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| import random | |
| import numpy as np | |
| import plotly.express as px | |
| import streamlit as st | |
| import xlsxwriter | |
| import pandas as pd | |
| from .lib import initialise_storytelling, set_input | |
| import io | |
| def run_create_statistics(gen, container_guide, container_param, container_button): | |
| first_sentence, first_emotion, length = initialise_storytelling( | |
| gen, container_guide, container_param, container_button) | |
| # story_till_now = first_sentence | |
| num_generation = set_input(container_param, | |
| label='Number of generation', min_value=1, max_value=100, value=5, step=1, | |
| key_slider='num_generation_slider', key_input='num_generation_input',) | |
| num_tests = set_input(container_param, | |
| label='Number of tests', min_value=1, max_value=1000, value=3, step=1, | |
| key_slider='num_tests_slider', key_input='num_tests_input',) | |
| reaction_weight_mode = container_param.radio( | |
| "Reaction Weight w:", ["Random", "Fixed"]) | |
| if reaction_weight_mode == "Fixed": | |
| reaction_weight = set_input(container_param, | |
| label='Reaction Weight w', min_value=0.0, max_value=1.0, value=0.5, step=0.01, | |
| key_slider='w_slider', key_input='w_input',) | |
| elif reaction_weight_mode == "Random": | |
| reaction_weight = -1 | |
| if container_button.button('Analyse'): | |
| gen.get_stats(story_till_now=first_sentence, | |
| num_generation=num_generation, length=length, reaction_weight=reaction_weight, num_tests=num_tests) | |
| # if len(gen.stories) > 0: | |
| # for si, story in enumerate(gen.stories): | |
| # st.markdown(f'### Story no. {si}:', unsafe_allow_html=False) | |
| # st.markdown(story, unsafe_allow_html=False) | |
| # data=gen.stats_df[gen.stats_df.sentence_no==3] | |
| # fig = px.violin(data_frame=data, x="reaction_weight", y="num_reactions", hover_data=data.columns) | |
| # st.plotly_chart(fig, use_container_width=True) | |
| # fig2 = px.box(data_frame=data, x="reaction_weight", y="num_reactions", hover_data=data.columns) | |
| # st.plotly_chart(fig2, use_container_width=True) | |
| if len(gen.data) > 0: | |
| for si, story in enumerate(gen.data): | |
| st.markdown(f'### Story {si}:', unsafe_allow_html=False) | |
| for i, sentence in enumerate(story): | |
| col_turn, col_sentence, col_emo = st.columns([1, 8, 2]) | |
| col_turn.markdown( | |
| sentence['turn'], unsafe_allow_html=False) | |
| col_sentence.markdown( | |
| sentence['sentence'], unsafe_allow_html=False) | |
| col_emo.markdown( | |
| f'{sentence["emotion"]} {np.round(sentence["confidence_score"], 3)}', unsafe_allow_html=False) | |
| st.table(data=gen.stats_df, ) | |
| data = gen.stats_df[gen.stats_df.sentence_no == 3] | |
| fig = px.violin(data_frame=data, x="reaction_weight", | |
| y="num_reactions", hover_data=data.columns) | |
| st.plotly_chart(fig, use_container_width=True) | |
| fig2 = px.box(data_frame=data, x="reaction_weight", | |
| y="num_reactions", hover_data=data.columns) | |
| st.plotly_chart(fig2, use_container_width=True) | |
| # csv = gen.stats_df.to_csv().encode('utf-8') | |
| buffer = io.BytesIO() | |
| with pd.ExcelWriter(buffer, engine='xlsxwriter') as writer: | |
| # Write each dataframe to a different worksheet. | |
| gen.stats_df.to_excel(writer, sheet_name='AllData') | |
| # Close the Pandas Excel writer and output the Excel file to the buffer | |
| writer.save() | |
| st.download_button( | |
| label="Download data", | |
| data=buffer, | |
| file_name='data.xlsx', | |
| mime='application/vnd.ms-excel', | |
| ) | |
| else: | |
| container_guide.markdown( | |
| '### You selected statistics. Now set your parameters and click the `Analyse` button.') | |