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Feat/obs interpolated position #104

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496483f
Add util to perform robust interpolation
jerabaul29 Sep 17, 2024
e667560
Add util to perform robust interpolation
jerabaul29 Sep 17, 2024
5df55d9
Handle NaT in interpolation time target
jerabaul29 Sep 17, 2024
d379f75
Handle NaT in interpolation time target
jerabaul29 Sep 17, 2024
de1dab3
Add the interpolated lat and lon at wave measurement to the omb xr
jerabaul29 Sep 17, 2024
87bb551
Make tests pass
jerabaul29 Oct 28, 2024
9ee375e
traj: add to_1d
gauteh Nov 12, 2024
54b5c7d
traj: add gridobs abstract method
gauteh Nov 12, 2024
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2 changes: 2 additions & 0 deletions docs/source/api.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -121,10 +121,12 @@ Methods
Dataset.traj.convex_hull_contains_point
Dataset.traj.get_area_convex_hull
Dataset.traj.gridtime
Dataset.traj.gridobs
Dataset.traj.seltime
Dataset.traj.iseltime
Dataset.traj.is_1d
Dataset.traj.is_2d
Dataset.traj.to_1d
Dataset.traj.to_2d
Dataset.traj.condense_obs

Expand Down
16 changes: 16 additions & 0 deletions tests/test_convert_datalayout.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,5 @@
from numpy.testing import assert_almost_equal
import pytest
import numpy as np
import trajan as ta
import xarray as xr
Expand All @@ -13,3 +14,18 @@ def test_to2d(barents):

b2d = gr.traj.to_2d()
assert b2d.traj.is_2d()

def test_to1d(barents):
# print(barents)
gr = barents.traj.gridtime('1H')
assert gr.traj.is_1d()

gr = gr.traj.to_1d()
assert gr.traj.is_1d()

with pytest.raises(ValueError):
barents.traj.to_1d()

print('converting to 1d')
gr = barents.isel(trajectory=0).traj.to_1d()
assert gr.traj.is_1d()
26 changes: 23 additions & 3 deletions tests/test_data/csv/omb1.csv
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Original file line number Diff line number Diff line change
@@ -1,6 +1,26 @@
Date Time (UTC),Device,Direction,Payload,Approx Lat/Lng,Payload (Text),Length (Bytes),Credits
12/Nov/2022 04:22:36,2022_DOFI_13,MO,59531f6f6342030000e5c8d83f2b28173e0e243e3ee040004024002e004a005100fe0035030d032a036d058f0762083413b8303e389651e383f06f443fac79fb721443204b4b6bc7590240735de1757f908d8c396ebc5ea2684e675eb0a6dae8fdb3cbf07f478dd780087d8eba4fa06b9fd97bdc850fc10babee930889d374c84ec04adc812ea3000045,"77.20068333333333,-2.26475",,138,3
12/Nov/2022 04:22:08,2022_DOFI_11,MO,59531f6f637e00000028d55a40c1d1083e8599303e5e88a64061004e00330046007d00f3005e02c30b2b22bc34ba362145355c0f5044572e466f6fdc973fab4aa3f985bd7bec8a3c9a29710778caaade8f7055ce5b9677c1bc4daf699ced8586a93acff172e7775d6ab67130922eaef978ca71f65117592a63df719c9a01c2dc91f775e0c7e8fd000045,"70.0308,-15.61395",,138,3
12/Nov/2022 02:31:16,2022_DOFI_13,MO,47fc4643056f631348fb2da085c2fe4645fe6e63f725fc2d8e3cc2fe463ef76e63edf1fc2d2520c2fe4637f06e63a0a6fd2df579c1fe4623e96e636a4efe2d4110c1fe4625e26e6310f7fe2d4e81c0fe45,"76.96878333333333,-6.69125",,81,2
12/Nov/2022 02:29:16,2022_DOFI_13,MT,2447465130323b2457465130343b,,$GFQ02;$WFQ04;,14,1
12/Nov/2022 02:20:16,2022_DOFI_13,MO,,"78.56353333333334,-1.4456333333333333",,0,1
12/Nov/2022 02:22:16,2022_DOFI_13,MO,5932036f6341030000e115f03f5a69133e7505393e9bbae33f450037003b006700f10056028602c5030f06ff096e0aec15a048857cc78aa0bc2d7f87994281839bfd70266231992a895889897b728cac83ffafc6836ab1c1bc7193f2987cdeb8a4d5947db6159738897d834384345c08b08fe6f0b2186f2bbaf4ee4cd4e8fdb7aefc86a49686cf000045,"77.16833333333334,-1.9360166666666667",,138,3
12/Nov/2022 00:22:08,2022_DOFI_13,MO,5913e76e63400300001682e63ff9e1193ede423c3eba56f23f360037002e004d0052008500e9008701fa01d50369082d10c922cb45855b6571ffcbcfb2a0ab82bbb16f935b1d788f85b39fb7b5c2b5c3a392a4f691c2a28c912882af62a95a1c6e209d6bdaaec4f2cbb9a46c734052d17135d5e8fddee8c4c9c195305efdaaaacd91d63ce7e47b000045,"77.16833333333334,-1.9360166666666667",,138,3
11/Nov/2022 23:31:23,2022_DOFI_13,MO,47f64620db6e6318a1ff2d5152c0fe4616d46e63284f002e530fc0fe4603cd6e63c506012e2f60bffe4606c66e631691012ec85dbefe46ffbe6e636814022ebbaabdfe46f6b76e63ba7c022e1371bdfe45,"77.20325,-1.9414833333333332",,81,2
11/Nov/2022 22:22:22,2022_DOFI_13,MO,59f3ca6e633f030000bbb4fc3ff864163e3c33363e43860140290020001f00250036008f007c010f01da019f040e07a90f39164e28557c42fde8fdd2daa7b2eed419c0a086017f449cf972dc58fc51336d9a8c9bcb07ee2c974576c0941b659c8d768f3d8b21becaf5d4aca371d0919b96c4b6a8a656b51184d561c47ec3b0679a389fb0d042bc000045,"77.20201666666667,-2.1031333333333335",,138,3
11/Nov/2022 20:31:21,2022_DOFI_13,MO,47f046e3b06e6368d3022e9e38bdfe46e7a96e63fa30032e0505bdfe46dea26e636b90032ee3fbbcfe46d79b6e6374db032ebffdbcfe46c2946e633e12042ed16ebdfe46ca8d6e63d044042ebd3cbdfe45,"77.20201666666667,-2.1031333333333335",,81,2
11/Nov/2022 20:22:12,2022_DOFI_13,MO,59d4ae6e633e030000771ff13fbcc9153e2aed363e3cc4e53f2d003800320032004a005c003a012302ed025304f10b4518203b7350e86148843bd1d0f6e8fdbdc7b7a2d8b2fd8f2866787852707b8d97b9d7a723999889997469711467526ce08b83b0f8d0279a94ae5fe782e51aad769550b0ced0df73b19b26b7cdc48fa80cadf6a8e06b73a9000045,"77.20201666666667,-2.1031333333333335",,138,3
11/Nov/2022 18:22:17,2022_DOFI_13,MO,59b9926e633d0300002be7dd3f292b1f3eefcf3c3e3dd3064012000d0017001e00260026004c00a0003f01e303b5053309e410841ab32cc4558d812f915c8be8fda9f2758db371136a599aa9bf70778483528bbe97aa93b065ef78226f94819393f9858ab220c5da8211b608c58a8f7396067e615a178070cfa98b7e72eba1cf88ea6c2e947a92000045,"77.20068333333333,-2.26475",,138,3
11/Nov/2022 17:31:21,2022_DOFI_13,MO,47ea46be866e636577042ed495bdfe46b67f6e630fb3042e8f5ebdfe46a2786e63a2db042e0861bdfe46a6716e63ecf3042e1a78bdfe469e6a6e63bc02052ea5a9bdfe4696636e635cfd042e37babdfe45,"77.20325,-1.9414833333333332",,81,2
11/Nov/2022 16:25:44,2022_DOFI_13,MO,5993766e633c030000f668ef3f459b1e3ea82d3c3eaaed0e40200030001a001c0045005a0060009000d9017d023404150ae6112716a63291419273e8fd32cf15c95fd76ed4bebb21cc348d75902e9303606e6a556bcb33838544d6e084f38d4db0bcb7ac76c59e69d578fa5bb593969b911492a9adc6f2aebc8e73604f6d564fad4e9f49acad78000045,"77.23561666666667,-2.27115",,138,3
11/Nov/2022 14:31:11,2022_DOFI_13,MO,47e446855c6e63c90d052e1b23befe4687556e637a35052e30cbbefe467f4e6e631863052e1918bffe4675476e635e84052e4226bffe4662406e6345ab052eae7fbffe4665396e6350cc052e610bc0fe45,"77.20201666666667,-2.1031333333333335",,81,2
11/Nov/2022 14:22:49,2022_DOFI_13,MO,59755a6e633b0300001356c03f3da0243e1558463e1a82014029001d000f001300440077006b007f00b501ee03ac0be415dd112b0e3a0c97254957256f687be780735e69554a5f676c137da8866d9a4aac2f682b6800844f75178d7485247b1f77a684cfedf6c18ab4647ee4771cb9629a6dbf71c96967106258efe8fd79816c6c284b78534993000045,"77.20325,-1.9414833333333332",,138,3
11/Nov/2022 12:23:08,2022_DOFI_13,MO,59523e6e633a0300005778bb3fd86a223e7216433ee080e43f19002c003500160025004700a70034011a02fc0669097009a70f4d1d14240424496aa498c77f255e4052705cde769d88034b407fce79d888f6e857bebdbd91bd249b7971336e1d6913b23597b6862c8a3aa31179b8801293bb69fac1e8fd316a6c607d95b09aa88410a14980936a000045,"77.20201666666667,-2.1031333333333335",,138,3
11/Nov/2022 11:31:28,2022_DOFI_13,MO,47de465e326e63dffc052e16e2c0fe46582b6e636934062e1276c2fe4643246e633685062e74cec3fe46461d6e63f8d7062ea9fdc4fe463d166e63434c072eb27dc5fe46360f6e63bbd7072ee32dc6fe45,"76.9842,4.30105",,81,2
11/Nov/2022 10:22:16,2022_DOFI_13,MO,5932226e6339030000ffb8b93f81b4223e4a50463e378a0e40220022002800210028002a0082001201bf010d034005b5074e093608381acd29a34d515cfe5c86968caef06a566a5e561c3e3e4e004f59522a4d8e4f0f67a255aa42977c6e80e65303631a7029749c7471673d61eb65849773848959eb68a75e626c8575dec1e8fd69a9c1a13aa5000045,"77.23818333333334,-1.9469666666666665",,138,3
11/Nov/2022 08:31:11,2022_DOFI_13,MO,47d84623086e63c269082eb138c7fe4627016e63d611092eb368c8fe461efa6d63c0d1092e82a0c9fe4616f36d6311a50a2e4ab8cafe4604ec6d630c870b2e8764cbfe4605e56d63da570c2e7a9acbfe45,"77.23933333333333,-1.7848333333333333",,81,2
11/Nov/2022 08:22:15,2022_DOFI_13,MO,5913066e6338030000eb8abe3f427e283e2c0b4a3e20b50d4029002400240022002d0045005b00a70049019002130501070708560aa70f8a1f334947770086d66f0958ad51a856348e1a685a5d82a9c1a2415d756a127013a6b784bca28976e766856f3b524b4594703078eca3d3d4c87da9e6e8fd7c9954962fdb08c8c493687bceb49c6fd580000045,"77.23818333333334,-1.9469666666666665",,138,3
11/Nov/2022 06:22:58,2022_DOFI_13,MO,59f2e96d6337030000e10ac93fdeae283eead94f3e24ed79401c002b002600300035002f00680065001601e701b101be020504f706f109130cb219cc432b83436bd2689e398638ea309b2f243d56328d297942123e3332ec2ef42514470f69b75b9c4eba60de3d0431bb299e47db78fd812e5b002e1b5cd9b647703ea4e8fdc5dc92911968d48b000045,"77.23933333333333,-1.7848333333333333",,138,3
11/Nov/2022 05:33:35,2022_DOFI_13,MO,47d246ffdd6d6356250d2e5debcbfe46f6d66d6389fe0d2e3ceccbfe46e2cf6d63eed20e2e70a2cbfe46e6c86d6384b70f2eef1bccfe46dec16d632eaa102e623ccdfe46d6ba6d6331bd112e3ab1cefe45,"77.27313333333333,-1.9525000000000001",,81,2
11/Nov/2022 04:22:12,2022_DOFI_13,MO,59d3cd6d633603000051f9c53f334a233e167f483e8ec716403b0049003e003a003b003b0053009f00b301a7036303a4040f068b0b530fb11cf1406086cdf9c188b45143527767ce8a9b7980432443f869b74b3d5174553a510644e24f924b0a4b4a4ed757555fa1653ebfacb95992a06d216ef2a792d152c88bb1fea44ad2e8fd86ced995d070000045,"77.27313333333333,-1.9525000000000001",,138,3
11/Nov/2022 02:31:11,2022_DOFI_13,MO,47cc46c5b36d63bae6122e4925d0fe46c9ac6d638608142ed446d1fe46bea56d631825152e4595d2fe46b69e6d63da37162e23bcd3fe46a4976d631d42172ea8e7d4fe46a7906d637e36182ea729d6fe45,"77.05806666666666,-6.25185",,81,2
11/Nov/2022 02:22:28,2022_DOFI_13,MO,59b6b16d633503000031acdf3f282c1c3e43343a3ea90e164033003f0063004c0061007b0057009c00a401f6025603cf04b50836187e22ab4ae15df5534ed3e8fde6ca01b5acad05a55285d282a7571f6ad881c24cfe643f6fd95d2b5cfe61d46c016ae2602a61c2398645f2680a77a560fc540e562fa41bc035c88c67215f2aa727b87194996a000045,"77.17703333333333,-4.200616666666667",,138,3
11/Nov/2022 00:22:03,2022_DOFI_13,MO,5994956d6334030000554fc63f17e0213e558b463e843701403a00600065003c002d003d006a00f100bc0116021203a402f605160f83267f4bb36ac9a0c08b1798c2980f85c68e255e59470f4ad94bc9514c8ea2765373ff88bd91728c9e9398818f712f651f727b7c27369451c678b67d0c67ed8fe9ebd4f9f4e375c3a8c862b8d1bee8fd6de2000045,"77.3531,-1.6365666666666667",,138,3
10/Nov/2022 23:31:26,2022_DOFI_13,MO,47c6469e896d63d127192ece9bd7fe4696826d63ea101a2ef60dd9fe46867b6d6374f81a2eb774dafe4686746d6365eb1b2e2c60dbfe46806d6d638ce41c2ef01bdcfe4676666d6380da1d2e8d7adcfe45,"77.3509,-1.96365",,81,2
11 changes: 5 additions & 6 deletions tests/test_read_omb_csv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,11 +7,10 @@ def test_read_csv_omb_default_waves(test_data, tmpdir):
path_to_test_data = test_data / 'csv' / 'omb1.csv'
ds = read_omb_csv(path_to_test_data)

# 1668207637
assert ds.attrs['time_coverage_start'] == '2022-11-12T00:00:37'
assert ds.attrs['time_coverage_start'] == '2022-11-10T21:00:38'
assert ds.attrs['time_coverage_end'] == '2022-11-12T02:30:27'

assert ds.sizes['trajectory'] == 2
assert ds.sizes['trajectory'] == 1
print(ds.time)

# grid dataset
Expand All @@ -21,10 +20,10 @@ def test_read_csv_omb_default_waves(test_data, tmpdir):
ds.to_netcdf(tmpdir / 'test.nc')

ds2 = xr.open_dataset(tmpdir / 'test.nc')
assert ds2.attrs['time_coverage_start'] == '2022-11-12T00:00:37'
assert ds2.attrs['time_coverage_end'] == '2022-11-12T02:30:27'
assert ds.attrs['time_coverage_start'] == '2022-11-10T21:00:38'
assert ds.attrs['time_coverage_end'] == '2022-11-12T02:30:27'

assert ds2.sizes['trajectory'] == 2
assert ds2.sizes['trajectory'] == 1

assert ds == ds2

Expand Down
157 changes: 157 additions & 0 deletions tests/test_utils.py
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@@ -0,0 +1,157 @@
import numpy as np
from trajan.utils import interpolate_variable_to_newtimes


def test_interpolate_variable_to_newtimes_order_0():
times = np.array(
[
np.datetime64("2024-09-17T12:00:00"),
np.datetime64("2024-09-17T20:00:00"),
np.datetime64("2024-09-17T21:00:00"),
np.datetime64("2024-09-18T12:00:00"),
np.datetime64("2024-09-18T13:00:00"),
np.datetime64("2024-09-18T14:00:00"),
np.datetime64("2024-09-18T15:00:00"),
]
)

variable_on_times = np.array(
[
0,
10,
11,
100,
200,
np.nan,
400,
]
)

newtimes = np.array(
[
np.datetime64("NaT"),
np.datetime64("2024-09-17T06:00:00"),
np.datetime64("2024-09-17T11:00:00"),
np.datetime64("2024-09-17T13:00:00"),
np.datetime64("2024-09-17T16:00:00"),
np.datetime64("2024-09-17T19:00:00"),
np.datetime64("2024-09-17T20:00:00"),
np.datetime64("2024-09-17T20:29:00"),
np.datetime64("2024-09-18T13:00:00"),
np.datetime64("2024-09-18T13:30:00"),
np.datetime64("2024-09-18T13:59:00"),
np.datetime64("2024-09-18T15:00:00"),
np.datetime64("NaT"),
np.datetime64("2024-09-18T16:00:00"),
np.datetime64("2024-09-18T20:00:00"),
np.datetime64("NaT"),
]
)

expected = np.array(
[
np.nan,
np.nan,
0,
0,
np.nan,
10,
10,
10,
200,
200,
200,
400,
np.nan,
400,
np.nan,
np.nan,
]
)

result = interpolate_variable_to_newtimes(times, variable_on_times, newtimes, max_order=0)

# print(f"{result}")
# print(f"{expected}")

assert ((result == expected) | (np.isnan(result) & np.isnan(expected))).all()


def test_interpolate_variable_to_newtimes_order_1():
times = np.array(
[
np.datetime64("2024-09-17T12:00:00"),
np.datetime64("2024-09-17T20:00:00"),
np.datetime64("2024-09-17T21:00:00"),
np.datetime64("2024-09-18T12:00:00"),
np.datetime64("2024-09-18T13:00:00"),
np.datetime64("2024-09-18T14:00:00"),
np.datetime64("2024-09-18T15:00:00"),
]
)

variable_on_times = np.array(
[
0,
10,
11,
100,
200,
np.nan,
400,
]
)

newtimes = np.array(
[
np.datetime64("NaT"),
np.datetime64("2024-09-17T06:00:00"),
np.datetime64("2024-09-17T11:00:00"),
np.datetime64("2024-09-17T13:00:00"),
np.datetime64("2024-09-17T16:00:00"),
np.datetime64("2024-09-17T19:00:00"),
np.datetime64("2024-09-17T20:00:00"),
np.datetime64("2024-09-17T20:29:00"),
np.datetime64("2024-09-18T13:00:00"),
np.datetime64("2024-09-18T13:30:00"),
np.datetime64("2024-09-18T14:00:00"),
np.datetime64("2024-09-18T15:00:00"),
np.datetime64("NaT"),
np.datetime64("2024-09-18T16:00:00"),
np.datetime64("2024-09-18T20:00:00"),
np.datetime64("NaT"),
]
)

expected = np.array(
[
np.nan,
np.nan,
0,
0,
np.nan,
10,
10,
10.5,
200,
250,
300,
400,
np.nan,
400,
np.nan,
np.nan,
]
)

result = interpolate_variable_to_newtimes(times, variable_on_times, newtimes, max_order=1)

# print(f"{result}")
# print(f"{expected}")

assert ((np.abs(result - expected) < 0.1) | (np.isnan(result) & np.isnan(expected))).all()


if __name__ == "__main__":
test_interpolate_variable_to_newtimes_order_0()
test_interpolate_variable_to_newtimes_order_1()
37 changes: 37 additions & 0 deletions trajan/readers/omb.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
from .omb_decoder import decode_message
from typing import Union
from .omb_decoder import GNSS_Metadata, Waves_Metadata, Thermistors_Metadata, GNSS_Packet, Waves_Packet, Thermistors_Packet, _BD_YWAVE_NBR_BINS
from ..utils import interpolate_variable_to_newtimes

logger = logging.getLogger(__name__)

Expand Down Expand Up @@ -273,6 +274,24 @@ def read_omb_csv(path_in: Path,
"long_name": "Time for the wave information records."
}),
#
'lat_waves_imu':
xr.DataArray(dims=["trajectory", "obs_waves_imu"],
data=np.nan * np.ones((trajectory, obs_waves_imu)),
attrs={
"_FillValue": "NaN",
"standard_name": "latitude",
"units": "degree_north",
}),
#
'lon_waves_imu':
xr.DataArray(dims=["trajectory", "obs_waves_imu"],
data=np.nan * np.ones((trajectory, obs_waves_imu)),
attrs={
"_FillValue": "NaN",
"standard_name": "longitude",
"units": "degree_east",
}),
#
'accel_energy_spectrum':
xr.DataArray(
dims=["trajectory", "obs_waves_imu", "frequencies_waves_imu"],
Expand Down Expand Up @@ -474,6 +493,24 @@ def read_omb_csv(path_in: Path,
xr_result["T24"][crrt_instrument_idx, crrt_wave_idx] = \
crrt_wave_data.data.Tc

crrt_lat_waves_imu = interpolate_variable_to_newtimes(
xr_result["time"][crrt_instrument_idx, :],
xr_result["lat"][crrt_instrument_idx, :],
xr_result["time_waves_imu"][crrt_instrument_idx, :]
)

xr_result["lat_waves_imu"][crrt_instrument_idx, :] = \
crrt_lat_waves_imu

crrt_lon_waves_imu = interpolate_variable_to_newtimes(
xr_result["time"][crrt_instrument_idx, :],
xr_result["lon"][crrt_instrument_idx, :],
xr_result["time_waves_imu"][crrt_instrument_idx, :]
)

xr_result["lon_waves_imu"][crrt_instrument_idx, :] = \
crrt_lon_waves_imu

xr_result = xr_result.traj.assign_cf_attrs(
creator_name="XX:TODO",
creator_email="XX:TODO",
Expand Down
22 changes: 22 additions & 0 deletions trajan/traj.py
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Original file line number Diff line number Diff line change
Expand Up @@ -666,6 +666,21 @@ def gridtime(self, times, timedim=None) -> xr.Dataset:
A new dataset interpolated to the target times. The dataset will be 1D (i.e. gridded) and the time dimension will be named `time`.
"""

@abstractmethod
def gridobs(self, times) -> xr.Dataset:
"""Interpolate dataset to observation times.

Parameters
----------
times : DataArray (trajectory, obs)
A time variable with the target times for each trajectory.

Returns
-------
Dataset
A new dataset interpolated to the target times. The dataset will be 2D (i.e. observational).
"""

@abstractmethod
def seltime(self, t0=None, t1=None) -> xr.Dataset:
"""Select observations in time window between `t0` and `t1` (inclusive). For 1D datasets prefer to use `xarray.Dataset.sel`.
Expand Down Expand Up @@ -861,6 +876,13 @@ def condense_obs(self) -> xr.Dataset:
A new Dataset with observations condensed.
"""

@abstractmethod
def to_1d(self) -> xr.Dataset:
"""
Convert dataset into a 1D dataset from. This is only possible if the
dataset has a single trajectory.
"""

@abstractmethod
def to_2d(self, obsdim='obs') -> xr.Dataset:
"""
Expand Down
6 changes: 4 additions & 2 deletions trajan/traj1d.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
import numpy as np
import xarray as xr
import numpy as np
import pandas as pd
import logging
from .traj import Traj
Expand Down Expand Up @@ -39,6 +38,9 @@ def to_2d(self, obsdim='obs'):

return ds

def to_1d(self):
return self.ds.copy()

def time_to_next(self):
time_step = self.ds.time[1] - self.ds.time[0]
return time_step
Expand Down Expand Up @@ -183,7 +185,7 @@ def gridtime(self, times, timedim=None, round=True):
else:
logger.warning(f"time dimension ({timedim}) is zero size")

if not 'trajectory' in ds.dims:
if 'trajectory' not in ds.dims:
ds = ds.expand_dims('trajectory')

return ds
15 changes: 15 additions & 0 deletions trajan/traj2d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -216,6 +216,21 @@ def select(t):

return self.ds.groupby('trajectory').map(select)

def to_1d(self):
if self.ds.sizes['trajectory'] > 1:
raise ValueError(
"Can not convert a 2D dataset with multiple trajectories to 1D."
)
else:
ds = self.ds.copy()
ds = ds.dropna(self.obsdim, how='all').rename({
self.obsdim:
self.timedim
}).set_coords(self.timedim)
ds[self.timedim] = ds[self.timedim].squeeze('trajectory')

return ds

@__require_obsdim__
def gridtime(self, times, timedim=None, round=True):
if isinstance(times, str) or isinstance(
Expand Down
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