surfinpy.utils¶

surfinpy.utils.build_xgrid(x, y)[source]¶

Builds a 2D grip of values for the x axis.

Parameters:	x (array like) – numpy array y (array like) – numpy array
Returns:	xnew – numpy array
Return type:	array like

surfinpy.utils.build_ygrid(x, y)[source]¶

Builds a 2D grip of values for the y axis.

Parameters:	x (array like) – numpy array y (array like) – numpy array
Returns:	xnew – numpy array
Return type:	array like

surfinpy.utils.calculate_coverage(data)[source]¶

Calcualte the coverage of the adsorbing species on each surface.

Parameters:	data (list) – list of dictionaries containing info on each surface calculation
Returns:	coverage – numpy array of coverage values in units of \(n/nm^2\)
Return type:	array like

surfinpy.utils.calculate_gibbs(t, s, h)[source]¶

Calculate the gibbs free energy from thermochemcial data obtained from the NIST_JANAF database

Parameters:	t (array like) – Temperature range s (array like) – delta s values from nist h (array like) – selta h values from nist
Returns:	g – gibbs energy as a function of temperature
Return type:	array like

surfinpy.utils.fit(x, y, t)[source]¶

Fit a polynominal function to thermochemical data from NIST_JANAF

Parameters:	x (array like) – x axis for fit y (array like) – y axis for fit t (array like) – x axis to be fitted
Returns:	shift – data fitted from x and y to t
Return type:	array like

surfinpy.utils.get_labels(ticks, data)[source]¶

Reads the phase diagram data and returns the labels that correspond to the phases displayed on the phase diagram.

Parameters:	ticks (list) – Phases that are displayed. data (list) – list of dictionaries.
Returns:	labels – list of labels.
Return type:	list

surfinpy.utils.get_levels(X)[source]¶

Builds the levels used in the contourf plot. This is neccesary to ensure that each color correpsonds to a single phase.

Parameters:	X (array like) – 2D array of ints corresponding to each phase.
Returns:	levels – numpy array of ints
Return type:	array like

surfinpy.utils.get_phase_data(S, nsurfaces)[source]¶

Determines which surface composition is most stable at a given x and y value.

Parameters:	S (array like) – 2D array of surface energies nsurfaces (int) – Total number of surfaces
Returns:	x – array of ints corresponding to the position of the lowest phase
Return type:	array like

surfinpy.utils.pressure(chemical_potential, t)[source]¶

Converts chemical potential at a specific temperature (T) to a pressure value.

\[P = \frac{\mu}{k * T}\]

where P is the pressure, \(\mu\) is the chemcial potential, k is the Boltzmann constant and T is the temperature.

Parameters:	chemical_potential (array like) – delta mu values t (int) – temperature
Returns:	pressure – pressure values as a function of chemcial potential
Return type:	array like

surfinpy.utils.read_nist(File)[source]¶

Read a downloaded NIST_JANAF thermochemcial table

surfinpy.utils.transform_numbers(Z, ticks)[source]¶

transform numbers - Takes the phase diagram array and converts the numbers to numbers scaled 0, 1, 2, etc in order to make plotting easier

Parameters:	Z (array like) – array of integers ticks (list) – unique phases
Returns:	Z – Normalised to a continuous set of numbers.
Return type:	array like

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