docs: use np.genfromtxt instead of recfromcsv

Use np.genfromtxt instead of np.recfromcsv,
since the latter is deprecated.

doc/examples/pyplots/basic_results.py

@@ -6,9 +6,13 @@
 
 # Import Data
 output_data_path = "../../../examples/basic/reference_output/timeseries_export.csv"
-results = np.recfromcsv(output_data_path, encoding=None)
+results = np.genfromtxt(
+    output_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 input_data_path = "../../../examples/basic/input/timeseries_import.csv"
-input_data = np.recfromcsv(input_data_path, encoding=None)
+input_data = np.genfromtxt(
+    input_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]

doc/examples/pyplots/cascading_channels_results.py

@@ -6,7 +6,9 @@
 
 # Import Data
 data_path = "../../../examples/cascading_channels/reference_output/timeseries_export.csv"
-record = np.recfromcsv(data_path, encoding=None)
+record = np.genfromtxt(
+    data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in record["time"]]

doc/examples/pyplots/channel_pulse_results.py

@@ -9,17 +9,46 @@
 output_dir = Path("../../../examples/channel_pulse/reference_output/").resolve()
 
 # Import Data
-rtc_tools_record = np.recfromcsv(output_dir / "timeseries_export_inertial_wave.csv", encoding=None)
-rtc_tools_semi_impl_record = np.recfromcsv(
-    output_dir / "timeseries_export_inertial_wave_semi_implicit.csv", encoding=None
+rtc_tools_record = np.genfromtxt(
+    output_dir / "timeseries_export_inertial_wave.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
 )
-rtc_tools_conv_acc_record = np.recfromcsv(
-    output_dir / "timeseries_export_saint_venant.csv", encoding=None
+rtc_tools_semi_impl_record = np.genfromtxt(
+    output_dir / "timeseries_export_inertial_wave_semi_implicit.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
 )
-rtc_tools_conv_acc_upwind_record = np.recfromcsv(
-    output_dir / "timeseries_export_saint_venant_upwind.csv", encoding=None
+rtc_tools_conv_acc_record = np.genfromtxt(
+    output_dir / "timeseries_export_saint_venant.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
+)
+rtc_tools_conv_acc_upwind_record = np.genfromtxt(
+    output_dir / "timeseries_export_saint_venant_upwind.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
+)
+hec_ras_record = np.genfromtxt(
+    output_dir / "HEC-RAS_export.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
 )
-hec_ras_record = np.recfromcsv(output_dir / "HEC-RAS_export.csv", encoding=None)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in rtc_tools_record["time"]]

doc/examples/pyplots/channel_wave_damping.py

@@ -7,10 +7,22 @@
 
 # Import Data
 output_dir = Path("../../../examples/channel_wave_damping/reference_output/").resolve()
-record_local_control = np.recfromcsv(
-    output_dir / "timeseries_export_local_control.csv", encoding=None
+record_local_control = np.genfromtxt(
+    output_dir / "timeseries_export_local_control.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
+)
+record_optimization = np.genfromtxt(
+    output_dir / "timeseries_export.csv",
+    delimiter=",",
+    encoding=None,
+    dtype=None,
+    names=True,
+    case_sensitive="lower",
 )
-record_optimization = np.recfromcsv(output_dir / "timeseries_export.csv", encoding=None)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in record_optimization["time"]]

doc/examples/pyplots/ensemble_results.py

@@ -12,7 +12,9 @@
 forcasts = {}
 for forecast in forecast_names:
     data_path = dir_template.format(forecast)
-    forcasts[forecast] = np.recfromcsv(data_path, encoding=None)
+    forcasts[forecast] = np.genfromtxt(
+        data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+    )
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in forcasts[forecast_names[0]]["time"]]

doc/examples/pyplots/goal_programming_results.py

@@ -6,7 +6,9 @@
 
 # Import Data
 data_path = "../../../examples/goal_programming/reference_output/timeseries_export.csv"
-results = np.recfromcsv(data_path, encoding=None)
+results = np.genfromtxt(
+    data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]

doc/examples/pyplots/integrator_delay.py

@@ -13,9 +13,13 @@
 output_data_path = (
     current_folder / "../../../examples/integrator_delay/output/timeseries_export.csv"
 )
-results = np.recfromcsv(output_data_path, encoding=None)
+results = np.genfromtxt(
+    output_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 input_data_path = current_folder / "../../../examples/integrator_delay/input/timeseries_import.csv"
-input_data = np.recfromcsv(input_data_path, encoding=None)
+input_data = np.genfromtxt(
+    input_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]

doc/examples/pyplots/lookup_table_results.py

@@ -6,7 +6,9 @@
 
 # Import Data
 data_path = "../../../examples/lookup_table/reference_output/timeseries_export.csv"
-results = np.recfromcsv(data_path, encoding=None)
+results = np.genfromtxt(
+    data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]

doc/examples/pyplots/mixed_integer_results.py

@@ -6,7 +6,9 @@
 
 # Import Data
 data_path = "../../../examples/mixed_integer/reference_output/timeseries_export.csv"
-results = np.recfromcsv(data_path, encoding=None)
+results = np.genfromtxt(
+    data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]

doc/examples/pyplots/pumped_hydropower_system_results.py

@@ -7,8 +7,12 @@
 # Import Data
 data_path = "../../../examples/pumped_hydropower_system/reference_output/timeseries_export.csv"
 import_data_path = "../../../examples/pumped_hydropower_system/input//timeseries_import.csv"
-results = np.recfromcsv(data_path, encoding=None)
-inputs = np.recfromcsv(import_data_path, encoding=None)
+results = np.genfromtxt(
+    data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
+inputs = np.genfromtxt(
+    import_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]

doc/examples/pyplots/simulation_results.py

@@ -6,9 +6,13 @@
 
 # Import Data
 output_data_path = "../../../examples/simulation/reference_output/timeseries_export.csv"
-results = np.recfromcsv(output_data_path, encoding=None)
+results = np.genfromtxt(
+    output_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 input_data_path = "../../../examples/simulation/input/timeseries_import.csv"
-input_data = np.recfromcsv(input_data_path, encoding=None)
+input_data = np.genfromtxt(
+    input_data_path, delimiter=",", encoding=None, dtype=None, names=True, case_sensitive="lower"
+)
 
 # Get times as datetime objects
 times = [datetime.strptime(x, "%Y-%m-%d %H:%M:%S") for x in results["time"]]