# DATAFRAME SAVING print("\n\n--------------------Started dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_cremad_female)) cremad_f_df_obj = confc.DataFrame(database=confv.database_cremad, gender=confv.gender_female, df=data_info_cremad_df_f) sl.save_dataframe(cremad_f_df_obj) print("--------------------Finished dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_cremad_female)) ''' # LOAD REQUIRED PICKLE print( "\n\n--------------------Started dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_female, name=confv.dataset_cremad_female)) cremad_f_df_obj = confc.DataFrame(database=confv.database_cremad, gender=confv.gender_female) cremad_f_df_obj = sl.load_dataframe(cremad_f_df_obj) data_info_cremad_df_f = cremad_f_df_obj.df print(cremad_f_df_obj.database) print(cremad_f_df_obj.gender) print(len(data_info_cremad_df_f)) print(data_info_cremad_df_f.head()) print(data_info_cremad_df_f.tail()) print(cremad_f_df_obj.dataset) print(cremad_f_df_obj.save_path) print( "--------------------Finished dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_female, name=confv.dataset_cremad_female)) ''' # ORIGINAL DATA DISTRIBUTION ANALYSIS SECTION print("\n\n--------------------Started original data distribution analysis for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_cremad_female)) pc.emotion_distribution_bar_plot(df=data_info_cremad_df_f, title="{database} - {gender} Isolation - No. of Files".format(database=confv.database_cremad, gender=confv.gender_female))
# DATAFRAME SAVING print("\n\n--------------------Started dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_ravdess_female)) ravdess_f_df_obj = confc.DataFrame(database=confv.database_ravdess, gender=confv.gender_female, df=data_info_ravdess_df_f) sl.save_dataframe(ravdess_f_df_obj) print("--------------------Finished dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_ravdess_female)) ''' # LOAD REQUIRED PICKLE print( "\n\n--------------------Started dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_female, name=confv.dataset_ravdess_female)) ravdess_f_df_obj = confc.DataFrame(database=confv.database_ravdess, gender=confv.gender_female) ravdess_f_df_obj = sl.load_dataframe(ravdess_f_df_obj) data_info_ravdess_df_f = ravdess_f_df_obj.df print(ravdess_f_df_obj.database) print(ravdess_f_df_obj.gender) print(len(data_info_ravdess_df_f)) print(data_info_ravdess_df_f.head()) print(data_info_ravdess_df_f.tail()) print(ravdess_f_df_obj.dataset) print(ravdess_f_df_obj.save_path) print( "--------------------Finished dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_female, name=confv.dataset_ravdess_female)) ''' # ORIGINAL DATA DISTRIBUTION ANALYSIS SECTION print("\n\n--------------------Started original data distribution analysis for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_ravdess_female)) pc.emotion_distribution_bar_plot(df=data_info_ravdess_df_f, title="{database} - {gender} Isolation - No. of Files".format(database=confv.database_ravdess, gender=confv.gender_female))
# DATAFRAME SAVING print("\n\n--------------------Started dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_shemo_female)) shemo_f_df_obj = confc.DataFrame(database=confv.database_shemo, gender=confv.gender_female, df=data_info_shemo_df_f) sl.save_dataframe(shemo_f_df_obj) print("--------------------Finished dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_shemo_female)) ''' # LOAD REQUIRED PICKLE print( "\n\n--------------------Started dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_female, name=confv.dataset_shemo_female)) shemo_f_df_obj = confc.DataFrame(database=confv.database_shemo, gender=confv.gender_female) shemo_f_df_obj = sl.load_dataframe(shemo_f_df_obj) data_info_shemo_df_f = shemo_f_df_obj.df print(shemo_f_df_obj.database) print(shemo_f_df_obj.gender) print(len(data_info_shemo_df_f)) print(data_info_shemo_df_f.head()) print(data_info_shemo_df_f.tail()) print(shemo_f_df_obj.dataset) print(shemo_f_df_obj.save_path) print( "--------------------Finished dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_female, name=confv.dataset_shemo_female)) ''' # ORIGINAL DATA DISTRIBUTION ANALYSIS SECTION print("\n\n--------------------Started original data distribution analysis for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_female, name=confv.dataset_shemo_female)) pc.emotion_distribution_bar_plot(df=data_info_shemo_df_f, title="{database} - {gender} Isolation - No. of Files".format(database=confv.database_shemo, gender=confv.gender_female))
# DATAFRAME SAVING print("\n\n--------------------Started dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_male, name=confv.dataset_emodb_male)) emodb_m_df_obj = confc.DataFrame(database=confv.database_emodb, gender=confv.gender_male, df=data_info_emodb_df_m) sl.save_dataframe(emodb_m_df_obj) print("--------------------Finished dataframe saving for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_male, name=confv.dataset_emodb_male)) ''' # LOAD REQUIRED PICKLE print( "\n\n--------------------Started dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_male, name=confv.dataset_emodb_male)) emodb_m_df_obj = confc.DataFrame(database=confv.database_emodb, gender=confv.gender_male) emodb_m_df_obj = sl.load_dataframe(emodb_m_df_obj) data_info_emodb_df_m = emodb_m_df_obj.df print(emodb_m_df_obj.database) print(emodb_m_df_obj.gender) print(len(data_info_emodb_df_m)) print(data_info_emodb_df_m.head()) print(data_info_emodb_df_m.tail()) print(emodb_m_df_obj.dataset) print(emodb_m_df_obj.save_path) print( "--------------------Finished dataframe loading for adjusted and {gender} isolated dataset: {name}--------------------" .format(gender=confv.gender_male, name=confv.dataset_emodb_male)) ''' # ORIGINAL DATA DISTRIBUTION ANALYSIS SECTION print("\n\n--------------------Started original data distribution analysis for adjusted and {gender} isolated dataset: {name}--------------------".format(gender=confv.gender_male, name=confv.dataset_emodb_male)) pc.emotion_distribution_bar_plot(df=data_info_emodb_df_m, title="{database} - {gender} Isolation - No. of Files".format(database=confv.database_emodb, gender=confv.gender_male))