signature
stringlengths 29
44.1k
| implementation
stringlengths 0
85.2k
|
|---|---|
def progression_linear ( week , start_weight , final_weight , start_week , end_week ) :
"""A linear progression function going through the points
( ' start _ week ' , ' start _ weight ' ) and ( ' end _ week ' , ' final _ weight ' ) , evaluated
in ' week ' .
Parameters
week
The week to evaluate the linear function at .
start _ weight
The weight at ' start _ week ' .
final _ weight
The weight at ' end _ week ' .
start _ week
The number of the first week , typically 1.
end _ week
The number of the final week , e . g . 8.
Returns
weight
The weight at ' week ' .
Examples
> > > progression _ linear ( week = 2 , start _ weight = 100 , final _ weight = 120,
. . . start _ week = 1 , end _ week = 3)
110.0
> > > progression _ linear ( 3 , 100 , 140 , 1 , 5)
120.0""" | # Calculate the slope of the linear function
slope = ( start_weight - final_weight ) / ( start_week - end_week )
# Return the answer y = slope ( x - x _ 0 ) + y _ 0
return slope * ( week - start_week ) + start_weight |
def _replace_image ( image_url , image_tag , ebook_folder , image_name = None ) :
"""Replaces the src of an image to link to the local copy in the images folder of the ebook . Tightly coupled with bs4
package .
Args :
image _ url ( str ) : The url of the image .
image _ tag ( bs4 . element . Tag ) : The bs4 tag containing the image .
ebook _ folder ( str ) : The directory where the ebook files are being saved . This must contain a subdirectory
called " images " .
image _ name ( Option [ str ] ) : The short name to save the image as . Should not contain a directory or an extension .""" | try :
assert isinstance ( image_tag , bs4 . element . Tag )
except AssertionError :
raise TypeError ( "image_tag cannot be of type " + str ( type ( image_tag ) ) )
if image_name is None :
image_name = str ( uuid . uuid4 ( ) )
try :
image_full_path = os . path . join ( ebook_folder , 'images' )
assert os . path . exists ( image_full_path )
image_extension = save_image ( image_url , image_full_path , image_name )
image_tag [ 'src' ] = 'images' + '/' + image_name + '.' + image_extension
except ImageErrorException :
image_tag . decompose ( )
except AssertionError :
raise ValueError ( '%s doesn\'t exist or doesn\'t contain a subdirectory images' % ebook_folder )
except TypeError :
image_tag . decompose ( ) |
def multi_layer_feature ( body , from_layers , num_filters , strides , pads , min_filter = 128 ) :
"""Wrapper function to extract features from base network , attaching extra
layers and SSD specific layers
Parameters
from _ layers : list of str
feature extraction layers , use ' ' for add extra layers
For example :
from _ layers = [ ' relu4_3 ' , ' fc7 ' , ' ' , ' ' , ' ' , ' ' ]
which means extract feature from relu4_3 and fc7 , adding 4 extra layers
on top of fc7
num _ filters : list of int
number of filters for extra layers , you can use - 1 for extracted features ,
however , if normalization and scale is applied , the number of filter for
that layer must be provided .
For example :
num _ filters = [ 512 , - 1 , 512 , 256 , 256 , 256]
strides : list of int
strides for the 3x3 convolution appended , - 1 can be used for extracted
feature layers
pads : list of int
paddings for the 3x3 convolution , - 1 can be used for extracted layers
min _ filter : int
minimum number of filters used in 1x1 convolution
Returns
list of mx . Symbols""" | # arguments check
assert len ( from_layers ) > 0
assert isinstance ( from_layers [ 0 ] , str ) and len ( from_layers [ 0 ] . strip ( ) ) > 0
assert len ( from_layers ) == len ( num_filters ) == len ( strides ) == len ( pads )
internals = body . get_internals ( )
layers = [ ]
for k , params in enumerate ( zip ( from_layers , num_filters , strides , pads ) ) :
from_layer , num_filter , s , p = params
if from_layer . strip ( ) : # extract from base network
layer = internals [ from_layer . strip ( ) + '_output' ]
layers . append ( layer )
else : # attach from last feature layer
assert len ( layers ) > 0
assert num_filter > 0
layer = layers [ - 1 ]
num_1x1 = max ( min_filter , num_filter // 2 )
conv_1x1 = conv_act_layer ( layer , 'multi_feat_%d_conv_1x1' % ( k ) , num_1x1 , kernel = ( 1 , 1 ) , pad = ( 0 , 0 ) , stride = ( 1 , 1 ) , act_type = 'relu' )
conv_3x3 = conv_act_layer ( conv_1x1 , 'multi_feat_%d_conv_3x3' % ( k ) , num_filter , kernel = ( 3 , 3 ) , pad = ( p , p ) , stride = ( s , s ) , act_type = 'relu' )
layers . append ( conv_3x3 )
return layers |
def cell_styles ( self ) :
"""dict of { ( row name , col name ) : style }""" | styles = { }
for colname , col in self . dataframe . items ( ) :
for rowname , value in col . items ( ) :
if isinstance ( value , Value ) and value . style is not None :
style = value . style
if not isinstance ( style , CellStyle ) :
style = self . _named_styles [ style ]
styles [ ( rowname , colname ) ] = style
return styles |
def get_error_probability ( self ) :
"""This means for the base we are talking about how many errors between 0 and 1 do we attribute to it ?
For the ' unobserved ' errors , these can only count when one is adjacent to base
: returns : error probability p ( error _ observed ) + ( 1 - p _ error _ observed ) * error _ unobserved
: rtype : float""" | a = self . _observable . get_error_probability ( )
b = self . _unobservable . get_error_probability ( )
return a + ( 1 - a ) * b |
def add_reorganize_data ( self , name , input_name , output_name , mode = 'SPACE_TO_DEPTH' , block_size = 2 ) :
"""Add a data reorganization layer of type " SPACE _ TO _ DEPTH " or " DEPTH _ TO _ SPACE " .
Parameters
name : str
The name of this layer .
input _ name : str
The input blob name of this layer .
output _ name : str
The output blob name of this layer .
mode : str
- If mode = = ' SPACE _ TO _ DEPTH ' : data is moved from the spatial to the channel dimension .
Input is spatially divided into non - overlapping blocks of size block _ size X block _ size
and data from each block is moved to the channel dimension .
Output CHW dimensions are : [ C * block _ size * block _ size , H / block _ size , C / block _ size ] .
- If mode = = ' DEPTH _ TO _ SPACE ' : data is moved from the channel to the spatial dimension .
Reverse of the operation ' SPACE _ TO _ DEPTH ' .
Output CHW dimensions are : [ C / ( block _ size * block _ size ) , H * block _ size , C * block _ size ] .
block _ size : int
Must be greater than 1 . Must divide H and W , when mode is ' SPACE _ TO _ DEPTH ' . ( block _ size * block _ size )
must divide C when mode is ' DEPTH _ TO _ SPACE ' .
See Also
add _ flatten , add _ reshape""" | spec = self . spec
nn_spec = self . nn_spec
# Add a new layer
spec_layer = nn_spec . layers . add ( )
spec_layer . name = name
spec_layer . input . append ( input_name )
spec_layer . output . append ( output_name )
spec_layer_params = spec_layer . reorganizeData
# Set the parameters
if block_size < 2 :
raise ValueError ( "Invalid block_size value %d. Must be greater than 1." % block_size )
spec_layer_params . blockSize = block_size
if mode == 'SPACE_TO_DEPTH' :
spec_layer_params . mode = _NeuralNetwork_pb2 . ReorganizeDataLayerParams . ReorganizationType . Value ( 'SPACE_TO_DEPTH' )
elif mode == 'DEPTH_TO_SPACE' :
spec_layer_params . mode = _NeuralNetwork_pb2 . ReorganizeDataLayerParams . ReorganizationType . Value ( 'DEPTH_TO_SPACE' )
else :
raise NotImplementedError ( 'Unknown reorganization mode %s ' % mode ) |
def connect_widget ( self , wid , getter = None , setter = None , signal = None , arg = None , update = True , flavour = None ) :
"""Finish set - up by connecting the widget . The model was already
specified in the constructor .
* wid * is a widget instance .
* getter * is a callable . It is passed * wid * and must return its
current value .
* setter * is a callable . It is passed * wid * and the current value of
the model property and must update the widget .
* signal * is a string naming the signal to connect to on * wid * . When
it is emitted we update the model .
* getter * , * setter * and * signal * are optional . Missing values are
guessed from * wid * using
: meth : ` gtkmvc3 . adapters . default . search _ adapter _ info ` . If nothing is
found this raises : exc : ` TypeError ` .
* arg * is an optional value passed to the handler for * signal * . This
doesn ' t do anything unless a subclass overrides the handler .
* update * denotes whether to update the widget from the model
immediately . Otherwise the widget stays unchanged until the first
notification .
* flavour * can be used to select special behaviours about
the adaptation when twice or more possibilities are
possibly handled for the same widget type . See
adapters . default for further information .""" | if wid in self . _wid_info :
raise ValueError ( "Widget " + str ( wid ) + " was already connected" )
wid_type = None
if None in ( getter , setter , signal ) :
w = search_adapter_info ( wid , flavour )
if getter is None :
getter = w [ GETTER ]
if setter is None :
setter = w [ SETTER ]
wid_type = w [ WIDTYPE ]
if signal is None :
signal = w [ SIGNAL ]
# saves information about the widget
self . _wid_info [ wid ] = ( getter , setter , wid_type )
# connects the widget
if signal :
if arg :
wid . connect ( signal , self . _on_wid_changed , arg )
else :
wid . connect ( signal , self . _on_wid_changed )
self . _wid = wid
# updates the widget :
if update :
self . update_widget ( ) |
def get_state_search_path_list ( saltenv = 'base' ) :
'''For the state file system , return a list of paths to search for states''' | # state cache should be updated before running this method
search_list = [ ]
cachedir = __opts__ . get ( 'cachedir' , None )
log . info ( "Searching for files in saltenv: %s" , saltenv )
path = cachedir + os . sep + "files" + os . sep + saltenv
search_list . append ( path )
return search_list |
def update_ids ( self , docids ) :
"""Update id - > pos mapping with new document ids .""" | logger . info ( "updating %i id mappings" % len ( docids ) )
for docid in docids :
if docid is not None :
pos = self . id2pos . get ( docid , None )
if pos is not None :
logger . info ( "replacing existing document %r in %s" % ( docid , self ) )
del self . pos2id [ pos ]
self . id2pos [ docid ] = self . length
try :
del self . id2sims [ docid ]
except :
pass
self . length += 1
self . id2sims . sync ( )
self . update_mappings ( ) |
def background_bin_from_string ( background_bins , data ) :
"""Return template ids for each bin as defined by the format string
Parameters
bins : list of strings
List of strings which define how a background bin is taken from the
list of templates .
data : dict of numpy . ndarrays
Dict with parameter key values and numpy . ndarray values which define
the parameters of the template bank to bin up .
Returns
bins : dict
Dictionary of location indices indexed by a bin name""" | used = numpy . array ( [ ] , dtype = numpy . uint32 )
bins = { }
for mbin in background_bins :
name , bin_type , boundary = tuple ( mbin . split ( ':' ) )
if boundary [ 0 : 2 ] == 'lt' :
member_func = lambda vals , bd = boundary : vals < float ( bd [ 2 : ] )
elif boundary [ 0 : 2 ] == 'gt' :
member_func = lambda vals , bd = boundary : vals > float ( bd [ 2 : ] )
else :
raise RuntimeError ( "Can't parse boundary condition! Must begin " "with 'lt' or 'gt'" )
if bin_type == 'component' and boundary [ 0 : 2 ] == 'lt' : # maximum component mass is less than boundary value
vals = numpy . maximum ( data [ 'mass1' ] , data [ 'mass2' ] )
if bin_type == 'component' and boundary [ 0 : 2 ] == 'gt' : # minimum component mass is greater than bdary
vals = numpy . minimum ( data [ 'mass1' ] , data [ 'mass2' ] )
elif bin_type == 'total' :
vals = data [ 'mass1' ] + data [ 'mass2' ]
elif bin_type == 'chirp' :
vals = pycbc . pnutils . mass1_mass2_to_mchirp_eta ( data [ 'mass1' ] , data [ 'mass2' ] ) [ 0 ]
elif bin_type == 'SEOBNRv2Peak' :
vals = pycbc . pnutils . get_freq ( 'fSEOBNRv2Peak' , data [ 'mass1' ] , data [ 'mass2' ] , data [ 'spin1z' ] , data [ 'spin2z' ] )
elif bin_type == 'SEOBNRv4Peak' :
vals = pycbc . pnutils . get_freq ( 'fSEOBNRv4Peak' , data [ 'mass1' ] , data [ 'mass2' ] , data [ 'spin1z' ] , data [ 'spin2z' ] )
elif bin_type == 'SEOBNRv2duration' :
vals = pycbc . pnutils . get_imr_duration ( data [ 'mass1' ] , data [ 'mass2' ] , data [ 'spin1z' ] , data [ 'spin2z' ] , data [ 'f_lower' ] , approximant = 'SEOBNRv2' )
else :
raise ValueError ( 'Invalid bin type %s' % bin_type )
locs = member_func ( vals )
del vals
# make sure we don ' t reuse anything from an earlier bin
locs = numpy . where ( locs ) [ 0 ]
locs = numpy . delete ( locs , numpy . where ( numpy . in1d ( locs , used ) ) [ 0 ] )
used = numpy . concatenate ( [ used , locs ] )
bins [ name ] = locs
return bins |
def _docstring_key ( self , line ) :
"""Returns the key to use for the docblock immediately preceding
the specified line .""" | decormatch = self . docparser . RE_DECOR . match ( line )
if decormatch is not None :
key = "{}.{}" . format ( self . docelement . name , decormatch . group ( "name" ) )
else :
key = self . element . name
return key |
def print_tweets ( tweets ) :
"""Print a list of tweets one by one separated by " = " s .
Parameters
tweets : list ( dict )
A list of tweets . Each tweet is a dict containing the username of the tweet ' s author ,
the post time , and the tweet body .""" | print ( '=' * 60 )
for index , tweet in enumerate ( tweets ) :
print ( '-' * 60 )
print ( 'Tweet {}:' . format ( index ) )
print ( 'Username:' , tweet [ pytwis_constants . USERNAME_KEY ] )
print ( 'Time:' , datetime . datetime . fromtimestamp ( int ( tweet [ pytwis_constants . TWEET_UNIXTIME_KEY ] ) ) . strftime ( '%Y-%m-%d %H:%M:%S' ) )
print ( 'Body:\n\t' , tweet [ pytwis_constants . TWEET_BODY_KEY ] )
print ( '-' * 60 )
print ( '=' * 60 ) |
def send_metrics_to_cloudwatch ( self , rule , metric , dimensions ) :
"""Send metrics to CloudWatch for the given dimensions""" | timestamp = datetime . datetime . utcfromtimestamp ( metric . timestamp )
self . log . debug ( "CloudWatch: Attempting to publish metric: %s to %s " "with value (%s) for dimensions %s @%s" , rule [ 'name' ] , rule [ 'namespace' ] , str ( metric . value ) , str ( dimensions ) , str ( metric . timestamp ) )
try :
self . connection . put_metric_data ( str ( rule [ 'namespace' ] ) , str ( rule [ 'name' ] ) , str ( metric . value ) , timestamp , str ( rule [ 'unit' ] ) , dimensions )
self . log . debug ( "CloudWatch: Successfully published metric: %s to" " %s with value (%s) for dimensions %s" , rule [ 'name' ] , rule [ 'namespace' ] , str ( metric . value ) , str ( dimensions ) )
except AttributeError as e :
self . log . error ( "CloudWatch: Failed publishing - %s " , str ( e ) )
except Exception as e : # Rough connection re - try logic .
self . log . error ( "CloudWatch: Failed publishing - %s\n%s " , str ( e ) , str ( sys . exc_info ( ) [ 0 ] ) )
self . _bind ( ) |
def parse_signature ( self , statement , element , module = None ) :
"""Parses the specified line as a new version of the signature for ' element ' .
: arg statement : the string that has the new signature .
: arg element : the code element whose signature will be changed .""" | # If the signature changes , the user might not have had a chance to add the
# detailed member information for it yet . Here
# we will just update the modifiers and attributes . Also , since all the mods
# etc . will be overwritten , we don ' t need to handle replace separately .
smatch = self . RE_SIG . match ( statement )
result = ( None , None , None )
eresult = None
if smatch is not None :
name = smatch . group ( "name" ) . strip ( )
modifiers = smatch . group ( "modifiers" ) or [ ]
codetype = smatch . group ( "codetype" )
# If the exec is a function , we also may have a type and kind specified .
if codetype . lower ( ) == "function" :
dtype = smatch . group ( "type" )
kind = smatch . group ( "kind" )
if module is None :
element . update ( name , modifiers , dtype , kind )
else :
eresult = Function ( name , modifiers , dtype , kind , module )
else :
if module is None :
element . update ( name , modifiers )
else :
eresult = Subroutine ( name , modifiers , module )
# The parameter sets are actually driven by the body of the executable
# rather than the call signature . However , the declarations will be
# interpreted as members if we don ' t add the parameters to the ordered
# list of parameter names . Overwrite that list with the new names .
params = re . split ( "[\s,]+" , smatch . group ( "parameters" ) . lower ( ) )
if eresult is None :
element . paramorder = params
else :
eresult . paramorder = params
result = ( eresult , smatch . start ( ) , smatch . end ( ) )
return result |
def compute_results ( self , voting_method , votes = None , winners = 1 , ** kwargs ) :
"""Compute voting results to decide the winner ( s ) from the
: attr : ` votes ` .
The votes should have been made for the current
: attr : ` ~ creamas . vote . VoteOrganizer . candidates ` .
: param voting _ method :
A function which computes the results from the votes . Should
accept at least three parameters : candidates , votes and number of
vote winners . The function should return at least a list of vote
winners . See , e . g . : func : ` ~ creamas . vote . vote _ mean ` or
: func : ` ~ creamas . vote . vote _ best ` . Additional ` ` * * kwargs ` ` are passed
down to the voting method .
: param list votes :
A list of votes by which the voting is performed . Each vote should
have the same set of artifacts in them . If ` ` None ` ` the results
are computed for the current list of
: attr : ` ~ creamas . vote . VoteOrganizer . votes ` .
: param int winners :
The number of vote winners
: returns :
list of : py : class : ` ~ creamas . core . artifact . Artifact ` objects ,
the winning artifacts . Some voting methods may also return a score
associated with each winning artifact .
: rtype : list""" | if votes is None :
votes = self . votes
if len ( votes ) == 0 :
self . _log ( logging . DEBUG , "Could not compute results as there are " "no votes!" )
return [ ]
self . _log ( logging . DEBUG , "Computing results from {} votes." . format ( len ( votes ) ) )
return voting_method ( self . candidates , votes , winners , ** kwargs ) |
def reporter ( self ) :
"""Creates a report of the results""" | logging . info ( 'Creating {} report' . format ( self . analysistype ) )
# Create the path in which the reports are stored
make_path ( self . reportpath )
header = 'Strain,Serotype\n'
data = ''
with open ( os . path . join ( self . reportpath , '{}.csv' . format ( self . analysistype ) ) , 'w' ) as report :
for sample in self . runmetadata . samples :
if sample . general . bestassemblyfile != 'NA' :
data += sample . name + ','
if sample [ self . analysistype ] . results : # Set the O - type as either the appropriate attribute , or O - untypable
if ';' . join ( sample . serosippr . o_set ) == '-' :
otype = 'O-untypeable'
else :
otype = '{oset} ({opid})' . format ( oset = ';' . join ( sample . serosippr . o_set ) , opid = sample . serosippr . best_o_pid )
# Same as above , but for the H - type
if ';' . join ( sample . serosippr . h_set ) == '-' :
htype = 'H-untypeable'
else :
htype = '{hset} ({hpid})' . format ( hset = ';' . join ( sample . serosippr . h_set ) , hpid = sample . serosippr . best_h_pid )
serotype = '{otype}:{htype}' . format ( otype = otype , htype = htype )
# Populate the data string
data += serotype if serotype != 'O-untypeable:H-untypeable' else 'ND'
data += '\n'
else :
data += '\n'
report . write ( header )
report . write ( data ) |
def _create_config_signature ( config ) :
"""return the signature for a config object .
The signature is computed as sha1 digest of the contents of
working _ directory , include _ paths , define _ symbols and
undefine _ symbols .
: param config : Configuration object
: type config : : class : ` parser . xml _ generator _ configuration _ t `
: rtype : str""" | m = hashlib . sha1 ( )
m . update ( config . working_directory . encode ( "utf-8" ) )
for p in config . include_paths :
m . update ( p . encode ( "utf-8" ) )
for p in config . define_symbols :
m . update ( p . encode ( "utf-8" ) )
for p in config . undefine_symbols :
m . update ( p . encode ( "utf-8" ) )
for p in config . cflags :
m . update ( p . encode ( "utf-8" ) )
return m . digest ( ) |
def query_most_pic ( num , kind = '1' ) :
'''Query most pics .''' | return TabPost . select ( ) . where ( ( TabPost . kind == kind ) & ( TabPost . logo != "" ) ) . order_by ( TabPost . view_count . desc ( ) ) . limit ( num ) |
def save_object ( self , obj ) :
"""Save an object with Discipline
Only argument is a Django object . This function saves the object
( regardless of whether it already exists or not ) and registers with
Discipline , creating a new Action object . Do not use obj . save ( ) !""" | obj . save ( )
try :
save_object ( obj , editor = self )
except DisciplineException :
pass |
def get_daily ( self , date = None ) :
"""Get time entries for a date ( defaults to today ) .""" | if date == None :
return self . get ( "/daily.json" )
url = "/daily/{}/{}/{}.json" . format ( date . year , date . month , date . day )
return self . get ( url ) |
def _author_uid_get ( post ) :
"""Get the UID of the post author .
: param Post post : The post object to determine authorship of
: return : Author UID
: rtype : str""" | u = post . meta ( 'author.uid' )
return u if u else str ( current_user . uid ) |
def shorten_text ( self , text ) :
"""Shortens text to fit into the : attr : ` width ` .""" | if len ( text ) > self . width :
return text [ : self . width - 3 ] + '...'
return text |
def insert_asm ( self , addr , asm_code , before_label = False ) :
"""Insert some assembly code at the specific address . There must be an instruction starting at that address .
: param int addr : Address of insertion
: param str asm _ code : The assembly code to insert
: return : None""" | if before_label :
self . _inserted_asm_before_label [ addr ] . append ( asm_code )
else :
self . _inserted_asm_after_label [ addr ] . append ( asm_code ) |
def profile_validation ( self , status ) :
"""Return run total value .""" | self . selected_profile . data . setdefault ( 'validation_pass_count' , 0 )
self . selected_profile . data . setdefault ( 'validation_fail_count' , 0 )
if status :
self . selected_profile . data [ 'validation_pass_count' ] += 1
else :
self . selected_profile . data [ 'validation_fail_count' ] += 1 |
def _from_dict ( cls , _dict ) :
"""Initialize a DocStructure object from a json dictionary .""" | args = { }
if 'section_titles' in _dict :
args [ 'section_titles' ] = [ SectionTitles . _from_dict ( x ) for x in ( _dict . get ( 'section_titles' ) ) ]
if 'leading_sentences' in _dict :
args [ 'leading_sentences' ] = [ LeadingSentence . _from_dict ( x ) for x in ( _dict . get ( 'leading_sentences' ) ) ]
return cls ( ** args ) |
def items ( self , folder_id , subfolder_id , ann_id = None ) :
'''Yields an unodered generator of items in a subfolder .
The generator yields items , which are represented by a tuple
of ` ` content _ id ` ` and ` ` subtopic _ id ` ` . The format of these
identifiers is unspecified .
By default ( with ` ` ann _ id = None ` ` ) , subfolders are shown for all
anonymous users . Optionally , ` ` ann _ id ` ` can be set to a username ,
which restricts the list to only subfolders owned by that user .
: param str folder _ id : Folder id
: param str subfolder _ id : Subfolder id
: param str ann _ id : Username
: rtype : generator of ` ` ( content _ id , subtopic _ id ) ` `''' | self . assert_valid_folder_id ( folder_id )
self . assert_valid_folder_id ( subfolder_id )
ann_id = self . _annotator ( ann_id )
folder_cid = self . wrap_folder_content_id ( ann_id , folder_id )
subfolder_sid = self . wrap_subfolder_subtopic_id ( subfolder_id )
ident = ( folder_cid , subfolder_sid )
if self . store . get ( folder_cid ) is None :
raise KeyError ( folder_id )
for lab in self . label_store . directly_connected ( ident ) :
cid = lab . other ( folder_cid )
subid = lab . subtopic_for ( cid )
yield ( cid , subid ) |
def check ( self , func = None , name = None ) :
"""A decorator to register a new Dockerflow check to be run
when the / _ _ heartbeat _ _ endpoint is called . , e . g . : :
from dockerflow . flask import checks
@ dockerflow . check
def storage _ reachable ( ) :
try :
acme . storage . ping ( )
except SlowConnectionException as exc :
return [ checks . Warning ( exc . msg , id = ' acme . health . 0002 ' ) ]
except StorageException as exc :
return [ checks . Error ( exc . msg , id = ' acme . health . 0001 ' ) ]
or using a custom name : :
@ dockerflow . check ( name = ' acme - storage - check )
def storage _ reachable ( ) :""" | if func is None :
return functools . partial ( self . check , name = name )
if name is None :
name = func . __name__
self . logger . info ( 'Registered Dockerflow check %s' , name )
@ functools . wraps ( func )
def decorated_function ( * args , ** kwargs ) :
self . logger . info ( 'Called Dockerflow check %s' , name )
return func ( * args , ** kwargs )
self . checks [ name ] = decorated_function
return decorated_function |
def _is_qstring ( message ) :
"""Check if its a QString without adding any dep to PyQt5.""" | my_class = str ( message . __class__ )
my_class_name = my_class . replace ( '<class \'' , '' ) . replace ( '\'>' , '' )
if my_class_name == 'PyQt5.QtCore.QString' :
return True
return False |
def ne ( self , other , axis = "columns" , level = None ) :
"""Checks element - wise that this is not equal to other .
Args :
other : A DataFrame or Series or scalar to compare to .
axis : The axis to perform the ne over .
level : The Multilevel index level to apply ne over .
Returns :
A new DataFrame filled with Booleans .""" | return self . _binary_op ( "ne" , other , axis = axis , level = level ) |
def set_autocamera ( self , mode = 'density' ) :
"""- set _ autocamera ( mode = ' density ' ) : By default , Scene defines its
own Camera . However , there is no a general way for doing so . Scene
uses a density criterion for getting the point of view . If this is
not a good option for your problem , you can choose among :
| ' minmax ' | ' density ' | ' median ' | ' mean ' | . If None of the previous methods
work well , you may define the camera params by yourself .""" | self . Camera . set_autocamera ( self . _Particles , mode = mode )
self . _camera_params = self . Camera . get_params ( )
self . _x , self . _y , self . _hsml , self . _kview = self . __compute_scene ( )
self . _m = self . _Particles . _mass [ self . _kview ] |
def cat ( args ) :
"""% prog cat * . pdf - o output . pdf
Concatenate pages from pdf files into a single pdf file .
Page ranges refer to the previously - named file .
A file not followed by a page range means all the pages of the file .
PAGE RANGES are like Python slices .
{ page _ range _ help }
EXAMPLES
pdfcat - o output . pdf head . pdf content . pdf : 6 7 : tail . pdf - 1
Concatenate all of head . pdf , all but page seven of content . pdf ,
and the last page of tail . pdf , producing output . pdf .
pdfcat chapter * . pdf > book . pdf
You can specify the output file by redirection .
pdfcat chapter ? . pdf chapter10 . pdf > book . pdf
In case you don ' t want chapter 10 before chapter 2.""" | p = OptionParser ( cat . __doc__ . format ( page_range_help = PAGE_RANGE_HELP ) )
p . add_option ( "--nosort" , default = False , action = "store_true" , help = "Do not sort file names" )
p . add_option ( "--cleanup" , default = False , action = "store_true" , help = "Remove individual pdfs after merging" )
p . set_outfile ( )
p . set_verbose ( help = "Show page ranges as they are being read" )
opts , args = p . parse_args ( args )
if len ( args ) < 1 :
sys . exit ( not p . print_help ( ) )
outfile = opts . outfile
if outfile in args :
args . remove ( outfile )
if not opts . nosort :
args = natsorted ( args )
filename_page_ranges = parse_filename_page_ranges ( args )
verbose = opts . verbose
fw = must_open ( outfile , "wb" )
merger = PdfFileMerger ( )
in_fs = { }
try :
for ( filename , page_range ) in filename_page_ranges :
if verbose :
print ( filename , page_range , file = sys . stderr )
if filename not in in_fs :
in_fs [ filename ] = open ( filename , "rb" )
merger . append ( in_fs [ filename ] , pages = page_range )
except :
print ( traceback . format_exc ( ) , file = sys . stderr )
print ( "Error while reading " + filename , file = sys . stderr )
sys . exit ( 1 )
merger . write ( fw )
fw . close ( )
if opts . cleanup :
logging . debug ( "Cleaning up {} files" . format ( len ( args ) ) )
for arg in args :
os . remove ( arg ) |
def is_binary ( var , allow_none = False ) :
"""Returns True if var is a binary ( bytes ) objects
Result py - 2 py - 3
b ' bytes literal ' True True
' string literal ' True False
u ' unicode literal ' False False
Also works with the corresponding numpy types .""" | return isinstance ( var , six . binary_type ) or ( var is None and allow_none ) |
def confidence_intervals ( self , X , width = .95 , quantiles = None ) :
"""estimate confidence intervals for the model .
Parameters
X : array - like of shape ( n _ samples , m _ features )
Input data matrix
width : float on [ 0,1 ] , optional
quantiles : array - like of floats in ( 0 , 1 ) , optional
Instead of specifying the prediciton width , one can specify the
quantiles . So ` ` width = . 95 ` ` is equivalent to ` ` quantiles = [ . 025 , . 975 ] ` `
Returns
intervals : np . array of shape ( n _ samples , 2 or len ( quantiles ) )
Notes
Wood 2006 , section 4.9
Confidence intervals based on section 4.8 rely on large sample results to deal with
non - Gaussian distributions , and treat the smoothing parameters as fixed , when in
reality they are estimated from the data .""" | if not self . _is_fitted :
raise AttributeError ( 'GAM has not been fitted. Call fit first.' )
X = check_X ( X , n_feats = self . statistics_ [ 'm_features' ] , edge_knots = self . edge_knots_ , dtypes = self . dtype , features = self . feature , verbose = self . verbose )
return self . _get_quantiles ( X , width , quantiles , prediction = False ) |
def check_common_elements_order ( list1 , list2 ) :
"""Function to verify if the common elements between two given lists maintain the same sequence .
Examples :
check _ common _ elements _ order ( [ ' red ' , ' green ' , ' black ' , ' orange ' ] , [ ' red ' , ' pink ' , ' green ' , ' white ' , ' black ' ] ) - > True
check _ common _ elements _ order ( [ ' red ' , ' pink ' , ' green ' , ' white ' , ' black ' ] , [ ' white ' , ' orange ' , ' pink ' , ' black ' ] ) - > False
check _ common _ elements _ order ( [ ' red ' , ' green ' , ' black ' , ' orange ' ] , [ ' red ' , ' pink ' , ' green ' , ' white ' , ' black ' ] ) - > True
Args :
list1 and list2 : Two lists
Returns :
Boolean value indicating whether common elements between list1 and list2 have the same order in both lists .""" | shared_elements = set ( list1 ) & set ( list2 )
ordered_list1 = [ item for item in list1 if item in shared_elements ]
ordered_list2 = [ item for item in list2 if item in shared_elements ]
return ordered_list1 == ordered_list2 |
def get_quant_NAs ( quantdata , quantheader ) :
"""Takes quantdata in a dict and header with quantkeys
( eg iTRAQ isotopes ) . Returns dict of quant intensities
with missing keys set to NA .""" | out = { }
for qkey in quantheader :
out [ qkey ] = quantdata . get ( qkey , 'NA' )
return out |
def components ( self , extra_params = None ) :
"""All components in this Space""" | return self . api . _get_json ( Component , space = self , rel_path = self . _build_rel_path ( 'ticket_components' ) , extra_params = extra_params , ) |
def infer_modifications ( stmts ) :
"""Return inferred Modification from RegulateActivity + ActiveForm .
This function looks for combinations of Activation / Inhibition Statements
and ActiveForm Statements that imply a Modification Statement .
For example , if we know that A activates B , and phosphorylated B is
active , then we can infer that A leads to the phosphorylation of B .
An additional requirement when making this assumption is that the
activity of B should only be dependent on the modified state and not
other context - otherwise the inferred Modification is not necessarily
warranted .
Parameters
stmts : list [ indra . statements . Statement ]
A list of Statements to infer Modifications from .
Returns
linked _ stmts : list [ indra . mechlinker . LinkedStatement ]
A list of LinkedStatements representing the inferred Statements .""" | linked_stmts = [ ]
for act_stmt in _get_statements_by_type ( stmts , RegulateActivity ) :
for af_stmt in _get_statements_by_type ( stmts , ActiveForm ) :
if not af_stmt . agent . entity_matches ( act_stmt . obj ) :
continue
mods = af_stmt . agent . mods
# Make sure the ActiveForm only involves modified sites
if af_stmt . agent . mutations or af_stmt . agent . bound_conditions or af_stmt . agent . location :
continue
if not af_stmt . agent . mods :
continue
for mod in af_stmt . agent . mods :
evs = act_stmt . evidence + af_stmt . evidence
for ev in evs :
ev . epistemics [ 'direct' ] = False
if mod . is_modified :
mod_type_name = mod . mod_type
else :
mod_type_name = modtype_to_inverse [ mod . mod_type ]
mod_class = modtype_to_modclass [ mod_type_name ]
if not mod_class :
continue
st = mod_class ( act_stmt . subj , act_stmt . obj , mod . residue , mod . position , evidence = evs )
ls = LinkedStatement ( [ act_stmt , af_stmt ] , st )
linked_stmts . append ( ls )
logger . info ( 'inferred: %s' % st )
return linked_stmts |
def AddSpecification ( self , specification ) :
"""Adds a format specification .
Args :
specification ( FormatSpecification ) : format specification .
Raises :
KeyError : if the store already contains a specification with
the same identifier .""" | if specification . identifier in self . _format_specifications :
raise KeyError ( 'Format specification {0:s} is already defined in store.' . format ( specification . identifier ) )
self . _format_specifications [ specification . identifier ] = specification
for signature in specification . signatures :
signature_index = len ( self . _signature_map )
signature_identifier = '{0:s}:{1:d}' . format ( specification . identifier , signature_index )
if signature_identifier in self . _signature_map :
raise KeyError ( 'Signature {0:s} is already defined in map.' . format ( signature_identifier ) )
signature . SetIdentifier ( signature_identifier )
self . _signature_map [ signature_identifier ] = specification |
def parse_string ( self , string ) :
"""Parse ASCII output of JPrintMeta""" | self . log . info ( "Parsing ASCII data" )
if not string :
self . log . warning ( "Empty metadata" )
return
lines = string . splitlines ( )
application_data = [ ]
application = lines [ 0 ] . split ( ) [ 0 ]
self . log . debug ( "Reading meta information for '%s'" % application )
for line in lines :
if application is None :
self . log . debug ( "Reading meta information for '%s'" % application )
application = line . split ( ) [ 0 ]
application_data . append ( line )
if line . startswith ( application + b' Linux' ) :
self . _record_app_data ( application_data )
application_data = [ ]
application = None |
def models ( self ) :
"""Return all the models defined for this module""" | app = get_app ( self . __class__ . __module__ . split ( '.' ) [ - 2 ] )
return get_models ( app ) |
def _append ( self , menu ) :
'''append this menu item to a menu''' | menu . AppendCheckItem ( self . id ( ) , self . name , self . description )
menu . Check ( self . id ( ) , self . checked ) |
def split_by_idxs ( seq , idxs ) :
'''A generator that returns sequence pieces , seperated by indexes specified in idxs .''' | last = 0
for idx in idxs :
if not ( - len ( seq ) <= idx < len ( seq ) ) :
raise KeyError ( f'Idx {idx} is out-of-bounds' )
yield seq [ last : idx ]
last = idx
yield seq [ last : ] |
def cmd_relay ( self , args ) :
'''set relays''' | if len ( args ) == 0 or args [ 0 ] not in [ 'set' , 'repeat' ] :
print ( "Usage: relay <set|repeat>" )
return
if args [ 0 ] == "set" :
if len ( args ) < 3 :
print ( "Usage: relay set <RELAY_NUM> <0|1>" )
return
self . master . mav . command_long_send ( self . target_system , self . target_component , mavutil . mavlink . MAV_CMD_DO_SET_RELAY , 0 , int ( args [ 1 ] ) , int ( args [ 2 ] ) , 0 , 0 , 0 , 0 , 0 )
if args [ 0 ] == "repeat" :
if len ( args ) < 4 :
print ( "Usage: relay repeat <RELAY_NUM> <COUNT> <PERIOD>" )
return
self . master . mav . command_long_send ( self . target_system , self . target_component , mavutil . mavlink . MAV_CMD_DO_REPEAT_RELAY , 0 , int ( args [ 1 ] ) , int ( args [ 2 ] ) , float ( args [ 3 ] ) , 0 , 0 , 0 , 0 ) |
def create_doc_id_from_json ( doc ) -> str :
"""Docs with identical contents get the same ID .
Args :
doc :
Returns : a string with the hash of the given document .""" | return hashlib . sha256 ( json . dumps ( doc , sort_keys = True ) . encode ( 'utf-8' ) ) . hexdigest ( ) |
def asDirect ( self ) :
"""Returns the image data as a direct representation of an
` ` x * y * planes ` ` array . This method is intended to remove the
need for callers to deal with palettes and transparency
themselves . Images with a palette ( colour type 3)
are converted to RGB or RGBA ; images with transparency ( a
` ` tRNS ` ` chunk ) are converted to LA or RGBA as appropriate .
When returned in this format the pixel values represent the
colour value directly without needing to refer to palettes or
transparency information .
Like the : meth : ` read ` method this method returns a 4 - tuple :
( * width * , * height * , * pixels * , * meta * )
This method normally returns pixel values with the bit depth
they have in the source image , but when the source PNG has an
` ` sBIT ` ` chunk it is inspected and can reduce the bit depth of
the result pixels ; pixel values will be reduced according to
the bit depth specified in the ` ` sBIT ` ` chunk ( PNG nerds should
note a single result bit depth is used for all channels ; the
maximum of the ones specified in the ` ` sBIT ` ` chunk . An RGB565
image will be rescaled to 6 - bit RGB666 ) .
The * meta * dictionary that is returned reflects the ` direct `
format and not the original source image . For example , an RGB
source image with a ` ` tRNS ` ` chunk to represent a transparent
colour , will have ` ` planes = 3 ` ` and ` ` alpha = False ` ` for the
source image , but the * meta * dictionary returned by this method
will have ` ` planes = 4 ` ` and ` ` alpha = True ` ` because an alpha
channel is synthesized and added .
* pixels * is the pixel data in boxed row flat pixel format ( just
like the : meth : ` read ` method ) .
All the other aspects of the image data are not changed .""" | self . preamble ( )
# Simple case , no conversion necessary .
if not self . colormap and not self . trns and not self . sbit :
return self . read ( )
x , y , pixels , meta = self . read ( )
if self . colormap :
meta [ 'colormap' ] = False
meta [ 'alpha' ] = bool ( self . trns )
meta [ 'bitdepth' ] = 8
meta [ 'planes' ] = 3 + bool ( self . trns )
plte = self . palette ( )
def iterpal ( pixels ) :
for row in pixels :
row = map ( plte . __getitem__ , row )
yield array ( 'B' , itertools . chain ( * row ) )
pixels = iterpal ( pixels )
elif self . trns : # It would be nice if there was some reasonable way
# of doing this without generating a whole load of
# intermediate tuples . But tuples does seem like the
# easiest way , with no other way clearly much simpler or
# much faster . ( Actually , the L to LA conversion could
# perhaps go faster ( all those 1 - tuples ! ) , but I still
# wonder whether the code proliferation is worth it )
it = self . transparent
maxval = 2 ** meta [ 'bitdepth' ] - 1
planes = meta [ 'planes' ]
meta [ 'alpha' ] = True
meta [ 'planes' ] += 1
typecode = 'BH' [ meta [ 'bitdepth' ] > 8 ]
def itertrns ( pixels ) :
for row in pixels : # For each row we group it into pixels , then form a
# characterisation vector that says whether each
# pixel is opaque or not . Then we convert
# True / False to 0 / maxval ( by multiplication ) ,
# and add it as the extra channel .
row = group ( row , planes )
opa = map ( it . __ne__ , row )
opa = map ( maxval . __mul__ , opa )
opa = zip ( opa )
# convert to 1 - tuples
yield array ( typecode , itertools . chain ( * map ( operator . add , row , opa ) ) )
pixels = itertrns ( pixels )
targetbitdepth = None
if self . sbit :
sbit = struct . unpack ( '%dB' % len ( self . sbit ) , self . sbit )
targetbitdepth = max ( sbit )
if targetbitdepth > meta [ 'bitdepth' ] :
raise Error ( 'sBIT chunk %r exceeds bitdepth %d' % ( sbit , self . bitdepth ) )
if min ( sbit ) <= 0 :
raise Error ( 'sBIT chunk %r has a 0-entry' % sbit )
if targetbitdepth == meta [ 'bitdepth' ] :
targetbitdepth = None
if targetbitdepth :
shift = meta [ 'bitdepth' ] - targetbitdepth
meta [ 'bitdepth' ] = targetbitdepth
def itershift ( pixels ) :
for row in pixels :
yield map ( shift . __rrshift__ , row )
pixels = itershift ( pixels )
return x , y , pixels , meta |
def ordering_step ( self , oneway = False ) :
"""iterator that computes all vertices ordering in their layers
( one layer after the other from top to bottom , to top again unless
oneway is True ) .""" | self . dirv = - 1
crossings = 0
for l in self . layers :
mvmt = l . order ( )
crossings += mvmt
yield ( l , mvmt )
if oneway or ( crossings == 0 ) :
return
self . dirv = + 1
while l :
mvmt = l . order ( )
yield ( l , mvmt )
l = l . nextlayer ( ) |
def _AddMessageMethods ( message_descriptor , cls ) :
"""Adds implementations of all Message methods to cls .""" | _AddListFieldsMethod ( message_descriptor , cls )
_AddHasFieldMethod ( message_descriptor , cls )
_AddClearFieldMethod ( message_descriptor , cls )
if message_descriptor . is_extendable :
_AddClearExtensionMethod ( cls )
_AddHasExtensionMethod ( cls )
_AddEqualsMethod ( message_descriptor , cls )
_AddStrMethod ( message_descriptor , cls )
_AddReprMethod ( message_descriptor , cls )
_AddUnicodeMethod ( message_descriptor , cls )
_AddByteSizeMethod ( message_descriptor , cls )
_AddSerializeToStringMethod ( message_descriptor , cls )
_AddSerializePartialToStringMethod ( message_descriptor , cls )
_AddMergeFromStringMethod ( message_descriptor , cls )
_AddIsInitializedMethod ( message_descriptor , cls )
_AddMergeFromMethod ( cls )
_AddWhichOneofMethod ( message_descriptor , cls )
_AddReduceMethod ( cls )
# Adds methods which do not depend on cls .
cls . Clear = _Clear
cls . DiscardUnknownFields = _DiscardUnknownFields
cls . _SetListener = _SetListener |
def info ( self , section = 'default' ) :
"""Get information and statistics about the server .
If called without argument will return default set of sections .
For available sections , see http : / / redis . io / commands / INFO
: raises ValueError : if section is invalid""" | if not section :
raise ValueError ( "invalid section" )
fut = self . execute ( b'INFO' , section , encoding = 'utf-8' )
return wait_convert ( fut , parse_info ) |
async def is_ready ( self ) :
"""Check if the multi - environment has been fully initialized .
This calls each slave environment managers ' : py : meth : ` is _ ready ` and
checks if the multi - environment itself is ready by calling
: py : meth : ` ~ creamas . mp . MultiEnvironment . check _ ready ` .
. . seealso : :
: py : meth : ` creamas . core . environment . Environment . is _ ready `""" | async def slave_task ( addr , timeout ) :
try :
r_manager = await self . env . connect ( addr , timeout = timeout )
ready = await r_manager . is_ready ( )
if not ready :
return False
except :
return False
return True
if not self . env . is_ready ( ) :
return False
if not self . check_ready ( ) :
return False
rets = await create_tasks ( slave_task , self . addrs , 0.5 )
if not all ( rets ) :
return False
return True |
def _prepare_sort_options ( self , has_pk ) :
"""Prepare sort options for _ values attributes .
If we manager sort by score after getting the result , we do not want to
get values from the first sort call , but only from the last one , after
converting results in zset into keys""" | sort_options = super ( ExtendedCollectionManager , self ) . _prepare_sort_options ( has_pk )
if self . _values : # if we asked for values , we have to use the redis ' sort '
# command , which is able to return other fields .
if not sort_options :
sort_options = { }
sort_options [ 'get' ] = self . _values [ 'fields' ] [ 'keys' ]
if self . _sort_by_sortedset_after :
for key in ( 'get' , 'store' ) :
if key in self . _sort_by_sortedset :
del self . _sort_by_sortedset [ key ]
if sort_options and ( not has_pk or self . _want_score_value ) :
for key in ( 'get' , 'store' ) :
if key in sort_options :
self . _sort_by_sortedset [ key ] = sort_options . pop ( key )
if not sort_options :
sort_options = None
return sort_options |
def calc_2d_ellipse_properties ( cov , nstd = 2 ) :
"""Calculate the properties for 2d ellipse given the covariance matrix .""" | def eigsorted ( cov ) :
vals , vecs = np . linalg . eigh ( cov )
order = vals . argsort ( ) [ : : - 1 ]
return vals [ order ] , vecs [ : , order ]
vals , vecs = eigsorted ( cov )
width , height = 2 * nstd * np . sqrt ( vals [ : 2 ] )
normal = vecs [ : , 2 ] if vecs [ 2 , 2 ] > 0 else - vecs [ : , 2 ]
d = np . cross ( normal , ( 0 , 0 , 1 ) )
M = rotation_matrix ( d )
x_trans = np . dot ( M , ( 1 , 0 , 0 ) )
cos_val = np . dot ( vecs [ : , 0 ] , x_trans ) / np . linalg . norm ( vecs [ : , 0 ] ) / np . linalg . norm ( x_trans )
theta = np . degrees ( np . arccos ( np . clip ( cos_val , - 1 , 1 ) ) )
# if you really want the angle
return { 'width' : width , 'height' : height , 'angle' : theta } , normal |
def to_java_doubles ( m ) :
'''to _ java _ doubles ( m ) yields a java array object for the vector or matrix m .''' | global _java
if _java is None :
_init_registration ( )
m = np . asarray ( m )
dims = len ( m . shape )
if dims > 2 :
raise ValueError ( '1D and 2D arrays supported only' )
bindat = serialize_numpy ( m , 'd' )
return ( _java . jvm . nben . util . Numpy . double2FromBytes ( bindat ) if dims == 2 else _java . jvm . nben . util . Numpy . double1FromBytes ( bindat ) ) |
def build_pdf ( source , texinputs = [ ] , builder = None ) :
"""Builds a LaTeX source to PDF .
Will automatically instantiate an available builder ( or raise a
: class : ` exceptions . RuntimeError ` if none are available ) and build the
supplied source with it .
Parameters are passed on to the builder ' s
: meth : ` ~ latex . build . LatexBuilder . build _ pdf ` function .
: param builder : Specify which builder should be used - ` ` latexmk ` ` ,
` ` pdflatex ` ` or ` ` xelatexmk ` ` .""" | if builder is None :
builders = PREFERRED_BUILDERS
elif builder not in BUILDERS :
raise RuntimeError ( 'Invalid Builder specified' )
else :
builders = ( builder , )
for bld in builders :
bld_cls = BUILDERS [ bld ]
builder = bld_cls ( )
if not builder . is_available ( ) :
continue
return builder . build_pdf ( source , texinputs )
else :
raise RuntimeError ( 'No available builder could be instantiated. ' 'Please make sure LaTeX is installed.' ) |
def stop_containers ( self ) :
"""Stops all containers used by this instance of the backend .""" | while len ( self . _containers ) :
container = self . _containers . pop ( )
try :
container . kill ( signal . SIGKILL )
except docker . errors . APIError : # probably doesn ' t exist anymore
pass |
def ckgpav ( inst , sclkdp , tol , ref ) :
"""Get pointing ( attitude ) and angular velocity
for a specified spacecraft clock time .
http : / / naif . jpl . nasa . gov / pub / naif / toolkit _ docs / C / cspice / ckgpav _ c . html
: param inst : NAIF ID of instrument , spacecraft , or structure .
: type inst : int
: param sclkdp : Encoded spacecraft clock time .
: type sclkdp : float
: param tol : Time tolerance .
: type tol : float
: param ref : Reference frame .
: type ref : str
: return :
C - matrix pointing data ,
Angular velocity vector ,
Output encoded spacecraft clock time .
: rtype : tuple""" | inst = ctypes . c_int ( inst )
sclkdp = ctypes . c_double ( sclkdp )
tol = ctypes . c_double ( tol )
ref = stypes . stringToCharP ( ref )
cmat = stypes . emptyDoubleMatrix ( )
av = stypes . emptyDoubleVector ( 3 )
clkout = ctypes . c_double ( )
found = ctypes . c_int ( )
libspice . ckgpav_c ( inst , sclkdp , tol , ref , cmat , av , ctypes . byref ( clkout ) , ctypes . byref ( found ) )
return stypes . cMatrixToNumpy ( cmat ) , stypes . cVectorToPython ( av ) , clkout . value , bool ( found . value ) |
def gen_locustfile ( testcase_file_path ) :
"""generate locustfile from template .""" | locustfile_path = 'locustfile.py'
template_path = os . path . join ( os . path . dirname ( os . path . realpath ( __file__ ) ) , "templates" , "locustfile_template" )
with io . open ( template_path , encoding = 'utf-8' ) as template :
with io . open ( locustfile_path , 'w' , encoding = 'utf-8' ) as locustfile :
template_content = template . read ( )
template_content = template_content . replace ( "$TESTCASE_FILE" , testcase_file_path )
locustfile . write ( template_content )
return locustfile_path |
def route ( regex , method , name ) :
"""Route the decorated view .
: param regex : A string describing a regular expression to which the request path will be matched .
: param method : A string describing the HTTP method that this view accepts .
: param name : A string describing the name of the URL pattern .
` ` regex ` ` may also be a lambda that accepts the parent resource ' s ` ` prefix ` ` argument and returns
a string describing a regular expression to which the request path will be matched .
` ` name ` ` may also be a lambda that accepts the parent resource ' s ` ` views ` ` argument and returns
a string describing the name of the URL pattern .""" | def decorator ( function ) :
function . route = routes . route ( regex = regex , view = function . __name__ , method = method , name = name )
@ wraps ( function )
def wrapper ( self , * args , ** kwargs ) :
return function ( self , * args , ** kwargs )
return wrapper
return decorator |
def next ( self ) :
"""Pops and returns the first outgoing message from the list .
If message list currently has no messages , the calling thread will
be put to sleep until we have at - least one message in the list that
can be popped and returned .""" | # We pick the first outgoing available and send it .
outgoing_msg = self . outgoing_msg_list . pop_first ( )
# If we do not have any outgoing msg . , we wait .
if outgoing_msg is None :
self . outgoing_msg_event . clear ( )
self . outgoing_msg_event . wait ( )
outgoing_msg = self . outgoing_msg_list . pop_first ( )
return outgoing_msg |
def download ( URLs , dest_dir = '.' , dest_file = None , decompress = False , max_jobs = 5 ) :
'''Download files from specified URL , which should be space , tab or
newline separated URLs . The files will be downloaded to specified
destination . If ` filename . md5 ` files are downloaded , they are used to
validate downloaded ` filename ` . Unless otherwise specified , compressed
files are decompressed . If ` max _ jobs ` is given , a maximum of ` max _ jobs `
concurrent download jobs will be used for each domain . This restriction
applies to domain names and will be applied to multiple download
instances .''' | if env . config [ 'run_mode' ] == 'dryrun' :
print ( f'HINT: download\n{URLs}\n' )
return None
if isinstance ( URLs , str ) :
urls = [ x . strip ( ) for x in URLs . split ( ) if x . strip ( ) ]
else :
urls = list ( URLs )
if not urls :
env . logger . debug ( f'No download URL specified: {URLs}' )
return
if dest_file is not None and len ( urls ) != 1 :
raise RuntimeError ( 'Only one URL is allowed if a destination file is specified.' )
if dest_file is None :
filenames = [ ]
for idx , url in enumerate ( urls ) :
token = urllib . parse . urlparse ( url )
# if no scheme or netloc , the URL is not acceptable
if not all ( [ getattr ( token , qualifying_attr ) for qualifying_attr in ( 'scheme' , 'netloc' ) ] ) :
raise ValueError ( f'Invalid URL {url}' )
filename = os . path . split ( token . path ) [ - 1 ]
if not filename :
raise ValueError ( f'Cannot determine destination file for {url}' )
filenames . append ( os . path . join ( dest_dir , filename ) )
else :
token = urllib . parse . urlparse ( urls [ 0 ] )
if not all ( [ getattr ( token , qualifying_attr ) for qualifying_attr in ( 'scheme' , 'netloc' ) ] ) :
raise ValueError ( f'Invalid URL {url}' )
filenames = [ dest_file ]
succ = [ ( False , None ) for x in urls ]
with ProcessPoolExecutor ( max_workers = max_jobs ) as executor :
for idx , ( url , filename ) in enumerate ( zip ( urls , filenames ) ) : # if there is alot , start download
succ [ idx ] = executor . submit ( downloadURL , url , filename , decompress , idx )
succ = [ x . result ( ) for x in succ ]
# for su , url in zip ( succ , urls ) :
# if not su :
# env . logger . warning ( ' Failed to download { } ' . format ( url ) )
failed = [ y for x , y in zip ( succ , urls ) if not x ]
if failed :
if len ( urls ) == 1 :
raise RuntimeError ( 'Failed to download {urls[0]}' )
else :
raise RuntimeError ( f'Failed to download {failed[0]} ({len(failed)} out of {len(urls)})' )
return 0 |
def main ( github_token , github_api_url , progress ) :
"""A CLI to easily manage GitHub releases , assets and references .""" | global progress_reporter_cls
progress_reporter_cls . reportProgress = sys . stdout . isatty ( ) and progress
if progress_reporter_cls . reportProgress :
progress_reporter_cls = _progress_bar
global _github_token_cli_arg
_github_token_cli_arg = github_token
global _github_api_url
_github_api_url = github_api_url |
def get_max_muO2 ( self , min_voltage = None , max_voltage = None ) :
"""Maximum critical oxygen chemical potential along path .
Args :
min _ voltage : The minimum allowable voltage .
max _ voltage : The maximum allowable voltage .
Returns :
Maximum critical oxygen chemical of all compounds along the
insertion path ( a subset of the path can be chosen by the optional
arguments ) .""" | data = [ ]
for pair in self . _select_in_voltage_range ( min_voltage , max_voltage ) :
if pair . muO2_discharge is not None :
data . extend ( [ d [ 'chempot' ] for d in pair . muO2_discharge ] )
if pair . muO2_charge is not None :
data . extend ( [ d [ 'chempot' ] for d in pair . muO2_discharge ] )
return max ( data ) if len ( data ) > 0 else None |
def get_residuals ( ds , m ) :
"""Using the dataset and model object , calculate the residuals and return
Parameters
ds : dataset object
m : model object
Return
residuals : array of residuals , spec minus model spec""" | model_spectra = get_model_spectra ( ds , m )
resid = ds . test_flux - model_spectra
return resid |
def next_builder ( self ) :
"""Create a new builder based off of this one with its sequence number
incremented .
: return : A new Builder instance
: rtype : : class : ` Builder `""" | sequence = self . sequence + 1
next_builder = Builder ( horizon_uri = self . horizon . horizon_uri , address = self . address , network = self . network , sequence = sequence , fee = self . fee )
next_builder . keypair = self . keypair
return next_builder |
def get_default_config ( self ) :
"""Returns the default collector settings""" | config = super ( NetstatCollector , self ) . get_default_config ( )
config . update ( { 'path' : 'netstat' , } )
return config |
def render_word ( self , text , tag , i ) :
"""Render individual word .
text ( unicode ) : Word text .
tag ( unicode ) : Part - of - speech tag .
i ( int ) : Unique ID , typically word index .
RETURNS ( unicode ) : Rendered SVG markup .""" | y = self . offset_y + self . word_spacing
x = self . offset_x + i * self . distance
if self . direction == "rtl" :
x = self . width - x
html_text = escape_html ( text )
return TPL_DEP_WORDS . format ( text = html_text , tag = tag , x = x , y = y ) |
def _get_singlekws ( skw_matches , spires = False ) :
"""Get single keywords .
: var skw _ matches : dict of { keyword : [ info , . . . ] }
: keyword spires : bool , to get the spires output
: return : list of formatted keywords""" | output = { }
for single_keyword , info in skw_matches :
output [ single_keyword . output ( spires ) ] = len ( info [ 0 ] )
output = [ { 'keyword' : key , 'number' : value } for key , value in output . iteritems ( ) ]
return sorted ( output , key = lambda x : x [ 'number' ] , reverse = True ) |
def offset ( self , offset ) :
"""Move all the intervals in the list by the given ` ` offset ` ` .
: param offset : the shift to be applied
: type offset : : class : ` ~ aeneas . exacttiming . TimeValue `
: raises TypeError : if ` ` offset ` ` is not an instance of ` ` TimeValue ` `""" | self . log ( u"Applying offset to all fragments..." )
self . log ( [ u" Offset %.3f" , offset ] )
for fragment in self . fragments :
fragment . interval . offset ( offset = offset , allow_negative = False , min_begin_value = self . begin , max_end_value = self . end )
self . log ( u"Applying offset to all fragments... done" ) |
def mozjpeg ( ext_args ) :
"""Create argument list for mozjpeg .""" | args = copy . copy ( _MOZJPEG_ARGS )
if Settings . destroy_metadata :
args += [ "-copy" , "none" ]
else :
args += [ "-copy" , "all" ]
args += [ '-outfile' ]
args += [ ext_args . new_filename , ext_args . old_filename ]
extern . run_ext ( args )
return _JPEG_FORMAT |
def _parse_css_color ( color ) :
'''_ parse _ css _ color ( css _ color ) - > gtk . gdk . Color''' | if color . startswith ( "rgb(" ) and color . endswith ( ')' ) :
r , g , b = [ int ( c ) * 257 for c in color [ 4 : - 1 ] . split ( ',' ) ]
return gtk . gdk . Color ( r , g , b )
else :
return gtk . gdk . color_parse ( color ) |
def _makeStoreOwnerPerson ( self ) :
"""Make a L { Person } representing the owner of the store that this
L { Organizer } is installed in .
@ rtype : L { Person }""" | if self . store is None :
return None
userInfo = self . store . findFirst ( signup . UserInfo )
name = u''
if userInfo is not None :
name = userInfo . realName
account = self . store . findUnique ( LoginAccount , LoginAccount . avatars == self . store , None )
ownerPerson = self . createPerson ( name )
if account is not None :
for method in ( self . store . query ( LoginMethod , attributes . AND ( LoginMethod . account == account , LoginMethod . internal == False ) ) ) :
self . createContactItem ( EmailContactType ( self . store ) , ownerPerson , dict ( email = method . localpart + u'@' + method . domain ) )
return ownerPerson |
def update ( self , session , arrays = None , frame = None ) :
'''Creates a frame and writes it to disk .
Args :
arrays : a list of np arrays . Use the " custom " option in the client .
frame : a 2D np array . This way the plugin can be used for video of any
kind , not just the visualization that comes with the plugin .
frame can also be a function , which only is evaluated when the
" frame " option is selected by the client .''' | new_config = self . _get_config ( )
if self . _enough_time_has_passed ( self . previous_config [ 'FPS' ] ) :
self . visualizer . update ( new_config )
self . last_update_time = time . time ( )
final_image = self . _update_frame ( session , arrays , frame , new_config )
self . _update_recording ( final_image , new_config ) |
def _reset ( self , framer ) :
"""Reset the state for the framer . It is safe to call this
method multiple times with the same framer ; the ID of the
framer object will be saved and the state only reset if the
IDs are different . After resetting the state , the framer ' s
` ` init _ state ( ) ` ` method will be called .""" | # Do nothing if we ' re already properly initialized
if id ( framer ) == self . _framer_id :
return
# Reset the state
self . _other = { }
# Initialize the state and save the framer ID
framer . init_state ( self )
self . _framer_id = id ( framer ) |
async def handle_exception ( self , exc : Exception , action : str , request_id ) :
"""Handle any exception that occurs , by sending an appropriate message""" | if isinstance ( exc , APIException ) :
await self . reply ( action = action , errors = self . _format_errors ( exc . detail ) , status = exc . status_code , request_id = request_id )
elif exc == Http404 or isinstance ( exc , Http404 ) :
await self . reply ( action = action , errors = self . _format_errors ( 'Not found' ) , status = 404 , request_id = request_id )
else :
raise exc |
def close_others ( self ) :
"""Closes every editors tabs except the current one .""" | current_widget = self . widget ( self . tab_under_menu ( ) )
if self . _try_close_dirty_tabs ( exept = current_widget ) :
i = 0
while self . count ( ) > 1 :
widget = self . widget ( i )
if widget != current_widget :
self . remove_tab ( i )
else :
i = 1 |
def grid_search ( script : str , params : typing . Iterable [ str ] , dry_run : bool = False ) -> None :
"""Build all grid search parameter configurations and optionally run them .
: param script : String of command prefix , e . g . ` ` cxflow train - v - o log ` ` .
: param params : Iterable collection of strings in standard * * cxflow * * param form , e . g . ` ` ' numerical _ param = [ 1 , 2 ] ' ` `
or ` ` ' text _ param = [ " hello " , " cio " ] ' ` ` .
: param dry _ run : If set to ` ` True ` ` , the built commands will only be printed instead of executed .""" | commands = _build_grid_search_commands ( script = script , params = params )
if dry_run :
logging . warning ( 'Dry run' )
for command in commands :
logging . info ( command )
else :
for command in commands :
try :
completed_process = subprocess . run ( command )
logging . info ( 'Command `%s` completed with exit code %d' , command , completed_process . returncode )
except Exception as _ : # pylint : disable = broad - except
logging . error ( 'Command `%s` failed.' , command ) |
def single_node_env ( num_gpus = 1 ) :
"""Setup environment variables for Hadoop compatibility and GPU allocation""" | import tensorflow as tf
# ensure expanded CLASSPATH w / o glob characters ( required for Spark 2.1 + JNI )
if 'HADOOP_PREFIX' in os . environ and 'TFOS_CLASSPATH_UPDATED' not in os . environ :
classpath = os . environ [ 'CLASSPATH' ]
hadoop_path = os . path . join ( os . environ [ 'HADOOP_PREFIX' ] , 'bin' , 'hadoop' )
hadoop_classpath = subprocess . check_output ( [ hadoop_path , 'classpath' , '--glob' ] ) . decode ( )
os . environ [ 'CLASSPATH' ] = classpath + os . pathsep + hadoop_classpath
os . environ [ 'TFOS_CLASSPATH_UPDATED' ] = '1'
# reserve GPU , if requested
if tf . test . is_built_with_cuda ( ) :
gpus_to_use = gpu_info . get_gpus ( num_gpus )
logging . info ( "Using gpu(s): {0}" . format ( gpus_to_use ) )
os . environ [ 'CUDA_VISIBLE_DEVICES' ] = gpus_to_use
else : # CPU
logging . info ( "Using CPU" )
os . environ [ 'CUDA_VISIBLE_DEVICES' ] = '' |
def close ( self , reply_code = 0 , reply_text = '' , class_id = 0 , method_id = 0 ) :
'''Close this channel . Routes to channel . close .''' | # In the off chance that we call this twice . A good example is if
# there ' s an error in close listeners and so we ' re still inside a
# single call to process _ frames , which will try to close this channel
# if there ' s an exception .
if hasattr ( self , 'channel' ) :
self . channel . close ( reply_code , reply_text , class_id , method_id ) |
def tocimxml ( self ) :
"""Return the CIM - XML representation of this CIM property ,
as an object of an appropriate subclass of : term : ` Element ` .
The returned CIM - XML representation is a ` PROPERTY ` ,
` PROPERTY . REFERENCE ` , or ` PROPERTY . ARRAY ` element dependent on the
property type , and consistent with : term : ` DSP0201 ` . Note that
array properties cannot be of reference type .
The order of qualifiers in the returned CIM - XML representation is
preserved from the : class : ` ~ pywbem . CIMProperty ` object .
Returns :
The CIM - XML representation , as an object of an appropriate subclass
of : term : ` Element ` .""" | qualifiers = [ q . tocimxml ( ) for q in self . qualifiers . values ( ) ]
if self . is_array : # pylint : disable = no - else - return
assert self . type != 'reference'
if self . value is None :
value_xml = None
else :
array_xml = [ ]
for v in self . value :
if v is None :
if SEND_VALUE_NULL :
array_xml . append ( cim_xml . VALUE_NULL ( ) )
else :
array_xml . append ( cim_xml . VALUE ( None ) )
elif self . embedded_object is not None :
assert isinstance ( v , ( CIMInstance , CIMClass ) )
array_xml . append ( cim_xml . VALUE ( v . tocimxml ( ) . toxml ( ) ) )
else :
array_xml . append ( cim_xml . VALUE ( atomic_to_cim_xml ( v ) ) )
value_xml = cim_xml . VALUE_ARRAY ( array_xml )
return cim_xml . PROPERTY_ARRAY ( self . name , self . type , value_xml , self . array_size , self . class_origin , self . propagated , embedded_object = self . embedded_object , qualifiers = qualifiers )
elif self . type == 'reference' : # scalar
if self . value is None :
value_xml = None
else :
value_xml = cim_xml . VALUE_REFERENCE ( self . value . tocimxml ( ) )
return cim_xml . PROPERTY_REFERENCE ( self . name , value_xml , reference_class = self . reference_class , class_origin = self . class_origin , propagated = self . propagated , qualifiers = qualifiers )
else : # scalar non - reference
if self . value is None :
value_xml = None
else :
if self . embedded_object is not None :
assert isinstance ( self . value , ( CIMInstance , CIMClass ) )
value_xml = cim_xml . VALUE ( self . value . tocimxml ( ) . toxml ( ) )
else :
value_xml = cim_xml . VALUE ( atomic_to_cim_xml ( self . value ) )
return cim_xml . PROPERTY ( self . name , self . type , value_xml , class_origin = self . class_origin , propagated = self . propagated , embedded_object = self . embedded_object , qualifiers = qualifiers ) |
def ecg_systole ( ecg , rpeaks , t_waves_ends ) :
"""Returns the localization of systoles and diastoles .
Parameters
ecg : list or ndarray
ECG signal ( preferably filtered ) .
rpeaks : list or ndarray
R peaks localization .
t _ waves _ ends : list or ndarray
T waves localization .
Returns
systole : ndarray
Array indicating where systole ( 1 ) and diastole ( 0 ) .
Example
> > > import neurokit as nk
> > > systole = nk . ecg _ systole ( ecg , rpeaks , t _ waves _ ends )
Notes
* Authors *
- ` Dominique Makowski < https : / / dominiquemakowski . github . io / > ` _
* Details *
- * * Systole / Diastole * * : One prominent channel of body and brain communication is that conveyed by baroreceptors , pressure and stretch - sensitive receptors within the heart and surrounding arteries . Within each cardiac cycle , bursts of baroreceptor afferent activity encoding the strength and timing of each heartbeat are carried via the vagus and glossopharyngeal nerve afferents to the nucleus of the solitary tract . This is the principal route that communicates to the brain the dynamic state of the heart , enabling the representation of cardiovascular arousal within viscerosensory brain regions , and influence ascending neuromodulator systems implicated in emotional and motivational behaviour . Because arterial baroreceptors are activated by the arterial pulse pressure wave , their phasic discharge is maximal during and immediately after the cardiac systole , that is , when the blood is ejected from the heart , and minimal during cardiac diastole , that is , between heartbeats ( Azevedo , 2017 ) .
References
- Azevedo , R . T . , Garfinkel , S . N . , Critchley , H . D . , & Tsakiris , M . ( 2017 ) . Cardiac afferent activity modulates the expression of racial stereotypes . Nature communications , 8.
- Edwards , L . , Ring , C . , McIntyre , D . , & Carroll , D . ( 2001 ) . Modulation of the human nociceptive flexion reflex across the cardiac cycle . Psychophysiology , 38(4 ) , 712-718.
- Gray , M . A . , Rylander , K . , Harrison , N . A . , Wallin , B . G . , & Critchley , H . D . ( 2009 ) . Following one ' s heart : cardiac rhythms gate central initiation of sympathetic reflexes . Journal of Neuroscience , 29(6 ) , 1817-1825.""" | waves = np . array ( [ "" ] * len ( ecg ) )
waves [ rpeaks ] = "R"
waves [ t_waves_ends ] = "T"
systole = [ 0 ]
current = 0
for index , value in enumerate ( waves [ 1 : ] ) :
if waves [ index - 1 ] == "R" :
current = 1
if waves [ index - 1 ] == "T" :
current = 0
systole . append ( current )
return ( systole ) |
def omero_bin ( self , command ) :
"""Runs the omero command - line client with an array of arguments using the
old environment""" | assert isinstance ( command , list )
if not self . old_env :
raise Exception ( 'Old environment not initialised' )
log . info ( "Running [old environment]: %s" , " " . join ( command ) )
self . run ( 'omero' , command , capturestd = True , env = self . old_env ) |
def has_entities ( status ) :
"""Returns true if a Status object has entities .
Args :
status : either a tweepy . Status object or a dict returned from Twitter API""" | try :
if sum ( len ( v ) for v in status . entities . values ( ) ) > 0 :
return True
except AttributeError :
if sum ( len ( v ) for v in status [ 'entities' ] . values ( ) ) > 0 :
return True
return False |
def get_version ( dev_version = False ) :
"""Generates a version string .
Arguments :
dev _ version : Generate a verbose development version from git commits .
Examples :
1.1
1.1 . dev43 # If ' dev _ version ' was passed .""" | if dev_version :
version = git_dev_version ( )
if not version :
raise RuntimeError ( "Could not generate dev version from git." )
return version
return "1!%d.%d" % ( MAJOR , MINOR ) |
def play ( self ) :
"""Send signal to resume playback at the paused offset""" | self . _response [ 'shouldEndSession' ] = True
self . _response [ 'action' ] [ 'audio' ] [ 'interface' ] = 'play'
self . _response [ 'action' ] [ 'audio' ] [ 'sources' ] = [ ]
return self |
def limit ( self , maximum ) :
"""Return a new query , limited to a certain number of results .
Unlike core reporting queries , you cannot specify a starting
point for live queries , just the maximum results returned .
` ` ` python
# first 50
query . limit ( 50)""" | self . meta [ 'limit' ] = maximum
self . raw . update ( { 'max_results' : maximum , } )
return self |
def add_triple ( self , subj : Union [ URIRef , str ] , pred : Union [ URIRef , str ] , obj : Union [ URIRef , Literal , str ] ) -> None :
"""Adds triple to rdflib Graph
Triple can be of any subject , predicate , and object of the entity without a need for order .
Args :
subj : Entity subject
pred : Entity predicate
obj : Entity object
Example :
In [ 1 ] : add _ triple (
. . . : ' http : / / uri . interlex . org / base / ilx _ 0101431 ' ,
. . . : RDF . type ,
. . . : ' http : / / www . w3 . org / 2002/07 / owl # Class ' )""" | if obj in [ None , "" , " " ] :
return
# Empty objects are bad practice
_subj = self . process_subj_or_pred ( subj )
_pred = self . process_subj_or_pred ( pred )
_obj = self . process_obj ( obj )
self . g . add ( ( _subj , _pred , _obj ) ) |
def xmoe2_v1_l4k_compressed_c4 ( ) :
"""With compressed attention .""" | hparams = xmoe2_v1_l4k ( )
hparams . decoder_layers = [ "compressed_att" if l == "att" else l for l in hparams . decoder_layers ]
hparams . compression_factor = 4
return hparams |
def get_broks ( self , broker_name ) :
"""Send a HTTP request to the satellite ( GET / _ broks )
Get broks from the satellite .
Un - serialize data received .
: param broker _ name : the concerned broker link
: type broker _ name : BrokerLink
: return : Broks list on success , [ ] on failure
: rtype : list""" | res = self . con . get ( '_broks' , { 'broker_name' : broker_name } , wait = False )
logger . debug ( "Got broks from %s: %s" , self . name , res )
return unserialize ( res , True ) |
async def close_wallet_search ( wallet_search_handle : int ) -> None :
"""Close wallet search ( make search handle invalid )
: param wallet _ search _ handle : wallet wallet handle ( created by open _ wallet _ search )
: return : None""" | logger = logging . getLogger ( __name__ )
logger . debug ( "close_wallet_search: >>> wallet_search_handle: %r" , wallet_search_handle )
if not hasattr ( close_wallet_search , "cb" ) :
logger . debug ( "close_wallet_search: Creating callback" )
close_wallet_search . cb = create_cb ( CFUNCTYPE ( None , c_int32 , c_int32 ) )
c_wallet_search_handle = c_int32 ( wallet_search_handle )
res = await do_call ( 'indy_close_wallet_search' , c_wallet_search_handle , close_wallet_search . cb )
logger . debug ( "close_wallet_search: <<< res: %r" , res )
return res |
def most_similar ( self , word , number = 5 ) :
"""Run a similarity query , retrieving number
most similar words .""" | if self . word_vectors is None :
raise Exception ( 'Model must be fit before querying' )
if self . dictionary is None :
raise Exception ( 'No word dictionary supplied' )
try :
word_idx = self . dictionary [ word ]
except KeyError :
raise Exception ( 'Word not in dictionary' )
return self . _similarity_query ( self . word_vectors [ word_idx ] , number ) [ 1 : ] |
def audiorate ( filename ) :
"""Determines the samplerate of the given audio recording file
: param filename : filename of the audiofile
: type filename : str
: returns : int - - samplerate of the recording""" | if '.wav' in filename . lower ( ) :
wf = wave . open ( filename )
fs = wf . getframerate ( )
wf . close ( )
elif '.call' in filename . lower ( ) :
fs = 333333
else :
raise IOError ( "Unsupported audio format for file: {}" . format ( filename ) )
return fs |
def _createBitpattern ( functioncode , value ) :
"""Create the bit pattern that is used for writing single bits .
This is basically a storage of numerical constants .
Args :
* functioncode ( int ) : can be 5 or 15
* value ( int ) : can be 0 or 1
Returns :
The bit pattern ( string ) .
Raises :
TypeError , ValueError""" | _checkFunctioncode ( functioncode , [ 5 , 15 ] )
_checkInt ( value , minvalue = 0 , maxvalue = 1 , description = 'inputvalue' )
if functioncode == 5 :
if value == 0 :
return '\x00\x00'
else :
return '\xff\x00'
elif functioncode == 15 :
if value == 0 :
return '\x00'
else :
return '\x01' |
def flush ( self , hard = False ) :
"""Drop existing entries from the cache .
Args :
hard ( bool ) : If True , all current entries are flushed from the
server ( s ) , which affects all users . If False , only the local
process is affected .""" | if not self . servers :
return
if hard :
self . client . flush_all ( )
self . reset_stats ( )
else :
from uuid import uuid4
tag = uuid4 ( ) . hex
if self . debug :
tag = "flushed" + tag
self . current = tag |
def split_arg_to_name_type_value ( self , args_list ) :
"""Split argument text to name , type , value .""" | for arg in args_list :
arg_type = None
arg_value = None
has_type = False
has_value = False
pos_colon = arg . find ( ':' )
pos_equal = arg . find ( '=' )
if pos_equal > - 1 :
has_value = True
if pos_colon > - 1 :
if not has_value :
has_type = True
elif pos_equal > pos_colon : # exception for def foo ( arg1 = " : " )
has_type = True
if has_value and has_type :
arg_name = arg [ 0 : pos_colon ] . strip ( )
arg_type = arg [ pos_colon + 1 : pos_equal ] . strip ( )
arg_value = arg [ pos_equal + 1 : ] . strip ( )
elif not has_value and has_type :
arg_name = arg [ 0 : pos_colon ] . strip ( )
arg_type = arg [ pos_colon + 1 : ] . strip ( )
elif has_value and not has_type :
arg_name = arg [ 0 : pos_equal ] . strip ( )
arg_value = arg [ pos_equal + 1 : ] . strip ( )
else :
arg_name = arg . strip ( )
self . arg_name_list . append ( arg_name )
self . arg_type_list . append ( arg_type )
self . arg_value_list . append ( arg_value ) |
def n_orifices_per_row ( self ) :
"""Calculate number of orifices at each level given an orifice
diameter .""" | # H is distance from the bottom of the next row of orifices to the
# center of the current row of orifices
H = self . b_rows - 0.5 * self . orifice_diameter
flow_per_orifice = pc . flow_orifice_vert ( self . orifice_diameter , H , con . VC_ORIFICE_RATIO )
n = np . zeros ( self . n_rows )
for i in range ( self . n_rows ) : # calculate the ideal number of orifices at the current row without
# constraining to an integer
flow_needed = self . flow_ramp [ i ] - self . flow_actual ( i , n )
n_orifices_real = ( flow_needed / flow_per_orifice ) . to ( u . dimensionless )
# constrain number of orifices to be less than the max per row and
# greater or equal to 0
n [ i ] = min ( ( max ( 0 , round ( n_orifices_real ) ) ) , self . n_orifices_per_row_max )
return n |
def parts ( self ) :
"""Return an array of batch parts to submit""" | parts = [ ]
upserts = dict ( )
deletes = [ ]
# we keep track of the batch size as we go ( pretty close approximation ! ) so we can chunk it small enough
# to limit the HTTP posts to under 700KB - server limits to 750KB , so play it safe
max_upload_size = 700000
# loop upserts first - fit the deletes in afterward
# ' { " replace _ all " : true , " complete " : false , " guid " : " 6659fbfc - 3f08-42ee - 998c - 9109f650f4b7 " , " upserts " : [ ] , " deletes " : [ ] } '
base_part_size = 118
if not self . replace_all :
base_part_size += 1
# yeah , this is totally overkill : )
part_size = base_part_size
for value in self . upserts :
if ( part_size + self . upserts_size [ value ] ) >= max_upload_size : # this record would put us over the limit - close out the batch part and start a new one
parts . append ( BatchPart ( self . replace_all , upserts , deletes ) )
upserts = dict ( )
deletes = [ ]
part_size = base_part_size
# for the new upserts dict , drop the lower - casing of value
upserts [ self . lower_val_to_val [ value ] ] = self . upserts [ value ]
part_size += self . upserts_size [ value ]
# updating the approximate size of the batch
for value in self . deletes : # delete adds length of string plus quotes , comma and space
if ( part_size + len ( value ) + 4 ) >= max_upload_size :
parts . append ( BatchPart ( self . replace_all , upserts , deletes ) )
upserts = dict ( )
deletes = [ ]
part_size = base_part_size
# for the new deletes set , drop the lower - casing of value
deletes . append ( { 'value' : self . lower_val_to_val [ value ] } )
part_size += len ( value ) + 4
if len ( upserts ) + len ( deletes ) > 0 : # finish the batch
parts . append ( BatchPart ( self . replace_all , upserts , deletes ) )
if len ( parts ) == 0 :
if not self . replace_all :
raise ValueError ( "Batch has no data, and 'replace_all' is False" )
parts . append ( BatchPart ( self . replace_all , dict ( ) , [ ] ) )
# last part finishes the batch
parts [ - 1 ] . set_last_part ( )
return parts |
def _keepVol ( self , vol ) :
"""Mark this volume to be kept in path .""" | if vol is None :
return
if vol in self . extraVolumes :
del self . extraVolumes [ vol ]
return
if vol not in self . paths :
raise Exception ( "%s not in %s" % ( vol , self ) )
paths = [ os . path . basename ( path ) for path in self . paths [ vol ] ]
newPath = self . selectReceivePath ( paths )
if self . _skipDryRun ( logger , 'INFO' ) ( "Copy %s to %s" , vol , newPath ) :
return
self . butterVolumes [ vol . uuid ] . copy ( newPath ) |
def get_sls_opts ( opts , ** kwargs ) :
'''Return a copy of the opts for use , optionally load a local config on top''' | opts = copy . deepcopy ( opts )
if 'localconfig' in kwargs :
return salt . config . minion_config ( kwargs [ 'localconfig' ] , defaults = opts )
if 'saltenv' in kwargs :
saltenv = kwargs [ 'saltenv' ]
if saltenv is not None :
if not isinstance ( saltenv , six . string_types ) :
saltenv = six . text_type ( saltenv )
if opts [ 'lock_saltenv' ] and saltenv != opts [ 'saltenv' ] :
raise CommandExecutionError ( 'lock_saltenv is enabled, saltenv cannot be changed' )
opts [ 'saltenv' ] = kwargs [ 'saltenv' ]
pillarenv = None
if kwargs . get ( 'pillarenv' ) :
pillarenv = kwargs . get ( 'pillarenv' )
if opts . get ( 'pillarenv_from_saltenv' ) and not pillarenv :
pillarenv = kwargs . get ( 'saltenv' )
if pillarenv is not None and not isinstance ( pillarenv , six . string_types ) :
opts [ 'pillarenv' ] = six . text_type ( pillarenv )
else :
opts [ 'pillarenv' ] = pillarenv
return opts |
def _create_latent_variables ( self ) :
"""Creates model latent variables
Returns
None ( changes model attributes )""" | for parm in range ( self . z_no ) :
self . latent_variables . add_z ( 'Scale ' + self . X_names [ parm ] , fam . Flat ( transform = 'exp' ) , fam . Normal ( 0 , 3 ) )
self . latent_variables . z_list [ parm ] . start = - 5.0
self . z_no = len ( self . latent_variables . z_list ) |
def _get_by_id ( collection , id ) :
'''Get item from a list by the id field''' | matches = [ item for item in collection if item . id == id ]
if not matches :
raise ValueError ( 'Could not find a matching item' )
elif len ( matches ) > 1 :
raise ValueError ( 'The id matched {0} items, not 1' . format ( len ( matches ) ) )
return matches [ 0 ] |
def getlang_by_native_name ( native_name ) :
"""Try to lookup a Language object by native _ name , e . g . ' English ' , in internal language list .
Returns None if lookup by language name fails in resources / languagelookup . json .""" | direct_match = _iget ( native_name , _LANGUAGE_NATIVE_NAME_LOOKUP )
if direct_match :
return direct_match
else :
simple_native_name = native_name . split ( ',' ) [ 0 ]
# take part before comma
simple_native_name = simple_native_name . split ( '(' ) [ 0 ] . strip ( )
# and before any bracket
return _LANGUAGE_NATIVE_NAME_LOOKUP . get ( simple_native_name , None ) |
End of preview. Expand
in Dataset Viewer.
README.md exists but content is empty.
- Downloads last month
- 56