Merge pull request #20 from fenfisdi/issue/11/update_unit_tests

Issue/11/update unit tests

Pipfile

@@ -6,8 +6,6 @@ name = "pypi"
 [packages]
 scipy = "*"
 numpy = "*"
-matplotlib = "*"
-pillow = ">=8.1.1"
 
 [dev-packages]
 pytest = "*"
@@ -16,6 +14,9 @@ flake8 = "*"
 pytest-cov = "*"
 sphinx = "*"
 sphinx-rtd-theme = "*"
+matplotlib = "*"
+pillow = ">=8.1.1"
+dinjo = {editable = true, path = "."}
 
 [scripts]
 tests = "python -m pytest tests"

dinjo/model.py

@@ -47,7 +47,7 @@ class Parameter(Variable):
     """
     def __init__(
         self, name: str, representation: str, initial_value: float = 0,
-        *args, bounds: Optional[List[float]] = None, **kwargs
+        bounds: Optional[List[float]] = None, *args, **kwargs
     ) -> None:
         super().__init__(name, representation, initial_value)
         self.bounds = bounds if bounds else [initial_value, initial_value]
@@ -69,18 +69,18 @@ def bounds(self, bounds_input):
         )
 
         if not type_check:
-            raise AttributeError(attr_err_message)
+            raise ValueError(attr_err_message)
 
         order_check: bool = bounds_input[0] <= bounds_input[1]
 
         if not order_check:
-            raise AttributeError(attr_err_message)
+            raise ValueError(attr_err_message)
 
         if not (
             bounds_input[0] <= self.initial_value
             and bounds_input[1] >= self.initial_value
         ):
-            raise AttributeError(init_val_not_in_bounds_range)
+            raise ValueError(init_val_not_in_bounds_range)
 
         self._bounds = bounds_input
 
@@ -151,7 +151,7 @@ def build_model(self, t, y, *args):
             time at which the differential equation must be evaluated.
         y : list[float]
             state vector at which the differential must be evaluated.
-        \*args : any
+        *args : any
             other parameters of the differential equation
 
         Returns
@@ -240,7 +240,7 @@ def run_model(
         )
 
         parameters_permitted_types = (list, tuple, np.ndarray)
-        parameters_type_is_permitted = True
+        parameters_type_is_permitted = False
 
         for permitted_type in parameters_permitted_types:
             parameters_type_is_permitted += isinstance(parameters, permitted_type)

dinjo/optimizer.py

@@ -52,7 +52,7 @@ def __init__(
                     reference_state_variable
                 )
         except ValueError:
-            raise AttributeError(
+            raise ValueError(
                 "self.reference_state_variable must be in model.state_variables"
             )
 
@@ -63,13 +63,13 @@ def reference_t_values(self):
     @reference_t_values.setter
     def reference_t_values(self, reference_t_values_input: List[float]):
         if len(self.reference_values) != len(reference_t_values_input):
-            raise AttributeError(
+            raise ValueError(
                 "self.reference_values and self.reference_t_values must have the same length"
             )
 
         for i, t in enumerate(reference_t_values_input[:-1]):
             if not t < reference_t_values_input[i + 1]:
-                raise AttributeError(
+                raise ValueError(
                     "self.reference_t_values must be a list of floats in increasing order"
                 )
 
@@ -83,7 +83,7 @@ def reference_t_values(self, reference_t_values_input: List[float]):
             )
 
         if not t_span_condition:
-            raise AttributeError(
+            raise ValueError(
                 "self.model.t_span and self.reference_t_values initial and "
                 "final entries must coincide."
             )

examples/optimizer_oscillator.py

@@ -1,19 +1,18 @@
-from datetime import datetime, timedelta
 import os
-import sys
 from typing import Any, Dict, List, Union
 import pickle
+from datetime import datetime, timedelta
+
 
 import numpy as np
 import matplotlib.pyplot as plt
 import pandas as pd
 
-# Add project root directory to path
+from dinjo import model, optimizer
+
+
 this_file_dir = os.path.dirname(__file__)
 project_root_dir = os.path.join(this_file_dir, '..')
-sys.path.append(project_root_dir)
-
-from dinjo import model, optimizer
 
 
 class ModelOscillator(model.ModelIVP):

examples/optimizer_seirv_model_colombia.py

@@ -1,6 +1,5 @@
 # Optimize the seirv model for colombia
-# This script may take some hours to execute
-import sys
+# This script may take several minutes to execute
 import os
 import pickle
 from time import time
@@ -11,19 +10,15 @@
 import pandas as pd
 from pandas.errors import EmptyDataError
 
-from cmodel_examples_utilities import int_to_str_date, setup_csv
-
-# Add project root and this file's directories to path in order to find cmodel
-# package
-this_file_dir = os.path.dirname(__file__)
-project_root_dir = os.path.join(this_file_dir, '..')
-sys.path.append(this_file_dir)
-sys.path.append(project_root_dir)
-
 import dinjo.optimizer as optimizer
 from seirv_model_colombia import (
     seirv_state_variables_colombia, seirv_model_example, infected_reference_col
 )
+from cmodel_examples_utilities import int_to_str_date, setup_csv
+
+
+this_file_dir = os.path.dirname(__file__)
+project_root_dir = os.path.join(this_file_dir, '..')
 
 
 def optimizer_seirv_model_colombia_example(

examples/seirv_model_colombia.py

@@ -1,19 +1,11 @@
-import sys
 import os
-from time import time
 from typing import Any, Dict, List, Union
+from time import time
 
 import matplotlib.pyplot as plt
 import pandas as pd
 
-# Add project root and this file's directories to path in order to find cmodel
-# package
-this_file_dir = os.path.dirname(__file__)
-project_root_dir = os.path.join(this_file_dir, '..')
-sys.path.append(this_file_dir)
-sys.path.append(project_root_dir)
-
-from dinjo import model, predefined
+from dinjo import model
 from dinjo.predefined.epidemiology import ModelSEIRV
 # State variables and parameters are setup in col_vars_params.py module
 from examples.col_vars_params import (
@@ -26,6 +18,9 @@
 t_span_col = [0, 171]
 t_steps_col = 172
 
+this_file_dir = os.path.dirname(__file__)
+project_root_dir = os.path.join(this_file_dir, '..')
+
 infected_reference_col_path = os.path.join(
     this_file_dir, '..', 'example_data', 'infected_reference_col.csv'
 )

pyproject.toml

@@ -0,0 +1,3 @@
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta:__legacy__"

requirements-dev.txt

@@ -9,6 +9,7 @@
 # requirements. To emit only development requirements, pass "--dev-only".
 
 -i https://pypi.org/simple
+-e .
 alabaster==0.7.12
 attrs==21.2.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'
 babel==2.9.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
@@ -21,9 +22,9 @@ flake8==3.9.2
 idna==2.10; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 imagesize==1.2.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 iniconfig==1.1.1
-jinja2==2.11.3; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4'
+jinja2==3.0.1; python_version >= '3.6'
 kiwisolver==1.3.1; python_version >= '3.6'
-markupsafe==1.1.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
+markupsafe==2.0.1; python_version >= '3.6'
 matplotlib==3.4.2
 mccabe==0.6.1
 numpy==1.20.3
@@ -45,12 +46,12 @@ scipy==1.6.3
 six==1.16.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 snowballstemmer==2.1.0
 sphinx-rtd-theme==0.5.2
-sphinx==4.0.1
+sphinx==4.0.2
 sphinxcontrib-applehelp==1.0.2; python_version >= '3.5'
 sphinxcontrib-devhelp==1.0.2; python_version >= '3.5'
-sphinxcontrib-htmlhelp==1.0.3; python_version >= '3.5'
+sphinxcontrib-htmlhelp==2.0.0; python_version >= '3.6'
 sphinxcontrib-jsmath==1.0.1; python_version >= '3.5'
 sphinxcontrib-qthelp==1.0.3; python_version >= '3.5'
-sphinxcontrib-serializinghtml==1.1.4; python_version >= '3.5'
+sphinxcontrib-serializinghtml==1.1.5; python_version >= '3.5'
 toml==0.10.2; python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'
 urllib3==1.26.4; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4' and python_version < '4'

requirements.txt

@@ -6,12 +6,5 @@
 #
 
 -i https://pypi.org/simple
-cycler==0.10.0
-kiwisolver==1.3.1; python_version >= '3.6'
-matplotlib==3.4.2
 numpy==1.20.3
-pillow==8.2.0
-pyparsing==2.4.7; python_version >= '2.6' and python_version not in '3.0, 3.1, 3.2, 3.3'
-python-dateutil==2.8.1; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'
 scipy==1.6.3
-six==1.16.0; python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name='DINJO',
-    version='0.0.0',
+    version='0.0.dev1',
     description='DINJO lets you find optimal values of initial value problems\' parameters',
     long_description=long_description,
     long_description_content_type="text/markdown",

tests/conftest.py

@@ -0,0 +1,80 @@
+from typing import Any, List
+import pytest
+
+from numpy import pi
+from numpy.random import random
+
+from dinjo.model import StateVariable, Parameter
+from dinjo.optimizer import Optimizer
+from dinjo.predefined.physics import ModelOscillator
+
+
+@pytest.fixture(scope='session')
+def ho_state_vars():
+    # Harmonic Oscillator Initial Value Problem
+    q = StateVariable(
+        name='position', representation='q', initial_value=1.0
+    )
+    p = StateVariable(
+        name='momentum', representation='p', initial_value=0.0
+    )
+    return [q, p]
+
+
+@pytest.fixture(scope='session')
+def ho_params():
+    # Define Paramters
+    omega = Parameter(
+        name='frequency', representation='w', initial_value=2 * pi, bounds=[4, 8]
+    )
+    return [omega]
+
+
+@pytest.fixture(scope='session')
+def t_span():
+    return [0, 1]
+
+
+@pytest.fixture(scope='session')
+def t_steps():
+    return 50
+
+
+@pytest.fixture(scope='session')
+def model_oscillator(ho_state_vars, ho_params, t_span, t_steps):
+    # Instantiate the IVP class with appropiate State Variables and Parameters
+    return ModelOscillator(
+        state_variables=ho_state_vars,
+        parameters=ho_params,
+        t_span=t_span,
+        t_steps=t_steps
+    )
+
+
+@pytest.fixture(scope='session')
+def oscillator_solution(model_oscillator: ModelOscillator):
+    return model_oscillator.run_model()
+
+
+@pytest.fixture(scope='session')
+def ho_mock_values(oscillator_solution: Any, t_steps: List[float]):
+    noise_factor = 0.3
+    return (
+        oscillator_solution.y[0]
+        + (2 * random(t_steps) - 1) * noise_factor
+    )
+
+
+@pytest.fixture(scope='session')
+def ho_optimizer(
+    model_oscillator: ModelOscillator,
+    oscillator_solution: Any,
+    ho_mock_values: List[float],
+    ho_state_vars: List[StateVariable]
+):
+    return Optimizer(
+        model_oscillator,
+        ho_state_vars[0],
+        ho_mock_values,
+        oscillator_solution.t
+    )