def callback_input_barchart(topic_selection, element_selection):
# format bar labels
inputs = ['live_load', 'environment', 'maintenance_and_preservation']
formatted_inputs = [
inp.title().replace("_", " ").replace("And", "&") for inp in inputs
]
labels = [
"<br>".join(textwrap.wrap(label, width=15))
for label in formatted_inputs
]
# get project counts and doc_ids
counts, ids = [], []
for i in inputs:
count, id = aggregate.project_count_by_topic(
topic=i,
element=element_selection,
topic_selection=topic_selection)
counts.append(count)
ids.append(id)
# get request parameters
params = [
f"type=click_bar&query={i}&index=projects&topic={topic_selection}&element={element_selection}"
for i in inputs
]
# generate figure
figure = fig.bar_chart(labels=labels,
counts=counts,
ids=ids,
params=params)
return figure
def callback_performance_barchart(topic_selection, element_selection):
# format bar labels
performance = [
'structural_integrity', 'structural_condition', 'functionality', 'cost'
]
formatted_performance = [
perf.title().replace("_", " ").replace("And", "&")
for perf in performance
]
labels = [
"<br>".join(textwrap.wrap(label, width=15))
for label in formatted_performance
]
# get project counts and doc_ids
counts, ids = [], []
for p in performance:
count, id = aggregate.project_count_by_topic(
topic=p,
element=element_selection,
topic_selection=topic_selection)
counts.append(count)
ids.append(id)
# get request parameters
params = [
f"type=click_bar&query={perf}&index=projects&topic={topic_selection}&element={element_selection}"
for perf in performance
]
# generate figure
figure = fig.bar_chart(labels=labels,
counts=counts,
ids=ids,
params=params)
return figure
def callback_attribute_barchart(topic_selection, element_selection):
# format bar labels
attributes = [
'construction_quality', 'design_and_details', 'material_specifications'
]
formatted_attributes = [
attr.title().replace("_", " ").replace("And", "&")
for attr in attributes
]
labels = [
"<br>".join(textwrap.wrap(label, width=15))
for label in formatted_attributes
]
# get project counts and doc_ids
counts, ids = [], []
for attr in attributes:
count, id = aggregate.project_count_by_topic(
topic=attr,
element=element_selection,
topic_selection=topic_selection)
counts.append(count)
ids.append(id)
# get request parameters
params = [
f"type=click_bar&query={attr}&index=projects&topic={topic_selection}&element={element_selection}"
for attr in attributes
]
# generate figure
figure = fig.bar_chart(labels=labels,
counts=counts,
ids=ids,
params=params)
return figure