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- Shorter repr for DataArrays with many coordinates & dims · 3 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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272669140 | https://github.com/pydata/xarray/issues/680#issuecomment-272669140 | https://api.github.com/repos/pydata/xarray/issues/680 | MDEyOklzc3VlQ29tbWVudDI3MjY2OTE0MA== | shoyer 1217238 | 2017-01-15T02:35:24Z | 2017-01-15T02:35:24Z | MEMBER | I have a fix for this up for review in #1207 |
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Shorter repr for DataArrays with many coordinates & dims 122384593 | |
165985090 | https://github.com/pydata/xarray/issues/680#issuecomment-165985090 | https://api.github.com/repos/pydata/xarray/issues/680 | MDEyOklzc3VlQ29tbWVudDE2NTk4NTA5MA== | fmaussion 10050469 | 2015-12-19T13:44:28Z | 2015-12-19T13:44:28Z | MEMBER | I wonder if there should be a repr of values at all. I actually like the way xray displays netcdf variables when they are not yet read out of the file. See:
to be compared to: ``` python netcdf = xray.open_dataset('./data/ERA-Int-MonthlyAvg-4D-UVWZ.nc') netcdf.z.copy() <xray.DataArray 'z' (month: 12, level: 15, latitude: 241, longitude: 480)> array([[[[ 1.88768500e+05, 1.88769000e+05, 1.88768500e+05, ..., 1.88769000e+05, 1.88768500e+05, 1.88769000e+05], [ 1.88901000e+05, 1.88902500e+05, 1.88903000e+05, ..., 1.88898000e+05, 1.88899000e+05, 1.88900500e+05], [ 1.89048500e+05, 1.89051000e+05, 1.89052500e+05, ..., 1.89042000e+05, 1.89044000e+05, 1.89046500e+05], ..., [ 2.01986500e+05, 2.01987500e+05, 2.01987000e+05, ..., 2.01986500e+05, 2.01986000e+05, 2.01987000e+05], [ 2.01974500e+05, 2.01975000e+05, 2.01975000e+05, ..., 2.01974500e+05, 2.01974500e+05, 2.01975000e+05], [ 2.01957500e+05, 2.01958000e+05, 2.01957500e+05, ..., 2.01958000e+05, 2.01957500e+05, 2.01958000e+05]],
Coordinates: * latitude (latitude) float32 90.0 89.25 88.5 87.75 87.0 86.25 85.5 ... * level (level) int32 50 100 150 200 300 400 500 600 700 750 800 850 ... * month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12 * longitude (longitude) float32 -180.0 -179.25 -178.5 -177.75 -177.0 ... Attributes: units: m2 s-2 long_name: Geopotential standard_name: geopotential number_of_significant_digits: 5 ``` |
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Shorter repr for DataArrays with many coordinates & dims 122384593 | |
164937821 | https://github.com/pydata/xarray/issues/680#issuecomment-164937821 | https://api.github.com/repos/pydata/xarray/issues/680 | MDEyOklzc3VlQ29tbWVudDE2NDkzNzgyMQ== | shoyer 1217238 | 2015-12-15T23:46:31Z | 2015-12-15T23:46:31Z | MEMBER | Yes, I agree! Right now, we outsource the repr for DataArray values by calling NumPy. So fixing this would entail either forking the formatting logic from NumPy or adding our own wrapper. One way to do this might to use |
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Shorter repr for DataArrays with many coordinates & dims 122384593 |
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