diff --git a/src/roodmus/analysis/plot_alignment.py b/src/roodmus/analysis/plot_alignment.py
index a9b2585..c00bcfd 100644
--- a/src/roodmus/analysis/plot_alignment.py
+++ b/src/roodmus/analysis/plot_alignment.py
@@ -161,9 +161,10 @@ def true_pose_distribution_plot(
     vmax: float | None = None,
 ):
     df_truth["euler_phi"] = df_truth["euler_phi"].astype(float)
-    df_truth["euler_theta"] = -(
-        df_truth["euler_theta"].astype(float) - np.pi / 2
-    )
+    df_truth["euler_theta"] = df_truth["euler_theta"].astype(float)
+    # df_truth["euler_theta"] = -(
+    #     df_truth["euler_theta"].astype(float) - np.pi / 2
+    # )
     df_truth["euler_psi"] = df_truth["euler_psi"].astype(float)
 
     grid = sns.jointplot(
@@ -194,7 +195,7 @@ def true_pose_distribution_plot(
     )
     grid.ax_joint.set_xticklabels(
         [
-            "\u03C0",
+            "-\u03C0",
             "-3/4\u03C0",
             "-\u03C0/2",
             "-\u03C0/4",
@@ -205,12 +206,12 @@ def true_pose_distribution_plot(
             "\u03C0",
         ]
     )
-    grid.ax_joint.set_yticks([-np.pi / 2, -np.pi / 4, 0, np.pi / 4, np.pi / 2])
+    grid.ax_joint.set_yticks([0, np.pi / 4, np.pi / 2, 3 / 4 * np.pi, np.pi])
     grid.ax_joint.set_yticklabels(
-        ["\u03C0/2", "\u03C0/4", "0", "\u03C0/4", "\u03C0/2"]
+        ["0", "\u03C0/4", "\u03C0/2", "3/4\u03C0", "\u03C0"]
     )
     grid.ax_joint.set_xlabel("Azimuth")
-    grid.ax_joint.set_ylabel("Elevation")
+    grid.ax_joint.set_ylabel("Tilt")
     # add new sublot to the right of the jointplot
     cbar_ax = grid.fig.add_axes([1, 0.15, 0.02, 0.7])
     # add colorbar to the new subplot
@@ -275,7 +276,11 @@ def make_and_save_plots(
                     "metadata_filename"
                 ].unique()
             ):
-                self.grid, self.vmin, self.vmax = picked_pose_distribution(
+                (
+                    self.grid,
+                    self.vmin,
+                    self.vmax,
+                ) = picked_pose_distribution_plot(
                     self.plot_data["plot_picked_pose_distribution"][
                         "df_picked"
                     ],
@@ -310,7 +315,7 @@ def _save_plot(self, meta_file: str):
             )
 
 
-def picked_pose_distribution(
+def picked_pose_distribution_plot(
     df_picked: pd.DataFrame,
     metadata_filename: str | List[str],
     vmin: float | None = None,
@@ -324,15 +329,15 @@ def picked_pose_distribution(
     )
 
     # change data type of column euler_phi to float
-    df_picked_grouped["euler_phi"] = df_picked_grouped["euler_phi"].astype(
-        float
-    )
-    df_picked_grouped["euler_theta"] = -(
-        df_picked_grouped["euler_theta"].astype(float) - np.pi / 2
-    )
-    df_picked_grouped["euler_psi"] = df_picked_grouped["euler_psi"].astype(
-        float
-    )
+    # df_picked_grouped["euler_phi"] = df_picked_grouped["euler_phi"].astype(
+    #     float
+    # )
+    # df_picked_grouped["euler_theta"] = -(
+    #     df_picked_grouped["euler_theta"].astype(float) - np.pi / 2
+    # )
+    # df_picked_grouped["euler_psi"] = df_picked_grouped["euler_psi"].astype(
+    #     float
+    # )
 
     # plot the alignment
     grid = sns.jointplot(
@@ -363,7 +368,7 @@ def picked_pose_distribution(
     )
     grid.ax_joint.set_xticklabels(
         [
-            "\u03C0",
+            "-\u03C0",
             "-3/4\u03C0",
             "-\u03C0/2",
             "-\u03C0/4",
@@ -374,12 +379,12 @@ def picked_pose_distribution(
             "\u03C0",
         ]
     )
-    grid.ax_joint.set_yticks([-np.pi / 2, -np.pi / 4, 0, np.pi / 4, np.pi / 2])
+    grid.ax_joint.set_yticks([0, np.pi / 4, np.pi / 2, 3 / 4 * np.pi, np.pi])
     grid.ax_joint.set_yticklabels(
-        ["-\u03C0/2", "-\u03C0/4", "0", "\u03C0/4", "\u03C0/2"]
+        ["0", "\u03C0/4", "\u03C0/2", "3/4\u03C0", "\u03C0"]
     )
     grid.ax_joint.set_xlabel("Azimuth")
-    grid.ax_joint.set_ylabel("Elevation")
+    grid.ax_joint.set_ylabel("Tilt")
     # add new sublot to the right of the jointplot
     cbar_ax = grid.fig.add_axes([1, 0.15, 0.02, 0.7])
     # add colorbar to the new subplot
diff --git a/src/roodmus/analysis/plot_picking.py b/src/roodmus/analysis/plot_picking.py
index aa80744..cb83fce 100644
--- a/src/roodmus/analysis/plot_picking.py
+++ b/src/roodmus/analysis/plot_picking.py
@@ -2215,13 +2215,13 @@ def plot_precision(
     sm = plt.cm.ScalarMappable(
         cmap="RdYlBu",
         norm=plt.Normalize(
-            vmin=df_precision["defocus"].min(),
-            vmax=df_precision["defocus"].max(),
+            vmin=df_precision["defocus"].min() / 10000,
+            vmax=df_precision["defocus"].max() / 10000,
         ),
     )
     sm._A = []
     cbar = fig.colorbar(sm, ax=ax)
-    cbar.set_label("defocus (Å)", rotation=270, labelpad=20, fontsize=12)
+    cbar.set_label("defocus (\u03bcm)", rotation=270, labelpad=20, fontsize=12)
     # add labels
     ax.set_xlabel("")
     ax.set_ylabel("precision", fontsize=14)
@@ -2283,13 +2283,13 @@ def plot_recall(
     sm = plt.cm.ScalarMappable(
         cmap="RdYlBu",
         norm=plt.Normalize(
-            vmin=df_precision["defocus"].min(),
-            vmax=df_precision["defocus"].max(),
+            vmin=df_precision["defocus"].min() / 10000,
+            vmax=df_precision["defocus"].max() / 10000,
         ),
     )
     sm._A = []
     cbar = fig.colorbar(sm, ax=ax)
-    cbar.set_label("defocus (Å)", rotation=270, labelpad=20, fontsize=12)
+    cbar.set_label("defocus (\u03bcm)", rotation=270, labelpad=20, fontsize=12)
     # add labels
     ax.set_xlabel("")
     ax.set_ylabel("recall", fontsize=14)
diff --git a/src/roodmus/analysis/utils.py b/src/roodmus/analysis/utils.py
index dc6c671..c015160 100644
--- a/src/roodmus/analysis/utils.py
+++ b/src/roodmus/analysis/utils.py
@@ -29,6 +29,7 @@
 import yaml
 import numpy as np
 from scipy.spatial import cKDTree
+from scipy.spatial.transform import Rotation as R
 from tqdm import tqdm
 import pandas as pd
 import pickle
@@ -59,7 +60,8 @@ def load_cs(self, cs_path):
 
     @classmethod
     def get_ugraph_cs(self, metadata_cs: np.recarray) -> List[str]:
-        """Grab micrograph file paths from .cs data.
+        """Grab micrograph file paths from .cs data. if micrograph file
+        paths are not present in the metadata, return an empty list.
 
         Args:
             metadata_cs (np.recarray): .cs file metadata.
@@ -67,18 +69,16 @@ def get_ugraph_cs(self, metadata_cs: np.recarray) -> List[str]:
         Returns:
             ugraph_paths (List[str]): micrograph file paths.
         """
-        ugraph_paths = metadata_cs["location/micrograph_path"].tolist()
 
-        # elif "blob/path" in metadata_cs.dtype.names:
-        #     ugraph_paths = metadata_cs["blob/path"]
-        # removed None from within the function to stop mypy errors
-        # else:
-        #     return None
+        if "location/micrograph_path" in metadata_cs.dtype.names:
+            ugraph_paths = metadata_cs["location/micrograph_path"].tolist()
+            ugraph_paths = [
+                os.path.basename(path).decode("utf-8").split("_")[-1]
+                for path in ugraph_paths
+            ]
+        else:
+            ugraph_paths = []
 
-        ugraph_paths = [
-            os.path.basename(path).decode("utf-8").split("_")[-1]
-            for path in ugraph_paths
-        ]
         return ugraph_paths
 
     @classmethod
@@ -164,13 +164,13 @@ def get_orientations_cs(self, metadata_cs: np.recarray, return_pose=False):
                 "alignments3D/pose"
             ]  # orientations as rodriques vectors
             # convert to euler angles
-            euler = np.array(
-                [geom.rot2euler(geom.expmap(p)) for p in pose],
-                dtype=float,
-            )
-            # euler = R.from_rotvec(pose).as_euler(
-            #     "zyx", degrees=False
-            # )  # convert to euler angles
+            # euler = np.array(
+            #     [geom.rot2euler(geom.expmap(p)) for p in pose],
+            #     dtype=float,
+            # )
+            euler = R.from_rotvec(pose).as_euler(
+                "ZYZ", degrees=False
+            )  # convert to euler angles
             if return_pose:
                 return euler, pose
             else:
@@ -205,7 +205,7 @@ def get_class2D_cs(self, metadata_cs: np.recarray):
             np.ndarray: 2D class.
         """
         if "alignments2D/class" in metadata_cs.dtype.names:
-            class2d = metadata_cs["alignments2D/class"]
+            class2d = metadata_cs["alignments2D/class"].astype(int)
         else:
             class2d = None
         return class2d
@@ -359,10 +359,16 @@ def get_orientations_star(self, metadata_star) -> np.ndarray:
         )
         if not euler_phi:  # if empty
             euler_phi = [np.nan] * num_particles
+        else:
+            euler_phi = [np.deg2rad(float(r)) for r in euler_phi]
         if not euler_theta:
             euler_theta = [np.nan] * num_particles
+        else:
+            euler_theta = [np.deg2rad(float(r)) for r in euler_theta]
         if not euler_psi:
             euler_psi = [np.nan] * num_particles
+        else:
+            euler_psi = [np.deg2rad(float(r)) for r in euler_psi]
         euler = np.stack([euler_phi, euler_theta, euler_psi], axis=1)
         return euler
 
@@ -376,7 +382,12 @@ def get_class2D_star(self, metadata_star):
         Returns:
             class2d (np.ndarray): 2D class data.
         """
-        class2d = metadata_star.column_as_list("particles", "_rlnClassNumber")
+        class2d = [
+            int(r)
+            for r in metadata_star.column_as_list(
+                "particles", "_rlnClassNumber"
+            )
+        ]
         if class2d:
             return np.array(class2d)
         else:
@@ -1017,7 +1028,7 @@ def _extract_from_metadata(
                 ugraph_filename = IO.get_ugraph_cs(m)
                 uid = IO.get_uid_cs(m)
                 tmp_results["uid"].extend(uid)
-                if ugraph_filename is None:
+                if not ugraph_filename:
                     num_particles = len(uid)
                     tmp_results["ugraph_filename"].extend(
                         [np.nan] * num_particles
@@ -1402,8 +1413,8 @@ def _extract_from_config(
                 position = instance["position"]
                 orientation = instance["orientation"]  # rotation vector
                 # convert to euler angles
-                euler = geom.rot2euler(geom.expmap(np.array(orientation)))
-                # euler = R.from_rotvec(orientation).as_euler("zyx")
+                # euler = geom.rot2euler(geom.expmap(np.array(orientation)))
+                euler = R.from_rotvec(orientation).as_euler("ZYZ")
                 if return_pose:
                     orientations_list.append(orientation)
                 else:
diff --git a/tests/integration/fixtures/analysis_test_outputs/alignment_star/particles_picked_pose_distribution.png b/tests/integration/fixtures/analysis_test_outputs/alignment_star/particles_picked_pose_distribution.png
index 217b4a0..40e34b2 100644
Binary files a/tests/integration/fixtures/analysis_test_outputs/alignment_star/particles_picked_pose_distribution.png and b/tests/integration/fixtures/analysis_test_outputs/alignment_star/particles_picked_pose_distribution.png differ
diff --git a/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_picked_pose_distribution/df_picked.csv b/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_picked_pose_distribution/df_picked.csv
index f062728..e07a785 100644
--- a/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_picked_pose_distribution/df_picked.csv
+++ b/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_picked_pose_distribution/df_picked.csv
@@ -1,263 +1,263 @@
 ,metadata_filename,ugraph_filename,position_x,position_y,euler_phi,euler_theta,euler_psi,ugraph_shape,defocusU,defocusV,class2D
-0,meta_file/particles.star,000000.mrc,3503.0,2772.0,-169.116160,50.827670,162.107010,"(4000, 4000)",15287.149414,15261.893555,1
-1,meta_file/particles.star,000000.mrc,1105.0,2396.0,23.724220,27.109672,-81.202010,"(4000, 4000)",15287.149414,15261.893555,1
-2,meta_file/particles.star,000000.mrc,1375.0,1903.0,136.727620,158.571265,51.826657,"(4000, 4000)",15287.149414,15261.893555,1
-3,meta_file/particles.star,000000.mrc,3315.0,1210.0,75.238869,53.702962,-179.522340,"(4000, 4000)",15287.149414,15261.893555,1
-4,meta_file/particles.star,000000.mrc,3202.0,3500.0,136.189870,62.032442,-155.811970,"(4000, 4000)",15287.149414,15261.893555,1
-5,meta_file/particles.star,000000.mrc,2088.0,3608.0,-154.690000,44.241906,95.663057,"(4000, 4000)",15287.149414,15261.893555,1
-6,meta_file/particles.star,000000.mrc,420.0,3832.0,43.031414,27.610373,29.803769,"(4000, 4000)",15287.149414,15261.893555,1
-7,meta_file/particles.star,000000.mrc,2115.0,2986.0,-176.912340,32.267749,139.306789,"(4000, 4000)",15287.149414,15261.893555,1
-8,meta_file/particles.star,000000.mrc,697.0,1627.0,-47.113140,148.547825,-74.895770,"(4000, 4000)",15287.149414,15261.893555,1
-9,meta_file/particles.star,000000.mrc,3225.0,2522.0,4.145261,26.866117,168.092214,"(4000, 4000)",15287.149414,15261.893555,1
-10,meta_file/particles.star,000000.mrc,987.0,3696.0,135.272300,19.540964,-167.269090,"(4000, 4000)",15287.149414,15261.893555,1
-11,meta_file/particles.star,000000.mrc,878.0,1897.0,-166.955580,44.468726,117.355770,"(4000, 4000)",15287.149414,15261.893555,1
-12,meta_file/particles.star,000000.mrc,1747.0,3706.0,-145.618440,146.541464,-165.938370,"(4000, 4000)",15287.149414,15261.893555,1
-13,meta_file/particles.star,000000.mrc,3720.0,293.0,46.049747,15.705493,-130.516770,"(4000, 4000)",15287.149414,15261.893555,1
-14,meta_file/particles.star,000000.mrc,3340.0,3321.0,-99.158580,144.734826,143.385030,"(4000, 4000)",15287.149414,15261.893555,1
-15,meta_file/particles.star,000000.mrc,3836.0,2218.0,157.823212,82.966981,-19.667770,"(4000, 4000)",15287.149414,15261.893555,1
-16,meta_file/particles.star,000000.mrc,598.0,1445.0,17.326628,72.967632,-12.211540,"(4000, 4000)",15287.149414,15261.893555,1
-17,meta_file/particles.star,000000.mrc,2002.0,1098.0,-145.578470,19.705040,91.677983,"(4000, 4000)",15287.149414,15261.893555,1
-18,meta_file/particles.star,000000.mrc,3028.0,118.0,96.498336,75.941750,-29.020190,"(4000, 4000)",15287.149414,15261.893555,1
-19,meta_file/particles.star,000000.mrc,3690.0,821.0,-72.741540,93.856063,118.812592,"(4000, 4000)",15287.149414,15261.893555,1
-20,meta_file/particles.star,000000.mrc,2499.0,2669.0,156.342006,44.387641,2.295033,"(4000, 4000)",15287.149414,15261.893555,1
-21,meta_file/particles.star,000000.mrc,3545.0,3258.0,103.755756,48.907672,-179.746810,"(4000, 4000)",15287.149414,15261.893555,1
-22,meta_file/particles.star,000000.mrc,3419.0,324.0,149.753256,31.951277,136.204752,"(4000, 4000)",15287.149414,15261.893555,1
-23,meta_file/particles.star,000000.mrc,3822.0,107.0,107.602723,18.377158,-154.698960,"(4000, 4000)",15287.149414,15261.893555,1
-24,meta_file/particles.star,000000.mrc,129.0,1931.0,123.332157,25.059481,-159.253500,"(4000, 4000)",15287.149414,15261.893555,1
-25,meta_file/particles.star,000000.mrc,1154.0,150.0,22.308837,107.012813,-34.968850,"(4000, 4000)",15287.149414,15261.893555,1
-26,meta_file/particles.star,000000.mrc,917.0,3878.0,-117.703760,95.933113,66.221383,"(4000, 4000)",15287.149414,15261.893555,1
-27,meta_file/particles.star,000000.mrc,479.0,1795.0,-61.908140,83.823335,13.591717,"(4000, 4000)",15287.149414,15261.893555,1
-28,meta_file/particles.star,000000.mrc,231.0,337.0,156.819878,134.363388,-110.024130,"(4000, 4000)",15287.149414,15261.893555,1
-29,meta_file/particles.star,000000.mrc,3895.0,3842.0,16.850884,101.918839,130.310377,"(4000, 4000)",15287.149414,15261.893555,1
-30,meta_file/particles.star,000000.mrc,136.0,1714.0,-152.287150,67.711511,65.263545,"(4000, 4000)",15287.149414,15261.893555,1
-31,meta_file/particles.star,000000.mrc,2057.0,2478.0,82.623829,125.510490,52.914998,"(4000, 4000)",15287.149414,15261.893555,1
-32,meta_file/particles.star,000000.mrc,1904.0,167.0,-69.569420,47.072061,-7.897250,"(4000, 4000)",15287.149414,15261.893555,1
-33,meta_file/particles.star,000000.mrc,3577.0,544.0,-106.601080,36.226775,-29.222030,"(4000, 4000)",15287.149414,15261.893555,1
-34,meta_file/particles.star,000000.mrc,109.0,3233.0,97.033152,65.807489,-66.696110,"(4000, 4000)",15287.149414,15261.893555,1
-35,meta_file/particles.star,000000.mrc,1020.0,2785.0,-168.544230,92.634669,109.415090,"(4000, 4000)",15287.149414,15261.893555,1
-36,meta_file/particles.star,000000.mrc,3465.0,3347.0,50.116896,33.959656,-142.465630,"(4000, 4000)",15287.149414,15261.893555,1
-37,meta_file/particles.star,000000.mrc,294.0,954.0,141.914710,56.515513,-13.186060,"(4000, 4000)",15287.149414,15261.893555,1
-38,meta_file/particles.star,000000.mrc,2768.0,1728.0,-117.703760,95.933113,148.721383,"(4000, 4000)",15287.149414,15261.893555,1
-39,meta_file/particles.star,000000.mrc,3899.0,1692.0,-123.923970,81.806620,-53.893170,"(4000, 4000)",15287.149414,15261.893555,1
-40,meta_file/particles.star,000000.mrc,920.0,2688.0,94.570968,114.998374,75.784846,"(4000, 4000)",15287.149414,15261.893555,1
-41,meta_file/particles.star,000000.mrc,903.0,1327.0,-124.859530,61.419738,51.406675,"(4000, 4000)",15287.149414,15261.893555,1
-42,meta_file/particles.star,000000.mrc,2659.0,776.0,-163.554970,56.876595,94.847774,"(4000, 4000)",15287.149414,15261.893555,1
-43,meta_file/particles.star,000000.mrc,3611.0,1065.0,106.830877,95.694779,91.180523,"(4000, 4000)",15287.149414,15261.893555,1
-44,meta_file/particles.star,000000.mrc,2440.0,2937.0,153.564956,38.132620,166.875510,"(4000, 4000)",15287.149414,15261.893555,1
-45,meta_file/particles.star,000000.mrc,1184.0,923.0,-92.043020,41.754769,165.323665,"(4000, 4000)",15287.149414,15261.893555,1
-46,meta_file/particles.star,000000.mrc,3175.0,982.0,125.811298,49.847768,-141.602050,"(4000, 4000)",15287.149414,15261.893555,1
-47,meta_file/particles.star,000000.mrc,1316.0,3205.0,145.911745,111.797901,-35.249960,"(4000, 4000)",15287.149414,15261.893555,1
-48,meta_file/particles.star,000000.mrc,3298.0,3891.0,111.791481,110.618002,173.627658,"(4000, 4000)",15287.149414,15261.893555,1
-49,meta_file/particles.star,000000.mrc,989.0,2099.0,140.030468,116.798614,-20.559000,"(4000, 4000)",15287.149414,15261.893555,1
-50,meta_file/particles.star,000000.mrc,1768.0,1042.0,96.030531,85.628098,-133.945010,"(4000, 4000)",15287.149414,15261.893555,1
-51,meta_file/particles.star,000000.mrc,2389.0,3734.0,115.754938,30.773783,-143.594880,"(4000, 4000)",15287.149414,15261.893555,1
-52,meta_file/particles.star,000000.mrc,2323.0,3340.0,149.753256,31.951277,-178.795250,"(4000, 4000)",15287.149414,15261.893555,1
-53,meta_file/particles.star,000000.mrc,222.0,3560.0,-27.663310,102.016386,-10.066730,"(4000, 4000)",15287.149414,15261.893555,1
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diff --git a/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_truth_pose_distribution/df_truth.csv b/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_truth_pose_distribution/df_truth.csv
index b72f60e..7e31cbf 100644
--- a/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_truth_pose_distribution/df_truth.csv
+++ b/tests/integration/fixtures/analysis_test_outputs/alignment_star/plot_truth_pose_distribution/df_truth.csv
@@ -1,301 +1,301 @@
 ,ugraph_filename,ice_thickness,pdb_filename,position_x,position_y,position_z,euler_phi,euler_theta,euler_psi,defocus
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-1,000000.mrc,500.0,/mnt/parakeet_storage4/ConformationSampling/DESRES-Trajectory_sarscov2-11021571-all-glueCA/even_sampling_8334/conformation_000040.pdb,3784.304931640625,444.0520324707031,248.13645935058594,2.8549282995307457,1.5779837583047915,-2.423345861471819,-15309.73434082482
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diff --git a/tests/integration/fixtures/analysis_test_outputs/alignment_star/true_pose_distribution.png b/tests/integration/fixtures/analysis_test_outputs/alignment_star/true_pose_distribution.png
index 77c6bca..18461d6 100644
Binary files a/tests/integration/fixtures/analysis_test_outputs/alignment_star/true_pose_distribution.png and b/tests/integration/fixtures/analysis_test_outputs/alignment_star/true_pose_distribution.png differ
diff --git a/tests/integration/fixtures/analysis_test_outputs/classes_star/plot_classes/df_picked.csv b/tests/integration/fixtures/analysis_test_outputs/classes_star/plot_classes/df_picked.csv
index aad646d..44e5ae6 100644
--- a/tests/integration/fixtures/analysis_test_outputs/classes_star/plot_classes/df_picked.csv
+++ b/tests/integration/fixtures/analysis_test_outputs/classes_star/plot_classes/df_picked.csv
@@ -1,263 +1,263 @@
 ,metadata_filename,ugraph_filename,position_x,position_y,euler_phi,euler_theta,euler_psi,ugraph_shape,defocusU,defocusV,class2D,TP,closest_dist,closest_particle,closest_pdb,closest_pdb_index
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diff --git a/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_picked.csv b/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_picked.csv
index 78b4cfe..44e5ae6 100644
--- a/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_picked.csv
+++ b/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_picked.csv
@@ -1,263 +1,263 @@
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diff --git a/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_truth.csv b/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_truth.csv
index b72f60e..7e31cbf 100644
--- a/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_truth.csv
+++ b/tests/integration/fixtures/analysis_test_outputs/frames_star/frame_distribution/df_truth.csv
@@ -1,301 +1,301 @@
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