hyperspy._components.expression module

class hyperspy._components.expression.Expression(expression, name, position=None, module='numpy', autodoc=True, add_rotation=False, rotation_center=None, rename_pars={}, compute_gradients=True, linear_parameter_list=None, check_parameter_linearity=True, **kwargs)

Bases: Component

Create a component from a string expression.

It automatically generates the partial derivatives and the class docstring.

  • expression (str) – Component function in SymPy text expression format with substitutions separated by ;. See examples and the SymPy documentation for details. In order to vary the components along the signal dimensions, the variables x and y must be included for 1D or 2D components. Also, if module is “numexpr” the functions are limited to those that numexpr support. See its documentation for details.

  • name (str) – Name of the component.

  • position (str, optional) – The parameter name that defines the position of the component if applicable. It enables interative adjustment of the position of the component in the model. For 2D components, a tuple must be passed with the name of the two parameters e.g. (“x0”, “y0”).

  • module ({"numpy", "numexpr", "scipy"}, default "numpy") – Module used to evaluate the function. numexpr is often faster but it supports fewer functions and requires installing numexpr.

  • add_rotation (bool, default False) – This is only relevant for 2D components. If True it automatically adds rotation_angle parameter.

  • rotation_center ({None, tuple}) – If None, the rotation center is the center i.e. (0, 0) if position is not defined, otherwise the center is the coordinates specified by position. Alternatively a tuple with the (x, y) coordinates of the center can be provided.

  • rename_pars (dictionary) – The desired name of a parameter may sometimes coincide with e.g. the name of a scientific function, what prevents using it in the expression. rename_parameters is a dictionary to map the name of the parameter in the expression` to the desired name of the parameter in the Component. For example: {“_gamma”: “gamma”}.

  • compute_gradients (bool, optional) – If True, compute the gradient automatically using sympy. If sympy does not support the calculation of the partial derivatives, for example in case of expression containing a “where” condition, it can be disabled by using compute_gradients=False.

  • linear_parameter_list (list) – A list of the components parameters that are known to be linear parameters.

  • check_parameter_linearity (bool) – If True, automatically check if each parameter is linear and set its corresponding attribute accordingly. If False, the default is to set all parameters, except for those who are specified in linear_parameter_list.

  • **kwargs – Keyword arguments can be used to initialise the value of the parameters.


As of version 1.4, Sympy’s lambdify function, that the Expression components uses internally, does not support the differentiation of some expressions, for example those containing a “where” condition. In such cases, the gradients can be set manually if required.


The following creates a Gaussian component and set the initial value of the parameters:

>>> hs.model.components1D.Expression(
... expression="height * exp(-(x - x0) ** 2 * 4 * log(2)/ fwhm ** 2)",
... name="Gaussian",
... height=1,
... fwhm=1,
... x0=0,
... position="x0",)

Substitutions for long or complicated expressions are separated by semicolumns:

>>> expr = 'A*B/(A+B) ; A = sin(x)+one; B = cos(y) - two; y = tan(x)'
>>> comp = hs.model.components1D.Expression(
... expression=expr,
... name='my function')
>>> comp.parameters
(<Parameter one of my function component>,
 <Parameter two of my function component>)

Compute the expression for a given value or map[“values”].

property _constant_term

Get value of constant term of component, assuming that the nonlinear term are fixed.

The ‘constant’ part of a component is any part that doesn’t change when the free parameters are changed.


Separate an expression into a group of lambdified functions that can compute the free parts of the expression, and a single lambdified function that computes the fixed parts of the expression

Used by the _compute_expression_part method.

compile_function(module='numpy', position=False)

Compile the function and calculate the gradient automatically when possible. Useful to recompile the function and gradient with a different module.


Returns a numpy array containing the value of the component for all indices. If enough memory is available, this is useful to quickly to obtain the fitted component without iterating over the navigation axes.

hyperspy._components.expression._check_parameter_linearity(expr, name)

Check whether expression is linear for a given parameter.