diff --git a/docs/Makefile b/doc/Makefile
similarity index 100%
rename from docs/Makefile
rename to doc/Makefile
diff --git a/doc/examples/README.rst b/doc/examples/README.rst
new file mode 100644
index 0000000..74a2c9b
--- /dev/null
+++ b/doc/examples/README.rst
@@ -0,0 +1,9 @@
+.. examples-index:
+
+.. _gallery:
+
+========
+Examples
+========
+
+This page contains example plots. Click on any image to see the full image and source code.
diff --git a/doc/examples/distribution/README.rst b/doc/examples/distribution/README.rst
new file mode 100644
index 0000000..2077b05
--- /dev/null
+++ b/doc/examples/distribution/README.rst
@@ -0,0 +1,6 @@
+ .. _distribution_examples:
+
+.. _distribution-examples-index:
+
+Distribution of correlation times
+=================================
diff --git a/doc/examples/distribution/plot_ColeCole.py b/doc/examples/distribution/plot_ColeCole.py
new file mode 100644
index 0000000..88ebeed
--- /dev/null
+++ b/doc/examples/distribution/plot_ColeCole.py
@@ -0,0 +1,50 @@
+"""
+=========
+Cole-Cole
+=========
+
+Example for Cole-Cole distributions
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+from nmreval.distributions import ColeCole
+
+x = np.logspace(-5, 5, num=101)
+
+cc = ColeCole
+
+alpha_CC = [0.3, 0.5, 0.7]
+
+fig, axes = plt.subplots(2, 3, constrained_layout=True)
+
+lines = []
+for a in alpha_CC:
+ axes[0, 0].plot(np.log10(x), cc.correlation(x, 1, a))
+ axes[1, 0].plot(np.log10(x), np.log10(cc.specdens(x, 1, a)))
+ axes[0, 1].plot(np.log10(x), np.log10(cc.susceptibility(x, 1, a).real))
+ axes[1, 1].plot(np.log10(x), np.log10(cc.susceptibility(x, 1, a).imag))
+ l, = axes[0, 2].plot(np.log10(x), cc.distribution(x, 1, a),
+ label=rf'$\alpha={a}$')
+ lines.append(l)
+
+fig_titles = ('Correlation function', 'Susceptibility (real)', 'Distribution',
+ 'Spectral density', 'Susceptibility (imag)')
+fig_xlabel = (r'$\log(t/\tau_\mathrm{HN})$', r'$\log(\omega\tau_\mathrm{HN})$',
+ r'$\log(\tau/\tau_\mathrm{HN})$', r'$\log(\omega\tau_\mathrm{HN})$',
+ r'$\log(\omega\tau_\mathrm{HN})$')
+fig_ylabel = (r'$C(t)$', r"$\log(\chi'(\omega))$", r'$G(\ln\tau)$',
+ r'$\log(J(\omega))$', r"$\log(\chi''(\omega))$")
+
+for title, xlabel, ylabel, ax in zip(fig_titles, fig_xlabel, fig_ylabel, axes.ravel()):
+ ax.set_title(title)
+ ax.set_xlabel(xlabel)
+ ax.set_ylabel(ylabel)
+
+labels = [l.get_label() for l in lines]
+leg = fig.legend(lines, labels, loc='center left', bbox_to_anchor=(1.05, 0.50),
+ bbox_transform=axes[1, 1].transAxes)
+
+fig.delaxes(axes[1, 2])
+
+plt.show()
diff --git a/doc/examples/distribution/plot_ColeDavidson.py b/doc/examples/distribution/plot_ColeDavidson.py
new file mode 100644
index 0000000..62a6fa4
--- /dev/null
+++ b/doc/examples/distribution/plot_ColeDavidson.py
@@ -0,0 +1,50 @@
+"""
+=============
+Cole-Davidson
+=============
+
+Example for Cole-Davidson distributions
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+from nmreval.distributions import ColeDavidson
+
+x = np.logspace(-5, 5, num=101)
+
+cd = ColeDavidson
+
+gamma_CD = [0.3, 0.5, 0.7]
+
+fig, axes = plt.subplots(2, 3, constrained_layout=True)
+
+lines = []
+for g in gamma_CD:
+ axes[0, 0].plot(np.log10(x), cd.correlation(x, 1, g))
+ axes[1, 0].plot(np.log10(x), np.log10(cd.specdens(x, 1, g)))
+ axes[0, 1].plot(np.log10(x), np.log10(cd.susceptibility(x, 1, g).real))
+ axes[1, 1].plot(np.log10(x), np.log10(cd.susceptibility(x, 1, g).imag))
+ l, = axes[0, 2].plot(np.log10(x), cd.distribution(x, 1, g),
+ label=rf'$\gamma={g}$')
+ lines.append(l)
+
+fig_titles = ('Correlation function', 'Susceptibility (real)', 'Distribution',
+ 'Spectral density', 'Susceptibility (imag)')
+fig_xlabel = (r'$\log(t/\tau_\mathrm{CD})$', r'$\log(\omega\tau_\mathrm{CD})$',
+ r'$\log(\tau/\tau_\mathrm{CD})$', r'$\log(\omega\tau_\mathrm{CD})$',
+ r'$\log(\omega\tau_\mathrm{CD})$')
+fig_ylabel = (r'$C(t)$', r"$\log(\chi'(\omega))$", r'$G(\ln\tau)$',
+ r'$\log(J(\omega))$', r"$\log(\chi''(\omega))$")
+
+for title, xlabel, ylabel, ax in zip(fig_titles, fig_xlabel, fig_ylabel, axes.ravel()):
+ ax.set_title(title)
+ ax.set_xlabel(xlabel)
+ ax.set_ylabel(ylabel)
+
+labels = [l.get_label() for l in lines]
+leg = fig.legend(lines, labels, loc='center left', bbox_to_anchor=(1.05, 0.50),
+ bbox_transform=axes[1, 1].transAxes)
+
+fig.delaxes(axes[1, 2])
+
+plt.show()
diff --git a/doc/examples/distribution/plot_HavriliakNegami.py b/doc/examples/distribution/plot_HavriliakNegami.py
new file mode 100644
index 0000000..94bd0c9
--- /dev/null
+++ b/doc/examples/distribution/plot_HavriliakNegami.py
@@ -0,0 +1,53 @@
+"""
+================
+Havriliak-Negami
+================
+
+Example for Havriliak-Negami distributions
+"""
+from itertools import product
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+from nmreval.distributions import HavriliakNegami
+
+x = np.logspace(-5, 5, num=101)
+
+hn = HavriliakNegami
+
+alpha_CC = [0.4, 0.8]
+gamma_CD = [0.3, 0.7]
+
+fig, axes = plt.subplots(2, 3, constrained_layout=True)
+
+lines = []
+for a, g in product(alpha_CC, gamma_CD):
+ axes[0, 0].plot(np.log10(x), hn.correlation(x, 1, a, g))
+ axes[1, 0].plot(np.log10(x), np.log10(hn.specdens(x, 1, a, g)))
+ axes[0, 1].plot(np.log10(x), np.log10(hn.susceptibility(x, 1, a, g).real))
+ axes[1, 1].plot(np.log10(x), np.log10(hn.susceptibility(x, 1, a, g).imag))
+ l, = axes[0, 2].plot(np.log10(x), hn.distribution(x, 1, a, g),
+ label=rf'$\alpha={a}, \gamma={g}$')
+ lines.append(l)
+
+fig_titles = ('Correlation function', 'Susceptibility (real)', 'Distribution',
+ 'Spectral density', 'Susceptibility (imag)')
+fig_xlabel = (r'$\log(t/\tau_\mathrm{HN})$', r'$\log(\omega\tau_\mathrm{HN})$',
+ r'$\log(\tau/\tau_\mathrm{HN})$', r'$\log(\omega\tau_\mathrm{HN})$',
+ r'$\log(\omega\tau_\mathrm{HN})$')
+fig_ylabel = (r'$C(t)$', r"$\log(\chi'(\omega))$", r'$G(\ln\tau)$',
+ r'$\log(J(\omega))$', r"$\log(\chi''(\omega))$")
+
+for title, xlabel, ylabel, ax in zip(fig_titles, fig_xlabel, fig_ylabel, axes.ravel()):
+ ax.set_title(title)
+ ax.set_xlabel(xlabel)
+ ax.set_ylabel(ylabel)
+
+labels = [l.get_label() for l in lines]
+leg = fig.legend(lines, labels, loc='center left', bbox_to_anchor=(1.05, 0.50),
+ bbox_transform=axes[1, 1].transAxes)
+
+fig.delaxes(axes[1, 2])
+
+plt.show()
diff --git a/doc/examples/distribution/plot_KWW.py b/doc/examples/distribution/plot_KWW.py
new file mode 100644
index 0000000..e87e1e3
--- /dev/null
+++ b/doc/examples/distribution/plot_KWW.py
@@ -0,0 +1,50 @@
+"""
+=========================
+Kohlrausch-Williams-Watts
+=========================
+
+Example for KWW distributions
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+from nmreval.distributions import KWW
+
+x = np.logspace(-5, 5, num=101)
+
+kww = KWW
+
+beta_KWW = [0.3, 0.5, 0.7]
+
+fig, axes = plt.subplots(2, 3, constrained_layout=True)
+
+lines = []
+for b in beta_KWW:
+ axes[0, 0].plot(np.log10(x), kww.correlation(x, 1, b))
+ axes[1, 0].plot(np.log10(x), np.log10(kww.specdens(x, 1, b)))
+ axes[0, 1].plot(np.log10(x), np.log10(kww.susceptibility(x, 1, b).real))
+ axes[1, 1].plot(np.log10(x), np.log10(kww.susceptibility(x, 1, b).imag))
+ l, = axes[0, 2].plot(np.log10(x), kww.distribution(x, 1, b),
+ label=rf'$\beta={b}$')
+ lines.append(l)
+
+fig_titles = ('Correlation function', 'Susceptibility (real)', 'Distribution',
+ 'Spectral density', 'Susceptibility (imag)')
+fig_xlabel = (r'$\log(t/\tau_\mathrm{KWW})$', r'$\log(\omega\tau_\mathrm{KWW})$',
+ r'$\log(\tau/\tau_\mathrm{KWW})$', r'$\log(\omega\tau_\mathrm{KWW})$',
+ r'$\log(\omega\tau_\mathrm{KWW})$')
+fig_ylabel = (r'$C(t)$', r"$\log(\chi'(\omega))$", r'$G(\ln\tau)$',
+ r'$\log(J(\omega))$', r"$\log(\chi''(\omega))$")
+
+for title, xlabel, ylabel, ax in zip(fig_titles, fig_xlabel, fig_ylabel, axes.ravel()):
+ ax.set_title(title)
+ ax.set_xlabel(xlabel)
+ ax.set_ylabel(ylabel)
+
+labels = [l.get_label() for l in lines]
+leg = fig.legend(lines, labels, loc='center left', bbox_to_anchor=(1.05, 0.50),
+ bbox_transform=axes[1, 1].transAxes)
+
+fig.delaxes(axes[1, 2])
+
+plt.show()
diff --git a/doc/examples/distribution/plot_LogGaussian.py b/doc/examples/distribution/plot_LogGaussian.py
new file mode 100644
index 0000000..ac31db2
--- /dev/null
+++ b/doc/examples/distribution/plot_LogGaussian.py
@@ -0,0 +1,50 @@
+"""
+============
+Log-Gaussian
+============
+
+Example for Log-Gaussian distributions
+"""
+import matplotlib.pyplot as plt
+import numpy as np
+
+from nmreval.distributions import LogGaussian
+
+x = np.logspace(-5, 5, num=101)
+
+lg = LogGaussian
+
+sigma_lg = [1, 3, 5]
+
+fig, axes = plt.subplots(2, 3, constrained_layout=True)
+
+lines = []
+for s in sigma_lg:
+ axes[0, 0].plot(np.log10(x), lg.correlation(x, 1, s))
+ axes[1, 0].plot(np.log10(x), np.log10(lg.specdens(x, 1, s)))
+ axes[0, 1].plot(np.log10(x), np.log10(lg.susceptibility(x, 1, s).real))
+ axes[1, 1].plot(np.log10(x), np.log10(lg.susceptibility(x, 1, s).imag))
+ l, = axes[0, 2].plot(np.log10(x), lg.distribution(x, 1, s),
+ label=rf'$\sigma={s}$')
+ lines.append(l)
+
+fig_titles = ('Correlation function', 'Susceptibility (real)', 'Distribution',
+ 'Spectral density', 'Susceptibility (imag)')
+fig_xlabel = (r'$\log(t/\tau_\mathrm{LG})$', r'$\log(\omega\tau_\mathrm{LG})$',
+ r'$\log(\tau/\tau_\mathrm{LG})$', r'$\log(\omega\tau_\mathrm{LG})$',
+ r'$\log(\omega\tau_\mathrm{LG})$')
+fig_ylabel = (r'$C(t)$', r"$\log(\chi'(\omega))$", r'$G(\ln\tau)$',
+ r'$\log(J(\omega))$', r"$\log(\chi''(\omega))$")
+
+for title, xlabel, ylabel, ax in zip(fig_titles, fig_xlabel, fig_ylabel, axes.ravel()):
+ ax.set_title(title)
+ ax.set_xlabel(xlabel)
+ ax.set_ylabel(ylabel)
+
+labels = [l.get_label() for l in lines]
+leg = fig.legend(lines, labels, loc='center left', bbox_to_anchor=(1.05, 0.50),
+ bbox_transform=axes[1, 1].transAxes)
+
+fig.delaxes(axes[1, 2])
+
+plt.show()
diff --git a/doc/examples/nmr/README.rst b/doc/examples/nmr/README.rst
new file mode 100644
index 0000000..53e560d
--- /dev/null
+++ b/doc/examples/nmr/README.rst
@@ -0,0 +1,6 @@
+.. _nmr_examples:
+
+.. _nmr-examples-index:
+
+NMR specifics
+=============
diff --git a/doc/examples/nmr/plot_RelaxationEvaluation.py b/doc/examples/nmr/plot_RelaxationEvaluation.py
new file mode 100644
index 0000000..964c753
--- /dev/null
+++ b/doc/examples/nmr/plot_RelaxationEvaluation.py
@@ -0,0 +1,67 @@
+"""
+=======================
+Spin-lattice relaxation
+=======================
+
+Example for
+"""
+import numpy as np
+from matplotlib import pyplot as plt
+
+from nmreval.distributions import ColeDavidson
+from nmreval.nmr import Relaxation, RelaxationEvaluation
+from nmreval.nmr.coupling import Quadrupolar
+from nmreval.utils.constants import kB
+
+# Define temperature range
+inv_temp = np.linspace(3, 9, num=30)
+temperature = 1000/inv_temp
+
+# spectral density parameter
+ea = 0.45
+tau = 1e-21 * np.exp(ea / kB / temperature)
+gamma_cd = 0.1
+
+# interaction parameter
+omega = 2*np.pi*46e6
+delta = 120e3
+eta = 0
+
+r = Relaxation()
+r.set_distribution(ColeDavidson) # the only parameter that has to be set beforehand
+
+t1_values = r.t1(omega, tau, gamma_cd, mode='bpp',
+ prefactor=Quadrupolar.relax(delta, eta))
+# add noise
+rng = np.random.default_rng(123456789)
+noisy = (rng.random(t1_values.size)-0.5) * 0.5 * t1_values + t1_values
+
+# set parameter and data
+r_eval = RelaxationEvaluation()
+r_eval.set_distribution(ColeDavidson)
+r_eval.set_coupling(Quadrupolar, (delta, eta))
+r_eval.data(temperature, noisy)
+r_eval.omega = omega
+
+t1_min_data, _ = r_eval.calculate_t1_min() # second argument is None
+t1_min_inter, line = r_eval.calculate_t1_min(interpolate=1, trange=(160, 195), use_log=True)
+
+fig, ax = plt.subplots()
+ax.semilogy(1000/t1_min_data[0], t1_min_data[1], 'rx', label='Data minimum')
+ax.semilogy(1000/t1_min_inter[0], t1_min_inter[1], 'r+', label='Parabola')
+ax.semilogy(1000/line[0], line[1])
+
+found_gamma, found_height = r_eval.get_increase(t1_min_inter[1], idx=0, mode='distribution')
+print(found_gamma)
+
+plt.axhline(found_height)
+plt.show()
+
+#%%
+# Now we found temperature and height of the minimum we can calculate the correlation time
+
+plt.semilogy(1000/temperature, tau)
+tau_from_t1, opts = r_eval.correlation_from_t1()
+print(opts)
+plt.semilogy(1000/tau_from_t1[:, 0], tau_from_t1[:, 1], 'o')
+plt.show()
diff --git a/docs/make.bat b/doc/make.bat
similarity index 100%
rename from docs/make.bat
rename to doc/make.bat
diff --git a/docs/source/_static/fit_dialog.png b/doc/source/_static/fit_dialog.png
similarity index 100%
rename from docs/source/_static/fit_dialog.png
rename to doc/source/_static/fit_dialog.png
diff --git a/docs/source/_static/logo.png b/doc/source/_static/logo.png
similarity index 100%
rename from docs/source/_static/logo.png
rename to doc/source/_static/logo.png
diff --git a/doc/source/_templates/autosummary/class.rst b/doc/source/_templates/autosummary/class.rst
new file mode 100644
index 0000000..4fa8438
--- /dev/null
+++ b/doc/source/_templates/autosummary/class.rst
@@ -0,0 +1,14 @@
+:mod:`{{ module | escape }}`.{{ objname }}
+{{ underline }}==================
+
+.. currentmodule:: {{ module }}
+
+.. autoclass:: {{ objname }}
+ :members:
+ :inherited-members:
+
+.. include:: {{ fullname }}.examples
+
+.. raw:: html
+
+
diff --git a/doc/source/api/data.rst b/doc/source/api/data.rst
new file mode 100644
index 0000000..7f77c2e
--- /dev/null
+++ b/doc/source/api/data.rst
@@ -0,0 +1,5 @@
+.. automodule:: nmreval.data
+ :no-members:
+ :no-inherited-members:
+ :no-special-members:
+
diff --git a/doc/source/api/distributions.rst b/doc/source/api/distributions.rst
new file mode 100644
index 0000000..c62e52c
--- /dev/null
+++ b/doc/source/api/distributions.rst
@@ -0,0 +1,4 @@
+.. automodule:: nmreval.distributions
+ :no-members:
+ :no-inherited-members:
+ :no-special-members:
diff --git a/docs/source/api/distributions/index.rst b/doc/source/api/distributions2/index.rst
similarity index 100%
rename from docs/source/api/distributions/index.rst
rename to doc/source/api/distributions2/index.rst
diff --git a/doc/source/api/index.rst b/doc/source/api/index.rst
new file mode 100644
index 0000000..10f0748
--- /dev/null
+++ b/doc/source/api/index.rst
@@ -0,0 +1,13 @@
+=========
+Reference
+=========
+
+.. toctree::
+ :caption: Table of contents
+ :maxdepth: 1
+ :glob:
+
+ data
+ models
+ distributions
+ nmr
diff --git a/doc/source/api/models.rst b/doc/source/api/models.rst
new file mode 100644
index 0000000..3bcef09
--- /dev/null
+++ b/doc/source/api/models.rst
@@ -0,0 +1,4 @@
+.. automodule:: nmreval.models
+ :no-members:
+ :no-inherited-members:
+ :no-special-members:
diff --git a/docs/source/api/models/basic.rst b/doc/source/api/models2/basic.rst
similarity index 100%
rename from docs/source/api/models/basic.rst
rename to doc/source/api/models2/basic.rst
diff --git a/docs/source/api/models/index.rst b/doc/source/api/models2/index.rst
similarity index 100%
rename from docs/source/api/models/index.rst
rename to doc/source/api/models2/index.rst
diff --git a/docs/source/api/models/nmreval.models.basic.rst b/doc/source/api/models2/nmreval.models.basic.rst
similarity index 100%
rename from docs/source/api/models/nmreval.models.basic.rst
rename to doc/source/api/models2/nmreval.models.basic.rst
diff --git a/doc/source/api/nmr.rst b/doc/source/api/nmr.rst
new file mode 100644
index 0000000..a4fe784
--- /dev/null
+++ b/doc/source/api/nmr.rst
@@ -0,0 +1,4 @@
+.. automodule:: nmreval.nmr
+ :no-members:
+ :no-inherited-members:
+ :no-special-members:
diff --git a/docs/source/conf.py b/doc/source/conf.py
similarity index 92%
rename from docs/source/conf.py
rename to doc/source/conf.py
index 3d36539..e516330 100644
--- a/docs/source/conf.py
+++ b/doc/source/conf.py
@@ -10,6 +10,7 @@
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
+import os
import sys
import sphinx_bootstrap_theme
sys.path.append('/autohome/dominik/nmreval')
@@ -43,8 +44,46 @@ extensions = [
'sphinx.ext.napoleon',
'sphinx.ext.viewcode',
'sphinx.ext.intersphinx',
+ 'sphinx_gallery.gen_gallery',
]
+# configuration for intersphinx
+intersphinx_mapping = {
+ 'numpy': ('https://numpy.org/doc/stable/', None),
+ 'python': ('https://docs.python.org/3/', None),
+ 'scipy': ('https://docs.scipy.org/doc/scipy/', None),
+ 'PyQt': ('https://www.riverbankcomputing.com/static/Docs/PyQt5/', None),
+ 'matplotlib': ('https://matplotlib.org/stable', None),
+}
+
+# autodoc options
+autodoc_typehints = 'none'
+autodoc_class_signature = 'separated'
+autoclass_content = 'class'
+autodoc_member_order = 'groupwise'
+# autodoc_default_options = {'members': False, 'inherited-members': False}
+
+# autosummay options
+autosummary_generate = True
+
+# spinx-gallery
+sphinx_gallery_conf = {
+ 'examples_dirs': '../examples', # path to your example scripts
+ 'gallery_dirs': ['gallery'], # path to where to save gallery generated output
+ 'backreferences_dir': os.path.join('api', 'generated'), # directory where function/class granular galleries are stored
+ 'doc_module': 'nmreval', # Modules for which function/class level galleries are created.
+ 'reference_url': {
+ 'nmreval': None, # The module you locally document uses None
+ },
+ 'download_all_examples': False,
+ 'plot_gallery': True,
+ 'inspect_global_variables': False,
+ 'remove_config_comments': True,
+ 'min_reported_time': 10000000000,
+ 'show_memory': False,
+ 'show_signature': False,
+}
+
# The suffix(es) of source filenames.
# You can specify multiple suffix as a list of string:
#
@@ -115,30 +154,15 @@ todo_include_todos = False
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
-# html_theme = 'bootstrap'
html_theme = 'pydata_sphinx_theme'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
-#
-# html_theme_options = {
-# # 'source_link_position': "footer",
-# 'bootswatch_theme': "cosmo",
-# 'navbar_title': "Welcome to hell",
-# 'navbar_sidebarrel': True,
-# 'nosidebar': False,
-# 'body_max_width': '100%',
-# 'navbar_links': [
-# ('User guide', 'user_guide/index'),
-# ('References', 'api/index'),
-# ],
-# }
html_theme_options = {
'collapse_navigation': False,
'show_prev_next': False,
'navbar_end': ['navbar-icon-links.html', 'search-field.html'],
- 'show_toc_level': 3
}
# Add any paths that contain custom themes here, relative to this directory.
@@ -396,29 +420,3 @@ epub_exclude_files = ['search.html']
# If false, no index is generated.
#
# epub_use_index = True
-
-
-# configuration for intersphinx
-intersphinx_mapping = {
- 'Pillow': ('https://pillow.readthedocs.io/en/stable/', None),
- 'cycler': ('https://matplotlib.org/cycler/', None),
- 'dateutil': ('https://dateutil.readthedocs.io/en/stable/', None),
- 'ipykernel': ('https://ipykernel.readthedocs.io/en/latest/', None),
- 'numpy': ('https://numpy.org/doc/stable/', None),
- 'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None),
- 'pytest': ('https://pytest.org/en/stable/', None),
- 'python': ('https://docs.python.org/3/', None),
- 'scipy': ('https://docs.scipy.org/doc/scipy/', None),
- 'tornado': ('https://www.tornadoweb.org/en/stable/', None),
- 'xarray': ('https://xarray.pydata.org/en/stable/', None),
- 'PyQt': ('https://www.riverbankcomputing.com/static/Docs/PyQt5/', None),
-}
-
-# autodoc options
-autodoc_typehints = 'none'
-autodoc_class_signature = 'separated'
-autoclass_content = 'class'
-
-# autosummay options
-autosummary_generate = True
-
diff --git a/doc/source/gallery/index.rst b/doc/source/gallery/index.rst
new file mode 100644
index 0000000..37d2514
--- /dev/null
+++ b/doc/source/gallery/index.rst
@@ -0,0 +1,179 @@
+:orphan:
+
+
+
+.. _sphx_glr_gallery:
+
+.. examples-index:
+
+.. _gallery:
+
+========
+Examples
+========
+
+This page contains example plots. Click on any image to see the full image and source code.
+
+
+.. raw:: html
+
+
+
+
+
+.. _sphx_glr_gallery_distribution:
+
+ .. _distribution_examples:
+
+.. _distribution-examples-index:
+
+Distribution of correlation times
+=================================
+
+
+
+.. raw:: html
+
+
+
+.. only:: html
+
+ .. figure:: /gallery/distribution/images/thumb/sphx_glr_plot_KWW_thumb.png
+ :alt: Kohlrausch-Williams-Watts
+
+ :ref:`sphx_glr_gallery_distribution_plot_KWW.py`
+
+.. raw:: html
+
+
+
+
+.. toctree::
+ :hidden:
+
+ /gallery/distribution/plot_KWW
+
+.. raw:: html
+
+
+
+.. only:: html
+
+ .. figure:: /gallery/distribution/images/thumb/sphx_glr_plot_ColeCole_thumb.png
+ :alt: Cole-Cole
+
+ :ref:`sphx_glr_gallery_distribution_plot_ColeCole.py`
+
+.. raw:: html
+
+
+
+
+.. toctree::
+ :hidden:
+
+ /gallery/distribution/plot_ColeCole
+
+.. raw:: html
+
+
+
+.. only:: html
+
+ .. figure:: /gallery/distribution/images/thumb/sphx_glr_plot_LogGaussian_thumb.png
+ :alt: Log-Gaussian
+
+ :ref:`sphx_glr_gallery_distribution_plot_LogGaussian.py`
+
+.. raw:: html
+
+
+
+
+.. toctree::
+ :hidden:
+
+ /gallery/distribution/plot_LogGaussian
+
+.. raw:: html
+
+
+
+.. only:: html
+
+ .. figure:: /gallery/distribution/images/thumb/sphx_glr_plot_ColeDavidson_thumb.png
+ :alt: Cole-Davidson
+
+ :ref:`sphx_glr_gallery_distribution_plot_ColeDavidson.py`
+
+.. raw:: html
+
+
+
+
+.. toctree::
+ :hidden:
+
+ /gallery/distribution/plot_ColeDavidson
+
+.. raw:: html
+
+
+
+.. only:: html
+
+ .. figure:: /gallery/distribution/images/thumb/sphx_glr_plot_HavriliakNegami_thumb.png
+ :alt: Havriliak-Negami
+
+ :ref:`sphx_glr_gallery_distribution_plot_HavriliakNegami.py`
+
+.. raw:: html
+
+
+
+
+.. toctree::
+ :hidden:
+
+ /gallery/distribution/plot_HavriliakNegami
+.. raw:: html
+
+
+
+
+
+.. _sphx_glr_gallery_nmr:
+
+.. _nmr_examples:
+
+.. _nmr-examples-index:
+
+NMR specifics
+=============
+
+
+
+.. raw:: html
+
+
+
+.. only:: html
+
+ .. figure:: /gallery/nmr/images/thumb/sphx_glr_plot_RelaxationEvaluation_thumb.png
+ :alt: Spin-lattice relaxation
+
+ :ref:`sphx_glr_gallery_nmr_plot_RelaxationEvaluation.py`
+
+.. raw:: html
+
+
+
+
+.. toctree::
+ :hidden:
+
+ /gallery/nmr/plot_RelaxationEvaluation
+.. raw:: html
+
+
+
diff --git a/doc/source/gallery/searchindex.bak b/doc/source/gallery/searchindex.bak
new file mode 100644
index 0000000..38a4678
--- /dev/null
+++ b/doc/source/gallery/searchindex.bak
@@ -0,0 +1,3 @@
+'/autohome/dominik/nmreval/doc/_build/html/index.html', (0, 6969)
+'/autohome/dominik/nmreval/doc/_build/html/_static/documentation_options.js', (7168, 364)
+'/autohome/dominik/nmreval/doc/_build/html/searchindex.js', (7680, 29280)
diff --git a/doc/source/gallery/searchindex.dat b/doc/source/gallery/searchindex.dat
new file mode 100644
index 0000000..2173478
Binary files /dev/null and b/doc/source/gallery/searchindex.dat differ
diff --git a/doc/source/gallery/searchindex.dir b/doc/source/gallery/searchindex.dir
new file mode 100644
index 0000000..38a4678
--- /dev/null
+++ b/doc/source/gallery/searchindex.dir
@@ -0,0 +1,3 @@
+'/autohome/dominik/nmreval/doc/_build/html/index.html', (0, 6969)
+'/autohome/dominik/nmreval/doc/_build/html/_static/documentation_options.js', (7168, 364)
+'/autohome/dominik/nmreval/doc/_build/html/searchindex.js', (7680, 29280)
diff --git a/docs/source/index.rst b/doc/source/index.rst
similarity index 82%
rename from docs/source/index.rst
rename to doc/source/index.rst
index 98a6339..6b3d246 100644
--- a/docs/source/index.rst
+++ b/doc/source/index.rst
@@ -3,17 +3,15 @@
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
-###################################
+#####################
NMREval documentation
-###################################
+#####################
.. toctree::
:maxdepth: 1
user_guide/index
-
- nmr/index
-
+ gallery/index
api/index
diff --git a/docs/source/nmr/depake.png b/doc/source/nmr/depake.png
similarity index 100%
rename from docs/source/nmr/depake.png
rename to doc/source/nmr/depake.png
diff --git a/docs/source/nmr/index.rst b/doc/source/nmr/index.rst
similarity index 100%
rename from docs/source/nmr/index.rst
rename to doc/source/nmr/index.rst
diff --git a/docs/source/nmr/pake.rst b/doc/source/nmr/pake.rst
similarity index 100%
rename from docs/source/nmr/pake.rst
rename to doc/source/nmr/pake.rst
diff --git a/docs/source/user_guide/fit.rst b/doc/source/user_guide/fit.rst
similarity index 100%
rename from docs/source/user_guide/fit.rst
rename to doc/source/user_guide/fit.rst
diff --git a/docs/source/user_guide/index.rst b/doc/source/user_guide/index.rst
similarity index 100%
rename from docs/source/user_guide/index.rst
rename to doc/source/user_guide/index.rst
diff --git a/docs/source/user_guide/read.rst b/doc/source/user_guide/read.rst
similarity index 100%
rename from docs/source/user_guide/read.rst
rename to doc/source/user_guide/read.rst
diff --git a/docs/source/user_guide/shift_scale.rst b/doc/source/user_guide/shift_scale.rst
similarity index 100%
rename from docs/source/user_guide/shift_scale.rst
rename to doc/source/user_guide/shift_scale.rst
diff --git a/docs/source/_templates/autosummary.rst b/docs/source/_templates/autosummary.rst
deleted file mode 100644
index 0f54333..0000000
--- a/docs/source/_templates/autosummary.rst
+++ /dev/null
@@ -1,25 +0,0 @@
-{{ fullname | escape | underline }}
-
-
-.. currentmodule:: {{ module }}
-
-
-{% if objtype in ['class'] %}
-
-Inheritance diagram
-
-.. inheritance-diagram:: {{ objname }}
- :parts: 1
-
-{{ objtype }}
-
-.. auto{{ objtype }}:: {{ objname }}
- :special-members: __call__
- :members:
- :undoc-members:
-
-{% else %}
-.. auto{{ objtype }}:: {{ objname }}
-
-{% endif %}
-
diff --git a/docs/source/api/data.rst b/docs/source/api/data.rst
deleted file mode 100644
index 616a808..0000000
--- a/docs/source/api/data.rst
+++ /dev/null
@@ -1,23 +0,0 @@
-**************
-Data container
-**************
-
-.. automodule:: nmreval.data
- :no-members:
- :no-undoc-members:
-
-
-.. contents:: Table of Contents
- :depth: 3
- :local:
- :backlinks: entry
-
-
-.. autosummary::
- :toctree: generated/
- :template: autosummary.rst
- :nosignatures:
-
- nmreval.data.Points
- nmreval.data.Signal
- nmreval.data.BDS
diff --git a/docs/source/api/generated/nmreval.data.BDS.rst b/docs/source/api/generated/nmreval.data.BDS.rst
deleted file mode 100644
index 0818b3b..0000000
--- a/docs/source/api/generated/nmreval.data.BDS.rst
+++ /dev/null
@@ -1,23 +0,0 @@
-nmreval.data.BDS
-================
-
-
-.. currentmodule:: nmreval.data
-
-
-
-
-Inheritance diagram
-
-.. inheritance-diagram:: BDS
- :parts: 1
-
-class
-
-.. autoclass:: BDS
- :special-members: __call__
- :members:
- :undoc-members:
-
-
-
\ No newline at end of file
diff --git a/docs/source/api/generated/nmreval.data.Points.rst b/docs/source/api/generated/nmreval.data.Points.rst
deleted file mode 100644
index 16d7d60..0000000
--- a/docs/source/api/generated/nmreval.data.Points.rst
+++ /dev/null
@@ -1,23 +0,0 @@
-nmreval.data.Points
-===================
-
-
-.. currentmodule:: nmreval.data
-
-
-
-
-Inheritance diagram
-
-.. inheritance-diagram:: Points
- :parts: 1
-
-class
-
-.. autoclass:: Points
- :special-members: __call__
- :members:
- :undoc-members:
-
-
-
\ No newline at end of file
diff --git a/docs/source/api/generated/nmreval.data.Signal.rst b/docs/source/api/generated/nmreval.data.Signal.rst
deleted file mode 100644
index c913f1d..0000000
--- a/docs/source/api/generated/nmreval.data.Signal.rst
+++ /dev/null
@@ -1,23 +0,0 @@
-nmreval.data.Signal
-===================
-
-
-.. currentmodule:: nmreval.data
-
-
-
-
-Inheritance diagram
-
-.. inheritance-diagram:: Signal
- :parts: 1
-
-class
-
-.. autoclass:: Signal
- :special-members: __call__
- :members:
- :undoc-members:
-
-
-
\ No newline at end of file
diff --git a/docs/source/api/index.rst b/docs/source/api/index.rst
deleted file mode 100644
index acbad32..0000000
--- a/docs/source/api/index.rst
+++ /dev/null
@@ -1,12 +0,0 @@
-==========
-References
-==========
-
-.. toctree::
- :caption: Table of contents
- :maxdepth: 2
- :glob:
-
- data.rst
- models/index.rst
- distributions/index.rst
diff --git a/nmreval/data/__init__.py b/nmreval/data/__init__.py
index 7b73355..88788bd 100755
--- a/nmreval/data/__init__.py
+++ b/nmreval/data/__init__.py
@@ -1,3 +1,20 @@
+"""
+====================================
+Data container (:mod:`nmreval.data`)
+====================================
+
+.. autosummary::
+ :toctree: generated/
+ :nosignatures:
+
+ Points
+ Signal
+ FID
+ Spectrum
+ BDS
+
+"""
+
from .points import Points
from .signals import Signal
from .bds import BDS
diff --git a/nmreval/data/bds.py b/nmreval/data/bds.py
index 086313a..07e208c 100644
--- a/nmreval/data/bds.py
+++ b/nmreval/data/bds.py
@@ -15,10 +15,11 @@ class BDS(Signal):
def __init__(self, x, y, **kwargs: Any):
super().__init__(x, y, **kwargs)
- if np.all(self._x > 0) and not np.allclose(np.diff(self._x), self._x[1]-self._x[0]):
- self.dx = self.x[1] / self.x[0]
- else:
- self.dx = self._x[1] - self._x[0]
+ if len(self._x) > 1:
+ if np.all(self._x > 0) and np.allclose(self._x[1:]/self._x[:-1], self._x[1]/self._x[0]):
+ self.dx = self.x[1] / self.x[0]
+ else:
+ self.dx = self._x[1] - self._x[0]
def __repr__(self) -> str:
return f"{self.meta['mode']}: {self.name}"
@@ -32,10 +33,10 @@ class BDS(Signal):
window_length (int)
Returns:
- Points
+ Points:
New Points instance with
- References:
+ Reference:
Wübbenhorst, M.; van Turnhout, J.: Analysis of complex dielectric spectra.
I. One-dimensional derivative techniques and three-dimensional modelling.
J. Non-Cryst. Solid. 305 (2002) https://doi.org/10.1016/s0022-3093(02)01086-4
diff --git a/nmreval/data/nmr.py b/nmreval/data/nmr.py
index 79dc663..f9c18d8 100644
--- a/nmreval/data/nmr.py
+++ b/nmreval/data/nmr.py
@@ -7,6 +7,9 @@ from .signals import Signal
class FID(Signal):
+ """
+ Extensions if :class:`Signal` for NMR timesignals
+ """
def __init__(self, x, y, **kwargs):
super().__init__(x, y, **kwargs)
@@ -16,7 +19,16 @@ class FID(Signal):
def __repr__(self):
return f"FID: {self.name}"
- def baseline(self, percentage=0.12):
+ def baseline(self, percentage: float = 0.12):
+ """
+ Substract
+
+ Args:
+ percentage:
+
+ Returns:
+
+ """
self._y -= self._y[int(-percentage * self.length):].mean()
return self
@@ -51,7 +63,7 @@ class FID(Signal):
return self
- def fourier(self):
+ def fourier(self) -> 'Spectrum':
ft = np.fft.fftshift(np.fft.fft(self._y)) / self.dx
freq = np.fft.fftshift(np.fft.fftfreq(self.length, self.dx))
@@ -63,9 +75,15 @@ class FID(Signal):
def fft_depake(self, scale: bool = False):
"""
Calculate deconvoluted Pake spectra
- M.A. McCabe, S.R. Wassail:
- Rapid deconvolution of NMR powder spectra by weighted fast Fourier transformation,
- SSNMR (1997), Vol.10, Nr.1-2, pp. 53-61,
+
+ Args:
+ scale (bool):
+
+ Reference:
+ M.A. McCabe, S.R. Wassail:
+ Rapid deconvolution of NMR powder spectra by weighted fast Fourier transformation,
+ SSNMR (1997), Vol.10, Nr.1-2, pp. 53-61
+
"""
_y = self._y + 0
# Perform FFT depaking
@@ -102,8 +120,9 @@ class FID(Signal):
self._y_err = np.std(self._y[-int(0.1*self.length):])/1.41
return self._y_err * np.ones(self.length)
- def shift(self, points: Union[str, float], mode: str = 'pts'):
+ def shift(self, points: int, mode: str = 'pts') -> None:
"""
+ Shift y values to new x indexes
Args:
points : shift value,
@@ -113,13 +132,17 @@ class FID(Signal):
"""
if mode == 'pts':
- super().shift(points)
+ super().shift(int(points))
else:
pts = int(points//self.dx)
super().shift(pts)
class Spectrum(Signal):
+ """
+ Extension of :class:`Signal` for NMR spectra
+ """
+
def __init__(self, x, y, dx=None, **kwargs):
super().__init__(x, y, **kwargs)
if dx is None:
@@ -139,7 +162,7 @@ class Spectrum(Signal):
return self
- def fourier(self):
+ def fourier(self) -> FID:
ft = np.fft.ifft(np.fft.ifftshift(self._y * self.dx))
t = np.arange(len(ft))*self.dx
shifted = np.fft.ifftshift(self._x)[0]
@@ -172,8 +195,8 @@ class Spectrum(Signal):
return self._y_err * np.ones(self.length)
- def shift(self, points, mode='pts'):
+ def shift(self, points: int, mode: str = 'pts'):
if mode == 'pts':
- super().shift(points)
+ super().shift(int(points))
else:
return self
diff --git a/nmreval/data/points.py b/nmreval/data/points.py
index c143151..084f182 100644
--- a/nmreval/data/points.py
+++ b/nmreval/data/points.py
@@ -412,11 +412,15 @@ class Points:
def diff(self, log: bool = False, limits: Optional[Tuple[float, float]] = None) -> PointLike:
"""
+ Calculate first derivate :math:`dy/dx` or :math:`dy/d(\ln x)`.
+
+
Args:
- log:
- limits:
+ log (bool) : Flag if derivative is with respect to ln(x) instead of x. Default is `False`.
+ limits (tuple, optional): Range `(xmin, xmax)` which is differentiated.
Returns:
+ Copy of set with new y values.
"""
@@ -430,6 +434,8 @@ class Points:
else:
new_data.y = np.gradient(new_data.y, new_data.x)
+ new_data.remove(np.argwhere(np.isnan(new_data.y)))
+
return new_data
def magnitude(self) -> PointLike:
@@ -530,6 +536,8 @@ class Points:
def shift(self, points: int) -> PointLike:
"""
+ Shift indexes of y values.
+
Move y values `points` indexes, remove invalid indexes and fill remaining with zeros
Negative `points` shift to the left, positive `points` shift to the right
@@ -558,11 +566,21 @@ class Points:
return self
- def sort(self, axis=0):
- if axis == 0:
+ def sort(self, axis: str = 'x') -> PointLike:
+ """
+ Sort data in increased order.
+
+ Args:
+ axis (str, {`x`, `y`}) : Axis that determines new order. Default is `x`
+
+ """
+
+ if axis == 'x':
sort_order = np.argsort(self._x)
- else:
+ elif axis == 'y':
sort_order = np.argsort(self._y)
+ else:
+ raise ValueError('Unknown sort axis, use `x` or `y`.')
self._x = self._x[sort_order]
self._y = self._y[sort_order]
self._y_err = self._y_err[sort_order]
diff --git a/nmreval/data/signals.py b/nmreval/data/signals.py
index 222d03e..c4cf9b1 100644
--- a/nmreval/data/signals.py
+++ b/nmreval/data/signals.py
@@ -6,7 +6,7 @@ from .points import Points
class Signal(Points):
"""
- Extension of Points for complex y values.
+ Extension of :class:`Points` for complex y values.
"""
def __init__(self, x, y, **kwargs):
@@ -18,7 +18,10 @@ class Signal(Points):
super().__init__(x, y, **kwargs)
- self.dx = kwargs.get('dx', abs(self._x[1] - self._x[0]))
+ if len(self._x) > 1:
+ self.dx = kwargs.get('dx', abs(self._x[1] - self._x[0]))
+ else:
+ self.dx = 0
self.meta.update({'phase': [], 'shift': 0})
def __repr__(self):
diff --git a/nmreval/distributions/__init__.py b/nmreval/distributions/__init__.py
index 55d58aa..741b106 100644
--- a/nmreval/distributions/__init__.py
+++ b/nmreval/distributions/__init__.py
@@ -1,3 +1,25 @@
+"""
+=================================================================
+Distributions of correlation times (:mod:`nmreval.distributions`)
+=================================================================
+
+Each class provides a distribution of correlation times, correlation
+function, spectral density, susceptibility, and calculation of different
+types of correlation times.
+
+.. autosummary::
+ :toctree: generated/
+ :template: autosummary/class_with_attributes.rst
+ :nosignatures:
+
+ Debye
+ ColeCole
+ ColeDavidson
+ HavriliakNegami
+ KWW
+ LogGaussian
+
+"""
from .havriliaknegami import HavriliakNegami
from .colecole import ColeCole
diff --git a/nmreval/distributions/base.py b/nmreval/distributions/base.py
index d89a326..7d3695f 100644
--- a/nmreval/distributions/base.py
+++ b/nmreval/distributions/base.py
@@ -1,8 +1,11 @@
import abc
-from warnings import warn
+from typing import Any, Union
+
import numpy as np
+from nmreval.lib.utils import ArrayLike
+
class Distribution(abc.ABC):
name = 'Abstract distribution'
@@ -15,7 +18,12 @@ class Distribution(abc.ABC):
@staticmethod
@abc.abstractmethod
- def distribution(taus, tau0, *args):
+ def distribution(tau, tau0, *args):
+ pass
+
+ @staticmethod
+ @abc.abstractmethod
+ def correlation(t, tau, *args):
pass
@staticmethod
@@ -24,13 +32,8 @@ class Distribution(abc.ABC):
pass
@classmethod
- def specdens(cls, omega, tau, *args):
- return -cls.susceptibility(omega, tau, *args).imag / omega
-
- @staticmethod
- @abc.abstractmethod
- def correlation(t, tau0, *args):
- pass
+ def specdens(cls, omega: ArrayLike, tau: ArrayLike, *args: Any) -> Union[np.ndarray, float]:
+ return cls.susceptibility(omega, tau, *args).imag / omega
@classmethod
def mean_value(cls, *args, mode='mean'):
@@ -43,6 +46,27 @@ class Distribution(abc.ABC):
return args[0]
+ @staticmethod
+ def mean(*args):
+ return args[0]
+
+ @staticmethod
+ def logmean(*args):
+ """
+ Return mean logarithmic tau
+
+ Args:
+ *args:
+
+ Returns:
+
+ """
+ return np.log(args[0])
+
+ @staticmethod
+ def max(*args):
+ return args[0]
+
@classmethod
def convert(cls, *args, from_='raw', to_='mean'):
if from_ == to_:
@@ -62,24 +86,3 @@ class Distribution(abc.ABC):
return raw
else:
return cls.mean_value(raw, *args[1:], mode=to_)
-
- @staticmethod
- def logmean(*args):
- """
- Return mean logarithmic tau
-
- Args:
- *args:
-
- Returns:
-
- """
- return np.log(args[0])
-
- @staticmethod
- def mean(*args):
- return args[0]
-
- @staticmethod
- def max(*args):
- return args[0]
diff --git a/nmreval/distributions/colecole.py b/nmreval/distributions/colecole.py
index e85c58a..cc10f8d 100644
--- a/nmreval/distributions/colecole.py
+++ b/nmreval/distributions/colecole.py
@@ -1,6 +1,8 @@
import numpy as np
from .base import Distribution
+from ..lib.utils import ArrayLike
+from ..lib.decorator import adjust_dims
from ..math.mittagleffler import mlf
@@ -13,7 +15,7 @@ class ColeCole(Distribution):
bounds = [(0, 1)]
@staticmethod
- def distribution(taus, tau0, alpha):
+ def distribution(tau, tau0, alpha):
"""
Distribution of correlation times
@@ -21,32 +23,33 @@ class ColeCole(Distribution):
G(\ln\\tau) = \\frac{1}{2\pi} \\frac{\\sin(\\pi\\alpha)}{\cosh[\\alpha\ln(\\tau/\\tau_0)] + \cos(\\alpha \pi))}
Args:
- taus:
+ tau:
tau0:
alpha:
"""
- z = np.log(taus/tau0)
+ z = np.log(tau/tau0)
return np.sin(np.pi*alpha)/(np.cosh(z*alpha) + np.cos(alpha*np.pi))/(2*np.pi)
@staticmethod
- def susceptibility(omega, tau, alpha):
- """
- Susceptibility
+ @adjust_dims
+ def susceptibility(omega: ArrayLike, tau: ArrayLike, alpha: float) -> ArrayLike:
+ r"""
+ Complex susceptibility
.. math::
- \chi(\omega, \\tau, \\alpha) = \\frac{1}{1-(i\omega\\tau_0)^\\alpha}
+ \chi(\omega, \tau, \alpha) = \frac{1}{[1-(i\omega\tau)^\alpha]}
Args:
- omega:
- tau:
- alpha:
+ omega (array-like): Frequency axis in 1/s (not Hz).
+ tau (array-like): Correlation times :math:`\tau_\text{CC}` in s.
+ alpha (float): Shape parameter.
+
"""
- _tau = np.atleast_1d(tau)
- _omega = np.atleast_1d(omega)
- val = 1/(1+(1j*_omega[:, None]*_tau[None, :])**alpha)
- return np.conjugate(val).squeeze()
+ val = 1/(1+(1j*omega*tau)**alpha)
+ return np.conjugate(val)
@staticmethod
+ @adjust_dims
def specdens(omega, tau, alpha):
"""
Spectral density
@@ -59,12 +62,11 @@ class ColeCole(Distribution):
tau:
alpha:
"""
- _tau = np.atleast_1d(tau)
- _omega = np.atleast_1d(omega)
- omtau = (_omega*_tau)**alpha
+ omtau = (omega*tau)**alpha
return np.sin(alpha*np.pi/2) * omtau / (1 + omtau**2 + 2*np.cos(alpha*np.pi/2)*omtau) / omega
@staticmethod
+ @adjust_dims
def correlation(t, tau0, alpha):
"""
Correlation function :math:`C(t)`
@@ -80,26 +82,3 @@ class ColeCole(Distribution):
alpha:
"""
return mlf(-(t/tau0)**alpha, alpha)
-
-
-if __name__ == '__main__':
- import matplotlib.pyplot as plt
-
- x = np.logspace(-3, 3, num=61)
-
- fig, ax = plt.subplots(2, 2)
- ax[0, 0].set_title('Distribution')
- ax[0, 1].set_title('Correlation func.')
- ax[1, 0].set_title('Spectral density')
- ax[1, 1].set_title('Susceptibility')
-
- for a in [0.4, 0.6, 0.8]:
- ax[0, 0].loglog(x, ColeCole.distribution(x, 1, a))
- ax[0, 1].semilogx(x, ColeCole.correlation(x, 1, a))
- ax[1, 0].loglog(x, ColeCole.specdens(x, 1, a))
- g = ax[1, 1].loglog(x, ColeCole.susceptibility(x, 1, a).imag)
- ax[1, 1].loglog(x, ColeCole.susceptibility(x, 1, a).real, '--', color=g[0].get_color())
-
- fig.tight_layout()
-
- plt.show()
diff --git a/nmreval/distributions/coledavidson.py b/nmreval/distributions/coledavidson.py
index 8d2fab6..827901e 100644
--- a/nmreval/distributions/coledavidson.py
+++ b/nmreval/distributions/coledavidson.py
@@ -4,6 +4,8 @@ import numpy as np
from scipy.special import psi, gammaincc
from .base import Distribution
+from ..lib.decorator import adjust_dims
+from ..lib.utils import ArrayLike
from ..utils.constants import Eu
@@ -16,22 +18,50 @@ class ColeDavidson(Distribution):
bounds = [(0, 1)]
@staticmethod
- def susceptibility(omega, tau, gamma):
+ def distribution(tau, tau0, gamma):
"""
- Susceptibility
+ Distribution of correlation times
.. math::
- \chi(\omega, \\tau, \\gamma) = \\frac{1}{(1-i\omega\\tau_0)^\\gamma}
+ G(\ln\\tau) =
+ \\begin{cases}
+ \\frac{\sin(\pi\gamma)}{\pi} \\Big(\\frac{\\tau}{\\tau_0 - \\tau}\\Big)^\gamma & \\tau < \\tau_0 \\\\
+ 0 & \\text{else}
+ \end{cases}
Args:
- omega:
tau:
+ tau0:
gamma:
"""
+
+ ratio = tau0/tau
+
+ ret_val = np.zeros_like(ratio)
+ ret_val[ratio > 1] = np.sin(np.pi*gamma) / np.pi * (1 / (ratio[ratio>1] - 1))**gamma
+
+ return ret_val
+
+ @staticmethod
+ @adjust_dims
+ def susceptibility(omega: ArrayLike, tau: ArrayLike, gamma: float) -> ArrayLike:
+ r"""
+ Complex susceptibility
+
+ .. math::
+ \chi(\omega, \tau, \alpha, \gamma) = \frac{1}{[1-i\omega\tau]^\gamma}
+
+ Args:
+ omega (array-like): Frequency axis in 1/s (not Hz).
+ tau (array-like): Correlation times in s.
+ gamma (float): Shape parameter.
+
+ """
return (1/(1+1j*omega*tau)**gamma).conjugate()
@staticmethod
- def specdens(omega, tau,gamma):
+ @adjust_dims
+ def specdens(omega, tau, gamma):
"""
Spectral density
@@ -43,15 +73,12 @@ class ColeDavidson(Distribution):
tau:
gamma:
"""
- gam = gamma
- _w = np.atleast_1d(omega)
- _t = np.atleast_1d(tau)
- omtau = _w[:, None] * _t[None, :]
+ omtau = omega*tau
- ret_val = np.sin(gam*np.arctan2(omtau, 1)) / (1 + omtau**2)**(gam/2.) / _w[:, None]
- ret_val[_w == 0, :] = gam*_t
+ ret_val = np.sin(gamma*np.arctan2(omtau, 1)) / (1 + omtau**2)**(gamma/2.) / omega
+ ret_val[np.argwhere(omega == 0)] = gamma*tau
- return np.squeeze(ret_val)
+ return ret_val
@staticmethod
def mean(tau, gamma):
@@ -113,33 +140,8 @@ class ColeDavidson(Distribution):
return tau/np.tan(np.pi/(2*gamma+2))
@staticmethod
- def distribution(tau, tau0, gamma):
- """
- Distribution of correlation times
-
- .. math::
- G(\ln\\tau) =
- \\begin{cases}
- \\frac{\sin(\pi\gamma)}{\pi} \\Big(\\frac{\\tau}{\\tau_0 - \\tau}\\Big)^\gamma & \\tau < \\tau_0 \\\\
- 0 & \\text{else}
- \end{cases}
-
- Args:
- tau:
- tau0:
- gamma:
- """
-
- if isinstance(tau, numbers.Number):
- return np.sin(np.pi*gamma) / np.pi * (1 / (tau0/tau - 1))**gamma if tau < tau0 else 0
-
- ret_val = np.zeros_like(tau)
- ret_val[tau < tau0] = np.sin(np.pi*gamma) / np.pi * (1 / (tau0/tau[tau < tau0] - 1))**gamma
-
- return ret_val
-
- @staticmethod
- def correlation(t, tau0, gamma):
+ @adjust_dims
+ def correlation(t, tau, gamma):
r"""
Correlation function
@@ -153,14 +155,14 @@ class ColeDavidson(Distribution):
Args:
t:
- tau0:
+ tau:
gamma:
References:
R. Hilfer: H-function representations for stretched exponential relaxation and non-Debye susceptibilities in glassy systems. Phys. Rev. E (2002) https://doi.org/10.1103/PhysRevE.65.061510
"""
- return gammaincc(gamma, t / tau0)
+ return gammaincc(gamma, t / tau)
if __name__ == '__main__':
diff --git a/nmreval/distributions/debye.py b/nmreval/distributions/debye.py
index dc76bd4..d342648 100644
--- a/nmreval/distributions/debye.py
+++ b/nmreval/distributions/debye.py
@@ -3,28 +3,44 @@ import numbers
import numpy as np
from .base import Distribution
+from ..lib.decorator import adjust_dims
+from ..lib.utils import ArrayLike
class Debye(Distribution):
name = 'Debye'
@staticmethod
- def correlation(t, tau0, *args):
- return np.exp(-t/tau0)
+ def distribution(tau: ArrayLike, tau0: float) -> ArrayLike:
+ if isinstance(tau, numbers.Number):
+ return 1 if tau == tau0 else 0
- @staticmethod
- def susceptibility(omega, tau0, *args):
- return 1/(1 + 1j*omega*tau0)
-
- @staticmethod
- def specdens(omega, tau0, *args):
- return tau0 / (1 + (omega*tau0)**2)
-
- @staticmethod
- def distribution(taus, tau0, *args):
- if isinstance(taus, numbers.Number):
- return 1 if taus == tau0 else 0
-
- ret_val = np.zeros_like(taus)
- ret_val[np.argmin(abs(taus - tau0))] = 1
+ ret_val = np.zeros_like(tau)
+ ret_val[tau == tau0] = 1.
return ret_val
+
+ @staticmethod
+ @adjust_dims
+ def correlation(t, tau, *args):
+ return np.exp(-t/tau)
+
+ @staticmethod
+ @adjust_dims
+ def susceptibility(omega: ArrayLike, tau: ArrayLike) -> ArrayLike:
+ r"""
+ Complex susceptibility
+
+ .. math::
+ \chi(\omega, \tau) = \frac{1}{1-i\omega\tau}
+
+ Args:
+ omega (array-like): Frequency axis in 1/s (not Hz).
+ tau (array-like): Correlation times in s.
+
+ """
+ return 1/(1 - 1j*omega*tau)
+
+ @staticmethod
+ @adjust_dims
+ def specdens(omega: ArrayLike, tau: ArrayLike) -> ArrayLike:
+ return tau / (1 + (omega*tau)**2)
diff --git a/nmreval/distributions/havriliaknegami.py b/nmreval/distributions/havriliaknegami.py
index 5e771a3..e5d5986 100644
--- a/nmreval/distributions/havriliaknegami.py
+++ b/nmreval/distributions/havriliaknegami.py
@@ -1,14 +1,18 @@
+from typing import Union
+
import numpy as np
from scipy.special import psi
from .base import Distribution
+from ..lib.utils import ArrayLike
+from ..lib.decorator import adjust_dims
from ..math.mittagleffler import mlf
from ..utils import Eu
class HavriliakNegami(Distribution):
"""
- Functions based on Cole-Davidson distribution
+ Functions based on Havriliak-Negami distribution
"""
name = 'Havriliak-Negami'
@@ -16,51 +20,31 @@ class HavriliakNegami(Distribution):
bounds = [(0, 1), (0, 1)]
@staticmethod
- def correlation(t, tau0, alpha, gamma):
+ def distribution(tau: ArrayLike, tau0: float, alpha: float, gamma: float) -> ArrayLike:
r"""
- Correlation function
+ Distribution of correlation times :math:`G(\ln\tau)`.
.. math::
- C(t, \tau_0, \alpha, \gamma) = 1 - \left(\frac{t}{\tau_0}\right)^{\alpha\gamma} \text{E}_{\alpha,\alpha\gamma+1}^\gamma\left[-\left(\frac{t}{\tau_0}\right)^\alpha\right]
-
- with incomplete Gamma function
-
- .. math::
- \Gamma(\gamma, t/\tau_0) = \frac{1}{\Gamma(\gamma)}\int_{t/\tau_0}^\infty x^{\gamma-1}\text{e}^{-x}\,\mathrm{d}x
+ G(\ln\tau) = \frac{(\tau/\tau_0)^{\alpha\gamma}
+ \sin\left\lbrace\gamma\arctan\left[\frac{\sin\alpha\pi}{(\tau/\tau_0)^\alpha + \cos\alpha\pi}\right] \right\rbrace}{\pi\left[1+2(\tau/\tau_0)^\alpha\cos\alpha\pi + (\tau/\tau_0)^{2\gamma}\right]}
Args:
- t:
- tau0:
+ tau (array_like) :
+ tau0 (array-like) :
alpha:
gamma:
- References:
- R. Hilfer: H-function representations for stretched exponential relaxation and non-Debye susceptibilities in glassy systems. Phys. Rev. E (2002) https://doi.org/10.1103/PhysRevE.65.061510
+ Returns:
"""
- return 1 - (t/tau0)**(alpha*gamma) * mlf(-(t/tau0)**alpha, alpha, alpha*gamma+1, gamma)
-
- @staticmethod
- def susceptibility(omega, tau, alpha, gamma):
- return np.conjugate(1/(1 + (1j*omega[:, None]*tau[None, :])**alpha)**gamma).squeeze()
-
- @staticmethod
- def specdens(omega, tau, alpha, gamma):
- omtau = (omega[:, None]*tau[None, :])**alpha
-
- zaehler = np.sin(gamma * np.arctan2(omtau*np.sin(0.5*alpha*np.pi), 1 + omtau*np.cos(0.5*alpha*np.pi)))
- nenner = (1 + 2*omtau * np.cos(0.5*alpha*np.pi) + omtau**2)**(0.5*gamma)
-
- return ((1 / omega) * (zaehler/nenner)).squeeze()
-
- @staticmethod
- def distribution(tau, tau0, alpha, gamma):
if alpha == 1:
from .coledavidson import ColeDavidson
return ColeDavidson.distribution(tau, tau0, gamma)
+
elif gamma == 1:
from .colecole import ColeCole
return ColeCole.distribution(tau, tau0, alpha)
+
else:
_y = tau/tau0
om_y = (1 + 2*np.cos(np.pi*alpha)*(_y**alpha) + _y**(2*alpha))**(-gamma/2)
@@ -69,11 +53,104 @@ class HavriliakNegami(Distribution):
return np.sin(gamma*theta_y) * om_y * (_y**(alpha*gamma)) / np.pi
@staticmethod
- def max(tau, alpha, gamma):
- return tau*(np.sin(0.5*np.pi*alpha*gamma/(gamma+1)) / np.sin(0.5*np.pi*alpha/(gamma+1)))**(1/alpha)
+ @adjust_dims
+ def correlation(t: ArrayLike, tau: ArrayLike, alpha: float, gamma: float) -> ArrayLike:
+ r"""
+ Correlation function
+
+ .. math::
+ C(t, \tau_\text{HN}, \alpha, \gamma) = 1 - \left(\frac{t}{\tau_\text{HN}}\right)^{\alpha\gamma}
+ \text{E}_{\alpha,\alpha\gamma+1}^\gamma\left[-\left(\frac{t}{\tau_\text{HN}}\right)^\alpha\right]
+
+ with three-parameter Mittag-Leffler function
+
+ .. math::
+ \text{E}_{a,b}^g (z) = \frac{1}{\Gamma(g)} \sum_{k=0}^\infty \frac{\Gamma(g+k) z^k}{k!\Gamma(ak+b)}
+
+ Args:
+ t (array-like): Time axis in s.
+ tau (array-like): Correlation times :math:`\tau_\text{HN}` in s.
+ alpha (float): Cole-Cole shape parameter.
+ gamma (float): Cole-Davidson shape parameter.
+
+ References:
+ R. Garrappa: Models of dielectric relaxation based on completely monotone functions.
+ Frac. Calc Appl. Anal. 19 (2016) https://arxiv.org/abs/1611.04028
+
+ """
+ return 1 - (t/tau)**(alpha*gamma) * mlf(-(t/tau)**alpha, alpha, alpha*gamma+1, gamma)
@staticmethod
- def logmean(tau, alpha, gamma):
+ @adjust_dims
+ def susceptibility(omega: ArrayLike, tau: ArrayLike, alpha: float, gamma: float) -> Union[np.ndarray, complex]:
+ r"""
+ Complex susceptibility
+
+ .. math::
+ \chi(\omega, \tau, \alpha, \gamma) = \frac{1}{[1-(i\omega\tau)^\alpha]^\gamma}
+
+ Args:
+ omega (array-like): Frequency axis in 1/s (not Hz).
+ tau (array-like): Correlation times in s.
+ alpha (float): Shape parameter.
+ gamma (float): Even more shape parameter.
+
+ """
+ return np.conjugate(1/(1 + (1j*omega*tau)**alpha)**gamma)
+
+ @staticmethod
+ @adjust_dims
+ def specdens(omega: ArrayLike, tau: ArrayLike, alpha: float, gamma: float) -> Union[np.ndarray, float]:
+ r"""
+ Spectral density :math:`J(\omega)`
+
+ .. math::
+ J(\omega) = \frac{\sin\left\lbrace \gamma\arctan\left[ \frac{(\omega\tau)^\alpha\sin(\alpha\pi/2)}{1+(\omega\tau)^\alpha\cos(\alpha\pi/2)} \right] \right\rbrace}
+ {\omega \left[ 1+(\omega\tau)^\alpha \cos(\alpha\pi/2) + (\omega\tau)^{2\alpha} \right]^{\gamma/2}}
+
+ Args:
+ omega (array-like): Frequency axis in 1/s (not Hz).
+ tau (array-like): Correlation times in s.
+ alpha (float): Cole-Cole shape parameter.
+ gamma (float): Cole-Davidson shape parameter.
+
+ Returns:
+
+ """
+ omtau = (omega*tau)**alpha
+
+ zaehler = np.sin(gamma * np.arctan2(omtau*np.sin(0.5*alpha*np.pi), 1 + omtau*np.cos(0.5*alpha*np.pi)))
+ nenner = (1 + 2*omtau * np.cos(0.5*alpha*np.pi) + omtau**2)**(0.5*gamma)
+
+ result = (1 / omega) * (zaehler/nenner)
+
+ return result
+
+ @staticmethod
+ def mean(tau: ArrayLike, alpha: float, gamma: float) -> Union[np.ndarray, float]:
+ r"""
+
+ .. math::
+ \langle \tau \rangle \approx \tau_\text{HN} \alpha \gamma
+
+ This is an approximation given in `[1]`_
+
+ Args:
+ tau (array-like): Function parameter in s.
+ alpha (float): Shape parameter.
+ gamma (float): Even more shape parameter.
+
+ Reference:
+ _`[1]` Bauer, Th., Köhler, M., Lunkenheimer, P., Angell, C.A.:
+ Relaxation dynamics and ionic conductivity in a fragile plastic crystal.
+ J. Chem. Phys. 133, 144509 (2010). https://doi.org/10.1063/1.3487521
+
+
+ """
+ return tau * alpha*gamma
+
+ @staticmethod
+ def logmean(tau: ArrayLike, alpha: float, gamma: float) -> ArrayLike:
r"""
Calculate mean logarithm of tau
@@ -82,25 +159,12 @@ class HavriliakNegami(Distribution):
Args:
tau:
- alpha:
- gamma:
-
- Returns:
+ alpha (float):
+ gamma (float):
"""
return np.log(tau) + (psi(gamma)+Eu)/alpha
@staticmethod
- def mean(tau, alpha, gamma):
- # approximation according to Th. Bauer et al., J. Chem. Phys. 133, 144509 (2010).
- return tau * alpha*gamma
-
-
-if __name__ == '__main__':
- import matplotlib.pyplot as plt
-
- x = np.logspace(-7, 3)
- y = HavriliakNegami.correlation(x, 1, 0.8, 0.26)
-
- plt.semilogx(x, y)
- plt.show()
+ def max(tau: ArrayLike, alpha: float, gamma: float) -> ArrayLike:
+ return tau*(np.sin(0.5*np.pi*alpha*gamma/(gamma+1)) / np.sin(0.5*np.pi*alpha/(gamma+1)))**(1/alpha)
diff --git a/nmreval/distributions/kww.py b/nmreval/distributions/kww.py
index 87ee238..77132b4 100644
--- a/nmreval/distributions/kww.py
+++ b/nmreval/distributions/kww.py
@@ -2,6 +2,7 @@ import numpy as np
from scipy.interpolate import interp1d
from scipy.special import gamma
+from nmreval.lib.decorator import adjust_dims
from .base import Distribution
from ..math.kww import kww_cos, kww_sin
from ..utils.constants import Eu
@@ -13,52 +14,52 @@ class KWW(Distribution):
boounds = [(0, 1)]
@staticmethod
- def distribution(taus, tau, *args):
- b = args[0]
- assert 0.1 <= b <= 0.9
+ def distribution(taus, tau, beta):
+ if not (0.1 <= beta <= 0.9):
+ raise ValueError('KWW distribution is only defined between 0.1 and 0.9')
b_supp = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
B_supp = [0.145, 0.197, 0.243, 0.285, 0.382, 0.306, 0.360, 0.435, 0.700]
C_supp = [0.89, 0.50, 0.35, 0.25, 0, 0.13, 0.22, 0.4015, 0.32]
- B = interp1d(b_supp, B_supp)(b)
- C = interp1d(b_supp, C_supp)(b)
+ B = interp1d(b_supp, B_supp)(beta)
+ C = interp1d(b_supp, C_supp)(beta)
tt = tau/taus
- delta = b * abs(b-0.5) / (1-b)
- if b > 0.5:
+ delta = beta * abs(beta-0.5) / (1-beta)
+ if beta > 0.5:
f = 1 + C * tt**delta
else:
f = 1 / (1 + C * tt**delta)
- ret_val = tau * B * np.exp(-(1-b) * b**(b/(1-b)) / tt**(b/(1-b))) / tt**((1-0.5*b)/(1-b))
+ ret_val = tau * B * np.exp(-(1-beta) * beta**(beta/(1-beta)) / tt**(beta/(1-beta))) / tt**((1-0.5*beta)/(1-beta))
return ret_val * f / taus
@staticmethod
- def correlation(t, tau, *args):
- return np.exp(-(t/tau)**args[0])
+ @adjust_dims
+ def correlation(t, tau, beta):
+ return np.exp(-(t/tau)**beta)
@staticmethod
- def susceptibility(omega, tau, *args):
- return 1-omega*kww_sin(omega, tau, args[0]) + 1j*omega*kww_cos(omega, tau, args[0])
+ @adjust_dims
+ def susceptibility(omega, tau, beta):
+ return 1-omega*kww_sin(omega, tau, beta) + 1j*omega*kww_cos(omega, tau, beta)
@staticmethod
- def specdens(omega, tau, *args):
- return kww_cos(omega, tau, args[0])
+ @adjust_dims
+ def specdens(omega, tau, beta):
+ return kww_cos(omega, tau, beta)
@staticmethod
- def mean(*args):
- tau, beta = args
+ def mean(tau, beta):
return tau/beta * gamma(1 / beta)
@staticmethod
- def logmean(*args):
- tau, beta = args
+ def logmean(tau, beta):
return (1-1/beta) * Eu + np.log(tau)
@staticmethod
- def max(*args):
- tau, beta = args
+ def max(tau, beta):
return (1.7851 - 0.87052*beta - 0.028836*beta**2 + 0.11391*beta**3) * tau
diff --git a/nmreval/distributions/loggaussian.py b/nmreval/distributions/loggaussian.py
index 065eacc..bcaa7db 100644
--- a/nmreval/distributions/loggaussian.py
+++ b/nmreval/distributions/loggaussian.py
@@ -2,6 +2,9 @@ from multiprocessing import Pool, cpu_count
from itertools import product
import numpy as np
+
+from nmreval.lib.decorator import adjust_dims
+
try:
from scipy.integrate import simpson
except ImportError:
@@ -25,8 +28,7 @@ class LogGaussian(Distribution):
return np.exp(-0.5*(np.log(tau/tau0)/sigma)**2)/np.sqrt(2*np.pi)/sigma
@staticmethod
- def correlation(t, tau0, *args):
- sigma = args[0]
+ def correlation(t, tau0, sigma: float):
_t = np.atleast_1d(t)
_tau = np.atleast_1d(tau0)
@@ -40,8 +42,7 @@ class LogGaussian(Distribution):
return ret_val.squeeze()
@staticmethod
- def susceptibility(omega, tau0, *args):
- sigma = args[0]
+ def susceptibility(omega, tau0, sigma: float):
_omega = np.atleast_1d(omega)
_tau = np.atleast_1d(tau0)
@@ -56,8 +57,7 @@ class LogGaussian(Distribution):
return ret_val.squeeze()
@staticmethod
- def specdens(omega, tau0, *args):
- sigma = args[0]
+ def specdens(omega, tau0, sigma):
_omega = np.atleast_1d(omega)
_tau = np.atleast_1d(tau0)
@@ -78,7 +78,7 @@ class LogGaussian(Distribution):
def _integrate_process_1(args):
omega_i, tau_j, sigma = args
- area = quad(_integrand_freq_imag_high, 0, 50, args=(omega_i, tau_j, sigma))[0]
+ area, _ = quad(_integrand_freq_imag_high, 0, 50, args=(omega_i, tau_j, sigma))
area += quad(_integrand_freq_imag_low, -50, 0, args=(omega_i, tau_j, sigma))[0]
return area
@@ -102,7 +102,9 @@ def _integrand_time(u, t, tau, sigma):
return LogGaussian.distribution(uu, tau, sigma) * np.exp(-t/uu)
+# integrands
def _integrand_freq_imag_low(u, omega, tau, sigma):
+ # integrand
uu = np.exp(u)
return LogGaussian.distribution(uu, tau, sigma) * omega * uu / (1 + (omega*uu)**2)
diff --git a/nmreval/gui_qt/_py/basewindow.py b/nmreval/gui_qt/_py/basewindow.py
index 4e8a29b..b90fa3c 100644
--- a/nmreval/gui_qt/_py/basewindow.py
+++ b/nmreval/gui_qt/_py/basewindow.py
@@ -2,14 +2,12 @@
# Form implementation generated from reading ui file 'resources/_ui/basewindow.ui'
#
-# Created by: PyQt5 UI code generator 5.12.3
+# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
-
from PyQt5 import QtCore, QtGui, QtWidgets
-
class Ui_BaseWindow(object):
def setupUi(self, BaseWindow):
BaseWindow.setObjectName("BaseWindow")
@@ -461,6 +459,9 @@ class Ui_BaseWindow(object):
self.toolBar.addAction(self.actionSave)
self.toolBar.addSeparator()
self.toolBar.addAction(self.actionMouse_behaviour)
+ self.toolBar.addSeparator()
+ self.toolBar.addAction(self.actionPrevious)
+ self.toolBar.addAction(self.actionNext_window)
self.toolbar_edit.addAction(self.action_calc)
self.toolbar_edit.addAction(self.action_mean_t1)
self.toolbar_edit.addAction(self.actionShift)
@@ -598,6 +599,7 @@ class Ui_BaseWindow(object):
self.actionLife.setText(_translate("BaseWindow", "Life..."))
self.actionTetris.setText(_translate("BaseWindow", "Not Tetris"))
self.actionUpdate.setText(_translate("BaseWindow", "Look for updates"))
+
from ..data.datawidget.datawidget import DataWidget
from ..data.point_select import PointSelectWidget
from ..data.signaledit.editsignalwidget import EditSignalWidget
diff --git a/nmreval/gui_qt/_py/bdsdialog.py b/nmreval/gui_qt/_py/bdsdialog.py
index 909eb76..3014019 100644
--- a/nmreval/gui_qt/_py/bdsdialog.py
+++ b/nmreval/gui_qt/_py/bdsdialog.py
@@ -2,19 +2,19 @@
# Form implementation generated from reading ui file 'resources/_ui/bdsdialog.ui'
#
-# Created by: PyQt5 UI code generator 5.12.3
+# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
-
from PyQt5 import QtCore, QtGui, QtWidgets
-
class Ui_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObjectName("Dialog")
- Dialog.resize(400, 319)
+ Dialog.resize(544, 443)
self.gridLayout = QtWidgets.QGridLayout(Dialog)
+ self.gridLayout.setContentsMargins(3, 3, 3, 3)
+ self.gridLayout.setSpacing(3)
self.gridLayout.setObjectName("gridLayout")
self.listWidget = QtWidgets.QListWidget(Dialog)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding)
@@ -23,7 +23,66 @@ class Ui_Dialog(object):
sizePolicy.setHeightForWidth(self.listWidget.sizePolicy().hasHeightForWidth())
self.listWidget.setSizePolicy(sizePolicy)
self.listWidget.setObjectName("listWidget")
- self.gridLayout.addWidget(self.listWidget, 1, 0, 1, 1)
+ self.gridLayout.addWidget(self.listWidget, 1, 0, 2, 1)
+ self.groupBox_2 = QtWidgets.QGroupBox(Dialog)
+ self.groupBox_2.setObjectName("groupBox_2")
+ self.verticalLayout_3 = QtWidgets.QVBoxLayout(self.groupBox_2)
+ self.verticalLayout_3.setContentsMargins(3, 3, 3, 3)
+ self.verticalLayout_3.setSpacing(3)
+ self.verticalLayout_3.setObjectName("verticalLayout_3")
+ self.freq_button = QtWidgets.QRadioButton(self.groupBox_2)
+ self.freq_button.setChecked(True)
+ self.freq_button.setObjectName("freq_button")
+ self.buttonGroup = QtWidgets.QButtonGroup(Dialog)
+ self.buttonGroup.setObjectName("buttonGroup")
+ self.buttonGroup.addButton(self.freq_button)
+ self.verticalLayout_3.addWidget(self.freq_button)
+ self.temp_button = QtWidgets.QRadioButton(self.groupBox_2)
+ self.temp_button.setObjectName("temp_button")
+ self.buttonGroup.addButton(self.temp_button)
+ self.verticalLayout_3.addWidget(self.temp_button)
+ self.gridLayout.addWidget(self.groupBox_2, 1, 1, 1, 1)
+ self.groupBox = QtWidgets.QGroupBox(Dialog)
+ self.groupBox.setObjectName("groupBox")
+ self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.groupBox)
+ self.verticalLayout_2.setContentsMargins(3, 3, 3, 3)
+ self.verticalLayout_2.setSpacing(3)
+ self.verticalLayout_2.setObjectName("verticalLayout_2")
+ self.eps_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.eps_checkBox.setChecked(True)
+ self.eps_checkBox.setObjectName("eps_checkBox")
+ self.verticalLayout_2.addWidget(self.eps_checkBox)
+ self.modul_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.modul_checkBox.setObjectName("modul_checkBox")
+ self.verticalLayout_2.addWidget(self.modul_checkBox)
+ self.cond_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.cond_checkBox.setObjectName("cond_checkBox")
+ self.verticalLayout_2.addWidget(self.cond_checkBox)
+ self.loss_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.loss_checkBox.setObjectName("loss_checkBox")
+ self.verticalLayout_2.addWidget(self.loss_checkBox)
+ self.line = QtWidgets.QFrame(self.groupBox)
+ self.line.setFrameShape(QtWidgets.QFrame.HLine)
+ self.line.setFrameShadow(QtWidgets.QFrame.Sunken)
+ self.line.setObjectName("line")
+ self.verticalLayout_2.addWidget(self.line)
+ self.cap_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.cap_checkBox.setObjectName("cap_checkBox")
+ self.verticalLayout_2.addWidget(self.cap_checkBox)
+ self.temp_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.temp_checkBox.setObjectName("temp_checkBox")
+ self.verticalLayout_2.addWidget(self.temp_checkBox)
+ self.time_checkBox = QtWidgets.QCheckBox(self.groupBox)
+ self.time_checkBox.setObjectName("time_checkBox")
+ self.verticalLayout_2.addWidget(self.time_checkBox)
+ spacerItem = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding)
+ self.verticalLayout_2.addItem(spacerItem)
+ self.gridLayout.addWidget(self.groupBox, 2, 1, 1, 1)
+ self.buttonBox = QtWidgets.QDialogButtonBox(Dialog)
+ self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
+ self.buttonBox.setStandardButtons(QtWidgets.QDialogButtonBox.Cancel|QtWidgets.QDialogButtonBox.Ok)
+ self.buttonBox.setObjectName("buttonBox")
+ self.gridLayout.addWidget(self.buttonBox, 3, 0, 1, 2)
self.label = QtWidgets.QLabel(Dialog)
sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum)
sizePolicy.setHorizontalStretch(0)
@@ -31,46 +90,31 @@ class Ui_Dialog(object):
sizePolicy.setHeightForWidth(self.label.sizePolicy().hasHeightForWidth())
self.label.setSizePolicy(sizePolicy)
self.label.setObjectName("label")
- self.gridLayout.addWidget(self.label, 0, 0, 1, 1)
- self.label_2 = QtWidgets.QLabel(Dialog)
- sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum)
- sizePolicy.setHorizontalStretch(0)
- sizePolicy.setVerticalStretch(0)
- sizePolicy.setHeightForWidth(self.label_2.sizePolicy().hasHeightForWidth())
- self.label_2.setSizePolicy(sizePolicy)
- self.label_2.setObjectName("label_2")
- self.gridLayout.addWidget(self.label_2, 0, 1, 1, 1)
- self.verticalLayout = QtWidgets.QVBoxLayout()
- self.verticalLayout.setObjectName("verticalLayout")
- self.eps_checkBox = QtWidgets.QCheckBox(Dialog)
- self.eps_checkBox.setChecked(True)
- self.eps_checkBox.setObjectName("eps_checkBox")
- self.verticalLayout.addWidget(self.eps_checkBox)
- self.modul_checkBox = QtWidgets.QCheckBox(Dialog)
- self.modul_checkBox.setObjectName("modul_checkBox")
- self.verticalLayout.addWidget(self.modul_checkBox)
- self.cond_checkBox = QtWidgets.QCheckBox(Dialog)
- self.cond_checkBox.setObjectName("cond_checkBox")
- self.verticalLayout.addWidget(self.cond_checkBox)
- spacerItem = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding)
- self.verticalLayout.addItem(spacerItem)
- self.gridLayout.addLayout(self.verticalLayout, 1, 1, 1, 1)
- self.buttonBox = QtWidgets.QDialogButtonBox(Dialog)
- self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
- self.buttonBox.setStandardButtons(QtWidgets.QDialogButtonBox.Cancel|QtWidgets.QDialogButtonBox.Ok)
- self.buttonBox.setObjectName("buttonBox")
- self.gridLayout.addWidget(self.buttonBox, 2, 0, 1, 2)
+ self.gridLayout.addWidget(self.label, 0, 0, 1, 2)
self.retranslateUi(Dialog)
self.buttonBox.accepted.connect(Dialog.accept)
self.buttonBox.rejected.connect(Dialog.reject)
QtCore.QMetaObject.connectSlotsByName(Dialog)
+ Dialog.setTabOrder(self.freq_button, self.temp_button)
+ Dialog.setTabOrder(self.temp_button, self.eps_checkBox)
+ Dialog.setTabOrder(self.eps_checkBox, self.modul_checkBox)
+ Dialog.setTabOrder(self.modul_checkBox, self.cond_checkBox)
+ Dialog.setTabOrder(self.cond_checkBox, self.listWidget)
def retranslateUi(self, Dialog):
_translate = QtCore.QCoreApplication.translate
Dialog.setWindowTitle(_translate("Dialog", "Read BDS data"))
- self.label.setText(_translate("Dialog", "Found temperatures"))
- self.label_2.setText(_translate("Dialog", "Read as:"))
+ self.groupBox_2.setTitle(_translate("Dialog", "X Axis"))
+ self.freq_button.setText(_translate("Dialog", "Frequency"))
+ self.temp_button.setText(_translate("Dialog", "Temperature"))
+ self.groupBox.setTitle(_translate("Dialog", "Y Axis"))
self.eps_checkBox.setText(_translate("Dialog", "Permittivity ε"))
self.modul_checkBox.setText(_translate("Dialog", "Modulus 1/ε"))
self.cond_checkBox.setText(_translate("Dialog", "Conductivity iεω"))
+ self.loss_checkBox.setText(_translate("Dialog", "Loss factor tan(δ)"))
+ self.cap_checkBox.setText(_translate("Dialog", "Capacity"))
+ self.temp_checkBox.setText(_translate("Dialog", "Meas. temperature"))
+ self.time_checkBox.setText(_translate("Dialog", "Meas. time"))
+ self.label.setText(_translate("Dialog", "Found entries"))
+
diff --git a/nmreval/gui_qt/data/container.py b/nmreval/gui_qt/data/container.py
index 7027698..fe18bff 100644
--- a/nmreval/gui_qt/data/container.py
+++ b/nmreval/gui_qt/data/container.py
@@ -599,10 +599,13 @@ class SignalContainer(ExperimentContainer):
if isinstance(self._data, BDS):
self.mode = 'bds'
-
if sym_kwargs['symbol'] is None and line_kwargs['style'] is None:
- sym_kwargs['symbol'] = next(PointContainer.symbols)
- line_kwargs['style'] = LineStyle.No
+ if len(self._data) <= 91:
+ sym_kwargs['symbol'] = next(PointContainer.symbols)
+ line_kwargs['style'] = LineStyle.No
+ else:
+ line_kwargs['style'] = LineStyle.Solid
+ sym_kwargs['symbol'] = SymbolStyle.No
elif isinstance(self._data, Signal):
if line_kwargs['style'] is None and sym_kwargs['symbol'] is None:
@@ -617,7 +620,7 @@ class SignalContainer(ExperimentContainer):
raise TypeError('Unknown class %s, should be FID, Spectrum, or BDS.' % type(self._data))
for mode in ['real', 'imag']:
- if mode == 'imag':
+ if mode == 'imag' and line_kwargs['style'] != LineStyle.No:
line_kwargs['style'] = LineStyle.Dashed
self.setSymbol(mode=mode, **sym_kwargs)
self.setLine(mode=mode, **line_kwargs)
diff --git a/nmreval/gui_qt/graphs/graphwindow.py b/nmreval/gui_qt/graphs/graphwindow.py
index fab3989..644f67e 100644
--- a/nmreval/gui_qt/graphs/graphwindow.py
+++ b/nmreval/gui_qt/graphs/graphwindow.py
@@ -591,6 +591,8 @@ class QGraphWindow(QtWidgets.QGraphicsView, Ui_GraphWindow):
if item_dic:
dic['items'].append(item_dic)
+ print(dic)
+
return dic
def get_state(self) -> dict:
diff --git a/nmreval/gui_qt/io/bdsreader.py b/nmreval/gui_qt/io/bdsreader.py
index 8ecc837..7eaf259 100644
--- a/nmreval/gui_qt/io/bdsreader.py
+++ b/nmreval/gui_qt/io/bdsreader.py
@@ -1,7 +1,6 @@
-from ...io.bds_reader import BDSReader
-
-from ..Qt import QtCore, QtWidgets
-from .._py.bdsdialog import Ui_Dialog
+from nmreval.io.bds_reader import BDSReader
+from nmreval.gui_qt.Qt import QtCore, QtWidgets
+from nmreval.gui_qt._py.bdsdialog import Ui_Dialog
class QBDSReader(QtWidgets.QDialog, Ui_Dialog):
@@ -11,22 +10,39 @@ class QBDSReader(QtWidgets.QDialog, Ui_Dialog):
def __init__(self, fname: str = None, parent=None):
super().__init__(parent=parent)
self.setupUi(self)
+ self.reader = None
+ self.fname = fname
- if fname is not None:
+ if self.fname is not None:
self.reader = BDSReader(fname)
self.setup_gui()
def __call__(self, fname: str):
self.reader = BDSReader(fname)
+ self.fname = fname
self.setup_gui()
return self
def setup_gui(self):
self.listWidget.clear()
+ self.label.setText(f'Found entries for {self.reader.fname.name}')
- for temp in self.reader.set_temp:
- item = QtWidgets.QListWidgetItem(str(temp))
+ self.make_list(True)
+
+ @QtCore.pyqtSlot(QtWidgets.QAbstractButton, name='on_buttonGroup_buttonClicked')
+ def change_list(self, bttn: QtWidgets.QAbstractButton):
+ self.make_list(bttn == self.freq_button)
+
+ def make_list(self, use_freq: bool) -> None:
+ self.listWidget.clear()
+ if use_freq:
+ secondary = self.reader.set_temp
+ else:
+ secondary = self.reader.frequencies
+
+ for x2 in secondary:
+ item = QtWidgets.QListWidgetItem(f'{x2:.8g}')
item.setFlags(QtCore.Qt.ItemIsEnabled | QtCore.Qt.ItemIsUserCheckable | QtCore.Qt.ItemIsSelectable)
item.setCheckState(QtCore.Qt.Checked)
self.listWidget.addItem(item)
@@ -34,19 +50,26 @@ class QBDSReader(QtWidgets.QDialog, Ui_Dialog):
def accept(self):
data = []
- temps = []
+ x2 = []
for i in range(self.listWidget.count()):
item = self.listWidget.item(i)
if item.checkState() == QtCore.Qt.Checked:
- temps.append(i)
+ x2.append(i)
- for (mode, cb) in [('epsilon', self.eps_checkBox),
- ('sigma', self.cond_checkBox),
- ('modulus', self.modul_checkBox)]:
+ xmode = 'freq' if self.freq_button.isChecked() else 'temp'
+ for (mode, cb) in [
+ ('epsilon', self.eps_checkBox),
+ ('sigma', self.cond_checkBox),
+ ('modulus', self.modul_checkBox),
+ ('capacity', self.cap_checkBox),
+ ('time', self.time_checkBox),
+ ('sample_temp', self.temp_checkBox),
+ ('loss_factor', self.loss_checkBox)
+ ]:
if cb.checkState() == QtCore.Qt.Checked:
- values = self.reader.export(mode=mode)
- for t in temps:
+ values = self.reader.export(ymode=mode, xmode=xmode)
+ for t in x2:
data.append(values[t])
self.data_read.emit(data)
@@ -60,7 +83,8 @@ if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
reader = QBDSReader()
- reader('/autohome/dominik/nmreval/testdata/ZWEITECHANCE_EGD4H2O.EPS')
+ # reader('/autohome/dominik/nmreval/testdata/ZWEITECHANCE_EGD4H2O.EPS')
+ # reader('/autohome/dominik/nmreval/testdata/MZ-ME/CHLOROFORM_2017-02-06.EPS')
+ reader('/autohome/dominik/nmreval/testdata/SBA_5P4NM_ISOCHRON_150-300K_18-03-22.EPS')
reader.show()
sys.exit(app.exec())
-
diff --git a/nmreval/gui_qt/io/exporters.py b/nmreval/gui_qt/io/exporters.py
index bbca4a6..b031d68 100644
--- a/nmreval/gui_qt/io/exporters.py
+++ b/nmreval/gui_qt/io/exporters.py
@@ -127,13 +127,13 @@ def pgitem_to_dic(item):
item_dic['symbolcolor'] = Colors.Black
else:
item_dic['symbol'] = SymbolStyle.from_str(opts['symbol'])
- item_dic['symbolcolor'] = Colors.from_rgb(*opts['symbolBrush'].color().getRgbF()[:3])
+ item_dic['symbolcolor'] = Colors.from_rgb(*opts['symbolBrush'].color().getRgbF()[:3], normed=True)
pen = opts['pen']
if pen is not None:
item_dic['linestyle'] = LineStyle(pen.style())
- item_dic['linecolor'] = Colors.from_rgb(*pen.color().getRgbF()[:3])
+ item_dic['linecolor'] = Colors.from_rgb(*pen.color().getRgbF()[:3], normed=True)
item_dic['linewidth'] = pen.widthF()
else:
item_dic['linestyle'] = LineStyle.No
diff --git a/nmreval/gui_qt/lib/forms.py b/nmreval/gui_qt/lib/forms.py
index fb3058d..00e9233 100644
--- a/nmreval/gui_qt/lib/forms.py
+++ b/nmreval/gui_qt/lib/forms.py
@@ -186,10 +186,7 @@ class SelectionWidget(QtWidgets.QWidget):
@property
def value(self):
- try:
- return float(self.options[str(self.comboBox.currentText())])
- except ValueError:
- return str(self.options[str(self.comboBox.currentText())])
+ return {self.argname: self.options[self.comboBox.currentText()]}
def get_parameter(self):
return str(self.comboBox.currentText())
diff --git a/nmreval/gui_qt/main/mainwindow.py b/nmreval/gui_qt/main/mainwindow.py
index 2747138..b0316a7 100644
--- a/nmreval/gui_qt/main/mainwindow.py
+++ b/nmreval/gui_qt/main/mainwindow.py
@@ -562,7 +562,7 @@ class NMRMainWindow(QtWidgets.QMainWindow, Ui_BaseWindow):
self.management.skip_points(**dial.get_arguments())
- @QtCore.pyqtSlot(str, name='on_action_coup_calc_triggered')
+ @QtCore.pyqtSlot(name='on_action_coup_calc_triggered')
def coupling_dialog(self):
dialog = QCoupCalcDialog(self)
dialog.show()
diff --git a/nmreval/gui_qt/main/management.py b/nmreval/gui_qt/main/management.py
index 5968933..3c7100c 100644
--- a/nmreval/gui_qt/main/management.py
+++ b/nmreval/gui_qt/main/management.py
@@ -977,10 +977,10 @@ class UpperManagement(QtCore.QObject):
sd.convert(_x, *sd_param, from_=opts['tau_type'], to_='raw')
relax = Relaxation()
- relax.distribution(sd, parameter=sd_param, keywords=opts['sd_param'][1])
+ relax.set_distribution(sd, parameter=sd_param, keywords=opts['sd_param'][1])
cp_param = [self.data[p].y.real if isinstance(p, str) else p for p in opts['cp_param'][0]]
- relax.coupling(opts['coup'], parameter=cp_param, keywords=opts['cp_param'][1])
+ relax.set_coupling(opts['coup'], parameter=cp_param, keywords=opts['cp_param'][1])
if opts['out'] == 't1':
y = relax.t1(x2, _x)
diff --git a/nmreval/gui_qt/nmr/coupling_calc.py b/nmreval/gui_qt/nmr/coupling_calc.py
index e68c895..b5bb877 100644
--- a/nmreval/gui_qt/nmr/coupling_calc.py
+++ b/nmreval/gui_qt/nmr/coupling_calc.py
@@ -1,4 +1,4 @@
-from ...nmr.couplings import *
+from ...nmr.coupling import *
from ...utils.text import convert
from ..Qt import QtWidgets, QtCore
@@ -11,7 +11,7 @@ class QCoupCalcDialog(QtWidgets.QDialog, Ui_coupling_calc_dialog):
super().__init__(parent)
self.setupUi(self)
- self.cp = [Quadrupolar, QuadrupolarQCC, Czjzek, HeteroDipolar, HomoDipolar]
+ self.cp = [Quadrupolar, Czjzek, HeteroDipolar, HomoDipolar]
for cp in self.cp:
self.comboBox.addItem(cp.name)
@@ -62,7 +62,7 @@ class QCoupCalcDialog(QtWidgets.QDialog, Ui_coupling_calc_dialog):
for pp in self._coupling_parameter:
p.append(pp.value)
- self.label.setText('Coupling constant: %.8g' % self.cp[self.comboBox.currentIndex()].func(*p))
+ self.label.setText('Coupling constant: %.8g' % self.cp[self.comboBox.currentIndex()].relax(*p))
if __name__ == '__main__':
diff --git a/nmreval/gui_qt/nmr/t1_from_tau.py b/nmreval/gui_qt/nmr/t1_from_tau.py
index dc0642c..51355e7 100644
--- a/nmreval/gui_qt/nmr/t1_from_tau.py
+++ b/nmreval/gui_qt/nmr/t1_from_tau.py
@@ -1,6 +1,6 @@
from typing import List, Tuple
-from ...nmr.couplings import *
+from ...nmr.coupling import *
from ...distributions import ColeCole, ColeDavidson, HavriliakNegami
from ...utils import pi
from ...utils.text import convert
@@ -20,7 +20,7 @@ class QRelaxCalc(QtWidgets.QDialog, Ui_Dialog):
self.graphs = {}
self.specdens = [ColeCole, ColeDavidson, HavriliakNegami]
- self.coupling = [Quadrupolar, QuadrupolarQCC, Czjzek, HomoDipolar]
+ self.coupling = [Quadrupolar, Czjzek, HomoDipolar]
self.tau_parameter = []
for line_edit in [self.ea_lineEdit, self.tau0_lineEdit, self.start_lineEdit, self.stop_lineEdit,
diff --git a/nmreval/gui_qt/nmr/t1widget.py b/nmreval/gui_qt/nmr/t1widget.py
index eb724a7..e76c891 100644
--- a/nmreval/gui_qt/nmr/t1widget.py
+++ b/nmreval/gui_qt/nmr/t1widget.py
@@ -4,7 +4,7 @@ from pyqtgraph import mkBrush, mkPen
from ..lib.pg_objects import PlotItem
from ...data.points import Points
from ...nmr.relaxation import RelaxationEvaluation
-from ...nmr.couplings import *
+from ...nmr.coupling import *
from ...distributions import *
from ..Qt import QtCore, QtWidgets, QtGui
@@ -37,7 +37,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.specdens_combobox.currentIndexChanged.connect(self.update_specdens)
self.cp_parameter = []
- self.coupling = [Quadrupolar, QuadrupolarQCC, Czjzek, HomoDipolar, Constant]
+ self.coupling = [Quadrupolar, Czjzek, HomoDipolar, Constant]
for i in self.coupling:
self.coupling_combobox.addItem(i.name)
self.coupling_combobox.currentIndexChanged.connect(self.update_coupling)
@@ -116,7 +116,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
self.verticalLayout_3.addWidget(_temp)
self.sd_parameter.append(_temp)
- self.t1calculator.distribution(self.sdmodels[idx])
+ self.t1calculator.set_distribution(self.sdmodels[idx])
self.update_model()
@QtCore.pyqtSlot()
@@ -159,6 +159,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
_temp.valueChanged.connect(self.update_coupling_parameter)
_temp.stateChanged.connect(self.update_coupling_parameter)
self.cp_parameter.append(_temp)
+ print(self.cp_parameter)
if self.coupling[idx].choice is not None:
for (name, kw_name, opts) in self.coupling[idx].choice:
@@ -172,10 +173,14 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
@QtCore.pyqtSlot()
def update_coupling_parameter(self):
new_p = []
+ new_kw = {}
for pp in self.cp_parameter:
- new_p.append(pp.value)
+ if isinstance(pp, FormWidget):
+ new_p.append(pp.value)
+ else:
+ new_kw.update(pp.value)
new_coupling = self.coupling[self.coupling_combobox.currentIndex()]
- self.t1calculator.coupling(new_coupling)
+ self.t1calculator.set_coupling(new_coupling, parameter=new_p, keywords=new_kw)
self.update_model()
@@ -253,30 +258,33 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
'Only one can be determined from a minimum.')
return
- notfix = ()
+ notfix = None
+ var_idx = 0
if not all(sd_fix):
- notfix = ('distribution', sd_fix.index(False))
+ notfix = 'distribution'
+ var_idx = sd_fix.index(False)
if not all(cp_fix):
- notfix = ('coupling', cp_fix.index(False))
+ notfix = 'coupling'
+ var_idx = cp_fix.index(False)
if not np.isfinite(self.t1calculator.t1min[1]):
return
- mini = np.nan
with busy_cursor():
- calc_stretching, mini = self.t1calculator.increase(notfix, height=self.minimum[1],
- 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')
if notfix:
- forms = self.sd_parameter if notfix[0] == 'distribution' else self.cp_parameter
- forms[notfix[1]].blockSignals(True)
- forms[notfix[1]].value = f'{calc_stretching:.4g}'
- forms[notfix[1]].blockSignals(False)
+ forms = self.sd_parameter if notfix == 'distribution' else self.cp_parameter
+ forms[var_idx].blockSignals(True)
+ forms[var_idx].value = f'{calc_stretching:.4g}'
+ forms[var_idx].blockSignals(False)
@QtCore.pyqtSlot(name='on_calc_pushButton_clicked')
def calculate_correlations(self):
@@ -317,7 +325,7 @@ class QT1Widget(QtWidgets.QDialog, Ui_t1dialog):
cp_args.append(p.value)
except AttributeError:
# SelectionWidget has no isChecked()
- cp_kwargs[p.argname] = p.value
+ cp_kwargs.update(p.value)
return cp_args, cp_kwargs, cp_fix
diff --git a/nmreval/io/bds_reader.py b/nmreval/io/bds_reader.py
index 93067d6..394508e 100644
--- a/nmreval/io/bds_reader.py
+++ b/nmreval/io/bds_reader.py
@@ -2,10 +2,11 @@ import re
import struct
import warnings
from pathlib import Path
+from typing import List
import numpy as np
-from ..data.signals import Signal
+from ..data import BDS, Points
MAGIC_RE = re.compile(b'NOVOCONTROL DK-RESULTS')
@@ -27,6 +28,9 @@ class BDSReader:
return self
+ def __getitem__(self, val):
+ return self.opts[val]
+
def _parse_file(self):
self.opts = {}
with self.fname.open(mode='rb') as f:
@@ -43,7 +47,7 @@ class BDSReader:
f.seek(1, 1)
self.opts['electrode thickness'] = struct.unpack('f', f.read(4))[0]
- self.opts['parameter'] += struct.unpack('3f', f.read(12))
+ self.opts['parameter'] += struct.unpack('3f', f.read(12)) # 1, 0.05, 0.06, 0.02
f.seek(2, 1)
self.opts['capacity'] = struct.unpack('f', f.read(4))[0]
@@ -56,43 +60,51 @@ class BDSReader:
self.opts['C_0'] = (self.opts['area']-self.opts['spacer area']) / self.opts['thickness'] * 8.8541878128e-12
f.seek(158)
- name_length = struct.unpack('b', f.read(1))[0]
+ name_length = struct.unpack('i', f.read(4))[0]
- f.seek(164)
+ f.seek(2, 1)
b = f.read(name_length)
self.opts['name'] = str(struct.unpack(f'<{name_length}s', b)[0][:-1], encoding='utf-8')
_ = struct.unpack('h', f.read(2))
- freq_values_length = struct.unpack('b', f.read(1))[0]
+ freq_values_length = struct.unpack('i', f.read(4))[0]
- f.seek(7, 1)
+ f.seek(4, 1)
self.x = np.empty(freq_values_length)
for freqs in range(freq_values_length):
- self.x[freqs] = struct.unpack('f', f.read(4))[0]
+ (self.x[freqs],) = struct.unpack('f', f.read(4))
- _ = struct.unpack('h', f.read(2))
- length_temps = struct.unpack('b', f.read(1))[0]
+ _ = struct.unpack('h', f.read(2)) # TODO if no temperature set this is not 400 and rest breaks
+ length_temps = struct.unpack('i', f.read(4))[0]
- f.seek(7, 1)
+ f.seek(4, 1)
self.opts['temperatures'] = np.array(struct.unpack('f' * length_temps, f.read(4*length_temps)))
f.seek(110, 1)
- date_length = (struct.unpack('b', f.read(1)))[0]
+ date_length = (struct.unpack('i', f.read(4)))[0]
- f.seek(5, 1)
+ f.seek(2, 1)
self.opts['date'] = str(struct.unpack(f'<{date_length}s', f.read(date_length))[0][:-1],
encoding='utf-8')
f.seek(47, 1)
- # there are 9 different values per frequency and temperature
_y = []
actual_temps_length = 0
- read_length = 9 * freq_values_length
+ read_length = 9 * freq_values_length # per entry 9 * 4 byte
while True:
+ # catch error if measurement was aborted
try:
- _y += struct.unpack('f' * read_length, f.read(4*read_length))
+ y_i = struct.unpack('f' * read_length, f.read(4*read_length))
+ if any([y_ii != 0.0 for y_ii in y_i[-3:]]):
+ # the last three should be zero
+ break
+
+ _y += y_i
actual_temps_length += 1
+ if actual_temps_length == length_temps:
+ break
+
except struct.error:
break
@@ -100,79 +112,86 @@ class BDSReader:
warnings.warn('Number of set temperatures does not match number of data points')
_y = np.array(_y).reshape((actual_temps_length, freq_values_length, 9))
+ print(_y.shape)
+ print(f.tell())
# last 3 entries are zero, save only 6
+ # Z.imag*omega), Z.real, meas.time, meas. temp., ac voltage, dc voltage
self.y = np.transpose(_y[:, :, :6], (2, 0, 1))
- def export(self, mode='epsilon') -> list:
- if mode == 'epsilon':
- eps = self.epsilon()
- elif mode == 'sigma':
- eps = self.sigma()
- elif mode == 'modulus':
- eps = self.modulus()
- else:
- raise ValueError(f'Unknown mode {mode}, not "epsilon", "sigma", or "modulus".')
-
- ret_val = []
+ def export(self, ymode: str = 'epsilon', xmode: str = 'freq') -> List[BDS]:
+ y = getattr(self, ymode)()
useful_info = {
'voltage': self.opts['voltage'],
'diameter': self.opts['diameter'],
'area': self.opts['area'],
'thickness': self.opts['thickness'],
- 'mode': mode
+ 'mode': ymode
}
- for i, temps in enumerate(self.temperature):
- ret_val.append(Signal(x=self.frequencies, y=eps[0][i, :] + 1j*eps[1][i, :],
- name=f'{temps:.2f}', value=temps, **useful_info))
+ if xmode == 'freq':
+ fmt = '.2f'
+ x2 = self.temperature
+ x = self.frequencies
+
+ elif xmode == 'temp':
+ fmt = '.2f'
+ x2 = self.frequencies
+ x = self.temperature
+ y = y.T
+
+ else:
+ raise ValueError(f'Unknown mode {xmode!r}, use `freq` or `temp`.')
+
+ ret_val = []
+ for i, label in enumerate(x2):
+ y_i = y[i]
+ if np.allclose(y_i.imag, 0):
+ ret_val.append(Points(x=x, y=y_i,
+ name=f'{label:{fmt}}', value=label, **useful_info))
+ else:
+ ret_val.append(BDS(x=x, y=y_i,
+ name=f'{label:{fmt}}', value=label, **useful_info))
return ret_val
- def __getitem__(self, val):
- return self.opts[val]
+ def capacity(self):
+ # NOTE: nobody ever used edge correction, so we ignore this option entirely
+ return self.y[0] - self.opts['capacity'] - 1j / self.y[1] / (self.frequencies*2*np.pi)
+
+ def sample_temp(self):
+ return self.y[2]
+
+ def time(self):
+ return self.y[3]
+
+ def sigma(self):
+ # sigma^* = i * omega * eps_0 * (eps^* - 1)
+ conv = 0.01 * 8.8541878128e-12 * 2*np.pi*self.x # factor 0.01: sigma in S/cm
+ return conv * (self.epsilon() - 1)
+
+ def epsilon(self):
+ # eps^* = Cp^* d/A/eps_0
+ c = self.capacity()
+ return (c.real - 1j * c.imag) / self.opts['C_0']
+
+ def modulus(self):
+ # M^* = 1/eps^*
+ return np.conjugate(1/self.epsilon())
+
+ def loss_factor(self):
+ eps = self.epsilon()
+
+ return eps.imag / eps.real
@property
def set_temp(self):
return self.opts['temperatures'][:len(self.temperature)]
- @property
- def probe_temp(self):
- return self.y[2]
-
@property
def temperature(self):
- return self.probe_temp.mean(axis=1)
+ return self.sample_temp().mean(axis=1)
@property
def frequencies(self):
return self.x
-
- def capacity(self):
- # NOTE: nobody ever used edge correction, so we ignore this option entirely
- return self.y[0] - self.opts['capacity'], -1./self.y[1] / (self.frequencies*2*np.pi)
-
- def voltage(self):
- return self.y[5]
-
- def sigma(self):
- # sigma^* = i * omega * eps_0 * (eps^* - 1)
- eps_r, eps_i = self.epsilon()
- conv = 0.01 * 8.8541878128e-12 * 2*np.pi*self.x # factor 0.01: sigma in S/cm
- return conv * eps_i, conv * (eps_r-1)
-
- def epsilon(self):
- # eps^* = Cp^* d/A/eps_0
- cr, ci = self.capacity()
- return cr / self.opts['C_0'], -ci / self.opts['C_0']
-
- def modulus(self):
- # M^* = 1/eps^*
- eps_r, eps_i = self.epsilon()
- magn = eps_r ** 2 + eps_i ** 2
- return eps_r / magn, eps_i / magn
-
- def loss_factor(self):
- eps_r, eps_i = self.epsilon()
-
- return eps_i / eps_r, None
diff --git a/nmreval/lib/decorator.py b/nmreval/lib/decorator.py
new file mode 100644
index 0000000..c0f4f59
--- /dev/null
+++ b/nmreval/lib/decorator.py
@@ -0,0 +1,30 @@
+from functools import wraps
+from typing import Callable
+
+import numpy as np
+
+
+def adjust_dims(func) -> Callable:
+
+ @wraps(func)
+ def wrapper(*args, **kwargs):
+ """
+ ALlow outer product for omega*tau and remove redundant dimension afterwards
+ """
+ x1, x2, *rest = args
+
+ x1 = np.asanyarray(x1)
+ x2 = np.asanyarray(x2)
+
+ if len(x1.shape) > 1 or len(x2.shape) > 1:
+ raise ValueError('Only numbers or 1d-arrays are supported')
+
+ result = func(x1[..., None], x2[None, ...], *rest, **kwargs)
+ if result.ndim == 1:
+ return result[0]
+ else:
+ return result.squeeze()
+
+ return wrapper
+ #
+ # return func
diff --git a/nmreval/lib/utils.py b/nmreval/lib/utils.py
index ce7e33d..0f90963 100644
--- a/nmreval/lib/utils.py
+++ b/nmreval/lib/utils.py
@@ -3,7 +3,6 @@ from typing import TypeVar
from ..math.mittagleffler import mlf
-
ArrayLike = TypeVar('ArrayLike')
diff --git a/nmreval/math/kww.py b/nmreval/math/kww.py
index c271a91..dd3e115 100644
--- a/nmreval/math/kww.py
+++ b/nmreval/math/kww.py
@@ -19,7 +19,8 @@ def _kww_low(w, beta, kappa):
ln_w = np.log(w[:, np.newaxis])
ln_a_k = scipy.special.gammaln((k+1) / beta) - scipy.special.gammaln(k+1) + k*ln_w
- a_k = np.exp(ln_a_k)
+ with np.errstate(over='ignore'):
+ a_k = np.exp(ln_a_k)
y_n = (sign * a_k).cumsum(axis=1)
y_n = np.nan_to_num(y_n)
@@ -45,7 +46,7 @@ def kwws_low(w, beta):
def _kww_high(w, beta, kappa):
if beta < 0.1 or beta > 2.0:
- raise ValueError("invalid call to kww_hig: beta out of range")
+ raise ValueError("invalid call to kww_high: beta out of range")
ln_omega = np.log(w[:, np.newaxis])
k = np.atleast_2d(np.arange(kappa, __max_terms+kappa))
@@ -89,7 +90,7 @@ def kwwc_high(w, beta):
def _kww_mid(w, beta, kappa):
if beta < 0.1 or beta > 2.0:
raise ValueError("invalid call to kww_mid: beta out of range")
- elif any(w < 0):
+ elif np.any(w < 0):
raise ValueError("invalid call to kww_mid: w out of range")
if kappa and beta == 2:
@@ -203,19 +204,19 @@ def _kwws_lim_hig(b):
def kww_cos(w, tau, beta):
- r"""
- Calculate \int_0^\infty dt cos(w*t) exp(-(t/tau)^beta)
- :param w: array-like
- :param tau: float
- :param beta: float; 0.1 < beta <= 2
- :return: array (w.shape)
+ """
+
+ Args:
+ w:
+ tau:
+ beta:
+
+ Returns:
+
"""
# check input data
- if beta < 0.1:
- raise ValueError("kww: beta smaller than 0.1")
-
- if beta > 2.0:
- raise ValueError("kww: beta larger than 2.0")
+ if not (0.1 <= beta <= 2.):
+ raise ValueError('KWW beta is not inside range 0.1-2')
if beta == 1:
return tau/(1 + (w*tau)**2)
@@ -246,11 +247,8 @@ def kww_cos(w, tau, beta):
# \int_0^\infty dt sin(w*t) exp(-(t/tau)^beta)
def kww_sin(w, tau, beta):
# check input data
- if beta < 0.1:
- raise ValueError("kww: beta smaller than 0.1")
-
- if beta > 2.0:
- raise ValueError("kww: beta larger than 2.0")
+ if not (0.1 <= beta <= 2.):
+ raise ValueError('KWW beta is not inside range 0.1-2')
if beta == 1:
return w*tau**2/(1+(w*tau)**2)
diff --git a/nmreval/math/mittagleffler.py b/nmreval/math/mittagleffler.py
index 44e42f1..1964045 100644
--- a/nmreval/math/mittagleffler.py
+++ b/nmreval/math/mittagleffler.py
@@ -1,10 +1,13 @@
from numbers import Number
+from typing import TypeVar, Union
import numpy as np
from math import sqrt, log, exp, ceil
from scipy.special import gamma
+T = TypeVar('T')
+
__all__ = ['mlf']
# calculate Mittag-Leffler based on MATLAB code
@@ -13,7 +16,7 @@ __all__ = ['mlf']
# SIAM Journal of Numerical Analysis, 2015, 53(3), 1350-1369
-def mlf(z, a: float, b: float = 1, g: float = 1):
+def mlf(z: T, a: float, b: float = 1, g: float = 1) -> T:
if b == 1 and gamma == 1:
if a == 0:
return 1 / (1 - z)
@@ -27,15 +30,16 @@ def mlf(z, a: float, b: float = 1, g: float = 1):
if isinstance(z, Number):
return _mlf_single(z, a, b, g)
+
else:
- ret_val = np.zeros_like(z)
- for i, zz in enumerate(z):
+ ret_val = np.zeros(z.size)
+ for i, zz in enumerate(z.ravel()):
ret_val[i] = _mlf_single(zz, a, b, g)
- return ret_val
+ return ret_val.reshape(z.shape)
-def _mlf_single(z, a, b, g):
+def _mlf_single(z: Union[int, float, complex], a: float, b: float, g: float):
if abs(z) < 1.0e-15:
ret_val = 1 / gamma(b)
else:
diff --git a/nmreval/models/__init__.py b/nmreval/models/__init__.py
index f5c368e..56158df 100755
--- a/nmreval/models/__init__.py
+++ b/nmreval/models/__init__.py
@@ -1,3 +1,26 @@
+"""
+=============
+Fit functions
+=============
+
+.. currentmodule:: nmreval.models
+
+.. autosummary::
+ :toctree: generated
+ :nosignatures:
+ :template: autosummary/class_with_attributes.rst
+
+ Constant
+ Linear
+ Parabola
+ PowerLaw
+ PowerLawCross
+ ExpFunc
+ MittagLeffler
+ Log
+ Sine
+
+"""
from .basic import *
from .relaxation import *
diff --git a/nmreval/models/basic.py b/nmreval/models/basic.py
index 64cdc5f..c7bc0c0 100644
--- a/nmreval/models/basic.py
+++ b/nmreval/models/basic.py
@@ -1,42 +1,44 @@
+"""
+***************
+Basic functions
+***************
+
+Simple basic functions
+"""
+
import numpy as np
+from ..lib.utils import ArrayLike
from ..math.mittagleffler import mlf
class Constant:
"""
- Constant
-
- .. math::
- y = c\cdot x
-
- Args:
- x (array_like): Input values
- c (float): constant
+ A boring constant line.
"""
-
type = 'Basic'
name = 'Constant'
equation = 'C'
params = ['C']
@staticmethod
- def func(x, c: float):
+ def func(x: ArrayLike, c: float) -> ArrayLike:
+ """
+ Constant
+
+ .. math::
+ y = c \cdot x
+
+ Args:
+ x (array-like): Input values
+ c (float): constant
+ """
return c*np.ones(len(x))
class Linear:
"""
- Straight line.
-
- .. math::
- y = m\cdot x + t
-
- Args:
- x (array_like): Input values
- m (float): Slope
- t (float): Intercept
-
+ Slightly more exciting line
"""
type = 'Basic'
name = 'Straight line'
@@ -44,7 +46,19 @@ class Linear:
params = ['m', 't']
@staticmethod
- def func(x, m: float, t: float):
+ def func(x: ArrayLike, m: float, t: float) -> ArrayLike:
+ """
+ Straight line.
+
+ .. math::
+ y = m\cdot x + t
+
+ Args:
+ x (array_like): Input values
+ m (float): Slope
+ t (float): Intercept
+
+ """
return m*x + t
diff --git a/nmreval/models/wideline.py b/nmreval/models/wideline.py
index eb11c45..ccdf5a2 100644
--- a/nmreval/models/wideline.py
+++ b/nmreval/models/wideline.py
@@ -1,5 +1,9 @@
import numpy as np
-from numpy import trapz
+try:
+ from scipy.integrate import simpson
+except ImportError:
+ from scipy.integrate import simps as simpson
+from numpy import pi
from ..math.orientations import zcw_spherical as crystallites
@@ -29,21 +33,22 @@ class Pake:
_x -= 0.5*_x[-1]
if broad == 'l':
- apd = 2 * sigma / (4 * _x**2 + sigma**2) / np.pi
+ apd = 2 * sigma / (4 * _x**2 + sigma**2) / pi
else:
- apd = np.exp(-4 * np.log(2) * (_x/sigma)**2) * 2 * np.sqrt(np.log(2) / np.pi) / sigma
+ apd = np.exp(-4 * np.log(2) * (_x/sigma)**2) * 2 * np.sqrt(np.log(2) / pi) / sigma
ret_val = np.convolve(s, apd, mode='same')
else:
ret_val = s
- omega_1 = np.pi/2/t_pulse
- attn = omega_1 * np.sin(t_pulse*np.sqrt(omega_1**2+0.5*(2*np.pi*x)**2)) / np.sqrt(omega_1**2+(np.pi*x)**2)
+ omega_1 = pi/2/t_pulse
+ attn = omega_1 * np.sin(t_pulse*np.sqrt(omega_1**2+0.5*(2*pi*x)**2)) / \
+ np.sqrt(omega_1**2+(np.pi*x)**2)
ret_val *= attn
- return c * ret_val / trapz(ret_val, x)
+ return c * ret_val / simpson(ret_val, x)
class CSA:
@@ -69,14 +74,14 @@ class CSA:
_x = np.arange(len(x)) * (x[1] - x[0])
_x -= 0.5 * _x[-1]
if broad == 'l':
- apd = 2 * sigma / (4*_x**2 + sigma**2) / np.pi
+ apd = 2 * sigma / (4*_x**2 + sigma**2) / pi
else:
- apd = np.exp(-4 * np.log(2) * (_x / sigma) ** 2) * 2 * np.sqrt(np.log(2) / np.pi) / sigma
+ apd = np.exp(-4 * np.log(2) * (_x / sigma) ** 2) * 2 * np.sqrt(np.log(2) / pi) / sigma
ret_val = np.convolve(s, apd, mode='same')
else:
ret_val = s
- return c * ret_val / trapz(ret_val, x)
+ return c * ret_val / simpson(ret_val, x)
class SecCentralLine:
diff --git a/nmreval/nmr/__init__.py b/nmreval/nmr/__init__.py
index e69de29..3c3fc06 100644
--- a/nmreval/nmr/__init__.py
+++ b/nmreval/nmr/__init__.py
@@ -0,0 +1,42 @@
+"""
+=========================================
+NMR specific methods (:mod:`nmreval.nmr`)
+=========================================
+
+Each class provides a distribution of correlation times, correlation
+function, spectral density, susceptibility, and calculation of different
+types of correlation times.
+
+.. currentmodule:: nmreval.nmr
+
+Relaxation
+**********
+
+Calculate spin-lattice and spin-spin relaxation, and evaluate T1 minima for correlation times.
+
+.. autosummary::
+ :toctree: generated/
+ :nosignatures:
+
+ Relaxation
+ RelaxationEvaluation
+
+Coupling constants (:mod:`nmreval.nmr.coupling`)
+************************************************
+
+.. autosummary::
+ :toctree: generated/
+ :template: autosummary/class_with_attributes.rst
+ :nosignatures:
+
+ ~coupling.Quadrupolar
+ ~coupling.HeteroDipolar
+ ~coupling.HomoDipolar
+ ~coupling.CSA
+ ~coupling.Constant
+ ~coupling.Czjzek
+
+"""
+
+from .relaxation import Relaxation, RelaxationEvaluation
+
diff --git a/nmreval/nmr/coupling.py b/nmreval/nmr/coupling.py
new file mode 100644
index 0000000..5e45e54
--- /dev/null
+++ b/nmreval/nmr/coupling.py
@@ -0,0 +1,236 @@
+"""
+NMR coupling values
+===================
+
+This is a compilation of NMR prefactors for calculation of relaxation times.
+A note of caution is
+
+"""
+
+import abc
+from math import log
+from collections import OrderedDict
+
+from ..utils.constants import gamma_full, hbar_joule, pi, gamma, mu0
+
+
+__all__ = ['Quadrupolar', 'Czjzek', 'HeteroDipolar',
+ 'HomoDipolar', 'Constant', 'CSA']
+
+
+class Coupling(metaclass=abc.ABCMeta):
+ name = 'coupling'
+ parameter = None
+ choice = None
+ unit = None
+ equation = ''
+
+ @staticmethod
+ @abc.abstractmethod
+ def relax(*args, **kwargs):
+ raise NotImplementedError
+
+
+class Quadrupolar(Coupling):
+ """ Quadrupolar interaction
+ """
+
+ name = 'Quadrupolar'
+ parameter = [r'\delta/C_{q}', r'\eta']
+ unit = ['Hz', '']
+ equation = r'3/50 \pi^{2} C_{q}^{2} (1+\eta^{2}/3) (2I+3)/(I^{2}(2I-1))'
+ choice = [
+ ('Spin', 'spin', OrderedDict([('1', 1), ('3/2', 1.5), ('2', 2), ('5/2', 2.5)])),
+ ('Type', 'is_delta', {'Anisotropy': True, 'QCC': False})
+ ]
+
+ @staticmethod
+ def relax(value: float, eta: float, spin: float = 1, is_delta: bool = True) -> float:
+ r"""Calculates prefactor for quadrupolar relaxation
+
+ .. math::
+ \frac{3}{200} (2\pi C_q)^2 \left(1+\frac{\eta^{2}}{3}\right) \frac{2I+3}{I^{2}(2I-1)}
+
+ If input is given as anisotropy :math:`\delta` then :math:`C_q` is calculated via
+
+ .. math::
+ C_q = \delta \frac{4I(2I-1)}{3(2m-1)}
+
+ where `m` is 1 for integer spin and 3/2 else.
+
+ Args:
+ value (float): Quadrupolar coupling constant in Hz.
+ eta (float): Asymmetry parameter
+ spin (float): Spin `I`. Default is 1.
+ is_delta (bool): If True, uses value as anisotropy :math:`\delta` else as QCC. Default is True.
+
+ """
+ m = 1 if (2*spin) % 2 == 0 else 1.5
+ if is_delta:
+ value *= 4*spin*(2*spin-1) / (3*(2*m-1))
+
+ return 0.06 * (2*spin+3) * (pi*value)**2 * (1 + eta**2 / 3) / (spin**2 * (2*spin-1))
+
+ @staticmethod
+ def convert(in_value: float, to: str = 'aniso', spin: float = 1) -> float:
+ r"""Convert between QCC and anisotropy.
+
+ Relation between quadrupole coupling constant :math:`C_q` and anisotropy :math:`\delta` is given by
+
+ .. math::
+ \delta = \frac{3(2m-1)}{4I(2I-1)} C_q
+
+ where `m` is 1 for integer spin and 3/2 else.
+
+ Args:
+ in_value (float): Input value
+ to (str, {`aniso`, `qcc`}): Direction of conversion. Default is `aniso`
+ spin (float): Spin number `I`. Default is 1.
+
+ Returns:
+ Converted value
+ """
+ if to not in ['aniso', 'qcc']:
+ raise ValueError(f'Cannot convert to {to} use `aniso` or `qcc`')
+
+ m = 1 if (2 * spin) % 2 == 0 else 1.5
+ fac = 4 * spin * (2 * spin - 1) / (3 * (2 * m - 1))
+ if to == 'delta':
+ return in_value * fac
+ else:
+ return in_value / fac
+
+
+class HomoDipolar(Coupling):
+ """Homonuclear dipolar coupling"""
+
+ name = 'Homonuclear Dipolar'
+ parameter = ['r']
+ unit = ['m']
+ choice = [
+ (r'\gamma', 'nucleus', {k: k for k in gamma}),
+ ('Spin', 'spin', OrderedDict([('1/2', 0.5), ('1', 1), ('3/2', 1.5), ('2', 2), ('5/2', 2.5), ('3', 3)])),
+ ]
+ equation = r'2/5 [\mu_{0}/(4\pi) \hbar \gamma^{2}/r^{3}]^{2} I(I+1)'
+
+ @staticmethod
+ def relax(r: float, nucleus: str = '1H', spin: float = 0.5) -> float:
+ """Calculate prefactor for homonuclear dipolar relaxation.
+
+ Args:
+ r (float): Distance in m.
+ nucleus (str): Name of isotope. Default is `1H`
+ spin (float): Spin `I` of isotope. Default is 1/2
+
+ """
+
+ if nucleus not in gamma_full:
+ raise KeyError(f'Unknown nucleus {nucleus}')
+
+ try:
+ coupling = mu0 / (4*pi) * hbar_joule * gamma_full[nucleus]**2 / (r+1e-34)**3
+ except ZeroDivisionError:
+ return 1e318
+
+ coupling **= 2
+ coupling *= 2 * spin * (spin+1) / 5
+
+ return coupling
+
+
+class HeteroDipolar(Coupling):
+ """Heteronuclear dipolar coupling"""
+
+ name = 'Heteronuclear Dipolar'
+ parameter = ['r']
+ unit = ['m']
+ choice = [
+ (r'\gamma_{1}', 'nucleus1', {k: k for k in gamma}),
+ (r'\gamma_{2}', 'nucleus2', {k: k for k in gamma}),
+ ('Spin', 'spin', dict([('1/2', 0.5), ('1', 1), ('3/2', 1.5), ('2', 2), ('5/2', 2.5), ('3', 3)]))
+ ]
+ equation = r'2/15 [\mu_{0}/(4\pi) \hbar \gamma^{2}/r^{3}]^{2} I(I+1)'
+
+ @staticmethod
+ def relax(r: float, nucleus1: str = '1H', nucleus2: str = '19F', spin: float = 0.5) -> float:
+ r"""Calculate prefactor for feteronuclear dipolar relaxation.
+
+ .. math::
+ \frac{2}{15} \left(\frac{\mu_0}{4\pi} \hbar \frac{\gamma_1 \gamma_2}{r^3} \right)^2 S(S+1)
+
+ Args:
+ r (float): Distance in m.
+ nucleus1 (str): Name of observed isotope. Default is `1H`
+ nucleus2 (str): Name of coupled isotope. Default is `19F`
+ spin (float): Spin `S` of the coupled isotope. Default is 1/2
+
+ """
+ if nucleus1 not in gamma_full:
+ raise KeyError(f'Unknown nucleus {nucleus1}')
+
+ if nucleus2 not in gamma_full:
+ raise KeyError(f'Unknown nucleus {nucleus2}')
+
+ try:
+ coupling = mu0 / (4*pi) * hbar_joule * gamma_full[nucleus1]*gamma_full[nucleus2] / r**3
+ except ZeroDivisionError:
+ return 1e318
+
+ coupling **= 2
+ coupling *= 2 * spin * (spin+1) / 15
+
+ return coupling
+
+
+class Czjzek(Coupling):
+ name = 'Czjzek'
+ parameter = [r'\Sigma']
+ unit = ['Hz']
+ choice = [('Spin', 'spin', {'1': 1, '3/2': 1.5, '5/2': 2.5, '7/2': 3.5})]
+ equation = r'3/[20log(2)] \pi^{2} \Sigma^{2} (2I+3)/(I^{2}(2I-1))'
+
+ @staticmethod
+ def relax(fwhm, spin=1):
+ return 3*(2+spin+3) * pi**2 * fwhm**2 / 20 / log(2) / spin**2 / (2*spin-1)
+
+
+class Constant(Coupling):
+ name = 'Constant'
+ parameter = ['C']
+ equation = 'C'
+
+ @staticmethod
+ def relax(c):
+ return c
+
+
+class CSA(Coupling):
+ """Chemical shift anisotropy"""
+
+ name = 'CSA'
+ equation = r'2/15 \Delta\sigma^{2} (1+\eta^{2}/2)'
+ parameter = [r'\Delta\sigma', '\eta']
+ unit = ['ppm', '']
+
+ @staticmethod
+ def relax(sigma: float, eta: float) -> float:
+ r"""Relaxation prefactor for chemical shift anisotropy.
+
+ .. math::
+ C = \frac{2}{15} \Delta\sigma^2 \left(1+\frac{\eta^2}{3}\right)
+
+ .. note::
+ The influence of the external magnetic field is missing here but
+ is multiplied in :func:`~nmreval.nmr.Relaxation.t1_csa`
+
+ Args:
+ sigma: Anisotropy (in ppm)
+ eta: Asymmetry parameter
+
+ Reference:
+ Spiess, H.W.: Rotation of Molecules and Nuclear Spin Relaxation.
+ In: NMR - Basic principles and progress, Vol. 15, (Springer, 1978)
+ https://doi.org/10.1007/978-3-642-66961-3_2
+
+ """
+ return 2 * sigma**2 * (1+eta**2 / 3) / 15
diff --git a/nmreval/nmr/couplings.py b/nmreval/nmr/couplings.py
deleted file mode 100644
index b54ed2b..0000000
--- a/nmreval/nmr/couplings.py
+++ /dev/null
@@ -1,102 +0,0 @@
-from math import log
-from collections import OrderedDict
-
-from ..utils.constants import pi, gamma, mu0, hbar
-
-
-__all__ = ['Quadrupolar', 'QuadrupolarQCC', 'Czjzek', 'HeteroDipolar', 'HomoDipolar', 'Constant']
-
-
-class Coupling(object):
- name = 'coupling'
- parameter = None
- choice = None
- unit = None
- equation = ''
-
-
-class Quadrupolar(Coupling):
- name = 'Quadrupolar'
- parameter = [r'\delta', r'\eta']
- unit = ['Hz', '']
- equation = r'24 (2I-1)(2I+3) / (25(6m+3)^{2}) (1+\eta^2/3) \pi^{2} \delta^{2}'
- choice = [('Spin', 'spin', OrderedDict([('1', 1), ('3/2', 1.5), ('2', 2),
- ('5/2', 2.5), ('3', 3), ('7/2', 3.5)]))]
-
- @staticmethod
- def func(delta, eta, spin=1):
- m = 0 if (2*spin) % 2 == 0 else 0.5
- return 24*(2*spin-1)*(2*spin+3) * pi**2 * delta**2 * (1+eta**2 / 3) / 25 / (6*m+3)**2
-
-
-class QuadrupolarQCC(Coupling):
- name = 'Quadrupolar (QCC)'
- parameter = ['C_{Q}', r'\eta']
- unit = ['Hz', '']
- choice = [('Spin', 'spin', {'1': 1, '3/2': 1.5, '5/2': 2.5, '7/2': 3.5})]
- equation = r'3/50 \pi^{2} C_{Q}^{2} (1+\eta^{2}/3) (2I+3)/(I^{2}(2I-1))'
-
- @staticmethod
- def func(cq, eta, spin=1):
- return 0.06 * (2*spin+3)*pi**2 * cq**2 * (1+eta**2 / 3) / spin**2 / (2*spin-1)
-
-
-class Czjzek(Coupling):
- name = 'Czjzek'
- parameter = [r'\Sigma']
- unit = ['Hz']
- choice = [('Spin', 'spin', {'1': 1, '3/2': 1.5, '5/2': 2.5, '7/2': 3.5})]
- equation = r'3/[20log(2)] \pi^{2} \Sigma^{2} (2I+3)/(I^{2}(2I-1))'
-
- @staticmethod
- def func(fwhm, spin=1):
- return 3*(2+spin+3) * pi**2 * fwhm**2 / 20 / log(2) / spin**2 / (2*spin-1)
-
-
-class HeteroDipolar(Coupling):
- name = 'Heteronuclear Dipolar'
- parameter = ['r']
- unit = ['m']
- choice = [(r'\gamma_{1}', 'nucleus1', {k: k for k in gamma.keys()}),
- (r'\gamma_{2}', 'nucleus2', {k: k for k in gamma.keys()})]
- equation = r'1/10 * [\mu_{0}/(4\pi) * \hbar * \gamma_{1}\gamma_{2}/r^{3}]^{2}'
-
- @staticmethod
- def func(r, nucleus1='1H', nucleus2='19F'):
- if nucleus1 not in gamma:
- raise KeyError('Unknown nucleus {}'.format(nucleus1))
- if nucleus2 not in gamma:
- raise KeyError('Unknown nucleus {}'.format(nucleus2))
-
- coupling = mu0 / (4*pi) * hbar*gamma[nucleus1]*gamma[nucleus2] / (r+1e-34)**3
- coupling **= 2
-
- return 0.1 * coupling
-
-
-class HomoDipolar(Coupling):
- name = 'Homonuclear Dipolar'
- parameter = ['r']
- unit = ['m']
- choice = [(r'\gamma', 'nucleus', {k: k for k in gamma.keys()})]
- equation = r'3/10 * [\mu_{0}/(4\pi) * \hbar * \gamma^{2}/r^{3}]^{2}'
-
- @staticmethod
- def func(r, nucleus='1H'):
- if nucleus not in gamma:
- raise KeyError('Unknown nucleus {}'.format(nucleus))
-
- coupling = mu0 / (4*pi) * hbar * gamma[nucleus]**2 / (r+1e-34)**3
- coupling **= 2
-
- return 0.3 * coupling
-
-
-class Constant(Coupling):
- name = 'Constant'
- parameter = ['C']
- equation = 'C'
-
- @staticmethod
- def func(c):
- return c
diff --git a/nmreval/nmr/relaxation.py b/nmreval/nmr/relaxation.py
index 1b8d2a6..c7e403d 100755
--- a/nmreval/nmr/relaxation.py
+++ b/nmreval/nmr/relaxation.py
@@ -1,6 +1,12 @@
-from numbers import Number
+"""
+Relaxation
+==========
+
+Classes to calculate spin-lattice and spin-spin relaxation, as well as to evaluate T1 data and calculate correlation times
+"""
+
from pathlib import Path
-from typing import Tuple
+from typing import Any, Optional, Tuple, Type, Union
from warnings import warn
import numpy as np
@@ -8,138 +14,417 @@ from scipy.interpolate import interp1d, Akima1DInterpolator
from scipy.optimize import minimize
from nmreval.lib.utils import ArrayLike
+from .coupling import Coupling
+from ..distributions.base import Distribution
from ..distributions.debye import Debye as Debye
+from ..utils import gamma_full
class Relaxation:
- def __init__(self, distribution=None):
- self._distribution = distribution
- self._dist_parameter = ()
+ """
+ Class to calculate relaxation times.
+ """
+
+ def __init__(self, distribution: Type[Distribution] = None):
+ self.distribution = distribution
+ self.dist_parameter = ()
self._dist_kw = {}
- self._coupling = None
- self._coup_parameter = ()
- self._coup_kw = {}
+ self.coupling = None
+ self.coup_parameter = []
+ self.coup_kw = {}
- self._prefactor = 1.
+ self.prefactor = 1.
def __repr__(self):
- if self._distribution is not None:
- return str(self._distribution.name)
+ if self.distribution is not None:
+ return str(self.distribution.name)
else:
return super().__repr__()
- def coupling(self, coupling, parameter: list = None, keywords: dict = None):
- self._coupling = coupling
+ def set_coupling(self, coupling: Union[float, Type[Coupling]],
+ parameter: Union[tuple, list] = None, keywords: dict = None):
if parameter is not None:
- self._coup_parameter = parameter
+ self.coup_parameter = parameter
if keywords is not None:
- self._coup_kw = keywords
+ self.coup_kw = keywords
- if isinstance(self._coupling, Number):
- self._prefactor = self._coupling
+ if isinstance(coupling, float):
+ self.prefactor = coupling
+ elif issubclass(coupling, Coupling):
+ self.coupling = coupling
+ if self.coup_kw is None:
+ raise ValueError('Coupling is missing parameter')
+ self.prefactor = self.coupling.relax(*self.coup_parameter, **self.coup_kw)
else:
- try:
- self._prefactor = self._coupling.func(*self._coup_parameter, **self._coup_kw)
- except TypeError:
- pass
+ raise ValueError(f'`coupling` is not number or of type `Coupling`, found {coupling!r}')
- def distribution(self, dist, parameter=None, keywords=None):
- self._distribution = dist
+ def set_distribution(self, dist: Type[Distribution], parameter: Union[tuple, list] = None, keywords: dict = None):
+ self.distribution = dist
if parameter is not None:
- self._dist_parameter = parameter
+ self.dist_parameter = parameter
if keywords is not None:
self._dist_kw = keywords
- def t1(self, omega, tau, *args, mode='bpp', **kwargs):
- # defaults to BPP
- if mode == 'bpp':
- return self.t1_bpp(omega, tau, *args, **kwargs)
- elif mode == 'dipolar':
- return self.t1_dipolar(omega, tau, *args, **kwargs)
- else:
- raise AttributeError(f'Unknown mode {mode}. Use either "bpp" or "dipolar".')
-
- def t1_dipolar(self, omega: ArrayLike, tau: ArrayLike, *args,
- inverse: bool = True, prefactor: float = None, **kwargs) -> ArrayLike:
- """
+ def t1(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ mode: str = 'bpp', **kwargs) -> Union[np.ndarray, float]:
+ r"""
+ Convenience function
Args:
- omega:
- tau:
- *args:
- inverse:
- prefactor:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args: Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ mode (str, {`bpp`, `dipolar`, `csa`}): Type of relaxation
+
+ - `bpp` : Homonuclear dipolar/quadrupolar interaction :func:`(see here) `
+ - `dipolar` : Heteronuclear dipolar interaction :func:`(see here) `
+ - `csa` : Chemical shift interaction :func:`(see here) `
+
+ Default is `bpp`
+
**kwargs:
Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
"""
- try:
- omega_2 = kwargs['omega_coup']
- except KeyError:
- if kwargs.get('gamma_obs', False):
- omega_2 = kwargs['gamma_coup'] / kwargs['gamma_obs'] * omega
- else:
- raise AttributeError('Unknown second frequency.')
+ if mode not in ['bpp', 'dipolar', 'csa']:
+ raise ValueError(f'Unknown mode {mode} not `bpp`, `dipolar`, `csa`.')
+
+ # defaults to BPP
+ if mode == 'bpp':
+ return self.t1_bpp(omega, tau, *specdens_args, **kwargs)
+ elif mode == 'dipolar':
+ return self.t1_dipolar(omega, tau, *specdens_args, **kwargs)
+
+ def t1_dipolar(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any, inverse: bool = True,
+ prefactor: float = None, omega_coup: ArrayLike = None,
+ gamma_coup: str = None, gamma_obs: str = None) -> Union[np.ndarray, float]:
+ r"""Calculate T1 under heteronuclear dipolar coupling.
+
+ .. math::
+ \frac{1}{T_1} = C [3J(\omega_I) + 6J(\omega_I + \omega_I) + J(\omega_I - \omega_S)]
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args: Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+ omega_coup (array-like, optional): Frequency of coupled isotope must be of same shape as omega.
+ gamma_obs (str, optional): Name of observed isotope ('1H', '23Na', ...).
+ Values is used if `omega_coup` is None.
+ gamma_coup (str, optional): Name of coupled isotope ('1H', '23Na', ...).
+ Values is used if `omega_coup` is None.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
+ omega = np.asanyarray(omega)
+
+ if omega_coup is not None:
+ omega_coup = np.asanyarray(omega_coup)
+ if omega.shape != omega_coup.shape:
+ raise ValueError('omega and omega_coup have not same shape')
+ omega_2 = omega_coup
+ elif (gamma_coup is not None) and (gamma_obs is not None):
+ omega_2 = gamma_full[gamma_coup] / gamma_full[gamma_obs] * omega
+ else:
+ raise AttributeError('Unknown second frequency. Set `omega_coup`, or `gamma_coup` and `gamma_obs`')
if prefactor is None:
- prefactor = self._prefactor
+ prefactor = self.prefactor
- if len(args) == 0:
- args = self._dist_parameter
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
- rate = prefactor * (3 * self._distribution.specdens(omega, tau, *args) +
- self._distribution.specdens(np.abs(omega - omega_2), tau, *args) +
- 6 * self._distribution.specdens(omega + omega_2, tau, *args))
+ rate = prefactor * (self.distribution.specdens(omega - omega_2, tau, *specdens_args) +
+ 3 * self.distribution.specdens(omega, tau, *specdens_args) +
+ 6 * self.distribution.specdens(omega + omega_2, tau, *specdens_args)) / 2
if inverse:
return 1 / rate
else:
return rate
- def t1_bpp(self, omega, tau, *args, inverse=True, prefactor=None, **kwargs):
+ def t1_bpp(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None) -> Union[np.ndarray, float]:
+ r"""Calculate T1 under homonuclear dipolar coupling or quadrupolar coupling.
+
+ .. math::
+ \frac{1}{T_1} = C [J(\omega) + 4J(2\omega)]
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args: Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
if prefactor is None:
- prefactor = self._prefactor
+ prefactor = self.prefactor
- if len(args) == 0:
- args = self._dist_parameter
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
- rate = prefactor * (self._distribution.specdens(omega, tau, *args) +
- 4*self._distribution.specdens(2*omega, tau, *args))
+ rate = prefactor * (self.distribution.specdens(omega, tau, *specdens_args) +
+ 4 * self.distribution.specdens(2 * omega, tau, *specdens_args))
if inverse:
return 1. / rate
else:
return rate
- def t1_rho(self, omega, tau, omega_rf, *args, inverse=True, prefactor=None, **kwargs):
+ def t1_csa(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None) -> Union[np.ndarray, float]:
+ r"""Calculate T1 under chemical shift anisotropy.
+
+ .. math::
+ \frac{1}{T_1} = C \omega^2 [J(\omega)]
+
+ This relation disregards antisymmetric CSA contributions
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args: Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
if prefactor is None:
- prefactor = self._prefactor
+ prefactor = self.prefactor
- if len(args) == 0:
- args = self._dist_parameter
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
- rate = prefactor * (10 * self._distribution.specdens(omega, tau, *args) +
- 4 * self._distribution.specdens(2 * omega, tau, *args) +
- 6 * self._distribution.specdens(omega_rf, tau, *args))
+ rate = prefactor * (self.distribution.specdens(omega, tau, *specdens_args) +
+ 4 * self.distribution.specdens(2 * omega, tau, *specdens_args))
if inverse:
return 1. / rate
else:
return rate
- def t2(self, omega, tau, *args, inverse=True, prefactor=None, **kwargs):
+ def t1q(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None) -> Union[np.ndarray, float]:
+ r"""Calculate T1q for homonuclear dipolar coupling or quadrupolar coupling (I=1).
+
+ .. math::
+ \frac{1}{T_{1q}} = 3 C J(\omega)
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args: Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
if prefactor is None:
- prefactor = self._prefactor / 2.
+ prefactor = self.prefactor
- if len(args) == 0:
- args = self._dist_parameter
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
- rate = prefactor * (3 * self._distribution.specdens(0, tau, *args) +
- 5 * self._distribution.specdens(omega, tau, *args) +
- 2 * self._distribution.specdens(2 * omega, tau, *args))
+ rate = 3 * prefactor * self.distribution.specdens(omega, tau, *specdens_args)
+ if inverse:
+ return 1. / rate
+ else:
+ return rate
+
+ def t1_rho(self, omega: ArrayLike, tau: ArrayLike, omega_rf: float, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None):
+ r"""Calculate T1rho for homonuclear dipolar coupling or quadrupolar coupling.
+
+ .. math::
+ \frac{1}{T_{1\rho}} = \frac{C}{2} [5J(\omega) + 2J(2\omega) + 3J(2\omega_{RF})]
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz).
+ tau (array-like): Correlation times in s.
+ omega_rf (float): Frequency of RF lock IN 1/s.
+ *specdens_args: Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
+ if prefactor is None:
+ prefactor = self.prefactor
+
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
+
+ rate = prefactor * (5 * self.distribution.specdens(omega, tau, *specdens_args) +
+ 2 * self.distribution.specdens(2 * omega, tau, *specdens_args) +
+ 3 * self.distribution.specdens(2 * omega_rf, tau, *specdens_args)) / 2
+ if inverse:
+ return 1. / rate
+ else:
+ return rate
+
+ def t2_bpp(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None) -> Union[np.ndarray, float]:
+ r"""Calculate T2 under homonuclear dipolar coupling or quadrupolar coupling.
+
+ .. math::
+ \frac{1}{T_2} = \frac{C}{2} [3J() + 5J(2\omega) + 3J(2\omega)]
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args (optional): Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
+ if prefactor is None:
+ prefactor = self.prefactor
+
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
+
+ rate = prefactor * (3 * self.distribution.specdens(0, tau, *specdens_args) +
+ 5 * self.distribution.specdens(omega, tau, *specdens_args) +
+ 2 * self.distribution.specdens(2 * omega, tau, *specdens_args)) / 2
+ if inverse:
+ return 1. / rate
+ else:
+ return rate
+
+ def t2_dipolar(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None, omega_coup: ArrayLike = None,
+ gamma_coup: str = None, gamma_obs: str = None) -> Union[np.ndarray, float]:
+ r"""Calculate T2 under heteronuclear dipolar coupling.
+
+ .. math::
+ \frac{1}{T_2} = \frac{C}{2} [4J(0) + J(\omega_I - \omega_I) + 3J(\omega_S) + 6J(\omega_I) + 6J(\omega_I + \omega_I)]
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args (optional): Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+ omega_coup (array-like, optional): Frequency of coupled isotope must be of same shape as omega.
+ gamma_obs (str, optional): Name of observed isotope ('1H', '23Na', ...).
+ Values is used if `omega_coup` is None.
+ gamma_coup (str, optional): Name of coupled isotope ('1H', '23Na', ...).
+ Values is used if `omega_coup` is None.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
+ omega = np.asanyarray(omega)
+
+ if omega_coup is not None:
+ omega_coup = np.asanyarray(omega_coup)
+ if omega.shape != omega_coup.shape:
+ raise ValueError('omega and omega_coup have not same shape')
+ omega_2 = omega_coup
+ elif (gamma_coup is not None) and (gamma_obs is not None):
+ omega_2 = gamma_full[gamma_coup] / gamma_full[gamma_obs] * omega
+ else:
+ raise AttributeError('Unknown second frequency. Set `omega_coup`, or `gamma_coup` and `gamma_obs`')
+
+ if prefactor is None:
+ prefactor = self.prefactor
+
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
+
+ rate = prefactor * (4 * self.distribution.specdens(0, tau, *specdens_args) +
+ self.distribution.specdens(omega - omega_2, tau, *specdens_args) +
+ 3 * self.distribution.specdens(omega_2, tau, *specdens_args) +
+ 6 * self.distribution.specdens(omega, tau, *specdens_args) +
+ 6 * self.distribution.specdens(omega + omega_2, tau, *specdens_args)) / 2.
+
+ if inverse:
+ return 1. / rate
+ else:
+ return rate
+
+ def t2_csa(self, omega: ArrayLike, tau: ArrayLike, *specdens_args: Any,
+ inverse: bool = True, prefactor: float = None) -> Union[np.ndarray, float]:
+ r"""Calculate T1 under chemical shift anisotropy.
+
+ .. math::
+ \frac{1}{T_2} = \frac{C}{2} \omega^2 \bigl[J(0) + \frac{4}{3}J(\omega)\bigr]
+
+ Args:
+ omega (array-like): Frequency in 1/s (not Hz)
+ tau (array-like): Correlation times in s
+ *specdens_args (optional): Additional parameter for spectral density.
+ If given this will replace previously set arguments during calculation
+ inverse (bool): Function returs relaxation time if True else relaxation rate. Default is `True`
+ prefactor (float, optional): If given it is used as prefactor `C`
+ instead of previously set coupling prefactor.
+
+ Returns:
+ float or ndarray:
+ A k by n array where k is length of ``omega`` and n is length of ``tau``.
+ If both are of length 1 a number is returned instead of array.
+
+ """
+ if prefactor is None:
+ prefactor = self.prefactor
+
+ if len(specdens_args) == 0:
+ specdens_args = self.dist_parameter
+
+ rate = prefactor * (self.distribution.specdens(0, tau, *specdens_args) +
+ 4 / 3 * self.distribution.specdens(omega, tau, *specdens_args)) / 2.
if inverse:
return 1. / rate
else:
@@ -158,60 +443,31 @@ class RelaxationEvaluation(Relaxation):
self.y = None
def data(self, temp, t1):
- temp = np.asarray(temp)
- t1 = np.asarray(t1)
+ temp = np.asanyarray(temp)
+ t1 = np.asanyarray(t1)
sortidx = temp.argsort()
self.x = temp[sortidx]
self.y = t1[sortidx]
self.calculate_t1_min()
- def calculate_t1_min(self, interpolate: int = None, trange=None):
- min_index = np.argmin(self.y)
- t1_min = (self.x[min_index], self.y[min_index])
- parabola = None
- self._interpolate_range = (None, None)
+ def get_increase(self, height: float = None, idx: int = 0, mode: str = None, omega: float = None,
+ dist_parameter: Union[tuple, list] = None, prefactor: Union[tuple, list, float] = None,
+ coupling_kwargs: dict = None):
+ """
+ Determine a single parameter from a T1 minimum
- if interpolate is not None:
- if interpolate not in [0, 1, 2, 3]:
- raise ValueError(f'Unknown interpolation value {interpolate}')
+ Args:
+ height (float, optional): Height of T1 minimum
+ mode (str, {`distribution`, `prefactor`}, optional): If given,
+ idx (int): Default is 0.
+ omega (float, optional): Larmor frequency (in 1/s)
+ dist_parameter (tuple, optional):
+ prefactor (tuple, float, optional):
+ coupling_kwargs (dict, optional):
- if interpolate != 0:
- if trange is None:
- left_b = max(min_index-2, 0)
- right_b = min(len(self.x), min_index+3)
- else:
- left_b = np.argmin(np.abs(self.x-trange[0]))
- right_b = np.argmin(np.abs(self.x-trange[1]))+1
+ Returns:
- temp_range = self.x[left_b:right_b]
- t1_range = self.y[left_b:right_b]
-
- try:
- x_inter = np.linspace(temp_range[0], temp_range[-1], num=51)
-
- if interpolate == 1:
- i_func = np.poly1d(np.polyfit(temp_range, t1_range, 2))
- elif interpolate == 2:
- i_func = interp1d(temp_range, t1_range, kind='cubic')
- else:
- i_func = Akima1DInterpolator(temp_range, t1_range)
-
- y_inter = i_func(x_inter)
- t1_min = (x_inter[np.argmin(y_inter)], y_inter[np.argmin(y_inter)])
- self._interpolate = i_func
- parabola = (x_inter, y_inter)
- self._interpolate_range = (temp_range[0], temp_range[-1])
-
- except IndexError:
- pass
-
- self.t1min = t1_min
-
- return t1_min, parabola
-
- def increase(self, variable: Tuple[str, int], height: float = None, omega: float = None,
- dist_parameter: list = None, prefactor=None,
- coupling_kwargs=None):
+ """
stretching = mini = np.nan
if height is None:
@@ -224,44 +480,62 @@ class RelaxationEvaluation(Relaxation):
omega = self.omega
if prefactor is None:
- prefactor = self._prefactor
+ prefactor = self.prefactor
if dist_parameter is None:
- dist_parameter = self._dist_parameter
+ dist_parameter = self.dist_parameter
- tau_lims = np.log10(1/omega)-3, np.log10(1/omega)+3
+ if coupling_kwargs is None:
+ coupling_kwargs = self.coup_kw
- if not variable:
- if isinstance(prefactor, list):
+ tau_lims = np.log10(1 / omega) - 3, np.log10(1 / omega) + 3
+
+ if mode is None:
+ # nothing is variable -> just calculate minimum for given parameter
+ if isinstance(prefactor, (tuple, list)):
if coupling_kwargs is None:
- coupling_kwargs = self._coup_kw
- prefactor = self._coupling.func(*prefactor, **coupling_kwargs)
+ coupling_kwargs = self.coup_kw
+ prefactor = self.coupling.relax(*prefactor, **coupling_kwargs)
return stretching, np.min(self.t1(omega, np.logspace(*tau_lims, num=1001),
*dist_parameter, prefactor=prefactor, inverse=True))
- if variable[0] == 'distribution':
- if isinstance(self._distribution, Debye):
- return 1.
+ if mode == 'distribution':
+ # width parameter of spectral density is variable
+
+ if isinstance(self.distribution, Debye):
+ # Debye is easy
+ return 1., np.min(self.t1(omega, np.logspace(*tau_lims, num=1001),
+ *dist_parameter, prefactor=prefactor, inverse=True))
+
+ if isinstance(prefactor, (list, tuple)):
+ # calculate prefactor from coupling
+ if self.coupling is None:
+ raise ValueError('Coupling must be set before evaluation of T1 min')
- if isinstance(prefactor, list):
if coupling_kwargs is None:
- coupling_kwargs = self._coup_kw
- prefactor = self._coupling.func(*prefactor, **coupling_kwargs)
+ coupling_kwargs = self.coup_kw
+
+ prefactor = self.coupling.relax(*prefactor, **coupling_kwargs)
use_fmin = True
- if self._distribution.name in ['KWW', 'Cole-Davidson', 'Cole-Cole', 'Log-Gaussian']:
-
+ if self.distribution.name in ['KWW', 'Cole-Davidson', 'Cole-Cole', 'Log-Gaussian']:
+ # using precalculated values is faster than actual calculation, especially KWW and LG
from importlib.resources import path
with path('resources.nmr', 'T1_min.npz') as fp:
if fp.exists():
- t1min_table = np.load(str(fp))[self._distribution.name.replace('-', '_')]
+ t1min_table = np.load(str(fp))[self.distribution.name.replace('-', '_')]
+
debye_min = omega / 1.42517571908650 / prefactor # Zahl kommt von Wolfram alpha
ratio = height / debye_min
- stretching = t1min_table[np.argmin(np.abs(t1min_table[:, 1]-ratio)), 0]
+ stretching = t1min_table[np.argmin(np.abs(t1min_table[:, 1] - ratio)), 0]
+
use_fmin = False
+ dist_parameter = [stretching]
if use_fmin:
+ # use for untabulated spectral densities or if something went wrong
+ #
def _f(_x, p, ii):
p[ii] = _x[0]
t1_calc = np.min(self.t1(omega, np.logspace(*tau_lims, num=1001), *p,
@@ -269,40 +543,100 @@ class RelaxationEvaluation(Relaxation):
return np.abs(t1_calc - height)
- stretching = minimize(_f, np.array([dist_parameter[variable[1]]]),
- args=(dist_parameter, variable[1]),
+ stretching = minimize(_f, np.array([dist_parameter[idx]]),
+ args=(dist_parameter, idx),
method='Nelder-Mead').x[0]
+ dist_parameter[idx] = stretching
+
+ elif mode == 'coupling':
+ # variable is somewhere in the prefcotor
- elif variable[0] == 'coupling':
t1_no_coup = np.min(self.t1(omega, np.logspace(*tau_lims, num=1001),
*dist_parameter, prefactor=1))
- if isinstance(prefactor, list):
- def _f(_x, p, ii):
- p[ii] = _x
- return np.abs(t1_no_coup/height - self._coupling.func(*p, **coupling_kwargs)[0])
+ if isinstance(prefactor, (tuple, list)):
+ prefactor = list(prefactor)
+
+ def _f(_x, p, ii):
+ p[ii] = _x[0]
+ return np.abs(t1_no_coup / height - self.coupling.relax(*p, **coupling_kwargs))
+
+ stretching = minimize(_f, np.array([prefactor[idx]]),
+ args=(prefactor, idx)).x[0]
- stretching = minimize(_f, np.array([prefactor[variable[1]]]),
- args=(prefactor, variable[1])).x[0]
else:
stretching = t1_no_coup / height
else:
- raise ValueError('Use "distribution" or "coupling" to set parameter')
+ raise ValueError('Use `distribution` or `coupling` to set parameter')
if stretching:
- self._prefactor = prefactor
- self._dist_parameter = dist_parameter
- if isinstance(prefactor, list):
- self._coup_parameter = prefactor
- mini = np.min(self.t1(omega, np.logspace(*tau_lims, num=1001), *self._dist_parameter,
- prefactor=self._prefactor))
+ self.prefactor = prefactor
+ self.dist_parameter = dist_parameter
+ if isinstance(prefactor, (tuple, list)):
+ self.coup_parameter = prefactor
+ self.prefactor = self.coupling.relax(*self.coup_parameter, **self.coup_kw)
+ else:
+ self.prefactor = prefactor
+ mini = np.min(self.t1(omega, np.logspace(*tau_lims, num=1001), *self.dist_parameter,
+ prefactor=self.prefactor))
return stretching, mini
- def correlation_from_t1(self, mode: str = 'raw', interpolate=False, omega=None,
- dist_parameter: list = None, prefactor: float = None,
- coupling_param: list = None, coupling_kwargs: dict = None):
+ def calculate_t1_min(self, interpolate: int = None, trange: Tuple[float, float] = None, use_log: bool = False) -> \
+ Tuple[Tuple[float, float], Optional[Tuple[np.ndarray, np.ndarray]]]:
+ min_index = np.argmin(self.y)
+ t1_min = (self.x[min_index], self.y[min_index])
+ parabola = None
+ self._interpolate_range = (None, None)
+
+ if interpolate is not None:
+ if interpolate not in [0, 1, 2, 3]:
+ raise ValueError(f'Unknown interpolation value {interpolate}')
+
+ if interpolate != 0:
+ if trange is None:
+ left_b = max(min_index - 2, 0)
+ right_b = min(len(self.x), min_index + 3)
+ else:
+ left_b = np.argmin(np.abs(self.x - trange[0]))
+ right_b = np.argmin(np.abs(self.x - trange[1])) + 1
+
+ temp_range = self.x[left_b:right_b]
+ t1_range = self.y[left_b:right_b]
+ if use_log:
+ t1_range = np.log10(t1_range)
+
+ try:
+ x_inter = np.linspace(temp_range[0], temp_range[-1], num=51)
+
+ if interpolate == 1:
+ i_func = np.poly1d(np.polyfit(temp_range, t1_range, 2))
+ elif interpolate == 2:
+ i_func = interp1d(temp_range, t1_range, kind='cubic')
+ else:
+ i_func = Akima1DInterpolator(temp_range, t1_range)
+
+ if use_log:
+ y_inter = 10**i_func(x_inter)
+ else:
+ y_inter = i_func(x_inter)
+ t1_min = (x_inter[np.argmin(y_inter)], y_inter[np.argmin(y_inter)])
+ self._interpolate = i_func
+ parabola = (x_inter, y_inter)
+ self._interpolate_range = (temp_range[0], temp_range[-1])
+ t1_min = x_inter[np.argmin(y_inter)], y_inter[np.argmin(y_inter)]
+
+ except IndexError:
+ pass
+
+ self.t1min = t1_min
+
+ return t1_min, parabola
+
+ def correlation_from_t1(self, mode: str = 'raw', interpolate: bool = False, omega: float = None,
+ dist_parameter: Union[float, list, tuple] = None, prefactor: Union[float, tuple, list] = None,
+ coupling_param: list = None, coupling_kwargs: dict = None) -> Tuple[np.ndarray, dict]:
if self.x is None:
raise ValueError('Temperature is not set')
@@ -317,40 +651,40 @@ class RelaxationEvaluation(Relaxation):
if prefactor is None:
if coupling_kwargs is None:
- coupling_kwargs = self._coup_kw
+ coupling_kwargs = self.coup_kw
if coupling_param is None:
- prefactor = self._prefactor
+ prefactor = self.prefactor
else:
- prefactor = self._coupling.func(*coupling_param, **coupling_kwargs)
+ prefactor = self.coupling.relax(*coupling_param, **coupling_kwargs)
if dist_parameter is None:
- dist_parameter = self._dist_parameter
+ dist_parameter = self.dist_parameter
fast_idx = self.x > self.t1min[0]
slow_t1 = self.y[~fast_idx]
slow_temp = self.x[~fast_idx]
- correlation_times = np.ones(self.x.shape)
+ correlation_times = np.ones_like(self.x)
offset = len(slow_t1)
base_taus = np.logspace(-10, -7, num=1001)
min_tau = base_taus[np.argmin(self.t1(omega, base_taus, *dist_parameter, prefactor=prefactor))]
- taus = np.geomspace(min_tau, 100.*min_tau, num=501)
+ taus = np.geomspace(min_tau, 100. * min_tau, num=501)
current_t1 = self.t1(omega, taus, *dist_parameter, prefactor=prefactor)
- for i in range(1, len(slow_t1)+1):
+ for i in range(1, len(slow_t1) + 1):
t1_i = slow_t1[-i]
if interpolate and self._interpolate is not None:
if slow_temp[-i] >= self._interpolate_range[0]:
t1_i = self._interpolate(slow_temp[-i])
- if min(current_t1) > t1_i:
+ if np.min(current_t1) > t1_i:
warn('Correlation time could not be calculated')
- correlation_times[offset-i] = taus[0]
+ correlation_times[offset - i] = taus[0]
continue
cross_idx = np.where(np.diff(np.sign(current_t1 - t1_i)))[0]
@@ -359,13 +693,13 @@ class RelaxationEvaluation(Relaxation):
current_t1 = self.t1(omega, taus, *dist_parameter, prefactor=prefactor)
cross_idx = np.where(np.diff(np.sign(current_t1 - t1_i)))[0]
- lamb = (t1_i - current_t1[cross_idx]) / (current_t1[cross_idx+1]-current_t1[cross_idx])
- correlation_times[offset-i] = (taus[cross_idx+1] * lamb + (1 - lamb) * taus[cross_idx])[0]
+ lamb = (t1_i - current_t1[cross_idx]) / (current_t1[cross_idx + 1] - current_t1[cross_idx])
+ correlation_times[offset - i] = (taus[cross_idx + 1] * lamb + (1 - lamb) * taus[cross_idx])[0]
fast_t1 = self.y[fast_idx]
fast_temp = self.x[fast_idx]
- taus = np.geomspace(0.01*min_tau, min_tau, num=501)
+ taus = np.geomspace(0.01 * min_tau, min_tau, num=501)
current_t1 = self.t1(omega, taus, *dist_parameter, prefactor=prefactor)
for i in range(len(fast_t1)):
@@ -376,8 +710,8 @@ class RelaxationEvaluation(Relaxation):
t1_i = self._interpolate(fast_temp[i])
if current_t1[-1] > t1_i:
- correlation_times[offset+i] = taus[-1]
- warn('Correlation time could not be calculated')
+ correlation_times[offset + i] = taus[-1]
+ warn(f'Correlation time for {correlation_times[offset + i]} could not be calculated')
continue
cross_idx = np.where(np.diff(np.sign(current_t1 - t1_i)))[0]
@@ -386,19 +720,22 @@ class RelaxationEvaluation(Relaxation):
current_t1 = self.t1(omega, taus, *dist_parameter, prefactor=prefactor)
cross_idx = np.where(np.diff(np.sign(current_t1 - t1_i)))[0]
- lamb = (t1_i - current_t1[cross_idx]) / (current_t1[cross_idx+1]-current_t1[cross_idx])
- correlation_times[offset+i] = (taus[cross_idx+1] * lamb + (1-lamb) * taus[cross_idx])[0]
+ lamb = (t1_i - current_t1[cross_idx]) / (current_t1[cross_idx + 1] - current_t1[cross_idx])
+ correlation_times[offset + i] = (taus[cross_idx + 1] * lamb + (1 - lamb) * taus[cross_idx])[0]
- opts = {'distribution': (self._distribution.name, dist_parameter),
- 'coupling': (self._coupling.name, coupling_param, coupling_kwargs),
- 'frequency': omega/2/np.pi}
+ opts = {'distribution': (self.distribution.name, dist_parameter),
+ 'frequency': omega / 2 / np.pi}
+ if self.coupling is not None:
+ opts['coupling'] = (self.coupling.name, self.prefactor, coupling_param, coupling_kwargs)
+ else:
+ opts['coupling'] = (self.prefactor,)
- return np.c_[self.x, self._distribution.mean_value(correlation_times, *dist_parameter, mode=mode)], opts
+ return np.c_[self.x, self.distribution.mean_value(correlation_times, *dist_parameter, mode=mode)], opts
def _create_minimum_file(self, filename):
x = np.geomspace(0.1, 1, num=10001)
with Path(filename).open('w') as f:
- f.write('#broadening\tT1_min/min_Debye\n')
+ f.write('# broadening\tT1_min/min_Debye\n')
for i, a in enumerate(np.geomspace(0.1, 10, num=10000)):
alpha = a
t1_i = self.t1_bpp(1, x, alpha)
diff --git a/nmreval/utils/constants.py b/nmreval/utils/constants.py
index 75e38c3..0c15f01 100755
--- a/nmreval/utils/constants.py
+++ b/nmreval/utils/constants.py
@@ -11,7 +11,7 @@ __all__ = ['NA', 'kb_joule', 'h_joule', 'hbar_joule',
NA = 6.02214076e23
kb_joule = 1.380649e-23
e = 1.602176634e-19
-h_joule = 6.62607015e-23
+h_joule = 6.62606896e-34
mu0 = 1.256637062124e-6
epsilon0 = 8.8541878128e-12
@@ -38,7 +38,7 @@ spintxt = """\
9Be 3/2 100 -3.759666 5.288
10B 3 19.9 2.8746786 8.459
11B 3/2 80.1 8.5847044 4.059
-13C 1/2 1.07 6.728 284
+13C 1/2 1.07 6.728284
14N 1 99.632 1.9337792 2.044
15N 1/2 0.368 -2.71261804
17O 5/2 0.038 -3.62808 -2.558
diff --git a/nmreval/utils/text.py b/nmreval/utils/text.py
index 2dcb5d9..1840abe 100644
--- a/nmreval/utils/text.py
+++ b/nmreval/utils/text.py
@@ -16,7 +16,7 @@ small_greek = [
r'\f{Symbol}s\f{} \f{Symbol}t\f{} \f{Symbol}u\f{} \f{Symbol}f\f{} \f{Symbol}c\f{} \f{Symbol}y\f{} '
r'\f{Symbol}w\f{}',
'alpha beta gamma delta epsilon zeta eta theta iota kappa lambda mu nu ' # plain
- 'xi omicron pi rho sigma sigma tau ypsilon phi chi psi omega'
+ 'xi omicron pi rho sigma sigma tau ypsilon phi chi psi omega',
]
big_greek = [
r'\Alpha \Beta \Gamma \Delta \Epsilon \Zeta \Eta \Theta \Iota \Kappa \Lambda \Mu ' # tex
@@ -28,7 +28,7 @@ big_greek = [
r'\f{Symbol}N\f{} \f{Symbol}X\f{} \f{Symbol}O\f{} \f{Symbol}P\f{} \f{Symbol}R\f{} \f{Symbol}S\f{} '
r'\f{Symbol}T\f{} \f{Symbol}Y\f{} \f{Symbol}F\f{} \f{Symbol}C\f{} \f{Symbol}U\f{} \f{Symbol}W\f{}',
'Alpha Beta Gamma Delta Epsilon Zeta Eta Theta Iota Kappa Lambda Mu ' # plain
- 'Nu Xi Omicron Pi Rho Sigma Tau Ypsilon Phi Chi Psi Omega'
+ 'Nu Xi Omicron Pi Rho Sigma Tau Ypsilon Phi Chi Psi Omega',
]
special_chars = [
r'\infty \int \sum \langle \rangle \pm \perp \para \leftarrow \rightarrow \leftrightarrow \cdot \hbar',
@@ -36,13 +36,13 @@ special_chars = [
r'\f{Symbol}¥\f{} \f{Symbol}ò\f{} \f{Symbol}å\f{} \f{Symbol}á\f{} \f{Symbol}ñ\f{} \f{Symbol}±\f{} '
r'\f{Symbol}^\f{} \f{Symbol}||\f{} \f{Symbol}¬\f{} \f{Symbol}®\f{} \f{Symbol}«\f{} \f{Symbol}×\f{Symbol} '
r'h\h{-0.6}\v{0.3}-\v{-0.3}\h{0.3}',
- 'infty int sum < > +- perp para <- -> <-> * hbar'
+ r'infty int sum < > \+- perp para <- -> <-> \* hbar',
]
funcs = [
r'\exp \log \ln \sin \cos \tan',
'exp log ln sin cos tan',
'exp log ln sin cos tan',
- 'exp log ln sin cos tan'
+ 'exp log ln sin cos tan',
]
delims = [
[(r'_{', r'}'), (r'', r''), (r'\\s', r'\\N'), (r'_{', r'}')],
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..5e8228b
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,8 @@
+matplotlib
+numpy
+scipy
+pyqtgraph
+bsddb3
+h5py
+PyQt5
+
diff --git a/resources/_ui/basewindow.ui b/resources/_ui/basewindow.ui
index bc10159..3f79593 100644
--- a/resources/_ui/basewindow.ui
+++ b/resources/_ui/basewindow.ui
@@ -353,6 +353,9 @@
+
+
+
diff --git a/resources/_ui/bdsdialog.ui b/resources/_ui/bdsdialog.ui
index 8707a18..fa275ee 100644
--- a/resources/_ui/bdsdialog.ui
+++ b/resources/_ui/bdsdialog.ui
@@ -6,15 +6,30 @@
0
0
- 400
- 319
+ 544
+ 443
Read BDS data
- -
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
-
@@ -24,74 +39,150 @@
- -
-
-
-
- 0
- 0
-
-
-
- Found temperatures
-
-
-
- -
-
-
-
- 0
- 0
-
-
-
- Read as:
-
-
-
-
-
-
-
-
-
- Permittivity ε
-
-
- true
-
-
-
- -
-
-
- Modulus 1/ε
-
-
-
- -
-
-
- Conductivity iεω
-
-
-
- -
-
-
- Qt::Vertical
-
-
-
- 20
- 40
-
-
-
-
-
+
+
+ X Axis
+
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+ -
+
+
+ Frequency
+
+
+ true
+
+
+ buttonGroup
+
+
+
+ -
+
+
+ Temperature
+
+
+ buttonGroup
+
+
+
+
+
- -
+
-
+
+
+ Y Axis
+
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
+ 3
+
+
-
+
+
+ Permittivity ε
+
+
+ true
+
+
+
+ -
+
+
+ Modulus 1/ε
+
+
+
+ -
+
+
+ Conductivity iεω
+
+
+
+ -
+
+
+ Loss factor tan(δ)
+
+
+
+ -
+
+
+ Qt::Horizontal
+
+
+
+ -
+
+
+ Capacity
+
+
+
+ -
+
+
+ Meas. temperature
+
+
+
+ -
+
+
+ Meas. time
+
+
+
+ -
+
+
+ Qt::Vertical
+
+
+
+ 20
+ 40
+
+
+
+
+
+
+
+ -
Qt::Horizontal
@@ -101,8 +192,29 @@
+ -
+
+
+
+ 0
+ 0
+
+
+
+ Found entries
+
+
+
+
+ freq_button
+ temp_button
+ eps_checkBox
+ modul_checkBox
+ cond_checkBox
+ listWidget
+
@@ -112,8 +224,8 @@
accept()
- 248
- 254
+ 254
+ 411
157
@@ -128,8 +240,8 @@
reject()
- 316
- 260
+ 322
+ 411
286
@@ -138,4 +250,7 @@
+
+
+
diff --git a/resources/nmr/Cole-Cole_min.dat b/resources/nmr/Cole-Cole_min.dat
new file mode 100644
index 0000000..e056573
--- /dev/null
+++ b/resources/nmr/Cole-Cole_min.dat
@@ -0,0 +1,9901 @@
+0.01 120.97050740586918
+0.0101 119.77273653414905
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diff --git a/resources/nmr/Cole-Davidson_min.dat b/resources/nmr/Cole-Davidson_min.dat
new file mode 100644
index 0000000..b14dfce
--- /dev/null
+++ b/resources/nmr/Cole-Davidson_min.dat
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diff --git a/resources/nmr/KWW_min.dat b/resources/nmr/KWW_min.dat
new file mode 100644
index 0000000..6ba7e16
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diff --git a/resources/nmr/Log-Gaussian_min.dat b/resources/nmr/Log-Gaussian_min.dat
new file mode 100644
index 0000000..b2b27c7
--- /dev/null
+++ b/resources/nmr/Log-Gaussian_min.dat
@@ -0,0 +1,10003 @@
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diff --git a/resources/nmr/T1_min.npz b/resources/nmr/T1_min.npz
index 3462be1..75c989a 100644
Binary files a/resources/nmr/T1_min.npz and b/resources/nmr/T1_min.npz differ