Skip to main content
`Ctrl`+`K`

# Header Data Unit

Header Data Units are the fundamental container structure of the FITS format consisting of a `data` member and its associated metadata in a `header`. They are defined in `astropy.io.fits.hdu`.

The `ImageHDU` and `CompImageHDU` classes are discussed in the section on Images.

The `TableHDU` and `BinTableHDU` classes are discussed in the section on Tables.

## `PrimaryHDU`

class astropy.io.fits.PrimaryHDU(data=None, header=None, do_not_scale_image_data=False, ignore_blank=False, uint=True, scale_back=None)

  Bases: `_ImageBaseHDU`

  FITS primary HDU class.

  Construct a primary HDU.

  Parameters:
    data `array` or `astropy.io.fits.hdu.base.DELAYED`, optional

      The data in the HDU.

    header `Header`, optional

      The header to be used (as a template). If `header` is `None`, a minimal header will be provided.

    do_not_scale_image_data bool, optional

      If `True`, image data is not scaled using BSCALE/BZERO values when read. (default: False)

    ignore_blank bool, optional

      If `True`, the BLANK header keyword will be ignored if present. Otherwise, pixels equal to this value will be replaced with NaNs. (default: False)

    uint bool, optional

      Interpret signed integer data where `BZERO` is the central value and `BSCALE == 1` as unsigned integer data. For example, `int16` data with `BZERO = 32768` and `BSCALE = 1` would be treated as `uint16` data. (default: True)

    scale_back bool, optional

      If `True`, when saving changes to a file that contained scaled image data, restore the data to the original type and reapply the original BSCALE/BZERO values. This could lead to loss of accuracy if scaling back to integer values after performing floating point operations on the data. Pseudo-unsigned integers are automatically rescaled unless scale_back is explicitly set to `False`. (default: None)

  add_checksum(when=None, override_datasum=False, checksum_keyword='CHECKSUM', datasum_keyword='DATASUM')

    Add the `CHECKSUM` and `DATASUM` cards to this HDU with the values set to the checksum calculated for the HDU and the data respectively. The addition of the `DATASUM` card may be overridden.

    Parameters:
      when `python:str`, optional

        comment string for the cards; by default the comments will represent the time when the checksum was calculated

      override_datasum bool, optional

        add the `CHECKSUM` card only

      checksum_keyword `python:str`, optional

        The name of the header keyword to store the checksum value in; this is typically ‘CHECKSUM’ per convention, but there exist use cases in which a different keyword should be used

      datasum_keyword `python:str`, optional

        See `checksum_keyword`

    Notes

    For testing purposes, first call `add_datasum` with a `when` argument, then call `add_checksum` with a `when` argument and `override_datasum` set to `True`. This will provide consistent comments for both cards and enable the generation of a `CHECKSUM` card with a consistent value.

  add_datasum(when=None, datasum_keyword='DATASUM')

    Add the `DATASUM` card to this HDU with the value set to the checksum calculated for the data.

    Parameters:
      when `python:str`, optional

        Comment string for the card that by default represents the time when the checksum was calculated

      datasum_keyword `python:str`, optional

        The name of the header keyword to store the datasum value in; this is typically ‘DATASUM’ per convention, but there exist use cases in which a different keyword should be used

    Returns:
      checksum `python:int`

        The calculated datasum

    Notes

    For testing purposes, provide a `when` argument to enable the comment value in the card to remain consistent. This will enable the generation of a `CHECKSUM` card with a consistent value.

  copy()

    Make a copy of the HDU, both header and data are copied.

  property data

    Image/array data as a `ndarray`.

    Please remember that the order of axes on an Numpy array are opposite of the order specified in the FITS file. For example for a 2D image the “rows” or y-axis are the first dimension, and the “columns” or x-axis are the second dimension.

    If the data is scaled using the BZERO and BSCALE parameters, this attribute returns the data scaled to its physical values unless the file was opened with `do_not_scale_image_data=True`.

  filebytes()

    Calculates and returns the number of bytes that this HDU will write to a file.

  fileinfo()

    Returns a dictionary detailing information about the locations of this HDU within any associated file. The values are only valid after a read or write of the associated file with no intervening changes to the `HDUList`.

    Returns:
      `python:dict` or `python:None`

        The dictionary details information about the locations of this HDU within an associated file. Returns `None` when the HDU is not associated with a file.

        Dictionary contents:

        Key | Value
        --- | ---
        file | File object associated with the HDU
        filemode | Mode in which the file was opened (readonly, copyonwrite, update, append, ostream)
        hdrLoc | Starting byte location of header in file
        datLoc | Starting byte location of data block in file
        datSpan | Data size including padding

  classmethod fromstring(data, checksum=False, ignore_missing_end=False, **kwargs)

    Creates a new HDU object of the appropriate type from a string containing the HDU’s entire header and, optionally, its data.

    Note: When creating a new HDU from a string without a backing file object, the data of that HDU may be read-only. It depends on whether the underlying string was an immutable Python str/bytes object, or some kind of read-write memory buffer such as a `memoryview`.

    Parameters:
      data `python:str`, `bytes`, `memoryview`, `ndarray`

        A byte string containing the HDU’s header and data.

      checksum bool, optional

        Check the HDU’s checksum and/or datasum.

      ignore_missing_end bool, optional

        Ignore a missing end card in the header data. Note that without the end card the end of the header may be ambiguous and resulted in a corrupt HDU. In this case the assumption is that the first 2880 block that does not begin with valid FITS header data is the beginning of the data.

      **kwargs optional

        May consist of additional keyword arguments specific to an HDU type–these correspond to keywords recognized by the constructors of different HDU classes such as `PrimaryHDU`, `ImageHDU`, or `BinTableHDU`. Any unrecognized keyword arguments are simply ignored.

  classmethod match_header(header)

    _ImageBaseHDU is sort of an abstract class for HDUs containing image data (as opposed to table data) and should never be used directly.

  classmethod readfrom(fileobj, checksum=False, ignore_missing_end=False, **kwargs)

    Read the HDU from a file. Normally an HDU should be opened with `open()` which reads the entire HDU list in a FITS file. But this method is still provided for symmetry with `writeto()`.

    Parameters:
      fileobj python:file-like object

        Input FITS file. The file’s seek pointer is assumed to be at the beginning of the HDU.

      checksum bool

        If `True`, verifies that both `DATASUM` and `CHECKSUM` card values (when present in the HDU header) match the header and data of all HDU’s in the file.

      ignore_missing_end bool

        Do not issue an exception when opening a file that is missing an `END` card in the last header.

  req_cards(keyword, pos, test, fix_value, option, errlist)

    Check the existence, location, and value of a required `Card`.

    Parameters:
      keyword `python:str`

        The keyword to validate

      pos `python:int`, `python:callable()`

        If an `int`, this specifies the exact location this card should have in the header. Remember that Python is zero-indexed, so this means `pos=0` requires the card to be the first card in the header. If given a callable, it should take one argument–the actual position of the keyword–and return `True` or `False`. This can be used for custom evaluation. For example if `pos=lambda idx: idx > 10` this will check that the keyword’s index is greater than 10.

      test `python:callable()`

        This should be a callable (generally a function) that is passed the value of the given keyword and returns `True` or `False`. This can be used to validate the value associated with the given keyword.

      fix_value `python:str`, `python:int`, `python:float`, `complex`, bool, `python:None`

        A valid value for a FITS keyword to use if the given `test` fails to replace an invalid value. In other words, this provides a default value to use as a replacement if the keyword’s current value is invalid. If `None`, there is no replacement value and the keyword is unfixable.

      option `python:str`

        Output verification option. Must be one of `"fix"`, `"silentfix"`, `"ignore"`, `"warn"`, or `"exception"`. May also be any combination of `"fix"` or `"silentfix"` with `"+ignore"`, `+warn`, or `+exception" (e.g. ``"fix+warn"`). See Verification Options for more info.

      errlist `python:list`

        A list of validation errors already found in the FITS file; this is used primarily for the validation system to collect errors across multiple HDUs and multiple calls to `req_cards`.

    Notes

    If `pos=None`, the card can be anywhere in the header. If the card does not exist, the new card will have the `fix_value` as its value when created. Also check the card’s value by using the `test` argument.

  run_option(option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True)

    Execute the verification with selected option.

  scale(type=None, option='old', bscale=None, bzero=None)

    Scale image data by using `BSCALE`/`BZERO`.

    Call to this method will scale `data` and update the keywords of `BSCALE` and `BZERO` in the HDU’s header. This method should only be used right before writing to the output file, as the data will be scaled and is therefore not very usable after the call.

    Parameters:
      type `python:str`, optional

        destination data type, use a string representing a numpy dtype name, (e.g. `'uint8'`, `'int16'`, `'float32'` etc.). If is `None`, use the current data type.

      option `python:str`, optional

        How to scale the data: `"old"` uses the original `BSCALE` and `BZERO` values from when the data was read/created (defaulting to 1 and 0 if they don’t exist). For integer data only, `"minmax"` uses the minimum and maximum of the data to scale. User-specified `bscale`/`bzero` values always take precedence.

      bscale, bzero `python:int`, optional

        User-specified `BSCALE` and `BZERO` values

  property section

    Access a section of the image array without loading the entire array into memory. The `Section` object returned by this attribute is not meant to be used directly by itself. Rather, slices of the section return the appropriate slice of the data, and loads only that section into memory.

    Sections are useful for retrieving a small subset of data from a remote file that has been opened with the `use_fsspec=True` parameter. For example, you can use this feature to download a small cutout from a large FITS image hosted in the Amazon S3 cloud (see the Working with remote and cloud-hosted files section of the Astropy documentation for more details.)

    For local files, sections are mostly obsoleted by memmap support, but should still be used to deal with very large scaled images.

    Note that sections cannot currently be written to. Moreover, any in-memory updates to the image’s `.data` property may not be reflected in the slices obtained via `.section`. See the Data Sections section of the documentation for more details.

  property shape

    Shape of the image array–should be equivalent to `self.data.shape`.

  property size

    Size (in bytes) of the data portion of the HDU.

  update_header()

    Update the header keywords to agree with the data.

  verify(option='warn')

    Verify all values in the instance.

    Parameters:
      option `python:str`

        Output verification option. Must be one of `"fix"`, `"silentfix"`, `"ignore"`, `"warn"`, or `"exception"`. May also be any combination of `"fix"` or `"silentfix"` with `"+ignore"`, `"+warn"`, or `"+exception"` (e.g. `"fix+warn"`). See Verification Options for more info.

  verify_checksum()

    Verify that the value in the `CHECKSUM` keyword matches the value calculated for the current HDU CHECKSUM.

    Returns:
      valid `python:int`

        - 0 - failure

        - 1 - success

        - 2 - no `CHECKSUM` keyword present

  verify_datasum()

    Verify that the value in the `DATASUM` keyword matches the value calculated for the `DATASUM` of the current HDU data.

    Returns:
      valid `python:int`

        - 0 - failure

        - 1 - success

        - 2 - no `DATASUM` keyword present

  writeto(name, output_verify='exception', overwrite=False, checksum=False)

    Write the HDU to a new file. This is a convenience method to provide a user easier output interface if only one HDU needs to be written to a file.

    Parameters:
      name python:path-like object or python:file-like object

        Output FITS file. If the file object is already opened, it must be opened in a writeable mode.

      output_verify `python:str`

        Output verification option. Must be one of `"fix"`, `"silentfix"`, `"ignore"`, `"warn"`, or `"exception"`. May also be any combination of `"fix"` or `"silentfix"` with `"+ignore"`, `"+warn"`, or `"+exception"` (e.g. `"fix+warn"`). See Verification Options for more info.

      overwrite bool, optional

        If `True`, overwrite the output file if it exists. Raises an `OSError` if `False` and the output file exists. Default is `False`.

      checksum bool

        When `True` adds both `DATASUM` and `CHECKSUM` cards to the header of the HDU when written to the file.

    Notes

    gzip, zip, bzip2 and lzma compression algorithms are natively supported. Compression mode is determined from the filename extension (‘.gz’, ‘.zip’, ‘.bz2’ or ‘.xz’ respectively). It is also possible to pass a compressed file object, e.g. `gzip.GzipFile`.

## `GroupsHDU`

class astropy.io.fits.GroupsHDU(data=None, header=None)

  Bases: `PrimaryHDU`, `_TableLikeHDU`

  FITS Random Groups HDU class.

  See the Random Access Groups section in the Astropy documentation for more details on working with this type of HDU.

  Construct a primary HDU.

  Parameters:
    data `array` or `astropy.io.fits.hdu.base.DELAYED`, optional

      The data in the HDU.

    header `Header`, optional

      The header to be used (as a template). If `header` is `None`, a minimal header will be provided.

    do_not_scale_image_data bool, optional

      If `True`, image data is not scaled using BSCALE/BZERO values when read. (default: False)

    ignore_blank bool, optional

      If `True`, the BLANK header keyword will be ignored if present. Otherwise, pixels equal to this value will be replaced with NaNs. (default: False)

    uint bool, optional

      Interpret signed integer data where `BZERO` is the central value and `BSCALE == 1` as unsigned integer data. For example, `int16` data with `BZERO = 32768` and `BSCALE = 1` would be treated as `uint16` data. (default: True)

    scale_back bool, optional

      If `True`, when saving changes to a file that contained scaled image data, restore the data to the original type and reapply the original BSCALE/BZERO values. This could lead to loss of accuracy if scaling back to integer values after performing floating point operations on the data. Pseudo-unsigned integers are automatically rescaled unless scale_back is explicitly set to `False`. (default: None)

  add_checksum(when=None, override_datasum=False, checksum_keyword='CHECKSUM', datasum_keyword='DATASUM')

    Add the `CHECKSUM` and `DATASUM` cards to this HDU with the values set to the checksum calculated for the HDU and the data respectively. The addition of the `DATASUM` card may be overridden.

    Parameters:
      when `python:str`, optional

        comment string for the cards; by default the comments will represent the time when the checksum was calculated

      override_datasum bool, optional

        add the `CHECKSUM` card only

      checksum_keyword `python:str`, optional

        The name of the header keyword to store the checksum value in; this is typically ‘CHECKSUM’ per convention, but there exist use cases in which a different keyword should be used

      datasum_keyword `python:str`, optional

        See `checksum_keyword`

    Notes

    For testing purposes, first call `add_datasum` with a `when` argument, then call `add_checksum` with a `when` argument and `override_datasum` set to `True`. This will provide consistent comments for both cards and enable the generation of a `CHECKSUM` card with a consistent value.

  add_datasum(when=None, datasum_keyword='DATASUM')

    Add the `DATASUM` card to this HDU with the value set to the checksum calculated for the data.

    Parameters:
      when `python:str`, optional

        Comment string for the card that by default represents the time when the checksum was calculated

      datasum_keyword `python:str`, optional

        The name of the header keyword to store the datasum value in; this is typically ‘DATASUM’ per convention, but there exist use cases in which a different keyword should be used

    Returns:
      checksum `python:int`

        The calculated datasum

    Notes

    For testing purposes, provide a `when` argument to enable the comment value in the card to remain consistent. This will enable the generation of a `CHECKSUM` card with a consistent value.

  property columns

    The `ColDefs` objects describing the columns in this table.

  copy()

    Make a copy of the HDU, both header and data are copied.

  property data

    The data of a random group FITS file will be like a binary table’s data.

  filebytes()

    Calculates and returns the number of bytes that this HDU will write to a file.

  fileinfo()

    Returns a dictionary detailing information about the locations of this HDU within any associated file. The values are only valid after a read or write of the associated file with no intervening changes to the `HDUList`.

    Returns:
      `python:dict` or `python:None`

        The dictionary details information about the locations of this HDU within an associated file. Returns `None` when the HDU is not associated with a file.

        Dictionary contents:

        Key | Value
        --- | ---
        file | File object associated with the HDU
        filemode | Mode in which the file was opened (readonly, copyonwrite, update, append, ostream)
        hdrLoc | Starting byte location of header in file
        datLoc | Starting byte location of data block in file
        datSpan | Data size including padding

  classmethod from_columns(columns, header=None, nrows=0, fill=False, character_as_bytes=False, **kwargs)

    Given either a `ColDefs` object, a sequence of `Column` objects, or another table HDU or table data (a `FITS_rec` or multi-field `numpy.ndarray` or `numpy.recarray` object, return a new table HDU of the class this method was called on using the column definition from the input.

    See also `FITS_rec.from_columns`.

    Parameters:
      columns python:sequence of `Column`, `ColDefs` astropy:-like

        The columns from which to create the table data, or an object with a column-like structure from which a `ColDefs` can be instantiated. This includes an existing `BinTableHDU` or `TableHDU`, or a `numpy.recarray` to give some examples.

        If these columns have data arrays attached that data may be used in initializing the new table. Otherwise the input columns will be used as a template for a new table with the requested number of rows.

      header `Header`

        An optional `Header` object to instantiate the new HDU yet. Header keywords specifically related to defining the table structure (such as the “TXXXn” keywords like TTYPEn) will be overridden by the supplied column definitions, but all other informational and data model-specific keywords are kept.

      nrows `python:int`

        Number of rows in the new table. If the input columns have data associated with them, the size of the largest input column is used. Otherwise the default is 0.

      fill bool

        If `True`, will fill all cells with zeros or blanks. If `False`, copy the data from input, undefined cells will still be filled with zeros/blanks.

      character_as_bytes bool

        Whether to return bytes for string columns when accessed from the HDU. By default this is `False` and (unicode) strings are returned, but for large tables this may use up a lot of memory.

    Notes

    Any additional keyword arguments accepted by the HDU class’s `__init__` may also be passed in as keyword arguments.

  classmethod fromstring(data, checksum=False, ignore_missing_end=False, **kwargs)

    Creates a new HDU object of the appropriate type from a string containing the HDU’s entire header and, optionally, its data.

    Note: When creating a new HDU from a string without a backing file object, the data of that HDU may be read-only. It depends on whether the underlying string was an immutable Python str/bytes object, or some kind of read-write memory buffer such as a `memoryview`.

    Parameters:
      data `python:str`, `bytes`, `memoryview`, `ndarray`

        A byte string containing the HDU’s header and data.

      checksum bool, optional

        Check the HDU’s checksum and/or datasum.

      ignore_missing_end bool, optional

        Ignore a missing end card in the header data. Note that without the end card the end of the header may be ambiguous and resulted in a corrupt HDU. In this case the assumption is that the first 2880 block that does not begin with valid FITS header data is the beginning of the data.

      **kwargs optional

        May consist of additional keyword arguments specific to an HDU type–these correspond to keywords recognized by the constructors of different HDU classes such as `PrimaryHDU`, `ImageHDU`, or `BinTableHDU`. Any unrecognized keyword arguments are simply ignored.

  classmethod match_header(header)

    _ImageBaseHDU is sort of an abstract class for HDUs containing image data (as opposed to table data) and should never be used directly.

  property parnames

    The names of the group parameters as described by the header.

  classmethod readfrom(fileobj, checksum=False, ignore_missing_end=False, **kwargs)

    Read the HDU from a file. Normally an HDU should be opened with `open()` which reads the entire HDU list in a FITS file. But this method is still provided for symmetry with `writeto()`.

    Parameters:
      fileobj python:file-like object

        Input FITS file. The file’s seek pointer is assumed to be at the beginning of the HDU.

      checksum bool

        If `True`, verifies that both `DATASUM` and `CHECKSUM` card values (when present in the HDU header) match the header and data of all HDU’s in the file.

      ignore_missing_end bool

        Do not issue an exception when opening a file that is missing an `END` card in the last header.

  req_cards(keyword, pos, test, fix_value, option, errlist)

    Check the existence, location, and value of a required `Card`.

    Parameters:
      keyword `python:str`

        The keyword to validate

      pos `python:int`, `python:callable()`

        If an `int`, this specifies the exact location this card should have in the header. Remember that Python is zero-indexed, so this means `pos=0` requires the card to be the first card in the header. If given a callable, it should take one argument–the actual position of the keyword–and return `True` or `False`. This can be used for custom evaluation. For example if `pos=lambda idx: idx > 10` this will check that the keyword’s index is greater than 10.

      test `python:callable()`

        This should be a callable (generally a function) that is passed the value of the given keyword and returns `True` or `False`. This can be used to validate the value associated with the given keyword.

      fix_value `python:str`, `python:int`, `python:float`, `complex`, bool, `python:None`

        A valid value for a FITS keyword to use if the given `test` fails to replace an invalid value. In other words, this provides a default value to use as a replacement if the keyword’s current value is invalid. If `None`, there is no replacement value and the keyword is unfixable.

      option `python:str`

        Output verification option. Must be one of `"fix"`, `"silentfix"`, `"ignore"`, `"warn"`, or `"exception"`. May also be any combination of `"fix"` or `"silentfix"` with `"+ignore"`, `+warn`, or `+exception" (e.g. ``"fix+warn"`). See Verification Options for more info.

      errlist `python:list`

        A list of validation errors already found in the FITS file; this is used primarily for the validation system to collect errors across multiple HDUs and multiple calls to `req_cards`.

    Notes

    If `pos=None`, the card can be anywhere in the header. If the card does not exist, the new card will have the `fix_value` as its value when created. Also check the card’s value by using the `test` argument.

  run_option(option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True)

    Execute the verification with selected option.

  scale(type=None, option='old', bscale=None, bzero=None)

    Scale image data by using `BSCALE`/`BZERO`.

    Call to this method will scale `data` and update the keywords of `BSCALE` and `BZERO` in the HDU’s header. This method should only be used right before writing to the output file, as the data will be scaled and is therefore not very usable after the call.

    Parameters:
      type `python:str`, optional

        destination data type, use a string representing a numpy dtype name, (e.g. `'uint8'`, `'int16'`, `'float32'` etc.). If is `None`, use the current data type.

      option `python:str`, optional

        How to scale the data: `"old"` uses the original `BSCALE` and `BZERO` values from when the data was read/created (defaulting to 1 and 0 if they don’t exist). For integer data only, `"minmax"` uses the minimum and maximum of the data to scale. User-specified `bscale`/`bzero` values always take precedence.

      bscale, bzero `python:int`, optional

        User-specified `BSCALE` and `BZERO` values

  property section

    Access a section of the image array without loading the entire array into memory. The `Section` object returned by this attribute is not meant to be used directly by itself. Rather, slices of the section return the appropriate slice of the data, and loads only that section into memory.

    Sections are useful for retrieving a small subset of data from a remote file that has been opened with the `use_fsspec=True` parameter. For example, you can use this feature to download a small cutout from a large FITS image hosted in the Amazon S3 cloud (see the Working with remote and cloud-hosted files section of the Astropy documentation for more details.)

    For local files, sections are mostly obsoleted by memmap support, but should still be used to deal with very large scaled images.

    Note that sections cannot currently be written to. Moreover, any in-memory updates to the image’s `.data` property may not be reflected in the slices obtained via `.section`. See the Data Sections section of the documentation for more details.

  property shape

    Shape of the image array–should be equivalent to `self.data.shape`.

  property size

    Returns the size (in bytes) of the HDU’s data part.

  update_header()

    Update the header keywords to agree with the data.

  verify(option='warn')

    Verify all values in the instance.

    Parameters:
      option `python:str`

        Output verification option. Must be one of `"fix"`, `"silentfix"`, `"ignore"`, `"warn"`, or `"exception"`. May also be any combination of `"fix"` or `"silentfix"` with `"+ignore"`, `"+warn"`, or `"+exception"` (e.g. `"fix+warn"`). See Verification Options for more info.

  verify_checksum()

    Verify that the value in the `CHECKSUM` keyword matches the value calculated for the current HDU CHECKSUM.

    Returns:
      valid `python:int`

        - 0 - failure

        - 1 - success

        - 2 - no `CHECKSUM` keyword present

  verify_datasum()

    Verify that the value in the `DATASUM` keyword matches the value calculated for the `DATASUM` of the current HDU data.

    Returns:
      valid `python:int`

        - 0 - failure

        - 1 - success

        - 2 - no `DATASUM` keyword present

  writeto(name, output_verify='exception', overwrite=False, checksum=False)

    Write the HDU to a new file. This is a convenience method to provide a user easier output interface if only one HDU needs to be written to a file.

    Parameters:
      name python:path-like object or python:file-like object

        Output FITS file. If the file object is already opened, it must be opened in a writeable mode.

      output_verify `python:str`

        Output verification option. Must be one of `"fix"`, `"silentfix"`, `"ignore"`, `"warn"`, or `"exception"`. May also be any combination of `"fix"` or `"silentfix"` with `"+ignore"`, `"+warn"`, or `"+exception"` (e.g. `"fix+warn"`). See Verification Options for more info.

      overwrite bool, optional

        If `True`, overwrite the output file if it exists. Raises an `OSError` if `False` and the output file exists. Default is `False`.

      checksum bool

        When `True` adds both `DATASUM` and `CHECKSUM` cards to the header of the HDU when written to the file.

    Notes

    gzip, zip, bzip2 and lzma compression algorithms are natively supported. Compression mode is determined from the filename extension (‘.gz’, ‘.zip’, ‘.bz2’ or ‘.xz’ respectively). It is also possible to pass a compressed file object, e.g. `gzip.GzipFile`.

## `GroupData`

class astropy.io.fits.GroupData(input=None, bitpix=None, pardata=None, parnames=[], bscale=None, bzero=None, parbscales=None, parbzeros=None)

  Bases: `FITS_rec`

  Random groups data object.

  Allows structured access to FITS Group data in a manner analogous to tables.

  Parameters:
    input `array` or `FITS_rec` instance

      input data, either the group data itself (a `numpy.ndarray`) or a record array (`FITS_rec`) which will contain both group parameter info and the data. The rest of the arguments are used only for the first case.

    bitpix `python:int`

      data type as expressed in FITS `BITPIX` value (8, 16, 32, 64, -32, or -64)

    pardata python:sequence of `array`

      parameter data, as a list of (numeric) arrays.

    parnames python:sequence of `python:str`

      list of parameter names.

    bscale `python:int`

      `BSCALE` of the data

    bzero `python:int`

      `BZERO` of the data

    parbscales python:sequence of `python:int`

      list of bscales for the parameters

    parbzeros python:sequence of `python:int`

      list of bzeros for the parameters

  property data

    The raw group data represented as a multi-dimensional `numpy.ndarray` array.

  par(parname)

    Get the group parameter values.

### `Group`

class astropy.io.fits.Group(input, row=0, start=None, end=None, step=None, base=None)

  Bases: `FITS_record`

  One group of the random group data.

  Parameters:
    input `array`

      The array to wrap.

    row `python:int`, optional

      The starting logical row of the array.

    start `python:int`, optional

      The starting column in the row associated with this object. Used for subsetting the columns of the `FITS_rec` object.

    end `python:int`, optional

      The ending column in the row associated with this object. Used for subsetting the columns of the `FITS_rec` object.

  par(parname)

    Get the group parameter value.

  setpar(parname, value)

    Set the group parameter value.

## `StreamingHDU`

class astropy.io.fits.StreamingHDU(name, header)

  Bases: `object`

  A class that provides the capability to stream data to a FITS file instead of requiring data to all be written at once.

  The following pseudocode illustrates its use:

      header = astropy.io.fits.Header()

      for all the cards you need in the header:
          header[key] = (value, comment)

      shdu = astropy.io.fits.StreamingHDU('filename.fits', header)

      for each piece of data:
          shdu.write(data)

      shdu.close()

  Construct a `StreamingHDU` object given a file name and a header.

  Parameters:
    name python:path-like object or python:file-like object

      The file to which the header and data will be streamed. If opened, the file object must be opened in a writeable binary mode such as ‘wb’ or ‘ab+’.

    header `Header` instance

      The header object associated with the data to be written to the file.

  Notes

  The file will be opened and the header appended to the end of the file. If the file does not already exist, it will be created, and if the header represents a Primary header, it will be written to the beginning of the file. If the file does not exist and the provided header is not a Primary header, a default Primary HDU will be inserted at the beginning of the file and the provided header will be added as the first extension. If the file does already exist, but the provided header represents a Primary header, the header will be modified to an image extension header and appended to the end of the file.

  close()

    Close the physical FITS file.

  property size

    Return the size (in bytes) of the data portion of the HDU.

  write(data)

    Write the given data to the stream.

    Parameters:
      data `ndarray`

        Data to stream to the file.

    Returns:
      writecomplete `python:int`

        Flag that when `True` indicates that all of the required data has been written to the stream.

    Notes

    Only the amount of data specified in the header provided to the class constructor may be written to the stream. If the provided data would cause the stream to overflow, an `OSError` exception is raised and the data is not written. Once sufficient data has been written to the stream to satisfy the amount specified in the header, the stream is padded to fill a complete FITS block and no more data will be accepted. An attempt to write more data after the stream has been filled will raise an `OSError` exception. If the dtype of the input data does not match what is expected by the header, a `TypeError` exception is raised.