[python-xrayutilities] 01/05: Imported Upstream version 1.1.2
Eugen Wintersberger
eugenwintersberger-guest at moszumanska.debian.org
Sat Apr 25 17:39:20 UTC 2015
This is an automated email from the git hooks/post-receive script.
eugenwintersberger-guest pushed a commit to branch master
in repository python-xrayutilities.
commit d70b227063f5879260b94246f5ea9ae52ad6a8fe
Author: Eugen Wintersberger <eugen.wintersberger at gmail.com>
Date: Sat Apr 25 13:02:16 2015 +0200
Imported Upstream version 1.1.2
---
CHANGES.txt | 9 +
PKG-INFO | 50 +-
README.txt | 41 +-
doc/source/_static/favicon.ico | Bin 2238 -> 4286 bytes
doc/source/conf.py | 11 +-
doc/source/examples.rst | 112 +-
doc/source/index.rst | 84 +-
doc/source/index.rst~ | 82 +-
doc/source/pics/favicon.ppm | 5 -
doc/source/pics/xray-logo-sf.png | Bin 4406 -> 0 bytes
doc/source/pics/xray-logo.png | Bin 11534 -> 17068 bytes
doc/source/pics/xu_usage.png | Bin 27536 -> 25172 bytes
doc/source/pics/xu_usage.svg | 569 +-
doc/source/pics/xu_usage_inkscape.svg | 414 +
doc/source/pics/xu_usage_planning.png | Bin 20586 -> 17437 bytes
doc/source/pics/xu_usage_planning.svg | 457 +-
doc/source/pics/xu_usage_planning_inkscape.svg | 303 +
examples/data/04-003-0996.cif | 8060 ------------
examples/data/1216385.cif | 166 -
examples/data/BaF2.cif | 456 +-
examples/data/Calcite.cif | 144 +-
examples/data/Silicon.cif | 454 +-
examples/data/bi2te3.cif | 176 +-
examples/xrayutilities_export_data2vtk.py | 164 +-
examples/xrayutilities_hotpixelkill_variant.py | 132 +-
examples/xrayutilities_kmap_example_ESRF.py | 202 +-
examples/xrayutilities_user.conf | 18 +-
setup.py | 11 +-
xrayutilities.pdf | 14147 +++++++++++-----------
xrayutilities/analysis/sample_align.py | 64 +-
xrayutilities/experiment.py | 47 +-
xrayutilities/gridder2d.py | 3 +-
xrayutilities/io/__init__.py | 1 +
xrayutilities/io/edf.py | 34 +-
xrayutilities/io/fastscan.py | 1544 +--
xrayutilities/io/helper.py | 5 +-
xrayutilities/io/spec.py | 77 +-
xrayutilities/materials/cif.py | 4 +-
xrayutilities/materials/data/README.txt~ | 13 -
xrayutilities/materials/material.py | 177 +-
xrayutilities/materials/predefined_materials.py | 4 +
xrayutilities/math/fit.py | 31 +-
xrayutilities/math/functions.py | 5 +-
xrayutilities/src/qconversion.h~ | 131 -
xrayutilities/utilities_noconf.py | 70 +-
xrayutilities/xrayutilities_default.conf | 2 +-
46 files changed, 10337 insertions(+), 18142 deletions(-)
diff --git a/CHANGES.txt b/CHANGES.txt
index c6397a8..3a75c72 100644
--- a/CHANGES.txt
+++ b/CHANGES.txt
@@ -1,3 +1,12 @@
+v1.1.2, 2015-04-22
+
+* new webpage theme to allow for easier reading (esp. mobile devices)
+* huge set of improvements for working with FastScans (ESRF ID01)
+* keep_open option in EDFFile to speed up reading of multiple images
+* new convenience function for parsing data from spec-files
+* improve peak position finding in area-detector calibration
+* added new material AlAs
+
v1.1.1, 2015-01-22
* new PseudoVoigt1dasym function implementing an asymmetric PseudoVoigt peak
diff --git a/PKG-INFO b/PKG-INFO
index 527e228..e2c4645 100644
--- a/PKG-INFO
+++ b/PKG-INFO
@@ -1,6 +1,6 @@
Metadata-Version: 1.1
Name: xrayutilities
-Version: 1.1.1
+Version: 1.1.2
Summary: package for x-ray diffraction data evaluation
Home-page: http://xrayutilities.sourceforge.net
Author: Dominik Kriegner
@@ -11,10 +11,10 @@ Description:
xrayutilities
=============
- xrayutilities is a collection of scripts used to analyze x-ray diffraction data.
- It consists of a Python package and several routines coded in C. It especially
- useful for the reciprocal space conversion of diffraction data taken with linear
- and area detectors.
+ xrayutilities is a collection of scripts used to analyze x-ray diffraction
+ data. It consists of a Python package and several routines coded in C. It is
+ especially useful for the reciprocal space conversion of diffraction data
+ taken with linear and area detectors.
Copyright (C) 2009-2015 Dominik Kriegner <dominik.kriegner at gmail.com>
@@ -62,7 +62,7 @@ Description:
- matplotlib (optionally)
refer to your operating system documentation to find out how to install
- those packages. On Microsoft Windows refer to the Documentation for the
+ those packages. On Microsoft Windows refer to the Documentation for the
easiest way of the installation (Python(x,y) or WinPython).
On Microsoft Windows it might be necessary to manually
@@ -79,29 +79,29 @@ Description:
Python-3 if possible, however, xrayutilies can be used with Python-2.7 as well.
Care was taken to make this possible from the same code-base
- The python package configuration
+ The Python package configuration
================================
The following steps should only be necessary for user local installation to
ensure the Python module is found by the Python interpreter:
- In this case the module is installed under
+ In this case the module is installed under
<prefix>/lib[64]/python?.?/site-packages on Unix systems and
- <prefix>/Lib/site-packages on Windows systems.
+ <prefix>/Lib/site-packages on Windows systems.
If you have installed the Python package in a directory unknown to your local
Python distribution, you have to tell Python where to look for the Package.
There are several ways how to do this:
- - add the directory where the package is installed to your
+ - add the directory where the package is installed to your
*PYTHONPATH* environment variable.
- - add the path to sys.path in the .pythonrc file placed in your home
+ - add the path to sys.path in the .pythonrc file placed in your home
directory ::
import sys
sys.path.append("path to the xrayutilities package")
- - simply apply the previous method in every script where you want to
+ - simply apply the previous method in every script where you want to
use the xrayutilities package before importing the package ::
import sys
@@ -116,7 +116,7 @@ Description:
$> git clone git://git.code.sf.net/p/xrayutilities/code xrayutilities
- to clone the git repository. If you would like to have commit rights
+ to clone the git repository. If you would like to have commit rights
contact one of the administrators.
UPDATE
@@ -126,7 +126,7 @@ Description:
its source folder and obtain the new sources by ::
$> git pull
-
+
or download the new tarball from sourceforge
(http://sf.net/projects/xrayutilities) if any code changed during the update you
need to reinstall the Python package. To determine the path in which
@@ -148,26 +148,25 @@ Description:
=============
Documention for xrayutilities is found in the xrayutilities.pdf file or on the
- webpage http://xrayutilities.sourceforge.net
+ webpage http://xrayutilities.sourceforge.net
The API-documentation can also be browsed by ::
$> pydoc -p PORT
-
+
in any web-browser, after the installation is finished.
To build the PDF documentation from the docu-sources use:
- python setup.py build_doc -b latex
- cd build/sphinx/latex; make
-
- You will need sphinx and pdflatex including latex-recommended, latex-extra
+ $> python setup.py build build_doc -b pdf
+
+ You will need sphinx and pdflatex including latex-recommended, latex-extra
and fonts-recommended.
- Or generate a texinfo file using
+ Or generate a texinfo file using
python setup.py build_doc -b texinfo
- cd build/sphinx/texinfo; make
+ cd build/sphinx/texinfo; make
PACKAGING
@@ -183,9 +182,14 @@ Description:
Platform: UNKNOWN
+Classifier: Programming Language :: C
+Classifier: Programming Language :: Python :: 2.7
+Classifier: Programming Language :: Python :: 3.2
+Classifier: Programming Language :: Python :: 3.3
+Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Intended Audience :: Science/Research
-Classifier: Development Status :: 4 - Beta
+Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)
Requires: numpy
Requires: scipy
diff --git a/README.txt b/README.txt
index e3b52a8..10a1ba0 100644
--- a/README.txt
+++ b/README.txt
@@ -3,10 +3,10 @@
xrayutilities
=============
-xrayutilities is a collection of scripts used to analyze x-ray diffraction data.
-It consists of a Python package and several routines coded in C. It especially
-useful for the reciprocal space conversion of diffraction data taken with linear
-and area detectors.
+xrayutilities is a collection of scripts used to analyze x-ray diffraction
+data. It consists of a Python package and several routines coded in C. It is
+especially useful for the reciprocal space conversion of diffraction data
+taken with linear and area detectors.
Copyright (C) 2009-2015 Dominik Kriegner <dominik.kriegner at gmail.com>
@@ -54,7 +54,7 @@ system
- matplotlib (optionally)
refer to your operating system documentation to find out how to install
-those packages. On Microsoft Windows refer to the Documentation for the
+those packages. On Microsoft Windows refer to the Documentation for the
easiest way of the installation (Python(x,y) or WinPython).
On Microsoft Windows it might be necessary to manually
@@ -71,29 +71,29 @@ The current developement focues Python-3.X and we ask all users to update to
Python-3 if possible, however, xrayutilies can be used with Python-2.7 as well.
Care was taken to make this possible from the same code-base
-The python package configuration
+The Python package configuration
================================
The following steps should only be necessary for user local installation to
ensure the Python module is found by the Python interpreter:
-In this case the module is installed under
+In this case the module is installed under
<prefix>/lib[64]/python?.?/site-packages on Unix systems and
-<prefix>/Lib/site-packages on Windows systems.
+<prefix>/Lib/site-packages on Windows systems.
If you have installed the Python package in a directory unknown to your local
Python distribution, you have to tell Python where to look for the Package.
There are several ways how to do this:
-- add the directory where the package is installed to your
+- add the directory where the package is installed to your
*PYTHONPATH* environment variable.
-- add the path to sys.path in the .pythonrc file placed in your home
+- add the path to sys.path in the .pythonrc file placed in your home
directory ::
import sys
sys.path.append("path to the xrayutilities package")
-- simply apply the previous method in every script where you want to
+- simply apply the previous method in every script where you want to
use the xrayutilities package before importing the package ::
import sys
@@ -108,7 +108,7 @@ Use ::
$> git clone git://git.code.sf.net/p/xrayutilities/code xrayutilities
-to clone the git repository. If you would like to have commit rights
+to clone the git repository. If you would like to have commit rights
contact one of the administrators.
UPDATE
@@ -118,7 +118,7 @@ if you already installed xrayutilities you can update it by navigating into
its source folder and obtain the new sources by ::
$> git pull
-
+
or download the new tarball from sourceforge
(http://sf.net/projects/xrayutilities) if any code changed during the update you
need to reinstall the Python package. To determine the path in which
@@ -140,26 +140,25 @@ DOCUMENTATION
=============
Documention for xrayutilities is found in the xrayutilities.pdf file or on the
-webpage http://xrayutilities.sourceforge.net
+webpage http://xrayutilities.sourceforge.net
The API-documentation can also be browsed by ::
$> pydoc -p PORT
-
+
in any web-browser, after the installation is finished.
To build the PDF documentation from the docu-sources use:
- python setup.py build_doc -b latex
- cd build/sphinx/latex; make
-
-You will need sphinx and pdflatex including latex-recommended, latex-extra
+ $> python setup.py build build_doc -b pdf
+
+You will need sphinx and pdflatex including latex-recommended, latex-extra
and fonts-recommended.
-Or generate a texinfo file using
+Or generate a texinfo file using
python setup.py build_doc -b texinfo
- cd build/sphinx/texinfo; make
+ cd build/sphinx/texinfo; make
PACKAGING
diff --git a/doc/source/_static/favicon.ico b/doc/source/_static/favicon.ico
index 0c19de2..944b149 100644
Binary files a/doc/source/_static/favicon.ico and b/doc/source/_static/favicon.ico differ
diff --git a/doc/source/conf.py b/doc/source/conf.py
index 5038d4f..f71467c 100644
--- a/doc/source/conf.py
+++ b/doc/source/conf.py
@@ -14,6 +14,8 @@
import sys
import os
+import sphinx_rtd_theme
+import re
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
@@ -60,7 +62,7 @@ copyright = u'2015, Dominik Kriegner, Eugen Wintersberger'
# The short X.Y version.
version = '1.1'
# The full version, including alpha/beta/rc tags.
-release = '1.1.1'
+release = '1.1.2'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
@@ -102,12 +104,13 @@ pygments_style = 'sphinx'
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
-html_theme = 'nature'
+html_theme = "sphinx_rtd_theme"
+html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
# 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 = {'sidebarwidth': 280}
+html_theme_options = {'logo_only': True}
# Add any paths that contain custom themes here, relative to this directory.
# html_theme_path = []
@@ -361,8 +364,6 @@ pdf_default_dpi = 120
# my additions for pre-processing the docstring
# parameter list of functions should be found and changed to be properly
# formated in the output
-import re
-
def process_docstring(app, what, name, obj, options, lines):
# highlight parameters names
diff --git a/doc/source/examples.rst b/doc/source/examples.rst
index ab4f9df..ac7d080 100644
--- a/doc/source/examples.rst
+++ b/doc/source/examples.rst
@@ -18,11 +18,11 @@ various formats. In the following few examples are given.
Reading SPEC files
^^^^^^^^^^^^^^^^^^
-Working with spec files in *xrayutilities* can be done in two distinct ways.
+Working with spec files in *xrayutilities* can be done in two distinct ways.
1. parsing the spec file for scan headers; and parsing the data only when needed
- 2. parsing the spec file for scan headers; parsing all data and dump them to an HDF5 file; reading the data from the HDF5 file.
+ 2. parsing the spec file for scan headers; parsing all data and dump them to an HDF5 file; reading the data from the HDF5 file.
-Both methods have their pros and cons. For example when you parse the spec-files over a network connection you need to re-read the data again over the network if using method 1) whereas you can dump them to a local file with method 2). But you will parse data of the complete file while dumping it to the HDF5 file.
+Both methods have their pros and cons. For example when you parse the spec-files over a network connection you need to re-read the data again over the network if using method 1) whereas you can dump them to a local file with method 2). But you will parse data of the complete file while dumping it to the HDF5 file.
Both methods work incremental, so they do not start at the beginning of the file when you reread it, but start from the last position they were reading and work with files including data from linear detectors.
@@ -31,16 +31,16 @@ An working example for both methods is given in the following.::
import tables
import xrayutilities as xu
import os
-
+
# open spec file or use open SPECfile instance
try: s
except NameError:
s = xu.io.SPECFile("sample_name.spec", path="./specdir")
-
+
# method (1)
s.scan10.ReadData()
scan10data = s.scan10.data
-
+
# method (2)
h5file = os.path.join("h5dir", "h5file.h5")
s.Save2HDF5(h5file) # save content of SPEC file to HDF5 file
@@ -58,11 +58,11 @@ In the following it is shown how to re-parsing the SPEC file for new scans and r
::
s.Update() # reparse for new scans in open SPECFile instance
-
+
# reread data method (1)
s.scan10.ReadData()
- scan10data = s.scan10.data
-
+ scan10data = s.scan10.data
+
# reread data method (2)
s.Save2HDF5(h5) # save content of SPEC file to HDF5 file
# read data from HDF5 file
@@ -76,17 +76,17 @@ Reading EDF files
EDF files are mostly used to store CCD frames at ESRF recorded from various different detectors. This format is therefore used in combination with SPEC files. In an example the EDFFile class is used to parse the data from EDF files and store them to an HDF5 file. HDF5 if perfectly suited because it can handle large amount of data and compression.::
- import tables
+ import tables
import xrayutilities as xu
import numpy
-
+
specfile = "specfile.spec"
h5file = "h5file.h5"
h5 = tables.openFile(h5file, mode='a')
-
+
s = xu.io.SPECFile(specfile, path=specdir)
s.Save2HDF5(h5) # save to hdf5 file
-
+
# read ccd frames from EDF files
for i in range(1, 1000, 1):
efile = "edfdir/sample_%04d.edf" %i
@@ -94,7 +94,7 @@ EDF files are mostly used to store CCD frames at ESRF recorded from various diff
e.ReadData()
g5 = h5.createGroup(h5.root, "frelon_%04d" %i)
e.Save2HDF5(h5, group=g5)
-
+
h5.close()
.. seealso::
@@ -106,7 +106,7 @@ Other formats
Other formats which can be read include
- * files recorded from `Panalytical <http://www.panalytical.com>`_ diffractometers in the ``.xrdml`` format.
+ * files recorded from `Panalytical <http://www.panalytical.com>`_ diffractometers in the ``.xrdml`` format.
* files produces by the experimental control software at Hasylab/Desy (spectra).
* ccd images in the tiff file format produced by RoperScientific CCD cameras and Perkin Elmer detectors.
* files from recorded by Seifert diffractometer control software (``.nja``)
@@ -123,7 +123,7 @@ Methods for high angle x-ray diffraction experiments. Mostly for experiments per
import xrayutilities as xu
Si = xu.materials.Si # load material from materials submodule
-
+
# initialize experimental class with directions from experiment
hxrd = xu.HXRD(Si.Q(1, 1, -2), Si.Q(1, 1, 1))
# calculate angles of Bragg reflections and print them to the screen
@@ -158,19 +158,19 @@ There exists also a powder diffraction class, which is able to convert powder sc
import xrayutilities as xu
import matplotlib.pyplot as plt
-
+
energy = (2 * 8048 + 8028) / 3. # copper k alpha 1,2
-
- # creating Indium powder
+
+ # creating Indium powder
In_powder = xu.Powder(xu.materials.In, en=energy)
# calculating the reflection strength for the powder
In_powder.PowderIntensity()
-
+
# convoluting the peaks with a gaussian in q-space
peak_width = 0.01 # in q-space
resolution = 0.0005 # resolution in q-space
In_th,In_int = In_powder.Convolute(resolution, peak_width)
-
+
plt.figure()
plt.xlabel(r"2Theta (deg)"); plt.ylabel(r"Intensity")
# plot the convoluted signal
@@ -180,13 +180,13 @@ There exists also a powder diffraction class, which is able to convert powder sc
plt.bar(In_powder.ang * 2, In_powder.data / In_powder.data.max(),
width=0.3, bottom=0, linewidth=0, color='r',
align='center', orientation='vertical', label="Indium bar plot")
-
+
plt.legend(); plt.set_xlim(15, 100); plt.grid()
One can also print the peak positions and other informations of a powder by
>>> print In_powder
- Powder diffraction object
+ Powder diffraction object
-------------------------
Material: In
Lattice:
@@ -197,7 +197,7 @@ One can also print the peak positions and other informations of a powder by
Lattice base:
Base point 0: In (49) (0.000000 0.000000 0.000000) occ=1.00 b=0.00
Base point 1: In (49) (0.500000 0.500000 0.500000) occ=1.00 b=0.00
- Reflections:
+ Reflections:
--------------
h k l | tth | |Q| | Int | Int (%)
---------------------------------------------------------------
@@ -210,17 +210,17 @@ One can also print the peak positions and other informations of a powder by
Using the ``Gridder`` classes
-----------------------------
-*xrayutilities* provides Gridder classes for 1D, 2D, and 3D data sets. These Gridders map irregular spaced data onto a regular grid.
+*xrayutilities* provides Gridder classes for 1D, 2D, and 3D data sets. These Gridders map irregular spaced data onto a regular grid.
This is often needed after transforming data measured at equally spaced angular positions to reciprocal space were their spacing is irregular.
-In 1D this process actually equals the calculation of a histogramm.
+In 1D this process actually equals the calculation of a histogram.
Below you find the most basic way of using the Gridder in 2D. Other dimensions work very similar.
The most easiest use (what most user might need) is:
::
- import xrayutilities as xu # import python package
- g = xu.Gridder2D(100, 101) # initialize the Gridder object, which will
+ import xrayutilities as xu # import Python package
+ g = xu.Gridder2D(100, 101) # initialize the Gridder object, which will
# perform Gridding to a regular grid with 100x101 points
#====== load some data here =====
g(x, y, data) # call the gridder with the data
@@ -228,10 +228,10 @@ The most easiest use (what most user might need) is:
_.. note: previously you could use the Gridder's gdata object, which was always an internal buffer and should not be used anymore!
-A more complicated example showing also sequential gridding is shown below. You need sequential gridding when you can not load all data at the same time, which is often problematic with 3D data sets. In such cases you need to specify the data range before the first call to the gridder.
+A more complicated example showing also sequential gridding is shown below. You need sequential gridding when you can not load all data at the same time, which is often problematic with 3D data sets. In such cases you need to specify the data range before the first call to the gridder.
::
- import xrayutilities as xu # import python package
+ import xrayutilities as xu # import Python package
g = xu.Gridder2D(100, 101) # initialize the Gridder object
g.KeepData(True)
g.dataRange(1, 2, 3, 4) # (xgrd_min, xgrd_max, ygrd_min, ygrd_max)
@@ -247,7 +247,7 @@ A more complicated example showing also sequential gridding is shown below. You
Using the ``material`` class
----------------------------
-*xrayutilities* provides a set of python classes to describe crystal lattices and
+*xrayutilities* provides a set of Python classes to describe crystal lattices and
materials.
Examples show how to define a new material by defining its lattice and deriving a new material, furthermore materials can be used to calculate the structure factor of a Bragg reflection for an specific energy or the energy dependency of its structure factor for anomalous scattering. Data for this are taken from a database which is included in the download.
@@ -255,7 +255,7 @@ Examples show how to define a new material by defining its lattice and deriving
First defining a new material from scratch is shown. This consists of an lattice with base and the type of atoms with elastic constants of the material::
import xrayutilities as xu
-
+
# defining a ZincBlendeLattice with two types of atoms
# and lattice constant a
def ZincBlendeLattice(aa, ab, a):
@@ -269,23 +269,23 @@ First defining a new material from scratch is shown. This consists of an lattice
lb.append(ab, [0.75, 0.75, 0.25])
lb.append(ab, [0.75, 0.25, 0.75])
lb.append(ab, [0.25, 0.75, 0.75])
-
+
#create lattice vectors
a1 = [a, 0, 0]
a2 = [0, a, 0]
a3 = [0, 0, a]
-
- l = xu.materials.Lattice(a1, a2, a3, base=lb)
+
+ l = xu.materials.Lattice(a1, a2, a3, base=lb)
return l
-
- # defining InP, no elastic properties are given,
+
+ # defining InP, no elastic properties are given,
# helper functions exist to create the (6, 6) elastic tensor
- # for cubic materials
+ # for cubic materials
atom_In = xu.materials.elements.In
atom_P = xu.materials.elements.P
elastictensor = xu.materials.CubicElasticTensor(10.11e+10, 5.61e+10,
4.56e+10)
- InP = xu.materials.Material("InP",
+ InP = xu.materials.Material("InP",
ZincBlendeLattice(atom_In, atom_P, 5.8687),
elastictensor)
@@ -301,11 +301,11 @@ Using the material properties the calculation of the reflection strength of a Br
import xrayutilities as xu
import numpy
-
+
# defining material and experimental setup
InAs = xu.materials.InAs
energy= 8048 # eV
-
+
# calculate the structure factor for InAs (111) (222) (333)
hkllist = [[1, 1, 1], [2, 2, 2], [3, 3, 3]]
for hkl in hkllist:
@@ -317,10 +317,10 @@ Using the material properties the calculation of the reflection strength of a Br
Similar also the energy dependence of the structure factor can be determined::
import matplotlib.pyplot as plt
-
+
energy= numpy.linspace(500, 20000, 5000) # 500 - 20000 eV
F = InAs.StructureFactorForEnergy(InAs.Q(1, 1, 1), energy)
-
+
plt.figure(); plt.clf()
plt.plot(energy, F.real, 'k-', label='Re(F)')
plt.plot(energy, F.imag, 'r-', label='Imag(F)')
@@ -333,7 +333,7 @@ It is also possible to calculate the components of the structure factor of atoms
# f = f0(|Q|) + f1(en) + j * f2(en)
import xrayutilities as xu
import numpy
-
+
Fe = xu.materials.elements.Fe # iron atom
Q = numpy.array([0, 0, 1.9], dtype=numpy.double)
en = 10000 # energy in eV
@@ -350,9 +350,9 @@ Calculation of diffraction angles for a general geometry
Often the restricted predefined geometries are not corresponding to the experimental setup, nevertheless *xrayutilities* is able to calculate the goniometer angles needed to reach a certain reciprocal space position.
For this purpose the goniometer together with the geometric restrictions need to be defined and the q-vector in laboratory reference frame needs to be specified.
-This works for arbitrary goniometer, however, the user is expected to set up bounds to put restrictions to the number of free angles to obtain reproducible results.
+This works for arbitrary goniometer, however, the user is expected to set up bounds to put restrictions to the number of free angles to obtain reproducible results.
In general only three angles are needed to fit an arbitrary q-vector (2 sample + 1 detector angles or
-1 sample + 2 detector).
+1 sample + 2 detector).
The example below shows the necessary code to perform such an angle calculation for a costum defined material with orthorhombic unit cell.
@@ -375,7 +375,7 @@ The example below shows the necessary code to perform such an angle calculation
hkl=(2, 0, 0)
q_material = SmFeO3.Q(hkl)
- q_laboratory = hxrd.Transform(q_material) # transform
+ q_laboratory = hxrd.Transform(q_material) # transform
print('SmFeO3: \thkl ', hkl, '\tqvec ', np.round(q_material, 5))
print('Lattice plane distance: %.4f' % SmFeO3.planeDistance(hkl))
@@ -388,7 +388,7 @@ The example below shows the necessary code to perform such an angle calculation
ang,qerror,errcode = xu.Q2AngFit(q_laboratory, hxrd, bounds)
print('err %d (%.3g) angles %s' % (errcode, qerror, str(np.round(ang, 5))))
# check that qerror is small!!
- print('sanity check with back-transformation (hkl): ',
+ print('sanity check with back-transformation (hkl): ',
np.round(hxrd.Ang2HKL(*ang,mat=SmFeO3),5))
@@ -398,7 +398,7 @@ User-specific config file
Several options of *xrayutilities* can be changed by options in a config file. This includes the default x-ray energy as well as parameters to set the number of threads used by the parallel code and the verbosity of the output.
The default options are stored inside the installad Python module and should not be changed. Instead it is suggested to use a user-specific config file
-'~/.xrayutilities.conf' or a 'xrayutilities.conf' file in the working directory.
+'~/.xrayutilities.conf' or a 'xrayutilities.conf' file in the working directory.
An example of such a user config file is shown below:
@@ -415,7 +415,7 @@ An example of such a user config file is shown below:
# levels can be changed in the config file as well
verbosity = 1
- # default wavelength in Angstrom,
+ # default wavelength in Angstrom,
wavelength = MoKa1 # Molybdenum K alpha1 radiation (17479.374eV)
# default energy in eV
@@ -426,7 +426,7 @@ An example of such a user config file is shown below:
nthreads = 1
# 0: the maximum number of available threads will be used (as returned by
# omp_get_max_threads())
- # n: n-threads will be used
+ # n: n-threads will be used
@@ -480,26 +480,26 @@ A possible output of this script could be
.. code-block:: python
fitted parameters: epsilon: 8.0712e-08 (2,['Parameter convergence'])
- param: (cch1,cch2,pwidth1,pwidth2,tiltazimuth,tilt,detrot,outerangle_offset)
+ param: (cch1,cch2,pwidth1,pwidth2,tiltazimuth,tilt,detrot,outerangle_offset)
param: 140.07 998.34 4.4545e-05 4.4996e-05 72.0 1.97 -0.792 -1.543
please check the resulting data (consider setting plot=True)
detector rotation axis / primary beam direction (given by user): ['z+', 'y-'] / x+
detector pixel directions / distance: z- y+ / 1
- detector initialization with: init_area('z-', 'y+', cch1=140.07,
+ detector initialization with: init_area('z-', 'y+', cch1=140.07,
cch2=998.34, Nch1=516, Nch2=516, pwidth1=4.4545e-05, pwidth2=4.4996e-05,
distance=1., detrot=-0.792, tiltazimuth=72.0, tilt=1.543)
AND ALWAYS USE an (additional) OFFSET of -1.9741deg in the OUTER DETECTOR ANGLE!
-The output gives the fitted detector parameters and compiles the python code line one needs to use to initialize the detector.
-Important to note is that the outer angle offset which was determined by the fit (-1.9741 degree in the aboves example) is not included in the initialization of the detector parameters *but* needs to be used in every call to the q-conversion function as offset.
+The output gives the fitted detector parameters and compiles the Python code line one needs to use to initialize the detector.
+Important to note is that the outer angle offset which was determined by the fit (-1.9741 degree in the aboves example) is not included in the initialization of the detector parameters *but* needs to be used in every call to the q-conversion function as offset.
This step needs to be performed manually by the user!
Area detector (Variant 2)
^^^^^^^^^^^^^^^^^^^^^^^^^
In addition to scans in the primary beam this variant enables also the use of detector images recorded in scans at Bragg reflections of a known reference materials. However this also required that the sample orientation and x-ray wavelength need to be fit.
-To keep the additional parameters as small as possible we only implemented this for symmetric coplanar diffractions.
+To keep the additional parameters as small as possible we only implemented this for symmetric coplanar diffractions.
The advantage of this method is that it is more sensitive to the outer angle offset also at large detector distances.
The additional parameters are:
diff --git a/doc/source/index.rst b/doc/source/index.rst
index 622a5bc..0b0d0f9 100644
--- a/doc/source/index.rst
+++ b/doc/source/index.rst
@@ -11,7 +11,7 @@ Installation instructions you find further down `Installation`_.
Read more about *xrayutilities* below or in `Journal of Applied Crystallography 2013, Volume 46, 1162-1170 <http://dx.doi.org/10.1107/S0021889813017214>`_
-
+
Introduction
============
@@ -30,25 +30,25 @@ Concept of usage
:align: right
:alt: Flow diagram showing how to analyze x-ray diffraction data using xrayutilities
-*xrayutilities* provides a set of functions to read experimental data from various data file formats.
+*xrayutilities* provides a set of functions to read experimental data from various data file formats.
All of them are gathered in the :mod:`io`-subpackage.
-After reading data with a function from the io-submodule the data might be corrected for monitor counts and/or absorption factor of a beam attenuator.
+After reading data with a function from the io-submodule the data might be corrected for monitor counts and/or absorption factor of a beam attenuator.
A special set of functions is provided to perform this for point, linear and area detectors.
-Since the amount of data taken with modern detectors often is too large to be able to work with them properly, a functions for reducing the data from linear and area detectors are provided.
-They use block-averaging to reduce the amount of data.
+Since the amount of data taken with modern detectors often is too large to be able to work with them properly, a functions for reducing the data from linear and area detectors are provided.
+They use block-averaging to reduce the amount of data.
Use those carefully not to loose the features you are interested in in your measurements.
-After the pre-treatment of the data, the core part of the package is the transformation of the angular data to reciprocal space.
-This is done as described in more detail below using the :mod:`experiment`-module`.
+After the pre-treatment of the data, the core part of the package is the transformation of the angular data to reciprocal space.
+This is done as described in more detail below using the :mod:`experiment`-module`.
The classes provided within the experiment module provide routines to help performing X-ray diffraction experiments.
This includes methods to calculate the diffraction angles (described below) needed to align crystalline samples and to convert data between angular and reciprocal space.
-The conversion from angular to reciprocal space is implemented very general for various goniometer geometries.
-It is especially useful in combination with linear and area detectors as described in this `article <http://dx.doi.org/10.1107/S0021889813017214>`_.
+The conversion from angular to reciprocal space is implemented very general for various goniometer geometries.
+It is especially useful in combination with linear and area detectors as described in this `article <http://dx.doi.org/10.1107/S0021889813017214>`_.
In standard cases, Users will only need the initialized routines, which predefine a certain goniometer geometry like the popular four-cirlce and six-circle geometries.
-After the conversion to reciprocal space, it is convenient to transform the data to a regular grid for visualization.
-For this purpose the :mod:`gridder`-module has been included into *xrayutilities*.
+After the conversion to reciprocal space, it is convenient to transform the data to a regular grid for visualization.
+For this purpose the :mod:`gridder`-module has been included into *xrayutilities*.
For the visualization of the data in reciprocal space the usage of `matplotlib <http://matplotlib.org>`_ is recommended.
A practical example showing the usage is given below.
@@ -63,11 +63,11 @@ Angle calculation using the material classes
Calculation of angles needed to align Bragg reflections in various diffraction geometries is done using the Materials defined in the :mod:`materials`-package.
This package provides a set of classes to describe crystal lattices and materials.
-Once such a material is properly defined one can calculate its properties, which includes the reciprocal lattice points, lattice plane distances, optical properties like
+Once such a material is properly defined one can calculate its properties, which includes the reciprocal lattice points, lattice plane distances, optical properties like
the refractive index, the structure factor (including the atomic scattering factor) and the complex polarizability.
These atomic properties are extracted from a database included in *xrayutilities*.
-Using such a material and an experimental class from the :mod:`experiment`-module, describing the experimental setup, the needed diffraction angles can be calculated for certain coplanar diffraction (high, low incidence), grazing incidence diffraction and also special non-coplanar diffraction geometries.
+Using such a material and an experimental class from the :mod:`experiment`-module, describing the experimental setup, the needed diffraction angles can be calculated for certain coplanar diffraction (high, low incidence), grazing incidence diffraction and also special non-coplanar diffraction geometries.
In the predefined experimental classes fixed geometries are used. For angle calculation of custom geometries using arbitrary geometries (max. of three free angles) the :mod:`q2ang_fit`-module can be used as described in one of the included example files.
.. _helloworld:
@@ -107,10 +107,10 @@ Express instructions
* open a command line and navigate to the downloaded sources and execute:
.. code-block:: bash
-
+
> python setup.py install
-which will install *xrayutilities* to the default directory. It should be possible to use it (*import xrayutilities*) from now on in python scripts.
+which will install *xrayutilities* to the default directory. It should be possible to use it (*import xrayutilities*) from now on in python scripts.
.. note:: The python package of *xrayutilities* was formerly called ''xrutils''
@@ -119,16 +119,16 @@ Detailed instructions
Installing *xrayutilities* is done using Python's distutils
-The package can be installed on Linux, Mac OS X and Microsoft Windows, however, it is mostly tested on Linux/Unix platforms.
+The package can be installed on Linux, Mac OS X and Microsoft Windows, however, it is mostly tested on Linux/Unix platforms.
Please inform one of the authors in case the installation fails!
Required third party software
-----------------------------
-To keep the coding effort as small as possible *xrayutilities* depends on a
-large number of third party libraries and Python modules.
+To keep the coding effort as small as possible *xrayutilities* depends on a
+large number of third party libraries and Python modules.
-The needed dependencies are:
+The needed dependencies are:
* **GCC** Gnu Compiler Collection or any compatible C compiler. On windows you most probably should use MinGW or CygWin. Others might work but are untested.
* **HDF5** a versatile binary data format (library is implemented in C).
Although the library is not called directly, it is needed by the pytables Python
@@ -139,7 +139,7 @@ The needed dependencies are:
Additionally, the following Python modules are needed in order to make *xrayutilities* work as intended:
* **Numpy** a Python module providing numerical array objects
* **Scipy** a Python module providing standard numerical routines, which is heavily using numpy arrays
- * **Python-Tables** a powerful Python interface to HDF5.
+ * **Python-Tables** a powerful Python interface to HDF5.
* **Matplotlib** a Python module for high quality 1D and 2D plotting (optionally)
* **IPython** although not a dependency of *xrayutilities* the IPython shell is perfectly suited for the interactive use of the *xrayutilities* python package.
@@ -149,10 +149,10 @@ building the C library.
Building and installing the library and python package
------------------------------------------------------
-*xrayutilities* uses the distutils packaging system to build and install all of its components. You can perform the installation by executing
+*xrayutilities* uses the distutils packaging system to build and install all of its components. You can perform the installation by executing
.. code-block:: bash
-
+
>python setup.py install
or
@@ -161,7 +161,7 @@ or
>python setup.py install --prefix=INSTALLPATH
-in the root directory of the source distribution.
+in the root directory of the source distribution.
The *--prefix* option sets the root directory for the installation. If it is omitted
the libary is installed under /usr/lib/ on Unix systems or in the Python installation directory on Windows.
@@ -171,20 +171,20 @@ Setup of the Python package
You need to make your Python installation aware of where to look for the module.
This is usually only needed when installing in non-standard *<install path>* locations.
-For this case append the installation directory to your *PYTHONPATH* environment variable by
+For this case append the installation directory to your *PYTHONPATH* environment variable by
.. code-block:: bash
-
+
>export PYTHONPATH=$PYTHONPATH:<local install path>/lib64/python2.7/site-packages
on a Unix/Linux terminal. Or, to make this configuration persistent append this line to
-your local *.bashrc* file in your home directory.
-On MS Windows you would like to create a environment variable in the
-system preferences under system in the advanced tab (Using pythonxy this is done automatically).
-Be sure to use the correct directory which might be similar to
+your local *.bashrc* file in your home directory.
+On MS Windows you would like to create a environment variable in the
+system preferences under system in the advanced tab (Using Python(x,y) this is done automatically).
+Be sure to use the correct directory which might be similar to
.. code-block:: bash
-
+
<local install path>/Lib/site-packages
on Windows systems.
@@ -192,23 +192,23 @@ on Windows systems.
Notes for installing on Windows
-------------------------------
-Since there is no packages manager on Windows the packages need to be installed manual
+Since there is no packages manager on Windows the packages need to be installed manual
(including all the dependecies) or a pre-packed solution needs two be used. We strongly suggest to
-use the `Python(x,y) <https://code.google.com/p/pythonxy/>`_ or
-`WinPython <http://winpython.sourceforge.net/>`_ python distributions,
+use the `Python(x,y) <https://code.google.com/p/pythonxy/>`_ or
+`WinPython <https://winpython.github.io/>`_ Python distributions,
which include already all of the needed dependencies for installing *xrayutilities*.
-The setup of the environment variables is also done by the python distributions.
+The setup of the environment variables is also done by the Python distributions.
One can proceed with the installation of *xrayutilities* directly!
-The easiest way to do this on windows is to use the binaries distributed on the `Python package index <https://pypi.python.org/pypi/xrayutilities>`_, otherwise one can follow the general installation instructions.
-Depending on your compiler on Microsoft Windows it might be necessary to perform the building of the Python extension separately and specify the compiler manually.
+The easiest way to do this on windows is to use the binaries distributed on the `Python package index <https://pypi.python.org/pypi/xrayutilities>`_, otherwise one can follow the general installation instructions.
+Depending on your compiler on Microsoft Windows it might be necessary to perform the building of the Python extension separately and specify the compiler manually.
This is done by
.. code-block:: bash
python setup.py build -c <compiler_name>
-Using Python(x,y) you want to specify 'mingw32' as compiler name. With the WinPython it
+Using Python(x,y) you want to specify 'mingw32' as compiler name. With the WinPython it
is recommended to use the MS Visual Studio Express 2008 (which is freely available for download)
and can also build the code for 64bit Windows. In this case us 'msvc' as compiler name.
@@ -222,7 +222,7 @@ In case you want to do it the hard way install all of the following (versions in
* matplotlib (1.1.0)
It is suggested to add the MinGW binary directory, as well as the Python and Python-scripts directory
-to the Path environment variable as described above! Installation is done as described above.
+to the Path environment variable as described above! Installation is done as described above.
.. _expapi:
@@ -231,16 +231,16 @@ Examples and API-documentation
.. toctree::
:maxdepth: 2
-
- examples
+
+ examples
xrayutilities
xrayutilities.analysis
xrayutilities.io
xrayutilities.materials
xrayutilities.math
modules
-
-
+
+
Indices and tables
==================
diff --git a/doc/source/index.rst~ b/doc/source/index.rst~
index 81bd576..b013516 100644
--- a/doc/source/index.rst~
+++ b/doc/source/index.rst~
@@ -11,7 +11,7 @@ Installation instructions you find further down `Installation`_.
Read more about *xrayutilities* below or in `Journal of Applied Crystallography 2013, Volume 46, 1162-1170 <http://dx.doi.org/10.1107/S0021889813017214>`_
-
+
Introduction
============
@@ -30,25 +30,25 @@ Concept of usage
:align: right
:alt: Flow diagram showing how to analyze x-ray diffraction data using xrayutilities
-*xrayutilities* provides a set of functions to read experimental data from various data file formats.
+*xrayutilities* provides a set of functions to read experimental data from various data file formats.
All of them are gathered in the :mod:`io`-subpackage.
-After reading data with a function from the io-submodule the data might be corrected for monitor counts and/or absorption factor of a beam attenuator.
+After reading data with a function from the io-submodule the data might be corrected for monitor counts and/or absorption factor of a beam attenuator.
A special set of functions is provided to perform this for point, linear and area detectors.
-Since the amount of data taken with modern detectors often is too large to be able to work with them properly, a functions for reducing the data from linear and area detectors are provided.
-They use block-averaging to reduce the amount of data.
+Since the amount of data taken with modern detectors often is too large to be able to work with them properly, a functions for reducing the data from linear and area detectors are provided.
+They use block-averaging to reduce the amount of data.
Use those carefully not to loose the features you are interested in in your measurements.
-After the pre-treatment of the data, the core part of the package is the transformation of the angular data to reciprocal space.
-This is done as described in more detail below using the :mod:`experiment`-module`.
+After the pre-treatment of the data, the core part of the package is the transformation of the angular data to reciprocal space.
+This is done as described in more detail below using the :mod:`experiment`-module`.
The classes provided within the experiment module provide routines to help performing X-ray diffraction experiments.
This includes methods to calculate the diffraction angles (described below) needed to align crystalline samples and to convert data between angular and reciprocal space.
-The conversion from angular to reciprocal space is implemented very general for various goniometer geometries.
-It is especially useful in combination with linear and area detectors as described in this `article <http://dx.doi.org/10.1107/S0021889813017214>`_.
+The conversion from angular to reciprocal space is implemented very general for various goniometer geometries.
+It is especially useful in combination with linear and area detectors as described in this `article <http://dx.doi.org/10.1107/S0021889813017214>`_.
In standard cases, Users will only need the initialized routines, which predefine a certain goniometer geometry like the popular four-cirlce and six-circle geometries.
-After the conversion to reciprocal space, it is convenient to transform the data to a regular grid for visualization.
-For this purpose the :mod:`gridder`-module has been included into *xrayutilities*.
+After the conversion to reciprocal space, it is convenient to transform the data to a regular grid for visualization.
+For this purpose the :mod:`gridder`-module has been included into *xrayutilities*.
For the visualization of the data in reciprocal space the usage of `matplotlib <http://matplotlib.org>`_ is recommended.
A practical example showing the usage is given below.
@@ -63,11 +63,11 @@ Angle calculation using the material classes
Calculation of angles needed to align Bragg reflections in various diffraction geometries is done using the Materials defined in the :mod:`materials`-package.
This package provides a set of classes to describe crystal lattices and materials.
-Once such a material is properly defined one can calculate its properties, which includes the reciprocal lattice points, lattice plane distances, optical properties like
+Once such a material is properly defined one can calculate its properties, which includes the reciprocal lattice points, lattice plane distances, optical properties like
the refractive index, the structure factor (including the atomic scattering factor) and the complex polarizability.
These atomic properties are extracted from a database included in *xrayutilities*.
-Using such a material and an experimental class from the :mod:`experiment`-module, describing the experimental setup, the needed diffraction angles can be calculated for certain coplanar diffraction (high, low incidence), grazing incidence diffraction and also special non-coplanar diffraction geometries.
+Using such a material and an experimental class from the :mod:`experiment`-module, describing the experimental setup, the needed diffraction angles can be calculated for certain coplanar diffraction (high, low incidence), grazing incidence diffraction and also special non-coplanar diffraction geometries.
In the predefined experimental classes fixed geometries are used. For angle calculation of custom geometries using arbitrary geometries (max. of three free angles) the :mod:`q2ang_fit`-module can be used as described in one of the included example files.
.. _helloworld:
@@ -107,10 +107,9 @@ Express instructions
* open a command line and navigate to the downloaded sources and execute:
.. code-block:: bash
-
> python setup.py install
-which will install *xrayutilities* to the default directory. It should be possible to use it (*import xrayutilities*) from now on in python scripts.
+which will install *xrayutilities* to the default directory. It should be possible to use it (*import xrayutilities*) from now on in python scripts.
.. note:: The python package of *xrayutilities* was formerly called ''xrutils''
@@ -119,16 +118,16 @@ Detailed instructions
Installing *xrayutilities* is done using Python's distutils
-The package can be installed on Linux, Mac OS X and Microsoft Windows, however it is mostly tested on Linux/Unix platforms.
+The package can be installed on Linux, Mac OS X and Microsoft Windows, however, it is mostly tested on Linux/Unix platforms.
Please inform one of the authors in case the installation fails!
Required third party software
-----------------------------
-To keep the coding effort as small as possible *xrayutilities* depends on a
-large number of third party libraries and Python modules.
+To keep the coding effort as small as possible *xrayutilities* depends on a
+large number of third party libraries and Python modules.
-The needed dependencies are:
+The needed dependencies are:
* **GCC** Gnu Compiler Collection or any compatible C compiler. On windows you most probably should use MinGW or CygWin. Others might work but are untested.
* **HDF5** a versatile binary data format (library is implemented in C).
Although the library is not called directly, it is needed by the pytables Python
@@ -139,7 +138,7 @@ The needed dependencies are:
Additionally, the following Python modules are needed in order to make *xrayutilities* work as intended:
* **Numpy** a Python module providing numerical array objects
* **Scipy** a Python module providing standard numerical routines, which is heavily using numpy arrays
- * **Python-Tables** a powerful Python interface to HDF5.
+ * **Python-Tables** a powerful Python interface to HDF5.
* **Matplotlib** a Python module for high quality 1D and 2D plotting (optionally)
* **IPython** although not a dependency of *xrayutilities* the IPython shell is perfectly suited for the interactive use of the *xrayutilities* python package.
@@ -149,10 +148,9 @@ building the C library.
Building and installing the library and python package
------------------------------------------------------
-*xrayutilities* uses the distutils packaging system to build and install all of its components. You can perform the installation by executing
+*xrayutilities* uses the distutils packaging system to build and install all of its components. You can perform the installation by executing
.. code-block:: bash
-
>python setup.py install
or
@@ -161,7 +159,7 @@ or
>python setup.py install --prefix=INSTALLPATH
-in the root directory of the source distribution.
+in the root directory of the source distribution.
The *--prefix* option sets the root directory for the installation. If it is omitted
the libary is installed under /usr/lib/ on Unix systems or in the Python installation directory on Windows.
@@ -171,20 +169,20 @@ Setup of the Python package
You need to make your Python installation aware of where to look for the module.
This is usually only needed when installing in non-standard *<install path>* locations.
-For this case append the installation directory to your *PYTHONPATH* environment variable by
+For this case append the installation directory to your *PYTHONPATH* environment variable by
.. code-block:: bash
-
+
>export PYTHONPATH=$PYTHONPATH:<local install path>/lib64/python2.7/site-packages
on a Unix/Linux terminal. Or, to make this configuration persistent append this line to
-your local *.bashrc* file in your home directory.
-On MS Windows you would like to create a environment variable in the
-system preferences under system in the advanced tab (Using pythonxy this is done automatically).
-Be sure to use the correct directory which might be similar to
+your local *.bashrc* file in your home directory.
+On MS Windows you would like to create a environment variable in the
+system preferences under system in the advanced tab (Using Python(x,y) this is done automatically).
+Be sure to use the correct directory which might be similar to
.. code-block:: bash
-
+
<local install path>/Lib/site-packages
on Windows systems.
@@ -192,23 +190,23 @@ on Windows systems.
Notes for installing on Windows
-------------------------------
-Since there is no packages manager on Windows the packages need to be installed manual
+Since there is no packages manager on Windows the packages need to be installed manual
(including all the dependecies) or a pre-packed solution needs two be used. We strongly suggest to
-use the `Python(x,y) <https://code.google.com/p/pythonxy/>`_ or
-`WinPython <http://winpython.sourceforge.net/>`_ python distributions,
+use the `Python(x,y) <https://code.google.com/p/pythonxy/>`_ or
+`WinPython <https://winpython.github.io/>`_ Python distributions,
which include already all of the needed dependencies for installing *xrayutilities*.
-The setup of the environment variables is also done by the python distributions.
+The setup of the environment variables is also done by the Python distributions.
One can proceed with the installation of *xrayutilities* directly!
-The easiest way to do this on windows is to use the binaries distributed on the `Python package index <https://pypi.python.org/pypi/xrayutilities>`_, otherwise one can follow the general installation instructions.
-Depending on your compiler on Microsoft Windows it might be necessary to perform the building of the Python extension separately and specify the compiler manually.
+The easiest way to do this on windows is to use the binaries distributed on the `Python package index <https://pypi.python.org/pypi/xrayutilities>`_, otherwise one can follow the general installation instructions.
+Depending on your compiler on Microsoft Windows it might be necessary to perform the building of the Python extension separately and specify the compiler manually.
This is done by
.. code-block:: bash
python setup.py build -c <compiler_name>
-Using Python(x,y) you want to specify 'mingw32' as compiler name. With the WinPython it
+Using Python(x,y) you want to specify 'mingw32' as compiler name. With the WinPython it
is recommended to use the MS Visual Studio Express 2008 (which is freely available for download)
and can also build the code for 64bit Windows. In this case us 'msvc' as compiler name.
@@ -222,7 +220,7 @@ In case you want to do it the hard way install all of the following (versions in
* matplotlib (1.1.0)
It is suggested to add the MinGW binary directory, as well as the Python and Python-scripts directory
-to the Path environment variable as described above! Installation is done as described above.
+to the Path environment variable as described above! Installation is done as described above.
.. _expapi:
@@ -231,16 +229,16 @@ Examples and API-documentation
.. toctree::
:maxdepth: 2
-
- examples
+
+ examples
xrayutilities
xrayutilities.analysis
xrayutilities.io
xrayutilities.materials
xrayutilities.math
modules
-
-
+
+
Indices and tables
==================
diff --git a/doc/source/pics/favicon.ppm b/doc/source/pics/favicon.ppm
deleted file mode 100644
index 992e882..0000000
--- a/doc/source/pics/favicon.ppm
+++ /dev/null
@@ -1,5 +0,0 @@
-P6
-# CREATOR: GIMP PNM Filter Version 1.1
-32 32
-255
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diff --git a/doc/source/pics/xu_usage_planning.png b/doc/source/pics/xu_usage_planning.png
index f460ca1..43474e7 100644
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diff --git a/examples/data/04-003-0996.cif b/examples/data/04-003-0996.cif
deleted file mode 100644
index 616c4cc..0000000
--- a/examples/data/04-003-0996.cif
+++ /dev/null
@@ -1,8060 +0,0 @@
-data_Sb2_Te3_-_04-003-0996
-#Copyright 2014 International Centre for Diffraction Data. All rights reserved.
-
-_audit_creation_date 2014-09-12
-_audit_creation_method 'Generated by PDF-4+ 2013 software 4.13.0.6'
-
-_chemical_name_systematic 'Antimony Tellurium'
-_chemical_formula_moiety 'Sb2 Te3'
-_chemical_formula_sum 'Sb2 Te3'
-_chemical_formula_weight 626.30
-
-_symmetry_cell_setting Rhombohedral
-_symmetry_space_group_name_H-M R-3m
-_symmetry_Int_Tables_number 166
-
-loop_
-_symmetry_equiv_pos_site_id
-_symmetry_equiv_pos_as_xyz
-1 x,y,z
-2 -x,-y,-z
-3 -y,x-y,z
-4 y,-x+y,-z
-5 -x+y,-x,z
-6 x-y,x,-z
-7 -y,-x,z
-8 y,x,-z
-9 x,x-y,z
-10 -x,-x+y,-z
-11 -x+y,y,z
-12 x-y,-y,-z
-
-_cell_length_a 4.264(1)
-_cell_length_b 4.264(1)
-_cell_length_c 30.458(7)
-_cell_angle_alpha 90
-_cell_angle_beta 90
-_cell_angle_gamma 120
-_cell_volume 479.59
-_cell_formula_units_Z 3
-
-loop_
-_atom_site_label
-_atom_site_type_symbol
-_atom_site_fract_x
-_atom_site_fract_y
-_atom_site_fract_z
-_atom_site_B_iso_or_equiv
-_atom_site_symmetry_multiplicity
-_atom_site_Wyckoff_symbol
-_atom_site_occupancy
-Te1 Te 0.0 0.0 0.0 1.4 3 a 1.0
-Te2 Te 0.0 0.0 0.7872 0.5 6 c 1.0
-Sb3 Sb 0.0 0.0 0.3988 0.8 6 c 1.0
-
-_diffrn_radiation_probe X-ray
-loop_
-_diffrn_radiation_wavelength
-_diffrn_radiation_wavelength_wt
-_diffrn_radiation_type
-_diffrn_radiation_wavelength_id
-1.54056 0.67 K\a~1~ 1
-1.54439 0.33 K\a~2~ 2
-
-_pd_instr_geometry 'Bragg-Brentano (Fixed Slit)'
-_pd_meas_scan_method step
-_pd_meas_number_of_points 7986
-_pd_meas_2theta_range_min 0.00239
-_pd_meas_2theta_range_max 159.70239
-_pd_meas_2theta_range_inc 0.02
-
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diff --git a/examples/data/1216385.cif b/examples/data/1216385.cif
deleted file mode 100644
index 19643a9..0000000
--- a/examples/data/1216385.cif
+++ /dev/null
@@ -1,166 +0,0 @@
-##############################################################################
-# #
-# Sb-Te # Sb2Te3 # 1216385 #
-# #
-##############################################################################
-# #
-# Pearson's Crystal Data #
-# Crystal Structure Database for Inorganic Compounds (on CD-ROM) #
-# Release 2013/14 #
-# Editors: Pierre Villars and Karin Cenzual #
-# #
-# Copyright (c) ASM International & Material Phases Data System (MPDS), #
-# Switzerland & National Institute for Materials Science (NIMS), Japan, 2013 #
-# (Data generated pre-2002: Copyright (c) ASM International & MPDS & NIMS; #
-# post-2001: Copyright (c) ASM International & MPDS) #
-# All rights reserved. #
-# #
-# This copy of Pearson's Crystal Data is licensed to: #
-# X-Ray Group, Faculty of Mathematics and Physics, Site License #
-# #
-##############################################################################
-
-data_1216385
-_audit_creation_date 2014-09-12
-_audit_creation_method
-;
-Pearson's Crystal Data browser
-;
-#_database_code_PCD 1216385
-
-# Entry summary
-
-_chemical_formula_structural Sb2Te3
-_chemical_formula_sum Sb2Te3
-_chemical_name_mineral tellurantimony
-_chemical_compound_source ?
-_chemical_name_structure_type Bi2Te3,hR15,166
-_chemical_formula_weight 626.3
-_chemical_melting_point ?
-
-# Bibliographic data
-
-_publ_section_title
-;
-Phase equilibria in Cu2Te-In2Te3-{Sb/Bi}2Te3 systems and crystal structure of CuIn5Te8 compound
-;
-_journal_coden_ASTM JALCEU
-_journal_name_full 'J. Alloys Compd.'
-_journal_year 2007
-_journal_volume 436
-_journal_page_first 247
-_journal_page_last 251
-_journal_language English
-loop_
- _publ_author_name
- _publ_author_address
-'Olekseyuk I.D.'
-;
-Lesya Ukrainka Volyn State University
-Department of General and Inorganic Chemistry
-Lutsk
-Ukraine
-;
-'Zhbankov O.Y.'
-;
-Lesya Ukrainka Volyn State University
-Department of General and Inorganic Chemistry
-Lutsk
-Ukraine
-;
-
-# Standardized crystallographic data
-
-_cell_length_a 4.26
-_cell_length_b 4.26
-_cell_length_c 30.462
-_cell_angle_alpha 90
-_cell_angle_beta 90
-_cell_angle_gamma 120
-_cell_volume 478.7
-_cell_formula_units_Z 3
-_symmetry_Int_Tables_number 166
-_symmetry_space_group_name_H-M 'R-3m h'
-loop_
- _symmetry_equiv_pos_site_id
- _symmetry_equiv_pos_as_xyz
- 1 'x, y, z'
- 2 '-x+y, -x, z'
- 3 '-x+y, y, z'
- 4 '-x, -x+y, -z'
- 5 '-x, -y, -z'
- 6 '-y, -x, z'
- 7 '-y, x-y, z'
- 8 'x, x-y, z'
- 9 'x-y, -y, -z'
- 10 'x-y, x, -z'
- 11 'y, -x+y, -z'
- 12 'y, x, -z'
- 13 '2/3+x, 1/3+y, 1/3+z'
- 14 '2/3-x+y, 1/3-x, 1/3+z'
- 15 '2/3-x+y, 1/3+y, 1/3+z'
- 16 '2/3-x, 1/3-x+y, 1/3-z'
- 17 '2/3-x, 1/3-y, 1/3-z'
- 18 '2/3-y, 1/3-x, 1/3+z'
- 19 '2/3-y, 1/3+x-y, 1/3+z'
- 20 '2/3+x, 1/3+x-y, 1/3+z'
- 21 '2/3+x-y, 1/3-y, 1/3-z'
- 22 '2/3+x-y, 1/3+x, 1/3-z'
- 23 '2/3+y, 1/3-x+y, 1/3-z'
- 24 '2/3+y, 1/3+x, 1/3-z'
- 25 '1/3+x, 2/3+y, 2/3+z'
- 26 '1/3-x+y, 2/3-x, 2/3+z'
- 27 '1/3-x+y, 2/3+y, 2/3+z'
- 28 '1/3-x, 2/3-x+y, 2/3-z'
- 29 '1/3-x, 2/3-y, 2/3-z'
- 30 '1/3-y, 2/3-x, 2/3+z'
- 31 '1/3-y, 2/3+x-y, 2/3+z'
- 32 '1/3+x, 2/3+x-y, 2/3+z'
- 33 '1/3+x-y, 2/3-y, 2/3-z'
- 34 '1/3+x-y, 2/3+x, 2/3-z'
- 35 '1/3+y, 2/3-x+y, 2/3-z'
- 36 '1/3+y, 2/3+x, 2/3-z'
-
-# Atomic positions taken from type-defining entry
-
-#loop_
-# _atom_type_symbol
-# _atom_type_oxidation_number
-# Te 0
-# Sb 0
-loop_
- _atom_site_label
- _atom_site_type_symbol
- _atom_site_Wyckoff_symbol
- _atom_site_symmetry_multiplicity
- _atom_site_fract_x
- _atom_site_fract_y
- _atom_site_fract_z
- _atom_site_occupancy
- Te1 Te c 6 0 0 0.2097 1
- Sb1 Sb c 6 0 0 0.40046 1
- Te2 Te a 3 0 0 0 1
-
-
-_exptl_crystal_colour ?
-_exptl_crystal_density_meas ?
-_cell_measurement_temperature ?
-_cell_measurement_radiation 'X-rays, Cu Ka'
-_cell_measurement_wavelength 1.54185
-_cell_measurement_reflns_used ?
-_diffrn_ambient_temperature ?
-_diffrn_measurement_device ?
-_diffrn_measurement_device_type ?
-_diffrn_radiation_type ?
-_diffrn_reflns_number ?
-_exptl_absorpt_coefficient_mu ?
-_exptl_absorpt_correction_type ?
-_computing_structure_solution ?
-_refine_ls_number_parameters ?
-_refine_ls_number_reflns ?
-_refine_ls_R_factor_all ?
-_refine_ls_wR_factor_all ?
-_computing_structure_refinement ?
-
-# End of data set 1216385
-
diff --git a/examples/data/BaF2.cif b/examples/data/BaF2.cif
index 880bb80..7b7ce8a 100755
--- a/examples/data/BaF2.cif
+++ b/examples/data/BaF2.cif
@@ -1,228 +1,228 @@
-data_global
-_chemical_name_mineral 'Frankdicksonite'
-loop_
-_publ_author_name
-'Wyckoff R W G'
-_journal_name_full 'Crystal Structures'
-_journal_volume 1
-_journal_year 1963
-_journal_page_first 239
-_journal_page_last 444
-_publ_section_title
-;
- Second edition. Interscience Publishers, New York, New York
- Fluorite structure
-;
-_database_code_amcsd 0011682
-_chemical_formula_sum 'Ba F2'
-_cell_length_a 6.2001
-_cell_length_b 6.2001
-_cell_length_c 6.2001
-_cell_angle_alpha 90
-_cell_angle_beta 90
-_cell_angle_gamma 90
-_cell_volume 238.340
-_exptl_crystal_density_diffrn 4.886
-_symmetry_space_group_name_H-M 'F m 3 m'
-loop_
-_space_group_symop_operation_xyz
- 'x,y,z'
- 'x,1/2+y,1/2+z'
- '1/2+x,y,1/2+z'
- '1/2+x,1/2+y,z'
- 'z,-x,y'
- 'z,1/2-x,1/2+y'
- '1/2+z,-x,1/2+y'
- '1/2+z,1/2-x,y'
- '-y,z,-x'
- '-y,1/2+z,1/2-x'
- '1/2-y,z,1/2-x'
- '1/2-y,1/2+z,-x'
- 'x,-y,z'
- 'x,1/2-y,1/2+z'
- '1/2+x,-y,1/2+z'
- '1/2+x,1/2-y,z'
- '-z,x,-y'
- '-z,1/2+x,1/2-y'
- '1/2-z,x,1/2-y'
- '1/2-z,1/2+x,-y'
- 'y,-z,x'
- 'y,1/2-z,1/2+x'
- '1/2+y,-z,1/2+x'
- '1/2+y,1/2-z,x'
- '-x,y,-z'
- '-x,1/2+y,1/2-z'
- '1/2-x,y,1/2-z'
- '1/2-x,1/2+y,-z'
- 'x,-z,-y'
- 'x,1/2-z,1/2-y'
- '1/2+x,-z,1/2-y'
- '1/2+x,1/2-z,-y'
- '-z,y,x'
- '-z,1/2+y,1/2+x'
- '1/2-z,y,1/2+x'
- '1/2-z,1/2+y,x'
- 'y,-x,-z'
- 'y,1/2-x,1/2-z'
- '1/2+y,-x,1/2-z'
- '1/2+y,1/2-x,-z'
- '-x,z,y'
- '-x,1/2+z,1/2+y'
- '1/2-x,z,1/2+y'
- '1/2-x,1/2+z,y'
- 'z,-y,-x'
- 'z,1/2-y,1/2-x'
- '1/2+z,-y,1/2-x'
- '1/2+z,1/2-y,-x'
- '-y,x,z'
- '-y,1/2+x,1/2+z'
- '1/2-y,x,1/2+z'
- '1/2-y,1/2+x,z'
- 'x,z,y'
- 'x,1/2+z,1/2+y'
- '1/2+x,z,1/2+y'
- '1/2+x,1/2+z,y'
- '-z,-y,-x'
- '-z,1/2-y,1/2-x'
- '1/2-z,-y,1/2-x'
- '1/2-z,1/2-y,-x'
- 'y,x,z'
- 'y,1/2+x,1/2+z'
- '1/2+y,x,1/2+z'
- '1/2+y,1/2+x,z'
- '-x,-z,-y'
- '-x,1/2-z,1/2-y'
- '1/2-x,-z,1/2-y'
- '1/2-x,1/2-z,-y'
- 'z,y,x'
- 'z,1/2+y,1/2+x'
- '1/2+z,y,1/2+x'
- '1/2+z,1/2+y,x'
- '-y,-x,-z'
- '-y,1/2-x,1/2-z'
- '1/2-y,-x,1/2-z'
- '1/2-y,1/2-x,-z'
- 'z,x,-y'
- 'z,1/2+x,1/2-y'
- '1/2+z,x,1/2-y'
- '1/2+z,1/2+x,-y'
- '-y,-z,x'
- '-y,1/2-z,1/2+x'
- '1/2-y,-z,1/2+x'
- '1/2-y,1/2-z,x'
- 'x,y,-z'
- 'x,1/2+y,1/2-z'
- '1/2+x,y,1/2-z'
- '1/2+x,1/2+y,-z'
- '-z,-x,y'
- '-z,1/2-x,1/2+y'
- '1/2-z,-x,1/2+y'
- '1/2-z,1/2-x,y'
- 'y,z,-x'
- 'y,1/2+z,1/2-x'
- '1/2+y,z,1/2-x'
- '1/2+y,1/2+z,-x'
- '-x,-y,z'
- '-x,1/2-y,1/2+z'
- '1/2-x,-y,1/2+z'
- '1/2-x,1/2-y,z'
- '-z,x,y'
- '-z,1/2+x,1/2+y'
- '1/2-z,x,1/2+y'
- '1/2-z,1/2+x,y'
- 'y,-z,-x'
- 'y,1/2-z,1/2-x'
- '1/2+y,-z,1/2-x'
- '1/2+y,1/2-z,-x'
- '-x,y,z'
- '-x,1/2+y,1/2+z'
- '1/2-x,y,1/2+z'
- '1/2-x,1/2+y,z'
- 'z,-x,-y'
- 'z,1/2-x,1/2-y'
- '1/2+z,-x,1/2-y'
- '1/2+z,1/2-x,-y'
- '-y,z,x'
- '-y,1/2+z,1/2+x'
- '1/2-y,z,1/2+x'
- '1/2-y,1/2+z,x'
- 'x,-y,-z'
- 'x,1/2-y,1/2-z'
- '1/2+x,-y,1/2-z'
- '1/2+x,1/2-y,-z'
- '-x,z,-y'
- '-x,1/2+z,1/2-y'
- '1/2-x,z,1/2-y'
- '1/2-x,1/2+z,-y'
- 'z,-y,x'
- 'z,1/2-y,1/2+x'
- '1/2+z,-y,1/2+x'
- '1/2+z,1/2-y,x'
- '-y,x,-z'
- '-y,1/2+x,1/2-z'
- '1/2-y,x,1/2-z'
- '1/2-y,1/2+x,-z'
- 'x,-z,y'
- 'x,1/2-z,1/2+y'
- '1/2+x,-z,1/2+y'
- '1/2+x,1/2-z,y'
- '-z,y,-x'
- '-z,1/2+y,1/2-x'
- '1/2-z,y,1/2-x'
- '1/2-z,1/2+y,-x'
- 'y,-x,z'
- 'y,1/2-x,1/2+z'
- '1/2+y,-x,1/2+z'
- '1/2+y,1/2-x,z'
- '-x,-z,y'
- '-x,1/2-z,1/2+y'
- '1/2-x,-z,1/2+y'
- '1/2-x,1/2-z,y'
- 'z,y,-x'
- 'z,1/2+y,1/2-x'
- '1/2+z,y,1/2-x'
- '1/2+z,1/2+y,-x'
- '-y,-x,z'
- '-y,1/2-x,1/2+z'
- '1/2-y,-x,1/2+z'
- '1/2-y,1/2-x,z'
- 'x,z,-y'
- 'x,1/2+z,1/2-y'
- '1/2+x,z,1/2-y'
- '1/2+x,1/2+z,-y'
- '-z,-y,x'
- '-z,1/2-y,1/2+x'
- '1/2-z,-y,1/2+x'
- '1/2-z,1/2-y,x'
- 'y,x,-z'
- 'y,1/2+x,1/2-z'
- '1/2+y,x,1/2-z'
- '1/2+y,1/2+x,-z'
- '-z,-x,-y'
- '-z,1/2-x,1/2-y'
- '1/2-z,-x,1/2-y'
- '1/2-z,1/2-x,-y'
- 'y,z,x'
- 'y,1/2+z,1/2+x'
- '1/2+y,z,1/2+x'
- '1/2+y,1/2+z,x'
- '-x,-y,-z'
- '-x,1/2-y,1/2-z'
- '1/2-x,-y,1/2-z'
- '1/2-x,1/2-y,-z'
- 'z,x,y'
- 'z,1/2+x,1/2+y'
- '1/2+z,x,1/2+y'
- '1/2+z,1/2+x,y'
- '-y,-z,-x'
- '-y,1/2-z,1/2-x'
- '1/2-y,-z,1/2-x'
- '1/2-y,1/2-z,-x'
-loop_
-_atom_site_label
-_atom_site_fract_x
-_atom_site_fract_y
-_atom_site_fract_z
-Ba 0.00000 0.00000 0.00000
-F 0.25000 0.25000 0.25000
-
+data_global
+_chemical_name_mineral 'Frankdicksonite'
+loop_
+_publ_author_name
+'Wyckoff R W G'
+_journal_name_full 'Crystal Structures'
+_journal_volume 1
+_journal_year 1963
+_journal_page_first 239
+_journal_page_last 444
+_publ_section_title
+;
+ Second edition. Interscience Publishers, New York, New York
+ Fluorite structure
+;
+_database_code_amcsd 0011682
+_chemical_formula_sum 'Ba F2'
+_cell_length_a 6.2001
+_cell_length_b 6.2001
+_cell_length_c 6.2001
+_cell_angle_alpha 90
+_cell_angle_beta 90
+_cell_angle_gamma 90
+_cell_volume 238.340
+_exptl_crystal_density_diffrn 4.886
+_symmetry_space_group_name_H-M 'F m 3 m'
+loop_
+_space_group_symop_operation_xyz
+ 'x,y,z'
+ 'x,1/2+y,1/2+z'
+ '1/2+x,y,1/2+z'
+ '1/2+x,1/2+y,z'
+ 'z,-x,y'
+ 'z,1/2-x,1/2+y'
+ '1/2+z,-x,1/2+y'
+ '1/2+z,1/2-x,y'
+ '-y,z,-x'
+ '-y,1/2+z,1/2-x'
+ '1/2-y,z,1/2-x'
+ '1/2-y,1/2+z,-x'
+ 'x,-y,z'
+ 'x,1/2-y,1/2+z'
+ '1/2+x,-y,1/2+z'
+ '1/2+x,1/2-y,z'
+ '-z,x,-y'
+ '-z,1/2+x,1/2-y'
+ '1/2-z,x,1/2-y'
+ '1/2-z,1/2+x,-y'
+ 'y,-z,x'
+ 'y,1/2-z,1/2+x'
+ '1/2+y,-z,1/2+x'
+ '1/2+y,1/2-z,x'
+ '-x,y,-z'
+ '-x,1/2+y,1/2-z'
+ '1/2-x,y,1/2-z'
+ '1/2-x,1/2+y,-z'
+ 'x,-z,-y'
+ 'x,1/2-z,1/2-y'
+ '1/2+x,-z,1/2-y'
+ '1/2+x,1/2-z,-y'
+ '-z,y,x'
+ '-z,1/2+y,1/2+x'
+ '1/2-z,y,1/2+x'
+ '1/2-z,1/2+y,x'
+ 'y,-x,-z'
+ 'y,1/2-x,1/2-z'
+ '1/2+y,-x,1/2-z'
+ '1/2+y,1/2-x,-z'
+ '-x,z,y'
+ '-x,1/2+z,1/2+y'
+ '1/2-x,z,1/2+y'
+ '1/2-x,1/2+z,y'
+ 'z,-y,-x'
+ 'z,1/2-y,1/2-x'
+ '1/2+z,-y,1/2-x'
+ '1/2+z,1/2-y,-x'
+ '-y,x,z'
+ '-y,1/2+x,1/2+z'
+ '1/2-y,x,1/2+z'
+ '1/2-y,1/2+x,z'
+ 'x,z,y'
+ 'x,1/2+z,1/2+y'
+ '1/2+x,z,1/2+y'
+ '1/2+x,1/2+z,y'
+ '-z,-y,-x'
+ '-z,1/2-y,1/2-x'
+ '1/2-z,-y,1/2-x'
+ '1/2-z,1/2-y,-x'
+ 'y,x,z'
+ 'y,1/2+x,1/2+z'
+ '1/2+y,x,1/2+z'
+ '1/2+y,1/2+x,z'
+ '-x,-z,-y'
+ '-x,1/2-z,1/2-y'
+ '1/2-x,-z,1/2-y'
+ '1/2-x,1/2-z,-y'
+ 'z,y,x'
+ 'z,1/2+y,1/2+x'
+ '1/2+z,y,1/2+x'
+ '1/2+z,1/2+y,x'
+ '-y,-x,-z'
+ '-y,1/2-x,1/2-z'
+ '1/2-y,-x,1/2-z'
+ '1/2-y,1/2-x,-z'
+ 'z,x,-y'
+ 'z,1/2+x,1/2-y'
+ '1/2+z,x,1/2-y'
+ '1/2+z,1/2+x,-y'
+ '-y,-z,x'
+ '-y,1/2-z,1/2+x'
+ '1/2-y,-z,1/2+x'
+ '1/2-y,1/2-z,x'
+ 'x,y,-z'
+ 'x,1/2+y,1/2-z'
+ '1/2+x,y,1/2-z'
+ '1/2+x,1/2+y,-z'
+ '-z,-x,y'
+ '-z,1/2-x,1/2+y'
+ '1/2-z,-x,1/2+y'
+ '1/2-z,1/2-x,y'
+ 'y,z,-x'
+ 'y,1/2+z,1/2-x'
+ '1/2+y,z,1/2-x'
+ '1/2+y,1/2+z,-x'
+ '-x,-y,z'
+ '-x,1/2-y,1/2+z'
+ '1/2-x,-y,1/2+z'
+ '1/2-x,1/2-y,z'
+ '-z,x,y'
+ '-z,1/2+x,1/2+y'
+ '1/2-z,x,1/2+y'
+ '1/2-z,1/2+x,y'
+ 'y,-z,-x'
+ 'y,1/2-z,1/2-x'
+ '1/2+y,-z,1/2-x'
+ '1/2+y,1/2-z,-x'
+ '-x,y,z'
+ '-x,1/2+y,1/2+z'
+ '1/2-x,y,1/2+z'
+ '1/2-x,1/2+y,z'
+ 'z,-x,-y'
+ 'z,1/2-x,1/2-y'
+ '1/2+z,-x,1/2-y'
+ '1/2+z,1/2-x,-y'
+ '-y,z,x'
+ '-y,1/2+z,1/2+x'
+ '1/2-y,z,1/2+x'
+ '1/2-y,1/2+z,x'
+ 'x,-y,-z'
+ 'x,1/2-y,1/2-z'
+ '1/2+x,-y,1/2-z'
+ '1/2+x,1/2-y,-z'
+ '-x,z,-y'
+ '-x,1/2+z,1/2-y'
+ '1/2-x,z,1/2-y'
+ '1/2-x,1/2+z,-y'
+ 'z,-y,x'
+ 'z,1/2-y,1/2+x'
+ '1/2+z,-y,1/2+x'
+ '1/2+z,1/2-y,x'
+ '-y,x,-z'
+ '-y,1/2+x,1/2-z'
+ '1/2-y,x,1/2-z'
+ '1/2-y,1/2+x,-z'
+ 'x,-z,y'
+ 'x,1/2-z,1/2+y'
+ '1/2+x,-z,1/2+y'
+ '1/2+x,1/2-z,y'
+ '-z,y,-x'
+ '-z,1/2+y,1/2-x'
+ '1/2-z,y,1/2-x'
+ '1/2-z,1/2+y,-x'
+ 'y,-x,z'
+ 'y,1/2-x,1/2+z'
+ '1/2+y,-x,1/2+z'
+ '1/2+y,1/2-x,z'
+ '-x,-z,y'
+ '-x,1/2-z,1/2+y'
+ '1/2-x,-z,1/2+y'
+ '1/2-x,1/2-z,y'
+ 'z,y,-x'
+ 'z,1/2+y,1/2-x'
+ '1/2+z,y,1/2-x'
+ '1/2+z,1/2+y,-x'
+ '-y,-x,z'
+ '-y,1/2-x,1/2+z'
+ '1/2-y,-x,1/2+z'
+ '1/2-y,1/2-x,z'
+ 'x,z,-y'
+ 'x,1/2+z,1/2-y'
+ '1/2+x,z,1/2-y'
+ '1/2+x,1/2+z,-y'
+ '-z,-y,x'
+ '-z,1/2-y,1/2+x'
+ '1/2-z,-y,1/2+x'
+ '1/2-z,1/2-y,x'
+ 'y,x,-z'
+ 'y,1/2+x,1/2-z'
+ '1/2+y,x,1/2-z'
+ '1/2+y,1/2+x,-z'
+ '-z,-x,-y'
+ '-z,1/2-x,1/2-y'
+ '1/2-z,-x,1/2-y'
+ '1/2-z,1/2-x,-y'
+ 'y,z,x'
+ 'y,1/2+z,1/2+x'
+ '1/2+y,z,1/2+x'
+ '1/2+y,1/2+z,x'
+ '-x,-y,-z'
+ '-x,1/2-y,1/2-z'
+ '1/2-x,-y,1/2-z'
+ '1/2-x,1/2-y,-z'
+ 'z,x,y'
+ 'z,1/2+x,1/2+y'
+ '1/2+z,x,1/2+y'
+ '1/2+z,1/2+x,y'
+ '-y,-z,-x'
+ '-y,1/2-z,1/2-x'
+ '1/2-y,-z,1/2-x'
+ '1/2-y,1/2-z,-x'
+loop_
+_atom_site_label
+_atom_site_fract_x
+_atom_site_fract_y
+_atom_site_fract_z
+Ba 0.00000 0.00000 0.00000
+F 0.25000 0.25000 0.25000
+
diff --git a/examples/data/Calcite.cif b/examples/data/Calcite.cif
index 2f926cf..8fcf61a 100755
--- a/examples/data/Calcite.cif
+++ b/examples/data/Calcite.cif
@@ -1,72 +1,72 @@
-data_global
-_chemical_name_mineral 'Calcite'
-loop_
-_publ_author_name
-'Graf D L'
-_journal_name_full 'American Mineralogist'
-_journal_volume 46
-_journal_year 1961
-_journal_page_first 1283
-_journal_page_last 1316
-_publ_section_title
-;
- Crystallographic tables for the rhombohedral carbonates
-;
-_database_code_amcsd 0000098
-_chemical_formula_sum 'Ca C O3'
-_cell_length_a 4.9900
-_cell_length_b 4.9900
-_cell_length_c 17.0615
-_cell_angle_alpha 90
-_cell_angle_beta 90
-_cell_angle_gamma 120
-_cell_volume 367.916
-_exptl_crystal_density_diffrn 2.710
-_symmetry_space_group_name_H-M 'R -3 c'
-loop_
-_space_group_symop_operation_xyz
- 'x,y,z'
- '2/3+x,1/3+y,1/3+z'
- '1/3+x,2/3+y,2/3+z'
- 'x,x-y,1/2+z'
- '2/3+x,1/3+x-y,5/6+z'
- '1/3+x,2/3+x-y,1/6+z'
- 'y,x,1/2-z'
- '2/3+y,1/3+x,5/6-z'
- '1/3+y,2/3+x,1/6-z'
- '-x+y,y,1/2+z'
- '2/3-x+y,1/3+y,5/6+z'
- '1/3-x+y,2/3+y,1/6+z'
- '-x,-x+y,1/2-z'
- '2/3-x,1/3-x+y,5/6-z'
- '1/3-x,2/3-x+y,1/6-z'
- '-y,-x,1/2+z'
- '2/3-y,1/3-x,5/6+z'
- '1/3-y,2/3-x,1/6+z'
- 'x-y,-y,1/2-z'
- '2/3+x-y,1/3-y,5/6-z'
- '1/3+x-y,2/3-y,1/6-z'
- 'y,-x+y,-z'
- '2/3+y,1/3-x+y,1/3-z'
- '1/3+y,2/3-x+y,2/3-z'
- '-x+y,-x,z'
- '2/3-x+y,1/3-x,1/3+z'
- '1/3-x+y,2/3-x,2/3+z'
- '-x,-y,-z'
- '2/3-x,1/3-y,1/3-z'
- '1/3-x,2/3-y,2/3-z'
- '-y,x-y,z'
- '2/3-y,1/3+x-y,1/3+z'
- '1/3-y,2/3+x-y,2/3+z'
- 'x-y,x,-z'
- '2/3+x-y,1/3+x,1/3-z'
- '1/3+x-y,2/3+x,2/3-z'
-loop_
-_atom_site_label
-_atom_site_fract_x
-_atom_site_fract_y
-_atom_site_fract_z
-Ca 0.00000 0.00000 0.00000
-C 0.00000 0.00000 0.25000
-O 0.25780 0.00000 0.25000
-
+data_global
+_chemical_name_mineral 'Calcite'
+loop_
+_publ_author_name
+'Graf D L'
+_journal_name_full 'American Mineralogist'
+_journal_volume 46
+_journal_year 1961
+_journal_page_first 1283
+_journal_page_last 1316
+_publ_section_title
+;
+ Crystallographic tables for the rhombohedral carbonates
+;
+_database_code_amcsd 0000098
+_chemical_formula_sum 'Ca C O3'
+_cell_length_a 4.9900
+_cell_length_b 4.9900
+_cell_length_c 17.0615
+_cell_angle_alpha 90
+_cell_angle_beta 90
+_cell_angle_gamma 120
+_cell_volume 367.916
+_exptl_crystal_density_diffrn 2.710
+_symmetry_space_group_name_H-M 'R -3 c'
+loop_
+_space_group_symop_operation_xyz
+ 'x,y,z'
+ '2/3+x,1/3+y,1/3+z'
+ '1/3+x,2/3+y,2/3+z'
+ 'x,x-y,1/2+z'
+ '2/3+x,1/3+x-y,5/6+z'
+ '1/3+x,2/3+x-y,1/6+z'
+ 'y,x,1/2-z'
+ '2/3+y,1/3+x,5/6-z'
+ '1/3+y,2/3+x,1/6-z'
+ '-x+y,y,1/2+z'
+ '2/3-x+y,1/3+y,5/6+z'
+ '1/3-x+y,2/3+y,1/6+z'
+ '-x,-x+y,1/2-z'
+ '2/3-x,1/3-x+y,5/6-z'
+ '1/3-x,2/3-x+y,1/6-z'
+ '-y,-x,1/2+z'
+ '2/3-y,1/3-x,5/6+z'
+ '1/3-y,2/3-x,1/6+z'
+ 'x-y,-y,1/2-z'
+ '2/3+x-y,1/3-y,5/6-z'
+ '1/3+x-y,2/3-y,1/6-z'
+ 'y,-x+y,-z'
+ '2/3+y,1/3-x+y,1/3-z'
+ '1/3+y,2/3-x+y,2/3-z'
+ '-x+y,-x,z'
+ '2/3-x+y,1/3-x,1/3+z'
+ '1/3-x+y,2/3-x,2/3+z'
+ '-x,-y,-z'
+ '2/3-x,1/3-y,1/3-z'
+ '1/3-x,2/3-y,2/3-z'
+ '-y,x-y,z'
+ '2/3-y,1/3+x-y,1/3+z'
+ '1/3-y,2/3+x-y,2/3+z'
+ 'x-y,x,-z'
+ '2/3+x-y,1/3+x,1/3-z'
+ '1/3+x-y,2/3+x,2/3-z'
+loop_
+_atom_site_label
+_atom_site_fract_x
+_atom_site_fract_y
+_atom_site_fract_z
+Ca 0.00000 0.00000 0.00000
+C 0.00000 0.00000 0.25000
+O 0.25780 0.00000 0.25000
+
diff --git a/examples/data/Silicon.cif b/examples/data/Silicon.cif
index a56ce9b..29e6bd1 100755
--- a/examples/data/Silicon.cif
+++ b/examples/data/Silicon.cif
@@ -1,227 +1,227 @@
-data_global
-_chemical_name_mineral 'Silicon'
-loop_
-_publ_author_name
-'Wyckoff R W G'
-_journal_name_full 'Crystal Structures'
-_journal_volume 1
-_journal_year 1963
-_journal_page_first 7
-_journal_page_last 83
-_publ_section_title
-;
- Second edition. Interscience Publishers, New York, New York
- Sample at T = 300 K
-;
-_database_code_amcsd 0011243
-_chemical_formula_sum 'Si'
-_cell_length_a 5.43070
-_cell_length_b 5.43070
-_cell_length_c 5.43070
-_cell_angle_alpha 90
-_cell_angle_beta 90
-_cell_angle_gamma 90
-_cell_volume 160.165
-_exptl_crystal_density_diffrn 2.329
-_symmetry_space_group_name_H-M 'F d 3 m'
-loop_
-_space_group_symop_operation_xyz
- 'x,y,z'
- 'x,1/2+y,1/2+z'
- '1/2+x,y,1/2+z'
- '1/2+x,1/2+y,z'
- '3/4+z,3/4-x,1/4+y'
- '3/4+z,1/4-x,3/4+y'
- '1/4+z,3/4-x,3/4+y'
- '1/4+z,1/4-x,1/4+y'
- '-y,1/2+z,1/2-x'
- '-y,+z,-x'
- '1/2-y,1/2+z,-x'
- '1/2-y,+z,1/2-x'
- '3/4+x,3/4-y,1/4+z'
- '3/4+x,1/4-y,3/4+z'
- '1/4+x,3/4-y,3/4+z'
- '1/4+x,1/4-y,1/4+z'
- '-z,1/2+x,1/2-y'
- '-z,+x,-y'
- '1/2-z,1/2+x,-y'
- '1/2-z,+x,1/2-y'
- '3/4+y,3/4-z,1/4+x'
- '3/4+y,1/4-z,3/4+x'
- '1/4+y,3/4-z,3/4+x'
- '1/4+y,1/4-z,1/4+x'
- '-x,1/2+y,1/2-z'
- '-x,+y,-z'
- '1/2-x,1/2+y,-z'
- '1/2-x,+y,1/2-z'
- '1/2+x,-z,1/2-y'
- '1/2+x,1/2-z,-y'
- '+x,-z,-y'
- '+x,1/2-z,1/2-y'
- '3/4-z,3/4+y,1/4+x'
- '3/4-z,1/4+y,3/4+x'
- '1/4-z,3/4+y,3/4+x'
- '1/4-z,1/4+y,1/4+x'
- '1/2+y,-x,1/2-z'
- '1/2+y,1/2-x,-z'
- '+y,-x,-z'
- '+y,1/2-x,1/2-z'
- '3/4-x,3/4+z,1/4+y'
- '3/4-x,1/4+z,3/4+y'
- '1/4-x,3/4+z,3/4+y'
- '1/4-x,1/4+z,1/4+y'
- '1/2+z,-y,1/2-x'
- '1/2+z,1/2-y,-x'
- '+z,-y,-x'
- '+z,1/2-y,1/2-x'
- '3/4-y,3/4+x,1/4+z'
- '3/4-y,1/4+x,3/4+z'
- '1/4-y,3/4+x,3/4+z'
- '1/4-y,1/4+x,1/4+z'
- 'x,1/2+z,1/2+y'
- 'x,+z,+y'
- '1/2+x,1/2+z,+y'
- '1/2+x,+z,1/2+y'
- '1/4-z,3/4-y,3/4-x'
- '1/4-z,1/4-y,1/4-x'
- '3/4-z,3/4-y,1/4-x'
- '3/4-z,1/4-y,3/4-x'
- 'y,1/2+x,1/2+z'
- 'y,+x,+z'
- '1/2+y,1/2+x,+z'
- '1/2+y,+x,1/2+z'
- '1/4-x,3/4-z,3/4-y'
- '1/4-x,1/4-z,1/4-y'
- '3/4-x,3/4-z,1/4-y'
- '3/4-x,1/4-z,3/4-y'
- 'z,1/2+y,1/2+x'
- 'z,+y,+x'
- '1/2+z,1/2+y,+x'
- '1/2+z,+y,1/2+x'
- '1/4-y,3/4-x,3/4-z'
- '1/4-y,1/4-x,1/4-z'
- '3/4-y,3/4-x,1/4-z'
- '3/4-y,1/4-x,3/4-z'
- '3/4+z,1/4+x,3/4-y'
- '3/4+z,3/4+x,1/4-y'
- '1/4+z,1/4+x,1/4-y'
- '1/4+z,3/4+x,3/4-y'
- '-y,1/2-z,1/2+x'
- '-y,-z,+x'
- '1/2-y,1/2-z,+x'
- '1/2-y,-z,1/2+x'
- '3/4+x,1/4+y,3/4-z'
- '3/4+x,3/4+y,1/4-z'
- '1/4+x,1/4+y,1/4-z'
- '1/4+x,3/4+y,3/4-z'
- '-z,1/2-x,1/2+y'
- '-z,-x,+y'
- '1/2-z,1/2-x,+y'
- '1/2-z,-x,1/2+y'
- '3/4+y,1/4+z,3/4-x'
- '3/4+y,3/4+z,1/4-x'
- '1/4+y,1/4+z,1/4-x'
- '1/4+y,3/4+z,3/4-x'
- '-x,1/2-y,1/2+z'
- '-x,-y,+z'
- '1/2-x,1/2-y,+z'
- '1/2-x,-y,1/2+z'
- '1/4-z,3/4+x,3/4+y'
- '1/4-z,1/4+x,1/4+y'
- '3/4-z,3/4+x,1/4+y'
- '3/4-z,1/4+x,3/4+y'
- 'y,-z,-x'
- 'y,1/2-z,1/2-x'
- '1/2+y,-z,1/2-x'
- '1/2+y,1/2-z,-x'
- '1/4-x,3/4+y,3/4+z'
- '1/4-x,1/4+y,1/4+z'
- '3/4-x,3/4+y,1/4+z'
- '3/4-x,1/4+y,3/4+z'
- 'z,-x,-y'
- 'z,1/2-x,1/2-y'
- '1/2+z,-x,1/2-y'
- '1/2+z,1/2-x,-y'
- '1/4-y,3/4+z,3/4+x'
- '1/4-y,1/4+z,1/4+x'
- '3/4-y,3/4+z,1/4+x'
- '3/4-y,1/4+z,3/4+x'
- 'x,-y,-z'
- 'x,1/2-y,1/2-z'
- '1/2+x,-y,1/2-z'
- '1/2+x,1/2-y,-z'
- '1/2-x,1/2+z,-y'
- '1/2-x,+z,1/2-y'
- '-x,1/2+z,1/2-y'
- '-x,+z,-y'
- '1/4+z,3/4-y,3/4+x'
- '1/4+z,1/4-y,1/4+x'
- '3/4+z,3/4-y,1/4+x'
- '3/4+z,1/4-y,3/4+x'
- '1/2-y,1/2+x,-z'
- '1/2-y,+x,1/2-z'
- '-y,1/2+x,1/2-z'
- '-y,+x,-z'
- '1/4+x,3/4-z,3/4+y'
- '1/4+x,1/4-z,1/4+y'
- '3/4+x,3/4-z,1/4+y'
- '3/4+x,1/4-z,3/4+y'
- '1/2-z,1/2+y,-x'
- '1/2-z,+y,1/2-x'
- '-z,1/2+y,1/2-x'
- '-z,+y,-x'
- '1/4+y,3/4-x,3/4+z'
- '1/4+y,1/4-x,1/4+z'
- '3/4+y,3/4-x,1/4+z'
- '3/4+y,1/4-x,3/4+z'
- '-x,-z,y'
- '-x,1/2-z,1/2+y'
- '1/2-x,-z,1/2+y'
- '1/2-x,1/2-z,y'
- '3/4+z,3/4+y,1/4-x'
- '3/4+z,1/4+y,3/4-x'
- '1/4+z,3/4+y,3/4-x'
- '1/4+z,1/4+y,1/4-x'
- '-y,-x,z'
- '-y,1/2-x,1/2+z'
- '1/2-y,-x,1/2+z'
- '1/2-y,1/2-x,z'
- '3/4+x,3/4+z,1/4-y'
- '3/4+x,1/4+z,3/4-y'
- '1/4+x,3/4+z,3/4-y'
- '1/4+x,1/4+z,1/4-y'
- '-z,-y,x'
- '-z,1/2-y,1/2+x'
- '1/2-z,-y,1/2+x'
- '1/2-z,1/2-y,x'
- '3/4+y,3/4+x,1/4-z'
- '3/4+y,1/4+x,3/4-z'
- '1/4+y,3/4+x,3/4-z'
- '1/4+y,1/4+x,1/4-z'
- '1/4-z,1/4-x,1/4-y'
- '1/4-z,3/4-x,3/4-y'
- '3/4-z,1/4-x,3/4-y'
- '3/4-z,3/4-x,1/4-y'
- 'y,z,x'
- 'y,1/2+z,1/2+x'
- '1/2+y,z,1/2+x'
- '1/2+y,1/2+z,x'
- '1/4-x,1/4-y,1/4-z'
- '1/4-x,3/4-y,3/4-z'
- '3/4-x,1/4-y,3/4-z'
- '3/4-x,3/4-y,1/4-z'
- 'z,x,y'
- 'z,1/2+x,1/2+y'
- '1/2+z,x,1/2+y'
- '1/2+z,1/2+x,y'
- '1/4-y,1/4-z,1/4-x'
- '1/4-y,3/4-z,3/4-x'
- '3/4-y,1/4-z,3/4-x'
- '3/4-y,3/4-z,1/4-x'
-loop_
-_atom_site_label
-_atom_site_fract_x
-_atom_site_fract_y
-_atom_site_fract_z
-Si 0.00000 0.00000 0.00000
-
+data_global
+_chemical_name_mineral 'Silicon'
+loop_
+_publ_author_name
+'Wyckoff R W G'
+_journal_name_full 'Crystal Structures'
+_journal_volume 1
+_journal_year 1963
+_journal_page_first 7
+_journal_page_last 83
+_publ_section_title
+;
+ Second edition. Interscience Publishers, New York, New York
+ Sample at T = 300 K
+;
+_database_code_amcsd 0011243
+_chemical_formula_sum 'Si'
+_cell_length_a 5.43070
+_cell_length_b 5.43070
+_cell_length_c 5.43070
+_cell_angle_alpha 90
+_cell_angle_beta 90
+_cell_angle_gamma 90
+_cell_volume 160.165
+_exptl_crystal_density_diffrn 2.329
+_symmetry_space_group_name_H-M 'F d 3 m'
+loop_
+_space_group_symop_operation_xyz
+ 'x,y,z'
+ 'x,1/2+y,1/2+z'
+ '1/2+x,y,1/2+z'
+ '1/2+x,1/2+y,z'
+ '3/4+z,3/4-x,1/4+y'
+ '3/4+z,1/4-x,3/4+y'
+ '1/4+z,3/4-x,3/4+y'
+ '1/4+z,1/4-x,1/4+y'
+ '-y,1/2+z,1/2-x'
+ '-y,+z,-x'
+ '1/2-y,1/2+z,-x'
+ '1/2-y,+z,1/2-x'
+ '3/4+x,3/4-y,1/4+z'
+ '3/4+x,1/4-y,3/4+z'
+ '1/4+x,3/4-y,3/4+z'
+ '1/4+x,1/4-y,1/4+z'
+ '-z,1/2+x,1/2-y'
+ '-z,+x,-y'
+ '1/2-z,1/2+x,-y'
+ '1/2-z,+x,1/2-y'
+ '3/4+y,3/4-z,1/4+x'
+ '3/4+y,1/4-z,3/4+x'
+ '1/4+y,3/4-z,3/4+x'
+ '1/4+y,1/4-z,1/4+x'
+ '-x,1/2+y,1/2-z'
+ '-x,+y,-z'
+ '1/2-x,1/2+y,-z'
+ '1/2-x,+y,1/2-z'
+ '1/2+x,-z,1/2-y'
+ '1/2+x,1/2-z,-y'
+ '+x,-z,-y'
+ '+x,1/2-z,1/2-y'
+ '3/4-z,3/4+y,1/4+x'
+ '3/4-z,1/4+y,3/4+x'
+ '1/4-z,3/4+y,3/4+x'
+ '1/4-z,1/4+y,1/4+x'
+ '1/2+y,-x,1/2-z'
+ '1/2+y,1/2-x,-z'
+ '+y,-x,-z'
+ '+y,1/2-x,1/2-z'
+ '3/4-x,3/4+z,1/4+y'
+ '3/4-x,1/4+z,3/4+y'
+ '1/4-x,3/4+z,3/4+y'
+ '1/4-x,1/4+z,1/4+y'
+ '1/2+z,-y,1/2-x'
+ '1/2+z,1/2-y,-x'
+ '+z,-y,-x'
+ '+z,1/2-y,1/2-x'
+ '3/4-y,3/4+x,1/4+z'
+ '3/4-y,1/4+x,3/4+z'
+ '1/4-y,3/4+x,3/4+z'
+ '1/4-y,1/4+x,1/4+z'
+ 'x,1/2+z,1/2+y'
+ 'x,+z,+y'
+ '1/2+x,1/2+z,+y'
+ '1/2+x,+z,1/2+y'
+ '1/4-z,3/4-y,3/4-x'
+ '1/4-z,1/4-y,1/4-x'
+ '3/4-z,3/4-y,1/4-x'
+ '3/4-z,1/4-y,3/4-x'
+ 'y,1/2+x,1/2+z'
+ 'y,+x,+z'
+ '1/2+y,1/2+x,+z'
+ '1/2+y,+x,1/2+z'
+ '1/4-x,3/4-z,3/4-y'
+ '1/4-x,1/4-z,1/4-y'
+ '3/4-x,3/4-z,1/4-y'
+ '3/4-x,1/4-z,3/4-y'
+ 'z,1/2+y,1/2+x'
+ 'z,+y,+x'
+ '1/2+z,1/2+y,+x'
+ '1/2+z,+y,1/2+x'
+ '1/4-y,3/4-x,3/4-z'
+ '1/4-y,1/4-x,1/4-z'
+ '3/4-y,3/4-x,1/4-z'
+ '3/4-y,1/4-x,3/4-z'
+ '3/4+z,1/4+x,3/4-y'
+ '3/4+z,3/4+x,1/4-y'
+ '1/4+z,1/4+x,1/4-y'
+ '1/4+z,3/4+x,3/4-y'
+ '-y,1/2-z,1/2+x'
+ '-y,-z,+x'
+ '1/2-y,1/2-z,+x'
+ '1/2-y,-z,1/2+x'
+ '3/4+x,1/4+y,3/4-z'
+ '3/4+x,3/4+y,1/4-z'
+ '1/4+x,1/4+y,1/4-z'
+ '1/4+x,3/4+y,3/4-z'
+ '-z,1/2-x,1/2+y'
+ '-z,-x,+y'
+ '1/2-z,1/2-x,+y'
+ '1/2-z,-x,1/2+y'
+ '3/4+y,1/4+z,3/4-x'
+ '3/4+y,3/4+z,1/4-x'
+ '1/4+y,1/4+z,1/4-x'
+ '1/4+y,3/4+z,3/4-x'
+ '-x,1/2-y,1/2+z'
+ '-x,-y,+z'
+ '1/2-x,1/2-y,+z'
+ '1/2-x,-y,1/2+z'
+ '1/4-z,3/4+x,3/4+y'
+ '1/4-z,1/4+x,1/4+y'
+ '3/4-z,3/4+x,1/4+y'
+ '3/4-z,1/4+x,3/4+y'
+ 'y,-z,-x'
+ 'y,1/2-z,1/2-x'
+ '1/2+y,-z,1/2-x'
+ '1/2+y,1/2-z,-x'
+ '1/4-x,3/4+y,3/4+z'
+ '1/4-x,1/4+y,1/4+z'
+ '3/4-x,3/4+y,1/4+z'
+ '3/4-x,1/4+y,3/4+z'
+ 'z,-x,-y'
+ 'z,1/2-x,1/2-y'
+ '1/2+z,-x,1/2-y'
+ '1/2+z,1/2-x,-y'
+ '1/4-y,3/4+z,3/4+x'
+ '1/4-y,1/4+z,1/4+x'
+ '3/4-y,3/4+z,1/4+x'
+ '3/4-y,1/4+z,3/4+x'
+ 'x,-y,-z'
+ 'x,1/2-y,1/2-z'
+ '1/2+x,-y,1/2-z'
+ '1/2+x,1/2-y,-z'
+ '1/2-x,1/2+z,-y'
+ '1/2-x,+z,1/2-y'
+ '-x,1/2+z,1/2-y'
+ '-x,+z,-y'
+ '1/4+z,3/4-y,3/4+x'
+ '1/4+z,1/4-y,1/4+x'
+ '3/4+z,3/4-y,1/4+x'
+ '3/4+z,1/4-y,3/4+x'
+ '1/2-y,1/2+x,-z'
+ '1/2-y,+x,1/2-z'
+ '-y,1/2+x,1/2-z'
+ '-y,+x,-z'
+ '1/4+x,3/4-z,3/4+y'
+ '1/4+x,1/4-z,1/4+y'
+ '3/4+x,3/4-z,1/4+y'
+ '3/4+x,1/4-z,3/4+y'
+ '1/2-z,1/2+y,-x'
+ '1/2-z,+y,1/2-x'
+ '-z,1/2+y,1/2-x'
+ '-z,+y,-x'
+ '1/4+y,3/4-x,3/4+z'
+ '1/4+y,1/4-x,1/4+z'
+ '3/4+y,3/4-x,1/4+z'
+ '3/4+y,1/4-x,3/4+z'
+ '-x,-z,y'
+ '-x,1/2-z,1/2+y'
+ '1/2-x,-z,1/2+y'
+ '1/2-x,1/2-z,y'
+ '3/4+z,3/4+y,1/4-x'
+ '3/4+z,1/4+y,3/4-x'
+ '1/4+z,3/4+y,3/4-x'
+ '1/4+z,1/4+y,1/4-x'
+ '-y,-x,z'
+ '-y,1/2-x,1/2+z'
+ '1/2-y,-x,1/2+z'
+ '1/2-y,1/2-x,z'
+ '3/4+x,3/4+z,1/4-y'
+ '3/4+x,1/4+z,3/4-y'
+ '1/4+x,3/4+z,3/4-y'
+ '1/4+x,1/4+z,1/4-y'
+ '-z,-y,x'
+ '-z,1/2-y,1/2+x'
+ '1/2-z,-y,1/2+x'
+ '1/2-z,1/2-y,x'
+ '3/4+y,3/4+x,1/4-z'
+ '3/4+y,1/4+x,3/4-z'
+ '1/4+y,3/4+x,3/4-z'
+ '1/4+y,1/4+x,1/4-z'
+ '1/4-z,1/4-x,1/4-y'
+ '1/4-z,3/4-x,3/4-y'
+ '3/4-z,1/4-x,3/4-y'
+ '3/4-z,3/4-x,1/4-y'
+ 'y,z,x'
+ 'y,1/2+z,1/2+x'
+ '1/2+y,z,1/2+x'
+ '1/2+y,1/2+z,x'
+ '1/4-x,1/4-y,1/4-z'
+ '1/4-x,3/4-y,3/4-z'
+ '3/4-x,1/4-y,3/4-z'
+ '3/4-x,3/4-y,1/4-z'
+ 'z,x,y'
+ 'z,1/2+x,1/2+y'
+ '1/2+z,x,1/2+y'
+ '1/2+z,1/2+x,y'
+ '1/4-y,1/4-z,1/4-x'
+ '1/4-y,3/4-z,3/4-x'
+ '3/4-y,1/4-z,3/4-x'
+ '3/4-y,3/4-z,1/4-x'
+loop_
+_atom_site_label
+_atom_site_fract_x
+_atom_site_fract_y
+_atom_site_fract_z
+Si 0.00000 0.00000 0.00000
+
diff --git a/examples/data/bi2te3.cif b/examples/data/bi2te3.cif
index 9983dfb..c001c58 100755
--- a/examples/data/bi2te3.cif
+++ b/examples/data/bi2te3.cif
@@ -1,88 +1,88 @@
-data_global
-_chemical_name_mineral 'Tellurobismuthite'
-loop_
-_publ_author_name
-'Feutelais Y'
-'Legendre B'
-'Rodier N'
-'Agafonov V'
-_journal_name_full 'Materials Research Bulletin'
-_journal_volume 28
-_journal_year 1993
-_journal_page_first 591
-_journal_page_last 596
-_publ_section_title
-;
- A study of the phases in the bismuth - tellurium system
-;
-_database_code_amcsd 0014367
-_chemical_compound_source 'Synthetic'
-_chemical_formula_sum 'Bi2 Te3'
-_cell_length_a 4.395
-_cell_length_b 4.395
-_cell_length_c 30.440
-_cell_angle_alpha 90
-_cell_angle_beta 90
-_cell_angle_gamma 120
-_cell_volume 509.205
-_exptl_crystal_density_diffrn 7.834
-_symmetry_space_group_name_H-M 'R -3 m'
-loop_
-_space_group_symop_operation_xyz
- 'x,y,z'
- '2/3+x,1/3+y,1/3+z'
- '1/3+x,2/3+y,2/3+z'
- 'x,x-y,z'
- '2/3+x,1/3+x-y,1/3+z'
- '1/3+x,2/3+x-y,2/3+z'
- 'y,x,-z'
- '2/3+y,1/3+x,1/3-z'
- '1/3+y,2/3+x,2/3-z'
- '-x+y,y,z'
- '2/3-x+y,1/3+y,1/3+z'
- '1/3-x+y,2/3+y,2/3+z'
- '-x,-x+y,-z'
- '2/3-x,1/3-x+y,1/3-z'
- '1/3-x,2/3-x+y,2/3-z'
- '-y,-x,z'
- '2/3-y,1/3-x,1/3+z'
- '1/3-y,2/3-x,2/3+z'
- 'x-y,-y,-z'
- '2/3+x-y,1/3-y,1/3-z'
- '1/3+x-y,2/3-y,2/3-z'
- 'y,-x+y,-z'
- '2/3+y,1/3-x+y,1/3-z'
- '1/3+y,2/3-x+y,2/3-z'
- '-x+y,-x,z'
- '2/3-x+y,1/3-x,1/3+z'
- '1/3-x+y,2/3-x,2/3+z'
- '-x,-y,-z'
- '2/3-x,1/3-y,1/3-z'
- '1/3-x,2/3-y,2/3-z'
- '-y,x-y,z'
- '2/3-y,1/3+x-y,1/3+z'
- '1/3-y,2/3+x-y,2/3+z'
- 'x-y,x,-z'
- '2/3+x-y,1/3+x,1/3-z'
- '1/3+x-y,2/3+x,2/3-z'
-loop_
-_atom_site_label
-_atom_site_fract_x
-_atom_site_fract_y
-_atom_site_fract_z
-_atom_site_U_iso_or_equiv
-Bi 0.00000 0.00000 0.40046 0.02330
-Te1 0.00000 0.00000 0.00000 0.01748
-Te2 0.00000 0.00000 0.79030 0.01912
-loop_
-_atom_site_aniso_label
-_atom_site_aniso_U_11
-_atom_site_aniso_U_22
-_atom_site_aniso_U_33
-_atom_site_aniso_U_12
-_atom_site_aniso_U_13
-_atom_site_aniso_U_23
-Bi 0.02260 0.02260 0.02441 0.01130 0.00000 0.00000
-Te1 0.01916 0.01916 0.01408 0.00961 0.00000 0.00000
-Te2 0.02092 0.02092 0.01549 0.01050 0.00000 0.00000
-
+data_global
+_chemical_name_mineral 'Tellurobismuthite'
+loop_
+_publ_author_name
+'Feutelais Y'
+'Legendre B'
+'Rodier N'
+'Agafonov V'
+_journal_name_full 'Materials Research Bulletin'
+_journal_volume 28
+_journal_year 1993
+_journal_page_first 591
+_journal_page_last 596
+_publ_section_title
+;
+ A study of the phases in the bismuth - tellurium system
+;
+_database_code_amcsd 0014367
+_chemical_compound_source 'Synthetic'
+_chemical_formula_sum 'Bi2 Te3'
+_cell_length_a 4.395
+_cell_length_b 4.395
+_cell_length_c 30.440
+_cell_angle_alpha 90
+_cell_angle_beta 90
+_cell_angle_gamma 120
+_cell_volume 509.205
+_exptl_crystal_density_diffrn 7.834
+_symmetry_space_group_name_H-M 'R -3 m'
+loop_
+_space_group_symop_operation_xyz
+ 'x,y,z'
+ '2/3+x,1/3+y,1/3+z'
+ '1/3+x,2/3+y,2/3+z'
+ 'x,x-y,z'
+ '2/3+x,1/3+x-y,1/3+z'
+ '1/3+x,2/3+x-y,2/3+z'
+ 'y,x,-z'
+ '2/3+y,1/3+x,1/3-z'
+ '1/3+y,2/3+x,2/3-z'
+ '-x+y,y,z'
+ '2/3-x+y,1/3+y,1/3+z'
+ '1/3-x+y,2/3+y,2/3+z'
+ '-x,-x+y,-z'
+ '2/3-x,1/3-x+y,1/3-z'
+ '1/3-x,2/3-x+y,2/3-z'
+ '-y,-x,z'
+ '2/3-y,1/3-x,1/3+z'
+ '1/3-y,2/3-x,2/3+z'
+ 'x-y,-y,-z'
+ '2/3+x-y,1/3-y,1/3-z'
+ '1/3+x-y,2/3-y,2/3-z'
+ 'y,-x+y,-z'
+ '2/3+y,1/3-x+y,1/3-z'
+ '1/3+y,2/3-x+y,2/3-z'
+ '-x+y,-x,z'
+ '2/3-x+y,1/3-x,1/3+z'
+ '1/3-x+y,2/3-x,2/3+z'
+ '-x,-y,-z'
+ '2/3-x,1/3-y,1/3-z'
+ '1/3-x,2/3-y,2/3-z'
+ '-y,x-y,z'
+ '2/3-y,1/3+x-y,1/3+z'
+ '1/3-y,2/3+x-y,2/3+z'
+ 'x-y,x,-z'
+ '2/3+x-y,1/3+x,1/3-z'
+ '1/3+x-y,2/3+x,2/3-z'
+loop_
+_atom_site_label
+_atom_site_fract_x
+_atom_site_fract_y
+_atom_site_fract_z
+_atom_site_U_iso_or_equiv
+Bi 0.00000 0.00000 0.40046 0.02330
+Te1 0.00000 0.00000 0.00000 0.01748
+Te2 0.00000 0.00000 0.79030 0.01912
+loop_
+_atom_site_aniso_label
+_atom_site_aniso_U_11
+_atom_site_aniso_U_22
+_atom_site_aniso_U_33
+_atom_site_aniso_U_12
+_atom_site_aniso_U_13
+_atom_site_aniso_U_23
+Bi 0.02260 0.02260 0.02441 0.01130 0.00000 0.00000
+Te1 0.01916 0.01916 0.01408 0.00961 0.00000 0.00000
+Te2 0.02092 0.02092 0.01549 0.01050 0.00000 0.00000
+
diff --git a/examples/xrayutilities_export_data2vtk.py b/examples/xrayutilities_export_data2vtk.py
index d9ea013..810005a 100644
--- a/examples/xrayutilities_export_data2vtk.py
+++ b/examples/xrayutilities_export_data2vtk.py
@@ -1,82 +1,82 @@
-# This file is part of xrayutilities.
-#
-# xrayutilities is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation; either version 2 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, see <http://www.gnu.org/licenses/>.
-#
-# Copyright (C) 2013 Eugen Wintersberger <eugen.wintersberger at desy.de>
-# Copyright (C) 2013 Dominik Kriegner <dominik.kriegner at gmail.com>
-
-
-import numpy
-import xrayutilities as xu
-import vtk
-from vtk.util import numpy_support
-import os
-import xrayutilities_id01_functions as id01
-
-home = "DATADIR" # data path (root)
-datadir = os.path.join(home, "FOLDERNAME") # data path for CCD/Maxipix files
-specdir = home # location of spec file
-
-sample = "SAMPLENAME" # sample name -> used as spec file name
-# template for the CCD file names
-ccdfiletmp = os.path.join(datadir, "CCDFILENAME_%04d.edf.gz")
-
-
-h5file = os.path.join(specdir, sample + ".h5")
-# read spec file and save to HDF5 (needs to be done only once)
-# try: s
-# except NameError: s = xu.io.SPECFile(sample+".spec",path=specdir)
-# else:
-# s.Update()
-# s.Save2HDF5(h5file)
-# in ipython run with: "run -i script" to just update the spec file and parse
-# for new scans only
-
-# number of points to be used during the gridding
-nx, ny, nz = 100, 101, 102
-
-# read and grid data with helper function
-qx, qy, qz, gint, gridder = id01.gridmap(h5file, SCANNR, ccdfiletmp,
- nx, ny, nz)
-
-# prepare data for export to VTK image file
-INT = xu.maplog(gint, 3.0, 0)
-
-qx0 = qx.min()
-dqx = (qx.max() - qx.min()) / nx
-
-qy0 = qy.min()
-dqy = (qy.max() - qy.min()) / ny
-
-qz0 = qz.min()
-dqz = (qz.max() - qz.min()) / nz
-
-INT = numpy.transpose(INT).reshape((INT.size))
-data_array = numpy_support.numpy_to_vtk(INT)
-
-image_data = vtk.vtkImageData()
-image_data.SetNumberOfScalarComponents(1)
-image_data.SetOrigin(qx0, qy0, qz0)
-image_data.SetSpacing(dqx, dqy, dqz)
-image_data.SetExtent(0, nx - 1, 0, ny - 1, 0, nz - 1)
-image_data.SetScalarTypeToDouble()
-
-pd = image_data.GetPointData()
-pd.SetScalars(data_array)
-
-# export data to file
-writer = vtk.vtkXMLImageDataWriter()
-writer.SetFileName("output.vti")
-writer.SetInput(image_data)
-writer.Write()
+# This file is part of xrayutilities.
+#
+# xrayutilities is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program; if not, see <http://www.gnu.org/licenses/>.
+#
+# Copyright (C) 2013 Eugen Wintersberger <eugen.wintersberger at desy.de>
+# Copyright (C) 2013 Dominik Kriegner <dominik.kriegner at gmail.com>
+
+
+import numpy
+import xrayutilities as xu
+import vtk
+from vtk.util import numpy_support
+import os
+import xrayutilities_id01_functions as id01
+
+home = "DATADIR" # data path (root)
+datadir = os.path.join(home, "FOLDERNAME") # data path for CCD/Maxipix files
+specdir = home # location of spec file
+
+sample = "SAMPLENAME" # sample name -> used as spec file name
+# template for the CCD file names
+ccdfiletmp = os.path.join(datadir, "CCDFILENAME_%04d.edf.gz")
+
+
+h5file = os.path.join(specdir, sample + ".h5")
+# read spec file and save to HDF5 (needs to be done only once)
+# try: s
+# except NameError: s = xu.io.SPECFile(sample+".spec",path=specdir)
+# else:
+# s.Update()
+# s.Save2HDF5(h5file)
+# in ipython run with: "run -i script" to just update the spec file and parse
+# for new scans only
+
+# number of points to be used during the gridding
+nx, ny, nz = 100, 101, 102
+
+# read and grid data with helper function
+qx, qy, qz, gint, gridder = id01.gridmap(h5file, SCANNR, ccdfiletmp,
+ nx, ny, nz)
+
+# prepare data for export to VTK image file
+INT = xu.maplog(gint, 3.0, 0)
+
+qx0 = qx.min()
+dqx = (qx.max() - qx.min()) / nx
+
+qy0 = qy.min()
+dqy = (qy.max() - qy.min()) / ny
+
+qz0 = qz.min()
+dqz = (qz.max() - qz.min()) / nz
+
+INT = numpy.transpose(INT).reshape((INT.size))
+data_array = numpy_support.numpy_to_vtk(INT)
+
+image_data = vtk.vtkImageData()
+image_data.SetNumberOfScalarComponents(1)
+image_data.SetOrigin(qx0, qy0, qz0)
+image_data.SetSpacing(dqx, dqy, dqz)
+image_data.SetExtent(0, nx - 1, 0, ny - 1, 0, nz - 1)
+image_data.SetScalarTypeToDouble()
+
+pd = image_data.GetPointData()
+pd.SetScalars(data_array)
+
+# export data to file
+writer = vtk.vtkXMLImageDataWriter()
+writer.SetFileName("output.vti")
+writer.SetInput(image_data)
+writer.Write()
diff --git a/examples/xrayutilities_hotpixelkill_variant.py b/examples/xrayutilities_hotpixelkill_variant.py
index e36a988..e3cb74c 100644
--- a/examples/xrayutilities_hotpixelkill_variant.py
+++ b/examples/xrayutilities_hotpixelkill_variant.py
@@ -1,66 +1,66 @@
-# This file is part of xrayutilities.
-#
-# xrayutilities is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation; either version 2 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, see <http://www.gnu.org/licenses/>.
-#
-# Copyright (C) 2013 Raphael Grifone <raphael.grifone at esrf.fr>
-# Copyright (C) 2013 Dominik Kriegner <dominik.kriegner at gmail.com>
-
-"""
-The function below is a modification of the hotpixelkill function included in
-the xrayutilities_id01_functions.py file.
-
-Instead of manually specifying the list of hot pixel they are automatically
-determined from a series of dark images. The idea is as follows: If in the
-average data of several dark images (no intentional x-ray radiations during
-acquisition) a signal above a certain threshold remains it is expected to arise
-from a hot pixel and such pixels should be removed to avoid spikes in the data.
-"""
-
-import numpy
-import xrayutilities as xu
-import glob
-
-
-def hotpixelkill(ccd):
- """
- function to remove hot pixels from CCD frames
- """
- ccd[hotpixelnumbers] = 0
- # one could also use NaN here, since NaN values are
- # ignored by the gridder
- return ccd
-
-# identify hot pixels numbers from a series of dark images
-
-# open a series of 2D detector frames
-ccdavg = numpy.empty(0)
-n = 0
-for f in glob.glob("G:\data\dark*.edf"):
- e = xu.io.EDFFile(f)
- ccdraw = e.data
- try:
- ccdavg += ccdraw
- except:
- ccdavg = ccdraw.astype(numpy.float)
- n += 1
-
-ccdavg /= float(n)
-
-# adjust treshold value: either as absolute value or in relation to the maximum
-threshold = 10 # counts
-# or
-# threshold = ccdraw.max()*0.1 #take 10% of maximum intensity
-
-# determine hot pixels by comparison with the threshold value
-hotpixelnumbers = numpy.where(ccdraw > threshold)
+# This file is part of xrayutilities.
+#
+# xrayutilities is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program; if not, see <http://www.gnu.org/licenses/>.
+#
+# Copyright (C) 2013 Raphael Grifone <raphael.grifone at esrf.fr>
+# Copyright (C) 2013 Dominik Kriegner <dominik.kriegner at gmail.com>
+
+"""
+The function below is a modification of the hotpixelkill function included in
+the xrayutilities_id01_functions.py file.
+
+Instead of manually specifying the list of hot pixel they are automatically
+determined from a series of dark images. The idea is as follows: If in the
+average data of several dark images (no intentional x-ray radiations during
+acquisition) a signal above a certain threshold remains it is expected to arise
+from a hot pixel and such pixels should be removed to avoid spikes in the data.
+"""
+
+import numpy
+import xrayutilities as xu
+import glob
+
+
+def hotpixelkill(ccd):
+ """
+ function to remove hot pixels from CCD frames
+ """
+ ccd[hotpixelnumbers] = 0
+ # one could also use NaN here, since NaN values are
+ # ignored by the gridder
+ return ccd
+
+# identify hot pixels numbers from a series of dark images
+
+# open a series of 2D detector frames
+ccdavg = numpy.empty(0)
+n = 0
+for f in glob.glob("G:\data\dark*.edf"):
+ e = xu.io.EDFFile(f)
+ ccdraw = e.data
+ try:
+ ccdavg += ccdraw
+ except:
+ ccdavg = ccdraw.astype(numpy.float)
+ n += 1
+
+ccdavg /= float(n)
+
+# adjust treshold value: either as absolute value or in relation to the maximum
+threshold = 10 # counts
+# or
+# threshold = ccdraw.max()*0.1 #take 10% of maximum intensity
+
+# determine hot pixels by comparison with the threshold value
+hotpixelnumbers = numpy.where(ccdraw > threshold)
diff --git a/examples/xrayutilities_kmap_example_ESRF.py b/examples/xrayutilities_kmap_example_ESRF.py
index 3965aa6..19f3187 100644
--- a/examples/xrayutilities_kmap_example_ESRF.py
+++ b/examples/xrayutilities_kmap_example_ESRF.py
@@ -1,101 +1,101 @@
-# This file is part of xrayutilities.
-#
-# xrayutilities is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation; either version 2 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, see <http://www.gnu.org/licenses/>.
-#
-# Copyright (C) 2014 Raphael Grifone <raphael.grifone at esrf.fr>
-# Copyright (C) 2014 Dominik Kriegner <dominik.kriegner at gmail.com>
-
-import xrayutilities as xu
-import os
-import numpy
-import matplotlib.pyplot as plt
-
-# define some convenience variables
-en = 9000.0 # x-ray energy in eV
-home = "\\homefolder"
-workdir = os.path.join(home, 'work')
-specdir = home # location of spec file
-sample = "sample" # sample name -> used as spec file name
-ccdfiletmp = "ccdfilename"
-# region of interest on the detector; useful to reduce the amount of data
-roi = [0, 516, 50, 300]
-
-# define experimental geometry and detector parameters
-# 2S+2D goniometer (simplified ID01 goniometer, sample mu,phi detector nu,del
-qconv = xu.experiment.QConversion(['z+', 'y-'], ['z+', 'y-'], [1, 0, 0])
-# convention for coordinate system: x downstream; z upwards; y to the
-# "outside" (righthanded)
-hxrd = xu.HXRD([1, 1, 0], [0, 0, 1], en=en, qconv=qconv)
-hxrd.Ang2Q.init_area('z-', 'y+', cch1=200.07, cch2=297.75, Nch1=516, Nch2=516,
- pwidth1=9.4489e-05, pwidth2=9.4452e-05, distance=1.,
- detrot=-0.801, tiltazimuth=30.3, tilt=1.611, roi=roi)
-
-
-def hotpixelkill(ccd):
- """
- function to remove hot pixels from CCD frames or apply any other filter.
- """
- # insert your own code here
- return ccd
-
-U = numpy.identity(3) # orientation matrix of the sample
-
-scannr = numpy.arange(0, 100)
-
-nx, ny = 100, 50
-
-# specfile, scannumbers, nx,ny, motornames, optional column names (ID01
-# values are default)
-fss = xu.io.FastScanSeries(sample, scannr, nx, ny, 'Mu', 'Eta', 'Nu', 'Delta',
- xmotor='adcY', ymotor='adcX', ccdnr='imgnr',
- path=specdir)
-# retrace clean all scans
-fss.retrace_clean()
-# align different scans (misalignment needs to be determined manually or if
-# your application allows also by a 2d correllation code
-# see e.g. scipy.signal.correlate2d
-# fss.align(deltax,deltay)
-
-# real space grid
-g2d = xu.Gridder2D(nx, ny)
-# read all motor positions from the data files
-fss.read_motors()
-
-# plot counter intensity on a grid
-for idx, fs in enumerate(fss.fastscans):
- print(idx)
- g2d.Clear()
- g2d(fs.data['adcX'], fs.data['adcY'], fs.data['mpx4int'])
- plt.figure()
- plt.contourf(g2d.xaxis, g2d.yaxis, g2d.data.T, 50)
- plt.xlabel("X (um)")
- plt.ylabel("Y (um)")
-
-posx, posy = 50, 30
-# reduce data: number of pixels to average in each detector direction
-nav = [2, 2]
-
-qnx, qny, qnz = (80, 100, 101)
-g = fss.gridRSM(posx, posy, qnx, qny, qnz, qconv, ccdfiletmp, path='',
- roi=roi, nav=nav, typ='index', filterfunc=hotpixelkill,
- UB=U)
-# with typ='real' the position should be real space coordinates. with
-# typ='index' the posx,y should specify indices within the range(nx)
-# range(ny)
-
-# g now contains a Gridder3D object which can be used for visualization
-# see xrayutilities_example_plot_3D_ESRF_ID01 for example code
-
-# Note: if you instead want to grid in two dimensions you can decrease one
-# of qnx,qny or qnz to 1 and interprate the data in 2D
+# This file is part of xrayutilities.
+#
+# xrayutilities is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program; if not, see <http://www.gnu.org/licenses/>.
+#
+# Copyright (C) 2014 Raphael Grifone <raphael.grifone at esrf.fr>
+# Copyright (C) 2014 Dominik Kriegner <dominik.kriegner at gmail.com>
+
+import xrayutilities as xu
+import os
+import numpy
+import matplotlib.pyplot as plt
+
+# define some convenience variables
+en = 9000.0 # x-ray energy in eV
+home = "\\homefolder"
+workdir = os.path.join(home, 'work')
+specdir = home # location of spec file
+sample = "sample" # sample name -> used as spec file name
+ccdfiletmp = "ccdfilename"
+# region of interest on the detector; useful to reduce the amount of data
+roi = [0, 516, 50, 300]
+
+# define experimental geometry and detector parameters
+# 2S+2D goniometer (simplified ID01 goniometer, sample mu,phi detector nu,del
+qconv = xu.experiment.QConversion(['z+', 'y-'], ['z+', 'y-'], [1, 0, 0])
+# convention for coordinate system: x downstream; z upwards; y to the
+# "outside" (righthanded)
+hxrd = xu.HXRD([1, 1, 0], [0, 0, 1], en=en, qconv=qconv)
+hxrd.Ang2Q.init_area('z-', 'y+', cch1=200.07, cch2=297.75, Nch1=516, Nch2=516,
+ pwidth1=9.4489e-05, pwidth2=9.4452e-05, distance=1.,
+ detrot=-0.801, tiltazimuth=30.3, tilt=1.611, roi=roi)
+
+
+def hotpixelkill(ccd):
+ """
+ function to remove hot pixels from CCD frames or apply any other filter.
+ """
+ # insert your own code here
+ return ccd
+
+U = numpy.identity(3) # orientation matrix of the sample
+
+scannr = numpy.arange(0, 100)
+
+nx, ny = 100, 50
+
+# specfile, scannumbers, nx,ny, motornames, optional column names (ID01
+# values are default)
+fss = xu.io.FastScanSeries(sample, scannr, nx, ny, 'Mu', 'Eta', 'Nu', 'Delta',
+ xmotor='adcY', ymotor='adcX', ccdnr='imgnr',
+ path=specdir)
+# retrace clean all scans
+fss.retrace_clean()
+# align different scans (misalignment needs to be determined manually or if
+# your application allows also by a 2d correllation code
+# see e.g. scipy.signal.correlate2d
+# fss.align(deltax,deltay)
+
+# real space grid
+g2d = xu.Gridder2D(nx, ny)
+# read all motor positions from the data files
+fss.read_motors()
+
+# plot counter intensity on a grid
+for idx, fs in enumerate(fss.fastscans):
+ print(idx)
+ g2d.Clear()
+ g2d(fs.data['adcX'], fs.data['adcY'], fs.data['mpx4int'])
+ plt.figure()
+ plt.contourf(g2d.xaxis, g2d.yaxis, g2d.data.T, 50)
+ plt.xlabel("X (um)")
+ plt.ylabel("Y (um)")
+
+posx, posy = 50, 30
+# reduce data: number of pixels to average in each detector direction
+nav = [2, 2]
+
+qnx, qny, qnz = (80, 100, 101)
+g = fss.gridRSM(posx, posy, qnx, qny, qnz, qconv, ccdfiletmp, path='',
+ roi=roi, nav=nav, typ='index', filterfunc=hotpixelkill,
+ UB=U)
+# with typ='real' the position should be real space coordinates. with
+# typ='index' the posx,y should specify indices within the range(nx)
+# range(ny)
+
+# g now contains a Gridder3D object which can be used for visualization
+# see xrayutilities_example_plot_3D_ESRF_ID01 for example code
+
+# Note: if you instead want to grid in two dimensions you can decrease one
+# of qnx,qny or qnz to 1 and interprate the data in 2D
diff --git a/examples/xrayutilities_user.conf b/examples/xrayutilities_user.conf
index 31c3c0a..d087dbd 100644
--- a/examples/xrayutilities_user.conf
+++ b/examples/xrayutilities_user.conf
@@ -1,15 +1,15 @@
-# XRUTILS user configuration
+# XRUTILS user configuration
# default values for some properties of xrayutilities may be set
-# the syntax follows the one of the ConfigParser python module,
+# the syntax follows the one of the ConfigParser Python module,
# which is similar to .ini files
-# if you want to use this user-specific config file you need to place it in
-# ~/.xrayutilities.conf
-# or the local directory
-# ./xrayutilities.conf
+# if you want to use this user-specific config file you need to place it in
+# ~/.xrayutilities.conf
+# or the local directory
+# ./xrayutilities.conf
-# The config file with the default parameters is found in the python installation
-# path of xrayutilities. It is however not recommended to change things there,
+# The config file with the default parameters is found in the Python installation
+# path of xrayutilities. It is however not recommended to change things there,
# instead the user-specific config file
# begin of xrayutilities configuration
@@ -22,7 +22,7 @@
# 3: debuging output (e.g. print everything, which could be interesing)
verbosity=1
-# default wavelength in Angstrom,
+# default wavelength in Angstrom,
# wavelength=1.5406
# default energy in eV
diff --git a/setup.py b/setup.py
index 9b36e14..831aa07 100644
--- a/setup.py
+++ b/setup.py
@@ -14,7 +14,7 @@
# along with this program; if not, see <http://www.gnu.org/licenses/>.
#
# Copyright (C) 2009 Eugen Wintersberger <eugen.wintersberger at desy.de>
-# Copyright (C) 2010-2011,2013 Dominik Kriegner <dominik.kriegner at gmail.com>
+# Copyright (C) 2010-2015 Dominik Kriegner <dominik.kriegner at gmail.com>
from distutils.core import setup, Extension
from distutils.command.build_ext import build_ext
@@ -120,13 +120,18 @@ except ImportError:
setup(
name="xrayutilities",
- version="1.1.1",
+ version="1.1.2",
author="Eugen Wintersberger, Dominik Kriegner",
description="package for x-ray diffraction data evaluation",
classifiers=[
+ "Programming Language :: C",
+ "Programming Language :: Python :: 2.7",
+ "Programming Language :: Python :: 3.2",
+ "Programming Language :: Python :: 3.3",
+ "Programming Language :: Python :: 3.4",
"Topic :: Scientific/Engineering :: Physics",
"Intended Audience :: Science/Research",
- "Development Status :: 4 - Beta",
+ "Development Status :: 5 - Production/Stable",
"License :: OSI Approved :: GNU General Public License v2 or later "
"(GPLv2+)"
],
diff --git a/xrayutilities.pdf b/xrayutilities.pdf
index 9477d79..035b0c9 100644
--- a/xrayutilities.pdf
+++ b/xrayutilities.pdf
@@ -8,8 +8,7 @@
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/Filter [/ASCII85Decode /FlateDecode]
/Length 99
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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>>
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 3580
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>>
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/Filter [/ASCII85Decode /FlateDecode]
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>>
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/Filter [/ASCII85Decode /FlateDecode]
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>>
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 1532
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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-/Filter [/ASCII85Decode /FlateDecode]
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<<
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
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<<
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2822
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>>
stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2797
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>>
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2666
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>>
stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2412
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2555
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2656
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2166
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>>
stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2180
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>>
stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2326
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2297
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 1622
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stream
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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+/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
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<<
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endstream
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<<
/Filter [/ASCII85Decode /FlateDecode]
-/Length 2552
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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>>
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<<
/Filter [/ASCII85Decode /FlateDecode]
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stream
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/Filter [/ASCII85Decode /FlateDecode]
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stream
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
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<<
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
/Filter [/ASCII85Decode /FlateDecode]
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<<
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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/Filter [/ASCII85Decode /FlateDecode]
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diff --git a/xrayutilities/analysis/sample_align.py b/xrayutilities/analysis/sample_align.py
index aecda43..7d9e112 100644
--- a/xrayutilities/analysis/sample_align.py
+++ b/xrayutilities/analysis/sample_align.py
@@ -224,12 +224,12 @@ def psd_chdeg(angles, channels, stdev=None, usetilt=True, plot=True,
ax2 = plt.subplot(212, sharex=ax1)
if modelline:
plt.plot(angp, models._unilin(fittan.beta,
- numpy.degrees(numpy.tan(numpy.radians(angp))))
- - models._unilin(fitlin.beta, angp),
+ numpy.degrees(numpy.tan(numpy.radians(angp)))) -
+ models._unilin(fitlin.beta, angp),
modelline, label=mlabel, lw=linewidth)
if usetilt:
- plt.plot(angp, straight_tilt(fittilt.beta, angp)
- - models._unilin(fitlin.beta, angp),
+ plt.plot(angp, straight_tilt(fittilt.beta, angp) -
+ models._unilin(fitlin.beta, angp),
modeltilt, label=mtiltlabel, lw=linewidth)
if stdev is None:
plt.plot(angles, channels - models._unilin(fitlin.beta, angles),
@@ -439,7 +439,8 @@ def linear_detector_calib(angle, mca_spectra, **keyargs):
def area_detector_calib(angle1, angle2, ccdimages, detaxis, r_i, plot=True,
cut_off=0.7, start=(0, 0, 0, 0),
fix=(False, False, False, False),
- fig=None, wl=None, plotlog=False, debug=False):
+ fig=None, wl=None, plotlog=False, debug=False,
+ nwindow=50):
"""
function to calibrate the detector parameters of an area detector
it determines the detector tilt possible rotations and offsets in the
@@ -472,6 +473,10 @@ def area_detector_calib(angle1, angle2, ccdimages, detaxis, r_i, plot=True,
affect the scaling of the error
plotlog . flag to specify if the created error plot should be on
log-scale
+ nwindow . window size for determination of the center of mass position
+ after the center of mass of every full image is determined,
+ the center of mass is determined again using a window of
+ size nwindow in order to reduce the effect of hot pixels.
debug ... flag to specify that you want to see verbose output and
saving of images to show if the CEN determination works
@@ -512,15 +517,23 @@ def area_detector_calib(angle1, angle2, ccdimages, detaxis, r_i, plot=True,
if debug:
print("average intensity per image: %.1f" % avg)
+ nw = nwindow // 2
for i in range(Npoints):
img = ccdimages[i]
if numpy.sum(img) > cut_off * avg:
- [cen1, cen2] = center_of_mass(img)
+ [cen1r, cen2r] = center_of_mass(img)
+ [cen1, cen2] = center_of_mass(
+ img[max(int(cen1r) - nw, 0):
+ min(int(cen1r) + nw, img.shape[0]),
+ max(int(cen2r) - nw, 0):
+ min(int(cen2r) + nw, img.shape[1])])
+ cen1 += max(int(cen1r) - nw, 0)
+ cen2 += max(int(cen2r) - nw, 0)
if debug:
plt.figure("_ccd")
plt.imshow(utilities.maplog(img), origin='low')
plt.plot(cen2, cen1, "wo", mfc='none')
- plt.axis([cen2 - 25, cen2 + 25, cen1 - 25, cen1 + 25])
+ plt.axis([cen2 - nw, cen2 + nw, cen1 - nw, cen1 + nw])
plt.savefig("xu_calib_ccd_img%d.png" % i)
plt.close("_ccd")
@@ -528,9 +541,9 @@ def area_detector_calib(angle1, angle2, ccdimages, detaxis, r_i, plot=True,
n2 = numpy.append(n2, cen2)
ang1 = numpy.append(ang1, angle1[i])
ang2 = numpy.append(ang2, angle2[i])
- # if debug:
- # print("%8.3f %8.3f \t%.2f %.2f" % (angle1[i], angle2[i],
- # cen1, cen2))
+ if debug:
+ print("%8.3f %8.3f \t%.2f %.2f" % (angle1[i], angle2[i],
+ cen1, cen2))
Nused = len(ang1)
if debug:
@@ -764,7 +777,7 @@ def _determine_detdir(ang1, ang2, n1, n2, detaxis, r_i):
def _area_detector_calib_fit(ang1, ang2, n1, n2, detaxis, r_i, detdir1,
detdir2, start=(0, 0, 0, 0),
- fix = (False, False, False, False),
+ fix=(False, False, False, False),
full_output=False, wl=1., debug=False):
"""
INTERNAL FUNCTION
@@ -967,8 +980,9 @@ def _area_detector_calib_fit(ang1, ang2, n1, n2, detaxis, r_i, detdir1,
dAngles = numpy.concatenate((dAngles, arg))
# add detector rotation around primary beam
dAngles = numpy.concatenate((dAngles,
- numpy.ones(arg.shape, dtype=numpy.double)
- * _area_rot))
+ numpy.ones(arg.shape,
+ dtype=numpy.double) *
+ _area_rot))
# read channel numbers
n1 = numpy.array((), dtype=numpy.double)
@@ -1104,7 +1118,7 @@ def _area_detector_calib_fit(ang1, ang2, n1, n2, detaxis, r_i, detdir1,
ifixb += (int(not fix[i]),)
my_odr = odr.ODR(data, model, beta0=param, ifixb=(1, 1, 1, 1) + ifixb,
- ifixx =(0, 0, 0, 0), stpb=(0.4, 0.4, pwidth1 / 50.,
+ ifixx=(0, 0, 0, 0), stpb=(0.4, 0.4, pwidth1 / 50.,
pwidth2 / 50., 2, 0.125, 0.01, 0.01),
sclb=(1 / numpy.abs(cch1), 1 / numpy.abs(cch2),
1 / pwidth1, 1 / pwidth2, 1 / 90., 1 / 0.2, 1 / 0.2,
@@ -1270,8 +1284,8 @@ def area_detector_calib_hkl(sampleang, angle1, angle2, ccdimages, hkls,
for i in range(Npoints):
img = ccdimages[i]
- if ((numpy.sum(img) > cut_off * avg)
- or (numpy.all(hkls[i] != (0, 0, 0)))):
+ if ((numpy.sum(img) > cut_off * avg) or
+ (numpy.all(hkls[i] != (0, 0, 0)))):
[cen1, cen2] = center_of_mass(img)
if debug:
plt.figure("_ccd")
@@ -1873,7 +1887,7 @@ def _area_detector_calib_fit2(sang, ang1, ang2, n1, n2, hkls, experiment,
ifixb += (int(not fix[i]),)
my_odr = odr.ODR(data, model, beta0=param, ifixb=(1, 1, 1, 1) + ifixb,
- ifixx =(0, 0, 0, 0, 0, 0, 0, 0),
+ ifixx=(0, 0, 0, 0, 0, 0, 0, 0),
stpb=(0.4, 0.4, pwidth1 / 50., pwidth2 / 50., 2, 0.125,
0.01, 0.01, 0.01, 1., 0.0001),
sclb=(1 / numpy.abs(cch1), 1 / numpy.abs(cch2),
@@ -2053,14 +2067,20 @@ def miscut_calc(phi, aomega, zeros=None, omega0=None, plot=True):
# first guess for the parameters
# omega0,phi0,miscut
p0 = (om.mean(), a[om.argmax()], om.max() - om.min())
- fitfunc = lambda p, phi: numpy.abs(p[2]) * \
- numpy.cos(numpy.radians(phi - (p[1] % 360.))) + p[0]
+
+ def fitfunc(p, phi):
+ return numpy.abs(p[2]) * \
+ numpy.cos(numpy.radians(phi - (p[1] % 360.))) + p[0]
+
else:
# first guess for the parameters
p0 = (a[om.argmax()], om.max() - om.min()) # omega0,phi0,miscut
- fitfunc = lambda p, phi: numpy.abs(p[1]) * \
- numpy.cos(numpy.radians(phi - (p[0] % 360.))) + omega0
- errfunc = lambda p, phi, om: fitfunc(p, phi) - om
+
+ def fitfunc(p, phi):
+ return numpy.abs(p[1]) * \
+ numpy.cos(numpy.radians(phi - (p[0] % 360.))) + omega0
+
+ def errfunc(p, phi, om): return fitfunc(p, phi) - om
p1, success = optimize.leastsq(errfunc, p0, args=(a, om), maxfev=10000)
if config.VERBOSITY >= config.INFO_ALL:
diff --git a/xrayutilities/experiment.py b/xrayutilities/experiment.py
index 0d379c4..da83a82 100644
--- a/xrayutilities/experiment.py
+++ b/xrayutilities/experiment.py
@@ -14,7 +14,7 @@
# along with this program; if not, see <http://www.gnu.org/licenses/>.
#
# Copyright (C) 2009-2010 Eugen Wintersberger <eugen.wintersberger at desy.de>
-# Copyright (C) 2009-2014 Dominik Kriegner <dominik.kriegner at gmail.com>
+# Copyright (C) 2009-2015 Dominik Kriegner <dominik.kriegner at gmail.com>
# Copyright (C) 2012 Tanja Etzelstorfer <tanja.etzelstorfer at jku.at>
"""
@@ -1436,26 +1436,27 @@ class Experiment(object):
Parameters
----------
- **kwargs: optional keyword arguments
- B: reciprocal space conversion matrix of a Material.
- you can specify the matrix B (default identiy matrix)
- shape needs to be (3,3)
- mat: Material object to use to obtain a B matrix
- (e.g. xu.materials.Si)
- can be used as alternative to the B keyword argument
- B is favored in case both are given
- U: orientation matrix U can be given
- if none is given the orientation defined in the Experiment
- class is used.
- dettype:detector type: one of ('point', 'linear', 'area')
- decides which routine of Ang2Q to call
- default 'point'
- delta: giving delta angles to correct the given ones for
- misalignment. delta must be an numpy array or list of
- length 2. used angles are than om,tt - delta
- wl: x-ray wavelength in angstroem (default: self._wl)
- en: x-ray energy in eV (default: converted self._wl)
- deg: flag to tell if angles are passed as degree (default: True)
+ **kwargs: optional keyword arguments
+ B: reciprocal space conversion matrix of a Material. you
+ can specify the matrix B (default identiy matrix) shape
+ needs to be (3,3)
+ mat: Material object to use to obtain a B matrix
+ (e.g. xu.materials.Si) can be used as alternative to
+ the B keyword argument B is favored in case both are
+ given
+ U: orientation matrix U can be given. If none is given the
+ orientation defined in the Experiment class is used.
+ dettype: detector type: one of ('point', 'linear', 'area')
+ decides which routine of Ang2Q to call. default 'point'
+ delta: giving delta angles to correct the given ones for
+ misalignment. delta must be an numpy array or list of
+ length 2. used angles are than om,tt - delta
+ wl: x-ray wavelength in angstroem (default: self._wl)
+ en: x-ray energy in eV (default: converted self._wl)
+ deg: flag to tell if angles are passed as degree (default:
+ True)
+ sampledis: sample displacement vector in relative units of the
+ detector distance (default: (0,0,0))
Returns
-------
@@ -1466,13 +1467,13 @@ class Experiment(object):
for k in kwargs.keys():
if k not in ['U', 'B', 'mat', 'dettype', 'delta', 'wl', 'en',
- 'deg']:
+ 'deg', 'sampledis']:
raise Exception("unknown keyword argument given: allowed are "
"'B': orthonormalization matrix, "
"'U': orientation matrix, "
"'mat': material object, "
"'dettype': string with detector type, "
- "'delta,wl,en,deg' from Ang2Q")
+ "'delta,wl,en,deg,sampledis' from Ang2Q")
if "B" in kwargs:
B = numpy.array(kwargs['B'])
diff --git a/xrayutilities/gridder2d.py b/xrayutilities/gridder2d.py
index a1b8154..08626dd 100644
--- a/xrayutilities/gridder2d.py
+++ b/xrayutilities/gridder2d.py
@@ -242,8 +242,7 @@ class Gridder2DList(Gridder2D):
if not self.fixed_range:
# assume that with setting keep_data the user wants to call the
# gridder more often and obtain a reasonable result
- self.dataRange((x.min(), x.max()), (y.min(), y.max()),
- self.keep_data)
+ self.dataRange(x.min(), x.max(), y.min(), y.max(), self.keep_data)
# perform gridding this should be moved to native code if possible
def gindex(x, min, delt):
diff --git a/xrayutilities/io/__init__.py b/xrayutilities/io/__init__.py
index dab338b..91055cc 100644
--- a/xrayutilities/io/__init__.py
+++ b/xrayutilities/io/__init__.py
@@ -38,6 +38,7 @@ from .spec import SPECFile
from .spec import SPECScan
from .spec import SPECLog
from .spec import geth5_scan
+from .spec import getspec_scan
# for backward compatibility import also as old name
from .spec import geth5_scan as geth5_map
diff --git a/xrayutilities/io/edf.py b/xrayutilities/io/edf.py
index 7908d92..b3d2429 100644
--- a/xrayutilities/io/edf.py
+++ b/xrayutilities/io/edf.py
@@ -14,7 +14,8 @@
# along with this program; if not, see <http://www.gnu.org/licenses/>.
#
# Copyright (C) 2009-2010 Eugen Wintersberger <eugen.wintersberger at desy.de>
-# Copyright (C) 2010-2012,2014 Dominik Kriegner <dominik.kriegner at gmail.com>
+# Copyright (C) 2010-2012,2014-2015
+# Dominik Kriegner <dominik.kriegner at gmail.com>
# Copyright (C) 2012 Tanja Etzelstorfer <tanja.etzelstorfer at jku.at>
# module for handling files stored in the EDF data format developed by the ESRF
@@ -61,7 +62,7 @@ DataTypeDict = {"SignedByte": "b",
class EDFFile(object):
def __init__(self, fname, nxkey="Dim_1", nykey="Dim_2",
- dtkey="DataType", path="", header=True):
+ dtkey="DataType", path="", header=True, keep_open=False):
"""
required arguments:
fname ....... name of the EDF file of type .edf or .edf.gz
@@ -75,6 +76,8 @@ class EDFFile(object):
for the binary data
path ........ path to the EDF file
header ...... has header (default true)
+ keep_open ... if True the file handle is kept open between multiple
+ calls which can cause significant speed-ups
"""
self.filename = fname
@@ -98,6 +101,11 @@ class EDFFile(object):
self._dtype = []
self.Parse()
+ if keep_open:
+ self.fid = xu_open(self.full_filename, 'rb')
+ else:
+ self.fid = None
+
self.nimages = len(self._data_offsets)
self.header = self._headers[0]
@@ -152,7 +160,7 @@ class EDFFile(object):
[key, value] = edf_kv_split.split(
line_buffer, 1)
except:
- print("XU.io.EDFFile.ReadData: "
+ print("XU.io.EDFFile.Parse: "
"line_buffer: %s" % line_buffer)
key = key.strip()
@@ -233,18 +241,26 @@ class EDFFile(object):
----------
nimg: number of the image which should be read (starts with 0)
"""
- # to read the data we have to open the file in binary mode
- with xu_open(self.full_filename, 'rb') as binfid:
+ if self.fid:
+ binfid = self.fid
# move to the data section - jump over the header
binfid.seek(self._data_offsets[nimg], 0)
# read the data
tot_nofp = self._dimx[nimg] * self._dimy[nimg]
fmt_str = self._fmt_str[nimg]
bindata = binfid.read(struct.calcsize(tot_nofp * fmt_str))
- if config.VERBOSITY >= config.DEBUG:
- print("XU.io.EDFFile: read binary data: nofp: %d len: %d"
- % (tot_nofp, len(bindata)))
- print("XU.io.EDFFile: format: %s" % fmt_str)
+ else:
+ with xu_open(self.full_filename, 'rb') as binfid:
+ # move to the data section - jump over the header
+ binfid.seek(self._data_offsets[nimg], 0)
+ # read the data
+ tot_nofp = self._dimx[nimg] * self._dimy[nimg]
+ fmt_str = self._fmt_str[nimg]
+ bindata = binfid.read(struct.calcsize(tot_nofp * fmt_str))
+ if config.VERBOSITY >= config.DEBUG:
+ print("XU.io.EDFFile: read binary data: nofp: %d len: %d"
+ % (tot_nofp, len(bindata)))
+ print("XU.io.EDFFile: format: %s" % fmt_str)
try:
num_data = struct.unpack(tot_nofp * fmt_str, bindata)
diff --git a/xrayutilities/io/fastscan.py b/xrayutilities/io/fastscan.py
index 9a896ff..ffb73b7 100644
--- a/xrayutilities/io/fastscan.py
+++ b/xrayutilities/io/fastscan.py
@@ -1,688 +1,856 @@
-# This file is part of xrayutilities.
-#
-# xrayutilities is free software; you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation; either version 2 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program; if not, see <http://www.gnu.org/licenses/>.
-#
-# Copyright (C) 2014 Raphael Grifone <raphael.grifone at esrf.fr>
-# Copyright (C) 2014 Dominik Kriegner <dominik.kriegner at gmail.com>
-
-"""
-modules to help with the analysis of FastScan data acquired at the ESRF.
-FastScan data are X-ray data (various detectors possible) acquired during
-scanning the sample in real space with a Piezo Scanner. The same functions
-might be used to analze traditional SPEC mesh scans.
-
-The module provides three core classes:
-
-* FastScan
-* FastScanCCD
-* FastScanSeries
-
-where the first two are able to parse single mesh/FastScans when one is
-interested in data of a single channel detector or are detector and the last
-one is able to parse full series of such mesh scans with either type of
-detector
-
-see examples/xrayutilities_kmap_ESRF.py for an example script
-"""
-
-import os.path
-import numpy
-
-# relative imports
-from . import SPECFile
-from . import EDFFile
-from ..exception import InputError
-from ..gridder import delta
-from ..gridder2d import Gridder2D
-from ..gridder2d import Gridder2DList
-from ..gridder3d import Gridder3D
-from ..normalize import blockAverage2D
-
-# python 2to3 compatibility
-try:
- basestring
-except NameError:
- basestring = str
-
-
-class FastScan(object):
-
- """
- class to help parsing and treating fast scan data. FastScan is the
- aquisition of X-ray data while scanning the sample with piezo stages in
- real space. It's is available at several beamlines at the ESRF synchrotron
- light-source.
- """
-
- def __init__(self, filename, scannr,
- xmotor='adcX', ymotor='adcY', path=""):
- """
- Constructor routine for the FastScan object. It initializes the object
- and parses the spec-scan for the needed data which are saved in
- properties of the FastScan object.
-
- Parameters
- ----------
- filename: file name of the fast scan spec file
- scannr: scannr of the to be parsed fast scan
- optional:
- xmotor: motor name of the x-motor (default: 'adcX' (ID01))
- ymotor: motor name of the y-motor (default: 'adcY' (ID01))
- path: optional path of the FastScan spec file
- """
- self.filename = filename
- self.full_filename = os.path.join(path, filename)
- self.filename = os.path.basename(self.full_filename)
-
- self.scannr = scannr
- self.xmotor = xmotor
- self.ymotor = ymotor
- # read the scan
- self.specscan = None
- self.parse()
-
- def parse(self):
- """
- parse the specfile for the scan number specified in the constructor and
- store the needed informations in the object properties
- """
-
- # parse the file
- self.specfile = SPECFile(self.full_filename)
- self.specscan = self.specfile.__getattr__('scan%d' % self.scannr)
- self.specscan.ReadData()
-
- self.xvalues = self.specscan.data[self.xmotor]
- self.yvalues = self.specscan.data[self.ymotor]
-
- self.data = self.specscan.data
-
- def motorposition(self, motorname):
- """
- read the position of motor with name given by motorname from the data
- file. In case the motor is included in the data columns the returned
- object is an array with all the values from the file (although retrace
- clean is respected if already performed). In the case the motor is not
- moved during the scan only one value is returned.
-
- Parameters
- ----------
- motorname: name of the motor for which the position is wanted
-
- Returns
- -------
- val: motor position(s) of motor with name motorname during the scan
- """
- if self.specscan:
- # try reading value from data
- try:
- return self.data[motorname]
- except ValueError:
- try:
- return self.specscan.init_motor_pos['INIT_MOPO_%s'
- % motorname]
- except ValueError:
- raise ValueError("given motorname '%s' not found in the "
- "Spec-data" % motorname)
- else:
- return None
-
- def retrace_clean(self):
- """
- function to clean the data of the scan from retrace artifacts created
- by the zig-zag scanning motion of the piezo actuators the function
- cleans the xvalues, yvalues and data attribute of the FastScan object.
- """
-
- # set window to determin the slope
- window = [-1, 0, 1]
- # calc the slope of x_motor movement using a window for better acuracy
- slope = numpy.convolve(self.xvalues, window, mode='same') / \
- numpy.convolve(numpy.arange(len(self.xvalues)), window, 'same')
- # select where slope is above the slope mean value
- # this can be modified if data points are missing of the retrace does
- # not clean all points
- mask = numpy.where(slope > slope.mean())
-
- # reduce data size by cutting out retrace
- self.xvalues = self.xvalues[mask]
- self.yvalues = self.yvalues[mask]
- self.data = self.data[mask]
-
- def grid2D(self, nx, ny, **kwargs):
- """
- function to grid the counter data and return the gridded X,Y and
- Intensity values.
-
- Parameters
- ----------
- nx,ny: number of bins in x,y direction
-
- optional keyword arguments:
- counter: name of the counter to use for gridding (default: 'mpx4int'
- (ID01))
- gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
-
- Returns
- -------
- Gridder2D object with X,Y,data on regular x,y-grid
- """
- if 'counter' in kwargs:
- self.counter = kwargs['counter']
- kwargs.pop("counter")
- else:
- self.counter = 'mpx4int'
-
- if 'gridrange' in kwargs:
- gridrange = kwargs['gridrange']
- kwargs.pop("gridrange")
- else:
- gridrange = None
-
- # define gridder
- g2d = Gridder2D(nx, ny)
- if gridrange:
- g2d.dataRange(gridrange[0][0], gridrange[0][1],
- gridrange[1][0], gridrange[1][1])
-
- # check if counter is in data fields
- try:
- inte = self.data[self.counter]
- except ValueError:
- raise ValueError("field named '%s' not found in data parsed from "
- "scan #%d in file %s"
- % (self.counter, self.scannr, self.filename))
-
- # grid data
- g2d(self.xvalues, self.yvalues, self.data[self.counter])
-
- # return gridded data
- return g2d
-
-
-class FastScanCCD(FastScan):
-
- """
- class to help parsing and treating fast scan data including CCD frames.
- FastScan is the aquisition of X-ray data while scanning the sample with
- piezo stages in real space. It's is available at several beamlines at the
- ESRF synchrotron light-source. During such fast scan at every grid point
- CCD frames are recorded and need to be analyzed
- """
-
- def _gridCCDnumbers(self, nx, ny, ccdnr, gridrange=None):
- """
- internal function to grid the CCD frame number to produce a list of
- ccd-files per bin needed for the further treatment
-
- Parameters
- ----------
- nx,ny: number of bins in x,y direction
- ccdnr: array with ccd file numbers of length
- length(FastScanCCD.data) OR a string with the data
- column name for the file ccd-numbers
-
- optional:
- gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
-
- Returns
- -------
- gridder object: regular x,y-grid as well as 4-dimensional data
- object
- """
- g2l = Gridder2DList(nx, ny)
- if gridrange:
- g2l.dataRange(gridrange[0][0], gridrange[0][1],
- gridrange[1][0], gridrange[1][1])
-
- if isinstance(ccdnr, basestring):
- # check if counter is in data fields
- try:
- ccdnumbers = self.data[ccdnr]
- except ValueError:
- raise ValueError("field named '%s' not found in data parsed "
- "from scan #%d in file %s"
- % (ccdnr, self.scannr, self.filename))
- elif isinstance(ccdnr, (list, tuple, numpy.ndarray)):
- ccdnumbers = ccdnr
- else:
- raise ValueError("xu.FastScanCCD: wrong data type for "
- "argument 'ccdnr'")
-
- # assign ccd frames to grid
- g2l(self.xvalues, self.yvalues, ccdnumbers)
-
- return g2l
-
- def gridCCD(self, nx, ny, ccdtemplate, ccdnr, roi=None, path="",
- nav=[1, 1], gridrange=None, filterfunc=None):
- """
- function to grid the internal data and ccd files and return the gridded
- X,Y and DATA values. DATA represents a 4D with first two dimensions
- representing X,Y and the remaining two dimensions representing detector
- channels
-
- Parameters
- ----------
- nx,ny: number of bins in x,y direction
- ccdtemplate: template string for the ccdfilenames
- ccdnr: array with ccd file numbers of length
- length(FastScanCCD.data) OR a string with the data
- column name for the file ccd-numbers
-
- optional:
- roi: region of interest on the 2D detector. should be a list
- of lower and upper bounds of detector channels for the
- two pixel directions (default: None)
- path: common path of the CCDframe
- nav: number of detector pixel which will be averaged together
- (reduces the date size)
- gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
- filterfunc: function applied to the CCD-frames before any
- processing. this function should take a single argument
- which is the ccddata which need to be returned with the
- same shape! e.g. remove hot pixels, flat/darkfield
- correction
-
- Returns
- -------
- X,Y,DATA: regular x,y-grid as well as 4-dimensional data object
- """
-
- g2l = _gridCCDnumbers(self, nx, ny, ccdnr, gridrange=gridrange)
- gdata = g2l.data
-
- self.ccdtemplate = os.path.join(path, ccdtemplate)
- # get CCDframe numbers and motor values
- valuelist = self.getCCDFrames(posx, posy, typ)
- # read ccd shape from first image
- ccdshape = blockAverage2D(
- EDFFile(self.ccdtemplate % (0, valuelist[0][-1][0])).data,
- nav[0], nav[1], roi=roi).shape
- self.ccddata = numpy.zeros((nx, ny, ccdshape[0], ccdshape[1]))
-
- # go through the gridded data and average the ccdframes
- for i in range(gdata.shape[0]):
- for j in range(gdata.shape[1]):
- if len(gdata[i, j]) == 0:
- continue
- else:
- framecount = 0
- # read ccdframes and average them
- for k in range(len(gdata[i, j])):
- e = EDFFile(self.ccdtemplate % gdata[i, j][k])
- if filterfunc:
- ccdfilt = filterfunc(e.data)
- else:
- ccdfilt = e.data
- ccdframe = blockAverage2D(ccdfilt, nav[0], nav[1],
- roi=roi)
- self.ccddata[i, j, :, :] += ccdframe
- framecount += 1
- self.ccddata[i, j, :, :] = self.ccddata[i, j, :, :] / \
- float(framecount)
-
- return g2l.xmatrix, g2l.ymatrix, self.ccddata
-
-
-class FastScanSeries(object):
-
- """
- class to help parsing and treating a series of fast scan data including CCD
- frames. FastScan is the aquisition of X-ray data while scanning the sample
- with piezo stages in real space. It's is available at several beamlines at
- the ESRF synchrotron light-source. During such fast scan at every grid
- point CCD frames are recorded and need to be analyzed.
-
- For the series of FastScans we assume that they are measured at different
- goniometer angles and therefore transform the data to reciprocal space.
- """
-
- def __init__(self, filenames, scannrs, nx, ny, *args, **kwargs):
- """
- Constructor routine for the FastScanSeries object. It initializes the
- object and creates a list of FastScanCCD objects. Importantly it also
- expects the motor names of the angles needed for reciprocal space
- conversion.
-
- Parameters
- ----------
- filenames: file names of the fast scan spec files, in case of more
- than one filename supply a list of names and also a list of
- scan numbers for the different files in the 'scannrs'
- argument
- scannrs: scannrs of the to be parsed fast scans. in case of one
- specfile this is a list of numbers (e.g. [1,2,3]). when
- multiple filenames are given supply a separate list for
- every file (e.g. [[1,2,3],[2,4]])
- nx,ny: grid-points for the real space grid
- *args: motor names for the Reciprocal space conversion. The order
- needs be as required by the QConversion.area() function.
- optional keyword arguments:
- xmotor: motor name of the x-motor (default: 'adcX' (ID01))
- ymotor: motor name of the y-motor (default: 'adcY' (ID01))
- ccdnr: name of the ccd-number data column
- (default: 'imgnr' (ID01))
- counter: name of a defined counter (roi) in the spec file
- (default: 'ccdint1' (ID01))
- path: optional path of the FastScan spec file (default: '')
-
- """
-
- if 'ccdnr' in kwargs:
- self.ccdnr = kwargs['ccdnr']
- kwargs.pop("ccdnr")
- else:
- self.ccdnr = 'imgnr'
-
- if 'counter' in kwargs:
- self.counter = kwargs['counter']
- kwargs.pop("counter")
- else:
- self.counter = 'ccdint1'
-
- self.fastscans = []
- self.nx = nx
- self.ny = ny
- self.motor_pos = None
- self.gridded = False
-
- self.gonio_motors = []
- # save motor names
- for arg in args:
- if not isinstance(arg, basestring):
- raise ValueError("one of the motor name arguments is not of "
- "type 'str' but %s" % str(type(arg)))
- self.gonio_motors.append(arg)
-
- # create list of FastScans
- if isinstance(filenames, basestring):
- filenames = [filenames]
- scannrs = [scannrs]
- if isinstance(filenames, (tuple, list)):
- for fname in filenames:
- for snrs in scannrs[filenames.index(fname)]:
- self.fastscans.append(FastScanCCD(fname, snrs, **kwargs))
- else:
- raise ValueError("argument 'filenames' is not of "
- "appropriate type!")
-
- def retrace_clean(self):
- """
- perform retrace clean for every FastScan in the series
- """
- self.gridded = False
- self.xmin = numpy.min(self.fastscans[0].xvalues)
- self.ymin = numpy.min(self.fastscans[0].yvalues)
- self.xmax = numpy.max(self.fastscans[0].xvalues)
- self.ymax = numpy.max(self.fastscans[0].yvalues)
-
- for fs in self.fastscans:
- fs.retrace_clean()
-
- if numpy.max(fs.xvalues) > self.xmax:
- self.xmax = numpy.max(fs.xvalues)
- if numpy.max(fs.yvalues) > self.ymax:
- self.ymax = numpy.max(fs.yvalues)
- if numpy.min(fs.xvalues) < self.xmin:
- self.xmin = numpy.min(fs.xvalues)
- if numpy.min(fs.yvalues) < self.ymin:
- self.ymin = numpy.min(fs.yvalues)
-
- def align(self, deltax, deltay):
- """
- Since a sample drift or shift due to rotation often occurs between
- different FastScans it should be correct before combining them. Since
- determining such a shift is not straight-forward in general the user
- needs to supply the routine with the shifts in order correct the
- x,y-values for the different FastScans. Such a routine could for
- example use the integrated CCD intensities and determine the shift
- using a cross-convolution.
-
- Parameters
- ----------
- deltax: list of shifts in x-direction for every FastScan in the
- data structure
- deltay: same for the y-direction
- """
- self.gridded = False
- self.xmin = numpy.min(self.fastscans[0].xvalues)
- self.ymin = numpy.min(self.fastscans[0].yvalues)
- self.xmax = numpy.max(self.fastscans[0].xvalues)
- self.ymax = numpy.max(self.fastscans[0].yvalues)
- for fs in self.fastscans:
- i = self.fastscans.index(fs)
- fs.xvalues += deltax[i]
- fs.yvalues += deltay[i]
-
- if numpy.max(fs.xvalues) > self.xmax:
- self.xmax = numpy.max(fs.xvalues)
- if numpy.max(fs.yvalues) > self.ymax:
- self.ymax = numpy.max(fs.yvalues)
- if numpy.min(fs.xvalues) < self.xmin:
- self.xmin = numpy.min(fs.xvalues)
- if numpy.min(fs.yvalues) < self.ymin:
- self.ymin = numpy.min(fs.yvalues)
-
- def read_motors(self):
- """
- read motor values from the series of fast scans
- """
- self.motor_pos = numpy.zeros((len(self.fastscans),
- len(self.gonio_motors)))
- for i in range(len(self.fastscans)):
- fs = self.fastscans[i]
- for j in range(len(self.gonio_motors)):
- mname = self.gonio_motors[j]
- self.motor_pos[i, j] = fs.motorposition(mname)
-
- def getCCDFrames(self, posx, posy, typ='real'):
- """
- function to determine the list of ccd-frame numbers for a specific real
- space position. The real space position must be within the data limits
- of the FastScanSeries otherwise an ValueError is thrown
-
- Parameters
- ----------
- posx: real space x-position or index in x direction
- posy: real space y-position or index in y direction
-
- optional:
- typ: type of coordinates. specifies if the position is specified as
- real space coordinate or as index. valid values are 'real' and
- 'index'. (default: 'real')
-
- Returns
- -------
- [[motorpos1, ccdnrs1], [motorpos2, ccdnrs2], ...] where motorposN is
- from the N-ths FastScan in the series and ccdnrsN is the list of
- according CCD-frames
- """
-
- # determine grid point for position x,y
- if typ == 'real':
- # grid point calculation
- def gindex(x, min, delt):
- return numpy.round((x - min) / delt)
-
- xdelta = delta(self.xmin, self.xmax, self.nx)
- ydelta = delta(self.ymin, self.ymax, self.ny)
- xidx = gindex(posx, self.xmin, xdelta)
- yidx = gindex(posy, self.ymin, ydelta)
- elif typ == 'index':
- xidx = posx
- yidx = posy
- else:
- raise ValueError("given value of 'typ' is invalid.")
-
- if xidx >= self.nx or xidx < 0:
- raise ValueError("specified x-position is out of the data range")
- if yidx > self.ny or yidx < 0:
- raise ValueError("specified y-position is out of the data range")
-
- # read motor values and perform gridding for all subscans
- if not self.gridded:
- self.read_motors()
- self.glist = []
- for fs in self.fastscans:
- g2l = fs._gridCCDnumbers(
- self.nx, self.ny, self.ccdnr,
- gridrange=((self.xmin, self.xmax), (self.ymin, self.ymax)))
- self.glist.append(g2l) # contains the ccdnumbers in g2l.data
-
- self.gridded = True
-
- # return the ccdnumbers and goniometer angles for this position
- ret = []
- for i in range(len(self.glist)):
- motorpos = self.motor_pos[i]
- ccdnrs = self.glist[i].data[xidx, yidx]
- ret.append([motorpos, ccdnrs])
-
- return ret
-
- def rawRSM(self, posx, posy, qconv, ccdtemp, path, roi=None,
- nav=[1, 1], typ='real', filterfunc=None, **kwargs):
- """
- function to return the reciprocal space map data at a certain
- x,y-position from a series of FastScan measurements. It necessary to
- give the QConversion-object to be used for the reciprocal space
- conversion. The QConversion-object is expected to have the 'area'
- conversion routines configured properly.
-
- Parameters
- ----------
- posx: real space x-position or index in x direction
- posy: real space y-position or index in y direction
- qconv: QConversion-object to be used for the conversion of the
- CCD-data to reciprocal space
- ccdtemp: template string for the ccdfilenames
-
- optional:
- path: common path of the CCDframes
- roi: region of interest on the 2D detector. should be a list
- of lower and upper bounds of detector channels for the
- two pixel directions (default: None)
- nav: number of detector pixel which will be averaged
- together (reduces the date size)
- typ: type of coordinates. specifies if the position is
- specified as real space coordinate or as index. valid
- values are 'real' and 'index'. (default: 'real')
- filterfunc: function applied to the CCD-frames before any
- processing. this function should take a single argument
- which is the ccddata which need to be returned with the
- same shape! e.g. remove hot pixels, flat/darkfield
- correction
- UB: sample orientation matrix
-
- Returns
- -------
- qx,qy,qz,ccddata,valuelist: raw data of the reciprocal space map and
- valuelist containing the ccdframe numbers
- and corresponding motor positions
- """
- if 'UB' in kwargs:
- U = kwargs['UB']
- kwargs.pop("UB")
- else:
- U = numpy.identity(3)
-
- # get CCDframe numbers and motor values
- valuelist = self.getCCDFrames(posx, posy, typ)
- # load ccd frames and convert to reciprocal space
- self.ccdtemplate = os.path.join(path, ccdtemp)
- # read ccd shape from first image
- ccdshape = blockAverage2D(
- EDFFile(self.ccdtemplate % (valuelist[0][1][0])).data,
- nav[0], nav[1], roi=roi).shape
- ccddata = numpy.zeros((len(self.fastscans), ccdshape[0], ccdshape[1]))
- motors = []
- for i in range(len(self.gonio_motors)):
- motors.append(numpy.zeros(0))
- # go through the gridded data and average the ccdframes
- for i in range(len(self.fastscans)):
- imotors, ccdnrs = valuelist[i]
- # read CCD
- if len(ccdnrs) == 0:
- continue
- else:
- # append motors
- for j in range(len(self.gonio_motors)):
- motors[j] = numpy.append(motors[j], imotors[j])
- framecount = 0
- # read ccdframes and average them
- for k in range(len(ccdnrs)):
- edf = EDFFile(self.ccdtemplate % ccdnrs[k])
- if filterfunc:
- ccdfilt = filterfunc(edf.data)
- else:
- ccdfilt = edf.data
- ccdframe = blockAverage2D(ccdfilt, nav[0], nav[1], roi=roi)
- ccddata[i, :, :] += ccdframe
- framecount += 1
- ccddata[i, :, :] = ccddata[i, :, :] / float(framecount)
-
- qx, qy, qz = qconv.area(*motors, roi=roi, Nav=nav, UB=U)
- return qx, qy, qz, ccddata, valuelist
-
- def gridRSM(self, posx, posy, qnx, qny, qnz, qconv, ccdtemp, path="",
- roi=None, nav=[1, 1], typ='real', filterfunc=None, **kwargs):
- """
- function to calculate the reciprocal space map at a certain
- x,y-position from a series of FastScan measurements it is necessary to
- specify the number of grid-oints for the reciprocal space map and the
- QConversion-object to be used for the reciprocal space conversion. The
- QConversion-object is expected to have the 'area' conversion routines
- configured properly.
-
- Parameters
- ----------
- posx: real space x-position or index in x direction
- posy: real space y-position or index in y direction
- qnx: number of points in the Qx direction of the gridded
- reciprocal space map
- qny: same for y direction
- qnz: same for z directino
- qconv: QConversion-object to be used for the conversion of the
- CCD-data to reciprocal space
- ccdtemp: template string for the ccdfilenames
-
- optional:
- path: common path of the CCDframes
- roi: region of interest on the 2D detector. should be a list
- of lower and upper bounds of detector channels for the
- two pixel directions (default: None)
- nav: number of detector pixel which will be averaged together
- (reduces the date size)
- typ: type of coordinates. specifies if the position is
- specified as real space coordinate or as index. valid
- values are 'real' and 'index'. (default: 'real')
- filterfunc: function applied to the CCD-frames before any
- processing. this function should take a single argument
- which is the ccddata which need to be returned with the
- same shape! e.g. remove hot pixels, flat/darkfield
- correction
- UB: sample orientation matrix
-
- Returns
- -------
- Gridder3D object with gridded reciprocal space map
- """
- qx, qy, qz, ccddata, vallist = self.rawRSM(
- posx, posy, qconv, ccdtemp, path, roi=roi, nav=nav,
- typ=typ, filterfunc=filterfunc, **kwargs)
- # perform 3D gridding and return the data or gridder
- g = Gridder3D(qnx, qny, qnz)
- g(qx, qy, qz, ccddata)
- return g
+# This file is part of xrayutilities.
+#
+# xrayutilities is free software; you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation; either version 2 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program; if not, see <http://www.gnu.org/licenses/>.
+#
+# Copyright (C) 2014 Raphael Grifone <raphael.grifone at esrf.fr>
+# Copyright (C) 2014 Dominik Kriegner <dominik.kriegner at gmail.com>
+
+"""
+modules to help with the analysis of FastScan data acquired at the ESRF.
+FastScan data are X-ray data (various detectors possible) acquired during
+scanning the sample in real space with a Piezo Scanner. The same functions
+might be used to analze traditional SPEC mesh scans.
+
+The module provides three core classes:
+
+* FastScan
+* FastScanCCD
+* FastScanSeries
+
+where the first two are able to parse single mesh/FastScans when one is
+interested in data of a single channel detector or are detector and the last
+one is able to parse full series of such mesh scans with either type of
+detector
+
+see examples/xrayutilities_kmap_ESRF.py for an example script
+"""
+
+import os.path
+import numpy
+import re
+import glob
+
+# relative imports
+from . import SPECFile
+from . import EDFFile
+from ..exception import InputError
+from ..gridder import delta
+from ..gridder2d import Gridder2D
+from ..gridder2d import Gridder2DList
+from ..gridder3d import Gridder3D
+from ..normalize import blockAverage2D
+from .. import config
+from .. import utilities
+
+# python 2to3 compatibility
+try:
+ basestring
+except NameError:
+ basestring = str
+
+SPEC_ImageFile = re.compile(r"^#C imageFile")
+
+
+class FastScan(object):
+
+ """
+ class to help parsing and treating fast scan data. FastScan is the
+ aquisition of X-ray data while scanning the sample with piezo stages in
+ real space. It's is available at several beamlines at the ESRF synchrotron
+ light-source.
+ """
+
+ def __init__(self, filename, scannr,
+ xmotor='adcX', ymotor='adcY', path=""):
+ """
+ Constructor routine for the FastScan object. It initializes the object
+ and parses the spec-scan for the needed data which are saved in
+ properties of the FastScan object.
+
+ Parameters
+ ----------
+ filename: file name of the fast scan spec file
+ scannr: scannr of the to be parsed fast scan
+ optional:
+ xmotor: motor name of the x-motor (default: 'adcX' (ID01))
+ ymotor: motor name of the y-motor (default: 'adcY' (ID01))
+ path: optional path of the FastScan spec file
+ """
+ self.scannr = scannr
+ self.xmotor = xmotor
+ self.ymotor = ymotor
+
+ if isinstance(filename, SPECFile):
+ self.specfile = filename
+ self.filename = self.specfile.filename
+ self.full_filename = self.specfile.full_filename
+ self.specscan = self.specfile.__getattr__('scan%d' % self.scannr)
+ else:
+ self.filename = filename
+ self.full_filename = os.path.join(path, filename)
+ self.filename = os.path.basename(self.full_filename)
+ self.specscan = None
+
+ # read the scan
+ self.parse()
+
+ def parse(self):
+ """
+ parse the specfile for the scan number specified in the constructor and
+ store the needed informations in the object properties
+ """
+
+ # parse the file
+ if not self.specscan:
+ self.specfile = SPECFile(self.full_filename)
+ self.specscan = self.specfile.__getattr__('scan%d' % self.scannr)
+ self.specscan.ReadData()
+
+ self.xvalues = self.specscan.data[self.xmotor]
+ self.yvalues = self.specscan.data[self.ymotor]
+
+ self.data = self.specscan.data
+
+ def motorposition(self, motorname):
+ """
+ read the position of motor with name given by motorname from the data
+ file. In case the motor is included in the data columns the returned
+ object is an array with all the values from the file (although retrace
+ clean is respected if already performed). In the case the motor is not
+ moved during the scan only one value is returned.
+
+ Parameters
+ ----------
+ motorname: name of the motor for which the position is wanted
+
+ Returns
+ -------
+ val: motor position(s) of motor with name motorname during the scan
+ """
+ if self.specscan:
+ # try reading value from data
+ try:
+ return self.data[motorname]
+ except ValueError:
+ try:
+ return self.specscan.init_motor_pos['INIT_MOPO_%s'
+ % motorname]
+ except ValueError:
+ raise ValueError("given motorname '%s' not found in the "
+ "Spec-data" % motorname)
+ else:
+ return None
+
+ def retrace_clean(self):
+ """
+ function to clean the data of the scan from retrace artifacts created
+ by the zig-zag scanning motion of the piezo actuators the function
+ cleans the xvalues, yvalues and data attribute of the FastScan object.
+ """
+
+ # set window to determin the slope
+ window = [-1, 0, 1]
+ # calc the slope of x_motor movement using a window for better acuracy
+ slope = numpy.convolve(self.xvalues, window, mode='same') / \
+ numpy.convolve(numpy.arange(len(self.xvalues)), window, 'same')
+ # select where slope is above the slope mean value
+ # this can be modified if data points are missing of the retrace does
+ # not clean all points
+ mask = numpy.where(slope > slope.mean())
+
+ # reduce data size by cutting out retrace
+ self.xvalues = self.xvalues[mask]
+ self.yvalues = self.yvalues[mask]
+ self.data = self.data[mask]
+
+ def grid2D(self, nx, ny, **kwargs):
+ """
+ function to grid the counter data and return the gridded X,Y and
+ Intensity values.
+
+ Parameters
+ ----------
+ nx,ny: number of bins in x,y direction
+
+ optional keyword arguments:
+ counter: name of the counter to use for gridding (default: 'mpx4int'
+ (ID01))
+ gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
+
+ Returns
+ -------
+ Gridder2D object with X,Y,data on regular x,y-grid
+ """
+ if 'counter' in kwargs:
+ self.counter = kwargs['counter']
+ kwargs.pop("counter")
+ else:
+ self.counter = 'mpx4int'
+
+ if 'gridrange' in kwargs:
+ gridrange = kwargs['gridrange']
+ kwargs.pop("gridrange")
+ else:
+ gridrange = None
+
+ # define gridder
+ g2d = Gridder2D(nx, ny)
+ if gridrange:
+ g2d.dataRange(gridrange[0][0], gridrange[0][1],
+ gridrange[1][0], gridrange[1][1])
+
+ # check if counter is in data fields
+ try:
+ inte = self.data[self.counter]
+ except ValueError:
+ raise ValueError("field named '%s' not found in data parsed from "
+ "scan #%d in file %s"
+ % (self.counter, self.scannr, self.filename))
+
+ # grid data
+ g2d(self.xvalues, self.yvalues, self.data[self.counter])
+
+ # return gridded data
+ return g2d
+
+
+class FastScanCCD(FastScan):
+
+ """
+ class to help parsing and treating fast scan data including CCD frames.
+ FastScan is the aquisition of X-ray data while scanning the sample with
+ piezo stages in real space. It's is available at several beamlines at the
+ ESRF synchrotron light-source. During such fast scan at every grid point
+ CCD frames are recorded and need to be analyzed
+ """
+
+ def _gridCCDnumbers(self, nx, ny, ccdnr, gridrange=None):
+ """
+ internal function to grid the CCD frame number to produce a list of
+ ccd-files per bin needed for the further treatment
+
+ Parameters
+ ----------
+ nx,ny: number of bins in x,y direction
+ ccdnr: array with ccd file numbers of length
+ length(FastScanCCD.data) OR a string with the data
+ column name for the file ccd-numbers
+
+ optional:
+ gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
+
+ Returns
+ -------
+ gridder object: regular x,y-grid as well as 4-dimensional data
+ object
+ """
+ g2l = Gridder2DList(nx, ny)
+ if gridrange:
+ g2l.dataRange(gridrange[0][0], gridrange[0][1],
+ gridrange[1][0], gridrange[1][1])
+
+ if isinstance(ccdnr, basestring):
+ # check if counter is in data fields
+ try:
+ ccdnumbers = self.data[ccdnr]
+ except ValueError:
+ raise ValueError("field named '%s' not found in data parsed "
+ "from scan #%d in file %s"
+ % (ccdnr, self.scannr, self.filename))
+ elif isinstance(ccdnr, (list, tuple, numpy.ndarray)):
+ ccdnumbers = ccdnr
+ else:
+ raise ValueError("xu.FastScanCCD: wrong data type for "
+ "argument 'ccdnr'")
+
+ # assign ccd frames to grid
+ g2l(self.xvalues, self.yvalues, ccdnumbers)
+
+ return g2l
+
+ def getccdFileTemplate(self, specscan, datadir=None, keepdir=0,
+ numfmt='%04d'):
+ """
+ function to extract the CCD file template string from the comment
+ in the SPEC-file scan-header
+
+ Parameters
+ ----------
+ specscan: spec-scan object from which header the CCD directory should
+ be extracted
+ datadir: the CCD filenames are usually parsed from the scan object.
+ With this option the directory used for the data can be
+ overwritten. Specify the datadir as simple string.
+ Alternatively the innermost directory structure can be
+ automatically taken from the specfile. If this is needed
+ specify the number of directories which should be kept
+ using the keepdir option.
+ keepdir: number of directories which should be taken from the
+ specscan. (default: 0)
+ numfmt: format string for the CCD file number (optional)
+
+ Returns
+ -------
+ fmtstr: format string for the CCD file name using one number to
+ build the real file name
+ """
+ for line in specscan.header:
+ if SPEC_ImageFile.match(line):
+ for substr in line.split(' '):
+ t = substr.split('[')
+ if len(t) == 2:
+ if t[0] == 'dir':
+ dir = t[1].strip(']')
+ elif t[0] == 'prefix':
+ prefix = t[1].strip(']')
+ elif t[0] == 'suffix':
+ suffix = t[1].strip(']')
+
+ ccdtmp = os.path.join(dir, prefix + numfmt + suffix)
+ return utilities.exchange_filepath(ccdtmp, datadir, keepdir)
+
+ def gridCCD(self, nx, ny, ccdnr, roi=None, datadir=None, keepdir=0,
+ nav=[1, 1], gridrange=None, filterfunc=None, imgoffset=0):
+ """
+ function to grid the internal data and ccd files and return the gridded
+ X,Y and DATA values. DATA represents a 4D with first two dimensions
+ representing X,Y and the remaining two dimensions representing detector
+ channels
+
+ Parameters
+ ----------
+ nx,ny: number of bins in x,y direction
+ ccdnr: array with ccd file numbers of length
+ length(FastScanCCD.data) OR a string with the data
+ column name for the file ccd-numbers
+
+ optional:
+ roi: region of interest on the 2D detector. should be a list
+ of lower and upper bounds of detector channels for the
+ two pixel directions (default: None)
+ datadir: the CCD filenames are usually parsed from the SPEC file.
+ With this option the directory used for the data can be
+ overwritten. Specify the datadir as simple string.
+ Alternatively the innermost directory structure can be
+ automatically taken from the specfile. If this is needed
+ specify the number of directories which should be kept
+ using the keepdir option.
+ keepdir: number of directories which should be taken from the
+ SPEC file. (default: 0)
+ nav: number of detector pixel which will be averaged together
+ (reduces the date size)
+ gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
+ filterfunc: function applied to the CCD-frames before any
+ processing. this function should take a single argument
+ which is the ccddata which need to be returned with the
+ same shape! e.g. remove hot pixels, flat/darkfield
+ correction
+
+ Returns
+ -------
+ X,Y,DATA: regular x,y-grid as well as 4-dimensional data object
+ """
+
+ g2l = self._gridCCDnumbers(nx, ny, ccdnr, gridrange=gridrange)
+ gdata = g2l.data
+
+ self.ccdtemplate = self.getccdFileTemplate(self.specscan, datadir,
+ keepdir)
+
+ # read ccd shape from first image
+ filename = sorted(glob.glob(self.ccdtemplate.replace('%04d', '*')))[0]
+ if config.VERBOSITY >= config.INFO_ALL:
+ print('XU.io.FastScanCCD: open file %s' % filename)
+ e = EDFFile(filename, keep_open=True)
+ ccdshape = blockAverage2D(e.ReadData(), nav[0], nav[1], roi=roi).shape
+ self.ccddata = numpy.zeros((nx, ny, ccdshape[0], ccdshape[1]))
+ nimage = e.nimages
+
+ # go through the gridded data and average the ccdframes
+ for j in range(gdata.shape[1]):
+ for i in range(gdata.shape[0]):
+ if len(gdata[i, j]) == 0:
+ continue
+ else:
+ framecount = 0
+ # read ccdframes and average them
+ for imgnum in gdata[i, j]:
+ filenumber = (imgnum - imgoffset) // nimage
+ imgindex = int((imgnum - imgoffset) % nimage)
+ newfile = self.ccdtemplate % (filenumber)
+ if e.filename != newfile:
+ if config.VERBOSITY >= config.INFO_ALL:
+ print('XU.io.FastScanCCD: open file %s'
+ % newfile)
+ e = EDFFile(newfile, keep_open=True)
+ if filterfunc:
+ ccdfilt = filterfunc(e.ReadData(imgindex))
+ else:
+ ccdfilt = e.ReadData(imgindex)
+ ccdframe = blockAverage2D(ccdfilt, nav[0], nav[1],
+ roi=roi)
+ self.ccddata[i, j, :, :] += ccdframe
+ framecount += 1
+ self.ccddata[i, j, :, :] = self.ccddata[i, j, :, :] / \
+ float(framecount)
+
+ return g2l.xmatrix, g2l.ymatrix, self.ccddata
+
+
+class FastScanSeries(object):
+
+ """
+ class to help parsing and treating a series of fast scan data including CCD
+ frames. FastScan is the aquisition of X-ray data while scanning the sample
+ with piezo stages in real space. It's is available at several beamlines at
+ the ESRF synchrotron light-source. During such fast scan at every grid
+ point CCD frames are recorded and need to be analyzed.
+
+ For the series of FastScans we assume that they are measured at different
+ goniometer angles and therefore transform the data to reciprocal space.
+ """
+
+ def __init__(self, filenames, scannrs, nx, ny, *args, **kwargs):
+ """
+ Constructor routine for the FastScanSeries object. It initializes the
+ object and creates a list of FastScanCCD objects. Importantly it also
+ expects the motor names of the angles needed for reciprocal space
+ conversion.
+
+ Parameters
+ ----------
+ filenames: file names of the fast scan spec files, in case of more
+ than one filename supply a list of names and also a list of
+ scan numbers for the different files in the 'scannrs'
+ argument
+ scannrs: scannrs of the to be parsed fast scans. in case of one
+ specfile this is a list of numbers (e.g. [1,2,3]). when
+ multiple filenames are given supply a separate list for
+ every file (e.g. [[1,2,3],[2,4]])
+ nx,ny: grid-points for the real space grid
+ *args: motor names for the Reciprocal space conversion. The order
+ needs be as required by the QConversion.area() function.
+ optional keyword arguments:
+ xmotor: motor name of the x-motor (default: 'adcX' (ID01))
+ ymotor: motor name of the y-motor (default: 'adcY' (ID01))
+ ccdnr: name of the ccd-number data column
+ (default: 'imgnr' (ID01))
+ counter: name of a defined counter (roi) in the spec file
+ (default: 'ccdint1' (ID01))
+ path: optional path of the FastScan spec file (default: '')
+
+ """
+
+ if 'ccdnr' in kwargs:
+ self.ccdnr = kwargs['ccdnr']
+ kwargs.pop("ccdnr")
+ else:
+ self.ccdnr = 'imgnr'
+
+ if 'counter' in kwargs:
+ self.counter = kwargs['counter']
+ kwargs.pop("counter")
+ else:
+ self.counter = 'ccdint1'
+
+ if 'path' in kwargs:
+ self.path = kwargs['path']
+ kwargs.pop("path")
+ else:
+ self.path = ''
+
+ self.fastscans = []
+ self.nx = nx
+ self.ny = ny
+ self.motor_pos = None
+ self.gridded = False
+
+ self.gonio_motors = []
+ # save motor names
+ for arg in args:
+ if not isinstance(arg, basestring):
+ raise ValueError("one of the motor name arguments is not of "
+ "type 'str' but %s" % str(type(arg)))
+ self.gonio_motors.append(arg)
+
+ # create list of FastScans
+ if isinstance(filenames, basestring):
+ filenames = [filenames]
+ scannrs = [scannrs]
+ if isinstance(filenames, (tuple, list)):
+ for fname in filenames:
+ full_filename = os.path.join(self.path, fname)
+ specfile = SPECFile(full_filename)
+ for snrs in scannrs[filenames.index(fname)]:
+ self.fastscans.append(FastScanCCD(specfile,
+ snrs, **kwargs))
+ else:
+ raise ValueError("argument 'filenames' is not of "
+ "appropriate type!")
+
+ self.xmin = numpy.min(self.fastscans[0].xvalues)
+ self.ymin = numpy.min(self.fastscans[0].yvalues)
+ self.xmax = numpy.max(self.fastscans[0].xvalues)
+ self.ymax = numpy.max(self.fastscans[0].yvalues)
+ for fs in self.fastscans:
+ if numpy.max(fs.xvalues) > self.xmax:
+ self.xmax = numpy.max(fs.xvalues)
+ if numpy.max(fs.yvalues) > self.ymax:
+ self.ymax = numpy.max(fs.yvalues)
+ if numpy.min(fs.xvalues) < self.xmin:
+ self.xmin = numpy.min(fs.xvalues)
+ if numpy.min(fs.yvalues) < self.ymin:
+ self.ymin = numpy.min(fs.yvalues)
+
+ def retrace_clean(self):
+ """
+ perform retrace clean for every FastScan in the series
+ """
+ self.gridded = False
+ self.xmin = numpy.min(self.fastscans[0].xvalues)
+ self.ymin = numpy.min(self.fastscans[0].yvalues)
+ self.xmax = numpy.max(self.fastscans[0].xvalues)
+ self.ymax = numpy.max(self.fastscans[0].yvalues)
+
+ for fs in self.fastscans:
+ fs.retrace_clean()
+
+ if numpy.max(fs.xvalues) > self.xmax:
+ self.xmax = numpy.max(fs.xvalues)
+ if numpy.max(fs.yvalues) > self.ymax:
+ self.ymax = numpy.max(fs.yvalues)
+ if numpy.min(fs.xvalues) < self.xmin:
+ self.xmin = numpy.min(fs.xvalues)
+ if numpy.min(fs.yvalues) < self.ymin:
+ self.ymin = numpy.min(fs.yvalues)
+
+ def align(self, deltax, deltay):
+ """
+ Since a sample drift or shift due to rotation often occurs between
+ different FastScans it should be corrected before combining them. Since
+ determining such a shift is not straight-forward in general the user
+ needs to supply the routine with the shifts in order correct the
+ x,y-values for the different FastScans. Such a routine could for
+ example use the integrated CCD intensities and determine the shift
+ using a cross-convolution.
+
+ Parameters
+ ----------
+ deltax: list of shifts in x-direction for every FastScan in the
+ data structure
+ deltay: same for the y-direction
+ """
+ self.gridded = False
+ self.xmin = numpy.min(self.fastscans[0].xvalues)
+ self.ymin = numpy.min(self.fastscans[0].yvalues)
+ self.xmax = numpy.max(self.fastscans[0].xvalues)
+ self.ymax = numpy.max(self.fastscans[0].yvalues)
+ for fs in self.fastscans:
+ i = self.fastscans.index(fs)
+ fs.xvalues += deltax[i]
+ fs.yvalues += deltay[i]
+
+ if numpy.max(fs.xvalues) > self.xmax:
+ self.xmax = numpy.max(fs.xvalues)
+ if numpy.max(fs.yvalues) > self.ymax:
+ self.ymax = numpy.max(fs.yvalues)
+ if numpy.min(fs.xvalues) < self.xmin:
+ self.xmin = numpy.min(fs.xvalues)
+ if numpy.min(fs.yvalues) < self.ymin:
+ self.ymin = numpy.min(fs.yvalues)
+
+ def read_motors(self):
+ """
+ read motor values from the series of fast scans
+ """
+ self.motor_pos = numpy.zeros((len(self.fastscans),
+ len(self.gonio_motors)))
+ for i in range(len(self.fastscans)):
+ fs = self.fastscans[i]
+ for j in range(len(self.gonio_motors)):
+ mname = self.gonio_motors[j]
+ self.motor_pos[i, j] = fs.motorposition(mname)
+
+ def getCCDFrames(self, posx, posy, typ='real'):
+ """
+ function to determine the list of ccd-frame numbers for a specific real
+ space position. The real space position must be within the data limits
+ of the FastScanSeries otherwise an ValueError is thrown
+
+ Parameters
+ ----------
+ posx: real space x-position or index in x direction
+ posy: real space y-position or index in y direction
+
+ optional:
+ typ: type of coordinates. specifies if the position is specified as
+ real space coordinate or as index. valid values are 'real' and
+ 'index'. (default: 'real')
+
+ Returns
+ -------
+ [[motorpos1, ccdnrs1], [motorpos2, ccdnrs2], ...] where motorposN is
+ from the N-ths FastScan in the series and ccdnrsN is the list of
+ according CCD-frames
+ """
+
+ # determine grid point for position x,y
+ if typ == 'real':
+ # grid point calculation
+ def gindex(x, min, delt):
+ return numpy.round((x - min) / delt)
+
+ xdelta = delta(self.xmin, self.xmax, self.nx)
+ ydelta = delta(self.ymin, self.ymax, self.ny)
+ xidx = gindex(posx, self.xmin, xdelta)
+ yidx = gindex(posy, self.ymin, ydelta)
+ elif typ == 'index':
+ xidx = posx
+ yidx = posy
+ else:
+ raise ValueError("given value of 'typ' is invalid.")
+
+ if xidx >= self.nx or xidx < 0:
+ raise ValueError("specified x-position is out of the data range")
+ if yidx > self.ny or yidx < 0:
+ raise ValueError("specified y-position is out of the data range")
+
+ # read motor values and perform gridding for all subscans
+ if not self.gridded:
+ self.read_motors()
+ self.glist = []
+ for fs in self.fastscans:
+ g2l = fs._gridCCDnumbers(
+ self.nx, self.ny, self.ccdnr,
+ gridrange=((self.xmin, self.xmax), (self.ymin, self.ymax)))
+ self.glist.append(g2l) # contains the ccdnumbers in g2l.data
+
+ self.gridded = True
+
+ # return the ccdnumbers and goniometer angles for this position
+ ret = []
+ for i in range(len(self.glist)):
+ motorpos = self.motor_pos[i]
+ ccdnrs = self.glist[i].data[xidx, yidx]
+ ret.append([motorpos, ccdnrs])
+
+ return ret
+
+ def rawRSM(self, posx, posy, qconv, roi=None, nav=[1, 1], typ='real',
+ datadir=None, keepdir=0, filterfunc=None, **kwargs):
+ """
+ function to return the reciprocal space map data at a certain
+ x,y-position from a series of FastScan measurements. It necessary to
+ give the QConversion-object to be used for the reciprocal space
+ conversion. The QConversion-object is expected to have the 'area'
+ conversion routines configured properly.
+
+ Parameters
+ ----------
+ posx: real space x-position or index in x direction
+ posy: real space y-position or index in y direction
+ qconv: QConversion-object to be used for the conversion of the
+ CCD-data to reciprocal space
+
+ optional:
+ roi: region of interest on the 2D detector. should be a list
+ of lower and upper bounds of detector channels for the
+ two pixel directions (default: None)
+ nav: number of detector pixel which will be averaged
+ together (reduces the date size)
+ typ: type of coordinates. specifies if the position is
+ specified as real space coordinate or as index. valid
+ values are 'real' and 'index'. (default: 'real')
+ filterfunc: function applied to the CCD-frames before any
+ processing. this function should take a single argument
+ which is the ccddata which need to be returned with the
+ same shape! e.g. remove hot pixels, flat/darkfield
+ correction
+ UB: sample orientation matrix
+ datadir: the CCD filenames are usually parsed from the SPEC
+ file. With this option the directory used for the data
+ can be overwritten. Specify the datadir as simple
+ string. Alternatively the innermost directory
+ structure can be automatically taken from the specfile.
+ If this is needed specify the number of directories
+ which should be kept using the keepdir option.
+ keepdir: number of directories which should be taken from the
+ SPEC file. (default: 0)
+
+ Returns
+ -------
+ qx,qy,qz,ccddata,valuelist: raw data of the reciprocal space map and
+ valuelist containing the ccdframe numbers
+ and corresponding motor positions
+ """
+ if 'UB' in kwargs:
+ U = kwargs['UB']
+ kwargs.pop("UB")
+ else:
+ U = numpy.identity(3)
+
+ if 'imgoffset' in kwargs:
+ imgoffset = kwargs['imgoffset']
+ kwargs.pop("imgoffset")
+ else:
+ imgoffset = 0
+
+ # get CCDframe numbers and motor values
+ valuelist = self.getCCDFrames(posx, posy, typ)
+ # load ccd frames and convert to reciprocal space
+ fsccd = self.fastscans[0]
+ self.ccdtemplate = fsccd.getccdFileTemplate(fsccd.specscan, datadir,
+ keepdir)
+ # read ccd shape from first image
+ filename = glob.glob(self.ccdtemplate.replace('%04d', '*'))[0]
+ e = EDFFile(filename, keep_open=True)
+ ccdshape = blockAverage2D(e.ReadData(), nav[0], nav[1], roi=roi).shape
+ ccddata = numpy.zeros((len(self.fastscans), ccdshape[0], ccdshape[1]))
+ motors = []
+ nimage = e.nimages
+
+ for i in range(len(self.gonio_motors)):
+ motors.append(numpy.zeros(0))
+ # go through the gridded data and average the ccdframes
+ for i in range(len(self.fastscans)):
+ imotors, ccdnrs = valuelist[i]
+ fsccd = self.fastscans[i]
+ # append motor positions
+ for j in range(len(self.gonio_motors)):
+ motors[j] = numpy.append(motors[j], imotors[j])
+ # read CCD
+ if len(ccdnrs) == 0:
+ continue
+ else:
+ self.ccdtemplate = fsccd.getccdFileTemplate(fsccd.specscan)
+ framecount = 0
+ # read ccdframes and average them
+ for imgnum in ccdnrs:
+ filenumber = (imgnum - imgoffset) // nimage
+ imgindex = int((imgnum - imgoffset) % nimage)
+ newfile = self.ccdtemplate % (filenumber)
+ if e.filename != newfile:
+ e = EDFFile(newfile, keep_open=True)
+ if filterfunc:
+ ccdfilt = filterfunc(e.ReadData(imgindex))
+ else:
+ ccdfilt = e.ReadData(imgindex)
+ ccdframe = blockAverage2D(ccdfilt, nav[0], nav[1], roi=roi)
+ ccddata[i, :, :] += ccdframe
+ framecount += 1
+ ccddata[i, :, :] = ccddata[i, :, :] / float(framecount)
+
+ qx, qy, qz = qconv.area(*motors, roi=roi, Nav=nav, UB=U)
+ return qx, qy, qz, ccddata, valuelist
+
+ def gridRSM(self, posx, posy, qnx, qny, qnz, qconv, roi=None, nav=[1, 1],
+ typ='real', filterfunc=None, **kwargs):
+ """
+ function to calculate the reciprocal space map at a certain
+ x,y-position from a series of FastScan measurements it is necessary to
+ specify the number of grid-oints for the reciprocal space map and the
+ QConversion-object to be used for the reciprocal space conversion. The
+ QConversion-object is expected to have the 'area' conversion routines
+ configured properly.
+
+ Parameters
+ ----------
+ posx: real space x-position or index in x direction
+ posy: real space y-position or index in y direction
+ qnx: number of points in the Qx direction of the gridded
+ reciprocal space map
+ qny: same for y direction
+ qnz: same for z directino
+ qconv: QConversion-object to be used for the conversion of the
+ CCD-data to reciprocal space
+
+ optional:
+ roi: region of interest on the 2D detector. should be a list
+ of lower and upper bounds of detector channels for the
+ two pixel directions (default: None)
+ nav: number of detector pixel which will be averaged together
+ (reduces the date size)
+ typ: type of coordinates. specifies if the position is
+ specified as real space coordinate or as index. valid
+ values are 'real' and 'index'. (default: 'real')
+ filterfunc: function applied to the CCD-frames before any
+ processing. this function should take a single argument
+ which is the ccddata which need to be returned with the
+ same shape! e.g. remove hot pixels, flat/darkfield
+ correction
+ UB: sample orientation matrix
+
+ Returns
+ -------
+ Gridder3D object with gridded reciprocal space map
+ """
+ qx, qy, qz, ccddata, vallist = self.rawRSM(
+ posx, posy, qconv, roi=roi, nav=nav,
+ typ=typ, filterfunc=filterfunc, **kwargs)
+ # perform 3D gridding and return the data or gridder
+ g = Gridder3D(qnx, qny, qnz)
+ g(qx, qy, qz, ccddata)
+ return g
+
+ def grid2Dall(self, nx, ny, **kwargs):
+ """
+ function to grid the counter data and return the gridded X,Y and
+ Intensity values from all the FastScanSeries.
+
+ Parameters
+ ----------
+ nx,ny: number of bins in x,y direction
+
+ optional keyword arguments:
+ counter: name of the counter to use for gridding (default: 'mpx4int'
+ (ID01))
+ gridrange: range for the gridder: format: ((xmin,xmax),(ymin,ymax))
+
+ Returns
+ -------
+ Gridder2D object with X,Y,data on regular x,y-grid
+ """
+ if 'counter' in kwargs:
+ counter = kwargs['counter']
+ kwargs.pop("counter")
+ else:
+ counter = 'mpx4int'
+
+ if 'gridrange' in kwargs:
+ gridrange = kwargs['gridrange']
+ kwargs.pop("gridrange")
+ else:
+ gridrange = ((self.xmin, self.xmax), (self.ymin, self.ymax))
+
+ # define gridder
+ g2d = Gridder2D(nx, ny)
+ if gridrange:
+ g2d.dataRange(gridrange[0][0], gridrange[0][1],
+ gridrange[1][0], gridrange[1][1])
+ g2d.KeepData(True)
+
+ for fs in self.fastscans:
+ # check if counter is in data fields
+ try:
+ inte = fs.data[counter]
+ except ValueError:
+ raise ValueError("field named '%s' not found in data parsed "
+ "from scan #%d in file %s"
+ % (counter, fs.scannr, fs.filename))
+
+ # grid data
+ g2d(fs.xvalues, fs.yvalues, fs.data[counter])
+
+ # return gridded data
+ return g2d
diff --git a/xrayutilities/io/helper.py b/xrayutilities/io/helper.py
index 88e9c0c..61c1cd3 100644
--- a/xrayutilities/io/helper.py
+++ b/xrayutilities/io/helper.py
@@ -29,11 +29,12 @@ import bz2
import sys
import tables
+from .. import config
+from ..exception import InputError
+
if sys.version_info >= (3, 3):
import lzma # new in python 3.3
-from .. import config
-from ..exception import InputError
# python 2to3 compatibility
try:
diff --git a/xrayutilities/io/spec.py b/xrayutilities/io/spec.py
index c6eea95..ed26837 100644
--- a/xrayutilities/io/spec.py
+++ b/xrayutilities/io/spec.py
@@ -676,8 +676,8 @@ class SPECFile(object):
os.path.splitext(self.filename)[0])[0])
for s in self.scan_list:
- if (((not g.__contains__(s.name)) or s.ischanged)
- and s.scan_status != "NODATA"):
+ if (((not g.__contains__(s.name)) or s.ischanged) and
+ s.scan_status != "NODATA"):
s.ReadData()
if s.data is not None:
s.Save2HDF5(h5, group=g, comp=comp)
@@ -1076,3 +1076,76 @@ def geth5_scan(h5f, scans, *args, **kwargs):
return MAP
else:
return retval, MAP
+
+
+def getspec_scan(specf, scans, *args):
+ """
+ function to obtain the angular cooridinates as well as intensity values
+ saved in a SPECFile. Especially useful to combine the data from multiple
+ scans.
+
+ further more it is possible to obtain even more positions from
+ the data file if more than two string arguments with its names are given
+
+ Parameters
+ ----------
+ specf: SPECFile object
+ scans: number of the scans of the reciprocal space map (int,tuple or
+ list)
+
+ *args: names of the motors and counters (strings)
+
+ Returns
+ -------
+ [ang1,ang2,...]:
+ coordinates and counters from the SPEC file
+
+ Example
+ -------
+ >>> [om, tt] = xu.io.getspec_scan(s, 36, 'omega', 'gamma', 'Counter2')
+ """
+ if len(args) == 0:
+ return
+
+ if numpy.iterable(scans):
+ scanlist = scans
+ else:
+ scanlist = list([scans])
+
+ angles = dict.fromkeys(args)
+ for key in angles.keys():
+ if not isinstance(key, str):
+ raise InputError("*arg values need to be strings with "
+ "motornames")
+ angles[key] = numpy.zeros(0)
+ buf = numpy.zeros(0)
+
+ for nr in scanlist:
+ sscan = specf.__getattr__("scan%d" % nr)
+ command = sscan.command
+ sscan.ReadData()
+ sdata = sscan.data
+ # check type of scan
+ notscanmotors = []
+ for i in range(len(args)):
+ motname = args[i]
+ try:
+ buf = sdata[motname]
+ scanshape = buf.shape
+ angles[motname] = numpy.concatenate((angles[motname], buf))
+ except:
+ notscanmotors.append(i)
+ if len(notscanmotors) == len(args):
+ scanshape = len(sdata)
+ for i in notscanmotors:
+ motname = args[i]
+ buf = (numpy.ones(scanshape) *
+ sscan.init_motor_pos["INIT_MOPO_%s" % motname])
+ angles[motname] = numpy.concatenate((angles[motname], buf))
+
+ retval = []
+ for motname in args:
+ # create return values in correct order
+ retval.append(angles[motname])
+
+ return retval
diff --git a/xrayutilities/materials/cif.py b/xrayutilities/materials/cif.py
index bdbc9b4..8d1760a 100644
--- a/xrayutilities/materials/cif.py
+++ b/xrayutilities/materials/cif.py
@@ -239,8 +239,8 @@ class CIFFile(object):
a3 = self.lattice_const[2] * numpy.array([
cb,
(ca - cb * cg) / sg,
- numpy.sqrt(1 - ca ** 2 - cb ** 2 - cg ** 2
- + 2 * ca * cb * cg) / sg],
+ numpy.sqrt(1 - ca ** 2 - cb ** 2 - cg ** 2 +
+ 2 * ca * cb * cg) / sg],
dtype=numpy.double)
# create lattice
l = Lattice(a1, a2, a3, base=lb)
diff --git a/xrayutilities/materials/data/README.txt~ b/xrayutilities/materials/data/README.txt~
deleted file mode 100644
index 7d0304c..0000000
--- a/xrayutilities/materials/data/README.txt~
+++ /dev/null
@@ -1,13 +0,0 @@
-Notes about origin/copyright of files:
-
-*.cif .... structure files created by the webform [1] from available
- data (Journal articles)
-
-f[01]*.dat.xz: database files from XOP/DABAX project [2]
-
-nist_atom.dat: included from NIST > Physical Reference Data
- > Atomic Weights [3]
-
-[1] http://www.cryst.ehu.es/cgi-bin/cryst/programs/mcif2vesta/index.php
-[2] http://ftp.esrf.eu/pub/scisoft/xop2.3/
-[3] http://www.nist.gov/pml/data/comp.cfm
diff --git a/xrayutilities/materials/material.py b/xrayutilities/materials/material.py
index 2ad54d4..89bacb0 100644
--- a/xrayutilities/materials/material.py
+++ b/xrayutilities/materials/material.py
@@ -1092,23 +1092,33 @@ class Alloy(Material):
# test if inplane direction of hkl is the same as the one for the
# experiment otherwise warn the user
hklinplane = numpy.cross(numpy.cross(exp.ndir, hkl), exp.ndir)
- if (numpy.linalg.norm(numpy.cross(hklinplane, exp.idir))
- > config.EPSILON):
+ if (numpy.linalg.norm(numpy.cross(hklinplane, exp.idir)) >
+ config.EPSILON):
warnings.warn("Alloy: given hkl differs from the geometry of the "
"Experiment instance in the azimuthal direction")
# calculate relaxed points for matA and matB as general as possible:
- a1 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a1, self.matB.lattice.a1, x)
- a2 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a2, self.matB.lattice.a2, x)
- a3 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a3, self.matB.lattice.a3, x)
- V = lambda x: numpy.dot(a3(x), numpy.cross(a1(x), a2(x)))
- b1 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a2(x), a3(x))
- b2 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a3(x), a1(x))
- b3 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a1(x), a2(x))
- qhklx = lambda x: hkl[0] * b1(x) + hkl[1] * b2(x) + hkl[2] * b3(x)
+ def a1(x):
+ return self.lattice_const_AB(self.matA.lattice.a1,
+ self.matB.lattice.a1, x)
+
+ def a2(x):
+ return self.lattice_const_AB(self.matA.lattice.a2,
+ self.matB.lattice.a2, x)
+
+ def a3(x):
+ return self.lattice_const_AB(self.matA.lattice.a3,
+ self.matB.lattice.a3, x)
+
+ def V(x): return numpy.dot(a3(x), numpy.cross(a1(x), a2(x)))
+
+ def b1(x): return 2 * numpy.pi / V(x) * numpy.cross(a2(x), a3(x))
+
+ def b2(x): return 2 * numpy.pi / V(x) * numpy.cross(a3(x), a1(x))
+
+ def b3(x): return 2 * numpy.pi / V(x) * numpy.cross(a1(x), a2(x))
+
+ def qhklx(x): return hkl[0] * b1(x) + hkl[1] * b2(x) + hkl[2] * b3(x)
qr_i = numpy.abs(transform(qhklx(self.x))[1])
qr_p = numpy.abs(transform(qhklx(self.x))[2])
@@ -1119,14 +1129,17 @@ class Alloy(Material):
# transform elastic constants to correct coordinate frame
cijA = Cijkl2Cij(transform(self.matA.cijkl))
cijB = Cijkl2Cij(transform(self.matB.cijkl))
- abulk = lambda x: numpy.linalg.norm(a1(x))
- frac = lambda x: (
- (cijB[0, 2] + cijB[1, 2] + cijB[2, 0] + cijB[2, 1] -
- (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) * x +
- (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1]))\
- / (2 * ((cijB[2, 2] - cijA[2, 2]) * x + cijA[2, 2]))
- aperp = lambda x: abulk(self.x) * (1 + frac(x) *
- (1 - asub / abulk(self.x)))
+
+ def abulk(x): return numpy.linalg.norm(a1(x))
+
+ def frac(x):
+ return ((cijB[0, 2] + cijB[1, 2] + cijB[2, 0] + cijB[2, 1] -
+ (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) * x +
+ (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) / \
+ (2 * ((cijB[2, 2] - cijA[2, 2]) * x + cijA[2, 2]))
+
+ def aperp(x):
+ return abulk(self.x) * (1 + frac(x) * (1 - asub / abulk(self.x)))
qp_i = 2 * numpy.pi / asub * numpy.linalg.norm(numpy.cross(ndir, hkl))
qp_p = 2 * numpy.pi / aperp(self.x) * numpy.abs(numpy.dot(ndir, hkl))
@@ -1212,37 +1225,50 @@ class CubicAlloy(Alloy):
cijA = Cijkl2Cij(trans(self.matA.cijkl))
cijB = Cijkl2Cij(trans(self.matB.cijkl))
- # define lambda functions for all things in the equation to solve
- a1 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a1, self.matB.lattice.a1, x)
- a2 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a2, self.matB.lattice.a2, x)
- a3 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a3, self.matB.lattice.a3, x)
- V = lambda x: numpy.dot(a3(x), numpy.cross(a1(x), a2(x)))
- b1 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a2(x), a3(x))
- b2 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a3(x), a1(x))
- b3 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a1(x), a2(x))
- qhklx = lambda x: hkl[0] * b1(x) + hkl[1] * b2(x) + hkl[2] * b3(x)
+ # define functions for all things in the equation to solve
+ def a1(x):
+ return self.lattice_const_AB(self.matA.lattice.a1,
+ self.matB.lattice.a1, x)
+
+ def a2(x):
+ return self.lattice_const_AB(self.matA.lattice.a2,
+ self.matB.lattice.a2, x)
+
+ def a3(x):
+ return self.lattice_const_AB(self.matA.lattice.a3,
+ self.matB.lattice.a3, x)
+
+ def V(x): return numpy.dot(a3(x), numpy.cross(a1(x), a2(x)))
+
+ def b1(x): return 2 * numpy.pi / V(x) * numpy.cross(a2(x), a3(x))
+
+ def b2(x): return 2 * numpy.pi / V(x) * numpy.cross(a3(x), a1(x))
+
+ def b3(x): return 2 * numpy.pi / V(x) * numpy.cross(a1(x), a2(x))
+
+ def qhklx(x): return hkl[0] * b1(x) + hkl[1] * b2(x) + hkl[2] * b3(x)
# the following line is not generally true! only cubic materials
- abulk_perp = lambda x: numpy.abs(
- 2 * numpy.pi / numpy.inner(qhklx(x), n) * numpy.inner(n, hkl))
+ def abulk_perp(x):
+ return numpy.abs(2 * numpy.pi / numpy.inner(qhklx(x), n) *
+ numpy.inner(n, hkl))
+
# can we use abulk_perp here? for cubic materials this should work?!
- ainp = lambda x: asub + relax * (abulk_perp(x) - asub)
+ def ainp(x): return asub + relax * (abulk_perp(x) - asub)
if config.VERBOSITY >= config.DEBUG:
print("XU.materials.Alloy.ContentB: abulk_perp: %8.5g"
% (abulk_perp(0.)))
- frac = lambda x: (
- (cijB[0, 2] + cijB[1, 2] + cijB[2, 0] + cijB[2, 1] -
- (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) * x +
- (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1]))\
- / (2 * ((cijB[2, 2] - cijA[2, 2]) * x + cijA[2, 2]))
+ def frac(x):
+ return ((cijB[0, 2] + cijB[1, 2] + cijB[2, 0] + cijB[2, 1] -
+ (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) * x +
+ (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) / \
+ (2 * ((cijB[2, 2] - cijA[2, 2]) * x + cijA[2, 2]))
- equation = lambda x: (aperp - abulk_perp(x)) + \
- (ainp(x) - abulk_perp(x)) * frac(x)
+ def equation(x):
+ return ((aperp - abulk_perp(x)) +
+ (ainp(x) - abulk_perp(x)) * frac(x))
x = scipy.optimize.brentq(equation, -0.1, 1.1)
@@ -1318,38 +1344,53 @@ class CubicAlloy(Alloy):
cijA = Cijkl2Cij(trans(self.matA.cijkl))
cijB = Cijkl2Cij(trans(self.matB.cijkl))
- # define lambda functions for all things in the equation to solve
- a1 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a1, self.matB.lattice.a1, x)
- a2 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a2, self.matB.lattice.a2, x)
- a3 = lambda x: self.lattice_const_AB(
- self.matA.lattice.a3, self.matB.lattice.a3, x)
- V = lambda x: numpy.dot(a3(x), numpy.cross(a1(x), a2(x)))
- b1 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a2(x), a3(x))
- b2 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a3(x), a1(x))
- b3 = lambda x: 2 * numpy.pi / V(x) * numpy.cross(a1(x), a2(x))
- qsurx = lambda x: sur[0] * b1(x) + sur[1] * b2(x) + sur[2] * b3(x)
- qhklx = lambda x: hkl[0] * b1(x) + hkl[1] * b2(x) + hkl[2] * b3(x)
+ # define functions for all things in the equation to solve
+ def a1(x):
+ return self.lattice_const_AB(self.matA.lattice.a1,
+ self.matB.lattice.a1, x)
+
+ def a2(x):
+ return self.lattice_const_AB(self.matA.lattice.a2,
+ self.matB.lattice.a2, x)
+
+ def a3(x):
+ return self.lattice_const_AB(self.matA.lattice.a3,
+ self.matB.lattice.a3, x)
+
+ def V(x): return numpy.dot(a3(x), numpy.cross(a1(x), a2(x)))
+
+ def b1(x): return 2 * numpy.pi / V(x) * numpy.cross(a2(x), a3(x))
+
+ def b2(x): return 2 * numpy.pi / V(x) * numpy.cross(a3(x), a1(x))
+
+ def b3(x): return 2 * numpy.pi / V(x) * numpy.cross(a1(x), a2(x))
+
+ def qsurx(x): return sur[0] * b1(x) + sur[1] * b2(x) + sur[2] * b3(x)
+
+ def qhklx(x): return hkl[0] * b1(x) + hkl[1] * b2(x) + hkl[2] * b3(x)
# the following two lines are not generally true! only cubic materials
- abulk_inp = lambda x: numpy.abs(
- 2 * numpy.pi / numpy.inner(qhklx(x), inp2) *
- numpy.linalg.norm(numpy.cross(n, hkl)))
- abulk_perp = lambda x: numpy.abs(
- 2 * numpy.pi / numpy.inner(qhklx(x), n) * numpy.inner(n, hkl))
+ def abulk_inp(x):
+ return numpy.abs(2 * numpy.pi / numpy.inner(qhklx(x), inp2) *
+ numpy.linalg.norm(numpy.cross(n, hkl)))
+
+ def abulk_perp(x):
+ return numpy.abs(2 * numpy.pi / numpy.inner(qhklx(x), n) *
+ numpy.inner(n, hkl))
+
if config.VERBOSITY >= config.DEBUG:
print("XU.materials.Alloy.ContentB: abulk_inp/perp: %8.5g %8.5g"
% (abulk_inp(0.), abulk_perp(0.)))
- frac = lambda x: (
- (cijB[0, 2] + cijB[1, 2] + cijB[2, 0] + cijB[2, 1] -
- (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) * x +
- (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1]))\
- / (2 * ((cijB[2, 2] - cijA[2, 2]) * x + cijA[2, 2]))
+ def frac(x):
+ return ((cijB[0, 2] + cijB[1, 2] + cijB[2, 0] + cijB[2, 1] -
+ (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) * x +
+ (cijA[0, 2] + cijA[1, 2] + cijA[2, 0] + cijA[2, 1])) / \
+ (2 * ((cijB[2, 2] - cijA[2, 2]) * x + cijA[2, 2]))
- equation = lambda x: (aperp - abulk_perp(x)) + \
- (ainp - abulk_inp(x)) * frac(x)
+ def equation(x):
+ return ((aperp - abulk_perp(x)) +
+ (ainp - abulk_inp(x)) * frac(x))
x = scipy.optimize.brentq(equation, -0.1, 1.1)
diff --git a/xrayutilities/materials/predefined_materials.py b/xrayutilities/materials/predefined_materials.py
index 9f4b8dd..cdd4ec6 100644
--- a/xrayutilities/materials/predefined_materials.py
+++ b/xrayutilities/materials/predefined_materials.py
@@ -55,6 +55,10 @@ GaAs = Material("GaAs",
lattice.ZincBlendeLattice(elements.Ga, elements.As, 5.65325),
CubicElasticTensor(11.9e+10, 5.34e+10, 5.96e+10),
thetaDebye=360)
+AlAs = Material("AlAs",
+ lattice.ZincBlendeLattice(elements.Al, elements.As, 5.6611),
+ CubicElasticTensor(12.02e+10, 5.70e+10, 5.99e+10),
+ thetaDebye=446)
GaSb = Material("GaSb",
lattice.ZincBlendeLattice(elements.Ga, elements.Sb, 6.09593),
CubicElasticTensor(8.83e+10, 4.02e+10, 4.32e+10),
diff --git a/xrayutilities/math/fit.py b/xrayutilities/math/fit.py
index db82875..12d0b5e 100644
--- a/xrayutilities/math/fit.py
+++ b/xrayutilities/math/fit.py
@@ -79,23 +79,28 @@ def peak_fit(xdata, ydata, iparams=[], peaktype='Gauss', maxit=300,
gfunc_dp = None
if peaktype == 'Gauss':
if background == 'linear':
- gfunc = lambda param, x: Gauss1d(x, *param) + x * param[-1]
+ def gfunc(param, x): return Gauss1d(x, *param) + x * param[-1]
else:
- gfunc = lambda param, x: Gauss1d(x, *param)
- gfunc_dx = lambda param, x: Gauss1d_der_x(x, *param)
- gfunc_dp = lambda param, x: Gauss1d_der_p(x, *param)
+ def gfunc(param, x): return Gauss1d(x, *param)
+
+ def gfunc_dx(param, x): return Gauss1d_der_x(x, *param)
+
+ def gfunc_dp(param, x): return Gauss1d_der_p(x, *param)
elif peaktype == 'Lorentz':
if background == 'linear':
- gfunc = lambda param, x: Lorentz1d(x, *param) + x * param[-1]
+ def gfunc(param, x): return Lorentz1d(x, *param) + x * param[-1]
else:
- gfunc = lambda param, x: Lorentz1d(x, *param)
- gfunc_dx = lambda param, x: Lorentz1d_der_x(x, *param)
- gfunc_dp = lambda param, x: Lorentz1d_der_p(x, *param)
+ def gfunc(param, x): return Lorentz1d(x, *param)
+
+ def gfunc_dx(param, x): return Lorentz1d_der_x(x, *param)
+
+ def gfunc_dp(param, x): return Lorentz1d_der_p(x, *param)
elif peaktype == 'PseudoVoigt':
if background == 'linear':
- gfunc = lambda param, x: PseudoVoigt1d(x, *param) + x * param[-1]
+ def gfunc(param, x):
+ return PseudoVoigt1d(x, *param) + x * param[-1]
else:
- gfunc = lambda param, x: PseudoVoigt1d(x, *param)
+ def gfunc(param, x): return PseudoVoigt1d(x, *param)
else:
raise InputError("keyword rgument peaktype takes invalid value!")
@@ -227,8 +232,10 @@ def fit_peak2d(x, y, data, start, drange, fit_function, maxfev=2000):
ly = ly[mask]
lx = lx[mask]
ldata = data.flatten()[mask]
- # /(numpy.abs(numpy.sqrt(data))+numpy.abs(numpy.sqrt(data[data!=0].min())))
- errfunc = lambda p, x, z, data: (fit_function(x, z, *p) - data)
+
+ def errfunc(p, x, z, data):
+ return fit_function(x, z, *p) - data
+
p, cov, infodict, errmsg, success = optimize.leastsq(
errfunc, start, args=(lx, ly, ldata), full_output=1, maxfev=maxfev)
diff --git a/xrayutilities/math/functions.py b/xrayutilities/math/functions.py
index b56a21c..128a536 100644
--- a/xrayutilities/math/functions.py
+++ b/xrayutilities/math/functions.py
@@ -365,8 +365,9 @@ def PseudoVoigt1dasym(x, *p):
lx = numpy.asarray(x)
f = numpy.zeros(lx.shape)
f[lx < p[0]] = (p[4] + pv *
- Lorentz1d(lx[x < p[0]], p[0], p[1], p[3], 0) + (1 - pv)
- * Gauss1d(lx[x < p[0]], p[0], sigmal, p[3], 0))
+ Lorentz1d(lx[x < p[0]], p[0], p[1], p[3], 0) +
+ (1 - pv) *
+ Gauss1d(lx[x < p[0]], p[0], sigmal, p[3], 0))
f[lx >= p[0]] = (p[4] + pv *
Lorentz1d(lx[x >= p[0]], p[0], p[2], p[3], 0) +
(1 - pv) *
diff --git a/xrayutilities/src/qconversion.h~ b/xrayutilities/src/qconversion.h~
deleted file mode 100644
index 051d6ad..0000000
--- a/xrayutilities/src/qconversion.h~
+++ /dev/null
@@ -1,131 +0,0 @@
-/*
- * This file is part of xrayutilities.
- *
- * xrayutilities is free software; you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation; either version 2 of the License, or
- * (at your option) any later version.
- *
- * This program is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with this program; if not, see <http://www.gnu.org/licenses/>.
- *
- * Copyright (C) 2013-2014 Dominik Kriegner <dominik.kriegner at gmail.com>
-*/
-#pragma once
-
-#include "xrayutilities.h"
-
-#define cdeg2rad (M_PI / 180.)
-#define crad2deg (180. / M_PI)
-
-#define deg2rad(ang) (ang * cdeg2rad)
-#define rad2deg(rad) (rad * crad2deg)
-
-
-/* ###################################
- * matrix vector operations for
- * 3x3 matrices and vectors of length
- * 3
- * ################################### */
-
-INLINE void ident(double *m);
-
-INLINE void sumvec(double *RESTRICT v1, double *RESTRICT v2);
-
-INLINE void diffvec(double *RESTRICT v1, double *RESTRICT v2);
-
-INLINE double norm(double *v);
-
-INLINE void normalize(double *v);
-
-INLINE void veccopy(double *RESTRICT v1, double *RESTRICT v2);
-
-INLINE void vecmul(double *RESTRICT r, double a);
-
-INLINE void cross(double *RESTRICT v1, double *RESTRICT v2,
- double *RESTRICT r);
-
-INLINE void vecmatcross(double *RESTRICT v, double *RESTRICT m,
- double *RESTRICT mr);
-
-INLINE void matmul(double *RESTRICT m1, double *RESTRICT m2);
-
-INLINE void matmulc(double *RESTRICT m, double c);
-
-INLINE void matvec(double *RESTRICT m, double *RESTRICT v,
- double *RESTRICT r);
-
-INLINE void tensorprod(double *RESTRICT v1, double *RESTRICT v2,
- double *RESTRICT m);
-
-INLINE void summat(double *RESTRICT m1, double *RESTRICT m2);
-
-INLINE void diffmat(double *RESTRICT m1, double *RESTRICT m2);
-
-INLINE void inversemat(double *RESTRICT m, double *RESTRICT i);
-
-INLINE double determinant(double *RESTRICT m);
-
-
-/*##############################################
-# functions which implement rotation matrices
-# for all coordinate axes and rotation senses
-#
-# the routines expect angles in radians
-# for conversion from degrees to radians
-# the functions and2rad and rad2ang are
-# supplied
-################################################*/
-
-typedef void (*fp_rot)(double, double *);
-
-INLINE void rotation_xp(double a, double *mat);
-INLINE void rotation_yp(double a, double *mat);
-INLINE void rotation_zp(double a, double *mat);
-
-INLINE void rotation_xm(double a, double *mat);
-INLINE void rotation_ym(double a, double *mat);
-INLINE void rotation_zm(double a, double *mat);
-
-INLINE void rotation_kappa(double a, double *mat);
-
-INLINE void rotation_arb(double a, double *RESTRICT e, double *RESTRICT mat);
-
-INLINE void apply_xp(double a, double *vec);
-INLINE void apply_yp(double a, double *vec);
-INLINE void apply_zp(double a, double *vec);
-
-INLINE void apply_xm(double a, double *vec);
-INLINE void apply_ym(double a, double *vec);
-INLINE void apply_zm(double a, double *vec);
-
-INLINE void apply_kappa(double a, double *vec);
-
-INLINE void apply_tx(double x, double *vec);
-INLINE void apply_ty(double y, double *vec);
-INLINE void apply_tz(double z, double *vec);
-
-/*##############################################
-# functions needed for reciprocal space converions
-################################################*/
-
-int determine_axes_directions(fp_rot *fp_circles, char *stringAxis,
- unsigned int n);
-
-int determine_axes_directions_ap(fp_rot *fp_circles, char *stringAxis,
- unsigned int n);
-
-int determine_detector_pixel(double *rpixel, char *dir, double dpixel,
- double *r_i, double tilt);
-
-int tilt_detector_axis(double tiltazimuth, double tilt,
- double *RESTRICT rpixel1, double *RESTRICT rpixel2);
-
-int print_matrix(double *m);
-int print_vector(double *m);
-
diff --git a/xrayutilities/utilities_noconf.py b/xrayutilities/utilities_noconf.py
index 309736a..21cc09a 100644
--- a/xrayutilities/utilities_noconf.py
+++ b/xrayutilities/utilities_noconf.py
@@ -23,6 +23,7 @@ this part of utilities does not need the config class
import numbers
import numpy
import scipy.constants
+import os
from .exception import InputError
@@ -84,7 +85,7 @@ def en2lam(inp):
Examples
--------
- >>> lambda = lam2en(8048)
+ >>> wavelength = en2lam(8048)
"""
# lambda(A) = h*c/(e * E(eV)) *1e10
inp = energy(inp)
@@ -101,7 +102,6 @@ def energy(en):
Parameter
---------
-
en: energy either as scalar or array with value in eV, which
will be returned unchanged; or string with name of emission line
@@ -128,7 +128,6 @@ def wavelength(wl):
Parameter
---------
-
wl: wavelength; If scalar or array the wavelength in Angstrom will be
returned unchanged, string with emission name is converted to
wavelength
@@ -147,3 +146,68 @@ def wavelength(wl):
return en2lam(energies[wl])
else:
raise InputError("wrong type for argument wavelength")
+
+
+def exchange_path(orig, new, keep=0):
+ """
+ function to exchange the root of a path with the option of keeping the
+ inner directory structure. This for example includes such a conversion
+ /dir_a/subdir/images/sample -> /home/user/data/images/sample
+ where the two innermost directory names are kept (keep=2)
+
+ Parameter
+ ---------
+ orig: original path which should be replaced by the new path
+ new: new path which should be used instead
+ keep: (optional) number of inner most directory names which should be
+ kept the same in the output (default = 0)
+
+ Returns
+ -------
+ directory path string
+
+ Examples
+ --------
+ >>> exchange_path('/dir_a/subdir/img/sam', '/home/user/data', 2)
+ '/home/user/data/img/sam'
+ """
+ subdirs = []
+ o = orig
+ for i in range(keep):
+ o, s = os.path.split(o)
+ subdirs.append(s)
+ out = new
+ subdirs.reverse()
+ for s in subdirs:
+ out = os.path.join(out, s)
+ return out
+
+
+def exchange_filepath(orig, new, keep=0):
+ """
+ function to exchange the root of a filename with the option of keeping the
+ inner directory structure. This for example includes such a conversion
+ /dir_a/subdir/sample/file.txt -> /home/user/data/sample/file.txt
+ where the innermost directory name is kept (keep=1)
+
+ Parameter
+ ---------
+ orig: original filename which should have its data root replaced
+ new: new path which should be used instead
+ keep: (optional) number of inner most directory names which should be
+ kept the same in the output (default = 0). Note that the filename
+ is always return unchanged also with keep=0.
+
+ Returns
+ -------
+ filename string
+
+ Examples
+ --------
+ >>> exchange_filepath('/dir_a/subdir/sam/file.txt', '/data', 1)
+ '/data/sam/file.txt'
+ """
+ if new:
+ return exchange_path(orig, new, keep+1)
+ else:
+ return orig
diff --git a/xrayutilities/xrayutilities_default.conf b/xrayutilities/xrayutilities_default.conf
index d07afe2..f06cdc9 100644
--- a/xrayutilities/xrayutilities_default.conf
+++ b/xrayutilities/xrayutilities_default.conf
@@ -1,6 +1,6 @@
# XRAYUTILITIES global default configuration
# default values for some properties of xrayutilities may be set
-# the syntax follows the one of the ConfigParser python module,
+# the syntax follows the one of the ConfigParser Python module,
# which is similar to .ini files
# begin of xrayutilities configuration
--
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