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How to fit Matplotlib's stock_img() with Cartopy's NearsidePerspective projection

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1

I am trying to use Cartopy's proejction NearsidePerspective, but overlaping with the real Earth image provided by Matplotlib, and zooming in a bit by lowering the satellite_height parameter. It appears that Cartopy is not able to trim the image properly for this specific type of setting. The image is displayed still oustide of what one would expect to be the map boundaries.

import cartopy.crs as ccrs
import matplotlib.pyplot as plt

fig=plt.figure(figsize=(10,10))

# Set Projection
height=3000000 
#height=35785831 # this is the default height
projection=ccrs.NearsidePerspective(central_longitude=120,
 central_latitude=78,
 satellite_height=height)
# Draw 
ax = plt.axes(projection=projection)
ax.stock_img()
ax.coastlines(resolution='50m')
plt.show()

How can I combine Matplotlib's stock_img() and this configuration of NearsidePerspective to work properly? Or what would be an alternative way to get the result desired?

I am using Python 3.6 on Jupyter Notebook, Matplotlib 3.0.2, and Cartopy 0.16.0.

python matplotlib map-projections cartopy

share|improve this question

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges

• 
  
  
  

  
  2
  

  
  
  
  
  
  

  
  
  For me the map image is cropped correctly. I'm using Python 3.7 on a mac, with matplotlib version 3.0.3 and cartopy version 0.17.0.
  
  – Thomas Kühn
  Mar 28 at 11:04
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  As @ThomasKühn says, it works as expected.
  
  – swatchai
  Mar 28 at 11:10
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Ok, then it is just probably a local setup/version problem. Thank you for the comments. Would you like to answer the question, pasting the correct image? Or should I just delete the question?
  
  – ouranos
  Mar 28 at 11:17
  

  
  
  
  


• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Let's leave it as a question. Especially if you can figure out what exactly caused the problem for you and how to fix it (be it a version upgrade or a setup in Jupyter), you can go ahead and edit my answer (I'll make it a community wiki).
  
  – Thomas Kühn
  Mar 28 at 11:25
  
  

  
  
  
  

add a comment
 | 

1

I am trying to use Cartopy's proejction NearsidePerspective, but overlaping with the real Earth image provided by Matplotlib, and zooming in a bit by lowering the satellite_height parameter. It appears that Cartopy is not able to trim the image properly for this specific type of setting. The image is displayed still oustide of what one would expect to be the map boundaries.

import cartopy.crs as ccrs
import matplotlib.pyplot as plt

fig=plt.figure(figsize=(10,10))

# Set Projection
height=3000000 
#height=35785831 # this is the default height
projection=ccrs.NearsidePerspective(central_longitude=120,
 central_latitude=78,
 satellite_height=height)
# Draw 
ax = plt.axes(projection=projection)
ax.stock_img()
ax.coastlines(resolution='50m')
plt.show()

How can I combine Matplotlib's stock_img() and this configuration of NearsidePerspective to work properly? Or what would be an alternative way to get the result desired?

I am using Python 3.6 on Jupyter Notebook, Matplotlib 3.0.2, and Cartopy 0.16.0.

python matplotlib map-projections cartopy

share|improve this question

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges

• 
  
  
  

  
  2
  

  
  
  
  
  
  

  
  
  For me the map image is cropped correctly. I'm using Python 3.7 on a mac, with matplotlib version 3.0.3 and cartopy version 0.17.0.
  
  – Thomas Kühn
  Mar 28 at 11:04
  
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  As @ThomasKühn says, it works as expected.
  
  – swatchai
  Mar 28 at 11:10
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Ok, then it is just probably a local setup/version problem. Thank you for the comments. Would you like to answer the question, pasting the correct image? Or should I just delete the question?
  
  – ouranos
  Mar 28 at 11:17
  

  
  
  
  


• 
  
  
  

  
  1
  

  
  
  
  
  
  

  
  
  Let's leave it as a question. Especially if you can figure out what exactly caused the problem for you and how to fix it (be it a version upgrade or a setup in Jupyter), you can go ahead and edit my answer (I'll make it a community wiki).
  
  – Thomas Kühn
  Mar 28 at 11:25
  
  

  
  
  
  

add a comment
 | 

I am trying to use Cartopy's proejction NearsidePerspective, but overlaping with the real Earth image provided by Matplotlib, and zooming in a bit by lowering the satellite_height parameter. It appears that Cartopy is not able to trim the image properly for this specific type of setting. The image is displayed still oustide of what one would expect to be the map boundaries.

import cartopy.crs as ccrs
import matplotlib.pyplot as plt

fig=plt.figure(figsize=(10,10))

# Set Projection
height=3000000 
#height=35785831 # this is the default height
projection=ccrs.NearsidePerspective(central_longitude=120,
 central_latitude=78,
 satellite_height=height)
# Draw 
ax = plt.axes(projection=projection)
ax.stock_img()
ax.coastlines(resolution='50m')
plt.show()

How can I combine Matplotlib's stock_img() and this configuration of NearsidePerspective to work properly? Or what would be an alternative way to get the result desired?

I am using Python 3.6 on Jupyter Notebook, Matplotlib 3.0.2, and Cartopy 0.16.0.

python matplotlib map-projections cartopy

share|improve this question

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges

import cartopy.crs as ccrs
import matplotlib.pyplot as plt

fig=plt.figure(figsize=(10,10))

# Set Projection
height=3000000 
#height=35785831 # this is the default height
projection=ccrs.NearsidePerspective(central_longitude=120,
 central_latitude=78,
 satellite_height=height)
# Draw 
ax = plt.axes(projection=projection)
ax.stock_img()
ax.coastlines(resolution='50m')
plt.show()

share|improve this question

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges

share|improve this question

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges

asked Mar 28 at 10:20

ouranosouranos

14477 bronze badges