Physics

Functions

EVA.core.physics.functions.gaussian(x, mean, sigma, intensity=1.0, offset=0.0)

Calculates a Gaussian function for given input array.

\[f(x) = \frac{1}{\sigma\sqrt{2\pi}}\exp{-\frac{(x-\mu)^2}{2\sigma^2}}\]

Parameters:

• x (ndarray) – x-values to calculate Gaussian for

• mean (float) – mean of Gaussian

• sigma (float) – standard deviation of Gaussian

• intensity (float) – area of Gaussian, defaults is 1

• offset (float) – height intercept, default is 0

Return type:

ndarray

Returns:

Array of points corresponding to the Gaussian function.

EVA.core.physics.functions.line(x, x0, x1)

Calculates a linear function for given input array.

\[f(x) = mx + c\]

Parameters:

• x (ndarray) – Input array to calculate for

• x0 (float) – “c”, intercept

• x1 (float) – “m”, gradient

Return type:

ndarray

Returns:

Array of points corresponding to line function.

EVA.core.physics.functions.quadratic(x, x0, x1, x2)

Calculates a quadratic function for given input array.

\[f(x) = ax^2 + bx + c\]

Parameters:

• x (ndarray) – Input array to calculate for

• x0 (float) – “c”, 0th degree coefficient

• x1 (float) – “b”, 1st degree coefficient

• x2 (float) – “a”, 2nd degree coefficient

Return type:

ndarray

Returns:

Array of points corresponding to quadratic function.

Normalisation

EVA.core.physics.normalisation.normalise_counts(ydata)

Normalise data to 10,000 counts.

Parameters:

ydata (ndarray) – input array

Return type:

ndarray

Returns:

Normalised array

EVA.core.physics.normalisation.normalise_events(ydata, spills)

Normalise data by number of spill events in comment.dat file.

Parameters:

• ydata (ndarray) – input array

• spills (int) – number of spill events

Return type:

ndarray

Returns:

Normalised array

Raises:

ValueError – If spills is empty (not loaded)