From df123d85261d2e2bc74264a1b910b381ca4b0f6a Mon Sep 17 00:00:00 2001 From: Ricardo Garcia Silva Date: Mon, 15 Jul 2024 15:58:49 +0100 Subject: [PATCH 1/2] Replaced loess.loess_1d() calls with pyloess.loess() This leads to lower processing times for generation of time series --- arpav_ppcv/operations.py | 15 +- arpav_ppcv/webapp/api_v2/routers/coverages.py | 2 + poetry.lock | 14 +- pyproject.toml | 1 + tests/notebooks/generic.ipynb | 397 ++++++++++-------- .../notebooks/timeseries-smoothing-demo.ipynb | 175 +++++++- 6 files changed, 414 insertions(+), 190 deletions(-) diff --git a/arpav_ppcv/operations.py b/arpav_ppcv/operations.py index 9b8a343b..0dcc3f29 100644 --- a/arpav_ppcv/operations.py +++ b/arpav_ppcv/operations.py @@ -12,6 +12,7 @@ import netCDF4 import numpy as np import pandas as pd +import pyloess import pymannkendall as mk import pyproj import shapely @@ -20,7 +21,6 @@ from anyio.from_thread import start_blocking_portal from dateutil.parser import isoparse from geoalchemy2.shape import to_shape -from loess.loess_1d import loess_1d from pyproj.enums import TransformDirection from shapely.ops import transform @@ -392,11 +392,11 @@ async def async_retrieve_data_via_ncss( async def retrieve_multiple_ncss_datasets( settings: ArpavPpcvSettings, + client: httpx.AsyncClient, datasets_to_retrieve: list[coverages.CoverageInternal], point_geom: shapely.Point, temporal_range: tuple[dt.datetime | None, dt.datetime | None], ): - client = httpx.AsyncClient() raw_data = {} async with anyio.create_task_group() as tg: for to_retrieve in datasets_to_retrieve: @@ -529,6 +529,7 @@ def get_related_coverages( def get_coverage_time_series( settings: ArpavPpcvSettings, session: sqlmodel.Session, + http_client: httpx.AsyncClient, coverage: coverages.CoverageInternal, point_geom: shapely.Point, temporal_range: str, @@ -564,6 +565,7 @@ def get_coverage_time_series( raw_data = portal.call( retrieve_multiple_ncss_datasets, settings, + http_client, to_retrieve_from_ncss, point_geom, (start, end), @@ -797,10 +799,13 @@ def _apply_loess_smoothing( with warnings.catch_warnings(): if ignore_warnings: warnings.simplefilter("ignore") - _, loess_smoothed, _ = loess_1d( - df.index.year.astype("int"), df[source_column_name], degree=0.2, frac=0.75 + loess_smoothed = pyloess.loess( + df.index.year.astype("int").values, + df[source_column_name], + span=0.75, + degree=2, ) - return loess_smoothed + return loess_smoothed[:, 1] def _parse_temporal_range( diff --git a/arpav_ppcv/webapp/api_v2/routers/coverages.py b/arpav_ppcv/webapp/api_v2/routers/coverages.py index 3320161c..04b1ca3d 100644 --- a/arpav_ppcv/webapp/api_v2/routers/coverages.py +++ b/arpav_ppcv/webapp/api_v2/routers/coverages.py @@ -397,6 +397,7 @@ def get_climate_barometer_time_series( def get_time_series( db_session: Annotated[Session, Depends(dependencies.get_db_session)], settings: Annotated[ArpavPpcvSettings, Depends(dependencies.get_settings)], + http_client: Annotated[httpx.AsyncClient, Depends(dependencies.get_http_client)], coverage_identifier: str, coords: str, datetime: Optional[str] = "../..", @@ -460,6 +461,7 @@ def get_time_series( ) = operations.get_coverage_time_series( settings, db_session, + http_client, coverage, point_geom, datetime, diff --git a/poetry.lock b/poetry.lock index 13667f77..8c244416 100644 --- a/poetry.lock +++ b/poetry.lock @@ -3781,6 +3781,18 @@ files = [ [package.extras] windows-terminal = ["colorama (>=0.4.6)"] +[[package]] +name = "pyloess" +version = "0.1.0" +description = "A fast implementation of the LOESS algorithm in Python" +category = "main" +optional = false +python-versions = ">=3.8" +files = [ + {file = "pyloess-0.1.0-py3-none-any.whl", hash = "sha256:4c4a5378dd07c0d6ce3cfbeb0ee47880d8a48f10821536532d5f7c1f28945fbb"}, + {file = "pyloess-0.1.0.tar.gz", hash = "sha256:344a76ea03930c3acc846efbef274e7c83ce48030f3a6a87975410f3dab3d214"}, +] + [[package]] name = "pymannkendall" version = "1.4.3" @@ -5667,4 +5679,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "bb8bb83eb53ab063ced06b29ec74111852141f401850220d2c4fcb8bf37fa7f7" +content-hash = "b4d4958ae503c388d21beb7d9d81122ac6950c58bddfbd49222d76bf0ca90e99" diff --git a/pyproject.toml b/pyproject.toml index 0e34018e..f0e35730 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -61,6 +61,7 @@ typing-extensions = "^4.12.1" netcdf4 = "^1.7.1" cftime = "^1.6.4" babel = "^2.15.0" +pyloess = "^0.1.0" [tool.poetry.group.dev] diff --git a/tests/notebooks/generic.ipynb b/tests/notebooks/generic.ipynb index 2fd6c336..773f91c2 100644 --- a/tests/notebooks/generic.ipynb +++ b/tests/notebooks/generic.ipynb @@ -73,124 +73,33 @@ }, { "cell_type": "code", - "execution_count": 9, - "id": "bd877307-fdf8-4f40-9a04-536e3577c55a", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "elapsed: 3.3230252265930176\n" - ] - } - ], - "source": [ - "time_start = time.time()\n", - "old_result = operations.get_coverage_time_series(\n", - " settings=settings,\n", - " session=session,\n", - " http_client=httpx.Client(),\n", - " coverage=cov,\n", - " point_geom=shapely.io.from_wkt(point_coords),\n", - " temporal_range=date_range,\n", - " coverage_smoothing_strategies=[\n", - " CoverageDataSmoothingStrategy.NO_SMOOTHING,\n", - " CoverageDataSmoothingStrategy.MOVING_AVERAGE_11_YEARS,\n", - " CoverageDataSmoothingStrategy.LOESS_SMOOTHING\n", - " ],\n", - " observation_smoothing_strategies=[\n", - " ObservationDataSmoothingStrategy.NO_SMOOTHING,\n", - " ObservationDataSmoothingStrategy.MOVING_AVERAGE_5_YEARS,\n", - " ],\n", - " include_coverage_data=True,\n", - " include_observation_data=False,\n", - " include_coverage_uncertainty=True,\n", - " include_coverage_related_data=True\n", - ")\n", - "time_end = time.time()\n", - "print(f\"elapsed: {time_end - time_start}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "0c153893-085a-4e2d-abd2-d69024493a06", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['tas_seasonal_absolute_model_ensemble-rcp26-DJF',\n", - " '**UNCERTAINTY**_LOWER_BOUND',\n", - " '**UNCERTAINTY**_UPPER_BOUND',\n", - " '**RELATED**_tas_seasonal_absolute_model_ec_earth_cclm4_8_17',\n", - " '**RELATED**_tas_seasonal_absolute_model_ec_earth_racmo22e',\n", - " '**RELATED**_tas_seasonal_absolute_model_ec_earth_rca4',\n", - " '**RELATED**_tas_seasonal_absolute_model_hadgem2_es_racmo22e',\n", - " '**RELATED**_tas_seasonal_absolute_model_mpi_esm_lr_remo2009']" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "list(old_result.keys())" - ] - }, - { - "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "93c28235-3793-4b3b-acd0-c00a56252cdf", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "INFO:arpav_ppcv.operations:[c.identifier for c in to_retrieve_from_ncss]=['tas_seasonal_absolute_model_ensemble-rcp26-DJF', 'tas_seasonal_absolute_model_ensemble_lower_uncertainty-rcp26-DJF', 'tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF', 'tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF', 'tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF', 'tas_seasonal_absolute_model_ec_earth_rca4-rcp26-DJF', 'tas_seasonal_absolute_model_hadgem2_es_racmo22e-rcp26-DJF', 'tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF']\n", - "DEBUG:asyncio:Using selector: EpollSelector\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ensemble-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ensemble_lower_uncertainty-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ec_earth_rca4-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_hadgem2_es_racmo22e-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:inside async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ec_earth_rca4-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ensemble_lower_uncertainty-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ensemble-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_hadgem2_es_racmo22e-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:leaving async_retrieve_data_via_ncss for cov 'tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF'\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.4472151669979212\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.52551889499955\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.40870382099819835\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.37498756399872946\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.35797891699985485\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.3648923950022436\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.3506568630000402\n", - "INFO:arpav_ppcv.operations:elapsed time for applying loess: 0.3570055259988294\n" + "DEBUG:asyncio:Using selector: EpollSelector\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "elapsed: 3.5332484245300293\n" + "elapsed: 0.49170613288879395\n" ] } ], "source": [ "new_time_start = time.time()\n", - "coverage_series, observation_series = operations.new_get_coverage_time_series(\n", + "coverage_series, observation_series = operations.get_coverage_time_series(\n", " settings=settings,\n", " session=session,\n", + " http_client=httpx.AsyncClient(),\n", " coverage=cov,\n", " point_geom=shapely.io.from_wkt(point_coords),\n", " temporal_range=date_range,\n", @@ -214,35 +123,41 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "id": "63fa30a2-13f9-4157-b3f7-dc131541d3b2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[('tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF', 'NO_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF',\n", - " 'MOVING_AVERAGE_11_YEARS'),\n", - " ('tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF',\n", - " 'LOESS_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF', 'NO_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF',\n", + "[('tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF', 'NO_SMOOTHING'),\n", + " ('tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF',\n", " 'MOVING_AVERAGE_11_YEARS'),\n", - " ('tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF',\n", + " ('tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF',\n", " 'LOESS_SMOOTHING'),\n", " ('tas_seasonal_absolute_model_ensemble-rcp26-DJF', 'NO_SMOOTHING'),\n", " ('tas_seasonal_absolute_model_ensemble-rcp26-DJF', 'MOVING_AVERAGE_11_YEARS'),\n", " ('tas_seasonal_absolute_model_ensemble-rcp26-DJF', 'LOESS_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF', 'NO_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF',\n", + " ('tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF', 'NO_SMOOTHING'),\n", + " ('tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF',\n", " 'MOVING_AVERAGE_11_YEARS'),\n", - " ('tas_seasonal_absolute_model_ec_earth_cclm4_8_17-rcp26-DJF',\n", + " ('tas_seasonal_absolute_model_ec_earth_racmo22e-rcp26-DJF',\n", " 'LOESS_SMOOTHING'),\n", " ('tas_seasonal_absolute_model_ec_earth_rca4-rcp26-DJF', 'NO_SMOOTHING'),\n", " ('tas_seasonal_absolute_model_ec_earth_rca4-rcp26-DJF',\n", " 'MOVING_AVERAGE_11_YEARS'),\n", " ('tas_seasonal_absolute_model_ec_earth_rca4-rcp26-DJF', 'LOESS_SMOOTHING'),\n", + " ('tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF',\n", + " 'NO_SMOOTHING'),\n", + " ('tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF',\n", + " 'MOVING_AVERAGE_11_YEARS'),\n", + " ('tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF',\n", + " 'LOESS_SMOOTHING'),\n", + " ('tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF', 'NO_SMOOTHING'),\n", + " ('tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF',\n", + " 'MOVING_AVERAGE_11_YEARS'),\n", + " ('tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF',\n", + " 'LOESS_SMOOTHING'),\n", " ('tas_seasonal_absolute_model_hadgem2_es_racmo22e-rcp26-DJF', 'NO_SMOOTHING'),\n", " ('tas_seasonal_absolute_model_hadgem2_es_racmo22e-rcp26-DJF',\n", " 'MOVING_AVERAGE_11_YEARS'),\n", @@ -253,16 +168,10 @@ " ('tas_seasonal_absolute_model_ensemble_lower_uncertainty-rcp26-DJF',\n", " 'MOVING_AVERAGE_11_YEARS'),\n", " ('tas_seasonal_absolute_model_ensemble_lower_uncertainty-rcp26-DJF',\n", - " 'LOESS_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF',\n", - " 'NO_SMOOTHING'),\n", - " ('tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF',\n", - " 'MOVING_AVERAGE_11_YEARS'),\n", - " ('tas_seasonal_absolute_model_ensemble_upper_uncertainty-rcp26-DJF',\n", " 'LOESS_SMOOTHING')]" ] }, - "execution_count": 9, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -273,89 +182,238 @@ }, { "cell_type": "code", - "execution_count": 12, - "id": "db9721ac-ac09-4ca7-8329-268a626505e5", + "execution_count": 5, + "id": "b3811df1-eb09-45eb-8bd6-e85286007a66", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "time\n", - "1976-02-15 12:00:00+00:00 2.954980\n", - "1977-02-14 17:54:11.613000+00:00 3.255182\n", - "1978-02-14 23:48:23.226000+00:00 2.340784\n", - "1979-02-15 05:42:34.839000+00:00 4.659448\n", - "1980-02-15 11:36:46.452000+00:00 3.844202\n", - " ... \n", - "2096-02-15 00:23:13.548000+00:00 4.219568\n", - "2097-02-14 06:17:25.161000+00:00 5.275751\n", - "2098-02-14 12:11:36.774000+00:00 4.540552\n", - "2099-02-14 18:05:48.387000+00:00 4.133020\n", - "2100-02-15 00:00:00+00:00 4.696100\n", - "Name: tas_seasonal_absolute_model_mpi_esm_lr_remo2009-rcp26-DJF, Length: 125, dtype: float64" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "next(iter(coverage_series.values()))" + "raw_data = await operations.retrieve_multiple_ncss_datasets(\n", + " settings, \n", + " httpx.AsyncClient(), \n", + " [\n", + " CoverageInternal(\n", + " identifier=coverage_identifier, \n", + " configuration=db.get_coverage_configuration_by_coverage_identifier(\n", + " session, coverage_identifier)\n", + " ),\n", + " ],\n", + " shapely.io.from_wkt(point_coords),\n", + " (None, None)\n", + ")\n", + " " ] }, { "cell_type": "code", - "execution_count": 3, - "id": "d9404e4b-d2fc-4587-94f9-df8388313f66", + "execution_count": 6, + "id": "d369153d-c155-4e27-ba7c-7228a56dd0f9", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'scenario': 'rcp26'}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], + "source": [ + "for cov, data_ in raw_data.items():\n", + " df = operations._parse_ncss_dataset(data_, cov.configuration.netcdf_main_dataset_name, None, None, cov.identifier)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "ca25cce2-36fb-44fb-a60c-b3f8ede028b8", + "metadata": {}, + "outputs": [], "source": [ - "cov.configuration.retrieve_configuration_parameters(cov_id)" + "import pyloess" ] }, { "cell_type": "code", - "execution_count": 8, - "id": "80632d8c-3174-4ef8-a9a8-0d2479599f55", + "execution_count": 10, + "id": "16946c48-0c1e-46bf-9cd2-453ee8f5bc2b", "metadata": {}, + "outputs": [], + "source": [ + "smoothed = pyloess.loess(df.index.year.astype(\"int\").values, df[coverage_identifier], span=0.75, degree=2)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "60dd97fa-6a8f-4ed8-b25b-d13a38d9d89b", + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { "text/plain": [ - "{'scenario': 'rcp26'}" + "array([[1976. , 3.39045092],\n", + " [1977. , 3.41520367],\n", + " [1978. , 3.43951448],\n", + " [1979. , 3.46338917],\n", + " [1980. , 3.48683499],\n", + " [1981. , 3.50985909],\n", + " [1982. , 3.53246727],\n", + " [1983. , 3.55466547],\n", + " [1984. , 3.57645893],\n", + " [1985. , 3.59785423],\n", + " [1986. , 3.6188608 ],\n", + " [1987. , 3.63948834],\n", + " [1988. , 3.65974729],\n", + " [1989. , 3.67964993],\n", + " [1990. , 3.69921081],\n", + " [1991. , 3.71844372],\n", + " [1992. , 3.73736291],\n", + " [1993. , 3.75598335],\n", + " [1994. , 3.77432163],\n", + " [1995. , 3.7923959 ],\n", + " [1996. , 3.81022421],\n", + " [1997. , 3.82782181],\n", + " [1998. , 3.8452036 ],\n", + " [1999. , 3.86238304],\n", + " [2000. , 3.87937367],\n", + " [2001. , 3.89618642],\n", + " [2002. , 3.91283006],\n", + " [2003. , 3.92931283],\n", + " [2004. , 3.94564078],\n", + " [2005. , 3.96181679],\n", + " [2006. , 3.97784126],\n", + " [2007. , 3.99370947],\n", + " [2008. , 4.00941002],\n", + " [2009. , 4.02492491],\n", + " [2010. , 4.04022963],\n", + " [2011. , 4.05528821],\n", + " [2012. , 4.07005002],\n", + " [2013. , 4.08445509],\n", + " [2014. , 4.09843551],\n", + " [2015. , 4.11190995],\n", + " [2016. , 4.12477485],\n", + " [2017. , 4.13690201],\n", + " [2018. , 4.14813488],\n", + " [2019. , 4.15831013],\n", + " [2020. , 4.16730638],\n", + " [2021. , 4.17513242],\n", + " [2022. , 4.18196441],\n", + " [2023. , 4.19625107],\n", + " [2024. , 4.21062102],\n", + " [2025. , 4.22493585],\n", + " [2026. , 4.23921175],\n", + " [2027. , 4.25354211],\n", + " [2028. 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4.70788883],\n", + " [2062. , 4.71332622],\n", + " [2063. , 4.71868373],\n", + " [2064. , 4.72392387],\n", + " [2065. , 4.72901914],\n", + " [2066. , 4.73395416],\n", + " [2067. , 4.7387202 ],\n", + " [2068. , 4.74331141],\n", + " [2069. , 4.74772083],\n", + " [2070. , 4.75194145],\n", + " [2071. , 4.75596588],\n", + " [2072. , 4.75978888],\n", + " [2073. , 4.76340877],\n", + " [2074. , 4.76682503],\n", + " [2075. , 4.77004131],\n", + " [2076. , 4.77306356],\n", + " [2077. , 4.7759003 ],\n", + " [2078. , 4.77855902],\n", + " [2079. , 4.78104787],\n", + " [2080. , 4.78337515],\n", + " [2081. , 4.78554851],\n", + " [2082. , 4.7875757 ],\n", + " [2083. , 4.78946472],\n", + " [2084. , 4.791222 ],\n", + " [2085. , 4.79285211],\n", + " [2086. , 4.79436069],\n", + " [2087. , 4.7957522 ],\n", + " [2088. , 4.79703161],\n", + " [2089. , 4.79820364],\n", + " [2090. , 4.79927258],\n", + " [2091. , 4.8002431 ],\n", + " [2092. , 4.80111915],\n", + " [2093. , 4.80190698],\n", + " [2094. , 4.80260852],\n", + " [2095. , 4.80322256],\n", + " [2096. , 4.80374603],\n", + " [2097. , 4.80417534],\n", + " [2098. , 4.8045086 ],\n", + " [2099. , 4.80474447]])" ] }, - "execution_count": 8, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "{pv.configuration_parameter_value.configuration_parameter.name: pv.configuration_parameter_value.name for pv in cov.configuration.retrieve_used_values(cov_id)}" + "smoothed" ] }, { "cell_type": "code", "execution_count": 12, - "id": "1cfd78d0-3ed1-47b1-8f51-074adb0c0bc9", + "id": "cf2d3db8-41e6-47e1-b93e-efa30e882e0f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'scenario': 'Scenario'}" + "array([3.39045092, 3.41520367, 3.43951448, 3.46338917, 3.48683499,\n", + " 3.50985909, 3.53246727, 3.55466547, 3.57645893, 3.59785423,\n", + " 3.6188608 , 3.63948834, 3.65974729, 3.67964993, 3.69921081,\n", + " 3.71844372, 3.73736291, 3.75598335, 3.77432163, 3.7923959 ,\n", + " 3.81022421, 3.82782181, 3.8452036 , 3.86238304, 3.87937367,\n", + " 3.89618642, 3.91283006, 3.92931283, 3.94564078, 3.96181679,\n", + " 3.97784126, 3.99370947, 4.00941002, 4.02492491, 4.04022963,\n", + " 4.05528821, 4.07005002, 4.08445509, 4.09843551, 4.11190995,\n", + " 4.12477485, 4.13690201, 4.14813488, 4.15831013, 4.16730638,\n", + " 4.17513242, 4.18196441, 4.19625107, 4.21062102, 4.22493585,\n", + " 4.23921175, 4.25354211, 4.26806956, 4.28300472, 4.29854456,\n", + " 4.31481714, 4.33193141, 4.34987622, 4.36855939, 4.38791159,\n", + " 4.40782196, 4.42815529, 4.44861772, 4.46891522, 4.48884042,\n", + " 4.50831509, 4.52728011, 4.54563333, 4.56325833, 4.58006323,\n", + " 4.59600293, 4.61099795, 4.6248397 , 4.63730183, 4.64824497,\n", + " 4.65766433, 4.66565783, 4.67241102, 4.67526526, 4.67849819,\n", + " 4.68235967, 4.68683354, 4.69177381, 4.69701813, 4.70242627,\n", + " 4.70788883, 4.71332622, 4.71868373, 4.72392387, 4.72901914,\n", + " 4.73395416, 4.7387202 , 4.74331141, 4.74772083, 4.75194145,\n", + " 4.75596588, 4.75978888, 4.76340877, 4.76682503, 4.77004131,\n", + " 4.77306356, 4.7759003 , 4.77855902, 4.78104787, 4.78337515,\n", + " 4.78554851, 4.7875757 , 4.78946472, 4.791222 , 4.79285211,\n", + " 4.79436069, 4.7957522 , 4.79703161, 4.79820364, 4.79927258,\n", + " 4.8002431 , 4.80111915, 4.80190698, 4.80260852, 4.80322256,\n", + " 4.80374603, 4.80417534, 4.8045086 , 4.80474447])" ] }, "execution_count": 12, @@ -364,10 +422,7 @@ } ], "source": [ - "{\n", - " pv.configuration_parameter_value.configuration_parameter.name: pv.configuration_parameter_value.configuration_parameter.display_name_english \n", - " for pv in cov.configuration.retrieve_used_values(cov_id)\n", - "}" + "smoothed[:, 1]" ] } ], diff --git a/tests/notebooks/timeseries-smoothing-demo.ipynb b/tests/notebooks/timeseries-smoothing-demo.ipynb index 661b2269..47b245f2 100644 --- a/tests/notebooks/timeseries-smoothing-demo.ipynb +++ b/tests/notebooks/timeseries-smoothing-demo.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 1, "id": "df4b0596-aef5-4211-829c-20cbab0ed146", "metadata": {}, "outputs": [], @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 15, "id": "803425ad-95a3-44cb-aecc-2dee787d2e7e", "metadata": {}, "outputs": [], @@ -64,10 +64,10 @@ " \"coverage_data_smoothing\": [\n", " \"NO_SMOOTHING\",\n", " \"MOVING_AVERAGE_11_YEARS\",\n", - " # \"LOESS_SMOOTHING\",\n", + " \"LOESS_SMOOTHING\",\n", " ],\n", - " \"include_coverage_uncertainty\": False,\n", - " \"include_coverage_related_data\": False,\n", + " \"include_coverage_uncertainty\": True,\n", + " \"include_coverage_related_data\": True,\n", " }\n", ")\n", "try:\n", @@ -91,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 6, "id": "c15d8402-3f27-4974-b1a3-6c895afbc166", "metadata": {}, "outputs": [ @@ -387,10 +387,159 @@ " 'coverage_configuration': {'en': 'TAS seasonal absolute model ensemble',\n", " 'it': 'TAS valore assoluto di stagione media ensemble'},\n", " 'scenario': {'en': 'RCP2.6', 'it': 'RCP2.6'},\n", + " 'year_period': {'en': 'Winter', 'it': 'Inverno'}}}},\n", + " {'name': 'tas_seasonal_absolute_model_ensemble-rcp26-DJF__LOESS_SMOOTHING',\n", + " 'values': [{'value': 3.390450916107852, 'datetime': '1976-02-15T12:00:00Z'},\n", + " {'value': 3.4152036707620823, 'datetime': '1977-02-14T17:57:04.390000Z'},\n", + " {'value': 3.4395144785386265, 'datetime': '1978-02-14T23:54:08.780000Z'},\n", + " {'value': 3.4633891655344087, 'datetime': '1979-02-15T05:51:13.171000Z'},\n", + " {'value': 3.486834992467891, 'datetime': '1980-02-15T11:48:17.561000Z'},\n", + " {'value': 3.509859088338601, 'datetime': '1981-02-14T17:45:21.951000Z'},\n", + " {'value': 3.532467268069297, 'datetime': '1982-02-14T23:42:26.341000Z'},\n", + " {'value': 3.554665473951445, 'datetime': '1983-02-15T05:39:30.732000Z'},\n", + " {'value': 3.5764589281731674, 'datetime': '1984-02-15T11:36:35.122000Z'},\n", + " {'value': 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'2093-02-14T12:17:33.659000Z'},\n", + " {'value': 4.802608520194497, 'datetime': '2094-02-14T18:14:38.049000Z'},\n", + " {'value': 4.803222559821052, 'datetime': '2095-02-15T00:11:42.439000Z'},\n", + " {'value': 4.803746026972874, 'datetime': '2096-02-15T06:08:46.829000Z'},\n", + " {'value': 4.804175343320935, 'datetime': '2097-02-14T12:05:51.220000Z'},\n", + " {'value': 4.804508602179396, 'datetime': '2098-02-14T18:02:55.610000Z'},\n", + " {'value': 4.804744469271952, 'datetime': '2099-02-15T00:00:00Z'}],\n", + " 'info': {'processing_method': 'LOESS_SMOOTHING',\n", + " 'coverage_identifier': 'tas_seasonal_absolute_model_ensemble-rcp26-DJF',\n", + " 'coverage_configuration': 'tas_seasonal_absolute_model_ensemble',\n", + " 'scenario': 'rcp26',\n", + " 'year_period': 'DJF'},\n", + " 'translations': {'parameter_names': {'series_name': {'en': 'series name',\n", + " 'it': 'Nome della serie'},\n", + " 'processing_method': {'en': 'processing method',\n", + " 'it': 'Metodo di elaborazione'},\n", + " 'coverage_identifier': {'en': 'coverage identifier',\n", + " 'it': 'Identificatore di copertura'},\n", + " 'coverage_configuration': {'en': 'coverage configuration',\n", + " 'it': 'Configurazione della copertura'},\n", + " 'scenario': {'en': 'Scenario', 'it': 'Scenario'},\n", + " 'year_period': {'en': 'Year period', 'it': \"Periodo dell'anno\"}},\n", + " 'parameter_values': {'series_name': {'en': 'TAS seasonal absolute model ensemble',\n", + " 'it': 'TAS valore assoluto di stagione media ensemble'},\n", + " 'processing_method': {'en': 'LOESS', 'it': 'LOESS'},\n", + " 'coverage_identifier': {'en': 'tas_seasonal_absolute_model_ensemble-rcp26-DJF',\n", + " 'it': 'tas_seasonal_absolute_model_ensemble-rcp26-DJF'},\n", + " 'coverage_configuration': {'en': 'TAS seasonal absolute model ensemble',\n", + " 'it': 'TAS valore assoluto di stagione media ensemble'},\n", + " 'scenario': {'en': 'RCP2.6', 'it': 'RCP2.6'},\n", " 'year_period': {'en': 'Winter', 'it': 'Inverno'}}}}]" ] }, - "execution_count": 20, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -409,35 +558,35 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 7, "id": "9b1ddd10-6e0e-478f-babe-464e16dc07d3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "177d900e79ee41179d235a5129cd18e5", + "model_id": "3933cb3985e740048d09ffd8831be756", "version_major": 2, "version_minor": 0 }, - "image/png": 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", + "image/png": 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", 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\n", " " ], From 2cb7cdd000e12cd3e37211c834690566a54d6701 Mon Sep 17 00:00:00 2001 From: Ricardo Garcia Silva Date: Mon, 15 Jul 2024 16:09:43 +0100 Subject: [PATCH 2/2] Removed the loess dependency, which is not needed anymore --- poetry.lock | 50 ++++++++------------------------------------------ pyproject.toml | 1 - 2 files changed, 8 insertions(+), 43 deletions(-) diff --git a/poetry.lock b/poetry.lock index 8c244416..1c983c8a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -802,7 +802,7 @@ files = [ name = "contourpy" version = "1.2.1" description = "Python library for calculating contours of 2D quadrilateral grids" -category = "main" +category = "dev" optional = false python-versions = ">=3.9" files = [ @@ -989,7 +989,7 @@ test-randomorder = ["pytest-randomly"] name = "cycler" version = "0.12.1" description = "Composable style cycles" -category = "main" +category = "dev" optional = false python-versions = ">=3.8" files = [ @@ -1415,7 +1415,7 @@ typing = ["typing-extensions (>=4.8)"] name = "fonttools" version = "4.52.4" description = "Tools to manipulate font files" -category = "main" +category = "dev" optional = false python-versions = ">=3.8" files = [ @@ -2315,7 +2315,7 @@ files = [ name = "kiwisolver" version = "1.4.5" description = "A fast implementation of the Cassowary constraint solver" -category = "main" +category = "dev" optional = false python-versions = ">=3.7" files = [ @@ -2456,23 +2456,6 @@ sqs = ["boto3 (>=1.4.4)", "pycurl (==7.43.0.2)"] yaml = ["PyYAML (>=3.10)"] zookeeper = ["kazoo (>=1.3.1)"] -[[package]] -name = "loess" -version = "2.1.2" -description = "LOESS: smoothing via robust locally-weighted regression in one or two dimensions" -category = "main" -optional = false -python-versions = "*" -files = [ - {file = "loess-2.1.2-py3-none-any.whl", hash = "sha256:105f12daa0fdff5185855ae57c2d3f25420fb30b475ae3f4078843a5c61699b9"}, - {file = "loess-2.1.2.tar.gz", hash = "sha256:f0c1e83e70c5f9b95da635495c0ec555cf7c225186f7e6d978ed7c20d2f3828a"}, -] - -[package.dependencies] -matplotlib = "*" -numpy = "*" -plotbin = "*" - [[package]] name = "lxml" version = "5.2.2" @@ -2751,7 +2734,7 @@ files = [ name = "matplotlib" version = "3.9.0" description = "Python plotting package" -category = "main" +category = "dev" optional = false python-versions = ">=3.9" files = [ @@ -3286,7 +3269,7 @@ ptyprocess = ">=0.5" name = "pillow" version = "10.3.0" description = "Python Imaging Library (Fork)" -category = "main" +category = "dev" optional = false python-versions = ">=3.8" files = [ @@ -3386,23 +3369,6 @@ docs = ["furo (>=2023.9.10)", "proselint (>=0.13)", "sphinx (>=7.2.6)", "sphinx- test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"] type = ["mypy (>=1.8)"] -[[package]] -name = "plotbin" -version = "3.1.5" -description = "PlotBin: Plotting Binned Maps and Other Utilities" -category = "main" -optional = false -python-versions = "*" -files = [ - {file = "plotbin-3.1.5-py3-none-any.whl", hash = "sha256:99b42dcff5fcc1930c0a24230113379eb913fa1702c2e377b169b793d9113b6f"}, - {file = "plotbin-3.1.5.tar.gz", hash = "sha256:9fb2d86bd887eaaad9612dea306f57fed5bcb4252a54d8ff040beb9bb1645410"}, -] - -[package.dependencies] -matplotlib = "*" -numpy = "*" -scipy = "*" - [[package]] name = "pluggy" version = "1.5.0" @@ -3832,7 +3798,7 @@ test = ["pretend", "pytest (>=3.0.1)", "pytest-rerunfailures"] name = "pyparsing" version = "3.1.2" description = "pyparsing module - Classes and methods to define and execute parsing grammars" -category = "main" +category = "dev" optional = false python-versions = ">=3.6.8" files = [ @@ -5679,4 +5645,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "b4d4958ae503c388d21beb7d9d81122ac6950c58bddfbd49222d76bf0ca90e99" +content-hash = "9daf9540f4c4bd5af48041eef82ba597ca213a7756d83897e63d9619d663f43e" diff --git a/pyproject.toml b/pyproject.toml index f0e35730..b05ef727 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,7 +55,6 @@ itsdangerous = "^2.2.0" jinja2 = "^3.1.4" pyyaml = "^6.0.1" alembic-postgresql-enum = "^1.2.0" -loess = "^2.1.2" pymannkendall = "^1.4.3" typing-extensions = "^4.12.1" netcdf4 = "^1.7.1"