Difference between revisions of "Python PDS4 Tools"

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m (Update for modified download URLs)
(Updated for v1.2 of pds4_tools)
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=== Download ===
=== Download ===
Download the ZIP file <span class="plainlinks">[https://pdssbn.astro.umd.edu/toolsrc/readpds_python/1.1/PDS4_tools-1.1.zip File:PDS4 tools-1.1.zip]</span>. Released on March 30, 2019.
Download the ZIP file <span class="plainlinks">[https://pdssbn.astro.umd.edu/toolsrc/readpds_python/1.2/PDS4_tools-1.2.zip File:PDS4 tools-1.2.zip]</span>. Released on October 4, 2020.
Note: A distributable version of the viewer only, which does not require Python, is [[PDS4 Viewer|available]].
Note: A distributable version of the viewer only, which does not require Python, is [[PDS4 Viewer|available]].
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==== Option 1 ====
==== Option 1 ====
Use "<tt>pip install PDS4_tools-1.1.zip</tt>"  
Use "<tt>pip install PDS4_tools-1.2.zip</tt>"  
==== Option 2 ====
==== Option 2 ====
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import sys
import sys
import pds4_tools
import pds4_tools
# The extraction_directory is the one that includes setup.py
# On a windows machine use backslashes (/) instead of windows' normal forward slashes to specify paths

Revision as of 22:38, 12 October 2020

Python and PDS4

This document describes the current status and usage of Python tools developed at PDS-SBN to read and visualize PDS4 data in Python. Please note that a PDS4 reader and visualizer for IDL is also available.

Reading and Displaying PDS4 Data


This section describes a Python package that can read and display PDS4 data and meta data. In the future this tool is expected to support all PDS4 data structures, currently support is limited to structures given in the Supported Data Structures section. The package expects valid PDS4 labels formatted according to the PDS4 Standard.

Contact Lev Nagdimunov with questions or comments regarding this code or its description.


Python 2.6+ or 3.3+

pds4_read: NumPy
pds4_viewer: NumPy, matplotlib

Supported Data Structures

PDS4 Data Standards >= v1.0 are supported.
PDS3 Data Standards are not supported.

The table below lists the main PDS4 data structures and the current status.

Read-in column indicates support by pds4_tools.read()
Display columns indicate support by pds4_tools.view().

Structure Read-in Display as Table Display as Image Display Columns as Plot
Header Yes No No No
Array Yes Yes Yes, N-dims Yes, 1-D only
Array_2D Yes Yes Yes No
Array_2D_* Yes Yes Yes No
Array_3D Yes Yes Yes No
Array_3D_* Yes Yes Yes No
Table_Character Yes Yes No Yes
Table_Binary Yes, except BitFields Yes No Yes
Table_Delimited Yes Yes No Yes
Composite_Structure No No No No

User Manual

Online usage documentation, both for scientists and for developers, is available.


Download the ZIP file File:PDS4 tools-1.2.zip. Released on October 4, 2020.

Note: A distributable version of the viewer only, which does not require Python, is available.


Option 1

Use "pip install PDS4_tools-1.2.zip"

Option 2

Extract the downloaded file to a directory Python can find. To use it follow the instructions in Example Usage except with the following lines first,

import sys

import pds4_tools

Example Usage

See also the User Manual.


Import via "import pds4_tools". You may then call pds4_tools.read() from your own code. The following is the docstring for pds4_tools.read():

        Reads PDS4 compliant data into a `StructureList`.

        Given a PDS4 label, reads the PDS4 data described in the label and
        associated label meta data into a `StructureList`, with each PDS4 data
        structure (e.g. Array_2D, Table_Binary, etc) as its own `Structure`. By
        default all data structures described in the label are immediately
        read into memory.

        Python 2 v. Python 3: Non-data strings (label, meta data, etc)  in
        Python 2 will be decoded to ``unicode`` and in Python 3 they will
        be decoded to ``str``. The return type of all data strings is
        controlled by *decode_strings*.

        Remote URLs are downloaded into an on-disk cache which is cleared on
        Python interpreter exit.

        filename : str or unicode
            The filename, including full or relative path, or a remote
            URL to the PDS4 label describing the data.
        quiet : bool, optional
            Suppresses all info/warnings from being output.
        lazy_load : bool, optional
            If True, then the data of each PDS4 data structure will not be
            read-in to memory until the first attempt to access it. Additionally,
            for remote URLs, the data is not downloaded until first access.
            Defaults to False.
        no_scale : bool, optional
            If True, returned data will be exactly as written in the data file,
            ignoring offset or scaling values. Defaults to False.
        decode_strings : bool, optional
            If True, strings data types contained in the returned data will be
            decoded to the a unicode in Python 2, and to the str type in
            Python 3. If False, leaves string types as byte strings.
            Defaults to True.

            Contains PDS4 data `Structure`'s, each of which contains the data,
            the meta data and the label portion describing that data structure.
            `StructureList` can be treated/accessed/used like a ``dict`` or


        Below we document how to read data described by an example label
        which has two data structures, an Array_2D_Image and a Table_Binary.
        An outline of the label, including the array and a table with 3
        fields, is given.

        # Local file
        >>> struct_list = pds4_tools.read('/path/to/Example_Label.xml')

        # Remote URL
        >>> struct_list = pds4_tools.read('http://url.com/Example_Label.xml')

        Example Label Outline::

           Array_2D_Image: unnamed
           Table_Binary: Observations
               Field: order
               Field: wavelength
               Group: unnamed
                   Field: pos_vector

        All below documentation assumes that the above outlined label,
        containing an array that does not have a name indicated in the label,
        and a table that has the name 'Observations' with 3 fields as shown,
        has been read-in.

        Accessing Example Structures:

            To access the data structures in `StructureList`, which is returned
            by `pds4_read()`, you may use any combination of ``dict``-like or
            ``list``-like access.

            >>> unnamed_array = struct_list[0]
            >>>              or struct_list['ARRAY_0']

            >>> obs_table = struct_list[1]
            >>>          or struct_list['Observations']

        Label or Structure Overview:

            To see a summary of the data structures, which for Arrays shows the
            type and dimensions of the array, and for Tables shows the type
            and number of fields, you may use the `StructureList.info()` method.
            Calling `Structure.info()` on a specific ``Structure`` instead will
            provide a more detailed summary, including all Fields for a table.

            >>> struct_list.info()
            >>> unnamed_array.info()
            >>> obs_table.info()

        Accessing Example Label data:

            To access the read-in data, as an array-like (subclass of ``ndarray``),
            you can use the data attribute for a PDS4 Array data structure, or
            list-like and the field() method to access a field for a table.

            PDS4 Arrays
            >>> unnamed_array.data

            PDS4 Table fields
            >>> obs_table['wavelength']
            >>> obs_table.field('wavelength')

            PDS4 Table records
            >>> obs_table[0:1000]

        Accessing Example Label meta data:

            You can access all meta data in the label for a given PDS4 data
            structure or field via the ``OrderedDict`` meta_data attribute. The
            below examples use the 'description' element.

            >>> unnamed_array.meta_data['description']

            >>> obs_table.field('wavelength').meta_data['description']
            >>> obs_table.field('pos_vector').meta_data['description']

        Accessing Example Label:

            The XML for a label is also accessible via the label attribute,
            either the entire label or for each PDS4 data structure.

            Entire label:
                >>> struct_list.label

            Part of label describing Observations table:
                >>> struct_list['Observations'].label
                >>> struct_list[1].label

            The returned object is similar to an ElementTree instance. It is
            searchable via `Label.find()` and `Label.findall()` methods and XPATH.
            Consult ``ElementTree`` manual for more details. For example,

            >>> struct_list.label.findall('.//disp:Display_Settings')

            Will find all elements in the entire label named 'Display_Settings'
            which are in the 'disp' prefix's namespace. You can additionally use the
            `Label.to_dict()` and `Label.to_string()` methods.

Usage is described above. A basic usage example is as follows:

""" Basic Reader example """

import pds4_tools

structures = pds4_tools.read('/path/to/label.xml')


0 - Array_3D_Spectrum 'table_name' (3 axes, 21 x 10 x 36)
1 - Table_Binary 'array_name' (5 fields x 1000 records)

# Table data access
table = structures['table_name'] # or
table = structures[0]


field_data = table.field('field_name') # or
field_data = table.fields[0] 

record_data = table[0:50]

# Array data access
array = structures['array_name'] # or
array = structures[1]

array_data = array.data

# Meta-data access
field_meta = table.field('field_name').meta_data # or
field_meta = table.fields[0].meta_data
array_meta = array.meta_data

print field_meta['description']
print field_meta['unit']
print array_meta['local_identifier']

# Label access
label = structures.label # Full label
label = table.label      # Label section describing the table object

display_settings = label.findall('.//disp:Display_Settings')

display_dict = display_settings.to_dict()
label_dict = label.to_dict()
label_string = label.to_string()


Import via "import pds4_tools". To display the data structures (such as images, spectra, or tables) in a label you may then call pds4_tools.view() from the Python interpreter, with or without any arguments:

    Displays PDS4 compliant data in a GUI.

    Given a PDS4 label, displays PDS4 data described in the label and
    associated label meta data in a GUI. By default all data structures described
    in the label are read-in and displayed. Can be called without any
    parameters, opening a GUI that has a File->Open function to select
    desired label to be read-in and displayed.


        filename : str, optional
            The filename, including full or relative path if necessary, of
            the PDS4 label describing the data to be viewed.
        from_existing_structures : StructureList, optional
            An existing StructureList, as returned by pds4_read(), to view. Takes
            precedence if given together with filename.
        lazy_load : bool, optional
            Do not read-in data of each data structure until attempt to view said
            data structure. Defaults to True.
        quiet : bool, optional
            If True, suppresses all info/warnings from being output and displayed.
            Defaults to False.

It is not necessary to include the filename parameter for pds4_tools.view, you may simplify call it without any options or arguments and a GUI will open from which you can open labels.

You may also call pds4_tools.view from another module or script. All the above arguments are available as optional named parameters. A basic example usage is as follows:

""" Basic Viewer example """

import pds4_tools


# or


# or 

struct_list = pds4_tools.view('label.xml')
pds4_tools.view(from_existing_structures=struct_list) # Won't re-read the data