utils, brc, co & hs: fix mistakes from rebase; TODO added

src/tlo/analysis/utils.py

@@ -263,7 +263,7 @@ def get_multiplier(_draw, _run):
                                            )['tlo.methods.population']['scaling_factor']['scaling_factor'].values[0]
 
     if custom_generate_series is None:
-        # If there is no `custom_generate_series` provided, it implies that function required selects a the specified
+        # If there is no `custom_generate_series` provided, it implies that function required selects the specified
         # column from the dataframe.
         assert column is not None, "Must specify which column to extract"
     else:

src/tlo/methods/breast_cancer.py

@@ -574,7 +574,7 @@ class BreastCancerMainPollingEvent(RegularEvent, PopulationScopeEventMixin):
 
     def __init__(self, module):
         super().__init__(module, frequency=DateOffset(months=1))
-        # scheduled to run every 3 months: do not change as this is hard-wired into the values of all the parameters.
+        # scheduled to run every month: do not change as this is hard-wired into the values of all the parameters.
 
     def apply(self, population):
         df = population.props  # shortcut to dataframe
@@ -645,7 +645,8 @@ def __init__(self, module, person_id):
 
         self.TREATMENT_ID = "BreastCancer_Investigation"
         self.EXPECTED_APPT_FOOTPRINT = self.make_appt_footprint({"Over5OPD": 1, "Mammography": 1})
-        self.ACCEPTED_FACILITY_LEVEL = '3'  # Mammography only available at level 3 and above.
+        self.ACCEPTED_FACILITY_LEVEL = '3'  # Biopsy only available at level 3 and above.
+        # TODO: but the appt footprints suggests mammography to be provided
 
     def apply(self, person_id, squeeze_factor):
         df = self.sim.population.props

src/tlo/methods/contraception.py

@@ -353,7 +353,7 @@ def avoid_sterilization_below30(probs):
             # Increase prob of 'female_sterilization' in older women accordingly
             probs_30plus = probs.copy()
             probs_30plus['female_sterilization'] = (
-                probs.loc['female_sterilization'] / 
+                probs.loc['female_sterilization'] /
                 self.ratio_n_females_30_49_to_15_49_in_2010
             )
             # Scale so that the probability of all outcomes sum to 1.0
@@ -633,7 +633,7 @@ def avoid_sterilization_below30(probs):
             # Increase prob of 'female_sterilization' in older women accordingly
             probs_30plus = probs.copy()
             probs_30plus['female_sterilization'] = (
-                probs.loc['female_sterilization'] / 
+                probs.loc['female_sterilization'] /
                 self.ratio_n_females_30_49_to_15_49_in_2010
             )
             # Scale so that the probability of all outcomes sum to 1.0
@@ -736,6 +736,7 @@ def get_item_code_for_each_contraceptive(self):
         get_items_from_pkg = self.sim.modules['HealthSystem'].get_item_codes_from_package_name
 
         _cons_codes = dict()
+        # items for each method that requires an HSI to switch to
         _cons_codes['pill'] = get_items_from_pkg('Pill')
         _cons_codes['male_condom'] = get_items_from_pkg('Male condom')
         _cons_codes['other_modern'] = get_items_from_pkg('Female Condom')
@@ -745,6 +746,7 @@ def get_item_code_for_each_contraceptive(self):
         _cons_codes['implant'] = get_items_from_pkg('Implant')
         _cons_codes['female_sterilization'] = get_items_from_pkg('Female sterilization')
         assert set(_cons_codes.keys()) == set(self.states_that_may_require_HSI_to_switch_to)
+        # items used when initiating a modern reliable method after not using or switching from non-reliable method
         _cons_codes['co_initiation'] = get_items_from_pkg('Contraception initiation')
 
         return _cons_codes

src/tlo/methods/healthsystem.py

@@ -355,7 +355,7 @@ def initialise(self):
             # If there are bed-days specified, add (if needed) the in-patient admission and in-patient day Appointment
             # Types.
             # (HSI that require a bed for one or more days always need such appointments, but this may have been
-            # missed in the declaration of the `EXPECTED_APPPT_FOOTPRINT` in the HSI.)
+            # missed in the declaration of the `EXPECTED_APPT_FOOTPRINT` in the HSI.)
             # NB. The in-patient day Appointment time is automatically applied on subsequent days.
             if sum(self.BEDDAYS_FOOTPRINT.values()):
                 self.EXPECTED_APPT_FOOTPRINT = health_system.bed_days.add_first_day_inpatient_appts_to_footprint(