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def view ( self , start , end , max_items = None , * args , ** kwargs ) : """Implements the CalendarView option to FindItem . The difference between filter ( ) and view ( ) is that filter ( ) only returns the master CalendarItem for recurring items , while view ( ) unfolds recurring items and returns all CalendarItem occurrences as one would normally expect when presenting a calendar . Supports the same semantics as filter , except for ' start ' and ' end ' keyword attributes which are both required and behave differently than filter . Here , they denote the start and end of the timespan of the view . All items the overlap the timespan are returned ( items that end exactly on ' start ' are also returned , for some reason ) . EWS does not allow combining CalendarView with search restrictions ( filter and exclude ) . ' max _ items ' defines the maximum number of items returned in this view . Optional ."""
qs = QuerySet ( self ) . filter ( * args , ** kwargs ) qs . calendar_view = CalendarView ( start = start , end = end , max_items = max_items ) return qs
def load_from_file ( path , fmt = None , is_training = True ) : '''load data from file'''
if fmt is None : fmt = 'squad' assert fmt in [ 'squad' , 'csv' ] , 'input format must be squad or csv' qp_pairs = [ ] if fmt == 'squad' : with open ( path ) as data_file : data = json . load ( data_file ) [ 'data' ] for doc in data : for paragraph in doc [ 'paragraphs' ] : passage = paragraph [ 'context' ] for qa_pair in paragraph [ 'qas' ] : question = qa_pair [ 'question' ] qa_id = qa_pair [ 'id' ] if not is_training : qp_pairs . append ( { 'passage' : passage , 'question' : question , 'id' : qa_id } ) else : for answer in qa_pair [ 'answers' ] : answer_begin = int ( answer [ 'answer_start' ] ) answer_end = answer_begin + len ( answer [ 'text' ] ) qp_pairs . append ( { 'passage' : passage , 'question' : question , 'id' : qa_id , 'answer_begin' : answer_begin , 'answer_end' : answer_end } ) else : with open ( path , newline = '' ) as csvfile : reader = csv . reader ( csvfile , delimiter = '\t' ) line_num = 0 for row in reader : qp_pairs . append ( { 'passage' : row [ 1 ] , 'question' : row [ 0 ] , 'id' : line_num } ) line_num += 1 return qp_pairs
def _enumerate_directions ( x ) : """For an n - dimensional tensor , returns tensors to enumerate each axis . > > > x = np . zeros ( [ 2 , 3 , 4 ] ) # or any other tensor > > > i , j , k = _ enumerate _ directions ( x ) > > > result = i + 2 * j + 3 * k result [ i , j , k ] = i + 2 * j + 3 * k , and also has the same shape as result Works very similarly to numpy . ogrid ( open indexing grid )"""
backend = get_backend ( x ) shape = backend . shape ( x ) result = [ ] for axis_id , axis_length in enumerate ( shape ) : shape = [ 1 ] * len ( shape ) shape [ axis_id ] = axis_length result . append ( backend . reshape ( backend . arange ( 0 , axis_length ) , shape ) ) return result
def get_trans_reg ( self , name : Text , default : Any = None ) -> Any : """Convenience function to access the transition register of a specific kind . : param name : Name of the register you want to see : param default : What to return by default"""
tr = self . register . get ( Register . TRANSITION , { } ) return tr . get ( name , default )
def bind ( self , instance , auto = False ) : """Bind deps to instance : param instance : : param auto : follow update of DI and refresh binds once we will get something new : return :"""
methods = [ ( m , cls . __dict__ [ m ] ) for cls in inspect . getmro ( type ( instance ) ) for m in cls . __dict__ if inspect . isfunction ( cls . __dict__ [ m ] ) ] try : deps_of_endpoints = [ ( method_ptr , self . entrypoint_deps ( method_ptr ) ) for ( method_name , method_ptr ) in methods ] for ( method_ptr , method_deps ) in deps_of_endpoints : if len ( method_deps ) > 0 : method_ptr ( instance , ** method_deps ) except KeyError : pass if auto and instance not in self . current_scope . get_auto_bind_list ( ) : self . current_scope . auto_bind ( instance ) return instance
def get_persistent_items ( self ) : """Returns attached container items and container configurations that are marked as persistent . Each returned item is in the format ` ` ( config name , instance / attached name ) ` ` , where the instance name can also be ` ` None ` ` . : return : Lists of attached items . : rtype : ( list [ ( unicode | str , unicode | str ) ] , list [ unicode | str , unicode | str | NoneType ] )"""
attached_items = [ ( container , ac ) for container , config in self for ac in config . attaches ] persistent_containers = [ ( container , ci ) for container , config in self if config . persistent for ci in config . instances or [ None ] ] return attached_items , persistent_containers
def X ( self , i , j = slice ( None , None , None ) ) : '''Computes the design matrix at the given * PLD * order and the given indices . The columns are the * PLD * vectors for the target at the corresponding order , computed as the product of the fractional pixel flux of all sets of : py : obj : ` n ` pixels , where : py : obj : ` n ` is the * PLD * order .'''
X1 = self . fpix [ j ] / self . norm [ j ] . reshape ( - 1 , 1 ) X = np . product ( list ( multichoose ( X1 . T , i + 1 ) ) , axis = 1 ) . T if self . X1N is not None : return np . hstack ( [ X , self . X1N [ j ] ** ( i + 1 ) ] ) else : return X
def create ( zpool , * vdevs , ** kwargs ) : '''. . versionadded : : 2015.5.0 Create a simple zpool , a mirrored zpool , a zpool having nested VDEVs , a hybrid zpool with cache , spare and log drives or a zpool with RAIDZ - 1 , RAIDZ - 2 or RAIDZ - 3 zpool : string Name of storage pool vdevs : string One or move devices force : boolean Forces use of vdevs , even if they appear in use or specify a conflicting replication level . mountpoint : string Sets the mount point for the root dataset altroot : string Equivalent to " - o cachefile = none , altroot = root " properties : dict Additional pool properties filesystem _ properties : dict Additional filesystem properties createboot : boolean create a boot partition . . versionadded : : 2018.3.0 . . warning : This is only available on illumos and Solaris CLI Examples : . . code - block : : bash salt ' * ' zpool . create myzpool / path / to / vdev1 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myzpool mirror / path / to / vdev1 / path / to / vdev2 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myzpool raidz1 / path / to / vdev1 / path / to / vdev2 raidz2 / path / to / vdev3 / path / to / vdev4 / path / to / vdev5 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myzpool mirror / path / to / vdev1 [ . . . ] mirror / path / to / vdev2 / path / to / vdev3 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myhybridzpool mirror / tmp / file1 [ . . . ] log mirror / path / to / vdev1 [ . . . ] cache / path / to / vdev2 [ . . . ] spare / path / to / vdev3 [ . . . ] [ force = True | False ] . . note : : Zpool properties can be specified at the time of creation of the pool by passing an additional argument called " properties " and specifying the properties with their respective values in the form of a python dictionary : . . code - block : : text properties = " { ' property1 ' : ' value1 ' , ' property2 ' : ' value2 ' } " Filesystem properties can be specified at the time of creation of the pool by passing an additional argument called " filesystem _ properties " and specifying the properties with their respective values in the form of a python dictionary : . . code - block : : text filesystem _ properties = " { ' property1 ' : ' value1 ' , ' property2 ' : ' value2 ' } " Example : . . code - block : : bash salt ' * ' zpool . create myzpool / path / to / vdev1 [ . . . ] properties = " { ' property1 ' : ' value1 ' , ' property2 ' : ' value2 ' } " CLI Example : . . code - block : : bash salt ' * ' zpool . create myzpool / path / to / vdev1 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myzpool mirror / path / to / vdev1 / path / to / vdev2 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myzpool raidz1 / path / to / vdev1 / path / to / vdev2 raidz2 / path / to / vdev3 / path / to / vdev4 / path / to / vdev5 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myzpool mirror / path / to / vdev1 [ . . . ] mirror / path / to / vdev2 / path / to / vdev3 [ . . . ] [ force = True | False ] salt ' * ' zpool . create myhybridzpool mirror / tmp / file1 [ . . . ] log mirror / path / to / vdev1 [ . . . ] cache / path / to / vdev2 [ . . . ] spare / path / to / vdev3 [ . . . ] [ force = True | False ]'''
# # Configure pool # NOTE : initialize the defaults flags = [ ] opts = { } target = [ ] # NOTE : push pool and filesystem properties pool_properties = kwargs . get ( 'properties' , { } ) filesystem_properties = kwargs . get ( 'filesystem_properties' , { } ) # NOTE : set extra config based on kwargs if kwargs . get ( 'force' , False ) : flags . append ( '-f' ) if kwargs . get ( 'createboot' , False ) or 'bootsize' in pool_properties : flags . append ( '-B' ) if kwargs . get ( 'altroot' , False ) : opts [ '-R' ] = kwargs . get ( 'altroot' ) if kwargs . get ( 'mountpoint' , False ) : opts [ '-m' ] = kwargs . get ( 'mountpoint' ) # NOTE : append the pool name and specifications target . append ( zpool ) target . extend ( vdevs ) # # Create storage pool res = __salt__ [ 'cmd.run_all' ] ( __utils__ [ 'zfs.zpool_command' ] ( command = 'create' , flags = flags , opts = opts , pool_properties = pool_properties , filesystem_properties = filesystem_properties , target = target , ) , python_shell = False , ) ret = __utils__ [ 'zfs.parse_command_result' ] ( res , 'created' ) if ret [ 'created' ] : # # NOTE : lookup zpool status for vdev config ret [ 'vdevs' ] = _clean_vdev_config ( __salt__ [ 'zpool.status' ] ( zpool = zpool ) [ zpool ] [ 'config' ] [ zpool ] , ) return ret
def disable_process_breakpoints ( self , dwProcessId ) : """Disables all breakpoints for the given process . @ type dwProcessId : int @ param dwProcessId : Process global ID ."""
# disable code breakpoints for bp in self . get_process_code_breakpoints ( dwProcessId ) : self . disable_code_breakpoint ( dwProcessId , bp . get_address ( ) ) # disable page breakpoints for bp in self . get_process_page_breakpoints ( dwProcessId ) : self . disable_page_breakpoint ( dwProcessId , bp . get_address ( ) ) # disable hardware breakpoints if self . system . has_process ( dwProcessId ) : aProcess = self . system . get_process ( dwProcessId ) else : aProcess = Process ( dwProcessId ) aProcess . scan_threads ( ) for aThread in aProcess . iter_threads ( ) : dwThreadId = aThread . get_tid ( ) for bp in self . get_thread_hardware_breakpoints ( dwThreadId ) : self . disable_hardware_breakpoint ( dwThreadId , bp . get_address ( ) )
def request ( self , method , * , path = None , json = None , params = None , headers = None , timeout = None , backoff_cap = None , ** kwargs ) : """Performs an HTTP request with the given parameters . Implements exponential backoff . If ` ConnectionError ` occurs , a timestamp equal to now + the default delay ( ` BACKOFF _ DELAY ` ) is assigned to the object . The timestamp is in UTC . Next time the function is called , it either waits till the timestamp is passed or raises ` TimeoutError ` . If ` ConnectionError ` occurs two or more times in a row , the retry count is incremented and the new timestamp is calculated as now + the default delay multiplied by two to the power of the number of retries . If a request is successful , the backoff timestamp is removed , the retry count is back to zero . Args : method ( str ) : HTTP method ( e . g . : ` ` ' GET ' ` ` ) . path ( str ) : API endpoint path ( e . g . : ` ` ' / transactions ' ` ` ) . json ( dict ) : JSON data to send along with the request . params ( dict ) : Dictionary of URL ( query ) parameters . headers ( dict ) : Optional headers to pass to the request . timeout ( int ) : Optional timeout in seconds . backoff _ cap ( int ) : The maximal allowed backoff delay in seconds to be assigned to a node . kwargs : Optional keyword arguments ."""
backoff_timedelta = self . get_backoff_timedelta ( ) if timeout is not None and timeout < backoff_timedelta : raise TimeoutError if backoff_timedelta > 0 : time . sleep ( backoff_timedelta ) connExc = None timeout = timeout if timeout is None else timeout - backoff_timedelta try : response = self . _request ( method = method , timeout = timeout , url = self . node_url + path if path else self . node_url , json = json , params = params , headers = headers , ** kwargs , ) except ConnectionError as err : connExc = err raise err finally : self . update_backoff_time ( success = connExc is None , backoff_cap = backoff_cap ) return response
def action_delete ( self , ids ) : """Delete selected sessions ."""
is_current = any ( SessionActivity . is_current ( sid_s = id_ ) for id_ in ids ) if is_current : flash ( 'You could not remove your current session' , 'error' ) return for id_ in ids : delete_session ( sid_s = id_ ) db . session . commit ( )
def separated ( p , sep , mint , maxt = None , end = None ) : '''Repeat a parser ` p ` separated by ` s ` between ` mint ` and ` maxt ` times . When ` end ` is None , a trailing separator is optional . When ` end ` is True , a trailing separator is required . When ` end ` is False , a trailing separator is not allowed . MATCHES AS MUCH AS POSSIBLE . Return list of values returned by ` p ` .'''
maxt = maxt if maxt else mint @ Parser def sep_parser ( text , index ) : cnt , values , res = 0 , Value . success ( index , [ ] ) , None while cnt < maxt : if end in [ False , None ] and cnt > 0 : res = sep ( text , index ) if res . status : # ` sep ` found , consume it ( advance index ) index , values = res . index , Value . success ( res . index , values . value ) elif cnt < mint : return res # error : need more elemnts , but no ` sep ` found . else : break res = p ( text , index ) if res . status : values = values . aggregate ( Value . success ( res . index , [ res . value ] ) ) index , cnt = res . index , cnt + 1 elif cnt >= mint : break else : return res # error : need more elements , but no ` p ` found . if end is True : res = sep ( text , index ) if res . status : index , values = res . index , Value . success ( res . index , values . value ) else : return res # error : trailing ` sep ` not found if cnt >= maxt : break return values return sep_parser
def _F ( self , X ) : """analytic solution of the projection integral : param x : R / Rs : type x : float > 0"""
if isinstance ( X , int ) or isinstance ( X , float ) : if X < 1 and X > 0 : a = 1 / ( X ** 2 - 1 ) * ( 1 - 2 / np . sqrt ( 1 - X ** 2 ) * np . arctanh ( np . sqrt ( ( 1 - X ) / ( 1 + X ) ) ) ) elif X == 1 : a = 1. / 3 elif X > 1 : a = 1 / ( X ** 2 - 1 ) * ( 1 - 2 / np . sqrt ( X ** 2 - 1 ) * np . arctan ( np . sqrt ( ( X - 1 ) / ( 1 + X ) ) ) ) else : # X = = 0: c = 0.0000001 a = 1 / ( - 1 ) * ( 1 - 2 / np . sqrt ( 1 ) * np . arctanh ( np . sqrt ( ( 1 - c ) / ( 1 + c ) ) ) ) else : a = np . empty_like ( X ) x = X [ ( X < 1 ) & ( X > 0 ) ] a [ ( X < 1 ) & ( X > 0 ) ] = 1 / ( x ** 2 - 1 ) * ( 1 - 2 / np . sqrt ( 1 - x ** 2 ) * np . arctanh ( np . sqrt ( ( 1 - x ) / ( 1 + x ) ) ) ) a [ X == 1 ] = 1. / 3. x = X [ X > 1 ] a [ X > 1 ] = 1 / ( x ** 2 - 1 ) * ( 1 - 2 / np . sqrt ( x ** 2 - 1 ) * np . arctan ( np . sqrt ( ( x - 1 ) / ( 1 + x ) ) ) ) # a [ X > y ] = 0 c = 0.0000001 a [ X == 0 ] = 1 / ( - 1 ) * ( 1 - 2 / np . sqrt ( 1 ) * np . arctanh ( np . sqrt ( ( 1 - c ) / ( 1 + c ) ) ) ) return a
def pretty ( self ) : '''Return a string like ' / foo / bar . py : 230 in foo . bar . my _ func ' .'''
return '{}:{} in {}.{}' . format ( self . filename , self . line_number , self . module_name , self . function_name )
def key_absent ( name , use_32bit_registry = False ) : r'''. . versionadded : : 2015.5.4 Ensure a registry key is removed . This will remove the key , subkeys , and all value entries . Args : name ( str ) : A string representing the full path to the key to be removed to include the hive and the keypath . The hive can be any of the following : - HKEY _ LOCAL _ MACHINE or HKLM - HKEY _ CURRENT _ USER or HKCU - HKEY _ USER or HKU use _ 32bit _ registry ( bool ) : Use the 32bit portion of the registry . Applies only to 64bit windows . 32bit Windows will ignore this parameter . Default is False . Returns : dict : A dictionary showing the results of the registry operation . CLI Example : The following example will delete the ` ` SOFTWARE \ DeleteMe ` ` key in the ` ` HKEY _ LOCAL _ MACHINE ` ` hive including all its subkeys and value pairs . . . code - block : : yaml remove _ key _ demo : reg . key _ absent : - name : HKEY _ CURRENT _ USER \ SOFTWARE \ DeleteMe In the above example the path is interpreted as follows : - ` ` HKEY _ CURRENT _ USER ` ` is the hive - ` ` SOFTWARE \ DeleteMe ` ` is the key'''
ret = { 'name' : name , 'result' : True , 'changes' : { } , 'comment' : '' } hive , key = _parse_key ( name ) # Determine what to do if not __utils__ [ 'reg.read_value' ] ( hive = hive , key = key , use_32bit_registry = use_32bit_registry ) [ 'success' ] : ret [ 'comment' ] = '{0} is already absent' . format ( name ) return ret ret [ 'changes' ] = { 'reg' : { 'Removed' : { 'Key' : r'{0}\{1}' . format ( hive , key ) } } } # Check for test option if __opts__ [ 'test' ] : ret [ 'result' ] = None return ret # Delete the value __utils__ [ 'reg.delete_key_recursive' ] ( hive = hive , key = key , use_32bit_registry = use_32bit_registry ) if __utils__ [ 'reg.read_value' ] ( hive = hive , key = key , use_32bit_registry = use_32bit_registry ) [ 'success' ] : ret [ 'result' ] = False ret [ 'changes' ] = { } ret [ 'comment' ] = 'Failed to remove registry key {0}' . format ( name ) return ret
def despike ( self , window_length = 33 , samples = True , z = 2 ) : """Args : window ( int ) : window length in samples . Default 33 ( or 5 m for most curves sampled at 0.1524 m intervals ) . samples ( bool ) : window length is in samples . Use False for a window length given in metres . z ( float ) : Z score Returns : Curve ."""
window_length //= 1 if samples else self . step z *= np . nanstd ( self ) # Transform to curve ' s units curve_sm = self . _rolling_window ( window_length , np . median ) spikes = np . where ( np . nan_to_num ( self - curve_sm ) > z ) [ 0 ] spukes = np . where ( np . nan_to_num ( curve_sm - self ) > z ) [ 0 ] out = np . copy ( self ) params = self . __dict__ . copy ( ) out [ spikes ] = curve_sm [ spikes ] + z out [ spukes ] = curve_sm [ spukes ] - z return Curve ( out , params = params )
def get_date ( context , value ) : """Tries to return a DateTime . DateTime object"""
if not value : return None if isinstance ( value , DateTime ) : return value if isinstance ( value , datetime ) : return dt2DT ( value ) if not isinstance ( value , basestring ) : return None def try_parse ( date_string , format ) : if not format : return None try : struct_time = strptime ( date_string , format ) return datetime ( * struct_time [ : 6 ] ) except ValueError : pass return None def get_locale_format ( key , context ) : format = context . translate ( key , domain = "senaite.core" , mapping = { } ) # TODO : Is this replacement below strictly necessary ? return format . replace ( r"${" , '%' ) . replace ( '}' , '' ) # Try with prioritized formats formats = [ get_locale_format ( "date_format_long" , context ) , get_locale_format ( "date_format_short" , context ) , "%Y-%m-%d %H:%M" , "%Y-%m-%d" , "%Y-%m-%d %H:%M:%S" ] for pri_format in formats : val = try_parse ( value , pri_format ) if not val : continue val = dt2DT ( val ) if val . timezoneNaive ( ) : # Use local timezone for tz naive strings # see http : / / dev . plone . org / plone / ticket / 10141 zone = val . localZone ( safelocaltime ( val . timeTime ( ) ) ) parts = val . parts ( ) [ : - 1 ] + ( zone , ) val = DateTime ( * parts ) return val logger . warn ( "Unable to convert {} to datetime" . format ( value ) ) return None
def plot_kmf ( df , condition_col , censor_col , survival_col , strata_col = None , threshold = None , title = None , xlabel = None , ylabel = None , ax = None , with_condition_color = "#B38600" , no_condition_color = "#A941AC" , with_condition_label = None , no_condition_label = None , color_map = None , label_map = None , color_palette = "Set1" , ci_show = False , print_as_title = False ) : """Plot survival curves by splitting the dataset into two groups based on condition _ col . Report results for a log - rank test ( if two groups are plotted ) or CoxPH survival analysis ( if > 2 groups ) for association with survival . Regarding definition of groups : If condition _ col is numeric , values are split into 2 groups . - if threshold is defined , the groups are split on being > or < condition _ col - if threshold = = ' median ' , the threshold is set to the median of condition _ col If condition _ col is categorical or string , results are plotted for each unique value in the dataset . If condition _ col is None , results are plotted for all observations Currently , if ` strata _ col ` is given , the results are repeated among each stratum of the df . A truly " stratified " analysis is not yet supported by may be soon . Parameters df : dataframe condition _ col : string , column which contains the condition to split on survival _ col : string , column which contains the survival time censor _ col : string , strata _ col : optional string , denoting column containing data to stratify by ( default : None ) threshold : int or string , if int , condition _ col is thresholded at int , if ' median ' , condition _ col thresholded at its median if ' median - per - strata ' , & if stratified analysis then condition _ col thresholded by strata title : Title for the plot , default None ax : an existing matplotlib ax , optional , default None note : not currently supported when ` strata _ col ` is not None with _ condition _ color : str , hex code color for the with - condition curve no _ condition _ color : str , hex code color for the no - condition curve with _ condition _ label : str , optional , label for True condition case no _ condition _ label : str , optional , label for False condition case color _ map : dict , optional , mapping of hex - values to condition text in the form of { value _ name : color _ hex _ code } . defaults to ` sb . color _ palette ` using ` default _ color _ palette ` name , or * _ condition _ color options in case of boolean operators . label _ map : dict , optional , mapping of labels to condition text . defaults to " condition _ name = condition _ value " , or * _ condition _ label options in case of boolean operators . color _ palette : str , optional , name of sb . color _ palette to use if color _ map not provided . print _ as _ title : bool , optional , whether or not to print text within the plot ' s title vs . stdout , default False"""
# set reasonable default threshold value depending on type of condition _ col if threshold is None : if df [ condition_col ] . dtype != "bool" and np . issubdtype ( df [ condition_col ] . dtype , np . number ) : threshold = "median" # check inputs for threshold for validity elif isinstance ( threshold , numbers . Number ) : logger . debug ( "threshold value is numeric" ) elif threshold not in ( "median" , "median-per-strata" ) : raise ValueError ( "invalid input for threshold. Must be numeric, None, 'median', or 'median-per-strata'." ) elif threshold == "median-per-strata" and strata_col is None : raise ValueError ( "threshold given was 'median-per-strata' and yet `strata_col` was None. Did you mean 'median'?" ) # construct kwarg dict to pass to _ plot _ kmf _ single . # start with args that do not vary according to strata _ col arglist = dict ( condition_col = condition_col , survival_col = survival_col , censor_col = censor_col , threshold = threshold , with_condition_color = with_condition_color , no_condition_color = no_condition_color , with_condition_label = with_condition_label , no_condition_label = no_condition_label , color_map = color_map , label_map = label_map , xlabel = xlabel , ylabel = ylabel , ci_show = ci_show , color_palette = color_palette , print_as_title = print_as_title ) # if strata _ col is None , pass all parameters to _ plot _ kmf _ single if strata_col is None : arglist . update ( dict ( df = df , title = title , ax = ax ) ) return _plot_kmf_single ( ** arglist ) else : # prepare for stratified analysis if threshold == "median" : # by default , " median " threshold should be intra - strata median arglist [ "threshold" ] = df [ condition_col ] . dropna ( ) . median ( ) elif threshold == "median-per-strata" : arglist [ "threshold" ] = "median" # create axis / subplots for stratified results if ax is not None : raise ValueError ( "ax not supported with stratified analysis." ) n_strata = len ( df [ strata_col ] . unique ( ) ) f , ax = plt . subplots ( n_strata , sharex = True ) # create results dict to hold per - strata results results = dict ( ) # call _ plot _ kmf _ single for each of the strata for i , ( strat_name , strat_df ) in enumerate ( df . groupby ( strata_col ) ) : if n_strata == 1 : arglist [ "ax" ] = ax else : arglist [ "ax" ] = ax [ i ] subtitle = "{}: {}" . format ( strata_col , strat_name ) arglist [ "title" ] = subtitle arglist [ "df" ] = strat_df results [ subtitle ] = plot_kmf ( ** arglist ) [ print ( desc ) for desc in results [ subtitle ] . desc ] if title : f . suptitle ( title ) return results
def dtype ( self ) : """Pixel data type ."""
pixels_group = self . label [ 'IsisCube' ] [ 'Core' ] [ 'Pixels' ] byte_order = self . BYTE_ORDERS [ pixels_group [ 'ByteOrder' ] ] pixel_type = self . PIXEL_TYPES [ pixels_group [ 'Type' ] ] return pixel_type . newbyteorder ( byte_order )
def _gettables ( self ) : """Return a list of hdf5 tables name PyMCsamples ."""
groups = self . _h5file . list_nodes ( "/" ) if len ( groups ) == 0 : return [ ] else : return [ gr . PyMCsamples for gr in groups if gr . _v_name [ : 5 ] == 'chain' ]
def _load_texture ( file_name , resolver ) : """Load a texture from a file into a PIL image ."""
file_data = resolver . get ( file_name ) image = PIL . Image . open ( util . wrap_as_stream ( file_data ) ) return image
def upload ( state , host , hostname , filename , remote_filename = None , use_remote_sudo = False , ssh_keyscan = False , ssh_user = None , ) : '''Upload files to other servers using ` ` scp ` ` . + hostname : hostname to upload to + filename : file to upload + remote _ filename : where to upload the file to ( defaults to ` ` filename ` ` ) + use _ remote _ sudo : upload to a temporary location and move using sudo + ssh _ keyscan : execute ` ` ssh . keyscan ` ` before uploading the file + ssh _ user : connect with this user'''
remote_filename = remote_filename or filename # Figure out where we ' re connecting ( host or user @ host ) connection_target = hostname if ssh_user : connection_target = '@' . join ( ( ssh_user , hostname ) ) if ssh_keyscan : yield keyscan ( state , host , hostname ) # If we ' re not using sudo on the remote side , just scp the file over if not use_remote_sudo : yield 'scp {0} {1}:{2}' . format ( filename , connection_target , remote_filename ) else : # Otherwise - we need a temporary location for the file temp_remote_filename = state . get_temp_filename ( ) # scp it to the temporary location upload_cmd = 'scp {0} {1}:{2}' . format ( filename , connection_target , temp_remote_filename , ) yield upload_cmd # And sudo sudo to move it yield command ( state , host , connection_target , 'sudo mv {0} {1}' . format ( temp_remote_filename , remote_filename , ) )
def norm_int_dict ( int_dict ) : """Normalizes values in the given dict with int values . Parameters int _ dict : list A dict object mapping each key to an int value . Returns dict A dict where each key is mapped to its relative part in the sum of all dict values . Example > > > dict _ obj = { ' a ' : 3 , ' b ' : 5 , ' c ' : 2} > > > result = norm _ int _ dict ( dict _ obj ) > > > print ( sorted ( result . items ( ) ) ) [ ( ' a ' , 0.3 ) , ( ' b ' , 0.5 ) , ( ' c ' , 0.2 ) ]"""
norm_dict = int_dict . copy ( ) val_sum = sum ( norm_dict . values ( ) ) for key in norm_dict : norm_dict [ key ] = norm_dict [ key ] / val_sum return norm_dict
def _AbandonInactiveProcessingTasks ( self ) : """Marks processing tasks that exceed the inactive time as abandoned . This method does not lock the manager and should be called by a method holding the manager lock ."""
if self . _tasks_processing : inactive_time = time . time ( ) - self . _TASK_INACTIVE_TIME inactive_time = int ( inactive_time * definitions . MICROSECONDS_PER_SECOND ) # Abandon all tasks after they ' re identified so as not to modify the # dict while iterating over it . tasks_to_abandon = [ ] for task_identifier , task in iter ( self . _tasks_processing . items ( ) ) : if task . last_processing_time < inactive_time : logger . debug ( 'Abandoned processing task: {0:s}.' . format ( task_identifier ) ) self . SampleTaskStatus ( task , 'abandoned_processing' ) tasks_to_abandon . append ( ( task_identifier , task ) ) for task_identifier , task in tasks_to_abandon : self . _tasks_abandoned [ task_identifier ] = task del self . _tasks_processing [ task_identifier ]
def on_KeyPress ( self , event ) : '''To adjust the distance between pitch markers .'''
if event . GetKeyCode ( ) == wx . WXK_UP : self . dist10deg += 0.1 print ( 'Dist per 10 deg: %.1f' % self . dist10deg ) elif event . GetKeyCode ( ) == wx . WXK_DOWN : self . dist10deg -= 0.1 if self . dist10deg <= 0 : self . dist10deg = 0.1 print ( 'Dist per 10 deg: %.1f' % self . dist10deg ) # Toggle Widgets elif event . GetKeyCode ( ) == 49 : widgets = [ self . modeText , self . wpText ] self . toggleWidgets ( widgets ) elif event . GetKeyCode ( ) == 50 : widgets = [ self . batOutRec , self . batInRec , self . voltsText , self . ampsText , self . batPerText ] self . toggleWidgets ( widgets ) elif event . GetKeyCode ( ) == 51 : widgets = [ self . rollText , self . pitchText , self . yawText ] self . toggleWidgets ( widgets ) elif event . GetKeyCode ( ) == 52 : widgets = [ self . airspeedText , self . altitudeText , self . climbRateText ] self . toggleWidgets ( widgets ) elif event . GetKeyCode ( ) == 53 : widgets = [ self . altHistRect , self . altPlot , self . altMarker , self . altText2 ] self . toggleWidgets ( widgets ) elif event . GetKeyCode ( ) == 54 : widgets = [ self . headingTri , self . headingText , self . headingNorthTri , self . headingNorthText , self . headingWPTri , self . headingWPText ] self . toggleWidgets ( widgets ) # Update Matplotlib Plot self . canvas . draw ( ) self . canvas . Refresh ( ) self . Refresh ( ) self . Update ( )
def ajax ( authenticated = True , data_required = False , json_encoder = json . JSONEncoder ) : """Decorator to allow the wrappered view to exist in an AJAX environment . Provide a decorator to wrap a view method so that it may exist in an entirely AJAX environment : - data decoded from JSON as input and data coded as JSON as output - result status is coded in the HTTP status code ; any non - 2xx response data will be coded as a JSON string , otherwise the response type ( always JSON ) is specific to the method called . if authenticated is true then we ' ll make sure the current user is authenticated . If data _ required is true then we ' ll assert that there is a JSON body present . The wrapped view method should return either : - JSON serialisable data - an object of the django http . HttpResponse subclass ( one of JSONResponse or CreatedResponse is suggested ) - nothing Methods returning nothing ( or None explicitly ) will result in a 204 " NO CONTENT " being returned to the caller ."""
def decorator ( function , authenticated = authenticated , data_required = data_required ) : @ functools . wraps ( function , assigned = decorators . available_attrs ( function ) ) def _wrapped ( self , request , * args , ** kw ) : if authenticated and not request . user . is_authenticated : return JSONResponse ( 'not logged in' , 401 ) if not request . is_ajax ( ) : return JSONResponse ( 'request must be AJAX' , 400 ) # decode the JSON body if present request . DATA = None if request . body : try : request . DATA = jsonutils . loads ( request . body ) except ( TypeError , ValueError ) as e : return JSONResponse ( 'malformed JSON request: %s' % e , 400 ) if data_required : if not request . DATA : return JSONResponse ( 'request requires JSON body' , 400 ) # invoke the wrapped function , handling exceptions sanely try : data = function ( self , request , * args , ** kw ) if isinstance ( data , http . HttpResponse ) : return data elif data is None : return JSONResponse ( '' , status = 204 ) return JSONResponse ( data , json_encoder = json_encoder ) except http_errors as e : # exception was raised with a specific HTTP status for attr in [ 'http_status' , 'code' , 'status_code' ] : if hasattr ( e , attr ) : http_status = getattr ( e , attr ) break else : LOG . exception ( 'HTTP exception with no status/code' ) return JSONResponse ( str ( e ) , 500 ) return JSONResponse ( str ( e ) , http_status ) except Exception as e : LOG . exception ( 'error invoking apiclient' ) return JSONResponse ( str ( e ) , 500 ) return _wrapped return decorator
def get_changelog ( repo_path , from_commit = None ) : """Given a repo path and an option commit / tag / refspec to start from , will get the rpm compatible changelog Args : repo _ path ( str ) : path to the git repo from _ commit ( str ) : refspec ( partial commit hash , tag , branch , full refspec , partial refspec ) to start the changelog from Returns : str : Rpm compatible changelog"""
repo = dulwich . repo . Repo ( repo_path ) tags = get_tags ( repo ) refs = get_refs ( repo ) changelog = [ ] maj_version = 0 feat_version = 0 fix_version = 0 start_including = False cur_line = '' if from_commit is None : start_including = True for commit_sha , children in reversed ( get_children_per_first_parent ( repo_path ) . items ( ) ) : commit = repo . get_object ( commit_sha ) maj_version , feat_version , fix_version = get_version ( commit = commit , tags = tags , maj_version = maj_version , feat_version = feat_version , fix_version = fix_version , ) version = '%s.%s.%s' % ( maj_version , feat_version , fix_version ) if ( start_including or commit_sha . startswith ( from_commit ) or fuzzy_matches_refs ( from_commit , refs . get ( commit_sha , [ ] ) ) ) : cur_line = pretty_commit ( commit , version , ) for child in children : cur_line += pretty_commit ( repo . get_object ( child ) , version = None ) start_including = True changelog . append ( cur_line ) return '\n' . join ( reversed ( changelog ) )
def placeholder_plugin_filter ( self , request , queryset ) : """This is only used on models which use placeholders from the django - cms"""
if not request : return queryset if GLL . is_active : return queryset . filter ( language = GLL . language_code ) return queryset
def _iter_convert_to_object ( self , iterable ) : """Iterable yields tuples of ( binsha , mode , name ) , which will be converted to the respective object representation"""
for binsha , mode , name in iterable : path = join_path ( self . path , name ) try : yield self . _map_id_to_type [ mode >> 12 ] ( self . repo , binsha , mode , path ) except KeyError : raise TypeError ( "Unknown mode %o found in tree data for path '%s'" % ( mode , path ) )
def scramble_string ( s , key ) : """s is the puzzle ' s solution in column - major order , omitting black squares : i . e . if the puzzle is : C A T solution is CATAR Key is a 4 - digit number in the range 1000 < = key < = 9999"""
key = key_digits ( key ) for k in key : # foreach digit in the key s = shift ( s , key ) # for each char by each digit in the key in sequence s = s [ k : ] + s [ : k ] # cut the sequence around the key digit s = shuffle ( s ) # do a 1:1 shuffle of the ' deck ' return s
def full_travel_count ( self ) : """Returns the number of tacho counts in the full travel of the motor . When combined with the ` count _ per _ m ` atribute , you can use this value to calculate the maximum travel distance of the motor . ( linear motors only )"""
( self . _full_travel_count , value ) = self . get_cached_attr_int ( self . _full_travel_count , 'full_travel_count' ) return value
def _kbos_from_survey_sym_model_input_file ( model_file ) : """Load a Survey Simulator model file as an array of ephem EllipticalBody objects . @ param model _ file : @ return :"""
lines = storage . open_vos_or_local ( model_file ) . read ( ) . split ( '\n' ) kbos = [ ] for line in lines : if len ( line ) == 0 or line [ 0 ] == '#' : # skip initial column descriptors and the final blank line continue kbo = ephem . EllipticalBody ( ) values = line . split ( ) kbo . name = values [ 8 ] kbo . j = values [ 9 ] kbo . k = values [ 10 ] kbo . _a = float ( values [ 0 ] ) kbo . _e = float ( values [ 1 ] ) kbo . _inc = float ( values [ 2 ] ) kbo . _Om = float ( values [ 3 ] ) kbo . _om = float ( values [ 4 ] ) kbo . _M = float ( values [ 5 ] ) kbo . _H = float ( values [ 6 ] ) epoch = ephem . date ( 2453157.50000 - ephem . julian_date ( 0 ) ) kbo . _epoch_M = epoch kbo . _epoch = epoch kbos . append ( kbo ) return kbos
def _initialize ( self , show_bounds , reset_camera , outline ) : """Outlines the input dataset and sets up the scene"""
self . plotter . subplot ( * self . loc ) if outline is None : self . plotter . add_mesh ( self . input_dataset . outline_corners ( ) , reset_camera = False , color = vtki . rcParams [ 'outline_color' ] , loc = self . loc ) elif outline : self . plotter . add_mesh ( self . input_dataset . outline ( ) , reset_camera = False , color = vtki . rcParams [ 'outline_color' ] , loc = self . loc ) # add the axis labels if show_bounds : self . plotter . show_bounds ( reset_camera = False , loc = loc ) if reset_camera : cpos = self . plotter . get_default_cam_pos ( ) self . plotter . camera_position = cpos self . plotter . reset_camera ( ) self . plotter . camera_set = False
def mutate ( self , p_mutate ) : """Simulate mutation against a probability . p _ mutate : probability for mutation to occur"""
new_dna = [ ] for bit in self . dna : if random . random ( ) < p_mutate : new_bit = bit while new_bit == bit : new_bit = random . choice ( self . GENETIC_MATERIAL_OPTIONS ) bit = new_bit new_dna . append ( bit ) self . dna = '' . join ( new_dna )
def import_locations ( self , zone_file ) : """Parse zoneinfo zone description data files . ` ` import _ locations ( ) ` ` returns a list of : class : ` Zone ` objects . It expects data files in one of the following formats : : AN + 1211-06900America / Curacao AO - 0848 + 01314Africa / Luanda AQ - 7750 + 16636Antarctica / McMurdoMcMurdo Station , Ross Island Files containing the data in this format can be found in the : file : ` zone . tab ` file that is normally found in : file : ` / usr / share / zoneinfo ` on UNIX - like systems , or from the ` standard distribution site ` _ . When processed by ` ` import _ locations ( ) ` ` a ` ` list ` ` object of the following style will be returned : : [ Zone ( None , None , " AN " , " America / Curacao " , None ) , Zone ( None , None , " AO " , " Africa / Luanda " , None ) , Zone ( None , None , " AO " , " Antartica / McMurdo " , [ " McMurdo Station " , " Ross Island " ] ) ] Args : zone _ file ( iter ) : ` ` zone . tab ` ` data to read Returns : list : Locations as : class : ` Zone ` objects Raises : FileFormatError : Unknown file format . . _ standard distribution site : ftp : / / elsie . nci . nih . gov / pub /"""
self . _zone_file = zone_file field_names = ( 'country' , 'location' , 'zone' , 'comments' ) data = utils . prepare_csv_read ( zone_file , field_names , delimiter = r" " ) for row in ( x for x in data if not x [ 'country' ] . startswith ( '#' ) ) : if row [ 'comments' ] : row [ 'comments' ] = row [ 'comments' ] . split ( ', ' ) self . append ( Zone ( ** row ) )
def checar ( cliente_sat ) : """Checa em sequência os alertas registrados ( veja : func : ` registrar ` ) contra os dados da consulta ao status operacional do equipamento SAT . Este método irá então resultar em uma lista dos alertas ativos . : param cliente _ sat : Uma instância de : class : ` satcfe . clientelocal . ClienteSATLocal ` ou : class : ` satcfe . clientesathub . ClienteSATHub ` onde será invocado o método para consulta ao status operacional do equipamento SAT . : rtype : list"""
resposta = cliente_sat . consultar_status_operacional ( ) alertas = [ ] for classe_alerta in AlertaOperacao . alertas_registrados : alerta = classe_alerta ( resposta ) if alerta . checar ( ) : alertas . append ( alerta ) return alertas
def create ( vm_ ) : '''Create a single VM from a data dict CLI Example : . . code - block : : bash salt - cloud - p proxmox - ubuntu vmhostname'''
try : # Check for required profile parameters before sending any API calls . if vm_ [ 'profile' ] and config . is_profile_configured ( __opts__ , __active_provider_name__ or 'proxmox' , vm_ [ 'profile' ] , vm_ = vm_ ) is False : return False except AttributeError : pass ret = { } __utils__ [ 'cloud.fire_event' ] ( 'event' , 'starting create' , 'salt/cloud/{0}/creating' . format ( vm_ [ 'name' ] ) , args = __utils__ [ 'cloud.filter_event' ] ( 'creating' , vm_ , [ 'name' , 'profile' , 'provider' , 'driver' ] ) , sock_dir = __opts__ [ 'sock_dir' ] , transport = __opts__ [ 'transport' ] ) log . info ( 'Creating Cloud VM %s' , vm_ [ 'name' ] ) if 'use_dns' in vm_ and 'ip_address' not in vm_ : use_dns = vm_ [ 'use_dns' ] if use_dns : from socket import gethostbyname , gaierror try : ip_address = gethostbyname ( six . text_type ( vm_ [ 'name' ] ) ) except gaierror : log . debug ( 'Resolving of %s failed' , vm_ [ 'name' ] ) else : vm_ [ 'ip_address' ] = six . text_type ( ip_address ) try : newid = _get_next_vmid ( ) data = create_node ( vm_ , newid ) except Exception as exc : log . error ( 'Error creating %s on PROXMOX\n\n' 'The following exception was thrown when trying to ' 'run the initial deployment: \n%s' , vm_ [ 'name' ] , exc , # Show the traceback if the debug logging level is enabled exc_info_on_loglevel = logging . DEBUG ) return False ret [ 'creation_data' ] = data name = vm_ [ 'name' ] # hostname which we know if 'clone' in vm_ and vm_ [ 'clone' ] is True : vmid = newid else : vmid = data [ 'vmid' ] # vmid which we have received host = data [ 'node' ] # host which we have received nodeType = data [ 'technology' ] # VM tech ( Qemu / OpenVZ ) if 'agent_get_ip' not in vm_ or vm_ [ 'agent_get_ip' ] == 0 : # Determine which IP to use in order of preference : if 'ip_address' in vm_ : ip_address = six . text_type ( vm_ [ 'ip_address' ] ) elif 'public_ips' in data : ip_address = six . text_type ( data [ 'public_ips' ] [ 0 ] ) # first IP elif 'private_ips' in data : ip_address = six . text_type ( data [ 'private_ips' ] [ 0 ] ) # first IP else : raise SaltCloudExecutionFailure ( "Could not determine an IP address to use" ) # wait until the vm has been created so we can start it if not wait_for_created ( data [ 'upid' ] , timeout = 300 ) : return { 'Error' : 'Unable to create {0}, command timed out' . format ( name ) } if 'clone' in vm_ and vm_ [ 'clone' ] is True and vm_ [ 'technology' ] == 'qemu' : # If we cloned a machine , see if we need to reconfigure any of the options such as net0, # ide2 , etc . This enables us to have a different cloud - init ISO mounted for each VM that ' s # brought up log . info ( 'Configuring cloned VM' ) # Modify the settings for the VM one at a time so we can see any problems with the values # as quickly as possible for setting in 'sockets' , 'cores' , 'cpulimit' , 'memory' , 'onboot' , 'agent' : if setting in vm_ : # if the property is set , use it for the VM request postParams = { } postParams [ setting ] = vm_ [ setting ] query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) # cloud - init settings for setting in 'ciuser' , 'cipassword' , 'sshkeys' , 'nameserver' , 'searchdomain' : if setting in vm_ : # if the property is set , use it for the VM request postParams = { } postParams [ setting ] = vm_ [ setting ] query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) for setting_number in range ( 3 ) : setting = 'ide{0}' . format ( setting_number ) if setting in vm_ : postParams = { } postParams [ setting ] = vm_ [ setting ] query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) for setting_number in range ( 5 ) : setting = 'sata{0}' . format ( setting_number ) if setting in vm_ : vm_config = query ( 'get' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) ) if setting in vm_config : setting_params = vm_ [ setting ] setting_storage = setting_params . split ( ':' ) [ 0 ] setting_size = _stringlist_to_dictionary ( setting_params ) [ 'size' ] vm_disk_params = vm_config [ setting ] vm_disk_storage = vm_disk_params . split ( ':' ) [ 0 ] vm_disk_size = _stringlist_to_dictionary ( vm_disk_params ) [ 'size' ] # if storage is different , move the disk if setting_storage != vm_disk_storage : postParams = { } postParams [ 'disk' ] = setting postParams [ 'storage' ] = setting_storage postParams [ 'delete' ] = 1 node = query ( 'post' , 'nodes/{0}/qemu/{1}/move_disk' . format ( vm_ [ 'host' ] , vmid ) , postParams ) data = _parse_proxmox_upid ( node , vm_ ) # wait until the disk has been moved if not wait_for_task ( data [ 'upid' ] , timeout = 300 ) : return { 'Error' : 'Unable to move disk {0}, command timed out' . format ( setting ) } # if storage is different , move the disk if setting_size != vm_disk_size : postParams = { } postParams [ 'disk' ] = setting postParams [ 'size' ] = setting_size query ( 'put' , 'nodes/{0}/qemu/{1}/resize' . format ( vm_ [ 'host' ] , vmid ) , postParams ) else : postParams = { } postParams [ setting ] = vm_ [ setting ] query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) for setting_number in range ( 13 ) : setting = 'scsi{0}' . format ( setting_number ) if setting in vm_ : vm_config = query ( 'get' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) ) if setting in vm_config : setting_params = vm_ [ setting ] setting_storage = setting_params . split ( ':' ) [ 0 ] setting_size = _stringlist_to_dictionary ( setting_params ) [ 'size' ] vm_disk_params = vm_config [ setting ] vm_disk_storage = vm_disk_params . split ( ':' ) [ 0 ] vm_disk_size = _stringlist_to_dictionary ( vm_disk_params ) [ 'size' ] # if storage is different , move the disk if setting_storage != vm_disk_storage : postParams = { } postParams [ 'disk' ] = setting postParams [ 'storage' ] = setting_storage postParams [ 'delete' ] = 1 node = query ( 'post' , 'nodes/{0}/qemu/{1}/move_disk' . format ( vm_ [ 'host' ] , vmid ) , postParams ) data = _parse_proxmox_upid ( node , vm_ ) # wait until the disk has been moved if not wait_for_task ( data [ 'upid' ] , timeout = 300 ) : return { 'Error' : 'Unable to move disk {0}, command timed out' . format ( setting ) } # if storage is different , move the disk if setting_size != vm_disk_size : postParams = { } postParams [ 'disk' ] = setting postParams [ 'size' ] = setting_size query ( 'put' , 'nodes/{0}/qemu/{1}/resize' . format ( vm_ [ 'host' ] , vmid ) , postParams ) else : postParams = { } postParams [ setting ] = vm_ [ setting ] query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) # net strings are a list of comma seperated settings . We need to merge the settings so that # the setting in the profile only changes the settings it touches and the other settings # are left alone . An example of why this is necessary is because the MAC address is set # in here and generally you don ' t want to alter or have to know the MAC address of the new # instance , but you may want to set the VLAN bridge for example for setting_number in range ( 20 ) : setting = 'net{0}' . format ( setting_number ) if setting in vm_ : data = query ( 'get' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) ) # Generate a dictionary of settings from the existing string new_setting = { } if setting in data : new_setting . update ( _stringlist_to_dictionary ( data [ setting ] ) ) # Merge the new settings ( as a dictionary ) into the existing dictionary to get the # new merged settings new_setting . update ( _stringlist_to_dictionary ( vm_ [ setting ] ) ) # Convert the dictionary back into a string list postParams = { setting : _dictionary_to_stringlist ( new_setting ) } query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) for setting_number in range ( 20 ) : setting = 'ipconfig{0}' . format ( setting_number ) if setting in vm_ : data = query ( 'get' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) ) # Generate a dictionary of settings from the existing string new_setting = { } if setting in data : new_setting . update ( _stringlist_to_dictionary ( data [ setting ] ) ) # Merge the new settings ( as a dictionary ) into the existing dictionary to get the # new merged settings if setting_number == 0 and 'ip_address' in vm_ : if 'gw' in _stringlist_to_dictionary ( vm_ [ setting ] ) : new_setting . update ( _stringlist_to_dictionary ( 'ip={0}/24,gw={1}' . format ( vm_ [ 'ip_address' ] , _stringlist_to_dictionary ( vm_ [ setting ] ) [ 'gw' ] ) ) ) else : new_setting . update ( _stringlist_to_dictionary ( 'ip={0}/24' . format ( vm_ [ 'ip_address' ] ) ) ) else : new_setting . update ( _stringlist_to_dictionary ( vm_ [ setting ] ) ) # Convert the dictionary back into a string list postParams = { setting : _dictionary_to_stringlist ( new_setting ) } query ( 'post' , 'nodes/{0}/qemu/{1}/config' . format ( vm_ [ 'host' ] , vmid ) , postParams ) # VM has been created . Starting . . if not start ( name , vmid , call = 'action' ) : log . error ( 'Node %s (%s) failed to start!' , name , vmid ) raise SaltCloudExecutionFailure # Wait until the VM has fully started log . debug ( 'Waiting for state "running" for vm %s on %s' , vmid , host ) if not wait_for_state ( vmid , 'running' ) : return { 'Error' : 'Unable to start {0}, command timed out' . format ( name ) } # For QEMU VMs , we can get the IP Address from qemu - agent if 'agent_get_ip' in vm_ and vm_ [ 'agent_get_ip' ] == 1 : def __find_agent_ip ( vm_ ) : log . debug ( "Waiting for qemu-agent to start..." ) endpoint = 'nodes/{0}/qemu/{1}/agent/network-get-interfaces' . format ( vm_ [ 'host' ] , vmid ) interfaces = query ( 'get' , endpoint ) # If we get a result from the agent , parse it if 'result' in interfaces : for interface in interfaces [ 'result' ] : if_name = interface [ 'name' ] # Only check ethernet type interfaces , as they are not returned in any order if if_name . startswith ( 'eth' ) or if_name . startswith ( 'ens' ) : for if_addr in interface [ 'ip-addresses' ] : ip_addr = if_addr [ 'ip-address' ] # Ensure interface has a valid IPv4 address if if_addr [ 'ip-address-type' ] == 'ipv4' and ip_addr is not None : return six . text_type ( ip_addr ) raise SaltCloudExecutionFailure # We have to wait for a bit for qemu - agent to start try : ip_address = __utils__ [ 'cloud.wait_for_fun' ] ( __find_agent_ip , vm_ = vm_ ) except ( SaltCloudExecutionTimeout , SaltCloudExecutionFailure ) as exc : try : # If VM was created but we can ' t connect , destroy it . destroy ( vm_ [ 'name' ] ) except SaltCloudSystemExit : pass finally : raise SaltCloudSystemExit ( six . text_type ( exc ) ) log . debug ( 'Using IP address %s' , ip_address ) ssh_username = config . get_cloud_config_value ( 'ssh_username' , vm_ , __opts__ , default = 'root' ) ssh_password = config . get_cloud_config_value ( 'password' , vm_ , __opts__ , ) ret [ 'ip_address' ] = ip_address ret [ 'username' ] = ssh_username ret [ 'password' ] = ssh_password vm_ [ 'ssh_host' ] = ip_address vm_ [ 'password' ] = ssh_password ret = __utils__ [ 'cloud.bootstrap' ] ( vm_ , __opts__ ) # Report success ! log . info ( 'Created Cloud VM \'%s\'' , vm_ [ 'name' ] ) log . debug ( '\'%s\' VM creation details:\n%s' , vm_ [ 'name' ] , pprint . pformat ( data ) ) __utils__ [ 'cloud.fire_event' ] ( 'event' , 'created instance' , 'salt/cloud/{0}/created' . format ( vm_ [ 'name' ] ) , args = __utils__ [ 'cloud.filter_event' ] ( 'created' , vm_ , [ 'name' , 'profile' , 'provider' , 'driver' ] ) , sock_dir = __opts__ [ 'sock_dir' ] , ) return ret
def get_host ( self , endpoint_or_address ) : """Find a host in the metadata for a specific endpoint . If a string inet address is passed , iterate all hosts to match the : attr : ` ~ . pool . Host . broadcast _ rpc _ address ` attribute ."""
if not isinstance ( endpoint_or_address , EndPoint ) : return self . _get_host_by_address ( endpoint_or_address ) return self . _hosts . get ( endpoint_or_address )
def send_message ( self , message , sign = True ) : """Send the given message to the connection . @ type message : OmapiMessage @ param sign : whether the message needs to be signed @ raises OmapiError : @ raises socket . error :"""
if sign : message . sign ( self . authenticators [ self . defauth ] ) logger . debug ( "sending %s" , LazyStr ( message . dump_oneline ) ) self . transport . write ( message . as_string ( ) )
def tournament_name2number ( self , name ) : """Translate tournament name to tournament number . Args : name ( str ) : tournament name to translate Returns : number ( int ) : number of the tournament or ` None ` if unknown . Examples : > > > NumerAPI ( ) . tournament _ name2number ( ' delta ' ) > > > NumerAPI ( ) . tournament _ name2number ( ' foo ' ) None"""
tournaments = self . get_tournaments ( ) d = { t [ 'name' ] : t [ 'tournament' ] for t in tournaments } return d . get ( name , None )
def set_rest_notification ( self , url , hit_type_id ) : """Set a REST endpoint to recieve notifications about the HIT The newer AWS MTurk API does not support this feature , which means we cannot use boto3 here . Instead , we make the call manually after assembling a properly signed request ."""
ISO8601 = "%Y-%m-%dT%H:%M:%SZ" notification_version = "2006-05-05" API_version = "2014-08-15" data = { "AWSAccessKeyId" : self . aws_key , "HITTypeId" : hit_type_id , "Notification.1.Active" : "True" , "Notification.1.Destination" : url , "Notification.1.EventType.1" : "AssignmentAccepted" , "Notification.1.EventType.2" : "AssignmentAbandoned" , "Notification.1.EventType.3" : "AssignmentReturned" , "Notification.1.EventType.4" : "AssignmentSubmitted" , "Notification.1.EventType.5" : "HITReviewable" , "Notification.1.EventType.6" : "HITExpired" , "Notification.1.Transport" : "REST" , "Notification.1.Version" : notification_version , "Operation" : "SetHITTypeNotification" , "SignatureVersion" : "1" , "Timestamp" : time . strftime ( ISO8601 , time . gmtime ( ) ) , "Version" : API_version , } query_string , signature = self . _calc_old_api_signature ( data ) body = query_string + "&Signature=" + urllib . parse . quote_plus ( signature ) data [ "Signature" ] = signature headers = { "Content-Type" : "application/x-www-form-urlencoded; charset=UTF-8" , "Content-Length" : str ( len ( body ) ) , "Host" : self . legacy_host , } resp = requests . post ( "https://" + self . legacy_host , headers = headers , data = body ) return "<IsValid>True</IsValid>" in resp . text
def _toolkit_repr_print ( model , fields , section_titles , width = None ) : """Display a toolkit repr according to some simple rules . Parameters model : Turi Create model fields : List of lists of tuples Each tuple should be ( display _ name , field _ name ) , where field _ name can be a string or a _ precomputed _ field object . section _ titles : List of section titles , one per list in the fields arg . Example model _ fields = [ ( " L1 penalty " , ' l1 _ penalty ' ) , ( " L2 penalty " , ' l2 _ penalty ' ) , ( " Examples " , ' num _ examples ' ) , ( " Features " , ' num _ features ' ) , ( " Coefficients " , ' num _ coefficients ' ) ] solver _ fields = [ ( " Solver " , ' solver ' ) , ( " Solver iterations " , ' training _ iterations ' ) , ( " Solver status " , ' training _ solver _ status ' ) , ( " Training time ( sec ) " , ' training _ time ' ) ] training _ fields = [ ( " Log - likelihood " , ' training _ loss ' ) ] fields = [ model _ fields , solver _ fields , training _ fields ] : section _ titles = [ ' Model description ' , ' Solver description ' , ' Training information ' ] _ toolkit _ repr _ print ( model , fields , section _ titles )"""
assert len ( section_titles ) == len ( fields ) , "The number of section titles ({0}) " . format ( len ( section_titles ) ) + "doesn't match the number of groups of fields, {0}." . format ( len ( fields ) ) out_fields = [ ( "Class" , model . __class__ . __name__ ) , "" ] # Record the max _ width so that if width is not provided , we calculate it . max_width = len ( "Class" ) for index , ( section_title , field_list ) in enumerate ( zip ( section_titles , fields ) ) : # Add in the section header . out_fields += [ section_title , "-" * len ( section_title ) ] # Add in all the key - value pairs for f in field_list : if isinstance ( f , tuple ) : f = ( str ( f [ 0 ] ) , f [ 1 ] ) out_fields . append ( ( f [ 0 ] , __extract_model_summary_value ( model , f [ 1 ] ) ) ) max_width = max ( max_width , len ( f [ 0 ] ) ) elif isinstance ( f , _SFrame ) : out_fields . append ( "" ) out_fields += _make_repr_table_from_sframe ( f ) out_fields . append ( "" ) else : raise TypeError ( "Type of field %s not recognized." % str ( f ) ) # Add in the empty footer . out_fields . append ( "" ) if width is None : width = max_width # Now , go through and format the key _ value pairs nicely . def format_key_pair ( key , value ) : if type ( key ) is list : key = ',' . join ( str ( k ) for k in key ) return key . ljust ( width , ' ' ) + ' : ' + str ( value ) out_fields = [ s if type ( s ) is str else format_key_pair ( * s ) for s in out_fields ] return '\n' . join ( out_fields )
def callback ( self , filename , lines , ** kwargs ) : """publishes lines one by one to the given topic"""
timestamp = self . get_timestamp ( ** kwargs ) if kwargs . get ( 'timestamp' , False ) : del kwargs [ 'timestamp' ] for line in lines : try : import warnings with warnings . catch_warnings ( ) : warnings . simplefilter ( 'error' ) m = self . format ( filename , line , timestamp , ** kwargs ) self . logger . debug ( "Sending message " + m ) self . conn . send ( destination = self . queue , body = m ) except Exception , e : self . logger . error ( e ) try : raise TransportException ( e ) except AttributeError : raise TransportException ( 'Unspecified exception encountered' )
def request_get_user ( self , user_ids ) -> dict : """Method to get users by ID , do not need authorization"""
method_params = { 'user_ids' : user_ids } response = self . session . send_method_request ( 'users.get' , method_params ) self . check_for_errors ( 'users.get' , method_params , response ) return response
def delete_consumer_group ( self , project , logstore , consumer_group ) : """Delete consumer group : type project : string : param project : project name : type logstore : string : param logstore : logstore name : type consumer _ group : string : param consumer _ group : consumer group name : return : None"""
headers = { "x-log-bodyrawsize" : '0' } params = { } resource = "/logstores/" + logstore + "/consumergroups/" + consumer_group ( resp , header ) = self . _send ( "DELETE" , project , None , resource , params , headers ) return DeleteConsumerGroupResponse ( header , resp )
def validate_plugin ( self , plugin_class , experimental = False ) : """Verifies that the plugin _ class should execute under this policy"""
valid_subclasses = [ IndependentPlugin ] + self . valid_subclasses if experimental : valid_subclasses += [ ExperimentalPlugin ] return any ( issubclass ( plugin_class , class_ ) for class_ in valid_subclasses )
def close ( self ) : """close an open connection"""
if not self . connected : return True self . _close ( ) self . connected = False self . log ( "Closed Connection {}" , self . connection_config . interface_name ) return True
def send_query ( self , ID , methodname , returnable , * args , ** kwargs ) : """将调用请求的ID , 方法名 , 参数包装为请求数据后编码为字节串发送出去 . Parameters : ID ( str ) : - 任务ID methodname ( str ) : - 要调用的方法名 returnable ( bool ) : - 是否要求返回结果 args ( Any ) : - 要调用的方法的位置参数 kwargs ( Any ) : - 要调用的方法的关键字参数 Return : ( bool ) : - 准确地说没有错误就会返回True"""
query = self . _make_query ( ID , methodname , returnable , * args , ** kwargs ) self . _send_query ( query ) self . tasks [ ID ] = self . loop . create_future ( ) return True
def ssh_sa_ssh_server_mac ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) ssh_sa = ET . SubElement ( config , "ssh-sa" , xmlns = "urn:brocade.com:mgmt:brocade-sec-services" ) ssh = ET . SubElement ( ssh_sa , "ssh" ) server = ET . SubElement ( ssh , "server" ) mac = ET . SubElement ( server , "mac" ) mac . text = kwargs . pop ( 'mac' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )
def _parse_param ( key , val ) : """Parse the query param looking for sparse fields params Ensure the ` val ` or what will become the sparse fields is always an array . If the query param is not a sparse fields query param then return None . : param key : the query parameter key in the request ( left of = ) : param val : the query parameter val in the request ( right of = ) : return : tuple of resource type to implement the sparse fields on & a array of the fields ."""
regex = re . compile ( r'fields\[([A-Za-z]+)\]' ) match = regex . match ( key ) if match : if not isinstance ( val , list ) : val = val . split ( ',' ) fields = [ field . lower ( ) for field in val ] rtype = match . groups ( ) [ 0 ] . lower ( ) return rtype , fields
def camel_to_snake ( name ) : """http : / / stackoverflow . com / questions / 1175208/ elegant - python - function - to - convert - camelcase - to - camel - case"""
s1 = FIRST_CAP_RE . sub ( r'\1_\2' , name ) return ALL_CAP_RE . sub ( r'\1_\2' , s1 ) . lower ( )
def join_url_params ( dic ) : """根据传入的键值对 , 拼接 url 后面 ? 的参数 , 比如 ? key1 = value1 & key2 = value2 : param : * dic : ( dict ) 参数键值对 : return : * result : ( string ) 拼接好的参数 举例如下 : : print ( ' - - - splice _ url _ params demo - - - ' ) dic1 = { ' key1 ' : ' value1 ' , ' key2 ' : ' value2 ' } print ( splice _ url _ params ( dic1 ) ) print ( ' - - - ' ) 执行结果 : : - - - splice _ url _ params demo - - - ? key1 = value1 & key2 = value2"""
od = OrderedDict ( sorted ( dic . items ( ) ) ) url = '?' temp_str = urlencode ( od ) url = url + temp_str return url
def get_spherical_bounding_box ( lons , lats ) : """Given a collection of points find and return the bounding box , as a pair of longitudes and a pair of latitudes . Parameters define longitudes and latitudes of a point collection respectively in a form of lists or numpy arrays . : return : A tuple of four items . These items represent western , eastern , northern and southern borders of the bounding box respectively . Values are floats in decimal degrees . : raises ValueError : If points collection has the longitudinal extent of more than 180 degrees ( it is impossible to define a single hemisphere bound to poles that would contain the whole collection ) ."""
north , south = numpy . max ( lats ) , numpy . min ( lats ) west , east = numpy . min ( lons ) , numpy . max ( lons ) assert ( - 180 <= west <= 180 ) and ( - 180 <= east <= 180 ) , ( west , east ) if get_longitudinal_extent ( west , east ) < 0 : # points are lying on both sides of the international date line # ( meridian 180 ) . the actual west longitude is the lowest positive # longitude and east one is the highest negative . if hasattr ( lons , 'flatten' ) : # fixes test _ surface _ crossing _ international _ date _ line lons = lons . flatten ( ) west = min ( lon for lon in lons if lon > 0 ) east = max ( lon for lon in lons if lon < 0 ) if not all ( ( get_longitudinal_extent ( west , lon ) >= 0 and get_longitudinal_extent ( lon , east ) >= 0 ) for lon in lons ) : raise ValueError ( 'points collection has longitudinal extent ' 'wider than 180 deg' ) return SphericalBB ( west , east , north , south )
def last_sleep_breakdown ( self ) : """Return durations of sleep stages for last complete session ."""
try : stages = self . intervals [ 1 ] [ 'stages' ] except KeyError : return None breakdown = { 'awake' : 0 , 'light' : 0 , 'deep' : 0 , 'rem' : 0 } for stage in stages : if stage [ 'stage' ] == 'awake' : breakdown [ 'awake' ] += stage [ 'duration' ] elif stage [ 'stage' ] == 'light' : breakdown [ 'light' ] += stage [ 'duration' ] elif stage [ 'stage' ] == 'deep' : breakdown [ 'deep' ] += stage [ 'duration' ] elif stage [ 'stage' ] == 'rem' : breakdown [ 'rem' ] += stage [ 'duration' ] return breakdown
def matches ( self , spec ) : """Matches a specification against the current Plot ."""
if callable ( spec ) and not isinstance ( spec , type ) : return spec ( self ) elif isinstance ( spec , type ) : return isinstance ( self , spec ) else : raise ValueError ( "Matching specs have to be either a type or a callable." )
def delete ( self , record ) : """Delete a record . : param record : Record instance ."""
index , doc_type = self . record_to_index ( record ) return self . client . delete ( id = str ( record . id ) , index = index , doc_type = doc_type , )
def OnTimer ( self , event ) : """Update all frozen cells because of timer call"""
self . timer_updating = True shape = self . grid . code_array . shape [ : 2 ] selection = Selection ( [ ( 0 , 0 ) ] , [ ( shape ) ] , [ ] , [ ] , [ ] ) self . grid . actions . refresh_selected_frozen_cells ( selection ) self . grid . ForceRefresh ( )
def _extract_core_semantics ( self , docs ) : """Extracts core semantics for a list of documents , returning them along with a list of all the concepts represented ."""
all_concepts = [ ] doc_core_sems = [ ] for doc in docs : core_sems = self . _process_doc ( doc ) doc_core_sems . append ( core_sems ) all_concepts += [ con for con , weight in core_sems ] return doc_core_sems , list ( set ( all_concepts ) )
def _encrypt ( self , archive ) : """Encrypts the compressed archive using GPG . If encryption fails for any reason , it should be logged by sos but not cause execution to stop . The assumption is that the unencrypted archive would still be of use to the user , and / or that the end user has another means of securing the archive . Returns the name of the encrypted archive , or raises an exception to signal that encryption failed and the unencrypted archive name should be used ."""
arc_name = archive . replace ( "sosreport-" , "secured-sosreport-" ) arc_name += ".gpg" enc_cmd = "gpg --batch -o %s " % arc_name env = None if self . enc_opts [ "key" ] : # need to assume a trusted key here to be able to encrypt the # archive non - interactively enc_cmd += "--trust-model always -e -r %s " % self . enc_opts [ "key" ] enc_cmd += archive if self . enc_opts [ "password" ] : # prevent change of gpg options using a long password , but also # prevent the addition of quote characters to the passphrase passwd = "%s" % self . enc_opts [ "password" ] . replace ( '\'"' , '' ) env = { "sos_gpg" : passwd } enc_cmd += "-c --passphrase-fd 0 " enc_cmd = "/bin/bash -c \"echo $sos_gpg | %s\"" % enc_cmd enc_cmd += archive r = sos_get_command_output ( enc_cmd , timeout = 0 , env = env ) if r [ "status" ] == 0 : return arc_name elif r [ "status" ] == 2 : if self . enc_opts [ "key" ] : msg = "Specified key not in keyring" else : msg = "Could not read passphrase" else : # TODO : report the actual error from gpg . Currently , we cannot as # sos _ get _ command _ output ( ) does not capture stderr msg = "gpg exited with code %s" % r [ "status" ] raise Exception ( msg )
def file_transfer_protocol_send ( self , target_network , target_system , target_component , payload , force_mavlink1 = False ) : '''File transfer message target _ network : Network ID ( 0 for broadcast ) ( uint8 _ t ) target _ system : System ID ( 0 for broadcast ) ( uint8 _ t ) target _ component : Component ID ( 0 for broadcast ) ( uint8 _ t ) payload : Variable length payload . The length is defined by the remaining message length when subtracting the header and other fields . The entire content of this block is opaque unless you understand any the encoding message _ type . The particular encoding used can be extension specific and might not always be documented as part of the mavlink specification . ( uint8 _ t )'''
return self . send ( self . file_transfer_protocol_encode ( target_network , target_system , target_component , payload ) , force_mavlink1 = force_mavlink1 )
def jsonstrlen ( self , name , path = Path . rootPath ( ) ) : """Returns the length of the string JSON value under ` ` path ` ` at key ` ` name ` `"""
return self . execute_command ( 'JSON.STRLEN' , name , str_path ( path ) )
def _schemaPrepareInsert ( self , store ) : """Prepare each attribute in my schema for insertion into a given store , either by upgrade or by creation . This makes sure all references point to this store and all relative paths point to this store ' s files directory ."""
for name , atr in self . getSchema ( ) : atr . prepareInsert ( self , store )
def maps_get_default_rules_output_rules_policyname ( self , ** kwargs ) : """Auto Generated Code"""
config = ET . Element ( "config" ) maps_get_default_rules = ET . Element ( "maps_get_default_rules" ) config = maps_get_default_rules output = ET . SubElement ( maps_get_default_rules , "output" ) rules = ET . SubElement ( output , "rules" ) policyname = ET . SubElement ( rules , "policyname" ) policyname . text = kwargs . pop ( 'policyname' ) callback = kwargs . pop ( 'callback' , self . _callback ) return callback ( config )
def forward_lmm ( snps , pheno , K = None , covs = None , qvalues = False , threshold = 5e-8 , maxiter = 2 , test = 'lrt' , ** kw_args ) : """univariate fixed effects test with forward selection Args : snps : [ N x S ] SP . array of S SNPs for N individuals ( test SNPs ) pheno : [ N x 1 ] SP . array of 1 phenotype for N individuals K : [ N x N ] SP . array of LMM - covariance / kinship koefficients ( optional ) If not provided , then linear regression analysis is performed covs : [ N x D ] SP . array of D covariates for N individuals threshold : ( float ) P - value thrashold for inclusion in forward selection ( default 5e - 8) maxiter : ( int ) maximum number of interaction scans . First scan is without inclusion , so maxiter - 1 inclusions can be performed . ( default 2) test : ' lrt ' for likelihood ratio test ( default ) or ' f ' for F - test Returns : lm : limix LMM object iadded : array of indices of SNPs included in order of inclusion pvadded : array of Pvalues obtained by the included SNPs in iteration before inclusion pvall : [ maxiter x S ] SP . array of Pvalues for all iterations"""
if K is None : K = SP . eye ( snps . shape [ 0 ] ) if covs is None : covs = SP . ones ( ( snps . shape [ 0 ] , 1 ) ) lm = simple_lmm ( snps , pheno , K = K , covs = covs , test = test , ** kw_args ) pvall = SP . zeros ( ( maxiter , snps . shape [ 1 ] ) ) pv = lm . getPv ( ) pvall [ 0 : 1 , : ] = pv imin = pv . argmin ( ) niter = 1 # start stuff iadded = [ ] pvadded = [ ] qvadded = [ ] if qvalues : assert pv . shape [ 0 ] == 1 , "This is untested with the fdr package. pv.shape[0]==1 failed" qvall = SP . zeros ( ( maxiter , snps . shape [ 1 ] ) ) qv = FDR . qvalues ( pv ) qvall [ 0 : 1 , : ] = qv score = qv . min ( ) else : score = pv . min ( ) while ( score < threshold ) and niter < maxiter : t0 = time . time ( ) iadded . append ( imin ) pvadded . append ( pv [ 0 , imin ] ) if qvalues : qvadded . append ( qv [ 0 , imin ] ) covs = SP . concatenate ( ( covs , snps [ : , imin : ( imin + 1 ) ] ) , 1 ) lm . setCovs ( covs ) lm . process ( ) pv = lm . getPv ( ) pvall [ niter : niter + 1 , : ] = pv imin = pv . argmin ( ) if qvalues : qv = FDR . qvalues ( pv ) qvall [ niter : niter + 1 , : ] = qv score = qv . min ( ) else : score = pv . min ( ) t1 = time . time ( ) print ( ( "finished GWAS testing in %.2f seconds" % ( t1 - t0 ) ) ) niter = niter + 1 RV = { } RV [ 'iadded' ] = iadded RV [ 'pvadded' ] = pvadded RV [ 'pvall' ] = pvall if qvalues : RV [ 'qvall' ] = qvall RV [ 'qvadded' ] = qvadded return lm , RV
def create_widget ( self ) : """Create the underlying widget . A dialog is not a subclass of view , hence we don ' t set name as widget or children will try to use it as their parent ."""
d = self . declaration style = d . style or '@style/Widget.DeviceDefault.PopupMenu' self . window = PopupWindow ( self . get_context ( ) , None , 0 , style ) self . showing = False
def channel_close ( self , registry_address : PaymentNetworkID , token_address : TokenAddress , partner_address : Address , retry_timeout : NetworkTimeout = DEFAULT_RETRY_TIMEOUT , ) : """Close a channel opened with ` partner _ address ` for the given ` token _ address ` . Race condition , this can fail if channel was closed externally ."""
self . channel_batch_close ( registry_address = registry_address , token_address = token_address , partner_addresses = [ partner_address ] , retry_timeout = retry_timeout , )
def right_click_high_equalarea ( self , event ) : """toggles between zoom and pan effects for the high equal area on right click Parameters event : the wx . MouseEvent that triggered the call of this function Alters high _ EA _ setting , toolbar4 setting"""
if event . LeftIsDown ( ) : return elif self . high_EA_setting == "Zoom" : self . high_EA_setting = "Pan" try : self . toolbar4 . pan ( 'off' ) except TypeError : pass elif self . high_EA_setting == "Pan" : self . high_EA_setting = "Zoom" try : self . toolbar4 . zoom ( ) except TypeError : pass
def check_container ( self , container_path , container_format = None , config_string = None ) : """Check whether the given container is well - formed . : param string container _ path : the path of the container to be checked : param container _ format : the format of the container : type container _ format : : class : ` ~ aeneas . container . ContainerFormat ` : param string config _ string : the configuration string generated by the wizard : rtype : : class : ` ~ aeneas . validator . ValidatorResult `"""
self . log ( [ u"Checking container '%s'" , container_path ] ) self . result = ValidatorResult ( ) if self . _are_safety_checks_disabled ( u"check_container" ) : return self . result if not ( gf . file_exists ( container_path ) or gf . directory_exists ( container_path ) ) : self . _failed ( u"Container '%s' not found." % container_path ) return self . result container = Container ( container_path , container_format ) try : self . log ( u"Checking container has config file" ) if config_string is not None : self . log ( u"Container with config string from wizard" ) self . check_config_txt ( config_string , is_config_string = True ) elif container . has_config_xml : self . log ( u"Container has XML config file" ) contents = container . read_entry ( container . entry_config_xml ) if contents is None : self . _failed ( u"Unable to read the contents of XML config file." ) return self . result self . check_config_xml ( contents ) elif container . has_config_txt : self . log ( u"Container has TXT config file" ) contents = container . read_entry ( container . entry_config_txt ) if contents is None : self . _failed ( u"Unable to read the contents of TXT config file." ) return self . result self . check_config_txt ( contents , is_config_string = False ) else : self . _failed ( u"Container does not have a TXT or XML configuration file." ) self . log ( u"Checking we have a valid job in the container" ) if not self . result . passed : return self . result self . log ( u"Analyze the contents of the container" ) analyzer = AnalyzeContainer ( container ) if config_string is not None : job = analyzer . analyze ( config_string = config_string ) else : job = analyzer . analyze ( ) self . _check_analyzed_job ( job , container ) except OSError : self . _failed ( u"Unable to read the contents of the container." ) return self . result
def _get_jwt_for_audience ( self , audience ) : """Get a JWT For a given audience . If there is already an existing , non - expired token in the cache for the audience , that token is used . Otherwise , a new token will be created . Args : audience ( str ) : The intended audience . Returns : bytes : The encoded JWT ."""
token , expiry = self . _cache . get ( audience , ( None , None ) ) if token is None or expiry < _helpers . utcnow ( ) : token , expiry = self . _make_jwt_for_audience ( audience ) self . _cache [ audience ] = token , expiry return token
def start_completion ( self , buffer_name = None , select_first = False , select_last = False , insert_common_part = False , complete_event = None ) : """Start asynchronous autocompletion of this buffer . ( This will do nothing if a previous completion was still in progress . )"""
buffer_name = buffer_name or self . current_buffer_name completer = self . _async_completers . get ( buffer_name ) if completer : completer ( select_first = select_first , select_last = select_last , insert_common_part = insert_common_part , complete_event = CompleteEvent ( completion_requested = True ) )
def create_ltp_package ( aleph_record , book_id , ebook_fn , data , url , urn_nbn = None ) : """Create LTP package as it is specified in specification v1.0 as I understand it . Args : aleph _ record ( str ) : XML containing full aleph record . book _ id ( str ) : UUID of the book . ebook _ fn ( str ) : Original filename of the ebook . data ( str / bytes ) : Ebook ' s content . url ( str ) : URL of the publication used when the URL can ' t be found in ` aleph _ record ` . urn _ nbn ( str , default None ) : URN : NBN . Returns : str : Name of the package ' s directory in ` ` / tmp ` ` ."""
root_dir , orig_dir , meta_dir = _create_package_hierarchy ( book_id = book_id ) # create original file original_fn = os . path . join ( orig_dir , fn_composers . original_fn ( book_id , ebook_fn ) ) with open ( original_fn , "wb" ) as f : f . write ( data ) # create metadata files metadata_filenames = [ ] records = marcxml2mods ( marc_xml = aleph_record , uuid = book_id , url = url ) for cnt , mods_record in enumerate ( records ) : fn = os . path . join ( meta_dir , fn_composers . volume_fn ( cnt ) ) with open ( fn , "w" ) as f : f . write ( mods_record ) metadata_filenames . append ( fn ) # collect md5 sums md5_fn = os . path . join ( root_dir , fn_composers . checksum_fn ( book_id ) ) checksums = checksum_generator . generate_hashfile ( root_dir ) with open ( md5_fn , "w" ) as f : f . write ( checksums ) # create info file info_fn = os . path . join ( root_dir , fn_composers . info_fn ( book_id ) ) with open ( info_fn , "w" ) as f : f . write ( info_composer . compose_info ( root_dir = root_dir , files = [ original_fn ] + metadata_filenames , hash_fn = md5_fn , aleph_record = aleph_record , urn_nbn = urn_nbn , ) ) return root_dir
def getVATAmount ( self ) : """Compute VAT Amount from the Price and system configured VAT"""
price , vat = self . getPrice ( ) , self . getVAT ( ) return float ( price ) * ( float ( vat ) / 100 )
def _set_traffic_class_exp_state ( self , v , load = False ) : """Setter method for traffic _ class _ exp _ state , mapped from YANG variable / traffic _ class _ exp _ state ( container ) If this variable is read - only ( config : false ) in the source YANG file , then _ set _ traffic _ class _ exp _ state is considered as a private method . Backends looking to populate this variable should do so via calling thisObj . _ set _ traffic _ class _ exp _ state ( ) directly . YANG Description : traffic _ class _ exp"""
if hasattr ( v , "_utype" ) : v = v . _utype ( v ) try : t = YANGDynClass ( v , base = traffic_class_exp_state . traffic_class_exp_state , is_container = 'container' , presence = False , yang_name = "traffic-class-exp-state" , rest_name = "traffic-class-exp-state" , parent = self , path_helper = self . _path_helper , extmethods = self . _extmethods , register_paths = True , extensions = { u'tailf-common' : { u'callpoint' : u'qos-traffic-class-exp' , u'cli-suppress-show-path' : None } } , namespace = 'urn:brocade.com:mgmt:brocade-qos-operational' , defining_module = 'brocade-qos-operational' , yang_type = 'container' , is_config = True ) except ( TypeError , ValueError ) : raise ValueError ( { 'error-string' : """traffic_class_exp_state must be of a type compatible with container""" , 'defined-type' : "container" , 'generated-type' : """YANGDynClass(base=traffic_class_exp_state.traffic_class_exp_state, is_container='container', presence=False, yang_name="traffic-class-exp-state", rest_name="traffic-class-exp-state", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'qos-traffic-class-exp', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-qos-operational', defining_module='brocade-qos-operational', yang_type='container', is_config=True)""" , } ) self . __traffic_class_exp_state = t if hasattr ( self , '_set' ) : self . _set ( )
def do_round ( value , precision = 0 , method = 'common' ) : """Round the number to a given precision . The first parameter specifies the precision ( default is ` ` 0 ` ` ) , the second the rounding method : - ` ` ' common ' ` ` rounds either up or down - ` ` ' ceil ' ` ` always rounds up - ` ` ' floor ' ` ` always rounds down If you don ' t specify a method ` ` ' common ' ` ` is used . . . sourcecode : : jinja { { 42.55 | round } } - > 43.0 { { 42.55 | round ( 1 , ' floor ' ) } } - > 42.5 Note that even if rounded to 0 precision , a float is returned . If you need a real integer , pipe it through ` int ` : . . sourcecode : : jinja { { 42.55 | round | int } } - > 43"""
if not method in ( 'common' , 'ceil' , 'floor' ) : raise FilterArgumentError ( 'method must be common, ceil or floor' ) if method == 'common' : return round ( value , precision ) func = getattr ( math , method ) return func ( value * ( 10 ** precision ) ) / ( 10 ** precision )
def get_current_user ( self , ** params ) : """https : / / developers . coinbase . com / api / v2 # show - current - user"""
response = self . _get ( 'v2' , 'user' , params = params ) return self . _make_api_object ( response , CurrentUser )
def _process_pathway_disease ( self , limit ) : """We make a link between the pathway identifiers , and any diseases associated with them . Since we model diseases as processes , we make a triple saying that the pathway may be causally upstream of or within the disease process . : param limit : : return :"""
LOG . info ( "Processing KEGG pathways to disease ids" ) if self . test_mode : graph = self . testgraph else : graph = self . graph line_counter = 0 raw = '/' . join ( ( self . rawdir , self . files [ 'pathway_disease' ] [ 'file' ] ) ) with open ( raw , 'r' , encoding = "iso-8859-1" ) as csvfile : filereader = csv . reader ( csvfile , delimiter = '\t' , quotechar = '\"' ) for row in filereader : line_counter += 1 ( disease_id , kegg_pathway_num ) = row if self . test_mode and kegg_pathway_num not in self . test_ids [ 'pathway' ] : continue disease_id = 'KEGG-' + disease_id # will look like KEGG - path : map04130 or KEGG - path : hsa04130 pathway_id = 'KEGG-' + kegg_pathway_num graph . addTriple ( pathway_id , self . globaltt [ 'causally upstream of or within' ] , disease_id ) if not self . test_mode and limit is not None and line_counter > limit : break return
def get_Sb ( data ) : """returns vgp scatter for data set"""
Sb , N = 0. , 0. for rec in data : delta = 90. - abs ( rec [ 'vgp_lat' ] ) if rec [ 'average_k' ] != 0 : k = rec [ 'average_k' ] L = rec [ 'average_lat' ] * np . pi / 180. # latitude in radians Nsi = rec [ 'average_nn' ] K = old_div ( k , ( 2. * ( 1. + 3. * np . sin ( L ) ** 2 ) / ( 5. - 3. * np . sin ( L ) ** 2 ) ) ) Sw = old_div ( 81. , np . sqrt ( K ) ) else : Sw , Nsi = 0 , 1. Sb += delta ** 2. - old_div ( ( Sw ** 2 ) , Nsi ) N += 1. return np . sqrt ( old_div ( Sb , float ( N - 1. ) ) )
def datasets_update ( self , dataset_name , dataset_info ) : """Updates the Dataset info . Args : dataset _ name : the name of the dataset to update as a tuple of components . dataset _ info : the Dataset resource with updated fields ."""
url = Api . _ENDPOINT + ( Api . _DATASETS_PATH % dataset_name ) return datalab . utils . Http . request ( url , method = 'PUT' , data = dataset_info , credentials = self . _credentials )
def main ( ) : """App entry point"""
# Check python version if sys . version_info < ( 3 , 0 , 0 ) : sys . stderr . write ( 'You need python 3.0 or later to run this script!' + os . linesep ) exit ( 1 ) # Generate requires if platform . system ( ) == 'Windows' : requirements_file = 'windows.txt' else : requirements_file = 'base.txt' requirements_file = os . path . join ( 'requirements' , requirements_file ) with open ( requirements_file ) as requirements_reader : requires = requirements_reader . read ( ) . splitlines ( ) # Get package description with open ( 'README.rst' ) as readme_reader : long_description = readme_reader . read ( ) # Describe installer settings = { 'name' : 'pyspectator' , 'version' : '1.2.1' , 'author' : 'Maxim Grischuk' , 'author_email' : 'uzumaxy@gmail.com' , 'maintainer' : 'Maxim Grischuk' , 'maintainer_email' : 'uzumaxy@gmail.com' , 'packages' : [ 'pyspectator' ] , 'url' : 'https://github.com/it-geeks-club/pyspectator' , 'download_url' : 'https://github.com/it-geeks-club/pyspectator/releases' , 'license' : 'BSD' , 'description' : 'pyspectator is a Python cross-platform tool for ' 'monitoring OS resources.' , 'long_description' : long_description , 'install_requires' : requires , 'keywords' : [ 'pyspectator' , 'spectator' , 'monitoring' , 'tool' , 'statistic' , 'stats' , 'computer' , 'pc' , 'server' , 'mem' , 'memory' , 'network' , 'net' , 'io' , 'processor' , 'cpu' , 'hdd' , 'hard' , 'disk' , 'drive' ] , 'platforms' : 'Platform Independent' , 'package_data' : { 'pyspectator' : [ 'LICENSE' , 'README.rst' ] } , 'scripts' : [ 'console.py' ] , 'tests_require' : [ 'pytest>=2.6.2' ] , 'cmdclass' : { 'test' : PyTest } , 'classifiers' : [ 'Development Status :: 5 - Production/Stable' , 'Environment :: Console' , 'Environment :: MacOS X' , 'Environment :: Win32 (MS Windows)' , 'Intended Audience :: Developers' , 'Intended Audience :: Information Technology' , 'Intended Audience :: System Administrators' , 'License :: OSI Approved :: BSD License' , 'Natural Language :: English' , 'Operating System :: MacOS :: MacOS X' , 'Operating System :: Microsoft :: Windows :: Windows 7' , 'Operating System :: Microsoft :: Windows :: Windows NT/2000' , 'Operating System :: Microsoft :: Windows :: Windows Server 2003' , 'Operating System :: Microsoft :: Windows :: Windows Server 2008' , 'Operating System :: Microsoft :: Windows :: Windows Vista' , 'Operating System :: Microsoft :: Windows :: Windows XP' , 'Operating System :: Microsoft' , 'Operating System :: OS Independent' , 'Operating System :: POSIX :: BSD :: FreeBSD' , 'Operating System :: POSIX :: Linux' , 'Operating System :: POSIX :: SunOS/Solaris' , 'Operating System :: POSIX' , 'Programming Language :: C' , 'Programming Language :: Python :: 3' , 'Programming Language :: Python :: 3.0' , 'Programming Language :: Python :: 3.1' , 'Programming Language :: Python :: 3.2' , 'Programming Language :: Python :: 3.3' , 'Programming Language :: Python :: 3.4' , 'Programming Language :: Python :: 3.5' , 'Programming Language :: Python :: Implementation :: CPython' , 'Programming Language :: Python' , 'Topic :: Software Development :: Libraries :: Python Modules' , 'Topic :: Software Development :: Libraries' , 'Topic :: System :: Benchmark' , 'Topic :: System :: Hardware' , 'Topic :: System :: Monitoring' , 'Topic :: System :: Networking :: Monitoring' , 'Topic :: System :: Networking' , 'Topic :: System :: Systems Administration' , 'Topic :: Utilities' , ] , } setup ( ** settings )
def execute ( self , stmt , args ) : """Execute a statement , returning a cursor . For internal use only ."""
self . logger ( stmt , args ) with self . cursor ( ) as cursor : cursor . execute ( stmt , args ) return cursor
def cluster ( dupes , threshold = .5 , max_components = 30000 ) : '''Takes in a list of duplicate pairs and clusters them in to a list records that all refer to the same entity based on a given threshold Keyword arguments : threshold - - number betweent 0 and 1 ( default is . 5 ) . lowering the number will increase precision , raising it will increase recall'''
distance_threshold = 1 - threshold dupe_sub_graphs = connected_components ( dupes , max_components ) for sub_graph in dupe_sub_graphs : if len ( sub_graph ) > 1 : i_to_id , condensed_distances , N = condensedDistance ( sub_graph ) linkage = fastcluster . linkage ( condensed_distances , method = 'centroid' , preserve_input = True ) partition = hcluster . fcluster ( linkage , distance_threshold , criterion = 'distance' ) clusters = defaultdict ( list ) for i , cluster_id in enumerate ( partition ) : clusters [ cluster_id ] . append ( i ) for cluster in viewvalues ( clusters ) : if len ( cluster ) > 1 : scores = confidences ( cluster , condensed_distances , N ) yield tuple ( i_to_id [ i ] for i in cluster ) , scores else : ( ids , score ) , = sub_graph if score > threshold : yield tuple ( ids ) , ( score , ) * 2
def estimate_umbrella_sampling ( us_trajs , us_dtrajs , us_centers , us_force_constants , md_trajs = None , md_dtrajs = None , kT = None , maxiter = 10000 , maxerr = 1.0E-15 , save_convergence_info = 0 , estimator = 'wham' , lag = 1 , dt_traj = '1 step' , init = None , init_maxiter = 10000 , init_maxerr = 1.0E-8 , width = None , ** kwargs ) : r"""This function acts as a wrapper for ` ` tram ( ) ` ` , ` ` dtram ( ) ` ` , ` ` mbar ( ) ` ` , and ` ` wham ( ) ` ` and handles the calculation of bias energies ( ` ` bias ` ` ) and thermodynamic state trajectories ( ` ` ttrajs ` ` ) when the data comes from umbrella sampling and ( optional ) unbiased simulations . Parameters us _ trajs : list of N arrays , each of shape ( T _ i , d ) List of arrays , each having T _ i rows , one for each time step , and d columns where d is the dimensionality of the subspace in which umbrella sampling was applied . Often d = 1 , and thus us _ trajs will be a list of 1d - arrays . us _ dtrajs : list of N int arrays , each of shape ( T _ i , ) The integers are indexes in 0 , . . . , n - 1 enumerating the n discrete states or the bins the umbrella sampling trajectory is in at any time . us _ centers : list of N floats or d - dimensional arrays of floats List or array of N center positions . Each position must be a d - dimensional vector . For 1d umbrella sampling , one can simply pass a list of centers , e . g . [ - 5.0 , - 4.0 , - 3.0 , . . . ] . us _ force _ constants : list of N floats or d - or dxd - dimensional arrays of floats The force constants used in the umbrellas , unit - less ( e . g . kT per squared length unit ) . For multidimensional umbrella sampling , the force matrix must be used . md _ trajs : list of M arrays , each of shape ( T _ i , d ) , optional , default = None Unbiased molecular dynamics simulations ; format like us _ trajs . md _ dtrajs : list of M int arrays , each of shape ( T _ i , ) The integers are indexes in 0 , . . . , n - 1 enumerating the n discrete states or the bins the unbiased trajectory is in at any time . kT : float or None , optional , default = None Use this attribute if the supplied force constants are NOT unit - less ; kT must have the same energy unit as the force constants . maxiter : int , optional , default = 10000 The maximum number of self - consistent iterations before the estimator exits unsuccessfully . maxerr : float , optional , default = 1.0E - 15 Convergence criterion based on the maximal free energy change in a self - consistent iteration step . save _ convergence _ info : int , optional , default = 0 Every save _ convergence _ info iteration steps , store the actual increment and the actual loglikelihood ; 0 means no storage . estimator : str , optional , default = ' wham ' Specify one of the available estimators | ' wham ' : use WHAM | ' mbar ' : use MBAR | ' dtram ' : use the discrete version of TRAM | ' tram ' : use TRAM lag : int or list of int , optional , default = 1 Integer lag time at which transitions are counted . Providing a list of lag times will trigger one estimation per lag time . dt _ traj : str , optional , default = ' 1 step ' Description of the physical time corresponding to the lag . May be used by analysis algorithms such as plotting tools to pretty - print the axes . By default ' 1 step ' , i . e . there is no physical time unit . Specify by a number , whitespace and unit . Permitted units are ( * is an arbitrary string ) : | ' fs ' , ' femtosecond * ' | ' ps ' , ' picosecond * ' | ' ns ' , ' nanosecond * ' | ' us ' , ' microsecond * ' | ' ms ' , ' millisecond * ' | ' s ' , ' second * ' init : str , optional , default = None Use a specific initialization for the self - consistent iteration : | None : use a hard - coded guess for free energies and Lagrangian multipliers | ' wham ' : perform a short WHAM estimate to initialize the free energies ( only with dtram ) | ' mbar ' : perform a short MBAR estimate to initialize the free energies ( only with tram ) init _ maxiter : int , optional , default = 10000 The maximum number of self - consistent iterations during the initialization . init _ maxerr : float , optional , default = 1.0E - 8 Convergence criterion for the initialization . width : array - like of float , optional , default = None Specify periodicity for individual us _ traj dimensions . Each positive entry will make the corresponding feature periodic and use the given value as width . None / zero values will be treated as non - periodic . * * kwargs : dict , optional You can use this to pass estimator - specific named parameters to the chosen estimator , which are not already coverd by ` ` estimate _ umbrella _ sampling ( ) ` ` . Returns A : class : ` MultiThermModel < pyemma . thermo . models . multi _ therm . MultiThermModel > ` or : class : ` MEMM < pyemma . thermo . models . memm . MEMM > ` object or list thereof The requested estimator / model object , i . e . , WHAM , MBAR , DTRAM or TRAM . If multiple lag times are given , a list of objects is returned ( one MEMM per lag time ) . Example We look at a 1D umbrella sampling simulation with two umbrellas at 1.1 and 1.3 on the reaction coordinate with spring constant of 1.0 ; additionally , we have two unbiased simulations . We start with a joint clustering and use TRAM for the estimation : > > > from pyemma . coordinates import cluster _ regspace as regspace > > > from pyemma . thermo import estimate _ umbrella _ sampling as estimate _ us > > > import numpy as np > > > us _ centers = [ 1.1 , 1.3] > > > us _ force _ constants = [ 1.0 , 1.0] > > > us _ trajs = [ np . array ( [ 1.0 , 1.1 , 1.2 , 1.1 , 1.0 , 1.1 ] ) . reshape ( ( - 1 , 1 ) ) , np . array ( [ 1.3 , 1.2 , 1.3 , 1.4 , 1.4 , 1.3 ] ) . reshape ( ( - 1 , 1 ) ) ] > > > md _ trajs = [ np . array ( [ 0.9 , 1.0 , 1.1 , 1.2 , 1.3 , 1.4 ] ) . reshape ( ( - 1 , 1 ) ) , np . array ( [ 1.5 , 1.4 , 1.3 , 1.4 , 1.4 , 1.5 ] ) . reshape ( ( - 1 , 1 ) ) ] > > > cluster = regspace ( data = us _ trajs + md _ trajs , max _ centers = 10 , dmin = 0.15) > > > us _ dtrajs = cluster . dtrajs [ : 2] > > > md _ dtrajs = cluster . dtrajs [ 2 : ] > > > centers = cluster . clustercenters > > > tram = estimate _ us ( us _ trajs , us _ dtrajs , us _ centers , us _ force _ constants , md _ trajs = md _ trajs , md _ dtrajs = md _ dtrajs , estimator = ' tram ' , lag = 1) > > > tram . f # doctest : + ELLIPSIS array ( [ 0.63 . . . , 1.60 . . . , 1.31 . . . ] ) See : class : ` MultiThermModel < pyemma . thermo . models . multi _ therm . MultiThermModel > ` or : class : ` MEMM < pyemma . thermo . models . memm . MEMM > ` for a full documentation . . . autoclass : : pyemma . thermo . models . multi _ therm . MultiThermModel : members : : undoc - members : . . rubric : : Methods . . autoautosummary : : pyemma . thermo . models . multi _ therm . MultiThermModel : methods : . . rubric : : Attributes . . autoautosummary : : pyemma . thermo . models . multi _ therm . MultiThermModel : attributes : . . autoclass : : pyemma . thermo . models . memm . MEMM : members : : undoc - members : . . rubric : : Methods . . autoautosummary : : pyemma . thermo . models . memm . MEMM : methods : . . rubric : : Attributes . . autoautosummary : : pyemma . thermo . models . memm . MEMM : attributes :"""
from . util import get_umbrella_sampling_data as _get_umbrella_sampling_data # sanity checks if estimator not in [ 'wham' , 'mbar' , 'dtram' , 'tram' ] : raise ValueError ( "unsupported estimator: %s" % estimator ) if not isinstance ( us_trajs , ( list , tuple ) ) : raise ValueError ( "The parameter us_trajs must be a list of numpy.ndarray objects" ) if not isinstance ( us_centers , ( list , tuple ) ) : raise ValueError ( "The parameter us_centers must be a list of floats or numpy.ndarray objects" ) if not isinstance ( us_force_constants , ( list , tuple ) ) : raise ValueError ( "The parameter us_force_constants must be a list of floats or numpy.ndarray objects" ) if len ( us_trajs ) != len ( us_centers ) : raise ValueError ( "Unmatching number of umbrella sampling trajectories and centers: %d!=%d" % ( len ( us_trajs ) , len ( us_centers ) ) ) if len ( us_trajs ) != len ( us_force_constants ) : raise ValueError ( "Unmatching number of umbrella sampling trajectories and force constants: %d!=%d" % ( len ( us_trajs ) , len ( us_force_constants ) ) ) if len ( us_trajs ) != len ( us_dtrajs ) : raise ValueError ( "Number of continuous and discrete umbrella sampling trajectories does not " + "match: %d!=%d" % ( len ( us_trajs ) , len ( us_dtrajs ) ) ) i = 0 for traj , dtraj in zip ( us_trajs , us_dtrajs ) : if traj . shape [ 0 ] != dtraj . shape [ 0 ] : raise ValueError ( "Lengths of continuous and discrete umbrella sampling trajectories with " + "index %d does not match: %d!=%d" % ( i , len ( us_trajs ) , len ( us_dtrajs ) ) ) i += 1 if md_trajs is not None : if not isinstance ( md_trajs , ( list , tuple ) ) : raise ValueError ( "The parameter md_trajs must be a list of numpy.ndarray objects" ) if md_dtrajs is None : raise ValueError ( "You have provided md_trajs, but md_dtrajs is None" ) if md_dtrajs is None : md_dtrajs = [ ] else : if md_trajs is None : raise ValueError ( "You have provided md_dtrajs, but md_trajs is None" ) if len ( md_trajs ) != len ( md_dtrajs ) : raise ValueError ( "Number of continuous and discrete unbiased trajectories does not " + "match: %d!=%d" % ( len ( md_trajs ) , len ( md_dtrajs ) ) ) i = 0 for traj , dtraj in zip ( md_trajs , md_dtrajs ) : if traj . shape [ 0 ] != dtraj . shape [ 0 ] : raise ValueError ( "Lengths of continuous and discrete unbiased trajectories with " + "index %d does not match: %d!=%d" % ( i , len ( md_trajs ) , len ( md_dtrajs ) ) ) i += 1 # data preparation ttrajs , btrajs , umbrella_centers , force_constants , unbiased_state = _get_umbrella_sampling_data ( us_trajs , us_centers , us_force_constants , md_trajs = md_trajs , kT = kT , width = width ) estimator_obj = None # estimation if estimator == 'wham' : estimator_obj = wham ( ttrajs , us_dtrajs + md_dtrajs , _get_averaged_bias_matrix ( btrajs , us_dtrajs + md_dtrajs ) , maxiter = maxiter , maxerr = maxerr , save_convergence_info = save_convergence_info , dt_traj = dt_traj ) elif estimator == 'mbar' : allowed_keys = [ 'direct_space' ] parsed_kwargs = dict ( [ ( i , kwargs [ i ] ) for i in allowed_keys if i in kwargs ] ) estimator_obj = mbar ( ttrajs , us_dtrajs + md_dtrajs , btrajs , maxiter = maxiter , maxerr = maxerr , save_convergence_info = save_convergence_info , dt_traj = dt_traj , ** parsed_kwargs ) elif estimator == 'dtram' : allowed_keys = [ 'count_mode' , 'connectivity' ] parsed_kwargs = dict ( [ ( i , kwargs [ i ] ) for i in allowed_keys if i in kwargs ] ) estimator_obj = dtram ( ttrajs , us_dtrajs + md_dtrajs , _get_averaged_bias_matrix ( btrajs , us_dtrajs + md_dtrajs ) , lag , unbiased_state = unbiased_state , maxiter = maxiter , maxerr = maxerr , save_convergence_info = save_convergence_info , dt_traj = dt_traj , init = init , init_maxiter = init_maxiter , init_maxerr = init_maxerr , ** parsed_kwargs ) elif estimator == 'tram' : allowed_keys = [ 'count_mode' , 'connectivity' , 'connectivity_factor' , 'nn' , 'direct_space' , 'N_dtram_accelerations' , 'equilibrium' , 'overcounting_factor' , 'callback' ] parsed_kwargs = dict ( [ ( i , kwargs [ i ] ) for i in allowed_keys if i in kwargs ] ) estimator_obj = tram ( ttrajs , us_dtrajs + md_dtrajs , btrajs , lag , unbiased_state = unbiased_state , maxiter = maxiter , maxerr = maxerr , save_convergence_info = save_convergence_info , dt_traj = dt_traj , init = init , init_maxiter = init_maxiter , init_maxerr = init_maxerr , ** parsed_kwargs ) # adding thermodynamic state information and return results try : estimator_obj . umbrella_centers = umbrella_centers estimator_obj . force_constants = force_constants except AttributeError : for obj in estimator_obj : obj . umbrella_centers = umbrella_centers obj . force_constants = force_constants return estimator_obj
def get_api ( i ) : """Input : { ( path ) - path to module , if comes from access function or ( module _ uoa ) - if comes from CMD ( func ) - func for API ( out ) - output Output : { return - return code = 0 , if successful > 0 , if error ( error ) - error text if return > 0 title - title string desc - original description module - module name api - api as string line - line in found module"""
p = i . get ( 'path' , '' ) f = i . get ( 'func' , '' ) o = i . get ( 'out' , '' ) muoa = i . get ( 'module_uoa' , '' ) t = '' # last function description ( if redirect to another API ) t_orig = '' # original function description l = 0 # API line a = '' # accumulated API if p == '' and muoa != '' : rx = load ( { 'module_uoa' : cfg [ 'module_name' ] , 'data_uoa' : muoa } ) if rx [ 'return' ] > 0 : return rx p = rx [ 'path' ] if p == '' : p1 = os . path . dirname ( os . path . dirname ( work [ 'dir_default_repo' ] ) ) p = os . path . join ( p1 , cfg [ 'file_kernel_py' ] ) if not os . path . isfile ( p ) : return { 'return' : 1 , 'error' : 'kernel not found in ' + p } else : p = os . path . join ( p , 'module.py' ) if os . path . isfile ( p ) : rx = load_text_file ( { 'text_file' : p , 'split_to_list' : 'yes' } ) if rx [ 'return' ] > 0 : return rx lst = rx [ 'lst' ] k = - 1 while k < len ( lst ) - 1 : k += 1 q = lst [ k ] if q . find ( 'def ' + f + '(' ) >= 0 or q . find ( 'def ' + f + ' (' ) >= 0 or q . find ( 'def\t' + f + '(' ) >= 0 or q . find ( 'def\t' + f + ' (' ) >= 0 : j = k - 1 if j >= 0 and lst [ j ] . strip ( ) == '' : j -= 1 x = 'x' while j >= 0 and x != '' and not x . startswith ( '###' ) : x = lst [ j ] . strip ( ) if x != '' and not x . startswith ( '###' ) : if x == '#' : x = ' ' elif x . startswith ( '# ' ) : x = x [ 2 : ] t = x + '\n' + t j -= 1 if t != '' : l = j + 2 if t_orig == '' : t_orig = t # Find starting point of an API j = k + 1 if j < len ( lst ) and lst [ j ] . find ( '"""' ) >= 0 : j += 1 # Check if redirect to another function restart = False if j < len ( lst ) : x = lst [ j ] . strip ( ) if x . lower ( ) . startswith ( "see" ) : z1 = x . find ( '"' ) if z1 > 0 : z2 = x . find ( '"' , z1 + 1 ) if z2 > 0 : f = x [ z1 + 1 : z2 ] # new function name k = - 1 restart = True # restart search for new function if not restart : x = '' while x . find ( '"""' ) < 0 and j < len ( lst ) : x = lst [ j ] if x . find ( '"""' ) < 0 : a += x + '\n' j += 1 if t == '' and a == '' : return { 'return' : 1 , 'error' : 'function not found' } dd = t_orig . strip ( ) if o == 'con' : out ( 'Description: ' + dd ) out ( '' ) out ( 'Module: ' + p ) out ( '' ) out ( 'Line: ' + str ( l ) ) out ( '' ) out ( 'API:' ) out ( a ) elif o == 'web' : out ( '<B>Function:</B> ' + t + '<BR>' ) out ( '<BR>' ) out ( '<B>Module:</B> ' + p + '<BR>' ) out ( '<BR>' ) out ( '<B>API:</B><BR>' ) out ( '<pre>' ) out ( a ) out ( '</pre><BR>' ) return { 'return' : 0 , 'title' : t , 'desc' : dd , 'module' : p , 'api' : a , 'line' : l }
def _inputLine ( self , prompt , ** kwargs ) : 'Add prompt to bottom of screen and get line of input from user .'
self . inInput = True rstatuslen = self . drawRightStatus ( self . scr , self . sheets [ 0 ] ) attr = 0 promptlen = clipdraw ( self . scr , self . windowHeight - 1 , 0 , prompt , attr , w = self . windowWidth - rstatuslen - 1 ) ret = self . editText ( self . windowHeight - 1 , promptlen , self . windowWidth - promptlen - rstatuslen - 2 , attr = colors . color_edit_cell , unprintablechar = options . disp_unprintable , truncchar = options . disp_truncator , ** kwargs ) self . inInput = False return ret
def is_mass_balanced ( reaction ) : """Confirm that a reaction is mass balanced ."""
balance = defaultdict ( int ) for metabolite , coefficient in iteritems ( reaction . metabolites ) : if metabolite . elements is None or len ( metabolite . elements ) == 0 : return False for element , amount in iteritems ( metabolite . elements ) : balance [ element ] += coefficient * amount return all ( amount == 0 for amount in itervalues ( balance ) )
def match_file ( pattern , filename ) : '''The function will match a pattern in a file and return a rex object , which will have all the matches found in the file .'''
# Validate user data . if pattern is None : return None if os . stat ( filename ) . st_size == 0 : return None rexobj = REX ( pattern , filename ) rexpatstr = reformat_pattern ( pattern ) # print " rexpatstr : " , rexpatstr rexpat = re . compile ( rexpatstr ) rexobj . rex_patternstr = rexpatstr rexobj . rex_pattern = rexpat sfile = open ( filename , 'r' ) data = sfile . read ( ) sfile . close ( ) line_count = 1 for line in data . splitlines ( ) : mobj = rexpat . match ( line ) if mobj : populate_resobj ( rexobj , mobj , line_count ) line_count += 1 return rexobj
def remove ( self , key ) : """Clear a column value in the object . Note that this happens immediately : it does not wait for save ( ) to be called ."""
payload = { key : { '__op' : 'Delete' } } self . __class__ . PUT ( self . _absolute_url , ** payload ) del self . __dict__ [ key ]
def add_untagged_ok ( self , text : MaybeBytes , code : Optional [ ResponseCode ] = None ) -> None : """Add an untagged ` ` OK ` ` response . See Also : : meth : ` . add _ untagged ` , : class : ` ResponseOk ` Args : text : The response text . code : Optional response code ."""
response = ResponseOk ( b'*' , text , code ) self . add_untagged ( response )
def match ( self , location ) : """Check if the given location " matches " . : param location : The : class : ` Location ` object to try to match . : returns : : data : ` True ` if the two locations are on the same system and the : attr : ` directory ` can be matched as a filename pattern or a literal match on the normalized pathname ."""
if self . ssh_alias != location . ssh_alias : # Never match locations on other systems . return False elif self . have_wildcards : # Match filename patterns using fnmatch ( ) . return fnmatch . fnmatch ( location . directory , self . directory ) else : # Compare normalized directory pathnames . self = os . path . normpath ( self . directory ) other = os . path . normpath ( location . directory ) return self == other
def mtf_image_transformer_cifar_mp_4x ( ) : """Data parallel CIFAR parameters ."""
hparams = mtf_image_transformer_base_cifar ( ) hparams . mesh_shape = "model:4;batch:8" hparams . layout = "batch:batch;d_ff:model;heads:model" hparams . batch_size = 32 hparams . num_heads = 8 hparams . d_ff = 8192 return hparams
def sync_hue_db ( self , * servers ) : """Synchronize the Hue server ' s database . @ param servers : Name of Hue Server roles to synchronize . Not required starting with API v10. @ return : List of submitted commands ."""
actual_version = self . _get_resource_root ( ) . version if actual_version < 10 : return self . _role_cmd ( 'hueSyncDb' , servers ) return self . _cmd ( 'hueSyncDb' , api_version = 10 )
def _concat ( self , egdfs ) : """Concatenate evaluated group dataframes Parameters egdfs : iterable Evaluated dataframes Returns edata : pandas . DataFrame Evaluated data"""
egdfs = list ( egdfs ) edata = pd . concat ( egdfs , axis = 0 , ignore_index = False , copy = False ) # groupby can mixup the rows . We try to maintain the original # order , but we can only do that if the result has a one to # one relationship with the original one2one = ( self . keep_index and not any ( edata . index . duplicated ( ) ) and len ( edata . index ) == len ( self . data . index ) ) if one2one : edata = edata . sort_index ( ) else : edata . reset_index ( drop = True , inplace = True ) # Maybe this should happen in the verb functions if self . keep_groups and self . groups : edata = GroupedDataFrame ( edata , groups = self . groups ) return edata
def file_resolve ( backend , filepath ) : """Mark a conflicted file as resolved , so that a merge can be completed"""
recipe = DKRecipeDisk . find_recipe_name ( ) if recipe is None : raise click . ClickException ( 'You must be in a recipe folder.' ) click . secho ( "%s - Resolving conflicts" % get_datetime ( ) ) for file_to_resolve in filepath : if not os . path . exists ( file_to_resolve ) : raise click . ClickException ( '%s does not exist' % file_to_resolve ) check_and_print ( DKCloudCommandRunner . resolve_conflict ( file_to_resolve ) )
def callback_url ( self , request ) : """the url to go back after the external service call : param request : contains the current session : type request : dict : rtype : string"""
service = self . service . split ( 'Service' ) [ 1 ] . lower ( ) return_to = '{service}_callback' . format ( service = service ) return '%s://%s%s' % ( request . scheme , request . get_host ( ) , reverse ( return_to ) )
def is_purrlog ( path ) : """Checks if path refers to a valid purrlog . Path must exist , and must contain either at least one directory called entry - YYYYMMDD - HHMMSS , or the file " dirconfig " """
if not os . path . isdir ( path ) : return False if list ( filter ( os . path . isdir , glob . glob ( os . path . join ( path , "entry-[0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9]-[0-9][0-9][0-9][0-9][0-9][0-9]" ) ) ) ) : return True return os . path . exists ( os . path . join ( path , "dirconfig" ) )
def loss ( args ) : """% prog loss a . b . i1 . blocks [ a . b - genomic . blast ] Extract likely gene loss candidates between genome a and b ."""
p = OptionParser ( loss . __doc__ ) p . add_option ( "--bed" , default = False , action = "store_true" , help = "Genomic BLAST is in bed format [default: %default]" ) p . add_option ( "--gdist" , default = 20 , type = "int" , help = "Gene distance [default: %default]" ) p . add_option ( "--bdist" , default = 20000 , type = "int" , help = "Base pair distance [default: %default]" ) p . set_beds ( ) opts , args = p . parse_args ( args ) if len ( args ) not in ( 1 , 2 ) : sys . exit ( not p . print_help ( ) ) blocksfile = args [ 0 ] emptyblast = ( len ( args ) == 1 ) if emptyblast : genomicblast = "empty.blast" sh ( "touch {0}" . format ( genomicblast ) ) else : genomicblast = args [ 1 ] gdist , bdist = opts . gdist , opts . bdist qbed , sbed , qorder , sorder , is_self = check_beds ( blocksfile , p , opts ) blocks = [ ] fp = open ( blocksfile ) genetrack = { } proxytrack = { } for row in fp : a , b = row . split ( ) genetrack [ a ] = b blocks . append ( ( a , b ) ) data = [ ] for key , rows in groupby ( blocks , key = lambda x : x [ - 1 ] ) : rows = list ( rows ) data . append ( ( key , rows ) ) imax = len ( data ) - 1 for i , ( key , rows ) in enumerate ( data ) : if i == 0 or i == imax : continue if key != '.' : continue before , br = data [ i - 1 ] after , ar = data [ i + 1 ] bi , bx = sorder [ before ] ai , ax = sorder [ after ] dist = abs ( bi - ai ) if bx . seqid != ax . seqid or dist > gdist : continue start , end = range_minmax ( ( ( bx . start , bx . end ) , ( ax . start , ax . end ) ) ) start , end = max ( start - bdist , 1 ) , end + bdist proxy = ( bx . seqid , start , end ) for a , b in rows : proxytrack [ a ] = proxy tags = { } if opts . bed : bed = Bed ( genomicblast , sorted = False ) key = lambda x : gene_name ( x . accn . rsplit ( "." , 1 ) [ 0 ] ) for query , bb in groupby ( bed , key = key ) : bb = list ( bb ) if query not in proxytrack : continue proxy = proxytrack [ query ] tag = "NS" best_b = bb [ 0 ] for b in bb : hsp = ( b . seqid , b . start , b . end ) if range_overlap ( proxy , hsp ) : tag = "S" best_b = b break hsp = ( best_b . seqid , best_b . start , best_b . end ) proxytrack [ query ] = hsp tags [ query ] = tag else : blast = Blast ( genomicblast ) for query , bb in blast . iter_hits ( ) : bb = list ( bb ) query = gene_name ( query ) if query not in proxytrack : continue proxy = proxytrack [ query ] tag = "NS" best_b = bb [ 0 ] for b in bb : hsp = ( b . subject , b . sstart , b . sstop ) if range_overlap ( proxy , hsp ) : tag = "S" best_b = b break hsp = ( best_b . subject , best_b . sstart , best_b . sstop ) proxytrack [ query ] = hsp tags [ query ] = tag for b in qbed : accn = b . accn target_region = genetrack [ accn ] if accn in proxytrack : target_region = region_str ( proxytrack [ accn ] ) if accn in tags : ptag = "[{0}]" . format ( tags [ accn ] ) else : ptag = "[NF]" target_region = ptag + target_region print ( "\t" . join ( ( b . seqid , accn , target_region ) ) ) if emptyblast : sh ( "rm -f {0}" . format ( genomicblast ) )
def search_lxc_bridges ( ) : '''Search which bridges are potentially available as LXC bridges CLI Example : . . code - block : : bash salt ' * ' lxc . search _ lxc _ bridges'''
bridges = __context__ . get ( 'lxc.bridges' , None ) # either match not yet called or no bridges were found # to handle the case where lxc was not installed on the first # call if not bridges : bridges = set ( ) running_bridges = set ( ) bridges . add ( DEFAULT_BR ) try : output = __salt__ [ 'cmd.run_all' ] ( 'brctl show' ) for line in output [ 'stdout' ] . splitlines ( ) [ 1 : ] : if not line . startswith ( ' ' ) : running_bridges . add ( line . split ( ) [ 0 ] . strip ( ) ) except ( SaltInvocationError , CommandExecutionError ) : pass for ifc , ip in six . iteritems ( __grains__ . get ( 'ip_interfaces' , { } ) ) : if ifc in running_bridges : bridges . add ( ifc ) elif os . path . exists ( '/sys/devices/virtual/net/{0}/bridge' . format ( ifc ) ) : bridges . add ( ifc ) bridges = list ( bridges ) # if we found interfaces that have lxc in their names # we filter them as being the potential lxc bridges # we also try to default on br0 on other cases def sort_bridges ( a ) : pref = 'z' if 'lxc' in a : pref = 'a' elif 'br0' == a : pref = 'c' return '{0}_{1}' . format ( pref , a ) bridges . sort ( key = sort_bridges ) __context__ [ 'lxc.bridges' ] = bridges return bridges
def get_raw_data ( self , times = 5 ) : """do some readings and aggregate them using the defined statistics function : param times : how many measures to aggregate : type times : int : return : the aggregate of the measured values : rtype float"""
self . _validate_measure_count ( times ) data_list = [ ] while len ( data_list ) < times : data = self . _read ( ) if data not in [ False , - 1 ] : data_list . append ( data ) return data_list
def read_in_config ( self ) : """Vyper will discover and load the configuration file from disk and key / value stores , searching in one of the defined paths ."""
log . info ( "Attempting to read in config file" ) if self . _get_config_type ( ) not in constants . SUPPORTED_EXTENSIONS : raise errors . UnsupportedConfigError ( self . _get_config_type ( ) ) with open ( self . _get_config_file ( ) ) as fp : f = fp . read ( ) self . _config = { } return self . _unmarshall_reader ( f , self . _config )
def extract_frame ( self ) : """Pulls one complete frame off the buffer and returns it . If there is no complete message in the buffer , returns None . Note that the buffer can contain more than once message . You should therefore call this method in a loop ( or use iterator functionality exposed by class ) until None returned . @ return : The next complete frame in the buffer . @ rtype : L { stomp . frame . Frame }"""
# ( mbytes , hbytes ) = self . _ find _ message _ bytes ( self . buffer ) # if not mbytes : # return None # msgdata = self . buffer [ : mbytes ] # self . buffer = self . buffer [ mbytes : ] # hdata = msgdata [ : hbytes ] # # Strip off any leading whitespace from headers ; this is necessary , because # # we do not ( any longer ) expect a trailing \ n after the \ x00 byte ( which means # # it will become a leading \ n to the next frame ) . # hdata = hdata . lstrip ( ) # elems = hdata . split ( ' \ n ' ) # cmd = elems . pop ( 0) # headers = { } # for e in elems : # try : # ( k , v ) = e . split ( ' : ' , 1 ) # header values may contain ' : ' so specify maxsplit # except ValueError : # continue # headers [ k . strip ( ) ] = v . strip ( ) # # hbytes points to the start of the ' \ n \ n ' at the end of the header , # # so 2 bytes beyond this is the start of the body . The body EXCLUDES # # the final byte , which is ' \ x00 ' . # body = msgdata [ hbytes + 2 : - 1] self . _buffer . seek ( self . _pointer , 0 ) try : f = Frame . from_buffer ( self . _buffer ) self . _pointer = self . _buffer . tell ( ) except ( IncompleteFrame , EmptyBuffer ) : self . _buffer . seek ( self . _pointer , 0 ) return None return f