diff --git a/Examples/base/plot_baseclass1.py b/Examples/base/plot_baseclass1.py index fa0539c8..f0ca9c13 100644 --- a/Examples/base/plot_baseclass1.py +++ b/Examples/base/plot_baseclass1.py @@ -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 diff --git a/examples_old/example1.py b/examples_old/example1.py index 342f9931..14609f7a 100644 --- a/examples_old/example1.py +++ b/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() diff --git a/examples_old/example1_dream.py b/examples_old/example1_dream.py index 74e90835..0b5621be 100644 --- a/examples_old/example1_dream.py +++ b/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() diff --git a/examples_old/example2.py b/examples_old/example2.py index 3e0f4a7f..6e1acbd2 100644 --- a/examples_old/example2.py +++ b/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 diff --git a/examples_old/example3.py b/examples_old/example3.py index d01a861e..49d6ede9 100644 --- a/examples_old/example3.py +++ b/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: diff --git a/examples_old/example4.py b/examples_old/example4.py index 376d4486..3b01387a 100644 --- a/examples_old/example4.py +++ b/examples_old/example4.py @@ -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}" diff --git a/examples_old/example5_broken.py b/examples_old/example5_broken.py index dd5fa5e0..de12e67a 100644 --- a/examples_old/example5_broken.py +++ b/examples_old/example5_broken.py @@ -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}" diff --git a/examples_old/example_dataset2.py b/examples_old/example_dataset2.py index f2d415f9..b235bc4f 100644 --- a/examples_old/example_dataset2.py +++ b/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() diff --git a/examples_old/example_dataset2pt2_broken.py b/examples_old/example_dataset2pt2_broken.py index 9c44f0a5..ef4dcbab 100644 --- a/examples_old/example_dataset2pt2_broken.py +++ b/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 diff --git a/examples_old/example_dataset3.py b/examples_old/example_dataset3.py index fb8bf7f0..4164dc5e 100644 --- a/examples_old/example_dataset3.py +++ b/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() diff --git a/examples_old/example_dataset3pt2.py b/examples_old/example_dataset3pt2.py index ac2c9666..187306dd 100644 --- a/examples_old/example_dataset3pt2.py +++ b/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) diff --git a/examples_old/example_dataset4.py b/examples_old/example_dataset4.py index 9e4c41cb..1e975d4e 100644 --- a/examples_old/example_dataset4.py +++ b/examples_old/example_dataset4.py @@ -18,7 +18,7 @@ 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() diff --git a/examples_old/example_dataset4_2.py b/examples_old/example_dataset4_2.py index 375e5a11..9bba2ffd 100644 --- a/examples_old/example_dataset4_2.py +++ b/examples_old/example_dataset4_2.py @@ -33,7 +33,7 @@ def from_params(cls, amplitude: float = 1, phase: float = 0, period: float = 2*n def fit_fun(self, x, *args, **kwargs): # In the real case we would gust call the evaluation fn without reference to the BaseObj - return self.amplitude.raw_value * np.sin((x + self.phase.raw_value)/self.period.raw_value) + return self.amplitude.value * np.sin((x + self.phase.value)/self.period.value) b = Wavey.from_params() bb = Wavey.from_params(1.1, 0.1, 1.9*np.pi)