episimlab.partition package

Submodules

episimlab.partition.contacts module

class episimlab.partition.contacts.ContactsFromCSV(*, contacts_fp)

Bases: object

Load baseline contact patterns from a CSV file to a contacts DataArray.

contacts_fpattr.Attribute

No description given

Variable properties:

  • type : variable

  • intent : in

  • dimensions : ()

contactsattr.Attribute

No description given

Variable properties:

  • type : global

  • intent : out

  • global name : contacts

TAGS = ('partition',)
get_contacts_da(df: pandas.core.frame.DataFrame) → xarray.core.dataarray.DataArray
get_contacts_df()
initialize()

episimlab.partition.partition module

class episimlab.partition.partition.Partition(*, travel_pat, contacts, coords={})

Bases: object

Given travel patterns travel_pat and baseline contact rates contacts, estimate the pairwise contact probabilities phi from contact partitioning.

phiattr.Attribute

No description given

Variable properties:

  • type : global

  • intent : out

  • global name : phi

travel_patattr.Attribute

Mobility/travel patterns

Variable properties:

  • type : variable

  • intent : in

  • global name : travel_pat

  • dimensions : (‘vertex0’, ‘vertex1’, ‘age0’)

contactsattr.Attribute

Pairwise baseline contact patterns

Variable properties:

  • type : variable

  • intent : in

  • global name : contacts

  • dimensions : (‘age0’, ‘age1’)

_coordsattr.Attribute

Mapping of all variables that belong to group ‘coords’

Variable properties:

  • type : group_dict

  • intent : in

  • default value : {}

CONTACTS_DIMS = ('age0', 'age1')
TAGS = ('partition',)
TRAVEL_PAT_DIMS = ('vertex0', 'vertex1', 'age0')
property contacts_coords
property contacts_dims
property coords
get_c_ijk(tp: xarray.core.dataarray.DataArray) → xarray.core.dataarray.DataArray
property phi_coords
property phi_dims

Overwrite this method if using different dims than BaseFOI.PHI_DIMS

run_step(step_delta)
property travel_pat_coords
property travel_pat_dims
unsuffixed_coords(dims)

episimlab.partition.travel_pat module

class episimlab.partition.travel_pat.TravelPatFromCSV(*, travel_pat_fp, dask_chunks=None)

Bases: object

Load travel patterns from a CSV file to a travel_pat DataArray.

travel_pat_fpattr.Attribute

Path to a csv file containing travel patterns

Variable properties:

  • type : variable

  • intent : in

  • dimensions : ()

  • static : True

travel_patattr.Attribute

No description given

Variable properties:

  • type : global

  • intent : out

  • global name : travel_pat

dask_chunksattr.Attribute

Number of chunks in which to divide the travel_pat dataarray using dask. none or 0 will skip dask chunking.

Variable properties:

  • type : variable

  • intent : in

  • global name : dask_chunks

  • dimensions : ()

  • default value : None

  • static : True

RAISE_NULL = False
TAGS = ('partition', 'dependency::dask')
get_date_mask(date: pandas.core.series.Series, step_start, step_end) → pandas.core.series.Series

Given timestamps step_start and step_end, returns a mask for the travel dataframe. Special handling for NaT and cases where step_start equals step_end.

get_travel_da(df: pandas.core.frame.DataFrame, chunks: Optional[int] = None) → xarray.core.dataarray.DataArray

Convert a DataFrame into a single DataArray, using Dask to chunk into chunk divisions if chunk is not None.

get_travel_df() → pandas.core.frame.DataFrame

Load travel patterns from a CSV file and run preprocessing.

initialize()
run_step(step_start, step_end)
class episimlab.partition.travel_pat.TravelPatRepeatDaily(*, travel_pat_fp, dask_chunks=None)

Bases: episimlab.partition.travel_pat.TravelPatFromCSV

Example process that sets travel_pat based on a travel patterns CSV with data for only one date. This effectively sets travel_pat to be the same for the entire simulation.

travel_pat_fpattr.Attribute

Path to a csv file containing travel patterns

Variable properties:

  • type : variable

  • intent : in

  • dimensions : ()

  • static : True

travel_patattr.Attribute

No description given

Variable properties:

  • type : global

  • intent : out

  • global name : travel_pat

dask_chunksattr.Attribute

Number of chunks in which to divide the travel_pat dataarray using dask. none or 0 will skip dask chunking.

Variable properties:

  • type : variable

  • intent : in

  • global name : dask_chunks

  • dimensions : ()

  • default value : None

  • static : True

TAGS = ('example', 'partition', 'dependency::dask')
run_step(step_start, step_end)

Module contents