diff --git a/contrib/test_data_generation/sofast_fringe/generate_test_data_multi_facet.py b/contrib/test_data_generation/sofast_fringe/generate_test_data_multi_facet.py
deleted file mode 100644
index d2acc6346..000000000
--- a/contrib/test_data_generation/sofast_fringe/generate_test_data_multi_facet.py
+++ /dev/null
@@ -1,97 +0,0 @@
-"""Generates test data from measurement file for mirror type 'multi_facet'.
-"""
-
-from os.path import join, dirname, exists
-
-import matplotlib.pyplot as plt
-import numpy as np
-
-from opencsp.app.sofast.lib.ImageCalibrationScaling import ImageCalibrationScaling
-from opencsp.app.sofast.lib.MeasurementSofastFringe import MeasurementSofastFringe as Measurement
-from opencsp.app.sofast.lib.ProcessSofastFringe import ProcessSofastFringe as Sofast
-from opencsp.app.sofast.lib.DisplayShape import DisplayShape as Display
-from opencsp.app.sofast.lib.DefinitionEnsemble import DefinitionEnsemble
-from opencsp.app.sofast.lib.DefinitionFacet import DefinitionFacet
-from opencsp.common.lib.camera.Camera import Camera
-from opencsp.common.lib.opencsp_path.opencsp_root_path import opencsp_code_dir
-
-
-def generate_dataset(
-    file_measurement: str,
-    file_camera: str,
-    file_display: str,
-    file_calibration: str,
-    file_facet: str,
-    file_ensemble: str,
-    file_dataset_out: str,
-):
-    """Generates and saves test data"""
-    # Check output file exists
-    if not exists(dirname(file_dataset_out)):
-        raise FileNotFoundError(f'Output directory {file_dataset_out:s} does not exist.')
-
-    # Load components
-    camera = Camera.load_from_hdf(file_camera)
-    display = Display.load_from_hdf(file_display)
-    measurement = Measurement.load_from_hdf(file_measurement)
-    calibration = ImageCalibrationScaling.load_from_hdf(file_calibration)
-    ensemble_data = DefinitionEnsemble.load_from_json(file_ensemble)
-    facet_data = [DefinitionFacet.load_from_json(file_facet)] * ensemble_data.num_facets
-
-    # Calibrate fringes
-    measurement.calibrate_fringe_images(calibration)
-
-    # Create sofast object
-    sofast = Sofast(measurement, camera, display)
-
-    # Update image processing parameters
-    sofast.params.mask_hist_thresh = 0.83
-    sofast.params.geometry_params.perimeter_refine_perpendicular_search_dist = 10.0
-    sofast.params.geometry_params.facet_corns_refine_frac_keep = 1.0
-    sofast.params.geometry_params.facet_corns_refine_perpendicular_search_dist = 3.0
-    sofast.params.geometry_params.facet_corns_refine_step_length = 5.0
-
-    # Define surface data
-    surface_data = [
-        dict(
-            surface_type='parabolic', initial_focal_lengths_xy=(100.0, 100.0), robust_least_squares=False, downsample=10
-        )
-    ] * ensemble_data.num_facets
-
-    # Process optic data
-    sofast.process_optic_multifacet(facet_data, ensemble_data, surface_data)
-
-    # Save data
-    sofast.save_to_hdf(file_dataset_out)
-    display.save_to_hdf(file_dataset_out)
-    camera.save_to_hdf(file_dataset_out)
-    calibration.save_to_hdf(file_dataset_out)
-    print(f'Data saved to: {file_dataset_out:s}')
-
-    # Show slope map
-    mask = sofast.data_image_processing_general.mask_raw
-    image = np.zeros(mask.shape) * np.nan
-    for idx in range(sofast.num_facets):
-        mask = sofast.data_image_processing_facet[idx].mask_processed
-        slopes_xy = sofast.data_calculation_facet[idx].slopes_facet_xy
-        slopes = np.sqrt(np.sum(slopes_xy**2, 0))
-        image[mask] = slopes
-    plt.figure()
-    plt.imshow(image, cmap='jet')
-    plt.title('Slope Magnitude')
-    plt.show()
-
-
-if __name__ == '__main__':
-    # Generate measurement set 1
-    base_dir = join(opencsp_code_dir(), 'test/data/measurements_sofast_fringe')
-
-    generate_dataset(
-        file_measurement=join(base_dir, 'measurement_ensemble.h5'),
-        file_camera=join(base_dir, 'camera.h5'),
-        file_display=join(base_dir, 'display_distorted_2d.h5'),
-        file_calibration=join(base_dir, 'image_calibration.h5'),
-        file_facet=join(base_dir, 'Facet_lab_6x4.json'),
-        file_ensemble=join(base_dir, 'Ensemble_lab_6x4.json'),
-        file_dataset_out=join(base_dir, 'calculations_facet_ensemble/data.h5'),
-    )
diff --git a/example/csp/example_optics_and_ray_tracing.py b/example/csp/example_optics_and_ray_tracing.py
index 428c4be61..27ae1c855 100644
--- a/example/csp/example_optics_and_ray_tracing.py
+++ b/example/csp/example_optics_and_ray_tracing.py
@@ -201,7 +201,7 @@ def define_mirror_array(focal_length: float) -> FacetEnsemble:
     # Build facet ensemble
     facet_ensemble = FacetEnsemble(facets)
     facet_ensemble.set_facet_positions(facet_locations)
-    facet_ensemble.set_facet_canting(facet_canting)
+    facet_ensemble.set_facet_cantings(facet_canting)
 
     return facet_ensemble  # FacetEnsemble.generate_rotation_defined(facets)
 
diff --git a/example/mirror/example_MirrorOutput.py b/example/mirror/example_MirrorOutput.py
index 99c16c1cc..0f04c7ec8 100644
--- a/example/mirror/example_MirrorOutput.py
+++ b/example/mirror/example_MirrorOutput.py
@@ -132,7 +132,7 @@ def setUp(self):
             tilt_left * tilt_down,
             tilt_right * tilt_down,
         ]
-        fe2x2.set_facet_canting(fe_2x2_canting_rotations)
+        fe2x2.set_facet_cantings(fe_2x2_canting_rotations)
 
         self.h2x2 = HeliostatAzEl(fe2x2, name='Simple 2x2 Heliostat')
         self.h2x2_title = 'Heliostat with Parametrically Defined Facets'
diff --git a/example/raytrace/example_RayTraceOutput.py b/example/raytrace/example_RayTraceOutput.py
index 71b0a1de0..ef59c8ff3 100644
--- a/example/raytrace/example_RayTraceOutput.py
+++ b/example/raytrace/example_RayTraceOutput.py
@@ -131,7 +131,7 @@ def setUp(self):
         self.fe2x2 = FacetEnsemble(self.h2x2_facets)
         fe2x2_positions = Pxyz([[-1.1, 1.1, -1.1, 1.1], [1.6, 1.6, -1.6, -1.6], [0, 0, 0, 0]])
         self.fe2x2.set_facet_positions(fe2x2_positions)
-        self.fe2x2.set_facet_canting(self.h2x2_canting)
+        self.fe2x2.set_facet_cantings(self.h2x2_canting)
         self.h2x2 = HeliostatAzEl(self.fe2x2, 'Simple 2x2 Heliostat')
         self.h2x2.pivot = 0
         self.h2x2_title = 'Heliostat with Parametrically Defined Facets'
diff --git a/example/sofast_fringe/example_process_facet_ensemble.py b/example/sofast_fringe/example_process_facet_ensemble.py
index 4cf83c4f3..8bf5b253a 100644
--- a/example/sofast_fringe/example_process_facet_ensemble.py
+++ b/example/sofast_fringe/example_process_facet_ensemble.py
@@ -1,40 +1,68 @@
+"""Module for processing and analyzing SOFAST data for an ensemble of mirrors.
+
+This script performs the following steps:
+
+1. Load saved facet ensemble SOFAST collection data from an HDF5 file.
+2. Save projected sinusoidal fringe images to PNG format.
+3. Save captured sinusoidal fringe images and mask images to PNG format.
+4. Process data with SOFAST and save processed data to HDF5.
+5. Generate a suite of plots and save image files.
+
+Examples
+--------
+To run the script, simply execute it as a standalone program:
+
+>>> python example_process_facet_ensemble.py
+
+This will perform the processing steps and save the results to the data/output/single_facet directory
+with the following subfolders:
+
+1_images_fringes_projected - The patterns sent to the display during the SOFAST measurement of the optic.
+2_images_captured - The captured images of the displayed patterns as seen by the SOFAST camera
+3_processed_data - The processed data from SOFAST.
+4_processed_output_figures - The output figure suite from a SOFAST characterization.
+
+Notes
+-----
+- The script assumes that the input data files are located in the specified directories.
+- Chat GPT 4o assisted with the generation of some docstrings in this file."""
+
+import json
 from os.path import join, dirname
-from scipy.spatial.transform import Rotation
+
+import imageio.v3 as imageio
 
 from opencsp.app.sofast.lib.DisplayShape import DisplayShape
 from opencsp.app.sofast.lib.DefinitionEnsemble import DefinitionEnsemble
 from opencsp.app.sofast.lib.DefinitionFacet import DefinitionFacet
+from opencsp.app.sofast.lib.Fringes import Fringes
 from opencsp.app.sofast.lib.ImageCalibrationScaling import ImageCalibrationScaling
 from opencsp.app.sofast.lib.MeasurementSofastFringe import MeasurementSofastFringe
 from opencsp.app.sofast.lib.ProcessSofastFringe import ProcessSofastFringe
-from opencsp.app.sofast.lib.SpatialOrientation import SpatialOrientation
 from opencsp.app.sofast.lib.SofastConfiguration import SofastConfiguration
+from opencsp.app.sofast.lib.SpatialOrientation import SpatialOrientation
 from opencsp.common.lib.camera.Camera import Camera
 from opencsp.common.lib.csp.FacetEnsemble import FacetEnsemble
+from opencsp.common.lib.csp.Facet import Facet
+from opencsp.common.lib.csp.LightSourceSun import LightSourceSun
+from opencsp.common.lib.csp.MirrorParametric import MirrorParametric
+from opencsp.common.lib.csp.StandardPlotOutput import StandardPlotOutput
 from opencsp.common.lib.deflectometry.Surface2DParabolic import Surface2DParabolic
+from opencsp.common.lib.geometry.Uxyz import Uxyz
+from opencsp.common.lib.geometry.Vxyz import Vxyz
 from opencsp.common.lib.opencsp_path.opencsp_root_path import opencsp_code_dir
-import opencsp.common.lib.render.figure_management as fm
-import opencsp.common.lib.render_control.RenderControlAxis as rca
-import opencsp.common.lib.render_control.RenderControlFigure as rcfg
-import opencsp.common.lib.render_control.RenderControlMirror as rcm
-import opencsp.common.lib.render_control.RenderControlFacet as rcf
-import opencsp.common.lib.render_control.RenderControlFacetEnsemble as rcfe
 import opencsp.common.lib.tool.file_tools as ft
 import opencsp.common.lib.tool.log_tools as lt
-from opencsp.common.lib.geometry.Vxyz import Vxyz
-from opencsp.common.lib.tool.hdf5_tools import load_hdf5_datasets
 
 
 def example_process_facet_ensemble():
-    """Performs processing of previously collected Sofast data
-    of multi facet mirror ensemble:
+    """Performs processing of previously collected SOFAST data of facet ensemble.
 
     1. Load saved facet ensemble Sofast collection data
-    2. Processes data with Sofast
-    3. Log best-fit parabolic focal lengths
-    4. Plot slope magnitude
-    5. Plot 3d representation of facet ensemble
-    6. Save slope data as HDF5 file
+    2. Save projected sinusoidal fringe images to PNG format
+    3. Save captured sinusoidal fringe images and mask images to PNG format
+    4. Processes data with SOFAST and save processed data to HDF5
+    5. Generate plot suite and save images files
     """
     # General setup
     # =============
@@ -44,35 +72,70 @@ def example_process_facet_ensemble():
     ft.create_directories_if_necessary(dir_save)
 
     # Set up logger
-    lt.logger(join(dir_save, 'log.txt'), lt.log.INFO)
+    lt.logger(join(dir_save, 'log.txt'), lt.log.WARN)
 
-    base_dir = join(opencsp_code_dir(), 'test/data/sofast_fringe')
+    # Define sample data directory
+    dir_data_sofast = join(opencsp_code_dir(), 'test/data/sofast_fringe')
+    dir_data_common = join(opencsp_code_dir(), 'test/data/sofast_common')
 
     # Directory Setup
-    file_dataset = join(base_dir, 'data_expected_facet_ensemble/data.h5')
-    file_measurement = join(base_dir, 'data_measurement/measurement_ensemble.h5')
-
-    # Load data
-    camera = Camera.load_from_hdf(file_dataset)
-    display = DisplayShape.load_from_hdf(file_dataset)
-    orientation = SpatialOrientation.load_from_hdf(file_dataset)
+    file_measurement = join(dir_data_sofast, 'data_measurement/measurement_ensemble.h5')
+    file_camera = join(dir_data_common, 'camera_sofast_downsampled.h5')
+    file_display = join(dir_data_common, 'display_distorted_2d.h5')
+    file_orientation = join(dir_data_common, 'spatial_orientation.h5')
+    file_calibration = join(dir_data_sofast, 'data_measurement/image_calibration.h5')
+    file_facet = join(dir_data_common, 'Facet_lab_6x4.json')
+    file_ensemble = join(dir_data_common, 'Ensemble_lab_6x4.json')
+    file_params = join(dir_data_sofast, 'data_expected_facet_ensemble/data.h5')
+
+    # 1. Load saved facet ensemble Sofast collection data
+    # =================================================
+    camera = Camera.load_from_hdf(file_camera)
+    display = DisplayShape.load_from_hdf(file_display)
+    orientation = SpatialOrientation.load_from_hdf(file_orientation)
     measurement = MeasurementSofastFringe.load_from_hdf(file_measurement)
-    calibration = ImageCalibrationScaling.load_from_hdf(file_dataset)
-
-    # Load sofast params
-    datasets = [
-        'DataSofastInput/sofast_params/mask_hist_thresh',
-        'DataSofastInput/sofast_params/mask_filt_width',
-        'DataSofastInput/sofast_params/mask_filt_thresh',
-        'DataSofastInput/sofast_params/mask_thresh_active_pixels',
-        'DataSofastInput/sofast_params/mask_keep_largest_area',
-        'DataSofastInput/sofast_params/perimeter_refine_axial_search_dist',
-        'DataSofastInput/sofast_params/perimeter_refine_perpendicular_search_dist',
-        'DataSofastInput/sofast_params/facet_corns_refine_step_length',
-        'DataSofastInput/sofast_params/facet_corns_refine_perpendicular_search_dist',
-        'DataSofastInput/sofast_params/facet_corns_refine_frac_keep',
-    ]
-    params = load_hdf5_datasets(datasets, file_dataset)
+    calibration = ImageCalibrationScaling.load_from_hdf(file_calibration)
+    data_ensemble = DefinitionEnsemble.load_from_json(file_ensemble)
+    data_facets = [DefinitionFacet.load_from_json(file_facet)] * data_ensemble.num_facets
+    data_surfaces = [Surface2DParabolic((500.0, 500.0), False, 10)] * data_ensemble.num_facets
+
+    # 2. Save projected sinusoidal fringe images to PNG format
+    # ========================================================
+    fringes = Fringes(measurement.fringe_periods_x, measurement.fringe_periods_y)
+    images = fringes.get_frames(640, 320, 'uint8', [0, 255])
+    dir_save_cur = join(dir_save, '1_images_fringes_projected')
+    ft.create_directories_if_necessary(dir_save_cur)
+    # Save y images
+    for idx_image in range(measurement.num_y_ims):
+        image = images[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'y_{idx_image:02d}.png'), image)
+    # Save x images
+    for idx_image in range(measurement.num_x_ims):
+        image = images[..., measurement.num_y_ims + idx_image]
+        imageio.imwrite(join(dir_save_cur, f'x_{idx_image:02d}.png'), image)
+
+    # 3. Save captured sinusoidal fringe images and mask images to PNG format
+    # =======================================================================
+    dir_save_cur = join(dir_save, '2_images_captured')
+    ft.create_directories_if_necessary(dir_save_cur)
+
+    # Save mask images
+    for idx_image in [0, 1]:
+        image = measurement.mask_images[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'mask_{idx_image:02d}.png'), image)
+    # Save y images
+    for idx_image in range(measurement.num_y_ims):
+        image = measurement.fringe_images_y[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'y_{idx_image:02d}.png'), image)
+    # Save x images
+    for idx_image in range(measurement.num_x_ims):
+        image = measurement.fringe_images_x[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'x_{idx_image:02d}.png'), image)
+
+    # 4. Processes data with Sofast and save processed data to HDF5
+    # =============================================================
+    dir_save_cur = join(dir_save, '3_processed_data')
+    ft.create_directories_if_necessary(dir_save_cur)
 
     # Calibrate measurement
     measurement.calibrate_fringe_images(calibration)
@@ -80,103 +143,61 @@ def example_process_facet_ensemble():
     # Instantiate sofast object
     sofast = ProcessSofastFringe(measurement, orientation, camera, display)
 
-    # Update parameters
-    sofast.params.mask.hist_thresh = params['mask_hist_thresh']
-    sofast.params.mask.filt_width = params['mask_filt_width']
-    sofast.params.mask.filt_thresh = params['mask_filt_thresh']
-    sofast.params.mask.thresh_active_pixels = params['mask_thresh_active_pixels']
-    sofast.params.mask.keep_largest_area = params['mask_keep_largest_area']
-
-    sofast.params.geometry.perimeter_refine_axial_search_dist = params['perimeter_refine_axial_search_dist']
-    sofast.params.geometry.perimeter_refine_perpendicular_search_dist = params[
-        'perimeter_refine_perpendicular_search_dist'
-    ]
-    sofast.params.geometry.facet_corns_refine_step_length = params['facet_corns_refine_step_length']
-    sofast.params.geometry.facet_corns_refine_perpendicular_search_dist = params[
-        'facet_corns_refine_perpendicular_search_dist'
-    ]
-    sofast.params.geometry.facet_corns_refine_frac_keep = params['facet_corns_refine_frac_keep']
-
-    # Load ensemble data
-    datasets = [
-        'DataSofastInput/optic_definition/ensemble/ensemble_perimeter',
-        'DataSofastInput/optic_definition/ensemble/r_facet_ensemble',
-        'DataSofastInput/optic_definition/ensemble/v_centroid_ensemble',
-        'DataSofastInput/optic_definition/ensemble/v_facet_locations',
-    ]
-    ensemble_data = load_hdf5_datasets(datasets, file_dataset)
-    ensemble_data = DefinitionEnsemble(
-        Vxyz(ensemble_data['v_facet_locations']),
-        [Rotation.from_rotvec(r) for r in ensemble_data['r_facet_ensemble']],
-        ensemble_data['ensemble_perimeter'],
-        Vxyz(ensemble_data['v_centroid_ensemble']),
-    )
-
-    facet_data = []
-    for idx in range(len(ensemble_data.r_facet_ensemble)):
-        datasets = [
-            f'DataSofastInput/optic_definition/facet_{idx:03d}/v_centroid_facet',
-            f'DataSofastInput/optic_definition/facet_{idx:03d}/v_facet_corners',
-        ]
-        data = load_hdf5_datasets(datasets, file_dataset)
-        facet_data.append(DefinitionFacet(Vxyz(data['v_facet_corners']), Vxyz(data['v_centroid_facet'])))
-
-    # Load surface data
-    surfaces = []
-    for idx in range(len(facet_data)):
-        datasets = [
-            f'DataSofastInput/surface_params/facet_{idx:03d}/downsample',
-            f'DataSofastInput/surface_params/facet_{idx:03d}/initial_focal_lengths_xy',
-            f'DataSofastInput/surface_params/facet_{idx:03d}/robust_least_squares',
-        ]
-        data = load_hdf5_datasets(datasets, file_dataset)
-        data['robust_least_squares'] = bool(data['robust_least_squares'])
-        surfaces.append(Surface2DParabolic(**data))
+    # Update sofast processing parameters
+    sofast.params = sofast.params.load_from_hdf(file_params, 'DataSofastInput/')
 
     # Process
-    sofast.process_optic_multifacet(facet_data, ensemble_data, surfaces)
-
-    # 3. Log best-fit parabolic focal lengths
-    # =======================================
-    sofast_config = SofastConfiguration()
-    sofast_config.load_sofast_object(sofast)
-    sofast_stats = sofast_config.get_measurement_stats()
-    for stat in sofast_stats:
-        focal_lengths_xy = stat['focal_lengths_parabolic_xy']
-        lt.info(f'Facet {idx:d} xy focal lengths (meters): {focal_lengths_xy[0]:.3f}, {focal_lengths_xy[1]:.3f}')
-
-    # 4. Plot slope magnitude
-    # =======================
-
-    # Get optic representation
-    ensemble: FacetEnsemble = sofast.get_optic()
-
-    # Generate plots
-    figure_control = rcfg.RenderControlFigure(tile_array=(1, 1), tile_square=True)
-    mirror_control = rcm.RenderControlMirror(centroid=True, surface_normals=True, norm_res=1)
-    facet_control = rcf.RenderControlFacet(
-        draw_mirror_curvature=True, mirror_styles=mirror_control, draw_outline=False, draw_surface_normal=True
-    )
-    facet_ensemble_control = rcfe.RenderControlFacetEnsemble(default_style=facet_control, draw_outline=True)
-    axis_control_m = rca.meters()
-
-    # Plot slope map
-    res = 0.002  # meter, make the plot with 2mm spatial resolution
-    clim = 7  # mrad, draw the plot with +/-7mrad scale bars, this mirror has erorrs that extend to about +/-7mrad
-    fig_record = fm.setup_figure(figure_control, axis_control_m, title='')
-    ensemble.plot_orthorectified_slope(res=res, clim=clim, axis=fig_record.axis)
-    fig_record.save(dir_save, 'slope_magnitude', 'png')
-
-    # 5. Plot 3d representation of facet ensemble
-    # ===========================================
-    fig_record = fm.setup_figure_for_3d_data(figure_control, axis_control_m, title='Facet Ensemble')
-    ensemble.draw(fig_record.view, facet_ensemble_control)
-    fig_record.axis.axis('equal')
-    fig_record.save(dir_save, 'facet_ensemble', 'png')
-
-    # 6. Save slope data as HDF5 file
-    # ===============================
-    sofast.save_to_hdf(f'{dir_save}/data_multifacet.h5')
+    sofast.process_optic_multifacet(data_facets, data_ensemble, data_surfaces)
+
+    # Save processed data to HDF5 format
+    sofast.save_to_hdf(join(dir_save_cur, 'data_sofast_processed.h5'))
+
+    # Save measurement statistics to JSON
+    config = SofastConfiguration()
+    config.load_sofast_object(sofast)
+    measurement_stats = config.get_measurement_stats()
+
+    # Save measurement stats as JSON
+    with open(join(dir_save_cur, 'measurement_statistics.json'), 'w', encoding='utf-8') as f:
+        json.dump(measurement_stats, f, indent=3)
+
+    # 5. Generate plot suite and save images files
+    # ============================================
+    dir_save_cur = join(dir_save, '4_processed_output_figures')
+    ft.create_directories_if_necessary(dir_save_cur)
+
+    # Get measured and reference optics
+    ensemble_measured = sofast.get_optic()
+    region = ensemble_measured.facets[0].mirror.region
+    facets = [Facet(MirrorParametric.generate_flat(region)) for _ in range(sofast.num_facets)]
+    ensemble_reference = FacetEnsemble(facets)
+    ensemble_reference.set_facet_positions(data_ensemble.v_facet_locations)
+
+    # Define viewing/illumination geometry
+    v_target_center = Vxyz((0, 0, 100))
+    v_target_normal = Vxyz((0, 0, -1))
+    source = LightSourceSun.from_given_sun_position(Uxyz((0, 0, -1)), resolution=40)
+
+    # Save optic objects
+    plots = StandardPlotOutput()
+    plots.optic_measured = ensemble_measured
+    plots.optic_reference = ensemble_reference
+
+    # Update visualization parameters
+    plots.options_slope_vis.clim = 7
+    plots.options_slope_deviation_vis.clim = 1.5
+    plots.options_ray_trace_vis.enclosed_energy_max_semi_width = 1
+    plots.options_file_output.to_save = True
+    plots.options_file_output.number_in_name = False
+    plots.options_file_output.output_dir = dir_save_cur
+
+    # Define ray trace parameters
+    plots.params_ray_trace.source = source
+    plots.params_ray_trace.v_target_center = v_target_center
+    plots.params_ray_trace.v_target_normal = v_target_normal
+
+    # Create standard output plots
+    plots.plot()
 
 
 if __name__ == '__main__':
diff --git a/example/sofast_fringe/example_process_single_facet.py b/example/sofast_fringe/example_process_single_facet.py
index a2772487a..a94bd8eec 100644
--- a/example/sofast_fringe/example_process_single_facet.py
+++ b/example/sofast_fringe/example_process_single_facet.py
@@ -1,30 +1,64 @@
+"""Module for processing and analyzing SOFAST data for a single facet mirror.
+
+This script performs the following steps:
+1. Load saved single facet SOFAST collection data from an HDF5 file.
+2. Save projected sinusoidal fringe images to PNG format.
+3. Save captured sinusoidal fringe images and mask images to PNG format.
+4. Process data with SOFAST and save processed data to HDF5.
+5. Generate a suite of plots and save image files.
+
+Examples
+--------
+To run the script, simply execute it as a standalone program:
+
+>>> python example_process_single_facet.py
+
+This will perform the processing steps and save the results to the data/output/single_facet directory
+with the following subfolders:
+1_images_fringes_projected - The patterns sent to the display during the SOFAST measurement of the optic.
+2_images_captured - The captured images of the displayed patterns as seen by the SOFAST camera
+3_processed_data - The processed data from SOFAST.
+4_processed_output_figures - The output figure suite from a SOFAST characterization.
+
+Notes
+-----
+- The script assumes that the input data files are located in the specified directories.
+- Chat GPT 40 assisted with the generation of some docstrings in this file.
+"""
+
+import json
 from os.path import join, dirname
 
+import imageio.v3 as imageio
+
 from opencsp.app.sofast.lib.DisplayShape import DisplayShape as Display
 from opencsp.app.sofast.lib.DefinitionFacet import DefinitionFacet
+from opencsp.app.sofast.lib.Fringes import Fringes
 from opencsp.app.sofast.lib.ImageCalibrationScaling import ImageCalibrationScaling
 from opencsp.app.sofast.lib.MeasurementSofastFringe import MeasurementSofastFringe
 from opencsp.app.sofast.lib.ProcessSofastFringe import ProcessSofastFringe as Sofast
+from opencsp.app.sofast.lib.SofastConfiguration import SofastConfiguration
 from opencsp.app.sofast.lib.SpatialOrientation import SpatialOrientation
 from opencsp.common.lib.camera.Camera import Camera
-from opencsp.common.lib.csp.Facet import Facet
+from opencsp.common.lib.csp.LightSourceSun import LightSourceSun
+from opencsp.common.lib.csp.MirrorParametric import MirrorParametric
+from opencsp.common.lib.csp.StandardPlotOutput import StandardPlotOutput
 from opencsp.common.lib.deflectometry.Surface2DParabolic import Surface2DParabolic
+from opencsp.common.lib.geometry.Uxyz import Uxyz
+from opencsp.common.lib.geometry.Vxyz import Vxyz
 from opencsp.common.lib.opencsp_path.opencsp_root_path import opencsp_code_dir
-import opencsp.common.lib.render.figure_management as fm
-import opencsp.common.lib.render_control.RenderControlAxis as rca
-import opencsp.common.lib.render_control.RenderControlFigure as rcfg
 import opencsp.common.lib.tool.file_tools as ft
 import opencsp.common.lib.tool.log_tools as lt
 
 
 def example_process_single_facet():
-    """Performs processing of previously collected Sofast data of single facet mirror.
+    """Performs processing of previously collected SOFAST data of single facet mirror.
 
-    1. Load saved single facet Sofast collection data
-    2. Processes data with Sofast
-    3. Log best-fit parabolic focal lengths
-    4. Plot slope magnitude
-    5. Save slope data as HDF5 file
+    1. Load saved single facet SOFAST collection data from HDF5 file
+    2. Save projected sinusoidal fringe images to PNG format
+    3. Save captured sinusoidal fringe images and mask images to PNG format
+    4. Processes data with SOFAST and save processed data to HDF5
+    5. Generate plot suite and save images files
     """
     # General setup
     # =============
@@ -34,7 +68,7 @@ def example_process_single_facet():
     ft.create_directories_if_necessary(dir_save)
 
     # Set up logger
-    lt.logger(join(dir_save, 'log.txt'), lt.log.INFO)
+    lt.logger(join(dir_save, 'log.txt'), lt.log.WARN)
 
     # Define sample data directory
     dir_data_sofast = join(opencsp_code_dir(), 'test/data/sofast_fringe')
@@ -48,6 +82,19 @@ def example_process_single_facet():
     file_calibration = join(dir_data_sofast, 'data_measurement/image_calibration.h5')
     file_facet = join(dir_data_common, 'Facet_NSTTF.json')
 
+    # Or, optionally, process high-resolution  SOFAST sample data by uncommenting the lines below
+    #
+    # dir_data_sofast = 'path/to/sample_data/sofast/sandia_lab/sofast_fringe'
+    # dir_data_common = 'path/to/sample_data/sofast/sandia_lab/sofast_common'
+    # file_measurement = join(dir_data_sofast, 'data_measurement/facet_landscape_rectangular.h5')
+    # file_camera = join(dir_data_common, 'camera_sofast_optics_lab_landscape.h5')
+    # file_display = join(dir_data_common, 'display_shape_optics_lab_landscape_rectangular_distorted_2d_11x11.h5')
+    # file_orientation = join(dir_data_common, 'spatial_orientation_optics_lab_landscape.h5')
+    # file_calibration = join(
+    #     dir_data_sofast, 'data_measurement/image_calibration_scaling_nominal_optics_lab_landscape.h5'
+    # )
+    # file_facet = join(dir_data_common, 'facet_NSTTF.json')
+
     # 1. Load saved single facet Sofast collection data
     # =================================================
     camera = Camera.load_from_hdf(file_camera)
@@ -57,8 +104,43 @@ def example_process_single_facet():
     calibration = ImageCalibrationScaling.load_from_hdf(file_calibration)
     facet_data = DefinitionFacet.load_from_json(file_facet)
 
-    # 2. Process data with Sofast
-    # ===========================
+    # 2. Save projected sinusoidal fringe images to PNG format
+    # ========================================================
+    fringes = Fringes(measurement.fringe_periods_x, measurement.fringe_periods_y)
+    images = fringes.get_frames(640, 320, 'uint8', [0, 255])
+    dir_save_cur = join(dir_save, '1_images_fringes_projected')
+    ft.create_directories_if_necessary(dir_save_cur)
+    # Save y images
+    for idx_image in range(measurement.num_y_ims):
+        image = images[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'y_{idx_image:02d}.png'), image)
+    # Save x images
+    for idx_image in range(measurement.num_x_ims):
+        image = images[..., measurement.num_y_ims + idx_image]
+        imageio.imwrite(join(dir_save_cur, f'x_{idx_image:02d}.png'), image)
+
+    # 3. Save captured sinusoidal fringe images and mask images to PNG format
+    # =======================================================================
+    dir_save_cur = join(dir_save, '2_images_captured')
+    ft.create_directories_if_necessary(dir_save_cur)
+
+    # Save mask images
+    for idx_image in [0, 1]:
+        image = measurement.mask_images[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'mask_{idx_image:02d}.png'), image)
+    # Save y images
+    for idx_image in range(measurement.num_y_ims):
+        image = measurement.fringe_images_y[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'y_{idx_image:02d}.png'), image)
+    # Save x images
+    for idx_image in range(measurement.num_x_ims):
+        image = measurement.fringe_images_x[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'x_{idx_image:02d}.png'), image)
+
+    # 4. Processes data with Sofast and save processed data to HDF5
+    # =============================================================
+    dir_save_cur = join(dir_save, '3_processed_data')
+    ft.create_directories_if_necessary(dir_save_cur)
 
     # Define surface definition (parabolic surface)
     surface = Surface2DParabolic(initial_focal_lengths_xy=(300.0, 300.0), robust_least_squares=True, downsample=10)
@@ -72,30 +154,59 @@ def example_process_single_facet():
     # Process
     sofast.process_optic_singlefacet(facet_data, surface)
 
-    # 3. Log best-fit parabolic focal lengths
-    # =======================================
-    surf_coefs = sofast.data_calculation_facet[0].surf_coefs_facet
-    focal_lengths_xy = [1 / 4 / surf_coefs[2], 1 / 4 / surf_coefs[5]]
-    lt.info(f'Facet xy focal lengths (meters): ' f'{focal_lengths_xy[0]:.3f}, {focal_lengths_xy[1]:.3f}')
+    # Save processed data to HDF5 format
+    sofast.save_to_hdf(join(dir_save_cur, 'data_sofast_processed.h5'))
+
+    # Save measurement statistics to JSON
+    config = SofastConfiguration()
+    config.load_sofast_object(sofast)
+    measurement_stats = config.get_measurement_stats()
+
+    # Save measurement stats as JSON
+    with open(join(dir_save_cur, 'measurement_statistics.json'), 'w', encoding='utf-8') as f:
+        json.dump(measurement_stats, f, indent=3)
+
+    # 5. Generate plot suite and save images files
+    # ============================================
+    dir_save_cur = join(dir_save, '4_processed_output_figures')
+    ft.create_directories_if_necessary(dir_save_cur)
+
+    # Get measured and reference optics
+    mirror_measured = sofast.get_optic().mirror.no_parent_copy()
+    mirror_reference = MirrorParametric.generate_symmetric_paraboloid(100, mirror_measured.region)
+
+    # Define viewing/illumination geometry
+    v_target_center = Vxyz((0, 0, 100))
+    v_target_normal = Vxyz((0, 0, -1))
+    source = LightSourceSun.from_given_sun_position(Uxyz((0, 0, -1)), resolution=40)
+
+    # Save optic objects
+    plots = StandardPlotOutput()
+    plots.optic_measured = mirror_measured
+    plots.optic_reference = mirror_reference
+
+    # Update visualization parameters
+    plots.options_slope_vis.clim = 7
+    plots.options_slope_vis.resolution = 0.001
+
+    plots.options_slope_deviation_vis.clim = 1.5
+    plots.options_slope_deviation_vis.resolution = 0.001
 
-    # 4. Plot slope magnitude
-    # =======================
+    plots.options_curvature_vis.resolution = 0.001
 
-    # Get optic representation
-    facet: Facet = sofast.get_optic()
+    plots.options_ray_trace_vis.enclosed_energy_max_semi_width = 1
 
-    # Generate plots
-    figure_control = rcfg.RenderControlFigure(tile_array=(1, 1), tile_square=True)
-    axis_control_m = rca.meters()
+    plots.options_file_output.to_save = True
+    plots.options_file_output.number_in_name = False
+    plots.options_file_output.output_dir = dir_save_cur
 
-    # Plot slope map
-    fig_record = fm.setup_figure(figure_control, axis_control_m, title='')
-    facet.plot_orthorectified_slope(res=0.002, clim=7, axis=fig_record.axis)
-    fig_record.save(dir_save, 'slope_magnitude', 'png')
+    # Define ray trace parameters
+    plots.params_ray_trace.source = source
+    plots.params_ray_trace.v_target_center = v_target_center
+    plots.params_ray_trace.v_target_normal = v_target_normal
 
-    # 5. Save slope data as HDF5 file
-    # ===============================
-    sofast.save_to_hdf(f'{dir_save}/data_singlefacet.h5')
+    # Create standard output plots
+    plots.plot()
 
 
 if __name__ == '__main__':
diff --git a/example/sofast_fringe/example_process_undefined_shape.py b/example/sofast_fringe/example_process_undefined_shape.py
index 45efa07f0..1c585fcc4 100644
--- a/example/sofast_fringe/example_process_undefined_shape.py
+++ b/example/sofast_fringe/example_process_undefined_shape.py
@@ -1,29 +1,65 @@
+"""Module for processing and analyzing SOFAST data for a single facet mirror of unknown shape.
+
+This script performs the following steps:
+1. Load saved single facet SOFAST collection data from an HDF5 file.
+2. Save projected sinusoidal fringe images to PNG format.
+3. Save captured sinusoidal fringe images and mask images to PNG format.
+4. Process data with SOFAST and save processed data to HDF5.
+5. Generate a suite of plots and save image files.
+
+Examples
+--------
+To run the script, simply execute it as a standalone program:
+
+>>> python example_process_undefined_shape.py
+
+This will perform the processing steps and save the results to the data/output/single_facet directory
+with the following subfolders:
+1_images_fringes_projected - The patterns sent to the display during the SOFAST measurement of the optic.
+2_images_captured - The captured images of the displayed patterns as seen by the SOFAST camera
+3_processed_data - The processed data from SOFAST.
+4_processed_output_figures - The output figure suite from a SOFAST characterization.
+
+Notes
+-----
+- The script assumes that the input data files are located in the specified directories.
+- Chat GPT 40 assisted with the generation of some docstrings in this file.
+"""
+
+import json
 from os.path import join, dirname
+import json
 
+import imageio.v3 as imageio
+
+from opencsp.app.sofast.lib.Fringes import Fringes
 from opencsp.app.sofast.lib.ImageCalibrationScaling import ImageCalibrationScaling
 from opencsp.app.sofast.lib.MeasurementSofastFringe import MeasurementSofastFringe
 from opencsp.app.sofast.lib.ProcessSofastFringe import ProcessSofastFringe as Sofast
+from opencsp.app.sofast.lib.SofastConfiguration import SofastConfiguration
 from opencsp.app.sofast.lib.DisplayShape import DisplayShape as Display
 from opencsp.app.sofast.lib.SpatialOrientation import SpatialOrientation
 from opencsp.common.lib.camera.Camera import Camera
-from opencsp.common.lib.csp.Facet import Facet
+from opencsp.common.lib.csp.LightSourceSun import LightSourceSun
+from opencsp.common.lib.csp.MirrorParametric import MirrorParametric
+from opencsp.common.lib.csp.StandardPlotOutput import StandardPlotOutput
 from opencsp.common.lib.deflectometry.Surface2DParabolic import Surface2DParabolic
+from opencsp.common.lib.geometry.Uxyz import Uxyz
+from opencsp.common.lib.geometry.Vxyz import Vxyz
 from opencsp.common.lib.opencsp_path.opencsp_root_path import opencsp_code_dir
-import opencsp.common.lib.render.figure_management as fm
-import opencsp.common.lib.render_control.RenderControlAxis as rca
-import opencsp.common.lib.render_control.RenderControlFigure as rcfg
 import opencsp.common.lib.tool.file_tools as ft
 import opencsp.common.lib.tool.log_tools as lt
 
 
 def example_process_undefined_shape_facet():
-    """Performs processing of previously collected Sofast data of single facet mirror:
-
-    1. Load saved single facet Sofast collection data
-    2. Processes data with Sofast (without using facet file)
-    3. Log best-fit parabolic focal lengths
-    4. Plot slope magnitude
-    5. Save slope data as HDF5 file
+    """Performs processing of previously collected SOFAST data of single facet mirror
+    with an unknown shape.
+
+    1. Load saved single facet SOFAST collection data from HDF5 file
+    2. Save projected sinusoidal fringe images to PNG format
+    3. Save captured sinusoidal fringe images and mask images to PNG format
+    4. Processes data with SOFAST and save processed data to HDF5
+    5. Generate plot suite and save images files
     """
     # General setup
     # =============
@@ -54,8 +90,43 @@ def example_process_undefined_shape_facet():
     measurement = MeasurementSofastFringe.load_from_hdf(file_measurement)
     calibration = ImageCalibrationScaling.load_from_hdf(file_calibration)
 
-    # 2. Process data with Sofast
-    # ===========================
+    # 2. Save projected sinusoidal fringe images to PNG format
+    # ========================================================
+    fringes = Fringes(measurement.fringe_periods_x, measurement.fringe_periods_y)
+    images = fringes.get_frames(640, 320, 'uint8', [0, 255])
+    dir_save_cur = join(dir_save, '1_images_fringes_projected')
+    ft.create_directories_if_necessary(dir_save_cur)
+    # Save y images
+    for idx_image in range(measurement.num_y_ims):
+        image = images[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'y_{idx_image:02d}.png'), image)
+    # Save x images
+    for idx_image in range(measurement.num_x_ims):
+        image = images[..., measurement.num_y_ims + idx_image]
+        imageio.imwrite(join(dir_save_cur, f'x_{idx_image:02d}.png'), image)
+
+    # 3. Save captured sinusoidal fringe images and mask images to PNG format
+    # =======================================================================
+    dir_save_cur = join(dir_save, '2_images_captured')
+    ft.create_directories_if_necessary(dir_save_cur)
+
+    # Save mask images
+    for idx_image in [0, 1]:
+        image = measurement.mask_images[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'mask_{idx_image:02d}.png'), image)
+    # Save y images
+    for idx_image in range(measurement.num_y_ims):
+        image = measurement.fringe_images_y[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'y_{idx_image:02d}.png'), image)
+    # Save x images
+    for idx_image in range(measurement.num_x_ims):
+        image = measurement.fringe_images_x[..., idx_image]
+        imageio.imwrite(join(dir_save_cur, f'x_{idx_image:02d}.png'), image)
+
+    # 4. Processes data with Sofast and save processed data to HDF5
+    # =============================================================
+    dir_save_cur = join(dir_save, '3_processed_data')
+    ft.create_directories_if_necessary(dir_save_cur)
 
     # Define surface definition (parabolic surface)
     surface = Surface2DParabolic(initial_focal_lengths_xy=(300.0, 300.0), robust_least_squares=True, downsample=10)
@@ -65,35 +136,57 @@ def example_process_undefined_shape_facet():
 
     # Instantiate sofast object
     sofast = Sofast(measurement, orientation, camera, display)
-    sofast.params.mask_keep_largest_area = True
+    sofast.params.mask.keep_largest_area = True
 
     # Process
     sofast.process_optic_undefined(surface)
 
-    # 3. Log best-fit parabolic focal lengths
-    # =======================================
-    surf_coefs = sofast.data_calculation_facet[0].surf_coefs_facet
-    focal_lengths_xy = [1 / 4 / surf_coefs[2], 1 / 4 / surf_coefs[5]]
-    lt.info(f'Facet xy focal lengths (meters): ' f'{focal_lengths_xy[0]:.3f}, {focal_lengths_xy[1]:.3f}')
-
-    # 4. Plot slope magnitude
-    # =======================
-
-    # Get optic representation
-    facet: Facet = sofast.get_optic()
-
-    # Generate plots
-    figure_control = rcfg.RenderControlFigure(tile_array=(1, 1), tile_square=True)
-    axis_control_m = rca.meters()
-
-    # Plot slope map
-    fig_record = fm.setup_figure(figure_control, axis_control_m, title='')
-    facet.plot_orthorectified_slope(res=0.002, clim=7, axis=fig_record.axis)
-    fig_record.save(dir_save, 'slope_magnitude', 'png')
-
-    # 5. Save slope data as HDF5 file
-    # ===============================
-    sofast.save_to_hdf(f'{dir_save}/data_undefined.h5')
+    # Save processed data to HDF5 format
+    sofast.save_to_hdf(join(dir_save_cur, 'data_sofast_processed.h5'))
+
+    # Save measurement statistics to JSON
+    config = SofastConfiguration()
+    config.load_sofast_object(sofast)
+    measurement_stats = config.get_measurement_stats()
+
+    # Save measurement stats as JSON
+    with open(join(dir_save_cur, 'measurement_statistics.json'), 'w', encoding='utf-8') as f:
+        json.dump(measurement_stats, f, indent=3)
+
+    # 5. Generate plot suite and save images files
+    # ============================================
+    dir_save_cur = join(dir_save, '4_processed_output_figures')
+    ft.create_directories_if_necessary(dir_save_cur)
+
+    # Get measured and reference optics
+    mirror_measured = sofast.get_optic().mirror.no_parent_copy()
+    mirror_reference = MirrorParametric.generate_symmetric_paraboloid(100, mirror_measured.region)
+
+    # Define viewing/illumination geometry
+    v_target_center = Vxyz((0, 0, 100))
+    v_target_normal = Vxyz((0, 0, -1))
+    source = LightSourceSun.from_given_sun_position(Uxyz((0, 0, -1)), resolution=40)
+
+    # Save optic objects
+    plots = StandardPlotOutput()
+    plots.optic_measured = mirror_measured
+    plots.optic_reference = mirror_reference
+
+    # Update visualization parameters
+    plots.options_slope_vis.clim = 7
+    plots.options_slope_deviation_vis.clim = 1.5
+    plots.options_ray_trace_vis.enclosed_energy_max_semi_width = 1
+    plots.options_file_output.to_save = True
+    plots.options_file_output.number_in_name = False
+    plots.options_file_output.output_dir = dir_save_cur
+
+    # Define ray trace parameters
+    plots.params_ray_trace.source = source
+    plots.params_ray_trace.v_target_center = v_target_center
+    plots.params_ray_trace.v_target_normal = v_target_normal
+
+    # Create standard output plots
+    plots.plot()
 
 
 if __name__ == '__main__':
diff --git a/opencsp/app/sofast/lib/DefinitionEnsemble.py b/opencsp/app/sofast/lib/DefinitionEnsemble.py
index eea2848b8..bc22c9f19 100644
--- a/opencsp/app/sofast/lib/DefinitionEnsemble.py
+++ b/opencsp/app/sofast/lib/DefinitionEnsemble.py
@@ -141,7 +141,7 @@ def save_to_hdf(self, file: str, prefix: str = '') -> None:
         hdf5_tools.save_hdf5_datasets(data, datasets, file)
 
     @classmethod
-    def load_from_hdf(cls, file: str, prefix: str) -> 'DefinitionEnsemble':
+    def load_from_hdf(cls, file: str, prefix: str = '') -> 'DefinitionEnsemble':
         """Loads DefinitionEnsemble object from given file.  Data is stored in PREFIX + DefinitionEnsemble/...
 
         Parameters
diff --git a/opencsp/app/sofast/lib/ParamsSofastFringe.py b/opencsp/app/sofast/lib/ParamsSofastFringe.py
index fe06d7a73..30bf21ffb 100644
--- a/opencsp/app/sofast/lib/ParamsSofastFringe.py
+++ b/opencsp/app/sofast/lib/ParamsSofastFringe.py
@@ -51,8 +51,8 @@ def load_from_hdf(cls, file: str, prefix: str = ''):
             Default is empty string ''.
         """
         # Load geometry parameters
-        params_mask = ParamsMaskCalculation.load_from_hdf(file, prefix + '/ParamsSofastFringe/')
-        params_geometry = ParamsOpticGeometry.load_from_hdf(file, prefix + '/ParamsSofastFringe/')
+        params_mask = ParamsMaskCalculation.load_from_hdf(file, prefix + 'ParamsSofastFringe/')
+        params_geometry = ParamsOpticGeometry.load_from_hdf(file, prefix + 'ParamsSofastFringe/')
 
         # Load sofast parameters
         data = {'geometry': params_geometry, 'mask': params_mask}
diff --git a/opencsp/app/sofast/test/test_image_processing.py b/opencsp/app/sofast/test/test_image_processing.py
index 1fe032780..7880c4e24 100644
--- a/opencsp/app/sofast/test/test_image_processing.py
+++ b/opencsp/app/sofast/test/test_image_processing.py
@@ -138,8 +138,8 @@ def test_refine_facet_corners(self):
         """Tests image_processing.refine_facet_corners()"""
         # Load edge data
         datasets = [
-            'DataSofastCalculation/image_processing/general/v_edges_image',
-            'DataSofastInput/optic_definition/ensemble/r_facet_ensemble',
+            'DataSofastCalculation/general/CalculationImageProcessingGeneral/v_edges_image',
+            'DataSofastInput/optic_definition/DefinitionEnsemble/r_facet_ensemble',
         ]
         data = load_hdf5_datasets(datasets, self.data_file_multi)
         num_facets = data['r_facet_ensemble'].shape[0]
@@ -151,9 +151,9 @@ def test_refine_facet_corners(self):
         for facet_idx in range(num_facets):
             # Get sofast parameters
             datasets = [
-                'DataSofastInput/sofast_params/facet_corns_refine_step_length',
-                'DataSofastInput/sofast_params/facet_corns_refine_perpendicular_search_dist',
-                'DataSofastInput/sofast_params/facet_corns_refine_frac_keep',
+                'DataSofastInput/ParamsSofastFringe/ParamsOpticGeometry/facet_corns_refine_step_length',
+                'DataSofastInput/ParamsSofastFringe/ParamsOpticGeometry/facet_corns_refine_perpendicular_search_dist',
+                'DataSofastInput/ParamsSofastFringe/ParamsOpticGeometry/facet_corns_refine_frac_keep',
             ]
             data = load_hdf5_datasets(datasets, self.data_file_multi)
             args = [
@@ -164,9 +164,9 @@ def test_refine_facet_corners(self):
 
             # Load input and expected output data
             datasets = [
-                f'DataSofastCalculation/image_processing/facet_{facet_idx:03d}/loop_facet_image_refine',
-                f'DataSofastCalculation/image_processing/facet_{facet_idx:03d}/v_facet_corners_image_exp',
-                f'DataSofastCalculation/image_processing/facet_{facet_idx:03d}/v_facet_centroid_image_exp',
+                f'DataSofastCalculation/facet/facet_{facet_idx:03d}/CalculationImageProcessingFacet/loop_facet_image_refine',
+                f'DataSofastCalculation/facet/facet_{facet_idx:03d}/CalculationImageProcessingFacet/v_facet_corners_image_exp',
+                f'DataSofastCalculation/facet/facet_{facet_idx:03d}/CalculationImageProcessingFacet/v_facet_centroid_image_exp',
             ]
             data = load_hdf5_datasets(datasets, self.data_file_multi)
             v_facet_corners_image_exp = Vxy(data['v_facet_corners_image_exp'])
diff --git a/opencsp/app/sofast/test/test_integration_multi_facet.py b/opencsp/app/sofast/test/test_integration_multi_facet.py
index fcdb71f35..ecee71cb6 100644
--- a/opencsp/app/sofast/test/test_integration_multi_facet.py
+++ b/opencsp/app/sofast/test/test_integration_multi_facet.py
@@ -1,10 +1,12 @@
 """Integration test. Testing processing of a 'multi_facet' type optic.
+
+To update the test data, simply run this test and replace the input SOFAST
+dataset HDF5 file with the output HDF5 file created when running this test.
 """
 
 import os
 import unittest
 
-from scipy.spatial.transform import Rotation
 import numpy as np
 
 from opencsp.app.sofast.lib.DisplayShape import DisplayShape
@@ -16,8 +18,8 @@
 from opencsp.app.sofast.lib.SpatialOrientation import SpatialOrientation
 from opencsp.common.lib.camera.Camera import Camera
 from opencsp.common.lib.deflectometry.Surface2DParabolic import Surface2DParabolic
-from opencsp.common.lib.geometry.Vxyz import Vxyz
 from opencsp.common.lib.tool.hdf5_tools import load_hdf5_datasets
+import opencsp.common.lib.tool.file_tools as ft
 from opencsp.common.lib.opencsp_path.opencsp_root_path import opencsp_code_dir
 
 
@@ -32,6 +34,10 @@ def setUpClass(cls, base_dir: str | None = None):
             Sets base directory. If None, uses 'data' directory in directory
             contianing file, by default None
         """
+        # Define save directory
+        cls.dir_save = os.path.join(os.path.dirname(__file__), 'data/output/sofast_ensemble')
+        ft.create_directories_if_necessary(cls.dir_save)
+
         # Get test data location
         if base_dir is None:
             base_dir = os.path.join(opencsp_code_dir(), 'test/data/sofast_fringe')
@@ -46,21 +52,13 @@ def setUpClass(cls, base_dir: str | None = None):
         orientation = SpatialOrientation.load_from_hdf(file_dataset)
         measurement = MeasurementSofastFringe.load_from_hdf(file_measurement)
         calibration = ImageCalibrationScaling.load_from_hdf(file_dataset)
-
-        # Load sofast params
-        datasets = [
-            'DataSofastInput/sofast_params/mask_hist_thresh',
-            'DataSofastInput/sofast_params/mask_filt_width',
-            'DataSofastInput/sofast_params/mask_filt_thresh',
-            'DataSofastInput/sofast_params/mask_thresh_active_pixels',
-            'DataSofastInput/sofast_params/mask_keep_largest_area',
-            'DataSofastInput/sofast_params/perimeter_refine_axial_search_dist',
-            'DataSofastInput/sofast_params/perimeter_refine_perpendicular_search_dist',
-            'DataSofastInput/sofast_params/facet_corns_refine_step_length',
-            'DataSofastInput/sofast_params/facet_corns_refine_perpendicular_search_dist',
-            'DataSofastInput/sofast_params/facet_corns_refine_frac_keep',
-        ]
-        params = load_hdf5_datasets(datasets, file_dataset)
+        data_ensemble = DefinitionEnsemble.load_from_hdf(file_dataset, 'DataSofastInput/optic_definition/')
+        data_facets = []
+        data_surfaces = []
+        for idx_facet in range(data_ensemble.num_facets):
+            prefix = f'DataSofastInput/optic_definition/facet_{idx_facet:03d}/'
+            data_surfaces.append(Surface2DParabolic.load_from_hdf(file_dataset, prefix))
+            data_facets.append(DefinitionFacet.load_from_hdf(file_dataset, prefix))
 
         # Calibrate measurement
         measurement.calibrate_fringe_images(calibration)
@@ -68,72 +66,25 @@ def setUpClass(cls, base_dir: str | None = None):
         # Instantiate sofast object
         sofast = ProcessSofastFringe(measurement, orientation, camera, display)
 
-        # Update parameters
-        sofast.params.mask.hist_thresh = params['mask_hist_thresh']
-        sofast.params.mask.filt_width = params['mask_filt_width']
-        sofast.params.mask.filt_thresh = params['mask_filt_thresh']
-        sofast.params.mask.thresh_active_pixels = params['mask_thresh_active_pixels']
-        sofast.params.mask.keep_largest_area = params['mask_keep_largest_area']
-
-        sofast.params.geometry.perimeter_refine_axial_search_dist = params['perimeter_refine_axial_search_dist']
-        sofast.params.geometry.perimeter_refine_perpendicular_search_dist = params[
-            'perimeter_refine_perpendicular_search_dist'
-        ]
-        sofast.params.geometry.facet_corns_refine_step_length = params['facet_corns_refine_step_length']
-        sofast.params.geometry.facet_corns_refine_perpendicular_search_dist = params[
-            'facet_corns_refine_perpendicular_search_dist'
-        ]
-        sofast.params.geometry.facet_corns_refine_frac_keep = params['facet_corns_refine_frac_keep']
-
-        # Load array data
-        datasets = [
-            'DataSofastInput/optic_definition/ensemble/ensemble_perimeter',
-            'DataSofastInput/optic_definition/ensemble/r_facet_ensemble',
-            'DataSofastInput/optic_definition/ensemble/v_centroid_ensemble',
-            'DataSofastInput/optic_definition/ensemble/v_facet_locations',
-        ]
-        ensemble_data = load_hdf5_datasets(datasets, file_dataset)
-        ensemble_data = DefinitionEnsemble(
-            Vxyz(ensemble_data['v_facet_locations']),
-            [Rotation.from_rotvec(r) for r in ensemble_data['r_facet_ensemble']],
-            ensemble_data['ensemble_perimeter'],
-            Vxyz(ensemble_data['v_centroid_ensemble']),
-        )
-
-        # Load facet data
-        facet_data = []
-        for idx in range(len(ensemble_data.r_facet_ensemble)):
-            datasets = [
-                f'DataSofastInput/optic_definition/facet_{idx:03d}/v_centroid_facet',
-                f'DataSofastInput/optic_definition/facet_{idx:03d}/v_facet_corners',
-            ]
-            data = load_hdf5_datasets(datasets, file_dataset)
-            facet_data.append(DefinitionFacet(Vxyz(data['v_facet_corners']), Vxyz(data['v_centroid_facet'])))
-
-        # Load surface data
-        surfaces = []
-        for idx in range(len(facet_data)):
-            datasets = [
-                f'DataSofastInput/surface_params/facet_{idx:03d}/downsample',
-                f'DataSofastInput/surface_params/facet_{idx:03d}/initial_focal_lengths_xy',
-                f'DataSofastInput/surface_params/facet_{idx:03d}/robust_least_squares',
-            ]
-            data = load_hdf5_datasets(datasets, file_dataset)
-            data['robust_least_squares'] = bool(data['robust_least_squares'])
-            surfaces.append(Surface2DParabolic(**data))
+        # Update sofast processing parameters
+        sofast.params = sofast.params.load_from_hdf(file_dataset, 'DataSofastInput/')
 
         # Run SOFAST
-        sofast.process_optic_multifacet(facet_data, ensemble_data, surfaces)
+        sofast.process_optic_multifacet(data_facets, data_ensemble, data_surfaces)
 
         # Store data
-        cls.data_test = {'slopes_facet_xy': [], 'surf_coefs_facet': []}
+        cls.data_test = {'slopes_facet_xy': [], 'surf_coefs_facet': [], 'facet_pointing': []}
 
         cls.num_facets = sofast.num_facets
         cls.file_dataset = file_dataset
+        cls.sofast = sofast
 
         for idx in range(sofast.num_facets):
             cls.data_test['slopes_facet_xy'].append(sofast.data_calculation_facet[idx].slopes_facet_xy)
             cls.data_test['surf_coefs_facet'].append(sofast.data_calculation_facet[idx].surf_coefs_facet)
+            cls.data_test['facet_pointing'].append(
+                sofast.data_calculation_ensemble[idx].v_facet_pointing_ensemble.data.squeeze()
+            )
 
     def test_slope(self):
         for idx in range(self.num_facets):
@@ -142,7 +93,7 @@ def test_slope(self):
                 data_calc = self.data_test['slopes_facet_xy'][idx]
 
                 # Get expected data
-                datasets = [f'DataSofastCalculation/facet/facet_{idx:03d}/slopes_facet_xy']
+                datasets = [f'DataSofastCalculation/facet/facet_{idx:03d}/SlopeSolverData/slopes_facet_xy']
                 data = load_hdf5_datasets(datasets, self.file_dataset)
 
                 # Test
@@ -155,12 +106,30 @@ def test_surf_coefs(self):
                 data_calc = self.data_test['surf_coefs_facet'][idx]
 
                 # Get expected data
-                datasets = [f'DataSofastCalculation/facet/facet_{idx:03d}/surf_coefs_facet']
+                datasets = [f'DataSofastCalculation/facet/facet_{idx:03d}/SlopeSolverData/surf_coefs_facet']
                 data = load_hdf5_datasets(datasets, self.file_dataset)
 
                 # Test
                 np.testing.assert_allclose(data['surf_coefs_facet'], data_calc, atol=1e-8, rtol=0)
 
+    def test_facet_pointing(self):
+        for idx in range(self.num_facets):
+            with self.subTest(i=idx):
+                # Get calculated data
+                data_calc = self.data_test['facet_pointing'][idx]
+
+                # Get expected data
+                datasets = [
+                    f'DataSofastCalculation/facet/facet_{idx:03d}/CalculationEnsemble/v_facet_pointing_ensemble'
+                ]
+                data = load_hdf5_datasets(datasets, self.file_dataset)
+
+                # Test
+                np.testing.assert_allclose(data['v_facet_pointing_ensemble'], data_calc, atol=1e-8, rtol=0)
+
+    def test_save_as_hdf5(self):
+        self.sofast.save_to_hdf(os.path.join(self.dir_save, 'sofast_processed_data_ensemble.h5'))
+
 
 if __name__ == '__main__':
     unittest.main()
diff --git a/opencsp/common/lib/csp/FacetEnsemble.py b/opencsp/common/lib/csp/FacetEnsemble.py
index 797e857c7..bfc8632da 100644
--- a/opencsp/common/lib/csp/FacetEnsemble.py
+++ b/opencsp/common/lib/csp/FacetEnsemble.py
@@ -192,7 +192,7 @@ def draw(
 
     def set_facet_transform_list(self, transformations: list[TransformXYZ]):
         """
-        Combines the `set_facet_positions` and `set_facet_canting` functions into a single action.
+        Combines the `set_facet_positions` and `set_facet_cantings` functions into a single action.
         """
         for transformation, facet in zip(transformations, self.facets):
             facet._self_to_parent_transform = transformation
@@ -231,7 +231,7 @@ def set_facet_positions(self, positions: Pxyz):
             pos: Pxyz
             facet._self_to_parent_transform = TransformXYZ.from_V(pos)
 
-    def set_facet_canting(self, canting_rotations: list[Rotation]):
+    def set_facet_cantings(self, canting_rotations: list[Rotation]):
         """
         Set the canting rotations of the facets relative to the ensemble.
         This function updates the canting rotations of the facets in the
diff --git a/opencsp/common/lib/csp/HeliostatAbstract.py b/opencsp/common/lib/csp/HeliostatAbstract.py
index bbc5bb1bb..92a4163f3 100644
--- a/opencsp/common/lib/csp/HeliostatAbstract.py
+++ b/opencsp/common/lib/csp/HeliostatAbstract.py
@@ -221,8 +221,8 @@ def set_tracking_configuration(self, aimpoint: Pxyz, location_lon_lat: Iterable,
     def set_facet_positions(self, positions: Pxyz):
         self.facet_ensemble.set_facet_positions(positions)
 
-    def set_facet_canting(self, canting_rotations: list[Rotation]):
-        self.facet_ensemble.set_facet_canting(canting_rotations)
+    def set_facet_cantings(self, canting_rotations: list[Rotation]):
+        self.facet_ensemble.set_facet_cantings(canting_rotations)
 
     # TODO TJL:make this work and make it faster
     def set_canting_from_equation(self, func: FunctionXYContinuous) -> None:
@@ -272,7 +272,7 @@ def set_canting_from_equation(self, func: FunctionXYContinuous) -> None:
 
             facet_canting_rotations.append(canting)
 
-        self.facet_ensemble.set_facet_canting(facet_canting_rotations)
+        self.facet_ensemble.set_facet_cantings(facet_canting_rotations)
 
     # RENDERING
 
diff --git a/opencsp/common/lib/test/test_MirrorOutput.py b/opencsp/common/lib/test/test_MirrorOutput.py
index 1548cc4b5..d1afdc540 100644
--- a/opencsp/common/lib/test/test_MirrorOutput.py
+++ b/opencsp/common/lib/test/test_MirrorOutput.py
@@ -129,7 +129,7 @@ def setUp(self):
             tilt_left * tilt_down,
             tilt_right * tilt_down,
         ]
-        fe2x2.set_facet_canting(fe_2x2_canting_rotations)
+        fe2x2.set_facet_cantings(fe_2x2_canting_rotations)
 
         self.h2x2 = HeliostatAzEl(fe2x2, name='Simple 2x2 Heliostat')
         self.h2x2_title = 'Heliostat with Parametrically Defined Facets'
diff --git a/opencsp/common/lib/test/test_RayTraceOutput.py b/opencsp/common/lib/test/test_RayTraceOutput.py
index 241de57cf..70bf749d0 100644
--- a/opencsp/common/lib/test/test_RayTraceOutput.py
+++ b/opencsp/common/lib/test/test_RayTraceOutput.py
@@ -130,7 +130,7 @@ def setUp(self):
         self.fe2x2 = FacetEnsemble(self.h2x2_facets)
         fe2x2_positions = Pxyz([[-1.1, 1.1, -1.1, 1.1], [1.6, 1.6, -1.6, -1.6], [0, 0, 0, 0]])
         self.fe2x2.set_facet_positions(fe2x2_positions)
-        self.fe2x2.set_facet_canting(self.h2x2_canting)
+        self.fe2x2.set_facet_cantings(self.h2x2_canting)
         self.h2x2 = HeliostatAzEl(self.fe2x2, 'Simple 2x2 Heliostat')
         self.h2x2.pivot = 0
         self.h2x2_title = 'Heliostat with Parametrically Defined Facets'
diff --git a/opencsp/test/data/sofast_fringe/data_expected_facet_ensemble/data.h5 b/opencsp/test/data/sofast_fringe/data_expected_facet_ensemble/data.h5
index 3d120ceec..195f7af9b 100644
Binary files a/opencsp/test/data/sofast_fringe/data_expected_facet_ensemble/data.h5 and b/opencsp/test/data/sofast_fringe/data_expected_facet_ensemble/data.h5 differ