Plot.CurveFit¶

class CurveFit(expression=None)¶

A CurveFit can be added to a Line or Scatter, and will then fit the supplied expression to the parent data.

Parameters:: expression (str) – The expression for the fit function.

addItem(item, emit=True)¶

Add item as child of this item.

Parameters:

item (PlotItem based) – The item.
emit (bool) – True, if change should be emitted.

addSubscriber(subscriber)¶

Add a subscriber. Each subscriber is called once every time the plot item updates.

Parameters:: subscriber (bound method) – The subscriber. Must be callable.

addTag(*args)¶

Add tag. Used for grouping plot items.

Parameters:: *args (tuple of str) – The tags to add.

alpha()¶

Returns:: The opacity for the line.
Return type:: float

applyStyle(style_scheme=None, style_properties=None)¶

Apply style properties from a style scheme.

Parameters:

style_scheme (dict) – The style scheme.
style_properties (dict | None) – A specific set of style properties to apply. If None, the style properties are retrieved from the plot model using the given style scheme.

attributes(latex=False, detail_level='full')¶

A description of the fit attributes.

Parameters:

latex (bool) – If True, return the attributes in Latex format.
detail_level (DETAIL_LEVELS enum) – The level of detail of the attributes.

Returns:

A description of the fit attributes.

Return type:

collections.OrderedDict

bounds()¶

Returns:: The bounds.
Return type:: tuple of physicalQuantity

color()¶

Returns:: The line color.
Return type:: str

conditions()¶

Returns:: The fit conditions.
Return type:: collections.OrderedDict

copy()¶

Make a copy of the plot storable by using the serialize/deserialize functionality.

This creates a new instance with a new id, but all other properties copied.

determination()¶

Returns:: The fit coefficient of determination.
Return type:: float | NoneType

emit(key, value=None)¶

Emit a single key and value change to all subscribers.

Parameters:

key (str) – The key to emit.
value (object) – The value to emit.

evaluate(x_data)¶

Evaluate the curve fit for the given x_data.

Parameters:: x_data (PhysicalQuantity) – The x-data.
Returns:: The evaluated x data and y data.
Return type:: 2-tuple of PhysicalQuantity

expression()¶

Returns:: The fit expression.
Return type:: str

extent(axis_name, padding=0.0)¶

Get the data limits.

Parameters:

axis_name (str) – ‘x’ or ‘y’.
padding (float) – Padding around the data.
Default: 0.0.

Returns:

The min/max data values for the requested axis.

Return type:

Sequence | PhysicalQuantity

classmethod fromProperties(properties)¶

Create a plot storable from a dict of properties.

Used when deserializing a PlotStorable.

Parameters:: properties (dict) – The properties which are used to populate the properties dict of the newly created plot storable.
Returns:: The newly created PlotStorable.
Return type:: PlotStorable

hoverDetails()¶

Returns:: The current hover details.
Return type:: dict | None

isAxisSpanned()¶

Returns:: True if the fit line should span the x-axis range of the plot.
Return type:: bool

isBoundsVisible()¶

Returns:: True, if fit bounds are shown in the plot.
Return type:: bool

isHoverable()¶

Returns:: True, if hoverable.
Return type:: bool

isHovered()¶

Returns:: True, if the item is hovered.
Return type:: bool

isInteractive()¶

Returns:: Whether the user can interact with this line.
Return type:: bool

isSelectable()¶

Returns:: True, if the item is selectable.
Return type:: bool

isSelected()¶

Returns:: True, if the item is selected.
Return type:: bool

classmethod isValidParent(item)¶

Check if an item is derivable.

Parameters:: item (PlotItem based) – The item to check.
Returns:: True, if the item can be derived.
Return type:: bool

isVisible()¶

Returns:: True, if the item is visible.
Return type:: bool

items(selected=None, tag=None)¶

Return the requested items.

The optional selected key word filter selected and deselected lines, with the options:

True : Only selected items
False : Only unselected items
None : All items.

Parameters:

selected (None | bool) – True, if only selected items should be returned.
tag (str) – The tag to filter on.

Returns:

The child items with the selected filtering.

Return type:

items

label()¶

Returns:: The line label.
Return type:: str

lineStyle()¶

Returns:: The line style.
Return type:: str | None

lineWidth()¶

Returns:: The line width.
Return type:: float

markerEdgeColor()¶

Returns:: The edge color of the marker in hex format.
Return type:: str

markerEvery()¶

Returns:: The number of points between every marker.
Return type:: int

markerFaceColor()¶

Returns:: The face color of the marker in hex format.
Return type:: str

markerSize()¶

Returns:: The marker size.
Return type:: float

markerStyle()¶: . :returns: The marker style. :rtype: str | None

model()¶

Returns:: The model that this item belongs to.
Return type:: PlotModel | None

order()¶

Returns:: A number describing the current order of the item within the PlotModel. Can be used for sorting.
Return type:: int | None

owner()¶

Returns:: The owner type.
Return type:: int | enum

parameters()¶

Returns:: The polynomial coefficients.
Return type:: numpy.ndarray

parent()¶

Returns:: The parent.
Return type:: PlotItem based | None

removeItem(item, emit=True)¶

Remove item from the child items.

Parameters:

item (PlotItem based) – The item to remove.
emit (bool) – True, if removal should be emitted.

removeSubscriber(subscriber)¶

Remove a subscriber method from the plot item updates.

Parameters:: subscriber (bound method) – The subscriber. Must be callable.

safeSetExpression(expression, update=True)¶

Safe setting of expression. Fails silently without changing anything.

Parameters:

expression (str) – The expression.
update (bool) – True if the fit should be updated.

selectionDetails()¶

Returns:: The current selection details.
Return type:: dict | None

setAlpha(alpha)¶

Set the opacity for the line.

Parameters:: alpha (float) – The opacity.

setBounds(lower, upper, update=True)¶

Set the derived line bounds.

Parameters:

lower (float | PhysicalQuantity) – The lower bound.
upper (float | PhysicalQuantity) – The upper bound.
update (bool) – True, if we should call update.

setBoundsVisible(visible)¶

Set whether to indicate the fit bounds in the plot.

Parameters:: visible (bool) – If True, fit bounds will be shown in the plot.

setColor(color)¶

Set the line color.

Parameters:: color (str) – The line color in hex format.

setConditions(conditions, update=True)¶

Set conditions.

Parameters:

conditions (dict or list of floats) – The conditions to set.
update (bool) – True, if the fit should be updated.

setData(x=None, y=None)¶

Overload since derived lines should not expose data setting.

Parameters:

x (iterable) – The x values.
y (iterable) – They values.

setExpression(expression, update=True)¶

Set the fit expression.

Parameters:

expression (str) – The fit expression to set.
update (bool) – True, if the fit should be updated.

setHoverable(hoverable)¶

Enable or disable hover evetn. When enabled the line will be set to hovered, once the mouse hovers over the item.

Parameters:: hoverable (bool) – True, if the item should be sensitive to hover events.

setHovered(hovered, details=None)¶

Set hovered with some details. This is called once the mouse hovers over the item. Should only be called once hoverable has been enabled.

Parameters:

hovered (bool) – True, if the item was hovered.
details (dict | NoneType) – The hover details.

setInteractive(interactive)¶

Set whether the user can interact with this line.

Parameters:: interactive (bool) – The desired state.

setLabel(label)¶

Set the label.

Parameters:: label (str) – The line label.

setLineStyle(line_style)¶

Set the line style.

Parameters:: line_style (str | None) – The line style.

setLineWidth(line_width)¶

Set the line width.

Parameters:: line_width (float) – The line width.

setMarkerColor(color)¶

Set color of the marker. Remember to also set a valid marker style.

Parameters:: color (valid color) – The color to set.

setMarkerEdgeColor(color)¶

Set the marker edge color. Remember to also set a valid marker style.

Parameters:: color (str) – The edge color of the marker.

setMarkerEvery(every)¶

Set the number of points between each marker. Remember to also set a valid marker style.

Parameters:: every (int) – The number of points between every marker.

setMarkerFaceColor(color)¶

Set the marker face-color. Remember to also set a valid marker style.

Parameters:: color (str) – The face color of the marker.

setMarkerSize(size)¶

Set the marker size. Remember to also set a valid marker style.

Parameters:: size (float) – The marker size.

setMarkerStyle(marker)¶

Set the marker style.

Parameters:: marker (str | None) – The marker style.

setOwner(owner)¶

Set the owner of the item (either OWNERS.MODEL or OWNERS.VIEW).

Parameters:: owner (int | enum) – The owner type.

setSelectable(selectable)¶

Set whether this item is selectable.

Parameters:: selectable (bool) – True, if the item should be selectable.

setSelected(selected, details=None)¶

Set the item as selected or unselected.

Parameters:

selected (bool) – True, if item should be selected.
details (dict | NoneType) – The selection details.

setSpanAxis(span_axis)¶

Set whether the fit line should span the x-axis range of the plot.

Parameters:: span_axis (bool) – If True, the fit line should span the x-axis range of the plot.

setVisible(visible)¶

Set visible.

Parameters:: visible (bool) – True, if the item should be visible.

sourceData()¶

Checks if the source data is valid, and if yes, return the valid source data on the form: (xs, ys, x_min, x_max, x_unit, y_unit) Else returns None

Returns:: The validated and clipped source data.
Return type:: tuple | None

style()¶

Returns:: All the current style properties.
Return type:: dict

styleProperties(style_scheme)¶

Check if the given style scheme has a style for this item.

Parameters:: style_scheme (dict) – The style scheme.
Returns:: The style, if any.
Return type:: dict | None

tags()¶

Returns:: The set of tags.
Return type:: set

update(data=None)¶

Perform the update.

Parameters:: data (tuple | NoneType) – The source data to use.

validSourceCoordinates(xs, ys)¶

Check valid source coordinates.

Parameters:

xs (numpy.ndarray) – The x data values.
ys (numpy.ndarray) – The y data values.

Returns:

True, if the source coordinates are valid input for the fit algorithm.

Return type:

bool

xData()¶

Returns:: The x-data.
Return type:: PhysicalQuantity

yData()¶

Returns:: The y-data.
Return type:: PhysicalQuantity

Usage Examples¶

Let us first construct a line object containing the data that we wish to fit.:

line = Plot.Line([0, 1, 2, 3, 4, 5], [1.3, 2.3, 4.2, 4.6, 2.6, 1.1])

Fitting to a parabola, can e.g. be done like this:

fit = Plot.CurveFit('curvature * (x - x0)**2 + offset')
line.addItem(fit)
print(fit.parameters())
print('R2=', fit.determination())

This will output the following values for curvature, x0 and offset:

{
    'curvature': -0.5017857159048791,
    'x0': 2.50854092811564,
    'offset': 4.14691159949586
}
R2=0.8912692142744284

Of course something similar could have been achieved using a Plot.PolynomialFit. However, CurveFit can also fit to e.g. a gaussian curve:

fit = Plot.CurveFit('a * gaussian(x - b, c)')
line.addItem(fit)
print(fit.parameters())
print('R2=', fit.determination())

And in this case it produces a slightly better fit as evidenced by the R2 value:

{
    'a': 16.505234582600096,
    'b': 2.5597234857461135,
    'c': 1.6884506777324249
}
R2= 0.9739999352271602

Notes¶

CurveFit can fit to any expression y = f(x). The expression can be composed of all valid python algebraic components like numbers, operators +, -, /, *`, the power operator **, the imaginary unit 1j and many more.

In addition a number of special functions can be used.

Table 16 Special functions available in NanoLab expressions.¶
Function	Notes
`abs`	Absolute value
`real`	Real part
`imag`	Imaginary part
`sin`	Sine (radians)
`cos`	Cosine (radians)
`tan`	Tangent (radians)
`asin`	Inverse sine
`acos`	Inverse cosine
`atan`	Inverse tangent
`atan2(a, b)`	Inverse tangent of a/b in correct quadrant.
`exp`	Exponential
`expm1`	exp(a) - 1
`sinh`	Hyperbolic sine
`cosh`	Hyperbolic cosine
`tanh`	Hyperbolic tangent
`asinh`	Inverse sinh
`acosh`	Inverse cosh
`atanh`	Inverse tanh
`log`	Natural logarithm
`log10`	Logarithm base 10
`log2`	Logarithm base 2
`sqrt`	Square root
`erf`	Error function
`erfc`	1 - erf
`gamma`	Euler gamma function
`ceil`	Ceiling function
`floor`	Floor function
`theta`	Heaviside theta function, theta(a) = 0 for a < 0 and 1 for a > 0.
`step`	Heaviside theta function
`sign`	Sign function
`sum`	Sum
`cumsum`	Cumulative sum
`cumtrapz`	Cumulative trapezoidal sum \|
`gradient`	1D gradient
`wofz`	Faddeeva function
`lorentzian(x, g)`	Lorentzian function, where `g` is the full width at half maximum (FWHM).
`gaussian(x, a)`	Gaussian function, wheere `a` is the full width at half maximum (FWHM).
`voigt(x, a, g)`	Voigt profile. Convolution of gaussian and lorentzian function. Here, `a` is the gaussian FWHM, and `g` is the lorentzian FWHM.
`arange(a, b, step=1)`	Range of values from a to b with custom step.