From 6cd630245cfd72c8eedbdcba06a75a8673b9768c Mon Sep 17 00:00:00 2001 From: dominik Date: Tue, 22 Mar 2022 20:07:59 +0100 Subject: [PATCH] doc added; reading of isochronal bds --- {docs => doc}/Makefile | 0 doc/examples/README.rst | 9 + doc/examples/distribution/README.rst | 6 + doc/examples/distribution/plot_ColeCole.py | 50 + .../distribution/plot_ColeDavidson.py | 50 + .../distribution/plot_HavriliakNegami.py | 53 + doc/examples/distribution/plot_KWW.py | 50 + doc/examples/distribution/plot_LogGaussian.py | 50 + doc/examples/nmr/README.rst | 6 + doc/examples/nmr/plot_RelaxationEvaluation.py | 67 + {docs => doc}/make.bat | 0 {docs => doc}/source/_static/fit_dialog.png | Bin {docs => doc}/source/_static/logo.png | Bin doc/source/_templates/autosummary/class.rst | 14 + doc/source/api/data.rst | 5 + doc/source/api/distributions.rst | 4 + .../source/api/distributions2}/index.rst | 0 doc/source/api/index.rst | 13 + doc/source/api/models.rst | 4 + .../source/api/models2}/basic.rst | 0 .../source/api/models2}/index.rst | 0 .../api/models2}/nmreval.models.basic.rst | 0 doc/source/api/nmr.rst | 4 + {docs => doc}/source/conf.py | 80 +- doc/source/gallery/index.rst | 179 + doc/source/gallery/searchindex.bak | 3 + doc/source/gallery/searchindex.dat | Bin 0 -> 36960 bytes doc/source/gallery/searchindex.dir | 3 + {docs => doc}/source/index.rst | 8 +- {docs => doc}/source/nmr/depake.png | Bin {docs => doc}/source/nmr/index.rst | 0 {docs => doc}/source/nmr/pake.rst | 0 {docs => doc}/source/user_guide/fit.rst | 0 {docs => doc}/source/user_guide/index.rst | 0 {docs => doc}/source/user_guide/read.rst | 0 .../source/user_guide/shift_scale.rst | 0 docs/source/_templates/autosummary.rst | 25 - 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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 + +
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zR<2viP^qawI|LJr2Iie8Sn9i({YvpuoVq|yb}t(I?)IUvcG8VX>cfyD$mXHWs$kG>N#;TYR0STUnXi>T(njvd+FrHbA?__DNgt6uY W^SI?HR>fv{I_UiN+aK}G%l`tgw_c$D literal 0 HcmV?d00001 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 +0.0102 118.5984509413873 +0.0103 117.44696659033286 +0.0104 116.3176257528597 +0.0105 115.20979575715107 +0.0106 114.12286780579883 +0.0107 113.05625586017617 +0.0108 112.00939558679067 +0.0109 110.98174336163582 +0.011 109.97277532885087 +0.0111 108.98198651026381 +0.0112 108.00888996263723 +0.0113 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