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WIP waveform request dap using parameters of the previous fit

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wyzula_j
2025-03-14 14:58:16 +01:00
parent 0753e359c6
commit 115da10d78
1 changed files with 25 additions and 3 deletions
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28
bec_widgets/widgets/plots_next_gen/waveform/waveform.py
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@ -1,5 +1,7 @@
from __future__ import annotations from __future__ import annotations
from bec_lib.lmfit_serializer import serialize_lmfit_params
import json import json
from typing import Literal from typing import Literal
@ -1152,8 +1154,8 @@ class Waveform(PlotBase):
MessageEndpoints.dap_response(f"{self.scan_id}-{self.gui_id}"), MessageEndpoints.dap_response(f"{self.scan_id}-{self.gui_id}"),
) )
# @SafeSlot() #FIXME type error @SafeSlot()
def request_dap(self): def request_dap(self, _=None):
"""Request new fit for data""" """Request new fit for data"""
for dap_curve in self._dap_curves: for dap_curve in self._dap_curves:
@ -1176,12 +1178,32 @@ class Waveform(PlotBase):
x_min = None x_min = None
x_max = None x_max = None
dice_roll = np.random.randint(0, 11)
if dap_curve.dap_params is not None:
fit_success = dap_curve.dap_summary.get("success", False)
else:
fit_success = False
params_serialized = {}
if fit_success and dice_roll < 9:
amplitude = dap_curve.dap_params.get("amplitude")
center = dap_curve.dap_params.get("center")
sigma = dap_curve.dap_params.get("sigma")
amplitude_param = lmfit.Parameter(name="amplitude", value=amplitude)
center_param = lmfit.Parameter(name="center", value=center)
sigma_param = lmfit.Parameter(name="sigma", value=sigma)
params_serialized = serialize_lmfit_params(
[amplitude_param, center_param, sigma_param]
)
msg = messages.DAPRequestMessage( msg = messages.DAPRequestMessage(
dap_cls="LmfitService1D", dap_cls="LmfitService1D",
dap_type="on_demand", dap_type="on_demand",
config={ config={
"args": [], "args": [],
"kwargs": {"data_x": x_data, "data_y": y_data}, "kwargs": {"data_x": x_data, "data_y": y_data, **params_serialized},
"class_args": model._plugin_info["class_args"], "class_args": model._plugin_info["class_args"],
"class_kwargs": model._plugin_info["class_kwargs"], "class_kwargs": model._plugin_info["class_kwargs"],
"curve_label": dap_curve.name(), "curve_label": dap_curve.name(),