Sweep steps

examples/article_figures/fig3B.py

@@ -9,8 +9,8 @@
     probe_templates=["NPC_Nup96_Cterminal_direct",],
     sweep_repetitions=20,
     # parameters for sweep
-    labelling_efficiency=(0,1,5),
-    defect=(0,1,5),
+    labelling_efficiency=(0,1,0.25),
+    defect=(0,1,0.25),
     defect_small_cluster=[300,],
     defect_large_cluster=[600,],
     exp_time=[0.001, 0.01,],

examples/parameter_sweep.py

@@ -6,8 +6,8 @@
     probe_templates=["NPC_Nup96_Cterminal_direct",],  # Probe template tailored to 7R5K
     sweep_repetitions=3,
     # parameters for sweep
-    labelling_efficiency=(0, 1, 3),  # 3 linearly spaced values between 0 and 1
-    defect=(0, 1, 3),  # 3 linearly spaced values between 0 and 1
+    labelling_efficiency=(0, 1, 0.5),  # values between 0 and 1 with step of 0.5
+    defect=(0, 1, 0.5),  # values between 0 and 1 with step of 0.5
     defect_small_cluster=[300,],  # 1 single value 
     defect_large_cluster=[600,],  # 1 single value 
     exp_time=[0.001, 0.01,],  # 2 values

src/vlab4mic/analysis/sweep.py

@@ -151,17 +151,21 @@ def sweep_vasmples(
                         #    keep=False, use_self_particle=True, **vsample_pars
                         # )
                         for rep in range(repetitions):
-                            if relative_positions_exist and relative_positions is not None:
+                            if relative_positions_exist and relative_positions is not None: # keep the same positions
                                 experiment.clear_virtual_sample()
                                 experiment.set_virtualsample_params(
                                     update_mode=True,
-                                    particle_positions = relative_positions)
+                                    particle_positions = relative_positions,
+                                    **vsample_pars)
                                 experiment.build(
                                     modules=["coordinate_field"],
                                     use_self_particle=True,
                                 )
                             else:
                                 experiment.clear_virtual_sample()
+                                experiment.set_virtualsample_params(
+                                    update_mode=True,
+                                    **vsample_pars)
                                 experiment.build(
                                     modules=["coordinate_field"],
                                     use_self_particle=True,
@@ -296,6 +300,7 @@ def sweep_modalities_updatemod(
                 mod_n = 0
                 for modality_name in experiment.selected_mods.keys():
                     for mod_pars_number, mod_pars in modality_params.items():
+                        print(f"Modality: {modality_name}, params set: {mod_pars} ")
                         experiment.update_modality(modality_name, **mod_pars)
                         # calculate virtual sample mask per modality
                         vsample_mask_per_mod = experiment.imager.generate_modality_mask(modality=modality_name)

src/vlab4mic/sweep_generator.py

@@ -252,6 +252,7 @@ def generate_acquisitions(self):
             vsample_outputs=self.virtual_samples,
             vsampl_pars=self.virtual_samples_parameters,
             modalities=self.modalities,
+            modality_params=self.modality_parameters,
             modality_acq_prams=self.acquisition_parameters,
         )
 
@@ -501,18 +502,19 @@ def set_parameter_values(self, param_group, param_name, values=None):
                             ]
                             == "int_slider"
                         ):
-                            step = np.ceil((values[1] - values[0]) / values[2])
+                            #step = np.ceil((values[1] - values[0]) / values[2])
                             self.params_by_group[param_group][param_name] = (
                                 np.arange(
                                     start=values[0],
                                     stop=values[1],
-                                    step=step,
+                                    step=values[2],
                                     dtype=int,
                                 )
                             )
                         else:
+                            num = int((values[1]-values[0]) / values[2]) + 1
                             param_iterables = np.linspace(
-                                values[0], values[1], values[2]
+                                values[0], values[1], num
                             )
                             self.params_by_group[param_group][
                                 param_name

tests/test_sweeps.py

@@ -10,8 +10,8 @@ def test_run_parameter_sweep():
         probe_templates=["NPC_Nup96_Cterminal_direct",],
         sweep_repetitions=3,
         # parameters for sweep
-        labelling_efficiency=(0,1,2),
-        defect=(0,1,2),
+        labelling_efficiency=(0,1,1),
+        defect=[0,0.5],
         defect_small_cluster=[300,],
         defect_large_cluster=[600,],
         #exp_time=[0.001, 0.01,],