Major upgrade of numpy dependency to v2

Also relaxed floating point requirements to avoid type checking errors.

Signed-off-by: cwasicki <[email protected]>

Author: cwasicki

RELEASE_NOTES.md

@@ -6,6 +6,9 @@
 
 ## Upgrading
 
+
+* Includes a major dependency upgrade of the numpy library to version 2.
+
 <!-- Here goes notes on how to upgrade from previous versions, including deprecations and what they should be replaced with -->
 
 ## New Features

pyproject.toml

@@ -27,8 +27,8 @@ classifiers = [
 requires-python = ">= 3.11, < 4"
 dependencies = [
   "typing-extensions >= 4.12.2, < 5",
-  "numpy >= 1.26.4, < 1.27.0",
-  "pandas >= 2.1.4, < 2.3.0",
+  "numpy >= 2.0, < 3",
+  "pandas >= 2.2.2, < 3",
   "matplotlib >= 3.8.4, < 3.11.0",
   "ipython == 9.2.0",
   "pvlib >= 0.11.0, < 0.12.0",
@@ -37,7 +37,7 @@ dependencies = [
   "plotly >= 6.0.0, < 6.1.0",
   "kaleido >= 0.2.1, < 0.3.0",
   "frequenz-client-reporting >= 0.16.0, < 0.17.0",
-  "frequenz-client-weather >= 0.1.0, < 0.2.0",
+  "frequenz-client-weather >= 0.2.0, < 0.3.0",
 ]
 dynamic = ["version"]
 

src/frequenz/lib/notebooks/solar/maintenance/models.py

@@ -95,7 +95,7 @@ def prepare_prediction_models(
     """
     data_copy = data.copy()
 
-    supported_models: dict[str, Callable[..., SeriesFloat | NDArray[np.float64]]] = {
+    supported_models: dict[str, Callable[..., SeriesFloat | NDArray[np.floating]]] = {
         "wma": weighted_moving_average,
         "sampled_ma": sampled_moving_average,
         "naive_eff_irr2power": naive_efficiency_factor_irr_to_power,
@@ -158,7 +158,7 @@ def weighted_moving_average(
     mode: str | None = None,
     win_size: int | None = None,
     weights: NDArray[np.float64] | None = None,
-) -> NDArray[np.float64]:
+) -> NDArray[np.floating]:
     """Perform moving average with different weighting schemes.
 
     Args: