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I am using a list of integers corresponding to an x,y index of a gridded NetCDF array to extract specific values, the initial code was derived from here. My NetCDF file has a single dimension at a single timestep, which is named TMAX2M. My code written to execute this is as follows (please note that I have not shown the call of netCDF4 at the top of the script): 

# grid point lists
lat = [914]
lon = [2141]

# Open netCDF File
fh = Dataset('/pathtofile/temperaturedataset.nc', mode='r')

# Variable Extraction
point_list = zip(lat,lon)
dataset_list = []
for i, j in point_list:
    dataset_list.append(fh.variables['TMAX2M'][i,j])

print(dataset_list)

The code executes, and the result is as follows: 

masked_array(data=73,mask=False,fill_value=999999,dtype=int16]

The data value here is correct, however I would like the output to only contain the integer contained in "data". The goal is to pass a number of x,y points as seen in the example linked above and join them into a single list.

Any suggestions on what to add to the code to make this achievable would be great.

TornadoEric
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2 Answers2

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The solution to calling the particular value from the x,y list on single step within the dataset can be done as follows: 

dataset_list = []
for i, j in point_list:
    dataset_list.append(fh.variables['TMAX2M'][:][i,j])

The previous linked example contained [0,16] for the indexed variables, [:] can be used in this case.

TornadoEric
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I suggest converting to NumPy array like this:

for i, j in point_list:
    dataset_list.append(np.array(fh.variables['TMAX2M'][i,j]))
msi_gerva
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