def Func ( arg_0 , arg_1 , arg_2 , arg_3 ) : if arg_0 . many and not is_collection ( arg_1 ) : raise arg_0 . _not_expected_type ( arg_1 , Iterable , fields = [ arg_0 ] , field_names = arg_2 , arg_3 = arg_3 ) arg_4 = super ( ) . Func arg_5 = [ ] arg_6 = arg_1 if arg_0 . many else [ arg_1 ] for arg_7 , arg_8 in enumerate ( arg_6 ) : try : arg_4 ( arg_8 , arg_7 , arg_6 ) except ValidationError as err : arg_5 . append ( err . messages ) if arg_5 : arg_5 = arg_5 if arg_0 . many else arg_5 [ 0 ] raise ValidationError ( arg_5 ) return arg_1

def Func(arg_0, arg_1, arg_2, arg_3):
        """Validate if the value is of the type of the schema's model.

        Assumes the nested schema is a ``BaseSchema``.
        """
        if arg_0.many and not is_collection(arg_1):
            raise arg_0._not_expected_type(
                arg_1, Iterable, fields=[arg_0], field_names=arg_2, arg_3=arg_3)

        arg_4 = super().Func

        arg_5 = []
        arg_6 = arg_1 if arg_0.many else [arg_1]
        for arg_7, arg_8 in enumerate(arg_6):
            try:
                arg_4(arg_8, arg_7, arg_6)
            except ValidationError as err:
                arg_5.append(err.messages)

        if arg_5:
            arg_5 = arg_5 if arg_0.many else arg_5[0]
            raise ValidationError(arg_5)

        return arg_1

Validate if the value is of the type of the schema s model .


def Func ( arg_0 ) : arg_1 = { } for arg_2 , arg_3 in enumerate ( arg_0 ) : for arg_4 in [ 'success' , 'failure' , 'always' ] : arg_3 [ '{0}_backlinks' . format ( arg_4 ) ] = [ ] arg_1 [ arg_3 [ 'id' ] ] = arg_2 for arg_3 in arg_0 : for arg_4 in [ 'success' , 'failure' , 'always' ] : for arg_6 in arg_3 [ '{0}_nodes' . format ( arg_4 ) ] : arg_7 = arg_1 [ arg_6 ] arg_0 [ arg_7 ] [ '{0}_backlinks' . format ( arg_4 ) ] . append ( arg_3 [ 'id' ] ) arg_8 = [ ] for arg_3 in arg_0 : arg_9 = True for arg_4 in [ 'success' , 'failure' , 'always' ] : if arg_3 [ '{0}_backlinks' . format ( arg_4 ) ] != [ ] : arg_9 = False break if arg_9 : arg_8 . append ( arg_3 [ 'id' ] ) def branch_schema ( arg_10 ) : arg_2 = arg_1 [ arg_10 ] arg_11 = arg_0 [ arg_2 ] arg_12 = { "id" : arg_10 } for arg_13 in NODE_STANDARD_FIELDS : arg_14 = arg_11 . get ( arg_13 , None ) if arg_14 is not None : if arg_13 == 'unified_job_template' : arg_15 = arg_11 [ 'summary_fields' ] [ 'unified_job_template' ] [ 'unified_job_type' ] arg_16 = JOB_TYPES [ arg_15 ] arg_12 [ arg_16 ] = arg_14 else : arg_12 [ arg_13 ] = arg_14 for arg_4 in [ 'success' , 'failure' , 'always' ] : arg_17 = arg_11 [ '{0}_nodes' . format ( arg_4 ) ] if len ( arg_17 ) == 0 : continue arg_18 = '{0}_nodes' . format ( arg_4 ) arg_12 [ arg_18 ] = [ ] for arg_6 in arg_17 : arg_12 [ arg_18 ] . append ( branch_schema ( arg_6 ) ) return arg_12 arg_19 = [ ] for arg_20 in arg_8 : arg_19 . append ( branch_schema ( arg_20 ) ) return arg_19

def Func(arg_0):
        '''
        Takes the list results from the API in `node_results` and
        translates this data into a dictionary organized in a
        human-readable heirarchial structure
        '''
        # Build list address translation, and create backlink lists
        arg_1 = {}
        for arg_2, arg_3 in enumerate(arg_0):
            for arg_4 in ['success', 'failure', 'always']:
                arg_3['{0}_backlinks'.format(arg_4)] = []
            arg_1[arg_3['id']] = arg_2

        # Populate backlink lists
        for arg_3 in arg_0:
            for arg_4 in ['success', 'failure', 'always']:
                for arg_6 in arg_3['{0}_nodes'.format(arg_4)]:
                    arg_7 = arg_1[arg_6]
                    arg_0[arg_7]['{0}_backlinks'.format(arg_4)].append(
                        arg_3['id'])

        # Find the root nodes
        arg_8 = []
        for arg_3 in arg_0:
            arg_9 = True
            for arg_4 in ['success', 'failure', 'always']:
                if arg_3['{0}_backlinks'.format(arg_4)] != []:
                    arg_9 = False
                    break
            if arg_9:
                arg_8.append(arg_3['id'])

        # Create network dictionary recursively from root nodes
        def branch_schema(arg_10):
            arg_2 = arg_1[arg_10]
            arg_11 = arg_0[arg_2]
            arg_12 = {"id": arg_10}
            for arg_13 in NODE_STANDARD_FIELDS:
                arg_14 = arg_11.get(arg_13, None)
                if arg_14 is not None:
                    if arg_13 == 'unified_job_template':
                        arg_15 = arg_11['summary_fields'][
                            'unified_job_template']['unified_job_type']
                        arg_16 = JOB_TYPES[arg_15]
                        arg_12[arg_16] = arg_14
                    else:
                        arg_12[arg_13] = arg_14
            for arg_4 in ['success', 'failure', 'always']:
                arg_17 = arg_11['{0}_nodes'.format(arg_4)]
                if len(arg_17) == 0:
                    continue
                arg_18 = '{0}_nodes'.format(arg_4)
                arg_12[arg_18] = []
                for arg_6 in arg_17:
                    arg_12[arg_18].append(
                        branch_schema(arg_6))
            return arg_12

        arg_19 = []
        for arg_20 in arg_8:
            arg_19.append(branch_schema(arg_20))
        return arg_19

Takes the list results from the API in node_results and translates this data into a dictionary organized in a human - readable heirarchial structure


(quantity=2, separator='\n\n', wrap_start='', wrap_end='',
         html=False, sentences_quantity=3, as_list=False)

return lorem_ipsum.paragraphs(quantity=quantity, separator=separator,
                                  wrap_start=wrap_start, wrap_end=wrap_end,
                                  html=html,
                                  sentences_quantity=sentences_quantity,
                                  as_list=as_list)

def Func(arg_0=2, arg_1='\n\n', arg_2='', arg_3='',
         arg_4=False, arg_5=3, arg_6=False):
    """Return a random email text."""
    return lorem_ipsum.paragraphs(arg_0=arg_0, arg_1=arg_1,
                                  arg_2=arg_2, arg_3=arg_3,
                                  arg_4=arg_4,
                                  arg_5=arg_5,
                                  arg_6=arg_6)


def Func ( arg_0 ) : for arg_1 , arg_2 in arg_0 . STATIC_FILES : shutil . copyfile ( data_filename ( arg_1 , arg_2 ) , os . path . join ( arg_0 . directory , arg_1 ) ) if arg_0 . extra_css : shutil . copyfile ( arg_0 . config . extra_css , os . path . join ( arg_0 . directory , arg_0 . extra_css ) )

def Func(arg_0):
        """Make local instances of static files for HTML report."""
        # The files we provide must always be copied.
        for arg_1, arg_2 in arg_0.STATIC_FILES:
            shutil.copyfile(
                data_filename(arg_1, arg_2),
                os.path.join(arg_0.directory, arg_1)
                )

        # The user may have extra CSS they want copied.
        if arg_0.extra_css:
            shutil.copyfile(
                arg_0.config.extra_css,
                os.path.join(arg_0.directory, arg_0.extra_css)
                )

Make local instances of static files for HTML report .


def Func ( arg_0 , arg_1 ) : from invenio_communities . models import Community from invenio_communities . utils import save_and_validate_logo arg_2 = logo_ext_wash ( arg_0 [ 'logo_ext' ] ) arg_3 = Community ( id = arg_0 [ 'id' ] , id_user = arg_0 [ 'id_user' ] , title = arg_0 [ 'title' ] , description = arg_0 [ 'description' ] , page = arg_0 [ 'page' ] , curation_policy = arg_0 [ 'curation_policy' ] , last_record_accepted = iso2dt_or_none ( arg_0 [ 'last_record_accepted' ] ) , logo_ext = arg_2 , ranking = arg_0 [ 'ranking' ] , fixed_points = arg_0 [ 'fixed_points' ] , created = iso2dt ( arg_0 [ 'created' ] ) , updated = iso2dt ( arg_0 [ 'last_modified' ] ) , ) arg_4 = join ( arg_1 , "{0}.{1}" . format ( arg_3 . id , arg_2 ) ) db . session . add ( arg_3 ) if isfile ( arg_4 ) : with open ( arg_4 , 'rb' ) as fp : save_and_validate_logo ( fp , arg_4 , arg_3 . id ) db . session . commit ( )

def Func(arg_0, arg_1):
    """Load community from data dump.

    :param data: Dictionary containing community data.
    :type data: dict
    :param logos_dir: Path to a local directory with community logos.
    :type logos_dir: str
    """
    from invenio_communities.models import Community
    from invenio_communities.utils import save_and_validate_logo
    arg_2 = logo_ext_wash(arg_0['logo_ext'])
    arg_3 = Community(
        id=arg_0['id'],
        id_user=arg_0['id_user'],
        title=arg_0['title'],
        description=arg_0['description'],
        page=arg_0['page'],
        curation_policy=arg_0['curation_policy'],
        last_record_accepted=iso2dt_or_none(arg_0['last_record_accepted']),
        logo_ext=arg_2,
        ranking=arg_0['ranking'],
        fixed_points=arg_0['fixed_points'],
        created=iso2dt(arg_0['created']),
        updated=iso2dt(arg_0['last_modified']),
    )
    arg_4 = join(arg_1, "{0}.{1}".format(arg_3.id, arg_2))
    db.session.add(arg_3)
    if isfile(arg_4):
        with open(arg_4, 'rb') as fp:
            save_and_validate_logo(fp, arg_4, arg_3.id)
    db.session.commit()


def Func(arg_0, arg_1):
        """
        Waits until all traits are present.
        If any of the traits is still not present after timeout, raises a TimeoutException.
        """
        arg_2 = time.time() + arg_0._timeout
        arg_3 = 1
        arg_4 = None
        while True:
            arg_4 = []
            try:
                arg_4 = arg_1.evaluate_traits()
                if len(arg_4) == 0:
                    return True
                else:
                    logger.debug("#{0} - wait until all traits are present: <{1}>".format(str(arg_3), '> <'.join(
                        arg_4)))
            except arg_0._ignored_exceptions as ex:  # pragma: no cover
                logger.debug("Captured {0}: {1}".format(str(ex.__class__).replace("<type '", "").replace("'>", ""),
                                                        str(ex)))  # pragma: no cover
                pass  # pragma: no cover
            time.sleep(arg_0._poll)
            arg_3 += 1
            if time.time() > arg_2:
                break
        raise TimeoutException(
            msg="conditions " + '<' + '> <'.join(arg_4) + '>' + " not true after " + str(
                arg_0._timeout) + " seconds.")

Waits until all traits are present . If any of the traits is still not present after timeout raises a TimeoutException .


def Func(arg_0):
        """main replot function"""
        assert arg_0.min_size <= arg_0.max_size
        assert arg_0.fignum > 0
        import glob
        from bs4 import BeautifulSoup

        # parsing files.......
        try:
            arg_1 = glob.glob(arg_0.indir+'*/edb/results.edb')[0]
            arg_2 =  glob.glob(arg_0.indir+'*/edb/*.rnk')[0]
            arg_3 =  glob.glob(arg_0.indir+'*/edb/gene_sets.gmt')[0]
        except IndexError as e:
            sys.stderr.write("Could not locate GSEA files in the given directory!")
            sys.exit(1)
        # extract sample names from .cls file
        arg_4 = glob.glob(arg_0.indir+'*/edb/*.cls')
        if arg_4:
            arg_5, arg_6, arg_7 = gsea_cls_parser(arg_4[0])
        else:
            # logic for prerank results
            arg_5, arg_6 = '',''
        # start reploting
        arg_0.gene_sets=arg_3
        # obtain gene sets
        arg_9 = arg_0.parse_gmt(gmt=arg_3)
        # obtain rank_metrics
        arg_10 = arg_0._load_ranking(arg_2)
        arg_11 =  arg_10.values
        arg_12 = arg_10.index.values
        # extract each enriment term in the results.edb files and plot.
        arg_13 = BeautifulSoup(open(arg_1), features='xml')
        arg_14 = len(arg_13.findAll('DTG'))
        arg_15 = arg_0.fignum if arg_0.fignum <= arg_14 else arg_14
        for arg_16 in range(arg_15):
            # extract statistical resutls from results.edb file
            arg_17, arg_18, arg_19, arg_20, arg_21= gsea_edb_parser(arg_1, index=arg_16)
            arg_22 = arg_9.get(arg_17)
            # calculate enrichment score
            arg_23 = enrichment_score(arg_12=arg_12,
                                   arg_11=arg_11,
                                   arg_22=arg_22,
                                   weighted_score_type=arg_0.weighted_score_type,
                                   nperm=0)[-1]
            # plotting
            arg_24 = arg_17.replace('/','_').replace(":","_")
            arg_25 = '{0}/{1}.{2}.{3}'.format(arg_0.outdir, arg_24, arg_0.module, arg_0.format)
            gseaplot(arg_10=arg_10, arg_24=arg_17,
                         hits_indices=arg_18, arg_19=arg_19, arg_20=arg_20, arg_21=arg_21,
                         arg_23=arg_23, pheno_pos=arg_5, pheno_neg=arg_6,
                         figsize=arg_0.figsize, ofname=arg_25)

        arg_0._logger.info("Congratulations! Your plots have been reproduced successfully!\n")


def Func(arg_0):
    """
    Parse the pylint output-format=parseable lines into PylintError tuples.
    """
    for arg_1 in arg_0:
        if not arg_1.strip():
            continue

        if arg_1[0:5] in ("-"*5, "*"*5):
            continue

        arg_2 = PYLINT_PARSEABLE_REGEX.search(arg_1)
        if arg_2 is None:
            LOG.warning(
                u"Unable to parse %r. If this is a lint failure, please re-run pylint with the "
                u"--output-format=parseable option, otherwise, you can ignore this message.",
                arg_1
            )
            continue

        arg_3 = arg_2.groupdict()
        arg_3['linenum'] = int(arg_3['linenum'])
        yield PylintError(**arg_3)

Parse the pylint output - format = parseable lines into PylintError tuples .


def Func(arg_0, arg_1, arg_2=True):
        '''Write the given state information into a file'''
        arg_3 = arg_0._state_file
        arg_0._assure_dir()
        try:
            arg_4 = os.O_WRONLY | os.O_CREAT
            if arg_2:
                arg_4 |= os.O_EXCL
            with os.fdopen(os.open(arg_3, arg_4), "w") as f:
                yaml.safe_dump(arg_0.__base_state(arg_1), f)
        except OSError as err:
            if err.errno == errno.EEXIST:
                raise AlreadyInitializedError(
                    "Path %s exists. "
                    "You may need to destroy a previous blockade." % arg_3)
            raise
        except Exception:
            # clean up our created file
            arg_0._state_delete()
            raise


def Func(arg_0):
        """Checks if the path is correct and exists, must be abs-> a dir -> and not a file."""
        if os.path.isabs(arg_0) and os.path.isdir(arg_0) and \
                not os.path.isfile(arg_0):
            return True
        else:
            raise LocalPortValidationError(
                'Port value %s is not a valid filesystem location' % arg_0
            )

Checks if the path is correct and exists must be abs - > a dir - > and not a file .


(total_sparse_pixels, mask,
                                                          unmasked_sparse_grid_pixel_centres)

def Func(arg_0, arg_1,
                                                          arg_2):
    """Determine the mapping between every masked pixelization-grid pixel and pixelization-grid pixel. This is
    performed by checking whether each pixelization-grid pixel is within the regular-masks, and mapping the indexes.

    Parameters
    -----------
    total_sparse_pixels : int
        The total number of pixels in the pixelization grid which fall within the regular-masks.
    mask : ccd.masks.Mask
        The regular-masks within which pixelization pixels must be inside
    unmasked_sparse_grid_pixel_centres : ndarray
        The centres of the unmasked pixelization grid pixels.
    """

    arg_3 = np.zeros(arg_0)

    arg_4 = 0

    for arg_5 in range(arg_2.shape[0]):

        arg_6 = arg_2[arg_5, 0]
        arg_7 = arg_2[arg_5, 1]

        if not arg_1[arg_6, arg_7]:
            arg_3[arg_4] = arg_5
            arg_4 += 1

    return arg_3

Determine the mapping between every masked pixelization - grid pixel and pixelization - grid pixel . This is performed by checking whether each pixelization - grid pixel is within the regular - masks and mapping the indexes .


def Func ( arg_0 , arg_1 ) : makedirs ( os . path . dirname ( arg_0 . get_path ( arg_1 ) ) )

def Func(arg_0, arg_1):
        """
        Create directory and subdirectory if necessary.

        Parameters
        ----------
        tile : ``BufferedTile``
            must be member of output ``TilePyramid``
        """
        makedirs(os.path.dirname(arg_0.get_path(arg_1)))

Create directory and subdirectory if necessary .


def Func(arg_0, arg_1=0):
    """Return a 3D volume from a 4D nifti image file

    Parameters
    ----------
    filename: str
        Path to the 4D .mhd file

    vol_idx: int
        Index of the 3D volume to be extracted from the 4D volume.

    Returns
    -------
    vol, hdr
        The data array and the new 3D image header.
    """
    def remove_4th_element_from_hdr_string(arg_2, arg_3):
        if arg_3 in arg_2:
            arg_2[arg_3] = ' '.join(arg_2[arg_3].split()[:3])

    arg_4, arg_2 = load_raw_data_with_mhd(arg_0)

    if arg_4.ndim != 4:
        raise ValueError('Volume in {} does not have 4 dimensions.'.format(op.join(op.dirname(arg_0),
                                                                                arg_2['ElementDataFile'])))

    if not 0 <= arg_1 < arg_4.shape[3]:
        raise IndexError('IndexError: 4th dimension in volume {} has {} volumes, not {}.'.format(arg_0,
                                                                                arg_4.shape[3], arg_1))

    arg_5 = arg_4[:, :, :, arg_1].copy()

    arg_2['NDims'] = 3
    remove_4th_element_from_hdr_string(arg_2, 'ElementSpacing')
    remove_4th_element_from_hdr_string(arg_2, 'DimSize')

    return arg_5, arg_2


def
Func
(
arg_0
,
arg_1
,
arg_2
=
True
)
:
arg_3
=
[
]
arg_3
=
arg_0
.
validate
(
arg_3
)
if
arg_2
and
arg_3
:
raise
InvalidDocumentError
(
arg_3
)
arg_1
.
write
(
'# Document Information\n\n'
)
write_value
(
'SPDXVersion'
,
str
(
arg_0
.
version
)
,
arg_1
)
write_value
(
'DataLicense'
,
arg_0
.
data_license
.
identifier
,
arg_1
)
write_value
(
'DocumentName'
,
arg_0
.
name
,
arg_1
)
write_value
(
'SPDXID'
,
'SPDXRef-DOCUMENT'
,
arg_1
)
write_value
(
'DocumentNamespace'
,
arg_0
.
namespace
,
arg_1
)
if
arg_0
.
has_comment
:
write_text_value
(
'DocumentComment'
,
arg_0
.
comment
,
arg_1
)
for
arg_4
in
arg_0
.
ext_document_references
:
arg_5
=
' '
.
join
(
[
arg_4
.
external_document_id
,
arg_4
.
spdx_document_uri
,
arg_4
.
check_sum
.
identifier
+
':'
+
arg_4
.
check_sum
.
value
]
)
write_value
(
'ExternalDocumentRef'
,
arg_5
,
arg_1
)
write_separators
(
arg_1
)
write_creation_info
(
arg_0
.
creation_info
,
arg_1
)
write_separators
(
arg_1
)
for
arg_6
in
sorted
(
arg_0
.
reviews
)
:
write_review
(
arg_6
,
arg_1
)
write_separators
(
arg_1
)
for
arg_7
in
sorted
(
arg_0
.
annotations
)
:
write_annotation
(
arg_7
,
arg_1
)
write_separators
(
arg_1
)
write_package
(
arg_0
.
package
,
arg_1
)
write_separators
(
arg_1
)
arg_1
.
write
(
'# Extracted Licenses\n\n'
)
for
arg_8
in
sorted
(
arg_0
.
extracted_licenses
)
:
write_extracted_licenses
(
arg_8
,
arg_1
)
write_separators
(
arg_1
)

def Func(arg_0, arg_1, arg_2=True):
    """
    Write an SPDX tag value document.
    - document - spdx.document instance.
    - out - file like object that will be written to.
    Optionally `validate` the document before writing and raise
    InvalidDocumentError if document.validate returns False.
    """
    arg_3 = []
    arg_3 = arg_0.validate(arg_3)
    if arg_2 and arg_3:
        raise InvalidDocumentError(arg_3)

    # Write out document information
    arg_1.write('# Document Information\n\n')
    write_value('SPDXVersion', str(arg_0.version), arg_1)
    write_value('DataLicense', arg_0.data_license.identifier, arg_1)
    write_value('DocumentName', arg_0.name, arg_1)
    write_value('SPDXID', 'SPDXRef-DOCUMENT', arg_1)
    write_value('DocumentNamespace', arg_0.namespace, arg_1)
    if arg_0.has_comment:
        write_text_value('DocumentComment', arg_0.comment, arg_1)
    for arg_4 in arg_0.ext_document_references:
        arg_5 = ' '.join([arg_4.external_document_id,
                                arg_4.spdx_document_uri,
                                arg_4.check_sum.identifier + ':' +
                                arg_4.check_sum.value])
        write_value('ExternalDocumentRef', arg_5, arg_1)
    write_separators(arg_1)
    # Write out creation info
    write_creation_info(arg_0.creation_info, arg_1)
    write_separators(arg_1)

    # Writesorted reviews
    for arg_6 in sorted(arg_0.reviews):
        write_review(arg_6, arg_1)
        write_separators(arg_1)

    #Write sorted annotations
    for arg_7 in sorted(arg_0.annotations):
        write_annotation(arg_7, arg_1)
        write_separators(arg_1)

    # Write out package info
    write_package(arg_0.package, arg_1)
    write_separators(arg_1)

    arg_1.write('# Extracted Licenses\n\n')
    for arg_8 in sorted(arg_0.extracted_licenses):
        write_extracted_licenses(arg_8, arg_1)
        write_separators(arg_1)

Write an SPDX tag value document . - document - spdx . document instance . - out - file like object that will be written to . Optionally validate the document before writing and raise InvalidDocumentError if document . validate returns False .


def Func(arg_0):
        """
        Func instruction.

        The ID flag (bit 21) in the EFLAGS register indicates support for the
        Func instruction.  If a software procedure can set and clear this
        flag, the processor executing the procedure supports the Func
        instruction. This instruction operates the same in non-64-bit modes and
        64-bit mode.  Func returns processor identification and feature
        information in the EAX, EBX, ECX, and EDX registers.

        The instruction's output is dependent on the contents of the EAX
        register upon execution.

        :param cpu: current CPU.
        """
        # FIXME Choose conservative values and consider returning some default when eax not here
        arg_1 = {0x0: (0x0000000d, 0x756e6547, 0x6c65746e, 0x49656e69),
                0x1: (0x000306c3, 0x05100800, 0x7ffafbff, 0xbfebfbff),
                0x2: (0x76035a01, 0x00f0b5ff, 0x00000000, 0x00c10000),
                0x4: {0x0: (0x1c004121, 0x01c0003f, 0x0000003f, 0x00000000),
                      0x1: (0x1c004122, 0x01c0003f, 0x0000003f, 0x00000000),
                      0x2: (0x1c004143, 0x01c0003f, 0x000001ff, 0x00000000),
                      0x3: (0x1c03c163, 0x03c0003f, 0x00000fff, 0x00000006)},
                0x7: (0x00000000, 0x00000000, 0x00000000, 0x00000000),
                0x8: (0x00000000, 0x00000000, 0x00000000, 0x00000000),
                0xb: {0x0: (0x00000001, 0x00000002, 0x00000100, 0x00000005),
                      0x1: (0x00000004, 0x00000004, 0x00000201, 0x00000003)},
                0xd: {0x0: (0x00000000, 0x00000000, 0x00000000, 0x00000000),
                      0x1: (0x00000000, 0x00000000, 0x00000000, 0x00000000)},
                }

        if arg_0.EAX not in arg_1:
            logger.warning('Func with EAX=%x not implemented @ %x', arg_0.EAX, arg_0.PC)
            arg_0.EAX, arg_0.EBX, arg_0.ECX, arg_0.EDX = 0, 0, 0, 0
            return

        if isinstance(arg_1[arg_0.EAX], tuple):
            arg_0.EAX, arg_0.EBX, arg_0.ECX, arg_0.EDX = arg_1[arg_0.EAX]
            return

        if arg_0.ECX not in arg_1[arg_0.EAX]:
            logger.warning('Func with EAX=%x ECX=%x not implemented', arg_0.EAX, arg_0.ECX)
            arg_0.EAX, arg_0.EBX, arg_0.ECX, arg_0.EDX = 0, 0, 0, 0
            return

        arg_0.EAX, arg_0.EBX, arg_0.ECX, arg_0.EDX = arg_1[arg_0.EAX][arg_0.ECX]

CPUID instruction.

        The ID flag (bit 21) in the EFLAGS register indicates support for the
        CPUID instruction.  If a software procedure can set and clear this
        flag, the processor executing the procedure supports the CPUID
        instruction. This instruction operates the same in non-64-bit modes and
        64-bit mode.  CPUID returns processor identification and feature
        information in the EAX, EBX, ECX, and EDX registers.

        The instruction's output is dependent on the contents of the EAX
        register upon execution.

        :param cpu: current CPU.


def Func ( arg_0 , arg_1 ) : arg_2 = { 'action' : 'reject' , } arg_3 = 'milestone_requests/{}' . format ( arg_1 ) arg_4 = make_put_request ( arg_0 , arg_3 , arg_2 = arg_2 ) arg_5 = arg_4 . json ( ) if arg_4 . status_code == 200 : return arg_5 [ 'status' ] else : raise MilestoneRequestNotRejectedException ( message = arg_5 [ 'message' ] , error_code = arg_5 [ 'error_code' ] , request_id = arg_5 [ 'request_id' ] )

def Func(arg_0, arg_1):
    """
    Reject a milestone request
    """
    arg_2 = {
        'action': 'reject',
    }
    # POST /api/projects/0.1/milestone_requests/{milestone_request_id}/?action=
    # reject
    arg_3 = 'milestone_requests/{}'.format(arg_1)
    arg_4 = make_put_request(arg_0, arg_3, arg_2=arg_2)
    arg_5 = arg_4.json()
    if arg_4.status_code == 200:
        return arg_5['status']
    else:
        raise MilestoneRequestNotRejectedException(
            message=arg_5['message'],
            error_code=arg_5['error_code'],
            request_id=arg_5['request_id'])


def
Func
(
arg_0
,
arg_1
,
arg_2
,
arg_3
,
arg_4
,
arg_5
)
:
if
arg_5
==
SIMPLE
:
arg_6
=
[
i
(
arg_1
)
for
i
in
arg_0
.
HeatCapacitySolids
]
return
mixing_simple
(
arg_3
,
arg_6
)
else
:
raise
Exception
(
'Method not valid'
)

def Func(arg_0, arg_1, arg_2, arg_3, arg_4, arg_5):
        r'''Method to Func heat capacity of a solid mixture at
        temperature `T`, pressure `P`, mole fractions `zs` and weight fractions
        `ws` with a given method.

        This method has no exception handling; see `mixture_property`
        for that.

        Parameters
        ----------
        T : float
            Temperature at which to Func the property, [K]
        P : float
            Pressure at which to Func the property, [Pa]
        zs : list[float]
            Mole fractions of all species in the mixture, [-]
        ws : list[float]
            Weight fractions of all species in the mixture, [-]
        method : str
            Name of the method to use

        Returns
        -------
        Cpsm : float
            Molar heat capacity of the solid mixture at the given conditions, [J/mol]
        '''
        if arg_5 == SIMPLE:
            arg_6 = [i(arg_1) for i in arg_0.HeatCapacitySolids]
            return mixing_simple(arg_3, arg_6)
        else:
            raise Exception('Method not valid')

r'''Method to calculate heat capacity of a solid mixture at
        temperature `T`, pressure `P`, mole fractions `zs` and weight fractions
        `ws` with a given method.

        This method has no exception handling; see `mixture_property`
        for that.

        Parameters
        ----------
        T : float
            Temperature at which to calculate the property, [K]
        P : float
            Pressure at which to calculate the property, [Pa]
        zs : list[float]
            Mole fractions of all species in the mixture, [-]
        ws : list[float]
            Weight fractions of all species in the mixture, [-]
        method : str
            Name of the method to use

        Returns
        -------
        Cpsm : float
            Molar heat capacity of the solid mixture at the given conditions, [J/mol]

r Method to calculate heat capacity of a solid mixture at temperature T pressure P mole fractions zs and weight fractions ws with a given method .


def Func(arg_0):
    """Registers dynamically created preferences models for Admin interface.

    :param admin.AdminSite admin_site: AdminSite object.

    """
    global arg_5

    arg_1 = get_prefs()

    for arg_2, arg_3 in arg_1.items():

        arg_4 = get_pref_model_class(arg_2, arg_3, get_app_prefs)

        if arg_4 is not None:
            arg_5[arg_2] = arg_4
            arg_0.register(arg_4, get_pref_model_admin_class(arg_3))

Registers dynamically created preferences models for Admin interface .


def Func(arg_0, arg_1):
  """
  Get a specific item by name out of the results dict.

  The format of itemName is a string of dictionary keys separated by colons,
  each key being one level deeper into the results dict. For example,
  'key1:key2' would fetch results['key1']['key2'].

  If itemName is not found in results, then None is returned

  """

  arg_2 = arg_0.split(':')
  arg_3 = arg_1
  for arg_4 in arg_2:
    arg_3 = arg_3[arg_4]

  return arg_3

Get a specific item by name out of the results dict .


def Func(arg_0):
        """Returns boolean whether current application is Admin contrib.

        :rtype: bool
        """
        arg_1 = arg_0._Func
        if arg_1 is None:
            arg_2 = arg_0.current_page_context

            arg_3 = getattr(
                # Try from request.resolver_match.app_name
                getattr(arg_2.get('request', None), 'resolver_match', None), 'app_name',
                # Try from global context obj.
                getattr(arg_2, 'current_app', None))

            if arg_3 is None:  # Try from global context dict.
                arg_3 = arg_2.get('current_app', '')

            arg_1 = arg_3 == ADMIN_APP_NAME
            arg_0._Func = arg_1

        return arg_1

Returns boolean whether current application is Admin contrib .


def Func ( arg_0 , arg_1 = None ) : arg_2 = tempfile . TemporaryFile ( ) for arg_3 in open_json_or_csv_somehow ( arg_0 , arg_1 = arg_1 ) : arg_2 . write ( json . dumps ( arg_3 , ensure_ascii = False ) . encode ( 'utf-8' ) ) arg_2 . write ( b'\n' ) arg_2 . seek ( 0 ) return arg_2

def Func(arg_0, arg_1=None):
    """
    Read a JSON or CSV file and convert it into a JSON stream, which will
    be saved in an anonymous temp file.
    """
    arg_2 = tempfile.TemporaryFile()
    for arg_3 in open_json_or_csv_somehow(arg_0,
                                          arg_1=arg_1):
        arg_2.write(json.dumps(arg_3, ensure_ascii=False).encode('utf-8'))
        arg_2.write(b'\n')
    arg_2.seek(0)
    return arg_2

Read a JSON or CSV file and convert it into a JSON stream which will be saved in an anonymous temp file .


def Func ( ) : arg_0 = _default_client_secrets ( ) arg_1 = get_secrets_file ( ) if arg_1 is not None : arg_0 = read_json ( arg_1 ) else : from sregistry . defaults import SREGISTRY_CLIENT_SECRETS write_json ( arg_0 , SREGISTRY_CLIENT_SECRETS ) return arg_0

def Func():
    '''for private or protected registries, a client secrets file is required
       to be located at .sregistry. If no secrets are found, we use default
       of Singularity Hub, and return a dummy secrets.
    '''
    arg_0 = _default_client_secrets()

    # If token file not provided, check environment
    arg_1 = get_secrets_file()

    # If exists, load
    if arg_1 is not None:
        arg_0 = read_json(arg_1)

    # Otherwise, initialize
    else:
        from sregistry.defaults import SREGISTRY_CLIENT_SECRETS
        write_json(arg_0, SREGISTRY_CLIENT_SECRETS)

    return arg_0

for private or protected registries a client secrets file is required to be located at . sregistry . If no secrets are found we use default of Singularity Hub and return a dummy secrets .


def Func(arg_0, arg_1, arg_2, arg_3):
    """Query Func for a variant."""
    arg_4 = ("{this[chromosome]}_{this[position]}_{this[reference]}_"
                    "{this[alternative]}".format(this=arg_3))
    arg_5 = arg_1.get_variant({'_id': arg_4}) or {}
    arg_5['total'] = arg_1.case_count()

    arg_5['cases'] = []
    arg_6 = arg_3['institute']
    for arg_7 in arg_5.get('families', []):
        if arg_7 != arg_3['case_id'] and arg_7.startswith(arg_6):
            arg_8 = arg_0.variant(arg_3['variant_id'], arg_7=arg_7)
            arg_9 = arg_0.case(arg_7)
            arg_5['cases'].append(dict(case=arg_9, variant=arg_8))

    return arg_5


def Func(arg_0, arg_1, arg_2):
    """Set a value at the front of an OrderedDict

    The original dict isn't modified, instead a copy is returned
    """
    arg_3 = OrderedDict()
    arg_3[arg_1] = arg_2
    arg_3.update(arg_0)
    return arg_3


(source, destination, debug, verbose, force, config, theme, title,
          ncpu)

def Func(arg_0, arg_1, arg_2, arg_3, arg_4, arg_5, arg_6, arg_7,
          arg_8):
    """Run sigal to process a directory.

    If provided, 'source', 'destination' and 'theme' will override the
    corresponding values from the settings file.

    """
    arg_9 = ((arg_2 and logging.DEBUG) or (arg_3 and logging.INFO) or
             logging.WARNING)
    init_logging(__name__, arg_9=arg_9)
    arg_10 = logging.getLogger(__name__)

    if not os.path.isfile(arg_5):
        arg_10.error("Settings file not found: %s", arg_5)
        sys.exit(1)

    arg_11 = time.time()
    arg_12 = read_settings(arg_5)

    for arg_13 in ('source', 'destination', 'theme'):
        arg_14 = locals()[arg_13]
        if arg_14 is not None:
            arg_12[arg_13] = os.path.abspath(arg_14)
        arg_10.info("%12s : %s", arg_13.capitalize(), arg_12[arg_13])

    if not arg_12['source'] or not os.path.isdir(arg_12['source']):
        arg_10.error("Input directory not found: %s", arg_12['source'])
        sys.exit(1)

    # on windows os.path.relpath raises a ValueError if the two paths are on
    # different drives, in that case we just ignore the exception as the two
    # paths are anyway not relative
    arg_15 = True
    try:
        arg_15 = os.path.relpath(arg_12['destination'],
                                         arg_12['source']).startswith('..')
    except ValueError:
        pass

    if not arg_15:
        arg_10.error("Output directory should be outside of the input "
                     "directory.")
        sys.exit(1)

    if arg_7:
        arg_12['title'] = arg_7

    locale.setlocale(locale.LC_ALL, arg_12['locale'])
    init_plugins(arg_12)

    arg_16 = Gallery(arg_12, arg_8=arg_8)
    arg_16.Func(arg_4=arg_4)

    # copy extra files
    for arg_17, arg_18 in arg_12['files_to_copy']:
        arg_17 = os.path.join(arg_12['source'], arg_17)
        arg_18 = os.path.join(arg_12['destination'], arg_18)
        arg_10.debug('Copy %s to %s', arg_17, arg_18)
        copy(arg_17, arg_18, symlink=arg_12['orig_link'], rellink=arg_12['rel_link'])

    arg_19 = arg_16.stats

    def format_stats(arg_20):
        arg_21 = ["{} {}".format(arg_19[arg_20 + '_' + subtype], subtype)
               for subtype in ('skipped', 'failed')
               if arg_19[arg_20 + '_' + subtype] > 0]
        arg_21 = ' ({})'.format(', '.join(arg_21)) if arg_21 else ''
        return '{} {}s{}'.format(arg_19[arg_20], arg_20, arg_21)

    print('Done.\nProcessed {} and {} in {:.2f} seconds.'
          .format(format_stats('image'), format_stats('video'),
                  time.time() - arg_11))


def Func(arg_0):
        """Check scene name and whether remote file exists. Raises
        WrongSceneNameError if the scene name is wrong.
        """
        if arg_0.sceneInfo.prefix not in arg_0.__satellitesMap:
            logger.error('Google Downloader: Prefix of %s (%s) is invalid'
                % (arg_0.sceneInfo.name, arg_0.sceneInfo.prefix))
            raise WrongSceneNameError('Google Downloader: Prefix of %s (%s) is invalid'
                % (arg_0.sceneInfo.name, arg_0.sceneInfo.prefix))

Check scene name and whether remote file exists . Raises WrongSceneNameError if the scene name is wrong .


def Func ( arg_0 ) : if arg_0 . enabled : arg_0 . _vertex_list . colors = arg_0 . _gl_colors arg_0 . _vertex_list . vertices = arg_0 . _gl_vertices arg_0 . _vertex_list . Func ( pyglet . gl . GL_TRIANGLES )

def Func(arg_0):
        """Draw the shape in the current OpenGL context.

        """
        if arg_0.enabled:
            arg_0._vertex_list.colors = arg_0._gl_colors
            arg_0._vertex_list.vertices = arg_0._gl_vertices
            arg_0._vertex_list.Func(pyglet.gl.GL_TRIANGLES)

Draw the shape in the current OpenGL context .


def Func ( arg_0 , arg_1 = True ) : if WINDOWS : arg_2 = user_data_dir ( arg_0 , arg_1 = arg_1 ) elif sys . platform == "darwin" : arg_2 = user_data_dir ( arg_0 ) else : arg_2 = os . getenv ( 'XDG_CONFIG_HOME' , os . path . expanduser ( "~/.config" ) ) arg_2 = os . path . join ( arg_2 , arg_0 ) return arg_2

def Func(arg_0, arg_1=True):
    """Return full path to the user-specific config dir for this application.

        "appname" is the name of application.
            If None, just the system directory is returned.
        "roaming" (boolean, default True) can be set False to not use the
            Windows roaming appdata directory. That means that for users on a
            Windows network setup for roaming profiles, this user data will be
            sync'd on login. See
            <http://technet.microsoft.com/en-us/library/cc766489(WS.10).aspx>
            for a discussion of issues.

    Typical user data directories are:
        Mac OS X:               same as user_data_dir
        Unix:                   ~/.config/<AppName>
        Win *:                  same as user_data_dir

    For Unix, we follow the XDG spec and support $XDG_CONFIG_HOME.
    That means, by deafult "~/.config/<AppName>".
    """
    if WINDOWS:
        arg_2 = user_data_dir(arg_0, arg_1=arg_1)
    elif sys.platform == "darwin":
        arg_2 = user_data_dir(arg_0)
    else:
        arg_2 = os.getenv('XDG_CONFIG_HOME', os.path.expanduser("~/.config"))
        arg_2 = os.path.join(arg_2, arg_0)

    return arg_2

Return full path to the user - specific config dir for this application .


return sum([p * U[s1] for (p, s1) in mdp.T(s, a)])

def Func ( arg_0 , arg_1 , arg_2 , arg_3 ) : return sum ( [ arg_4 * arg_2 [ arg_5 ] for ( arg_4 , arg_5 ) in arg_3 . T ( arg_1 , arg_0 ) ] )

def Func(arg_0, arg_1, arg_2, arg_3):
    "The expected utility of doing a in state s, according to the MDP and U."
    return sum([arg_4 * arg_2[arg_5] for (arg_4, arg_5) in arg_3.T(arg_1, arg_0)])

The expected utility of doing a in state s according to the MDP and U .


def Func(arg_0: arg_1) -> int:
    """
    Simulates the actions of the stack, to check safety.

    This returns the maximum needed stack.
    """

    arg_2 = 0
    arg_3 = 0

    def _check_stack(arg_4):
        if arg_3 < 0:
            raise CompileError("Stack turned negative on instruction: {}".format(arg_4))
        if arg_3 > arg_2:
            return arg_3

    # Iterate over the bytecode.
    for arg_5 in arg_0:
        assert isinstance(arg_5, dis.Instruction)
        if arg_5.arg is not None:
            try:
                arg_6 = dis.stack_effect(arg_5.opcode, arg_5.arg)
            except ValueError as e:
                raise CompileError("Invalid opcode `{}` when compiling"
                                   .format(arg_5.opcode)) from e
        else:
            try:
                arg_6 = dis.stack_effect(arg_5.opcode)
            except ValueError as e:
                raise CompileError("Invalid opcode `{}` when compiling"
                                   .format(arg_5.opcode)) from e
        arg_3 += arg_6
        # Re-check the stack.
        arg_7 = _check_stack(arg_5)
        if arg_7:
            arg_2 = arg_7

    return arg_2

Simulates the actions of the stack to check safety .


def Func ( arg_0 , arg_1 ) : arg_1 [ 'institute' ] = arg_0 . institute ( arg_1 [ 'institute_id' ] ) arg_1 [ 'case' ] = arg_0 . case ( arg_1 [ 'case_id' ] ) arg_1 [ 'variant' ] = arg_0 . variant ( arg_1 [ 'variant_specific' ] ) arg_1 [ 'criteria' ] = { criterion [ 'term' ] : criterion for criterion in arg_1 [ 'criteria' ] } arg_1 [ 'classification' ] = ACMG_COMPLETE_MAP [ arg_1 [ 'classification' ] ] return arg_1

def Func(arg_0, arg_1):
    """Fetch and fill-in Func object."""
    arg_1['institute'] = arg_0.institute(arg_1['institute_id'])
    arg_1['case'] = arg_0.case(arg_1['case_id'])
    arg_1['variant'] = arg_0.variant(arg_1['variant_specific'])
    arg_1['criteria'] = {criterion['term']: criterion for criterion in
                                  arg_1['criteria']}
    arg_1['classification'] = ACMG_COMPLETE_MAP[arg_1['classification']]
    return arg_1


async def Func ( arg_0 , arg_1 ) : arg_2 = hangouts_pb2 . CreateConversationResponse ( ) await arg_0 . _pb_request ( 'conversations/createconversation' , arg_1 , arg_2 ) return arg_2

async def Func(arg_0, arg_1):
        """Create a new conversation."""
        arg_2 = hangouts_pb2.CreateConversationResponse()
        await arg_0._pb_request('conversations/createconversation',
                               arg_1, arg_2)
        return arg_2


def
Func
(
arg_0
,
arg_1
=
True
)
:
if
arg_0
in
ISO_REFERENCE_VALID
:
return
True
if
arg_1
:
raise
ValueError
(
"'%s' is not in '%s'"
%
(
arg_0
,
ISO_REFERENCE_VALID
)
)
return
False

def Func(arg_0, arg_1=True):
    """Helper to make sure the given character is valid for a reference number"""
    if arg_0 in ISO_REFERENCE_VALID:
        return True
    if arg_1:
        raise ValueError("'%s' is not in '%s'" % (arg_0, ISO_REFERENCE_VALID))
    return False


def Func ( arg_0 ) : arg_0 = arg_0 . encode ( 'ascii' , 'replace' ) . replace ( b'?' , b'_' ) return arg_0 . decode ( 'ascii' )

def Func(arg_0):
    """Slugify a name in the ISO-9660 way.

    Example:
        >>> slugify('épatant')
        "_patant"
    """
    arg_0 = arg_0.encode('ascii', 'replace').replace(b'?', b'_')
    return arg_0.decode('ascii')


def Func(arg_0, arg_1):
    """
    Compute the binomial PMF according to Newman and Ziff

    Helper function for :func:`canonical_averages`

    See Also
    --------

    canonical_averages

    Notes
    -----

    See Newman & Ziff, Equation (10) [10]_

    References
    ----------

    .. [10] Newman, M. E. J. & Ziff, R. M. Fast monte carlo algorithm for site
        or bond percolation. Physical Review E 64, 016706+ (2001),
        `doi:10.1103/physreve.64.016706 <http://dx.doi.org/10.1103/physreve.64.016706>`_.

    """

    arg_0 = int(arg_0)
    arg_2 = np.empty(arg_0 + 1)

    arg_3 = int(np.round(arg_1 * arg_0))

    arg_2[arg_3] = 1.0

    arg_4 = np.seterr(under='ignore')  # seterr to known value

    for arg_5 in range(arg_3 + 1, arg_0 + 1):
        arg_2[arg_5] = arg_2[arg_5 - 1] * (arg_0 - arg_5 + 1.0) / arg_5 * arg_1 / (1.0 - arg_1)

    for arg_5 in range(arg_3 - 1, -1, -1):
        arg_2[arg_5] = arg_2[arg_5 + 1] * (arg_5 + 1.0) / (arg_0 - arg_5) * (1.0 - arg_1) / arg_1

    np.seterr(**arg_4)  # reset to default

    return arg_2 / arg_2.sum()


def Func ( arg_0 , arg_1 ) : arg_2 = arg_1 . data . strip ( ) if not arg_2 : return arg_3 = urlparse ( arg_2 ) if arg_3 . scheme == "" : arg_1 . data = "http://%s" % re . sub ( r'^:?/*' , '' , arg_2 )

def Func(arg_0, arg_1):
    """Check url schema."""
    arg_2 = arg_1.data.strip()
    if not arg_2:
        return
    arg_3 = urlparse(arg_2)
    if arg_3.scheme == "":
        arg_1.data = "http://%s" % re.sub(r'^:?/*', '', arg_2)


def
Func
(
arg_0
,
arg_1
,
arg_2
,
arg_3
,
arg_4
)
:
arg_5
=
" "
*
arg_1
arg_6
=
[
arg_5
+
cell
+
arg_5
for
cell
in
arg_0
]
arg_7
=
(
arg_2
+
arg_3
.
join
(
arg_6
)
+
arg_4
)
.
rstrip
(
)
if
len
(
arg_7
)
>
TTY_COLS
:
if
not
arg_0
[
1
]
.
endswith
(
" "
)
and
not
arg_0
[
1
]
.
endswith
(
"-"
)
:
arg_8
=
" ... "
else
:
arg_8
=
""
arg_7
=
"{0}{1}{2}"
.
format
(
arg_7
[
:
TTY_COLS
len
(
arg_8
)
1
]
,
arg_8
,
arg_4
)
return
arg_7

def Func(arg_0, arg_1, arg_2, arg_3, arg_4):
    "Return a string which represents a row of data cells."

    arg_5 = " " * arg_1
    arg_6 = [arg_5 + cell + arg_5 for cell in arg_0]

    # SolveBio: we're only displaying Key-Value tuples (dimension of 2).
    #  enforce that we don't wrap lines by setting a max
    #  limit on row width which is equal to TTY_COLS (see printing)
    arg_7 = (arg_2 + arg_3.join(arg_6) + arg_4).rstrip()
    if len(arg_7) > TTY_COLS:
        if not arg_0[-1].endswith(" ") and not arg_0[-1].endswith("-"):
            arg_8 = " ... "
        else:
            arg_8 = ""
        arg_7 = "{0}{1}{2}".format(
            arg_7[:TTY_COLS - len(arg_8) - 1],
            arg_8, arg_4)

    return arg_7

Return a string which represents a row of data cells .


def Func ( arg_0 , arg_1 ) : arg_2 = bytes ( arg_0 . pubkey ) + arg_1 arg_3 = hashlib . sha256 ( arg_2 ) . digest ( ) return arg_0 . derive_from_seed ( arg_3 )

def Func(arg_0, arg_1):
        """ Derive new private key from this key and a sha256 "offset"
        """
        arg_2 = bytes(arg_0.pubkey) + arg_1
        arg_3 = hashlib.sha256(arg_2).digest()
        return arg_0.derive_from_seed(arg_3)

Derive new private key from this key and a sha256 offset


def Func(arg_0, arg_1, arg_2):
        """Retrieve the appropriate method from the Resource,
        decorate it as a click command, and return that method.
        """
        # Sanity check: Does a method exist corresponding to this
        # command? If not, None is returned for click to raise
        # exception.
        if not hasattr(arg_0.resource, arg_2):
            return None

        # Get the method.
        arg_3 = getattr(arg_0.resource, arg_2)

        # Get any attributes that were given at command-declaration
        # time.
        arg_4 = getattr(arg_3, '_cli_command_attrs', {})

        # If the help message comes from the docstring, then
        # convert it into a message specifically for this resource.
        arg_5 = inspect.getdoc(arg_3)
        arg_4['help'] = arg_0._auto_help_text(arg_5 or '')

        # On some methods, we ignore the defaults, which are intended
        # for writing and not reading; process this.
        arg_6 = arg_4.pop('ignore_defaults', False)

        # Wrap the method, such that it outputs its final return
        # value rather than returning it.
        arg_7 = arg_0._echo_method(arg_3)

        # Soft copy the "__click_params__", if any exist.
        # This is the internal holding method that the click library
        # uses to store @click.option and @click.argument directives
        # before the method is converted into a command.
        #
        # Because self._echo_method uses @functools.wraps, this is
        # actually preserved; the purpose of copying it over is
        # so we can get our resource fields at the top of the help;
        # the easiest way to do this is to load them in before the
        # conversion takes place. (This is a happy result of Armin's
        # work to get around Python's processing decorators
        # bottom-to-top.)
        arg_8 = getattr(arg_3, '__click_params__', [])
        arg_7.__click_params__ = copy(arg_8)
        arg_7 = with_global_options(arg_7)

        # Write options based on the fields available on this resource.
        arg_10 = arg_4.pop('use_fields_as_options', True)
        if arg_10:
            for arg_11 in reversed(arg_0.resource.fields):
                if not arg_11.is_option:
                    continue

                # If we got an iterable rather than a boolean,
                # then it is a list of fields to use; check for
                # presence in that list.
                if not isinstance(arg_10, bool) and arg_11.name not in arg_10:
                    continue

                # Create the initial arguments based on the
                # option value. If we have a different key to use
                # (which is what gets routed to the Tower API),
                # ensure that is the first argument.
                arg_12 = [arg_11.option]
                if arg_11.key:
                    arg_12.insert(0, arg_11.key)

                # short name aliases for common flags
                arg_13 = {
                    'name': 'n',
                    'description': 'd',
                    'inventory': 'i',
                    'extra_vars': 'e'
                }
                if arg_11.name in arg_13:
                    arg_12.append('-'+arg_13[arg_11.name])

                # Apply the option to the method.
                arg_14 = arg_11.help
                if isinstance(arg_11.type, StructuredInput):
                    arg_14 += ' Use @ to get JSON or YAML from a file.'
                if arg_11.required:
                    arg_14 = '[REQUIRED] ' + arg_14
                elif arg_11.read_only:
                    arg_14 = '[READ ONLY] ' + arg_14
                arg_14 = '[FIELD]' + arg_14
                click.option(
                    *arg_12,
                    default=arg_11.default if not arg_6 else None,
                    help=arg_14,
                    type=arg_11.type,
                    show_default=arg_11.show_default,
                    multiple=arg_11.multiple,
                    is_eager=False
                )(arg_7)

        # Make a click Command instance using this method
        # as the callback, and return it.
        arg_15 = click.command(arg_2=arg_2, cls=ActionSubcommand, **arg_4)(arg_7)

        # If this method has a `pk` positional argument,
        # then add a click argument for it.
        arg_16 = six.get_function_code(arg_3)
        if 'pk' in arg_16.co_varnames:
            click.argument('pk', nargs=1, required=False, type=str, metavar='[ID]')(arg_15)

        # Done; return the command.
        return arg_15

Retrieve the appropriate method from the Resource decorate it as a click command and return that method .


def Func ( arg_0 , arg_1 ) : arg_2 , arg_3 = arg_0 . _mode_and_encoding_for_open ( ) with open ( arg_1 , arg_2 , arg_3 = arg_3 ) as file : arg_0 . __dump_to_file ( file )

def Func(arg_0, arg_1):
        """Saves the dump in a file named `path`."""
        arg_2, arg_3 = arg_0._mode_and_encoding_for_open()
        with open(arg_1, arg_2, arg_3=arg_3) as file:
            arg_0.__dump_to_file(file)


def Func ( arg_0 , arg_1 , arg_2 = "new" ) : if not arg_0 . active : return arg_3 = CacheItem ( arg_0 . address , arg_1 , arg_0 . _item_freshness_period , arg_0 . _item_expiration_period , arg_0 . _item_purge_period , arg_2 ) arg_0 . _object_handler ( arg_3 . address , arg_3 . value , arg_3 . state ) arg_0 . cache . add_item ( arg_3 ) arg_0 . _deactivate ( )

def Func(arg_0, arg_1, arg_2 = "new"):
        """Handle a successfull retrieval and call apriopriate handler.

        Should be called when retrieval succeeds.

        Do nothing when the fetcher is not active any more (after
        one of handlers was already called).

        :Parameters:
            - `value`: fetched object.
            - `state`: initial state of the object.
        :Types:
            - `value`: any
            - `state`: `str`"""
        if not arg_0.active:
            return
        arg_3 = CacheItem(arg_0.address, arg_1, arg_0._item_freshness_period,
                arg_0._item_expiration_period, arg_0._item_purge_period, arg_2)
        arg_0._object_handler(arg_3.address, arg_3.value, arg_3.state)
        arg_0.cache.add_item(arg_3)
        arg_0._deactivate()

Handle a successfull retrieval and call apriopriate handler .


def Func ( ) : if sys . platform == 'win32' : import multiprocessing arg_0 = multiprocessing . current_process ( ) if arg_0 . name != 'MainProcess' : return arg_1 = IPControllerApp . instance ( ) arg_1 . initialize ( ) arg_1 . start ( )

def Func():
    """Create and run the IPython controller"""
    if sys.platform == 'win32':
        # make sure we don't get called from a multiprocessing subprocess
        # this can result in infinite Controllers being started on Windows
        # which doesn't have a proper fork, so multiprocessing is wonky

        # this only comes up when IPython has been installed using vanilla
        # setuptools, and *not* distribute.
        import multiprocessing
        arg_0 = multiprocessing.current_process()
        # the main process has name 'MainProcess'
        # subprocesses will have names like 'Process-1'
        if arg_0.name != 'MainProcess':
            # we are a subprocess, don't start another Controller!
            return
    arg_1 = IPControllerApp.instance()
    arg_1.initialize()
    arg_1.start()


return Session(start_time, shift_time(start_time, int(mins)))

def Func ( arg_0 , arg_1 , arg_2 ) -> Session : if arg_1 not in arg_0 . exch : return SessNA arg_3 = arg_0 . exch [ arg_1 ] [ 0 ] return Session ( arg_3 , shift_time ( arg_3 , int ( arg_2 ) ) )

def Func(arg_0, arg_1, arg_2) -> Session:
        """
        Time intervals for market open

        Args:
            session: [allday, day, am, pm, night]
            mins: mintues after open

        Returns:
            Session of start_time and end_time
        """
        if arg_1 not in arg_0.exch: return SessNA
        arg_3 = arg_0.exch[arg_1][0]
        return Session(arg_3, shift_time(arg_3, int(arg_2)))


def Func ( arg_0 , arg_1 = False , arg_2 = None ) : with tf . compat . v1 . name_scope ( arg_2 , "chi_square" , [ arg_0 ] ) : arg_0 = tf . convert_to_tensor ( value = arg_0 , arg_2 = "logu" ) arg_3 = tf . nn . softplus ( arg_0 ) - arg_0 if arg_1 : arg_3 += 0.5 * tf . math . expm1 ( arg_0 ) return arg_3

def Func(arg_0, arg_1=False, arg_2=None):
  """The Modified-GAN Csiszar-function in log-space.

  A Csiszar-function is a member of,

  ```none
  F = { f:R_+ to R : f convex }.
  ```

  When `self_normalized = True` the modified-GAN (Generative/Adversarial
  Network) Csiszar-function is:

  ```none
  f(u) = log(1 + u) - log(u) + 0.5 (u - 1)
  ```

  When `self_normalized = False` the `0.5 (u - 1)` is omitted.

  The unmodified GAN Csiszar-function is identical to Jensen-Shannon (with
  `self_normalized = False`).

  Warning: this function makes non-log-space calculations and may therefore be
  numerically unstable for `|logu| >> 0`.

  Args:
    logu: `float`-like `Tensor` representing `log(u)` from above.
    self_normalized: Python `bool` indicating whether `f'(u=1)=0`. When
      `f'(u=1)=0` the implied Csiszar f-Divergence remains non-negative even
      when `p, q` are unnormalized measures.
    name: Python `str` name prefixed to Ops created by this function.

  Returns:
    chi_square_of_u: `float`-like `Tensor` of the Csiszar-function evaluated
      at `u = exp(logu)`.
  """

  with tf.compat.v1.name_scope(arg_2, "chi_square", [arg_0]):
    arg_0 = tf.convert_to_tensor(value=arg_0, arg_2="logu")
    arg_3 = tf.nn.softplus(arg_0) - arg_0
    if arg_1:
      arg_3 += 0.5 * tf.math.expm1(arg_0)
    return arg_3

The Modified - GAN Csiszar - function in log - space .


def Func(arg_0):
    """
    Export a numpy array to a blosc array.

    Arguments:
        array: The numpy array to compress to blosc array

    Returns:
        Bytes/String. A blosc compressed array
    """
    try:
        arg_1 = blosc.pack_array(arg_0)
    except Exception as e:
        raise ValueError("Could not compress data from array. {}".format(e))

    return arg_1


def Func(arg_0, **arg_1):
        """
        Get the list of top rated movies. By default, this list will only
        include movies that have 10 or more votes. This list refreshes every
        day.

        Args:
            page: (optional) Minimum value of 1.  Expected value is an integer.
            language: (optional) ISO 639-1 code.

        Returns:
            A dict representation of the JSON returned from the API.
        """
        arg_2 = arg_0._get_path('Func')

        arg_3 = arg_0._GET(arg_2, arg_1)
        arg_0._set_attrs_to_values(arg_3)
        return arg_3

Get the list of top rated movies . By default this list will only include movies that have 10 or more votes . This list refreshes every day .


(self, actual_node, split_name, recursive=False)

def Func(arg_0, arg_1, arg_2, arg_3=False):
        """Removes a given node from the tree.

        Starts from a given node and walks recursively down the tree to the location of the node
        we want to remove.

        We need to walk from a start node in case we want to check on the way back whether we got
        empty group nodes due to deletion.

        :param actual_node: Current node

        :param split_name: DEQUE of names to get the next nodes.

        :param recursive:

            To also delete all children of a group node

        :return: True if node was deleted, otherwise False

        """

        # If the names list is empty, we have reached the node we want to delete.

        if len(arg_2) == 0:
            if arg_1.v_is_group and arg_1.f_has_children():
                if arg_3:
                    for arg_4 in list(arg_1._children.keys()):
                        arg_1.f_remove_child(arg_4, arg_3=True)
                else:
                    raise TypeError('Cannot remove group `%s` it contains children. Please '
                                    'remove with `recursive=True`.' % arg_1.v_full_name)
            arg_0._delete_node(arg_1)
            return True

        # Otherwise get the next node by using the first name in the list
        arg_5 = arg_2.popleft()

        if arg_5 in arg_1._links:
            if len(arg_2)>0:
                raise RuntimeError('You cannot remove nodes while hopping over links!')
            arg_1.f_remove_link(arg_5)
        else:
            arg_4 = arg_1._children[arg_5]

            if arg_0.Func(arg_4, arg_2, arg_3=arg_3):

                del arg_1._children[arg_5]
                if arg_5 in arg_1._groups:
                    del arg_1._groups[arg_5]
                elif arg_5 in arg_1._leaves:
                    del arg_1._leaves[arg_5]
                else:
                    raise RuntimeError('You shall not pass!')
                del arg_4
                return False


def Func(arg_0, arg_1):
        """Get responses on unix-like system. Use select to wait for output."""
        arg_2 = time.time() + arg_1
        arg_3 = []
        while True:
            arg_4 = arg_2 - time.time()
            # I prefer to not pass a negative value to select
            if arg_4 <= 0:
                arg_4 = 0
            arg_5, arg_6, arg_6 = select.select(arg_0.read_list, [], [], arg_4)
            arg_7 = None  # to avoid infinite loop if using Python 2
            try:
                for arg_8 in arg_5:
                    # new data is ready to read
                    if arg_8 == arg_0.stdout_fileno:
                        arg_0.gdb_process.stdout.flush()
                        arg_9 = arg_0.gdb_process.stdout.read()
                        arg_10 = "stdout"

                    elif arg_8 == arg_0.stderr_fileno:
                        arg_0.gdb_process.stderr.flush()
                        arg_9 = arg_0.gdb_process.stderr.read()
                        arg_10 = "stderr"

                    else:
                        raise ValueError(
                            "Developer error. Got unexpected file number %d" % arg_8
                        )

                    arg_7 = arg_0._get_responses_list(arg_9, arg_10)
                    arg_3 += arg_7

            except IOError:  # only occurs in python 2.7
                pass

            if arg_1 == 0:  # just exit immediately
                break

            elif arg_7 and arg_0._allow_overwrite_timeout_times:
                # update timeout time to potentially be closer to now to avoid lengthy wait times when nothing is being output by gdb
                arg_2 = min(
                    time.time() + arg_0.time_to_check_for_additional_output_sec,
                    arg_2,
                )

            elif time.time() > arg_2:
                break

        return arg_3

Get responses on unix - like system . Use select to wait for output .


def Func ( arg_0 , arg_1 ) : arg_0 . execute ( files . delete ( ) . where ( files . c . user_id == arg_1 ) ) arg_0 . execute ( directories . delete ( ) . where ( directories . c . user_id == arg_1 ) ) arg_0 . execute ( users . delete ( ) . where ( users . c . id == arg_1 ) )

def Func(arg_0, arg_1):
    """
    Delete a user and all of their resources.
    """
    arg_0.execute(files.delete().where(
        files.c.user_id == arg_1
    ))
    arg_0.execute(directories.delete().where(
        directories.c.user_id == arg_1
    ))
    arg_0.execute(users.delete().where(
        users.c.id == arg_1
    ))

Delete a user and all of their resources .


def Func ( arg_0 , arg_1 ) : if arg_0 . _wrapAround : return topology . wrappingNeighborhood ( arg_1 , arg_0 . _potentialRadius , arg_0 . _inputDimensions ) else : return topology . neighborhood ( arg_1 , arg_0 . _potentialRadius , arg_0 . _inputDimensions )

def Func(arg_0, arg_1):
    """
    Gets a neighborhood of inputs.

    Simply calls topology.wrappingNeighborhood or topology.neighborhood.

    A subclass can insert different topology behavior by overriding this method.

    :param centerInput (int)
    The center of the neighborhood.

    @returns (1D numpy array of integers)
    The inputs in the neighborhood.
    """
    if arg_0._wrapAround:
      return topology.wrappingNeighborhood(arg_1,
                                           arg_0._potentialRadius,
                                           arg_0._inputDimensions)
    else:
      return topology.neighborhood(arg_1,
                                   arg_0._potentialRadius,
                                   arg_0._inputDimensions)


def Func(arg_0, arg_1, arg_2, arg_3):
        """
        Make a DELETE request using the session object to a Degreed endpoint.

        Args:
            url (str): The url to send a DELETE request to.
            data (str): The json encoded payload to DELETE.
            scope (str): Must be one of the scopes Degreed expects:
                        - `CONTENT_PROVIDER_SCOPE`
                        - `COMPLETION_PROVIDER_SCOPE`
        """
        arg_0._create_session(arg_3)
        arg_4 = arg_0.session.delete(arg_1, arg_2=arg_2)
        return arg_4.status_code, arg_4.text

Make a DELETE request using the session object to a Degreed endpoint .


def Func ( arg_0 , arg_1 ) : arg_0 . reset ( ) arg_0 . push ( arg_1 ) return arg_0 . source_reset ( )

def Func(arg_0, arg_1):
        """Process and translate a cell of input.
        """
        arg_0.reset()
        arg_0.push(arg_1)
        return arg_0.source_reset()


def Func ( arg_0 ) : if arg_0 . _Func is None : arg_0 . _Func = arg_0 . Func_class ( arg_0 . context , arg_0 . session , ( arg_0 . ip , arg_0 . shell_port ) ) return arg_0 . _Func

def Func(arg_0):
        """Get the REQ socket channel object to make requests of the kernel."""
        if arg_0._Func is None:
            arg_0._Func = arg_0.Func_class(arg_0.context,
                                                         arg_0.session,
                                                         (arg_0.ip, arg_0.shell_port))
        return arg_0._Func

Get the REQ socket channel object to make requests of the kernel .


(self, node, name, context_variable, group_variable)

return ast.FunctionDef(
            name=test_name,
            args=self.takes_only_self(),
            body=list(body),
            decorator_list=[],
        )

def Func ( arg_0 , arg_1 , arg_2 , arg_3 , arg_4 ) : arg_5 = "_" . join ( [ "test" , arg_4 ] + arg_2 . split ( ) ) arg_6 = arg_0 . Func_body ( arg_1 . body , arg_3 ) return ast . FunctionDef ( arg_2 = arg_5 , args = arg_0 . takes_only_self ( ) , arg_6 = list ( arg_6 ) , decorator_list = [ ] , )

def Func(arg_0, arg_1, arg_2, arg_3, arg_4):
        """
        Transform an example node into a test method.

        Returns the unchanged node if it wasn't an ``Example``.

        ``node`` is the node object.
        ``name`` is the name of the example being described.
        ``context_variable`` is the name bound in the context manager (usually
        "test").
        ``group_variable`` is the name bound in the surrounding example group's
        context manager (usually "it").

        """

        arg_5 = "_".join(["test", arg_4] + arg_2.split())
        arg_6 = arg_0.Func_body(arg_1.body, arg_3)

        return ast.FunctionDef(
            arg_2=arg_5,
            args=arg_0.takes_only_self(),
            arg_6=list(arg_6),
            decorator_list=[],
        )

Transform an example node into a test method .


def Func ( arg_0 ) : if arg_0 . num_qubits == 1 : arg_1 = QuantumRegister ( 1 , "q" ) arg_2 = euler_angles_1q ( arg_0 . to_matrix ( ) ) arg_0 . definition = [ ( U3Gate ( * arg_2 ) , [ arg_1 [ 0 ] ] , [ ] ) ] if arg_0 . num_qubits == 2 : arg_0 . definition = two_qubit_kak ( arg_0 . to_matrix ( ) )

def Func(arg_0):
        """Calculate a subcircuit that implements this unitary."""
        if arg_0.num_qubits == 1:
            arg_1 = QuantumRegister(1, "q")
            arg_2 = euler_angles_1q(arg_0.to_matrix())
            arg_0.definition = [(U3Gate(*arg_2), [arg_1[0]], [])]
        if arg_0.num_qubits == 2:
            arg_0.definition = two_qubit_kak(arg_0.to_matrix())

Calculate a subcircuit that implements this unitary .


def Func(arg_0):
        """
        Quit the player, blocking until the process has died
        """
        if arg_0._process is None:
            logger.debug('Quit was called after self._process had already been released')
            return
        try:
            logger.debug('Quitting OMXPlayer')
            arg_1 = os.getpgid(arg_0._process.pid)
            os.killpg(arg_1, signal.SIGTERM)
            logger.debug('SIGTERM Sent to pid: %s' % arg_1)
            arg_0._process_monitor.join()
        except OSError:
            logger.error('Could not find the process to kill')

        arg_0._process = None

Quit the player blocking until the process has died


def Func ( arg_0 , ** arg_1 ) : arg_2 = arg_1 . pop ( 'ax' , None ) arg_2 = mir_eval . display . __get_axes ( arg_2 = arg_2 ) [ 0 ] arg_3 , arg_4 = arg_0 . to_interval_values ( ) arg_5 = np . unique ( [ v [ 'index' ] for v in arg_4 ] ) for arg_6 in arg_5 : arg_7 = [ i for ( i , v ) in enumerate ( arg_4 ) if v [ 'index' ] == arg_6 ] arg_8 = np . asarray ( [ arg_4 [ r ] [ 'frequency' ] for r in arg_7 ] ) arg_9 = ~ np . asarray ( [ arg_4 [ r ] [ 'voiced' ] for r in arg_7 ] ) arg_8 [ arg_9 ] *= - 1 arg_2 = mir_eval . display . pitch ( arg_3 [ arg_7 , 0 ] , arg_8 , arg_9 = True , arg_2 = arg_2 , ** arg_1 ) return arg_2

def Func(arg_0, **arg_1):
    '''Plotting wrapper for pitch contours'''
    arg_2 = arg_1.pop('ax', None)

    # If the annotation is empty, we need to construct a new axes
    arg_2 = mir_eval.display.__get_axes(arg_2=arg_2)[0]

    arg_3, arg_4 = arg_0.to_interval_values()

    arg_5 = np.unique([v['index'] for v in arg_4])

    for arg_6 in arg_5:
        arg_7 = [i for (i, v) in enumerate(arg_4) if v['index'] == arg_6]
        arg_8 = np.asarray([arg_4[r]['frequency'] for r in arg_7])
        arg_9 = ~np.asarray([arg_4[r]['voiced'] for r in arg_7])
        arg_8[arg_9] *= -1

        arg_2 = mir_eval.display.pitch(arg_3[arg_7, 0], arg_8, arg_9=True,
                                    arg_2=arg_2,
                                    **arg_1)
    return arg_2


def Func ( arg_0 , arg_1 , arg_2 ) : arg_3 = arg_2 . __len__ ( ) arg_4 = arg_0 [ 'parent_breadth_path' ] [ - 1 ] if ( arg_0 [ 'sib_seq' ] == ( arg_1 - 1 ) ) : if ( arg_4 == ( arg_3 - 1 ) ) : pass else : arg_5 = arg_4 + 1 arg_6 = arg_2 [ arg_5 ] if ( arg_6 [ 'leaf' ] ) : pass else : arg_7 = copy . deepcopy ( arg_6 [ 'path' ] ) arg_7 . append ( 0 ) arg_0 [ 'rcin_path' ] = arg_7 else : pass return ( arg_0 )

def Func(arg_0,arg_1,arg_2):
    '''
        rightCousin
        nextCousin
        rightCin
        nextCin
        rcin
        ncin

        parents are neighbors,and on the right
    '''
    arg_3 = arg_2.__len__()
    arg_4 = arg_0['parent_breadth_path'][-1]
    if(arg_0['sib_seq']==(arg_1 - 1)):
        if(arg_4==(arg_3 -1)):
            pass
        else:
            arg_5 = arg_4 + 1
            arg_6 = arg_2[arg_5]
            #because from left to right to handle each level
            #sons_count will only be updated in the next-round
            if(arg_6['leaf']):
                pass
            else:
                arg_7 = copy.deepcopy(arg_6['path'])
                arg_7.append(0)
                arg_0['rcin_path'] = arg_7
    else:
        pass
    return(arg_0)

rightCousin nextCousin rightCin nextCin rcin ncin parents are neighbors and on the right


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.
_short_opts
arg_4
=
arg_1
.
_long_opts
if
arg_0
.
short_first
:
arg_5
=
arg_3
+
arg_4
else
:
arg_5
=
arg_4
+
arg_3
return
", "
.
join
(
arg_5
)

def Func(arg_0, arg_1):
        """Return a comma-separated list of option strings & metavariables."""
        if arg_1.takes_value():
            arg_2 = arg_1.metavar or arg_1.dest.upper()
            arg_3 = [arg_0._short_opt_fmt % (sopt, arg_2)
                          for sopt in arg_1._short_opts]
            arg_4 = [arg_0._long_opt_fmt % (lopt, arg_2)
                         for lopt in arg_1._long_opts]
        else:
            arg_3 = arg_1._short_opts
            arg_4 = arg_1._long_opts

        if arg_0.short_first:
            arg_5 = arg_3 + arg_4
        else:
            arg_5 = arg_4 + arg_3

        return ", ".join(arg_5)

Return a comma - separated list of option strings & metavariables .


def Func ( arg_0 ) : try : arg_1 = json . loads ( arg_0 . query ) except ValueError : return False arg_2 = arg_0 . model_query if 'filter' in arg_1 . keys ( ) : arg_2 = arg_0 . parse_filter ( arg_1 [ 'filter' ] ) if 'sort' in arg_1 . keys ( ) : arg_2 = arg_2 . order_by ( * arg_0 . sort ( arg_1 [ 'sort' ] ) ) return arg_2

def Func(arg_0):
        """ This is the most important method """
        try:
            arg_1 = json.loads(arg_0.query)
        except ValueError:
            return False

        arg_2 = arg_0.model_query
        if 'filter'in arg_1.keys():
            arg_2 = arg_0.parse_filter(arg_1['filter'])
        if 'sort'in arg_1.keys():
            arg_2 = arg_2.order_by(*arg_0.sort(arg_1['sort']))

        return arg_2


(lower_upper, perm, rhs,
             validate_args=False,
             name=None)

def Func ( arg_0 , arg_1 , arg_2 , arg_3 = False , arg_4 = None ) : with tf . compat . v1 . name_scope ( arg_4 , 'Func' , [ arg_0 , arg_1 , arg_2 ] ) : arg_0 = tf . convert_to_tensor ( value = arg_0 , dtype_hint = tf . float32 , arg_4 = 'lower_upper' ) arg_1 = tf . convert_to_tensor ( value = arg_1 , dtype_hint = tf . int32 , arg_4 = 'perm' ) arg_2 = tf . convert_to_tensor ( value = arg_2 , dtype_hint = arg_0 . dtype , arg_4 = 'rhs' ) arg_5 = _Func_assertions ( arg_0 , arg_1 , arg_2 , arg_3 ) if arg_5 : with tf . control_dependencies ( arg_5 ) : arg_0 = tf . identity ( arg_0 ) arg_1 = tf . identity ( arg_1 ) arg_2 = tf . identity ( arg_2 ) if arg_2 . shape . ndims == 2 and arg_1 . shape . ndims == 1 : arg_6 = tf . gather ( arg_2 , arg_1 , axis = - 2 ) else : arg_7 = tf . shape ( input = arg_2 ) arg_8 = tf . broadcast_dynamic_shape ( arg_7 [ : - 2 ] , tf . shape ( input = arg_1 ) [ : - 1 ] ) arg_9 , arg_10 = arg_7 [ - 2 ] , arg_7 [ - 1 ] arg_11 = tf . concat ( [ arg_8 , [ arg_9 , arg_10 ] ] , axis = 0 ) arg_12 = tf . broadcast_to ( arg_2 , arg_11 ) arg_12 = tf . reshape ( arg_12 , [ - 1 , arg_9 , arg_10 ] ) arg_13 = tf . broadcast_to ( arg_1 , arg_11 [ : - 1 ] ) arg_13 = tf . reshape ( arg_13 , [ - 1 , arg_9 ] ) arg_14 = tf . reduce_prod ( input_tensor = arg_8 ) arg_15 = tf . broadcast_to ( tf . range ( arg_14 ) [ : , tf . newaxis ] , [ arg_14 , arg_9 ] ) arg_13 = tf . stack ( [ arg_15 , arg_13 ] , axis = - 1 ) arg_6 = tf . gather_nd ( arg_12 , arg_13 ) arg_6 = tf . reshape ( arg_6 , arg_11 ) arg_16 = tf . linalg . set_diag ( tf . linalg . band_part ( arg_0 , num_lower = - 1 , num_upper = 0 ) , tf . ones ( tf . shape ( input = arg_0 ) [ : - 1 ] , dtype = arg_0 . dtype ) ) return linear_operator_util . matrix_triangular_solve_with_broadcast ( arg_0 , linear_operator_util . matrix_triangular_solve_with_broadcast ( arg_16 , arg_6 ) , arg_16 = False )

def Func(arg_0, arg_1, arg_2,
             arg_3=False,
             arg_4=None):
  """Solves systems of linear eqns `A X = RHS`, given LU factorizations.

  Note: this function does not verify the implied matrix is actually invertible
  nor is this condition checked even when `validate_args=True`.

  Args:
    lower_upper: `lu` as returned by `tf.linalg.lu`, i.e., if
      `matmul(P, matmul(L, U)) = X` then `lower_upper = L + U - eye`.
    perm: `p` as returned by `tf.linag.lu`, i.e., if
      `matmul(P, matmul(L, U)) = X` then `perm = argmax(P)`.
    rhs: Matrix-shaped float `Tensor` representing targets for which to solve;
      `A X = RHS`. To handle vector cases, use:
      `Func(..., rhs[..., tf.newaxis])[..., 0]`.
    validate_args: Python `bool` indicating whether arguments should be checked
      for correctness. Note: this function does not verify the implied matrix is
      actually invertible, even when `validate_args=True`.
      Default value: `False` (i.e., don't validate arguments).
    name: Python `str` name given to ops managed by this object.
      Default value: `None` (i.e., "Func").

  Returns:
    x: The `X` in `A @ X = RHS`.

  #### Examples

  ```python
  import numpy as np
  import tensorflow as tf
  import tensorflow_probability as tfp

  x = [[[1., 2],
        [3, 4]],
       [[7, 8],
        [3, 4]]]
  inv_x = tfp.math.Func(*tf.linalg.lu(x), rhs=tf.eye(2))
  tf.assert_near(tf.matrix_inverse(x), inv_x)
  # ==> True
  ```

  """

  with tf.compat.v1.name_scope(arg_4, 'Func', [arg_0, arg_1, arg_2]):
    arg_0 = tf.convert_to_tensor(
        value=arg_0, dtype_hint=tf.float32, arg_4='lower_upper')
    arg_1 = tf.convert_to_tensor(value=arg_1, dtype_hint=tf.int32, arg_4='perm')
    arg_2 = tf.convert_to_tensor(
        value=arg_2, dtype_hint=arg_0.dtype, arg_4='rhs')

    arg_5 = _Func_assertions(arg_0, arg_1, arg_2, arg_3)
    if arg_5:
      with tf.control_dependencies(arg_5):
        arg_0 = tf.identity(arg_0)
        arg_1 = tf.identity(arg_1)
        arg_2 = tf.identity(arg_2)

    if arg_2.shape.ndims == 2 and arg_1.shape.ndims == 1:
      # Both rhs and perm have scalar batch_shape.
      arg_6 = tf.gather(arg_2, arg_1, axis=-2)
    else:
      # Either rhs or perm have non-scalar batch_shape or we can't determine
      # this information statically.
      arg_7 = tf.shape(input=arg_2)
      arg_8 = tf.broadcast_dynamic_shape(
          arg_7[:-2],
          tf.shape(input=arg_1)[:-1])
      arg_9, arg_10 = arg_7[-2], arg_7[-1]
      arg_11 = tf.concat([arg_8, [arg_9, arg_10]], axis=0)

      # Tile out rhs.
      arg_12 = tf.broadcast_to(arg_2, arg_11)
      arg_12 = tf.reshape(arg_12, [-1, arg_9, arg_10])

      # Tile out perm and add batch indices.
      arg_13 = tf.broadcast_to(arg_1, arg_11[:-1])
      arg_13 = tf.reshape(arg_13, [-1, arg_9])
      arg_14 = tf.reduce_prod(input_tensor=arg_8)
      arg_15 = tf.broadcast_to(
          tf.range(arg_14)[:, tf.newaxis],
          [arg_14, arg_9])
      arg_13 = tf.stack([arg_15, arg_13],
                                axis=-1)

      arg_6 = tf.gather_nd(arg_12, arg_13)
      arg_6 = tf.reshape(arg_6, arg_11)

    arg_16 = tf.linalg.set_diag(
        tf.linalg.band_part(arg_0, num_lower=-1, num_upper=0),
        tf.ones(tf.shape(input=arg_0)[:-1], dtype=arg_0.dtype))
    return linear_operator_util.matrix_triangular_solve_with_broadcast(
        arg_0,  # Only upper is accessed.
        linear_operator_util.matrix_triangular_solve_with_broadcast(
            arg_16, arg_6),
        arg_16=False)

Solves systems of linear eqns `A X = RHS`, given LU factorizations.

  Note: this function does not verify the implied matrix is actually invertible
  nor is this condition checked even when `validate_args=True`.

  Args:
    lower_upper: `lu` as returned by `tf.linalg.lu`, i.e., if
      `matmul(P, matmul(L, U)) = X` then `lower_upper = L + U - eye`.
    perm: `p` as returned by `tf.linag.lu`, i.e., if
      `matmul(P, matmul(L, U)) = X` then `perm = argmax(P)`.
    rhs: Matrix-shaped float `Tensor` representing targets for which to solve;
      `A X = RHS`. To handle vector cases, use:
      `lu_solve(..., rhs[..., tf.newaxis])[..., 0]`.
    validate_args: Python `bool` indicating whether arguments should be checked
      for correctness. Note: this function does not verify the implied matrix is
      actually invertible, even when `validate_args=True`.
      Default value: `False` (i.e., don't validate arguments).
    name: Python `str` name given to ops managed by this object.
      Default value: `None` (i.e., "lu_solve").

  Returns:
    x: The `X` in `A @ X = RHS`.

  #### Examples

  ```python
  import numpy as np
  import tensorflow as tf
  import tensorflow_probability as tfp

  x = [[[1., 2],
        [3, 4]],
       [[7, 8],
        [3, 4]]]
  inv_x = tfp.math.lu_solve(*tf.linalg.lu(x), rhs=tf.eye(2))
  tf.assert_near(tf.matrix_inverse(x), inv_x)
  # ==> True
  ```

Solves systems of linear eqns A X = RHS given LU factorizations .


(self, i, first_layer, best_layout, best_depth,
                      best_circuit, layer_list)

def Func(arg_0, arg_1, arg_2, arg_3, arg_4,
                      arg_5, arg_6):
        """Provide a DAGCircuit for a new mapped layer.

        i (int) = layer number
        first_layer (bool) = True if this is the first layer in the
            circuit with any multi-qubit gates
        best_layout (Layout) = layout returned from _layer_permutation
        best_depth (int) = depth returned from _layer_permutation
        best_circuit (DAGCircuit) = swap circuit returned
            from _layer_permutation
        layer_list (list) = list of DAGCircuit objects for each layer,
            output of DAGCircuit layers() method

        Return a DAGCircuit object to append to the output DAGCircuit
        that the _mapper method is building.
        """
        arg_7 = arg_3
        logger.debug("layer_update: layout = %s", pformat(arg_7))
        logger.debug("layer_update: self.initial_layout = %s", pformat(arg_0.initial_layout))
        arg_8 = DAGCircuit()
        for arg_9 in arg_7.get_virtual_bits().keys():
            if arg_9[0] not in arg_8.qregs.values():
                arg_8.add_qreg(arg_9[0])

        # If this is the first layer with multi-qubit gates,
        # output all layers up to this point and ignore any
        # swap gates. Set the initial layout.
        if arg_2:
            logger.debug("layer_update: first multi-qubit gate layer")
            # Output all layers up to this point
            for arg_10 in range(arg_1 + 1):
                # Make qubit edge map and extend by classical bits
                arg_11 = arg_7.combine_into_edge_map(arg_0.initial_layout)
                for arg_12 in arg_8.clbits():
                    arg_11[arg_12] = arg_12
                arg_8.compose_back(arg_6[arg_10]["graph"], arg_11)
        # Otherwise, we output the current layer and the associated swap gates.
        else:
            # Output any swaps
            if arg_4 > 0:
                logger.debug("layer_update: there are swaps in this layer, "
                             "depth %d", arg_4)
                arg_8.extend_back(arg_5)
            else:
                logger.debug("layer_update: there are no swaps in this layer")
            # Make qubit edge map and extend by classical bits
            arg_11 = arg_7.combine_into_edge_map(arg_0.initial_layout)
            for arg_12 in arg_8.clbits():
                arg_11[arg_12] = arg_12
            # Output this layer
            arg_8.compose_back(arg_6[arg_1]["graph"], arg_11)

        return arg_8

Provide a DAGCircuit for a new mapped layer .


def Func ( arg_0 ) : arg_1 = inspect . getsource ( arg_0 ) arg_2 = CommentBlocker ( ) arg_2 . process_file ( StringIO ( arg_1 ) ) arg_3 = compiler . parse ( arg_1 ) arg_4 = arg_3 . node . nodes [ 0 ] for arg_5 in arg_4 . code . nodes : if isinstance ( arg_5 , compiler . ast . Assign ) : arg_6 = arg_5 . nodes [ 0 ] . name arg_7 = unparse ( arg_5 . expr ) . strip ( ) arg_8 = strip_comment_marker ( arg_2 . search_for_comment ( arg_5 . lineno , default = '' ) ) yield arg_6 , arg_7 , arg_8

def Func(arg_0):
    """ Yield all of the documentation for trait definitions on a class object.
    """
    # FIXME: gracefully handle errors here or in the caller?
    arg_1 = inspect.getsource(arg_0)
    arg_2 = CommentBlocker()
    arg_2.process_file(StringIO(arg_1))
    arg_3 = compiler.parse(arg_1)
    arg_4 = arg_3.node.nodes[0]
    for arg_5 in arg_4.code.nodes:
        # FIXME: handle other kinds of assignments?
        if isinstance(arg_5, compiler.ast.Assign):
            arg_6 = arg_5.nodes[0].name
            arg_7 = unparse(arg_5.expr).strip()
            arg_8 = strip_comment_marker(arg_2.search_for_comment(arg_5.lineno, default=''))
            yield arg_6, arg_7, arg_8

Yield all of the documentation for trait definitions on a class object .


return ExecutionPlan(pipeline_def, step_dict, deps, artifacts_persisted)

def Func ( arg_0 , arg_1 , arg_2 ) : arg_3 = { arg_4 . key : set ( ) for arg_4 in arg_0 . steps } for arg_4 in arg_0 . steps : for arg_5 in arg_4 . step_inputs : arg_3 [ arg_4 . key ] . add ( arg_5 . prev_output_handle . step_key ) arg_6 = { arg_4 . key : arg_4 for arg_4 in arg_0 . steps } return ExecutionPlan ( arg_1 , arg_6 , arg_3 , arg_2 )

def Func(arg_0, arg_1, arg_2):
        '''Builds the execution plan.
        '''

        # Construct dependency dictionary
        arg_3 = {arg_4.key: set() for arg_4 in arg_0.steps}

        for arg_4 in arg_0.steps:
            for arg_5 in arg_4.step_inputs:
                arg_3[arg_4.key].add(arg_5.prev_output_handle.step_key)

        arg_6 = {arg_4.key: arg_4 for arg_4 in arg_0.steps}

        return ExecutionPlan(arg_1, arg_6, arg_3, arg_2)


def Func ( arg_0 ) : arg_1 = [ ] for arg_2 in arg_0 : if isinstance ( arg_2 , bool ) : arg_1 . append ( { 'type' : ContractParameterTypes . BOOLEAN . value , 'value' : arg_2 } ) elif isinstance ( arg_2 , int ) : arg_1 . append ( { 'type' : ContractParameterTypes . INTEGER . value , 'value' : arg_2 } ) elif is_hash256 ( arg_2 ) : arg_1 . append ( { 'type' : ContractParameterTypes . HASH256 . value , 'value' : arg_2 } ) elif is_hash160 ( arg_2 ) : arg_1 . append ( { 'type' : ContractParameterTypes . HASH160 . value , 'value' : arg_2 } ) elif isinstance ( arg_2 , bytearray ) : arg_1 . append ( { 'type' : ContractParameterTypes . BYTE_ARRAY . value , 'value' : arg_2 } ) elif isinstance ( arg_2 , str ) : arg_1 . append ( { 'type' : ContractParameterTypes . STRING . value , 'value' : arg_2 } ) elif isinstance ( arg_2 , list ) : arg_3 = Func ( arg_2 ) arg_1 . append ( { 'type' : ContractParameterTypes . ARRAY . value , 'value' : arg_3 } ) return arg_1

def Func(arg_0):
    """ Returns a list of paramaters meant to be passed to JSON-RPC endpoints. """
    arg_1 = []
    for arg_2 in arg_0:
        if isinstance(arg_2, bool):
            arg_1.append({'type': ContractParameterTypes.BOOLEAN.value, 'value': arg_2})
        elif isinstance(arg_2, int):
            arg_1.append({'type': ContractParameterTypes.INTEGER.value, 'value': arg_2})
        elif is_hash256(arg_2):
            arg_1.append({'type': ContractParameterTypes.HASH256.value, 'value': arg_2})
        elif is_hash160(arg_2):
            arg_1.append({'type': ContractParameterTypes.HASH160.value, 'value': arg_2})
        elif isinstance(arg_2, bytearray):
            arg_1.append({'type': ContractParameterTypes.BYTE_ARRAY.value, 'value': arg_2})
        elif isinstance(arg_2, str):
            arg_1.append({'type': ContractParameterTypes.STRING.value, 'value': arg_2})
        elif isinstance(arg_2, list):
            arg_3 = Func(arg_2)
            arg_1.append({'type': ContractParameterTypes.ARRAY.value, 'value': arg_3})
    return arg_1

Returns a list of paramaters meant to be passed to JSON - RPC endpoints .


def Func ( arg_0 , arg_1 ) : arg_2 = [ ] if arg_0 : for arg_3 in arg_0 . split ( ',' ) : arg_4 = arg_3 . split ( ':' ) if arg_4 [ 0 ] == arg_1 : arg_2 = arg_4 [ 1 ] . split ( '|' ) return arg_2

def Func(arg_0, arg_1):
    """Parse the genetic models entry of a vcf

    Args:
        models_info(str): The raw vcf information
        case_id(str)

    Returns:
        genetic_models(list)

    """
    arg_2 = []
    if arg_0:
        for arg_3 in arg_0.split(','):
            arg_4 = arg_3.split(':')
            if arg_4[0] == arg_1:
                arg_2 = arg_4[1].split('|')

    return arg_2


def Func(arg_0, arg_1, arg_2=None):
    """Run a Kalman smoother to return posterior mean and cov.

    Note that the returned values `smoothed_means` depend on the observed
    time series `x`, while the `smoothed_covs` are independent
    of the observed series; i.e., they depend only on the model itself.
    This means that the mean values have shape `concat([sample_shape(x),
    batch_shape, [num_timesteps, {latent/observation}_size]])`,
    while the covariances have shape `concat[(batch_shape, [num_timesteps,
    {latent/observation}_size, {latent/observation}_size]])`, which
    does not depend on the sample shape.

    This function only performs smoothing. If the user wants the
    intermediate values, which are returned by filtering pass `forward_filter`,
    one could get it by:
    ```
    (log_likelihoods,
     filtered_means, filtered_covs,
     predicted_means, predicted_covs,
     observation_means, observation_covs) = model.forward_filter(x)
    smoothed_means, smoothed_covs = model.backward_smoothing_pass(x)
    ```
    where `x` is an observation sequence.

    Args:
      x: a float-type `Tensor` with rightmost dimensions
        `[num_timesteps, observation_size]` matching
        `self.event_shape`. Additional dimensions must match or be
        broadcastable to `self.batch_shape`; any further dimensions
        are interpreted as a sample shape.
      mask: optional bool-type `Tensor` with rightmost dimension
        `[num_timesteps]`; `True` values specify that the value of `x`
        at that timestep is masked, i.e., not conditioned on. Additional
        dimensions must match or be broadcastable to `self.batch_shape`; any
        further dimensions must match or be broadcastable to the sample
        shape of `x`.
        Default value: `None`.

    Returns:
      smoothed_means: Means of the per-timestep smoothed
         distributions over latent states, p(x_{t} | x_{:T}), as a
         Tensor of shape `sample_shape(x) + batch_shape +
         [num_timesteps, observation_size]`.
      smoothed_covs: Covariances of the per-timestep smoothed
         distributions over latent states, p(x_{t} | x_{:T}), as a
         Tensor of shape `sample_shape(mask) + batch_shape + [num_timesteps,
         observation_size, observation_size]`. Note that the covariances depend
         only on the model and the mask, not on the data, so this may have fewer
         dimensions than `filtered_means`.
    """

    with tf.name_scope("smooth"):
      arg_1 = tf.convert_to_tensor(value=arg_1, name="x")
      (arg_3, arg_4, arg_5,
       arg_6, arg_7, arg_3, arg_3) = arg_0.forward_filter(
           arg_1, arg_2=arg_2)

      (arg_8, arg_9) = arg_0.backward_smoothing_pass(
          arg_4, arg_5,
          arg_6, arg_7)

      return (arg_8, arg_9)

Run a Kalman smoother to return posterior mean and cov .


(node: BaseEntity, namespaces: Set[str])

return ns is not None and ns in namespaces

def Func ( arg_0 : arg_1 , arg_2 : arg_3 [ arg_4 ] ) -> bool : arg_5 = arg_0 . get ( NAMESPACE ) return arg_5 is not None and arg_5 in arg_2

def Func(arg_0: arg_1, arg_2: arg_3[arg_4]) -> bool:
    """Pass for nodes that have one of the given namespaces."""
    arg_5 = arg_0.get(NAMESPACE)
    return arg_5 is not None and arg_5 in arg_2

Pass for nodes that have one of the given namespaces .


def Func ( arg_0 , arg_1 ) : with arg_0 . ws_Funclock : arg_0 . ws . Func ( json . dumps ( arg_1 ) )

def Func(arg_0, arg_1):
        """Send the given command thru the websocket"""
        with arg_0.ws_Funclock:
            arg_0.ws.Func(json.dumps(arg_1))


def Func ( arg_0 , arg_1 ) : arg_2 = { "text/csv" : arg_0 . _render_as_csv , "text/html" : arg_0 . _render_as_html , None : arg_0 . _render_as_html , } Func = arg_2 [ arg_1 . content_type ] return Func ( arg_1 )

def Func(arg_0, arg_1):
        ''' Renders the reports based on data.content_type's value.

        Arguments:
            data (ReportViewRequestData): The report data. data.content_type
                is used to determine how the reports are rendered.

        Returns:
            HTTPResponse: The rendered version of the report.

        '''
        arg_2 = {
            "text/csv": arg_0._render_as_csv,
            "text/html": arg_0._render_as_html,
            None: arg_0._render_as_html,
        }
        Func = arg_2[arg_1.content_type]
        return Func(arg_1)

Renders the reports based on data . content_type s value .


def Func(arg_0, arg_1):
        """ Send a message object

            :type message: data.OutgoingMessage
            :param message: The message to Func
            :rtype: data.OutgoingMessage
            :returns: The sent message with populated fields
            :raises AssertionError: wrong provider name encountered (returned by the router, or provided to OutgoingMessage)
            :raises MessageSendError: generic errors
            :raises AuthError: provider authentication failed
            :raises LimitsError: Funcing limits exceeded
            :raises CreditError: not enough money on the account
        """
        # Which provider to use?
        arg_2 = arg_0._default_provider  # default
        if arg_1.provider is not None:
            assert arg_1.provider in arg_0._providers, \
                'Unknown provider specified in OutgoingMessage.provideer: {}'.format(arg_2)
            arg_3 = arg_0.get_provider(arg_1.provider)
        else:
            # Apply routing
            if arg_1.routing_values is not None: # Use the default provider when no routing values are given
                # Routing values are present
                arg_2 = arg_0.router(arg_1, *arg_1.routing_values) or arg_0._default_provider
                assert arg_2 in arg_0._providers, \
                    'Routing function returned an unknown provider name: {}'.format(arg_2)
            arg_3 = arg_0.get_provider(arg_2)

        # Set message provider name
        arg_1.provider = arg_3.name

        # Send the message using the provider
        arg_1 = arg_3.Func(arg_1)

        # Emit the Func event
        arg_0.onSend(arg_1)

        # Finish
        return arg_1

Send a message object

            :type message: data.OutgoingMessage
            :param message: The message to send
            :rtype: data.OutgoingMessage
            :returns: The sent message with populated fields
            :raises AssertionError: wrong provider name encountered (returned by the router, or provided to OutgoingMessage)
            :raises MessageSendError: generic errors
            :raises AuthError: provider authentication failed
            :raises LimitsError: sending limits exceeded
            :raises CreditError: not enough money on the account


def
Func
(
*
arg_0
)
:
if
arg_0
and
isinstance
(
arg_0
[
0
]
,
dataframe
.
DataFrame
)
:
return
arg_0
[
0
]
.
Func
(
*
arg_0
[
1
:
]
)
elif
not
arg_0
:
raise
ValueError
(
"No arguments provided"
)
else
:
return
pipeable
.
Pipeable
(
pipeable
.
PipingMethod
.
SUBSET
,
*
arg_0
)

def Func(*arg_0):
    """
    Pipeable Functing method.

    Takes either
     - a dataframe and a tuple of arguments required for Functing,
     - a tuple of arguments if a dataframe has already been piped into.

    :Example:

    Func(dataframe, "column")

    :Example:

    dataframe >> Func("column")

    :param args: tuple of arguments
    :type args: tuple
    :return: returns a dataframe object
    :rtype: DataFrame
    """

    if arg_0 and isinstance(arg_0[0], dataframe.DataFrame):
        return arg_0[0].Func(*arg_0[1:])
    elif not arg_0:
        raise ValueError("No arguments provided")
    else:
        return pipeable.Pipeable(pipeable.PipingMethod.SUBSET, *arg_0)

Pipeable subsetting method.

    Takes either
     - a dataframe and a tuple of arguments required for subsetting,
     - a tuple of arguments if a dataframe has already been piped into.

    :Example:

    subset(dataframe, "column")

    :Example:

    dataframe >> subset("column")

    :param args: tuple of arguments
    :type args: tuple
    :return: returns a dataframe object
    :rtype: DataFrame


def Func ( arg_0 , arg_1 = None ) : _print ( arg_0 , sys . stdout , log_func = arg_1 . info if arg_1 else None )

def Func(arg_0, arg_1=None):
    """Print 'msg' to stdout, and option 'log' at info level."""
    _print(arg_0, sys.stdout, log_func=arg_1.info if arg_1 else None)

Print msg to stdout and option log at info level .


(obj, param_name, key_type=None, value_type=None)

return _check_key_value_types(obj, key_type, value_type)

def Func ( arg_0 , arg_1 , arg_2 = None , arg_3 = None ) : if not isinstance ( arg_0 , dict ) : raise_with_traceback ( _param_type_mismatch_exception ( arg_0 , dict , arg_1 ) ) if not ( arg_2 or arg_3 ) : return arg_0 return _check_key_value_types ( arg_0 , arg_2 , arg_3 )

def Func(arg_0, arg_1, arg_2=None, arg_3=None):
    '''Ensures argument obj is a native Python dictionary, raises an exception if not, and otherwise
    returns obj.
    '''
    if not isinstance(arg_0, dict):
        raise_with_traceback(_param_type_mismatch_exception(arg_0, dict, arg_1))

    if not (arg_2 or arg_3):
        return arg_0

    return _check_key_value_types(arg_0, arg_2, arg_3)

Ensures argument obj is a native Python dictionary raises an exception if not and otherwise returns obj .


return image if (image.mode == mode) else image.convert(mode=mode)

def Func ( arg_0 , arg_1 = 'RGB' ) : deprecated . deprecated ( 'util.gif.Funcl' ) return arg_0 if ( arg_0 . mode == arg_1 ) else arg_0 . convert ( arg_1 = arg_1 )

def Func(arg_0, arg_1='RGB'):
    """Return an image in the given mode."""
    deprecated.deprecated('util.gif.Funcl')

    return arg_0 if (arg_0.mode == arg_1) else arg_0.convert(arg_1=arg_1)


def Func(arg_0, *arg_1):
        """
        Register monitors they should be tuple of name and Theano variable.
        """
        for arg_2, arg_3 in arg_1:
            if arg_2 not in arg_0._registered_monitors:
                arg_3 *= 1.0 # Avoid CudaNdarray
                arg_0.training_monitors.append((arg_2, arg_3))
                arg_0.testing_monitors.append((arg_2, arg_3))
                arg_0._registered_monitors.add(arg_2)

Register monitors they should be tuple of name and Theano variable .


def Func(arg_0, arg_1, arg_2=[]):
        """
        Cleanup the repo
        """

        # Clean up the rootdir
        arg_3 = arg_1.rootdir
        if os.path.exists(arg_3):
            print("Cleaning repo directory: {}".format(arg_3))
            shutil.rmtree(arg_3)

        # Cleanup the local version of the repo (this could be on
        # the server etc.
        arg_4 = arg_0.server_rootdir_from_repo(arg_1,
                                                       create=False)
        if os.path.exists(arg_4):
            print("Cleaning data from local git 'server': {}".format(arg_4))
            shutil.rmtree(arg_4)

        super(GitRepoManager, arg_0).Func(arg_1)

        return {
            'status': 'success',
            'message': "successful cleanup"
        }


return (before, item, after) if item else (after, item, before)

def Func(arg_0):
	"""
	Given a partition_dict result, if the partition missed, swap
	the before and after.
	"""
	arg_1, arg_2, arg_3 = arg_0
	return (arg_1, arg_2, arg_3) if arg_2 else (arg_3, arg_2, arg_1)

Given a partition_dict result if the partition missed swap the before and after .


def Func():
    """Return system per-CPU times as a list of named tuples."""
    arg_0 = []
    for arg_1 in _psutil_mswindows.get_system_cpu_times():
        arg_2, arg_3, arg_4 = arg_1
        arg_5 = _cputimes_ntuple(arg_2, arg_3, arg_4)
        arg_0.append(arg_5)
    return arg_0

Return system per - CPU times as a list of named tuples .


def Func(arg_0, arg_1, arg_2):
        """
        Query the enrollment API to get information about a single course enrollment.

        Args:
            username (str): The username by which the user goes on the OpenEdX platform
            course_id (str): The string value of the course's unique identifier

        Returns:
            dict: A dictionary containing details of the enrollment, including course details, mode, username, etc.

        """
        arg_3 = getattr(
            arg_0.client.enrollment,
            '{username},{course_id}'.format(arg_1=arg_1, arg_2=arg_2)
        )
        try:
            arg_4 = arg_3.get()
        except HttpNotFoundError:
            # This enrollment data endpoint returns a 404 if either the username or course_id specified isn't valid
            LOGGER.error(
                'Course enrollment details not found for invalid username or course; username=[%s], course=[%s]',
                arg_1,
                arg_2
            )
            return None
        # This enrollment data endpoint returns an empty string if the username and course_id is valid, but there's
        # no matching enrollment found
        if not arg_4:
            LOGGER.info('Failed to find course enrollment details for user [%s] and course [%s]', arg_1, arg_2)
            return None

        return arg_4

Query the enrollment API to get information about a single course enrollment .


def Func ( arg_0 , arg_1 ) : if arg_1 . startswith ( "http" ) : return arg_1 return "{0}{1}" . format ( arg_0 . server_url , arg_1 )

def Func(arg_0, arg_1):
        """
        Ensures that the request url is valid.
        Sometimes we have URLs that the server gives that are preformatted,
        sometimes we need to form our own.
        """
        if arg_1.startswith("http"):
            return arg_1
        return "{0}{1}".format(arg_0.server_url, arg_1)

Ensures that the request url is valid . Sometimes we have URLs that the server gives that are preformatted sometimes we need to form our own .


_rem_id_from_index - Removes an id from an index
			internal

(self, indexedField, pk, val, conn=None)

def Func(arg_0, arg_1, arg_2, arg_3, arg_4=None):
		'''
			Func - Removes an id from an index
			internal
		'''
		if arg_4 is None:
			arg_4 = arg_0._get_connection()
		arg_4.srem(arg_0._get_key_for_index(arg_1, arg_3), arg_2)


return (
        Maybe(v.meta)
        .map(lambda m: m.entry(SYM_MACRO_META_KEY, None))  # type: ignore
        .or_else_get(False)
    )

def Func ( arg_0 : arg_1 ) -> bool : return ( Maybe ( arg_0 . meta ) . map ( lambda m : m . entry ( SYM_MACRO_META_KEY , None ) ) . or_else_get ( False ) )

def Func(arg_0: arg_1) -> bool:
    """Return True if the Var holds a macro function."""
    return (
        Maybe(arg_0.meta)
        .map(lambda m: m.entry(SYM_MACRO_META_KEY, None))  # type: ignore
        .or_else_get(False)
    )

Return True if the Var holds a macro function .