Add support for temporal composites #2495
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Started work on unit tests for a temporal composites framework. Currently the unit test fails because there is no implementation, and it is also not quite testing the right thing.
Implement a first working draft of temporal compositors. Needs thinking and tuning still.
When blending a multiscene, build the new wishlist from the wishlists shared between the scenes, analogous to the common datasets. If we just copy the wishlist from the first scene, generating possible composites will fail if there are datasets in the first scene that are not in the multiscene because they don't have the same datasets.
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Although I still have some open ends, a first round of review would be already valuable, in case developers have doubt with the direction this is going. |
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No comments on the code, just a question: is this functional already? For example, can the "temporal RGB" in #2488 already created? If yes, we could close that in favor of this more flexible approach. A simple example built-in temporal composite would be great, and at some point a short section to |
import hdf5plugin
from glob import glob
from satpy.multiscene import MultiScene, timeseries
from satpy.utils import debug_on; debug_on()
ms = MultiScene.from_files(
glob("/media/nas/x21308/MTG_test_data/2022_05_MTG_Testdata/RC007[012]/*BODY*.nc"),
reader="fci_l1c_nc",
group_keys=["repeat_cycle_in_day"])
ms.load(["temporal_rgb_vis06"])
sc = ms.blend(blend_function=timeseries)
ls = sc.resample("eurol")
ls.save_datasets()
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Hmm. I tried this composite: temporal_rgb_hrv:
compositor: !!python/name:satpy.composites.TemporalRGB
prerequisites:
- name: HRV
time: 0
- name: HRV
time: -60 min
- name: HRV
time: -120 min
standard_name: temporal_rgb_hrvwith this code: import sys
from satpy import MultiScene
from satpy.multiscene import timeseries
fnames = sys.argv[1:]
mscn = MultiScene.from_files(
fnames,
reader='seviri_l1b_hrit',
group_keys=['start_time'],
)
mscn.load(['temporal_rgb_hrv'])
blended = mscn.blend(blend_function=timeseries)
scn = blended.resample('euron1', resampler='gradient_search')
scn.save_datasets(filename="/tmp/{start_time:%Y%m%d_%H%M}_{platform_name}_{name}.png")and get this trace: The following datasets were not created and may require resampling or temporal blending to be generated: DataID(name='temporal_rgb_hrv')
Traceback (most recent call last):
File "pandas/_libs/index.pyx", line 548, in pandas._libs.index.DatetimeEngine.get_loc
File "pandas/_libs/hashtable_class_helper.pxi", line 2263, in pandas._libs.hashtable.Int64HashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 2273, in pandas._libs.hashtable.Int64HashTable.get_item
KeyError: 1683705309504000000
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/pandas/core/indexes/base.py", line 3802, in get_loc
return self._engine.get_loc(casted_key)
File "pandas/_libs/index.pyx", line 516, in pandas._libs.index.DatetimeEngine.get_loc
File "pandas/_libs/index.pyx", line 550, in pandas._libs.index.DatetimeEngine.get_loc
KeyError: Timestamp('2023-05-10 07:55:09.504000')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/pandas/core/indexes/datetimes.py", line 736, in get_loc
return Index.get_loc(self, key, method, tolerance)
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/pandas/core/indexes/base.py", line 3804, in get_loc
raise KeyError(key) from err
KeyError: Timestamp('2023-05-10 07:55:09.504000')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/xarray/core/indexes.py", line 486, in sel
indexer = self.index.get_loc(label_value)
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/pandas/core/indexes/datetimes.py", line 738, in get_loc
raise KeyError(orig_key) from err
KeyError: numpy.datetime64('2023-05-10T07:55:09.504000000')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/lahtinep/bin/test_temporal_rgb_timeseries.py", line 17, in <module>
blended = mscn.blend(blend_function=timeseries)
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/multiscene/_multiscene.py", line 365, in blend
new_scn.generate_possible_composites(True)
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/scene.py", line 1430, in generate_possible_composites
keepables = self._generate_composites_from_loaded_datasets()
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/scene.py", line 1449, in _generate_composites_from_loaded_datasets
return self._generate_composites_nodes_from_loaded_datasets(needed_comp_nodes)
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/scene.py", line 1455, in _generate_composites_nodes_from_loaded_datasets
self._generate_composite(node, keepables)
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/scene.py", line 1513, in _generate_composite
composite = compositor(prereq_datasets,
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/composites/__init__.py", line 1775, in __call__
new_projectables = self._apply_temporal_prerequisites(projectables)
File "/home/lahtinep/Software/pytroll/pytroll_packages/satpy/satpy/composites/__init__.py", line 1763, in _apply_temporal_prerequisites
new_da = proj.sel(time=ref_time+pd.Timedelta(dq["time"]))
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/xarray/core/dataarray.py", line 1531, in sel
ds = self._to_temp_dataset().sel(
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/xarray/core/dataset.py", line 2580, in sel
query_results = map_index_queries(
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/xarray/core/indexing.py", line 189, in map_index_queries
results.append(index.sel(labels, **options))
File "/home/lahtinep/mambaforge/envs/py310/lib/python3.10/site-packages/xarray/core/indexes.py", line 488, in sel
raise KeyError(
KeyError: "not all values found in index 'time'. Try setting the `method` keyword argument (example: method='nearest')."Could this be something data related? |
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Good question. Maybe something about the different start times (nominal, actual, etc.). The time matching as I've currently implemented it needs to be exact, which would only work with nominal start times. I'll have a look. |
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We probably need a way to add tolerance or slicing capability, "search between T-65 and T-55" or so. |
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The SEVIRI datasets have these time-related keys: There doesn't seem to be exact times available... |
Co-authored-by: Panu Lahtinen <pnuu+git@iki.fi>
…te' into multiscene-load-temporal-composite
Add a test for a direct compositor construction and calling with the temporal RGB, and correct an error in the documentation that I found as a consequence.
djhoese
added
enhancement
| ... group_keys=["repeat_cycle_in_day"]) | ||
| >>> ms.load(["vis_06"]) | ||
| >>> sc = ms.blend(blend_function=satpy.multiscene.timeseries) | ||
| >>> comp = temporal([sc["vis_06"]]*3) # pass three times: same source for each timestep |
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I'm not sure how I feel about this. I had figured the user might ask for the prerequisites without any time information, have a separate time kwarg, and the composite would then parse the time dimension and coordinate to determine which time steps to use. So in this case it would receive a single vis_06 with (time, y, x) dimensions and use data_arr.coords["time"] to find/match the necessary time requirements.
This gets at a larger issue I have or at least something that scares me which is putting the time information in the DataQuery. The DataQuery was designed without time in mind and putting it there now just because it doesn't break seems...risky. Or at least, seems like something we're going to regret later on. I was hoping the time information would go in a separate kwarg like time_order or time_intervals or something.
| class MissingTime(Exception): | ||
| """Raised when temporal composite building lacks time dimension.""" |
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I'd prefer this at the top of the module next to IncompatibleAreas.
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Or maybe this exception and all of the temporal classes should go in a new satpy/composites/temporal.py?
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| class BaseTemporalCompositor(CompositeBase): | ||
| """Compositors combining multiple time steps. |
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| """Compositors combining multiple time steps. | |
| """Compositor combining data from different times. |
| To use this, the user must start with a :class:`MultiScene` and load the | ||
| temporal composite from there. Composite generation will fail due to missing | ||
| temporal information in the containing scenes, but it will add the temporal | ||
| composite to the scene wishlists. Now we run ``MultiScene.blend(timeseries)``, | ||
| which will create DataArrays with a time dimension. After blending, the | ||
| blend method tries again to generate the composites, and on this second run | ||
| the generation should work. |
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Theoretically a user could create a Scene and add a DataArray with a time dimension and do .load and it would work just fine (I think). Alternatively, a reader could (some day) return a DataArray with a time dimension.
| def _ensure_prerequisites_have_times(self, prerequisites): | ||
| """Make sure all prerequisites have times defined.""" | ||
| for preq in prerequisites: | ||
| if "time" not in preq.to_dict(): | ||
| raise KeyError( | ||
| "In a temporal composite, all prerequisites should have " | ||
| "time information defined. Time information is missing for " | ||
| f"{preq!s}") |
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Should this also make sure that pd.Timedelta understands the time value? Or should that wait until __call__ time as you have it now?
| prerequisites: | ||
| - wavelength: 0.64 | ||
| time: 0 | ||
| - wavelength: 0.64 | ||
| time: -10 min | ||
| - wavelength: 0.64 | ||
| time: -20 min |
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So this means green and blue are before the red channel in time? Just curious, is this a standard way of looking at this or would +10, +20, should something equivalent?
| new_scn._wishlist = self._shared_wishlist() | ||
| # without copying the dependency tree, there is a KeyError in dependency_tree.trunk | ||
| new_scn._dependency_tree = self.first_scene._dependency_tree.copy() | ||
| new_scn.generate_possible_composites(True) |
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Do you/we want to try copying the first Scene to get around this copying of hidden/private properties? I know we were worried about it, but maybe it is worth it? 🤷♂️
| except (IncompatibleAreas, MissingTime): | ||
| LOG.debug("Delaying generation of %s because of incompatible areas " | ||
| "or missing time dimension", str(compositor.id)) |
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Can we split this debug message or make it specific to the case (temporal versus area)?
Add a framework for temporal composites.
Current status
Implementation:
Draft.
When loading a temporal composite from a multiscene, the first iteration is failing as expected, because time dimension information is missing. The
MultiSceneblend function then callsgenerate_possible_compositesafter timeseries blending, and the composite is loaded.See below for a list of open tasks.
Unit tests
Passing.
Documentation
Present.