def test_cs_fit(self):
data = np.array([[0, 0, 0], [1, 1, 1], [2, 2, 2], [3, 3, 3], [4, 3, 5],
[5, 3, 8]])
y = np.array([1, 2, 3, 4])
x = ut.cs_fit(data[:, 0], data[:, 2], y)
expected = np.array([1., 2., 3., 5.])
assert_almost_equal(x, expected, decimal=2)
def inititalise(thermochem, adsorbant, max_t, min_p, max_p):
'''Builds the numpy arrays for each calculation.
Parameters
----------
thermochem : :py:attr:`array_like`
array containing NIST_JANAF thermochemical data
adsorbant : :py:attr:`float`
dft energy of adsorbing species
max_t : :py:attr:`int`
Maximum temperature of phase diagram
min_p : :py:attr:`int`
Minimum pressure of phase diagram
max_p : :py:attr:`int`
Maximum pressure of phase diagram
Returns
-------
lnP : :py:attr:`array_like`
numpy array of pressure values
logP : :py:attr:`array_like`
log of lnP (hard coded range -13 - 5.0)
T : :py:attr:`array_like`
array of temperature values (hard coded range 2 - 1000 K)
adsrobant_t : :py:attr:`array_like`
dft values of adsorbant scaled to temperature
'''
T = np.arange(2, max_t)
shift = ut.cs_fit(thermochem[:, 0], thermochem[:, 2], T)
shift = (T * (shift / 1000)) / 96.485
adsorbant_t = adsorbant - shift
logP = np.arange(min_p, max_p, 0.1)
lnP = np.log(10**logP)
return lnP, logP, T, adsorbant_t
def temperature_correction(T, thermochem, adsorbant):
"""Make the energy of the adsorbing species a temperature
dependent term by scaling it with experimental data.
Parameters
----------
T : :py:attr:`int`
Temperature to scale the energy to
thermochem : :py:attr:`array_like`
nist_janaf table
adsorbant : :py:attr:`float`
DFT energy of adsorbant
Returns
-------
adsorbant : :py:attr:`float`
Scaled energy of adsorbant
"""
temperature_range = np.arange(2, np.amax(thermochem[:, 0]))
shift = ut.cs_fit(thermochem[:, 0], thermochem[:, 2], temperature_range)
shift = (T * (shift[(T - 1)] / 1000)) / 96.485
adsorbant = adsorbant - shift
return adsorbant