Merge branch 'dev' into spcqe_quantiles

.github/workflows/build.yml

@@ -55,7 +55,7 @@ jobs:
       - name: Install the Conda Dependencies
         run: |
           conda config --set always_yes yes --set auto_update_conda false
-          conda update conda
+          conda install conda=24.1.2
           conda install -n base conda-libmamba-solver
           conda install python=3.10 conda-build colorama pip ruamel ruamel.yaml rich jsonschema -c conda-forge
           git fetch --prune --unshallow --tags

.github/workflows/test-build.yml

@@ -48,7 +48,7 @@ jobs:
       - name: Install the Conda Dependencies
         run: |
           conda config --set always_yes yes --set auto_update_conda false
-          conda update conda
+          conda install conda=24.1.2
           conda install -n base conda-libmamba-solver
           conda install python=3.10 conda-build colorama pip ruamel ruamel.yaml rich jsonschema -c conda-forge
           git fetch --prune --unshallow --tags

pvsystemprofiler/estimator.py

@@ -82,14 +82,13 @@ def __init__(
             solar_noon_method == "optimized_estimates"
             or daylight_method == "optimized_estimates"
         ):
-            ss = SunriseSunset()
+            ss = self.data_handler.daytime_analysis
 
         if solar_noon_method == "rise_set_average":
             self.solarnoon = avg_sunrise_sunset(self.data_matrix)
         elif solar_noon_method == "energy_com":
             self.solarnoon = energy_com(self.data_matrix)
         if solar_noon_method == "optimized_estimates":
-            ss.run_optimizer(data=self.data_matrix)
             self.solarnoon = np.nanmean(
                 [ss.sunrise_estimates, ss.sunset_estimates], axis=0
             )

requirements.txt

@@ -18,3 +18,5 @@ sig-decomp
 osqp
 clarabel
 qss
+tqdm
+spcqe

solardatatools/algorithms/__init__.py

@@ -7,3 +7,4 @@
 from solardatatools.algorithms.soiling import soiling_seperation_old
 from solardatatools.algorithms.soiling import soiling_seperation
 from solardatatools.algorithms.dilatation import Dilatation
+from solardatatools.algorithms.loss_factor_analysis import LossFactorAnalysis

solardatatools/algorithms/capacity_change.py

@@ -34,7 +34,7 @@ def run(
         quantile=1.00,
         w1=40e-6,  # scaled weights for QSS
         w2=6561e-6,
-        solver=None
+        solver=None,
     ):
         if filter is None:
             filter = np.ones(data.shape[1], dtype=bool)
@@ -43,24 +43,23 @@ def run(
             metric /= np.max(metric)
 
             s1, s2, s3 = l1_l1d1_l2d2p365(
-                metric,
-                use_ixs=filter,
-                w1=w1,
-                w2=w2,
-                solver=solver,
-                sum_card=True
+                metric, use_ixs=filter, w1=w1, w2=w2, solver=solver, sum_card=True
             )
         else:
             # print('No valid values! Please check your data and filter.')
             return
 
         # Get capacity assignments
-        rounded_s1 = np.round(s1, 1)
+        def custom_round(x, base=0.05):
+            ndigits = len(str(base).split(".")[-1])
+            return np.round(base * np.round(x / base), ndigits)
+
+        rounded_s1 = custom_round(s1)
         set_labels = list(set(rounded_s1))
         capacity_assignments = [set_labels.index(i) for i in rounded_s1]
 
         self.metric = metric
-        self.s1 = s1 # pwc
-        self.s2 = s2 # seasonal
-        self.s3 = s3 # linear
-        self.labels = capacity_assignments
+        self.s1 = s1  # pwc
+        self.s2 = s2  # seasonal
+        self.s3 = s3  # linear
+        self.labels = capacity_assignments