[med-svn] [Git][med-team/python-epimodels][upstream] New upstream version 0.4.0
Andreas Tille (@tille)
gitlab at salsa.debian.org
Fri Nov 25 07:35:36 GMT 2022
Andreas Tille pushed to branch upstream at Debian Med / python-epimodels
Commits:
3d75ef56 by Andreas Tille at 2022-11-25T08:08:27+01:00
New upstream version 0.4.0
- - - - -
6 changed files:
- condarecipe/epimodels/meta.yaml
- + pyproject.toml
- requirements.txt
- src/epimodels/continuous/models.py
- src/epimodels/discrete/models.py
- tests/test_continuous_models.py
Changes:
=====================================
condarecipe/epimodels/meta.yaml
=====================================
@@ -1,5 +1,5 @@
{% set name = "epimodels" %}
-{% set version = "0.3.19" %}
+{% set version = "0.3.20" %}
package:
name: "{{ name|lower }}"
@@ -7,7 +7,7 @@ package:
source:
url: "https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz"
- sha256: 8dec0de96e6ec506e3c61b7af6d687791c6db0eb5f74a90538f2844505db60e8
+ sha256: 8424e5487136dadfae92eb620a75a7cb174325c72be941a280900fc365e61ada
build:
number: 0
=====================================
pyproject.toml
=====================================
@@ -0,0 +1,23 @@
+[tool.poetry]
+name = "epimodels"
+description= "Library of mathematical epidemic models for use in simulation studies and inference"
+authors= ["Flávio Codeço Coelho"]
+version = "0.3.21"
+homepage = "https://github.com/fccoelho/epimodels"
+
+[tool.poetry.dependencies]
+python = "^3.9"
+cython = "0.29.32"
+numpy = "^1.23.3"
+scipy = "^1.9.2"
+matplotlib = "^3.6.1"
+mypy = "==0.982"
+pyitlib = "*"
+sphinx = "*"
+sympy = "^1.11.1"
+
+[tool.poetry.dev-dependencies]
+pytest = {optional = true, version = "*"}
+pytest-cov = {optional = true, version = "*"}
+nox-poetry = "^1.0.1"
+autoflake8 = "^0.4.0"
=====================================
requirements.txt
=====================================
@@ -14,4 +14,3 @@ matplotlib
mypy
sphinx
pyitlib
-numba
=====================================
src/epimodels/continuous/models.py
=====================================
@@ -9,7 +9,6 @@ from epimodels import BaseModel
import logging
from collections import OrderedDict
from functools import lru_cache
-import numba
logging.basicConfig(filename='epimodels.log', filemode='w', level=logging.DEBUG)
@@ -33,6 +32,15 @@ class ContinuousModel(BaseModel):
# logging.Error('Invalid model type: {}'.format(model_type))
def __call__(self, inits: list, trange: list, totpop: float, params: dict, method: str = 'RK45', **kwargs):
+ """
+ Run the model
+ :param inits: initial contitions
+ :param trange: time range: [t0, tf]
+ :param totpop: total population size
+ :param params: dictionary of parameters
+ :param method: integration method. default is 'RK45'
+ :param kwargs: Additional parameters passed on to solve_ivp
+ """
self.method = method
self.kwargs = kwargs
sol = self.run(inits, trange, totpop, params, **kwargs)
@@ -60,7 +68,7 @@ class SIR(ContinuousModel):
self.state_variables = OrderedDict({'S': 'Susceptible', 'I': 'Infectious', 'R': 'Removed'})
self.parameters = OrderedDict({'beta': r'$\beta$', 'gamma': r'$\gamma$'})
self.model_type = 'SIR'
- @numba.jit
+
def _model(self, t: float, y: list, params: dict) -> list:
"""
SIR Model.
@@ -78,6 +86,28 @@ class SIR(ContinuousModel):
]
+class SIR1D(ContinuousModel):
+ def __init__(self):
+ super().__init__()
+ self.state_variables = OrderedDict({'R': 'Recovered'})
+ self.parameters = {'R0': r'{\cal R}_0', 'gamma': r'\gamma', 'S0': r'S_0'}
+ self.model_type = 'SIR1D'
+
+ def _model(self, t: float, y: list, params: dict) -> list:
+ """
+ One dimensional SIR model
+ :param t:
+ :param y:
+ :param params:
+ """
+ N = params['N']
+ R = y
+ R0, gamma, S0 = params['R0'], params['gamma'], params['S0']
+ return [
+ gamma * (N - R - (S0 * np.exp(-R0 * R)))
+ ]
+
+
class SIS(ContinuousModel):
def __init__(self):
super().__init__()
@@ -86,7 +116,7 @@ class SIS(ContinuousModel):
self.model_type = 'SIS'
# @lru_cache(1000)
- @numba.jit
+
def _model(self, t: float, y: list, params: dict) -> list:
"""
SIS Model.
@@ -110,7 +140,7 @@ class SIRS(ContinuousModel):
self.parameters = OrderedDict({'beta': r'$\beta$', 'gamma': r'$\gamma$', 'xi': r'$\xi$'})
self.model_type = 'SIRS'
- @numba.jit
+
def _model(self, t: float, y: list, params: dict) -> list:
"""
SIR Model.
@@ -135,7 +165,7 @@ class SEIR(ContinuousModel):
self.parameters = OrderedDict({'beta': r'$\beta$', 'gamma': r'$\gamma$', 'epsilon': r'$\epsilon$'})
self.model_type = 'SEIR'
- @numba.jit
+
def _model(self, t: float, y: list, params: dict) -> list:
S, E, I, R = y
beta, gamma, epsilon, N = params['beta'], params['gamma'], params['epsilon'], params['N']
@@ -160,7 +190,7 @@ class SEQIAHR(ContinuousModel):
})
self.model_type = 'SEQIAHR'
- @numba.jit
+
def _model(self, t: float, y: list, params: dict) -> list:
S, E, I, A, H, R, C, D = y
chi, phi, beta, rho, delta, gamma, alpha, mu, p, q, r, N = params.values()
=====================================
src/epimodels/discrete/models.py
=====================================
@@ -15,8 +15,6 @@ import numpy as np
from collections import OrderedDict
# import cython
from typing import Dict, List, Iterable, Any
-# import numba
-# from numba.experimental import jitclass
from epimodels import BaseModel
model_types = {
=====================================
tests/test_continuous_models.py
=====================================
@@ -22,6 +22,14 @@ def test_SIR_with_t_eval():
assert len(model.traces['S']) == 500
# assert len(model.traces['time']) == 50
+def test_SIR1D():
+ model = SIR1D()
+ model([0], [0, 500], 100, {'R0': 1.5, 'gamma': .1, 'S0': 98})
+ # assert len(model.traces['R']) == 500
+ assert len(model.traces) == 2
+ model.plot_traces()
+ P.show()
+
def test_SIS():
model = SIS()
model([1000, 1], [0, 50], 1001, {'beta': 2, 'gamma': .1})
View it on GitLab: https://salsa.debian.org/med-team/python-epimodels/-/commit/3d75ef56a571a2a6c31def1ad3b794880f37cf43
--
View it on GitLab: https://salsa.debian.org/med-team/python-epimodels/-/commit/3d75ef56a571a2a6c31def1ad3b794880f37cf43
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