Hello, I encountered a problem when trying to use a "for loop" to get a sequence of different interpolation planes.
So I have tried this line, which works fine:
p_certain_level = wrf.interplevel(p,z,2893.9905)
I can plot this to get:
I also have other different height values that I want to plot. So I write a list:
height = [588.0741, 1751.7858, 2893.9905, 4019.048, 5129.8022, 6228.1494, ... ]
Then I write the for loop:
for a in range(0,3): ## here i'm just trying the first three heights, not the whole list
ss = wrf.interplevel(p, z, float(height[a]))
print(ss)
This returns something like:
As you can see, there are a lot of nan in the printed array. I also tried to plot the result:
As you can see, the middle values are kept unchanged. However, the other values are all missing. I'm not sure what's happening that leads to interplevel method not working. I've tried a few times and believe this is related to list and numpy.array (both list and np.array are producing the same problem).
I've tried wrf.getvar, in which I use a "timeidx = blabla_list [3]", which turns out to work properly.
Hello, I encountered a problem when trying to use a "for loop" to get a sequence of different interpolation planes.
So I have tried this line, which works fine: p_certain_level = wrf.interplevel(p,z,2893.9905)
I can plot this to get:
I also have other different height values that I want to plot. So I write a list: height = [588.0741, 1751.7858, 2893.9905, 4019.048, 5129.8022, 6228.1494, ... ]
Then I write the for loop: for a in range(0,3): ## here i'm just trying the first three heights, not the whole list ss = wrf.interplevel(p, z, float(height[a])) print(ss)
This returns something like:
As you can see, there are a lot of nan in the printed array. I also tried to plot the result:
As you can see, the middle values are kept unchanged. However, the other values are all missing. I'm not sure what's happening that leads to interplevel method not working. I've tried a few times and believe this is related to list and numpy.array (both list and np.array are producing the same problem).
I've tried wrf.getvar, in which I use a "timeidx = blabla_list [3]", which turns out to work properly.