dev #291

Merged
dominik merged 32 commits from dev into master 2024-09-29 17:21:40 +00:00
5 changed files with 65 additions and 36 deletions
Showing only changes of commit 50a811b7ec - Show all commits

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@ -31,7 +31,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.t1calculator = RelaxationEvaluation() self.t1calculator = RelaxationEvaluation()
self.sd_parameter = [] 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: for i in self.sdmodels:
self.specdens_combobox.addItem(i.name) self.specdens_combobox.addItem(i.name)
self.specdens_combobox.currentIndexChanged.connect(self.update_specdens) 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.conv_y = QT1Widget.time_conversion[self.t1_combobox.currentIndex()]
self.minimum = (1, np.inf) self.minimum = (1, np.inf)
self.min_pos = PlotItem(x=np.array([]), y=np.array([]), self.min_pos = PlotItem(
symbol='+', symbolBrush=mkBrush(color='r'), symbolPen=mkPen(color='r'), symbolSize=14) 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.parabola = PlotItem(x=np.array([]), y=np.array([]))
self.lineEdit_2.setValidator(QtGui.QDoubleValidator()) 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) right_b = min(np.argmin(y)+3, len(x)-1)
self.lineEdit_2.blockSignals(True) 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_2.blockSignals(False)
self.lineEdit_3.blockSignals(True) 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.lineEdit_3.blockSignals(False)
self.t1calculator.set_data(x, y) self.t1calculator.set_data(x, y)
@ -110,6 +116,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
if self.sdmodels[idx].parameter is not None: if self.sdmodels[idx].parameter is not None:
for name in self.sdmodels[idx].parameter: for name in self.sdmodels[idx].parameter:
print(name)
_temp = FormWidget(parent=self, name=name, fixable=True) _temp = FormWidget(parent=self, name=name, fixable=True)
_temp.value = 1 _temp.value = 1
_temp.setChecked(True) _temp.setChecked(True)
@ -133,7 +140,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
try: try:
for i, v, in enumerate(values): for i, v, in enumerate(values):
self.sd_parameter[i].blockSignals(True) 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) self.sd_parameter[i].blockSignals(False)
except IndexError: except IndexError:
pass pass
@ -219,7 +226,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.update_model() self.update_model()
@QtCore.pyqtSlot(int, name='on_interpol_combobox_currentIndexChanged') @QtCore.pyqtSlot(int, name='on_interpol_combobox_currentIndexChanged')
def determine_minimum(self, idx): def determine_minimum(self, idx: int):
if idx == 0: if idx == 0:
self.checkBox_interpol.setChecked(False) self.checkBox_interpol.setChecked(False)
self.checkBox_interpol.hide() self.checkBox_interpol.hide()
@ -229,9 +236,10 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.checkBox_interpol.show() self.checkBox_interpol.show()
self.frame.show() self.frame.show()
try: try:
m, i_func = self.t1calculator.calculate_t1_min(interpolate=idx, m, i_func = self.t1calculator.calculate_t1_min(
trange=(float(self.lineEdit_2.text()), interpolate=idx,
float(self.lineEdit_3.text()))) trange=(float(self.lineEdit_2.text()), float(self.lineEdit_3.text())),
)
except ValueError: except ValueError:
m, i_func = self.t1calculator.calculate_t1_min(interpolate=None) m, i_func = self.t1calculator.calculate_t1_min(interpolate=None)
@ -273,11 +281,13 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
return return
with busy_cursor(): with busy_cursor():
calc_stretching, mini = self.t1calculator.get_increase(height=self.minimum[1], calc_stretching, mini = self.t1calculator.get_increase(
height=self.minimum[1],
idx=var_idx, mode=notfix, idx=var_idx, mode=notfix,
omega=2*np.pi*self.frequency, omega=2*np.pi*self.frequency,
dist_parameter=sd_args, prefactor=cp_args, dist_parameter=sd_args, prefactor=cp_args,
coupling_kwargs=cp_kwargs) coupling_kwargs=cp_kwargs
)
self.label_t1min.setText(f'{mini:.4g} s') self.label_t1min.setText(f'{mini:.4g} s')
@ -292,9 +302,13 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
sd_args, _ = self.get_sd_values() sd_args, _ = self.get_sd_values()
cp_args, cp_kwargs, _ = self.get_cp_values() cp_args, cp_kwargs, _ = self.get_cp_values()
tau_mode = ['fit', 'peak', 'mean', 'logmean'][self.tau_combox.currentIndex()] 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, 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, coupling_param=cp_args, coupling_kwargs=cp_kwargs,
mode=tau_mode, interpolate=self.checkBox_interpol.isChecked()) mode=tau_mode,
interpolate=self.checkBox_interpol.isChecked()
)
name = self.name + '-' + str(self.t1calculator) + '(' name = self.name + '-' + str(self.t1calculator) + '('
name += ','.join([f'{a:.3g}' for a in sd_args]) 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') @QtCore.pyqtSlot(int, name='on_graph_checkbox_stateChanged')
def changed_state(self, checked): def changed_state(self, checked):
self.graph_combobox.setEnabled(checked != QtCore.Qt.Checked) self.graph_combobox.setEnabled(checked != QtCore.Qt.CheckState.Checked)

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

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@ -20,10 +20,10 @@ class AbstractGG(Distribution, ABC):
@classmethod @classmethod
def correlation(cls, t, tau0, *args): def correlation(cls, t, tau0, *args):
tt = np.asanyarray(t) tt = np.atleast_1d(t)
taus, ln_tau = AbstractGG._prepare_integration(tau0) taus, ln_tau = AbstractGG._prepare_integration(tau0)
g_tau = cls.distribution(taus, tau0, *args) 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 return ret_val
@ -32,11 +32,11 @@ class AbstractGG(Distribution, ABC):
r""" r"""
Calculate spectral density \int G(ln(tau) tau/(1+(w*tau)^2) dln(tau) 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) taus, ln_tau = AbstractGG._prepare_integration(tau0)
g_tau = cls.distribution(taus, tau0, *args) 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 return ret_val
@ -45,17 +45,23 @@ class AbstractGG(Distribution, ABC):
r""" r"""
Calculate spectral density \int G(ln(tau) tau/(1+(w*tau)^2) dln(tau) 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) _t = np.atleast_1d(tau0)
g_tau = cls.distribution(taus, tau0, *args) 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 @staticmethod
def _prepare_integration( 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]: ) -> tuple[np.ndarray, np.ndarray]:
""" """
Create array of correlation times for integration over ln(tau) Create array of correlation times for integration over ln(tau)
@ -77,8 +83,8 @@ class AbstractGG(Distribution, ABC):
# noinspection PyMethodOverriding # noinspection PyMethodOverriding
class GGAlpha(AbstractGG): class GGAlpha(AbstractGG):
name = r'General \Gamma (\alpha)' name = r'General Gamma (alpha)'
parameter = [r'\tau', r'\alpha', r'\beta'] parameter = [r'\alpha', r'\beta']
@staticmethod @staticmethod
def distribution(taus: float | np.ndarray, tau: float, alpha: float, beta: float) -> float | np.ndarray: def distribution(taus: float | np.ndarray, tau: float, alpha: float, beta: float) -> float | np.ndarray:
@ -92,8 +98,8 @@ class GGAlpha(AbstractGG):
# noinspection PyMethodOverriding # noinspection PyMethodOverriding
class GGAlphaEW(AbstractGG): class GGAlphaEW(AbstractGG):
name = r'General \Gamma (\alpha + EW)' name = r'General Gamma (alpha + EW)'
parameter = [r'\tau', r'\alpha', r'\beta', r'\sigma', r'\gamma'] parameter = [r'\alpha', r'\beta', r'\sigma', r'\gamma']
@staticmethod @staticmethod
def distribution(tau: float | np.ndarray, tau0: float, def distribution(tau: float | np.ndarray, tau0: float,
@ -117,8 +123,8 @@ class GGAlphaEW(AbstractGG):
# noinspection PyMethodOverriding # noinspection PyMethodOverriding
class GGBeta(AbstractGG): class GGBeta(AbstractGG):
name = r'General \Gamma (\beta)' name = r'General Gamma (beta)'
parameter = [r'\tau', 'a', 'b'] parameter = ['a', 'b']
@staticmethod @staticmethod
def distribution(tau: float | np.ndarray, tau0: float, a: float, b: float) -> float | np.ndarray: 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 import *
from ..distributions.energy import EnergyBarriers from ..distributions.energy import EnergyBarriers
from ..distributions.gengamma import GGAlpha
from ..distributions.intermolecular import FFHS from ..distributions.intermolecular import FFHS
from ..nmr.relaxation import Relaxation from ..nmr.relaxation import Relaxation
from ..utils.constants import gamma from ..utils.constants import gamma
@ -82,6 +83,13 @@ class FFHSFC(_AbstractFC):
relax = Relaxation(distribution=FFHS) 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): class EnergyFC(_AbstractFC):
name = 'Energy distribution' name = 'Energy distribution'
params = ['C', 'T'] + EnergyBarriers.parameter params = ['C', 'T'] + EnergyBarriers.parameter

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