Merge pull request #12 from UNGlobalPulse/dev_contactmatrices

Dev contactmatrices

camp_scripts/full_run_parse.py

@@ -404,7 +404,7 @@ def set_seed_numba(seed):
         learning_centers_sorted = learning_centers[np.argsort(enrolled)]
 
         # find top k most filled learning centers
-        top_k = learning_centers_sorted[-int(args.extra_learning_centers):]
+        top_k = learning_centers_sorted[-int(args.extra_learning_centers) :]
         for learning_center in top_k:
             extra_lc = LearningCenter(
                 coordinates=learning_center.super_area.coordinates

camp_scripts/full_run_parse_new.py

@@ -416,7 +416,7 @@ def set_seed_numba(seed):
         learning_centers_sorted = learning_centers[np.argsort(enrolled)]
 
         # find top k most filled learning centers
-        top_k = learning_centers_sorted[-int(args.extra_learning_centers):]
+        top_k = learning_centers_sorted[-int(args.extra_learning_centers) :]
         for learning_center in top_k:
             extra_lc = LearningCenter(
                 coordinates=learning_center.super_area.coordinates

camp_scripts/full_run_parse_newJoe.py

@@ -437,10 +437,12 @@ def set_seed_numba(seed):
 else:
     world = generate_empty_world({"region": args.region_only})
 
+print("Now populate")
 # populate empty world
 populate_world(world)
 
 # distribute people to households
+print("Now Distribute")
 distribute_people_to_households(world)
 
 # medical facilities
@@ -489,7 +491,7 @@ def set_seed_numba(seed):
         learning_centers_sorted = learning_centers[np.argsort(enrolled)]
 
         # find top k most filled learning centers
-        top_k = learning_centers_sorted[-int(args.extra_learning_centers):]
+        top_k = learning_centers_sorted[-int(args.extra_learning_centers) :]
         for learning_center in top_k:
             extra_lc = LearningCenter(
                 coordinates=learning_center.super_area.coordinates
@@ -715,10 +717,6 @@ def set_seed_numba(seed):
 # df = pd.DataFrame(index=mi, columns=["CXB-207"])
 df[:] = args.n_seeding_case_per_day / len(world.people)
 
-print("#### seeding df:")
-print(df)
-print("####")
-
 infection_seed = InfectionSeed(
     world=world,
     infection_selector=selector,
@@ -768,7 +766,6 @@ def set_seed_numba(seed):
         group_types=group_types,
         load_interactions_path=args.parameters,
         contact_sexes=["unisex", "male", "female"],
-        Tracker_Contact_Type=["1D", "All"],
     )
 else:
     tracker = None
@@ -821,41 +818,3 @@ def set_seed_numba(seed):
     simulator.tracker.contract_matrices("AC", np.array([0, 18, 60]))
     simulator.tracker.contract_matrices("All", np.array([0, 100]))
     simulator.tracker.post_process_simulation(save=True)
-
-    # Make Plots
-    Plots = PlotClass(record_path=args.save_path / "Tracker", Tracker_Contact_Type="1D")
-    Plots.make_plots(
-        plot_BBC=True,
-        plot_thumbprints=True,
-        SameCMAP="Log",
-        plot_INPUTOUTPUT=True,
-        plot_AvContactsLocation=True,
-        plot_dTLocationPopulation=True,
-        plot_InteractionMatrices=True,
-        plot_ContactMatrices=True,
-        plot_CompareSexMatrices=True,
-        plot_AgeBinning=True,
-        plot_Distances=True,
-
-        MaxAgeBin=60
-    )
-
-    # Make Plots
-    Plots = PlotClass(
-        record_path=args.save_path / "Tracker", Tracker_Contact_Type="All"
-    )
-    Plots.make_plots(
-        plot_BBC=True,
-        plot_thumbprints=True,
-        SameCMAP="Log",
-        plot_INPUTOUTPUT=False,
-        plot_AvContactsLocation=False,
-        plot_dTLocationPopulation=False,
-        plot_InteractionMatrices=True,
-        plot_ContactMatrices=True,
-        plot_CompareSexMatrices=True,
-        plot_AgeBinning=False,
-        plot_Distances=False,
-
-        MaxAgeBin=60
-    )

camps/camp_creation.py

@@ -96,21 +96,29 @@ def read_yaml(config_filename):
 # area_household_structure_params_exists = False
 
 
-def GenerateDiscretePDF(Type="Gaussian", datarange=[0, 100], Mean=0, SD=1, stretch=False):
+def GenerateDiscretePDF(
+    Type="Gaussian", datarange=[0, 100], Mean=0, SD=1, stretch=False
+):
     def PValue(Mean, SD, Xmin, Xmax, stretch=False):
         return integrate.quad(lambda x: Gaussian(Mean, SD, x, stretch), Xmin, Xmax)
 
-
-    def Gaussian(Mean, SD, x,stretch):
+    def Gaussian(Mean, SD, x, stretch):
         if stretch:
             if abs(x - Mean) < 2:
-                return 4*np.exp(-0.5 * ((x - Mean) / SD) ** 2.0) / (SD * np.sqrt(2 * np.pi))
+                return (
+                    4
+                    * np.exp(-0.5 * ((x - Mean) / SD) ** 2.0)
+                    / (SD * np.sqrt(2 * np.pi))
+                )
             else:
-                return 1*np.exp(-0.5 * ((x - Mean) / SD) ** 2.0) / (SD * np.sqrt(2 * np.pi))
+                return (
+                    1
+                    * np.exp(-0.5 * ((x - Mean) / SD) ** 2.0)
+                    / (SD * np.sqrt(2 * np.pi))
+                )
         else:
             return np.exp(-0.5 * ((x - Mean) / SD) ** 2.0) / (SD * np.sqrt(2 * np.pi))
 
-
     Vals = np.arange(datarange[0], datarange[1] + 1, 1)
     dist = {}
     for a_i in range(len(Vals) - 1):
@@ -252,9 +260,7 @@ def distribute_people_to_households(world: CampWorld):
             ]["min_age_gap_between_childen"],
         )
     else:
-        household_distributor = CampHouseholdDistributor(
-            max_household_size=12,
-        )
+        household_distributor = CampHouseholdDistributor(max_household_size=12)
 
     households_total = []
     for area in world.areas:
@@ -300,20 +306,17 @@ def distribute_people_to_households(world: CampWorld):
         mother_firstchild_gap_generator, dist = GenerateDiscretePDF(
             datarange=[14, 60],
             Mean=mother_firstchild_gap_mean + 0.5 + (9.0 / 12.0),
-            SD=mother_firstchild_gap_STD
-
+            SD=mother_firstchild_gap_STD,
         )
         partner_age_gap_generator, dist = GenerateDiscretePDF(
-            datarange=[-20, 20], 
-            Mean=partner_age_gap_mean + 0.5, 
+            datarange=[-20, 20],
+            Mean=partner_age_gap_mean + 0.5,
             SD=partner_age_gap_mean_STD,
-            stretch=stretch
+            stretch=stretch,
         )
 
         nchildren_generator, dist = GenerateDiscretePDF(
-            datarange=[0, 8], 
-            Mean=n_children, 
-            SD=n_children_STD,
+            datarange=[0, 8], Mean=n_children, SD=n_children_STD
         )
 
         n_families = int(area_data["families"])

camps/distributors/__init__.py

@@ -1,3 +1,3 @@
-#from .camp_household_distributor_legacy import CampHouseholdDistributor
+# from .camp_household_distributor_legacy import CampHouseholdDistributor
 from .camp_household_distributor import CampHouseholdDistributor
 from .learning_center_distributor import LearningCenterDistributor

camps/distributors/camp_household_distributor.py

@@ -405,8 +405,7 @@ def not_in(list_A, list_B, permute=True):
 
         Houses_Single = list(
             np.random.choice(
-                np.array(Houses_W_Children)[indexes],
-                size=n_families_singleparent,
+                np.array(Houses_W_Children)[indexes], size=n_families_singleparent
             )
         )
         household_Single_sizes = np.array(
@@ -451,6 +450,7 @@ def not_in(list_A, list_B, permute=True):
 
         # put adults households with kids start
         Intersection = intersection(Houses_W_Children, households_with_space)
+        # print(f"Point A: {len(Intersection)},Nkids:{n_kids},Nmen:{n_men},Nkids:{n_women}")
         for household in Intersection:
             # Single House
             if household in Houses_Single:
@@ -487,7 +487,7 @@ def not_in(list_A, list_B, permute=True):
             # House now full?
             if household.size >= household.max_size:
                 households_with_space.remove(household)
-        #print("Parents done")
+        # print("Parents done")
 
         # Distribute all the children
         Loop_1 = True
@@ -499,13 +499,16 @@ def not_in(list_A, list_B, permute=True):
             if Loop_1:
                 Intersection = intersection(Houses_W_Children, households_with_space)
             else:
-                Intersection = intersection(not_in(Houses_W_Children,Houses_Single), households_with_space)
+                Intersection = intersection(
+                    not_in(Houses_W_Children, Houses_Single), households_with_space
+                )
 
             if len(Intersection) == 0:
                 # Need to find space for final children we sqeeze them into Houses_W_Children even if full
                 squeeze = True
                 Intersection = intersection(Houses_W_Children, Houses_W_Children)
 
+            # print(f"Point B: {len(Intersection)},Nkids:{n_kids},Nmen:{n_men},Nkids:{n_women}")
             for household in Intersection:
                 NKids = len(household.kids)
                 NAdults = len(household.adults)
@@ -575,6 +578,7 @@ def not_in(list_A, list_B, permute=True):
             if len(Intersection) == 0:
                 break
 
+            # print(f"Point C: {len(Intersection)},Nkids:{n_kids},Nmen:{n_men},Nkids:{n_women}")
             for household in Intersection:
                 NKids = len(household.kids)
                 NAdults = len(household.adults)
@@ -620,7 +624,7 @@ def not_in(list_A, list_B, permute=True):
                 # Check if we finished up adults
                 if not men_by_age and not women_by_age:
                     break
-        #print("All multigen adults done")
+        # print("All multigen adults done")
 
         while True:
             sqeeze = False
@@ -635,19 +639,22 @@ def not_in(list_A, list_B, permute=True):
                         sqeeze = True
                         Intersection = intersection(Houses_Multigen, Houses_Multigen)
 
-                #Find houses with space
+                # Find houses with space
                 if len(households_with_space) > 0:
-                    Intersection = intersection(households_with_space, households_with_space)
+                    Intersection = intersection(
+                        households_with_space, households_with_space
+                    )
                 else:
                     # Sqeeze in the final adults
                     sqeeze = True
                     Intersection = intersection(Houses_WO_Children, Houses_WO_Children)
 
+            # print(f"Point D: {len(Intersection)},Nkids:{n_kids},Nmen:{n_men},Nkids:{n_women}")
             if len(Intersection) == 0:
                 sqeeze = True
-                intersection(households, households)
-
+                Intersection = intersection(households, households)
 
+            # print(f"Point E: {len(Intersection)},Nkids:{n_kids},Nmen:{n_men},Nkids:{n_women}")
             for household in Intersection:
                 NAdults = len(household.adults)
 
@@ -708,8 +715,9 @@ def not_in(list_A, list_B, permute=True):
                 # Check if we finished up adults
                 if not men_by_age and not women_by_age:
                     break
-        #print("All adults only houses done")
+        # print("All adults only houses done")
 
+        # print(f"END")
         # check everyone has a house
         people_in_households = len(
             [person for household in households for person in household.people]

camps/distributors/camp_household_distributor_legacy.py

@@ -230,9 +230,7 @@ def get_closest_person_of_age(self, men_by_age, women_by_age, age, sex):
                 return None
 
     def distribute_people_to_households(
-        self,
-        area: Area,
-        n_families: int,
+        self, area: Area, n_families: int
     ) -> Households:
         """
         Distributes people to household given an area with a given number of families

test_camps/test_shelter_visits.py

@@ -31,7 +31,7 @@ def setup_shelter_visits(camps_world):
         daytypes={
             "weekday": ["Sunday", "Monday", "Tuesday", "Wednesday", "Thursday"],
             "weekend": ["Friday", "Saturday"],
-        },
+        }
     )
     shelter_visits_distributor.link_shelters_to_shelters(camps_world.super_areas)
     return camps_world