Preparation for 1.4.0 release

Examples/base/README.rst

@@ -3,4 +3,4 @@
 Subclassing Examples
 ------------------------
 
-This section gathers examples which correspond to subclassing the :class:`easyscience.Objects.Base.BaseObj`  class.
+This section gathers examples which correspond to subclassing the :class:`easyscience.base_classes.ObjBase`  class.

Examples/base/plot_baseclass1.py

@@ -1,8 +1,8 @@
 """
-Subclassing BaseObj - Simple Pendulum
+Subclassing ObjBase - Simple Pendulum
 =====================================
-This  example shows how to subclass :class:`easyscience.Objects.Base.BaseObj` with parameters from
-:class:`EasyScience.Objects.Base.Parameter`. For this example a simple pendulum will be modeled.
+This  example shows how to subclass :class:`easyscience.base_classes.ObjBase` with parameters from
+:class:`EasyScience.variable.Parameter`. For this example a simple pendulum will be modeled.
 
 .. math::
     y = A \sin (2 \pi f t + \phi )
@@ -17,8 +17,8 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-from easyscience.Objects.ObjectClasses import BaseObj
-from easyscience.Objects.ObjectClasses import Parameter
+from easyscience.base_classes import ObjBase
+from easyscience.variable import Parameter
 
 # %%
 # Subclassing
@@ -29,7 +29,7 @@
 # embedded rST text block:
 
 
-class Pendulum(BaseObj):
+class Pendulum(ObjBase):
     def __init__(self, A: Parameter, f: Parameter, p: Parameter):
         super(Pendulum, self).__init__('SimplePendulum', A=A, f=f, p=p)
 
@@ -41,13 +41,13 @@ def from_pars(cls, A: float = 1, f: float = 1, p: float = 0):
         return cls(A, f, p)
 
     def __call__(self, t):
-        return self.A.raw_value * np.sin(2 * np.pi * self.f.raw_value * t + self.p.raw_value)
+        return self.A.value * np.sin(2 * np.pi * self.f.value * t + self.p.value)
 
     def plot(self, time, axis=None, **kwargs):
         if axis is None:
             axis = plt
         else:
-            axis.set_title(f'A={self.A.raw_value}, F={self.f.raw_value}, P={self.p.raw_value}')
+            axis.set_title(f'A={self.A.value}, F={self.f.value}, P={self.p.value}')
         p = axis.plot(time, self(time), **kwargs)
         return p
 

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2024, Easyscience contributors (https://github.com/EasyScience)
+Copyright (c) 2025, Easyscience contributors (https://github.com/EasyScience)
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

docs/src/conf.py

@@ -51,9 +51,7 @@
 
 intersphinx_mapping = {
     'python': ('https://docs.python.org/3', None),
-    'numpy': ('https://numpy.org/doc/stable/', None),
-    'pint': ('https://pint.readthedocs.io/en/stable/', None),
-    'xarray': ('https://xarray.pydata.org/en/stable/', None)
+    'numpy': ('https://numpy.org/doc/stable/', None)
 }
 
 # -- General configuration ---------------------------------------------------

docs/src/index.rst

@@ -56,7 +56,6 @@ Documentation
    :maxdepth: 3
 
    fitting/introduction
-   fitting/constraints
 
 .. toctree::
    :maxdepth: 2

docs/src/reference/base.rst

@@ -5,13 +5,13 @@ Parameters and Objects
 Descriptors
 ===========
 
-.. autoclass:: easyscience.Objects.Variable.Descriptor
+.. autoclass:: easyscience.variable.Descriptor
   :members:
 
 Parameters
 ==========
 
-.. autoclass:: easyscience.Objects.Variable.Parameter
+.. autoclass:: easyscience.variable.Parameter
   :members:
   :inherited-members:
 
@@ -22,30 +22,17 @@ Super Classes and Collections
 Super Classes
 =============
 
-.. autoclass:: easyscience.Objects.ObjectClasses.BasedBase
+.. autoclass:: easyscience.base_classes.BasedBase
   :members:
   :inherited-members:
 
-.. autoclass:: easyscience.Objects.ObjectClasses.BaseObj
+.. autoclass:: easyscience.base_classes.ObjBase
   :members: +_add_component
   :inherited-members:
 
 Collections
 ===========
 
-.. autoclass:: easyscience.Objects.Groups.BaseCollection
+.. autoclass:: easyscience.CollectionBase
   :members:
   :inherited-members:
-
-===============
-Data Containers
-===============
-
-.. autoclass:: easyscience.Datasets.xarray.EasyScienceDataarrayAccessor
-  :members:
-  :inherited-members:
-
-.. autoclass:: easyscience.Datasets.xarray.EasyScienceDatasetAccessor
-  :members:
-  :inherited-members:
-

examples_old/example1.py

@@ -16,7 +16,7 @@
 
 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
+    return b.c.value + b.m.value * x
 
 
 f = Fitter()

examples_old/example1_dream.py

@@ -14,7 +14,7 @@
 
 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
+    return b.c.value + b.m.value * x
 
 
 f = Fitter()

examples_old/example2.py

@@ -27,11 +27,11 @@ def _defaults(self):
 
     @property
     def gradient(self):
-        return self.m.raw_value
+        return self.m.value
 
     @property
     def intercept(self):
-        return self.c.raw_value
+        return self.c.value
 
     def fit_func(self, x: np.ndarray) -> np.ndarray:
         return self.gradient * x + self.intercept

examples_old/example3.py

@@ -57,14 +57,14 @@ def gradient(self):
         if self.interface:
             return self.interface.get_value('m')
         else:
-            return self.m.raw_value
+            return self.m.value
 
     @property
     def intercept(self):
         if self.interface:
             return self.interface.get_value('c')
         else:
-            return self.c.raw_value
+            return self.c.value
 
     def fit_func(self, x: np.ndarray) -> np.ndarray:
         if self.interface:

examples_old/example4.py

@@ -11,7 +11,7 @@
 
 from easyscience import global_object
 from easyscience.fitting import Fitter
-from easyscience.Objects.core import ComponentSerializer
+from easyscience.Objects.component_serializer import ComponentSerializer
 from easyscience.Objects.ObjectClasses import BaseObj
 from easyscience.Objects.ObjectClasses import Parameter
 
@@ -407,14 +407,14 @@ def gradient(self):
         if self.interface:
             return self.interface().get_value("m")
         else:
-            return self.m.raw_value
+            return self.m.value
 
     @property
     def intercept(self):
         if self.interface:
             return self.interface().get_value("c")
         else:
-            return self.c.raw_value
+            return self.c.value
 
     def __repr__(self):
         return f"Line: m={self.m}, c={self.c}"

examples_old/example5_broken.py

@@ -12,7 +12,7 @@
 from easyscience.fitting import Fitter
 from easyscience.Objects.Base import BaseObj
 from easyscience.Objects.Base import Parameter
-from easyscience.Objects.core import ComponentSerializer
+from easyscience.Objects.component_serializer import ComponentSerializer
 
 # from easyscience.Objects.Base import LoggedProperty
 from easyscience.Objects.Inferface import InterfaceFactoryTemplate
@@ -325,14 +325,14 @@ def gradient(self):
         # if self.interface:
         #     return self.interface().get_value('m')
         # else:
-        return self.m.raw_value
+        return self.m.value
 
     @property
     def intercept(self):
         # if self.interface:
         #     return self.interface().get_value('c')
         # else:
-        return self.c.raw_value
+        return self.c.value
 
     def __repr__(self):
         return f"Line: m={self.m}, c={self.c}"

examples_old/example6_broken.py

@@ -12,7 +12,7 @@
 from easyscience.fitting import Fitter
 from easyscience.Objects.ObjectClasses import BaseObj
 from easyscience.Objects.Variable import Parameter
-from easyscience.Objects.core import ComponentSerializer
+from easyscience.Objects.component_serializer import ComponentSerializer
 from easyscience.Objects.Inferface import InterfaceFactoryTemplate
 
 # This is a much more complex case where we have calculators, interfaces, interface factory and an

examples_old/example_dataset2.py

@@ -16,7 +16,7 @@
 
 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
+    return b.c.value + b.m.value * x
 
 
 f = Fitter()

examples_old/example_dataset2pt2_broken.py

@@ -22,7 +22,7 @@
 
 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
+    return b.c.value + b.m.value * x
 
 
 nx = 1E3

examples_old/example_dataset3.py

@@ -36,7 +36,7 @@
 
 def fit_fun(x, *args, **kwargs):
     # In the real case we would gust call the evaluation fn without reference to the BaseObj
-    return np.sin(2*np.pi*(x[:, 0] + b.s_off.raw_value)) * np.cos(2*np.pi*(x[:, 1] + b.c_off.raw_value))
+    return np.sin(2*np.pi*(x[:, 0] + b.s_off.value)) * np.cos(2*np.pi*(x[:, 1] + b.c_off.value))
 
 
 f = Fitter()

examples_old/example_dataset3pt2.py

@@ -34,7 +34,7 @@
 
 def fit_fun(x, *args, **kwargs):
     # In the real case we would gust call the evaluation fn without reference to the BaseObj
-    return np.sin(2*np.pi*(x[:, 0] + b.s_off.raw_value)) * np.cos(2*np.pi*(x[:, 1] + b.c_off.raw_value))
+    return np.sin(2*np.pi*(x[:, 0] + b.s_off.value)) * np.cos(2*np.pi*(x[:, 1] + b.c_off.value))
 
 
 fig, ax = plt.subplots(2, 3, sharey=True, sharex=True)
@@ -55,7 +55,7 @@ def fit_fun(x, *args, **kwargs):
     p1 = d[f'computed_{minimizer}'].plot(ax=ax[0, idx], cbar_kwargs={'cax': cbar_ax1})
     p2 = d[f'dz_{minimizer}'].plot(ax=ax[1, idx], cbar_kwargs={'cax': cbar_ax2})
     ax[0, idx].set_title(f'{minimizer}')
-    ax[1, idx].set_title('s_off - {:0.03f}\nc_off - {:0.03f}'.format(b.s_off.raw_value, b.c_off.raw_value))
+    ax[1, idx].set_title('s_off - {:0.03f}\nc_off - {:0.03f}'.format(b.s_off.value, b.c_off.value))
     ax[0, idx].set_aspect('equal', 'box')
     ax[1, idx].set_aspect('equal', 'box')
 fig.subplots_adjust(right=0.8)