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Fixed: Fixed a bug with session state that cause the front-end to han…
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…g. Changed: Changed the name of Two features scatter-plot to Two features plot, to better reflect the resuting visualization.
AAnzel committed Dec 12, 2021

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dovydas55 Dovydas Stankevicius
1 parent 50d5e07 commit 3673c44
Showing 6 changed files with 25 additions and 30 deletions.
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53 changes: 23 additions & 30 deletions Source/common.py
Original file line number Diff line number Diff line change
@@ -757,7 +757,7 @@ def show_calculated_data_set(df, text_info):
def show_clustering_info(df, key_suffix):

clustering_methods = st.multiselect(
'Choose clustering method:', ['K-Means', 'OPTICS'],
'Choose clustering method:', options=['K-Means', 'OPTICS'],
key='choose_clus' + key_suffix
)

@@ -1212,7 +1212,7 @@ def modify_data_set(orig_df, temporal_column, feature_list, key_suffix):

if filter_checkbox:
columns_to_remove = st.multiselect(
'Select columns to remove', feature_list,
'Select columns to remove', options=feature_list,
key='Col_remove_' + key_suffix)

if len(columns_to_remove) != 0:
@@ -1547,22 +1547,18 @@ def work_with_data_set(df, data_set_type, folder_path, recache, key_suffix):
def visualize_data_set(df, temporal_feature, feature_list, key_suffix):

chosen_charts = []
feature_list = list(feature_list)

if key_suffix.startswith('Cluster'):
visualizations = st.multiselect('Choose your visualization',
['PCA visualization',
'MDS visualization',
't-SNE visualization'],
key='vis_data_' + key_suffix)
visualizations = st.multiselect(
'Choose your visualization', options=['PCA visualization',
'MDS visualization', 't-SNE visualization'],
key='vis_data_' + key_suffix)
else:
visualizations = st.multiselect('Choose your visualization',
['Feature through time',
'Two features scatter-plot',
'Scatter-plot matrix',
'Multiple features parallel chart',
'Heatmap',
'Top 10 share through time'],
key='vis_data_' + key_suffix)
options=['Feature through time', 'Two features plot',
'Scatter-plot matrix', 'Multiple features parallel chart', 'Heatmap',
'Top 10 share through time'], key='vis_data_' + key_suffix)

for i in visualizations:
# I have to check which clustering method was used and visualize it
@@ -1586,25 +1582,22 @@ def visualize_data_set(df, temporal_feature, feature_list, key_suffix):

elif i == 'Feature through time' and temporal_feature is not None:
selected_features = st.multiselect(
i + ': select features to visualize', feature_list)
i + ': select features to visualize', options=feature_list)

encode_feature_color = st.checkbox(
'Encode one nominal feature with color?',
key=i + '_' + key_suffix + 'color checkbox')

if encode_feature_color:
for j in selected_features:
feature_list.remove(j)
color_feature_list = [feature for feature in feature_list
if feature not in selected_features]
target_feature = st.selectbox(
i + ': select target feature', feature_list)
i + ': select target feature', color_feature_list)

if target_feature in feature_list:
feature_list.remove(target_feature)

for j in selected_features:
for one_feature in selected_features:
chosen_charts.append(
(visualize.time_feature(
df, j, temporal_feature, target_feature),
df, one_feature, temporal_feature, target_feature),
i + '_' + key_suffix))
else:
for j in selected_features:
@@ -1613,18 +1606,18 @@ def visualize_data_set(df, temporal_feature, feature_list, key_suffix):
df, j, temporal_feature, None),
i + '_' + key_suffix))

elif i == 'Two features scatter-plot':
elif i == 'Two features plot':
feature_1 = None
feature_2 = None

feature_1 = st.selectbox(i + ': select 1. feature', feature_list,
key=i + '_' + key_suffix + '1. feature')

if feature_1 in feature_list:
feature_list.remove(feature_1)
new_feature_list = [i for i in feature_list if i != feature_1]

feature_2 = st.selectbox(i + ': select 2. feature', feature_list,
key=i + '_' + key_suffix + '2. feature')
feature_2 = st.selectbox(
i + ': select 2. feature', new_feature_list,
key=i + '_' + key_suffix + '2. feature')

if feature_1 is not None and feature_2 is not None:
chosen_charts.append(
@@ -1637,7 +1630,7 @@ def visualize_data_set(df, temporal_feature, feature_list, key_suffix):
i + ': select target feature for color', feature_list)

list_of_features = st.multiselect(
i + ': choose at least 2 features', feature_list)
i + ': choose at least 2 features', options=feature_list)

if len(list_of_features) >= 2:
list_of_features.append(target_feature)
@@ -1659,7 +1652,7 @@ def visualize_data_set(df, temporal_feature, feature_list, key_suffix):
index=len(feature_list))

list_of_features = st.multiselect(
i + ': choose at least 2 features', feature_list)
i + ': choose at least 2 features', options=feature_list)

if len(list_of_features) >= 2:
list_of_features.append(target_feature)

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