feat(flomni): offer tomo-param reset on account change at session start

At BEC session start, compare bec.active_account against the new global var defaults_applied_for_account. On a genuine account change, interactively offer to reset all tomo scan parameters to their defaults for the new experiment; a client restart within the same account is a silent no-op. Add _set_default_tomo_params() writing all 20 scan parameters via the property setters.
2026-07-08 11:55:03 +02:00
parent 401312fcbb
commit b638f4d982
1 changed files with 62 additions and 0 deletions
@@ -1718,10 +1718,72 @@ class Flomni(
        self.align = XrayEyeAlign(self.client, self)
        self.set_client(client)

+        self._maybe_reset_params_on_account_change()
+
    def set_web_password(self, password: str) -> None:
        """Set the web password for the current BEC account."""
        self._webpage_gen.set_web_password(password)

+    def _maybe_reset_params_on_account_change(self) -> None:
+        """Offer a tomo-parameter reset when the active account has changed.
+
+        Called at BEC session start. The account for which defaults were last
+        applied is stored in the global var ``defaults_applied_for_account`` so
+        it survives client restarts. Only a genuine change of account triggers
+        the (interactive) reset; the same account is a silent no-op, so
+        restarting a client within the same experiment never disturbs tuned
+        parameters.
+        """
+        bec = builtins.__dict__.get("bec")
+        try:
+            account = bec.active_account
+        except Exception as exc:
+            print(f"account-change check skipped: cannot read active_account: {exc}")
+            return
+        if not account:
+            return
+
+        last_account = self.client.get_global_var("defaults_applied_for_account")
+        if account == last_account:
+            return
+
+        if self.OMNYTools.yesno(
+            f"New account '{account}' detected (previous: '{last_account}').\n"
+            "Reset tomo parameters to defaults for the new experiment?",
+            "y",
+        ):
+            self._set_default_tomo_params()
+            print(f"Tomo parameters reset to defaults for account '{account}'.")
+        self.client.set_global_var("defaults_applied_for_account", account)
+
+    def _set_default_tomo_params(self) -> None:
+        """Write all tomo scan parameters back to their default values.
+
+        These are the same baseline values used as the getter fallbacks. Per-
+        sample alignment state (corrections, alignment offsets) is deliberately
+        not reset here, as it is overwritten by the next alignment anyway.
+        """
+        self.tomo_shellstep = 1
+        self.tomo_countingtime = 0.1
+        self.manual_shift_y = 0.0
+        self.single_point_random_shift_max = 0.0
+        self.fovx = 20
+        self.fovy = 20
+        self.tomo_type = 1
+        self.corridor_size = -1
+        self.stitch_x = 0
+        self.stitch_y = 0
+        self.ptycho_reconstruct_foldername = "ptycho_reconstruct"
+        self.tomo_angle_stepsize = 10.0
+        self.golden_max_number_of_projections = 1000.0
+        self.tomo_stitch_overlap = 0.2
+        self.tomo_angle_range = 180
+        self.golden_projections_at_0_deg_for_damage_estimation = 0
+        self.zero_deg_reference_at_each_subtomo = False
+        self.golden_ratio_bunch_size = 20
+        self.frames_per_trigger = 1
+        self.single_point_instead_of_fermat_scan = False
+
    def start_x_ray_eye_alignment(self, keep_shutter_open=False):

        if self.OMNYTools.yesno(