How can I do this? Here is some code that seems close to

I have array: a = np.array([[ 0, 1, 2, 0, 0, 0], [ 0, 4, 1, 35, 0, 10], [ 0, 0, 5, 4, 0, 4], [ 1, 2, 5, 4, 0, 4]]) I need select only from first consecutive 0 in each row: [[ True False False False False False] [ True False False False False False] [ True True False False False False] [ False False False False False False]] I try: a[np.arange(len(a)), a.argmax(1): np.arange(len(a)), [0,0,0]] = True But this is wrong. You can use np.cumsum . Assumption: you are looking for zeros only at the start of each row. a = np.array([[ 0, 1, 2, 0, 0, 0], [ 0, 4, 1, 35, 0, 10], [ 0, 0, 5, 4, 0, 4]]) a

I am developing an App on xCode with Swift. My screen has an Image of an animal (outlet "backImage"), over this image I have a view (outlet "coverView"), color black, which covers all the screen. So so far you can't see the animal image, because the "coverView" is in front of it. Then I have another view (outlet "maskView") which is smaller and it's over the big view "coverView". What I want is to use this "maskView" as mask and therefor see the "backImage" through it, like a window. Is there anyone out there able to figure this out? Here is my screen, I want to see the woman character behind

I have a 3-dimensional array that I want to mask using a 2-dimensional array that has the same dimensions as the two rightmost of the 3-dimensional array. Is there a way to do this without writing the following loop? import numpy as np nx = 2 nt = 4 field3d = np.random.rand(nt, nx, nx) field2d = np.random.rand(nx, nx) field3d_mask = np.zeros(field3d.shape, dtype=bool) for t in range(nt): field3d_mask[t,:,:] = field2d > 0.3 field3d = np.ma.array(field3d, mask=field3d_mask) print field2d print field3d Without the loop you could write it as: field3d_mask[:,:,:] = field2d[np.newaxis,:,:] > 0.3 For