def test_baseobj_get_parameters(setup_pars: dict):
name = setup_pars['name']
del setup_pars['name']
obj = BaseObj(name, **setup_pars)
pars = obj.get_parameters()
assert isinstance(pars, list)
assert len(pars) == 2
par_names = [par.name for par in pars]
assert 'p2' in par_names
assert 'p3' in par_names
def test_baseobj_set(setup_pars: dict):
from copy import deepcopy
name = setup_pars['name']
explicit_name1 = 'par1'
kwargs = {
setup_pars[explicit_name1].name: setup_pars[explicit_name1],
}
obj = BaseObj(name, **kwargs)
new_value = 5.0
with not_raises([AttributeError, ValueError]):
obj.p1 = new_value
assert obj.p1.raw_value == new_value
def test_baseobj_get(setup_pars: dict):
name = setup_pars['name']
explicit_name1 = 'par1'
explicit_name2 = 'par2'
kwargs = {
setup_pars[explicit_name1].name: setup_pars[explicit_name1],
setup_pars[explicit_name2].name: setup_pars[explicit_name2]
}
obj = BaseObj(name, **kwargs)
with not_raises(AttributeError):
p1: Parameter = obj.p1
with not_raises(AttributeError):
p2: Parameter = obj.p2
def test_baseobj_create(setup_pars: dict, a: List[str], kw: List[str]):
name = setup_pars['name']
args = []
for key in a:
args.append(setup_pars[key])
kwargs = {}
for key in kw:
kwargs[key] = setup_pars[key]
base = BaseObj(name, *args, **kwargs)
assert base.name == name
for key in a:
item = getattr(base, setup_pars[key].name)
assert isinstance(item, setup_pars[key].__class__)
def test_baseobj_dir(setup_pars):
name = setup_pars['name']
del setup_pars['name']
obj = BaseObj(name, **setup_pars)
expected = [
'REDIRECT', 'as_dict', 'des1', 'des2', 'from_dict',
'generate_bindings', 'get_parameters', 'par1', 'par2', 'par3',
'switch_interface', 'to_json', 'unsafe_hash'
]
obtained = dir(obj)
assert len(obtained) == len(expected)
assert obtained == sorted(obtained)
for this_item, this_expect in zip(obtained, expected):
assert this_item == this_expect
__author__ = 'github.com/wardsimon'
__version__ = '0.0.1'
import numpy as np
from easyCore.Objects.Base import Parameter, BaseObj
from easyCore.Fitting.Fitting import Fitter
# This is a simple example of creating an object which has fitable parameters
b = BaseObj('line', m=Parameter('m', 1), c=Parameter('c', 1))
def fit_fun(x):
# In the real case we would gust call the evaluation fn without reference to the BaseObj
return b.c.raw_value + b.m.raw_value * x
f = Fitter()
f.initialize(b, fit_fun)
x = np.array([1, 2, 3])
y = np.array([2, 4, 6]) - 1
f_res = f.fit(x, y)
print(f_res.fit_report())
def test_baseobj_as_dict(setup_pars: dict):
name = setup_pars['name']
del setup_pars['name']
obj = BaseObj(name, **setup_pars)
obtained = obj.as_dict()
assert isinstance(obtained, dict)
expected = {
'@module': 'easyCore.Objects.Base',
'@class': 'BaseObj',
'@version': '0.0.1',
'name': 'test',
'par1': {
'@module': 'easyCore.Objects.Base',
'@class': 'Parameter',
'@version': '0.0.1',
'name': 'p1',
'value': 0.1,
'error': 0.0,
'min': -np.inf,
'max': np.inf,
'fixed': True,
'units': 'dimensionless'
},
'des1': {
'@module': 'easyCore.Objects.Base',
'@class': 'Descriptor',
'@version': '0.0.1',
'name': 'd1',
'value': 0.1,
'units': 'dimensionless',
'description': '',
'url': '',
'display_name': 'd1'
},
'par2': {
'@module': 'easyCore.Objects.Base',
'@class': 'Parameter',
'@version': '0.0.1',
'name': 'p2',
'value': 0.1,
'error': 0.0,
'min': -np.inf,
'max': np.inf,
'fixed': False,
'units': 'dimensionless'
},
'des2': {
'@module': 'easyCore.Objects.Base',
'@class': 'Descriptor',
'@version': '0.0.1',
'name': 'd2',
'value': 0.1,
'units': 'dimensionless',
'description': '',
'url': '',
'display_name': 'd2'
},
'par3': {
'@module': 'easyCore.Objects.Base',
'@class': 'Parameter',
'@version': '0.0.1',
'name': 'p3',
'value': 0.1,
'error': 0.0,
'min': -np.inf,
'max': np.inf,
'fixed': False,
'units': 'dimensionless'
}
}
def check_dict(check, item):
if isinstance(check, dict) and isinstance(item, dict):
if '@module' in item.keys():
with not_raises([ValueError, AttributeError]):
this_obj = MontyDecoder().process_decoded(item)
for this_check_key, this_item_key in zip(check.keys(),
item.keys()):
check_dict(check[this_check_key], item[this_item_key])
else:
assert isinstance(item, type(check))
assert item == check
check_dict(expected, obtained)
__author__ = 'github.com/wardsimon'
__version__ = '0.1.0'
from easyCore import np
from easyCore.Datasets.xarray import xr
import matplotlib.pyplot as plt
from easyCore.Objects.Base import Parameter, BaseObj
from easyCore.Fitting.Fitting import Fitter
d = xr.Dataset()
m_starting_point = 1
c_starting_point = 1
b = BaseObj('line',
m=Parameter('m', m_starting_point),
c=Parameter('c', c_starting_point))
def fit_fun(x, *args, **kwargs):
# In the real case we would gust call the evaluation fn without reference to the BaseObj
return b.c.raw_value + b.m.raw_value * x
nx = 1E3
x_min = 0
x_max = 100
x = np.linspace(x_min, x_max, num=int(nx))
y = 2 * x - 1 + 5 * (np.random.random(size=x.shape) - 0.5)