fixed performance and deprecation warnings

fm2prof/CrossSection.py

@@ -8,7 +8,7 @@
 import numpy as np
 import pandas as pd
 import scipy.optimize as so
-from scipy.integrate import cumtrapz
+from scipy.integrate import cumulative_trapezoid
 from tqdm import tqdm
 
 from fm2prof import Functions as FE
@@ -287,13 +287,12 @@ def get_timeseries(name: str):
 
         # Convert area to a matrix for matrix operations
         # (much more efficient than for-loops)
-        area_matrix = pd.DataFrame(index=area.index)
-        for t in waterdepth:
-            area_matrix[t] = area
+        area_matrix = pd.DataFrame({col: area for col in waterdepth.columns})
+        area_matrix.index = area.index
+
+        bedlevel_matrix = pd.DataFrame({col: area for col in waterdepth.columns})
+        bedlevel_matrix.index = bedlevel.index
 
-        bedlevel_matrix = pd.DataFrame(index=bedlevel.index)
-        for t in waterdepth:
-            bedlevel_matrix[t] = bedlevel
 
         # Retrieve the water-depth
         # & water level nearest to the cross-section location
@@ -374,10 +373,10 @@ def get_timeseries(name: str):
 
         # Compute 1D volume as integral of width with respect to z times length
         self._css_total_volume = np.append(
-            [0], cumtrapz(self._css_total_width, self._css_z) * self.length
+            [0], cumulative_trapezoid(self._css_total_width, self._css_z) * self.length
         )
         self._css_flow_volume = np.append(
-            [0], cumtrapz(self._css_flow_width, self._css_z) * self.length
+            [0], cumulative_trapezoid(self._css_flow_width, self._css_z) * self.length
         )
 
         # If sd correction is run, these attributes will be updated.

fm2prof/Fm2ProfRunner.py

@@ -10,6 +10,7 @@
 import tqdm
 from geojson import Feature, FeatureCollection, Polygon
 from netCDF4 import Dataset
+import pandas as pd
 from scipy.spatial import ConvexHull
 
 from fm2prof import Functions as FE
@@ -95,7 +96,7 @@ def run(self, overwrite: bool = False) -> None:
             return
 
         # Check for already existing output
-        if self._output_exists() & ~overwrite:
+        if self._output_exists() and not overwrite:
             self.set_logger_message(
                 "Output already exists. Use overwrite option if you want to re-run the program",
                 "warning",
@@ -567,10 +568,13 @@ def _classify_roughness_sections_by_variance(self, data, variable):
             splitpoint = split_candidates[np.nanargmin(variance_list)]
 
             # High chezy values are assigned to section number '1' (Main channel)
-            data[key][end_values > splitpoint] = 1
-
             # Low chezy values are assigned to section number '2' (Flood plain)
-            data[key][end_values <= splitpoint] = 2
+            if isinstance(data, pd.DataFrame):
+                data.loc[end_values > splitpoint, key] = 1
+                data.loc[end_values <= splitpoint, key] = 2
+            else:            
+                data[key][end_values > splitpoint] = 1           
+                data[key][end_values <= splitpoint] = 2
         return data
 
     def _get_region_map_file(self, polytype):

fm2prof/utils.py

@@ -621,7 +621,7 @@ def figure_cross_section(
             os.mkdir(output_dir)
 
         output_file = output_dir.joinpath(f"{css['id']}.png")
-        if output_file.is_file() & ~overwrite:
+        if output_file.is_file() and not overwrite:
             self.set_logger_message("file already exists", "debug")
             return
         try: