Parameter object refactoring

scripts/s03_make_figures.py

@@ -432,7 +432,7 @@ def agg_result(
 
 # %% ar-dhm
 fig_path = FIG_PATH_PN / "ar-dhm.svg"
-fig_w, fig_h = 6.8, 2
+fig_w, fig_h = 6.2, 1.8
 with sns.axes_style("white"):
     fig, axs = plt.subplots(1, 2, figsize=(fig_w, fig_h))
 end = 60
@@ -506,7 +506,9 @@ def agg_result(
     axs[iplt].set_xlabel("Timesteps")
 fig.tight_layout()
 fig.legend(
-    loc="center left", bbox_to_anchor=(1.01, 0.5), bbox_transform=axs[-1].transAxes
+    loc="lower center",
+    bbox_to_anchor=(0.5, 0.95),
+    ncol=3,
 )
 fig.savefig(fig_path, bbox_inches="tight")
 
@@ -539,7 +541,7 @@ def AR_scatter(
 fig_path = FIG_PATH_PN / "ar-full.svg"
 resdf = load_agg_result(IN_MET_PATH / "test_demo_solve_fit_h_num")
 ressub = (
-    resdf.query("taus == '(6, 1)' & upsamp < 5 & rand_seed == 2")
+    resdf.query("taus == '(6, 1)' & upsamp == 1 & rand_seed == 2")
     .astype({"upsamp": int})
     .copy()
 )
@@ -555,9 +557,7 @@ def AR_scatter(
     "solve_fit": "InDeCa",
     "solve_fit-all": "InDeCa /w \nshared kernel",
 }
-g = sns.FacetGrid(
-    ressub, row="upsamp", col="ns_lev", height=1.5, aspect=1.15, margin_titles=True
-)
+g = sns.FacetGrid(ressub, col="ns_lev", height=1.7, aspect=1, margin_titles=True)
 g.map_dataframe(
     AR_scatter,
     x="dhm0",
@@ -577,12 +577,12 @@ def AR_scatter(
     frameon=RC_PARAM["legend.frameon"],
     fancybox=RC_PARAM["legend.fancybox"],
     framealpha=RC_PARAM["legend.framealpha"],
-    bbox_to_anchor=(1.02, 0.5),
+    bbox_to_anchor=(0.5, 1.06),
+    ncol=4,
 )
 g.set_xlabels(r"$\text{DHM}_r$ (timesteps)")
 g.set_ylabels(r"$\text{DHM}_d$" + "\n(timesteps)")
 g.set_titles(
-    row_template="Upsampling $k$: {row_name}",
     col_template="Noise level (A.U.): {col_name}",
 )
 for lab in g._legend.texts:

src/indeca/core/deconv/deconv.py

@@ -144,14 +144,14 @@ def __init__(
         backend: str = "osqp",
         nthres: int = 1000,
         err_weighting: str = None,
-        wt_trunc_thres: float = 1e-2,
+        wt_trunc_thres: float = None,
         masking_radius: int = None,
         pks_polish: bool = True,
         th_min: float = 0,
         th_max: float = 1,
         density_thres: float = None,
         ncons_thres: int = None,
-        min_rel_scl: float = "auto",
+        min_rel_scl: float = None,
         max_iter_l0: int = 30,
         max_iter_penal: int = 500,
         max_iter_scal: int = 50,
@@ -484,15 +484,17 @@ def update(
                     A_before = self.A.copy()
                     self._update_A()
                     assert self.A.shape == A_before.shape
-                    assert (self.A.nonzero()[0] == A_before.nonzero()[0]).all()
-                    assert (self.A.nonzero()[1] == A_before.nonzero()[1]).all()
+                    if not setup_prob:
+                        assert (self.A.nonzero()[0] == A_before.nonzero()[0]).all()
+                        assert (self.A.nonzero()[1] == A_before.nonzero()[1]).all()
                     updt_A = True
                 if any((scale is not None, scale_mul is not None, updt_HG, updt_P)):
                     P_before = self.P.copy()
                     self._update_P()
                     assert self.P.shape == P_before.shape
-                    assert (self.P.nonzero()[0] == P_before.nonzero()[0]).all()
-                    assert (self.P.nonzero()[1] == P_before.nonzero()[1]).all()
+                    if not setup_prob:
+                        assert (self.P.nonzero()[0] == P_before.nonzero()[0]).all()
+                        assert (self.P.nonzero()[1] == P_before.nonzero()[1]).all()
                     updt_P = True
                 if any(
                     (

src/indeca/pipeline/pipeline.py

@@ -432,7 +432,6 @@ def pipeline_bin(
             opt_idx = metric_df.loc[
                 metric_df[metric_df["cell"] == icell]["obj"].idxmin(), "iter"
             ]
-        opt_idx = -1
         opt_C[icell, :] = C_ls[opt_idx][icell, :]
         opt_S[icell, :] = S_ls[opt_idx][icell, :]
     C_ls.append(opt_C)

tests/regression/test_deconv_thres.py

@@ -43,8 +43,12 @@ def test_solve_thres(
         )
         s_direct = intm[0]
         s_bin = s_bin.astype(float)
+        ttol = max(upsamp_y / upsamp, upsamp, upsamp_y)
         mdist, f1, precs, recall = assignment_distance(
-            s_ref=s_org, s_slv=s_bin, tdist_thres=5, include_range=(0, len(s_org) - 5)
+            s_ref=s_org,
+            s_slv=s_bin,
+            tdist_thres=ttol,
+            include_range=(0, len(s_org) - max(int(ttol), 5)),
         )
         # plotting
         fig = go.Figure()

tests/validation/test_deconv_realds.py

@@ -53,9 +53,16 @@ def test_demo_solve_scale_realds(
             err_weighting=err_weighting,
             use_base=True,
         )
-        opt_s, opt_c, cur_scl, cur_obj, cur_penal, iterdf = deconv.solve_scale(
-            return_met=True, obj_crit=obj_crit
-        )
+        (
+            opt_s,
+            opt_c,
+            cur_scl,
+            cur_obj,
+            err_rel,
+            nnz,
+            cur_penal,
+            iterdf,
+        ) = deconv.solve_scale(return_met=True, obj_crit=obj_crit)
         deconv.update(update_weighting=True)
         err_wt = deconv.err_wt.squeeze()
         deconv.update(update_weighting=True, clear_weighting=True, scale=1)