issues: 244702576
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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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| 244702576 | MDU6SXNzdWUyNDQ3MDI1NzY= | 1484 | Matrix cross product in xarray | 10137 | closed | 0 | 4 | 2017-07-21T15:21:37Z | 2017-07-24T16:36:22Z | 2017-07-24T16:36:22Z | NONE | Hi I am new to xarray and need some advice on one task. I need to do a cross product calculation using variables from a netcdf file and write the output to a new netcdf file. I feel this could be done using netcdf-python and pandas, but I hope to use xarray to simplify the task. My code will be something like this: ds = xr.open_dataset(NC_FILE) var1 = ds['VAR1'] var2 = ds['VAR2'] var3 = ds['VAR3'] var4 = ds['VAR4'] var1-4 above will have dimensions [latitude, longitude]. I will use var1-4 to generate a matrix of dimensions [Nlat, Nlon, M], something like: [var1, var1-var2, var1-var3, (var1-var2)*np.cos(var4)] (here, M=4). My question here is, how do I build this matrix in xarray Dataset? Since this matrix will be eventually used to cross product with another matrix (pd.DataFrame) of dimensions [M, K], is it better to convert var1-4 to pd.DataFrame first? Following code will be like this: matrix = [var1, var1-var2, var1-var3, (var1-var2)*np.cos(var4)] # Nlat x Nlon x M factor = pd.read_csv(somefile) # M x K result = pd.DataFrame.dot(matrix,factor) # Nlat x Nlon x K result2 = xr.Dataset(result) result2.to_netcdf(outfile) Can someone show me the correct code to build the Nlat x Nlon x M matrix? Can the cross product be done in xr.Dataset to avoid conversion to and from pd.DataFrame? Thank you, Xin |
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completed | 13221727 | issue |