Skip to content

Generic fitter

GenericFitter

GenericFitter is a base implementation of a fit function. All fit functions must inherit GenericFitter.

Source code in itfit/fit_functions/common/generic_fitter.py 
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
class GenericFitter:
    """GenericFitter is a base implementation of a fit function.
    All fit functions must inherit GenericFitter."""

    name = "generic"

    @staticmethod
    def function(x,*args) -> float:
        """Fit function: `f(x,*args)=...`.

        Parameters:
            x (float):
                Independent variable.
            *args (list[float,...]):
                0, 1 or multiple arguments.
        Returns:
            (float):
                `f(x, *args)`
        """
        ...

    @staticmethod
    def gradient(x,*args) -> float:
        """Fit gradient: 'f(x,*args)=...'.

        Paremeters:
            x (float):
                Independent variable.
            *args (list[float,...]):
                0, 1 or multiple arguments.
        Returns:
            (float):
                'f(x,*args)'
        """
        ...

    def get_args_length(self):
        """Gets number of arguments of `function`.

        Returns:
            (int): Number of arguments of `function`.
        """
        return self.fitter_drag_collection.get_args_length()

    def __init__(self, app: Fitter, data: DataSelection):
        """Generic fitter constructor.

        Parameters:
            app (Fitter):
                Main application.
            data (DataSelection):
                Data to fit.
        """
        self.app = app
        self.fig = app.figure
        self.ax = app.ax
        self.data = data

        self.fitter_drag_collection: DragPointCollection

        # TODO: this may change when dedicated ui is implemented
        self.button_axes = plt.axes([0.81, 0.000001, 0.1, 0.055])
        self.button = Button(self.button_axes, "Fit",color="red")
        self.button.on_clicked(self.on_fit)

    def get_args(self):
        """Return arguments needed for `self.function`.

        Returns:
            (Tuple[float]):
                0, 1 or multiple arguments.
        """
        return self.fitter_drag_collection.get_args()

    def prop_errors(xdata,self):
        """Returns the error of the fit, given a gradient.

        Returns:
            (float):
                sigma
        """
        return np.sqrt( float( self.gradient(xdata,*self.fit[0]).T @ self.fit[1] @ self.gradient(xdata,*self.fit[0]) ))


    def on_fit(self, event):
        """Event for fit button.

        Parameters:
            event (Matplotlib event): 
                Not used
        """

        # If there is not data selected use all data
        xdata, ydata = self.data.get_selected()
        xerr, yerr = self.data.get_selected_errors()
        if np.sum(self.data.indexes_used)==0:
            xdata, ydata = self.data.xdata.copy(), self.data.ydata.copy()

        self.fit = optimize.curve_fit(self.function, xdata, ydata, p0=self.get_args(), full_output=True, sigma=yerr)
        fit_result = FitResultContainer(self.data.copy(), self, self.fit)

        # Plot fit line in background, and the confidence interval
        with self.app.blit_manager.disabled():
            self.fit_line = Line2D(xdata, fit_result.evaluate(xdata), linestyle='--', color='purple')

            verts_positive, verts_negative = fit_result.error_verts()
            if verts_positive and verts_negative:
                self.fit_fill = Polygon(verts_positive + list(reversed(verts_negative)),facecolor='red',edgecolor='None',alpha=0.3)
                self.ax.add_artist(self.fit_fill)
                self.ax.draw_artist(self.fit_fill)

            self.ax.add_artist(self.fit_line)
            self.ax.draw_artist(self.fit_line)


       # Redraw plot to show line     
        self.app.blit_manager.draw()

        # Save fit in app
        self.app._add_fit(fit_result)

    def delete(self):
        """Remove trigger. Used when tool is disabled."""
        try:
            del self.button
            self.button_axes.remove()

            # Remove artists in order to clean canvas
            for pm in self.drag_points_managers:
                pm.dragpoint.remove()
                self.app.blit_manager.artists.remove(pm)

            self.fitter_drag_collection.remove()
            self.app.blit_manager.artists.remove(self.fitter_drag_collection) 

        except AttributeError:
            pass

__init__(app, data)

Generic fitter constructor.

Parameters:

Name Type Description Default
app Fitter

Main application.

 required
data DataSelection

Data to fit.

 required
Source code in itfit/fit_functions/common/generic_fitter.py 
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
def __init__(self, app: Fitter, data: DataSelection):
    """Generic fitter constructor.

    Parameters:
        app (Fitter):
            Main application.
        data (DataSelection):
            Data to fit.
    """
    self.app = app
    self.fig = app.figure
    self.ax = app.ax
    self.data = data

    self.fitter_drag_collection: DragPointCollection

    # TODO: this may change when dedicated ui is implemented
    self.button_axes = plt.axes([0.81, 0.000001, 0.1, 0.055])
    self.button = Button(self.button_axes, "Fit",color="red")
    self.button.on_clicked(self.on_fit)

delete()

Remove trigger. Used when tool is disabled.

Source code in itfit/fit_functions/common/generic_fitter.py 
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
def delete(self):
    """Remove trigger. Used when tool is disabled."""
    try:
        del self.button
        self.button_axes.remove()

        # Remove artists in order to clean canvas
        for pm in self.drag_points_managers:
            pm.dragpoint.remove()
            self.app.blit_manager.artists.remove(pm)

        self.fitter_drag_collection.remove()
        self.app.blit_manager.artists.remove(self.fitter_drag_collection) 

    except AttributeError:
        pass

function(x, *args) staticmethod

Fit function: f(x,*args)=....

Parameters:

Name Type Description Default
x float

Independent variable.

 required
*args list[float, ...]

0, 1 or multiple arguments.

 ()

Returns:

Type Description
float

f(x, *args)
Source code in itfit/fit_functions/common/generic_fitter.py 
38
39
40
41
42
43
44
45
46
47
48
49
50
51
@staticmethod
def function(x,*args) -> float:
    """Fit function: `f(x,*args)=...`.

    Parameters:
        x (float):
            Independent variable.
        *args (list[float,...]):
            0, 1 or multiple arguments.
    Returns:
        (float):
            `f(x, *args)`
    """
    ...

get_args()

Return arguments needed for self.function.

Returns:

Type Description
Tuple[float]

0, 1 or multiple arguments.
Source code in itfit/fit_functions/common/generic_fitter.py 
 97
 98
 99
100
101
102
103
104
def get_args(self):
    """Return arguments needed for `self.function`.

    Returns:
        (Tuple[float]):
            0, 1 or multiple arguments.
    """
    return self.fitter_drag_collection.get_args()

get_args_length()

Gets number of arguments of function.

Returns:

Type Description
int

Number of arguments of function.
Source code in itfit/fit_functions/common/generic_fitter.py 
68
69
70
71
72
73
74
def get_args_length(self):
    """Gets number of arguments of `function`.

    Returns:
        (int): Number of arguments of `function`.
    """
    return self.fitter_drag_collection.get_args_length()

gradient(x, *args) staticmethod

Fit gradient: 'f(x,*args)=...'.

Paremeters

x (float): Independent variable. *args (list[float,...]): 0, 1 or multiple arguments.

Returns:

Type Description
float

'f(x,*args)'
Source code in itfit/fit_functions/common/generic_fitter.py 
53
54
55
56
57
58
59
60
61
62
63
64
65
66
@staticmethod
def gradient(x,*args) -> float:
    """Fit gradient: 'f(x,*args)=...'.

    Paremeters:
        x (float):
            Independent variable.
        *args (list[float,...]):
            0, 1 or multiple arguments.
    Returns:
        (float):
            'f(x,*args)'
    """
    ...

on_fit(event)

Event for fit button.

Parameters:

Name Type Description Default
event Matplotlib event

Not used

 required
Source code in itfit/fit_functions/common/generic_fitter.py 
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
def on_fit(self, event):
    """Event for fit button.

    Parameters:
        event (Matplotlib event): 
            Not used
    """

    # If there is not data selected use all data
    xdata, ydata = self.data.get_selected()
    xerr, yerr = self.data.get_selected_errors()
    if np.sum(self.data.indexes_used)==0:
        xdata, ydata = self.data.xdata.copy(), self.data.ydata.copy()

    self.fit = optimize.curve_fit(self.function, xdata, ydata, p0=self.get_args(), full_output=True, sigma=yerr)
    fit_result = FitResultContainer(self.data.copy(), self, self.fit)

    # Plot fit line in background, and the confidence interval
    with self.app.blit_manager.disabled():
        self.fit_line = Line2D(xdata, fit_result.evaluate(xdata), linestyle='--', color='purple')

        verts_positive, verts_negative = fit_result.error_verts()
        if verts_positive and verts_negative:
            self.fit_fill = Polygon(verts_positive + list(reversed(verts_negative)),facecolor='red',edgecolor='None',alpha=0.3)
            self.ax.add_artist(self.fit_fill)
            self.ax.draw_artist(self.fit_fill)

        self.ax.add_artist(self.fit_line)
        self.ax.draw_artist(self.fit_line)


   # Redraw plot to show line     
    self.app.blit_manager.draw()

    # Save fit in app
    self.app._add_fit(fit_result)

prop_errors(xdata, self)

Returns the error of the fit, given a gradient.

Returns:

Type Description
float

sigma
Source code in itfit/fit_functions/common/generic_fitter.py 
106
107
108
109
110
111
112
113
def prop_errors(xdata,self):
    """Returns the error of the fit, given a gradient.

    Returns:
        (float):
            sigma
    """
    return np.sqrt( float( self.gradient(xdata,*self.fit[0]).T @ self.fit[1] @ self.gradient(xdata,*self.fit[0]) ))

GenericFitterTool

Bases: ToolToggleBase

Toggles Generic Fitter Tool.

Source code in itfit/fit_functions/common/generic_fitter.py 
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
class GenericFitterTool(ToolToggleBase):
    """Toggles Generic Fitter Tool."""

    default_toggled = False 
    radio_group = "fitter"

    def __init__(self, *args, app: Fitter, data: DataSelection, **kwargs):
        """Creates a GenericFitterTool.

        Parameters:
            app (Fitter):
                Main application.
            data (DataSelection):
                Data selected.
        """
        self.app = app
        self.data = data
        self.fitter: GenericFitter
        super().__init__(*args, **kwargs)

    def enable(self, *args):
        """Triggered when GenericTool is enabled.
        Uses BlitManager for faster rendering of DragObjects.
        """
        self.app.blit_manager.enable()

    def disable(self, *args):
        """Triggered when GenericTool is disabled.
        Removes DragObjects and disables BlitManager.
        """
        self.fitter.delete()
        self.app.blit_manager.disable()
        self.app.figure.canvas.draw_idle()

__init__(*args, app, data, **kwargs)

Creates a GenericFitterTool.

Parameters:

Name Type Description Default
app Fitter

Main application.

 required
data DataSelection

Data selected.

 required
Source code in itfit/fit_functions/common/generic_fitter.py 
179
180
181
182
183
184
185
186
187
188
189
190
191
def __init__(self, *args, app: Fitter, data: DataSelection, **kwargs):
    """Creates a GenericFitterTool.

    Parameters:
        app (Fitter):
            Main application.
        data (DataSelection):
            Data selected.
    """
    self.app = app
    self.data = data
    self.fitter: GenericFitter
    super().__init__(*args, **kwargs)

disable(*args)

Triggered when GenericTool is disabled. Removes DragObjects and disables BlitManager.

Source code in itfit/fit_functions/common/generic_fitter.py 
199
200
201
202
203
204
205
def disable(self, *args):
    """Triggered when GenericTool is disabled.
    Removes DragObjects and disables BlitManager.
    """
    self.fitter.delete()
    self.app.blit_manager.disable()
    self.app.figure.canvas.draw_idle()

enable(*args)

Triggered when GenericTool is enabled. Uses BlitManager for faster rendering of DragObjects.

Source code in itfit/fit_functions/common/generic_fitter.py 
193
194
195
196
197
def enable(self, *args):
    """Triggered when GenericTool is enabled.
    Uses BlitManager for faster rendering of DragObjects.
    """
    self.app.blit_manager.enable()