matplotlib-basemap

By using ax.axhline & ax.axvline I can plot the grid network shows like this: http://i4.tietuku.com/e90652c9a56b5e61.png the code are reproduced here: lon_grid = np.linspace(113.5,115.49,36) lat_grid = np.linspace(37.40,38.78,30) lon_grid,lat_grid = np.linspace(xc1,xc2,36), np.linspace(yc1,yc2,30) for i in range(0,len(lon_grid),1): ax.axvline(x=lon_grid[i], linestyle='-', color='black', linewidth=0.75, zorder=3) for i in range(0,len(lat_grid),1): ax.axhline(y=lat_grid[i], linestyle='-', color='black', linewidth=0.75, zorder=3) Here is my question Can I use pcolor/pcolrmesh to just draw the

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

Plotting a very, very simple map of only europe in matplotlib / basemap takes so much time ( around 10 seconds! ). This is just unreal!? Setting of resolution is only "l" (low). Here is the very simple code: import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt from mpl_toolkits.basemap import Basemap m = Basemap(projection='stere',lon_0=5,lat_0=90.0,rsphere=6371200.,\ llcrnrlon=-25.0,urcrnrlon=72.0,llcrnrlat=26.0,urcrnrlat=65.0,resolution='l') m.drawcoastlines(linewidth=0.2) m.drawcountries(linewidth=0.2) plt.savefig('/var/www/map.png') I need to plot hundreds of these maps

I'm having an issue plotting an RGB image using Python's Basemap module with latitude and longitude data. Now, I am able to make the plots that I want, but the problem is how slow it is, since it is able to plot single channel data much faster than the RGB data, and in general, plotting RGB images on their own is also fast. Since I have lat/lon data, that is where things get complicated. I've checked out the solution to this problem: How to plot an irregular spaced RGB image using python and basemap? which is how I got to where I am right now. It essentially comes down to the following issue.

When I plot the pcolormesh plot use the colormap from matplotlib.cm (like "jet" , "Set2" , etc), I can use: cMap = plt.cm.get_cmap("jet",lut=6) The colorbar shows like this: But if I want to call the colormap from the Basemap package (like GMT_drywet , GMT_no_green , etc). I can't use plt.cm,get_cmap to get these colormap and divide them. Does mpl_toolkits.basemap.cm have a similiar function like lut ? As long as the plot you are making has discrete color values (e.g. contour or contourf ), then colorbar should automatically generate a colorbar with discrete steps. Here's a plot based on the

I'm in the process of rewriting a coworkers IDL code into python and am coming up with some differences that I'm confused about. According to other SO questions and mailing list threads I've found if you use scipy.ndimage.interpolation.map_coordinates and specify order=1 it is supposed to do bilinear interpolation. When comparing results between the IDL code (run in GDL) and python (map_coordinates) I got different results. Then I tried using mpl_toolkits.basemap.interp and I got the same result as the IDL code. Below is a simple example that shows what is wrong. Could someone help me figure