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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Project: Azimuthal integration
# https://github.com/silx-kit/pyFAI
#
# Copyright (C) 2014-2018 European Synchrotron Radiation Facility, Grenoble, France
#
# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# .
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
# .
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
"""Calibrant
A module containing classical calibrant and also tools to generate d-spacing.
Interesting formula:
http://geoweb3.princeton.edu/research/MineralPhy/xtalgeometry.pdf
"""
__author__ = "Jerome Kieffer"
__contact__ = "Jerome.Kieffer@ESRF.eu"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "19/01/2021"
__status__ = "production"
import os
import logging
import numpy
import itertools
from math import sin, asin, cos, sqrt, pi, ceil
import threading
from .utils import get_calibration_dir
from .utils.decorators import deprecated
from . import units
logger = logging.getLogger(__name__)
epsilon = 1.0e-6 # for floating point comparison
class Cell(object):
"""
This is a cell object, able to calculate the volume and d-spacing according to formula from:
http://geoweb3.princeton.edu/research/MineralPhy/xtalgeometry.pdf
"""
lattices = ["cubic", "tetragonal", "hexagonal", "rhombohedral", "orthorhombic", "monoclinic", "triclinic"]
types = {"P": "Primitive",
"I": "Body centered",
"F": "Face centered",
"C": "Side centered",
"R": "Rhombohedral"}
def __init__(self, a=1, b=1, c=1, alpha=90, beta=90, gamma=90, lattice="triclinic", lattice_type="P"):
"""Constructor of the Cell class:
Crystalographic units are Angstrom for distances and degrees for angles !
:param a,b,c: unit cell length in Angstrom
:param alpha, beta, gamma: unit cell angle in degrees
:param lattice: "cubic", "tetragonal", "hexagonal", "rhombohedral", "orthorhombic", "monoclinic", "triclinic"
:param lattice_type: P, I, F, C or R
"""
self.a = a
self.b = b
self.c = c
self.alpha = alpha
self.beta = beta
self.gamma = gamma
self.lattice = lattice if lattice in self.lattices else "triclinic"
self._volume = None
self.S11 = None
self.S12 = None
self.S13 = None
self.S22 = None
self.S23 = None
self.selection_rules = []
"contains a list of functions returning True(allowed)/False(forbiden)/None(unknown)"
self._type = "P"
self.set_type(lattice_type)
def __repr__(self, *args, **kwargs):
return "%s %s cell a=%.4f b=%.4f c=%.4f alpha=%.3f beta=%.3f gamma=%.3f" % \
(self.types[self.type], self.lattice, self.a, self.b, self.c, self.alpha, self.beta, self.gamma)
@classmethod
def cubic(cls, a, lattice_type="P"):
"""Factory for cubic lattices
:param a: unit cell length
"""
a = float(a)
self = cls(a, a, a, 90, 90, 90,
lattice="cubic", lattice_type=lattice_type)
return self
@classmethod
def tetragonal(cls, a, c, lattice_type="P"):
"""Factory for tetragonal lattices
:param a: unit cell length
:param c: unit cell length
"""
a = float(a)
self = cls(a, a, float(c), 90, 90, 90,
lattice="tetragonal", lattice_type=lattice_type)
return self
@classmethod
def orthorhombic(cls, a, b, c, lattice_type="P"):
"""Factory for orthorhombic lattices
:param a: unit cell length
:param b: unit cell length
:param c: unit cell length
"""
self = cls(float(a), float(b), float(c), 90, 90, 90,
lattice="orthorhombic", lattice_type=lattice_type)
return self
@classmethod
def hexagonal(cls, a, c, lattice_type="P"):
"""Factory for hexagonal lattices
:param a: unit cell length
:param c: unit cell length
"""
a = float(a)
self = cls(a, a, float(c), 90, 90, 120,
lattice="hexagonal", lattice_type=lattice_type)
return self
@classmethod
def monoclinic(cls, a, b, c, beta, lattice_type="P"):
"""Factory for hexagonal lattices
:param a: unit cell length
:param b: unit cell length
:param c: unit cell length
:param beta: unit cell angle
"""
self = cls(float(a), float(b), float(c), 90, float(beta), 90,
lattice_type=lattice_type, lattice="monoclinic")
return self
@classmethod
def rhombohedral(cls, a, alpha, lattice_type="P"):
"""Factory for hexagonal lattices
:param a: unit cell length
:param alpha: unit cell angle
"""
a = float(a)
alpha = float(a)
self = cls(a, a, a, alpha, alpha, alpha,
lattice="rhombohedral", lattice_type=lattice_type)
return self
@classmethod
def diamond(cls, a):
"""Factory for Diamond type FCC like Si and Ge
:param a: unit cell length
"""
self = cls.cubic(a, lattice_type="F")
self.selection_rules.append(lambda h, k, l: not((h % 2 == 0) and (k % 2 == 0) and (l % 2 == 0) and ((h + k + l) % 4 != 0)))
return self
@property
def volume(self):
if self._volume is None:
self._volume = self.a * self.b * self.c
if self.lattice not in ["cubic", "tetragonal", "orthorhombic"]:
cosa = cos(self.alpha * pi / 180.)
cosb = cos(self.beta * pi / 180.)
cosg = cos(self.gamma * pi / 180.)
self._volume *= sqrt(1 - cosa ** 2 - cosb ** 2 - cosg ** 2 + 2 * cosa * cosb * cosg)
return self._volume
def get_type(self):
return self._type
def set_type(self, lattice_type):
self._type = lattice_type if lattice_type in self.types else "P"
self.selection_rules = [lambda h, k, l: not(h == 0 and k == 0 and l == 0)]
if self._type == "I":
self.selection_rules.append(lambda h, k, l: (h + k + l) % 2 == 0)
if self._type == "F":
self.selection_rules.append(lambda h, k, l: (h % 2 + k % 2 + l % 2) in (0, 3))
if self._type == "R":
self.selection_rules.append(lambda h, k, l: ((h - k + l) % 3 == 0))
type = property(get_type, set_type)
def d(self, hkl):
"""
Calculate the actual d-spacing for a 3-tuple of integer representing a
family of Miller plans
:param hkl: 3-tuple of integers
:return: the inter-planar distance
"""
h, k, l = hkl
if self.lattice in ["cubic", "tetragonal", "orthorhombic"]:
invd2 = (h / self.a) ** 2 + (k / self.b) ** 2 + (l / self.c) ** 2
else:
if self.S11 is None:
alpha = self.alpha * pi / 180.
cosa = cos(alpha)
sina = sin(alpha)
beta = self.beta * pi / 180.
cosb = cos(beta)
sinb = sin(beta)
gamma = self.gamma * pi / 180.
cosg = cos(gamma)
sing = sin(gamma)
self.S11 = (self.b * self.c * sina) ** 2
self.S22 = (self.a * self.c * sinb) ** 2
self.S33 = (self.a * self.b * sing) ** 2
self.S12 = self.a * self.b * self.c * self.c * (cosa * cosb - cosg)
self.S23 = self.a * self.a * self.b * self.c * (cosb * cosg - cosa)
self.S13 = self.a * self.b * self.b * self.c * (cosg * cosa - cosb)
invd2 = (self.S11 * h * h +
self.S22 * k * k +
self.S33 * l * l +
2 * self.S12 * h * k +
2 * self.S23 * k * l +
2 * self.S13 * h * l)
invd2 /= (self.volume) ** 2
return sqrt(1 / invd2)
def d_spacing(self, dmin=1.0):
"""Calculate all d-spacing down to dmin
applies selection rules
:param dmin: minimum value of spacing requested
:return: dict d-spacing as string, list of tuple with Miller indices
preceded with the numerical value
"""
hmax = int(ceil(self.a / dmin))
kmax = int(ceil(self.b / dmin))
lmax = int(ceil(self.c / dmin))
res = {}
for hkl in itertools.product(range(-hmax, hmax + 1),
range(-kmax, kmax + 1),
range(-lmax, lmax + 1)):
# Apply selection rule
valid = True
for rule in self.selection_rules:
valid = rule(*hkl)
if not valid:
break
if not valid:
continue
d = self.d(hkl)
strd = "%.8e" % d
if d < dmin:
continue
if strd in res:
res[strd].append(hkl)
else:
res[strd] = [d, hkl]
return res
def save(self, name, long_name=None, doi=None, dmin=1.0, dest_dir=None):
"""Save informations about the cell in a d-spacing file, usable as Calibrant
:param name: name of the calibrant
:param doi: reference of the publication used to parametrize the cell
:param dmin: minimal d-spacing
:param dest_dir: name of the directory where to save the result
"""
fname = name + ".D"
if dest_dir:
fname = os.path.join(dest_dir, fname)
with open(fname, "w") as f:
if long_name:
f.write("# Calibrant: %s (%s)%s" % (long_name, name, os.linesep))
else:
f.write("# Calibrant: %s%s" % (name, os.linesep))
f.write("# %s%s" % (self, os.linesep))
if doi:
f.write("# Ref: %s%s" % (doi, os.linesep))
d = self.d_spacing(dmin)
ds = [i[0] for i in d.values()]
ds.sort(reverse=True)
for k in ds:
strk = "%.8e" % k
f.write("%.8f # %s %s%s" % (k, d[strk][-1], len(d[strk]) - 1, os.linesep))
class Calibrant(object):
"""
A calibrant is a reference compound where the d-spacing (interplanar distances)
are known. They are expressed in Angstrom (in the file)
"""
def __init__(self, filename=None, dSpacing=None, wavelength=None):
object.__init__(self)
self._filename = filename
self._wavelength = wavelength
self._sem = threading.Semaphore()
self._2th = []
if filename is not None:
self._dSpacing = None
elif dSpacing is None:
self._dSpacing = []
else:
self._dSpacing = list(dSpacing)
self._out_dSpacing = []
if self._dSpacing and self._wavelength:
self._calc_2th()
def __eq__(self, other):
"""
Test the equality with another object
It only takes into acount the wavelength and dSpacing, not the
filename.
:param object other: Another object
:rtype: bool
"""
if other is None:
return False
if not isinstance(other, Calibrant):
return False
if self._wavelength != other._wavelength:
return False
if self.dSpacing != other.dSpacing:
return False
return True
def __ne__(self, other):
"""
Test the non-equality with another object
It only takes into acount the wavelength and dSpacing, not the
filename.
:param object other: Another object
:rtype: bool
"""
return not (self == other)
def __hash__(self):
"""
Returns the hash of the object.
It only takes into acount the wavelength and dSpacing, not the
filename.
:rtype: int
"""
h = hash(self._wavelength)
for d in self.dSpacing:
h = h ^ hash(d)
return h
def __copy__(self):
"""
Copy a calibrant
:rtype: Calibrant
"""
self._initialize()
return Calibrant(filename=self._filename,
dSpacing=self._dSpacing + self._out_dSpacing,
wavelength=self._wavelength)
def __repr__(self):
name = "undefined"
if self._filename:
name = os.path.splitext(os.path.basename(self._filename))[0]
name += " Calibrant "
if len(self.dSpacing):
name += "with %i reflections " % len(self._dSpacing)
if self._wavelength:
name += "at wavelength %s" % self._wavelength
return name
def get_filename(self):
return self._filename
filename = property(get_filename)
def load_file(self, filename=None):
with self._sem:
self._load_file(filename)
def _load_file(self, filename=None):
if filename:
self._filename = filename
if not os.path.isfile(self._filename):
logger.error("No such calibrant file: %s", self._filename)
return
self._filename = os.path.abspath(self._filename)
self._dSpacing = numpy.unique(numpy.loadtxt(self._filename))
self._dSpacing = list(self._dSpacing[-1::-1]) # reverse order
# self._dSpacing.sort(reverse=True)
if self._wavelength:
self._calc_2th()
def _initialize(self):
"""Initialize the object if expected."""
if self._dSpacing is None:
if self._filename:
self._load_file()
else:
self._dSpacing = []
def count_registered_dSpacing(self):
"""Count of registered dSpacing positons."""
self._initialize()
return len(self._dSpacing) + len(self._out_dSpacing)
def save_dSpacing(self, filename=None):
"""
save the d-spacing to a file
"""
self._initialize()
if (filename is None) and (self._filename is not None):
filename = self._filename
else:
return
with open(filename) as f:
f.write("# %s Calibrant" % filename)
for i in self.dSpacing:
f.write("%s\n" % i)
def get_dSpacing(self):
self._initialize()
return self._dSpacing
def set_dSpacing(self, lst):
self._dSpacing = list(lst)
self._out_dSpacing = []
self._filename = "Modified"
if self._wavelength:
self._calc_2th()
dSpacing = property(get_dSpacing, set_dSpacing)
def append_dSpacing(self, value):
self._initialize()
with self._sem:
delta = [abs(value - v) / v for v in self._dSpacing if v is not None]
if not delta or min(delta) > epsilon:
self._dSpacing.append(value)
self._dSpacing.sort(reverse=True)
self._calc_2th()
def append_2th(self, value):
with self._sem:
self._initialize()
if value not in self._2th:
self._2th.append(value)
self._2th.sort()
self._calc_dSpacing()
def setWavelength_change2th(self, value=None):
with self._sem:
if value:
self._wavelength = float(value)
if self._wavelength < 1e-15 or self._wavelength > 1e-6:
logger.warning("This is an unlikely wavelength (in meter): %s", self._wavelength)
self._calc_2th()
def setWavelength_changeDs(self, value=None):
"""
This is probably not a good idea, but who knows !
"""
with self._sem:
if value:
self._wavelength = float(value)
if self._wavelength < 1e-15 or self._wavelength > 1e-6:
logger.warning("This is an unlikely wavelength (in meter): %s", self._wavelength)
self._calc_dSpacing()
def set_wavelength(self, value=None):
updated = False
with self._sem:
if self._wavelength is None:
if value:
self._wavelength = float(value)
if (self._wavelength < 1e-15) or (self._wavelength > 1e-6):
logger.warning("This is an unlikely wavelength (in meter): %s", self._wavelength)
updated = True
elif abs(self._wavelength - value) / self._wavelength > epsilon:
logger.warning("Forbidden to change the wavelength once it is fixed !!!!")
logger.warning("%s != %s, delta= %s", self._wavelength, value, self._wavelength - value)
if updated:
self._calc_2th()
def get_wavelength(self):
return self._wavelength
wavelength = property(get_wavelength, set_wavelength)
def _calc_2th(self):
"""Calculate the 2theta positions for all peaks"""
self._initialize()
if self._wavelength is None:
logger.error("Cannot calculate 2theta angle without knowing wavelength")
return
tths = []
dSpacing = self._dSpacing[:] + self._out_dSpacing # explicit copy
try:
for ds in dSpacing:
tth = 2.0 * asin(5.0e9 * self._wavelength / ds)
tths.append(tth)
except ValueError:
size = len(tths)
# remove dSpacing outside of 0..180
self._dSpacing = dSpacing[:size]
self._out_dSpacing = dSpacing[size:]
else:
self._dSpacing = dSpacing
self._out_dSpacing = []
self._2th = tths
def _calc_dSpacing(self):
if self._wavelength is None:
logger.error("Cannot calculate 2theta angle without knowing wavelength")
return
self._dSpacing = [5.0e9 * self._wavelength / sin(tth / 2.0) for tth in self._2th]
def get_2th(self):
"""Returns the 2theta positions for all peaks (cached)"""
if not self._2th:
self._initialize()
if not self._dSpacing:
logger.error("Not d-spacing for calibrant: %s", self)
with self._sem:
if not self._2th:
self._calc_2th()
return self._2th
def get_2th_index(self, angle, delta=None):
"""Returns the index in the 2theta angle index
:param angle: expected angle in radians
:param delta: precision on angle
:return: 0-based index or None
"""
if angle and angle in self._2th:
return self._2th.index(angle)
if delta:
d2th = abs(numpy.array(self._2th) - angle)
if d2th.min() < delta:
return d2th.argmin()
def get_max_wavelength(self, index=None):
"""Calculate the maximum wavelength assuming the ring at index is visible
Bragg's law says: $\\lambda = 2d sin(\\theta)$
So at 180° $\\lambda = 2d$
:param index: Ring number, otherwise assumes all rings are visible
:return: the maximum visible wavelength
"""
dSpacing = self._dSpacing[:] + self._out_dSpacing # get all rings
if index is None:
index = len(dSpacing) - 1
if index >= len(dSpacing):
raise IndexError("There are not than many (%s) rings indices in this calibrant" % (index))
return dSpacing[index] * 2e-10
def get_peaks(self, unit="2th_deg"):
"""Calculate the peak position as
:return: numpy array (unlike other methods which return lists)
"""
unit = units.to_unit(unit)
scale = unit.scale
name = unit.name
size = len(self.get_2th())
if name.startswith("2th"):
values = numpy.array(self.get_2th())
elif name.startswith("q"):
values = 20.0 * pi / numpy.array(self.get_dSpacing()[:size])
else:
raise ValueError("Only 2\theta and *q* units are supported for now")
return values * scale
def fake_calibration_image(self, ai, shape=None, Imax=1.0,
U=0, V=0, W=0.0001):
"""
Generates a fake calibration image from an azimuthal integrator
:param ai: azimuthal integrator
:param Imax: maximum intensity of rings
:param U, V, W: width of the peak from Caglioti's law (FWHM^2 = Utan(th)^2 + Vtan(th) + W)
"""
if shape is None:
if ai.detector.shape:
shape = ai.detector.shape
elif ai.detector.max_shape:
shape = ai.detector.max_shape
if shape is None:
raise RuntimeError("No shape available")
if (self.wavelength is None) and (ai._wavelength is not None):
self.wavelength = ai.wavelength
elif (self.wavelength is None) and (ai._wavelength is None):
raise RuntimeError("Wavelength needed to calculate 2theta position")
elif (self.wavelength is not None) and (ai._wavelength is not None) and\
abs(self.wavelength - ai.wavelength) > 1e-15:
logger.warning("Mismatch between wavelength for calibrant (%s) and azimutal integrator (%s)",
self.wavelength, ai.wavelength)
tth = ai.twoThetaArray(shape)
tth_min = tth.min()
tth_max = tth.max()
dim = int(numpy.sqrt(shape[0] * shape[0] + shape[1] * shape[1]))
tth_1d = numpy.linspace(tth_min, tth_max, dim)
tanth = numpy.tan(tth_1d / 2.0)
fwhm2 = U * tanth ** 2 + V * tanth + W
sigma2 = fwhm2 / (8.0 * numpy.log(2.0))
signal = numpy.zeros_like(sigma2)
for t in self.get_2th():
if t >= tth_max:
break
else:
signal += Imax * numpy.exp(-(tth_1d - t) ** 2 / (2.0 * sigma2))
res = ai.calcfrom1d(tth_1d, signal, shape=shape, mask=ai.mask,
dim1_unit='2th_rad', correctSolidAngle=True)
return res
def __getnewargs_ex__(self):
return (self._filename, self._dSpacing, self._wavelength), {}
def __getstate__(self):
state_blacklist = ('_sem',)
state = self.__dict__.copy()
for key in state_blacklist:
if key in state:
del state[key]
return state
def __setstate__(self, state):
for statekey, statevalue in state.items():
setattr(self, statekey, statevalue)
self._sem = threading.Semaphore()
class CalibrantFactory(object):
"""Behaves like a dict but is actually a factory:
Each time one retrieves an object it is a new geniune new calibrant (unmodified)
"""
def __init__(self, basedir=None):
"""
Constructor
:param basedir: directory name where to search for the calibrants
"""
if basedir is None:
basedir = get_calibration_dir()
self.directory = basedir
if not os.path.isdir(self.directory):
logger.warning("No calibrant directory: %s", self.directory)
self.all = {}
else:
self.all = dict([(os.path.splitext(i)[0], os.path.join(self.directory, i))
for i in os.listdir(self.directory)
if i.endswith(".D")])
def __call__(self, calibrant_name):
"""Returns a new instance of a calibrant by it's name."""
return Calibrant(self.all[calibrant_name])
def get(self, what, notfound=None):
if what in self.all:
return Calibrant(self.all[what])
else:
return notfound
def __contains__(self, k):
return k in self.all
def __repr__(self):
return "Calibrants available: %s" % (", ".join(list(self.all.keys())))
def __len__(self):
return len(self.all)
def keys(self):
return list(self.all.keys())
def values(self):
return [Calibrant(i) for i in self.all.values()]
def items(self):
return [(i, Calibrant(j)) for i, j in self.all.items()]
@deprecated # added on 2017-03-06
def __getitem__(self, calibration_name):
return self(calibration_name)
has_key = __contains__
CALIBRANT_FACTORY = CalibrantFactory()
"""Default calibration factory provided by the library."""
ALL_CALIBRANTS = CALIBRANT_FACTORY
@deprecated # added on 2017-03-06
class calibrant_factory(CalibrantFactory):
pass
def get_calibrant(calibrant_name):
"""Returns a new instance of the calibrant by it's name.
:param str calibrant_name: Name of the calibrant
"""
return CALIBRANT_FACTORY(calibrant_name)
def names():
"""Returns the list of registred calibrant names.
:rtype: str
"""
return CALIBRANT_FACTORY.keys()
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