Fix: fix examples for release (#444)

Co-authored-by: Samuel Lopez <[email protected]>

Author: eblanco-ansys

examples/high_frequency/layout/signal_integrity/ami.py

@@ -143,26 +143,23 @@
 tstop_ns = scale_time * tstop
 tstart_ns = scale_time * tstart
 
-for time_value in original_data_value[plot_name].index:
-    if tstart_ns <= time_value[0]:
-        start_index_original_data = time_value[0]
-        break
-for time_value in original_data_value[plot_name][start_index_original_data:].index:
-    if time_value[0] >= tstop_ns:
-        stop_index_original_data = time_value[0]
-        break
-for time_value in sample_waveform[0].index:
-    if tstart <= time_value:
-        sample_index = sample_waveform[0].index == time_value
-        start_index_waveform = sample_index.tolist().index(True)
-        break
-for time_value in sample_waveform[0].index:
-    if time_value >= tstop:
-        sample_index = sample_waveform[0].index == time_value
-        stop_index_waveform = sample_index.tolist().index(True)
-        break
-
-original_data_zoom = original_data_value[
+orig_times = np.array([row[0] for row in original_data_value[plot_name]])
+start_index_original_data = int(np.searchsorted(orig_times, tstart_ns, side="left"))
+if start_index_original_data >= orig_times.size:
+    start_index_original_data = orig_times.size - 1
+stop_index_original_data = int(np.searchsorted(orig_times, tstop_ns, side="left"))
+if stop_index_original_data >= orig_times.size:
+    stop_index_original_data = orig_times.size - 1
+
+sample_index_array = np.array(sample_waveform[0].index)
+start_index_waveform = int(np.searchsorted(sample_index_array, tstart, side="left"))
+if start_index_waveform >= sample_index_array.size:
+    start_index_waveform = sample_index_array.size - 1
+stop_index_waveform = int(np.searchsorted(sample_index_array, tstop, side="left"))
+if stop_index_waveform >= sample_index_array.size:
+    stop_index_waveform = sample_index_array.size - 1
+
+original_data_zoom = original_data_value[plot_name][
     start_index_original_data:stop_index_original_data
 ]
 sampled_data_zoom = (
@@ -175,8 +172,8 @@
 fig, ax = plt.subplots()
 ax.plot(sampled_time_zoom, sampled_data_zoom, "r*")
 ax.plot(
-    np.array(list(original_data_zoom.index.values)),
-    original_data_zoom.values,
+    np.array(list(original_data_zoom[:,0])),
+    original_data_zoom[:,1],
     color="blue",
 )
 ax.set_title("WaveAfterProbe")
@@ -190,7 +187,7 @@
 # Create the plot from a start time to stop time in seconds.
 
 fig, ax2 = plt.subplots()
-ax2.plot(sample_waveform[0].index, sample_waveform[0].values, "r*")
+ax2.plot(sample_waveform[0].index, np.concatenate(sample_waveform[0].values), "r*")
 ax2.set_title("Slicer Scatter: WaveAfterProbe")
 ax2.set_xlabel("s")
 ax2.set_ylabel("V")
@@ -202,7 +199,7 @@
 
 fig, ax4 = plt.subplots()
 ax4.set_title("Slicer Histogram: WaveAfterProbe")
-ax4.hist(sample_waveform[0].values, orientation="horizontal")
+ax4.hist(np.concatenate(sample_waveform[0].values), orientation="horizontal")
 ax4.set_ylabel("V")
 ax4.grid()
 plt.show()
@@ -226,9 +223,10 @@
 
 # +
 original_data.enable_pandas_output = False
-original_data_value = original_data.data_real()
+original_data_value = original_data.get_expression_data(formula="real")[1]
 original_data_sweep = original_data.primary_sweep_values
 waveform_unit = original_data.units_data[plot_name]
+
 waveform_sweep_unit = original_data.units_sweeps["Time"]
 tics = np.arange(20e-9, 100e-9, 1e-10, dtype=float)
 
@@ -260,14 +258,14 @@
 tstop_ns = scale_time * tstop
 tstart_ns = scale_time * tstart
 
-for time_value in original_data_sweep:
-    if tstart_ns <= time_value:
-        start_index_original_data = original_data_sweep.index(time_value.value)
-        break
-for time_value in original_data_sweep[start_index_original_data:]:
-    if time_value >= tstop_ns:
-        stop_index_original_data = original_data_sweep.index(time_value.value)
-        break
+start_index_original_data = int(np.searchsorted(original_data_sweep, tstart_ns, side="left"))
+if start_index_original_data >= original_data_sweep.size:
+    start_index_original_data = original_data_sweep.size - 1
+
+stop_index_original_data = int(np.searchsorted(original_data_sweep, tstop_ns, side="left"))
+if stop_index_original_data >= original_data_sweep.size:
+    stop_index_original_data = original_data_sweep.size - 1
+
 cont = 0
 for frame in sample_waveform:
     if tstart <= frame[0]:
@@ -290,11 +288,23 @@
     list(map(list, zip(original_sweep_zoom, original_data_zoom)))
 )
 original_data_zoom_array[:, 0] *= 1
-sampled_data_zoom_array = np.array(
-    sample_waveform[start_index_waveform:stop_index_waveform]
-)
-sampled_data_zoom_array[:, 0] *= scale_time
-sampled_data_zoom_array[:, 1] *= scale_data
+sampled_slice = sample_waveform[start_index_waveform:stop_index_waveform]
+# Build a homogeneous Nx2 array [time, value] from the sliced frames, with a guard for empty slices.
+if len(sampled_slice):
+    sampled_data_zoom_array = np.array(
+        [
+            [
+                float(np.asarray(frame[0]).ravel()[0]),
+                float(np.asarray(frame[1]).ravel()[0]),
+            ]
+            for frame in sampled_slice
+        ],
+        dtype=float,
+    )
+    sampled_data_zoom_array[:, 0] *= scale_time
+    sampled_data_zoom_array[:, 1] *= scale_data
+else:
+    sampled_data_zoom_array = np.empty((0, 2))
 
 fig, ax = plt.subplots()
 ax.plot(sampled_data_zoom_array[:, 0], sampled_data_zoom_array[:, 1], "r*")
@@ -309,7 +319,14 @@
 #
 # Create the plot from a start time to stop time in seconds.
 
-sample_waveform_array = np.array(sample_waveform)
+sample_waveform_array = np.array(
+        [
+            [float(frame[0]), float(np.asarray(frame[1]).ravel()[0])]
+            for frame in sample_waveform
+        ],
+        dtype=float,
+)
+
 fig, ax2 = plt.subplots()
 ax2.plot(sample_waveform_array[:, 0], sample_waveform_array[:, 1], "r*")
 ax2.set_title("Slicer Scatter: " + plot_name)

examples/low_frequency/general/field_export.py

@@ -17,6 +17,7 @@
 
 import ansys.aedt.core
 from ansys.aedt.core.examples.downloads import download_file
+from ansys.aedt.core.generic.constants import unit_converter
 # -
 
 # Define constants.
@@ -141,17 +142,17 @@
 # The J field is plotted on the surface of each coil for every time-step.
 # Fields data is exported to the temporary folder as an AEDTPLT file.
 
-for time_step in time_steps:
-    time_step = time_step.to("ms")
-
+unit = data.units_sweeps["Time"]
+converted = unit_converter(time_steps, "Time", unit, "ms")
+for time_step in converted:
     m3d.post.create_fieldplot_surface(
         assignment=m3d.modeler.objects_by_name["Coil_A2"],
         quantity=quantity[0],
-        plot_name="J_{}_ms".format(time_step.value),
-        intrinsics={"Time": time_step.expression},
+        plot_name="J_{}_ms".format(time_step),
+        intrinsics={"Time": "ms"},
     )
     mean_j_field_export = m3d.post.export_field_plot(
-        plot_name="J_{}_ms".format(time_step.value),
+        plot_name="J_{}_ms".format(time_step),
         output_dir=temp_folder.name,
         file_format="aedtplt",
     )
@@ -160,11 +161,11 @@
             o for o in m3d.modeler.solid_objects if o.material_name == "copper"
         ],
         quantity="Mag_J",
-        plot_name="Mag_J_Coils_{}_ms".format(time_step.value),
-        intrinsics={"Time": time_step.expression},
+        plot_name="Mag_J_Coils_{}_ms".format(time_step),
+        intrinsics={"Time": "ms"},
     )
     mag_j_field_export = m3d.post.export_field_plot(
-        plot_name="Mag_J_Coils_{}_ms".format(time_step.value),
+        plot_name="Mag_J_Coils_{}_ms".format(time_step),
         output_dir=temp_folder.name,
         file_format="aedtplt",
     )

examples/low_frequency/general/resistance.py

@@ -178,7 +178,7 @@
 # and plot data outside AEDT.
 
 data = report.get_solution_data()
-resistance = data.data_magnitude()
+resistance = data.get_expression_data(formula="magnitude")[1]
 material_index = data.primary_sweep_values
 data.primary_sweep = "MaterialIndex"
 data.plot(snapshot_path=os.path.join(temp_folder.name, "M2D_DCConduction.jpg"))

examples/low_frequency/magnetic/magnet_collector.py

@@ -111,15 +111,15 @@
 
 # +
 collector = m3d.modeler.create_cylinder(
-    orientation=ansys.aedt.core.constants.AXIS.Z,
+    orientation=ansys.aedt.core.constants.Axis.Z,
     origin=[12, 13, 25],
     height="3mm",
     radius="9.5mm",
     axisdir="Z",
     name="collector",
 )
 cylinder2 = m3d.modeler.create_cylinder(
-    orientation=ansys.aedt.core.constants.AXIS.Z,
+    orientation=ansys.aedt.core.constants.Axis.Z,
     origin=[12, 13, 25],
     height="3mm",
     radius="8mm",
@@ -132,15 +132,15 @@
 )
 
 cylinder3 = m3d.modeler.create_cylinder(
-    orientation=ansys.aedt.core.constants.AXIS.Z,
+    orientation=ansys.aedt.core.constants.Axis.Z,
     origin=[12, 13, 28],
     height="3mm",
     radius="8.7mm",
     axisdir="Z",
     name="cyl3",
 )
 cylinder4 = m3d.modeler.create_cylinder(
-    orientation=ansys.aedt.core.constants.AXIS.Z,
+    orientation=ansys.aedt.core.constants.Axis.Z,
     origin=[12, 13, 28],
     height="3mm",
     radius="2mm",
@@ -190,8 +190,8 @@
 )
 section = m3d.modeler.create_rectangle(
     orientation="XZ",
-    position=[-25, 0, -35],
-    dimension_list=["50mm", "50mm"],
+    origin=[-25, 0, -35],
+    sizes=["50mm", "50mm"],
     name="section",
 )
 m3d.modeler.set_working_coordinate_system("Global")

examples/low_frequency/motor/aedt_motor/ipm_optimization.py

@@ -294,9 +294,9 @@
     core_loss_data.active_variation = var
     solid_loss_data.active_variation = var
 
-    torque_values = torque_data.data_magnitude()
-    core_loss_values = core_loss_data.data_magnitude()
-    solid_loss_values = solid_loss_data.data_magnitude()
+    torque_values = torque_data.get_expression_data(formula="magnitude")[1]
+    core_loss_values = core_loss_data.get_expression_data(formula="magnitude")[1]
+    solid_loss_values = solid_loss_data.get_expression_data(formula="magnitude")[1]
 
     torque_data_average = sum(torque_values) / len(torque_values)
     core_loss_average = sum(core_loss_values) / len(core_loss_values)

examples/low_frequency/motor/aedt_motor/pm_synchronous.py

@@ -18,6 +18,7 @@
 
 import ansys.aedt.core
 import matplotlib.pyplot as plt
+import numpy as np
 from ansys.aedt.core.examples.downloads import download_leaf
 from ansys.aedt.core.generic.constants import unit_converter
 from ansys.aedt.core.generic.numbers_utils import Quantity
@@ -896,7 +897,7 @@ def create_cs_magnets(pm_id, cs_name, point_direction):
 #
 # List of shaft torque points and compute average.
 
-mag = solutions.data_magnitude()
+mag = solutions.get_expression_data(formula="magnitude")[1]
 avg = sum(mag) / len(mag)
 
 # ## Export a report to a file
@@ -930,12 +931,22 @@ def create_cs_magnets(pm_id, cs_name, point_direction):
 
 # Find the indices corresponding to the start and stop times
 
-index_start_time = time_interval.index(start_time)
-index_stop_time = time_interval.index(stop_time)
+# Convert Quantity objects to numeric values (time_intrinsics are in ns)
+numeric_start = start_time.value
+numeric_stop = stop_time.value
+
+# Use numpy.searchsorted to find the indices in the numpy array
+index_start_time = int(np.searchsorted(time_interval, numeric_start, side="left"))
+index_stop_time = int(np.searchsorted(time_interval, numeric_stop, side="right"))
+
+# Clamp indices to valid range
+index_start_time = max(0, min(index_start_time, len(time_interval) - 1))
+index_stop_time = max(0, min(index_stop_time, len(time_interval)))
 
 # ## Extract the torque values within the specified time range
 
-torque_values = solutions.data_real()
+# Ensure torque values are a numpy array for slicing
+torque_values = solutions.get_expression_data(formula="Real")[1]
 time_electric_period = time_interval[index_start_time:index_stop_time]
 torque_electric_period = torque_values[index_start_time:index_stop_time]
 

examples/low_frequency/multiphysics/maxwell_icepak.py

@@ -18,7 +18,7 @@
 import time
 
 import ansys.aedt.core  # Interface to Ansys Electronics Desktop
-from ansys.aedt.core.generic.constants import AXIS
+from ansys.aedt.core.generic.constants import Axis
 # -
 
 # ### Define constants
@@ -81,15 +81,15 @@
 coil = m3d.modeler.create_rectangle(
     orientation="XZ", origin=coil_origin, sizes=coil_xsection, name="Coil"
 )
-coil.sweep_around_axis(axis=AXIS.Z)
+coil.sweep_around_axis(axis=Axis.Z)
 coil_terminal = m3d.modeler.create_rectangle(
     orientation="XZ", origin=coil_origin, sizes=coil_xsection, name="Coil_terminal"
 )
 
 core = m3d.modeler.create_rectangle(
     orientation="XZ", origin=core_origin, sizes=core_xsection, name="Core"
 )
-core.sweep_around_axis(axis=AXIS.Z)
+core.sweep_around_axis(axis=Axis.Z)
 
 # The air region should be sufficiently large to avoid interaction with the
 # coil magnetic field.
@@ -216,11 +216,11 @@
 # +
 report = m3d.post.create_report(expressions="Matrix1.R(Winding1,Winding1)")
 solution = report.get_solution_data()
-resistance = solution.data_magnitude()[0]  # Resistance is the first matrix element.
+resistance = solution.get_expression_data(formula="magnitude")[0][0]  # Resistance is the first matrix element.
 
 report_loss = m3d.post.create_report(expressions="StrandedLossAC")
 solution_loss = report_loss.get_solution_data()
-em_loss = solution_loss.data_magnitude()[0]
+em_loss = solution_loss.get_expression_data(formula="magnitude")[0][0]
 # -
 
 # ### Analyitic calculation of DC resistance
@@ -349,7 +349,7 @@
     expressions="PointMonitor1.Temperature", primary_sweep_variable="X"
 )
 solution_temp = report_temp.get_solution_data()
-temp = solution_temp.data_magnitude()[0]
+temp = solution_temp.get_expression_data(formula="magnitude")[1][0]
 m3d.logger.info("*******Coil temperature =  {:.2f}deg C".format(temp))
 # -
 
@@ -360,12 +360,12 @@
 # +
 report_new = m3d.post.create_report(expressions="Matrix1.R(Winding1,Winding1)")
 solution_new = report_new.get_solution_data()
-resistance_new = solution_new.data_magnitude()[0]
+resistance_new = solution_new.get_expression_data(formula="magnitude")[1][0]
 resistance_increase = (resistance_new - resistance) / resistance * 100
 
 report_loss_new = m3d.post.create_report(expressions="StrandedLossAC")
 solution_loss_new = report_loss_new.get_solution_data()
-em_loss_new = solution_loss_new.data_magnitude()[0]
+em_loss_new = solution_loss_new.get_expression_data(formula="magnitude")[1][0]
 
 m3d.logger.info(
     "*******Coil resistance at 150kHz AFTER temperature feedback =  {:.2f}Ohm".format(