pyFAI.detectors package¶

Module contents¶

Description of all detectors with a factory to instantiate them.

class pyFAI.detectors.Detector(pixel1=None, pixel2=None, splineFile=None, max_shape=None)¶

Bases: object

Generic class representing a 2D detector

API_VERSION = '1.0'¶

HAVE_TAPER = False¶: If true a spline file is mandatory to correct the geometry

IS_CONTIGUOUS = True¶

IS_FLAT = True¶

MANUFACTURER = None¶

__init__(pixel1=None, pixel2=None, splineFile=None, max_shape=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = []¶

property binning¶

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!! Adapted to Nexus detector definition

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)
center – retrieve the coordinate of the center of the pixel, unless gives one corner
use_cython – set to False to test Python implementation

Returns

position in meter of the center of each pixels.

Return type

3xndarray, the later being None if IS_FLAT

d1 and d2 must have the same shape, returned array will have the same shape.

pos_z is None for flat detectors

calc_mask()¶

Method calculating the mask for a given detector

Detectors with gaps should overwrite this method with something actually calculating the mask!

Returns: the mask with valid pixel to 0
Return type: numpy ndarray of int8 or None

property darkcurrent¶

classmethod factory(name, config=None)¶

A kind of factory…

Parameters

name (str) – name of a detector
config (dict or JSON representation of it.) – configuration of the detector

Returns

an instance of the right detector, set-up if possible

Return type

pyFAI.detectors.Detector

property flatfield¶

force_pixel = False¶

classmethod from_dict(dico)¶

Creates a brand new detector from the description of the detector as a dict

Parameters: dico – JSON serializable dictionary
Returns: Detector instance

getFit2D()¶

Helper method to serialize the description of a detector using the Fit2d units

Returns: representation of the detector easy to serialize
Return type: dict

getPyFAI()¶

Helper method to serialize the description of a detector using the pyFAI way with everything in S.I units.

Returns: representation of the detector easy to serialize
Return type: dict

get_binning()¶

get_config()¶

Return the configuration with arguments to the constructor

Derivative classes should implement this method if they change the constructor!

Returns: dict with param for serialization

get_darkcurrent()¶

get_darkcurrent_crc()¶

get_flatfield()¶

get_flatfield_crc()¶

get_mask()¶

get_mask_crc()¶

get_maskfile()¶

get_name()¶: Get a meaningful name for detector

get_pixel1()¶

get_pixel2()¶

get_pixel_corners()¶

Calculate the position of the corner of the pixels

This should be overwritten by class representing non-contiguous detector (Xpad, …)

Precision float32 is ok: precision of 1µm for a detector size of 1m

Returns: 4D array containing: pixel index (slow dimension) pixel index (fast dimension) corner index (A, B, C or D), triangles or hexagons can be handled the same way vertex position (z,y,x)

get_splineFile()¶

guess_binning(data)¶

Guess the binning/mode depending on the image shape

If the binning changes, this enforces the reset of the mask.

Parameters: data – 2-tuple with the shape of the image or the image with a .shape attribute.
Returns: True if the data fit the detector
Return type: bool

property mask¶

property maskfile¶

property name¶: Get a meaningful name for detector

property pixel1¶

property pixel2¶

registry = {'aarhus': <class 'pyFAI.detectors._others.Aarhus'>, 'aca1300': <class 'pyFAI.detectors._others.Basler'>, 'adsc_q210': <class 'pyFAI.detectors._adsc.ADSC_Q210'>, 'adsc_q270': <class 'pyFAI.detectors._adsc.ADSC_Q270'>, 'adsc_q315': <class 'pyFAI.detectors._adsc.ADSC_Q315'>, 'adsc_q4': <class 'pyFAI.detectors._adsc.ADSC_Q4'>, 'agilent_titan': <class 'pyFAI.detectors._others.Titan'>, 'agilenttitan': <class 'pyFAI.detectors._others.Titan'>, 'apex2': <class 'pyFAI.detectors._others.Apex2'>, 'apexii': <class 'pyFAI.detectors._others.Apex2'>, 'basler': <class 'pyFAI.detectors._others.Basler'>, 'bruker': <class 'pyFAI.detectors._others.Apex2'>, 'cirpad': <class 'pyFAI.detectors._imxpad.Cirpad'>, 'condor': <class 'pyFAI.detectors._others.Fairchild'>, 'd5': <class 'pyFAI.detectors._imxpad.Xpad_flat'>, 'detector': <class 'pyFAI.detectors._common.Detector'>, 'dexela2923': <class 'pyFAI.detectors._others.Dexela2923'>, 'dexela_2923': <class 'pyFAI.detectors._others.Dexela2923'>, 'eiger16m': <class 'pyFAI.detectors._dectris.Eiger16M'>, 'eiger1m': <class 'pyFAI.detectors._dectris.Eiger1M'>, 'eiger4m': <class 'pyFAI.detectors._dectris.Eiger4M'>, 'eiger500k': <class 'pyFAI.detectors._dectris.Eiger500k'>, 'eiger9m': <class 'pyFAI.detectors._dectris.Eiger9M'>, 'eiger_16m': <class 'pyFAI.detectors._dectris.Eiger16M'>, 'eiger_1m': <class 'pyFAI.detectors._dectris.Eiger1M'>, 'eiger_4m': <class 'pyFAI.detectors._dectris.Eiger4M'>, 'eiger_500k': <class 'pyFAI.detectors._dectris.Eiger500k'>, 'eiger_9m': <class 'pyFAI.detectors._dectris.Eiger9M'>, 'fairchild': <class 'pyFAI.detectors._others.Fairchild'>, 'fairchild_condor_486:90': <class 'pyFAI.detectors._others.Fairchild'>, 'fairchildcondor486:90': <class 'pyFAI.detectors._others.Fairchild'>, 'frelon': <class 'pyFAI.detectors._esrf.FReLoN'>, 'hf-130k': <class 'pyFAI.detectors._adsc.HF_130K'>, 'hf-1m': <class 'pyFAI.detectors._adsc.HF_1M'>, 'hf-2.4m': <class 'pyFAI.detectors._adsc.HF_2M'>, 'hf-262k': <class 'pyFAI.detectors._adsc.HF_262k'>, 'hf-4m': <class 'pyFAI.detectors._adsc.HF_4M'>, 'hf-9.4m': <class 'pyFAI.detectors._adsc.HF_9M'>, 'hf_130k': <class 'pyFAI.detectors._adsc.HF_130K'>, 'hf_1m': <class 'pyFAI.detectors._adsc.HF_1M'>, 'hf_262k': <class 'pyFAI.detectors._adsc.HF_262k'>, 'hf_2m': <class 'pyFAI.detectors._adsc.HF_2M'>, 'hf_4m': <class 'pyFAI.detectors._adsc.HF_4M'>, 'hf_9m': <class 'pyFAI.detectors._adsc.HF_9M'>, 'imxpad_s10': <class 'pyFAI.detectors._imxpad.ImXPadS10'>, 'imxpad_s140': <class 'pyFAI.detectors._imxpad.ImXPadS140'>, 'imxpad_s70': <class 'pyFAI.detectors._imxpad.ImXPadS70'>, 'imxpad_s70_v': <class 'pyFAI.detectors._imxpad.ImXPadS70V'>, 'imxpads10': <class 'pyFAI.detectors._imxpad.ImXPadS10'>, 'imxpads140': <class 'pyFAI.detectors._imxpad.ImXPadS140'>, 'imxpads70': <class 'pyFAI.detectors._imxpad.ImXPadS70'>, 'imxpads70v': <class 'pyFAI.detectors._imxpad.ImXPadS70V'>, 'mar133': <class 'pyFAI.detectors._rayonix.Rayonix133'>, 'mar165': <class 'pyFAI.detectors._rayonix.RayonixSx165'>, 'mar225': <class 'pyFAI.detectors._rayonix.RayonixMx225'>, 'mar300': <class 'pyFAI.detectors._rayonix.RayonixMx300'>, 'mar345': <class 'pyFAI.detectors._rayonix.Mar345'>, 'mar3450': <class 'pyFAI.detectors._rayonix.Mar345'>, 'mar555': <class 'pyFAI.detectors._rayonix.Mar555'>, 'mar_133': <class 'pyFAI.detectors._rayonix.Rayonix133'>, 'mar_165': <class 'pyFAI.detectors._rayonix.RayonixSx165'>, 'mar_225': <class 'pyFAI.detectors._rayonix.RayonixMx225'>, 'mar_300': <class 'pyFAI.detectors._rayonix.RayonixMx300'>, 'mar_345': <class 'pyFAI.detectors._rayonix.Mar345'>, 'mar_555': <class 'pyFAI.detectors._rayonix.Mar555'>, 'maxipix': <class 'pyFAI.detectors._esrf.Maxipix'>, 'maxipix1x1': <class 'pyFAI.detectors._esrf.Maxipix'>, 'maxipix2x2': <class 'pyFAI.detectors._esrf.Maxipix2x2'>, 'maxipix5x1': <class 'pyFAI.detectors._esrf.Maxipix5x1'>, 'maxipix_1x1': <class 'pyFAI.detectors._esrf.Maxipix'>, 'maxipix_2x2': <class 'pyFAI.detectors._esrf.Maxipix2x2'>, 'maxipix_5x1': <class 'pyFAI.detectors._esrf.Maxipix5x1'>, 'mythen': <class 'pyFAI.detectors._dectris.Mythen'>, 'mythen1280': <class 'pyFAI.detectors._dectris.Mythen'>, 'mythen_1280': <class 'pyFAI.detectors._dectris.Mythen'>, 'oxd_titan': <class 'pyFAI.detectors._others.Titan'>, 'oxdtitan': <class 'pyFAI.detectors._others.Titan'>, 'perkin': <class 'pyFAI.detectors._others.Perkin'>, 'perkin_detector': <class 'pyFAI.detectors._others.Perkin'>, 'perkin_elmer': <class 'pyFAI.detectors._others.Perkin'>, 'perkindetector': <class 'pyFAI.detectors._others.Perkin'>, 'perkinelmer': <class 'pyFAI.detectors._others.Perkin'>, 'picam_v1': <class 'pyFAI.detectors._others.RaspberryPi5M'>, 'picam_v2': <class 'pyFAI.detectors._others.RaspberryPi8M'>, 'picamv1': <class 'pyFAI.detectors._others.RaspberryPi5M'>, 'picamv2': <class 'pyFAI.detectors._others.RaspberryPi8M'>, 'pilatus100k': <class 'pyFAI.detectors._dectris.Pilatus100k'>, 'pilatus1m': <class 'pyFAI.detectors._dectris.Pilatus1M'>, 'pilatus1m_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe1M'>, 'pilatus1mcdte': <class 'pyFAI.detectors._dectris.PilatusCdTe1M'>, 'pilatus200k': <class 'pyFAI.detectors._dectris.Pilatus200k'>, 'pilatus2m': <class 'pyFAI.detectors._dectris.Pilatus2M'>, 'pilatus2m_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe2M'>, 'pilatus2mcdte': <class 'pyFAI.detectors._dectris.PilatusCdTe2M'>, 'pilatus300k': <class 'pyFAI.detectors._dectris.Pilatus300k'>, 'pilatus300k_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe300k'>, 'pilatus300kcdte': <class 'pyFAI.detectors._dectris.PilatusCdTe300k'>, 'pilatus300kw': <class 'pyFAI.detectors._dectris.Pilatus300kw'>, 'pilatus300kw_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe300kw'>, 'pilatus300kwcdte': <class 'pyFAI.detectors._dectris.PilatusCdTe300kw'>, 'pilatus6m': <class 'pyFAI.detectors._dectris.Pilatus6M'>, 'pilatus900kw_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe900kw'>, 'pilatus900kwcdte': <class 'pyFAI.detectors._dectris.PilatusCdTe900kw'>, 'pilatus_100k': <class 'pyFAI.detectors._dectris.Pilatus100k'>, 'pilatus_1m': <class 'pyFAI.detectors._dectris.Pilatus1M'>, 'pilatus_1m_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe1M'>, 'pilatus_200k': <class 'pyFAI.detectors._dectris.Pilatus200k'>, 'pilatus_2m': <class 'pyFAI.detectors._dectris.Pilatus2M'>, 'pilatus_2m_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe2M'>, 'pilatus_300k': <class 'pyFAI.detectors._dectris.Pilatus300k'>, 'pilatus_300k_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe300k'>, 'pilatus_300kw': <class 'pyFAI.detectors._dectris.Pilatus300kw'>, 'pilatus_300kw_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe300kw'>, 'pilatus_6m': <class 'pyFAI.detectors._dectris.Pilatus6M'>, 'pilatus_900kw_cdte': <class 'pyFAI.detectors._dectris.PilatusCdTe900kw'>, 'pilatus_cdte_1m': <class 'pyFAI.detectors._dectris.PilatusCdTe1M'>, 'pilatus_cdte_2m': <class 'pyFAI.detectors._dectris.PilatusCdTe2M'>, 'pilatus_cdte_300k': <class 'pyFAI.detectors._dectris.PilatusCdTe300k'>, 'pilatus_cdte_300kw': <class 'pyFAI.detectors._dectris.PilatusCdTe300kw'>, 'pilatus_cdte_900kw': <class 'pyFAI.detectors._dectris.PilatusCdTe900kw'>, 'pilatuscdte1m': <class 'pyFAI.detectors._dectris.PilatusCdTe1M'>, 'pilatuscdte2m': <class 'pyFAI.detectors._dectris.PilatusCdTe2M'>, 'pilatuscdte300k': <class 'pyFAI.detectors._dectris.PilatusCdTe300k'>, 'pilatuscdte300kw': <class 'pyFAI.detectors._dectris.PilatusCdTe300kw'>, 'pilatuscdte900kw': <class 'pyFAI.detectors._dectris.PilatusCdTe900kw'>, 'pixium': <class 'pyFAI.detectors._others.Pixium'>, 'pixium4700': <class 'pyFAI.detectors._others.Pixium'>, 'pixium4700detector': <class 'pyFAI.detectors._others.Pixium'>, 'pixium_4700': <class 'pyFAI.detectors._others.Pixium'>, 'pixium_4700_detector': <class 'pyFAI.detectors._others.Pixium'>, 'quantum210': <class 'pyFAI.detectors._adsc.ADSC_Q210'>, 'quantum270': <class 'pyFAI.detectors._adsc.ADSC_Q270'>, 'quantum315': <class 'pyFAI.detectors._adsc.ADSC_Q315'>, 'quantum4': <class 'pyFAI.detectors._adsc.ADSC_Q4'>, 'quantum_210': <class 'pyFAI.detectors._adsc.ADSC_Q210'>, 'quantum_270': <class 'pyFAI.detectors._adsc.ADSC_Q270'>, 'quantum_315': <class 'pyFAI.detectors._adsc.ADSC_Q315'>, 'quantum_4': <class 'pyFAI.detectors._adsc.ADSC_Q4'>, 'raspberrypi5m': <class 'pyFAI.detectors._others.RaspberryPi5M'>, 'raspberrypi8m': <class 'pyFAI.detectors._others.RaspberryPi8M'>, 'rayonix133': <class 'pyFAI.detectors._rayonix.Rayonix133'>, 'rayonix_lx170': <class 'pyFAI.detectors._rayonix.RayonixLx170'>, 'rayonix_lx170-hs': <class 'pyFAI.detectors._rayonix.RayonixLx170'>, 'rayonix_lx170_hs': <class 'pyFAI.detectors._rayonix.RayonixLx170'>, 'rayonix_lx255': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonix_lx255-hs': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonix_lx_255hs': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonix_mx170': <class 'pyFAI.detectors._rayonix.RayonixMx170'>, 'rayonix_mx170-hs': <class 'pyFAI.detectors._rayonix.RayonixMx170'>, 'rayonix_mx170_hs': <class 'pyFAI.detectors._rayonix.RayonixMx170'>, 'rayonix_mx225': <class 'pyFAI.detectors._rayonix.RayonixMx225'>, 'rayonix_mx225_hs': <class 'pyFAI.detectors._rayonix.RayonixMx225hs'>, 'rayonix_mx225hs': <class 'pyFAI.detectors._rayonix.RayonixMx225hs'>, 'rayonix_mx300': <class 'pyFAI.detectors._rayonix.RayonixMx300'>, 'rayonix_mx300_hs': <class 'pyFAI.detectors._rayonix.RayonixMx300hs'>, 'rayonix_mx300hs': <class 'pyFAI.detectors._rayonix.RayonixMx300hs'>, 'rayonix_mx325': <class 'pyFAI.detectors._rayonix.RayonixMx325'>, 'rayonix_mx340hs': <class 'pyFAI.detectors._rayonix.RayonixMx340hs'>, 'rayonix_mx425_hs': <class 'pyFAI.detectors._rayonix.RayonixMx425hs'>, 'rayonix_mx425hs': <class 'pyFAI.detectors._rayonix.RayonixMx425hs'>, 'rayonix_sx165': <class 'pyFAI.detectors._rayonix.RayonixSx165'>, 'rayonix_sx200': <class 'pyFAI.detectors._rayonix.RayonixSx200'>, 'rayonix_sx30_hs': <class 'pyFAI.detectors._rayonix.RayonixSx30hs'>, 'rayonix_sx30hs': <class 'pyFAI.detectors._rayonix.RayonixSx30hs'>, 'rayonix_sx85_hs': <class 'pyFAI.detectors._rayonix.RayonixSx85hs'>, 'rayonix_sx85hs': <class 'pyFAI.detectors._rayonix.RayonixSx85hs'>, 'rayonixlx170': <class 'pyFAI.detectors._rayonix.RayonixLx170'>, 'rayonixlx170-hs': <class 'pyFAI.detectors._rayonix.RayonixLx170'>, 'rayonixlx170hs': <class 'pyFAI.detectors._rayonix.RayonixLx170'>, 'rayonixlx225hs': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonixlx255': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonixlx255-hs': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonixlx255hs': <class 'pyFAI.detectors._rayonix.RayonixLx255'>, 'rayonixmx170': <class 'pyFAI.detectors._rayonix.RayonixMx170'>, 'rayonixmx170-hs': <class 'pyFAI.detectors._rayonix.RayonixMx170'>, 'rayonixmx170hs': <class 'pyFAI.detectors._rayonix.RayonixMx170'>, 'rayonixmx225': <class 'pyFAI.detectors._rayonix.RayonixMx225'>, 'rayonixmx225hs': <class 'pyFAI.detectors._rayonix.RayonixMx225hs'>, 'rayonixmx300': <class 'pyFAI.detectors._rayonix.RayonixMx300'>, 'rayonixmx300hs': <class 'pyFAI.detectors._rayonix.RayonixMx300hs'>, 'rayonixmx325': <class 'pyFAI.detectors._rayonix.RayonixMx325'>, 'rayonixmx340hs': <class 'pyFAI.detectors._rayonix.RayonixMx340hs'>, 'rayonixmx425hs': <class 'pyFAI.detectors._rayonix.RayonixMx425hs'>, 'rayonixsx165': <class 'pyFAI.detectors._rayonix.RayonixSx165'>, 'rayonixsx200': <class 'pyFAI.detectors._rayonix.RayonixSx200'>, 'rayonixsx30hs': <class 'pyFAI.detectors._rayonix.RayonixSx30hs'>, 'rayonixsx85hs': <class 'pyFAI.detectors._rayonix.RayonixSx85hs'>, 'thales_electronics': <class 'pyFAI.detectors._others.Pixium'>, 'thaleselectronics': <class 'pyFAI.detectors._others.Pixium'>, 'titan': <class 'pyFAI.detectors._others.Titan'>, 'titan2kx2k': <class 'pyFAI.detectors._others.Titan'>, 'titan_2k_x_2k': <class 'pyFAI.detectors._others.Titan'>, 'xcirpad': <class 'pyFAI.detectors._imxpad.Cirpad'>, 'xpad_flat': <class 'pyFAI.detectors._imxpad.Xpad_flat'>, 'xpad_s540_flat': <class 'pyFAI.detectors._imxpad.Xpad_flat'>, 'xpads540flat': <class 'pyFAI.detectors._imxpad.Xpad_flat'>}¶

save(filename)¶

Saves the detector description into a NeXus file, adapted from: http://download.nexusformat.org/sphinx/classes/base_classes/NXdetector.html Main differences:

differentiate pixel center from pixel corner offsets

store all offsets are ndarray according to slow/fast dimension (not x, y)

Parameters: filename – name of the file on the disc

setFit2D(**kwarg)¶

Twin method of getFit2D: setup a detector instance according to a description

Parameters: kwarg – dictionary containing pixel1, pixel2 and splineFile

setPyFAI(**kwarg)¶

Twin method of getPyFAI: setup a detector instance according to a description

Parameters: kwarg – dictionary containing detector, pixel1, pixel2 and splineFile

set_binning(bin_size=(1, 1))¶

Set the “binning” of the detector,

Parameters: bin_size ((int, int)) – binning as integer or tuple of integers.

set_config(config)¶

Sets the configuration of the detector.

The configuration is either a python dictionary or a JSON string or a file containing this JSON configuration

keys in that dictionary are: pixel1, pixel2, splineFile, max_shape

Parameters: config – string or JSON-serialized dict
Returns: self

set_darkcurrent(dark)¶

set_darkfiles(files=None, method='mean')¶

Parameters

files (str or list(str) or None) – file(s) used to compute the dark.
method (str) – method used to compute the dark, “mean” or “median”

Set the dark current from one or mutliple files, avaraged according to the method provided

set_dx(dx=None)¶: set the pixel-wise displacement along X (dim2):

set_dy(dy=None)¶: set the pixel-wise displacement along Y (dim1):

set_flatfield(flat)¶

set_flatfiles(files, method='mean')¶

Parameters

files (str or list(str) or None) – file(s) used to compute the flat-field.
method (str) – method used to compute the dark, “mean” or “median”

Set the flat field from one or mutliple files, averaged according to the method provided

set_mask(mask)¶

set_maskfile(maskfile)¶

set_pixel1(value)¶

set_pixel2(value)¶

set_pixel_corners(ary)¶

Sets the position of pixel corners with some additional validation

Parameters: ary – This a 4D array which contains: number of lines, number of columns, corner index, position in space Z, Y, X

set_splineFile(splineFile)¶

property splineFile¶

uniform_pixel = True¶

class pyFAI.detectors.NexusDetector(filename=None)¶

Bases: pyFAI.detectors._common.Detector

Class representing a 2D detector loaded from a NeXus file

__init__(filename=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

property filename¶

Returns the filename containing the description of this detector.

Return type: Enum[None|str]

getFit2D()¶

Helper method to serialize the description of a detector using the Fit2d units

Returns: representation of the detector easy to serialize
Return type: dict

getPyFAI()¶

Helper method to serialize the description of a detector using the pyFAI way with everything in S.I units.

Returns: representation of the detector easy to serialize
Return type: dict

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

get_filename()¶

Returns the filename containing the description of this detector.

Return type: Enum[None|str]

load(filename)¶

Loads the detector description from a NeXus file, adapted from: http://download.nexusformat.org/sphinx/classes/base_classes/NXdetector.html

Parameters: filename – name of the file on the disk

set_config(config)¶

set the config of the detector

For Nexus detector, the only valid key is “filename”

Parameters: config – dict or JSON serialized dict
Returns: detector instance

classmethod sload(filename)¶

Instantiate the detector description from a NeXus file, adapted from: http://download.nexusformat.org/sphinx/classes/base_classes/NXdetector.html

Parameters: filename – name of the file on the disk
Returns: Detector instance

class pyFAI.detectors.ADSC_Q315(pixel1=5.1e-05, pixel2=5.1e-05)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC Quantum 315r detector, 3x3 chips

Informations from http://www.adsc-xray.com/products/ccd-detectors/q315r-ccd-detector/

Question: how are the gaps handled ?

MAX_SHAPE = (6144, 6144)¶

__init__(pixel1=5.1e-05, pixel2=5.1e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Quantum 315']¶

force_pixel = True¶

class pyFAI.detectors.ADSC_Q210(pixel1=5.1e-05, pixel2=5.1e-05)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC Quantum 210r detector, 2x2 chips

Informations from http://www.adsc-xray.com/products/ccd-detectors/q210r-ccd-detector/

Question: how are the gaps handled ?

MAX_SHAPE = (4096, 4096)¶

__init__(pixel1=5.1e-05, pixel2=5.1e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Quantum 210']¶

force_pixel = True¶

class pyFAI.detectors.ADSC_Q270(pixel1=6.48e-05, pixel2=6.48e-05)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC Quantum 270r detector, 2x2 chips

Informations from http://www.adsc-xray.com/products/ccd-detectors/q270-ccd-detector/

Question: how are the gaps handled ?

MAX_SHAPE = (4168, 4168)¶

__init__(pixel1=6.48e-05, pixel2=6.48e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Quantum 270']¶

force_pixel = True¶

class pyFAI.detectors.ADSC_Q4(pixel1=8.2e-05, pixel2=8.2e-05)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC Quantum 4r detector, 2x2 chips

Informations from http://proteincrystallography.org/detectors/adsc.php

Question: how are the gaps handled ?

MAX_SHAPE = (2304, 2304)¶

__init__(pixel1=8.2e-05, pixel2=8.2e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Quantum 4']¶

force_pixel = True¶

class pyFAI.detectors.HF_130K(pixel1=0.00015, pixel2=0.00015)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC HF-130K 1 module

Informations from http://www.adsc-xray.com/products/pixel-array-detectors/hf-130k/

MAX_SHAPE = (256, 512)¶

__init__(pixel1=0.00015, pixel2=0.00015)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['HF-130k']¶

force_pixel = True¶

class pyFAI.detectors.HF_262k(pixel1=0.00015, pixel2=0.00015)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC HF-262k 2 module

Informations from http://www.adsc-xray.com/products/pixel-array-detectors/hf-262k/

Nota: gaps between modules is not known/described

MAX_SHAPE = (512, 512)¶

__init__(pixel1=0.00015, pixel2=0.00015)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['HF-262k']¶

force_pixel = True¶

class pyFAI.detectors.HF_1M(pixel1=0.00015, pixel2=0.00015)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC HF-1M 2x4 modules

Informations from http://www.adsc-xray.com/products/pixel-array-detectors/hf-1m/

Nota: gaps between modules is not known/described

MAX_SHAPE = (1024, 1024)¶

__init__(pixel1=0.00015, pixel2=0.00015)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['HF-1M']¶

force_pixel = True¶

class pyFAI.detectors.HF_2M(pixel1=0.00015, pixel2=0.00015)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC HF-1M 3x6 modules

Informations from http://www.adsc-xray.com/products/pixel-array-detectors/hf-2.4m/

Nota: gaps between modules is not known/described

MAX_SHAPE = (1536, 1536)¶

__init__(pixel1=0.00015, pixel2=0.00015)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['HF-2.4M']¶

force_pixel = True¶

class pyFAI.detectors.HF_4M(pixel1=0.00015, pixel2=0.00015)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC HF-4M 4x8 modules

Informations from http://www.adsc-xray.com/products/pixel-array-detectors/hf-4m/

MAX_SHAPE = (2048, 2048)¶

__init__(pixel1=0.00015, pixel2=0.00015)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['HF-4M']¶

force_pixel = True¶

class pyFAI.detectors.HF_9M(pixel1=0.00015, pixel2=0.00015)¶

Bases: pyFAI.detectors._adsc._ADSC

ADSC HF-130K 1 module

Informations from http://www.adsc-xray.com/products/pixel-array-detectors/hf-9-4m/

MAX_SHAPE = (3072, 3072)¶

__init__(pixel1=0.00015, pixel2=0.00015)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['HF-9.4M']¶

force_pixel = True¶

class pyFAI.detectors.Eiger(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._dectris._Dectris

Eiger detector: generic description containing mask algorithm

Nota: 512k modules (514*1030) are made of 2x4 submodules of 256*256 pixels. Two missing pixels are interpolated at each sub-module boundary which explains the +2 and the +6 pixels.

MODULE_GAP = (37, 10)¶

MODULE_SIZE = (514, 1030)¶

__init__(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!!

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)

Returns

p1, p2 position in meter of the center of each pixels.

Return type

2-tuple of numpy.ndarray

d1 and d2 must have the same shape, returned array will have the same shape.

calc_mask()¶: Returns a generic mask for Pilatus detectors…

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

set_config(config)¶

set the config of the detector

For Eiger detector, possible keys are: max_shape, module_size

Parameters: config – dict or JSON serialized dict
Returns: detector instance

class pyFAI.detectors.Eiger500k(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._dectris.Eiger

Eiger 1M detector

MAX_SHAPE = (514, 1030)¶

aliases = ['Eiger 500k']¶

class pyFAI.detectors.Eiger1M(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._dectris.Eiger

Eiger 1M detector

MAX_SHAPE = (1065, 1030)¶

aliases = ['Eiger 1M']¶

class pyFAI.detectors.Eiger4M(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._dectris.Eiger

Eiger 4M detector

MAX_SHAPE = (2167, 2070)¶

aliases = ['Eiger 4M']¶

class pyFAI.detectors.Eiger9M(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._dectris.Eiger

Eiger 9M detector

MAX_SHAPE = (3269, 3110)¶

aliases = ['Eiger 9M']¶

class pyFAI.detectors.Eiger16M(pixel1=7.5e-05, pixel2=7.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._dectris.Eiger

Eiger 16M detector

MAX_SHAPE = (4371, 4150)¶

aliases = ['Eiger 16M']¶

class pyFAI.detectors.Mythen(pixel1=0.008, pixel2=5e-05)¶

Bases: pyFAI.detectors._dectris._Dectris

Mythen dtrip detector from Dectris

MAX_SHAPE = (1, 1280)¶

__init__(pixel1=0.008, pixel2=5e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Mythen 1280']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.Pilatus(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris._Dectris

Pilatus detector: generic description containing mask algorithm

Sub-classed by Pilatus1M, Pilatus2M and Pilatus6M

MODULE_GAP = (17, 7)¶

MODULE_SIZE = (195, 487)¶

__init__(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!!

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)

Returns

position in meter of the center of each pixels.

Return type

ndarray

d1 and d2 must have the same shape, returned array will have the same shape.

calc_mask()¶: Returns a generic mask for Pilatus detectors…

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

get_splineFile()¶

set_config(config)¶

set the config of the detector

For Eiger detector, possible keys are: max_shape, module_size, x_offset_file, y_offset_file

Parameters: config – dict or JSON serialized dict
Returns: detector instance

set_offset_files(x_offset_file=None, y_offset_file=None)¶

set_splineFile(splineFile=None)¶: In this case splinefile is a couple filenames

property splineFile¶

class pyFAI.detectors.Pilatus100k(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 100k detector

MAX_SHAPE = (195, 487)¶

aliases = ['Pilatus 100k']¶

class pyFAI.detectors.Pilatus200k(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 200k detector

MAX_SHAPE = (407, 487)¶

aliases = ['Pilatus 200k']¶

class pyFAI.detectors.Pilatus300k(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 300k detector

MAX_SHAPE = (619, 487)¶

aliases = ['Pilatus 300k']¶

class pyFAI.detectors.Pilatus300kw(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 300k-wide detector

MAX_SHAPE = (195, 1475)¶

aliases = ['Pilatus 300kw']¶

class pyFAI.detectors.Pilatus1M(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 1M detector

MAX_SHAPE = (1043, 981)¶

aliases = ['Pilatus 1M']¶

class pyFAI.detectors.Pilatus2M(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 2M detector

MAX_SHAPE = (1679, 1475)¶

aliases = ['Pilatus 2M']¶

class pyFAI.detectors.Pilatus6M(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus 6M detector

MAX_SHAPE = (2527, 2463)¶

aliases = ['Pilatus 6M']¶

class pyFAI.detectors.PilatusCdTe(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.Pilatus

Pilatus CdTe detector: Like the Pilatus with an extra 3 pixel in the middle of every module (vertically)

calc_mask()¶: Returns a generic mask for Pilatus detectors…

class pyFAI.detectors.PilatusCdTe300k(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.PilatusCdTe

Pilatus CdTe 300k detector

MAX_SHAPE = (619, 487)¶

aliases = ['Pilatus CdTe 300k', 'Pilatus 300k CdTe', 'Pilatus300k CdTe', 'Pilatus300kCdTe']¶

class pyFAI.detectors.PilatusCdTe300kw(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.PilatusCdTe

Pilatus CdTe 300k-wide detector

MAX_SHAPE = (195, 1475)¶

aliases = ['Pilatus CdTe 300kw', 'Pilatus 300kw CdTe', 'Pilatus300kw CdTe', 'Pilatus300kwCdTe']¶

class pyFAI.detectors.PilatusCdTe900kw(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.PilatusCdTe

Pilatus CdTe 900k-wide detector

MAX_SHAPE = (195, 4439)¶

aliases = ['Pilatus CdTe 900kw', 'Pilatus 900kw CdTe', 'Pilatus900kw CdTe', 'Pilatus900kwCdTe']¶

class pyFAI.detectors.PilatusCdTe1M(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.PilatusCdTe

Pilatus CdTe 1M detector

MAX_SHAPE = (1043, 981)¶

aliases = ['Pilatus CdTe 1M', 'Pilatus 1M CdTe', 'Pilatus1M CdTe', 'Pilatus1MCdTe']¶

class pyFAI.detectors.PilatusCdTe2M(pixel1=0.000172, pixel2=0.000172, max_shape=None, module_size=None, x_offset_file=None, y_offset_file=None)¶

Bases: pyFAI.detectors._dectris.PilatusCdTe

Pilatus CdTe 2M detector

MAX_SHAPE = (1679, 1475)¶

aliases = ['Pilatus CdTe 2M', 'Pilatus 2M CdTe', 'Pilatus2M CdTe', 'Pilatus2MCdTe']¶

class pyFAI.detectors.ImXPadS10(pixel1=0.00013, pixel2=0.00013, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._common.Detector

ImXPad detector: ImXPad s10 detector with 1x1modules

BORDER_SIZE_RELATIVE = 2.5¶

MANUFACTURER = 'ImXPad'¶

MAX_SHAPE = (120, 80)¶

MODULE_SIZE = (120, 80)¶

PIXEL_SIZE = (0.00013, 0.00013)¶

__init__(pixel1=0.00013, pixel2=0.00013, max_shape=None, module_size=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Imxpad S10']¶

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!!

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)

Returns

position in meter of the center of each pixels.

Return type

ndarray

d1 and d2 must have the same shape, returned array will have the same shape.

calc_mask()¶: Calculate the mask

calc_pixels_edges()¶: Calculate the position of the pixel edges

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

get_pixel_corners(d1=None, d2=None)¶

Calculate the position of the corner of the pixels

This should be overwritten by class representing non-contiguous detector (Xpad, …)

Precision float32 is ok: precision of 1µm for a detector size of 1m

Returns: 4D array containing: pixel index (slow dimension) pixel index (fast dimension) corner index (A, B, C or D), triangles or hexagons can be handled the same way vertex position (z,y,x)

set_config(config)¶

set the config of the detector

For Xpad detector, possible keys are: max_shape, module_size

Parameters: config – dict or JSON serialized dict
Returns: detector instance

uniform_pixel = False¶

class pyFAI.detectors.ImXPadS70(pixel1=0.00013, pixel2=0.00013)¶

Bases: pyFAI.detectors._imxpad.ImXPadS10

ImXPad detector: ImXPad s70 detector with 1x7modules

BORDER_SIZE_RELATIVE = 2.5¶

MAX_SHAPE = (120, 560)¶

MODULE_SIZE = (120, 80)¶

PIXEL_EDGES = None¶

PIXEL_SIZE = (0.00013, 0.00013)¶

__init__(pixel1=0.00013, pixel2=0.00013)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Imxpad S70']¶

force_pixel = True¶

class pyFAI.detectors.ImXPadS70V(pixel1=0.00013, pixel2=0.00013)¶

Bases: pyFAI.detectors._imxpad.ImXPadS10

ImXPad detector: ImXPad s70 detector with 1x7modules

BORDER_SIZE_RELATIVE = 2.5¶

MAX_SHAPE = (560, 120)¶

MODULE_SIZE = (80, 120)¶

PIXEL_EDGES = None¶

PIXEL_SIZE = (0.00013, 0.00013)¶

__init__(pixel1=0.00013, pixel2=0.00013)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Imxpad S70 V']¶

force_pixel = True¶

class pyFAI.detectors.ImXPadS140(pixel1=0.00013, pixel2=0.00013)¶

Bases: pyFAI.detectors._imxpad.ImXPadS10

ImXPad detector: ImXPad s140 detector with 2x7modules

BORDER_PIXEL_SIZE_RELATIVE = 2.5¶

MAX_SHAPE = (240, 560)¶

MODULE_SIZE = (120, 80)¶

PIXEL_SIZE = (0.00013, 0.00013)¶

__init__(pixel1=0.00013, pixel2=0.00013)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Imxpad S140']¶

force_pixel = True¶

class pyFAI.detectors.Xpad_flat(pixel1=0.00013, pixel2=0.00013, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._imxpad.ImXPadS10

Xpad detector: generic description for ImXPad detector with 8x7modules

BORDER_PIXEL_SIZE_RELATIVE = 2.5¶

IS_CONTIGUOUS = False¶

MAX_SHAPE = (960, 560)¶

MODULE_GAP = (0.00357, 0)¶

MODULE_SIZE = (120, 80)¶

PIXEL_SIZE = (0.00013, 0.00013)¶

__init__(pixel1=0.00013, pixel2=0.00013, max_shape=None, module_size=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Xpad S540 flat', 'd5']¶

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!! Adapted to Nexus detector definition

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)
center – retrieve the coordinate of the center of the pixel
use_cython – set to False to test Numpy implementation

Returns

position in meter of the center of each pixels.

Return type

ndarray

d1 and d2 must have the same shape, returned array will have the same shape.

calc_mask()¶: Returns a generic mask for Xpad detectors… discards the first line and raw form all modules: those are 2.5x bigger and often mis - behaving

calc_pixels_edges()¶: Calculate the position of the pixel edges, specific to the S540, d5 detector

force_pixel = True¶

get_pixel_corners()¶

Calculate the position of the corner of the pixels

Returns: 4D array containing: pixel index (slow dimension) pixel index (fast dimension) corner index (A, B, C or D), triangles or hexagons can be handled the same way vertex position (z,y,x)

uniform_pixel = False¶

class pyFAI.detectors.Cirpad(pixel1=0.00013, pixel2=0.00013)¶

Bases: pyFAI.detectors._imxpad.ImXPadS10

DIFFERENT_PIXEL_SIZE = 2.5¶

IS_CONTIGUOUS = False¶

IS_FLAT = False¶

MAX_SHAPE = (11200, 120)¶

MEDIUM_MODULE_SIZE = (560, 120)¶

MODULE_SIZE = (80, 120)¶

PIXEL_SIZE = (0.00013, 0.00013)¶

ROT = [0, 0, -6.74]¶

__init__(pixel1=0.00013, pixel2=0.00013)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['CirPAD', 'XCirpad']¶

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!!

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)

Returns

position in meter of the center of each pixels.

Return type

ndarray

d1 and d2 must have the same shape, returned array will have the same shape.

force_pixel = True¶

get_pixel_corners()¶

Calculate the position of the corner of the pixels

This should be overwritten by class representing non-contiguous detector (Xpad, …)

Precision float32 is ok: precision of 1µm for a detector size of 1m

Returns: 4D array containing: pixel index (slow dimension) pixel index (fast dimension) corner index (A, B, C or D), triangles or hexagons can be handled the same way vertex position (z,y,x)

uniform_pixel = False¶

class pyFAI.detectors.Rayonix133(pixel1=6.4e-05, pixel2=6.4e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix 133 2D CCD detector detector also known as mar133

Personnal communication from M. Blum

What should be the default binning factor for those cameras ?

Circular detector

BINNED_PIXEL_SIZE = {1: 3.2e-05, 2: 6.4e-05, 4: 0.000128, 8: 0.000256}¶

MANUFACTURER = ['Rayonix', 'Mar Research']¶

MAX_SHAPE = (4096, 4096)¶

__init__(pixel1=6.4e-05, pixel2=6.4e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix133', 'MAR 133', 'MAR133']¶

calc_mask()¶: Circular mask

force_pixel = True¶

class pyFAI.detectors.RayonixSx165(pixel1=3.95e-05, pixel2=3.95e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix sx165 2d Detector also known as MAR165.

Circular detector

BINNED_PIXEL_SIZE = {1: 3.95e-05, 2: 7.9e-05, 3: 0.000118616, 4: 0.000158, 8: 0.000316}¶

MANUFACTURER = ['Rayonix', 'Mar Research']¶

MAX_SHAPE = (4096, 4096)¶

__init__(pixel1=3.95e-05, pixel2=3.95e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix SX165', 'MAR 165', 'MAR165']¶

calc_mask()¶: Circular mask

force_pixel = True¶

class pyFAI.detectors.RayonixSx200(pixel1=4.8e-05, pixel2=4.8e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix sx200 2d CCD Detector.

Pixel size are personnal communication from M. Blum.

BINNED_PIXEL_SIZE = {1: 4.8e-05, 2: 9.6e-05, 3: 0.000144, 4: 0.000192, 8: 0.000384}¶

MAX_SHAPE = (4096, 4096)¶

__init__(pixel1=4.8e-05, pixel2=4.8e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix SX200']¶

class pyFAI.detectors.RayonixLx170(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix lx170 2d CCD Detector (2x1 CCDs).

Nota: this is the same for lx170hs

BINNED_PIXEL_SIZE = {1: 4.42708e-05, 2: 8.85417e-05, 3: 0.0001328125, 4: 0.0001770833, 5: 0.0002213542, 6: 0.000265625, 8: 0.0003541667, 10: 0.0004427083}¶

MAX_SHAPE = (1920, 3840)¶

__init__(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix LX170', 'Rayonix LX170-HS', 'Rayonix LX170 HS', 'RayonixLX170HS']¶

force_pixel = True¶

class pyFAI.detectors.RayonixMx170(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx170 2d CCD Detector (2x2 CCDs).

Nota: this is the same for mx170hs

BINNED_PIXEL_SIZE = {1: 4.42708e-05, 2: 8.85417e-05, 3: 0.0001328125, 4: 0.0001770833, 5: 0.0002213542, 6: 0.000265625, 8: 0.0003541667, 10: 0.0004427083}¶

MAX_SHAPE = (3840, 3840)¶

__init__(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX170', 'Rayonix MX170-HS', 'RayonixMX170HS', 'Rayonix MX170 HS']¶

class pyFAI.detectors.RayonixLx255(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix lx255 2d Detector (3x1 CCDs)

Nota: this detector is also called lx255hs

BINNED_PIXEL_SIZE = {1: 4.42708e-05, 2: 8.85417e-05, 3: 0.0001328125, 4: 0.0001770833, 5: 0.0002213542, 6: 0.000265625, 8: 0.0003541667, 10: 0.0004427083}¶

MAX_SHAPE = (1920, 5760)¶

__init__(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix LX255', 'Rayonix LX255-HS', 'Rayonix LX 255HS', 'RayonixLX225HS']¶

class pyFAI.detectors.RayonixMx225(pixel1=7.3242e-05, pixel2=7.3242e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx225 2D CCD detector detector

Nota: this is the same definition for mx225he Personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 3.6621e-05, 2: 7.3242e-05, 3: 0.000109971, 4: 0.000146484, 8: 0.000292969}¶

MANUFACTURER = ['Rayonix', 'Mar Research']¶

MAX_SHAPE = (6144, 6144)¶

__init__(pixel1=7.3242e-05, pixel2=7.3242e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX225', 'MAR 225', 'MAR225']¶

force_pixel = True¶

class pyFAI.detectors.RayonixMx225hs(pixel1=7.8125e-05, pixel2=7.8125e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx225hs 2D CCD detector detector

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 3.90625e-05, 2: 7.8125e-05, 3: 0.0001171875, 4: 0.00015625, 5: 0.0001953125, 6: 0.000234375, 8: 0.0003125, 10: 0.000390625}¶

MAX_SHAPE = (5760, 5760)¶

__init__(pixel1=7.8125e-05, pixel2=7.8125e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX225HS', 'Rayonix MX225 HS']¶

force_pixel = True¶

class pyFAI.detectors.RayonixMx300(pixel1=7.3242e-05, pixel2=7.3242e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx300 2D detector (4x4 CCDs)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 3.6621e-05, 2: 7.3242e-05, 3: 0.000109971, 4: 0.000146484, 8: 0.000292969}¶

MANUFACTURER = ['Rayonix', 'Mar Research']¶

MAX_SHAPE = (8192, 8192)¶

__init__(pixel1=7.3242e-05, pixel2=7.3242e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX300', 'MAR 300', 'MAR300']¶

force_pixel = True¶

class pyFAI.detectors.RayonixMx300hs(pixel1=7.8125e-05, pixel2=7.8125e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx300hs 2D detector (4x4 CCDs)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 3.90625e-05, 2: 7.8125e-05, 3: 0.0001171875, 4: 0.00015625, 5: 0.0001953125, 6: 0.000234375, 8: 0.0003125, 10: 0.000390625}¶

MAX_SHAPE = (7680, 7680)¶

__init__(pixel1=7.8125e-05, pixel2=7.8125e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX300HS', 'Rayonix MX300 HS']¶

force_pixel = True¶

class pyFAI.detectors.RayonixMx340hs(pixel1=8.85417e-05, pixel2=8.85417e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx340hs 2D detector (4x4 CCDs)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 4.42708e-05, 2: 8.85417e-05, 3: 0.0001328125, 4: 0.0001770833, 5: 0.0002213542, 6: 0.000265625, 8: 0.0003541667, 10: 0.0004427083}¶

MAX_SHAPE = (7680, 7680)¶

__init__(pixel1=8.85417e-05, pixel2=8.85417e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX340HS', 'Rayonix MX340HS']¶

force_pixel = True¶

class pyFAI.detectors.RayonixSx30hs(pixel1=1.5625e-05, pixel2=1.5625e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix sx30hs 2D CCD camera (1 CCD chip)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 1.5625e-05, 2: 3.125e-05, 3: 4.6875e-05, 4: 6.25e-05, 5: 7.8125e-05, 6: 9.375e-05, 8: 0.000125, 10: 0.00015625}¶

MAX_SHAPE = (1920, 1920)¶

__init__(pixel1=1.5625e-05, pixel2=1.5625e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix SX30HS', 'Rayonix SX30 HS']¶

class pyFAI.detectors.RayonixSx85hs(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix sx85hs 2D CCD camera (1 CCD chip)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 4.42708e-05, 2: 8.85417e-05, 3: 0.0001328125, 4: 0.0001770833, 5: 0.0002213542, 6: 0.000265625, 8: 0.0003541667, 10: 0.0004427083}¶

MAX_SHAPE = (1920, 1920)¶

__init__(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix SX85HS', 'Rayonix SX85 HS']¶

class pyFAI.detectors.RayonixMx425hs(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx425hs 2D CCD camera (5x5 CCD chip)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 4.42708e-05, 2: 8.85417e-05, 3: 0.0001328125, 4: 0.0001770833, 5: 0.0002213542, 6: 0.000265625, 8: 0.0003541667, 10: 0.0004427083}¶

MAX_SHAPE = (9600, 9600)¶

__init__(pixel1=4.42708e-05, pixel2=4.42708e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX425HS', 'Rayonix MX425 HS']¶

class pyFAI.detectors.RayonixMx325(pixel1=7.9346e-05, pixel2=7.9346e-05)¶

Bases: pyFAI.detectors._rayonix._Rayonix

Rayonix mx325 and mx325he 2D detector (4x4 CCD chips)

Pixel size from a personnal communication from M. Blum

BINNED_PIXEL_SIZE = {1: 3.9673e-05, 2: 7.9346e-05, 3: 0.000119135, 4: 0.000158691, 8: 0.000317383}¶

MAX_SHAPE = (8192, 8192)¶

__init__(pixel1=7.9346e-05, pixel2=7.9346e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Rayonix MX325']¶

class pyFAI.detectors.Mar345(pixel1=0.0001, pixel2=0.0001)¶

Bases: pyFAI.detectors._common.Detector

Mar345 Imaging plate detector

In this detector, pixels are always square The valid image size are 2300, 2000, 1600, 1200, 3450, 3000, 2400, 1800

MANUFACTURER = 'Mar Research'¶

MAX_SHAPE = (3450, 3450)¶

VALID_SIZE = {1200: 0.00015, 1600: 0.00015, 1800: 0.0001, 2000: 0.00015, 2300: 0.00015, 2400: 0.0001, 3000: 0.0001, 3450: 0.0001}¶

__init__(pixel1=0.0001, pixel2=0.0001)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['MAR 345', 'Mar3450']¶

calc_mask()¶

Method calculating the mask for a given detector

Detectors with gaps should overwrite this method with something actually calculating the mask!

Returns: the mask with valid pixel to 0
Return type: numpy ndarray of int8 or None

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

guess_binning(data)¶: Guess the binning/mode depending on the image shape :param data: 2-tuple with the shape of the image or the image with a .shape attribute. :return: True if the data fit the detector :rtype: bool

set_config(config)¶

set the config of the detector

For Eiger detector, possible keys are: max_shape, module_size

Parameters: config – dict or JSON serialized dict
Returns: detector instance

class pyFAI.detectors.Mar555(pixel1=0.000139, pixel2=0.000139)¶

Bases: pyFAI.detectors._common.Detector

Mar555 is a Selenium flat panel detector.

The detector specifications are adapted from http://xds.mpimf-heidelberg.mpg.de/html_doc/detectors.html

MANUFACTURER = 'Mar Research'¶

MAX_SHAPE = (3072, 2560)¶

__init__(pixel1=0.000139, pixel2=0.000139)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['MAR 555']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

set_config(config)¶

set the config of the detector

For Eiger detector, possible keys are: max_shape, module_size

Parameters: config – dict or JSON serialized dict
Returns: detector instance

class pyFAI.detectors.FReLoN(splineFile=None)¶

Bases: pyFAI.detectors._common.Detector

FReLoN detector: The spline is mandatory to correct for geometric distortion of the taper

TODO: create automatically a mask that removes pixels out of the “valid reagion”

HAVE_TAPER = True¶

MANUFACTURER = 'ESRF'¶

MAX_SHAPE = (2048, 2048)¶

__init__(splineFile=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

calc_mask()¶: Returns a generic mask for Frelon detectors… All pixels which (center) turns to be out of the valid region are by default discarded

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.Maxipix(pixel1=5.5e-05, pixel2=5.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._common.Detector

ESRF Maxipix detector: generic description containing mask algorithm

Sub-classed by Maxipix2x2 and Maxipix5x1

MANUFACTURER = 'ESRF'¶

MAX_SHAPE = (256, 256)¶

MODULE_GAP = (4, 4)¶

MODULE_SIZE = (256, 256)¶

__init__(pixel1=5.5e-05, pixel2=5.5e-05, max_shape=None, module_size=None)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Maxipix 1x1', 'Maxipix1x1']¶

calc_mask()¶: Returns a generic mask for Mexipix detectors…

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

set_config(config)¶

set the config of the detector

For Eiger detector, possible keys are: max_shape, module_size

Parameters: config – dict or JSON serialized dict
Returns: detector instance

class pyFAI.detectors.Maxipix2x2(pixel1=5.5e-05, pixel2=5.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._esrf.Maxipix

Maxipix 2x2 detector

MAX_SHAPE = (516, 516)¶

aliases = ['Maxipix 2x2']¶

class pyFAI.detectors.Maxipix5x1(pixel1=5.5e-05, pixel2=5.5e-05, max_shape=None, module_size=None)¶

Bases: pyFAI.detectors._esrf.Maxipix

Maxipix 5x1 detector

MAX_SHAPE = (256, 1296)¶

aliases = ['Maxipix 5x1']¶

class pyFAI.detectors.Fairchild(pixel1=1.5e-05, pixel2=1.5e-05)¶

Bases: pyFAI.detectors._common.Detector

Fairchild Condor 486:90 detector

MANUFACTURER = 'Fairchild Semiconductor'¶

MAX_SHAPE = (4096, 4096)¶

__init__(pixel1=1.5e-05, pixel2=1.5e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Fairchild', 'Condor', 'Fairchild Condor 486:90']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

uniform_pixel = True¶

class pyFAI.detectors.Titan(pixel1=6e-05, pixel2=6e-05)¶

Bases: pyFAI.detectors._common.Detector

Titan CCD detector from Agilent. Mask not handled

MANUFACTURER = ['Agilent', 'Oxford Diffraction']¶

MAX_SHAPE = (2048, 2048)¶

__init__(pixel1=6e-05, pixel2=6e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Titan 2k x 2k', 'Titan 2k x 2k', 'OXD Titan', 'Agilent Titan']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

uniform_pixel = True¶

class pyFAI.detectors.Dexela2923(pixel1=7.5e-05, pixel2=7.5e-05)¶

Bases: pyFAI.detectors._common.Detector

Dexela CMOS family detector

MAX_SHAPE = (3888, 3072)¶

__init__(pixel1=7.5e-05, pixel2=7.5e-05)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Dexela 2923']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.Basler(pixel=3.75e-06)¶

Bases: pyFAI.detectors._common.Detector

Basler camera are simple CCD camara over GigaE

MANUFACTURER = 'Basler'¶

MAX_SHAPE = (966, 1296)¶

__init__(pixel=3.75e-06)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['aca1300']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

set_config(config)¶

Sets the configuration of the detector.

The configuration is either a python dictionary or a JSON string or a file containing this JSON configuration

keys in that dictionary are: pixel

Parameters: config – string or JSON-serialized dict
Returns: self

class pyFAI.detectors.Perkin(pixel1=0.0002, pixel2=0.0002)¶

Bases: pyFAI.detectors._common.Detector

Perkin detector

DEFAULT_PIXEL1 = 0.0002¶

DEFAULT_PIXEL2 = 0.0002¶

MANUFACTURER = 'Perkin Elmer'¶

MAX_SHAPE = (4096, 4096)¶

__init__(pixel1=0.0002, pixel2=0.0002)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Perkin detector', 'Perkin Elmer']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.Aarhus(pixel1=2.4893e-05, pixel2=2.4893e-05, radius=0.29989)¶

Bases: pyFAI.detectors._common.Detector

Cylindrical detector made of a bent imaging-plate. Developped at the Danish university of Aarhus r = 1.2m or 0.3m

Credits: Private communication; B. B. Iversen, Center for Materials Crystallography & Dept. of Chemistry and iNANO, Aarhus University

The image has to be laid-out horizontally

Nota: the detector is bend towards the sample, hence reducing the sample-detector distance. This is why z<0 (or p3<0)

TODO: update cython code for 3d detectors use expand2d instead of outer product with ones

IS_FLAT = False¶

MANUFACTURER = 'Aarhus University'¶

MAX_SHAPE = (1000, 16000)¶

__init__(pixel1=2.4893e-05, pixel2=2.4893e-05, radius=0.29989)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

calc_cartesian_positions(d1=None, d2=None, center=True, use_cython=True)¶

Calculate the position of each pixel center in cartesian coordinate and in meter of a couple of coordinates. The half pixel offset is taken into account here !!! Adapted to Nexus detector definition

Parameters

d1 (ndarray (1D or 2D)) – the Y pixel positions (slow dimension)
d2 (ndarray (1D or 2D)) – the X pixel positions (fast dimension)
center – retrieve the coordinate of the center of the pixel
use_cython – set to False to test Python implementeation

Returns

position in meter of the center of each pixels.

Return type

ndarray

d1 and d2 must have the same shape, returned array will have the same shape.

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

get_pixel_corners(use_cython=True)¶

Calculate the position of the corner of the pixels

This should be overwritten by class representing non-contiguous detector (Xpad, …)

Returns: 4D array containing: pixel index (slow dimension) pixel index (fast dimension) corner index (A, B, C or D), triangles or hexagons can be handled the same way vertex position (z,y,x)

set_config(config)¶

Sets the configuration of the detector.

The configuration is either a python dictionary or a JSON string or a file containing this JSON configuration

keys in that dictionary are: pixel1, pixel2, radius

Parameters: config – string or JSON-serialized dict
Returns: self

class pyFAI.detectors.Pixium(pixel1=0.000308, pixel2=0.000308)¶

Bases: pyFAI.detectors._common.Detector

PIXIUM 4700 detector

High energy X ray diffraction using the Pixium 4700 flat panel detector J E Daniels, M Drakopoulos, et al.; Journal of Synchrotron Radiation 16(Pt 4):463-8 · August 2009

DEFAULT_PIXEL1 = 0.000154¶

DEFAULT_PIXEL2 = 0.000154¶

MANUFACTURER = 'Thales Electronics'¶

MAX_SHAPE = (1910, 2480)¶

__init__(pixel1=0.000308, pixel2=0.000308)¶: Defaults to 2x2 binning

aliases = ['Pixium 4700', 'Pixium 4700 detector', 'Thales Electronics']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.Apex2(pixel1=0.00012, pixel2=0.00012)¶

Bases: pyFAI.detectors._common.Detector

BrukerApex2 detector

Actually a derivative from the Fairchild detector with higher binning

DEFAULT_PIXEL1 = 6e-05¶

DEFAULT_PIXEL2 = 6e-05¶

MANUFACTURER = 'Bruker'¶

MAX_SHAPE = (1024, 1024)¶

__init__(pixel1=0.00012, pixel2=0.00012)¶: Defaults to 2x2 binning

aliases = ['ApexII', 'Bruker']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.RaspberryPi5M(pixel1=1.4e-06, pixel2=1.4e-06)¶

Bases: pyFAI.detectors._common.Detector

5 Mpix detector from Raspberry Pi

MAX_SHAPE = (1944, 2592)¶

__init__(pixel1=1.4e-06, pixel2=1.4e-06)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Picam v1']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

class pyFAI.detectors.RaspberryPi8M(pixel1=1.12e-06, pixel2=1.12e-06)¶

Bases: pyFAI.detectors._common.Detector

8 Mpix detector from Raspberry Pi

MAX_SHAPE = (2464, 3280)¶

__init__(pixel1=1.12e-06, pixel2=1.12e-06)¶

Parameters

pixel1 (float) – size of the pixel in meter along the slow dimension (often Y)
pixel2 (float) – size of the pixel in meter along the fast dimension (often X)
splineFile (str) – path to file containing the geometric correction.
max_shape (2-tuple of integrers) – maximum size of the detector

aliases = ['Picam v2']¶

force_pixel = True¶

get_config()¶

Return the configuration with arguments to the constructor

Returns: dict with param for serialization

pyFAI.detectors.detector_factory(name, config=None)¶

A kind of factory…

Parameters

name (str) – name of a detector
config (dict or JSON representation of it.) – configuration of the detector

Returns

an instance of the right detector, set-up if possible

Return type

pyFAI.detectors.Detector

pyFAI.detectors.load(filename)¶

Instantiate the detector description from a NeXus file, adapted from: http://download.nexusformat.org/sphinx/classes/base_classes/NXdetector.html

Parameters: filename – name of the file on the disk
Returns: Detector instance

pyFAI.detectors package¶

Module contents¶

Table of Contents

Previous topic

Next topic

This Page