From 282d7dba29b5a1342cbf2d3065274fcd70621494 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Thu, 1 Feb 2024 23:50:14 +0000
Subject: [PATCH 01/15] add data synthesis script

---
 .gitignore                              |   1 -
 pyrealm_build_data/data_model_params.nc | Bin 0 -> 38187311 bytes
 pyrealm_build_data/synth.py             | 109 ++++++++++++++++++++++++
 3 files changed, 109 insertions(+), 1 deletion(-)
 create mode 100644 pyrealm_build_data/data_model_params.nc
 create mode 100644 pyrealm_build_data/synth.py

diff --git a/.gitignore b/.gitignore
index 597dc5c0..7b2841d1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -30,7 +30,6 @@ pyrealm.egg-info
 
 # Data
 pyrealm_build_data/inputs_data_24.25.nc
-pyrealm_build_data/eda.py
 
 # Profiling
 prof/
diff --git a/pyrealm_build_data/data_model_params.nc b/pyrealm_build_data/data_model_params.nc
new file mode 100644
index 0000000000000000000000000000000000000000..a9456b30df9cb4721ac0a294258b685170808ed3
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diff --git a/pyrealm_build_data/synth.py b/pyrealm_build_data/synth.py
new file mode 100644
index 00000000..53627ca3
--- /dev/null
+++ b/pyrealm_build_data/synth.py
@@ -0,0 +1,109 @@
+"""This script uses a parametrized model to compress the input dataset.
+
+It fits a time series model to the input data and stores the model parameters,
+which can be later used to reconstruct the original dataset.
+"""
+import numpy as np
+import pandas as pd
+import statsmodels.api as sm
+import xarray as xr
+from np.typing import ArrayLike
+from tqdm import tqdm
+
+ds = xr.open_dataset("inputs_data_24.25.nc")
+
+const_vars_over_time = ["patm"]
+const_vars_over_space = ["co2"]
+
+
+def make_time_features(dt: ArrayLike, is_const: bool = False) -> pd.DataFrame:
+    """Make time features for a given time index."""
+    dt = pd.to_datetime(dt).rename("time")
+    df = sm.add_constant(pd.DataFrame(index=dt))
+
+    if is_const:
+        return df
+
+    # Linear trend
+    df["linear"] = (dt - pd.Timestamp("2000-01-01")) / pd.Timedelta("1h")
+
+    # El-Nino and La-Nina seasonality component
+    for k in [1, 2, 3, 4]:
+        df[f"cross_year_{k}_sin"] = np.sin(2 * k * np.pi * dt.year / 12)
+        df[f"cross_year_{k}_cos"] = np.cos(2 * k * np.pi * dt.year / 12)
+
+    # Yearly seasonality component
+    for k in [1, 2, 3, 4]:
+        df[f"yearly_{k}_sin"] = np.sin(2 * k * np.pi * dt.dayofyear / 365)
+        df[f"yearly_{k}_cos"] = np.cos(2 * k * np.pi * dt.dayofyear / 365)
+
+    # Daily seasonality component
+    for k in [1, 2, 3, 4]:
+        df[f"daily_{k}_sin"] = np.sin(2 * k * np.pi * dt.hour / 24)
+        df[f"daily_{k}_cos"] = np.cos(2 * k * np.pi * dt.hour / 24)
+
+    return df
+
+
+def fit_ts_model(da: xr.DataArray, is_const: bool = False) -> pd.DataFrame:
+    """Fit a time series model to the data."""
+    df = da.sel(time=slice(None, None, 2)).to_series().unstack("time").T
+    df = df.dropna(axis=1, how="all")
+    features = make_time_features(df.index, is_const=is_const)
+    params = pd.DataFrame(index=df.columns, columns=features.columns)
+    for k in tqdm(df.columns):
+        y = df[k].dropna()
+        X = features.loc[y.index]
+        model = sm.OLS(y, X).fit()
+        params.loc[k] = model.params
+    return params.astype(float)
+
+
+params_ds = xr.Dataset()
+
+for k in ds.data_vars:
+    print("Fitting", k)
+    if k in const_vars_over_space:
+        da = ds[k].isel(lat=[0], lon=[0])
+    else:
+        da = ds[k]
+    if k in const_vars_over_time:
+        ps = fit_ts_model(da, is_const=True)
+    else:
+        ps = fit_ts_model(da)
+    params_ds[k] = ps.to_xarray().to_dataarray()
+
+for k, a in params_ds.items():
+    if k in const_vars_over_space:
+        params_ds[k] = a.fillna(a.isel(lat=0, lon=0))
+    elif k in const_vars_over_time:
+        params_ds[k] = a.fillna(0)
+
+fs = make_time_features(ds.time).to_xarray().to_dataarray()
+params_ds["feature"] = fs
+params_ds.to_netcdf("data_model_params.nc")
+
+
+def reconstruct_data(params_ds: xr.Dataset) -> xr.Dataset:
+    """Reconstruct the data from the model parameters."""
+    rec_ds = xr.Dataset()
+    f = params_ds["feature"]
+    for k, a in params_ds.items():
+        if k != "feature":
+            rec_ds[k] = xr.dot(f, a)
+    return rec_ds
+
+
+rec_ds = reconstruct_data(params_ds)
+
+
+def r2_score(y_true: ArrayLike, y_pred: ArrayLike) -> float:
+    """Compute the R2 score."""
+    return 1 - ((y_true - y_pred) ** 2).sum() / ((y_true - y_true.mean()) ** 2).sum()
+
+
+for k in ds.data_vars:
+    t = ds[k].sel(lat=rec_ds.lat).squeeze()[::321]
+    p = rec_ds[k].squeeze()[::321]
+    r2 = r2_score(t, p)
+    print(f"R2 score for {k}: {r2:.2f}")

From 7ae44e266dd3985ec5fbf8aea85484efed028725 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Fri, 2 Feb 2024 10:33:43 +0000
Subject: [PATCH 02/15] add regression test for data synthesis

---
 .../{synth.py => synth_data.py}               | 25 -------------
 tests/regression/data/test_synth_data.py      | 36 +++++++++++++++++++
 2 files changed, 36 insertions(+), 25 deletions(-)
 rename pyrealm_build_data/{synth.py => synth_data.py} (79%)
 create mode 100644 tests/regression/data/test_synth_data.py

diff --git a/pyrealm_build_data/synth.py b/pyrealm_build_data/synth_data.py
similarity index 79%
rename from pyrealm_build_data/synth.py
rename to pyrealm_build_data/synth_data.py
index 53627ca3..100aa1c1 100644
--- a/pyrealm_build_data/synth.py
+++ b/pyrealm_build_data/synth_data.py
@@ -82,28 +82,3 @@ def fit_ts_model(da: xr.DataArray, is_const: bool = False) -> pd.DataFrame:
 fs = make_time_features(ds.time).to_xarray().to_dataarray()
 params_ds["feature"] = fs
 params_ds.to_netcdf("data_model_params.nc")
-
-
-def reconstruct_data(params_ds: xr.Dataset) -> xr.Dataset:
-    """Reconstruct the data from the model parameters."""
-    rec_ds = xr.Dataset()
-    f = params_ds["feature"]
-    for k, a in params_ds.items():
-        if k != "feature":
-            rec_ds[k] = xr.dot(f, a)
-    return rec_ds
-
-
-rec_ds = reconstruct_data(params_ds)
-
-
-def r2_score(y_true: ArrayLike, y_pred: ArrayLike) -> float:
-    """Compute the R2 score."""
-    return 1 - ((y_true - y_pred) ** 2).sum() / ((y_true - y_true.mean()) ** 2).sum()
-
-
-for k in ds.data_vars:
-    t = ds[k].sel(lat=rec_ds.lat).squeeze()[::321]
-    p = rec_ds[k].squeeze()[::321]
-    r2 = r2_score(t, p)
-    print(f"R2 score for {k}: {r2:.2f}")
diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
new file mode 100644
index 00000000..b7e3a6cb
--- /dev/null
+++ b/tests/regression/data/test_synth_data.py
@@ -0,0 +1,36 @@
+"""Test the quality of the synthetic data generated from the model parameters."""
+
+import numpy as np
+import pytest
+import xarray as xr
+
+
+def r2_score(y_true: xr.DataArray, y_pred: xr.DataArray) -> float:
+    """Compute the R2 score."""
+    SSE = ((y_true - y_pred) ** 2).sum().item()
+    SST = ((y_true - y_true.mean()) ** 2).sum().item()
+    return 1 - SSE / SST
+
+
+@pytest.fixture
+def dataset(path="pyrealm_build_data/inputs_data_24.25.nc"):
+    """The original dataset."""
+    return xr.open_dataset(path)
+
+
+@pytest.fixture
+def synth_dataset(path="pyrealm_build_data/data_model_params.nc"):
+    """Generate the synthetic dataset from the model parameters."""
+    ds = xr.open_dataset(path)
+    return xr.Dataset({k: a @ ds["feature"] for k, a in ds.items() if k != "feature"})
+
+
+def test_synth_data_quality(dataset, synth_dataset):
+    """Test the quality of the synthetic data."""
+    sample = np.random.choice(dataset.time.size, 1000, replace=False)
+    for k in dataset.data_vars:
+        t = dataset[k].sel(lat=synth_dataset.lat).isel(time=sample)
+        p = synth_dataset[k].isel(time=sample)
+        r2 = r2_score(t, p)
+        print(f"R2 score for {k}: {r2:.2f}")
+        assert r2 > 0.85

From 25515ee309db0312c55f964cc45d8309dd6af3c1 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Fri, 2 Feb 2024 11:27:56 +0000
Subject: [PATCH 03/15] refactor code

---
 pyrealm_build_data/synth_data.py         | 81 +++++++++++++-----------
 tests/regression/data/test_synth_data.py | 10 ++-
 2 files changed, 50 insertions(+), 41 deletions(-)

diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index 100aa1c1..915c0acb 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -5,30 +5,22 @@
 """
 import numpy as np
 import pandas as pd
-import statsmodels.api as sm
 import xarray as xr
-from np.typing import ArrayLike
-from tqdm import tqdm
 
-ds = xr.open_dataset("inputs_data_24.25.nc")
 
-const_vars_over_time = ["patm"]
-const_vars_over_space = ["co2"]
-
-
-def make_time_features(dt: ArrayLike, is_const: bool = False) -> pd.DataFrame:
+def make_time_features(t: np.ndarray, const_only: bool = False) -> pd.DataFrame:
     """Make time features for a given time index."""
-    dt = pd.to_datetime(dt).rename("time")
+    dt = pd.to_datetime(t).rename("time")
     df = sm.add_constant(pd.DataFrame(index=dt))
 
-    if is_const:
+    if const_only:
         return df
 
     # Linear trend
     df["linear"] = (dt - pd.Timestamp("2000-01-01")) / pd.Timedelta("1h")
 
     # El-Nino and La-Nina seasonality component
-    for k in [1, 2, 3, 4]:
+    for k in [2, 3, 4, 6]:
         df[f"cross_year_{k}_sin"] = np.sin(2 * k * np.pi * dt.year / 12)
         df[f"cross_year_{k}_cos"] = np.cos(2 * k * np.pi * dt.year / 12)
 
@@ -45,11 +37,11 @@ def make_time_features(dt: ArrayLike, is_const: bool = False) -> pd.DataFrame:
     return df
 
 
-def fit_ts_model(da: xr.DataArray, is_const: bool = False) -> pd.DataFrame:
+def fit_ts_model(da: xr.DataArray, const_only: bool = False) -> pd.DataFrame:
     """Fit a time series model to the data."""
-    df = da.sel(time=slice(None, None, 2)).to_series().unstack("time").T
+    df = da.resample(time="2h").to_series().unstack("time").T
     df = df.dropna(axis=1, how="all")
-    features = make_time_features(df.index, is_const=is_const)
+    features = make_time_features(df.index, const_only=const_only)
     params = pd.DataFrame(index=df.columns, columns=features.columns)
     for k in tqdm(df.columns):
         y = df[k].dropna()
@@ -59,26 +51,39 @@ def fit_ts_model(da: xr.DataArray, is_const: bool = False) -> pd.DataFrame:
     return params.astype(float)
 
 
-params_ds = xr.Dataset()
-
-for k in ds.data_vars:
-    print("Fitting", k)
-    if k in const_vars_over_space:
-        da = ds[k].isel(lat=[0], lon=[0])
-    else:
-        da = ds[k]
-    if k in const_vars_over_time:
-        ps = fit_ts_model(da, is_const=True)
-    else:
-        ps = fit_ts_model(da)
-    params_ds[k] = ps.to_xarray().to_dataarray()
-
-for k, a in params_ds.items():
-    if k in const_vars_over_space:
-        params_ds[k] = a.fillna(a.isel(lat=0, lon=0))
-    elif k in const_vars_over_time:
-        params_ds[k] = a.fillna(0)
-
-fs = make_time_features(ds.time).to_xarray().to_dataarray()
-params_ds["feature"] = fs
-params_ds.to_netcdf("data_model_params.nc")
+def decompress(ds: xr.Dataset) -> xr.Dataset:
+    """Decompress the dataset from the model parameters."""
+    return xr.Dataset({k: a @ ds["feature"] for k, a in ds.items() if k != "feature"})
+
+
+if __name__ == "__main__":
+    import statsmodels.api as sm
+    from tqdm import tqdm
+
+    ds = xr.open_dataset("inputs_data_24.25.nc")
+
+    const_vars_over_time = ["patm"]
+    const_vars_over_space = ["co2"]
+
+    params_ds = xr.Dataset()
+
+    for k in ds.data_vars:
+        print("Fitting", k)
+        if k in const_vars_over_space:
+            da = ds[k].isel(lat=[0], lon=[0])
+        else:
+            da = ds[k]
+        if k in const_vars_over_time:
+            ps = fit_ts_model(da, const_only=True)
+        else:
+            ps = fit_ts_model(da)
+        params_ds[k] = ps.to_xarray().to_dataarray()
+
+    for k, a in params_ds.items():
+        if k in const_vars_over_space:
+            params_ds[k] = a.fillna(a.isel(lat=0, lon=0))
+        elif k in const_vars_over_time:
+            params_ds[k] = a.fillna(0)
+
+    params_ds["feature"] = make_time_features(ds.time).to_xarray().to_dataarray()
+    params_ds.to_netcdf("data_model_params.nc")
diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
index b7e3a6cb..bdc5109d 100644
--- a/tests/regression/data/test_synth_data.py
+++ b/tests/regression/data/test_synth_data.py
@@ -15,14 +15,18 @@ def r2_score(y_true: xr.DataArray, y_pred: xr.DataArray) -> float:
 @pytest.fixture
 def dataset(path="pyrealm_build_data/inputs_data_24.25.nc"):
     """The original dataset."""
-    return xr.open_dataset(path)
+    try:
+        return xr.open_dataset(path)
+    except ValueError:
+        pytest.skip("Original LFS dataset not checked out.")
 
 
 @pytest.fixture
 def synth_dataset(path="pyrealm_build_data/data_model_params.nc"):
     """Generate the synthetic dataset from the model parameters."""
-    ds = xr.open_dataset(path)
-    return xr.Dataset({k: a @ ds["feature"] for k, a in ds.items() if k != "feature"})
+    from pyrealm_build_data.synth_data import decompress
+
+    return decompress(xr.open_dataset(path))
 
 
 def test_synth_data_quality(dataset, synth_dataset):

From f3efac2acb4a5c4f5ce6e27722d18a559fc6377e Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Mon, 5 Feb 2024 12:43:41 +0000
Subject: [PATCH 04/15] reduce size of saved weights

---
 pyrealm_build_data/data_model.nc         | Bin 0 -> 294738 bytes
 pyrealm_build_data/data_model_params.nc  | Bin 38187311 -> 0 bytes
 pyrealm_build_data/synth_data.py         | 100 ++++++++++-------------
 tests/regression/data/test_synth_data.py |  52 +++++++-----
 4 files changed, 76 insertions(+), 76 deletions(-)
 create mode 100644 pyrealm_build_data/data_model.nc
 delete mode 100644 pyrealm_build_data/data_model_params.nc

diff --git a/pyrealm_build_data/data_model.nc b/pyrealm_build_data/data_model.nc
new file mode 100644
index 0000000000000000000000000000000000000000..fc628a0bd7ad12b779ccf1a35eb908391cfb7567
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diff --git a/pyrealm_build_data/data_model_params.nc b/pyrealm_build_data/data_model_params.nc
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diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index 915c0acb..5cf77361 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -3,87 +3,75 @@
 It fits a time series model to the input data and stores the model parameters,
 which can be later used to reconstruct the original dataset.
 """
+from typing import Tuple
+
 import numpy as np
 import pandas as pd
 import xarray as xr
 
 
-def make_time_features(t: np.ndarray, const_only: bool = False) -> pd.DataFrame:
+def make_time_features(t: np.ndarray) -> pd.DataFrame:
     """Make time features for a given time index."""
     dt = pd.to_datetime(t).rename("time")
-    df = sm.add_constant(pd.DataFrame(index=dt))
-
-    if const_only:
-        return df
-
-    # Linear trend
-    df["linear"] = (dt - pd.Timestamp("2000-01-01")) / pd.Timedelta("1h")
-
-    # El-Nino and La-Nina seasonality component
-    for k in [2, 3, 4, 6]:
-        df[f"cross_year_{k}_sin"] = np.sin(2 * k * np.pi * dt.year / 12)
-        df[f"cross_year_{k}_cos"] = np.cos(2 * k * np.pi * dt.year / 12)
+    df = pd.DataFrame(index=dt).assign(const=1.0)
 
-    # Yearly seasonality component
-    for k in [1, 2, 3, 4]:
-        df[f"yearly_{k}_sin"] = np.sin(2 * k * np.pi * dt.dayofyear / 365)
-        df[f"yearly_{k}_cos"] = np.cos(2 * k * np.pi * dt.dayofyear / 365)
+    df["linear"] = (dt - pd.Timestamp("2000-01-01")) / pd.Timedelta("365.25d")
 
-    # Daily seasonality component
-    for k in [1, 2, 3, 4]:
-        df[f"daily_{k}_sin"] = np.sin(2 * k * np.pi * dt.hour / 24)
-        df[f"daily_{k}_cos"] = np.cos(2 * k * np.pi * dt.hour / 24)
+    for f in [365.25, 12, 6, 4, 3, 2, 1, 1 / 2, 1 / 3, 1 / 4, 1 / 6]:
+        df[f"freq_{f:.2f}_sin"] = np.sin(2 * np.pi * f * df["linear"])
+        df[f"freq_{f:.2f}_cos"] = np.cos(2 * np.pi * f * df["linear"])
 
     return df
 
 
-def fit_ts_model(da: xr.DataArray, const_only: bool = False) -> pd.DataFrame:
+def fit_ts_model(df: pd.DataFrame, fs: pd.DataFrame) -> Tuple[pd.DataFrame, pd.Series]:
     """Fit a time series model to the data."""
-    df = da.resample(time="2h").to_series().unstack("time").T
+    from tqdm import tqdm
+
     df = df.dropna(axis=1, how="all")
-    features = make_time_features(df.index, const_only=const_only)
-    params = pd.DataFrame(index=df.columns, columns=features.columns)
+    params = pd.DataFrame(index=df.columns, columns=fs.columns)
+    losses = []
     for k in tqdm(df.columns):
         y = df[k].dropna()
-        X = features.loc[y.index]
-        model = sm.OLS(y, X).fit()
-        params.loc[k] = model.params
-    return params.astype(float)
+        X = fs.loc[y.index]
+        c, r, *_ = np.linalg.lstsq(X, y, rcond=None)
+        # TODO: optimize with constraints, e.g. ppfd >= 0
+        losses.extend(r / np.sum(y**2))
+        params.loc[k] = c
 
+    return params, pd.Series(losses, index=df.columns)
 
-def decompress(ds: xr.Dataset) -> xr.Dataset:
-    """Decompress the dataset from the model parameters."""
-    return xr.Dataset({k: a @ ds["feature"] for k, a in ds.items() if k != "feature"})
+
+def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset:
+    """Reconstruct the full dataset from the model parameters."""
+    x = make_time_features(dt).to_xarray().to_dataarray()
+    return xr.Dataset({k: a @ x for k, a in ds.items() if k != "features"})
 
 
 if __name__ == "__main__":
-    import statsmodels.api as sm
-    from tqdm import tqdm
+    ds = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
 
-    ds = xr.open_dataset("inputs_data_24.25.nc")
+    mask = ~ds.isnull().all("time").to_dataarray().any("variable")
+    ds = ds.where(mask, drop=True)
 
-    const_vars_over_time = ["patm"]
-    const_vars_over_space = ["co2"]
+    special_time_features = dict(
+        patm=["const"],
+        co2=["const", "linear"],
+    )
 
-    params_ds = xr.Dataset()
+    features = make_time_features(ds.time)
+    model = xr.Dataset()
 
     for k in ds.data_vars:
         print("Fitting", k)
-        if k in const_vars_over_space:
-            da = ds[k].isel(lat=[0], lon=[0])
-        else:
-            da = ds[k]
-        if k in const_vars_over_time:
-            ps = fit_ts_model(da, const_only=True)
-        else:
-            ps = fit_ts_model(da)
-        params_ds[k] = ps.to_xarray().to_dataarray()
-
-    for k, a in params_ds.items():
-        if k in const_vars_over_space:
-            params_ds[k] = a.fillna(a.isel(lat=0, lon=0))
-        elif k in const_vars_over_time:
-            params_ds[k] = a.fillna(0)
-
-    params_ds["feature"] = make_time_features(ds.time).to_xarray().to_dataarray()
-    params_ds.to_netcdf("data_model_params.nc")
+        da = ds[k].isel(time=slice(None, None, 4))  # downsample along time
+        df = da.to_series().unstack("time").T  # (datetimes, locations)
+        fs = features.loc[df.index]  # (datetimes, features)
+        fs = fs[special_time_features.get(k, fs.columns)]
+        ps, ls = fit_ts_model(df, fs)  # (locations, features)
+        print("Loss:", ls.mean())
+        ps[features.keys().difference(ps.columns)] = 0.0
+        model[k] = ps.to_xarray().to_dataarray()
+
+    # model["features"] = features.to_xarray().to_dataarray()
+    model.to_netcdf("pyrealm_build_data/data_model.nc")
diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
index bdc5109d..f1d7a859 100644
--- a/tests/regression/data/test_synth_data.py
+++ b/tests/regression/data/test_synth_data.py
@@ -1,40 +1,52 @@
 """Test the quality of the synthetic data generated from the model parameters."""
 
 import numpy as np
+import pandas as pd
 import pytest
 import xarray as xr
 
+DATASET = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
+VARS = DATASET.data_vars
+
 
 def r2_score(y_true: xr.DataArray, y_pred: xr.DataArray) -> float:
     """Compute the R2 score."""
-    SSE = ((y_true - y_pred) ** 2).sum().item()
-    SST = ((y_true - y_true.mean()) ** 2).sum().item()
+    SSE = ((y_true - y_pred) ** 2).sum()
+    SST = ((y_true - y_true.mean()) ** 2).sum()
     return 1 - SSE / SST
 
 
 @pytest.fixture
-def dataset(path="pyrealm_build_data/inputs_data_24.25.nc"):
+def syndata(modelpath="pyrealm_build_data/data_model.nc"):
+    """The synthetic dataset."""
+    from pyrealm_build_data.synth_data import reconstruct
+
+    model = xr.open_dataset(modelpath)
+    ts = pd.date_range("2010-01-01", "2018-01-01", freq="8h")
+    return reconstruct(model, ts)
+
+
+@pytest.fixture
+def dataset(syndata):
     """The original dataset."""
     try:
-        return xr.open_dataset(path)
+        return DATASET.sel(time=syndata.time)
     except ValueError:
         pytest.skip("Original LFS dataset not checked out.")
 
 
-@pytest.fixture
-def synth_dataset(path="pyrealm_build_data/data_model_params.nc"):
-    """Generate the synthetic dataset from the model parameters."""
-    from pyrealm_build_data.synth_data import decompress
-
-    return decompress(xr.open_dataset(path))
-
-
-def test_synth_data_quality(dataset, synth_dataset):
+@pytest.mark.parametrize("var", VARS)
+def test_synth_data_quality(dataset, syndata, var):
     """Test the quality of the synthetic data."""
-    sample = np.random.choice(dataset.time.size, 1000, replace=False)
-    for k in dataset.data_vars:
-        t = dataset[k].sel(lat=synth_dataset.lat).isel(time=sample)
-        p = synth_dataset[k].isel(time=sample)
-        r2 = r2_score(t, p)
-        print(f"R2 score for {k}: {r2:.2f}")
-        assert r2 > 0.85
+    times = syndata.time[np.random.choice(syndata.time.size, 1000, replace=False)]
+    lats = syndata.lat[np.random.choice(syndata.lat.size, 100, replace=False)]
+    t = dataset[var].sel(lat=lats, time=times)
+    p = syndata[var].sel(lat=lats, time=times)
+    s = r2_score(t, p)
+    print(f"R2 score for {var} is {s:.2f}")
+    if s < 0.8:
+        # import matplotlib.pyplot as plt
+        # t.sortby("time").mean(["lat", "lon"]).plot()
+        # p.sortby("time").mean(["lat", "lon"]).plot()
+        # plt.show()
+        raise AssertionError

From 5de33732ce1e9fc53fd67f3102967b8f44630838 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Mon, 5 Feb 2024 16:09:36 +0000
Subject: [PATCH 05/15] fix file not found issue in test

---
 tests/regression/data/test_synth_data.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
index f1d7a859..ebf0faad 100644
--- a/tests/regression/data/test_synth_data.py
+++ b/tests/regression/data/test_synth_data.py
@@ -5,7 +5,11 @@
 import pytest
 import xarray as xr
 
-DATASET = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
+try:
+    DATASET = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
+except ValueError:
+    pytest.skip("Original LFS dataset not checked out.")
+
 VARS = DATASET.data_vars
 
 
@@ -22,17 +26,14 @@ def syndata(modelpath="pyrealm_build_data/data_model.nc"):
     from pyrealm_build_data.synth_data import reconstruct
 
     model = xr.open_dataset(modelpath)
-    ts = pd.date_range("2010-01-01", "2018-01-01", freq="8h")
+    ts = pd.date_range("2012-01-01", "2018-01-01", freq="12h")
     return reconstruct(model, ts)
 
 
 @pytest.fixture
 def dataset(syndata):
     """The original dataset."""
-    try:
-        return DATASET.sel(time=syndata.time)
-    except ValueError:
-        pytest.skip("Original LFS dataset not checked out.")
+    return DATASET.sel(time=syndata.time)
 
 
 @pytest.mark.parametrize("var", VARS)

From 1b85b25254943e32c4777b42d9515c68a5fcac2d Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Mon, 5 Feb 2024 16:14:34 +0000
Subject: [PATCH 06/15] fix `pytest.skip`

---
 tests/regression/data/test_synth_data.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
index ebf0faad..5c185ab2 100644
--- a/tests/regression/data/test_synth_data.py
+++ b/tests/regression/data/test_synth_data.py
@@ -8,7 +8,7 @@
 try:
     DATASET = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
 except ValueError:
-    pytest.skip("Original LFS dataset not checked out.")
+    pytest.skip("Original LFS dataset not checked out.", allow_module_level=True)
 
 VARS = DATASET.data_vars
 

From abf2a6b5cfae00cfde3d570f0afeb42acc422b96 Mon Sep 17 00:00:00 2001
From: TZCai <13818704679@163.com>
Date: Tue, 6 Feb 2024 11:27:58 +0000
Subject: [PATCH 07/15] update pandas version in requirement

---
 poetry.lock                              | 4096 +++++++++++-----------
 pyproject.toml                           |    2 +-
 tests/regression/data/test_synth_data.py |    3 +-
 3 files changed, 1987 insertions(+), 2114 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 2b47aac1..b3fbd1ed 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,26 +1,37 @@
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+
 [[package]]
 name = "alabaster"
-version = "0.7.13"
-description = "A configurable sidebar-enabled Sphinx theme"
-category = "dev"
+version = "0.7.16"
+description = "A light, configurable Sphinx theme"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.9"
+files = [
+    {file = "alabaster-0.7.16-py3-none-any.whl", hash = "sha256:b46733c07dce03ae4e150330b975c75737fa60f0a7c591b6c8bf4928a28e2c92"},
+    {file = "alabaster-0.7.16.tar.gz", hash = "sha256:75a8b99c28a5dad50dd7f8ccdd447a121ddb3892da9e53d1ca5cca3106d58d65"},
+]
 
 [[package]]
 name = "appnope"
-version = "0.1.3"
+version = "0.1.4"
 description = "Disable App Nap on macOS >= 10.9"
-category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=3.6"
+files = [
+    {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
+    {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
+]
 
 [[package]]
 name = "asttokens"
 version = "2.4.1"
 description = "Annotate AST trees with source code positions"
-category = "dev"
 optional = false
 python-versions = "*"
+files = [
+    {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
+    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
+]
 
 [package.dependencies]
 six = ">=1.12.0"
@@ -33,9 +44,12 @@ test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 name = "attrs"
 version = "23.2.0"
 description = "Classes Without Boilerplate"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
+]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
@@ -49,9 +63,12 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
 name = "autodocsumm"
 version = "0.2.12"
 description = "Extended sphinx autodoc including automatic autosummaries"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "autodocsumm-0.2.12-py3-none-any.whl", hash = "sha256:b842b53c686c07a4f174721ca4e729b027367703dbf42e2508863a3c6d6c049c"},
+    {file = "autodocsumm-0.2.12.tar.gz", hash = "sha256:848fe8c38df433c6635489499b969cb47cc389ed3d7b6e75c8ccbc94d4b3bf9e"},
+]
 
 [package.dependencies]
 Sphinx = ">=2.2,<8.0"
@@ -60,9 +77,12 @@ Sphinx = ">=2.2,<8.0"
 name = "babel"
 version = "2.14.0"
 description = "Internationalization utilities"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
+    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
+]
 
 [package.extras]
 dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
@@ -71,9 +91,22 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 name = "black"
 version = "22.12.0"
 description = "The uncompromising code formatter."
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "black-22.12.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eedd20838bd5d75b80c9f5487dbcb06836a43833a37846cf1d8c1cc01cef59d"},
+    {file = "black-22.12.0-cp310-cp310-win_amd64.whl", hash = "sha256:159a46a4947f73387b4d83e87ea006dbb2337eab6c879620a3ba52699b1f4351"},
+    {file = "black-22.12.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d30b212bffeb1e252b31dd269dfae69dd17e06d92b87ad26e23890f3efea366f"},
+    {file = "black-22.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:7412e75863aa5c5411886804678b7d083c7c28421210180d67dfd8cf1221e1f4"},
+    {file = "black-22.12.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c116eed0efb9ff870ded8b62fe9f28dd61ef6e9ddd28d83d7d264a38417dcee2"},
+    {file = "black-22.12.0-cp37-cp37m-win_amd64.whl", hash = "sha256:1f58cbe16dfe8c12b7434e50ff889fa479072096d79f0a7f25e4ab8e94cd8350"},
+    {file = "black-22.12.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77d86c9f3db9b1bf6761244bc0b3572a546f5fe37917a044e02f3166d5aafa7d"},
+    {file = "black-22.12.0-cp38-cp38-win_amd64.whl", hash = "sha256:82d9fe8fee3401e02e79767016b4907820a7dc28d70d137eb397b92ef3cc5bfc"},
+    {file = "black-22.12.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:101c69b23df9b44247bd88e1d7e90154336ac4992502d4197bdac35dd7ee3320"},
+    {file = "black-22.12.0-cp39-cp39-win_amd64.whl", hash = "sha256:559c7a1ba9a006226f09e4916060982fd27334ae1998e7a38b3f33a37f7a2148"},
+    {file = "black-22.12.0-py3-none-any.whl", hash = "sha256:436cc9167dd28040ad90d3b404aec22cedf24a6e4d7de221bec2730ec0c97bcf"},
+    {file = "black-22.12.0.tar.gz", hash = "sha256:229351e5a18ca30f447bf724d007f890f97e13af070bb6ad4c0a441cd7596a2f"},
+]
 
 [package.dependencies]
 click = ">=8.0.0"
@@ -91,19 +124,75 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "certifi"
-version = "2023.11.17"
+version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
-category = "dev"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
+    {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
+]
 
 [[package]]
 name = "cffi"
 version = "1.16.0"
 description = "Foreign Function Interface for Python calling C code."
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "cffi-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6b3d6606d369fc1da4fd8c357d026317fbb9c9b75d36dc16e90e84c26854b088"},
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 [package.dependencies]
 pycparser = "*"
@@ -112,17 +201,42 @@ pycparser = "*"
 name = "cfgv"
 version = "3.4.0"
 description = "Validate configuration and produce human readable error messages."
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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+]
 
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 name = "cftime"
 version = "1.6.3"
 description = "Time-handling functionality from netcdf4-python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
 numpy = {version = ">1.13.3", markers = "python_version < \"3.12.0.rc1\""}
@@ -131,17 +245,111 @@ numpy = {version = ">1.13.3", markers = "python_version < \"3.12.0.rc1\""}
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 version = "3.3.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "dev"
 optional = false
 python-versions = ">=3.7.0"
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 [[package]]
 name = "click"
 version = "8.1.7"
 description = "Composable command line interface toolkit"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
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 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
@@ -150,17 +358,23 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "dev"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
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 [[package]]
 name = "comm"
 version = "0.2.1"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
 traitlets = ">=4"
@@ -172,9 +386,54 @@ test = ["pytest"]
 name = "contourpy"
 version = "1.2.0"
 description = "Python library for calculating contours of 2D quadrilateral grids"
-category = "dev"
 optional = false
 python-versions = ">=3.9"
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+]
 
 [package.dependencies]
 numpy = ">=1.20,<2.0"
@@ -188,11 +447,64 @@ test-no-images = ["pytest", "pytest-cov", "pytest-xdist", "wurlitzer"]
 
 [[package]]
 name = "coverage"
-version = "7.4.0"
+version = "7.4.1"
 description = "Code coverage measurement for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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 tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.11.0a6\" and extra == \"toml\""}
@@ -204,9 +516,12 @@ toml = ["tomli"]
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 version = "0.12.1"
 description = "Composable style cycles"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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@@ -216,9 +531,11 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
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 version = "1.8.1"
 description = "Simple creation of data classes from dictionaries."
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 [package.extras]
 dev = ["black", "coveralls", "mypy", "pre-commit", "pylint", "pytest (>=5)", "pytest-benchmark", "pytest-cov"]
@@ -227,41 +544,72 @@ dev = ["black", "coveralls", "mypy", "pre-commit", "pylint", "pytest (>=5)", "py
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 python-versions = ">=3.8"
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 description = "Decorators for Humans"
-category = "dev"
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 python-versions = ">=3.5"
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 python-versions = "*"
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 version = "0.20.1"
 description = "Docutils -- Python Documentation Utilities"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
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 name = "exceptiongroup"
 version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
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 [package.extras]
 test = ["pytest (>=6)"]
@@ -270,9 +618,12 @@ test = ["pytest (>=6)"]
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 version = "2.0.1"
 description = "Get the currently executing AST node of a frame, and other information"
-category = "dev"
 optional = false
 python-versions = ">=3.5"
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 tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
@@ -281,9 +632,12 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 name = "fastjsonschema"
 version = "2.19.1"
 description = "Fastest Python implementation of JSON schema"
-category = "dev"
 optional = false
 python-versions = "*"
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 [package.extras]
 devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
@@ -292,9 +646,12 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
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 version = "3.13.1"
 description = "A platform independent file lock."
-category = "dev"
 optional = false
 python-versions = ">=3.8"
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 docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.24)"]
@@ -305,9 +662,12 @@ typing = ["typing-extensions (>=4.8)"]
 name = "flake8"
 version = "4.0.1"
 description = "the modular source code checker: pep8 pyflakes and co"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
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 mccabe = ">=0.6.0,<0.7.0"
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 version = "1.7.0"
 description = "Extension for flake8 which uses pydocstyle to check docstrings"
-category = "dev"
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 python-versions = ">=3.7"
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 flake8 = ">=3"
@@ -328,11 +691,54 @@ pydocstyle = ">=2.1"
 
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 optional = false
 python-versions = ">=3.8"
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 version = "2022.7.29"
 description = "Generate a dot graph from the output of several profilers."
-category = "dev"
 optional = false
 python-versions = ">=2.7"
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+]
 
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 version = "0.20.1"
 description = "Simple Python interface for Graphviz"
-category = "main"
 optional = false
 python-versions = ">=3.7"
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+]
 
 [package.extras]
 dev = ["flake8", "pep8-naming", "tox (>=3)", "twine", "wheel"]
@@ -373,9 +785,68 @@ test = ["coverage", "mock (>=4)", "pytest (>=7)", "pytest-cov", "pytest-mock (>=
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 version = "3.0.3"
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-category = "dev"
 optional = false
 python-versions = ">=3.7"
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+    {file = "greenlet-3.0.3.tar.gz", hash = "sha256:43374442353259554ce33599da8b692d5aa96f8976d567d4badf263371fbe491"},
+]
 
 [package.extras]
 docs = ["Sphinx", "furo"]
@@ -385,9 +856,12 @@ test = ["objgraph", "psutil"]
 name = "identify"
 version = "2.5.33"
 description = "File identification library for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "identify-2.5.33-py2.py3-none-any.whl", hash = "sha256:d40ce5fcd762817627670da8a7d8d8e65f24342d14539c59488dc603bf662e34"},
+    {file = "identify-2.5.33.tar.gz", hash = "sha256:161558f9fe4559e1557e1bff323e8631f6a0e4837f7497767c1782832f16b62d"},
+]
 
 [package.extras]
 license = ["ukkonen"]
@@ -396,25 +870,34 @@ license = ["ukkonen"]
 name = "idna"
 version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
-category = "dev"
 optional = false
 python-versions = ">=3.5"
+files = [
+    {file = "idna-3.6-py3-none-any.whl", hash = "sha256:c05567e9c24a6b9faaa835c4821bad0590fbb9d5779e7caa6e1cc4978e7eb24f"},
+    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
+]
 
 [[package]]
 name = "imagesize"
 version = "1.4.1"
 description = "Getting image size from png/jpeg/jpeg2000/gif file"
-category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b"},
+    {file = "imagesize-1.4.1.tar.gz", hash = "sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a"},
+]
 
 [[package]]
 name = "importlib-metadata"
 version = "7.0.1"
 description = "Read metadata from Python packages"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "importlib_metadata-7.0.1-py3-none-any.whl", hash = "sha256:4805911c3a4ec7c3966410053e9ec6a1fecd629117df5adee56dfc9432a1081e"},
+    {file = "importlib_metadata-7.0.1.tar.gz", hash = "sha256:f238736bb06590ae52ac1fab06a3a9ef1d8dce2b7a35b5ab329371d6c8f5d2cc"},
+]
 
 [package.dependencies]
 zipp = ">=0.5"
@@ -428,9 +911,12 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs
 name = "importlib-resources"
 version = "6.1.1"
 description = "Read resources from Python packages"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "importlib_resources-6.1.1-py3-none-any.whl", hash = "sha256:e8bf90d8213b486f428c9c39714b920041cb02c184686a3dee24905aaa8105d6"},
+    {file = "importlib_resources-6.1.1.tar.gz", hash = "sha256:3893a00122eafde6894c59914446a512f728a0c1a45f9bb9b63721b6bacf0b4a"},
+]
 
 [package.dependencies]
 zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
@@ -443,17 +929,23 @@ testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)",
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
+    {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
+]
 
 [[package]]
 name = "ipykernel"
-version = "6.28.0"
+version = "6.29.1"
 description = "IPython Kernel for Jupyter"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "ipykernel-6.29.1-py3-none-any.whl", hash = "sha256:e5dfba210fc9da74a5dae8fa6c41f816e11bd18d10381b2517d9a0d57cc987c4"},
+    {file = "ipykernel-6.29.1.tar.gz", hash = "sha256:1547352b32da95a2761011a8dac2af930c26a0703dfa07690d16b7d74dac0ba1"},
+]
 
 [package.dependencies]
 appnope = {version = "*", markers = "platform_system == \"Darwin\""}
@@ -461,7 +953,7 @@ comm = ">=0.1.1"
 debugpy = ">=1.6.5"
 ipython = ">=7.23.1"
 jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 matplotlib-inline = ">=0.1"
 nest-asyncio = "*"
 packaging = "*"
@@ -475,15 +967,18 @@ cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
 pyqt5 = ["pyqt5"]
 pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (==0.23.4)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "ipython"
 version = "8.18.1"
 description = "IPython: Productive Interactive Computing"
-category = "dev"
 optional = false
 python-versions = ">=3.9"
+files = [
+    {file = "ipython-8.18.1-py3-none-any.whl", hash = "sha256:e8267419d72d81955ec1177f8a29aaa90ac80ad647499201119e2f05e99aa397"},
+    {file = "ipython-8.18.1.tar.gz", hash = "sha256:ca6f079bb33457c66e233e4580ebfc4128855b4cf6370dddd73842a9563e8a27"},
+]
 
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
@@ -515,9 +1010,12 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pa
 name = "isort"
 version = "5.13.2"
 description = "A Python utility / library to sort Python imports."
-category = "dev"
 optional = false
 python-versions = ">=3.8.0"
+files = [
+    {file = "isort-5.13.2-py3-none-any.whl", hash = "sha256:8ca5e72a8d85860d5a3fa69b8745237f2939afe12dbf656afbcb47fe72d947a6"},
+    {file = "isort-5.13.2.tar.gz", hash = "sha256:48fdfcb9face5d58a4f6dde2e72a1fb8dcaf8ab26f95ab49fab84c2ddefb0109"},
+]
 
 [package.extras]
 colors = ["colorama (>=0.4.6)"]
@@ -526,9 +1024,12 @@ colors = ["colorama (>=0.4.6)"]
 name = "jedi"
 version = "0.19.1"
 description = "An autocompletion tool for Python that can be used for text editors."
-category = "dev"
 optional = false
 python-versions = ">=3.6"
+files = [
+    {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"},
+    {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"},
+]
 
 [package.dependencies]
 parso = ">=0.8.3,<0.9.0"
@@ -540,11 +1041,14 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.2"
+version = "3.1.3"
 description = "A very fast and expressive template engine."
-category = "dev"
 optional = false
 python-versions = ">=3.7"
+files = [
+    {file = "Jinja2-3.1.3-py3-none-any.whl", hash = "sha256:7d6d50dd97d52cbc355597bd845fabfbac3f551e1f99619e39a35ce8c370b5fa"},
+    {file = "Jinja2-3.1.3.tar.gz", hash = "sha256:ac8bd6544d4bb2c9792bf3a159e80bba8fda7f07e81bc3aed565432d5925ba90"},
+]
 
 [package.dependencies]
 MarkupSafe = ">=2.0"
@@ -554,11 +1058,14 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "jsonschema"
-version = "4.20.0"
+version = "4.21.1"
 description = "An implementation of JSON Schema validation for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jsonschema-4.21.1-py3-none-any.whl", hash = "sha256:7996507afae316306f9e2290407761157c6f78002dcf7419acb99822143d1c6f"},
+    {file = "jsonschema-4.21.1.tar.gz", hash = "sha256:85727c00279f5fa6bedbe6238d2aa6403bedd8b4864ab11207d07df3cc1b2ee5"},
+]
 
 [package.dependencies]
 attrs = ">=22.2.0"
@@ -574,9 +1081,12 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 name = "jsonschema-specifications"
 version = "2023.12.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jsonschema_specifications-2023.12.1-py3-none-any.whl", hash = "sha256:87e4fdf3a94858b8a2ba2778d9ba57d8a9cafca7c7489c46ba0d30a8bc6a9c3c"},
+    {file = "jsonschema_specifications-2023.12.1.tar.gz", hash = "sha256:48a76787b3e70f5ed53f1160d2b81f586e4ca6d1548c5de7085d1682674764cc"},
+]
 
 [package.dependencies]
 referencing = ">=0.31.0"
@@ -585,9 +1095,12 @@ referencing = ">=0.31.0"
 name = "jupyter-cache"
 version = "1.0.0"
 description = "A defined interface for working with a cache of jupyter notebooks."
-category = "dev"
 optional = false
 python-versions = ">=3.9"
+files = [
+    {file = "jupyter_cache-1.0.0-py3-none-any.whl", hash = "sha256:594b1c4e29b488b36547e12477645f489dbdc62cc939b2408df5679f79245078"},
+    {file = "jupyter_cache-1.0.0.tar.gz", hash = "sha256:d0fa7d7533cd5798198d8889318269a8c1382ed3b22f622c09a9356521f48687"},
+]
 
 [package.dependencies]
 attrs = "*"
@@ -609,13 +1122,16 @@ testing = ["coverage", "ipykernel", "jupytext", "matplotlib", "nbdime", "nbforma
 name = "jupyter-client"
 version = "8.6.0"
 description = "Jupyter protocol implementation and client libraries"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jupyter_client-8.6.0-py3-none-any.whl", hash = "sha256:909c474dbe62582ae62b758bca86d6518c85234bdee2d908c778db6d72f39d99"},
+    {file = "jupyter_client-8.6.0.tar.gz", hash = "sha256:0642244bb83b4764ae60d07e010e15f0e2d275ec4e918a8f7b80fbbef3ca60c7"},
+]
 
 [package.dependencies]
 importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
-jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 python-dateutil = ">=2.8.2"
 pyzmq = ">=23.0"
 tornado = ">=6.2"
@@ -627,11 +1143,14 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 
 [[package]]
 name = "jupyter-core"
-version = "5.7.0"
+version = "5.7.1"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
-category = "dev"
 optional = false
 python-versions = ">=3.8"
+files = [
+    {file = "jupyter_core-5.7.1-py3-none-any.whl", hash = "sha256:c65c82126453a723a2804aa52409930434598fd9d35091d63dfb919d2b765bb7"},
+    {file = "jupyter_core-5.7.1.tar.gz", hash = "sha256:de61a9d7fc71240f688b2fb5ab659fbb56979458dc66a71decd098e03c79e218"},
+]
 
 [package.dependencies]
 platformdirs = ">=2.5"
@@ -646,1692 +1165,9 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
 name = "kiwisolver"
 version = "1.4.5"
 description = "A fast implementation of the Cassowary constraint solver"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "latexcodec"
-version = "2.0.1"
-description = "A lexer and codec to work with LaTeX code in Python."
-category = "dev"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-
-[package.dependencies]
-six = ">=1.4.1"
-
-[[package]]
-name = "markdown-it-py"
-version = "3.0.0"
-description = "Python port of markdown-it. Markdown parsing, done right!"
-category = "dev"
-optional = false
-python-versions = ">=3.8"
-
-[package.dependencies]
-mdurl = ">=0.1,<1.0"
-
-[package.extras]
-benchmarking = ["psutil", "pytest", "pytest-benchmark"]
-code-style = ["pre-commit (>=3.0,<4.0)"]
-compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "mistletoe (>=1.0,<2.0)", "mistune (>=2.0,<3.0)", "panflute (>=2.3,<3.0)"]
-linkify = ["linkify-it-py (>=1,<3)"]
-plugins = ["mdit-py-plugins"]
-profiling = ["gprof2dot"]
-rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"]
-testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
-
-[[package]]
-name = "markupsafe"
-version = "2.1.3"
-description = "Safely add untrusted strings to HTML/XML markup."
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-
-[[package]]
-name = "matplotlib"
-version = "3.8.2"
-description = "Python plotting package"
-category = "dev"
-optional = false
-python-versions = ">=3.9"
-
-[package.dependencies]
-contourpy = ">=1.0.1"
-cycler = ">=0.10"
-fonttools = ">=4.22.0"
-importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
-kiwisolver = ">=1.3.1"
-numpy = ">=1.21,<2"
-packaging = ">=20.0"
-pillow = ">=8"
-pyparsing = ">=2.3.1"
-python-dateutil = ">=2.7"
-
-[[package]]
-name = "matplotlib-inline"
-version = "0.1.6"
-description = "Inline Matplotlib backend for Jupyter"
-category = "dev"
-optional = false
-python-versions = ">=3.5"
-
-[package.dependencies]
-traitlets = "*"
-
-[[package]]
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+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
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diff --git a/pyproject.toml b/pyproject.toml
index 07202830..25213fdc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -47,7 +47,7 @@ flake8 = "^4.0.1"
 flake8-docstrings = "^1.6.0"
 mypy = "^0.991"
 isort = "^5.12.0"
-pandas = ">1.3.0"
+pandas = "^2.2.0"
 matplotlib = "^3.5.2"
 ipython = "^8.9.0"
 
diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
index 5c185ab2..0783daf2 100644
--- a/tests/regression/data/test_synth_data.py
+++ b/tests/regression/data/test_synth_data.py
@@ -1,7 +1,6 @@
 """Test the quality of the synthetic data generated from the model parameters."""
 
 import numpy as np
-import pandas as pd
 import pytest
 import xarray as xr
 
@@ -26,7 +25,7 @@ def syndata(modelpath="pyrealm_build_data/data_model.nc"):
     from pyrealm_build_data.synth_data import reconstruct
 
     model = xr.open_dataset(modelpath)
-    ts = pd.date_range("2012-01-01", "2018-01-01", freq="12h")
+    ts = xr.date_range("2012-01-01", "2018-01-01", freq="12h")
     return reconstruct(model, ts)
 
 

From 07a79d91b152acf963df99242a74264b2270884f Mon Sep 17 00:00:00 2001
From: TZCai <13818704679@163.com>
Date: Wed, 7 Feb 2024 11:43:05 +0000
Subject: [PATCH 08/15] add constraint to optimization

---
 pyrealm_build_data/synth_data.py | 28 ++++++++++++++--------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index 5cf77361..bcff4d1a 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -17,7 +17,7 @@ def make_time_features(t: np.ndarray) -> pd.DataFrame:
 
     df["linear"] = (dt - pd.Timestamp("2000-01-01")) / pd.Timedelta("365.25d")
 
-    for f in [365.25, 12, 6, 4, 3, 2, 1, 1 / 2, 1 / 3, 1 / 4, 1 / 6]:
+    for f in [730.5, 365.25, 12, 6, 4, 3, 2, 1, 1 / 2, 1 / 3, 1 / 4, 1 / 6]:
         df[f"freq_{f:.2f}_sin"] = np.sin(2 * np.pi * f * df["linear"])
         df[f"freq_{f:.2f}_cos"] = np.cos(2 * np.pi * f * df["linear"])
 
@@ -27,19 +27,19 @@ def make_time_features(t: np.ndarray) -> pd.DataFrame:
 def fit_ts_model(df: pd.DataFrame, fs: pd.DataFrame) -> Tuple[pd.DataFrame, pd.Series]:
     """Fit a time series model to the data."""
     from tqdm import tqdm
-
-    df = df.dropna(axis=1, how="all")
-    params = pd.DataFrame(index=df.columns, columns=fs.columns)
-    losses = []
-    for k in tqdm(df.columns):
-        y = df[k].dropna()
-        X = fs.loc[y.index]
-        c, r, *_ = np.linalg.lstsq(X, y, rcond=None)
-        # TODO: optimize with constraints, e.g. ppfd >= 0
-        losses.extend(r / np.sum(y**2))
-        params.loc[k] = c
-
-    return params, pd.Series(losses, index=df.columns)
+    from scipy.optimize import minimize, LinearConstraint
+
+    df = df.dropna(axis=1, how="all")  # drop locations with all NaNs
+    df = df.interpolate(method="time")  # fill NaNs with linear interpolation
+    T, M, D = df.shape[0], df.shape[1], fs.shape[1]  # times, locs, feats
+    X = fs.values  # (T, D)
+    Y = df.values  # (T, M)
+    cons = LinearConstraint(X, Y.min(axis=0), Y.max(axis=0))
+    res = minimize(lambda a: np.sum((X @ a.reshape(D, M) - Y)**2), np.zeros(M * D), constraints=cons)
+    if res.success:
+        pars = pd.DataFrame(res.x.reshape(D, M), index=df.columns, columns=fs.columns)
+        losses = np.mean((X @ pars.values - Y) ** 2, axis=0) / np.var(Y, axis=0)
+        return pars, pd.Series(losses, index=df.columns)
 
 
 def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset:

From 7c6acccd3cab5e080d209012268de3c9dc00c8f8 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Wed, 7 Feb 2024 15:02:06 +0000
Subject: [PATCH 09/15] simplify optimization method

---
 pyrealm_build_data/data_model.nc | Bin 294738 -> 318390 bytes
 pyrealm_build_data/synth_data.py |  28 ++++++++++------------------
 2 files changed, 10 insertions(+), 18 deletions(-)

diff --git a/pyrealm_build_data/data_model.nc b/pyrealm_build_data/data_model.nc
index fc628a0bd7ad12b779ccf1a35eb908391cfb7567..424ce1d3b637ba3a7bcbe4a33e59f8cfb855e306 100644
GIT binary patch
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diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index bcff4d1a..700395bb 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -24,22 +24,15 @@ def make_time_features(t: np.ndarray) -> pd.DataFrame:
     return df
 
 
-def fit_ts_model(df: pd.DataFrame, fs: pd.DataFrame) -> Tuple[pd.DataFrame, pd.Series]:
+def fit_ts_model(df: pd.DataFrame, fs: pd.DataFrame) -> Tuple[pd.DataFrame, float]:
     """Fit a time series model to the data."""
-    from tqdm import tqdm
-    from scipy.optimize import minimize, LinearConstraint
-
-    df = df.dropna(axis=1, how="all")  # drop locations with all NaNs
-    df = df.interpolate(method="time")  # fill NaNs with linear interpolation
-    T, M, D = df.shape[0], df.shape[1], fs.shape[1]  # times, locs, feats
-    X = fs.values  # (T, D)
-    Y = df.values  # (T, M)
-    cons = LinearConstraint(X, Y.min(axis=0), Y.max(axis=0))
-    res = minimize(lambda a: np.sum((X @ a.reshape(D, M) - Y)**2), np.zeros(M * D), constraints=cons)
-    if res.success:
-        pars = pd.DataFrame(res.x.reshape(D, M), index=df.columns, columns=fs.columns)
-        losses = np.mean((X @ pars.values - Y) ** 2, axis=0) / np.var(Y, axis=0)
-        return pars, pd.Series(losses, index=df.columns)
+    df = df.dropna(axis=1, how="all").fillna(df.mean())
+    Y = df.values  # (times, locs)
+    X = fs.values  # (times, feats)
+    A = np.linalg.pinv(X) @ Y  # (feats, locs)
+    loss = np.mean((X @ A - Y) ** 2) / np.var(Y)
+    pars = pd.DataFrame(A.T, index=df.columns, columns=fs.columns)
+    return pars, loss
 
 
 def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset:
@@ -68,10 +61,9 @@ def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset
         df = da.to_series().unstack("time").T  # (datetimes, locations)
         fs = features.loc[df.index]  # (datetimes, features)
         fs = fs[special_time_features.get(k, fs.columns)]
-        ps, ls = fit_ts_model(df, fs)  # (locations, features)
-        print("Loss:", ls.mean())
+        ps, r = fit_ts_model(df, fs)  # (locations, features)
+        print("Loss:", r)
         ps[features.keys().difference(ps.columns)] = 0.0
         model[k] = ps.to_xarray().to_dataarray()
 
-    # model["features"] = features.to_xarray().to_dataarray()
     model.to_netcdf("pyrealm_build_data/data_model.nc")

From b6921f792ba9caad50f648f93598a98b56c45d3c Mon Sep 17 00:00:00 2001
From: TZCai <13818704679@163.com>
Date: Wed, 7 Feb 2024 17:12:53 +0000
Subject: [PATCH 10/15] update doc of synth_data and refactor

---
 pyrealm_build_data/synth_data.py         |  5 +++--
 tests/regression/data/test_synth_data.py | 10 ++--------
 2 files changed, 5 insertions(+), 10 deletions(-)

diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index 700395bb..aa1ee56c 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -1,7 +1,8 @@
 """This script uses a parametrized model to compress the input dataset.
 
-It fits a time series model to the input data and stores the model parameters,
-which can be later used to reconstruct the original dataset.
+It fits a time series model to the input data and stores the model parameters.
+The dataset can then be reconstructed from the model parameters using the `reconstruct` function,
+provided with a custom time index.
 """
 from typing import Tuple
 
diff --git a/tests/regression/data/test_synth_data.py b/tests/regression/data/test_synth_data.py
index 0783daf2..6e582689 100644
--- a/tests/regression/data/test_synth_data.py
+++ b/tests/regression/data/test_synth_data.py
@@ -6,11 +6,10 @@
 
 try:
     DATASET = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
+    VARS = DATASET.data_vars
 except ValueError:
     pytest.skip("Original LFS dataset not checked out.", allow_module_level=True)
 
-VARS = DATASET.data_vars
-
 
 def r2_score(y_true: xr.DataArray, y_pred: xr.DataArray) -> float:
     """Compute the R2 score."""
@@ -44,9 +43,4 @@ def test_synth_data_quality(dataset, syndata, var):
     p = syndata[var].sel(lat=lats, time=times)
     s = r2_score(t, p)
     print(f"R2 score for {var} is {s:.2f}")
-    if s < 0.8:
-        # import matplotlib.pyplot as plt
-        # t.sortby("time").mean(["lat", "lon"]).plot()
-        # p.sortby("time").mean(["lat", "lon"]).plot()
-        # plt.show()
-        raise AssertionError
+    assert s > 0.85

From 165a7734ae407311e113df3b0253f403b77cf11a Mon Sep 17 00:00:00 2001
From: TZCai <13818704679@163.com>
Date: Mon, 19 Feb 2024 18:19:36 +0000
Subject: [PATCH 11/15] fix flake8 issue E501

---
 pyrealm_build_data/synth_data.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index aa1ee56c..d70e428c 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -1,8 +1,8 @@
 """This script uses a parametrized model to compress the input dataset.
 
 It fits a time series model to the input data and stores the model parameters.
-The dataset can then be reconstructed from the model parameters using the `reconstruct` function,
-provided with a custom time index.
+The dataset can then be reconstructed from the model parameters using the `reconstruct`
+function, provided with a custom time index.
 """
 from typing import Tuple
 

From 3aa2b7d347162e78794863ee4ce1e4b47bca2175 Mon Sep 17 00:00:00 2001
From: TZCai <13818704679@163.com>
Date: Mon, 19 Feb 2024 18:36:28 +0000
Subject: [PATCH 12/15] add value bounds to the reconstructed data

---
 pyrealm_build_data/synth_data.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index d70e428c..44b85c72 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -10,6 +10,15 @@
 import pandas as pd
 import xarray as xr
 
+VAR_BOUNDS = dict(
+    temp=(-25, 80),
+    patm=(3e4, 11e4),
+    vpd=(0, 1e4),
+    co2=(0, 1e3),
+    fapar=(0, 1),
+    ppfd=(0, 1e4),
+)
+
 
 def make_time_features(t: np.ndarray) -> pd.DataFrame:
     """Make time features for a given time index."""
@@ -39,7 +48,9 @@ def fit_ts_model(df: pd.DataFrame, fs: pd.DataFrame) -> Tuple[pd.DataFrame, floa
 def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset:
     """Reconstruct the full dataset from the model parameters."""
     x = make_time_features(dt).to_xarray().to_dataarray()
-    return xr.Dataset({k: a @ x for k, a in ds.items() if k != "features"})
+    ds = xr.Dataset({k: a @ x for k, a in ds.items()})
+    ds = xr.Dataset({k: a.clip(*VAR_BOUNDS[k]) for k, a in ds.items()})
+    return ds
 
 
 if __name__ == "__main__":

From 983aa9fdfcc48b9ee286f7724a135a782ce18578 Mon Sep 17 00:00:00 2001
From: TZCai <13818704679@163.com>
Date: Wed, 21 Feb 2024 18:35:15 +0000
Subject: [PATCH 13/15] refactor synth_data and extend docstring

---
 pyrealm_build_data/data_model.nc | Bin 318390 -> 316369 bytes
 pyrealm_build_data/synth_data.py |  91 ++++++++++++++++++++-----------
 2 files changed, 58 insertions(+), 33 deletions(-)

diff --git a/pyrealm_build_data/data_model.nc b/pyrealm_build_data/data_model.nc
index 424ce1d3b637ba3a7bcbe4a33e59f8cfb855e306..27e46de6612ad901763c70ac04791bccf6d69ecc 100644
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diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index 44b85c72..20620246 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -4,24 +4,23 @@
 The dataset can then be reconstructed from the model parameters using the `reconstruct`
 function, provided with a custom time index.
 """
-from typing import Tuple
-
 import numpy as np
 import pandas as pd
 import xarray as xr
+from numpy.typing import ArrayLike
+
 
-VAR_BOUNDS = dict(
-    temp=(-25, 80),
-    patm=(3e4, 11e4),
-    vpd=(0, 1e4),
-    co2=(0, 1e3),
-    fapar=(0, 1),
-    ppfd=(0, 1e4),
-)
+def make_time_features(t: ArrayLike) -> pd.DataFrame:
+    """Make time features for a given time index.
 
+    The model can be written as
+    g(t) = a₀ + a₁ t + ∑_i b_i sin(2π f_i t) + c_i cos(2π f_i t),
+    where t is the time index, f_i are the frequencies, and a₀, a₁, b_i, c_i are the
+    model parameters.
 
-def make_time_features(t: np.ndarray) -> pd.DataFrame:
-    """Make time features for a given time index."""
+    Args:
+        t: An array of datetime values.
+    """
     dt = pd.to_datetime(t).rename("time")
     df = pd.DataFrame(index=dt).assign(const=1.0)
 
@@ -34,28 +33,60 @@ def make_time_features(t: np.ndarray) -> pd.DataFrame:
     return df
 
 
-def fit_ts_model(df: pd.DataFrame, fs: pd.DataFrame) -> Tuple[pd.DataFrame, float]:
-    """Fit a time series model to the data."""
-    df = df.dropna(axis=1, how="all").fillna(df.mean())
+def fit_ts_model(da: xr.DataArray, fs: pd.DataFrame) -> xr.DataArray:
+    """Fit a time series model to the data.
+
+    Args:
+        da: A DataArray with the input data.
+        fs: A DataFrame with the time features.
+    """
+    print("Fitting", da.name)
+
+    da = da.isel(time=slice(None, None, 4))  # downsample along time
+    da = da.dropna("time", how="all")
+    da = da.fillna(da.mean("time"))
+    df = da.to_series().unstack("time").T
+
     Y = df.values  # (times, locs)
-    X = fs.values  # (times, feats)
-    A = np.linalg.pinv(X) @ Y  # (feats, locs)
-    loss = np.mean((X @ A - Y) ** 2) / np.var(Y)
-    pars = pd.DataFrame(A.T, index=df.columns, columns=fs.columns)
-    return pars, loss
+    X = fs.loc[df.index].values  # (times, feats)
+    A, res, *_ = np.linalg.lstsq(X, Y, rcond=None)  # (feats, locs)
 
+    loss = np.mean(res) / len(X) / np.var(Y)
+    pars = pd.DataFrame(A.T, index=df.columns, columns=fs.columns)
 
-def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset:
-    """Reconstruct the full dataset from the model parameters."""
+    print("Loss:", loss)
+    return pars.to_xarray().to_dataarray()
+
+
+def reconstruct(
+    ds: xr.Dataset, dt: ArrayLike, bounds: dict | None = None
+) -> xr.Dataset:
+    """Reconstruct the full dataset from the model parameters.
+
+    Args:
+        ds: A Dataset with the model parameters.
+        dt: An array of datetime values.
+        bounds: A dictionary with the bounds for the reconstructed variables.
+    """
+    if bounds is None:
+        bounds = dict(
+            temp=(-25, 80),
+            patm=(3e4, 11e4),
+            vpd=(0, 1e4),
+            co2=(0, 1e3),
+            fapar=(0, 1),
+            ppfd=(0, 1e4),
+        )
     x = make_time_features(dt).to_xarray().to_dataarray()
     ds = xr.Dataset({k: a @ x for k, a in ds.items()})
-    ds = xr.Dataset({k: a.clip(*VAR_BOUNDS[k]) for k, a in ds.items()})
+    ds = xr.Dataset({k: a.clip(*bounds[k]) for k, a in ds.items()})
     return ds
 
 
 if __name__ == "__main__":
     ds = xr.open_dataset("pyrealm_build_data/inputs_data_24.25.nc")
 
+    # drop locations with all NaNs (for any variable)
     mask = ~ds.isnull().all("time").to_dataarray().any("variable")
     ds = ds.where(mask, drop=True)
 
@@ -65,17 +96,11 @@ def reconstruct(ds: xr.Dataset, dt: np.ndarray | pd.DatetimeIndex) -> xr.Dataset
     )
 
     features = make_time_features(ds.time)
-    model = xr.Dataset()
 
+    model = xr.Dataset()
     for k in ds.data_vars:
-        print("Fitting", k)
-        da = ds[k].isel(time=slice(None, None, 4))  # downsample along time
-        df = da.to_series().unstack("time").T  # (datetimes, locations)
-        fs = features.loc[df.index]  # (datetimes, features)
-        fs = fs[special_time_features.get(k, fs.columns)]
-        ps, r = fit_ts_model(df, fs)  # (locations, features)
-        print("Loss:", r)
-        ps[features.keys().difference(ps.columns)] = 0.0
-        model[k] = ps.to_xarray().to_dataarray()
+        cols = special_time_features.get(k, features.columns)
+        model[k] = fit_ts_model(ds[k], features[cols])
 
+    model = model.fillna(0.0)
     model.to_netcdf("pyrealm_build_data/data_model.nc")

From 7ca9c1ca37ffb96ffa777864c6b4840d1a6fa719 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Thu, 28 Mar 2024 09:36:27 +0000
Subject: [PATCH 14/15] fix mypy issue

---
 pyrealm_build_data/synth_data.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/pyrealm_build_data/synth_data.py b/pyrealm_build_data/synth_data.py
index 20620246..4aff6334 100644
--- a/pyrealm_build_data/synth_data.py
+++ b/pyrealm_build_data/synth_data.py
@@ -4,13 +4,14 @@
 The dataset can then be reconstructed from the model parameters using the `reconstruct`
 function, provided with a custom time index.
 """
+from typing import Sequence
+
 import numpy as np
 import pandas as pd
 import xarray as xr
-from numpy.typing import ArrayLike
 
 
-def make_time_features(t: ArrayLike) -> pd.DataFrame:
+def make_time_features(t: Sequence[float]) -> pd.DataFrame:
     """Make time features for a given time index.
 
     The model can be written as
@@ -59,7 +60,7 @@ def fit_ts_model(da: xr.DataArray, fs: pd.DataFrame) -> xr.DataArray:
 
 
 def reconstruct(
-    ds: xr.Dataset, dt: ArrayLike, bounds: dict | None = None
+    ds: xr.Dataset, dt: Sequence[float], bounds: dict | None = None
 ) -> xr.Dataset:
     """Reconstruct the full dataset from the model parameters.
 

From 48e4418fba533d0f0b2f06e12f44b65abfc35f87 Mon Sep 17 00:00:00 2001
From: tztsai <1213815284@qq.com>
Date: Thu, 28 Mar 2024 09:46:08 +0000
Subject: [PATCH 15/15] update poetry lock

---
 poetry.lock | 1363 +++++----------------------------------------------
 1 file changed, 125 insertions(+), 1238 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index e2405c0c..a0f572a7 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,3 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
-
 [[package]]
 name = "alabaster"
 version = "0.7.16"
@@ -12,6 +10,7 @@ python-versions = ">=3.9"
 name = "appnope"
 version = "0.1.4"
 description = "Disable App Nap on macOS >= 10.9"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 
@@ -19,12 +18,9 @@ python-versions = ">=3.6"
 name = "asttokens"
 version = "2.4.1"
 description = "Annotate AST trees with source code positions"
+category = "dev"
 optional = false
 python-versions = "*"
-files = [
-    {file = "asttokens-2.4.1-py2.py3-none-any.whl", hash = "sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24"},
-    {file = "asttokens-2.4.1.tar.gz", hash = "sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0"},
-]
 
 [package.dependencies]
 six = ">=1.12.0"
@@ -37,12 +33,9 @@ test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 name = "attrs"
 version = "23.2.0"
 description = "Classes Without Boilerplate"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
-files = [
-    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
-    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
-]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
@@ -56,12 +49,9 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
 name = "autodocsumm"
 version = "0.2.12"
 description = "Extended sphinx autodoc including automatic autosummaries"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
-files = [
-    {file = "autodocsumm-0.2.12-py3-none-any.whl", hash = "sha256:b842b53c686c07a4f174721ca4e729b027367703dbf42e2508863a3c6d6c049c"},
-    {file = "autodocsumm-0.2.12.tar.gz", hash = "sha256:848fe8c38df433c6635489499b969cb47cc389ed3d7b6e75c8ccbc94d4b3bf9e"},
-]
 
 [package.dependencies]
 Sphinx = ">=2.2,<8.0"
@@ -70,12 +60,9 @@ Sphinx = ">=2.2,<8.0"
 name = "babel"
 version = "2.14.0"
 description = "Internationalization utilities"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
-files = [
-    {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
-    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
-]
 
 [package.extras]
 dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
@@ -84,22 +71,9 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 name = "black"
 version = "22.12.0"
 description = "The uncompromising code formatter."
+category = "dev"
 optional = false
 python-versions = ">=3.7"
-files = [
-    {file = "black-22.12.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9eedd20838bd5d75b80c9f5487dbcb06836a43833a37846cf1d8c1cc01cef59d"},
-    {file = "black-22.12.0-cp310-cp310-win_amd64.whl", hash = "sha256:159a46a4947f73387b4d83e87ea006dbb2337eab6c879620a3ba52699b1f4351"},
-    {file = "black-22.12.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d30b212bffeb1e252b31dd269dfae69dd17e06d92b87ad26e23890f3efea366f"},
-    {file = "black-22.12.0-cp311-cp311-win_amd64.whl", hash = "sha256:7412e75863aa5c5411886804678b7d083c7c28421210180d67dfd8cf1221e1f4"},
-    {file = "black-22.12.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c116eed0efb9ff870ded8b62fe9f28dd61ef6e9ddd28d83d7d264a38417dcee2"},
-    {file = "black-22.12.0-cp37-cp37m-win_amd64.whl", hash = "sha256:1f58cbe16dfe8c12b7434e50ff889fa479072096d79f0a7f25e4ab8e94cd8350"},
-    {file = "black-22.12.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:77d86c9f3db9b1bf6761244bc0b3572a546f5fe37917a044e02f3166d5aafa7d"},
-    {file = "black-22.12.0-cp38-cp38-win_amd64.whl", hash = "sha256:82d9fe8fee3401e02e79767016b4907820a7dc28d70d137eb397b92ef3cc5bfc"},
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 click = ">=8.0.0"
@@ -119,73 +93,17 @@ uvloop = ["uvloop (>=0.15.2)"]
 name = "certifi"
 version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
+category = "dev"
 optional = false
 python-versions = ">=3.6"
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 version = "1.16.0"
 description = "Foreign Function Interface for Python calling C code."
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 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
 pycparser = "*"
@@ -194,42 +112,17 @@ pycparser = "*"
 name = "cfgv"
 version = "3.4.0"
 description = "Validate configuration and produce human readable error messages."
+category = "dev"
 optional = false
 python-versions = ">=3.8"
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 [[package]]
 name = "cftime"
 version = "1.6.3"
 description = "Time-handling functionality from netcdf4-python"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
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 numpy = {version = ">1.13.3", markers = "python_version < \"3.12.0.rc1\""}
@@ -238,111 +131,17 @@ numpy = {version = ">1.13.3", markers = "python_version < \"3.12.0.rc1\""}
 name = "charset-normalizer"
 version = "3.3.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "dev"
 optional = false
 python-versions = ">=3.7.0"
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 [[package]]
 name = "click"
 version = "8.1.7"
 description = "Composable command line interface toolkit"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
-files = [
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 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
@@ -351,23 +150,17 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
+category = "dev"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
-files = [
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-]
 
 [[package]]
 name = "comm"
 version = "0.2.2"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+category = "dev"
 optional = false
 python-versions = ">=3.8"
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 tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.11.0a6\" and extra == \"toml\""}
@@ -509,12 +204,9 @@ toml = ["tomli"]
 name = "cycler"
 version = "0.12.1"
 description = "Composable style cycles"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
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 [package.extras]
 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
@@ -524,11 +216,9 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 name = "dacite"
 version = "1.8.1"
 description = "Simple creation of data classes from dictionaries."
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 optional = false
 python-versions = ">=3.6"
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 dev = ["black", "coveralls", "mypy", "pre-commit", "pylint", "pytest (>=5)", "pytest-benchmark", "pytest-cov"]
@@ -537,39 +227,17 @@ dev = ["black", "coveralls", "mypy", "pre-commit", "pylint", "pytest (>=5)", "py
 name = "debugpy"
 version = "1.8.1"
 description = "An implementation of the Debug Adapter Protocol for Python"
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 optional = false
 python-versions = ">=3.8"
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 [[package]]
 name = "decorator"
 version = "5.1.1"
 description = "Decorators for Humans"
+category = "dev"
 optional = false
 python-versions = ">=3.5"
-files = [
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 [[package]]
 name = "dill"
@@ -587,34 +255,25 @@ profile = ["gprof2dot (>=2022.7.29)"]
 name = "distlib"
 version = "0.3.8"
 description = "Distribution utilities"
+category = "dev"
 optional = false
 python-versions = "*"
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 [[package]]
 name = "docutils"
 version = "0.20.1"
 description = "Docutils -- Python Documentation Utilities"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
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 [[package]]
 name = "exceptiongroup"
 version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
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 [package.extras]
 test = ["pytest (>=6)"]
@@ -623,12 +282,9 @@ test = ["pytest (>=6)"]
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 version = "2.0.1"
 description = "Get the currently executing AST node of a frame, and other information"
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-python-versions = ">=3.5"
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+category = "dev"
+optional = false
+python-versions = ">=3.5"
 
 [package.extras]
 tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
@@ -637,12 +293,9 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 name = "fastjsonschema"
 version = "2.19.1"
 description = "Fastest Python implementation of JSON schema"
+category = "dev"
 optional = false
 python-versions = "*"
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 [package.extras]
 devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
@@ -651,12 +304,9 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 name = "filelock"
 version = "3.13.3"
 description = "A platform independent file lock."
+category = "dev"
 optional = false
 python-versions = ">=3.8"
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 docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
@@ -667,12 +317,9 @@ typing = ["typing-extensions (>=4.8)"]
 name = "flake8"
 version = "4.0.1"
 description = "the modular source code checker: pep8 pyflakes and co"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
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 mccabe = ">=0.6.0,<0.7.0"
@@ -683,12 +330,9 @@ pyflakes = ">=2.4.0,<2.5.0"
 name = "flake8-docstrings"
 version = "1.7.0"
 description = "Extension for flake8 which uses pydocstyle to check docstrings"
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 python-versions = ">=3.7"
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 [package.dependencies]
 flake8 = ">=3"
@@ -698,52 +342,9 @@ pydocstyle = ">=2.1"
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 version = "4.50.0"
 description = "Tools to manipulate font files"
+category = "dev"
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 version = "0.20.3"
 description = "Simple Python interface for Graphviz"
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 optional = false
 python-versions = ">=3.8"
 
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 [package.extras]
 docs = ["Sphinx", "furo"]
@@ -857,12 +397,9 @@ test = ["objgraph", "psutil"]
 name = "identify"
 version = "2.5.35"
 description = "File identification library for Python"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
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 [package.extras]
 license = ["ukkonen"]
@@ -871,34 +408,25 @@ license = ["ukkonen"]
 name = "idna"
 version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
+category = "dev"
 optional = false
 python-versions = ">=3.5"
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 [[package]]
 name = "imagesize"
 version = "1.4.1"
 description = "Getting image size from png/jpeg/jpeg2000/gif file"
+category = "dev"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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 [[package]]
 name = "importlib-metadata"
 version = "7.1.0"
 description = "Read metadata from Python packages"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
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 [package.dependencies]
 zipp = ">=0.5"
@@ -912,12 +440,9 @@ testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)",
 name = "importlib-resources"
 version = "6.4.0"
 description = "Read resources from Python packages"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
 zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
@@ -930,23 +455,17 @@ testing = ["jaraco.test (>=5.4)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "p
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 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
+category = "dev"
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 python-versions = ">=3.7"
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 name = "ipykernel"
 version = "6.29.3"
 description = "IPython Kernel for Jupyter"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
-    {file = "ipykernel-6.29.1-py3-none-any.whl", hash = "sha256:e5dfba210fc9da74a5dae8fa6c41f816e11bd18d10381b2517d9a0d57cc987c4"},
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-]
 
 [package.dependencies]
 appnope = {version = "*", markers = "platform_system == \"Darwin\""}
@@ -954,7 +473,7 @@ comm = ">=0.1.1"
 debugpy = ">=1.6.5"
 ipython = ">=7.23.1"
 jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
 matplotlib-inline = ">=0.1"
 nest-asyncio = "*"
 packaging = "*"
@@ -974,12 +493,9 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 name = "ipython"
 version = "8.18.1"
 description = "IPython: Productive Interactive Computing"
+category = "dev"
 optional = false
 python-versions = ">=3.9"
-files = [
-    {file = "ipython-8.18.1-py3-none-any.whl", hash = "sha256:e8267419d72d81955ec1177f8a29aaa90ac80ad647499201119e2f05e99aa397"},
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-]
 
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
@@ -1011,12 +527,9 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pa
 name = "isort"
 version = "5.13.2"
 description = "A Python utility / library to sort Python imports."
+category = "dev"
 optional = false
 python-versions = ">=3.8.0"
-files = [
-    {file = "isort-5.13.2-py3-none-any.whl", hash = "sha256:8ca5e72a8d85860d5a3fa69b8745237f2939afe12dbf656afbcb47fe72d947a6"},
-    {file = "isort-5.13.2.tar.gz", hash = "sha256:48fdfcb9face5d58a4f6dde2e72a1fb8dcaf8ab26f95ab49fab84c2ddefb0109"},
-]
 
 [package.extras]
 colors = ["colorama (>=0.4.6)"]
@@ -1025,12 +538,9 @@ colors = ["colorama (>=0.4.6)"]
 name = "jedi"
 version = "0.19.1"
 description = "An autocompletion tool for Python that can be used for text editors."
+category = "dev"
 optional = false
 python-versions = ">=3.6"
-files = [
-    {file = "jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0"},
-    {file = "jedi-0.19.1.tar.gz", hash = "sha256:cf0496f3651bc65d7174ac1b7d043eff454892c708a87d1b683e57b569927ffd"},
-]
 
 [package.dependencies]
 parso = ">=0.8.3,<0.9.0"
@@ -1044,12 +554,9 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 name = "jinja2"
 version = "3.1.3"
 description = "A very fast and expressive template engine."
+category = "dev"
 optional = false
 python-versions = ">=3.7"
-files = [
-    {file = "Jinja2-3.1.3-py3-none-any.whl", hash = "sha256:7d6d50dd97d52cbc355597bd845fabfbac3f551e1f99619e39a35ce8c370b5fa"},
-    {file = "Jinja2-3.1.3.tar.gz", hash = "sha256:ac8bd6544d4bb2c9792bf3a159e80bba8fda7f07e81bc3aed565432d5925ba90"},
-]
 
 [package.dependencies]
 MarkupSafe = ">=2.0"
@@ -1061,12 +568,9 @@ i18n = ["Babel (>=2.7)"]
 name = "jsonschema"
 version = "4.21.1"
 description = "An implementation of JSON Schema validation for Python"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
-    {file = "jsonschema-4.21.1-py3-none-any.whl", hash = "sha256:7996507afae316306f9e2290407761157c6f78002dcf7419acb99822143d1c6f"},
-    {file = "jsonschema-4.21.1.tar.gz", hash = "sha256:85727c00279f5fa6bedbe6238d2aa6403bedd8b4864ab11207d07df3cc1b2ee5"},
-]
 
 [package.dependencies]
 attrs = ">=22.2.0"
@@ -1082,12 +586,9 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 name = "jsonschema-specifications"
 version = "2023.12.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
-    {file = "jsonschema_specifications-2023.12.1-py3-none-any.whl", hash = "sha256:87e4fdf3a94858b8a2ba2778d9ba57d8a9cafca7c7489c46ba0d30a8bc6a9c3c"},
-    {file = "jsonschema_specifications-2023.12.1.tar.gz", hash = "sha256:48a76787b3e70f5ed53f1160d2b81f586e4ca6d1548c5de7085d1682674764cc"},
-]
 
 [package.dependencies]
 referencing = ">=0.31.0"
@@ -1096,12 +597,9 @@ referencing = ">=0.31.0"
 name = "jupyter-cache"
 version = "1.0.0"
 description = "A defined interface for working with a cache of jupyter notebooks."
+category = "dev"
 optional = false
 python-versions = ">=3.9"
-files = [
-    {file = "jupyter_cache-1.0.0-py3-none-any.whl", hash = "sha256:594b1c4e29b488b36547e12477645f489dbdc62cc939b2408df5679f79245078"},
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-]
 
 [package.dependencies]
 attrs = "*"
@@ -1123,16 +621,13 @@ testing = ["coverage", "ipykernel", "jupytext", "matplotlib", "nbdime", "nbforma
 name = "jupyter-client"
 version = "8.6.1"
 description = "Jupyter protocol implementation and client libraries"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
-    {file = "jupyter_client-8.6.0-py3-none-any.whl", hash = "sha256:909c474dbe62582ae62b758bca86d6518c85234bdee2d908c778db6d72f39d99"},
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-]
 
 [package.dependencies]
 importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""}
-jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+jupyter-core = ">=4.12,<5.0.0 || >=5.1.0"
 python-dateutil = ">=2.8.2"
 pyzmq = ">=23.0"
 tornado = ">=6.2"
@@ -1146,12 +641,9 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 name = "jupyter-core"
 version = "5.7.2"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
+category = "dev"
 optional = false
 python-versions = ">=3.8"
-files = [
-    {file = "jupyter_core-5.7.1-py3-none-any.whl", hash = "sha256:c65c82126453a723a2804aa52409930434598fd9d35091d63dfb919d2b765bb7"},
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-]
 
 [package.dependencies]
 platformdirs = ">=2.5"
@@ -2989,17 +2481,7 @@ latexcodec = [
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 ]
-
-[package.dependencies]
-six = ">=1.4.1"
-
-[[package]]
-name = "markdown-it-py"
-version = "3.0.0"
-description = "Python port of markdown-it. Markdown parsing, done right!"
-optional = false
-python-versions = ">=3.8"
-files = [
+markdown-it-py = [
     {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"},
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 ]
@@ -3095,81 +2577,37 @@ matplotlib = [
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 ]
-
-[package.dependencies]
-contourpy = ">=1.0.1"
-cycler = ">=0.10"
-fonttools = ">=4.22.0"
-importlib-resources = {version = ">=3.2.0", markers = "python_version < \"3.10\""}
-kiwisolver = ">=1.3.1"
-numpy = ">=1.21,<2"
-packaging = ">=20.0"
-pillow = ">=8"
-pyparsing = ">=2.3.1"
-python-dateutil = ">=2.7"
-
-[[package]]
-name = "matplotlib-inline"
-version = "0.1.6"
-description = "Inline Matplotlib backend for Jupyter"
-optional = false
-python-versions = ">=3.5"
-files = [
+matplotlib-inline = [
     {file = "matplotlib-inline-0.1.6.tar.gz", hash = "sha256:f887e5f10ba98e8d2b150ddcf4702c1e5f8b3a20005eb0f74bfdbd360ee6f304"},
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 ]
-
-[package.dependencies]
-traitlets = "*"
-
-[[package]]
-name = "mccabe"
-version = "0.6.1"
-description = "McCabe checker, plugin for flake8"
-optional = false
-python-versions = "*"
-files = [
+mccabe = [
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-
-[[package]]
-name = "mdit-py-plugins"
-version = "0.4.0"
-description = "Collection of plugins for markdown-it-py"
-optional = false
-python-versions = ">=3.8"
-files = [
+mdit-py-plugins = [
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 ]
-
-[package.dependencies]
-markdown-it-py = ">=1.0.0,<4.0.0"
-
-[package.extras]
-code-style = ["pre-commit"]
-rtd = ["myst-parser", "sphinx-book-theme"]
-testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
-
-[[package]]
-name = "mdurl"
-version = "0.1.2"
-description = "Markdown URL utilities"
-optional = false
-python-versions = ">=3.7"
-files = [
+mdurl = [
     {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
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 ]
-
-[[package]]
-name = "mypy"
-version = "0.991"
-description = "Optional static typing for Python"
-optional = false
-python-versions = ">=3.7"
-files = [
+multiprocess = [
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+    {file = "multiprocess-0.70.16-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:ba8c31889abf4511c7308a8c52bb4a30b9d590e7f58523302ba00237702ca054"},
+    {file = "multiprocess-0.70.16-pp39-pypy39_pp73-macosx_10_13_x86_64.whl", hash = "sha256:0dfd078c306e08d46d7a8d06fb120313d87aa43af60d66da43ffff40b44d2f41"},
+    {file = "multiprocess-0.70.16-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:e7b9d0f307cd9bd50851afaac0dba2cb6c44449efff697df7c7645f7d3f2be3a"},
+    {file = "multiprocess-0.70.16-py310-none-any.whl", hash = "sha256:c4a9944c67bd49f823687463660a2d6daae94c289adff97e0f9d696ba6371d02"},
+    {file = "multiprocess-0.70.16-py311-none-any.whl", hash = "sha256:af4cabb0dac72abfb1e794fa7855c325fd2b55a10a44628a3c1ad3311c04127a"},
+    {file = "multiprocess-0.70.16-py312-none-any.whl", hash = "sha256:fc0544c531920dde3b00c29863377f87e1632601092ea2daca74e4beb40faa2e"},
+    {file = "multiprocess-0.70.16-py38-none-any.whl", hash = "sha256:a71d82033454891091a226dfc319d0cfa8019a4e888ef9ca910372a446de4435"},
+    {file = "multiprocess-0.70.16-py39-none-any.whl", hash = "sha256:a0bafd3ae1b732eac64be2e72038231c1ba97724b60b09400d68f229fcc2fbf3"},
+    {file = "multiprocess-0.70.16.tar.gz", hash = "sha256:161af703d4652a0e1410be6abccecde4a7ddffd19341be0a7011b94aeb171ac1"},
+]
+mypy = [
     {file = "mypy-0.991-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7d17e0a9707d0772f4a7b878f04b4fd11f6f5bcb9b3813975a9b13c9332153ab"},
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@@ -3201,64 +2639,15 @@ files = [
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 ]
-
-[package.dependencies]
-mypy-extensions = ">=0.4.3"
-tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
-typing-extensions = ">=3.10"
-
-[package.extras]
-dmypy = ["psutil (>=4.0)"]
-install-types = ["pip"]
-python2 = ["typed-ast (>=1.4.0,<2)"]
-reports = ["lxml"]
-
-[[package]]
-name = "mypy-extensions"
-version = "1.0.0"
-description = "Type system extensions for programs checked with the mypy type checker."
-optional = false
-python-versions = ">=3.5"
-files = [
+mypy-extensions = [
     {file = "mypy_extensions-1.0.0-py3-none-any.whl", hash = "sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d"},
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-
-[[package]]
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-version = "1.0.0"
-description = "A Jupyter Notebook Sphinx reader built on top of the MyST markdown parser."
-optional = false
-python-versions = ">=3.9"
-files = [
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-jupyter-cache = ">=0.5"
-myst-parser = ">=1.0.0"
-nbclient = "*"
-nbformat = ">=5.0"
-pyyaml = "*"
-sphinx = ">=5"
-typing-extensions = "*"
-
-[package.extras]
-code-style = ["pre-commit"]
-rtd = ["alabaster", "altair", "bokeh", "coconut (>=1.4.3,<3.1.0)", "ipykernel (>=5.5,<7.0)", "ipywidgets", "jupytext (>=1.11.2,<1.16.0)", "matplotlib", "numpy", "pandas", "plotly", "sphinx-book-theme (>=0.3)", "sphinx-copybutton", "sphinx-design (>=0.4.0,<0.5.0)", "sphinxcontrib-bibtex", "sympy"]
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-
-[[package]]
-name = "myst-parser"
-version = "2.0.0"
-description = "An extended [CommonMark](https://spec.commonmark.org/) compliant parser,"
-optional = false
-python-versions = ">=3.8"
-files = [
+]
+myst-nb = [
+    {file = "myst_nb-1.0.0-py3-none-any.whl", hash = "sha256:ee8febc6dd7d9e32bede0c66a9b962b2e2fdab697428ee9fbfd4919d82380911"},
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 ]
@@ -3274,14 +2663,7 @@ nest-asyncio = [
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 ]
-
-[[package]]
-name = "netcdf4"
-version = "1.6.5"
-description = "Provides an object-oriented python interface to the netCDF version 4 library"
-optional = false
-python-versions = ">=3.7"
-files = [
+netcdf4 = [
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@@ -4369,87 +3367,19 @@ sqlalchemy = [
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@@ -4470,18 +3400,7 @@ types-pytz = [
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-
-[[package]]
-name = "wcwidth"
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-python-versions = "*"
-files = [
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-python-versions = ">=3.9"
-files = [
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-content-hash = "f41a2e96ea3391591b619b39f3cd2db4e91d41d98be72feeeb2a231ef0bcaa75"
+]
\ No newline at end of file