import ast
import ipywidgets as widgets
from IPython.display import display
from ipywidgets import Output
from pyccapt.calibration import clustering
from pyccapt.calibration.reconstructions import reconstruction
# Define a layout for labels to make them a fixed width
label_layout = widgets.Layout(width='200px')
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def call_x_y_z_calculation(variables, flight_path_length, element_selected, colab=False):
# Call the function or perform calculations here
# You can replace this with the actual implementation
# For demonstration purposes, I'm just printing the inputs
out = Output()
avg_dens = element_selected.value[2]
field_evap = element_selected.value[3]
if variables.range_data.empty or variables.range_data['ion'].iloc[0] == 'unranged':
element_percentage = str({'unranged': 0.01})
else:
# Iterate over unique elements in the "element" column
element_percentage = {}
for element_list in variables.range_data['element']:
for element in element_list:
# Check if the element is already a key in the dictionary
if element not in element_percentage:
element_percentage[element] = 0.01
element_percentage = str(element_percentage)
# Create widgets with initial values
kf_widget = widgets.FloatText(value=4, step=0.1)
det_eff_widget = widgets.FloatText(value=0.7, step=0.1)
icf_widget = widgets.FloatText(value=1.4, step=0.1)
field_evap_widget = widgets.FloatText(value=field_evap)
avg_dens_widget = widgets.FloatText(value=avg_dens)
element_percentage_widget = widgets.Textarea(value=element_percentage)
figname_widget = widgets.Text(value='3d')
mode_widget = widgets.Dropdown(options=[('Gault', 'Gault'), ('Bas', 'Bas')])
opacity_widget = widgets.FloatText(value=0.5, min=0, max=1, step=0.1)
save_widget = widgets.Dropdown(options=[('True', True), ('False', False)], value=False)
cluster_enabled_widget = widgets.Dropdown(options=[('False', False), ('True', True)], value=False)
cluster_labels_widget = widgets.Text(value='', placeholder='Ni3Al, Al')
# Create a button widget to trigger the function
button_calculate_plot = widgets.Button(description="Reconstruct & plot")
def on_button_click(b, variables, flight_path_length):
# Disable the button while the code is running
button_calculate_plot.disabled = True
# Get the values from the widgets
kf_value = kf_widget.value
det_eff_value = det_eff_widget.value
icf_value = icf_widget.value
field_evap_value = field_evap_widget.value
avg_dens_value = avg_dens_widget.value
element_percentage_value = element_percentage_widget.value
figname_value = figname_widget.value
mode_value = mode_widget.value
opacity_value = opacity_widget.value
save_value = save_widget.value
with out:
out.clear_output()
# Call the function
element_percentage_dic = ast.literal_eval(element_percentage_value)
# Iterate through the 'element' column
element_percentage_list = []
for row_elements in variables.range_data['element']:
max_value = 0.1 # Default value if no matching element is found
for element in row_elements:
if element in element_percentage_dic:
max_value = element_percentage_dic[element]
element_percentage_list.append(max_value)
cluster_result = None
if cluster_enabled_widget.value:
cluster_selection = clustering.parse_label_selection(cluster_labels_widget.value)
if not cluster_selection:
print('Clustering is enabled, but no ion or element labels were provided. Skipping segmentation.')
else:
cluster_result = clustering.segment_ions_by_min_max(variables, cluster_selection, n_clusters=2)
print('Min-Max clustering counts:', cluster_result.counts)
reconstruction.x_y_z_calculation_and_plot(
kf=kf_value,
det_eff=det_eff_value,
icf=icf_value,
field_evap=field_evap_value,
avg_dens=avg_dens_value,
element_percentage=element_percentage_list,
rotary_fig_save=False,
variables=variables,
flight_path_length=flight_path_length.value,
figname=figname_value,
mode=mode_value,
opacity=opacity_value,
save=save_value,
colab=colab,
cluster_result=cluster_result)
# Enable the button when the code is finished
button_calculate_plot.disabled = False
button_calculate_plot.on_click(lambda b: on_button_click(b, variables, flight_path_length))
widget_container = widgets.VBox([
widgets.HBox([widgets.Label(value='KF:', layout=label_layout), kf_widget, widgets.Label(value='(EV/nm)')]),
widgets.HBox([widgets.Label(value='Det_eff:', layout=label_layout), det_eff_widget]),
widgets.HBox([widgets.Label(value='ICF:', layout=label_layout), icf_widget]),
widgets.HBox([widgets.Label(value='Field_evap:', layout=label_layout), field_evap_widget,
widgets.Label(value='(V/nm)')]),
widgets.HBox([widgets.Label(value='Avg_dens:', layout=label_layout), avg_dens_widget,
widgets.Label(value='(Amu/nm^3)')]),
widgets.HBox([widgets.Label(value='Element_percentage:', layout=label_layout), element_percentage_widget]),
widgets.HBox([widgets.Label(value='Fig name:', layout=label_layout), figname_widget]),
widgets.HBox([widgets.Label(value='Save fig:', layout=label_layout), save_widget]),
widgets.HBox([widgets.Label(value='Cluster precipitate:', layout=label_layout), cluster_enabled_widget]),
widgets.HBox([widgets.Label(value='Cluster ions/elements:', layout=label_layout), cluster_labels_widget]),
widgets.HBox([widgets.Label(value='Mode:', layout=label_layout), mode_widget]),
widgets.HBox([widgets.Label(value='Opacity:', layout=label_layout), opacity_widget]),
widgets.HBox([button_calculate_plot]),
])
display(widget_container)
display(out)