✨ Developing PerturbationMatrix class

pyproject.toml

@@ -37,6 +37,7 @@ diskcache = "^5.3.0"
 imageio = "^2.9.0"
 imageio-ffmpeg = "^0.4.5"
 kbackground = "0.1.6"
+fbpca = "^1.0"
 
 [tool.poetry.dev-dependencies]
 pytest = "^6.1.2"

src/psfmachine/machine.py

@@ -887,7 +887,7 @@ def build_time_model(self, plot=False, downsample=False, split_time_model=False)
             dy,
             n_knots=self.n_time_knots,
             radius=self.time_radius,
-            spacing=self.cartesian_knot_spacing,
+            knot_spacing_type=self.cartesian_knot_spacing,
         )
         A2 = sparse.vstack([A_c] * time_binned.shape[0], format="csr")
         # Cartesian spline with time dependence
@@ -1049,7 +1049,7 @@ def plot_time_model(self, segment=0):
             dy,
             n_knots=self.n_time_knots,
             radius=self.time_radius,
-            spacing=self.cartesian_knot_spacing,
+            knot_spacing_type=self.cartesian_knot_spacing,
         )
         # if self.seg_splits.shape[0] == 2 and segment == 0:
         #     seg_mask = np.ones(time_binned.shape[0], dtype=bool)
@@ -1576,7 +1576,7 @@ def fit_model(self, fit_va=False):
                 dy,
                 n_knots=self.n_time_knots,
                 radius=self.time_radius,
-                spacing=self.cartesian_knot_spacing,
+                knot_spacing_type=self.cartesian_knot_spacing,
             )
             A_cp3 = sparse.hstack([A_cp, A_cp, A_cp, A_cp], format="csr")