astrodata package

This package add another abstraction layer to astronomical data by parsing the information contained in the headers as attributes. To do so, one must subclass astrodata.AstroData and add parse methods accordingly to the TagSet received.

class astrodata.AstroData(nddata=None, tables=None, phu=None, indices=None)[source]

Bases: object

Base class for the AstroData software package. It provides an interface to manipulate astronomical data sets.

Parameters
add(oper)

Performs inplace addition by evaluating self += operand.

Parameters

oper (number or object) – The operand to perform the operation self += operand.

Returns

Return type

AstroData instance

append(ext, name=None, header=None)[source]

Adds a new top-level extension.

Parameters
  • ext (array, astropy.nddata.NDData, astropy.table.Table, other) – The contents for the new extension. The exact accepted types depend on the class implementing this interface. Implementations specific to certain data formats may accept specialized types (eg. a FITS provider will accept an astropy.io.fits.ImageHDU and extract the array out of it).

  • name (str, optional) – A name that may be used to access the new object, as an attribute of the provider. The name is typically ignored for top-level (global) objects, and required for the others. If the name cannot be derived from the metadata associated to ext, you will have to provider one. It can consist in a combination of numbers and letters, with the restriction that the letters have to be all capital, and the first character cannot be a number (“[A-Z][A-Z0-9]*”).

Returns

  • The same object, or a new one, if it was necessary to convert it to

  • a more suitable format for internal use.

Raises
  • TypeError – If adding the object in an invalid situation (eg. name is None when adding to a single slice).

  • ValueError – Raised if the extension is of a proper type, but its value is illegal somehow.

crop(x1, y1, x2, y2)[source]

Crop the NDData objects given indices.

Parameters
  • x1 (int) – Minimum and maximum indices for the x and y axis.

  • y1 (int) – Minimum and maximum indices for the x and y axis.

  • x2 (int) – Minimum and maximum indices for the x and y axis.

  • y2 (int) – Minimum and maximum indices for the x and y axis.

property data

A list of the arrays (or single array, if this is a single slice) corresponding to the science data attached to each extension.

property descriptors

Returns a sequence of names for the methods that have been decorated as descriptors.

Returns

Return type

tuple of str

divide(oper)

Performs inplace division by evaluating self /= operand.

Parameters

oper (number or object) – The operand to perform the operation self /= operand.

Returns

Return type

AstroData instance

property exposed

A collection of strings with the names of objects that can be accessed directly by name as attributes of this instance, and that are not part of its standard interface (i.e. data objects that have been added dynamically).

Examples

>>> ad[0].exposed  
set(['OBJMASK', 'OBJCAT'])
property filename

Return the file name.

property hdr

Return all headers, as a astrodata.fits.FitsHeaderCollection.

property header
property id

Returns the extension identifier (1-based extension number) for sliced objects.

property indices

Returns the extensions indices for sliced objects.

info()[source]

Prints out information about the contents of this instance.

instrument()[source]

Returns the name of the instrument making the observation.

is_settable(attr)[source]

Return True if the attribute is meant to be modified.

property is_single

If this data provider represents a single slice out of a whole dataset, return True. Otherwise, return False.

property is_sliced

If this data provider instance represents the whole dataset, return False. If it represents a slice out of the whole, return True.

classmethod load(source, extname_parser=None)

Read from a file, file object, HDUList, etc.

property mask

A list of the mask arrays (or a single array, if this is a single slice) attached to the science data, for each extension.

For objects that miss a mask, None will be provided instead.

multiply(oper)

Performs inplace multiplication by evaluating self *= operand.

Parameters

oper (number or object) – The operand to perform the operation self *= operand.

Returns

Return type

AstroData instance

property nddata

Return the list of astrodata.NDAstroData objects.

If the AstroData object is sliced, this returns only the NDData objects of the sliced extensions. And if this is a single extension object, the NDData object is returned directly (i.e. not a list).

object()[source]

Returns the name of the object being observed.

operate(operator, *args, **kwargs)[source]

Applies a function to the main data array on each extension, replacing the data with the result. The data will be passed as the first argument to the function.

It will be applied to the mask and variance of each extension, too, if they exist.

This is a convenience method, which is equivalent to:

for ext in ad:
    ext.data = operator(ext.data, *args, **kwargs)
    if ext.mask is not None:
        ext.mask = operator(ext.mask, *args, **kwargs)
    if ext.variance is not None:
        ext.variance = operator(ext.variance, *args, **kwargs)

with the additional advantage that it will work on single slices, too.

Parameters
  • operator (callable) – A function that takes an array (and, maybe, other arguments) and returns an array.

  • args (optional) – Additional arguments to be passed to the operator.

  • kwargs (optional) – Additional arguments to be passed to the operator.

Examples

>>> import numpy as np
>>> ad.operate(np.squeeze)  
property orig_filename

Return the original file name (before it was modified).

property path

Return the file path.

property phu

Return the primary header.

classmethod read(source, extname_parser=None)[source]

Read from a file, file object, HDUList, etc.

reset(data, mask=<object object>, variance=<object object>, check=True)[source]

Sets the .data, and optionally .mask and .variance attributes of a single-extension AstroData slice. This function will optionally check whether these attributes have the same shape.

Parameters
  • data (ndarray) – The array to assign to the .data attribute (“SCI”).

  • mask (ndarray, optional) – The array to assign to the .mask attribute (“DQ”).

  • variance (ndarray, optional) – The array to assign to the .variance attribute (“VAR”).

  • check (bool) – If set, then the function will check that the mask and variance arrays have the same shape as the data array.

Raises
  • TypeError – if an attempt is made to set the .mask or .variance attributes with something other than an array

  • ValueError – if the .mask or .variance attributes don’t have the same shape as .data, OR if this is called on an AD instance that isn’t a single extension slice

property shape
subtract(oper)

Performs inplace subtraction by evaluating self -= operand.

Parameters

oper (number or object) – The operand to perform the operation self -= operand.

Returns

Return type

AstroData instance

table()[source]
property tables

Return the names of the astropy.table.Table objects associated to the object or its extensions.

property tags

A set of strings that represent the tags defining this instance.

telescope()[source]

Returns the name of the telescope.

property uncertainty

A list of the uncertainty objects (or a single object, if this is a single slice) attached to the science data, for each extension.

The objects are instances of AstroPy’s astropy.nddata.NDUncertainty, or None where no information is available.

See also

variance

The actual array supporting the uncertainty object.

update_filename(prefix=None, suffix=None, strip=False)[source]

Update the “filename” attribute of the AstroData object.

A prefix and/or suffix can be specified. If strip=True, these will replace the existing prefix/suffix; if strip=False, they will simply be prepended/appended.

The current filename is broken down into its existing prefix, root, and suffix using the ORIGNAME phu keyword, if it exists and is contained within the current filename. Otherwise, the filename is split at the last underscore and the part before is assigned as the root and the underscore and part after the suffix. No prefix is assigned.

Note that, if strip=True, a prefix or suffix will only be stripped if ‘’ is specified.

Parameters
  • prefix (str, optional) – New prefix (None => leave alone)

  • suffix (str, optional) – New suffix (None => leave alone)

  • strip (bool, optional) – Strip existing prefixes and suffixes if new ones are given?

property variance

A list of the variance arrays (or a single array, if this is a single slice) attached to the science data, for each extension.

For objects that miss uncertainty information, None will be provided instead.

See also

uncertainty

The uncertainty objects used under the hood.

property wcs

Returns the list of WCS objects for each extension.

write(filename=None, overwrite=False)[source]

Write the object to disk.

Parameters
  • filename (str, optional) – If the filename is not given, self.path is used.

  • overwrite (bool) – If True, overwrites existing file.

exception astrodata.AstroDataError[source]

Bases: Exception

class astrodata.NDAstroData(data, uncertainty=None, mask=None, wcs=None, meta=None, unit=None, copy=False, window=None, variance=None)[source]

Bases: astropy.nddata.mixins.ndarithmetic.NDArithmeticMixin, astropy.nddata.mixins.ndslicing.NDSlicingMixin, astropy.nddata.nddata.NDData

Implements NDData with all Mixins, plus some AstroData specifics.

This class implements an NDData-like container that supports reading and writing as implemented in the astropy.io.registry and also slicing (indexing) and simple arithmetics (add, subtract, divide and multiply).

A very important difference between NDAstroData and NDData is that the former attempts to load all its data lazily. There are also some important differences in the interface (eg. .data lets you reset its contents after initialization).

Documentation is provided where our class differs.

See also

NDData, NDArithmeticMixin, NDSlicingMixin

Examples

The mixins allow operation that are not possible with NDData or NDDataBase, i.e. simple arithmetics:

>>> from astropy.nddata import StdDevUncertainty
>>> import numpy as np
>>> data = np.ones((3,3), dtype=np.float)
>>> ndd1 = NDAstroData(data, uncertainty=StdDevUncertainty(data))
>>> ndd2 = NDAstroData(data, uncertainty=StdDevUncertainty(data))
>>> ndd3 = ndd1.add(ndd2)
>>> ndd3.data
array([[2., 2., 2.],
    [2., 2., 2.],
    [2., 2., 2.]])
>>> ndd3.uncertainty.array
array([[1.41421356, 1.41421356, 1.41421356],
    [1.41421356, 1.41421356, 1.41421356],
    [1.41421356, 1.41421356, 1.41421356]])

see NDArithmeticMixin for a complete list of all supported arithmetic operations.

But also slicing (indexing) is possible:

>>> ndd4 = ndd3[1,:]
>>> ndd4.data
array([2., 2., 2.])
>>> ndd4.uncertainty.array
array([1.41421356, 1.41421356, 1.41421356])

See NDSlicingMixin for a description how slicing works (which attributes) are sliced.

property T
property data

An array representing the raw data stored in this instance. It implements a setter.

property mask

Mask for the dataset, if any.

Masks should follow the numpy convention that valid data points are marked by False and invalid ones with True.

Type

any type

set_section(section, input)[source]

Sets only a section of the data. This method is meant to prevent fragmentation in the Python heap, by reusing the internal structures instead of replacing them with new ones.

Parameters
  • section (slice) – The area that will be replaced

  • input (NDData-like instance) – This object needs to implement at least data, uncertainty, and mask. Their entire contents will replace the data in the area defined by section.

Examples

>>> sec = NDData(np.zeros((100,100)))  
>>> ad[0].nddata.set_section((slice(None,100),slice(None,100)), sec)  
property shape
transpose()[source]
property uncertainty

Uncertainty in the dataset, if any.

Should have an attribute uncertainty_type that defines what kind of uncertainty is stored, such as 'std' for standard deviation or 'var' for variance. A metaclass defining such an interface is NDUncertainty but isn’t mandatory.

Type

any type

property variance

A convenience property to access the contents of uncertainty, squared (as the uncertainty data is stored as standard deviation).

property wcs

A world coordinate system (WCS) for the dataset, if any.

Type

any type

property window

Interface to access a section of the data, using lazy access whenever possible.

Returns

  • An instance of NDWindowing, which provides __getitem__,

  • to allow the use of square brackets when specifying the window.

  • Ultimately, an NDWindowingAstrodata instance is returned.

Examples

>>> ad[0].nddata.window[100:200, 100:200]  
<NDWindowingAstrodata .....>
class astrodata.TagSet(add=None, remove=None, blocked_by=None, blocks=None, if_present=None)[source]

Bases: astrodata.utils.TagSet

Named tuple that is used by tag methods to return which actions should be performed on a tag set. All the attributes are optional, and any combination of them can be used, allowing to create complex tag structures. Read the documentation on the tag-generating algorithm if you want to better understand the interactions.

The simplest TagSet, though, tends to just add tags to the global set.

It can be initialized by position, like any other tuple (the order of the arguments is the one in which the attributes are listed below). It can also be initialized by name.

add

Tags to be added to the global set

Type

set of str, optional

remove

Tags to be removed from the global set

Type

set of str, optional

blocked_by

Tags that will prevent this TagSet from being applied

Type

set of str, optional

blocks

Other TagSets containing these won’t be applied

Type

set of str, optional

if_present

This TagSet will be applied only all of these tags are present

Type

set of str, optional

Examples

>>> TagSet()
TagSet(add=set(), remove=set(), blocked_by=set(), blocks=set(), if_present=set())
>>> TagSet({'BIAS', 'CAL'})
TagSet(add={'BIAS', 'CAL'}, remove=set(), blocked_by=set(), blocks=set(), if_present=set())
>>> TagSet(remove={'BIAS', 'CAL'})
TagSet(add=set(), remove={'BIAS', 'CAL'}, blocked_by=set(), blocks=set(), if_present=set())
astrodata.add_header_to_table(table)[source]
astrodata.astro_data_descriptor(fn)[source]

Decorator that will mark a class method as an AstroData descriptor. Useful to produce list of descriptors, for example.

If used in combination with other decorators, this one must be the one on the top (ie. the last one applying). It doesn’t modify the method in any other way.

Parameters

fn (method) – The method to be decorated

Returns

Return type

The tagged method (not a wrapper)

astrodata.astro_data_tag(fn)[source]

Decorator that marks methods of an AstroData derived class as part of the tag-producing system.

It wraps the method around a function that will ensure a consistent return value: the wrapped method can return any sequence of sequences of strings, and they will be converted to a TagSet. If the wrapped method returns None, it will be turned into an empty TagSet.

Parameters

fn (method) – The method to be decorated

Returns

Return type

A wrapper function

astrodata.create(phu, extensions=None)

Creates an AstroData object from a collection of objects.

Parameters
  • phu (fits.PrimaryHDU or fits.Header or dict or list) – FITS primary HDU or header, or something that can be used to create a fits.Header (a dict, a list of “cards”).

  • extensions (list of HDUs) – List of HDU objects.

astrodata.open(source)

Takes either a string (with the path to a file) or an HDUList as input, and tries to return an AstroData instance.

It will raise exceptions if the file is not found, or if there is no match for the HDUList, among the registered AstroData classes.

Returns an instantiated object, or raises AstroDataError if it was not possible to find a match

Parameters

source (str or pathlib.Path or fits.HDUList) – The file path or HDUList to read.

astrodata.version(short=False, tag='dev')[source]

Returns DRAGONS’s version based on the api, feature and bug numbers.

Returns

str

Return type

formatted version

Submodules

astrodata.core module

class astrodata.core.AstroData(nddata=None, tables=None, phu=None, indices=None)[source]

Bases: object

Base class for the AstroData software package. It provides an interface to manipulate astronomical data sets.

Parameters
add(oper)

Performs inplace addition by evaluating self += operand.

Parameters

oper (number or object) – The operand to perform the operation self += operand.

Returns

Return type

AstroData instance

append(ext, name=None, header=None)[source]

Adds a new top-level extension.

Parameters
  • ext (array, astropy.nddata.NDData, astropy.table.Table, other) – The contents for the new extension. The exact accepted types depend on the class implementing this interface. Implementations specific to certain data formats may accept specialized types (eg. a FITS provider will accept an astropy.io.fits.ImageHDU and extract the array out of it).

  • name (str, optional) – A name that may be used to access the new object, as an attribute of the provider. The name is typically ignored for top-level (global) objects, and required for the others. If the name cannot be derived from the metadata associated to ext, you will have to provider one. It can consist in a combination of numbers and letters, with the restriction that the letters have to be all capital, and the first character cannot be a number (“[A-Z][A-Z0-9]*”).

Returns

  • The same object, or a new one, if it was necessary to convert it to

  • a more suitable format for internal use.

Raises
  • TypeError – If adding the object in an invalid situation (eg. name is None when adding to a single slice).

  • ValueError – Raised if the extension is of a proper type, but its value is illegal somehow.

crop(x1, y1, x2, y2)[source]

Crop the NDData objects given indices.

Parameters
  • x1 (int) – Minimum and maximum indices for the x and y axis.

  • y1 (int) – Minimum and maximum indices for the x and y axis.

  • x2 (int) – Minimum and maximum indices for the x and y axis.

  • y2 (int) – Minimum and maximum indices for the x and y axis.

property data

A list of the arrays (or single array, if this is a single slice) corresponding to the science data attached to each extension.

property descriptors

Returns a sequence of names for the methods that have been decorated as descriptors.

Returns

Return type

tuple of str

divide(oper)

Performs inplace division by evaluating self /= operand.

Parameters

oper (number or object) – The operand to perform the operation self /= operand.

Returns

Return type

AstroData instance

property exposed

A collection of strings with the names of objects that can be accessed directly by name as attributes of this instance, and that are not part of its standard interface (i.e. data objects that have been added dynamically).

Examples

>>> ad[0].exposed  
set(['OBJMASK', 'OBJCAT'])
property filename

Return the file name.

property hdr

Return all headers, as a astrodata.fits.FitsHeaderCollection.

property header
property id

Returns the extension identifier (1-based extension number) for sliced objects.

property indices

Returns the extensions indices for sliced objects.

info()[source]

Prints out information about the contents of this instance.

instrument()[source]

Returns the name of the instrument making the observation.

is_settable(attr)[source]

Return True if the attribute is meant to be modified.

property is_single

If this data provider represents a single slice out of a whole dataset, return True. Otherwise, return False.

property is_sliced

If this data provider instance represents the whole dataset, return False. If it represents a slice out of the whole, return True.

classmethod load(source, extname_parser=None)

Read from a file, file object, HDUList, etc.

property mask

A list of the mask arrays (or a single array, if this is a single slice) attached to the science data, for each extension.

For objects that miss a mask, None will be provided instead.

multiply(oper)

Performs inplace multiplication by evaluating self *= operand.

Parameters

oper (number or object) – The operand to perform the operation self *= operand.

Returns

Return type

AstroData instance

property nddata

Return the list of astrodata.NDAstroData objects.

If the AstroData object is sliced, this returns only the NDData objects of the sliced extensions. And if this is a single extension object, the NDData object is returned directly (i.e. not a list).

object()[source]

Returns the name of the object being observed.

operate(operator, *args, **kwargs)[source]

Applies a function to the main data array on each extension, replacing the data with the result. The data will be passed as the first argument to the function.

It will be applied to the mask and variance of each extension, too, if they exist.

This is a convenience method, which is equivalent to:

for ext in ad:
    ext.data = operator(ext.data, *args, **kwargs)
    if ext.mask is not None:
        ext.mask = operator(ext.mask, *args, **kwargs)
    if ext.variance is not None:
        ext.variance = operator(ext.variance, *args, **kwargs)

with the additional advantage that it will work on single slices, too.

Parameters
  • operator (callable) – A function that takes an array (and, maybe, other arguments) and returns an array.

  • args (optional) – Additional arguments to be passed to the operator.

  • kwargs (optional) – Additional arguments to be passed to the operator.

Examples

>>> import numpy as np
>>> ad.operate(np.squeeze)  
property orig_filename

Return the original file name (before it was modified).

property path

Return the file path.

property phu

Return the primary header.

classmethod read(source, extname_parser=None)[source]

Read from a file, file object, HDUList, etc.

reset(data, mask=<object object>, variance=<object object>, check=True)[source]

Sets the .data, and optionally .mask and .variance attributes of a single-extension AstroData slice. This function will optionally check whether these attributes have the same shape.

Parameters
  • data (ndarray) – The array to assign to the .data attribute (“SCI”).

  • mask (ndarray, optional) – The array to assign to the .mask attribute (“DQ”).

  • variance (ndarray, optional) – The array to assign to the .variance attribute (“VAR”).

  • check (bool) – If set, then the function will check that the mask and variance arrays have the same shape as the data array.

Raises
  • TypeError – if an attempt is made to set the .mask or .variance attributes with something other than an array

  • ValueError – if the .mask or .variance attributes don’t have the same shape as .data, OR if this is called on an AD instance that isn’t a single extension slice

property shape
subtract(oper)

Performs inplace subtraction by evaluating self -= operand.

Parameters

oper (number or object) – The operand to perform the operation self -= operand.

Returns

Return type

AstroData instance

table()[source]
property tables

Return the names of the astropy.table.Table objects associated to the object or its extensions.

property tags

A set of strings that represent the tags defining this instance.

telescope()[source]

Returns the name of the telescope.

property uncertainty

A list of the uncertainty objects (or a single object, if this is a single slice) attached to the science data, for each extension.

The objects are instances of AstroPy’s astropy.nddata.NDUncertainty, or None where no information is available.

See also

variance

The actual array supporting the uncertainty object.

update_filename(prefix=None, suffix=None, strip=False)[source]

Update the “filename” attribute of the AstroData object.

A prefix and/or suffix can be specified. If strip=True, these will replace the existing prefix/suffix; if strip=False, they will simply be prepended/appended.

The current filename is broken down into its existing prefix, root, and suffix using the ORIGNAME phu keyword, if it exists and is contained within the current filename. Otherwise, the filename is split at the last underscore and the part before is assigned as the root and the underscore and part after the suffix. No prefix is assigned.

Note that, if strip=True, a prefix or suffix will only be stripped if ‘’ is specified.

Parameters
  • prefix (str, optional) – New prefix (None => leave alone)

  • suffix (str, optional) – New suffix (None => leave alone)

  • strip (bool, optional) – Strip existing prefixes and suffixes if new ones are given?

property variance

A list of the variance arrays (or a single array, if this is a single slice) attached to the science data, for each extension.

For objects that miss uncertainty information, None will be provided instead.

See also

uncertainty

The uncertainty objects used under the hood.

property wcs

Returns the list of WCS objects for each extension.

write(filename=None, overwrite=False)[source]

Write the object to disk.

Parameters
  • filename (str, optional) – If the filename is not given, self.path is used.

  • overwrite (bool) – If True, overwrites existing file.

astrodata.factory module

exception astrodata.factory.AstroDataError[source]

Bases: Exception

class astrodata.factory.AstroDataFactory[source]

Bases: object

addClass(cls)[source]

Add a new class to the AstroDataFactory registry. It will be used when instantiating an AstroData class for a FITS file.

createFromScratch(phu, extensions=None)[source]

Creates an AstroData object from a collection of objects.

Parameters
  • phu (fits.PrimaryHDU or fits.Header or dict or list) – FITS primary HDU or header, or something that can be used to create a fits.Header (a dict, a list of “cards”).

  • extensions (list of HDUs) – List of HDU objects.

getAstroData(source)[source]

Takes either a string (with the path to a file) or an HDUList as input, and tries to return an AstroData instance.

It will raise exceptions if the file is not found, or if there is no match for the HDUList, among the registered AstroData classes.

Returns an instantiated object, or raises AstroDataError if it was not possible to find a match

Parameters

source (str or pathlib.Path or fits.HDUList) – The file path or HDUList to read.

astrodata.fits module

class astrodata.fits.FitsHeaderCollection(headers)[source]

Bases: object

Group access to a list of FITS Header-like objects.

It exposes a number of methods (set, get, etc.) that operate over all the headers at the same time. It can also be iterated.

Parameters

headers (list of astropy.io.fits.Header) – List of Header objects.

get(key, default=None)[source]
get_comment(key)[source]
remove(key)[source]
set(key, value=None, comment=None)[source]
set_comment(key, comment)[source]
class astrodata.fits.FitsLazyLoadable(obj)[source]

Bases: object

property data
property dtype

Need to to some overriding of astropy.io.fits since it doesn’t know about BITPIX=8

property header
property shape
astrodata.fits.ad_to_hdulist(ad)[source]

Creates an HDUList from an AstroData object.

astrodata.fits.add_header_to_table(table)[source]
astrodata.fits.asdftablehdu_to_wcs(hdu)[source]

Recreate a gWCS object from its serialization in a FITS table extension.

Returns None (issuing a warning) if the extension cannot be parsed, so the rest of the file can still be read.

astrodata.fits.card_filter(cards, include=None, exclude=None)[source]
astrodata.fits.fits_ext_comp_key(ext)[source]

Returns a pair (int, str) that will be used to sort extensions.

astrodata.fits.header_for_table(table)[source]
astrodata.fits.new_imagehdu(data, header, name=None)[source]
astrodata.fits.read_fits(cls, source, extname_parser=None)[source]

Takes either a string (with the path to a file) or an HDUList as input, and tries to return a populated AstroData (or descendant) instance.

It will raise exceptions if the file is not found, or if there is no match for the HDUList, among the registered AstroData classes.

astrodata.fits.table_to_bintablehdu(table, extname=None)[source]

Convert an astropy Table object to a BinTableHDU before writing to disk.

Parameters
  • table (astropy.table.Table instance) – the table to be converted to a BinTableHDU

  • extname (str) – name to go in the EXTNAME field of the FITS header

Returns

Return type

BinTableHDU

astrodata.fits.update_header(headera, headerb)[source]
astrodata.fits.wcs_to_asdftablehdu(wcs, extver=None)[source]

Serialize a gWCS object as a FITS TableHDU (ASCII) extension.

The ASCII table is actually a mini ASDF file. The constituent AstroPy models must have associated ASDF “tags” that specify how to serialize them.

In the event that serialization as pure ASCII fails (this should not happen), a binary table representation will be used as a fallback.

astrodata.fits.windowedOp(func, sequence, kernel, shape=None, dtype=None, with_uncertainty=False, with_mask=False, **kwargs)[source]

Apply function on a NDData obbjects, splitting the data in chunks to limit memory usage.

Parameters
  • func (callable) – The function to apply.

  • sequence (list of NDData) – List of NDData objects.

  • kernel (tuple of int) – Shape of the blocks.

  • shape (tuple of int) – Shape of inputs. Defaults to sequence[0].shape.

  • dtype (str or dtype) – Type of the output array. Defaults to sequence[0].dtype.

  • with_uncertainty (bool) – Compute uncertainty?

  • with_mask (bool) – Compute mask?

  • **kwargs – Additional args are passed to func.

astrodata.fits.write_fits(ad, filename, overwrite=False)[source]

Writes the AstroData object to a FITS file.

astrodata.nddata module

This module implements a derivative class based on NDData with some Mixins, implementing windowing and on-the-fly data scaling.

class astrodata.nddata.NDAstroData(data, uncertainty=None, mask=None, wcs=None, meta=None, unit=None, copy=False, window=None, variance=None)[source]

Bases: astropy.nddata.mixins.ndarithmetic.NDArithmeticMixin, astropy.nddata.mixins.ndslicing.NDSlicingMixin, astropy.nddata.nddata.NDData

Implements NDData with all Mixins, plus some AstroData specifics.

This class implements an NDData-like container that supports reading and writing as implemented in the astropy.io.registry and also slicing (indexing) and simple arithmetics (add, subtract, divide and multiply).

A very important difference between NDAstroData and NDData is that the former attempts to load all its data lazily. There are also some important differences in the interface (eg. .data lets you reset its contents after initialization).

Documentation is provided where our class differs.

See also

NDData, NDArithmeticMixin, NDSlicingMixin

Examples

The mixins allow operation that are not possible with NDData or NDDataBase, i.e. simple arithmetics:

>>> from astropy.nddata import StdDevUncertainty
>>> import numpy as np
>>> data = np.ones((3,3), dtype=np.float)
>>> ndd1 = NDAstroData(data, uncertainty=StdDevUncertainty(data))
>>> ndd2 = NDAstroData(data, uncertainty=StdDevUncertainty(data))
>>> ndd3 = ndd1.add(ndd2)
>>> ndd3.data
array([[2., 2., 2.],
    [2., 2., 2.],
    [2., 2., 2.]])
>>> ndd3.uncertainty.array
array([[1.41421356, 1.41421356, 1.41421356],
    [1.41421356, 1.41421356, 1.41421356],
    [1.41421356, 1.41421356, 1.41421356]])

see NDArithmeticMixin for a complete list of all supported arithmetic operations.

But also slicing (indexing) is possible:

>>> ndd4 = ndd3[1,:]
>>> ndd4.data
array([2., 2., 2.])
>>> ndd4.uncertainty.array
array([1.41421356, 1.41421356, 1.41421356])

See NDSlicingMixin for a description how slicing works (which attributes) are sliced.

property T
property data

An array representing the raw data stored in this instance. It implements a setter.

property mask

Mask for the dataset, if any.

Masks should follow the numpy convention that valid data points are marked by False and invalid ones with True.

Type

any type

set_section(section, input)[source]

Sets only a section of the data. This method is meant to prevent fragmentation in the Python heap, by reusing the internal structures instead of replacing them with new ones.

Parameters
  • section (slice) – The area that will be replaced

  • input (NDData-like instance) – This object needs to implement at least data, uncertainty, and mask. Their entire contents will replace the data in the area defined by section.

Examples

>>> sec = NDData(np.zeros((100,100)))  
>>> ad[0].nddata.set_section((slice(None,100),slice(None,100)), sec)  
property shape
transpose()[source]
property uncertainty

Uncertainty in the dataset, if any.

Should have an attribute uncertainty_type that defines what kind of uncertainty is stored, such as 'std' for standard deviation or 'var' for variance. A metaclass defining such an interface is NDUncertainty but isn’t mandatory.

Type

any type

property variance

A convenience property to access the contents of uncertainty, squared (as the uncertainty data is stored as standard deviation).

property wcs

A world coordinate system (WCS) for the dataset, if any.

Type

any type

property window

Interface to access a section of the data, using lazy access whenever possible.

Returns

  • An instance of NDWindowing, which provides __getitem__,

  • to allow the use of square brackets when specifying the window.

  • Ultimately, an NDWindowingAstrodata instance is returned.

Examples

>>> ad[0].nddata.window[100:200, 100:200]  
<NDWindowingAstrodata .....>

astrodata.provenance module

astrodata.provenance.add_provenance(ad, filename, md5, primitive, timestamp=None)[source]

Add the given provenance entry to the full set of provenance records on this object.

Provenance is not added if the incoming md5 is None or ‘’. These indicate source data for the provenance that are not on disk, so not useful as provenance.

Parameters
astrodata.provenance.add_provenance_history(ad, timestamp_start, timestamp_stop, primitive, args)[source]

Add the given ProvenanceHistory entry to the full set of history records on this object.

Parameters
  • ad (astrodata.AstroData) – AstroData object to add history record to.

  • timestamp_start (datetime.datetime) – Date of the start of this operation.

  • timestamp_stop (datetime.datetime) – Date of the end of this operation.

  • primitive (str) – Name of the primitive performed.

  • args (str) – Arguments used for the primitive call.

astrodata.provenance.clone_provenance(provenance_data, ad)[source]

For a single input’s provenance, copy it into the output AstroData object as appropriate.

This takes a dictionary with a source filename, md5 and both it’s original provenance and provenance_history information. It duplicates the provenance data into the outgoing AstroData ad object.

Parameters
  • provenance_data – Pointer to the AstroData table with the provenance information. Note this may be the output AstroData as well, so we need to handle that.

  • ad (astrodata.AstroData) – Outgoing AstroData object to add provenance data to.

astrodata.provenance.clone_provenance_history(provenance_history_data, ad)[source]

For a single input’s provenance history, copy it into the output AstroData object as appropriate.

This takes a dictionary with a source filename, md5 and both it’s original provenance and provenance_history information. It duplicates the provenance data into the outgoing AstroData ad object.

Parameters
  • provenance_history_data – pointer to the AstroData table with the history information. Note this may be the output AstroData as well, so we need to handle that.

  • ad (astrodata.AstroData) – Outgoing AstroData object to add provenance history data to.

astrodata.testing module

astrodata.utils module

exception astrodata.utils.AstroDataDeprecationWarning[source]

Bases: DeprecationWarning

class astrodata.utils.TagSet(add=None, remove=None, blocked_by=None, blocks=None, if_present=None)[source]

Bases: astrodata.utils.TagSet

Named tuple that is used by tag methods to return which actions should be performed on a tag set. All the attributes are optional, and any combination of them can be used, allowing to create complex tag structures. Read the documentation on the tag-generating algorithm if you want to better understand the interactions.

The simplest TagSet, though, tends to just add tags to the global set.

It can be initialized by position, like any other tuple (the order of the arguments is the one in which the attributes are listed below). It can also be initialized by name.

add

Tags to be added to the global set

Type

set of str, optional

remove

Tags to be removed from the global set

Type

set of str, optional

blocked_by

Tags that will prevent this TagSet from being applied

Type

set of str, optional

blocks

Other TagSets containing these won’t be applied

Type

set of str, optional

if_present

This TagSet will be applied only all of these tags are present

Type

set of str, optional

Examples

>>> TagSet()
TagSet(add=set(), remove=set(), blocked_by=set(), blocks=set(), if_present=set())
>>> TagSet({'BIAS', 'CAL'})
TagSet(add={'BIAS', 'CAL'}, remove=set(), blocked_by=set(), blocks=set(), if_present=set())
>>> TagSet(remove={'BIAS', 'CAL'})
TagSet(add=set(), remove={'BIAS', 'CAL'}, blocked_by=set(), blocks=set(), if_present=set())
astrodata.utils.assign_only_single_slice(fn)[source]

Raise ValueError if assigning to a non-single slice.

astrodata.utils.astro_data_descriptor(fn)[source]

Decorator that will mark a class method as an AstroData descriptor. Useful to produce list of descriptors, for example.

If used in combination with other decorators, this one must be the one on the top (ie. the last one applying). It doesn’t modify the method in any other way.

Parameters

fn (method) – The method to be decorated

Returns

Return type

The tagged method (not a wrapper)

astrodata.utils.astro_data_tag(fn)[source]

Decorator that marks methods of an AstroData derived class as part of the tag-producing system.

It wraps the method around a function that will ensure a consistent return value: the wrapped method can return any sequence of sequences of strings, and they will be converted to a TagSet. If the wrapped method returns None, it will be turned into an empty TagSet.

Parameters

fn (method) – The method to be decorated

Returns

Return type

A wrapper function

astrodata.utils.deprecated(reason)[source]
astrodata.utils.normalize_indices(slc, nitems)[source]
astrodata.utils.returns_list(fn)[source]

Decorator to ensure that descriptors that should return a list (of one value per extension) only returns single values when operating on single slices; and vice versa.

This is a common case, and you can use the decorator to simplify the logic of your descriptors.

Parameters

fn (method) – The method to be decorated

Returns

Return type

A function

astrodata.wcs module

class astrodata.wcs.AffineMatrices(matrix, offset)

Bases: tuple

property matrix

Alias for field number 0

property offset

Alias for field number 1

astrodata.wcs.calculate_affine_matrices(func, shape)[source]

Compute the matrix and offset necessary of an affine transform that represents the supplied function. This is done by computing the linear matrix along all axes extending from the centre of the region, and then calculating the offset such that the transformation is accurate at the centre of the region. The matrix and offset are returned in the standard python order (i.e., y-first for 2D).

Parameters
  • func (callable) – function that maps input->output coordinates

  • shape (sequence) – shape to use for fiducial points

Returns

affine matrix and offset

Return type

AffineMatrices(array, array)

astrodata.wcs.fitswcs_image(header)[source]

Make a complete transform from CRPIX-shifted pixels to sky coordinates from FITS WCS keywords. A Mapping is inserted at the beginning, which may be removed later

Parameters

header (astropy.io.fits.Header or dict) – FITS Header or dict with basic FITS WCS keywords.

astrodata.wcs.fitswcs_linear(header)[source]

Create WCS linear transforms for any axes not associated with celestial coordinates. We require that each world axis aligns precisely with only a single pixel axis.

Parameters

header (astropy.io.fits.Header or dict) – FITS Header or dict with basic FITS WCS keywords.

astrodata.wcs.fitswcs_to_gwcs(hdr)[source]

Create and return a gWCS object from a FITS header. If it can’t construct one, it should quietly return None.

astrodata.wcs.get_axes(header)[source]

Matches input with spectral and sky coordinate axes.

Parameters

header (astropy.io.fits.Header or dict) – FITS Header (or dict) with basic WCS information.

Returns

sky_inmap, spectral_inmap, unknown – indices in the output representing sky and spectral coordinates.

Return type

list

astrodata.wcs.gwcs_to_fits(ndd, hdr=None)[source]

Convert a gWCS object to a collection of FITS WCS keyword/value pairs, if possible. If the FITS WCS is only approximate, this should be indicated with a dict entry {‘FITS-WCS’: ‘APPROXIMATE’}. If there is no suitable FITS representation, then a ValueError or NotImplementedError can be raised.

Parameters
Returns

values to insert into the FITS header to express this WCS

Return type

dict

astrodata.wcs.make_fitswcs_transform(header)[source]

Create a basic FITS WCS transform. It does not include distortions.

Parameters

header (astropy.io.fits.Header or dict) – FITS Header (or dict) with basic WCS information

astrodata.wcs.model_is_affine(model)[source]

” Test a Model for affinity. This is currently done by checking the name of its class (or the class names of all its submodels)

TODO: Is this the right thing to do? We could compute the affine matrices assuming affinity, and then check that a number of random points behave as expected. Is that better?

astrodata.wcs.read_wcs_from_header(header)[source]

Extract basic FITS WCS keywords from a FITS Header.

Parameters

header (astropy.io.fits.Header) – FITS Header with WCS information.

Returns

wcs_info – A dictionary with WCS keywords.

Return type

dict