pull_requests: 700865417

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700865417 MDExOlB1bGxSZXF1ZXN0NzAwODY1NDE3 5662 closed 0 Limit and format number of displayed dimensions in repr 14371165 When there's a lot of dims, create a new line and continue printing. If there's even more dims that even a few rows can't display them all then limit the number of dims displayed in similar fashion to coordinates. Questions: * Where should this be used? Datasets, dataarrays, dimensions without coords? * Should `dim_summary_limited` be a straight replacement for `dim_summary`? I'm not super familiar with all the places it is used so I'm unsure. * Should we print the number of dims shown and the total number of dims? If yes, then we need to rethink how the dimensions are displayed, as it's not possible with the current style. See the example with short names. <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #5546 - [x] Tests added - [x] Passes `pre-commit run --all-files` - [x] User visible changes (including notable bug fixes) are documented in `whats-new.rst` Test case: ```python import numpy as np import xarray as xr # A few dims with long names: a = np.arange(0, 24) data_vars = dict() for i in a: data_vars[f"long_variable_name_{i}"] = xr.DataArray( name=f"long_variable_name_{i}", data=np.arange(0, 20), dims=[f"long_coord_name_{i}_x"], coords={f"long_coord_name_{i}_x": np.arange(0, 20) * 2}, ) ds0 = xr.Dataset(data_vars) ds0.attrs = {f"attr_{k}": 2 for k in a} print(ds0) <xarray.Dataset> Dimensions: (long_coord_name_0_x: 20, long_coord_name_10_x: 20, long_coord_name_11_x: 20, long_coord_name_12_x: 20, long_coord_name_13_x: 20, long_coord_name_14_x: 20, long_coord_name_15_x: 20, long_coord_name_16_x: 20, long_coord_name_17_x: 20, long_coord_name_18_x: 20, long_coord_name_19_x: 20, long_coord_name_1_x: 20, long_coord_name_20_x: 20, long_coord_name_21_x: 20, long_coord_name_22_x: 20, long_coord_name_23_x: 20, long_coord_name_2_x: 20, long_coord_name_3_x: 20, long_coord_name_4_x: 20, long_coord_name_5_x: 20, long_coord_name_6_x: 20, long_coord_name_7_x: 20, long_coord_name_8_x: 20, long_coord_name_9_x: 20) Coordinates: (12/24) * long_coord_name_0_x (long_coord_name_0_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_1_x (long_coord_name_1_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_2_x (long_coord_name_2_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_3_x (long_coord_name_3_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_4_x (long_coord_name_4_x) int32 0 2 4 6 8 ... 32 34 36 38 * long_coord_name_5_x (long_coord_name_5_x) int32 0 2 4 6 8 ... 32 34 36 38 ... * long_coord_name_18_x (long_coord_name_18_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_19_x (long_coord_name_19_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_20_x (long_coord_name_20_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_21_x (long_coord_name_21_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_22_x (long_coord_name_22_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_23_x (long_coord_name_23_x) int32 0 2 4 6 ... 32 34 36 38 Data variables: (12/24) long_variable_name_0 (long_coord_name_0_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_1 (long_coord_name_1_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_2 (long_coord_name_2_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_3 (long_coord_name_3_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_4 (long_coord_name_4_x) int32 0 1 2 3 4 ... 16 17 18 19 long_variable_name_5 (long_coord_name_5_x) int32 0 1 2 3 4 ... 16 17 18 19 ... long_variable_name_18 (long_coord_name_18_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_19 (long_coord_name_19_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_20 (long_coord_name_20_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_21 (long_coord_name_21_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_22 (long_coord_name_22_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_23 (long_coord_name_23_x) int32 0 1 2 3 ... 16 17 18 19 Attributes: (12/24) attr_0: 2 attr_1: 2 attr_2: 2 attr_3: 2 attr_4: 2 attr_5: 2 ... attr_18: 2 attr_19: 2 attr_20: 2 attr_21: 2 attr_22: 2 attr_23: 2 ``` ```python # Many dims with long names: a = np.arange(0, 200) data_vars = dict() for i in a: data_vars[f"long_variable_name_{i}"] = xr.DataArray( name=f"long_variable_name_{i}", data=np.arange(0, 20), dims=[f"long_coord_name_{i}_x"], coords={f"long_coord_name_{i}_x": np.arange(0, 20) * 2}, ) ds1 = xr.Dataset(data_vars) ds1.attrs = {f"attr_{k}": 2 for k in a} print(ds1) <xarray.Dataset> Dimensions: (long_coord_name_0_x: 20, long_coord_name_100_x: 20, long_coord_name_101_x: 20, long_coord_name_102_x: 20, long_coord_name_103_x: 20, long_coord_name_104_x: 20, ... long_coord_name_94_x: 20, long_coord_name_95_x: 20, long_coord_name_96_x: 20, long_coord_name_97_x: 20, long_coord_name_98_x: 20, long_coord_name_99_x: 20, long_coord_name_9_x: 20) Coordinates: (12/200) * long_coord_name_0_x (long_coord_name_0_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_1_x (long_coord_name_1_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_2_x (long_coord_name_2_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_3_x (long_coord_name_3_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_4_x (long_coord_name_4_x) int32 0 2 4 6 ... 32 34 36 38 * long_coord_name_5_x (long_coord_name_5_x) int32 0 2 4 6 ... 32 34 36 38 ... * long_coord_name_194_x (long_coord_name_194_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_195_x (long_coord_name_195_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_196_x (long_coord_name_196_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_197_x (long_coord_name_197_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_198_x (long_coord_name_198_x) int32 0 2 4 6 ... 34 36 38 * long_coord_name_199_x (long_coord_name_199_x) int32 0 2 4 6 ... 34 36 38 Data variables: (12/200) long_variable_name_0 (long_coord_name_0_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_1 (long_coord_name_1_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_2 (long_coord_name_2_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_3 (long_coord_name_3_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_4 (long_coord_name_4_x) int32 0 1 2 3 ... 16 17 18 19 long_variable_name_5 (long_coord_name_5_x) int32 0 1 2 3 ... 16 17 18 19 ... long_variable_name_194 (long_coord_name_194_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_195 (long_coord_name_195_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_196 (long_coord_name_196_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_197 (long_coord_name_197_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_198 (long_coord_name_198_x) int32 0 1 2 3 ... 17 18 19 long_variable_name_199 (long_coord_name_199_x) int32 0 1 2 3 ... 17 18 19 Attributes: (12/200) attr_0: 2 attr_1: 2 attr_2: 2 attr_3: 2 attr_4: 2 attr_5: 2 ... attr_194: 2 attr_195: 2 attr_196: 2 attr_197: 2 attr_198: 2 attr_199: 2 ``` ```python # Many dims with short names: data_vars = dict() for i in a: data_vars[f"n_{i}"] = xr.DataArray( name=f"n_{i}", data=np.arange(0, 20), dims=[f"{i}_x"], coords={f"{i}_x": np.arange(0, 20) * 2}, ) ds2 = xr.Dataset(data_vars) ds2.attrs = {f"attr_{k}": 2 for k in a} print(ds2) <xarray.Dataset> Dimensions: (0_x: 20, 100_x: 20, 101_x: 20, 102_x: 20, 103_x: 20, 104_x: 20, 105_x: 20, 106_x: 20, 107_x: 20, 108_x: 20, 109_x: 20, 10_x: 20, 110_x: 20, 111_x: 20, 112_x: 20, 113_x: 20, 114_x: 20, 115_x: 20, 116_x: 20, 117_x: 20, 118_x: 20, 119_x: 20, 11_x: 20, 120_x: 20, 121_x: 20, 122_x: 20, 123_x: 20, 124_x: 20, 125_x: 20, 126_x: 20, 127_x: 20, 128_x: 20, 129_x: 20, 12_x: 20, 130_x: 20, 131_x: 20, ... 71_x: 20, 72_x: 20, 73_x: 20, 74_x: 20, 75_x: 20, 76_x: 20, 77_x: 20, 78_x: 20, 79_x: 20, 7_x: 20, 80_x: 20, 81_x: 20, 82_x: 20, 83_x: 20, 84_x: 20, 85_x: 20, 86_x: 20, 87_x: 20, 88_x: 20, 89_x: 20, 8_x: 20, 90_x: 20, 91_x: 20, 92_x: 20, 93_x: 20, 94_x: 20, 95_x: 20, 96_x: 20, 97_x: 20, 98_x: 20, 99_x: 20, 9_x: 20) Coordinates: (12/200) * 0_x (0_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 1_x (1_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 2_x (2_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 3_x (3_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 4_x (4_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 * 5_x (5_x) int32 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 ... * 194_x (194_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 195_x (195_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 196_x (196_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 197_x (197_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 198_x (198_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 * 199_x (199_x) int32 0 2 4 6 8 10 12 14 16 ... 22 24 26 28 30 32 34 36 38 Data variables: (12/200) n_0 (0_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_1 (1_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_2 (2_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_3 (3_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_4 (4_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_5 (5_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ... n_194 (194_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_195 (195_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_196 (196_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_197 (197_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_198 (198_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 n_199 (199_x) int32 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Attributes: (12/200) attr_0: 2 attr_1: 2 attr_2: 2 attr_3: 2 attr_4: 2 attr_5: 2 ... attr_194: 2 attr_195: 2 attr_196: 2 attr_197: 2 attr_198: 2 attr_199: 2 ``` ```python # DataArray with many dimensions: dims = {f"dim_{v}": 2 for v in np.arange(12)} a = xr.DataArray( name="LongDataArrayName", data=np.random.randn(*dims.values()), dims=dims.keys(), coords={k: np.arange(v) * (i + 1) for i, (k, v) in enumerate(dims.items())}, ) print(a) <xarray.DataArray 'LongDataArrayName' (dim_0: 2, dim_1: 2, dim_2: 2, dim_3: 2, dim_4: 2, dim_5: 2, dim_6: 2, dim_7: 2, dim_8: 2, dim_9: 2, dim_10: 2, dim_11: 2)> array([[[[[[[[[[[[ 8.28296160e-01, 2.08993090e-01], [ 8.70468836e-01, 8.90423004e-01]], [[ 7.34784427e-01, 2.05408058e-01], [-8.57071909e-02, 8.44265228e-01]]], [[[-9.35953498e-01, -1.28911601e+00], [ 1.10041466e+00, 6.65778297e-02]], [[-1.20951652e+00, 6.75763964e-01], [-4.71836513e-02, 9.06088516e-01]]]], [[[[ 1.59629635e+00, 7.32189004e-01], [-3.93944434e-01, 2.46067012e+00]], [[ 1.20534658e-01, -1.10855175e+00], [ 1.75768289e+00, 1.82771876e+00]]], ... [[[ 1.24664897e+00, 1.72548620e+00], [-7.64230130e-02, -7.96243220e-01]], [[-7.02358327e-01, 2.20921513e+00], [-7.45919399e-01, 8.16166442e-01]]]], [[[[-1.06278662e+00, -3.01061594e-01], [-2.68674730e-01, 7.61941899e-01]], [[-7.40916926e-01, 1.85122750e+00], [-5.42460065e-02, -7.57741769e-01]]], [[[-4.12356234e-02, 7.41777992e-01], [-1.36243505e+00, -1.25845181e+00]], [[-7.42535368e-01, 1.13262286e-01], [ 1.03699306e+00, -8.51127899e-01]]]]]]]]]]]]) Coordinates: * dim_0 (dim_0) int32 0 1 * dim_1 (dim_1) int32 0 2 * dim_2 (dim_2) int32 0 3 * dim_3 (dim_3) int32 0 4 * dim_4 (dim_4) int32 0 5 * dim_5 (dim_5) int32 0 6 * dim_6 (dim_6) int32 0 7 * dim_7 (dim_7) int32 0 8 * dim_8 (dim_8) int32 0 9 * dim_9 (dim_9) int32 0 10 * dim_10 (dim_10) int32 0 11 * dim_11 (dim_11) int32 0 12 ``` ```python # DataArray with many dimensions but no coords: dims = {f"dim_{v}": 2 for v in np.arange(12)} a = xr.DataArray( name="LongDataArrayName", data=np.random.randn(*dims.values()), dims=dims.keys(), ) print(a) <xarray.DataArray 'LongDataArrayName' (dim_0: 2, dim_1: 2, dim_2: 2, dim_3: 2, dim_4: 2, dim_5: 2, dim_6: 2, dim_7: 2, dim_8: 2, dim_9: 2, dim_10: 2, dim_11: 2)> array([[[[[[[[[[[[ 2.53218063e-02, -2.01034380e+00], [ 3.07624042e-01, 1.82085569e-01]], [[ 1.23998647e+00, 2.80961964e-01], [ 5.22623248e-01, -2.10621456e-01]]], [[[ 1.55794218e+00, -1.32803310e+00], [-7.41474289e-01, -3.35995545e-01]], [[ 9.96489723e-03, -1.84197059e-01], [-1.24173835e+00, 4.94205388e-01]]]], [[[[-2.11962358e-01, 1.18012909e+00], [-4.62991218e-01, -9.49171994e-01]], [[ 3.90534280e-01, -2.63453002e+00], [ 3.57944636e-01, 2.16335768e-01]]], ... [[[-1.11275429e+00, -9.33574221e-01], [ 8.62574702e-01, 1.14185983e+00]], [[ 1.36795402e+00, 1.14331852e+00], [ 5.96785305e-01, 1.47307855e+00]]]], [[[[ 1.95270558e+00, -7.76150298e-01], [ 2.05301468e+00, -1.15633640e+00]], [[-9.45507288e-01, 1.21096830e+00], [ 1.59340121e+00, -3.60261023e-01]]], [[[ 2.25343528e+00, -2.84332626e-01], [ 1.86644712e-01, -2.78371182e-01]], [[-8.86245009e-01, -4.00356195e-01], [-2.44036388e-01, -1.53543170e+00]]]]]]]]]]]]) Dimensions without coordinates: dim_0, dim_1, dim_2, dim_3, dim_4, dim_5, dim_6, dim_7, dim_8, dim_9, dim_10, dim_11 ``` 2021-08-01T09:12:24Z 2022-08-12T09:07:49Z 2022-01-03T17:38:49Z 2022-01-03T17:38:48Z be4b9809b47e1816dbf6a37a263aeb77df95e6b7     0 be49eb7e442c3efbda6a7a47ad7a97130fd82223 2694046c748a51125de6d460073635f1d789958e MEMBER   13221727 https://github.com/pydata/xarray/pull/5662  

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