pyFAI.io package

pyFAI.io.image module

Module function to read images.

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)

Initialize self. See help(type(self)) for accurate signature.

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

pyFAI.io.integration_config.normalize(config, inplace=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

Raises

ValueError – If the configuration do not match.

pyFAI.io.ponifile module

Module function to manage poni files.

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

Bases: object

__init__(data=None)

Initialize self. See help(type(self)) for accurate signature.

as_dict()

detector

Return type

Union[None,float]

dist

Return type

Union[None,float]

poni1

Return type

Union[None,float]

poni2

Return type

Union[None,float]

read_from_dict(config)

Initialize this object using a dictionary.

Note

The dictionary is versionned.

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)

rot1

Return type

Union[None,float]

rot2

Return type

Union[None,float]

rot3

Return type

Union[None,float]

wavelength

Return type

Union[None,float]

write(fd)

Write this object to an open stream.

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: pyFAI.io.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: pyFAI.io.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', has_mask=None, has_dark=False, has_flat=False, polarization_factor=None, normalization_factor=None, metadata=None)

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

• 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

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)

Bases: pyFAI.io.Writer

Image file writer based on FabIO

TODO !!!

__init__(filename=None)

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

Bases: pyFAI.io.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

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.Nexus(filename, mode='r')

Bases: object

Writer class to handle Nexus/HDF5 data

Manages:

• entry

  • pyFAI-subentry

    • detector

TODO: make it thread-safe !!!

__init__(filename, mode='r')

Constructor

Parameters

• filename – name of the hdf5 file containing the nexus

• mode – can be r or a

close()

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

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

Parameters

• grp – HDF5 group

• class_type – name of the NeXus class

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='description of experiment', 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 – value of the field as string

• 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

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.from_isotime(text, use_tz=False)

Parameters

text – string representing the time is iso format

pyFAI.io.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.is_hdf5(filename)

Check if a file is actually a HDF5 file

Parameters

filename – this file has better to exist