ADD: Utility to subset a radar volume for the column above a location #1113
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given the lat/lon of the location. Return is a dictionary containing all radar object fields for the column above the location, as well as, x,y,z gates for the column. Tested with ppi (nexrad) and rhi (csapr) scans
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Thanks for the PR @jrobrien91 ! I had some minor suggestions, did you plan on including unittests as well? |
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Thanks for taking the time to add this new functionality @jrobrien91 !! I added a few comments - let me know if you have any questions!
Also, I agree with @zssherman here - unit tests with this PR would be great!
pyart/util/columnsect.py
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| from ..core.transforms import antenna_vectors_to_cartesian | ||
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| def sphere_distance(rad_lat, tar_lat, rad_lon, tar_lon): |
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Can you spell out radar_latitude, target_latitude... I think this would make it more clear to the end user in terms of the API.
pyart/util/columnsect.py
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| check_lat(tar_lat) | ||
| check_lon(rad_lon) | ||
| check_lon(tar_lon) | ||
| # convert latitude/longitudes to radians |
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I think spaces would help in between each of these sections
pyart/util/columnsect.py
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| return distance | ||
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| def for_azimuth(rad_lat, tar_lat, rad_lon, tar_lon): |
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Same as the previous comment - more clear variable names would help
pyart/util/columnsect.py
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| check_lat(tar_lat) | ||
| check_lon(rad_lon) | ||
| check_lon(tar_lon) | ||
| # convert latitude/longitudes to radians |
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Same comment as above in terms of separating sections
pyart/util/columnsect.py
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| return azimuth | ||
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| def get_fields_latlon(radar, lat, lon): |
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Could you make this get_field_location? Ans spell out latitude/longitude?
| column = dict(meta) | ||
| column.update(moment) | ||
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| return column |
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this would be a good point to convert to either an Xarray.Dataset or a pyart.core.Radar object...
pyart/util/columnsect.py
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| for i in range(len(ray)): | ||
| tar_gate = np.argmin(abs(rhidis[i, 1:] - (dis))) | ||
| for key in moment: | ||
| moment[key].append(radar.fields[key]['data'][ray[i], tar_gate]) | ||
| # fill the meta dictionary for further analysis | ||
| meta['xgate'].append(rhi_x[i, tar_gate]) | ||
| meta['ygate'].append(rhi_y[i, tar_gate]) | ||
| meta['zgate'].append(rhi_z[i, tar_gate]) |
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How long does this usually take using this for loop?
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Working through the other comments and changing output to an Xarray Dataset, but the timing is:
with a NEXRAD Level 2 file - 0.0005 sec
with a CSAPR-2 RHI file - 0.0006 sec
pyart/util/columnsect.py
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| if (isinstance(lat, int) or isinstance(lat, float) or | ||
| isinstance(lat, np.floating)) is True: | ||
| if (lat <= -90) or (lat >= 90): | ||
| raise ValueError("latitude not valid") |
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Can you add a more descriptive error here? Ex. latitude not between -90 to 90, need to convert to values between -90 and 180
pyart/util/columnsect.py
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| if (lat <= -90) or (lat >= 90): | ||
| raise ValueError("latitude not valid") | ||
| else: | ||
| raise TypeError("latitude type not valid") |
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Same thing here - maybe mention that lat needs to be an int or float? Does this support a list of lats? Maybe add a check for that.
pyart/util/columnsect.py
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| """ | ||
| Function to check if input latitude is valid for type and value | ||
| """ | ||
| if (isinstance(lon, int) or isinstance(lon, float) or |
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Same as the lat function - and change these to check_lat, check_lon
Still working on transfering output to an xarry object
…ion functions within columnsect.py utility
…nclude changing the output of get_field_location form a dictionary to xarray Datatset.
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Looks fantastic! Thanks for all your hard work on this @jrobrien91
Given the lat/lon of the location, return a dictionary containing all radar object fields for the column above the location, as well as, x,y,z gates for the column. Tested with ppi (nexrad) and rhi (csapr) scans.