pydicom.dataset.FileDataset¶

An extension of Dataset to make reading and writing to file-like easier.

preamble¶

The optional DICOM preamble prepended to the FileDataset, if available.

Type:: str or bytes or None

file_meta¶

The Dataset’s file meta information as a FileMetaDataset, if available (None if not present). Consists of group 0x0002 elements.

Type:: FileMetaDataset or None

filename¶

The filename that the FileDataset was read from (if read from file) or None if the filename is not available (if read from a io.BytesIO or similar).

Type:: str or None

fileobj_type¶: The object type of the file-like the FileDataset was read from.

is_implicit_VR¶

True if the dataset encoding is implicit VR, False otherwise.

Type:: bool

is_little_endian¶

True if the dataset encoding is little endian byte ordering, False otherwise.

Type:: bool

timestamp¶

The modification time of the file the FileDataset was read from, None if the modification time is not available.

Type:: float or None

Initialize a FileDataset read from a DICOM file.

Parameters:

filename_or_obj (str or PathLike or BytesIO or None) – Full path and filename to the file, memory buffer object, or None if is a io.BytesIO.
dataset (Dataset or dict) – Some form of dictionary, usually a Dataset returned from dcmread().
preamble (bytes or str, optional) – The 128-byte DICOM preamble.
file_meta (FileMetaDataset, optional) – The file meta FileMetaDataset, such as the one returned by read_file_meta_info(), or an empty FileMetaDataset if no file meta information is in the file.
is_implicit_VR (bool, optional) – True (default) if implicit VR transfer syntax used; False if explicit VR.
is_little_endian (bool) – True (default) if little-endian transfer syntax used; False if big-endian.

Methods

`__init__`(filename_or_obj, dataset[, ...])	Initialize a `FileDataset` read from a DICOM file.
`add`(data_element)	Add an element to the `Dataset`.
`add_new`(tag, VR, value)	Create a new element and add it to the `Dataset`.
`clear`()	Delete all the elements from the `Dataset`.
`compress`(transfer_syntax_uid[, arr, ...])	Compress and update an uncompressed dataset in-place with the resulting encapsulated pixel data.
`convert_pixel_data`([handler_name])	Convert pixel data to a `numpy.ndarray` internally.
`copy`()	Return a shallow copy of the dataset.
`data_element`(name)	Return the element corresponding to the element keyword name.
`decode`()	Apply character set decoding to the elements in the `Dataset`.
`decompress`([handler_name])	Decompresses Pixel Data and modifies the `Dataset` in-place.
`dir`(*filters)	Return an alphabetical list of element keywords in the `Dataset`.
`elements`()	Yield the top-level elements of the `Dataset`.
`ensure_file_meta`()	Create an empty `Dataset.file_meta` if none exists.
`fix_meta_info`([enforce_standard])	Ensure the file meta info exists and has the correct values for transfer syntax and media storage UIDs.
`formatted_lines`([element_format, ...])	Iterate through the `Dataset` yielding formatted `str` for each element.
`from_json`(json_dataset[, bulk_data_uri_handler])	Return a `Dataset` from a DICOM JSON Model object.
`get`(key[, default])	Simulate `dict.get()` to handle element tags and keywords.
`get_item`(key)	Return the raw data element if possible.
`get_private_item`(group, element_offset, ...)	Return the data element for the given private tag group.
`group_dataset`(group)	Return a `Dataset` containing only elements of a certain group.
`items`()	Return the `Dataset` items to simulate `dict.items()`.
`iterall`()	Iterate through the `Dataset`, yielding all the elements.
`keys`()	Return the `Dataset` keys to simulate `dict.keys()`.
`overlay_array`(group)	Return the Overlay Data in group as a `numpy.ndarray`.
`pop`(key, *args)	Emulate `dict.pop()` with support for tags and keywords.
`popitem`()	Emulate `dict.popitem()`.
`private_block`(group, private_creator[, create])	Return the block for the given tag group and private_creator.
`private_creators`(group)	Return a list of private creator names in the given group.
`remove_private_tags`()	Remove all private elements from the `Dataset`.
`save_as`(filename[, write_like_original])	Write the `Dataset` to filename.
`set_original_encoding`(is_implicit_vr, ...)	Set the values for the original transfer syntax and encoding.
`setdefault`(key[, default])	Emulate `dict.setdefault()` with support for tags and keywords.
`to_json`([bulk_data_threshold, ...])	Return a JSON representation of the `Dataset`.
`to_json_dict`([bulk_data_threshold, ...])	Return a dictionary representation of the `Dataset` conforming to the DICOM JSON Model as described in the DICOM Standard, Part 18, Annex F.
`top`()	Return a `str` representation of the top level elements.
`trait_names`()	Return a `list` of valid names for auto-completion code.
`update`(d)	Extend `dict.update()` to handle DICOM tags and keywords.
`values`()	Return the `Dataset` values to simulate `dict.values()`.
`walk`(callback[, recursive])	Iterate through the `Dataset's` elements and run callback on each.
`waveform_array`(index)	Return an `ndarray` for the multiplex group at index in the (5400,0100) Waveform Sequence.

Attributes

`default_element_format`
`default_sequence_element_format`
`indent_chars`
`is_original_encoding`	Return `True` if the encoding to be used for writing is set and is the same as that used to originally encode the `Dataset`.
`parent`	Return a weak reference to the parent Sequence's parent Dataset.
`parent_seq`	Return a weak reference to the parent `Sequence`.
`pixel_array`	Return the pixel data as a `numpy.ndarray`.