pyFAI.io package

pyFAI.io.image module

Module function to read images.

pyFAI.io.image.read_data(image_path)

Returns a numpy.array image from a file name or a URL.

Parameters:

image_path (str) – Path of the image file

Return type:

numpy.ndarray regardless the dimention or the content

Raises:

IOError – if the data is not reachable
TypeError – if the data is not an image (wrong size, wrong dimension)

pyFAI.io.image.read_image_data(image_path)

Returns a numpy.array image from a file name or a URL.

Parameters:

image_path (str) – Path of the image file

Return type:

numpy.ndarray

Raises:

IOError – if the data is not reachable
TypeError – if the data is not an image (wrong size, wrong dimension)

pyFAI.io.integration_config module

Module function to manage poni files.

class pyFAI.io.integration_config.ConfigurationReader(config)

Bases: object

__init__(config)

Parameters:: config – dictonary

pop_detector()

Returns the detector stored in the json configuration.

Return type:: pyFAI.detectors.Detector

pop_method(default=None)

Returns a Method from the method field from the json dictionary.

Return type:: pyFAI.method_registry.Method

pop_ponifile(): Returns the geometry subpart of the configuration

pyFAI.io.integration_config.normalize(config, inplace=False, do_raise=False)

Normalize the configuration file to the one supported internally (the last one).

Parameters:

config (dict) – The configuration dictionary to read
inplace (bool) – In true, the dictionary is edited inplace
do_raise (bool) – raise ValueError if set. Else use logger.error

Raises:

ValueError – If the configuration do not match & do_raise is set

pyFAI.io.nexus module

Module for writing HDF5 in the Nexus style

class pyFAI.io.nexus.Nexus(filename, mode=None, creator=None, start_time=None)

Bases: object

Writer class to handle Nexus/HDF5 data

Manages:

entry
- pyFAI-subentry
  detector

TODO: make it thread-safe !!!

__init__(filename, mode=None, creator=None, start_time=None)

Constructor

Parameters:

filename – name of the hdf5 file containing the nexus
mode – can be ‘r’, ‘a’, ‘w’, ‘+’ ….
creator – set as attr of the NXroot
start_time – set as attr of the NXroot

close(end_time=None): close the filename and update all entries

deep_copy(name, obj, where='/', toplevel=None, excluded=None, overwrite=False)

perform a deep copy: create a “name” entry in self containing a copy of the object

Parameters:

where – path to the toplevel object (i.e. root)
toplevel – firectly the top level Group
excluded – list of keys to be excluded
overwrite – replace content if already existing

find_detector(all=False)

Tries to find a detector within a NeXus file, takes the first compatible detector

Parameters:: all – return all detectors found as a list

flush()

classmethod get_attr(dset, name, default=None)

Return the attribute of the dataset

Handles the ascii -> unicode issue in python3 #275

Parameters:

dset – a HDF5 dataset (or a group)
name – name of the attribute
default – default value to be returned

Returns:

attribute value decoded in python3 or default

get_class(grp, class_type='NXcollection')

return all sub-groups of the given type within a group

Parameters:

grp – HDF5 group
class_type – name of the NeXus class

get_data(grp, class_type='NXdata')

return all dataset of the the NeXus class NXdata WRONG, do not use…

Parameters:

grp – HDF5 group
class_type – name of the NeXus class

get_dataset(grp, attr=None, value=None)

return list of dataset of the group matching the given attribute having the given value

Parameters:

grp – HDF5 group
attr – name of an attribute
value – requested value for the attribute

Returns:

list of dataset

get_default_NXdata()

Return the default plot configured in the nexus structure.

Returns:: the group with the default plot or None if not found

get_entries()

retrieves all entry sorted the latest first.

Returns:: list of HDF5 groups

get_entry(name)

Retrieves an entry from its name

Parameters:: name – name of the entry to retrieve
Returns:: HDF5 group of NXclass == NXentry

new_class(grp, name, class_type='NXcollection'): create a new sub-group with type class_type :param grp: parent group :param name: name of the sub-group :param class_type: NeXus class name :return: subgroup created

new_detector(name='detector', entry='entry', subentry='pyFAI')

Create a new entry/pyFAI/Detector

Parameters:

detector – name of the detector
entry – name of the entry
subentry – all pyFAI description of detectors should be in a pyFAI sub-entry

new_entry(entry='entry', program_name='pyFAI', title=None, force_time=None, force_name=False)

Create a new entry

Parameters:

entry – name of the entry
program_name – value of the field as string
title – description of experiment as str
force_time – enforce the start_time (as string!)
force_name – force the entry name as such, without numerical suffix.

Returns:

the corresponding HDF5 group

new_instrument(entry='entry', instrument_name='id00'): Create an instrument in an entry or create both the entry and the instrument if

pyFAI.io.nexus.from_isotime(text, use_tz=False)

Parameters:: text – string representing the time is iso format

pyFAI.io.nexus.get_isotime(forceTime=None)

Parameters:: forceTime (float) – enforce a given time (current by default)
Returns:: the current time as an ISO8601 string
Return type:: string

pyFAI.io.nexus.is_hdf5(filename)

Check if a file is actually a HDF5 file

Parameters:: filename – this file has better to exist

pyFAI.io.nexus.load_nexus(filename)

Tried to read-back a file from a Nexus file written by pyFAI

Parameters:: filename – the name of the nexus file
Returns:: parsed result

pyFAI.io.nexus.save_NXcansas(filename, result, title='something descriptive yet short', run='run-number', entry='entry', instrument='beamline', source_name='ESRF', source_type='synchotron', source_probe='x-ray', sample='sample', extra=None)

Save integrated data into a HDF5-file following the Nexus canSAS application definition: https://manual.nexusformat.org/classes/applications/NXcanSAS.html

Parameters:

filename – name of the file to be written
result – instance of Integrate1dResult
title – title of the experiment
entry – name of the entry
instrument – name/brand of the instrument
source_name – name/brand of the particule source
source_type – kind of source as a string
source_probe – Any of these values: ‘neutron’ | ‘x-ray’ | ‘electron’
sample – sample name
extra – extra metadata as a dict

pyFAI.io.nexus.save_NXmonpd(filename, result, title='monopd', entry='entry', instrument='beamline', source_name='ESRF', source_type='synchotron', source_probe='x-ray', sample='sample', extra=None)

Save integrated data into a HDF5-file following the Nexus powder diffraction application definition: https://manual.nexusformat.org/classes/applications/NXmonopd.html

Parameters:

filename – name of the file to be written
result – instance of Integrate1dResult
title – title of the experiment
entry – name of the entry
instrument – name/brand of the instrument
source_name – name/brand of the particule source
source_type – kind of source as a string
source_probe – Any of these values: ‘neutron’ | ‘x-ray’ | ‘electron’
sample – sample name
extra – extra metadata as a dict

pyFAI.io.ponifile module

Module function to manage poni files.

class pyFAI.io.ponifile.PoniFile(data=None)

Bases: object

API_VERSION = 2.1

__init__(data=None)

as_dict()

property detector

Return type:: Union[None, object]

property dist

Return type:: Union[None,float]

make_headers(type_='list'): Generate a header for files, as list or dict or str

property poni1

Return type:: Union[None,float]

property poni2

Return type:: Union[None,float]

read_from_dict(config)

Initialize this object using a dictionary.

Note

The dictionary is versionned.

Version: * 1: Historical version (i.e. unversioned) * 2: store detector and detector_config instead of pixelsize1, pixelsize2 and splinefile * 2.1: manage orientation of detector in detector_config

read_from_duck(duck)

Initialize the object using an object providing the same API.

The duck object must provide dist, poni1, poni2, rot1, rot2, rot3, wavelength, and detector.

read_from_file(filename)

read_from_geometryModel(model: GeometryModel, detector=None)

Initialize the object from a GeometryModel

pyFAI.gui.model.GeometryModel.GeometryModel

property rot1

Return type:: Union[None,float]

property rot2

Return type:: Union[None,float]

property rot3

Return type:: Union[None,float]

property wavelength

Return type:: Union[None,float]

write(fd)

Write this object to an open stream.

Parameters:: fd – file descriptor (opened file)
Returns:: nothing

pyFAI.io.sparse_frame module

Module for writing sparse frames in HDF5 in the Nexus style

pyFAI.io.sparse_frame.save_sparse(filename, frames, beamline='beamline', ai=None, source=None, extra={}, start_time=None)

Write the list of frames into a HDF5 file

Parameters:

filename – name of the file
frames – list of sparse frames (as built by sparsify)
beamline – name of the beamline as text
ai – Instance of geometry or azimuthal integrator
source – list of input files
extra – dict with extra metadata
start_time – float with the time of start of the processing

Returns:

None

Module contents

Module for “high-performance” writing in either 1D with Ascii , or 2D with FabIO or even nD with n varying from 2 to 4 using HDF5

Stand-alone module which tries to offer interface to HDF5 via H5Py and capabilities to write EDF or other formats using fabio.

Can be imported without h5py but then limited to fabio & ascii formats.

TODO:

Add monitor to HDF5

class pyFAI.io.AsciiWriter(filename=None, prefix='fai_', extension='.dat')

Bases: Writer

Ascii file writer (.xy or .dat)

__init__(filename=None, prefix='fai_', extension='.dat')

init(fai_cfg=None, lima_cfg=None): Creates the directory that will host the output file(s)

write(data, index=0): To be implemented

class pyFAI.io.DefaultAiWriter(filename, engine=None)

Bases: Writer

__init__(filename, engine=None)

Constructor of the historical writer of azimuthalIntegrator.

Parameters:

filename – name of the output file
ai – integrator, should provide make_headers method.

close()

flush(): To be implemented

init(fai_cfg=None, lima_cfg=None): Creates the directory that will host the output file(s) :param fai_cfg: configuration for worker :param lima_cfg: configuration for acquisition

make_headers(hdr='#', has_mask=None, has_dark=None, has_flat=None, polarization_factor=None, normalization_factor=None, metadata=None)

Parameters:

hdr (str) – string used as comment in the header
has_dark (bool) – save the darks filenames (default: no)
has_flat (bool) – save the flat filenames (default: no)
polarization_factor (float) – the polarization factor

Returns:

the header

Return type:

str

save1D(filename, dim1, I, error=None, dim1_unit='2th_deg', has_mask=None, has_dark=False, has_flat=False, polarization_factor=None, normalization_factor=None, metadata=None)

This method save the result of a 1D integration as ASCII file.

Parameters:

filename (str) – the filename used to save the 1D integration
dim1 (numpy.ndarray) – the x coordinates of the integrated curve
I (numpy.mdarray) – The integrated intensity
error (numpy.ndarray or None) – the error bar for each intensity
dim1_unit (pyFAI.units.Unit) – the unit of the dim1 array
has_mask – a mask was used
has_dark – a dark-current was applied
has_flat – flat-field was applied
polarization_factor (float, None) – the polarization factor
normalization_factor (float, None) – the monitor value
metadata – JSON serializable dictionary containing the metadata

save2D(filename, I, dim1, dim2, error=None, dim1_unit='2th_deg', dim2_unit='chi_deg', has_mask=None, has_dark=False, has_flat=False, polarization_factor=None, normalization_factor=None, metadata=None, format_='edf')

This method save the result of a 2D integration.

Parameters:

filename (str) – the filename used to save the 2D histogram
dim1 (numpy.ndarray) – the 1st coordinates of the histogram
dim1 – the 2nd coordinates of the histogram
I (numpy.mdarray) – The integrated intensity
error (numpy.ndarray or None) – the error bar for each intensity
dim1_unit (pyFAI.units.Unit) – the unit of the dim1 array
dim2_unit (pyFAI.units.Unit) – the unit of the dim2 array
has_mask – a mask was used
has_dark – a dark-current was applied
has_flat – flat-field was applied
polarization_factor (float, None) – the polarization factor
normalization_factor (float, None) – the monitor value
metadata – JSON serializable dictionary containing the metadata
format – file-format to be used (FabIO format)

set_filename(filename): Define the filename while will be used

write(data)

Minimalistic method to limit the overhead.

Parameters:: data – array with intensities or tuple (2th,I) or (I,2th,chi) :type data: Integrate1dResult, Integrate2dResult

class pyFAI.io.FabioWriter(filename=None, extension=None, directory='', prefix=None, index_format='_%04d', start_index=0, fabio_class=None)

Bases: Writer

Image file writer based on FabIO

__init__(filename=None, extension=None, directory='', prefix=None, index_format='_%04d', start_index=0, fabio_class=None)

Constructor of the class

Parameters:

filename –
extension –
prefix – basename of the file
index_format – “_%04s” gives “_0001” for example
start_index – often 0 or 1
fabio_class – type of file to write

close()

init(fai_cfg=None, lima_cfg=None, directory='pyFAI'): Creates the directory that will host the output file(s)

write(data, index=None, header=None)

Parameters:

data – 2d array to save
index – index of the file
header –

class pyFAI.io.HDF5Writer(filename, hpath=None, entry_template=None, fast_scan_width=None, append_frames=False, mode='error')

Bases: Writer

Class allowing to write HDF5 Files.

CONFIG = 'configuration'

DATASET_NAME = 'data'

MODE_APPEND = 'append'

MODE_DELETE = 'delete'

MODE_ERROR = 'error'

MODE_OVERWRITE = 'overwrite'

__init__(filename, hpath=None, entry_template=None, fast_scan_width=None, append_frames=False, mode='error')

Constructor of an HDF5 writer:

Parameters:

filename (str) – name of the file
hpath (str) – Name of the entry group that will contains the NXprocess.
entry_template (str) – Formattable template to create a new entry (if hpath is not specified)
fast_scan_width (int) – set it to define the width of

close()

flush(radial=None, azimuthal=None)

Update some data like axis units and so on.

Parameters:

radial – position in radial direction
azimuthal – position in azimuthal direction

init(fai_cfg=None, lima_cfg=None): Initializes the HDF5 file for writing :param fai_cfg: the configuration of the worker as a dictionary

set_hdf5_input_dataset(dataset): record the input dataset with an external link

write(data, index=None): Minimalistic method to limit the overhead. :param data: array with intensities or tuple (2th,I) or (I,2th,chi)

class pyFAI.io.Writer(filename=None, extension=None)

Bases: object

Abstract class for writers.

CONFIG_ITEMS = ['filename', 'dirname', 'extension', 'subdir', 'hpath']

__init__(filename=None, extension=None): Constructor of the class

flush(*arg, **kwarg): To be implemented

init(fai_cfg=None, lima_cfg=None): Creates the directory that will host the output file(s) :param fai_cfg: configuration for worker :param lima_cfg: configuration for acquisition

setJsonConfig(json_config=None): Sets the JSON configuration

write(data): To be implemented

pyFAI.io.save_integrate_result(filename, result, title='title', sample='sample', instrument='beamline'): Dispatcher for saving in different formats