june.groups.school¶
-
exception
june.groups.school.
SchoolError
¶ -
__init__
(*args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
-
with_traceback
()¶ Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
-
args
¶
-
-
class
june.groups.school.
School
(coordinates: Tuple[float, float] = None, n_pupils_max: int = None, age_min: int = 0, age_max: int = 18, sector: str = None, area: june.geography.geography.Area = None, n_classrooms: Optional[int] = None, years: Optional[int] = None)¶ Create a School given its description.
- coordinates:
latitude and longitude
- n_pupils_max:
maximum number of pupils that can attend the school
- age_min:
minimum age of the pupils
- age_max:
maximum age of the pupils
- sector:
whether it is a “primary”, “secondary” or both “primary_secondary”
- area:
area the school belongs to
- n_classrooms:
number of classrooms in the school
- years:
age group year per classroom
number of SubGroups N = age_max-age_min year +1 (student years) + 1 (teachers): 0 - teachers 1 - year of lowest age (age_min) … n - year of highest age (age_max)
-
__init__
(coordinates: Tuple[float, float] = None, n_pupils_max: int = None, age_min: int = 0, age_max: int = 18, sector: str = None, area: june.geography.geography.Area = None, n_classrooms: Optional[int] = None, years: Optional[int] = None)¶ Create a School given its description.
- coordinates:
latitude and longitude
- n_pupils_max:
maximum number of pupils that can attend the school
- age_min:
minimum age of the pupils
- age_max:
maximum age of the pupils
- sector:
whether it is a “primary”, “secondary” or both “primary_secondary”
- area:
area the school belongs to
- n_classrooms:
number of classrooms in the school
- years:
age group year per classroom
number of SubGroups N = age_max-age_min year +1 (student years) + 1 (teachers): 0 - teachers 1 - year of lowest age (age_min) … n - year of highest age (age_max)
-
_collate_from_subgroups
(attribute: str) → List[june.demography.person.Person]¶ Return a set of all of the people in the subgroups with a particular health status
- attribute
The name of the attribute in the subgroup, e.g. “in_hospital”
The union of all the sets with the given attribute name in all of the sub groups.
-
classmethod
_next_id
() → int¶ Iterate an id for this class. Each group class has its own id iterator starting at 0
-
add
(person, subgroup_type=<SubgroupType.students: 1>)¶ Add a person to a given subgroup. For example, in a school a student is added to the subgroup matching their age.
- person
A person
group_type
-
clear
()¶
-
get_spec
() → str¶ Returns the speciailization of the group.
-
limit_classroom_sizes
(max_classroom_size: int)¶ Make all subgroups smaller than
`max_classroom_size`
- max_classroom_size:
maximum number of students per classroom (subgroup)
-
remove_person
(person: june.demography.person.Person)¶ Remove a person from this group by removing them from the subgroup to which they belong
- person
A person
-
_abc_impl
= <_abc_data object>¶
-
age_max
¶
-
age_min
¶
-
age_structure
¶
-
property
contains_people
¶ Does this group contain at least one person?
-
coordinates
¶
-
property
dead
¶
-
external
= False¶
-
id
¶
-
property
in_hospital
¶
-
property
infected
¶
-
property
is_full
¶
-
property
must_timestep
¶
-
property
n_pupils
¶
-
n_pupils_max
¶
-
property
n_teachers
¶
-
n_teachers_max
¶
-
property
name
¶ The name is computed on the fly to reduce memory footprint. It combines the name fo the class with the id of the instance.
-
property
people
¶ All the people in this group
-
property
recovered
¶
-
sector
¶
-
property
size
¶
-
property
size_infected
¶
-
property
size_recovered
¶
-
property
size_susceptible
¶
-
spec
¶
-
property
students
¶
-
subgroups
¶
-
property
super_area
¶
-
property
susceptible
¶
-
property
teachers
¶
-
years
¶
-
class
june.groups.school.
Schools
(schools: List[School], school_trees: Optional[Dict[int, sklearn.neighbors._ball_tree.BallTree]] = None, agegroup_to_global_indices: dict = None)¶ Create a group of Schools, and provide functionality to access closest school
- area_names
list of areas for which to build schools
- schools:
list of school instances
- school_tree:
BallTree built on all schools coordinates
- agegroup_to_global_indices:
dictionary to map the
-
__init__
(schools: List[School], school_trees: Optional[Dict[int, sklearn.neighbors._ball_tree.BallTree]] = None, agegroup_to_global_indices: dict = None)¶ Create a group of Schools, and provide functionality to access closest school
- area_names
list of areas for which to build schools
- schools:
list of school instances
- school_tree:
BallTree built on all schools coordinates
- agegroup_to_global_indices:
dictionary to map the
-
static
_create_school_tree
(schools_coordinates: numpy.ndarray) → sklearn.neighbors._ball_tree.BallTree¶ Reads school location and sizes, it initializes a KD tree on a sphere, to query the closest schools to a given location.
- school_df:
dataframe with school characteristics data
Tree to query nearby schools
-
_make_member_ids_dict
(members)¶ Makes a dictionary with the ids of the members.
-
add
(group)¶
-
classmethod
build_schools_for_areas
(areas: june.geography.geography.Areas, school_df: pandas.core.frame.DataFrame, age_range: Tuple[int, int] = 0, 19, employee_per_clients: Dict[str, int] = None) → june.groups.school.Schools¶ area Returns ——-
An infrastructure of schools
-
clear
()¶
-
classmethod
for_areas
(areas: june.geography.geography.Areas, data_file: str = PosixPath('/home/sadie/JUNE/data/input/schools/england_schools.csv'), config_file: str = PosixPath('/home/sadie/JUNE/configs/defaults/groups/schools.yaml')) → june.groups.school.Schools¶ - area_names
list of areas for which to create populations
- data_path
The path to the data directory
config
-
classmethod
for_box_mode
()¶
-
classmethod
for_geography
(geography: june.geography.geography.Geography, data_file: str = PosixPath('/home/sadie/JUNE/data/input/schools/england_schools.csv'), config_file: str = PosixPath('/home/sadie/JUNE/configs/defaults/groups/schools.yaml')) → june.groups.school.Schools¶ - geography
an instance of the geography class
-
classmethod
from_file
(areas: june.geography.geography.Areas, data_file: str = PosixPath('/home/sadie/JUNE/data/input/schools/england_schools.csv'), config_file: str = PosixPath('/home/sadie/JUNE/configs/defaults/groups/schools.yaml')) → june.groups.school.Schools¶ Initialize Schools from path to data frame, and path to config file
- filename:
path to school dataframe
- config_filename:
path to school config dictionary
Schools instance
-
get_closest_schools
(age: int, coordinates: Tuple[float, float], k: int) → int¶ Get the k-th closest school to a given coordinate, that accepts pupils aged age
- age:
age of the pupil
- coordinates:
latitude and longitude
- k:
k-th neighbour
ID of the k-th closest school, within school trees for a given age group
-
get_from_id
(id)¶
-
get_spec
() → str¶ Returns the speciailization of the super group.
-
static
init_trees
(school_df: pandas.core.frame.DataFrame, age_range: Tuple[int, int]) → june.groups.school.Schools¶ Create trees to easily find the closest school that accepts a pupil given their age
- school_df:
dataframe with school characteristics data
-
property
group_spec
¶
-
property
member_ids
¶