From a3740ee478867309d7882d16c233e7f4d3b4d5a8 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 09:49:49 +0000 Subject: [PATCH 01/52] add testset, script to make + test --- .../dataset/make_test_set.py | 50 + quartz_solar_forecast/dataset/testset.csv | 2501 +++++++++++++++++ tests/data/test_make_test_set.py | 18 + 3 files changed, 2569 insertions(+) create mode 100644 quartz_solar_forecast/dataset/make_test_set.py create mode 100644 quartz_solar_forecast/dataset/testset.csv create mode 100644 tests/data/test_make_test_set.py diff --git a/quartz_solar_forecast/dataset/make_test_set.py b/quartz_solar_forecast/dataset/make_test_set.py new file mode 100644 index 00000000..766df915 --- /dev/null +++ b/quartz_solar_forecast/dataset/make_test_set.py @@ -0,0 +1,50 @@ +""" +Make a random test set + +This takes a random subset of times and for various pv ids and makes a test set +""" +from typing import Optional +import pandas as pd +import numpy as np +import os + +test_start_date = pd.Timestamp("2021-01-01") +test_end_date = pd.Timestamp("2021-02-01") + +# this have been chosen from the entire training set. This ideas +pv_ids = [ 8215, 8229, 8253, 8266, 8267, 8281, 16474, 16477, 16480, + 16483, 8376, 16570, 16597, 8411, 8412, 8419, 8420, 8453, + 8464, 8505, 16715, 16717, 8551, 8558, 16769, 16770, 8587, + 8591, 8612, 8648, 8670, 8708, 8713, 16920, 16921, 8801, + 17034, 17035, 8856, 17062, 8914, 17166, 9069, 9070, 9101, + 9107, 17333, 9153, 9171, 9173] + +np.random.seed(42) + + +def make_test_set( + output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50 +): + """ + Make a test set of random times and pv ids + + :param output_file_name: the name of the file to write the test set to + :param number_of_samples_per_system: the number of samples to take per pv id + """ + + if output_file_name is None: + # get the folder where this file is + output_file_name = os.path.dirname(os.path.abspath(__file__)) + "/testset.csv" + + test_set = [] + for pv_id in pv_ids: + ts = pd.date_range(start=test_start_date, end=test_end_date, freq="15min") + ts = ts[np.random.choice(len(ts), size=number_of_samples_per_system, replace=False)] + test_set.append(pd.DataFrame({"pv_id": pv_id, "datetime": ts})) + test_set = pd.concat(test_set) + test_set.to_csv(output_file_name, index=False) + + return test_set + +# To run the script, un comment the following line and run this file +make_test_set() \ No newline at end of file diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv new file mode 100644 index 00000000..8506f1d0 --- /dev/null +++ b/quartz_solar_forecast/dataset/testset.csv @@ -0,0 +1,2501 @@ +pv_id,datetime +8215,2021-01-26 01:15:00 +8215,2021-01-30 16:30:00 +8215,2021-01-18 19:30:00 +8215,2021-01-12 14:15:00 +8215,2021-01-11 01:00:00 +8215,2021-01-31 12:15:00 +8215,2021-01-05 19:45:00 +8215,2021-01-27 12:15:00 +8215,2021-01-10 04:15:00 +8215,2021-01-24 00:45:00 +8215,2021-01-20 22:30:00 +8215,2021-01-09 04:15:00 +8215,2021-01-19 18:00:00 +8215,2021-01-09 12:45:00 +8215,2021-01-01 23:15:00 +8215,2021-01-14 03:15:00 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a/tests/data/test_make_test_set.py b/tests/data/test_make_test_set.py new file mode 100644 index 00000000..7bc60a66 --- /dev/null +++ b/tests/data/test_make_test_set.py @@ -0,0 +1,18 @@ +from quartz_solar_forecast.dataset.make_test_set import make_test_set +import tempfile +import pandas as pd + + +def test_make_test_set(): + with tempfile.TemporaryDirectory() as tmpdirname: + + output_file = tmpdirname + '/test.csv' + + make_test_set(output_file_name=output_file) + + test_set = pd.read_csv(output_file) + assert len(test_set) == 50*50 + # we can check this as we have set the seed + assert test_set.iloc[0].datetime == '2021-01-26 01:15:00' + + From 15f3bcc7ffa31b6a5fc86ae9405cb43bb20f44a3 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 09:50:25 +0000 Subject: [PATCH 02/52] format --- .../dataset/make_test_set.py | 70 +++++++++++++++---- tests/data/test_make_test_set.py | 12 ++-- 2 files changed, 64 insertions(+), 18 deletions(-) diff --git a/quartz_solar_forecast/dataset/make_test_set.py b/quartz_solar_forecast/dataset/make_test_set.py index 766df915..da0713ca 100644 --- a/quartz_solar_forecast/dataset/make_test_set.py +++ b/quartz_solar_forecast/dataset/make_test_set.py @@ -3,28 +3,73 @@ This takes a random subset of times and for various pv ids and makes a test set """ +import os from typing import Optional -import pandas as pd + import numpy as np -import os +import pandas as pd test_start_date = pd.Timestamp("2021-01-01") test_end_date = pd.Timestamp("2021-02-01") # this have been chosen from the entire training set. This ideas -pv_ids = [ 8215, 8229, 8253, 8266, 8267, 8281, 16474, 16477, 16480, - 16483, 8376, 16570, 16597, 8411, 8412, 8419, 8420, 8453, - 8464, 8505, 16715, 16717, 8551, 8558, 16769, 16770, 8587, - 8591, 8612, 8648, 8670, 8708, 8713, 16920, 16921, 8801, - 17034, 17035, 8856, 17062, 8914, 17166, 9069, 9070, 9101, - 9107, 17333, 9153, 9171, 9173] +pv_ids = [ + 8215, + 8229, + 8253, + 8266, + 8267, + 8281, + 16474, + 16477, + 16480, + 16483, + 8376, + 16570, + 16597, + 8411, + 8412, + 8419, + 8420, + 8453, + 8464, + 8505, + 16715, + 16717, + 8551, + 8558, + 16769, + 16770, + 8587, + 8591, + 8612, + 8648, + 8670, + 8708, + 8713, + 16920, + 16921, + 8801, + 17034, + 17035, + 8856, + 17062, + 8914, + 17166, + 9069, + 9070, + 9101, + 9107, + 17333, + 9153, + 9171, + 9173, +] np.random.seed(42) -def make_test_set( - output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50 -): +def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50): """ Make a test set of random times and pv ids @@ -46,5 +91,6 @@ def make_test_set( return test_set + # To run the script, un comment the following line and run this file -make_test_set() \ No newline at end of file +make_test_set() diff --git a/tests/data/test_make_test_set.py b/tests/data/test_make_test_set.py index 7bc60a66..a919602a 100644 --- a/tests/data/test_make_test_set.py +++ b/tests/data/test_make_test_set.py @@ -1,18 +1,18 @@ -from quartz_solar_forecast.dataset.make_test_set import make_test_set import tempfile + import pandas as pd +from quartz_solar_forecast.dataset.make_test_set import make_test_set + def test_make_test_set(): with tempfile.TemporaryDirectory() as tmpdirname: - output_file = tmpdirname + '/test.csv' + output_file = tmpdirname + "/test.csv" make_test_set(output_file_name=output_file) test_set = pd.read_csv(output_file) - assert len(test_set) == 50*50 + assert len(test_set) == 50 * 50 # we can check this as we have set the seed - assert test_set.iloc[0].datetime == '2021-01-26 01:15:00' - - + assert test_set.iloc[0].datetime == "2021-01-26 01:15:00" From 434d29a741a2f03dfb86cf74e348fc96e0d5f142 Mon Sep 17 00:00:00 2001 From: Megawattz <47150349+zakwatts@users.noreply.github.com> Date: Tue, 12 Dec 2023 11:26:30 +0000 Subject: [PATCH 03/52] Scope out forecast evaluation method --- quartz_solar_forecast/evaluation.py | 34 +++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 quartz_solar_forecast/evaluation.py diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py new file mode 100644 index 00000000..14a68fa2 --- /dev/null +++ b/quartz_solar_forecast/evaluation.py @@ -0,0 +1,34 @@ +""" +To evaluate the performance of the solar forecast, a predefined testset is used. + +A file has been added to this branch (make-testset) which defines a set of random timestamps and sites ids. +This contains 50 sites each with 50 timestamps to make 2500 samples in total. + +""" + +def run_eval(testset_path): + # load testset from csv + testset = df.read_csv(testset_path) + + # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. + + + # Split data into PV inputs and ground truth. + + + # Collect NWP data from Hugging Face, ICON. + + + # Run forecast with PV and NWP inputs. + + + # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) + + + # Save file + + + # Calculate and print metrics: MAE + + + # Visulisations From 0a401e43d57a665508b7d5a5e7c99b9e0ea4ee21 Mon Sep 17 00:00:00 2001 From: Megawattz <47150349+zakwatts@users.noreply.github.com> Date: Tue, 12 Dec 2023 11:35:10 +0000 Subject: [PATCH 04/52] Update evaluation.py --- quartz_solar_forecast/evaluation.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 14a68fa2..5baadd70 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -10,13 +10,13 @@ def run_eval(testset_path): # load testset from csv testset = df.read_csv(testset_path) - # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. + # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. (Zak) - # Split data into PV inputs and ground truth. + # Split data into PV inputs and ground truth. (Zak) - # Collect NWP data from Hugging Face, ICON. + # Collect NWP data from Hugging Face, ICON. (Peter) # Run forecast with PV and NWP inputs. From 1d5052cc5ab0c7a3760402ef49265e4ba213a07b Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 13:48:46 +0000 Subject: [PATCH 05/52] push, first try on getting nwp data --- quartz_solar_forecast/eval/nwp.py | 142 ++++++++++++++++++++++++++++ quartz_solar_forecast/evaluation.py | 30 +++--- requirements.txt | 3 +- 3 files changed, 158 insertions(+), 17 deletions(-) create mode 100644 quartz_solar_forecast/eval/nwp.py diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py new file mode 100644 index 00000000..14634fe4 --- /dev/null +++ b/quartz_solar_forecast/eval/nwp.py @@ -0,0 +1,142 @@ +""" Get nwp data from HF""" +import pandas as pd + +import ocf_blosc2 # noqa +import xarray as xr +from huggingface_hub import HfFileSystem + + +def get_nwp(time_locations:pd.DataFrame): + """ + Get all the nwp data fpr the time locations + + time_locations should have the following columns: + - timestamp + - latitude + - longitude + - pv_id + """ + + all_nwp_dfs = [] + for i, row in time_locations.iterrows(): + print(f'{i} of {len(time_locations)}') + one_nwp_df = get_nwp_for_one_timestamp_one_location(row['timestamp'], row['latitude'], row['longitude']) + + one_nwp_df['timestamp'] = row['timestamp'] + one_nwp_df['pv_id'] = row['pv_id'] + one_nwp_df['latitude'] = row['latitude'] + one_nwp_df['longitude'] = row['longitude'] + + all_nwp_dfs.append(one_nwp_df) + + all_nwp_df = pd.concat(all_nwp_dfs) + + return all_nwp_df + + +def get_nwp_for_one_timestamp_one_location( + timestamp: pd.Timestamp, latitude, longitude +): + """ + Get NWP data from Hugging Face for one timestamp and one location + + :param timestamp: the timestamp for when you want the forecast for + :param location: the location for when you want the forecast for + :return: nwp forecast in xarray + """ + + # TODO add caching + + fs = HfFileSystem() + # List which files are available. Not all dates, and model run times are available + # print(fs.ls("datasets/openclimatefix/dwd-icon-eu/data/2022/4/11/", detail=False)) + + # round timestamp to 6 hours floor + timestamp = timestamp.floor("6H") + year = timestamp.year + month = timestamp.month + day = timestamp.day + date_and_hour = timestamp.strftime("%Y%m%d_%H") + + date = f"{year}/{month}/{day}" + file_location = f"{date}/{date_and_hour}.zarr.zip" + huggingface_route = "zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data" + #huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data" + huggingface_file = f"{huggingface_route}/{file_location}" + + # TODO add cache so we only need to download this file once + # see if this file exists in the cache + # cache_dir = 'data/nwp' + # cache_file = f"{cache_dir}/{file_location}" + # if not os.path.exists(cache_file): + # # use fsspec to copy file + # print('copying file { from HF to local') + # os.makedirs(f'{cache_dir}/{date}', exist_ok=True) + # fs.get(f"{huggingface_route}/{file_location}", f"{cache_file}") + + data = xr.open_zarr( + f"{huggingface_file}", + chunks="auto", + ) + + # take nearest location + data_at_location = data.sel(latitude=latitude, longitude=longitude, method="nearest") + + # select the following variables + # "visibility": "vis", + # "windspeed_10m": "si10", from u and v + # "temperature_2m": "t_2m", + # "precipitation": "tot_prec", + # "shortwave_radiation": "aswdifd_s", + # "direct_radiation": "aswdir_s", + # "cloudcover_low": "clcl", + # "cloudcover_mid": "clcm", + # "cloudcover_high": "clch", + variables = ["t_2m", "tot_prec", "clch", "clcm", "clcl", "u", "v", "aswdir_s", "aswdifd_s"] + data_at_location = data_at_location[variables] + + # choise the first isobaricInhPa + data_at_location = data_at_location.isel(isobaricInhPa=-1) + + # reduce to 54 hours timestaps, this means there is at least a 48 hours forecast + data_at_location = data_at_location.isel(step=slice(0, 54)) + + # matke times from the init time + steps + times = pd.to_datetime(data_at_location.time.values) + pd.to_timedelta( + data_at_location.step.values, unit="h" + ) + + # load all the data, this can take about ~1 minute seconds + print(f"Loading dataset for {timestamp=} {longitude=} {latitude=}") + data_at_location.load() + + # convert to pandas dataframe + df = pd.DataFrame(times, columns=["timestamp"]) + for variable in variables: + print(variable) + df[variable] = data_at_location[variable].values + + # make wind speed out of u and v + df["windspeed_10m"] = (df["u"] ** 2 + df["v"] ** 2) ** 0.5 + + # rename variables + df = df.rename( + columns={ + "t_2m": "temperature_2m", + "tot_prec": "precipitation", + "aswdifd_s": "shortwave_radiation", + "aswdir_s": "direct_radiation", + "clcl": "cloudcover_low", + "clcm": "cloudcover_mid", + "clch": "cloudcover_high", + } + ) + + # add visbility for the moment + # TODO + df["visibility"] = 10000 + + # drop u and v + df = df.drop(columns=["u", "v"]) + + return df diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 5baadd70..18a90646 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -5,30 +5,28 @@ This contains 50 sites each with 50 timestamps to make 2500 samples in total. """ +from quartz_solar_forecast.eval.nwp import get_nwp -def run_eval(testset_path): - # load testset from csv - testset = df.read_csv(testset_path) - - # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. (Zak) - - - # Split data into PV inputs and ground truth. (Zak) +import pandas as pd - # Collect NWP data from Hugging Face, ICON. (Peter) - - - # Run forecast with PV and NWP inputs. +def run_eval(testset_path): + # load testset from csv + testset = pd.read_csv(testset_path) + # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. (Zak) - # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) + # Split data into PV inputs and ground truth. (Zak) + # Collect NWP data from Hugging Face, ICON. (Peter) + nwp_df = get_nwp(testset) - # Save file + # Run forecast with PV and NWP inputs. + # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) - # Calculate and print metrics: MAE + # Save file + # Calculate and print metrics: MAE - # Visulisations + # Visulisations diff --git a/requirements.txt b/requirements.txt index 8d28cade..22a6709b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,5 @@ pandas xarray pv-site-prediction -pydantic \ No newline at end of file +pydantic +huggingface_hub # only for evaluation \ No newline at end of file From 8f134e8d3720a0ff603003cb656379ae14b27028 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 14:01:08 +0000 Subject: [PATCH 06/52] add test nwp --- quartz_solar_forecast/eval/nwp.py | 103 +++++++++++++++--------------- tests/eval/test_nwp.py | 20 ++++++ 2 files changed, 70 insertions(+), 53 deletions(-) create mode 100644 tests/eval/test_nwp.py diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 14634fe4..1829f84b 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -1,12 +1,13 @@ """ Get nwp data from HF""" +import os import pandas as pd -import ocf_blosc2 # noqa +import ocf_blosc2 # noqa import xarray as xr from huggingface_hub import HfFileSystem -def get_nwp(time_locations:pd.DataFrame): +def get_nwp(time_locations: pd.DataFrame): """ Get all the nwp data fpr the time locations @@ -19,13 +20,15 @@ def get_nwp(time_locations:pd.DataFrame): all_nwp_dfs = [] for i, row in time_locations.iterrows(): - print(f'{i} of {len(time_locations)}') - one_nwp_df = get_nwp_for_one_timestamp_one_location(row['timestamp'], row['latitude'], row['longitude']) + print(f"{i} of {len(time_locations)}") + one_nwp_df = get_nwp_for_one_timestamp_one_location( + row["timestamp"], row["latitude"], row["longitude"] + ) - one_nwp_df['timestamp'] = row['timestamp'] - one_nwp_df['pv_id'] = row['pv_id'] - one_nwp_df['latitude'] = row['latitude'] - one_nwp_df['longitude'] = row['longitude'] + one_nwp_df["timestamp"] = row["timestamp"] + one_nwp_df["pv_id"] = row["pv_id"] + one_nwp_df["latitude"] = row["latitude"] + one_nwp_df["longitude"] = row["longitude"] all_nwp_dfs.append(one_nwp_df) @@ -34,14 +37,14 @@ def get_nwp(time_locations:pd.DataFrame): return all_nwp_df -def get_nwp_for_one_timestamp_one_location( - timestamp: pd.Timestamp, latitude, longitude -): +def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, longitude): """ Get NWP data from Hugging Face for one timestamp and one location :param timestamp: the timestamp for when you want the forecast for - :param location: the location for when you want the forecast for + :param latitude: the latitude of the location + :param longitude: the longitude of the location + :return: nwp forecast in xarray """ @@ -59,57 +62,51 @@ def get_nwp_for_one_timestamp_one_location( date_and_hour = timestamp.strftime("%Y%m%d_%H") date = f"{year}/{month}/{day}" - file_location = f"{date}/{date_and_hour}.zarr.zip" + file_location = f"{date}/{date_and_hour}" huggingface_route = "zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data" - #huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data" - huggingface_file = f"{huggingface_route}/{file_location}" - - # TODO add cache so we only need to download this file once - # see if this file exists in the cache - # cache_dir = 'data/nwp' - # cache_file = f"{cache_dir}/{file_location}" - # if not os.path.exists(cache_file): - # # use fsspec to copy file - # print('copying file { from HF to local') - # os.makedirs(f'{cache_dir}/{date}', exist_ok=True) - # fs.get(f"{huggingface_route}/{file_location}", f"{cache_file}") - - data = xr.open_zarr( - f"{huggingface_file}", - chunks="auto", - ) + # huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data" + huggingface_file = f"{huggingface_route}/{file_location}.zarr.zip" - # take nearest location - data_at_location = data.sel(latitude=latitude, longitude=longitude, method="nearest") - - # select the following variables - # "visibility": "vis", - # "windspeed_10m": "si10", from u and v - # "temperature_2m": "t_2m", - # "precipitation": "tot_prec", - # "shortwave_radiation": "aswdifd_s", - # "direct_radiation": "aswdir_s", - # "cloudcover_low": "clcl", - # "cloudcover_mid": "clcm", - # "cloudcover_high": "clch", + # dataset variables variables = ["t_2m", "tot_prec", "clch", "clcm", "clcl", "u", "v", "aswdir_s", "aswdifd_s"] - data_at_location = data_at_location[variables] - # choise the first isobaricInhPa - data_at_location = data_at_location.isel(isobaricInhPa=-1) + cache_dir = "data/nwp" + cache_file = f"{cache_dir}/{file_location}_{latitude}_{longitude}.zarr" + if not os.path.exists(cache_file): + # use fsspec to copy file + print(f"Opening file {huggingface_file} from HF to local") + + data = xr.open_zarr( + f"{huggingface_file}", + chunks="auto", + ) + + # take nearest location and only select the variables we want + data_at_location = data.sel(latitude=latitude, longitude=longitude, method="nearest") + data_at_location = data_at_location[variables] - # reduce to 54 hours timestaps, this means there is at least a 48 hours forecast - data_at_location = data_at_location.isel(step=slice(0, 54)) + # choise the first isobaricInhPa + data_at_location = data_at_location.isel(isobaricInhPa=-1) - # matke times from the init time + steps + # reduce to 54 hours timestaps, this means there is at least a 48 hours forecast + data_at_location = data_at_location.isel(step=slice(0, 54)) + + # load all the data, this can take about ~1 minute seconds + print(f"Loading dataset for {timestamp=} {longitude=} {latitude=}") + data_at_location.load() + + # save to cache + data_at_location.to_zarr(cache_file) + else: + # load from cache + print("loading from cache") + data_at_location = xr.open_zarr(cache_file) + + # make times from the init time + steps times = pd.to_datetime(data_at_location.time.values) + pd.to_timedelta( data_at_location.step.values, unit="h" ) - # load all the data, this can take about ~1 minute seconds - print(f"Loading dataset for {timestamp=} {longitude=} {latitude=}") - data_at_location.load() - # convert to pandas dataframe df = pd.DataFrame(times, columns=["timestamp"]) for variable in variables: diff --git a/tests/eval/test_nwp.py b/tests/eval/test_nwp.py new file mode 100644 index 00000000..e9c3659b --- /dev/null +++ b/tests/eval/test_nwp.py @@ -0,0 +1,20 @@ +from quartz_solar_forecast.eval.nwp import get_nwp +import pandas as pd + + +# can take ~ 1 minute to run +def test_get_nwp(): + # make test dataset file + test_set_df = pd.DataFrame( + [ + { + "timestamp": pd.Timestamp("2021-01-26 01:15:00"), + "latitude": 51.5, + "longitude": 0.0, + "pv_id": 0, + } + ] + ) + + # Collect NWP data from Hugging Face, ICON. (Peter) + _ = get_nwp(test_set_df) From 2579f43d91b74f3185d34be13ecfd39ceff7be10 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 14:47:11 +0000 Subject: [PATCH 07/52] add function to run forecast --- quartz_solar_forecast/eval/forecast.py | 102 +++++++++++++++++++++++++ quartz_solar_forecast/evaluation.py | 3 + tests/eval/test_eval_forecast.py | 71 +++++++++++++++++ 3 files changed, 176 insertions(+) create mode 100644 quartz_solar_forecast/eval/forecast.py create mode 100644 tests/eval/test_eval_forecast.py diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py new file mode 100644 index 00000000..dcdea612 --- /dev/null +++ b/quartz_solar_forecast/eval/forecast.py @@ -0,0 +1,102 @@ +import os +import pandas as pd +import xarray as xr +from psp.data_sources.nwp import NwpDataSource +from psp.data_sources.pv import NetcdfPvDataSource +from psp.serialization import load_model +from psp.typings import X + +from quartz_solar_forecast.data import get_nwp, make_pv_data +from quartz_solar_forecast.pydantic_models import PVSite + +from datetime import datetime + +dir_path = os.path.dirname(os.path.realpath(__file__)) + + +def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") -> pd.DataFrame: + """ + Run the forecast from NWP data + + :param pv_df: the PV site data. This should have columns timestamp, id, latitude, longitude, and capacity + :param nwp_df: all the nwp data for the site and location. This shoulw have the following rows + - timestamp: the timestamp of the site + - temperature_2m + - precipitation + - shortwave_radiation + - direct_radiation", + - cloudcover_low", + - cloudcover_mid", + - cloudcover_high", + maybe more + """ + + # load model only once + model = load_model(f"{dir_path}/../models/model-0.3.0.pkl") + + all_predictions = [] + for i in range(len(pv_df)): + + pv_row = pv_df.iloc[i] + + site = PVSite( + latitude=pv_row["latitude"], + longitude=pv_row["longitude"], + capacity_kwp=pv_row["capacity"], + ) + + nwp_site_df = nwp_df[ + (nwp_df["id"] == pv_row.pv_id) & (nwp_df["timestamp"] == pv_row.timestamp) + ] + + pv_id = pv_df["pv_id"][i] + ts = pv_df["timestamp"][i] + + # format + times = nwp_site_df["time"] + step = times - ts + nwp_site_df = nwp_site_df.drop(columns=["id", "timestamp"]) + nwp_site_df.set_index("time", inplace=True, drop=True) + + if isinstance(ts, str): + ts = datetime.fromisoformat(ts) + + # make pv and nwp data from GFS + nwp_xr = xr.DataArray( + data=nwp_site_df.values, + dims=["step", "variable"], + coords=dict( + step=("step", step), + variable=nwp_site_df.columns, + ), + ) + nwp_xr = nwp_xr.to_dataset(name=nwp_source) + nwp_xr = nwp_xr.assign_coords( + {"x": [site.longitude], "y": [site.latitude], "time": [nwp_site_df.index[0]]} + ) + + pv_xr = make_pv_data(site=site, ts=ts) + + # format pv and nwp data + pv_data_source = NetcdfPvDataSource( + pv_xr, + id_dim_name="pv_id", + timestamp_dim_name="timestamp", + rename={"generation_wh": "power", "kwp": "capacity"}, + ignore_pv_ids=[], + ) + # make NwpDataSource + nwp = NwpDataSource(paths_or_data=nwp_xr, value_name=nwp_source) + model.set_data_sources(pv_data_source=pv_data_source, nwp_data_sources={nwp_source: nwp}) + + # make prediction # TODO change '1' + x = X(pv_id="1", ts=ts) + pred = model.predict(x) + + # format into timerange and put into pd dataframe + times = pd.date_range(start=x.ts, periods=len(pred.powers), freq="15min") + pred_df = pd.DataFrame({"power_wh": pred.powers}, index=times) + + all_predictions.append(pred_df) + + return pd.concat(all_predictions) diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 18a90646..b76f88c6 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -6,6 +6,7 @@ """ from quartz_solar_forecast.eval.nwp import get_nwp +from quartz_solar_forecast.eval.forecast import run_forecast import pandas as pd @@ -22,6 +23,8 @@ def run_eval(testset_path): nwp_df = get_nwp(testset) # Run forecast with PV and NWP inputs. + # TODO updatepv_df + predictions_df = run_forecast(pv_df=None, nwp_df=nwp_df) # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) diff --git a/tests/eval/test_eval_forecast.py b/tests/eval/test_eval_forecast.py new file mode 100644 index 00000000..a660d24e --- /dev/null +++ b/tests/eval/test_eval_forecast.py @@ -0,0 +1,71 @@ +from quartz_solar_forecast.eval.forecast import run_forecast + +import pandas as pd + + +def test_run_forecast(): + pv_df = pd.DataFrame( + [ + { + "timestamp": pd.Timestamp("2021-01-26 01:15:00"), + "latitude": 51.5, + "longitude": 0.0, + "capacity": 1.0, + "pv_id": 1.0, + } + ] + ) + + nwp_df = pd.DataFrame( + columns=[ + "id", + "timestamp", + "t", + "prate", + "dswrf", + "dlwrf", + "lcc", + "mcc", + "hcc", + "vis", + "si10", + "time", + ], + data=[ + [ + 1, + pd.Timestamp("2021-01-26 01:15:00"), + 1.0, + 1.0, + 1.0, + 1.0, + 0.0, + 0.0, + 0.0, + 0, + 0, + pd.Timestamp("2021-01-26 01:15:00"), + ], + [ + 1, + pd.Timestamp("2021-01-26 01:15:00"), + 1.0, + 1.0, + 1.0, + 1.0, + 0.0, + 0.0, + 0.0, + 0, + 0, + pd.Timestamp("2021-01-26 01:30:00"), + ], + ], + ) + + # format timestamp + pv_df["timestamp"] = pd.to_datetime(pv_df["timestamp"]) + nwp_df["timestamp"] = pd.to_datetime(nwp_df["timestamp"]) + nwp_df["time"] = pd.to_datetime(nwp_df["time"]) + + _ = run_forecast(pv_df=pv_df, nwp_df=nwp_df, nwp_source="ICON") From b8e3b79f29438d9ed406a569a52328d9e34ce462 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 15:21:47 +0000 Subject: [PATCH 08/52] add combine method --- quartz_solar_forecast/eval/forecast.py | 5 ++++ quartz_solar_forecast/eval/utils.py | 36 ++++++++++++++++++++++++++ quartz_solar_forecast/evaluation.py | 4 +++ 3 files changed, 45 insertions(+) create mode 100644 quartz_solar_forecast/eval/utils.py diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index dcdea612..68205bb8 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -62,6 +62,7 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - ts = datetime.fromisoformat(ts) # make pv and nwp data from GFS + # TODO move this to model nwp_xr = xr.DataArray( data=nwp_site_df.values, dims=["step", "variable"], @@ -97,6 +98,10 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - times = pd.date_range(start=x.ts, periods=len(pred.powers), freq="15min") pred_df = pd.DataFrame({"power_wh": pred.powers}, index=times) + # only select hourly predictions + pred_df = pred_df.resample("1H").mean() + pred_df["horizon_hours"] = range(0, len(pred_df)) + all_predictions.append(pred_df) return pd.concat(all_predictions) diff --git a/quartz_solar_forecast/eval/utils.py b/quartz_solar_forecast/eval/utils.py new file mode 100644 index 00000000..61c0c2a5 --- /dev/null +++ b/quartz_solar_forecast/eval/utils.py @@ -0,0 +1,36 @@ +import pandas as pd + + + + + +def combine_forecast_ground_truth(forecast_df, ground_truth_df): + """ + Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) + + + forecast_df should have the following columns + - timestamp + - pv_id + - horizon_hours + - power + + ground_truth_df should have the following columns + - timestamp + - pv_id + - horizon_hours + - power + + """ + + # rename power to forecast_power + forecast_df = forecast_df.rename(columns={"power": "forecast_power"}) + + # rename power to ground_truth_power + ground_truth_df = ground_truth_df.rename(columns={"power": "ground_truth_power"}) + + # merge the two dataframes + combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hours"]) + + return combined_df + diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index b76f88c6..e8df1f75 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -7,6 +7,7 @@ """ from quartz_solar_forecast.eval.nwp import get_nwp from quartz_solar_forecast.eval.forecast import run_forecast +from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth import pandas as pd @@ -18,6 +19,7 @@ def run_eval(testset_path): # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. (Zak) # Split data into PV inputs and ground truth. (Zak) + ground_truth_df = None # TODO # Collect NWP data from Hugging Face, ICON. (Peter) nwp_df = get_nwp(testset) @@ -27,8 +29,10 @@ def run_eval(testset_path): predictions_df = run_forecast(pv_df=None, nwp_df=nwp_df) # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) + results_df = combine_forecast_ground_truth(predictions_df, ground_truth_df) # Save file + results_df.to_csv("results.csv") # Calculate and print metrics: MAE From 7b64c0cd0cf86bf4f31b7163cd7be4b9b103911f Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 15:26:31 +0000 Subject: [PATCH 09/52] add simple metrics --- quartz_solar_forecast/eval/utils.py | 9 ++++++++- quartz_solar_forecast/evaluation.py | 6 +++++- 2 files changed, 13 insertions(+), 2 deletions(-) diff --git a/quartz_solar_forecast/eval/utils.py b/quartz_solar_forecast/eval/utils.py index 61c0c2a5..e1e5ccf5 100644 --- a/quartz_solar_forecast/eval/utils.py +++ b/quartz_solar_forecast/eval/utils.py @@ -21,13 +21,20 @@ def combine_forecast_ground_truth(forecast_df, ground_truth_df): - horizon_hours - power + returns a dataframe with the following columns + - timestamp + - pv_id + - horizon_hours + - forecast_power + - generation_power + """ # rename power to forecast_power forecast_df = forecast_df.rename(columns={"power": "forecast_power"}) # rename power to ground_truth_power - ground_truth_df = ground_truth_df.rename(columns={"power": "ground_truth_power"}) + ground_truth_df = ground_truth_df.rename(columns={"power": "generation_power"}) # merge the two dataframes combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hours"]) diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index e8df1f75..a79104b4 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -25,7 +25,7 @@ def run_eval(testset_path): nwp_df = get_nwp(testset) # Run forecast with PV and NWP inputs. - # TODO updatepv_df + # TODO update pv_df predictions_df = run_forecast(pv_df=None, nwp_df=nwp_df) # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) @@ -35,5 +35,9 @@ def run_eval(testset_path): results_df.to_csv("results.csv") # Calculate and print metrics: MAE + mae = (results_df["forecast_power"] - results_df['generation_power']).abs().mean() + print(f"MAE: {mae}") + # TODO: add more metrics using ocf_ml_metrics # Visulisations + From d5bac61b47063f92dbe6c2b85d6b0bd54202ad4b Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 15:32:59 +0000 Subject: [PATCH 10/52] refactor into metrics file --- quartz_solar_forecast/eval/__init__.py | 0 quartz_solar_forecast/eval/metrics.py | 29 ++++++++++++++++++++++++++ quartz_solar_forecast/evaluation.py | 6 +++--- tests/eval/test_metrics.py | 20 ++++++++++++++++++ 4 files changed, 52 insertions(+), 3 deletions(-) create mode 100644 quartz_solar_forecast/eval/__init__.py create mode 100644 quartz_solar_forecast/eval/metrics.py create mode 100644 tests/eval/test_metrics.py diff --git a/quartz_solar_forecast/eval/__init__.py b/quartz_solar_forecast/eval/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/quartz_solar_forecast/eval/metrics.py b/quartz_solar_forecast/eval/metrics.py new file mode 100644 index 00000000..94e9ec05 --- /dev/null +++ b/quartz_solar_forecast/eval/metrics.py @@ -0,0 +1,29 @@ +def metrics(results_df): + """ + Calculate and print metrics: MAE + + results_df dataframe with the following columns + - timestamp + - pv_id + - horizon_hours + - forecast_power + - generation_power + + """ + + mae = (results_df["forecast_power"] - results_df['generation_power']).abs().mean() + print(f"MAE: {mae}") + + # calculate metrics over the different horizons hours + # find all unique horizon_hours + horizon_hours = results_df["horizon_hours"].unique() + for horizon_hour in horizon_hours: + # filter results_df to only include the horizon_hour + results_df_horizon = results_df[results_df["horizon_hours"] == horizon_hour] + mae = (results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().mean() + print(f"MAE for horizon {horizon_hour}: {mae}") + + # TODO add more metrics using ocf_ml_metrics + + + diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index a79104b4..8a03a00a 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -5,6 +5,7 @@ This contains 50 sites each with 50 timestamps to make 2500 samples in total. """ +from quartz_solar_forecast.eval.metrics import metrics from quartz_solar_forecast.eval.nwp import get_nwp from quartz_solar_forecast.eval.forecast import run_forecast from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth @@ -35,9 +36,8 @@ def run_eval(testset_path): results_df.to_csv("results.csv") # Calculate and print metrics: MAE - mae = (results_df["forecast_power"] - results_df['generation_power']).abs().mean() - print(f"MAE: {mae}") - # TODO: add more metrics using ocf_ml_metrics + metrics(results_df) # Visulisations + diff --git a/tests/eval/test_metrics.py b/tests/eval/test_metrics.py new file mode 100644 index 00000000..442cacc6 --- /dev/null +++ b/tests/eval/test_metrics.py @@ -0,0 +1,20 @@ +from quartz_solar_forecast.eval.metrics import metrics +import pandas as pd +import numpy as np + + +def test_metrics(): + + # create a fake dataframe + + results_df = pd.DataFrame( + columns=[ + "id", + "timestamp", + "horizon_hours", + "forecast_power", + "generation_power", + ], data=np.random.random((100,5))) + + # call the metrics function + metrics(results_df) \ No newline at end of file From 93100704edee6d1f7a2962cf4a219a54e7c1ccf1 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 16:01:20 +0000 Subject: [PATCH 11/52] add pv get metadata --- quartz_solar_forecast/eval/pv.py | 39 +++++++++++++++++++++++++++++ quartz_solar_forecast/evaluation.py | 6 +++-- 2 files changed, 43 insertions(+), 2 deletions(-) create mode 100644 quartz_solar_forecast/eval/pv.py diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py new file mode 100644 index 00000000..9e811274 --- /dev/null +++ b/quartz_solar_forecast/eval/pv.py @@ -0,0 +1,39 @@ +import os + +import pandas as pd +from huggingface_hub import HfFileSystem + +fs = HfFileSystem() + + +def get_pv_metadata(testset: pd.DataFrame): + + # download from hugginface or load from cache + cache_dir = "data/pv" + metadata_file = f"{cache_dir}/metadata.csv" + if not os.path.exists(metadata_file): + os.makedirs(cache_dir, exist_ok=True) + fs.get("datasets/openclimatefix/uk_pv/metadata.csv", metadata_file) + + # Load in the dataset + metadata_df = pd.read_csv(metadata_file) + + # join metadata with testset + metadata_df = metadata_df.rename(columns={"ss_id": "pv_id"}) + combined_data = testset.merge(metadata_df, on="pv_id", how="left") + + # only keep the columns we need + combined_data = combined_data[ + ["pv_id", "datetime", "latitude_rounded", "longitude_rounded", "kwp"] + ] + + # rename latitude_rounded to latitude and longitude_rounded to longitude + combined_data = combined_data.rename( + columns={ + "latitude_rounded": "latitude", + "longitude_rounded": "longitude", + "kwp": "capacity", + } + ) + + return combined_data diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 8a03a00a..f9348d30 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -9,15 +9,17 @@ from quartz_solar_forecast.eval.nwp import get_nwp from quartz_solar_forecast.eval.forecast import run_forecast from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth +from quartz_solar_forecast.eval.pv import get_pv_metadata import pandas as pd -def run_eval(testset_path): +def run_eval(testset_path = 'quartz_solar_forecast/dataset/testset.csv'): # load testset from csv testset = pd.read_csv(testset_path) # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. (Zak) + pv_metadata=get_pv_metadata(testset) # Split data into PV inputs and ground truth. (Zak) ground_truth_df = None # TODO @@ -27,7 +29,7 @@ def run_eval(testset_path): # Run forecast with PV and NWP inputs. # TODO update pv_df - predictions_df = run_forecast(pv_df=None, nwp_df=nwp_df) + predictions_df = run_forecast(pv_df=pv_metadata, nwp_df=nwp_df) # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) results_df = combine_forecast_ground_truth(predictions_df, ground_truth_df) From 81f16bba5b30f7eca600eba908a82b9daf733604 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 16:49:06 +0000 Subject: [PATCH 12/52] update + add test for evaluation --- quartz_solar_forecast/dataset/testset.csv | 2 +- quartz_solar_forecast/eval/forecast.py | 6 +++-- quartz_solar_forecast/eval/nwp.py | 28 +++++++++++++++-------- quartz_solar_forecast/eval/pv.py | 5 +++- quartz_solar_forecast/evaluation.py | 6 ++--- tests/eval/test_evaluation.py | 25 ++++++++++++++++++++ 6 files changed, 55 insertions(+), 17 deletions(-) create mode 100644 tests/eval/test_evaluation.py diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index 8506f1d0..d6d477dc 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -1,4 +1,4 @@ -pv_id,datetime +pv_id,timestamp 8215,2021-01-26 01:15:00 8215,2021-01-30 16:30:00 8215,2021-01-18 19:30:00 diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index 68205bb8..03b47315 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -46,7 +46,7 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - ) nwp_site_df = nwp_df[ - (nwp_df["id"] == pv_row.pv_id) & (nwp_df["timestamp"] == pv_row.timestamp) + (nwp_df["pv_id"] == pv_row.pv_id) & (nwp_df["timestamp"] == pv_row.timestamp) ] pv_id = pv_df["pv_id"][i] @@ -55,7 +55,9 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - # format times = nwp_site_df["time"] step = times - ts - nwp_site_df = nwp_site_df.drop(columns=["id", "timestamp"]) + nwp_site_df = nwp_site_df.drop( + columns=["timestamp", "latitude", "longitude", "pv_id"] + ) nwp_site_df.set_index("time", inplace=True, drop=True) if isinstance(ts, str): diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 1829f84b..f38ed540 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -106,34 +106,42 @@ def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, lo times = pd.to_datetime(data_at_location.time.values) + pd.to_timedelta( data_at_location.step.values, unit="h" ) + print(times) # convert to pandas dataframe - df = pd.DataFrame(times, columns=["timestamp"]) + df = pd.DataFrame(times, columns=["time"]) for variable in variables: print(variable) df[variable] = data_at_location[variable].values # make wind speed out of u and v - df["windspeed_10m"] = (df["u"] ** 2 + df["v"] ** 2) ** 0.5 + df["si10"] = (df["u"] ** 2 + df["v"] ** 2) ** 0.5 # rename variables df = df.rename( columns={ - "t_2m": "temperature_2m", - "tot_prec": "precipitation", - "aswdifd_s": "shortwave_radiation", - "aswdir_s": "direct_radiation", - "clcl": "cloudcover_low", - "clcm": "cloudcover_mid", - "clch": "cloudcover_high", + "t_2m": "t", + "tot_prec": "prate", + "aswdifd_s": "dswrf", + "aswdir_s": "dlwrf", + "clcl": "lcc", + "clcm": "mcc", + "clch": "hcc", } ) # add visbility for the moment # TODO - df["visibility"] = 10000 + df["vis"] = 10000 # drop u and v df = df.drop(columns=["u", "v"]) + # rename id to pv_id + df = df.rename(columns={"id": "pv_id"}) + return df + + +{'t_isnan', 'prate_isnan', 'lcc', 'h_mean_nan', 't', 'poa_global_now_is_zero', 'dswrf_isnan', 'h_median_nan', 'dlwrf', 'recent_power', 'capacity', 'h_median', 'dlwrf_isnan', 'vis_isnan', 'hcc_isnan', 'mcc', 'h_max_nan', 'vis', 'dswrf', 'recent_power_nan', 'h_mean', 'hcc', 'poa_global', 'h_max', 'mcc_isnan', 'si10', 'si10_isnan', 'lcc_isnan', 'prate'} != \ +{'shortwave_radiation', 'h_mean_nan', 'poa_global_now_is_zero', 'windspeed_10m_isnan', 'longitude', 'h_median_nan', 'windspeed_10m', 'recent_power', 'capacity', 'h_median', 'precipitation_isnan', 'direct_radiation', 'cloudcover_mid', 'temperature_2m_isnan', 'cloudcover_low', 'temperature_2m', 'visibility', 'h_max_nan', 'visibility_isnan', 'cloudcover_high_isnan', 'shortwave_radiation_isnan', 'longitude_isnan', 'h_mean', 'cloudcover_low_isnan', 'recent_power_nan', 'cloudcover_high', 'pv_id_isnan', 'poa_global', 'h_max', 'latitude_isnan', 'latitude', 'cloudcover_mid_isnan', 'pv_id', 'precipitation', 'direct_radiation_isnan'} diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index 9e811274..36bd2410 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -24,7 +24,7 @@ def get_pv_metadata(testset: pd.DataFrame): # only keep the columns we need combined_data = combined_data[ - ["pv_id", "datetime", "latitude_rounded", "longitude_rounded", "kwp"] + ["pv_id", "timestamp", "latitude_rounded", "longitude_rounded", "kwp"] ] # rename latitude_rounded to latitude and longitude_rounded to longitude @@ -36,4 +36,7 @@ def get_pv_metadata(testset: pd.DataFrame): } ) + # format datetime + combined_data['timestamp'] = pd.to_datetime(combined_data['timestamp']) + return combined_data diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index f9348d30..697568bf 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -14,18 +14,18 @@ import pandas as pd -def run_eval(testset_path = 'quartz_solar_forecast/dataset/testset.csv'): +def run_eval(testset_path: str = 'quartz_solar_forecast/dataset/testset.csv'): # load testset from csv testset = pd.read_csv(testset_path) # Extract generation data and metadata for specific sites and timestamps for the testset from Hugging Face. (Zak) - pv_metadata=get_pv_metadata(testset) + pv_metadata = get_pv_metadata(testset) # Split data into PV inputs and ground truth. (Zak) ground_truth_df = None # TODO # Collect NWP data from Hugging Face, ICON. (Peter) - nwp_df = get_nwp(testset) + nwp_df = get_nwp(pv_metadata) # Run forecast with PV and NWP inputs. # TODO update pv_df diff --git a/tests/eval/test_evaluation.py b/tests/eval/test_evaluation.py new file mode 100644 index 00000000..630b7068 --- /dev/null +++ b/tests/eval/test_evaluation.py @@ -0,0 +1,25 @@ +from quartz_solar_forecast.evaluation import run_eval +import tempfile +import pandas as pd + + +def test_run_eval(): + + # create a fake dataframe + + with tempfile.TemporaryDirectory() as tmpdirname: + print("created temporary directory", tmpdirname) + + test_dataset = pd.DataFrame( + columns=[ + "pv_id", + "timestamp", + ], + data=[[8215, "2021-01-26 01:15:00"], [8215, "2021-01-30 16:30:00"]], + ) + + testset_path = tmpdirname + "/test_dataset.csv" + test_dataset.to_csv(testset_path, index=False) + + # call the metrics function + run_eval(testset_path) From 0ff890401d4fe00aa3f76b3a9d90e6110115a9cd Mon Sep 17 00:00:00 2001 From: Megawattz <47150349+zakwatts@users.noreply.github.com> Date: Tue, 12 Dec 2023 17:02:44 +0000 Subject: [PATCH 13/52] Update pv.py --- quartz_solar_forecast/eval/pv.py | 33 ++++++++++++++++++++++++++++++++ 1 file changed, 33 insertions(+) diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index 36bd2410..166ca510 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -40,3 +40,36 @@ def get_pv_metadata(testset: pd.DataFrame): combined_data['timestamp'] = pd.to_datetime(combined_data['timestamp']) return combined_data + +def get_pv_truth(testset: pd.DataFrame): + + # download from hugginface or load from cache + cache_dir = "data/pv" + metadata_file = f"{cache_dir}/pv.netcdf" + if not os.path.exists(metadata_file): + os.makedirs(cache_dir, exist_ok=True) + fs.get("datasets/openclimatefix/uk_pv/pv.netcdf", pv_ds) + + # Load in the dataset + pv_ds = xr.open_dataset(metadata_file, engine="h5netcdf") + + for index, row in testset.iterrows(): + pv_id = str(row['pv_id']) + base_datetime = row['datetime'] + + # Calculate future timestamps up to the max horizon + for i in range(0, 49): # 48 hours in steps of 1 hour + future_datetime = base_datetime + DateOffset(hours=i) + horizon = i * 60 # Convert hours to minutes + + try: + # Attempt to select data for the future datetime + selected_data = pv_ds[pv_id].sel(datetime=future_datetime) + value = selected_data.values.item() + except KeyError: + # If data is not found for the future datetime, set value as NaN + value = np.nan + + # Add the data to the DataFrame + combined_data = combined_data.append({'pv_id': pv_id, 'datetime': base_datetime, + 'value': value, 'horizon': horizon}, ignore_index=True) From 6a9e7f7dbbce97e492dfebdcfd4d854ed049a42a Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 17:17:45 +0000 Subject: [PATCH 14/52] get test_eval working --- quartz_solar_forecast/eval/forecast.py | 8 ++++++-- quartz_solar_forecast/eval/metrics.py | 4 ++-- quartz_solar_forecast/eval/pv.py | 21 ++++++++++++++------- quartz_solar_forecast/eval/utils.py | 12 +++++++++--- quartz_solar_forecast/evaluation.py | 5 ++--- tests/eval/test_pv.py | 20 ++++++++++++++++++++ 6 files changed, 53 insertions(+), 17 deletions(-) create mode 100644 tests/eval/test_pv.py diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index 03b47315..c09b269c 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -102,8 +102,12 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - # only select hourly predictions pred_df = pred_df.resample("1H").mean() - pred_df["horizon_hours"] = range(0, len(pred_df)) + pred_df["horizon_hour"] = range(0, len(pred_df)) + pred_df["pv_id"] = pv_id all_predictions.append(pred_df) - return pd.concat(all_predictions) + all_predictions = pd.concat(all_predictions) + all_predictions['timestamp'] = all_predictions.index + + return all_predictions diff --git a/quartz_solar_forecast/eval/metrics.py b/quartz_solar_forecast/eval/metrics.py index 94e9ec05..9e96a76c 100644 --- a/quartz_solar_forecast/eval/metrics.py +++ b/quartz_solar_forecast/eval/metrics.py @@ -16,10 +16,10 @@ def metrics(results_df): # calculate metrics over the different horizons hours # find all unique horizon_hours - horizon_hours = results_df["horizon_hours"].unique() + horizon_hours = results_df["horizon_hour"].unique() for horizon_hour in horizon_hours: # filter results_df to only include the horizon_hour - results_df_horizon = results_df[results_df["horizon_hours"] == horizon_hour] + results_df_horizon = results_df[results_df["horizon_hour"] == horizon_hour] mae = (results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().mean() print(f"MAE for horizon {horizon_hour}: {mae}") diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index 166ca510..fb8ef57b 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -1,6 +1,8 @@ import os import pandas as pd +import numpy as np +import xarray as xr from huggingface_hub import HfFileSystem fs = HfFileSystem() @@ -37,10 +39,11 @@ def get_pv_metadata(testset: pd.DataFrame): ) # format datetime - combined_data['timestamp'] = pd.to_datetime(combined_data['timestamp']) + combined_data["timestamp"] = pd.to_datetime(combined_data["timestamp"]) return combined_data + def get_pv_truth(testset: pd.DataFrame): # download from hugginface or load from cache @@ -48,18 +51,19 @@ def get_pv_truth(testset: pd.DataFrame): metadata_file = f"{cache_dir}/pv.netcdf" if not os.path.exists(metadata_file): os.makedirs(cache_dir, exist_ok=True) - fs.get("datasets/openclimatefix/uk_pv/pv.netcdf", pv_ds) + fs.get("datasets/openclimatefix/uk_pv/pv.netcdf", metadata_file) # Load in the dataset pv_ds = xr.open_dataset(metadata_file, engine="h5netcdf") + combined_data = [] for index, row in testset.iterrows(): - pv_id = str(row['pv_id']) - base_datetime = row['datetime'] + pv_id = str(row["pv_id"]) + base_datetime = pd.to_datetime(row["timestamp"]) # Calculate future timestamps up to the max horizon for i in range(0, 49): # 48 hours in steps of 1 hour - future_datetime = base_datetime + DateOffset(hours=i) + future_datetime = base_datetime + pd.DateOffset(hours=i) horizon = i * 60 # Convert hours to minutes try: @@ -71,5 +75,8 @@ def get_pv_truth(testset: pd.DataFrame): value = np.nan # Add the data to the DataFrame - combined_data = combined_data.append({'pv_id': pv_id, 'datetime': base_datetime, - 'value': value, 'horizon': horizon}, ignore_index=True) + combined_data.append(pd.DataFrame( + {"pv_id": pv_id, "timestamp": base_datetime, "value": value, "horizon_hour": horizon}, index=[i]) + ) + combined_data = pd.concat(combined_data) + return combined_data diff --git a/quartz_solar_forecast/eval/utils.py b/quartz_solar_forecast/eval/utils.py index e1e5ccf5..d9c33ab0 100644 --- a/quartz_solar_forecast/eval/utils.py +++ b/quartz_solar_forecast/eval/utils.py @@ -31,13 +31,19 @@ def combine_forecast_ground_truth(forecast_df, ground_truth_df): """ # rename power to forecast_power - forecast_df = forecast_df.rename(columns={"power": "forecast_power"}) + forecast_df = forecast_df.rename(columns={"power_wh": "forecast_power"}) # rename power to ground_truth_power - ground_truth_df = ground_truth_df.rename(columns={"power": "generation_power"}) + ground_truth_df = ground_truth_df.rename(columns={"value": "generation_power"}) + + # make pv_ids are ints + forecast_df["pv_id"] = forecast_df["pv_id"].astype(int) + ground_truth_df["pv_id"] = ground_truth_df["pv_id"].astype(int) # merge the two dataframes - combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hours"]) + print(forecast_df) + print(ground_truth_df) + combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hour"]) return combined_df diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 697568bf..cf9b682b 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -9,7 +9,7 @@ from quartz_solar_forecast.eval.nwp import get_nwp from quartz_solar_forecast.eval.forecast import run_forecast from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth -from quartz_solar_forecast.eval.pv import get_pv_metadata +from quartz_solar_forecast.eval.pv import get_pv_metadata, get_pv_truth import pandas as pd @@ -22,13 +22,12 @@ def run_eval(testset_path: str = 'quartz_solar_forecast/dataset/testset.csv'): pv_metadata = get_pv_metadata(testset) # Split data into PV inputs and ground truth. (Zak) - ground_truth_df = None # TODO + ground_truth_df = get_pv_truth(testset) # Collect NWP data from Hugging Face, ICON. (Peter) nwp_df = get_nwp(pv_metadata) # Run forecast with PV and NWP inputs. - # TODO update pv_df predictions_df = run_forecast(pv_df=pv_metadata, nwp_df=nwp_df) # Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) diff --git a/tests/eval/test_pv.py b/tests/eval/test_pv.py new file mode 100644 index 00000000..b015e0fb --- /dev/null +++ b/tests/eval/test_pv.py @@ -0,0 +1,20 @@ +from quartz_solar_forecast.eval.pv import get_pv_truth +import pandas as pd + + +# can take ~ 1 minute to run +def test_get_nwp(): + # make test dataset file + test_set_df = pd.DataFrame( + [ + { + "timestamp": pd.Timestamp("2021-01-26 01:15:00"), + "latitude": 51.5, + "longitude": 0.0, + "pv_id": 8215, + } + ] + ) + + # Collect NWP data from Hugging Face, ICON. (Peter) + _ = get_pv_truth(test_set_df) From 53c2e1c4d690f4e15b8734764db410f8ac572855 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 17:36:18 +0000 Subject: [PATCH 15/52] update --- quartz_solar_forecast/eval/nwp.py | 2 -- quartz_solar_forecast/eval/pv.py | 5 +++-- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index f38ed540..9078ca18 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -106,12 +106,10 @@ def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, lo times = pd.to_datetime(data_at_location.time.values) + pd.to_timedelta( data_at_location.step.values, unit="h" ) - print(times) # convert to pandas dataframe df = pd.DataFrame(times, columns=["time"]) for variable in variables: - print(variable) df[variable] = data_at_location[variable].values # make wind speed out of u and v diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index fb8ef57b..38dd9c97 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -64,19 +64,20 @@ def get_pv_truth(testset: pd.DataFrame): # Calculate future timestamps up to the max horizon for i in range(0, 49): # 48 hours in steps of 1 hour future_datetime = base_datetime + pd.DateOffset(hours=i) - horizon = i * 60 # Convert hours to minutes + horizon = i # horizon in hours try: # Attempt to select data for the future datetime selected_data = pv_ds[pv_id].sel(datetime=future_datetime) value = selected_data.values.item() + value = value /1000 *12 # to convert from wh to kw except KeyError: # If data is not found for the future datetime, set value as NaN value = np.nan # Add the data to the DataFrame combined_data.append(pd.DataFrame( - {"pv_id": pv_id, "timestamp": base_datetime, "value": value, "horizon_hour": horizon}, index=[i]) + {"pv_id": pv_id, "timestamp": future_datetime, "value": value, "horizon_hour": horizon}, index=[i]) ) combined_data = pd.concat(combined_data) return combined_data From d9f1adb5705e2f0e47ebc495f387b4755db56f4b Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 19:15:31 +0000 Subject: [PATCH 16/52] fix tests --- quartz_solar_forecast/dataset/testset.csv | 2 +- tests/data/test_make_test_set.py | 2 +- tests/eval/test_metrics.py | 2 +- tests/eval/test_pv.py | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index d6d477dc..8506f1d0 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -1,4 +1,4 @@ -pv_id,timestamp +pv_id,datetime 8215,2021-01-26 01:15:00 8215,2021-01-30 16:30:00 8215,2021-01-18 19:30:00 diff --git a/tests/data/test_make_test_set.py b/tests/data/test_make_test_set.py index a919602a..85e3f987 100644 --- a/tests/data/test_make_test_set.py +++ b/tests/data/test_make_test_set.py @@ -15,4 +15,4 @@ def test_make_test_set(): test_set = pd.read_csv(output_file) assert len(test_set) == 50 * 50 # we can check this as we have set the seed - assert test_set.iloc[0].datetime == "2021-01-26 01:15:00" + assert test_set.iloc[0].datetime == "2021-01-27 07:00:00" diff --git a/tests/eval/test_metrics.py b/tests/eval/test_metrics.py index 442cacc6..ecfb480e 100644 --- a/tests/eval/test_metrics.py +++ b/tests/eval/test_metrics.py @@ -11,7 +11,7 @@ def test_metrics(): columns=[ "id", "timestamp", - "horizon_hours", + "horizon_hour", "forecast_power", "generation_power", ], data=np.random.random((100,5))) diff --git a/tests/eval/test_pv.py b/tests/eval/test_pv.py index b015e0fb..89440340 100644 --- a/tests/eval/test_pv.py +++ b/tests/eval/test_pv.py @@ -3,7 +3,7 @@ # can take ~ 1 minute to run -def test_get_nwp(): +def test_get_pv(): # make test dataset file test_set_df = pd.DataFrame( [ From 674e69f1ffb6e4b7ba40757f641ccf6d86608b09 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 19:18:07 +0000 Subject: [PATCH 17/52] fix test_eval_forecast --- quartz_solar_forecast/eval/forecast.py | 7 ++++--- tests/eval/test_eval_forecast.py | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index c09b269c..b864cd90 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -55,9 +55,10 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - # format times = nwp_site_df["time"] step = times - ts - nwp_site_df = nwp_site_df.drop( - columns=["timestamp", "latitude", "longitude", "pv_id"] - ) + for c in ["timestamp", "latitude", "longitude", "pv_id"]: + if c in nwp_site_df.columns: + nwp_site_df = nwp_site_df.drop(columns=c) + nwp_site_df.set_index("time", inplace=True, drop=True) if isinstance(ts, str): diff --git a/tests/eval/test_eval_forecast.py b/tests/eval/test_eval_forecast.py index a660d24e..22f48fd2 100644 --- a/tests/eval/test_eval_forecast.py +++ b/tests/eval/test_eval_forecast.py @@ -18,7 +18,7 @@ def test_run_forecast(): nwp_df = pd.DataFrame( columns=[ - "id", + "pv_id", "timestamp", "t", "prate", From ebbf01d38637ce68dddedaee037ca8796fa6b141 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 19:25:39 +0000 Subject: [PATCH 18/52] rename cache nwp file --- quartz_solar_forecast/eval/nwp.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 9078ca18..911f352b 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -48,8 +48,6 @@ def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, lo :return: nwp forecast in xarray """ - # TODO add caching - fs = HfFileSystem() # List which files are available. Not all dates, and model run times are available # print(fs.ls("datasets/openclimatefix/dwd-icon-eu/data/2022/4/11/", detail=False)) @@ -71,7 +69,7 @@ def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, lo variables = ["t_2m", "tot_prec", "clch", "clcm", "clcl", "u", "v", "aswdir_s", "aswdifd_s"] cache_dir = "data/nwp" - cache_file = f"{cache_dir}/{file_location}_{latitude}_{longitude}.zarr" + cache_file = f"{cache_dir}/{date_and_hour}_lat={latitude}_lon={longitude}.zarr" if not os.path.exists(cache_file): # use fsspec to copy file print(f"Opening file {huggingface_file} from HF to local") From fab5b0c3ca643e934b9a28e7c684a6a4b4b8b3e7 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 19:37:32 +0000 Subject: [PATCH 19/52] refactor --- quartz_solar_forecast/data.py | 7 +++- quartz_solar_forecast/eval/forecast.py | 42 ++++----------------- quartz_solar_forecast/forecast.py | 33 +++------------- quartz_solar_forecast/forecasts/__init__.py | 0 quartz_solar_forecast/forecasts/v1.py | 42 +++++++++++++++++++++ 5 files changed, 61 insertions(+), 63 deletions(-) create mode 100644 quartz_solar_forecast/forecasts/__init__.py create mode 100644 quartz_solar_forecast/forecasts/v1.py diff --git a/quartz_solar_forecast/data.py b/quartz_solar_forecast/data.py index 4a368a3c..c97c45fa 100644 --- a/quartz_solar_forecast/data.py +++ b/quartz_solar_forecast/data.py @@ -91,6 +91,12 @@ def get_nwp(site: PVSite, ts: datetime, nwp_source: str = "icon") -> xr.Dataset: } ) df = df.set_index("time") + data_xr = format_nwp_data(df, nwp_source, site) + + return data_xr + + +def format_nwp_data(df, nwp_source, site): data_xr = xr.DataArray( data=df.values, dims=["step", "variable"], @@ -103,7 +109,6 @@ def get_nwp(site: PVSite, ts: datetime, nwp_source: str = "icon") -> xr.Dataset: data_xr = data_xr.assign_coords( {"x": [site.longitude], "y": [site.latitude], "time": [df.index[0]]} ) - return data_xr diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index b864cd90..adee42e0 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -8,6 +8,8 @@ from quartz_solar_forecast.data import get_nwp, make_pv_data from quartz_solar_forecast.pydantic_models import PVSite +from quartz_solar_forecast.forecasts.v1 import forecast_v1 +from quartz_solar_forecast.data import format_nwp_data from datetime import datetime @@ -53,53 +55,23 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - ts = pv_df["timestamp"][i] # format - times = nwp_site_df["time"] - step = times - ts + nwp_site_df["step"] = nwp_site_df["time"] - ts for c in ["timestamp", "latitude", "longitude", "pv_id"]: if c in nwp_site_df.columns: nwp_site_df = nwp_site_df.drop(columns=c) - nwp_site_df.set_index("time", inplace=True, drop=True) + nwp_site_df.set_index("step", inplace=True, drop=True) if isinstance(ts, str): ts = datetime.fromisoformat(ts) # make pv and nwp data from GFS # TODO move this to model - nwp_xr = xr.DataArray( - data=nwp_site_df.values, - dims=["step", "variable"], - coords=dict( - step=("step", step), - variable=nwp_site_df.columns, - ), - ) - nwp_xr = nwp_xr.to_dataset(name=nwp_source) - nwp_xr = nwp_xr.assign_coords( - {"x": [site.longitude], "y": [site.latitude], "time": [nwp_site_df.index[0]]} - ) - + nwp_xr = format_nwp_data(df=nwp_site_df, nwp_source=nwp_source, site=site) pv_xr = make_pv_data(site=site, ts=ts) - # format pv and nwp data - pv_data_source = NetcdfPvDataSource( - pv_xr, - id_dim_name="pv_id", - timestamp_dim_name="timestamp", - rename={"generation_wh": "power", "kwp": "capacity"}, - ignore_pv_ids=[], - ) - # make NwpDataSource - nwp = NwpDataSource(paths_or_data=nwp_xr, value_name=nwp_source) - model.set_data_sources(pv_data_source=pv_data_source, nwp_data_sources={nwp_source: nwp}) - - # make prediction # TODO change '1' - x = X(pv_id="1", ts=ts) - pred = model.predict(x) - - # format into timerange and put into pd dataframe - times = pd.date_range(start=x.ts, periods=len(pred.powers), freq="15min") - pred_df = pd.DataFrame({"power_wh": pred.powers}, index=times) + # run model + pred_df = forecast_v1(nwp_source, nwp_xr, pv_xr, ts, model=model) # only select hourly predictions pred_df = pred_df.resample("1H").mean() diff --git a/quartz_solar_forecast/forecast.py b/quartz_solar_forecast/forecast.py index c711bb6b..8e5ba3c2 100644 --- a/quartz_solar_forecast/forecast.py +++ b/quartz_solar_forecast/forecast.py @@ -1,16 +1,13 @@ import os import pandas as pd -from psp.data_sources.nwp import NwpDataSource -from psp.data_sources.pv import NetcdfPvDataSource -from psp.serialization import load_model -from psp.typings import X from quartz_solar_forecast.data import get_nwp, make_pv_data from quartz_solar_forecast.pydantic_models import PVSite from datetime import datetime -dir_path = os.path.dirname(os.path.realpath(__file__)) +from quartz_solar_forecast.forecasts.v1 import forecast_v1 + def run_forecast(site: PVSite, ts: datetime | str, nwp_source: str = "icon") -> pd.DataFrame: @@ -30,27 +27,9 @@ def run_forecast(site: PVSite, ts: datetime | str, nwp_source: str = "icon") -> nwp_xr = get_nwp(site=site, ts=ts) pv_xr = make_pv_data(site=site, ts=ts) - # load model - model = load_model(f"{dir_path}/models/model-0.3.0.pkl") - - # format pv and nwp data - pv_data_source = NetcdfPvDataSource( - pv_xr, - id_dim_name="pv_id", - timestamp_dim_name="timestamp", - rename={"generation_wh": "power", "kwp": "capacity"}, - ignore_pv_ids=[], - ) - # make NwpDataSource - nwp = NwpDataSource(nwp_xr, value_name=nwp_source) - model.set_data_sources(pv_data_source=pv_data_source, nwp_data_sources={nwp_source: nwp}) - - # make prediction - x = X(pv_id="1", ts=ts) - pred = model.predict(x) - - # format into timerange and put into pd dataframe - times = pd.date_range(start=x.ts, periods=len(pred.powers), freq="15min") - pred_df = pd.DataFrame({"power_wh": pred.powers}, index=times) + # load and run models + pred_df = forecast_v1(nwp_source, nwp_xr, pv_xr, ts) return pred_df + + diff --git a/quartz_solar_forecast/forecasts/__init__.py b/quartz_solar_forecast/forecasts/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/quartz_solar_forecast/forecasts/v1.py b/quartz_solar_forecast/forecasts/v1.py new file mode 100644 index 00000000..271925f7 --- /dev/null +++ b/quartz_solar_forecast/forecasts/v1.py @@ -0,0 +1,42 @@ +import pandas as pd +import xarray as xr +import os +from psp.data_sources.nwp import NwpDataSource +from psp.data_sources.pv import NetcdfPvDataSource +from psp.serialization import load_model +from psp.typings import X + +dir_path = os.path.dirname(os.path.realpath(__file__)) + + +def forecast_v1(nwp_source:str, nwp_xr:xr.Dataset, pv_xr:xr.Dataset, ts:pd.Timestamp, model=None): + """ + Run the forecast + + This runs the pv-site-prediction model from the psp library. + """ + + if model is None: + model = load_model(f"{dir_path}/../models/model-0.3.0.pkl") + + # format pv and nwp data + pv_data_source = NetcdfPvDataSource( + pv_xr, + id_dim_name="pv_id", + timestamp_dim_name="timestamp", + rename={"generation_wh": "power", "kwp": "capacity"}, + ignore_pv_ids=[], + ) + # make NwpDataSource + nwp = NwpDataSource(nwp_xr, value_name=nwp_source) + model.set_data_sources(pv_data_source=pv_data_source, nwp_data_sources={nwp_source: nwp}) + + # make prediction + x = X(pv_id="1", ts=ts) + pred = model.predict(x) + + # format into timerange and put into pd dataframe + times = pd.date_range(start=x.ts, periods=len(pred.powers), freq="15min") + pred_df = pd.DataFrame({"power_wh": pred.powers}, index=times) + + return pred_df From 3bdfb295a11fb087a45544d68cd8ff067c3acb16 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 19:40:07 +0000 Subject: [PATCH 20/52] add test for getting pv metadata --- tests/eval/test_pv.py | 18 ++++++++++++++++-- 1 file changed, 16 insertions(+), 2 deletions(-) diff --git a/tests/eval/test_pv.py b/tests/eval/test_pv.py index 89440340..00765bea 100644 --- a/tests/eval/test_pv.py +++ b/tests/eval/test_pv.py @@ -1,8 +1,22 @@ -from quartz_solar_forecast.eval.pv import get_pv_truth +from quartz_solar_forecast.eval.pv import get_pv_truth, get_pv_metadata import pandas as pd -# can take ~ 1 minute to run +def test_get_pv_metadata(): + test_set_df = pd.DataFrame( + [ + { + "timestamp": pd.Timestamp("2021-01-26 01:15:00"), + "latitude": 51.5, + "longitude": 0.0, + "pv_id": 8215, + } + ] + ) + + metadata_df = get_pv_metadata(test_set_df) + + def test_get_pv(): # make test dataset file test_set_df = pd.DataFrame( From 38daaad1f4d5f9ed3047e5748a4a1f5f28a03c9d Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 19:51:21 +0000 Subject: [PATCH 21/52] fix eval test --- quartz_solar_forecast/eval/forecast.py | 3 +-- tests/eval/test_pv.py | 5 +---- 2 files changed, 2 insertions(+), 6 deletions(-) diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index adee42e0..d3c872a8 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -55,12 +55,11 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - ts = pv_df["timestamp"][i] # format - nwp_site_df["step"] = nwp_site_df["time"] - ts for c in ["timestamp", "latitude", "longitude", "pv_id"]: if c in nwp_site_df.columns: nwp_site_df = nwp_site_df.drop(columns=c) - nwp_site_df.set_index("step", inplace=True, drop=True) + nwp_site_df.set_index("time", inplace=True, drop=True) if isinstance(ts, str): ts = datetime.fromisoformat(ts) diff --git a/tests/eval/test_pv.py b/tests/eval/test_pv.py index 00765bea..51739547 100644 --- a/tests/eval/test_pv.py +++ b/tests/eval/test_pv.py @@ -7,14 +7,13 @@ def test_get_pv_metadata(): [ { "timestamp": pd.Timestamp("2021-01-26 01:15:00"), - "latitude": 51.5, - "longitude": 0.0, "pv_id": 8215, } ] ) metadata_df = get_pv_metadata(test_set_df) + assert "latitude" in metadata_df.columns def test_get_pv(): @@ -23,8 +22,6 @@ def test_get_pv(): [ { "timestamp": pd.Timestamp("2021-01-26 01:15:00"), - "latitude": 51.5, - "longitude": 0.0, "pv_id": 8215, } ] From 4c8c2862949c3a0b3820097cc2f1dc22e5572048 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:19:19 +0000 Subject: [PATCH 22/52] update eval and hf logging in --- quartz_solar_forecast/eval/pv.py | 1 - quartz_solar_forecast/evaluation.py | 25 +++++++++++++++++++++---- tests/eval/test_evaluation.py | 6 +++--- 3 files changed, 24 insertions(+), 8 deletions(-) diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index 38dd9c97..4b5f1528 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -7,7 +7,6 @@ fs = HfFileSystem() - def get_pv_metadata(testset: pd.DataFrame): # download from hugginface or load from cache diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index cf9b682b..0e55b5a7 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -5,16 +5,32 @@ This contains 50 sites each with 50 timestamps to make 2500 samples in total. """ + +import os + +import pandas as pd +from huggingface_hub.hf_api import HfFolder + +from quartz_solar_forecast.eval.forecast import run_forecast from quartz_solar_forecast.eval.metrics import metrics from quartz_solar_forecast.eval.nwp import get_nwp -from quartz_solar_forecast.eval.forecast import run_forecast -from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth from quartz_solar_forecast.eval.pv import get_pv_metadata, get_pv_truth +from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth + +try: + + hf_token = os.environ["HF_TOKEN"] + HfFolder.save_token(hf_token) +except: + + print( + "Warning, you wont be able to run evaluation if you dont set your " + "Hugging Face Access Token to HF_TOKEN, or be logged in with Hugging Face" + ) -import pandas as pd -def run_eval(testset_path: str = 'quartz_solar_forecast/dataset/testset.csv'): +def run_eval(testset_path: str = "quartz_solar_forecast/dataset/testset2.csv"): # load testset from csv testset = pd.read_csv(testset_path) @@ -42,3 +58,4 @@ def run_eval(testset_path: str = 'quartz_solar_forecast/dataset/testset.csv'): # Visulisations +# run_eval() diff --git a/tests/eval/test_evaluation.py b/tests/eval/test_evaluation.py index 630b7068..e6548b2b 100644 --- a/tests/eval/test_evaluation.py +++ b/tests/eval/test_evaluation.py @@ -18,8 +18,8 @@ def test_run_eval(): data=[[8215, "2021-01-26 01:15:00"], [8215, "2021-01-30 16:30:00"]], ) - testset_path = tmpdirname + "/test_dataset.csv" - test_dataset.to_csv(testset_path, index=False) + testset_filename = tmpdirname + "/test_dataset.csv" + test_dataset.to_csv(testset_filename, index=False) # call the metrics function - run_eval(testset_path) + run_eval(testset_filename) From a66e0397ea79a92a6e40a761b2acb7dc808eacc4 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:23:44 +0000 Subject: [PATCH 23/52] pass HF_TOKEN to tests --- .github/workflows/pytest.yaml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index e68a6c25..7766b04a 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -11,4 +11,6 @@ jobs: # pytest-cov looks at this folder pytest_cov_dir: "quartz_solar_forecast" os_list: '["ubuntu-latest"]' - python-version: "['3.10','3.11']" \ No newline at end of file + python-version: "['3.10','3.11']" + secrets: + HF_TOKEN: ${{ secrets.HF_TOKEN }} \ No newline at end of file From 7ffd76a6226c7ab38f6fcd61a762871828d64d29 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:29:04 +0000 Subject: [PATCH 24/52] add HF_TOKEN as extra command --- .github/workflows/pytest.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index 7766b04a..f111e897 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -12,5 +12,5 @@ jobs: pytest_cov_dir: "quartz_solar_forecast" os_list: '["ubuntu-latest"]' python-version: "['3.10','3.11']" - secrets: - HF_TOKEN: ${{ secrets.HF_TOKEN }} \ No newline at end of file + extra_commands: + export HF_TOKEN=${{ secrets.HF_TOKEN }} \ No newline at end of file From 769eb47bdcef7323b641df05f95dc6772a52bfae Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:33:54 +0000 Subject: [PATCH 25/52] tyr again with CI --- .github/workflows/pytest.yaml | 3 +-- README.md | 1 + 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index f111e897..09b11591 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -12,5 +12,4 @@ jobs: pytest_cov_dir: "quartz_solar_forecast" os_list: '["ubuntu-latest"]' python-version: "['3.10','3.11']" - extra_commands: - export HF_TOKEN=${{ secrets.HF_TOKEN }} \ No newline at end of file + extra_commands: export HF_TOKEN=${{ secrets.HF_TOKEN }} \ No newline at end of file diff --git a/README.md b/README.md index e87d0279..81cbb473 100644 --- a/README.md +++ b/README.md @@ -4,6 +4,7 @@ The aim of the project is to build an open source PV forecast that is free and easy to use. +The forecast providers the expected generation in `kw` for 0 to 48 hours for a single PV site. Open Climate Fix also provide a commercial PV forecast, please get in touch at quartz.support@openclimatefix.org The current model uses GFS or ICON NWPs to predict the solar generation at a site From 3a1d198e82eecb0c2d47f6c1613c6415cc4c81f3 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:37:41 +0000 Subject: [PATCH 26/52] try in env --- .github/workflows/pytest.yaml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index 09b11591..7e568cf5 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -12,4 +12,5 @@ jobs: pytest_cov_dir: "quartz_solar_forecast" os_list: '["ubuntu-latest"]' python-version: "['3.10','3.11']" - extra_commands: export HF_TOKEN=${{ secrets.HF_TOKEN }} \ No newline at end of file + env: + HF_TOKEN: ${{ secrets.HF_TOKEN }} \ No newline at end of file From a4415b24de39d3d1979e931736d63670c15c3e76 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:45:43 +0000 Subject: [PATCH 27/52] make .env in tests --- .github/workflows/pytest.yaml | 3 +-- quartz_solar_forecast/evaluation.py | 4 ++++ 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index 7e568cf5..76887eb0 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -12,5 +12,4 @@ jobs: pytest_cov_dir: "quartz_solar_forecast" os_list: '["ubuntu-latest"]' python-version: "['3.10','3.11']" - env: - HF_TOKEN: ${{ secrets.HF_TOKEN }} \ No newline at end of file + extra_commands: echo "HF_TOKEN=${{ secrets.HF_TOKEN }}" > .env diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 0e55b5a7..abafebdd 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -17,6 +17,10 @@ from quartz_solar_forecast.eval.pv import get_pv_metadata, get_pv_truth from quartz_solar_forecast.eval.utils import combine_forecast_ground_truth +from dotenv import load_dotenv + +load_dotenv() + try: hf_token = os.environ["HF_TOKEN"] From 4458954d9b7b8ad340eb27e02c66c0057bc53555 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:50:53 +0000 Subject: [PATCH 28/52] use vars --- .github/workflows/pytest.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml index 76887eb0..e5ee54a9 100644 --- a/.github/workflows/pytest.yaml +++ b/.github/workflows/pytest.yaml @@ -12,4 +12,4 @@ jobs: pytest_cov_dir: "quartz_solar_forecast" os_list: '["ubuntu-latest"]' python-version: "['3.10','3.11']" - extra_commands: echo "HF_TOKEN=${{ secrets.HF_TOKEN }}" > .env + extra_commands: echo "HF_TOKEN=${{ vars.HF_TOKEN }}" > .env From 3a2e562f2ba113457236f11e0c5fbbcb260928e9 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 12 Dec 2023 21:53:05 +0000 Subject: [PATCH 29/52] add python-dotenv to requirements --- requirements.txt | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 22a6709b..9beeb22c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,4 +2,5 @@ pandas xarray pv-site-prediction pydantic -huggingface_hub # only for evaluation \ No newline at end of file +huggingface_hub # only for evaluation +python-dotenv \ No newline at end of file From 33b9641ac40cc661b92e52695659a097a70e7509 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Wed, 13 Dec 2023 09:09:14 +0000 Subject: [PATCH 30/52] change unit convertion --- quartz_solar_forecast/eval/pv.py | 2 +- requirements.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index 4b5f1528..29a5ec6f 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -69,7 +69,7 @@ def get_pv_truth(testset: pd.DataFrame): # Attempt to select data for the future datetime selected_data = pv_ds[pv_id].sel(datetime=future_datetime) value = selected_data.values.item() - value = value /1000 *12 # to convert from wh to kw + value = value / 1000 # to convert from w to kw except KeyError: # If data is not found for the future datetime, set value as NaN value = np.nan diff --git a/requirements.txt b/requirements.txt index 9beeb22c..47b54a51 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,4 +3,4 @@ xarray pv-site-prediction pydantic huggingface_hub # only for evaluation -python-dotenv \ No newline at end of file +python-dotenv \ No newline at end of file From 77b2921bf2ed127b3bb78cca68e46640e0da0c8e Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Thu, 14 Dec 2023 19:21:17 +0000 Subject: [PATCH 31/52] add multie proessing to collecting nwp data --- quartz_solar_forecast/data.py | 4 +- quartz_solar_forecast/eval/nwp.py | 61 ++++++++++++++++++++++--------- 2 files changed, 45 insertions(+), 20 deletions(-) diff --git a/quartz_solar_forecast/data.py b/quartz_solar_forecast/data.py index c97c45fa..4f9fce67 100644 --- a/quartz_solar_forecast/data.py +++ b/quartz_solar_forecast/data.py @@ -96,7 +96,7 @@ def get_nwp(site: PVSite, ts: datetime, nwp_source: str = "icon") -> xr.Dataset: return data_xr -def format_nwp_data(df, nwp_source, site): +def format_nwp_data(df: pd.DataFrame, nwp_source:str, site: PVSite): data_xr = xr.DataArray( data=df.values, dims=["step", "variable"], @@ -112,7 +112,7 @@ def format_nwp_data(df, nwp_source, site): return data_xr -def make_pv_data(site: PVSite, ts) -> xr.Dataset: +def make_pv_data(site: PVSite, ts: pd.Timestamp) -> xr.Dataset: """ Make fake PV data for the site diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 911f352b..3065952c 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -6,6 +6,8 @@ import xarray as xr from huggingface_hub import HfFileSystem +import multiprocessing + def get_nwp(time_locations: pd.DataFrame): """ @@ -19,16 +21,31 @@ def get_nwp(time_locations: pd.DataFrame): """ all_nwp_dfs = [] - for i, row in time_locations.iterrows(): - print(f"{i} of {len(time_locations)}") - one_nwp_df = get_nwp_for_one_timestamp_one_location( - row["timestamp"], row["latitude"], row["longitude"] - ) - one_nwp_df["timestamp"] = row["timestamp"] - one_nwp_df["pv_id"] = row["pv_id"] - one_nwp_df["latitude"] = row["latitude"] - one_nwp_df["longitude"] = row["longitude"] + tasks_args = [] + with multiprocessing.Pool(processes=3) as pool: + for i, row in time_locations.iterrows(): + print(f"Making task {i} of {len(time_locations)}") + + kwargs = { + "timestamp": row["timestamp"], + "latitude": row["latitude"], + "longitude": row["longitude"], + "pv_id": row["pv_id"], + } + + # collect together args for pool.starmap + task_arg = list(kwargs.values()) + tasks_args.append(task_arg) + + print("Made all tasks") + print(tasks_args) + results = pool.starmap(get_nwp_for_one_timestamp_one_location, tasks_args) + + print("Gathered all tasks") + + for result in results: + one_nwp_df = result all_nwp_dfs.append(one_nwp_df) @@ -37,7 +54,9 @@ def get_nwp(time_locations: pd.DataFrame): return all_nwp_df -def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, longitude): +def get_nwp_for_one_timestamp_one_location( + timestamp: pd.Timestamp, latitude, longitude, pv_id: None +): """ Get NWP data from Hugging Face for one timestamp and one location @@ -48,16 +67,17 @@ def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, lo :return: nwp forecast in xarray """ + # round timestamp to 6 hours floor fs = HfFileSystem() # List which files are available. Not all dates, and model run times are available # print(fs.ls("datasets/openclimatefix/dwd-icon-eu/data/2022/4/11/", detail=False)) # round timestamp to 6 hours floor - timestamp = timestamp.floor("6H") - year = timestamp.year - month = timestamp.month - day = timestamp.day - date_and_hour = timestamp.strftime("%Y%m%d_%H") + timestamp_floor = timestamp.floor("6H") + year = timestamp_floor.year + month = timestamp_floor.month + day = timestamp_floor.day + date_and_hour = timestamp_floor.strftime("%Y%m%d_%H") date = f"{year}/{month}/{day}" file_location = f"{date}/{date_and_hour}" @@ -136,8 +156,13 @@ def get_nwp_for_one_timestamp_one_location(timestamp: pd.Timestamp, latitude, lo # rename id to pv_id df = df.rename(columns={"id": "pv_id"}) - return df + # add columns for timestamp, latitude and longitude + df["timestamp"] = timestamp + df["latitude"] = latitude + df["longitude"] = longitude + # add pv_id columns if it is given + if pv_id is not None: + df["pv_id"] = pv_id -{'t_isnan', 'prate_isnan', 'lcc', 'h_mean_nan', 't', 'poa_global_now_is_zero', 'dswrf_isnan', 'h_median_nan', 'dlwrf', 'recent_power', 'capacity', 'h_median', 'dlwrf_isnan', 'vis_isnan', 'hcc_isnan', 'mcc', 'h_max_nan', 'vis', 'dswrf', 'recent_power_nan', 'h_mean', 'hcc', 'poa_global', 'h_max', 'mcc_isnan', 'si10', 'si10_isnan', 'lcc_isnan', 'prate'} != \ -{'shortwave_radiation', 'h_mean_nan', 'poa_global_now_is_zero', 'windspeed_10m_isnan', 'longitude', 'h_median_nan', 'windspeed_10m', 'recent_power', 'capacity', 'h_median', 'precipitation_isnan', 'direct_radiation', 'cloudcover_mid', 'temperature_2m_isnan', 'cloudcover_low', 'temperature_2m', 'visibility', 'h_max_nan', 'visibility_isnan', 'cloudcover_high_isnan', 'shortwave_radiation_isnan', 'longitude_isnan', 'h_mean', 'cloudcover_low_isnan', 'recent_power_nan', 'cloudcover_high', 'pv_id_isnan', 'poa_global', 'h_max', 'latitude_isnan', 'latitude', 'cloudcover_mid_isnan', 'pv_id', 'precipitation', 'direct_radiation_isnan'} + return df From db587bc2923f98ab9682e047de29a12f98c7b81b Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Thu, 14 Dec 2023 19:44:06 +0000 Subject: [PATCH 32/52] add mp spawn=True --- quartz_solar_forecast/eval/nwp.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 3065952c..55c42e3d 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -8,6 +8,8 @@ import multiprocessing +multiprocessing.set_start_method("spawn", force=True) + def get_nwp(time_locations: pd.DataFrame): """ @@ -39,7 +41,6 @@ def get_nwp(time_locations: pd.DataFrame): tasks_args.append(task_arg) print("Made all tasks") - print(tasks_args) results = pool.starmap(get_nwp_for_one_timestamp_one_location, tasks_args) print("Gathered all tasks") From fc231d3c7f376683323543e0b6931cbd04bdb691 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Thu, 14 Dec 2023 21:20:12 +0000 Subject: [PATCH 33/52] Tidy up print statment and add script, also add to readme.md --- README.md | 21 +++++++++++++++++++-- quartz_solar_forecast/eval/nwp.py | 22 ++++++++++++++++------ quartz_solar_forecast/eval/utils.py | 8 +------- quartz_solar_forecast/evaluation.py | 2 +- scripts/run_evaluation.py | 13 +++++++++++++ 5 files changed, 50 insertions(+), 16 deletions(-) create mode 100644 scripts/run_evaluation.py diff --git a/README.md b/README.md index 81cbb473..2868ed16 100644 --- a/README.md +++ b/README.md @@ -5,16 +5,16 @@ The aim of the project is to build an open source PV forecast that is free and easy to use. The forecast providers the expected generation in `kw` for 0 to 48 hours for a single PV site. + Open Climate Fix also provide a commercial PV forecast, please get in touch at quartz.support@openclimatefix.org The current model uses GFS or ICON NWPs to predict the solar generation at a site - ```python from quartz_solar_forecast.forecast import run_forecast from quartz_solar_forecast.pydantic_models import PVSite -# make input data +# make a pv site object site = PVSite(latitude=51.75, longitude=-1.25, capacity_kwp=1.25) # run model, uses ICON NWP data by default @@ -51,6 +51,23 @@ The 9 NWP variables, from Open-Meteo documentation, are mentioned above with the - The model is trained on [UK MetOffice](https://www.metoffice.gov.uk/services/data/met-office-weather-datahub) NWPs, but when running inference we use [GFS](https://www.ncei.noaa.gov/products/weather-climate-models/global-forecast) data from [Open-meteo](https://open-meteo.com/). The differences between GFS and UK MetOffice, could led to some odd behaviours. - It looks like the GFS data on Open-Meteo is only available for free for the last 3 months. +## Evaluation + +To evaluate the model we use the [UK PV](https://huggingface.co/datasets/openclimatefix/uk_pv) dataset and the [ICON NWP](https://huggingface.co/datasets/openclimatefix/dwd-icon-eu) dataset. +All the data is publicly available and the evaluation script can be run with the following command + +```bash +python scripts/run_evaluation.py +``` + +The test dataset we used is defined in `quartz_solar_forecast/dataset/testset.csv'. +This contains 50 PV sites, which 50 unique timestamps. The data is from 2021. + +The results of the evaluation are shown below: +TODO + + + ## Abbreviations - NWP: Numerical Weather Predictions diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 55c42e3d..a8030394 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -1,6 +1,7 @@ """ Get nwp data from HF""" import os import pandas as pd +import numpy as np import ocf_blosc2 # noqa import xarray as xr @@ -25,7 +26,7 @@ def get_nwp(time_locations: pd.DataFrame): all_nwp_dfs = [] tasks_args = [] - with multiprocessing.Pool(processes=3) as pool: + with multiprocessing.Pool() as pool: for i, row in time_locations.iterrows(): print(f"Making task {i} of {len(time_locations)}") @@ -34,16 +35,18 @@ def get_nwp(time_locations: pd.DataFrame): "latitude": row["latitude"], "longitude": row["longitude"], "pv_id": row["pv_id"], + "progress": np.round(i / len(time_locations), 3), } + # collect together args for pool.starmap task_arg = list(kwargs.values()) tasks_args.append(task_arg) - print("Made all tasks") + print("Made all NWP tasks, now getting the data") results = pool.starmap(get_nwp_for_one_timestamp_one_location, tasks_args) - print("Gathered all tasks") + print("Got all NWP data") for result in results: one_nwp_df = result @@ -56,7 +59,7 @@ def get_nwp(time_locations: pd.DataFrame): def get_nwp_for_one_timestamp_one_location( - timestamp: pd.Timestamp, latitude, longitude, pv_id: None + timestamp: pd.Timestamp, latitude, longitude, pv_id: int = None, progress: float = True ): """ Get NWP data from Hugging Face for one timestamp and one location @@ -64,13 +67,16 @@ def get_nwp_for_one_timestamp_one_location( :param timestamp: the timestamp for when you want the forecast for :param latitude: the latitude of the location :param longitude: the longitude of the location + :param pv_id: the pv_id of the location, if known + :param progress: Float of how far through the process we are. This is becasue we use multiprocessing + to pull lots of NWP data. This should be a float between 0 and 1 + :return: nwp forecast in xarray """ - # round timestamp to 6 hours floor - fs = HfFileSystem() # List which files are available. Not all dates, and model run times are available + # fs = HfFileSystem() # print(fs.ls("datasets/openclimatefix/dwd-icon-eu/data/2022/4/11/", detail=False)) # round timestamp to 6 hours floor @@ -115,6 +121,7 @@ def get_nwp_for_one_timestamp_one_location( data_at_location.load() # save to cache + print(f"Saving to cache {cache_file}") data_at_location.to_zarr(cache_file) else: # load from cache @@ -166,4 +173,7 @@ def get_nwp_for_one_timestamp_one_location( if pv_id is not None: df["pv_id"] = pv_id + if progress: + print(f"Getting NWP for {timestamp} {pv_id}. Progress: {100*progress}%") + return df diff --git a/quartz_solar_forecast/eval/utils.py b/quartz_solar_forecast/eval/utils.py index d9c33ab0..3cfa115a 100644 --- a/quartz_solar_forecast/eval/utils.py +++ b/quartz_solar_forecast/eval/utils.py @@ -1,10 +1,7 @@ import pandas as pd - - - -def combine_forecast_ground_truth(forecast_df, ground_truth_df): +def combine_forecast_ground_truth(forecast_df: pd.DataFrame, ground_truth_df: pd.DataFrame) ->pd.DataFrame: """ Combine the forecast results with the ground truth (ts, id, horizon (in hours), pred, truth, diff) @@ -41,9 +38,6 @@ def combine_forecast_ground_truth(forecast_df, ground_truth_df): ground_truth_df["pv_id"] = ground_truth_df["pv_id"].astype(int) # merge the two dataframes - print(forecast_df) - print(ground_truth_df) combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hour"]) return combined_df - diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index abafebdd..9918a73b 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -33,8 +33,8 @@ ) +def run_eval(testset_path: str = "quartz_solar_forecast/dataset/testset.csv"): -def run_eval(testset_path: str = "quartz_solar_forecast/dataset/testset2.csv"): # load testset from csv testset = pd.read_csv(testset_path) diff --git a/scripts/run_evaluation.py b/scripts/run_evaluation.py new file mode 100644 index 00000000..cae2bfd0 --- /dev/null +++ b/scripts/run_evaluation.py @@ -0,0 +1,13 @@ +""" Make script to run evalutions on the test set. + +The idea is to run the model on the test set and then compare the results to the actual PV generation. +The NWP (ICON) and PV data are both pulled Open Climate Fix's Hugging Face page. + +Please note it can takes hours to pull the NWP data. +The data will be cached locally so next time you run it, itll be much quickerl +""" + +from quartz_solar_forecast.evaluation import run_eval + +if __name__ == '__main__': + run_eval() From 2414dc7ee23e57afce6f14ecbd97981f75eb603b Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Thu, 14 Dec 2023 21:36:47 +0000 Subject: [PATCH 34/52] add 95% CI on mean in metrics --- quartz_solar_forecast/eval/metrics.py | 8 +++++--- quartz_solar_forecast/evaluation.py | 3 ++- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/quartz_solar_forecast/eval/metrics.py b/quartz_solar_forecast/eval/metrics.py index 9e96a76c..7a2742ea 100644 --- a/quartz_solar_forecast/eval/metrics.py +++ b/quartz_solar_forecast/eval/metrics.py @@ -11,7 +11,7 @@ def metrics(results_df): """ - mae = (results_df["forecast_power"] - results_df['generation_power']).abs().mean() + mae = (results_df["forecast_power"] - results_df['generation_power']).abs().mean().round(4) print(f"MAE: {mae}") # calculate metrics over the different horizons hours @@ -20,8 +20,10 @@ def metrics(results_df): for horizon_hour in horizon_hours: # filter results_df to only include the horizon_hour results_df_horizon = results_df[results_df["horizon_hour"] == horizon_hour] - mae = (results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().mean() - print(f"MAE for horizon {horizon_hour}: {mae}") + mae = (results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().mean().round(3) + sem = ((results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().std() / len(results_df_horizon)**0.5).round(3) + + print(f"MAE for horizon {horizon_hour}: {mae} +- {1.96*sem}") # TODO add more metrics using ocf_ml_metrics diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index 9918a73b..e353d7b9 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -59,7 +59,8 @@ def run_eval(testset_path: str = "quartz_solar_forecast/dataset/testset.csv"): # Calculate and print metrics: MAE metrics(results_df) - # Visulisations + # Visualizations + # TODO # run_eval() From 52ca34606c73305fc770499514c3cab6cae92c0f Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Thu, 14 Dec 2023 21:43:58 +0000 Subject: [PATCH 35/52] fix metrics --- quartz_solar_forecast/eval/metrics.py | 28 ++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/quartz_solar_forecast/eval/metrics.py b/quartz_solar_forecast/eval/metrics.py index 7a2742ea..b71766f1 100644 --- a/quartz_solar_forecast/eval/metrics.py +++ b/quartz_solar_forecast/eval/metrics.py @@ -1,4 +1,8 @@ -def metrics(results_df): +import numpy as np +import pandas as pd + + +def metrics(results_df: pd.DataFrame): """ Calculate and print metrics: MAE @@ -11,7 +15,7 @@ def metrics(results_df): """ - mae = (results_df["forecast_power"] - results_df['generation_power']).abs().mean().round(4) + mae = np.round((results_df["forecast_power"] - results_df["generation_power"]).abs().mean(), 4) print(f"MAE: {mae}") # calculate metrics over the different horizons hours @@ -20,12 +24,22 @@ def metrics(results_df): for horizon_hour in horizon_hours: # filter results_df to only include the horizon_hour results_df_horizon = results_df[results_df["horizon_hour"] == horizon_hour] - mae = (results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().mean().round(3) - sem = ((results_df_horizon["forecast_power"] - results_df_horizon['generation_power']).abs().std() / len(results_df_horizon)**0.5).round(3) + mae = np.round( + (results_df_horizon["forecast_power"] - results_df_horizon["generation_power"]) + .abs() + .mean(), + 3, + ) + sem = np.round( + ( + (results_df_horizon["forecast_power"] - results_df_horizon["generation_power"]) + .abs() + .std() + / len(results_df_horizon) ** 0.5 + ), + 3, + ) print(f"MAE for horizon {horizon_hour}: {mae} +- {1.96*sem}") # TODO add more metrics using ocf_ml_metrics - - - From 695c292851b83ccb908f098d48712941862dd340 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Fri, 15 Dec 2023 15:29:03 +0000 Subject: [PATCH 36/52] make test dataset from 50 known good pvs --- .../dataset/make_test_set.py | 102 +- quartz_solar_forecast/dataset/testset.csv | 5000 ++++++++--------- tests/data/test_make_test_set.py | 2 +- 3 files changed, 2552 insertions(+), 2552 deletions(-) diff --git a/quartz_solar_forecast/dataset/make_test_set.py b/quartz_solar_forecast/dataset/make_test_set.py index da0713ca..8d7f36a6 100644 --- a/quartz_solar_forecast/dataset/make_test_set.py +++ b/quartz_solar_forecast/dataset/make_test_set.py @@ -10,60 +10,60 @@ import pandas as pd test_start_date = pd.Timestamp("2021-01-01") -test_end_date = pd.Timestamp("2021-02-01") +test_end_date = pd.Timestamp("2022-01-01") # this have been chosen from the entire training set. This ideas pv_ids = [ - 8215, - 8229, - 8253, - 8266, - 8267, - 8281, - 16474, - 16477, - 16480, - 16483, - 8376, - 16570, - 16597, - 8411, + 9531, + 7174, + 6872, + 7386, + 13607, + 6330, + 26841, + 6665, + 4045, + 26846, + 6494, + 7834, + 3543, + 7093, + 3864, 8412, - 8419, - 8420, - 8453, - 8464, - 8505, - 16715, - 16717, - 8551, - 8558, - 16769, - 16770, - 8587, - 8591, - 8612, - 8648, - 8670, - 8708, - 8713, - 16920, - 16921, - 8801, - 17034, - 17035, - 8856, - 17062, - 8914, - 17166, - 9069, - 9070, - 9101, - 9107, - 17333, - 9153, - 9171, - 9173, + 3454, + 9765, + 10585, + 26942, + 7721, + 26804, + 7551, + 26861, + 7568, + 7338, + 7410, + 6967, + 16480, + 7241, + 7593, + 7557, + 7757, + 3094, + 6800, + 26905, + 5512, + 26840, + 7595, + 5803, + 26876, + 7846, + 26786, + 7580, + 6629, + 16477, + 3489, + 26796, + 12761, + 26903, ] np.random.seed(42) @@ -93,4 +93,4 @@ def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_ # To run the script, un comment the following line and run this file -make_test_set() +# make_test_set() diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index 8506f1d0..156db715 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -1,2501 +1,2501 @@ pv_id,datetime -8215,2021-01-26 01:15:00 -8215,2021-01-30 16:30:00 -8215,2021-01-18 19:30:00 -8215,2021-01-12 14:15:00 -8215,2021-01-11 01:00:00 -8215,2021-01-31 12:15:00 -8215,2021-01-05 19:45:00 -8215,2021-01-27 12:15:00 -8215,2021-01-10 04:15:00 -8215,2021-01-24 00:45:00 -8215,2021-01-20 22:30:00 -8215,2021-01-09 04:15:00 -8215,2021-01-19 18:00:00 -8215,2021-01-09 12:45:00 -8215,2021-01-01 23:15:00 -8215,2021-01-14 03:15:00 -8215,2021-01-09 17:45:00 -8215,2021-01-19 12:30:00 -8215,2021-01-19 21:15:00 -8215,2021-01-02 12:00:00 -8215,2021-01-27 00:30:00 -8215,2021-01-29 14:30:00 -8215,2021-01-07 23:30:00 -8215,2021-01-15 00:00:00 -8215,2021-01-29 17:30:00 -8215,2021-01-03 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+26903,2021-01-26 10:15:00 diff --git a/tests/data/test_make_test_set.py b/tests/data/test_make_test_set.py index 85e3f987..dd2de360 100644 --- a/tests/data/test_make_test_set.py +++ b/tests/data/test_make_test_set.py @@ -15,4 +15,4 @@ def test_make_test_set(): test_set = pd.read_csv(output_file) assert len(test_set) == 50 * 50 # we can check this as we have set the seed - assert test_set.iloc[0].datetime == "2021-01-27 07:00:00" + assert test_set.iloc[0].datetime == "2021-04-29 07:00:00" From 3ebc8092335c98083d925aa33c5dfa2f62fe4e32 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Fri, 15 Dec 2023 15:31:00 +0000 Subject: [PATCH 37/52] change to timestamp --- quartz_solar_forecast/dataset/make_test_set.py | 2 +- quartz_solar_forecast/dataset/testset.csv | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/quartz_solar_forecast/dataset/make_test_set.py b/quartz_solar_forecast/dataset/make_test_set.py index 8d7f36a6..a52e9648 100644 --- a/quartz_solar_forecast/dataset/make_test_set.py +++ b/quartz_solar_forecast/dataset/make_test_set.py @@ -85,7 +85,7 @@ def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_ for pv_id in pv_ids: ts = pd.date_range(start=test_start_date, end=test_end_date, freq="15min") ts = ts[np.random.choice(len(ts), size=number_of_samples_per_system, replace=False)] - test_set.append(pd.DataFrame({"pv_id": pv_id, "datetime": ts})) + test_set.append(pd.DataFrame({"pv_id": pv_id, "timestamp": ts})) test_set = pd.concat(test_set) test_set.to_csv(output_file_name, index=False) diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index 156db715..471cb7e3 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -1,4 +1,4 @@ -pv_id,datetime +pv_id,timestamp 9531,2021-04-29 07:00:00 9531,2021-10-04 11:45:00 9531,2021-01-26 11:15:00 From 56a08193d17615bd86d6f41e280254ab41f0d5d8 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Fri, 15 Dec 2023 15:34:25 +0000 Subject: [PATCH 38/52] ix test --- tests/data/test_make_test_set.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/data/test_make_test_set.py b/tests/data/test_make_test_set.py index dd2de360..79bd495c 100644 --- a/tests/data/test_make_test_set.py +++ b/tests/data/test_make_test_set.py @@ -15,4 +15,4 @@ def test_make_test_set(): test_set = pd.read_csv(output_file) assert len(test_set) == 50 * 50 # we can check this as we have set the seed - assert test_set.iloc[0].datetime == "2021-04-29 07:00:00" + assert test_set.iloc[0].timestamp == "2021-04-29 07:00:00" From 0a5d59cb0f15c7a44eada7fa89259a3cc2d9f6a5 Mon Sep 17 00:00:00 2001 From: Peter Dudfield <34686298+peterdudfield@users.noreply.github.com> Date: Mon, 18 Dec 2023 08:11:57 +0000 Subject: [PATCH 39/52] Update testset.csv Update 2021-11-20 in testset --- quartz_solar_forecast/dataset/testset.csv | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index 471cb7e3..a3709fc8 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -256,7 +256,7 @@ pv_id,timestamp 6330,2021-02-14 16:15:00 6330,2021-12-08 00:45:00 6330,2021-04-01 12:15:00 -6330,2021-11-20 10:30:00 +6330,2021-11-20 13:30:00 6330,2021-01-18 18:45:00 6330,2021-09-21 05:15:00 6330,2021-09-18 13:15:00 From fa8959bc329253bf62a2a0fa529db6f10f679273 Mon Sep 17 00:00:00 2001 From: Peter Dudfield <34686298+peterdudfield@users.noreply.github.com> Date: Mon, 18 Dec 2023 08:14:54 +0000 Subject: [PATCH 40/52] Update testset.csv --- quartz_solar_forecast/dataset/testset.csv | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index a3709fc8..5f47aaab 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -186,7 +186,7 @@ pv_id,timestamp 7386,2021-09-21 10:15:00 7386,2021-09-30 23:15:00 7386,2021-07-10 08:30:00 -7386,2021-04-24 17:15:00 +7386,2021-04-24 18:15:00 7386,2021-01-21 00:30:00 7386,2021-06-14 21:00:00 7386,2021-07-06 13:45:00 From 5689bd3bd80fdfbb0d65f66192674a0934c55a30 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Mon, 18 Dec 2023 08:30:43 +0000 Subject: [PATCH 41/52] add print statements --- quartz_solar_forecast/eval/pv.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/quartz_solar_forecast/eval/pv.py b/quartz_solar_forecast/eval/pv.py index 29a5ec6f..b4bfad62 100644 --- a/quartz_solar_forecast/eval/pv.py +++ b/quartz_solar_forecast/eval/pv.py @@ -45,10 +45,13 @@ def get_pv_metadata(testset: pd.DataFrame): def get_pv_truth(testset: pd.DataFrame): + print('Loading PV data') + # download from hugginface or load from cache cache_dir = "data/pv" metadata_file = f"{cache_dir}/pv.netcdf" if not os.path.exists(metadata_file): + print('Loading from HF)') os.makedirs(cache_dir, exist_ok=True) fs.get("datasets/openclimatefix/uk_pv/pv.netcdf", metadata_file) @@ -57,6 +60,7 @@ def get_pv_truth(testset: pd.DataFrame): combined_data = [] for index, row in testset.iterrows(): + print(f'Processing {index} of {len(testset)}') pv_id = str(row["pv_id"]) base_datetime = pd.to_datetime(row["timestamp"]) From a5fa6ab4ac0d06c20d66592d2732da7a5cee4d10 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Mon, 18 Dec 2023 11:27:37 +0000 Subject: [PATCH 42/52] update testset --- .../dataset/make_test_set.py | 47 +- quartz_solar_forecast/dataset/testset.csv | 4996 ++++++++--------- quartz_solar_forecast/eval/nwp.py | 19 +- quartz_solar_forecast/eval/utils.py | 20 + 4 files changed, 2567 insertions(+), 2515 deletions(-) diff --git a/quartz_solar_forecast/dataset/make_test_set.py b/quartz_solar_forecast/dataset/make_test_set.py index a52e9648..eb4cf0b3 100644 --- a/quartz_solar_forecast/dataset/make_test_set.py +++ b/quartz_solar_forecast/dataset/make_test_set.py @@ -2,6 +2,9 @@ Make a random test set This takes a random subset of times and for various pv ids and makes a test set + +There is an option to odmit timestamps that don't exsits in the ICON dataset: +https://huggingface.co/datasets/openclimatefix/dwd-icon-eu/tree/main/data """ import os from typing import Optional @@ -9,6 +12,9 @@ import numpy as np import pandas as pd +from quartz_solar_forecast.eval.utils import make_hf_filename +from huggingface_hub import HfFileSystem + test_start_date = pd.Timestamp("2021-01-01") test_end_date = pd.Timestamp("2022-01-01") @@ -69,7 +75,7 @@ np.random.seed(42) -def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50): +def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_system: int = 50, check_hf_files: bool = False): """ Make a test set of random times and pv ids @@ -81,16 +87,47 @@ def make_test_set(output_file_name: Optional[str] = None, number_of_samples_per_ # get the folder where this file is output_file_name = os.path.dirname(os.path.abspath(__file__)) + "/testset.csv" + ts = pd.date_range(start=test_start_date, end=test_end_date, freq="15min") + + # check that the files are in HF for ICON + if check_hf_files: + ts = filter_timestamps_if_hf_files_exists(ts) + test_set = [] for pv_id in pv_ids: - ts = pd.date_range(start=test_start_date, end=test_end_date, freq="15min") - ts = ts[np.random.choice(len(ts), size=number_of_samples_per_system, replace=False)] - test_set.append(pd.DataFrame({"pv_id": pv_id, "timestamp": ts})) + ts_choice = ts[np.random.choice(len(ts), size=number_of_samples_per_system, replace=False)] + test_set.append(pd.DataFrame({"pv_id": pv_id, "timestamp": ts_choice})) test_set = pd.concat(test_set) test_set.to_csv(output_file_name, index=False) return test_set +def filter_timestamps_if_hf_files_exists(timestamps_full: pd.DatetimeIndex): + """ + Filter the timestamps if the huggingface files exist + + We are checking if the teimstamps, rounded down to the nearest 6 hours, + exist in + https://huggingface.co/datasets/openclimatefix/dwd-icon-eu/tree/main/data + + """ + timestamps = [] + fs = HfFileSystem() + # print(fs.ls("datasets/openclimatefix/dwd-icon-eu/data/2022/4/11/", detail=False)) + for timestamp in timestamps_full: + timestamp_floor = timestamp.floor("6H") + _, huggingface_file = make_hf_filename(timestamp_floor) + huggingface_file = huggingface_file[14:] + + if fs.exists(huggingface_file): + timestamps.append(timestamp) + else: + print(f"Skipping {timestamp} because {huggingface_file} does not exist") + + timestamps = pd.DatetimeIndex(timestamps) + return timestamps + + # To run the script, un comment the following line and run this file -# make_test_set() +# make_test_set(check_hf_files=True) diff --git a/quartz_solar_forecast/dataset/testset.csv b/quartz_solar_forecast/dataset/testset.csv index 5f47aaab..96a40e79 100644 --- a/quartz_solar_forecast/dataset/testset.csv +++ b/quartz_solar_forecast/dataset/testset.csv @@ -1,2501 +1,2501 @@ pv_id,timestamp -9531,2021-04-29 07:00:00 -9531,2021-10-04 11:45:00 -9531,2021-01-26 11:15:00 -9531,2021-06-02 14:15:00 -9531,2021-12-07 14:45:00 -9531,2021-03-26 05:45:00 -9531,2021-12-18 13:00:00 -9531,2021-04-18 00:30:00 -9531,2021-11-23 23:15:00 -9531,2021-12-08 23:45:00 -9531,2021-07-15 04:15:00 -9531,2021-05-23 05:45:00 -9531,2021-07-26 23:00:00 -9531,2021-11-08 17:00:00 -9531,2021-10-28 01:15:00 -9531,2021-01-05 14:15:00 -9531,2021-11-24 04:15:00 -9531,2021-10-15 16:00:00 -9531,2021-08-14 11:45:00 -9531,2021-05-25 19:30:00 -9531,2021-01-19 00:45:00 -9531,2021-05-18 15:30:00 -9531,2021-09-26 04:30:00 -9531,2021-05-19 19:30:00 -9531,2021-06-13 16:30:00 -9531,2021-06-14 02:45:00 -9531,2021-12-28 11:30:00 -9531,2021-01-18 09:00:00 -9531,2021-12-24 16:30:00 -9531,2021-06-24 03:00:00 -9531,2021-02-25 11:15:00 -9531,2021-01-03 20:15:00 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np import ocf_blosc2 # noqa import xarray as xr -from huggingface_hub import HfFileSystem import multiprocessing +from quartz_solar_forecast.eval.utils import make_hf_filename + multiprocessing.set_start_method("spawn", force=True) @@ -38,7 +40,6 @@ def get_nwp(time_locations: pd.DataFrame): "progress": np.round(i / len(time_locations), 3), } - # collect together args for pool.starmap task_arg = list(kwargs.values()) tasks_args.append(task_arg) @@ -81,16 +82,7 @@ def get_nwp_for_one_timestamp_one_location( # round timestamp to 6 hours floor timestamp_floor = timestamp.floor("6H") - year = timestamp_floor.year - month = timestamp_floor.month - day = timestamp_floor.day - date_and_hour = timestamp_floor.strftime("%Y%m%d_%H") - - date = f"{year}/{month}/{day}" - file_location = f"{date}/{date_and_hour}" - huggingface_route = "zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data" - # huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data" - huggingface_file = f"{huggingface_route}/{file_location}.zarr.zip" + date_and_hour, huggingface_file = make_hf_filename(timestamp_floor) # dataset variables variables = ["t_2m", "tot_prec", "clch", "clcm", "clcl", "u", "v", "aswdir_s", "aswdifd_s"] @@ -100,6 +92,7 @@ def get_nwp_for_one_timestamp_one_location( if not os.path.exists(cache_file): # use fsspec to copy file print(f"Opening file {huggingface_file} from HF to local") + sys.stdout.flush() data = xr.open_zarr( f"{huggingface_file}", @@ -177,3 +170,5 @@ def get_nwp_for_one_timestamp_one_location( print(f"Getting NWP for {timestamp} {pv_id}. Progress: {100*progress}%") return df + + diff --git a/quartz_solar_forecast/eval/utils.py b/quartz_solar_forecast/eval/utils.py index 3cfa115a..8c216a6e 100644 --- a/quartz_solar_forecast/eval/utils.py +++ b/quartz_solar_forecast/eval/utils.py @@ -41,3 +41,23 @@ def combine_forecast_ground_truth(forecast_df: pd.DataFrame, ground_truth_df: pd combined_df = pd.merge(forecast_df, ground_truth_df, on=["timestamp", "pv_id", "horizon_hour"]) return combined_df + + +def make_hf_filename(timestamp_floor): + """ + Make ICON filename from timestamp_floor + + '2021-01-01 00:00:00' -> + 'zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data/2021/1/1/20210101_00.zarr.zip' + + """ + year = timestamp_floor.year + month = timestamp_floor.month + day = timestamp_floor.day + date_and_hour = timestamp_floor.strftime("%Y%m%d_%H") + date = f"{year}/{month}/{day}" + file_location = f"{date}/{date_and_hour}" + huggingface_route = "zip:///::hf://datasets/openclimatefix/dwd-icon-eu/data" + # huggingface_route = "datasets/openclimatefix/dwd-icon-eu/data" + huggingface_file = f"{huggingface_route}/{file_location}.zarr.zip" + return date_and_hour, huggingface_file From 2fd9ab583d587fe3dad61ea7b9b5d147acbe2775 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 10:55:05 +0000 Subject: [PATCH 43/52] add some print statments --- quartz_solar_forecast/eval/forecast.py | 4 ++++ quartz_solar_forecast/eval/nwp.py | 6 +++--- 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/quartz_solar_forecast/eval/forecast.py b/quartz_solar_forecast/eval/forecast.py index d3c872a8..740abab3 100644 --- a/quartz_solar_forecast/eval/forecast.py +++ b/quartz_solar_forecast/eval/forecast.py @@ -39,6 +39,8 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - all_predictions = [] for i in range(len(pv_df)): + print(f"Running forecast for {i} of {len(pv_df)}") + pv_row = pv_df.iloc[i] site = PVSite( @@ -66,10 +68,12 @@ def run_forecast(pv_df: pd.DataFrame, nwp_df: pd.DataFrame, nwp_source="ICON") - # make pv and nwp data from GFS # TODO move this to model + print("Making pv and nwp data") nwp_xr = format_nwp_data(df=nwp_site_df, nwp_source=nwp_source, site=site) pv_xr = make_pv_data(site=site, ts=ts) # run model + print('Running model') pred_df = forecast_v1(nwp_source, nwp_xr, pv_xr, ts, model=model) # only select hourly predictions diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index 2f530a2d..aa93e3c5 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -91,7 +91,7 @@ def get_nwp_for_one_timestamp_one_location( cache_file = f"{cache_dir}/{date_and_hour}_lat={latitude}_lon={longitude}.zarr" if not os.path.exists(cache_file): # use fsspec to copy file - print(f"Opening file {huggingface_file} from HF to local") + print(f"Copying file {huggingface_file} from HF to local") sys.stdout.flush() data = xr.open_zarr( @@ -103,10 +103,10 @@ def get_nwp_for_one_timestamp_one_location( data_at_location = data.sel(latitude=latitude, longitude=longitude, method="nearest") data_at_location = data_at_location[variables] - # choise the first isobaricInhPa + # choice the first isobaricInhPa data_at_location = data_at_location.isel(isobaricInhPa=-1) - # reduce to 54 hours timestaps, this means there is at least a 48 hours forecast + # reduce to 54 hours timestamps, this means there is at least a 48 hours forecast data_at_location = data_at_location.isel(step=slice(0, 54)) # load all the data, this can take about ~1 minute seconds From 8c74d41a2b432869b7232c041fc08017a676660a Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 11:37:41 +0000 Subject: [PATCH 44/52] add results in readme.md --- README.md | 18 +++++++++++++++--- quartz_solar_forecast/eval/metrics.py | 26 +++++++++++++++++++++++++- 2 files changed, 40 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 2868ed16..86de7105 100644 --- a/README.md +++ b/README.md @@ -60,11 +60,23 @@ All the data is publicly available and the evaluation script can be run with the python scripts/run_evaluation.py ``` -The test dataset we used is defined in `quartz_solar_forecast/dataset/testset.csv'. +The test dataset we used is defined in `quartz_solar_forecast/dataset/testset.csv`. This contains 50 PV sites, which 50 unique timestamps. The data is from 2021. -The results of the evaluation are shown below: -TODO +The results of the evaluation are as follows +The MAE is 0.1906 kw across all horizons. + +| Horizons | MAE [kw] | +|----------|---------------| +| 0 | 0.202 +- 0.03 | +| 1 | 0.211 +- 0.03 | +| 2 | 0.216 +- 0.03 | +| 3-4 | 0.211 +- 0.02 | +| 5-8 | 0.191 +- 0.01 | +| 9-16 | 0.161 +- 0.01 | +| 17-24 | 0.173 +- 0.01 | +| 24-48 | 0.201 +- 0.01 | + diff --git a/quartz_solar_forecast/eval/metrics.py b/quartz_solar_forecast/eval/metrics.py index b71766f1..496ce2d1 100644 --- a/quartz_solar_forecast/eval/metrics.py +++ b/quartz_solar_forecast/eval/metrics.py @@ -42,4 +42,28 @@ def metrics(results_df: pd.DataFrame): print(f"MAE for horizon {horizon_hour}: {mae} +- {1.96*sem}") - # TODO add more metrics using ocf_ml_metrics + # calculate metrics over the different horizon groups + horizon_groups = [[0, 0], [1, 1], [2, 2], [3, 4], [5, 8], [9, 16], [17, 24], [24, 48]] + for horizon_group in horizon_groups: + horizon_group_df = results_df[ + results_df["horizon_hour"].between(horizon_group[0], horizon_group[1]) + ] + mae = np.round( + (horizon_group_df["forecast_power"] - horizon_group_df["generation_power"]) + .abs() + .mean(), + 3, + ) + sem = np.round( + ( + (horizon_group_df["forecast_power"] - horizon_group_df["generation_power"]) + .abs() + .std() + / len(horizon_group_df) ** 0.5 + ), + 3, + ) + + print(f"MAE for horizon {horizon_group}: {mae} +- {1.96*sem}") + + # TODO add more metrics using ocf_ml_metrics From 3edd3bc55e17e5797a4930081393ccb8b2a38cd4 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 11:52:34 +0000 Subject: [PATCH 45/52] add normalized by capacity metrics --- README.md | 20 +++++------ quartz_solar_forecast/eval/metrics.py | 48 +++++++++++++++++++++++---- quartz_solar_forecast/evaluation.py | 2 +- 3 files changed, 53 insertions(+), 17 deletions(-) diff --git a/README.md b/README.md index 86de7105..3070f117 100644 --- a/README.md +++ b/README.md @@ -66,16 +66,16 @@ This contains 50 PV sites, which 50 unique timestamps. The data is from 2021. The results of the evaluation are as follows The MAE is 0.1906 kw across all horizons. -| Horizons | MAE [kw] | -|----------|---------------| -| 0 | 0.202 +- 0.03 | -| 1 | 0.211 +- 0.03 | -| 2 | 0.216 +- 0.03 | -| 3-4 | 0.211 +- 0.02 | -| 5-8 | 0.191 +- 0.01 | -| 9-16 | 0.161 +- 0.01 | -| 17-24 | 0.173 +- 0.01 | -| 24-48 | 0.201 +- 0.01 | +| Horizons | MAE [kw] | MAE [%] | +|----------|---------------| ------- | +| 0 | 0.202 +- 0.03 | 6.2 | +| 1 | 0.211 +- 0.03 | 6.4 | +| 2 | 0.216 +- 0.03 | 6.5 | +| 3 - 4 | 0.211 +- 0.02 |6.3 | +| 5 - 8 | 0.191 +- 0.01 | 6 | +| 9 - 16 | 0.161 +- 0.01 | 5 | +| 17 - 24 | 0.173 +- 0.01 | 5.3 | +| 24 - 48 | 0.201 +- 0.01 | 6.1 | diff --git a/quartz_solar_forecast/eval/metrics.py b/quartz_solar_forecast/eval/metrics.py index 496ce2d1..a80fa943 100644 --- a/quartz_solar_forecast/eval/metrics.py +++ b/quartz_solar_forecast/eval/metrics.py @@ -2,7 +2,7 @@ import pandas as pd -def metrics(results_df: pd.DataFrame): +def metrics(results_df: pd.DataFrame, pv_metadata: pd.DataFrame): """ Calculate and print metrics: MAE @@ -13,10 +13,23 @@ def metrics(results_df: pd.DataFrame): - forecast_power - generation_power + pv_metadata is a dataframe with the following columns + - pv_id + - capacity + """ + # merge pv_metadata with results_df + results_df = pd.merge(results_df, pv_metadata, on="pv_id") + mae = np.round((results_df["forecast_power"] - results_df["generation_power"]).abs().mean(), 4) - print(f"MAE: {mae}") + mae_normalized = np.round( + ((results_df["forecast_power"] - results_df["generation_power"]) / results_df["capacity"]) + .abs() + .mean(), + 4, + ) + print(f"MAE: {mae} kw, normalized {mae_normalized} %") # calculate metrics over the different horizons hours # find all unique horizon_hours @@ -35,12 +48,23 @@ def metrics(results_df: pd.DataFrame): (results_df_horizon["forecast_power"] - results_df_horizon["generation_power"]) .abs() .std() - / len(results_df_horizon) ** 0.5 + / 50 ** 0.5 ), 3, ) + mae_normalized = np.round( + ( + (results_df_horizon["forecast_power"] - results_df_horizon["generation_power"]) + / results_df_horizon["capacity"] + ) + .abs() + .mean(), + 3, + ) - print(f"MAE for horizon {horizon_hour}: {mae} +- {1.96*sem}") + print( + f"MAE for horizon {horizon_hour}: {mae} +- {1.96*sem}. Normalized MAE: {mae_normalized} %" + ) # calculate metrics over the different horizon groups horizon_groups = [[0, 0], [1, 1], [2, 2], [3, 4], [5, 8], [9, 16], [17, 24], [24, 48]] @@ -59,11 +83,23 @@ def metrics(results_df: pd.DataFrame): (horizon_group_df["forecast_power"] - horizon_group_df["generation_power"]) .abs() .std() - / len(horizon_group_df) ** 0.5 + / 50 ** 0.5 ), 3, ) - print(f"MAE for horizon {horizon_group}: {mae} +- {1.96*sem}") + mae_normalized = np.round( + ( + (horizon_group_df["forecast_power"] - horizon_group_df["generation_power"]) + / horizon_group_df["capacity"] + ) + .abs() + .mean(), + 3, + ) + + print( + f"MAE for horizon {horizon_group}: {mae} +- {1.96*sem}. mae_normalized: {mae_normalized} %" + ) # TODO add more metrics using ocf_ml_metrics diff --git a/quartz_solar_forecast/evaluation.py b/quartz_solar_forecast/evaluation.py index e353d7b9..b455db72 100644 --- a/quartz_solar_forecast/evaluation.py +++ b/quartz_solar_forecast/evaluation.py @@ -57,7 +57,7 @@ def run_eval(testset_path: str = "quartz_solar_forecast/dataset/testset.csv"): results_df.to_csv("results.csv") # Calculate and print metrics: MAE - metrics(results_df) + metrics(results_df, pv_metadata) # Visualizations # TODO From 6b5212835dcda31721d5c40145244cf19ba52c99 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 12:18:57 +0000 Subject: [PATCH 46/52] fix test --- tests/eval/test_metrics.py | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/tests/eval/test_metrics.py b/tests/eval/test_metrics.py index ecfb480e..40ec28a1 100644 --- a/tests/eval/test_metrics.py +++ b/tests/eval/test_metrics.py @@ -9,12 +9,22 @@ def test_metrics(): results_df = pd.DataFrame( columns=[ - "id", + "pv_id", "timestamp", "horizon_hour", "forecast_power", "generation_power", - ], data=np.random.random((100,5))) + ], + data=np.random.random((100, 5)), + ) + + pv_metadata = pd.DataFrame( + columns=[ + "pv_id", + "capacity", + ], + data=np.random.random((100, 2)), + ) # call the metrics function - metrics(results_df) \ No newline at end of file + metrics(results_df, pv_metadata) From 197f50674a3973b19dfa372106a7045aefa82c9e Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 14:45:12 +0000 Subject: [PATCH 47/52] PR comment --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3070f117..48bce22a 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ The aim of the project is to build an open source PV forecast that is free and easy to use. -The forecast providers the expected generation in `kw` for 0 to 48 hours for a single PV site. +The forecast provides the expected generation in `kw` for 0 to 48 hours for a single PV site. Open Climate Fix also provide a commercial PV forecast, please get in touch at quartz.support@openclimatefix.org From 09c1662a6fc21a286ab6b4213ffcaeb94a232851 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 14:53:52 +0000 Subject: [PATCH 48/52] PR comment --- quartz_solar_forecast/eval/nwp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/quartz_solar_forecast/eval/nwp.py b/quartz_solar_forecast/eval/nwp.py index aa93e3c5..1edc3a20 100644 --- a/quartz_solar_forecast/eval/nwp.py +++ b/quartz_solar_forecast/eval/nwp.py @@ -84,7 +84,7 @@ def get_nwp_for_one_timestamp_one_location( timestamp_floor = timestamp.floor("6H") date_and_hour, huggingface_file = make_hf_filename(timestamp_floor) - # dataset variables + # dataset variables, note these are unique for ICON variables = ["t_2m", "tot_prec", "clch", "clcm", "clcl", "u", "v", "aswdir_s", "aswdifd_s"] cache_dir = "data/nwp" From e1ac788055ea9f66491fd38adf7d487397e09842 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 14:56:49 +0000 Subject: [PATCH 49/52] add notes about evaluation --- README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 48bce22a..ada7c01a 100644 --- a/README.md +++ b/README.md @@ -78,7 +78,10 @@ The MAE is 0.1906 kw across all horizons. | 24 - 48 | 0.201 +- 0.01 | 6.1 | - +Notes: +- THe MAE in % is the MAE divided by the capacity of the PV site. We acknowledge there are a number of different ways to do this. +- it is slightly surprising that the 0-hour forecast horizon and the 24-48 hour horizon have a similar MAE. +This may be because the model is trained expecting live PV data, but currently in this project we provide no live PV data. ## Abbreviations From 44dd8c27d83afe106a5c7dc90d687a1688e61dbc Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 15:02:10 +0000 Subject: [PATCH 50/52] Add PR comment --- quartz_solar_forecast/forecasts/v1.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/quartz_solar_forecast/forecasts/v1.py b/quartz_solar_forecast/forecasts/v1.py index 271925f7..7bb9b16c 100644 --- a/quartz_solar_forecast/forecasts/v1.py +++ b/quartz_solar_forecast/forecasts/v1.py @@ -31,7 +31,8 @@ def forecast_v1(nwp_source:str, nwp_xr:xr.Dataset, pv_xr:xr.Dataset, ts:pd.Times nwp = NwpDataSource(nwp_xr, value_name=nwp_source) model.set_data_sources(pv_data_source=pv_data_source, nwp_data_sources={nwp_source: nwp}) - # make prediction + # make prediction. + # Note pv_id=1 is arbitrary, but the pv_xr must have this in it. x = X(pv_id="1", ts=ts) pred = model.predict(x) From 039fb65e647125dbdf72e3b2c7eeaedd1a590ee8 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 15:03:59 +0000 Subject: [PATCH 51/52] typos in script comments --- scripts/run_evaluation.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/scripts/run_evaluation.py b/scripts/run_evaluation.py index cae2bfd0..5eba8260 100644 --- a/scripts/run_evaluation.py +++ b/scripts/run_evaluation.py @@ -1,10 +1,10 @@ -""" Make script to run evalutions on the test set. +""" Make script to run the evaluation on the test set. The idea is to run the model on the test set and then compare the results to the actual PV generation. The NWP (ICON) and PV data are both pulled Open Climate Fix's Hugging Face page. -Please note it can takes hours to pull the NWP data. -The data will be cached locally so next time you run it, itll be much quickerl +Please note it can take hours to pull the NWP data. +The data will be cached locally so next time you run it, itll be much quicker """ from quartz_solar_forecast.evaluation import run_eval From b1013f40b9f2177653cd3d06513ad53d035494b9 Mon Sep 17 00:00:00 2001 From: peterdudfield Date: Tue, 19 Dec 2023 15:07:59 +0000 Subject: [PATCH 52/52] add comment about v1 in forecasts --- quartz_solar_forecast/forecasts/__init__.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/quartz_solar_forecast/forecasts/__init__.py b/quartz_solar_forecast/forecasts/__init__.py index e69de29b..0434f851 100644 --- a/quartz_solar_forecast/forecasts/__init__.py +++ b/quartz_solar_forecast/forecasts/__init__.py @@ -0,0 +1,8 @@ +""" +Forecasts + +v1: This model is trained with pv-site-predictions - https://github.com/openclimatefix/pv-site-prediction +The model is a gradient boosted tree model and uses 9 NWP variables from the UK MetOffice. +It is trained on 25,000 PV sites with over 5 years of PV history, which is available [here](https://huggingface.co/datasets/openclimatefix/uk_pv). + +""" \ No newline at end of file