Tox fixes

Author: marghe-molaro

src/scripts/Alri_analyses/alri_azure_run_scenarios/base_scenario_inc_mort_plots.py

@@ -9,7 +9,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-
 from tlo.analysis.utils import (
     extract_params,
     extract_results,

src/scripts/Alri_analyses/alri_azure_run_scenarios/base_scenario_plots.py

@@ -8,7 +8,6 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-
 from tlo.analysis.utils import (
     extract_params,
     extract_results,

src/scripts/Alri_analyses/alri_calibration_plots/GBD_comparison_plots.py

@@ -9,7 +9,6 @@
 
 import pandas as pd
 from matplotlib import pyplot as plt
-
 from tlo import Date, Simulation, logging
 from tlo.analysis.utils import compare_number_of_deaths, parse_log_file
 from tlo.methods import (

src/scripts/Alri_analyses/alri_calibration_plots/analysis_Alri_default_params.py

@@ -11,7 +11,6 @@
 
 import pandas as pd
 from matplotlib import pyplot as plt
-
 from tlo import Date, Simulation, logging
 from tlo.analysis.utils import compare_number_of_deaths, parse_log_file
 from tlo.methods import (

src/scripts/Alri_analyses/alri_calibration_plots/analysis_Alri_with_and_without_treatment.py

@@ -8,7 +8,6 @@
 
 import pandas as pd
 from matplotlib import pyplot as plt
-
 from tlo import Date, Simulation, logging
 from tlo.analysis.utils import parse_log_file
 from tlo.methods import (

src/scripts/Alri_analyses/alri_calibration_plots/analysis_effect_of_treatment.py

@@ -6,7 +6,6 @@
 
 import pandas as pd
 from matplotlib import pyplot as plt
-
 from tlo import Date, Simulation
 from tlo.methods import (
     alri,

src/scripts/Alri_analyses/alri_calibration_plots/analysis_pulse_oximeter_vs_none.py

@@ -9,7 +9,6 @@
 
 import pandas as pd
 from matplotlib import pyplot as plt
-
 from tlo import Date, Simulation, logging
 from tlo.analysis.utils import parse_log_file
 from tlo.methods import (

src/scripts/Alri_analyses/alri_calibration_plots/baseline_outputs.py

@@ -9,7 +9,6 @@
 
 import matplotlib.pyplot as plt
 import pandas as pd
-
 from tlo import Date, Simulation, logging
 from tlo.analysis.utils import parse_log_file
 from tlo.methods import (

src/scripts/analysis_data_generation/analysis_extract_data.py

@@ -4,17 +4,14 @@
 # short tclose -> ideal case
 # long tclose -> status quo
 import argparse
+from collections import Counter
+from datetime import datetime
 from pathlib import Path
 from typing import Tuple
 
 import pandas as pd
-import matplotlib.pyplot as plt
-
 from tlo import Date
-from tlo.analysis.utils import extract_results, extract_event_chains
-from datetime import datetime
-from collections import Counter
-import ast
+from tlo.analysis.utils import extract_event_chains, extract_results
 
 # Time simulated to collect data
 start_date = Date(2010, 1, 1)
@@ -76,7 +73,6 @@ def apply(results_folder: Path, output_folder: Path, resourcefilepath: Path = No
         'nan': float('nan'),       # Include NaN for eval (can also use pd.NA if preferred)
     }
 
-    initial_properties_of_interest = ['rt_MAIS_military_score','rt_ISS_score','rt_disability','rt_polytrauma','rt_injury_1','rt_injury_2','rt_injury_3','rt_injury_4','rt_injury_5','rt_injury_6', 'rt_imm_death','sy_injury','sy_severe_trauma','sex','li_urban', 'li_wealth', 'li_mar_stat', 'li_in_ed', 'li_ed_lev']
 
     # Will be added through computation: age at time of RTI
     # Will be added through computation: total duration of event
@@ -104,17 +100,7 @@ def apply(results_folder: Path, output_folder: Path, resourcefilepath: Path = No
             )
 
         for r in range(0,num_runs):
-            initial_properties = {}
-            key_first_event = {}
-            key_last_event = {}
-            first_event = {}
-            last_event = {}
-            properties = {}
-            average_disability = 0
-            total_dt_included = 0
-            dt_in_prev_disability = 0
-            prev_disability_incurred = 0
-            ind_Counter = {'0': Counter(), '1a': Counter(), '1b' : Counter(), '2' : Counter()}
+            {'0': Counter(), '1a': Counter(), '1b' : Counter(), '2' : Counter()}
             # Count total appts
 
             list_for_individual = []

src/scripts/analysis_data_generation/postprocess_events_chain.py

@@ -1,6 +1,7 @@
 import pandas as pd
 from dateutil.relativedelta import relativedelta
 
+
 # Remove from every individual's event chain all events that were fired after death
 def cut_off_events_after_death(df):