calculate t1 for generalized gamma

This commit is contained in:
Dominik Demuth 2024-01-09 14:20:20 +01:00
parent 73bdc71a83
commit 50a811b7ec
5 changed files with 65 additions and 36 deletions

View File

@ -31,7 +31,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.t1calculator = RelaxationEvaluation()
self.sd_parameter = []
self.sdmodels = [Debye, ColeCole, ColeDavidson, KWW, HavriliakNegami, LogGaussian]
self.sdmodels = [Debye, ColeCole, ColeDavidson, KWW, HavriliakNegami, LogGaussian, GGAlpha]
for i in self.sdmodels:
self.specdens_combobox.addItem(i.name)
self.specdens_combobox.currentIndexChanged.connect(self.update_specdens)
@ -51,8 +51,14 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.conv_y = QT1Widget.time_conversion[self.t1_combobox.currentIndex()]
self.minimum = (1, np.inf)
self.min_pos = PlotItem(x=np.array([]), y=np.array([]),
symbol='+', symbolBrush=mkBrush(color='r'), symbolPen=mkPen(color='r'), symbolSize=14)
self.min_pos = PlotItem(
x=np.array([]),
y=np.array([]),
symbol='+',
symbolBrush=mkBrush(color='r'),
symbolPen=mkPen(color='r'),
symbolSize=14,
)
self.parabola = PlotItem(x=np.array([]), y=np.array([]))
self.lineEdit_2.setValidator(QtGui.QDoubleValidator())
@ -83,10 +89,10 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
right_b = min(np.argmin(y)+3, len(x)-1)
self.lineEdit_2.blockSignals(True)
self.lineEdit_2.setText('{:.2f}'.format(x[left_b]))
self.lineEdit_2.setText(f'{x[left_b]:.2f}')
self.lineEdit_2.blockSignals(False)
self.lineEdit_3.blockSignals(True)
self.lineEdit_3.setText('{:.2f}'.format(x[right_b]))
self.lineEdit_3.setText(f'{x[right_b]:.2f}')
self.lineEdit_3.blockSignals(False)
self.t1calculator.set_data(x, y)
@ -110,6 +116,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
if self.sdmodels[idx].parameter is not None:
for name in self.sdmodels[idx].parameter:
print(name)
_temp = FormWidget(parent=self, name=name, fixable=True)
_temp.value = 1
_temp.setChecked(True)
@ -133,7 +140,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
try:
for i, v, in enumerate(values):
self.sd_parameter[i].blockSignals(True)
self.sd_parameter[i].value = '{:.3g}'.format(round(v, 3))
self.sd_parameter[i].value = f'{v:.3g}'
self.sd_parameter[i].blockSignals(False)
except IndexError:
pass
@ -219,7 +226,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.update_model()
@QtCore.pyqtSlot(int, name='on_interpol_combobox_currentIndexChanged')
def determine_minimum(self, idx):
def determine_minimum(self, idx: int):
if idx == 0:
self.checkBox_interpol.setChecked(False)
self.checkBox_interpol.hide()
@ -229,9 +236,10 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.checkBox_interpol.show()
self.frame.show()
try:
m, i_func = self.t1calculator.calculate_t1_min(interpolate=idx,
trange=(float(self.lineEdit_2.text()),
float(self.lineEdit_3.text())))
m, i_func = self.t1calculator.calculate_t1_min(
interpolate=idx,
trange=(float(self.lineEdit_2.text()), float(self.lineEdit_3.text())),
)
except ValueError:
m, i_func = self.t1calculator.calculate_t1_min(interpolate=None)
@ -273,11 +281,13 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
return
with busy_cursor():
calc_stretching, mini = self.t1calculator.get_increase(height=self.minimum[1],
idx=var_idx, mode=notfix,
omega=2*np.pi*self.frequency,
dist_parameter=sd_args, prefactor=cp_args,
coupling_kwargs=cp_kwargs)
calc_stretching, mini = self.t1calculator.get_increase(
height=self.minimum[1],
idx=var_idx, mode=notfix,
omega=2*np.pi*self.frequency,
dist_parameter=sd_args, prefactor=cp_args,
coupling_kwargs=cp_kwargs
)
self.label_t1min.setText(f'{mini:.4g} s')
@ -292,9 +302,13 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
sd_args, _ = self.get_sd_values()
cp_args, cp_kwargs, _ = self.get_cp_values()
tau_mode = ['fit', 'peak', 'mean', 'logmean'][self.tau_combox.currentIndex()]
corr, opts = self.t1calculator.correlation_from_t1(omega=2*np.pi*self.frequency, dist_parameter=sd_args,
coupling_param=cp_args, coupling_kwargs=cp_kwargs,
mode=tau_mode, interpolate=self.checkBox_interpol.isChecked())
corr, opts = self.t1calculator.correlation_from_t1(
omega=2*np.pi*self.frequency,
dist_parameter=sd_args,
coupling_param=cp_args, coupling_kwargs=cp_kwargs,
mode=tau_mode,
interpolate=self.checkBox_interpol.isChecked()
)
name = self.name + '-' + str(self.t1calculator) + '('
name += ','.join([f'{a:.3g}' for a in sd_args])
@ -332,4 +346,4 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
@QtCore.pyqtSlot(int, name='on_graph_checkbox_stateChanged')
def changed_state(self, checked):
self.graph_combobox.setEnabled(checked != QtCore.Qt.Checked)
self.graph_combobox.setEnabled(checked != QtCore.Qt.CheckState.Checked)

View File

@ -26,3 +26,4 @@ from .coledavidson import ColeDavidson
from .debye import Debye
from .kww import KWW
from .loggaussian import LogGaussian
from .gengamma import GGAlpha

View File

@ -20,10 +20,10 @@ class AbstractGG(Distribution, ABC):
@classmethod
def correlation(cls, t, tau0, *args):
tt = np.asanyarray(t)
tt = np.atleast_1d(t)
taus, ln_tau = AbstractGG._prepare_integration(tau0)
g_tau = cls.distribution(taus, tau0, *args)
ret_val = np.array([simpson(np.exp(-t_i/taus) * g_tau, ln_tau) for t_i in tt])
ret_val = np.array([simpson(np.exp(-t_i/taus) * g_tau, ln_tau) for t_i in tt]).squeeze()
return ret_val
@ -32,11 +32,11 @@ class AbstractGG(Distribution, ABC):
r"""
Calculate spectral density \int G(ln(tau) tau/(1+(w*tau)^2) dln(tau)
"""
w = np.asanyarray(omega)
w = np.atleast_1d(omega)
taus, ln_tau = AbstractGG._prepare_integration(tau0)
g_tau = cls.distribution(taus, tau0, *args)
ret_val = np.array([simpson(g_tau / (1 - 1j*w_i*taus), ln_tau) for w_i in w])
ret_val = np.array([simpson(g_tau / (1 - 1j*w_i*taus), ln_tau) for w_i in w]).squeeze()
return ret_val
@ -45,17 +45,23 @@ class AbstractGG(Distribution, ABC):
r"""
Calculate spectral density \int G(ln(tau) tau/(1+(w*tau)^2) dln(tau)
"""
w = np.asanyarray(omega)
taus, ln_tau = AbstractGG._prepare_integration(tau0)
g_tau = cls.distribution(taus, tau0, *args)
w = np.atleast_1d(omega)
_t = np.atleast_1d(tau0)
ret_val = np.zeros((w.size, _t.size))
ret_val = np.array([simpson(g_tau * taus / (1 + (w_i*taus)**2), ln_tau) for w_i in w])
for i, tau_i in enumerate(_t):
taus, ln_tau = AbstractGG._prepare_integration(tau_i)
g_tau = cls.distribution(taus, tau_i, *args)
return ret_val
ret_val[:, i] = np.array([simpson(g_tau * taus / (1 + (w_i*taus)**2), ln_tau) for w_i in w]).squeeze()
return ret_val.squeeze()
@staticmethod
def _prepare_integration(
tau0: float, limits: tuple[int, int] = (20, 20), num_steps: int = 4001
tau0: float,
limits: tuple[int, int] = (20, 20),
num_steps: int = 4001,
) -> tuple[np.ndarray, np.ndarray]:
"""
Create array of correlation times for integration over ln(tau)
@ -77,8 +83,8 @@ class AbstractGG(Distribution, ABC):
# noinspection PyMethodOverriding
class GGAlpha(AbstractGG):
name = r'General \Gamma (\alpha)'
parameter = [r'\tau', r'\alpha', r'\beta']
name = r'General Gamma (alpha)'
parameter = [r'\alpha', r'\beta']
@staticmethod
def distribution(taus: float | np.ndarray, tau: float, alpha: float, beta: float) -> float | np.ndarray:
@ -92,8 +98,8 @@ class GGAlpha(AbstractGG):
# noinspection PyMethodOverriding
class GGAlphaEW(AbstractGG):
name = r'General \Gamma (\alpha + EW)'
parameter = [r'\tau', r'\alpha', r'\beta', r'\sigma', r'\gamma']
name = r'General Gamma (alpha + EW)'
parameter = [r'\alpha', r'\beta', r'\sigma', r'\gamma']
@staticmethod
def distribution(tau: float | np.ndarray, tau0: float,
@ -117,8 +123,8 @@ class GGAlphaEW(AbstractGG):
# noinspection PyMethodOverriding
class GGBeta(AbstractGG):
name = r'General \Gamma (\beta)'
parameter = [r'\tau', 'a', 'b']
name = r'General Gamma (beta)'
parameter = ['a', 'b']
@staticmethod
def distribution(tau: float | np.ndarray, tau0: float, a: float, b: float) -> float | np.ndarray:

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@ -2,6 +2,7 @@ import numpy as np
from ..distributions import *
from ..distributions.energy import EnergyBarriers
from ..distributions.gengamma import GGAlpha
from ..distributions.intermolecular import FFHS
from ..nmr.relaxation import Relaxation
from ..utils.constants import gamma
@ -82,6 +83,13 @@ class FFHSFC(_AbstractFC):
relax = Relaxation(distribution=FFHS)
class GGAFC(_AbstractFC):
name = 'GG(alpha)'
params = _AbstractFC.params + [r'\alpha', r'\beta']
bounds = _AbstractFC.bounds + [(None, None), (None, None)]
relax = Relaxation(distribution=GGAlpha)
class EnergyFC(_AbstractFC):
name = 'Energy distribution'
params = ['C', 'T'] + EnergyBarriers.parameter

View File

@ -525,7 +525,7 @@ class RelaxationEvaluation(Relaxation):
dist_parameter: tuple | list = None,
prefactor: tuple | list | float = None,
coupling_kwargs: dict = None,
) -> None:
) -> tuple[float, float] :
"""
Determine a single parameter from a T1 minimum.
It replaces the previously set value.