def redraw_integral(self):
dis = []
if self.curveplot.data:
x = np.sort(getx(self.curveplot.data))
previews = self.flow_view.preview_n()
for i in range(self.preprocessormodel.rowCount()):
if i in previews:
item = self.preprocessormodel.item(i)
m = create_model(item, i)
p = prepare_params(item, m)
# Show initial fit values for now
init = np.atleast_2d(
np.broadcast_to(m.eval(p, x=x), x.shape))
di = [("curve", (x, init, INTEGRATE_DRAW_BASELINE_PENARGS))
]
color = self.flow_view.preview_color(i)
dis.append({"draw": di, "color": color})
result = None
if np.any(self.curveplot.selection_group) and self.curveplot.data \
and self.preview_runner.preview_model_result:
# select result
ind = np.flatnonzero(self.curveplot.selection_group)[0]
row_id = self.curveplot.data[ind].id
result = self.preview_runner.preview_model_result.get(row_id, None)
if result is not None:
# show total fit
eval = np.atleast_2d(np.broadcast_to(result.eval(x=x), x.shape))
di = [("curve", (x, eval, INTEGRATE_DRAW_CURVE_PENARGS))]
dis.append({"draw": di, "color": 'red'})
# show components
eval_comps = result.eval_components(x=x)
for i in range(self.preprocessormodel.rowCount()):
item = self.preprocessormodel.item(i)
prefix = unique_prefix(item.data(DescriptionRole).viewclass, i)
comp = eval_comps.get(prefix, None)
if comp is not None:
comp = np.atleast_2d(np.broadcast_to(comp, x.shape))
di = [("curve", (x, comp, INTEGRATE_DRAW_CURVE_PENARGS))]
color = self.flow_view.preview_color(i)
dis.append({"draw": di, "color": color})
refresh_integral_markings(dis, self.markings_list, self.curveplot)
def redraw_integral(self):
dis = []
if np.any(self.curveplot.selection_group) and self.curveplot.data:
# select data
ind = np.flatnonzero(self.curveplot.selection_group)[0]
show = self.curveplot.data[ind:ind+1]
previews = self.flow_view.preview_n()
for i in range(self.preprocessormodel.rowCount()):
if i in previews:
item = self.preprocessormodel.item(i)
desc = item.data(DescriptionRole)
params = item.data(ParametersRole)
if not isinstance(params, dict):
params = {}
preproc = desc.viewclass.createinstance(params)
preproc.metas = False
datai = preproc(show)
di = datai.domain.attributes[0].compute_value.draw_info(show)
color = self.flow_view.preview_color(i)
dis.append({"draw": di, "color": color})
refresh_integral_markings(dis, self.markings_list, self.curveplot)
def redraw_integral(self):
dis = []
if np.any(self.curveplot.selection_group) and self.curveplot.data:
# select data
ind = np.flatnonzero(self.curveplot.selection_group)[0]
show = self.curveplot.data[ind:ind+1]
previews = self.flow_view.preview_n()
for i in range(self.preprocessormodel.rowCount()):
if i in previews:
item = self.preprocessormodel.item(i)
desc = item.data(DescriptionRole)
params = item.data(ParametersRole)
if not isinstance(params, dict):
params = {}
preproc = desc.viewclass.createinstance(params)
preproc.metas = False
datai = preproc(show)
di = datai.domain.attributes[0].compute_value.draw_info(show)
color = self.flow_view.preview_color(i)
dis.append({"draw": di, "color": color})
refresh_integral_markings(dis, self.markings_list, self.curveplot)
def show_preview(self, show_info_anyway=False):
""" Shows preview and also passes preview data to the widgets """
master = self.master
self.preview_pos = master.flow_view.preview_n()
self.last_partial = None
self.show_info_anyway = show_info_anyway
self.preview_data = None
self.after_data = None
pp_def = [
master.preprocessormodel.item(i)
for i in range(master.preprocessormodel.rowCount())
]
if master.data is not None:
# Clear markings to indicate preview is running
refresh_integral_markings([], master.markings_list,
master.curveplot)
data = master.sample_data(master.data)
# Pass preview data to widgets here as we don't use on_partial_result()
for w in self.master.flow_view.widgets():
w.set_preview_data(data)
self.start(self.run_preview, data, pp_def, self.pool)
else:
master.curveplot.set_data(None)
master.curveplot_after.set_data(None)