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76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
authenticate
<not_specific>
def authenticate(lexicon, action='read'): """ Authentication check. Used when but data is sent to the user, but Karp is not involved (Karp takes care of this otherwise). Args: lexicon (str): the lexicon name action (str, optional): defines which permission to verify. Possible...
Authentication check. Used when but data is sent to the user, but Karp is not involved (Karp takes care of this otherwise). Args: lexicon (str): the lexicon name action (str, optional): defines which permission to verify. Possible values: read, write. Raises: MflExce...
Authentication check. Used when but data is sent to the user, but Karp is not involved (Karp takes care of this otherwise).
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def authenticate(lexicon, action='read'): if action == 'checkopen': auth = None else: auth = request.authorization postdata = {"include_open_resources": "true"} if auth is not None: user, pw = auth.username, auth.password server = C.config['AUTH_SERVER'] mdcode = ...
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Authentication check.
[ "Authentication", "check", "." ]
[ "\"\"\"\n Authentication check. Used when but data is sent to the user, but Karp is\n not involved (Karp takes care of this otherwise).\n Args:\n lexicon (str): the lexicon name\n action (str, optional): defines which permission to verify.\n Possible values: read, write.\n Raise...
[ { "param": "lexicon", "type": null }, { "param": "action", "type": null } ]
{ "returns": [], "raises": [ { "docstring": "if the user is not granted the action in the lexicon", "docstring_tokens": [ "if", "the", "user", "is", "not", "granted", "the", "action", "in", "the", "lexicon" ...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
karp_wftableize
<not_specific>
def karp_wftableize(lexicon, paradigm, table, classes=None, baseform='', identifier='', pos='', resource=''): """ Format a word table into a Karp friendly json object """ def default(paradigm, table, classes, baseform, identifier, pos, resource): # TODO implement something more gener...
Format a word table into a Karp friendly json object
Format a word table into a Karp friendly json object
[ "Format", "a", "word", "table", "into", "a", "Karp", "friendly", "json", "object" ]
def karp_wftableize(lexicon, paradigm, table, classes=None, baseform='', identifier='', pos='', resource=''): def default(paradigm, table, classes, baseform, identifier, pos, resource): table = table.split(',') obj = {'lexiconName': resource} wfs = [] for l in tab...
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Format a word table into a Karp friendly json object
[ "Format", "a", "word", "table", "into", "a", "Karp", "friendly", "json", "object" ]
[ "\"\"\" Format a word table into a Karp friendly json object \"\"\"", "# TODO implement something more generic?" ]
[ { "param": "lexicon", "type": null }, { "param": "paradigm", "type": null }, { "param": "table", "type": null }, { "param": "classes", "type": null }, { "param": "baseform", "type": null }, { "param": "identifier", "type": null }, { "param"...
{ "returns": [], "raises": [], "params": [ { "identifier": "lexicon", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "paradigm", "type": null, "docstring": null, "docstring_tok...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
karp_tableize
<not_specific>
def karp_tableize(lexicon, table, paradigm=None, pos='', identifier='', score=0): " Format a generated inflection table into a Karp friendly json object " table = table.split(',') obj = {'score': score, 'paradigm': '', 'new': True} if paradigm is not None: obj['variables'] = dict([var for var in...
Format a generated inflection table into a Karp friendly json object
Format a generated inflection table into a Karp friendly json object
[ "Format", "a", "generated", "inflection", "table", "into", "a", "Karp", "friendly", "json", "object" ]
def karp_tableize(lexicon, table, paradigm=None, pos='', identifier='', score=0): table = table.split(',') obj = {'score': score, 'paradigm': '', 'new': True} if paradigm is not None: obj['variables'] = dict([var for var in paradigm.var_insts[0][1:]]) obj['paradigm'] = paradigm.name ...
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Format a generated inflection table into a Karp friendly json object
[ "Format", "a", "generated", "inflection", "table", "into", "a", "Karp", "friendly", "json", "object" ]
[ "\" Format a generated inflection table into a Karp friendly json object \"" ]
[ { "param": "lexicon", "type": null }, { "param": "table", "type": null }, { "param": "paradigm", "type": null }, { "param": "pos", "type": null }, { "param": "identifier", "type": null }, { "param": "score", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lexicon", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "table", "type": null, "docstring": null, "docstring_tokens...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
make_identifier
<not_specific>
def make_identifier(lexicon, baseform, pos, field='', default=False): """ Suggest an identifier for an entry Args: lexicon (str): the name of the lexicon in which the identifier should be used baseform (str): the entry's baseform pos (str): the entry's word class fiel...
Suggest an identifier for an entry Args: lexicon (str): the name of the lexicon in which the identifier should be used baseform (str): the entry's baseform pos (str): the entry's word class field (str, optional): the identier's field name. Defaults to the lex...
Suggest an identifier for an entry
[ "Suggest", "an", "identifier", "for", "an", "entry" ]
def make_identifier(lexicon, baseform, pos, field='', default=False): lexconf = lexconfig.get_lexiconconf(lexicon) func = extra_src(lexicon, 'yield_identifier', None) if default or func is None: return str(uuid.uuid1()) field = field or lexconf['identifier'] mode = lexconf['lexiconMode'] ...
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Suggest an identifier for an entry
[ "Suggest", "an", "identifier", "for", "an", "entry" ]
[ "\"\"\" Suggest an identifier for an entry\n Args:\n lexicon (str): the name of the lexicon in which the identifier\n should be used\n baseform (str): the entry's baseform\n pos (str): the entry's word class\n field (str, optional): the identier's field name.\n D...
[ { "param": "lexicon", "type": null }, { "param": "baseform", "type": null }, { "param": "pos", "type": null }, { "param": "field", "type": null }, { "param": "default", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lexicon", "type": null, "docstring": "the name of the lexicon in which the identifier\nshould be used", "docstring_tokens": [ "the", "name", "of", "the", "lexicon", "in", ...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
read_pos
<not_specific>
def read_pos(lexconf): " Return a list of pos tags, either from the parameters or the config " pos = request.args.get('pos', '') partofspeech = request.args.get('partOfSpeech', lexconf['defaultpos']) pos = pos or partofspeech return pos.split(',')
Return a list of pos tags, either from the parameters or the config
Return a list of pos tags, either from the parameters or the config
[ "Return", "a", "list", "of", "pos", "tags", "either", "from", "the", "parameters", "or", "the", "config" ]
def read_pos(lexconf): pos = request.args.get('pos', '') partofspeech = request.args.get('partOfSpeech', lexconf['defaultpos']) pos = pos or partofspeech return pos.split(',')
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Return a list of pos tags, either from the parameters or the config
[ "Return", "a", "list", "of", "pos", "tags", "either", "from", "the", "parameters", "or", "the", "config" ]
[ "\" Return a list of pos tags, either from the parameters or the config \"" ]
[ { "param": "lexconf", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lexconf", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
read_restriction
<not_specific>
def read_restriction(lexconf): """ Check whether restrict_to_baseform is true, either from the parameters or the config """ restrict = request.args.get('restrict_to_baseform') if restrict is None: return lexconf['restrict_to_baseform'] return restrict in ['True', 'true', True]
Check whether restrict_to_baseform is true, either from the parameters or the config
Check whether restrict_to_baseform is true, either from the parameters or the config
[ "Check", "whether", "restrict_to_baseform", "is", "true", "either", "from", "the", "parameters", "or", "the", "config" ]
def read_restriction(lexconf): restrict = request.args.get('restrict_to_baseform') if restrict is None: return lexconf['restrict_to_baseform'] return restrict in ['True', 'true', True]
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Check whether restrict_to_baseform is true, either from the parameters or the config
[ "Check", "whether", "restrict_to_baseform", "is", "true", "either", "from", "the", "parameters", "or", "the", "config" ]
[ "\"\"\" Check whether restrict_to_baseform is true,\n either from the parameters or the config \"\"\"" ]
[ { "param": "lexconf", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lexconf", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
identifier2pos
<not_specific>
def identifier2pos(lexicon, lemgram): " Try to find the pos tag by looking at the identfier " func = extra_src(lexicon, 'get_pos', lambda x: re.search('.*\.\.(.*?)\..*', x)) return func(lemgram)
Try to find the pos tag by looking at the identfier
Try to find the pos tag by looking at the identfier
[ "Try", "to", "find", "the", "pos", "tag", "by", "looking", "at", "the", "identfier" ]
def identifier2pos(lexicon, lemgram): func = extra_src(lexicon, 'get_pos', lambda x: re.search('.*\.\.(.*?)\..*', x)) return func(lemgram)
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Try to find the pos tag by looking at the identfier
[ "Try", "to", "find", "the", "pos", "tag", "by", "looking", "at", "the", "identfier" ]
[ "\" Try to find the pos tag by looking at the identfier \"" ]
[ { "param": "lexicon", "type": null }, { "param": "lemgram", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lexicon", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "lemgram", "type": null, "docstring": null, "docstring_toke...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
extra_src
<not_specific>
def extra_src(lexicon, funcname, default): " Return a lexicon specific function if there is any " import importlib # If importing fails, try with a different path. logging.debug('look for %s', funcname) lexconf = lexconfig.get_lexiconconf(lexicon) try: logging.debug('file: %s', lexconf['...
Return a lexicon specific function if there is any
Return a lexicon specific function if there is any
[ "Return", "a", "lexicon", "specific", "function", "if", "there", "is", "any" ]
def extra_src(lexicon, funcname, default): import importlib logging.debug('look for %s', funcname) lexconf = lexconfig.get_lexiconconf(lexicon) try: logging.debug('file: %s', lexconf['src']) classmodule = importlib.import_module(lexconf['src']) logging.debug('\n\ngo look in %s\n\...
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Return a lexicon specific function if there is any
[ "Return", "a", "lexicon", "specific", "function", "if", "there", "is", "any" ]
[ "\" Return a lexicon specific function if there is any \"", "# If importing fails, try with a different path." ]
[ { "param": "lexicon", "type": null }, { "param": "funcname", "type": null }, { "param": "default", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lexicon", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "funcname", "type": null, "docstring": null, "docstring_tok...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
relevant_paradigms
<not_specific>
def relevant_paradigms(paradigmdict, lexicon, pos, possible_p=[]): """ Returns a subset of the paradigms. Args: paradigmdict (dict): a dictionary with all paradigms '{"lexname": {"nn": [], "vb": []}' lexicon (str): the lexicon name pos (str): the tables word class pos...
Returns a subset of the paradigms. Args: paradigmdict (dict): a dictionary with all paradigms '{"lexname": {"nn": [], "vb": []}' lexicon (str): the lexicon name pos (str): the tables word class possible_p (list, optional): a list of all acceptable paradigm id:s. ...
Returns a subset of the paradigms.
[ "Returns", "a", "subset", "of", "the", "paradigms", "." ]
def relevant_paradigms(paradigmdict, lexicon, pos, possible_p=[]): try: all_paras, numex, lms, alpha = paradigmdict[lexicon].get(pos, ({}, 0, None, '')) if possible_p: all_paras = [all_paras[p] for p in possible_p if p in all_paras] else: all_paras = list(all_paras.va...
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Returns a subset of the paradigms.
[ "Returns", "a", "subset", "of", "the", "paradigms", "." ]
[ "\"\"\" Returns a subset of the paradigms.\n Args:\n paradigmdict (dict): a dictionary with all paradigms\n '{\"lexname\": {\"nn\": [], \"vb\": []}'\n lexicon (str): the lexicon name\n pos (str): the tables word class\n possible_p (list, optional): a list of all acceptable ...
[ { "param": "paradigmdict", "type": null }, { "param": "lexicon", "type": null }, { "param": "pos", "type": null }, { "param": "possible_p", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "paradigmdict", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "lexicon", "type": null, "docstring": null, "docstring...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
compile_list
<not_specific>
def compile_list(query, searchfield, querystr, lexicon, show, size, start, mode, isfilter=False): " Ask karp about entries matching the given query " query = search_q(query, searchfield, querystr, lexicon, isfilter=isfilter) res = karp_query('minientry', {'q': query, 's...
Ask karp about entries matching the given query
Ask karp about entries matching the given query
[ "Ask", "karp", "about", "entries", "matching", "the", "given", "query" ]
def compile_list(query, searchfield, querystr, lexicon, show, size, start, mode, isfilter=False): query = search_q(query, searchfield, querystr, lexicon, isfilter=isfilter) res = karp_query('minientry', {'q': query, 'show': show, 'size': size, 'start':...
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Ask karp about entries matching the given query
[ "Ask", "karp", "about", "entries", "matching", "the", "given", "query" ]
[ "\" Ask karp about entries matching the given query \"" ]
[ { "param": "query", "type": null }, { "param": "searchfield", "type": null }, { "param": "querystr", "type": null }, { "param": "lexicon", "type": null }, { "param": "show", "type": null }, { "param": "size", "type": null }, { "param": "sta...
{ "returns": [], "raises": [], "params": [ { "identifier": "query", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "searchfield", "type": null, "docstring": null, "docstring_to...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
check_identifier
<not_specific>
def check_identifier(_id, field, resource, mode, unique=True, fail=True): " Check whether an identifier has been used before " q = {'size': 0, 'q': 'extended||and|%s.search|equals|%s' % (field, _id)} res = karp_query('query', q, mode=mode, resource=resource) used = es_total(res) > 0 ok = (used and n...
Check whether an identifier has been used before
Check whether an identifier has been used before
[ "Check", "whether", "an", "identifier", "has", "been", "used", "before" ]
def check_identifier(_id, field, resource, mode, unique=True, fail=True): q = {'size': 0, 'q': 'extended||and|%s.search|equals|%s' % (field, _id)} res = karp_query('query', q, mode=mode, resource=resource) used = es_total(res) > 0 ok = (used and not unique) or (not used and unique) if not ok and fai...
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Check whether an identifier has been used before
[ "Check", "whether", "an", "identifier", "has", "been", "used", "before" ]
[ "\" Check whether an identifier has been used before \"" ]
[ { "param": "_id", "type": null }, { "param": "field", "type": null }, { "param": "resource", "type": null }, { "param": "mode", "type": null }, { "param": "unique", "type": null }, { "param": "fail", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "_id", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "field", "type": null, "docstring": null, "docstring_tokens": [...
76578b14619d11b40e693cbf46944e8db78e6656
spraakbanken/karp-mfl
mflbackend/src/helpers.py
[ "MIT" ]
Python
give_info
<not_specific>
def give_info(identifier, id_field, mode, resource, show=[]): " Give information for the word/paradigm infobox " q = 'extended||and|%s.search|equals|%s' %\ (id_field, identifier) body = {'q': q} action = 'query' if show: body['show'] = ','.join(show) action = 'minientry' ...
Give information for the word/paradigm infobox
Give information for the word/paradigm infobox
[ "Give", "information", "for", "the", "word", "/", "paradigm", "infobox" ]
def give_info(identifier, id_field, mode, resource, show=[]): q = 'extended||and|%s.search|equals|%s' %\ (id_field, identifier) body = {'q': q} action = 'query' if show: body['show'] = ','.join(show) action = 'minientry' res = karp_query(action, body, mode=mode, resource=reso...
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Give information for the word/paradigm infobox
[ "Give", "information", "for", "the", "word", "/", "paradigm", "infobox" ]
[ "\" Give information for the word/paradigm infobox \"" ]
[ { "param": "identifier", "type": null }, { "param": "id_field", "type": null }, { "param": "mode", "type": null }, { "param": "resource", "type": null }, { "param": "show", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "identifier", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "id_field", "type": null, "docstring": null, "docstring_...
116c5e3f153f0cd7af5fd302cd07860b98ffd0f2
kevinjp2000/wificoin
test/functional/test_framework/test_node.py
[ "MIT" ]
Python
wait_for_rpc_connection
<not_specific>
def wait_for_rpc_connection(self): """Sets up an RPC connection to the wificoind process. Returns False if unable to connect.""" # Poll at a rate of four times per second poll_per_s = 4 for _ in range(poll_per_s * self.rpc_timeout): assert self.process.poll() is None, "wifico...
Sets up an RPC connection to the wificoind process. Returns False if unable to connect.
Sets up an RPC connection to the wificoind process. Returns False if unable to connect.
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def wait_for_rpc_connection(self): poll_per_s = 4 for _ in range(poll_per_s * self.rpc_timeout): assert self.process.poll() is None, "wificoind exited with status %i during initialization" % self.process.returncode try: self.rpc = get_rpc_proxy(rpc_url(self.datadi...
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Sets up an RPC connection to the wificoind process.
[ "Sets", "up", "an", "RPC", "connection", "to", "the", "wificoind", "process", "." ]
[ "\"\"\"Sets up an RPC connection to the wificoind process. Returns False if unable to connect.\"\"\"", "# Poll at a rate of four times per second", "# If the call to getblockcount() succeeds then the RPC connection is up", "# Port not yet open?", "# unknown IO error", "# Initialization phase", "# RPC in...
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
116c5e3f153f0cd7af5fd302cd07860b98ffd0f2
kevinjp2000/wificoin
test/functional/test_framework/test_node.py
[ "MIT" ]
Python
send_cli
<not_specific>
def send_cli(self, command, *args, **kwargs): """Run wificoin-cli command. Deserializes returned string as python object.""" pos_args = [str(arg) for arg in args] named_args = [str(key) + "=" + str(value) for (key, value) in kwargs.items()] assert not (pos_args and named_args), "Cannot ...
Run wificoin-cli command. Deserializes returned string as python object.
Run wificoin-cli command. Deserializes returned string as python object.
[ "Run", "wificoin", "-", "cli", "command", ".", "Deserializes", "returned", "string", "as", "python", "object", "." ]
def send_cli(self, command, *args, **kwargs): pos_args = [str(arg) for arg in args] named_args = [str(key) + "=" + str(value) for (key, value) in kwargs.items()] assert not (pos_args and named_args), "Cannot use positional arguments and named arguments in the same wificoin-cli call" p_ar...
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Run wificoin-cli command.
[ "Run", "wificoin", "-", "cli", "command", "." ]
[ "\"\"\"Run wificoin-cli command. Deserializes returned string as python object.\"\"\"", "# Ignore cli_stdout, raise with cli_stderr" ]
[ { "param": "self", "type": null }, { "param": "command", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "command", "type": null, "docstring": null, "docstring_tokens"...
c7ce035564b5eb6ca7529376434c4fcbfa89e46f
whiteking64/lang-seg
additional_utils/models.py
[ "MIT" ]
Python
parallel_forward
<not_specific>
def parallel_forward(self, inputs, label_set='', **kwargs): """Multi-GPU Mult-size Evaluation Args: inputs: list of Tensors """ if len(label_set) < 10: print('** MultiEvalModule parallel_forward phase: {} **'.format(label_set)) self.nclass = len(label_set...
Multi-GPU Mult-size Evaluation Args: inputs: list of Tensors
Multi-GPU Mult-size Evaluation
[ "Multi", "-", "GPU", "Mult", "-", "size", "Evaluation" ]
def parallel_forward(self, inputs, label_set='', **kwargs): if len(label_set) < 10: print('** MultiEvalModule parallel_forward phase: {} **'.format(label_set)) self.nclass = len(label_set) inputs = [(input.unsqueeze(0).cuda(device),) for input, device in zip(inputs,...
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Multi-GPU Mult-size Evaluation
[ "Multi", "-", "GPU", "Mult", "-", "size", "Evaluation" ]
[ "\"\"\"Multi-GPU Mult-size Evaluation\n\n Args:\n inputs: list of Tensors\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "inputs", "type": null }, { "param": "label_set", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "inputs", "type": null, "docstring": "list of Tensors", "docst...
8d30ed0f72def0f29eb433d2dbb8ac2312d5e210
PyFunceble/docker
pyfunceble_docker/base.py
[ "MIT" ]
Python
log_response
null
def log_response(cls, response: dict): """ Given a response from the Docker client. We log it. """ if "stream" in response: for line in response["stream"].splitlines(): if line: logging.info(line) if "progressDetail" in re...
Given a response from the Docker client. We log it.
Given a response from the Docker client. We log it.
[ "Given", "a", "response", "from", "the", "Docker", "client", ".", "We", "log", "it", "." ]
def log_response(cls, response: dict): if "stream" in response: for line in response["stream"].splitlines(): if line: logging.info(line) if "progressDetail" in response and "status" in response: if "id" in response and response["progressDetail"...
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Given a response from the Docker client.
[ "Given", "a", "response", "from", "the", "Docker", "client", "." ]
[ "\"\"\"\n Given a response from the Docker client.\n We log it.\n \"\"\"" ]
[ { "param": "cls", "type": null }, { "param": "response", "type": "dict" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "cls", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "response", "type": "dict", "docstring": null, "docstring_token...
8d30ed0f72def0f29eb433d2dbb8ac2312d5e210
PyFunceble/docker
pyfunceble_docker/base.py
[ "MIT" ]
Python
is_already_pushed
<not_specific>
def is_already_pushed(self, tag: str): """ Checks if the given tag was already pushed. """ url = f"https://registry.hub.docker.com/v2/repositories/{self.docker_repository}/tags/" tag_published = False while True: req = requests.get(url) req.rais...
Checks if the given tag was already pushed.
Checks if the given tag was already pushed.
[ "Checks", "if", "the", "given", "tag", "was", "already", "pushed", "." ]
def is_already_pushed(self, tag: str): url = f"https://registry.hub.docker.com/v2/repositories/{self.docker_repository}/tags/" tag_published = False while True: req = requests.get(url) req.raise_for_status() data = req.json() tag_published = any([x...
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Checks if the given tag was already pushed.
[ "Checks", "if", "the", "given", "tag", "was", "already", "pushed", "." ]
[ "\"\"\"\n Checks if the given tag was already pushed.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "tag", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "tag", "type": "str", "docstring": null, "docstring_tokens": [...
dbe776914e162bd6b48ef4a4d805539afd94e736
PyFunceble/docker
pyfunceble_docker/publish.py
[ "MIT" ]
Python
are_we_authorized_to_push
bool
def are_we_authorized_to_push(self, images: dict) -> bool: """ Checks if we are authorized to push. """ if "RepoTags" not in images or not images["RepoTags"]: return False for repo_tag in images["RepoTags"]: tag = repo_tag.split(":")[-1] if ...
Checks if we are authorized to push.
Checks if we are authorized to push.
[ "Checks", "if", "we", "are", "authorized", "to", "push", "." ]
def are_we_authorized_to_push(self, images: dict) -> bool: if "RepoTags" not in images or not images["RepoTags"]: return False for repo_tag in images["RepoTags"]: tag = repo_tag.split(":")[-1] if tag == "latest": continue if self.is_already...
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Checks if we are authorized to push.
[ "Checks", "if", "we", "are", "authorized", "to", "push", "." ]
[ "\"\"\"\n Checks if we are authorized to push.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "images", "type": "dict" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "images", "type": "dict", "docstring": null, "docstring_tokens...
3759b86a1269044ce3a9dc45463a6b17dc100294
PyFunceble/docker
pyfunceble_docker/cli.py
[ "MIT" ]
Python
add_common_commands
<not_specific>
def add_common_commands(parser): """ Adds some common commands to the given parser. """ parser.add_argument( "-v", "--version", help="Show the version and exit.", action="version", version=f"%(prog)s {VERSION}", ) parser.add_argument( "-d", ...
Adds some common commands to the given parser.
Adds some common commands to the given parser.
[ "Adds", "some", "common", "commands", "to", "the", "given", "parser", "." ]
def add_common_commands(parser): parser.add_argument( "-v", "--version", help="Show the version and exit.", action="version", version=f"%(prog)s {VERSION}", ) parser.add_argument( "-d", "--debug", help="Activated the debug mode.", actio...
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Adds some common commands to the given parser.
[ "Adds", "some", "common", "commands", "to", "the", "given", "parser", "." ]
[ "\"\"\"\n Adds some common commands to the given parser.\n \"\"\"" ]
[ { "param": "parser", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "parser", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
8d429d14e9a90874cea930fa21709a7459fd73bc
mburtless/opal
opal_common/sources/api_policy_source.py
[ "Apache-2.0" ]
Python
fetch_policy_bundle_from_api_source
Tuple[Path, BundleHash, BundleHash]
async def fetch_policy_bundle_from_api_source( self, url: str, token: Optional[str] ) -> Tuple[Path, BundleHash, BundleHash]: """ Fetches the bundle. May throw, in which case we retry again. Checks that the bundle file isn't the same with Etag, if server doesn...
Fetches the bundle. May throw, in which case we retry again. Checks that the bundle file isn't the same with Etag, if server doesn't have Etag it checks it with hash on the bundle file Read more on Etag here: https://developer.mozilla.org/en-US/docs/Web/HTTP/Headers/ETag ...
Fetches the bundle. May throw, in which case we retry again. Checks that the bundle file isn't the same with Etag, if server doesn't have Etag it checks it with hash on the bundle file
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async def fetch_policy_bundle_from_api_source( self, url: str, token: Optional[str] ) -> Tuple[Path, BundleHash, BundleHash]: auth_headers = tuple_to_dict( get_authorization_header(token)) if token else {} etag_headers = {'ETag': self.etag, ...
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Fetches the bundle.
[ "Fetches", "the", "bundle", "." ]
[ "\"\"\"\n Fetches the bundle. May throw, in which case we retry again.\n Checks that the bundle file isn't the same with Etag, if server\n doesn't have Etag it checks it with hash on the bundle file\n\n Read more on Etag here:\n https://developer.mozilla.org/en-US/docs/Web/HTTP/He...
[ { "param": "self", "type": null }, { "param": "url", "type": "str" }, { "param": "token", "type": "Optional[str]" } ]
{ "returns": [ { "docstring": "path to the bundle file that we just downloaded from the remote API source\nBundleHash: previous bundle hash on None if this is the initial bundle file\nBundleHash: current bundle hash", "docstring_tokens": [ "path", "to", "the", "bundle",...
8d429d14e9a90874cea930fa21709a7459fd73bc
mburtless/opal
opal_common/sources/api_policy_source.py
[ "Apache-2.0" ]
Python
check_for_changes
null
async def check_for_changes(self): """ Calling this method will trigger an api check to the remote. If after the request the watcher detects new bundle, it will call the callbacks registered with _on_new_policy(). """ logger.info( "Fetching changes from remote...
Calling this method will trigger an api check to the remote. If after the request the watcher detects new bundle, it will call the callbacks registered with _on_new_policy().
Calling this method will trigger an api check to the remote. If after the request the watcher detects new bundle, it will call the callbacks registered with _on_new_policy().
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async def check_for_changes(self): logger.info( "Fetching changes from remote: '{remote}'", remote=self.remote_source_url) has_changes, prev, latest, prev_commit, new_commit = await self.api_update_policy() if not has_changes: logger.info( "No new version:...
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Calling this method will trigger an api check to the remote.
[ "Calling", "this", "method", "will", "trigger", "an", "api", "check", "to", "the", "remote", "." ]
[ "\"\"\"\n Calling this method will trigger an api check to the remote.\n If after the request the watcher detects new bundle, it will call the\n callbacks registered with _on_new_policy().\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
9b559d2db2124099f99b815d9f3c9f1cc8ae52fc
mburtless/opal
opal_server/policy/watcher/factory.py
[ "Apache-2.0" ]
Python
trigger_repo_watcher_pull
null
async def trigger_repo_watcher_pull(watcher: PolicyWatcherTask, topic: Topic, data: Any): """ triggers the policy watcher check for changes. will trigger a task on the watcher's thread. """ logger.info("webhook listener triggered") watcher.trigger()
triggers the policy watcher check for changes. will trigger a task on the watcher's thread.
triggers the policy watcher check for changes. will trigger a task on the watcher's thread.
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async def trigger_repo_watcher_pull(watcher: PolicyWatcherTask, topic: Topic, data: Any): logger.info("webhook listener triggered") watcher.trigger()
[ "async", "def", "trigger_repo_watcher_pull", "(", "watcher", ":", "PolicyWatcherTask", ",", "topic", ":", "Topic", ",", "data", ":", "Any", ")", ":", "logger", ".", "info", "(", "\"webhook listener triggered\"", ")", "watcher", ".", "trigger", "(", ")" ]
triggers the policy watcher check for changes.
[ "triggers", "the", "policy", "watcher", "check", "for", "changes", "." ]
[ "\"\"\"\n triggers the policy watcher check for changes.\n will trigger a task on the watcher's thread.\n \"\"\"" ]
[ { "param": "watcher", "type": "PolicyWatcherTask" }, { "param": "topic", "type": "Topic" }, { "param": "data", "type": "Any" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "watcher", "type": "PolicyWatcherTask", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "topic", "type": "Topic", "docstring": null, ...
0c6ce63fa3796bbd252c35c4cbc1508f3c01fc12
mburtless/opal
opal_common/git/branch_tracker.py
[ "Apache-2.0" ]
Python
pull
Tuple[bool, Commit, Commit]
def pull(self) -> Tuple[bool, Commit, Commit]: """ git pulls from tracked remote. Returns: pull_result (bool, Commit, Commit): a tuple consisting of: has_changes (bool): whether the remote had new commits on our tracked branch prev (Commit): the previ...
git pulls from tracked remote. Returns: pull_result (bool, Commit, Commit): a tuple consisting of: has_changes (bool): whether the remote had new commits on our tracked branch prev (Commit): the previous (before the pull) top-most commit on the tracked branc...
git pulls from tracked remote.
[ "git", "pulls", "from", "tracked", "remote", "." ]
def pull(self) -> Tuple[bool, Commit, Commit]: self._pull() if (self.prev_commit.hexsha == self.latest_commit.hexsha): return False, self.prev_commit, self.prev_commit else: prev = self._prev_commit self._save_latest_commit_as_prev_commit() return ...
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git pulls from tracked remote.
[ "git", "pulls", "from", "tracked", "remote", "." ]
[ "\"\"\"\n git pulls from tracked remote.\n\n Returns:\n pull_result (bool, Commit, Commit): a tuple consisting of:\n has_changes (bool): whether the remote had new commits on our tracked branch\n prev (Commit): the previous (before the pull) top-most commit on ...
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "pull_result (bool, Commit, Commit): a tuple consisting of:\nhas_changes (bool): whether the remote had new commits on our tracked branch\nprev (Commit): the previous (before the pull) top-most commit on the tracked branch\nlatest (Commit): the new top-most (latest) commit on t...
0c6ce63fa3796bbd252c35c4cbc1508f3c01fc12
mburtless/opal
opal_common/git/branch_tracker.py
[ "Apache-2.0" ]
Python
_pull
<not_specific>
def _pull(self): """ runs git pull with retries. """ attempt_pull = retry(**self._retry_config)(self.tracked_remote.pull) return attempt_pull()
runs git pull with retries.
runs git pull with retries.
[ "runs", "git", "pull", "with", "retries", "." ]
def _pull(self): attempt_pull = retry(**self._retry_config)(self.tracked_remote.pull) return attempt_pull()
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runs git pull with retries.
[ "runs", "git", "pull", "with", "retries", "." ]
[ "\"\"\"\n runs git pull with retries.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
0c6ce63fa3796bbd252c35c4cbc1508f3c01fc12
mburtless/opal
opal_common/git/branch_tracker.py
[ "Apache-2.0" ]
Python
prev_commit
Commit
def prev_commit(self) -> Commit: """ the last previously known HEAD of the tracked branch """ return self._prev_commit
the last previously known HEAD of the tracked branch
the last previously known HEAD of the tracked branch
[ "the", "last", "previously", "known", "HEAD", "of", "the", "tracked", "branch" ]
def prev_commit(self) -> Commit: return self._prev_commit
[ "def", "prev_commit", "(", "self", ")", "->", "Commit", ":", "return", "self", ".", "_prev_commit" ]
the last previously known HEAD of the tracked branch
[ "the", "last", "previously", "known", "HEAD", "of", "the", "tracked", "branch" ]
[ "\"\"\"\n the last previously known HEAD of the tracked branch\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
0c6ce63fa3796bbd252c35c4cbc1508f3c01fc12
mburtless/opal
opal_common/git/branch_tracker.py
[ "Apache-2.0" ]
Python
tracked_branch
Head
def tracked_branch(self) -> Head: """ returns the tracked branch object (of type git.HEAD) or throws if such branch does not exist on the repo """ try: return getattr(self._repo.heads, self._branch_name) except AttributeError as e: branches = [{'na...
returns the tracked branch object (of type git.HEAD) or throws if such branch does not exist on the repo
returns the tracked branch object (of type git.HEAD) or throws if such branch does not exist on the repo
[ "returns", "the", "tracked", "branch", "object", "(", "of", "type", "git", ".", "HEAD", ")", "or", "throws", "if", "such", "branch", "does", "not", "exist", "on", "the", "repo" ]
def tracked_branch(self) -> Head: try: return getattr(self._repo.heads, self._branch_name) except AttributeError as e: branches = [{'name': head.name, 'path': head.path} for head in self._repo.heads] logger.exception("did not find main branch: {error}, instead found: ...
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returns the tracked branch object (of type git.HEAD) or throws if such branch does not exist on the repo
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[ "\"\"\"\n returns the tracked branch object (of type git.HEAD)\n or throws if such branch does not exist on the repo\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
0c6ce63fa3796bbd252c35c4cbc1508f3c01fc12
mburtless/opal
opal_common/git/branch_tracker.py
[ "Apache-2.0" ]
Python
tracked_remote
Remote
def tracked_remote(self) -> Remote: """ returns the tracked remote object (of type git.Remote) or throws if such remote does not exist on the repo """ try: return getattr(self._repo.remotes, self._remote_name) except AttributeError as e: remotes = ...
returns the tracked remote object (of type git.Remote) or throws if such remote does not exist on the repo
returns the tracked remote object (of type git.Remote) or throws if such remote does not exist on the repo
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def tracked_remote(self) -> Remote: try: return getattr(self._repo.remotes, self._remote_name) except AttributeError as e: remotes = [remote.name for remote in self._repo.remotes] logger.exception("did not find main branch: {error}, instead found: {remotes_found}", er...
[ "def", "tracked_remote", "(", "self", ")", "->", "Remote", ":", "try", ":", "return", "getattr", "(", "self", ".", "_repo", ".", "remotes", ",", "self", ".", "_remote_name", ")", "except", "AttributeError", "as", "e", ":", "remotes", "=", "[", "remote", ...
returns the tracked remote object (of type git.Remote) or throws if such remote does not exist on the repo
[ "returns", "the", "tracked", "remote", "object", "(", "of", "type", "git", ".", "Remote", ")", "or", "throws", "if", "such", "remote", "does", "not", "exist", "on", "the", "repo" ]
[ "\"\"\"\n returns the tracked remote object (of type git.Remote)\n or throws if such remote does not exist on the repo\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5b1d22a1de091f1d2de9bacfddce740fc6481f67
mburtless/opal
opal_common/git/repo_cloner.py
[ "Apache-2.0" ]
Python
is_ssh_repo_url
<not_specific>
def is_ssh_repo_url(repo_url: str): """ return True if the repo url uses SSH authentication. (see: https://docs.github.com/en/github/authenticating-to-github/connecting-to-github-with-ssh) """ return repo_url.startswith(SSH_PREFIX) or repo_url.startswith(GIT_SSH_USER_PREFIX)
return True if the repo url uses SSH authentication. (see: https://docs.github.com/en/github/authenticating-to-github/connecting-to-github-with-ssh)
return True if the repo url uses SSH authentication.
[ "return", "True", "if", "the", "repo", "url", "uses", "SSH", "authentication", "." ]
def is_ssh_repo_url(repo_url: str): return repo_url.startswith(SSH_PREFIX) or repo_url.startswith(GIT_SSH_USER_PREFIX)
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return True if the repo url uses SSH authentication.
[ "return", "True", "if", "the", "repo", "url", "uses", "SSH", "authentication", "." ]
[ "\"\"\"\n return True if the repo url uses SSH authentication.\n (see: https://docs.github.com/en/github/authenticating-to-github/connecting-to-github-with-ssh)\n \"\"\"" ]
[ { "param": "repo_url", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "repo_url", "type": "str", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5b1d22a1de091f1d2de9bacfddce740fc6481f67
mburtless/opal
opal_common/git/repo_cloner.py
[ "Apache-2.0" ]
Python
clone
CloneResult
async def clone(self) -> CloneResult: """ initializes a git.Repo and returns the clone result. it either: - does not found a cloned repo locally and clones from remote url - finds a cloned repo locally and does not clone from remote. """ logger.info("Cloni...
initializes a git.Repo and returns the clone result. it either: - does not found a cloned repo locally and clones from remote url - finds a cloned repo locally and does not clone from remote.
initializes a git.Repo and returns the clone result. it either: does not found a cloned repo locally and clones from remote url finds a cloned repo locally and does not clone from remote.
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async def clone(self) -> CloneResult: logger.info("Cloning repo from '{url}' to '{to_path}' (branch: '{branch}')", url=self.url, to_path=self.path, branch=self.branch_name) loop = asyncio.get_running_loop() return await loop.run_in_executor(None, self._attempt_clone_from_url)
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initializes a git.Repo and returns the clone result.
[ "initializes", "a", "git", ".", "Repo", "and", "returns", "the", "clone", "result", "." ]
[ "\"\"\"\n initializes a git.Repo and returns the clone result.\n it either:\n - does not found a cloned repo locally and clones from remote url\n - finds a cloned repo locally and does not clone from remote.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5b1d22a1de091f1d2de9bacfddce740fc6481f67
mburtless/opal
opal_common/git/repo_cloner.py
[ "Apache-2.0" ]
Python
_attempt_clone_from_url
CloneResult
def _attempt_clone_from_url(self) -> CloneResult: """ clones the repo from url or throws GitFailed """ env = self._provide_git_ssh_environment() _clone_func = partial(self._clone, env=env) _clone_with_retries = retry(**self._retry_config)(_clone_func) try: ...
clones the repo from url or throws GitFailed
clones the repo from url or throws GitFailed
[ "clones", "the", "repo", "from", "url", "or", "throws", "GitFailed" ]
def _attempt_clone_from_url(self) -> CloneResult: env = self._provide_git_ssh_environment() _clone_func = partial(self._clone, env=env) _clone_with_retries = retry(**self._retry_config)(_clone_func) try: repo: Repo = _clone_with_retries() except (GitError, GitCommandE...
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clones the repo from url or throws GitFailed
[ "clones", "the", "repo", "from", "url", "or", "throws", "GitFailed" ]
[ "\"\"\"\n clones the repo from url or throws GitFailed\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
5b1d22a1de091f1d2de9bacfddce740fc6481f67
mburtless/opal
opal_common/git/repo_cloner.py
[ "Apache-2.0" ]
Python
_provide_git_ssh_environment
<not_specific>
def _provide_git_ssh_environment(self): """ provides git SSH configuration via GIT_SSH_COMMAND. the git ssh config will be provided only if the following conditions are met: - the repo url is a git ssh url - an ssh private key is provided in Repo Cloner __init__ """ ...
provides git SSH configuration via GIT_SSH_COMMAND. the git ssh config will be provided only if the following conditions are met: - the repo url is a git ssh url - an ssh private key is provided in Repo Cloner __init__
provides git SSH configuration via GIT_SSH_COMMAND. the git ssh config will be provided only if the following conditions are met: the repo url is a git ssh url an ssh private key is provided in Repo Cloner __init
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def _provide_git_ssh_environment(self): if not is_ssh_repo_url(self.url) or self._ssh_key is None: return None git_ssh_identity_file = self._save_ssh_key_to_pem_file(self._ssh_key) return { "GIT_SSH_COMMAND": f"ssh -o StrictHostKeyChecking=no -o IdentitiesOnly=yes -i {gi...
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provides git SSH configuration via GIT_SSH_COMMAND.
[ "provides", "git", "SSH", "configuration", "via", "GIT_SSH_COMMAND", "." ]
[ "\"\"\"\n provides git SSH configuration via GIT_SSH_COMMAND.\n\n the git ssh config will be provided only if the following conditions are met:\n - the repo url is a git ssh url\n - an ssh private key is provided in Repo Cloner __init__\n \"\"\"", "# no ssh config" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
2fedacbbf7cf0fe96e6a661116198686c58400fc
mburtless/opal
opal_common/sources/git_policy_source.py
[ "Apache-2.0" ]
Python
check_for_changes
null
async def check_for_changes(self): """ Calling this method will trigger a git pull from the tracked remote. If after the pull the watcher detects new commits, it will call the callbacks registered with _on_new_policy(). """ logger.info("Pulling changes from remote: '{remo...
Calling this method will trigger a git pull from the tracked remote. If after the pull the watcher detects new commits, it will call the callbacks registered with _on_new_policy().
Calling this method will trigger a git pull from the tracked remote. If after the pull the watcher detects new commits, it will call the callbacks registered with _on_new_policy().
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async def check_for_changes(self): logger.info("Pulling changes from remote: '{remote}'", remote=self._tracker.tracked_remote.name) has_changes, prev, latest = self._tracker.pull() if not has_changes: logger.info("No new commits: HEAD is at '{head}'", head=latest.hexsha) else...
[ "async", "def", "check_for_changes", "(", "self", ")", ":", "logger", ".", "info", "(", "\"Pulling changes from remote: '{remote}'\"", ",", "remote", "=", "self", ".", "_tracker", ".", "tracked_remote", ".", "name", ")", "has_changes", ",", "prev", ",", "latest"...
Calling this method will trigger a git pull from the tracked remote.
[ "Calling", "this", "method", "will", "trigger", "a", "git", "pull", "from", "the", "tracked", "remote", "." ]
[ "\"\"\"\n Calling this method will trigger a git pull from the tracked remote.\n If after the pull the watcher detects new commits, it will call the\n callbacks registered with _on_new_policy().\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
33bf7db44db21fea5cea3abdcacf3747ac25890b
mburtless/opal
opal_server/server.py
[ "Apache-2.0" ]
Python
_configure_api_routes
<not_specific>
def _configure_api_routes(self, app: FastAPI): """ mounts the api routes on the app object """ authenticator = JWTAuthenticator(self.signer) data_update_publisher: Optional[DataUpdatePublisher] = None if self.publisher is not None: data_update_publisher = Dat...
mounts the api routes on the app object
mounts the api routes on the app object
[ "mounts", "the", "api", "routes", "on", "the", "app", "object" ]
def _configure_api_routes(self, app: FastAPI): authenticator = JWTAuthenticator(self.signer) data_update_publisher: Optional[DataUpdatePublisher] = None if self.publisher is not None: data_update_publisher = DataUpdatePublisher(self.publisher) data_updates_router = init_data_...
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mounts the api routes on the app object
[ "mounts", "the", "api", "routes", "on", "the", "app", "object" ]
[ "\"\"\"\n mounts the api routes on the app object\n \"\"\"", "# Init api routers with required dependencies", "# mount the api routes on the app object", "# mount jwts (static) route", "# top level routes (i.e: healthchecks)" ]
[ { "param": "self", "type": null }, { "param": "app", "type": "FastAPI" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "app", "type": "FastAPI", "docstring": null, "docstring_tokens...
33bf7db44db21fea5cea3abdcacf3747ac25890b
mburtless/opal
opal_server/server.py
[ "Apache-2.0" ]
Python
start_server_background_tasks
null
async def start_server_background_tasks(self): """ starts the background processes (as asyncio tasks) if such are configured. all workers will start these tasks: - publisher: a client that is used to publish updates to the client. only the leader worker (first to obtain leaders...
starts the background processes (as asyncio tasks) if such are configured. all workers will start these tasks: - publisher: a client that is used to publish updates to the client. only the leader worker (first to obtain leadership lock) will start these tasks: - (repo) watcher...
starts the background processes (as asyncio tasks) if such are configured. all workers will start these tasks: publisher: a client that is used to publish updates to the client. only the leader worker (first to obtain leadership lock) will start these tasks: (repo) watcher: monitors the policy git repository for chang...
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async def start_server_background_tasks(self): if self.publisher is not None: async with self.publisher: if self._init_policy_watcher: self.leadership_lock = NamedLock(opal_server_config.LEADER_LOCK_FILE_PATH) async with self.leadership_lock: ...
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starts the background processes (as asyncio tasks) if such are configured.
[ "starts", "the", "background", "processes", "(", "as", "asyncio", "tasks", ")", "if", "such", "are", "configured", "." ]
[ "\"\"\"\n starts the background processes (as asyncio tasks) if such are configured.\n\n all workers will start these tasks:\n - publisher: a client that is used to publish updates to the client.\n\n only the leader worker (first to obtain leadership lock) will start these tasks:\n ...
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
ccc965eff9628527b39585e341a7e5816bc08dc3
mburtless/opal
opal_client/policy/fetcher.py
[ "Apache-2.0" ]
Python
_fetch_policy_bundle
Optional[PolicyBundle]
async def _fetch_policy_bundle( self, directories: List[str] = ['.'], base_hash: Optional[str] = None ) -> Optional[PolicyBundle]: """ Fetches the bundle. May throw, in which case we retry again. """ params = {"path": directories} if base_hash is not N...
Fetches the bundle. May throw, in which case we retry again.
Fetches the bundle. May throw, in which case we retry again.
[ "Fetches", "the", "bundle", ".", "May", "throw", "in", "which", "case", "we", "retry", "again", "." ]
async def _fetch_policy_bundle( self, directories: List[str] = ['.'], base_hash: Optional[str] = None ) -> Optional[PolicyBundle]: params = {"path": directories} if base_hash is not None: params["base_hash"] = base_hash async with aiohttp.ClientSession() a...
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Fetches the bundle.
[ "Fetches", "the", "bundle", "." ]
[ "\"\"\"\n Fetches the bundle. May throw, in which case we retry again.\n \"\"\"", "# may throw ValueError", "# may throw Validation Error" ]
[ { "param": "self", "type": null }, { "param": "directories", "type": "List[str]" }, { "param": "base_hash", "type": "Optional[str]" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "directories", "type": "List[str]", "docstring": null, "docstr...
fd75ecce24b333f42f926e73bf7ba4be0a0e180b
chelnak/vRAAPIClient
vraapiclient/catalog.py
[ "MIT" ]
Python
requestResource
<not_specific>
def requestResource(self, payload): """ Function that will submit a request based on payload. payload = json body (example in request.json) Parameters: payload = JSON request body. """ host = self.host token = self.token url = 'https://{host}/catalog-service/api/consumer/req...
Function that will submit a request based on payload. payload = json body (example in request.json) Parameters: payload = JSON request body.
Function that will submit a request based on payload. payload = json body (example in request.json) Parameters: payload = JSON request body.
[ "Function", "that", "will", "submit", "a", "request", "based", "on", "payload", ".", "payload", "=", "json", "body", "(", "example", "in", "request", ".", "json", ")", "Parameters", ":", "payload", "=", "JSON", "request", "body", "." ]
def requestResource(self, payload): host = self.host token = self.token url = 'https://{host}/catalog-service/api/consumer/requests'.format(host=host) headers = { 'Content-Type': 'application/json', 'Accept': 'application/json', 'Authorization': token ...
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Function that will submit a request based on payload.
[ "Function", "that", "will", "submit", "a", "request", "based", "on", "payload", "." ]
[ "\"\"\"\n\t\tFunction that will submit a request based on payload.\n\t\tpayload = json body (example in request.json)\n\t\tParameters:\n\t\t\tpayload = JSON request body.\n\t\t\"\"\"" ]
[ { "param": "self", "type": null }, { "param": "payload", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "payload", "type": null, "docstring": null, "docstring_tokens"...
6d50f946e40013abbcafc07ec78af4cd88c985f1
chelnak/vRAAPIClient
vraapiclient/helpers.py
[ "MIT" ]
Python
checkResponse
null
def checkResponse(r): """ Quick logic to check the http response code. Parameters: r = http response object. """ acceptedResponses = [200, 201, 203, 204] if not r.status_code in acceptedResponses: print "STATUS: {status} ".format(status=r.status_code) print "ERROR: " + r.text ...
Quick logic to check the http response code. Parameters: r = http response object.
Quick logic to check the http response code. Parameters: r = http response object.
[ "Quick", "logic", "to", "check", "the", "http", "response", "code", ".", "Parameters", ":", "r", "=", "http", "response", "object", "." ]
def checkResponse(r): acceptedResponses = [200, 201, 203, 204] if not r.status_code in acceptedResponses: print "STATUS: {status} ".format(status=r.status_code) print "ERROR: " + r.text sys.exit(r.status_code)
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Quick logic to check the http response code.
[ "Quick", "logic", "to", "check", "the", "http", "response", "code", "." ]
[ "\"\"\"\n\tQuick logic to check the http response code.\n\n\tParameters:\n\t\tr = http response object.\n\t\"\"\"" ]
[ { "param": "r", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "r", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
6d50f946e40013abbcafc07ec78af4cd88c985f1
chelnak/vRAAPIClient
vraapiclient/helpers.py
[ "MIT" ]
Python
authenticate
<not_specific>
def authenticate(host, user, password, tenant): """ Function that will authenticate a user and build. Parameters: host = vRA Appliance fqdn. user = user account with access to the vRA portal. passowrd = valid password for above user. tenant = tenant for the user. """ headers = { 'Content-Ty...
Function that will authenticate a user and build. Parameters: host = vRA Appliance fqdn. user = user account with access to the vRA portal. passowrd = valid password for above user. tenant = tenant for the user.
Function that will authenticate a user and build. Parameters: host = vRA Appliance fqdn. user = user account with access to the vRA portal. passowrd = valid password for above user. tenant = tenant for the user.
[ "Function", "that", "will", "authenticate", "a", "user", "and", "build", ".", "Parameters", ":", "host", "=", "vRA", "Appliance", "fqdn", ".", "user", "=", "user", "account", "with", "access", "to", "the", "vRA", "portal", ".", "passowrd", "=", "valid", ...
def authenticate(host, user, password, tenant): headers = { 'Content-Type': 'application/json', 'Accept': 'application/json' } payload = {"username": user, "password": password, "tenant": tenant} url = 'https://' + host + '/identity/api/tokens' r = requests.post(url=url, ...
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Function that will authenticate a user and build.
[ "Function", "that", "will", "authenticate", "a", "user", "and", "build", "." ]
[ "\"\"\"\n\tFunction that will authenticate a user and build.\n\n\tParameters:\n\t\thost = vRA Appliance fqdn.\n\t\tuser = user account with access to the vRA portal.\n\t\tpassowrd = valid password for above user.\n\t\ttenant = tenant for the user.\n\t\"\"\"" ]
[ { "param": "host", "type": null }, { "param": "user", "type": null }, { "param": "password", "type": null }, { "param": "tenant", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "host", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "user", "type": null, "docstring": null, "docstring_tokens": [...
89e54cba1a9d5d2c741379fe3fb869542a296615
BenbqZhang/ground-recognition
ground_recognition/batchtrainer.py
[ "MIT" ]
Python
save_batch
<not_specific>
def save_batch(batch): """ make batch directory and save batch info. """ batch_name = batch["batch_name"] batch_dir = result_base_dir / batch_name batch_dir.mkdir() # save batch information info_file = batch_dir / "batch_info.txt" with open(info_file, "w") as info_f: info_f....
make batch directory and save batch info.
make batch directory and save batch info.
[ "make", "batch", "directory", "and", "save", "batch", "info", "." ]
def save_batch(batch): batch_name = batch["batch_name"] batch_dir = result_base_dir / batch_name batch_dir.mkdir() info_file = batch_dir / "batch_info.txt" with open(info_file, "w") as info_f: info_f.write(f"batch_name: {batch_name}\n") info_f.write(f"batch_time: {batchs['time']}\n")...
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make batch directory and save batch info.
[ "make", "batch", "directory", "and", "save", "batch", "info", "." ]
[ "\"\"\"\n make batch directory and save batch info.\n \"\"\"", "# save batch information", "# save batch config snapshot to file", "# save snapshot to json format too" ]
[ { "param": "batch", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "batch", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
89e54cba1a9d5d2c741379fe3fb869542a296615
BenbqZhang/ground-recognition
ground_recognition/batchtrainer.py
[ "MIT" ]
Python
save_group
<not_specific>
def save_group(batch_dir, group): """ make group directory and save group info. """ group_name = group["group_name"] group_dir = batch_dir / group_name group_dir.mkdir() # save group information info_file = group_dir / "group_info.txt" with open(info_file, "w") as info_f: in...
make group directory and save group info.
make group directory and save group info.
[ "make", "group", "directory", "and", "save", "group", "info", "." ]
def save_group(batch_dir, group): group_name = group["group_name"] group_dir = batch_dir / group_name group_dir.mkdir() info_file = group_dir / "group_info.txt" with open(info_file, "w") as info_f: info_f.write(f"group_name: {group_name}\n") info_f.write(f"group_info: {group['group_i...
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make group directory and save group info.
[ "make", "group", "directory", "and", "save", "group", "info", "." ]
[ "\"\"\"\n make group directory and save group info.\n \"\"\"", "# save group information" ]
[ { "param": "batch_dir", "type": null }, { "param": "group", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "batch_dir", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "group", "type": null, "docstring": null, "docstring_toke...
6adfaeb159e4b5e0b85cf2217f1aec9d807a6bed
byfaith/pb_chime5
toolbox/nt/database/iterator.py
[ "MIT" ]
Python
filter
<not_specific>
def filter(self, filter_fn, lazy=True): """ The filter_fn consumes an example. If the filter_fn returns True, we keep the example. If it is False, we drop the example. Filtering examples. If using lazy=False this method should be called before applying expensive map functions. ...
The filter_fn consumes an example. If the filter_fn returns True, we keep the example. If it is False, we drop the example. Filtering examples. If using lazy=False this method should be called before applying expensive map functions. Syntax is inspired by: https://docs...
The filter_fn consumes an example. If the filter_fn returns True, we keep the example. If it is False, we drop the example. Filtering examples. If using lazy=False this method should be called before applying expensive map functions.
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def filter(self, filter_fn, lazy=True): if lazy: return FilterIterator(filter_fn, self) else: try: _ = self.keys() except Exception: raise RuntimeError( 'You can only use lazy=False if the incoming iterator is ' ...
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The filter_fn consumes an example.
[ "The", "filter_fn", "consumes", "an", "example", "." ]
[ "\"\"\"\n The filter_fn consumes an example. If the filter_fn returns True, we\n keep the example. If it is False, we drop the example.\n\n Filtering examples. If using lazy=False this method should be called\n before applying expensive map functions.\n\n Syntax is inspired by:\n ...
[ { "param": "self", "type": null }, { "param": "filter_fn", "type": null }, { "param": "lazy", "type": null } ]
{ "returns": [ { "docstring": "FilterIterator iterating over filtered examples.", "docstring_tokens": [ "FilterIterator", "iterating", "over", "filtered", "examples", "." ], "type": null } ], "raises": [], "params": [ { "i...
6adfaeb159e4b5e0b85cf2217f1aec9d807a6bed
byfaith/pb_chime5
toolbox/nt/database/iterator.py
[ "MIT" ]
Python
concatenate
<not_specific>
def concatenate(self, *others): """ Concatenate this iterator with others. keys need to be unambiguous. :param others: list of other iterators to be concatenated :return: ExamplesIterator iterating over all examples. """ if len(others) == 0: return self ...
Concatenate this iterator with others. keys need to be unambiguous. :param others: list of other iterators to be concatenated :return: ExamplesIterator iterating over all examples.
Concatenate this iterator with others. keys need to be unambiguous.
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def concatenate(self, *others): if len(others) == 0: return self return ConcatenateIterator(self, *others)
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Concatenate this iterator with others.
[ "Concatenate", "this", "iterator", "with", "others", "." ]
[ "\"\"\"\n Concatenate this iterator with others. keys need to be unambiguous.\n :param others: list of other iterators to be concatenated\n :return: ExamplesIterator iterating over all examples.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "ExamplesIterator iterating over all examples.", "docstring_tokens": [ "ExamplesIterator", "iterating", "over", "all", "examples", "." ], "type": null } ], "raises": [], "params": [ { "identif...
6adfaeb159e4b5e0b85cf2217f1aec9d807a6bed
byfaith/pb_chime5
toolbox/nt/database/iterator.py
[ "MIT" ]
Python
zip
<not_specific>
def zip(self, *others): """ Creates a `Dataset` by zipping together the given datasets. This method has two major differences to the built-in `zip()` function in Python. First the zipping happen based on the keys of the first dataset (i.e. The first defines the order). ...
Creates a `Dataset` by zipping together the given datasets. This method has two major differences to the built-in `zip()` function in Python. First the zipping happen based on the keys of the first dataset (i.e. The first defines the order). Second it is assumes that all datas...
Creates a `Dataset` by zipping together the given datasets. This method has two major differences to the built-in `zip()` function in Python. First the zipping happen based on the keys of the first dataset . Second it is assumes that all datasets have the same length and keys. (Could be removed, when someone needs it....
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def zip(self, *others): return ZipIterator(self, *others)
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Creates a `Dataset` by zipping together the given datasets.
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[ "\"\"\"\n Creates a `Dataset` by zipping together the given datasets.\n\n This method has two major differences to the built-in `zip()` function\n in Python. First the zipping happen based on the keys of the\n first dataset (i.e. The first defines the order).\n\n Second it is assu...
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
6adfaeb159e4b5e0b85cf2217f1aec9d807a6bed
byfaith/pb_chime5
toolbox/nt/database/iterator.py
[ "MIT" ]
Python
apply
<not_specific>
def apply(self, apply_fn: callable): """Allows to apply functions to the complete iterator, not to the examples itself. Args: apply_fn: For now, it is a single function, e.g. `lambda it: it.shard(num_shards, shard_index)` but can potentially be a list...
Allows to apply functions to the complete iterator, not to the examples itself. Args: apply_fn: For now, it is a single function, e.g. `lambda it: it.shard(num_shards, shard_index)` but can potentially be a list in future implementations. Returns: ...
Allows to apply functions to the complete iterator, not to the examples itself.
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def apply(self, apply_fn: callable): if apply_fn is None: return self elif isinstance(apply_fn, list): raise NotImplementedError else: return apply_fn(self)
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Allows to apply functions to the complete iterator, not to the examples itself.
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[ "\"\"\"Allows to apply functions to the complete iterator, not to the\n examples itself.\n\n Args:\n apply_fn: For now, it is a single function, e.g.\n `lambda it: it.shard(num_shards, shard_index)` but can\n potentially be a list in future implementations.\n\n...
[ { "param": "self", "type": null }, { "param": "apply_fn", "type": "callable" } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null ...
6adfaeb159e4b5e0b85cf2217f1aec9d807a6bed
byfaith/pb_chime5
toolbox/nt/database/iterator.py
[ "MIT" ]
Python
recursive_transform
<not_specific>
def recursive_transform(func, dict_list_val, list2array=False): """ Applies a function func to all leaf values in a dict or list or directly to a value. The hierarchy of dict_list_val is inherited. Lists are stacked to numpy arrays. This function can e.g. be used to recursively apply a transformatio...
Applies a function func to all leaf values in a dict or list or directly to a value. The hierarchy of dict_list_val is inherited. Lists are stacked to numpy arrays. This function can e.g. be used to recursively apply a transformation (e.g. audioread) to all audio paths in an example dict (see top o...
Applies a function func to all leaf values in a dict or list or directly to a value. The hierarchy of dict_list_val is inherited. Lists are stacked to numpy arrays.
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def recursive_transform(func, dict_list_val, list2array=False): if isinstance(dict_list_val, dict): return {key: recursive_transform(func, val, list2array) for key, val in dict_list_val.items()} if isinstance(dict_list_val, (list, tuple)): l = type(dict_list_val)( [re...
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Applies a function func to all leaf values in a dict or list or directly to a value.
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[ "\"\"\"\n Applies a function func to all leaf values in a dict or list or directly to\n a value. The hierarchy of dict_list_val is inherited. Lists are stacked\n to numpy arrays. This function can e.g. be used to recursively apply a\n transformation (e.g. audioread) to all audio paths in an example dict...
[ { "param": "func", "type": null }, { "param": "dict_list_val", "type": null }, { "param": "list2array", "type": null } ]
{ "returns": [ { "docstring": "dict, list or value with transformed elements", "docstring_tokens": [ "dict", "list", "or", "value", "with", "transformed", "elements" ], "type": null } ], "raises": [], "params": [ { ...
45af14cd10e3eaba4e58d4bb764a21f8df33f608
byfaith/pb_chime5
toolbox/nt/io/audiowrite.py
[ "MIT" ]
Python
dump_audio
<not_specific>
def dump_audio( obj, path, *, sample_rate=16000, dtype=np.int16, start=None, normalize=True, ): """ If normalize is False and the dytpe is float, the values of obj should be in the range [-1, 1). Params: obj: Shape (channels, samples) or (...
If normalize is False and the dytpe is float, the values of obj should be in the range [-1, 1). Params: obj: Shape (channels, samples) or (samples,) path: sample_rate: dtype: start: normalize: >>> from nt.utils.process_caller import run_process >>> ...
If normalize is False and the dytpe is float, the values of obj should be in the range [-1, 1).
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def dump_audio( obj, path, *, sample_rate=16000, dtype=np.int16, start=None, normalize=True, ): assert isinstance(path, (str, Path)), path if isinstance(path, Path): path = str(path) if normalize: if not obj.dtype.kind in ['f', 'i']: ...
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If normalize is False and the dytpe is float, the values of obj should be in the range [-1, 1).
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[ "\"\"\"\n If normalize is False and the dytpe is float, the values of obj should be in\n the range [-1, 1).\n\n Params:\n obj: Shape (channels, samples) or (samples,)\n path:\n sample_rate:\n dtype:\n start:\n normalize:\n\n >>> from nt.utils.process_caller impo...
[ { "param": "obj", "type": null }, { "param": "path", "type": null }, { "param": "sample_rate", "type": null }, { "param": "dtype", "type": null }, { "param": "start", "type": null }, { "param": "normalize", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "obj", "type": null, "docstring": "Shape (channels, samples) or (samples,)", "docstring_tokens": [ "Shape", "(", "channels", "samples", ")", "or", "(", "samples", ...
1bf8f41c1e9b7cf2e6801da679657578b5d57c76
byfaith/pb_chime5
toolbox/nt/transform/module_stft.py
[ "MIT" ]
Python
stft
np.array
def stft( time_signal, size: int=1024, shift: int=256, *, axis=-1, window: typing.Callable=signal.blackman, window_length: int=None, fading: bool=True, pad: bool=True, symmetric_window: bool=False, ) -> np.array: """ ToDo: Open poin...
ToDo: Open points: - sym_window need literature - fading why it is better? - should pad have more degrees of freedom? Calculates the short time Fourier transformation of a multi channel multi speaker time signal. It is able to add additional zeros for fade-in and fade out and should yie...
Open points: sym_window need literature fading why it is better. Calculates the short time Fourier transformation of a multi channel multi speaker time signal. It is able to add additional zeros for fade-in and fade out and should yield an STFT signal which allows perfect reconstruction.
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def stft( time_signal, size: int=1024, shift: int=256, *, axis=-1, window: typing.Callable=signal.blackman, window_length: int=None, fading: bool=True, pad: bool=True, symmetric_window: bool=False, ) -> np.array: time_signal = np.array(...
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ToDo: Open points: sym_window need literature fading why it is better?
[ "ToDo", ":", "Open", "points", ":", "sym_window", "need", "literature", "fading", "why", "it", "is", "better?" ]
[ "\"\"\"\n ToDo: Open points:\n - sym_window need literature\n - fading why it is better?\n - should pad have more degrees of freedom?\n\n Calculates the short time Fourier transformation of a multi channel multi\n speaker time signal. It is able to add additional zeros for fade-in and\n fade...
[ { "param": "time_signal", "type": null }, { "param": "size", "type": "int" }, { "param": "shift", "type": "int" }, { "param": "axis", "type": null }, { "param": "window", "type": "typing.Callable" }, { "param": "window_length", "type": "int" }, ...
{ "returns": [ { "docstring": "Single channel complex STFT signal with dimensions\nAA x ... x AZ x T' times size/2+1 times BA x ... x BZ.", "docstring_tokens": [ "Single", "channel", "complex", "STFT", "signal", "with", "dimensions", "AA"...
1bf8f41c1e9b7cf2e6801da679657578b5d57c76
byfaith/pb_chime5
toolbox/nt/transform/module_stft.py
[ "MIT" ]
Python
stft_with_kaldi_dimensions
<not_specific>
def stft_with_kaldi_dimensions( time_signal, size: int = 512, shift: int = 160, *, axis=-1, window=signal.blackman, window_length=400, symmetric_window: bool = False ): """ The Kaldi implementation uses another non standard window. See: - ...
The Kaldi implementation uses another non standard window. See: - https://github.com/kaldi-asr/kaldi/blob/master/src/feat/feature-window.h#L48 - https://github.com/kaldi-asr/kaldi/blob/81b7a1947fb8df501a2bbb680b65ce18ce606cff/src/feat/feature-window.h#L48 ..note:: Kaldi uses symmetric_win...
The Kaldi implementation uses another non standard window.
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def stft_with_kaldi_dimensions( time_signal, size: int = 512, shift: int = 160, *, axis=-1, window=signal.blackman, window_length=400, symmetric_window: bool = False ): return stft( time_signal, size=size, shift=shift, a...
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The Kaldi implementation uses another non standard window.
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[ "\"\"\"\n The Kaldi implementation uses another non standard window.\n See:\n - https://github.com/kaldi-asr/kaldi/blob/master/src/feat/feature-window.h#L48\n - https://github.com/kaldi-asr/kaldi/blob/81b7a1947fb8df501a2bbb680b65ce18ce606cff/src/feat/feature-window.h#L48\n\n ..note::\n Kaldi ...
[ { "param": "time_signal", "type": null }, { "param": "size", "type": "int" }, { "param": "shift", "type": "int" }, { "param": "axis", "type": null }, { "param": "window", "type": null }, { "param": "window_length", "type": null }, { "param"...
{ "returns": [], "raises": [], "params": [ { "identifier": "time_signal", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "size", "type": "int", "docstring": null, "docstring_to...
1bf8f41c1e9b7cf2e6801da679657578b5d57c76
byfaith/pb_chime5
toolbox/nt/transform/module_stft.py
[ "MIT" ]
Python
_samples_to_stft_frames
<not_specific>
def _samples_to_stft_frames( samples, size, shift, *, fading=False, ): """ Calculates STFT frames from samples in time domain. :param samples: Number of samples in time domain. :param size: window_length often equal to FFT size. The name size shou...
Calculates STFT frames from samples in time domain. :param samples: Number of samples in time domain. :param size: window_length often equal to FFT size. The name size should be marked as deprecated and replaced with window_length. :param shift: Hop in samples. :pa...
Calculates STFT frames from samples in time domain.
[ "Calculates", "STFT", "frames", "from", "samples", "in", "time", "domain", "." ]
def _samples_to_stft_frames( samples, size, shift, *, fading=False, ): if fading: samples = samples + 2 * (size - shift) return ceil((samples - size + shift) / shift)
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Calculates STFT frames from samples in time domain.
[ "Calculates", "STFT", "frames", "from", "samples", "in", "time", "domain", "." ]
[ "\"\"\"\n Calculates STFT frames from samples in time domain.\n :param samples: Number of samples in time domain.\n :param size: window_length often equal to FFT size.\n The name size should be marked as deprecated and replaced with\n window_length.\n :param shift: Hop in...
[ { "param": "samples", "type": null }, { "param": "size", "type": null }, { "param": "shift", "type": null }, { "param": "fading", "type": null } ]
{ "returns": [ { "docstring": "Number of STFT frames.\n\n\n\n\n\n\n\n", "docstring_tokens": [ "Number", "of", "STFT", "frames", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "samples", "type": null, ...
1bf8f41c1e9b7cf2e6801da679657578b5d57c76
byfaith/pb_chime5
toolbox/nt/transform/module_stft.py
[ "MIT" ]
Python
_stft_frames_to_samples
<not_specific>
def _stft_frames_to_samples(frames, size, shift, fading=False): """ Calculates samples in time domain from STFT frames :param frames: Number of STFT frames. :param size: FFT size. :param shift: Hop in samples. :return: Number of samples in time domain. >>> _stft_frames_to_samples(2, 16, 4) ...
Calculates samples in time domain from STFT frames :param frames: Number of STFT frames. :param size: FFT size. :param shift: Hop in samples. :return: Number of samples in time domain. >>> _stft_frames_to_samples(2, 16, 4) 20
Calculates samples in time domain from STFT frames
[ "Calculates", "samples", "in", "time", "domain", "from", "STFT", "frames" ]
def _stft_frames_to_samples(frames, size, shift, fading=False): if fading: assert 'Not implemented' return frames * shift + size - shift
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Calculates samples in time domain from STFT frames
[ "Calculates", "samples", "in", "time", "domain", "from", "STFT", "frames" ]
[ "\"\"\"\n Calculates samples in time domain from STFT frames\n :param frames: Number of STFT frames.\n :param size: FFT size.\n :param shift: Hop in samples.\n :return: Number of samples in time domain.\n\n >>> _stft_frames_to_samples(2, 16, 4)\n 20\n \"\"\"" ]
[ { "param": "frames", "type": null }, { "param": "size", "type": null }, { "param": "shift", "type": null }, { "param": "fading", "type": null } ]
{ "returns": [ { "docstring": "Number of samples in time domain.", "docstring_tokens": [ "Number", "of", "samples", "in", "time", "domain", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "frames...
1bf8f41c1e9b7cf2e6801da679657578b5d57c76
byfaith/pb_chime5
toolbox/nt/transform/module_stft.py
[ "MIT" ]
Python
sample_id_to_stft_frame_id
<not_specific>
def sample_id_to_stft_frame_id(sample, window_length, shift, fading=True): """ Calculates the best frame index for a given sample index :param sample: Sample index in time domain. :param size: FFT size. :param shift: Hop in samples. :return: Best STFT frame index. ## ## ## ## ## ## ...
Calculates the best frame index for a given sample index :param sample: Sample index in time domain. :param size: FFT size. :param shift: Hop in samples. :return: Best STFT frame index. ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## ## 00 00 01 12 23 34 45 ...
Calculates the best frame index for a given sample index
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def sample_id_to_stft_frame_id(sample, window_length, shift, fading=True): if (window_length + 1) // 2 > sample: frame = 0 else: frame = (sample - (window_length + 1) // 2) // shift + 1 if fading: frame = frame + ceil((window_length - shift) / shift) return frame
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Calculates the best frame index for a given sample index
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[ "\"\"\"\n Calculates the best frame index for a given sample index\n :param sample: Sample index in time domain.\n :param size: FFT size.\n :param shift: Hop in samples.\n :return: Best STFT frame index.\n\n\n ## ## ## ##\n ## ## ## ##\n ## ## ## ##\n ## ## ## ##\n 00...
[ { "param": "sample", "type": null }, { "param": "window_length", "type": null }, { "param": "shift", "type": null }, { "param": "fading", "type": null } ]
{ "returns": [ { "docstring": "Best STFT frame index.\n\n\n\n\n\n\n\n\n\n", "docstring_tokens": [ "Best", "STFT", "frame", "index", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "sample", "type": null, ...
1bf8f41c1e9b7cf2e6801da679657578b5d57c76
byfaith/pb_chime5
toolbox/nt/transform/module_stft.py
[ "MIT" ]
Python
istft
<not_specific>
def istft( stft_signal, size: int=1024, shift: int=256, *, window: typing.Callable=signal.blackman, fading: bool=True, window_length: int=None, symmetric_window: bool=False, ): """ Calculated the inverse short time Fourier transform to exactly reco...
Calculated the inverse short time Fourier transform to exactly reconstruct the time signal. ..note:: Be careful if you make modifications in the frequency domain (e.g. beamforming) because the synthesis window is calculated according to the unmodified! analysis window. :param ...
Calculated the inverse short time Fourier transform to exactly reconstruct the time signal. : Be careful if you make modifications in the frequency domain because the synthesis window is calculated according to the unmodified. analysis window.
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def istft( stft_signal, size: int=1024, shift: int=256, *, window: typing.Callable=signal.blackman, fading: bool=True, window_length: int=None, symmetric_window: bool=False, ): stft_signal = np.array(stft_signal) assert stft_signal.shape[-1] == siz...
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Calculated the inverse short time Fourier transform to exactly reconstruct the time signal.
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[ "\"\"\"\n Calculated the inverse short time Fourier transform to exactly reconstruct\n the time signal.\n\n ..note::\n Be careful if you make modifications in the frequency domain (e.g.\n beamforming) because the synthesis window is calculated according to\n the unmodified! analysis wi...
[ { "param": "stft_signal", "type": null }, { "param": "size", "type": "int" }, { "param": "shift", "type": "int" }, { "param": "window", "type": "typing.Callable" }, { "param": "fading", "type": "bool" }, { "param": "window_length", "type": "int" ...
{ "returns": [ { "docstring": "Single channel complex STFT signal", "docstring_tokens": [ "Single", "channel", "complex", "STFT", "signal" ], "type": null }, { "docstring": "Single channel time signal.", "docstring_tokens": [ ...
402450efd066ada3a13d893ccea9d53bd3623299
byfaith/pb_chime5
toolbox/nt/database/chime5/__init__.py
[ "MIT" ]
Python
word2id
<not_specific>
def word2id(self, word): """Returns the integer ID for a given word. If the word is not found, it returns the ID for `<UNK>`. """ try: return self._word2id_dict[word] except KeyError: return self._word2id_dict['<eps>']
Returns the integer ID for a given word. If the word is not found, it returns the ID for `<UNK>`.
Returns the integer ID for a given word. If the word is not found, it returns the ID for ``.
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def word2id(self, word): try: return self._word2id_dict[word] except KeyError: return self._word2id_dict['<eps>']
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Returns the integer ID for a given word.
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[ "\"\"\"Returns the integer ID for a given word.\n\n If the word is not found, it returns the ID for `<UNK>`.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "word", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "word", "type": null, "docstring": null, "docstring_tokens": [...
402450efd066ada3a13d893ccea9d53bd3623299
byfaith/pb_chime5
toolbox/nt/database/chime5/__init__.py
[ "MIT" ]
Python
recursive_transform
<not_specific>
def recursive_transform(func, dict_list_val, start, end, list2array=False): """ Applies a function func to all leaf values in a dict or list or directly to a value. The hierarchy of dict_list_val is inherited. Lists are stacked to numpy arrays. This function can e.g. be used to recursively apply a t...
Applies a function func to all leaf values in a dict or list or directly to a value. The hierarchy of dict_list_val is inherited. Lists are stacked to numpy arrays. This function can e.g. be used to recursively apply a transformation (e.g. audioread) to all audio paths in an example dict (see top o...
Applies a function func to all leaf values in a dict or list or directly to a value. The hierarchy of dict_list_val is inherited. Lists are stacked to numpy arrays.
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def recursive_transform(func, dict_list_val, start, end, list2array=False): if isinstance(dict_list_val, dict): return { key: recursive_transform( func, val, start=start[key], end=end[key], list2array=list2array, ...
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Applies a function func to all leaf values in a dict or list or directly to a value.
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[ "\"\"\"\n Applies a function func to all leaf values in a dict or list or directly to\n a value. The hierarchy of dict_list_val is inherited. Lists are stacked\n to numpy arrays. This function can e.g. be used to recursively apply a\n transformation (e.g. audioread) to all audio paths in an example dict...
[ { "param": "func", "type": null }, { "param": "dict_list_val", "type": null }, { "param": "start", "type": null }, { "param": "end", "type": null }, { "param": "list2array", "type": null } ]
{ "returns": [ { "docstring": "dict, list or value with transformed elements", "docstring_tokens": [ "dict", "list", "or", "value", "with", "transformed", "elements" ], "type": null } ], "raises": [], "params": [ { ...
34a7c7c8bbfbbadedd342a4ae9a01b7241119d45
byfaith/pb_chime5
toolbox/nt/database/__init__.py
[ "MIT" ]
Python
to_list
<not_specific>
def to_list(x, item_type=None): """ Note: It is recommended to use item_type, when the type of the list is known to catch as much cases as possible. The problem is that many python functions return a type that does not inherit from tuple and/or list. e.g. dict keys, dict ...
Note: It is recommended to use item_type, when the type of the list is known to catch as much cases as possible. The problem is that many python functions return a type that does not inherit from tuple and/or list. e.g. dict keys, dict values, map, sorted, ... The i...
It is recommended to use item_type, when the type of the list is known to catch as much cases as possible. The problem is that many python functions return a type that does not inherit from tuple and/or list. The instance check with collections.Sequence could produce problem with str. (isinstance('any str', collection...
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def to_list(x, item_type=None): if item_type is None: if isinstance(x, (list, tuple)): return x return [x] else: if isinstance(x, item_type): return [x] return list(x)
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Note: It is recommended to use item_type, when the type of the list is known to catch as much cases as possible.
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[ "\"\"\"\n Note:\n It is recommended to use item_type, when the type of the list is known\n to catch as much cases as possible.\n The problem is that many python functions return a type that does not\n inherit from tuple and/or list.\n e.g. dict keys, dict values, map, sorted, ....
[ { "param": "x", "type": null }, { "param": "item_type", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "x", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "item_type", "type": null, "docstring": null, "docstring_tokens":...
34a7c7c8bbfbbadedd342a4ae9a01b7241119d45
byfaith/pb_chime5
toolbox/nt/database/__init__.py
[ "MIT" ]
Python
ali_path_train
<not_specific>
def ali_path_train(self): """Path containing the kaldi alignments for train data.""" if self.lfr: return self.ali_path_train_lfr else: return self.ali_path_train_ffr
Path containing the kaldi alignments for train data.
Path containing the kaldi alignments for train data.
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def ali_path_train(self): if self.lfr: return self.ali_path_train_lfr else: return self.ali_path_train_ffr
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Path containing the kaldi alignments for train data.
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[ "\"\"\"Path containing the kaldi alignments for train data.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
34a7c7c8bbfbbadedd342a4ae9a01b7241119d45
byfaith/pb_chime5
toolbox/nt/database/__init__.py
[ "MIT" ]
Python
hclg_path
<not_specific>
def hclg_path(self): """Path to HCLG directory created by Kaldi.""" if self.lfr: return self.hclg_path_lfr else: return self.hclg_path_ffr
Path to HCLG directory created by Kaldi.
Path to HCLG directory created by Kaldi.
[ "Path", "to", "HCLG", "directory", "created", "by", "Kaldi", "." ]
def hclg_path(self): if self.lfr: return self.hclg_path_lfr else: return self.hclg_path_ffr
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Path to HCLG directory created by Kaldi.
[ "Path", "to", "HCLG", "directory", "created", "by", "Kaldi", "." ]
[ "\"\"\"Path to HCLG directory created by Kaldi.\"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
34a7c7c8bbfbbadedd342a4ae9a01b7241119d45
byfaith/pb_chime5
toolbox/nt/database/__init__.py
[ "MIT" ]
Python
word2id
<not_specific>
def word2id(self, word): """Returns the integer ID for a given word. If the word is not found, it returns the ID for `<UNK>`. """ try: return self._word2id_dict[word] except KeyError: return self._word2id_dict['<UNK>']
Returns the integer ID for a given word. If the word is not found, it returns the ID for `<UNK>`.
Returns the integer ID for a given word. If the word is not found, it returns the ID for ``.
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def word2id(self, word): try: return self._word2id_dict[word] except KeyError: return self._word2id_dict['<UNK>']
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Returns the integer ID for a given word.
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[ "\"\"\"Returns the integer ID for a given word.\n\n If the word is not found, it returns the ID for `<UNK>`.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "word", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "word", "type": null, "docstring": null, "docstring_tokens": [...
bff2146aaea27d8f670b2a02577fadda7ba9c2de
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_examples/scripts/gripper_joystick.py
[ "Apache-2.0" ]
Python
map_joystick
<not_specific>
def map_joystick(joystick, limb): """ maps joystick input to gripper commands @param joystick: an instance of a Joystick """ print("Getting robot state... ") rs = intera_interface.RobotEnable(intera_interface.CHECK_VERSION) init_state = rs.state() try: gripper = intera_interface...
maps joystick input to gripper commands @param joystick: an instance of a Joystick
maps joystick input to gripper commands
[ "maps", "joystick", "input", "to", "gripper", "commands" ]
def map_joystick(joystick, limb): print("Getting robot state... ") rs = intera_interface.RobotEnable(intera_interface.CHECK_VERSION) init_state = rs.state() try: gripper = intera_interface.Gripper(limb) except ValueError: rospy.logerr("Could not detect a gripper attached to the robot...
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maps joystick input to gripper commands
[ "maps", "joystick", "input", "to", "gripper", "commands" ]
[ "\"\"\"\n maps joystick input to gripper commands\n\n @param joystick: an instance of a Joystick\n \"\"\"", "# decrease position dead_zone", "# abbreviations", "#(test, command, description)", "# test each joystick condition and call binding cmd if true" ]
[ { "param": "joystick", "type": null }, { "param": "limb", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "joystick", "type": null, "docstring": "an instance of a Joystick", "docstring_tokens": [ "an", "instance", "of", "a", "Joystick" ], "default": null, "is_optional": fals...
0c3fcaec256f7fa2c5e6991653f97e6ef171ddc9
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_examples/scripts/gripper_keyboard.py
[ "Apache-2.0" ]
Python
main
<not_specific>
def main(): """RSDK Gripper Example: Keyboard Control Use your dev machine's keyboard to control and configure grippers. Run this example to command various gripper movements while adjusting gripper parameters, including calibration, velocity, and force. Uses the intera_interface.Gripper class and...
RSDK Gripper Example: Keyboard Control Use your dev machine's keyboard to control and configure grippers. Run this example to command various gripper movements while adjusting gripper parameters, including calibration, velocity, and force. Uses the intera_interface.Gripper class and the helper fun...
RSDK Gripper Example: Keyboard Control Use your dev machine's keyboard to control and configure grippers. Run this example to command various gripper movements while adjusting gripper parameters, including calibration, velocity, and force.
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def main(): epilog = """ See help inside the example with the '?' key for key bindings. """ rp = intera_interface.RobotParams() valid_limbs = rp.get_limb_names() if not valid_limbs: rp.log_message(("Cannot detect any limb parameters on this robot. " "Exiting."), "ERRO...
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RSDK Gripper Example: Keyboard Control Use your dev machine's keyboard to control and configure grippers.
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[ "\"\"\"RSDK Gripper Example: Keyboard Control\n\n Use your dev machine's keyboard to control and configure grippers.\n\n Run this example to command various gripper movements while\n adjusting gripper parameters, including calibration, velocity,\n and force. Uses the intera_interface.Gripper class and t...
[]
{ "returns": [], "raises": [], "params": [], "outlier_params": [], "others": [] }
dacac992daacbb7d787f5b1561bcd81b8a5bd22a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_examples/scripts/ar10_hand_pressurecontrol.py
[ "Apache-2.0" ]
Python
response
null
def response(data): # main that is called when a message from commands is recieved ''' Reads in data from tactile sensors. either keeps continue grabbing motion or stop based on the readings. ''' hand = ar10() #creating instance of ar10 hand #hand.open_hand() # opens the hand rospy.loginfo(...
Reads in data from tactile sensors. either keeps continue grabbing motion or stop based on the readings.
Reads in data from tactile sensors. either keeps continue grabbing motion or stop based on the readings.
[ "Reads", "in", "data", "from", "tactile", "sensors", ".", "either", "keeps", "continue", "grabbing", "motion", "or", "stop", "based", "on", "the", "readings", "." ]
def response(data): hand = ar10() rospy.loginfo(rospy.get_caller_id() + '\nI heard %s', data.data) message = data.data global target,targetstep if message == "q": print("object grabbed!!!!") sub.unregister() print("Finished Grabbing.") print('target value:{}'....
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Reads in data from tactile sensors.
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[ "# main that is called when a message from commands is recieved", "'''\n Reads in data from tactile sensors.\n either keeps continue grabbing motion or stop based on the readings. \n '''", "#creating instance of ar10 hand", "#hand.open_hand() # opens the hand", "# logs messages recieved from comman...
[ { "param": "data", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "data", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
838da429cb810b320a5e36462c2bebd0e3264401
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/camera.py
[ "Apache-2.0" ]
Python
_camera_streaming_status
<not_specific>
def _camera_streaming_status(self, camera_name): """ Private function to check if the camera is currently in streaming mode. @type camera_name: str @param camera_name: camera name @rtype: bool @return: True if the camera is streaming, False otherwise """ ...
Private function to check if the camera is currently in streaming mode. @type camera_name: str @param camera_name: camera name @rtype: bool @return: True if the camera is streaming, False otherwise
Private function to check if the camera is currently in streaming mode.
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def _camera_streaming_status(self, camera_name): return self.cameras_io[camera_name]['interface'].get_signal_value( "camera_streaming")
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Private function to check if the camera is currently in streaming mode.
[ "Private", "function", "to", "check", "if", "the", "camera", "is", "currently", "in", "streaming", "mode", "." ]
[ "\"\"\"\n Private function to check if the camera is currently in streaming mode.\n\n @type camera_name: str\n @param camera_name: camera name\n\n @rtype: bool\n @return: True if the camera is streaming, False otherwise\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "camera_name", "type": null } ]
{ "returns": [ { "docstring": "True if the camera is streaming, False otherwise", "docstring_tokens": [ "True", "if", "the", "camera", "is", "streaming", "False", "otherwise" ], "type": "bool" } ], "raises": [], "par...
838da429cb810b320a5e36462c2bebd0e3264401
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/camera.py
[ "Apache-2.0" ]
Python
list_cameras
<not_specific>
def list_cameras(self): """ Return the list of all camera names on current robot. @rtype: [str] @return: ordered list of camera names """ return self.cameras_io.keys()
Return the list of all camera names on current robot. @rtype: [str] @return: ordered list of camera names
Return the list of all camera names on current robot.
[ "Return", "the", "list", "of", "all", "camera", "names", "on", "current", "robot", "." ]
def list_cameras(self): return self.cameras_io.keys()
[ "def", "list_cameras", "(", "self", ")", ":", "return", "self", ".", "cameras_io", ".", "keys", "(", ")" ]
Return the list of all camera names on current robot.
[ "Return", "the", "list", "of", "all", "camera", "names", "on", "current", "robot", "." ]
[ "\"\"\"\n Return the list of all camera names on current robot.\n\n @rtype: [str]\n @return: ordered list of camera names\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "ordered list of camera names", "docstring_tokens": [ "ordered", "list", "of", "camera", "names" ], "type": "[str]" } ], "raises": [], "params": [ { "identifier": "self", "type": null, "do...
838da429cb810b320a5e36462c2bebd0e3264401
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/camera.py
[ "Apache-2.0" ]
Python
verify_camera_exists
<not_specific>
def verify_camera_exists(self, camera_name): """ Verify if the given camera name is in the list of camera names or not. @type camera_name: str @param camera_name: camera name @rtype: bool @return: True if the name exists in camera name list, False otherwise. """...
Verify if the given camera name is in the list of camera names or not. @type camera_name: str @param camera_name: camera name @rtype: bool @return: True if the name exists in camera name list, False otherwise.
Verify if the given camera name is in the list of camera names or not.
[ "Verify", "if", "the", "given", "camera", "name", "is", "in", "the", "list", "of", "camera", "names", "or", "not", "." ]
def verify_camera_exists(self, camera_name): if camera_name not in self.list_cameras(): rospy.logerr(' '.join([camera_name, "not in the list of cameras" " detected on this robot:", ' , '.join(self.list_cameras())])) return False return True
[ "def", "verify_camera_exists", "(", "self", ",", "camera_name", ")", ":", "if", "camera_name", "not", "in", "self", ".", "list_cameras", "(", ")", ":", "rospy", ".", "logerr", "(", "' '", ".", "join", "(", "[", "camera_name", ",", "\"not in the list of camer...
Verify if the given camera name is in the list of camera names or not.
[ "Verify", "if", "the", "given", "camera", "name", "is", "in", "the", "list", "of", "camera", "names", "or", "not", "." ]
[ "\"\"\"\n Verify if the given camera name is in the list of camera names or not.\n\n @type camera_name: str\n @param camera_name: camera name\n\n @rtype: bool\n @return: True if the name exists in camera name list, False otherwise.\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "camera_name", "type": null } ]
{ "returns": [ { "docstring": "True if the name exists in camera name list, False otherwise.", "docstring_tokens": [ "True", "if", "the", "name", "exists", "in", "camera", "name", "list", "False", "otherwise", ...
838da429cb810b320a5e36462c2bebd0e3264401
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/camera.py
[ "Apache-2.0" ]
Python
is_camera_streaming
<not_specific>
def is_camera_streaming(self, camera_name): """ Check the given camera name is streaming or not. @type camera_name: str @param camera_name: camera name @rtype: bool @return: True if the camera is streaming, False camera is not streaming, False with log ...
Check the given camera name is streaming or not. @type camera_name: str @param camera_name: camera name @rtype: bool @return: True if the camera is streaming, False camera is not streaming, False with log error means camera name not exists in ...
Check the given camera name is streaming or not.
[ "Check", "the", "given", "camera", "name", "is", "streaming", "or", "not", "." ]
def is_camera_streaming(self, camera_name): if self.verify_camera_exists(camera_name): return self._camera_streaming_status(camera_name) return False
[ "def", "is_camera_streaming", "(", "self", ",", "camera_name", ")", ":", "if", "self", ".", "verify_camera_exists", "(", "camera_name", ")", ":", "return", "self", ".", "_camera_streaming_status", "(", "camera_name", ")", "return", "False" ]
Check the given camera name is streaming or not.
[ "Check", "the", "given", "camera", "name", "is", "streaming", "or", "not", "." ]
[ "\"\"\"\n Check the given camera name is streaming or not.\n\n @type camera_name: str\n @param camera_name: camera name\n\n @rtype: bool\n @return: True if the camera is streaming, False camera is not\n streaming, False with log error means camera name not exists\n...
[ { "param": "self", "type": null }, { "param": "camera_name", "type": null } ]
{ "returns": [ { "docstring": "True if the camera is streaming, False camera is not\nstreaming, False with log error means camera name not exists\nin camera name list", "docstring_tokens": [ "True", "if", "the", "camera", "is", "streaming", "Fals...
838da429cb810b320a5e36462c2bebd0e3264401
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/camera.py
[ "Apache-2.0" ]
Python
start_streaming
<not_specific>
def start_streaming(self, camera_name): """ Start camera streaming for the given camera name, This only allows one camera open at one time and forces closed any other open cameras before open the wanted one. @type camera_name: str @param camera_name: camera name ...
Start camera streaming for the given camera name, This only allows one camera open at one time and forces closed any other open cameras before open the wanted one. @type camera_name: str @param camera_name: camera name @rtype: bool @return: False if camera not ...
Start camera streaming for the given camera name, This only allows one camera open at one time and forces closed any other open cameras before open the wanted one.
[ "Start", "camera", "streaming", "for", "the", "given", "camera", "name", "This", "only", "allows", "one", "camera", "open", "at", "one", "time", "and", "forces", "closed", "any", "other", "open", "cameras", "before", "open", "the", "wanted", "one", "." ]
def start_streaming(self, camera_name): if not self.verify_camera_exists(camera_name): return False elif not self._camera_streaming_status(camera_name): other_cameras_list = list(set(self.list_cameras())-set([ camera_name])) for other_camera in other_c...
[ "def", "start_streaming", "(", "self", ",", "camera_name", ")", ":", "if", "not", "self", ".", "verify_camera_exists", "(", "camera_name", ")", ":", "return", "False", "elif", "not", "self", ".", "_camera_streaming_status", "(", "camera_name", ")", ":", "other...
Start camera streaming for the given camera name, This only allows one camera open at one time and forces closed any other open cameras before open the wanted one.
[ "Start", "camera", "streaming", "for", "the", "given", "camera", "name", "This", "only", "allows", "one", "camera", "open", "at", "one", "time", "and", "forces", "closed", "any", "other", "open", "cameras", "before", "open", "the", "wanted", "one", "." ]
[ "\"\"\"\n Start camera streaming for the given camera name, This only allows\n one camera open at one time and forces closed any other open cameras\n before open the wanted one.\n\n @type camera_name: str\n @param camera_name: camera name\n\n @rtype: bool\n @return: ...
[ { "param": "self", "type": null }, { "param": "camera_name", "type": null } ]
{ "returns": [ { "docstring": "False if camera not exists in camera_name_list or the\ninterface is not able to stop streaming other camera.\nAdditionally, returns False if the interface is not able\nto start streaming the desired camera. Returns True if the\ncamera already streaming or the camera successful...
838da429cb810b320a5e36462c2bebd0e3264401
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/camera.py
[ "Apache-2.0" ]
Python
stop_streaming
<not_specific>
def stop_streaming(self, camera_name): """ Stop camera streaming by given the camera name. @type camera_name: str @param camera_name: camera name @rtype: bool @return: False if camera not exists in camera name list or not able to stop streaming camera. ...
Stop camera streaming by given the camera name. @type camera_name: str @param camera_name: camera name @rtype: bool @return: False if camera not exists in camera name list or not able to stop streaming camera. True if the camera not is streaming ...
Stop camera streaming by given the camera name.
[ "Stop", "camera", "streaming", "by", "given", "the", "camera", "name", "." ]
def stop_streaming(self, camera_name): if not self.verify_camera_exists(camera_name): return False elif self._camera_streaming_status(camera_name): self.cameras_io[camera_name]['interface'].set_signal_value( "camera_streaming", False) if self._camera_s...
[ "def", "stop_streaming", "(", "self", ",", "camera_name", ")", ":", "if", "not", "self", ".", "verify_camera_exists", "(", "camera_name", ")", ":", "return", "False", "elif", "self", ".", "_camera_streaming_status", "(", "camera_name", ")", ":", "self", ".", ...
Stop camera streaming by given the camera name.
[ "Stop", "camera", "streaming", "by", "given", "the", "camera", "name", "." ]
[ "\"\"\"\n Stop camera streaming by given the camera name.\n\n @type camera_name: str\n @param camera_name: camera name\n\n @rtype: bool\n @return: False if camera not exists in camera name list or not able\n to stop streaming camera. True if the camera not is strea...
[ { "param": "self", "type": null }, { "param": "camera_name", "type": null } ]
{ "returns": [ { "docstring": "False if camera not exists in camera name list or not able\nto stop streaming camera. True if the camera not is streaming\nmode or the camera successfully stop streaming.", "docstring_tokens": [ "False", "if", "camera", "not", "exi...
047f9e5cf280deaa6a3bf73cdb11e47a123784ad
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_examples/scripts/manageArmTrajectory.py
[ "Apache-2.0" ]
Python
response
null
def response(data): # main that is called when a message from commands is recieved ''' Reads in data from tactile sensors. either keeps continue grabbing motion or stop based on the readings. ''' rospy.loginfo(rospy.get_caller_id() + '\nI heard %s', data.data) # logs messages recieved from commands...
Reads in data from tactile sensors. either keeps continue grabbing motion or stop based on the readings.
Reads in data from tactile sensors. either keeps continue grabbing motion or stop based on the readings.
[ "Reads", "in", "data", "from", "tactile", "sensors", ".", "either", "keeps", "continue", "grabbing", "motion", "or", "stop", "based", "on", "the", "readings", "." ]
def response(data): rospy.loginfo(rospy.get_caller_id() + '\nI heard %s', data.data) message = data.data global target,targetstep if message == "q": print("object grabbed!!!!") sub.unregister() print("Finished Grabbing.") os.system(r"rosrun intera_examples head_dis...
[ "def", "response", "(", "data", ")", ":", "rospy", ".", "loginfo", "(", "rospy", ".", "get_caller_id", "(", ")", "+", "'\\nI heard %s'", ",", "data", ".", "data", ")", "message", "=", "data", ".", "data", "global", "target", ",", "targetstep", "if", "m...
Reads in data from tactile sensors.
[ "Reads", "in", "data", "from", "tactile", "sensors", "." ]
[ "# main that is called when a message from commands is recieved", "'''\n Reads in data from tactile sensors.\n either keeps continue grabbing motion or stop based on the readings. \n '''", "# logs messages recieved from commands to /rosout", "#os.system(r\"rosrun intera_examples head_display_image.py...
[ { "param": "data", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "data", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
24e65b07affb37ff3dad1baf1d93658fa2ada001
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/limb.py
[ "Apache-2.0" ]
Python
has_collided
<not_specific>
def has_collided(self): """ Return True if the specified limb has experienced a collision. @rtype: bool @return: True if the arm is in collision, False otherwise. """ return self._collision_state
Return True if the specified limb has experienced a collision. @rtype: bool @return: True if the arm is in collision, False otherwise.
Return True if the specified limb has experienced a collision.
[ "Return", "True", "if", "the", "specified", "limb", "has", "experienced", "a", "collision", "." ]
def has_collided(self): return self._collision_state
[ "def", "has_collided", "(", "self", ")", ":", "return", "self", ".", "_collision_state" ]
Return True if the specified limb has experienced a collision.
[ "Return", "True", "if", "the", "specified", "limb", "has", "experienced", "a", "collision", "." ]
[ "\"\"\"\n Return True if the specified limb has experienced a collision.\n\n @rtype: bool\n @return: True if the arm is in collision, False otherwise.\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "True if the arm is in collision, False otherwise.", "docstring_tokens": [ "True", "if", "the", "arm", "is", "in", "collision", "False", "otherwise", "." ], "type": "bool" } ...
24e65b07affb37ff3dad1baf1d93658fa2ada001
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/limb.py
[ "Apache-2.0" ]
Python
move_to_neutral
<not_specific>
def move_to_neutral(self, timeout=15.0, speed=0.3): """ Command the Limb joints to a predefined set of "neutral" joint angles. From rosparam named_poses/<limb>/poses/neutral. @type timeout: float @param timeout: seconds to wait for move to finish [15] @type speed: float ...
Command the Limb joints to a predefined set of "neutral" joint angles. From rosparam named_poses/<limb>/poses/neutral. @type timeout: float @param timeout: seconds to wait for move to finish [15] @type speed: float @param speed: ratio of maximum joint speed for executio...
Command the Limb joints to a predefined set of "neutral" joint angles.
[ "Command", "the", "Limb", "joints", "to", "a", "predefined", "set", "of", "\"", "neutral", "\"", "joint", "angles", "." ]
def move_to_neutral(self, timeout=15.0, speed=0.3): try: neutral_pose = rospy.get_param("named_poses/{0}/poses/neutral".format(self.name)) except KeyError: rospy.logerr(("Get neutral pose failed, arm: \"{0}\".").format(self.name)) return angles = dict(zip(self...
[ "def", "move_to_neutral", "(", "self", ",", "timeout", "=", "15.0", ",", "speed", "=", "0.3", ")", ":", "try", ":", "neutral_pose", "=", "rospy", ".", "get_param", "(", "\"named_poses/{0}/poses/neutral\"", ".", "format", "(", "self", ".", "name", ")", ")",...
Command the Limb joints to a predefined set of "neutral" joint angles.
[ "Command", "the", "Limb", "joints", "to", "a", "predefined", "set", "of", "\"", "neutral", "\"", "joint", "angles", "." ]
[ "\"\"\"\n Command the Limb joints to a predefined set of \"neutral\" joint angles.\n From rosparam named_poses/<limb>/poses/neutral.\n\n @type timeout: float\n @param timeout: seconds to wait for move to finish [15]\n @type speed: float\n @param speed: ratio of maximum join...
[ { "param": "self", "type": null }, { "param": "timeout", "type": null }, { "param": "speed", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "timeout", "type": null, "docstring": "seconds to wait for move to f...
24e65b07affb37ff3dad1baf1d93658fa2ada001
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/limb.py
[ "Apache-2.0" ]
Python
move_to_joint_positions
<not_specific>
def move_to_joint_positions(self, positions, timeout=15.0, threshold=settings.JOINT_ANGLE_TOLERANCE, test=None): """ (Blocking) Commands the limb to the provided positions. Waits until the reported joint state matches that specifie...
(Blocking) Commands the limb to the provided positions. Waits until the reported joint state matches that specified. This function uses a low-pass filter to smooth the movement. @type positions: dict({str:float}) @param positions: joint_name:angle command @type timeou...
(Blocking) Commands the limb to the provided positions. Waits until the reported joint state matches that specified. This function uses a low-pass filter to smooth the movement.
[ "(", "Blocking", ")", "Commands", "the", "limb", "to", "the", "provided", "positions", ".", "Waits", "until", "the", "reported", "joint", "state", "matches", "that", "specified", ".", "This", "function", "uses", "a", "low", "-", "pass", "filter", "to", "sm...
def move_to_joint_positions(self, positions, timeout=15.0, threshold=settings.JOINT_ANGLE_TOLERANCE, test=None): cmd = self.joint_angles() def genf(joint, angle): def joint_diff(): return abs(angle - self._joint_...
[ "def", "move_to_joint_positions", "(", "self", ",", "positions", ",", "timeout", "=", "15.0", ",", "threshold", "=", "settings", ".", "JOINT_ANGLE_TOLERANCE", ",", "test", "=", "None", ")", ":", "cmd", "=", "self", ".", "joint_angles", "(", ")", "def", "ge...
(Blocking) Commands the limb to the provided positions.
[ "(", "Blocking", ")", "Commands", "the", "limb", "to", "the", "provided", "positions", "." ]
[ "\"\"\"\n (Blocking) Commands the limb to the provided positions.\n\n Waits until the reported joint state matches that specified.\n\n This function uses a low-pass filter to smooth the movement.\n\n @type positions: dict({str:float})\n @param positions: joint_name:angle command\n...
[ { "param": "self", "type": null }, { "param": "positions", "type": null }, { "param": "timeout", "type": null }, { "param": "threshold", "type": null }, { "param": "test", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "positions", "type": null, "docstring": null, "docstring_token...
78454e14cc85a0930a2799bddf948b48567d229a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/gripper.py
[ "Apache-2.0" ]
Python
reboot
<not_specific>
def reboot(self): """ Power cycle the gripper, removing calibration information. Basic call to the gripper reboot command. Waits for gripper to return ready state but does not clear errors that could occur during boot. @rtype: bool @return: True if successfully Rebooted...
Power cycle the gripper, removing calibration information. Basic call to the gripper reboot command. Waits for gripper to return ready state but does not clear errors that could occur during boot. @rtype: bool @return: True if successfully Rebooted, False otherwise
Power cycle the gripper, removing calibration information. Basic call to the gripper reboot command. Waits for gripper to return ready state but does not clear errors that could occur during boot.
[ "Power", "cycle", "the", "gripper", "removing", "calibration", "information", ".", "Basic", "call", "to", "the", "gripper", "reboot", "command", ".", "Waits", "for", "gripper", "to", "return", "ready", "state", "but", "does", "not", "clear", "errors", "that", ...
def reboot(self): return self.gripper_io.set_signal_value("reboot", True)
[ "def", "reboot", "(", "self", ")", ":", "return", "self", ".", "gripper_io", ".", "set_signal_value", "(", "\"reboot\"", ",", "True", ")" ]
Power cycle the gripper, removing calibration information.
[ "Power", "cycle", "the", "gripper", "removing", "calibration", "information", "." ]
[ "\"\"\"\n Power cycle the gripper, removing calibration information.\n\n Basic call to the gripper reboot command. Waits for gripper to return\n ready state but does not clear errors that could occur during boot.\n\n @rtype: bool\n @return: True if successfully Rebooted, False oth...
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "True if successfully Rebooted, False otherwise", "docstring_tokens": [ "True", "if", "successfully", "Rebooted", "False", "otherwise" ], "type": "bool" } ], "raises": [], "params": [ { "ident...
78454e14cc85a0930a2799bddf948b48567d229a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/gripper.py
[ "Apache-2.0" ]
Python
stop
<not_specific>
def stop(self): """ Set the gripper to stop executing command at the current position, apply holding force. @rtype: bool @return: True if successfully Stopped, False otherwise """ return self.gripper_io.set_signal_value("go", False)
Set the gripper to stop executing command at the current position, apply holding force. @rtype: bool @return: True if successfully Stopped, False otherwise
Set the gripper to stop executing command at the current position, apply holding force.
[ "Set", "the", "gripper", "to", "stop", "executing", "command", "at", "the", "current", "position", "apply", "holding", "force", "." ]
def stop(self): return self.gripper_io.set_signal_value("go", False)
[ "def", "stop", "(", "self", ")", ":", "return", "self", ".", "gripper_io", ".", "set_signal_value", "(", "\"go\"", ",", "False", ")" ]
Set the gripper to stop executing command at the current position, apply holding force.
[ "Set", "the", "gripper", "to", "stop", "executing", "command", "at", "the", "current", "position", "apply", "holding", "force", "." ]
[ "\"\"\"\n Set the gripper to stop executing command at the current\n position, apply holding force.\n\n @rtype: bool\n @return: True if successfully Stopped, False otherwise\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "True if successfully Stopped, False otherwise", "docstring_tokens": [ "True", "if", "successfully", "Stopped", "False", "otherwise" ], "type": "bool" } ], "raises": [], "params": [ { "identif...
78454e14cc85a0930a2799bddf948b48567d229a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/gripper.py
[ "Apache-2.0" ]
Python
start
<not_specific>
def start(self): """ Set the gripper to start executing command at the current position, apply holding force. @rtype: bool @return: True if successfully Started, False otherwise """ return self.gripper_io.set_signal_value("go", True)
Set the gripper to start executing command at the current position, apply holding force. @rtype: bool @return: True if successfully Started, False otherwise
Set the gripper to start executing command at the current position, apply holding force.
[ "Set", "the", "gripper", "to", "start", "executing", "command", "at", "the", "current", "position", "apply", "holding", "force", "." ]
def start(self): return self.gripper_io.set_signal_value("go", True)
[ "def", "start", "(", "self", ")", ":", "return", "self", ".", "gripper_io", ".", "set_signal_value", "(", "\"go\"", ",", "True", ")" ]
Set the gripper to start executing command at the current position, apply holding force.
[ "Set", "the", "gripper", "to", "start", "executing", "command", "at", "the", "current", "position", "apply", "holding", "force", "." ]
[ "\"\"\"\n Set the gripper to start executing command at the current\n position, apply holding force.\n\n @rtype: bool\n @return: True if successfully Started, False otherwise\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "True if successfully Started, False otherwise", "docstring_tokens": [ "True", "if", "successfully", "Started", "False", "otherwise" ], "type": "bool" } ], "raises": [], "params": [ { "identif...
78454e14cc85a0930a2799bddf948b48567d229a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/gripper.py
[ "Apache-2.0" ]
Python
open
<not_specific>
def open(self, position=MAX_POSITION): """ Set the gripper position to open by providing opening position. @type: float @param: the postion of gripper in meters @rtype: bool @return: True if successfully set Position, False otherwise """ return self.gripp...
Set the gripper position to open by providing opening position. @type: float @param: the postion of gripper in meters @rtype: bool @return: True if successfully set Position, False otherwise
Set the gripper position to open by providing opening position. @type: float @param: the postion of gripper in meters @rtype: bool @return: True if successfully set Position, False otherwise
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def open(self, position=MAX_POSITION): return self.gripper_io.set_signal_value("position_m", position)
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Set the gripper position to open by providing opening position.
[ "Set", "the", "gripper", "position", "to", "open", "by", "providing", "opening", "position", "." ]
[ "\"\"\"\n Set the gripper position to open by providing opening position.\n @type: float\n @param: the postion of gripper in meters\n\n @rtype: bool\n @return: True if successfully set Position, False otherwise\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "position", "type": null, "docstring": null, "docstring_tokens...
78454e14cc85a0930a2799bddf948b48567d229a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/gripper.py
[ "Apache-2.0" ]
Python
close
<not_specific>
def close(self, position=MIN_POSITION): """ Set the gripper position to close by providing closing position. @type: float @param: the postion of gripper in meters @rtype: bool @return: True if successfully set Position, False otherwise """ return self.gri...
Set the gripper position to close by providing closing position. @type: float @param: the postion of gripper in meters @rtype: bool @return: True if successfully set Position, False otherwise
Set the gripper position to close by providing closing position. @type: float @param: the postion of gripper in meters @rtype: bool @return: True if successfully set Position, False otherwise
[ "Set", "the", "gripper", "position", "to", "close", "by", "providing", "closing", "position", ".", "@type", ":", "float", "@param", ":", "the", "postion", "of", "gripper", "in", "meters", "@rtype", ":", "bool", "@return", ":", "True", "if", "successfully", ...
def close(self, position=MIN_POSITION): return self.gripper_io.set_signal_value("position_m", position)
[ "def", "close", "(", "self", ",", "position", "=", "MIN_POSITION", ")", ":", "return", "self", ".", "gripper_io", ".", "set_signal_value", "(", "\"position_m\"", ",", "position", ")" ]
Set the gripper position to close by providing closing position.
[ "Set", "the", "gripper", "position", "to", "close", "by", "providing", "closing", "position", "." ]
[ "\"\"\"\n Set the gripper position to close by providing closing position.\n @type: float\n @param: the postion of gripper in meters\n\n @rtype: bool\n @return: True if successfully set Position, False otherwise\n \"\"\"" ]
[ { "param": "self", "type": null }, { "param": "position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "position", "type": null, "docstring": null, "docstring_tokens...
78454e14cc85a0930a2799bddf948b48567d229a
CNCR-NTU/Sawyer-AR10hand-WeissTactile
intera_interface/src/intera_interface/gripper.py
[ "Apache-2.0" ]
Python
calibrate
<not_specific>
def calibrate(self): """ Calibrate the gripper in order to set maximum and minimum travel distance. @rtype: bool @return: True if successfully calibrating, False otherwise """ return self.gripper_io.set_signal_value("calibrate", True)
Calibrate the gripper in order to set maximum and minimum travel distance. @rtype: bool @return: True if successfully calibrating, False otherwise
Calibrate the gripper in order to set maximum and minimum travel distance.
[ "Calibrate", "the", "gripper", "in", "order", "to", "set", "maximum", "and", "minimum", "travel", "distance", "." ]
def calibrate(self): return self.gripper_io.set_signal_value("calibrate", True)
[ "def", "calibrate", "(", "self", ")", ":", "return", "self", ".", "gripper_io", ".", "set_signal_value", "(", "\"calibrate\"", ",", "True", ")" ]
Calibrate the gripper in order to set maximum and minimum travel distance.
[ "Calibrate", "the", "gripper", "in", "order", "to", "set", "maximum", "and", "minimum", "travel", "distance", "." ]
[ "\"\"\"\n Calibrate the gripper in order to set maximum and\n minimum travel distance.\n\n @rtype: bool\n @return: True if successfully calibrating, False otherwise\n \"\"\"" ]
[ { "param": "self", "type": null } ]
{ "returns": [ { "docstring": "True if successfully calibrating, False otherwise", "docstring_tokens": [ "True", "if", "successfully", "calibrating", "False", "otherwise" ], "type": "bool" } ], "raises": [], "params": [ { ...
a4c932907311cd366fd079226d4547757cf8bd1b
ArcetriAdaptiveOptics/arte
test/utils/tabular_report_test.py
[ "MIT" ]
Python
testDocstring
null
def testDocstring(self): ''' doctest's automated tests only check one line at a time, while we want the entire output, so we make our own ''' # Run the example docstring = doctest.script_from_examples(TabularReport.__doc__ ) with capture_output() as (out, err): ...
doctest's automated tests only check one line at a time, while we want the entire output, so we make our own
doctest's automated tests only check one line at a time, while we want the entire output, so we make our own
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def testDocstring(self): docstring = doctest.script_from_examples(TabularReport.__doc__ ) with capture_output() as (out, err): exec(docstring) out = ['# '+x for x in out.getvalue().splitlines()] ref = docstring.splitlines()[-len(out):] assert( strip_all(out) == strip...
[ "def", "testDocstring", "(", "self", ")", ":", "docstring", "=", "doctest", ".", "script_from_examples", "(", "TabularReport", ".", "__doc__", ")", "with", "capture_output", "(", ")", "as", "(", "out", ",", "err", ")", ":", "exec", "(", "docstring", ")", ...
doctest's automated tests only check one line at a time, while we want the entire output, so we make our own
[ "doctest", "'", "s", "automated", "tests", "only", "check", "one", "line", "at", "a", "time", "while", "we", "want", "the", "entire", "output", "so", "we", "make", "our", "own" ]
[ "'''\n doctest's automated tests only check one line at a time,\n while we want the entire output, so we make our own\n '''", "# Run the example", "# Add '#' like doctest.script_from_examples() does.", "# The reference lines are the last x lines of the docstring" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
a4cbd14a47884ddc036cdec229bdbc37ab5540a7
ArcetriAdaptiveOptics/arte
arte/utils/iterators.py
[ "MIT" ]
Python
flatten
null
def flatten(x): ''' Generator that flatten arbitrarily nested lists. This generator will flatten a list that may contain other lists (nested arbitrarily) and simple items into a flat list. >>> flat = flatten([[1,[2,3]],4,[5,6]]) >>> list(flat) [1, 2, 3, 4, 5, 6] ''' for item in...
Generator that flatten arbitrarily nested lists. This generator will flatten a list that may contain other lists (nested arbitrarily) and simple items into a flat list. >>> flat = flatten([[1,[2,3]],4,[5,6]]) >>> list(flat) [1, 2, 3, 4, 5, 6]
Generator that flatten arbitrarily nested lists. This generator will flatten a list that may contain other lists (nested arbitrarily) and simple items into a flat list.
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def flatten(x): for item in x: try: yield from flatten(item) except TypeError: yield item
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Generator that flatten arbitrarily nested lists.
[ "Generator", "that", "flatten", "arbitrarily", "nested", "lists", "." ]
[ "'''\n Generator that flatten arbitrarily nested lists.\n\n This generator will flatten a list that may contain\n other lists (nested arbitrarily) and simple items\n into a flat list.\n\n >>> flat = flatten([[1,[2,3]],4,[5,6]])\n >>> list(flat)\n [1, 2, 3, 4, 5, 6]\n '''" ]
[ { "param": "x", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "x", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
3c3312eb6c1eb450816938133e92c15efd57206a
ArcetriAdaptiveOptics/arte
test/utils/circular_buffer_test.py
[ "MIT" ]
Python
task
null
def task(arr): ''' A task that polls on a trigger for max 5 seconds, and when triggered, modifies the input array. ''' timeout = 5 now = time.time() while True: if arr.counter() == 3: break ...
A task that polls on a trigger for max 5 seconds, and when triggered, modifies the input array.
A task that polls on a trigger for max 5 seconds, and when triggered, modifies the input array.
[ "A", "task", "that", "polls", "on", "a", "trigger", "for", "max", "5", "seconds", "and", "when", "triggered", "modifies", "the", "input", "array", "." ]
def task(arr): timeout = 5 now = time.time() while True: if arr.counter() == 3: break time.sleep(0.01) if time.time() - now >= timeout: raise TimeoutError arr.store(np.ones(2,))
[ "def", "task", "(", "arr", ")", ":", "timeout", "=", "5", "now", "=", "time", ".", "time", "(", ")", "while", "True", ":", "if", "arr", ".", "counter", "(", ")", "==", "3", ":", "break", "time", ".", "sleep", "(", "0.01", ")", "if", "time", "...
A task that polls on a trigger for max 5 seconds, and when triggered, modifies the input array.
[ "A", "task", "that", "polls", "on", "a", "trigger", "for", "max", "5", "seconds", "and", "when", "triggered", "modifies", "the", "input", "array", "." ]
[ "'''\n A task that polls on a trigger for max 5 seconds,\n and when triggered, modifies the input array.\n '''" ]
[ { "param": "arr", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "arr", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
1b9322c377072ca8d869b1731e55f6f98da48faf
ArcetriAdaptiveOptics/arte
arte/utils/quadratic_sum.py
[ "MIT" ]
Python
quadraticSum
<not_specific>
def quadraticSum(arrayOfErrorsWithSign): ''' quadraticSum(arrayOfErrorsWithSign) Sum in quadrature of errors, considering sign 5 = quadraticSum([3, 4]) 8 = quadraticSum(10, -6]) ''' total = 0. for err in arrayOfErrorsWithSign: if err < 0: total -= err ** 2 else:...
quadraticSum(arrayOfErrorsWithSign) Sum in quadrature of errors, considering sign 5 = quadraticSum([3, 4]) 8 = quadraticSum(10, -6])
quadraticSum(arrayOfErrorsWithSign) Sum in quadrature of errors, considering sign
[ "quadraticSum", "(", "arrayOfErrorsWithSign", ")", "Sum", "in", "quadrature", "of", "errors", "considering", "sign" ]
def quadraticSum(arrayOfErrorsWithSign): total = 0. for err in arrayOfErrorsWithSign: if err < 0: total -= err ** 2 else: total += err ** 2 return np.sqrt(total)
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quadraticSum(arrayOfErrorsWithSign) Sum in quadrature of errors, considering sign
[ "quadraticSum", "(", "arrayOfErrorsWithSign", ")", "Sum", "in", "quadrature", "of", "errors", "considering", "sign" ]
[ "''' quadraticSum(arrayOfErrorsWithSign)\n Sum in quadrature of errors, considering sign\n\n 5 = quadraticSum([3, 4])\n 8 = quadraticSum(10, -6])\n\n '''" ]
[ { "param": "arrayOfErrorsWithSign", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "arrayOfErrorsWithSign", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
136f9ac4ea003d0c16293268aa6237ef61ecc8a4
ArcetriAdaptiveOptics/arte
arte/time_series/multi_time_series.py
[ "MIT" ]
Python
add_series
null
def add_series(self, series): ''' Adds a new series to this MultiTimeSeries instance Parameters ---------- series: :class:`~arte.time_series.time_series.TimeSeries` or :class:`~arte.time_series.time_series.TimeSeriesWithInterpolation` instance the series to be...
Adds a new series to this MultiTimeSeries instance Parameters ---------- series: :class:`~arte.time_series.time_series.TimeSeries` or :class:`~arte.time_series.time_series.TimeSeriesWithInterpolation` instance the series to be added
Adds a new series to this MultiTimeSeries instance Parameters
[ "Adds", "a", "new", "series", "to", "this", "MultiTimeSeries", "instance", "Parameters" ]
def add_series(self, series): self._series.append(series)
[ "def", "add_series", "(", "self", ",", "series", ")", ":", "self", ".", "_series", ".", "append", "(", "series", ")" ]
Adds a new series to this MultiTimeSeries instance Parameters
[ "Adds", "a", "new", "series", "to", "this", "MultiTimeSeries", "instance", "Parameters" ]
[ "'''\n Adds a new series to this MultiTimeSeries instance\n \n Parameters\n ----------\n series: :class:`~arte.time_series.time_series.TimeSeries` or :class:`~arte.time_series.time_series.TimeSeriesWithInterpolation` instance\n the series to be added \n '''...
[ { "param": "self", "type": null }, { "param": "series", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "series", "type": null, "docstring": null, "docstring_tokens":...
136f9ac4ea003d0c16293268aa6237ef61ecc8a4
ArcetriAdaptiveOptics/arte
arte/time_series/multi_time_series.py
[ "MIT" ]
Python
is_homogeneous
<not_specific>
def is_homogeneous(self, *args, **kwargs): '''Returns True if all selected series have the same :py:attr:`~arte.time_series.time_series.TimeSeries.delta_time` ''' dt = [x.value for x in self.delta_times(*args, **kwargs)] return len(set(dt)) == 1
Returns True if all selected series have the same :py:attr:`~arte.time_series.time_series.TimeSeries.delta_time`
Returns True if all selected series have the same
[ "Returns", "True", "if", "all", "selected", "series", "have", "the", "same" ]
def is_homogeneous(self, *args, **kwargs): dt = [x.value for x in self.delta_times(*args, **kwargs)] return len(set(dt)) == 1
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Returns True if all selected series have the same
[ "Returns", "True", "if", "all", "selected", "series", "have", "the", "same" ]
[ "'''Returns True if all selected series have the same\n :py:attr:`~arte.time_series.time_series.TimeSeries.delta_time`\n '''" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [ { "identifier": "py", "docstring": null, "...
136f9ac4ea003d0c16293268aa6237ef61ecc8a4
ArcetriAdaptiveOptics/arte
arte/time_series/multi_time_series.py
[ "MIT" ]
Python
delta_times
<not_specific>
def delta_times(self, *args, **kwargs): '''Returns a vector of delta times''' # Known astropy bug (numpy < 1.17): units are lost when using hstack # We remove them before stacking, and add them later dt = np.hstack( \ [np.repeat(x.delta_time.to('s').value, x.ensemble_size...
Returns a vector of delta times
Returns a vector of delta times
[ "Returns", "a", "vector", "of", "delta", "times" ]
def delta_times(self, *args, **kwargs): dt = np.hstack( \ [np.repeat(x.delta_time.to('s').value, x.ensemble_size()) for x in self._series]) dt = dt * u.s index = self.get_index_of(*args, **kwargs) if index is not None and len(index)>0: dt = dt[ind...
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Returns a vector of delta times
[ "Returns", "a", "vector", "of", "delta", "times" ]
[ "'''Returns a vector of delta times'''", "# Known astropy bug (numpy < 1.17): units are lost when using hstack ", "# We remove them before stacking, and add them later" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
136f9ac4ea003d0c16293268aa6237ef61ecc8a4
ArcetriAdaptiveOptics/arte
arte/time_series/multi_time_series.py
[ "MIT" ]
Python
ensemble_average
<not_specific>
def ensemble_average(self, times=None, *args, **kwargs): ''' Average across series at each sampling time ''' if self.is_homogeneous(*args, **kwargs): self._impersonateDeltaTime(*args, **kwargs) return super().ensemble_average(times, *args, **kwargs) else: rai...
Average across series at each sampling time
Average across series at each sampling time
[ "Average", "across", "series", "at", "each", "sampling", "time" ]
def ensemble_average(self, times=None, *args, **kwargs): if self.is_homogeneous(*args, **kwargs): self._impersonateDeltaTime(*args, **kwargs) return super().ensemble_average(times, *args, **kwargs) else: raise Exception('Data series cannot be combined')
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Average across series at each sampling time
[ "Average", "across", "series", "at", "each", "sampling", "time" ]
[ "''' Average across series at each sampling time '''" ]
[ { "param": "self", "type": null }, { "param": "times", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "times", "type": null, "docstring": null, "docstring_tokens": ...
136f9ac4ea003d0c16293268aa6237ef61ecc8a4
ArcetriAdaptiveOptics/arte
arte/time_series/multi_time_series.py
[ "MIT" ]
Python
ensemble_std
<not_specific>
def ensemble_std(self, times=None, *args, **kwargs): ''' Standard deviation across series at each sampling time ''' if self.is_homogeneous(*args, **kwargs): self._impersonateDeltaTime(*args, **kwargs) return super().ensemble_std(times, *args, **kwargs) else: ...
Standard deviation across series at each sampling time
Standard deviation across series at each sampling time
[ "Standard", "deviation", "across", "series", "at", "each", "sampling", "time" ]
def ensemble_std(self, times=None, *args, **kwargs): if self.is_homogeneous(*args, **kwargs): self._impersonateDeltaTime(*args, **kwargs) return super().ensemble_std(times, *args, **kwargs) else: raise Exception('Data series cannot be combined')
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Standard deviation across series at each sampling time
[ "Standard", "deviation", "across", "series", "at", "each", "sampling", "time" ]
[ "''' Standard deviation across series at each sampling time '''" ]
[ { "param": "self", "type": null }, { "param": "times", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "times", "type": null, "docstring": null, "docstring_tokens": ...
136f9ac4ea003d0c16293268aa6237ef61ecc8a4
ArcetriAdaptiveOptics/arte
arte/time_series/multi_time_series.py
[ "MIT" ]
Python
ensemble_median
<not_specific>
def ensemble_median(self, times=None, *args, **kwargs): ''' Standard deviation across series at each sampling time ''' if self.is_homogeneous(*args, **kwargs): self._impersonateDeltaTime(*args, **kwargs) return super().ensemble_median(times, *args, **kwargs) else: ...
Standard deviation across series at each sampling time
Standard deviation across series at each sampling time
[ "Standard", "deviation", "across", "series", "at", "each", "sampling", "time" ]
def ensemble_median(self, times=None, *args, **kwargs): if self.is_homogeneous(*args, **kwargs): self._impersonateDeltaTime(*args, **kwargs) return super().ensemble_median(times, *args, **kwargs) else: raise Exception('Data series cannot be combined')
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Standard deviation across series at each sampling time
[ "Standard", "deviation", "across", "series", "at", "each", "sampling", "time" ]
[ "''' Standard deviation across series at each sampling time '''" ]
[ { "param": "self", "type": null }, { "param": "times", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "times", "type": null, "docstring": null, "docstring_tokens": ...
9e17f2c29f8301325787a297a3f3e525f6ec93c3
ArcetriAdaptiveOptics/arte
arte/utils/tabular_report.py
[ "MIT" ]
Python
report
<not_specific>
def report(self): ''' Increment the iteration counter and if, conditions match, print a header and/or a line of values. ''' self.counter += 1 if self.counter % self.decimation != 0: return if self.hdr_counter % self.hdr_decimation == 0: se...
Increment the iteration counter and if, conditions match, print a header and/or a line of values.
Increment the iteration counter and if, conditions match, print a header and/or a line of values.
[ "Increment", "the", "iteration", "counter", "and", "if", "conditions", "match", "print", "a", "header", "and", "/", "or", "a", "line", "of", "values", "." ]
def report(self): self.counter += 1 if self.counter % self.decimation != 0: return if self.hdr_counter % self.hdr_decimation == 0: self.print_header() self.hdr_counter += 1 self.print_line()
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Increment the iteration counter and if, conditions match, print a header and/or a line of values.
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[ "'''\n Increment the iteration counter and if, conditions match,\n print a header and/or a line of values.\n '''" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
9e17f2c29f8301325787a297a3f3e525f6ec93c3
ArcetriAdaptiveOptics/arte
arte/utils/tabular_report.py
[ "MIT" ]
Python
print_header
null
def print_header(self): '''Unconditionally print a line with the header.''' cols = self.values.keys() if self.add_iter: cols = ['iteration'] + list(cols) fmt = '%%-%ds ' % self.column_width hdr = ''.join([fmt % col for col in cols]) print() print(hd...
Unconditionally print a line with the header.
Unconditionally print a line with the header.
[ "Unconditionally", "print", "a", "line", "with", "the", "header", "." ]
def print_header(self): cols = self.values.keys() if self.add_iter: cols = ['iteration'] + list(cols) fmt = '%%-%ds ' % self.column_width hdr = ''.join([fmt % col for col in cols]) print() print(hdr) print('-' * len(hdr))
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Unconditionally print a line with the header.
[ "Unconditionally", "print", "a", "line", "with", "the", "header", "." ]
[ "'''Unconditionally print a line with the header.'''" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
9e17f2c29f8301325787a297a3f3e525f6ec93c3
ArcetriAdaptiveOptics/arte
arte/utils/tabular_report.py
[ "MIT" ]
Python
print_line
null
def print_line(self): '''Unconditionally print a line with all the current values''' cols = self.values.keys() formatted_values = [self.fmt[col](self.values[col]) for col in cols] if self.add_iter: formatted_values = [str(self.counter)] + formatted_values fmt = '%%...
Unconditionally print a line with all the current values
Unconditionally print a line with all the current values
[ "Unconditionally", "print", "a", "line", "with", "all", "the", "current", "values" ]
def print_line(self): cols = self.values.keys() formatted_values = [self.fmt[col](self.values[col]) for col in cols] if self.add_iter: formatted_values = [str(self.counter)] + formatted_values fmt = '%%-%ds ' % self.column_width line = ''.join([fmt % value for value i...
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Unconditionally print a line with all the current values
[ "Unconditionally", "print", "a", "line", "with", "all", "the", "current", "values" ]
[ "'''Unconditionally print a line with all the current values'''" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
0d8958b9229822a8178d208d35f792c292f79b4e
ArcetriAdaptiveOptics/arte
arte/utils/circular_buffer.py
[ "MIT" ]
Python
store
null
def store(self, data, position=None): ''' Store a record in the circular buffer. By default, the record is stored following an internal counter, which is then incremented. ''' if position is None: position = self._position[0] self._buf[position,:] = ...
Store a record in the circular buffer. By default, the record is stored following an internal counter, which is then incremented.
Store a record in the circular buffer. By default, the record is stored following an internal counter, which is then incremented.
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def store(self, data, position=None): if position is None: position = self._position[0] self._buf[position,:] = data self._counter[0] = self._counter[0] + 1 self._position[0] = self._counter[0] % self._len
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Store a record in the circular buffer.
[ "Store", "a", "record", "in", "the", "circular", "buffer", "." ]
[ "'''\n Store a record in the circular buffer.\n\n By default, the record is stored following an internal counter,\n which is then incremented.\n '''" ]
[ { "param": "self", "type": null }, { "param": "data", "type": null }, { "param": "position", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "data", "type": null, "docstring": null, "docstring_tokens": [...
9a1dc8b097eff9b240b2162004a1a5b75bbd18ea
ArcetriAdaptiveOptics/arte
arte/utils/compareIDL.py
[ "MIT" ]
Python
compareIDL
<not_specific>
def compareIDL(idlscript, pyscript, vars_to_compare, precision=1e-5, verbose=0, tmpfile=None): ''' Compare IDL and Python routines results, to aid in porting. This function will run an IDL batch script (containing statements that will be executed as if they were typed on the IDL command ...
Compare IDL and Python routines results, to aid in porting. This function will run an IDL batch script (containing statements that will be executed as if they were typed on the IDL command prompt) and a Python script. After both scripts have been run, the variables listed in vars_to_compare are ex...
Compare IDL and Python routines results, to aid in porting. This function will run an IDL batch script (containing statements that will be executed as if they were typed on the IDL command prompt) and a Python script. After both scripts have been run, the variables listed in vars_to_compare are extracted from both sess...
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def compareIDL(idlscript, pyscript, vars_to_compare, precision=1e-5, verbose=0, tmpfile=None): if tmpfile is None: tmpfile = os.path.join(tempfile.gettempdir(), 'idl_compare.sav') savecmd = ','.join(['\nSAVE', *vars_to_compare, 'FILENAME="%s"\...
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Compare IDL and Python routines results, to aid in porting.
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[ "'''\n Compare IDL and Python routines results, to aid in porting.\n\n This function will run an IDL batch script (containing statements\n that will be executed as if they were typed on the IDL command prompt)\n and a Python script. After both scripts have been run, the variables\n listed in vars_to_...
[ { "param": "idlscript", "type": null }, { "param": "pyscript", "type": null }, { "param": "vars_to_compare", "type": null }, { "param": "precision", "type": null }, { "param": "verbose", "type": null }, { "param": "tmpfile", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "idlscript", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "pyscript", "type": null, "docstring": null, "docstring_t...
6126ec8df66bbae0b55f22f87d224f08b44208a4
ArcetriAdaptiveOptics/arte
arte/photometry/eso_sky_calc.py
[ "MIT" ]
Python
lam
<not_specific>
def lam(self): ''' Wavelength array in astropy units of nm ''' return self._res['lam'] * u.nm
Wavelength array in astropy units of nm
Wavelength array in astropy units of nm
[ "Wavelength", "array", "in", "astropy", "units", "of", "nm" ]
def lam(self): return self._res['lam'] * u.nm
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Wavelength array in astropy units of nm
[ "Wavelength", "array", "in", "astropy", "units", "of", "nm" ]
[ "'''\n Wavelength array in astropy units of nm\n '''" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
c013eeadcf96245479512775019615540190efc8
ArcetriAdaptiveOptics/arte
arte/time_series/time_series.py
[ "MIT" ]
Python
_apply
<not_specific>
def _apply(self, func, times=None, *args, **kwargs): '''Extract data and apply the passed function''' data = self.get_data(*args, **kwargs) if times is None: result = func(data) else: idxs = np.array(np.arange(times[0], times[1]) / self.__delta_time, ...
Extract data and apply the passed function
Extract data and apply the passed function
[ "Extract", "data", "and", "apply", "the", "passed", "function" ]
def _apply(self, func, times=None, *args, **kwargs): data = self.get_data(*args, **kwargs) if times is None: result = func(data) else: idxs = np.array(np.arange(times[0], times[1]) / self.__delta_time, dtype='int32') result = func(d...
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Extract data and apply the passed function
[ "Extract", "data", "and", "apply", "the", "passed", "function" ]
[ "'''Extract data and apply the passed function'''" ]
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{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "func", "type": null, "docstring": null, "docstring_tokens": [...
c013eeadcf96245479512775019615540190efc8
ArcetriAdaptiveOptics/arte
arte/time_series/time_series.py
[ "MIT" ]
Python
plot_spectra
<not_specific>
def plot_spectra(self, from_freq=None, to_freq=None, segment_factor=None, overplot=False, label=None, *args, **kwargs): '''Plot the PSD across specified series''' power = self.power(from_freq, to_freq, ...
Plot the PSD across specified series
Plot the PSD across specified series
[ "Plot", "the", "PSD", "across", "specified", "series" ]
def plot_spectra(self, from_freq=None, to_freq=None, segment_factor=None, overplot=False, label=None, *args, **kwargs): power = self.power(from_freq, to_freq, segment_factor, ...
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Plot the PSD across specified series
[ "Plot", "the", "PSD", "across", "specified", "series" ]
[ "'''Plot the PSD across specified series'''" ]
[ { "param": "self", "type": null }, { "param": "from_freq", "type": null }, { "param": "to_freq", "type": null }, { "param": "segment_factor", "type": null }, { "param": "overplot", "type": null }, { "param": "label", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "from_freq", "type": null, "docstring": null, "docstring_token...
c013eeadcf96245479512775019615540190efc8
ArcetriAdaptiveOptics/arte
arte/time_series/time_series.py
[ "MIT" ]
Python
plot_cumulative_spectra
<not_specific>
def plot_cumulative_spectra(self, from_freq=None, to_freq=None, segment_factor=None, overplot=False, *args, **kwargs): '''Plot the cumulative PSD across specified series''' power = self.power(from_freq, to_freq, s...
Plot the cumulative PSD across specified series
Plot the cumulative PSD across specified series
[ "Plot", "the", "cumulative", "PSD", "across", "specified", "series" ]
def plot_cumulative_spectra(self, from_freq=None, to_freq=None, segment_factor=None, overplot=False, *args, **kwargs): power = self.power(from_freq, to_freq, segment_factor, *args, **kwargs) ...
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Plot the cumulative PSD across specified series
[ "Plot", "the", "cumulative", "PSD", "across", "specified", "series" ]
[ "'''Plot the cumulative PSD across specified series'''" ]
[ { "param": "self", "type": null }, { "param": "from_freq", "type": null }, { "param": "to_freq", "type": null }, { "param": "segment_factor", "type": null }, { "param": "overplot", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "from_freq", "type": null, "docstring": null, "docstring_token...
c013eeadcf96245479512775019615540190efc8
ArcetriAdaptiveOptics/arte
arte/time_series/time_series.py
[ "MIT" ]
Python
interpolate_missing_data
<not_specific>
def interpolate_missing_data(self, data): ''' Interpolate missing data. Parameters ---------- data: ndarray the original data Returns ------- ndarray the interpolated array Raises ------ ValueError ...
Interpolate missing data. Parameters ---------- data: ndarray the original data Returns ------- ndarray the interpolated array Raises ------ ValueError if the frame counter first dimension does not ha...
Interpolate missing data. Parameters ndarray the original data Returns ndarray the interpolated array Raises ValueError if the frame counter first dimension does not have the same length as the data first dimension.
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def interpolate_missing_data(self, data): counter = self.get_original_counter() if isinstance(counter, NotAvailable): return NotAvailable() if data.shape[0] != counter.shape[0]: raise ValueError('Shape mismatch between frame counter and data:' ...
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Interpolate missing data.
[ "Interpolate", "missing", "data", "." ]
[ "'''\n Interpolate missing data.\n\n Parameters\n ----------\n data: ndarray\n the original data\n\n Returns\n -------\n ndarray\n the interpolated array\n\n Raises\n ------\n ValueError\n if the frame counter fir...
[ { "param": "self", "type": null }, { "param": "data", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "data", "type": null, "docstring": null, "docstring_tokens": [...
31f4de776a33bad63cd59a635d0b983170e982b4
ArcetriAdaptiveOptics/arte
arte/atmo/von_karman_psd.py
[ "MIT" ]
Python
spatial_psd
<not_specific>
def spatial_psd(self, freqs): ''' Spatial Power Spectral Density of Von Karman turbulence Parameters ---------- freqs: :class:`~numpy:numpy.ndarray` Spatial frequencies vector[m^-1]. Returns ------- psd: :class:`~numpy:numpy.ndarray` ...
Spatial Power Spectral Density of Von Karman turbulence Parameters ---------- freqs: :class:`~numpy:numpy.ndarray` Spatial frequencies vector[m^-1]. Returns ------- psd: :class:`~numpy:numpy.ndarray` power spectral density computed at th...
Spatial Power Spectral Density of Von Karman turbulence Parameters Returns :class:`~numpy:numpy.ndarray` power spectral density computed at the specified frequencies
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def spatial_psd(self, freqs): self._computeVonKarmanPsd(freqs) return self._psd
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Spatial Power Spectral Density of Von Karman turbulence Parameters
[ "Spatial", "Power", "Spectral", "Density", "of", "Von", "Karman", "turbulence", "Parameters" ]
[ "'''\n Spatial Power Spectral Density of Von Karman turbulence\n\n Parameters\n ----------\n freqs: :class:`~numpy:numpy.ndarray`\n Spatial frequencies vector[m^-1].\n\n Returns\n -------\n psd: :class:`~numpy:numpy.ndarray`\n power spectral den...
[ { "param": "self", "type": null }, { "param": "freqs", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "freqs", "type": null, "docstring": null, "docstring_tokens": ...
0bf300bd7a2a73b4e8790f58766473ae74211404
ArcetriAdaptiveOptics/arte
arte/photometry/mag_estimator.py
[ "MIT" ]
Python
flux_zero
<not_specific>
def flux_zero(self): '''Zero point in photons/sec''' wl, ergs = self._bands[self._bandname] photons = self._ergs_to_photons(ergs, wl) return (photons * self._telescope.area() * self._bandwidth).to(u.ph / u.s)
Zero point in photons/sec
Zero point in photons/sec
[ "Zero", "point", "in", "photons", "/", "sec" ]
def flux_zero(self): wl, ergs = self._bands[self._bandname] photons = self._ergs_to_photons(ergs, wl) return (photons * self._telescope.area() * self._bandwidth).to(u.ph / u.s)
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Zero point in photons/sec
[ "Zero", "point", "in", "photons", "/", "sec" ]
[ "'''Zero point in photons/sec'''" ]
[ { "param": "self", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "self", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
0bf300bd7a2a73b4e8790f58766473ae74211404
ArcetriAdaptiveOptics/arte
arte/photometry/mag_estimator.py
[ "MIT" ]
Python
photons_per_subap_per_frame
<not_specific>
def photons_per_subap_per_frame(self): '''Photons/subap/frame detected by sensor''' gain = self._detector_gain nsubaps = self._detector_nsubaps adu_e_ratio = self._detector_adu_e_ratio qe = self._detector_qe return self._total_adus * adu_e_ratio / gain / nsubaps / qe
Photons/subap/frame detected by sensor
Photons/subap/frame detected by sensor
[ "Photons", "/", "subap", "/", "frame", "detected", "by", "sensor" ]
def photons_per_subap_per_frame(self): gain = self._detector_gain nsubaps = self._detector_nsubaps adu_e_ratio = self._detector_adu_e_ratio qe = self._detector_qe return self._total_adus * adu_e_ratio / gain / nsubaps / qe
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Photons/subap/frame detected by sensor
[ "Photons", "/", "subap", "/", "frame", "detected", "by", "sensor" ]
[ "'''Photons/subap/frame detected by sensor'''" ]
[ { "param": "self", "type": null } ]
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