pydicom.dataset.Dataset¶
- class pydicom.dataset.Dataset(*args: Dataset | MutableMapping[BaseTag, DataElement | RawDataElement], **kwargs: Any)[source]¶
A DICOM dataset as a mutable mapping of DICOM Data Elements.
Examples
Add an element to the
Dataset
(for elements in the DICOM dictionary):>>> ds = Dataset() >>> ds.PatientName = "CITIZEN^Joan" >>> ds.add_new(0x00100020, 'LO', '12345') >>> ds[0x0010, 0x0030] = DataElement(0x00100030, 'DA', '20010101')
Add a sequence element to the
Dataset
>>> ds.BeamSequence = [Dataset(), Dataset(), Dataset()] >>> ds.BeamSequence[0].Manufacturer = "Linac, co." >>> ds.BeamSequence[1].Manufacturer = "Linac and Sons, co." >>> ds.BeamSequence[2].Manufacturer = "Linac and Daughters, co."
Add private elements to the
Dataset
>>> block = ds.private_block(0x0041, 'My Creator', create=True) >>> block.add_new(0x01, 'LO', '12345')
Updating and retrieving element values:
>>> ds.PatientName = "CITIZEN^Joan" >>> ds.PatientName 'CITIZEN^Joan' >>> ds.PatientName = "CITIZEN^John" >>> ds.PatientName 'CITIZEN^John'
Retrieving an element’s value from a Sequence:
>>> ds.BeamSequence[0].Manufacturer 'Linac, co.' >>> ds.BeamSequence[1].Manufacturer 'Linac and Sons, co.'
Accessing the
DataElement
items:>>> elem = ds['PatientName'] >>> elem (0010,0010) Patient's Name PN: 'CITIZEN^John' >>> elem = ds[0x00100010] >>> elem (0010,0010) Patient's Name PN: 'CITIZEN^John' >>> elem = ds.data_element('PatientName') >>> elem (0010,0010) Patient's Name PN: 'CITIZEN^John'
Accessing a private
DataElement
item:>>> block = ds.private_block(0x0041, 'My Creator') >>> elem = block[0x01] >>> elem (0041,1001) Private tag data LO: '12345' >>> elem.value '12345'
Alternatively:
>>> ds.get_private_item(0x0041, 0x01, 'My Creator').value '12345'
Deleting an element from the
Dataset
>>> del ds.PatientID >>> del ds.BeamSequence[1].Manufacturer >>> del ds.BeamSequence[2]
Deleting a private element from the
Dataset
>>> block = ds.private_block(0x0041, 'My Creator') >>> if 0x01 in block: ... del block[0x01]
Determining if an element is present in the
Dataset
>>> 'PatientName' in ds True >>> 'PatientID' in ds False >>> (0x0010, 0x0030) in ds True >>> 'Manufacturer' in ds.BeamSequence[0] True
Iterating through the top level of a
Dataset
only (excluding Sequences):>>> for elem in ds: ... print(elem) (0010,0010) Patient's Name PN: 'CITIZEN^John'
Iterating through the entire
Dataset
(including Sequences):>>> for elem in ds.iterall(): ... print(elem) (0010,0010) Patient's Name PN: 'CITIZEN^John'
Recursively iterate through a
Dataset
(including Sequences):>>> def recurse(ds): ... for elem in ds: ... if elem.VR == 'SQ': ... [recurse(item) for item in elem.value] ... else: ... # Do something useful with each DataElement
Converting the
Dataset
to and from JSON:>>> ds = Dataset() >>> ds.PatientName = "Some^Name" >>> jsonmodel = ds.to_json() >>> ds2 = Dataset() >>> ds2.from_json(jsonmodel) (0010,0010) Patient's Name PN: 'Some^Name'
- indent_chars¶
For string display, the characters used to indent nested Sequences. Default is
" "
.- Type:
- __init__(*args: Dataset | MutableMapping[BaseTag, DataElement | RawDataElement], **kwargs: Any) None [source]¶
Create a new
Dataset
instance.
Methods
__init__
(*args, **kwargs)Create a new
Dataset
instance.add
(data_element)Add an element to the
Dataset
.add_new
(tag, VR, value)Create a new element and add it to the
Dataset
.add_new_private
(private_creator, group, ...)Create a new private 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
.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 formattedstr
for each element.from_json
(json_dataset[, bulk_data_uri_handler])Return a
Dataset
from a DICOM JSON Model object.get
()Simulate
dict.get()
to handle element tags and keywords.get_item
()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 simulatedict.items()
.iterall
()Iterate through the
Dataset
, yielding all the elements.keys
()Return the
Dataset
keys to simulatedict.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 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.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 simulatedict.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
is_implicit_VR
is_little_endian
Return
True
if the encoding to be used for writing is set and is the same as that used to originally encode theDataset
.Return the original character set encoding for a dataset decoded from a file or buffer.
Return the original encoding used for a dataset decoded from a file or buffer.
Return the pixel data as a
numpy.ndarray
.read_encoding
Get the VR method used by the original encoding of the dataset.
Get the endianness used by the original encoding of the dataset.
- add(data_element: DataElement) None [source]¶
Add an element to the
Dataset
.Equivalent to
ds[data_element.tag] = data_element
- Parameters:
data_element (dataelem.DataElement) – The
DataElement
to add.
- add_new(tag: int | str | tuple[int, int] | BaseTag, VR: str, value: Any) None [source]¶
Create a new element and add it to the
Dataset
.- Parameters:
tag – The DICOM (group, element) tag in any form accepted by
Tag()
such as[0x0010, 0x0010]
,(0x10, 0x10)
,0x00100010
, etc.VR (str) – The 2 character DICOM value representation (see DICOM Standard, Part 5, Section 6.2).
value –
The value of the data element. One of the following:
- add_new_private(private_creator: str, group: int, element_offset: int, value: Any, vr: str | None = None) None [source]¶
Create a new private element and add it to the
Dataset
.- Parameters:
private_creator (str) – The private creator string related to the new tag.
group (int) – The group ID (0x0009 - 0xFFFF) for the private tag. Must be an odd number.
element_offset (int) – The tag offset, e.g. the lower byte of the tag element of the private tag (0x00 - 0xFF). The higher byte is defined by the location of the private creator tag.
value (Any) –
The value of the data element. One of the following:
vr (str | None) – The two-letter DICOM value representation, or
None
. If set toNone
, it is taken from the private tag dictionary.
- Raises:
ValueError – If group doesn’t belong to a private tag or private_creator is empty.
KeyError – If vr is
None
and the tag is not found in the private tag dictionary.
- compress(transfer_syntax_uid: str, arr: ndarray | None = None, encoding_plugin: str = '', decoding_plugin: str = '', encapsulate_ext: bool = False, **kwargs: Any) None [source]¶
Compress and update an uncompressed dataset in-place with the resulting encapsulated pixel data.
New in version 2.2.
The dataset must already have the following Image Pixel module elements present with correct values that correspond to the resulting compressed pixel data:
(0028,0002) Samples per Pixel
(0028,0004) Photometric Interpretation
(0028,0008) Number of Frames (if more than 1 frame will be present)
(0028,0010) Rows
(0028,0011) Columns
(0028,0100) Bits Allocated
(0028,0101) Bits Stored
(0028,0103) Pixel Representation
This method will add the file meta dataset if none is present and add or modify the following elements:
(0002,0010) Transfer Syntax UID
(7FE0,0010) Pixel Data
If Samples per Pixel is greater than 1 then the following element will also be added:
(0028,0006) Planar Configuration
If the compressed pixel data is too large for encapsulation using a basic offset table then an extended offset table will also be used, in which case the following elements will also be added:
(7FE0,0001) Extended Offset Table
(7FE0,0002) Extended Offset Table Lengths
Supported Transfer Syntax UIDs
UID
Plugins
Encoding Guide
RLE Lossless - 1.2.840.10008.1.2.5
pydicom, pylibjpeg, gdcm
Examples
Compress the existing uncompressed Pixel Data in place:
>>> from pydicom import examples >>> from pydicom.uid import RLELossless >>> ds = examples.ct >>> ds.compress(RLELossless) >>> ds.save_as("ct_rle_lossless.dcm")
- Parameters:
transfer_syntax_uid (pydicom.uid.UID) – The UID of the transfer syntax to use when compressing the pixel data.
arr (numpy.ndarray, optional) – Compress the uncompressed pixel data in arr and use it to set the Pixel Data. If arr is not used then the existing Pixel Data in the dataset will be compressed instead. The
shape
,dtype
and contents of the array should match the dataset.encoding_plugin (str, optional) – Use the encoding_plugin to compress the pixel data. See the user guide for a list of plugins available for each UID and their dependencies. If not specified then all available plugins will be tried (default).
decoding_plugin (str, optional) – Placeholder for future functionality.
encapsulate_ext (bool, optional) – If
True
then force the addition of an extended offset table. IfFalse
(default) then an extended offset table will be added if needed for large amounts of compressed Pixel Data, otherwise just the basic offset table will be used.**kwargs – Optional keyword parameters for the encoding plugin may also be present. See the encoding plugins options for more information.
- convert_pixel_data(handler_name: str = '') None [source]¶
Convert pixel data to a
numpy.ndarray
internally.- Parameters:
handler_name (str, optional) – The name of the pixel handler that shall be used to decode the data. Supported names are:
'gdcm'
,'pillow'
,'jpeg_ls'
,'rle'
,'numpy'
and'pylibjpeg'
. If not used (the default), a matching handler is used from the handlers configured inpixel_data_handlers
.- Returns:
Converted pixel data is stored internally in the dataset.
- Return type:
None
- Raises:
ValueError – If handler_name is not a valid handler name.
NotImplementedError – If the given handler or any handler, if none given, is unable to decompress pixel data with the current transfer syntax
RuntimeError – If the given handler, or the handler that has been selected if none given, is not available.
Notes
If the pixel data is in a compressed image format, the data is decompressed and any related data elements are changed accordingly.
- data_element(name: str) DataElement | None [source]¶
Return the element corresponding to the element keyword name.
- Parameters:
name (str) – A DICOM element keyword.
- Returns:
For the given DICOM element keyword, return the corresponding
DataElement
if present,None
otherwise.- Return type:
dataelem.DataElement or None
- decode() None [source]¶
Apply character set decoding to the elements in the
Dataset
.See DICOM Standard, Part 5, Section 6.1.1.
- decompress(handler_name: str = '') None [source]¶
Decompresses Pixel Data and modifies the
Dataset
in-place.New in version 1.4: The handler_name keyword argument was added
If not a compressed transfer syntax, then pixel data is converted to a
numpy.ndarray
internally, but not returned.If compressed pixel data, then is decompressed using an image handler, and internal state is updated appropriately:
Dataset.file_meta.TransferSyntaxUID
is updated to non-compressed formis_undefined_length
isFalse
for the (7FE0,0010) Pixel Data element.
Changed in version 1.4: The handler_name keyword argument was added
- Parameters:
handler_name (str, optional) – The name of the pixel handler that shall be used to decode the data. Supported names are:
'gdcm'
,'pillow'
,'jpeg_ls'
,'rle'
,'numpy'
and'pylibjpeg'
. If not used (the default), a matching handler is used from the handlers configured inpixel_data_handlers
.- Return type:
None
- Raises:
NotImplementedError – If the pixel data was originally compressed but file is not Explicit VR Little Endian as required by the DICOM Standard.
- dir(*filters: str) list[str] [source]¶
Return an alphabetical list of element keywords in the
Dataset
.Intended mainly for use in interactive Python sessions. Only lists the element keywords in the current level of the
Dataset
(i.e. the contents of any sequence elements are ignored).
- elements() Iterator[DataElement] [source]¶
Yield the top-level elements of the
Dataset
.New in version 1.1.
Examples
>>> ds = Dataset() >>> for elem in ds.elements(): ... print(elem)
The elements are returned in the same way as in
Dataset.__getitem__()
.- Yields:
dataelem.DataElement or dataelem.RawDataElement – The unconverted elements sorted by increasing tag order.
- ensure_file_meta() None [source]¶
Create an empty
Dataset.file_meta
if none exists.New in version 1.2.
- fix_meta_info(enforce_standard: bool = True) None [source]¶
Ensure the file meta info exists and has the correct values for transfer syntax and media storage UIDs.
New in version 1.2.
Warning
The transfer syntax for
is_implicit_VR = False
andis_little_endian = True
is ambiguous and will therefore not be set.- Parameters:
enforce_standard (bool, optional) – If
True
, a check for incorrect and missing elements is performed (seevalidate_file_meta()
).
- formatted_lines(element_format: str = '%(tag)s %(name)-35.35s %(VR)s: %(repval)s', sequence_element_format: str = '%(tag)s %(name)-35.35s %(VR)s: %(repval)s', indent_format: str | None = None) Iterator[str] [source]¶
Iterate through the
Dataset
yielding formattedstr
for each element.- Parameters:
element_format (str) – The string format to use for non-sequence elements. Formatting uses the attributes of
DataElement
. Default is"%(tag)s %(name)-35.35s %(VR)s: %(repval)s"
.sequence_element_format (str) – The string format to use for sequence elements. Formatting uses the attributes of
DataElement
. Default is"%(tag)s %(name)-35.35s %(VR)s: %(repval)s"
indent_format (str or None) – Placeholder for future functionality.
- Yields:
str – A string representation of an element.
- classmethod from_json(json_dataset: dict[str, Any] | str | bytes | bytearray, bulk_data_uri_handler: Callable[[str, str, str], None | str | int | float | bytes] | Callable[[str], None | str | int | float | bytes] | None = None) Dataset [source]¶
Return a
Dataset
from a DICOM JSON Model object.New in version 1.3.
See the DICOM Standard, Part 18, Annex F.
- Parameters:
json_dataset (dict, str, bytes or bytearray) –
dict
,str
,bytes
orbytearray
representing a DICOM Data Set formatted based on the DICOM JSON Model.bulk_data_uri_handler (callable, optional) – Callable function that accepts either the tag, vr and “BulkDataURI” value or just the “BulkDataURI” value of the JSON representation of a data element and returns the actual value of that data element (retrieved via DICOMweb WADO-RS). If no bulk_data_uri_handler is specified (default) then the corresponding element will have an “empty” value such as
""
,b""
orNone
depending on the vr (i.e. the Value Multiplicity will be 0).
- Return type:
- get(key: str, default: Any | None = None) Any [source]¶
- get(key: int | tuple[int, int] | BaseTag, default: Any | None = None) DataElement
Simulate
dict.get()
to handle element tags and keywords.- Parameters:
- Returns:
value – If key is the keyword for an element in the
Dataset
then return the element’s value.dataelem.DataElement – If key is a tag for a element in the
Dataset
then return theDataElement
instance.value – If key is a class attribute then return its value.
- get_item(key: slice) Dataset [source]¶
- get_item(key: int | str | tuple[int, int] | BaseTag) DataElement
Return the raw data element if possible.
It will be raw if the user has never accessed the value, or set their own value. Note if the data element is a deferred-read element, then it is read and converted before being returned.
- get_private_item(group: int, element_offset: int, private_creator: str) DataElement [source]¶
Return the data element for the given private tag group.
New in version 1.3.
This is analogous to
Dataset.__getitem__()
, but only for private tags. This allows to find the private tag for the correct private creator without the need to add the tag to the private dictionary first.- Parameters:
- Returns:
The corresponding element.
- Return type:
- Raises:
ValueError – If group is not part of a private tag or private_creator is empty.
KeyError – If the private creator tag is not found in the given group. If the private tag is not found.
- group_dataset(group: int) Dataset [source]¶
Return a
Dataset
containing only elements of a certain group.
- property is_original_encoding: bool¶
Return
True
if the encoding to be used for writing is set and is the same as that used to originally encode theDataset
.New in version 1.1.
This includes properties related to endianness, VR handling and the (0008,0005) Specific Character Set.
- items() Set[tuple[BaseTag, DataElement | RawDataElement]] [source]¶
Return the
Dataset
items to simulatedict.items()
.- Returns:
The top-level (
BaseTag
,DataElement
) items for theDataset
.- Return type:
dict_items
- iterall() Iterator[DataElement] [source]¶
Iterate through the
Dataset
, yielding all the elements.Unlike
iter(Dataset)
, this does recurse into sequences, and so yields all elements as if dataset were “flattened”.- Yields:
dataelem.DataElement
- property original_character_set: str | MutableSequence[str]¶
Return the original character set encoding for a dataset decoded from a file or buffer.
- property original_encoding: tuple[bool, bool] | tuple[None, None]¶
Return the original encoding used for a dataset decoded from a file or buffer.
- overlay_array(group: int) ndarray [source]¶
Return the Overlay Data in group as a
numpy.ndarray
.New in version 1.4.
- Parameters:
group (int) – The group number of the overlay data.
- Returns:
The (group,3000) Overlay Data converted to a
numpy.ndarray
.- Return type:
- property pixel_array: ndarray¶
Return the pixel data as a
numpy.ndarray
.Changed in version 1.4: Added support for Float Pixel Data and Double Float Pixel Data
- Returns:
The (7FE0,0008) Float Pixel Data, (7FE0,0009) Double Float Pixel Data or (7FE0,0010) Pixel Data converted to a
numpy.ndarray
.- Return type:
- pop(key: BaseTag | TagType, *args: Any) DataElement | RawDataElement [source]¶
Emulate
dict.pop()
with support for tags and keywords.Removes the element for key if it exists and returns it, otherwise returns a default value if given or raises
KeyError
.- Parameters:
*args (zero or one argument) – Defines the behavior if no tag exists for key: if given, it defines the return value, if not given,
KeyError
is raised
- Returns:
The element for key if it exists, or the default value if given.
- Return type:
- Raises:
KeyError – If the key is not a valid tag or keyword. If the tag does not exist and no default is given.
- popitem() tuple[BaseTag, DataElement | RawDataElement] [source]¶
Emulate
dict.popitem()
.- Return type:
tuple of (BaseTag, DataElement)
- private_block(group: int, private_creator: str, create: bool = False) PrivateBlock [source]¶
Return the block for the given tag group and private_creator.
New in version 1.3.
If create is
True
and the private_creator does not exist, the private creator tag is added.Notes
We ignore the unrealistic case that no free block is available.
- Parameters:
group (int) – The group of the private tag to be found as a 32-bit
int
. Must be an odd number (e.g. a private group).private_creator (str) – The private creator string associated with the tag.
create (bool, optional) – If
True
and private_creator does not exist, a new private creator tag is added at the next free block. IfFalse
(the default) and private_creator does not exist,KeyError
is raised instead.
- Returns:
The existing or newly created private block.
- Return type:
- Raises:
ValueError – If group doesn’t belong to a private tag or private_creator is empty.
KeyError – If the private creator tag is not found in the given group and the create parameter is
False
.
- private_creators(group: int) list[str] [source]¶
Return a list of private creator names in the given group.
New in version 1.3.
Examples
This can be used to check if a given private creator exists in the group of the dataset:
>>> ds = Dataset() >>> if 'My Creator' in ds.private_creators(0x0041): ... block = ds.private_block(0x0041, 'My Creator')
- Parameters:
group (int) – The private group as a 32-bit
int
. Must be an odd number.- Returns:
All private creator names for private blocks in the group.
- Return type:
- Raises:
ValueError – If group is not a private group.
- property read_implicit_vr: bool | None¶
Get the VR method used by the original encoding of the dataset.
Deprecated since version 3.0:
read_implicit_vr
will be removed in v4.0, , useoriginal_encoding
instead.- Returns:
Returns
None
if the dataset has been created from scratch, otherwise returnsTrue
if the dataset was decoded from file or buffer and used implicit VR,False
if it used explicit VR.- Return type:
bool | None
- property read_little_endian: bool | None¶
Get the endianness used by the original encoding of the dataset.
Deprecated since version 3.0:
read_little_endian
will be removed in v4.0, useoriginal_encoding
instead.- Returns:
Returns
None
if the dataset has been created from scratch, otherwise returnsTrue
if the dataset was decoded from file or buffer and used little endian encoding,False
for big endian.- Return type:
bool | None
- save_as(filename: str | PathLike | BinaryIO, write_like_original: bool = True) None [source]¶
Write the
Dataset
to filename.Wrapper for pydicom.filewriter.dcmwrite, passing this dataset to it. See documentation for that function for details.
See also
pydicom.filewriter.dcmwrite
Write a DICOM file from a
FileDataset
instance.
- set_original_encoding(is_implicit_vr: bool | None, is_little_endian: bool | None, character_encoding: str | MutableSequence[str]) None [source]¶
Set the values for the original transfer syntax and encoding.
New in version 1.2.
Can be used for a
Dataset
with raw data elements to enable optimized writing (e.g. without decoding the data elements).
- setdefault(key: int | str | tuple[int, int] | BaseTag, default: Any | None = None) DataElement [source]¶
Emulate
dict.setdefault()
with support for tags and keywords.Examples
>>> ds = Dataset() >>> elem = ds.setdefault((0x0010, 0x0010), "Test") >>> elem (0010,0010) Patient's Name PN: 'Test' >>> elem.value 'Test' >>> elem = ds.setdefault('PatientSex', ... DataElement(0x00100040, 'CS', 'F')) >>> elem.value 'F'
- Parameters:
default (pydicom.dataelem.DataElement or object, optional) – The
DataElement
to use with key, or the value of theDataElement
to use with key (defaultNone
).
- Returns:
The
DataElement
for key.- Return type:
- Raises:
ValueError – If key is not convertible to a valid tag or a known element keyword.
KeyError – If
reading_validation_mode
isRAISE
and key is an unknown non-private tag.
- to_json(bulk_data_threshold: int = 1024, bulk_data_element_handler: Callable[[DataElement], str] | None = None, dump_handler: Callable[[dict[str, Any]], str] | None = None, suppress_invalid_tags: bool = False) str [source]¶
Return a JSON representation of the
Dataset
.New in version 1.3.
See the DICOM Standard, Part 18, Annex F.
- Parameters:
bulk_data_threshold (int, optional) – Threshold for the length of a base64-encoded binary data element above which the element should be considered bulk data and the value provided as a URI rather than included inline (default:
1024
). Ignored if no bulk data handler is given.bulk_data_element_handler (callable, optional) – Callable function that accepts a bulk data element and returns a JSON representation of the data element (dictionary including the “vr” key and either the “InlineBinary” or the “BulkDataURI” key).
dump_handler (callable, optional) –
Callable function that accepts a
dict
and returns the serialized (dumped) JSON string (by default usesjson.dumps()
).suppress_invalid_tags (bool, optional) – Flag to specify if errors while serializing tags should be logged and the tag dropped or if the error should be bubbled up.
- Returns:
Dataset
serialized into a string based on the DICOM JSON Model.- Return type:
Examples
>>> def my_json_dumps(data): ... return json.dumps(data, indent=4, sort_keys=True) >>> ds.to_json(dump_handler=my_json_dumps)
- to_json_dict(bulk_data_threshold: int = 1024, bulk_data_element_handler: Callable[[DataElement], str] | None = None, suppress_invalid_tags: bool = False) dict[str, Any] [source]¶
Return a dictionary representation of the
Dataset
conforming to the DICOM JSON Model as described in the DICOM Standard, Part 18, Annex F.New in version 1.4.
- Parameters:
bulk_data_threshold (int, optional) – Threshold for the length of a base64-encoded binary data element above which the element should be considered bulk data and the value provided as a URI rather than included inline (default:
1024
). Ignored if no bulk data handler is given.bulk_data_element_handler (callable, optional) – Callable function that accepts a bulk data element and returns a JSON representation of the data element (dictionary including the “vr” key and either the “InlineBinary” or the “BulkDataURI” key).
suppress_invalid_tags (bool, optional) – Flag to specify if errors while serializing tags should be logged and the tag dropped or if the error should be bubbled up.
- Returns:
Dataset
representation based on the DICOM JSON Model.- Return type:
- trait_names() list[str] [source]¶
Return a
list
of valid names for auto-completion code.Used in IPython, so that data element names can be found and offered for autocompletion on the IPython command line.
- update(d: Dataset | MutableMapping[BaseTag, DataElement | RawDataElement]) None [source]¶
Extend
dict.update()
to handle DICOM tags and keywords.
- values() ValuesView[DataElement | RawDataElement] [source]¶
Return the
Dataset
values to simulatedict.values()
.- Returns:
The
DataElements
that make up the values of theDataset
.- Return type:
dict_keys
- walk(callback: Callable[[Dataset, DataElement], None], recursive: bool = True) None [source]¶
Iterate through the
Dataset's
elements and run callback on each.Visit all elements in the
Dataset
, possibly recursing into sequences and their items. The callback function is called for eachDataElement
(including elements with a VR of ‘SQ’). Can be used to perform an operation on certain types of elements.For example,
remove_private_tags()
finds all elements with private tags and deletes them.The elements will be returned in order of increasing tag number within their current
Dataset
.- Parameters:
callback –
A callable function that takes two arguments:
a
Dataset
a
DataElement
belonging to thatDataset
recursive (bool, optional) – Flag to indicate whether to recurse into sequences (default
True
).
- waveform_array(index: int) ndarray [source]¶
Return an
ndarray
for the multiplex group at index in the (5400,0100) Waveform Sequence.New in version 2.1.
- Parameters:
index (int) – The index of the multiplex group to return the array for.
- Returns:
The Waveform Data for the multiplex group as an
ndarray
with shape (samples, channels). If (003A,0210) Channel Sensitivity is present then the values will be in the units specified by the (003A,0211) Channel Sensitivity Units Sequence.- Return type:
See also