"""
This module contains the classes and functions for creating demographics files
for malaria simulations. For more information on |EMOD_s| demographics files,
see :doc:`emod/software-demographics`.
"""
import os
import emod_api.demographics.Demographics as Demog
from emod_api.demographics import DemographicsTemplates as DT
import emod_api.config.default_from_schema_no_validation as dfs
[docs]
class MalariaDemographics(Demog.Demographics):
"""
This class is derived from :py:class:`emod_api:emod_api.demographics.Demographics.Demographics`
and sets certain defaults for malaria in construction.
Args:
nodes: The number of nodes to create.
idref: Method describing how the latitude and longitude values are created
for each of the nodes in a simulation. "Gridded world" values use a grid
overlaid across the globe at some arcsec resolution. You may also generate
the grid using another tool or coordinate system. For more information,
see :ref:`demo-metadata`.
base_file: A basic demographics file used as a starting point for
creating more complicated demographics files. For example,
using a single node file to create a multi-node file for spatial
simulations.
init_prev: The initial malaria prevalence of the population. Defaults to 0%.
include_biting_heterogeneity: variable biting rates. Defaults to on.
Returns:
None
"""
def __init__(self, nodes, idref="Gridded world grump2.5arcmin", base_file=None, init_prev=0.0,
include_biting_heterogeneity=True):
super().__init__(nodes, idref, base_file)
super().SetDefaultNodeAttributes(birth=True)
if init_prev > 0:
# Do constant intial prevalence as uniform with same min and max.
super().SetInitPrevFromUniformDraw(init_prev, init_prev, f"Constant Initial Prevalence ({init_prev})")
if include_biting_heterogeneity:
self.set_risk_lowmedium() # lognormal, default=1.6
[docs]
def set_risk_lowmedium(self):
"""
Set initial risk for low-medium transmission settings per:
https://wiki.idmod.org/display/MAL/Heterogeneous+biting+risk+in+simulations+vs+data.
"""
super().SetHeteroRiskLognormalDist(mean=0.0, sigma=1.6)
[docs]
def set_risk_high(self):
"""
Set initial risk for high transmission settings per:
https://wiki.idmod.org/display/MAL/Heterogeneous+biting+risk+in+simulations+vs+data.
"""
super().SetHeteroRiskExponDist(mean=1.0) # 1.0 is placeholder
[docs]
def add_larval_habitat_multiplier(self, schema, hab_type, multiplier, species="ALL_SPECIES", node_id=0):
"""
Add LarvalHabitatMultiplier to node(s).
Args:
schema: Path to schema.json.
hab_type: Habitat type.
multiplier: Multiplier or Factor.
species: Specific species (defaults to ALL).
node_id: Nodes for this LHM. Defaults to all.
Returns:
Nothing.
"""
lhm = dfs.schema_to_config_subnode(schema, ["idmTypes", "idmType:LarvalHabitatMultiplierSpec"])
lhm.parameters.Factor = multiplier
lhm.parameters.Habitat = hab_type
lhm.parameters.Species = species
lhm.parameters.finalize()
# set params
if node_id == 0:
if "LarvalHabitatMultiplier" in self.raw['Defaults']['NodeAttributes']:
lhm_dict = self.raw['Defaults']['NodeAttributes']["LarvalHabitatMultiplier"]
else:
lhm_dict = []
lhm_dict.append(lhm.parameters)
self.SetNodeDefaultFromTemplate({"LarvalHabitatMultiplier": lhm_dict}, setter_fn=None)
else:
if self.get_node(node_id).node_attributes.larval_habitat_multiplier:
lhm_dict = self.get_node(node_id).node_attributes.larval_habitat_multiplier
else:
lhm_dict = []
lhm_dict.append(lhm.parameters)
self.get_node(node_id).node_attributes.larval_habitat_multiplier = lhm_dict
[docs]
def add_initial_vectors_per_species(self, init_vector_species, node_ids=None):
"""
Add an InitialVectorsForSpecies configuration for all nodes or just a set of nodes.
Args:
init_vector_species: Dictionary of vector species (strings) to initial populations. There is no
checking for coherence of species named in other input settings.
node_ids: Array of node ids. Defaults to None for all nodes.
Returns:
N/A.
"""
if node_ids is None:
ivs_dict = dict()
ivs_dict["InitialVectorsPerSpecies"] = init_vector_species
self.SetNodeDefaultFromTemplate(ivs_dict, setter_fn=None)
else:
for node_id in node_ids:
self.get_node(node_id).node_attributes.add_parameter("InitialVectorsPerSpecies", init_vector_species)
# no implicits
[docs]
def add_initial_vectors_per_species_from_csv(self, csv_path):
"""
Add initial vector species population to 'demographics' nodes from a csv file.
Args:
csv_path: Path to CSV file with the initial vector species populations for each node.
Returns:
N/A.
"""
import csv
if not os.path.exists(csv_path):
raise ValueError(f"File not found at {csv_path}.")
with open(csv_path) as csv_file:
reader = csv.DictReader(csv_file)
for line in reader:
# collect all the initial vector species values for a given node.
node = int(line["node_id"])
ivps = dict()
for species in line:
if species != "node_id":
ivps[species] = int(line[species])
self.add_initial_vectors_per_species(ivps, [node])
[docs]
def from_template_node(lat=0, lon=0, pop=1e6, name=1, forced_id=1, init_prev=0.2, include_biting_heterogeneity=True):
"""
Create a single-node :py:class:`~emodpy_malaria.demographics.MalariaDemographics`
instance from the parameters you supply.
Args:
lat: Latitude of the centroid of the node to create.
lon: Longitude of the centroid of the node to create.
pop: Human population of the node.
name: The name of the node. This may be a characteristic of the
node, such as "rural" or "urban", or an identifying integer.
forced_id: The node ID for the single node.
init_prev: The initial malaria prevalence of the node.
Returns:
A :py:class:`~emodpy_malaria.demographics.MalariaDemographics` instance.
"""
new_nodes = [Demog.Node(lat=lat, lon=lon, pop=pop, name=name, forced_id=forced_id)]
return MalariaDemographics(nodes=new_nodes, init_prev=init_prev,
include_biting_heterogeneity=include_biting_heterogeneity)
[docs]
def from_pop_csv(pop_filename_in, pop_filename_out="spatial_gridded_pop_dir", site="No_Site"):
"""
Create a multi-node :py:class:`~emodpy_malaria.demographics.MalariaDemographics`
instance from a CSV file describing a population.
Args:
pop_filename_in: The path to the demographics file to ingest.
pop_filename_out: The path to the file to output.
site: A string to identify the country, village, or trial site.
Returns:
A :py:class:`~emodpy_malaria.demographics.MalariaDemographics` instance
"""
if not os.path.exists(pop_filename_in):
raise ValueError(f"Can't find input data file {pop_filename_in}")
generic_demog = Demog.from_pop_csv(pop_filename_in=pop_filename_in, res=1/120, id_ref="from_pop_csv",
pop_filename_out=pop_filename_out, site=site)
nodes = generic_demog._nodes
return MalariaDemographics(nodes=nodes, idref=site)
[docs]
def from_csv(input_file, res=30 / 3600, id_ref="from_csv", init_prev=0.0, include_biting_heterogeneity=True):
"""
Create a multi-node :py:class:`~emodpy_malaria.demographics.MalariaDemographics`
instance from a CSV file describing a population.
Args:
input_file: The path to the csv file to ingest.
res: Resolution.
id_ref: A string to identify the file, needs to match other input files.
init_prev: The initial malaria prevalence of the population. Defaults to 0%.
include_biting_heterogeneity: variable biting rates. Defaults to on.
Returns:
A :py:class:`~emodpy_malaria.demographics.MalariaDemographics` instance
"""
if os.path.exists(input_file) == False:
raise ValueError(f"Can't find input data file {input_file}")
generic_demog = Demog.from_csv(input_file, res, id_ref)
nodes = generic_demog._nodes
return MalariaDemographics(nodes=nodes, idref=id_ref, init_prev=init_prev,
include_biting_heterogeneity=include_biting_heterogeneity)
[docs]
def from_params(tot_pop=1e6, num_nodes=100, frac_rural=0.3, id_ref="from_params"):
"""
Creates nodes with following logic: First node is the urban node, which contains
tot_pop * (1-frac_rural) of the population, the rest of the nodes splip the left-over
population with less and less people in each node.
Create a multi-node :py:class:`~emodpy_malaria.demographics.MalariaDemographics`
instance as a synthetic population based on a few parameters.
Args:
tot_pop: The total human population in the node.
num_nodes: The number of nodes to create.
frac_rural: The fraction of the population that will be distributed between
nodes 2 and higher
id_ref: Method describing how the latitude and longitude values are created
for each of the nodes in a simulation. "Gridded world" values use a grid
overlaid across the globe at some arcsec resolution. You may also generate
the grid using another tool or coordinate system. For more information,
see :ref:`demo-metadata`.
Returns:
A :py:class:`~emodpy_malaria.demographics.MalariaDemographics` instance.
"""
generic_demog = Demog.from_params(tot_pop, num_nodes, frac_rural, id_ref)
nodes = generic_demog.nodes
return MalariaDemographics(nodes=nodes, idref=id_ref)
