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RudolfCardinal/pythonlib
cardinal_pythonlib/platformfunc.py
validate_pair
def validate_pair(ob: Any) -> bool: """ Does the object have length 2? """ try: if len(ob) != 2: log.warning("Unexpected result: {!r}", ob) raise ValueError() except ValueError: return False return True
python
def validate_pair(ob: Any) -> bool: """ Does the object have length 2? """ try: if len(ob) != 2: log.warning("Unexpected result: {!r}", ob) raise ValueError() except ValueError: return False return True
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Does the object have length 2?
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/platformfunc.py#L174-L184
train
53,300
RudolfCardinal/pythonlib
cardinal_pythonlib/email/mailboxpurge.py
clean_message
def clean_message(message: Message, topmost: bool = False) -> Message: """ Clean a message of all its binary parts. This guts all binary attachments, and returns the message itself for convenience. """ if message.is_multipart(): # Don't recurse in already-deleted attachments if message.get_content_type() != 'message/external-body': parts = message.get_payload() parts[:] = map(clean_message, parts) elif message_is_binary(message): # Don't gut if this is the topmost message if not topmost: message = gut_message(message) return message
python
def clean_message(message: Message, topmost: bool = False) -> Message: """ Clean a message of all its binary parts. This guts all binary attachments, and returns the message itself for convenience. """ if message.is_multipart(): # Don't recurse in already-deleted attachments if message.get_content_type() != 'message/external-body': parts = message.get_payload() parts[:] = map(clean_message, parts) elif message_is_binary(message): # Don't gut if this is the topmost message if not topmost: message = gut_message(message) return message
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Clean a message of all its binary parts. This guts all binary attachments, and returns the message itself for convenience.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/email/mailboxpurge.py#L80-L98
train
53,301
RudolfCardinal/pythonlib
cardinal_pythonlib/crypto.py
is_password_valid
def is_password_valid(plaintextpw: str, storedhash: str) -> bool: """ Checks if a plaintext password matches a stored hash. Uses ``bcrypt``. The stored hash includes its own incorporated salt. """ # Upon CamCOPS from MySQL 5.5.34 (Ubuntu) to 5.1.71 (CentOS 6.5), the # VARCHAR was retrieved as Unicode. We needed to convert that to a str. # For Python 3 compatibility, we just str-convert everything, avoiding the # unicode keyword, which no longer exists. if storedhash is None: storedhash = "" storedhash = str(storedhash) if plaintextpw is None: plaintextpw = "" plaintextpw = str(plaintextpw) try: h = bcrypt.hashpw(plaintextpw, storedhash) except ValueError: # e.g. ValueError: invalid salt return False return h == storedhash
python
def is_password_valid(plaintextpw: str, storedhash: str) -> bool: """ Checks if a plaintext password matches a stored hash. Uses ``bcrypt``. The stored hash includes its own incorporated salt. """ # Upon CamCOPS from MySQL 5.5.34 (Ubuntu) to 5.1.71 (CentOS 6.5), the # VARCHAR was retrieved as Unicode. We needed to convert that to a str. # For Python 3 compatibility, we just str-convert everything, avoiding the # unicode keyword, which no longer exists. if storedhash is None: storedhash = "" storedhash = str(storedhash) if plaintextpw is None: plaintextpw = "" plaintextpw = str(plaintextpw) try: h = bcrypt.hashpw(plaintextpw, storedhash) except ValueError: # e.g. ValueError: invalid salt return False return h == storedhash
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/crypto.py#L56-L76
train
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JohnVinyard/featureflow
featureflow/extractor.py
FunctionalNode.version
def version(self): """ Compute the version identifier for this functional node using the func code and local names. Optionally, also allow closed-over variable values to affect the version number when closure_fingerprint is specified """ try: f = self.func.__call__.__code__ except AttributeError: f = self.func.__code__ h = md5() h.update(f.co_code) h.update(str(f.co_names).encode()) try: closure = self.func.__closure__ except AttributeError: return h.hexdigest() if closure is None or self.closure_fingerprint is None: return h.hexdigest() d = dict( (name, cell.cell_contents) for name, cell in zip(f.co_freevars, closure)) h.update(self.closure_fingerprint(d).encode()) return h.hexdigest()
python
def version(self): """ Compute the version identifier for this functional node using the func code and local names. Optionally, also allow closed-over variable values to affect the version number when closure_fingerprint is specified """ try: f = self.func.__call__.__code__ except AttributeError: f = self.func.__code__ h = md5() h.update(f.co_code) h.update(str(f.co_names).encode()) try: closure = self.func.__closure__ except AttributeError: return h.hexdigest() if closure is None or self.closure_fingerprint is None: return h.hexdigest() d = dict( (name, cell.cell_contents) for name, cell in zip(f.co_freevars, closure)) h.update(self.closure_fingerprint(d).encode()) return h.hexdigest()
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7731487b00e38fa4f58c88b7881870fda2d69fdb
https://github.com/JohnVinyard/featureflow/blob/7731487b00e38fa4f58c88b7881870fda2d69fdb/featureflow/extractor.py#L189-L218
train
53,303
meyersj/geotweet
geotweet/mapreduce/state_county_wordcount.py
StateCountyWordCountJob.mapper_init
def mapper_init(self): """ Download counties geojson from S3 and build spatial index and cache """ self.counties = CachedCountyLookup(precision=GEOHASH_PRECISION) self.extractor = WordExtractor()
python
def mapper_init(self): """ Download counties geojson from S3 and build spatial index and cache """ self.counties = CachedCountyLookup(precision=GEOHASH_PRECISION) self.extractor = WordExtractor()
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1a6b55f98adf34d1b91f172d9187d599616412d9
https://github.com/meyersj/geotweet/blob/1a6b55f98adf34d1b91f172d9187d599616412d9/geotweet/mapreduce/state_county_wordcount.py#L60-L63
train
53,304
meyersj/geotweet
geotweet/geomongo/__init__.py
GeoMongo.run
def run(self): """ Top level runner to load State and County GeoJSON files into Mongo DB """ logging.info("Starting GeoJSON MongoDB loading process.") mongo = dict(uri=self.mongo, db=self.db, collection=self.collection) self.load(self.source, **mongo) logging.info("Finished loading {0} into MongoDB".format(self.source))
python
def run(self): """ Top level runner to load State and County GeoJSON files into Mongo DB """ logging.info("Starting GeoJSON MongoDB loading process.") mongo = dict(uri=self.mongo, db=self.db, collection=self.collection) self.load(self.source, **mongo) logging.info("Finished loading {0} into MongoDB".format(self.source))
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1a6b55f98adf34d1b91f172d9187d599616412d9
https://github.com/meyersj/geotweet/blob/1a6b55f98adf34d1b91f172d9187d599616412d9/geotweet/geomongo/__init__.py#L19-L24
train
53,305
meyersj/geotweet
geotweet/geomongo/__init__.py
GeoMongo.load
def load(self, geojson, uri=None, db=None, collection=None): """ Load geojson file into mongodb instance """ logging.info("Mongo URI: {0}".format(uri)) logging.info("Mongo DB: {0}".format(db)) logging.info("Mongo Collection: {0}".format(collection)) logging.info("Geojson File to be loaded: {0}".format(geojson)) mongo = MongoGeo(db=db, collection=collection, uri=uri) GeoJSONLoader().load(geojson, mongo.insert)
python
def load(self, geojson, uri=None, db=None, collection=None): """ Load geojson file into mongodb instance """ logging.info("Mongo URI: {0}".format(uri)) logging.info("Mongo DB: {0}".format(db)) logging.info("Mongo Collection: {0}".format(collection)) logging.info("Geojson File to be loaded: {0}".format(geojson)) mongo = MongoGeo(db=db, collection=collection, uri=uri) GeoJSONLoader().load(geojson, mongo.insert)
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1a6b55f98adf34d1b91f172d9187d599616412d9
https://github.com/meyersj/geotweet/blob/1a6b55f98adf34d1b91f172d9187d599616412d9/geotweet/geomongo/__init__.py#L26-L33
train
53,306
DCOD-OpenSource/django-project-version
djversion/utils.py
get_version
def get_version(): """ Return formatted version string. Returns: str: string with project version or empty string. """ if all([VERSION, UPDATED, any([isinstance(UPDATED, date), isinstance(UPDATED, datetime), ]), ]): return FORMAT_STRING.format(**{"version": VERSION, "updated": UPDATED, }) elif VERSION: return VERSION elif UPDATED: return localize(UPDATED) if any([isinstance(UPDATED, date), isinstance(UPDATED, datetime), ]) else "" else: return ""
python
def get_version(): """ Return formatted version string. Returns: str: string with project version or empty string. """ if all([VERSION, UPDATED, any([isinstance(UPDATED, date), isinstance(UPDATED, datetime), ]), ]): return FORMAT_STRING.format(**{"version": VERSION, "updated": UPDATED, }) elif VERSION: return VERSION elif UPDATED: return localize(UPDATED) if any([isinstance(UPDATED, date), isinstance(UPDATED, datetime), ]) else "" else: return ""
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5fc63609cdf0cb2777f9e9155aa88f443e252b71
https://github.com/DCOD-OpenSource/django-project-version/blob/5fc63609cdf0cb2777f9e9155aa88f443e252b71/djversion/utils.py#L25-L44
train
53,307
RudolfCardinal/pythonlib
cardinal_pythonlib/openxml/find_recovered_openxml.py
process_file
def process_file(filename: str, filetypes: List[str], move_to: str, delete_if_not_specified_file_type: bool, show_zip_output: bool) -> None: """ Deals with an OpenXML, including if it is potentially corrupted. Args: filename: filename to process filetypes: list of filetypes that we care about, e.g. ``['docx', 'pptx', 'xlsx']``. move_to: move matching files to this directory delete_if_not_specified_file_type: if ``True``, and the file is **not** a type specified in ``filetypes``, then delete the file. show_zip_output: show the output from the external ``zip`` tool? """ # log.critical("process_file: start") try: reader = CorruptedOpenXmlReader(filename, show_zip_output=show_zip_output) if reader.file_type in filetypes: log.info("Found {}: {}", reader.description, filename) if move_to: dest_file = os.path.join(move_to, os.path.basename(filename)) _, ext = os.path.splitext(dest_file) if ext != reader.suggested_extension(): dest_file += reader.suggested_extension() reader.move_to(destination_filename=dest_file) else: log.info("Unrecognized or unwanted contents: " + filename) if delete_if_not_specified_file_type: log.info("Deleting: " + filename) os.remove(filename) except Exception as e: # Must explicitly catch and report errors, since otherwise they vanish # into the ether. log.critical("Uncaught error in subprocess: {!r}\n{}", e, traceback.format_exc()) raise
python
def process_file(filename: str, filetypes: List[str], move_to: str, delete_if_not_specified_file_type: bool, show_zip_output: bool) -> None: """ Deals with an OpenXML, including if it is potentially corrupted. Args: filename: filename to process filetypes: list of filetypes that we care about, e.g. ``['docx', 'pptx', 'xlsx']``. move_to: move matching files to this directory delete_if_not_specified_file_type: if ``True``, and the file is **not** a type specified in ``filetypes``, then delete the file. show_zip_output: show the output from the external ``zip`` tool? """ # log.critical("process_file: start") try: reader = CorruptedOpenXmlReader(filename, show_zip_output=show_zip_output) if reader.file_type in filetypes: log.info("Found {}: {}", reader.description, filename) if move_to: dest_file = os.path.join(move_to, os.path.basename(filename)) _, ext = os.path.splitext(dest_file) if ext != reader.suggested_extension(): dest_file += reader.suggested_extension() reader.move_to(destination_filename=dest_file) else: log.info("Unrecognized or unwanted contents: " + filename) if delete_if_not_specified_file_type: log.info("Deleting: " + filename) os.remove(filename) except Exception as e: # Must explicitly catch and report errors, since otherwise they vanish # into the ether. log.critical("Uncaught error in subprocess: {!r}\n{}", e, traceback.format_exc()) raise
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/openxml/find_recovered_openxml.py#L294-L333
train
53,308
oxalorg/Stab
stab/watchman.py
Watchman.should_build
def should_build(self, fpath, meta): """ Checks if the file should be built or not Only skips layouts which are tagged as INCREMENTAL Rebuilds only those files with mtime changed since previous build """ if meta.get('layout', self.default_template) in self.inc_layout: if self.prev_mtime.get(fpath, 0) == os.path.getmtime(fpath): return False else: return True return True
python
def should_build(self, fpath, meta): """ Checks if the file should be built or not Only skips layouts which are tagged as INCREMENTAL Rebuilds only those files with mtime changed since previous build """ if meta.get('layout', self.default_template) in self.inc_layout: if self.prev_mtime.get(fpath, 0) == os.path.getmtime(fpath): return False else: return True return True
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8f0ded780fd7a53a674835c9cb1b7ca08b98f562
https://github.com/oxalorg/Stab/blob/8f0ded780fd7a53a674835c9cb1b7ca08b98f562/stab/watchman.py#L24-L35
train
53,309
calston/rhumba
rhumba/backends/redis.py
Backend.clusterQueues
def clusterQueues(self): """ Return a dict of queues in cluster and servers running them """ servers = yield self.getClusterServers() queues = {} for sname in servers: qs = yield self.get('rhumba.server.%s.queues' % sname) uuid = yield self.get('rhumba.server.%s.uuid' % sname) qs = json.loads(qs) for q in qs: if q not in queues: queues[q] = [] queues[q].append({'host': sname, 'uuid': uuid}) defer.returnValue(queues)
python
def clusterQueues(self): """ Return a dict of queues in cluster and servers running them """ servers = yield self.getClusterServers() queues = {} for sname in servers: qs = yield self.get('rhumba.server.%s.queues' % sname) uuid = yield self.get('rhumba.server.%s.uuid' % sname) qs = json.loads(qs) for q in qs: if q not in queues: queues[q] = [] queues[q].append({'host': sname, 'uuid': uuid}) defer.returnValue(queues)
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05e3cbf4e531cc51b4777912eb98a4f006893f5e
https://github.com/calston/rhumba/blob/05e3cbf4e531cc51b4777912eb98a4f006893f5e/rhumba/backends/redis.py#L207-L226
train
53,310
avihad/twistes
twistes/client.py
Elasticsearch.close
def close(self): """ close all http connections. returns a deferred that fires once they're all closed. """ def validate_client(client): """ Validate that the connection is for the current client :param client: :return: """ host, port = client.addr parsed_url = urlparse(self._hostname) return host == parsed_url.hostname and port == parsed_url.port # read https://github.com/twisted/treq/issues/86 # to understand the following... def _check_fds(_): fds = set(reactor.getReaders() + reactor.getReaders()) if not [fd for fd in fds if isinstance(fd, Client) and validate_client(fd)]: return return deferLater(reactor, 0, _check_fds, None) pool = self._async_http_client_params["pool"] return pool.closeCachedConnections().addBoth(_check_fds)
python
def close(self): """ close all http connections. returns a deferred that fires once they're all closed. """ def validate_client(client): """ Validate that the connection is for the current client :param client: :return: """ host, port = client.addr parsed_url = urlparse(self._hostname) return host == parsed_url.hostname and port == parsed_url.port # read https://github.com/twisted/treq/issues/86 # to understand the following... def _check_fds(_): fds = set(reactor.getReaders() + reactor.getReaders()) if not [fd for fd in fds if isinstance(fd, Client) and validate_client(fd)]: return return deferLater(reactor, 0, _check_fds, None) pool = self._async_http_client_params["pool"] return pool.closeCachedConnections().addBoth(_check_fds)
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9ab8f5aa088b8886aefe3dec85a400e5035e034a
https://github.com/avihad/twistes/blob/9ab8f5aa088b8886aefe3dec85a400e5035e034a/twistes/client.py#L666-L692
train
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davenquinn/Attitude
attitude/helpers/dem.py
extract_line
def extract_line(geom, dem, **kwargs): """ Extract a linear feature from a `rasterio` geospatial dataset. """ kwargs.setdefault('masked', True) coords_in = coords_array(geom) # Transform geometry into pixels f = lambda *x: ~dem.transform * x px = transform(f,geom) # Subdivide geometry segments if option is given interval = kwargs.pop('subdivide', 1) if interval is not None: px = subdivide(px, interval=interval) # Transform pixels back to geometry # to capture subdivisions f = lambda *x: dem.transform * (x[0],x[1]) geom = transform(f,px) # Get min and max coords for windowing # Does not deal with edge cases where points # are outside of footprint of DEM coords_px = coords_array(px) mins = N.floor(coords_px.min(axis=0)) maxs = N.ceil(coords_px.max(axis=0)) window = tuple((int(mn),int(mx)) for mn,mx in zip(mins[::-1],maxs[::-1])) aff = Affine.translation(*(-mins)) f = lambda *x: aff * x px_to_extract = transform(f,px) band = dem.read(1, window=window, **kwargs) extracted = bilinear(band, px_to_extract) coords = coords_array(extracted) coords[:,:2] = coords_array(geom) return coords
python
def extract_line(geom, dem, **kwargs): """ Extract a linear feature from a `rasterio` geospatial dataset. """ kwargs.setdefault('masked', True) coords_in = coords_array(geom) # Transform geometry into pixels f = lambda *x: ~dem.transform * x px = transform(f,geom) # Subdivide geometry segments if option is given interval = kwargs.pop('subdivide', 1) if interval is not None: px = subdivide(px, interval=interval) # Transform pixels back to geometry # to capture subdivisions f = lambda *x: dem.transform * (x[0],x[1]) geom = transform(f,px) # Get min and max coords for windowing # Does not deal with edge cases where points # are outside of footprint of DEM coords_px = coords_array(px) mins = N.floor(coords_px.min(axis=0)) maxs = N.ceil(coords_px.max(axis=0)) window = tuple((int(mn),int(mx)) for mn,mx in zip(mins[::-1],maxs[::-1])) aff = Affine.translation(*(-mins)) f = lambda *x: aff * x px_to_extract = transform(f,px) band = dem.read(1, window=window, **kwargs) extracted = bilinear(band, px_to_extract) coords = coords_array(extracted) coords[:,:2] = coords_array(geom) return coords
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2ce97b9aba0aa5deedc6617c2315e07e6396d240
https://github.com/davenquinn/Attitude/blob/2ce97b9aba0aa5deedc6617c2315e07e6396d240/attitude/helpers/dem.py#L58-L101
train
53,312
calston/rhumba
rhumba/utils.py
fork
def fork(executable, args=(), env={}, path=None, timeout=3600): """fork Provides a deferred wrapper function with a timeout function :param executable: Executable :type executable: str. :param args: Tupple of arguments :type args: tupple. :param env: Environment dictionary :type env: dict. :param timeout: Kill the child process if timeout is exceeded :type timeout: int. """ d = defer.Deferred() p = ProcessProtocol(d, timeout) reactor.spawnProcess(p, executable, (executable,)+tuple(args), env, path) return d
python
def fork(executable, args=(), env={}, path=None, timeout=3600): """fork Provides a deferred wrapper function with a timeout function :param executable: Executable :type executable: str. :param args: Tupple of arguments :type args: tupple. :param env: Environment dictionary :type env: dict. :param timeout: Kill the child process if timeout is exceeded :type timeout: int. """ d = defer.Deferred() p = ProcessProtocol(d, timeout) reactor.spawnProcess(p, executable, (executable,)+tuple(args), env, path) return d
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05e3cbf4e531cc51b4777912eb98a4f006893f5e
https://github.com/calston/rhumba/blob/05e3cbf4e531cc51b4777912eb98a4f006893f5e/rhumba/utils.py#L52-L68
train
53,313
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
number_to_dp
def number_to_dp(number: Optional[float], dp: int, default: Optional[str] = "", en_dash_for_minus: bool = True) -> str: """ Format number to ``dp`` decimal places, optionally using a UTF-8 en dash for minus signs. """ if number is None: return default if number == float("inf"): return u"∞" if number == float("-inf"): s = u"-∞" else: s = u"{:.{precision}f}".format(number, precision=dp) if en_dash_for_minus: s = s.replace("-", u"–") # hyphen becomes en dash for minus sign return s
python
def number_to_dp(number: Optional[float], dp: int, default: Optional[str] = "", en_dash_for_minus: bool = True) -> str: """ Format number to ``dp`` decimal places, optionally using a UTF-8 en dash for minus signs. """ if number is None: return default if number == float("inf"): return u"∞" if number == float("-inf"): s = u"-∞" else: s = u"{:.{precision}f}".format(number, precision=dp) if en_dash_for_minus: s = s.replace("-", u"–") # hyphen becomes en dash for minus sign return s
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Format number to ``dp`` decimal places, optionally using a UTF-8 en dash for minus signs.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L109-L127
train
53,314
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
debug_form_contents
def debug_form_contents(form: cgi.FieldStorage, to_stderr: bool = True, to_logger: bool = False) -> None: """ Writes the keys and values of a CGI form to ``stderr``. """ for k in form.keys(): text = "{0} = {1}".format(k, form.getvalue(k)) if to_stderr: sys.stderr.write(text) if to_logger: log.info(text)
python
def debug_form_contents(form: cgi.FieldStorage, to_stderr: bool = True, to_logger: bool = False) -> None: """ Writes the keys and values of a CGI form to ``stderr``. """ for k in form.keys(): text = "{0} = {1}".format(k, form.getvalue(k)) if to_stderr: sys.stderr.write(text) if to_logger: log.info(text)
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L134-L145
train
53,315
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
cgi_method_is_post
def cgi_method_is_post(environ: Dict[str, str]) -> bool: """ Determines if the CGI method was ``POST``, given the CGI environment. """ method = environ.get("REQUEST_METHOD", None) if not method: return False return method.upper() == "POST"
python
def cgi_method_is_post(environ: Dict[str, str]) -> bool: """ Determines if the CGI method was ``POST``, given the CGI environment. """ method = environ.get("REQUEST_METHOD", None) if not method: return False return method.upper() == "POST"
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Determines if the CGI method was ``POST``, given the CGI environment.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L149-L156
train
53,316
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_cgi_parameter_str_or_none
def get_cgi_parameter_str_or_none(form: cgi.FieldStorage, key: str) -> Optional[str]: """ Extracts a string parameter from a CGI form, or ``None`` if the key doesn't exist or the string is zero-length. """ s = get_cgi_parameter_str(form, key) if s is None or len(s) == 0: return None return s
python
def get_cgi_parameter_str_or_none(form: cgi.FieldStorage, key: str) -> Optional[str]: """ Extracts a string parameter from a CGI form, or ``None`` if the key doesn't exist or the string is zero-length. """ s = get_cgi_parameter_str(form, key) if s is None or len(s) == 0: return None return s
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L172-L181
train
53,317
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_cgi_parameter_list
def get_cgi_parameter_list(form: cgi.FieldStorage, key: str) -> List[str]: """ Extracts a list of values, all with the same key, from a CGI form. """ return form.getlist(key)
python
def get_cgi_parameter_list(form: cgi.FieldStorage, key: str) -> List[str]: """ Extracts a list of values, all with the same key, from a CGI form. """ return form.getlist(key)
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L184-L188
train
53,318
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_cgi_parameter_bool
def get_cgi_parameter_bool(form: cgi.FieldStorage, key: str) -> bool: """ Extracts a boolean parameter from a CGI form, on the assumption that ``"1"`` is ``True`` and everything else is ``False``. """ return is_1(get_cgi_parameter_str(form, key))
python
def get_cgi_parameter_bool(form: cgi.FieldStorage, key: str) -> bool: """ Extracts a boolean parameter from a CGI form, on the assumption that ``"1"`` is ``True`` and everything else is ``False``. """ return is_1(get_cgi_parameter_str(form, key))
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L191-L196
train
53,319
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_cgi_parameter_int
def get_cgi_parameter_int(form: cgi.FieldStorage, key: str) -> Optional[int]: """ Extracts an integer parameter from a CGI form, or ``None`` if the key is absent or the string value is not convertible to ``int``. """ return get_int_or_none(get_cgi_parameter_str(form, key))
python
def get_cgi_parameter_int(form: cgi.FieldStorage, key: str) -> Optional[int]: """ Extracts an integer parameter from a CGI form, or ``None`` if the key is absent or the string value is not convertible to ``int``. """ return get_int_or_none(get_cgi_parameter_str(form, key))
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L221-L226
train
53,320
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_cgi_parameter_float
def get_cgi_parameter_float(form: cgi.FieldStorage, key: str) -> Optional[float]: """ Extracts a float parameter from a CGI form, or None if the key is absent or the string value is not convertible to ``float``. """ return get_float_or_none(get_cgi_parameter_str(form, key))
python
def get_cgi_parameter_float(form: cgi.FieldStorage, key: str) -> Optional[float]: """ Extracts a float parameter from a CGI form, or None if the key is absent or the string value is not convertible to ``float``. """ return get_float_or_none(get_cgi_parameter_str(form, key))
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L229-L235
train
53,321
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_cgi_parameter_file
def get_cgi_parameter_file(form: cgi.FieldStorage, key: str) -> Optional[bytes]: """ Extracts a file's contents from a "file" input in a CGI form, or None if no such file was uploaded. """ (filename, filecontents) = get_cgi_parameter_filename_and_file(form, key) return filecontents
python
def get_cgi_parameter_file(form: cgi.FieldStorage, key: str) -> Optional[bytes]: """ Extracts a file's contents from a "file" input in a CGI form, or None if no such file was uploaded. """ (filename, filecontents) = get_cgi_parameter_filename_and_file(form, key) return filecontents
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L258-L265
train
53,322
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
cgi_parameter_exists
def cgi_parameter_exists(form: cgi.FieldStorage, key: str) -> bool: """ Does a CGI form contain the key? """ s = get_cgi_parameter_str(form, key) return s is not None
python
def cgi_parameter_exists(form: cgi.FieldStorage, key: str) -> bool: """ Does a CGI form contain the key? """ s = get_cgi_parameter_str(form, key) return s is not None
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L312-L317
train
53,323
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
getenv_escaped
def getenv_escaped(key: str, default: str = None) -> Optional[str]: """ Returns an environment variable's value, CGI-escaped, or ``None``. """ value = os.getenv(key, default) # noinspection PyDeprecation return cgi.escape(value) if value is not None else None
python
def getenv_escaped(key: str, default: str = None) -> Optional[str]: """ Returns an environment variable's value, CGI-escaped, or ``None``. """ value = os.getenv(key, default) # noinspection PyDeprecation return cgi.escape(value) if value is not None else None
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Returns an environment variable's value, CGI-escaped, or ``None``.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L349-L355
train
53,324
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
get_png_data_url
def get_png_data_url(blob: Optional[bytes]) -> str: """ Converts a PNG blob into a local URL encapsulating the PNG. """ return BASE64_PNG_URL_PREFIX + base64.b64encode(blob).decode('ascii')
python
def get_png_data_url(blob: Optional[bytes]) -> str: """ Converts a PNG blob into a local URL encapsulating the PNG. """ return BASE64_PNG_URL_PREFIX + base64.b64encode(blob).decode('ascii')
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L401-L405
train
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RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
print_result_for_plain_cgi_script_from_tuple
def print_result_for_plain_cgi_script_from_tuple( contenttype_headers_content: WSGI_TUPLE_TYPE, status: str = '200 OK') -> None: """ Writes HTTP result to stdout. Args: contenttype_headers_content: the tuple ``(contenttype, extraheaders, data)`` status: HTTP status message (default ``"200 OK``) """ contenttype, headers, content = contenttype_headers_content print_result_for_plain_cgi_script(contenttype, headers, content, status)
python
def print_result_for_plain_cgi_script_from_tuple( contenttype_headers_content: WSGI_TUPLE_TYPE, status: str = '200 OK') -> None: """ Writes HTTP result to stdout. Args: contenttype_headers_content: the tuple ``(contenttype, extraheaders, data)`` status: HTTP status message (default ``"200 OK``) """ contenttype, headers, content = contenttype_headers_content print_result_for_plain_cgi_script(contenttype, headers, content, status)
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Writes HTTP result to stdout. Args: contenttype_headers_content: the tuple ``(contenttype, extraheaders, data)`` status: HTTP status message (default ``"200 OK``)
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L520-L533
train
53,326
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
print_result_for_plain_cgi_script
def print_result_for_plain_cgi_script(contenttype: str, headers: TYPE_WSGI_RESPONSE_HEADERS, content: bytes, status: str = '200 OK') -> None: """ Writes HTTP request result to stdout. """ headers = [ ("Status", status), ("Content-Type", contenttype), ("Content-Length", str(len(content))), ] + headers sys.stdout.write("\n".join([h[0] + ": " + h[1] for h in headers]) + "\n\n") sys.stdout.write(content)
python
def print_result_for_plain_cgi_script(contenttype: str, headers: TYPE_WSGI_RESPONSE_HEADERS, content: bytes, status: str = '200 OK') -> None: """ Writes HTTP request result to stdout. """ headers = [ ("Status", status), ("Content-Type", contenttype), ("Content-Length", str(len(content))), ] + headers sys.stdout.write("\n".join([h[0] + ": " + h[1] for h in headers]) + "\n\n") sys.stdout.write(content)
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Writes HTTP request result to stdout.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L536-L549
train
53,327
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
wsgi_simple_responder
def wsgi_simple_responder( result: Union[str, bytes], handler: Callable[[Union[str, bytes]], WSGI_TUPLE_TYPE], start_response: TYPE_WSGI_START_RESPONSE, status: str = '200 OK', extraheaders: TYPE_WSGI_RESPONSE_HEADERS = None) \ -> TYPE_WSGI_APP_RESULT: """ Simple WSGI app. Args: result: the data to be processed by ``handler`` handler: a function returning a ``(contenttype, extraheaders, data)`` tuple, e.g. ``text_result``, ``html_result`` start_response: standard WSGI ``start_response`` function status: status code (default ``"200 OK"``) extraheaders: optional extra HTTP headers Returns: WSGI application result """ extraheaders = extraheaders or [] (contenttype, extraheaders2, output) = handler(result) response_headers = [('Content-Type', contenttype), ('Content-Length', str(len(output)))] response_headers.extend(extraheaders) if extraheaders2 is not None: response_headers.extend(extraheaders2) # noinspection PyArgumentList start_response(status, response_headers) return [output]
python
def wsgi_simple_responder( result: Union[str, bytes], handler: Callable[[Union[str, bytes]], WSGI_TUPLE_TYPE], start_response: TYPE_WSGI_START_RESPONSE, status: str = '200 OK', extraheaders: TYPE_WSGI_RESPONSE_HEADERS = None) \ -> TYPE_WSGI_APP_RESULT: """ Simple WSGI app. Args: result: the data to be processed by ``handler`` handler: a function returning a ``(contenttype, extraheaders, data)`` tuple, e.g. ``text_result``, ``html_result`` start_response: standard WSGI ``start_response`` function status: status code (default ``"200 OK"``) extraheaders: optional extra HTTP headers Returns: WSGI application result """ extraheaders = extraheaders or [] (contenttype, extraheaders2, output) = handler(result) response_headers = [('Content-Type', contenttype), ('Content-Length', str(len(output)))] response_headers.extend(extraheaders) if extraheaders2 is not None: response_headers.extend(extraheaders2) # noinspection PyArgumentList start_response(status, response_headers) return [output]
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Simple WSGI app. Args: result: the data to be processed by ``handler`` handler: a function returning a ``(contenttype, extraheaders, data)`` tuple, e.g. ``text_result``, ``html_result`` start_response: standard WSGI ``start_response`` function status: status code (default ``"200 OK"``) extraheaders: optional extra HTTP headers Returns: WSGI application result
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L556-L587
train
53,328
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
bold_if_not_blank
def bold_if_not_blank(x: Optional[str]) -> str: """ HTML-emboldens content, unless blank. """ if x is None: return u"{}".format(x) return u"<b>{}</b>".format(x)
python
def bold_if_not_blank(x: Optional[str]) -> str: """ HTML-emboldens content, unless blank. """ if x is None: return u"{}".format(x) return u"<b>{}</b>".format(x)
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HTML-emboldens content, unless blank.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L628-L634
train
53,329
RudolfCardinal/pythonlib
cardinal_pythonlib/rnc_web.py
make_urls_hyperlinks
def make_urls_hyperlinks(text: str) -> str: """ Adds hyperlinks to text that appears to contain URLs. See - http://stackoverflow.com/questions/1071191 - ... except that double-replaces everything; e.g. try with ``text = "me@somewhere.com me@somewhere.com"`` - http://stackp.online.fr/?p=19 """ find_url = r''' (?x)( # verbose identify URLs within text (http|ftp|gopher) # make sure we find a resource type :// # ...needs to be followed by colon-slash-slash (\w+[:.]?){2,} # at least two domain groups, e.g. (gnosis.)(cx) (/?| # could be just the domain name (maybe w/ slash) [^ \n\r"]+ # or stuff then space, newline, tab, quote [\w/]) # resource name ends in alphanumeric or slash (?=[\s\.,>)'"\]]) # assert: followed by white or clause ending ) # end of match group ''' replace_url = r'<a href="\1">\1</a>' find_email = re.compile(r'([.\w\-]+@(\w[\w\-]+\.)+[\w\-]+)') # '.' doesn't need escaping inside square brackets # https://stackoverflow.com/questions/10397968/escape-dot-in-a-regex-range replace_email = r'<a href="mailto:\1">\1</a>' text = re.sub(find_url, replace_url, text) text = re.sub(find_email, replace_email, text) return text
python
def make_urls_hyperlinks(text: str) -> str: """ Adds hyperlinks to text that appears to contain URLs. See - http://stackoverflow.com/questions/1071191 - ... except that double-replaces everything; e.g. try with ``text = "me@somewhere.com me@somewhere.com"`` - http://stackp.online.fr/?p=19 """ find_url = r''' (?x)( # verbose identify URLs within text (http|ftp|gopher) # make sure we find a resource type :// # ...needs to be followed by colon-slash-slash (\w+[:.]?){2,} # at least two domain groups, e.g. (gnosis.)(cx) (/?| # could be just the domain name (maybe w/ slash) [^ \n\r"]+ # or stuff then space, newline, tab, quote [\w/]) # resource name ends in alphanumeric or slash (?=[\s\.,>)'"\]]) # assert: followed by white or clause ending ) # end of match group ''' replace_url = r'<a href="\1">\1</a>' find_email = re.compile(r'([.\w\-]+@(\w[\w\-]+\.)+[\w\-]+)') # '.' doesn't need escaping inside square brackets # https://stackoverflow.com/questions/10397968/escape-dot-in-a-regex-range replace_email = r'<a href="mailto:\1">\1</a>' text = re.sub(find_url, replace_url, text) text = re.sub(find_email, replace_email, text) return text
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/rnc_web.py#L637-L668
train
53,330
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
rst_underline
def rst_underline(heading: str, underline_char: str) -> str: """ Underlines a heading for RST files. Args: heading: text to underline underline_char: character to use Returns: underlined heading, over two lines (without a final terminating newline) """ assert "\n" not in heading assert len(underline_char) == 1 return heading + "\n" + (underline_char * len(heading))
python
def rst_underline(heading: str, underline_char: str) -> str: """ Underlines a heading for RST files. Args: heading: text to underline underline_char: character to use Returns: underlined heading, over two lines (without a final terminating newline) """ assert "\n" not in heading assert len(underline_char) == 1 return heading + "\n" + (underline_char * len(heading))
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Underlines a heading for RST files. Args: heading: text to underline underline_char: character to use Returns: underlined heading, over two lines (without a final terminating newline)
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L78-L92
train
53,331
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
write_if_allowed
def write_if_allowed(filename: str, content: str, overwrite: bool = False, mock: bool = False) -> None: """ Writes the contents to a file, if permitted. Args: filename: filename to write content: contents to write overwrite: permit overwrites? mock: pretend to write, but don't Raises: RuntimeError: if file exists but overwriting not permitted """ # Check we're allowed if not overwrite and exists(filename): fail("File exists, not overwriting: {!r}".format(filename)) # Make the directory, if necessary directory = dirname(filename) if not mock: mkdir_p(directory) # Write the file log.info("Writing to {!r}", filename) if mock: log.warning("Skipping writes as in mock mode") else: with open(filename, "wt") as outfile: outfile.write(content)
python
def write_if_allowed(filename: str, content: str, overwrite: bool = False, mock: bool = False) -> None: """ Writes the contents to a file, if permitted. Args: filename: filename to write content: contents to write overwrite: permit overwrites? mock: pretend to write, but don't Raises: RuntimeError: if file exists but overwriting not permitted """ # Check we're allowed if not overwrite and exists(filename): fail("File exists, not overwriting: {!r}".format(filename)) # Make the directory, if necessary directory = dirname(filename) if not mock: mkdir_p(directory) # Write the file log.info("Writing to {!r}", filename) if mock: log.warning("Skipping writes as in mock mode") else: with open(filename, "wt") as outfile: outfile.write(content)
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Writes the contents to a file, if permitted. Args: filename: filename to write content: contents to write overwrite: permit overwrites? mock: pretend to write, but don't Raises: RuntimeError: if file exists but overwriting not permitted
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L100-L131
train
53,332
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
FileToAutodocument.rst_filename_rel_autodoc_index
def rst_filename_rel_autodoc_index(self, index_filename: str) -> str: """ Returns the filename of the target RST file, relative to a specified index file. Used to make the index refer to the RST. """ index_dir = dirname(abspath(expanduser(index_filename))) return relpath(self.target_rst_filename, start=index_dir)
python
def rst_filename_rel_autodoc_index(self, index_filename: str) -> str: """ Returns the filename of the target RST file, relative to a specified index file. Used to make the index refer to the RST. """ index_dir = dirname(abspath(expanduser(index_filename))) return relpath(self.target_rst_filename, start=index_dir)
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Returns the filename of the target RST file, relative to a specified index file. Used to make the index refer to the RST.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L291-L297
train
53,333
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
FileToAutodocument.python_module_name
def python_module_name(self) -> str: """ Returns the name of the Python module that this instance refers to, in dotted Python module notation, or a blank string if it doesn't. """ if not self.is_python: return "" filepath = self.source_filename_rel_python_root dirs_and_base = splitext(filepath)[0] dir_and_file_parts = dirs_and_base.split(sep) return ".".join(dir_and_file_parts)
python
def python_module_name(self) -> str: """ Returns the name of the Python module that this instance refers to, in dotted Python module notation, or a blank string if it doesn't. """ if not self.is_python: return "" filepath = self.source_filename_rel_python_root dirs_and_base = splitext(filepath)[0] dir_and_file_parts = dirs_and_base.split(sep) return ".".join(dir_and_file_parts)
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Returns the name of the Python module that this instance refers to, in dotted Python module notation, or a blank string if it doesn't.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L300-L310
train
53,334
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
FileToAutodocument.write_rst
def write_rst(self, prefix: str = "", suffix: str = "", heading_underline_char: str = "=", method: AutodocMethod = None, overwrite: bool = False, mock: bool = False) -> None: """ Writes the RST file to our destination RST filename, making any necessary directories. Args: prefix: as for :func:`rst_content` suffix: as for :func:`rst_content` heading_underline_char: as for :func:`rst_content` method: as for :func:`rst_content` overwrite: overwrite the file if it exists already? mock: pretend to write, but don't """ content = self.rst_content( prefix=prefix, suffix=suffix, heading_underline_char=heading_underline_char, method=method ) write_if_allowed(self.target_rst_filename, content, overwrite=overwrite, mock=mock)
python
def write_rst(self, prefix: str = "", suffix: str = "", heading_underline_char: str = "=", method: AutodocMethod = None, overwrite: bool = False, mock: bool = False) -> None: """ Writes the RST file to our destination RST filename, making any necessary directories. Args: prefix: as for :func:`rst_content` suffix: as for :func:`rst_content` heading_underline_char: as for :func:`rst_content` method: as for :func:`rst_content` overwrite: overwrite the file if it exists already? mock: pretend to write, but don't """ content = self.rst_content( prefix=prefix, suffix=suffix, heading_underline_char=heading_underline_char, method=method ) write_if_allowed(self.target_rst_filename, content, overwrite=overwrite, mock=mock)
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Writes the RST file to our destination RST filename, making any necessary directories. Args: prefix: as for :func:`rst_content` suffix: as for :func:`rst_content` heading_underline_char: as for :func:`rst_content` method: as for :func:`rst_content` overwrite: overwrite the file if it exists already? mock: pretend to write, but don't
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L414-L440
train
53,335
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
AutodocIndex.add_source_files
def add_source_files( self, source_filenames_or_globs: Union[str, List[str]], method: AutodocMethod = None, recursive: bool = None, source_rst_title_style_python: bool = None, pygments_language_override: Dict[str, str] = None) -> None: """ Adds source files to the index. Args: source_filenames_or_globs: string containing a filename or a glob, describing the file(s) to be added, or a list of such strings method: optional method to override ``self.method`` recursive: use :func:`glob.glob` in recursive mode? (If ``None``, the default, uses the version from the constructor.) source_rst_title_style_python: optional to override ``self.source_rst_title_style_python`` pygments_language_override: optional to override ``self.pygments_language_override`` """ if not source_filenames_or_globs: return if method is None: # Use the default method = self.method if recursive is None: recursive = self.recursive if source_rst_title_style_python is None: source_rst_title_style_python = self.source_rst_title_style_python if pygments_language_override is None: pygments_language_override = self.pygments_language_override # Get a sorted list of filenames final_filenames = self.get_sorted_source_files( source_filenames_or_globs, recursive=recursive ) # Process that sorted list for source_filename in final_filenames: self.files_to_index.append(FileToAutodocument( source_filename=source_filename, project_root_dir=self.project_root_dir, python_package_root_dir=self.python_package_root_dir, target_rst_filename=self.specific_file_rst_filename( source_filename ), method=method, source_rst_title_style_python=source_rst_title_style_python, pygments_language_override=pygments_language_override, ))
python
def add_source_files( self, source_filenames_or_globs: Union[str, List[str]], method: AutodocMethod = None, recursive: bool = None, source_rst_title_style_python: bool = None, pygments_language_override: Dict[str, str] = None) -> None: """ Adds source files to the index. Args: source_filenames_or_globs: string containing a filename or a glob, describing the file(s) to be added, or a list of such strings method: optional method to override ``self.method`` recursive: use :func:`glob.glob` in recursive mode? (If ``None``, the default, uses the version from the constructor.) source_rst_title_style_python: optional to override ``self.source_rst_title_style_python`` pygments_language_override: optional to override ``self.pygments_language_override`` """ if not source_filenames_or_globs: return if method is None: # Use the default method = self.method if recursive is None: recursive = self.recursive if source_rst_title_style_python is None: source_rst_title_style_python = self.source_rst_title_style_python if pygments_language_override is None: pygments_language_override = self.pygments_language_override # Get a sorted list of filenames final_filenames = self.get_sorted_source_files( source_filenames_or_globs, recursive=recursive ) # Process that sorted list for source_filename in final_filenames: self.files_to_index.append(FileToAutodocument( source_filename=source_filename, project_root_dir=self.project_root_dir, python_package_root_dir=self.python_package_root_dir, target_rst_filename=self.specific_file_rst_filename( source_filename ), method=method, source_rst_title_style_python=source_rst_title_style_python, pygments_language_override=pygments_language_override, ))
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Adds source files to the index. Args: source_filenames_or_globs: string containing a filename or a glob, describing the file(s) to be added, or a list of such strings method: optional method to override ``self.method`` recursive: use :func:`glob.glob` in recursive mode? (If ``None``, the default, uses the version from the constructor.) source_rst_title_style_python: optional to override ``self.source_rst_title_style_python`` pygments_language_override: optional to override ``self.pygments_language_override``
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L654-L707
train
53,336
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
AutodocIndex.filename_matches_glob
def filename_matches_glob(filename: str, globtext: str) -> bool: """ The ``glob.glob`` function doesn't do exclusion very well. We don't want to have to specify root directories for exclusion patterns. We don't want to have to trawl a massive set of files to find exclusion files. So let's implement a glob match. Args: filename: filename globtext: glob Returns: does the filename match the glob? See also: - https://stackoverflow.com/questions/20638040/glob-exclude-pattern """ # Quick check on basename-only matching if fnmatch(filename, globtext): log.debug("{!r} matches {!r}", filename, globtext) return True bname = basename(filename) if fnmatch(bname, globtext): log.debug("{!r} matches {!r}", bname, globtext) return True # Directory matching: is actually accomplished by the code above! # Otherwise: return False
python
def filename_matches_glob(filename: str, globtext: str) -> bool: """ The ``glob.glob`` function doesn't do exclusion very well. We don't want to have to specify root directories for exclusion patterns. We don't want to have to trawl a massive set of files to find exclusion files. So let's implement a glob match. Args: filename: filename globtext: glob Returns: does the filename match the glob? See also: - https://stackoverflow.com/questions/20638040/glob-exclude-pattern """ # Quick check on basename-only matching if fnmatch(filename, globtext): log.debug("{!r} matches {!r}", filename, globtext) return True bname = basename(filename) if fnmatch(bname, globtext): log.debug("{!r} matches {!r}", bname, globtext) return True # Directory matching: is actually accomplished by the code above! # Otherwise: return False
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The ``glob.glob`` function doesn't do exclusion very well. We don't want to have to specify root directories for exclusion patterns. We don't want to have to trawl a massive set of files to find exclusion files. So let's implement a glob match. Args: filename: filename globtext: glob Returns: does the filename match the glob? See also: - https://stackoverflow.com/questions/20638040/glob-exclude-pattern
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L740-L769
train
53,337
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
AutodocIndex.should_exclude
def should_exclude(self, filename) -> bool: """ Should we exclude this file from consideration? """ for skip_glob in self.skip_globs: if self.filename_matches_glob(filename, skip_glob): return True return False
python
def should_exclude(self, filename) -> bool: """ Should we exclude this file from consideration? """ for skip_glob in self.skip_globs: if self.filename_matches_glob(filename, skip_glob): return True return False
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Should we exclude this file from consideration?
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L771-L778
train
53,338
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
AutodocIndex.specific_file_rst_filename
def specific_file_rst_filename(self, source_filename: str) -> str: """ Gets the RST filename corresponding to a source filename. See the help for the constructor for more details. Args: source_filename: source filename within current project Returns: RST filename Note in particular: the way we structure the directories means that we won't get clashes between files with idential names in two different directories. However, we must also incorporate the original source filename, in particular for C++ where ``thing.h`` and ``thing.cpp`` must not generate the same RST filename. So we just add ``.rst``. """ highest_code_to_target = relative_filename_within_dir( source_filename, self.highest_code_dir) bname = basename(source_filename) result = join(self.autodoc_rst_root_dir, dirname(highest_code_to_target), bname + EXT_RST) log.debug("Source {!r} -> RST {!r}", source_filename, result) return result
python
def specific_file_rst_filename(self, source_filename: str) -> str: """ Gets the RST filename corresponding to a source filename. See the help for the constructor for more details. Args: source_filename: source filename within current project Returns: RST filename Note in particular: the way we structure the directories means that we won't get clashes between files with idential names in two different directories. However, we must also incorporate the original source filename, in particular for C++ where ``thing.h`` and ``thing.cpp`` must not generate the same RST filename. So we just add ``.rst``. """ highest_code_to_target = relative_filename_within_dir( source_filename, self.highest_code_dir) bname = basename(source_filename) result = join(self.autodoc_rst_root_dir, dirname(highest_code_to_target), bname + EXT_RST) log.debug("Source {!r} -> RST {!r}", source_filename, result) return result
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Gets the RST filename corresponding to a source filename. See the help for the constructor for more details. Args: source_filename: source filename within current project Returns: RST filename Note in particular: the way we structure the directories means that we won't get clashes between files with idential names in two different directories. However, we must also incorporate the original source filename, in particular for C++ where ``thing.h`` and ``thing.cpp`` must not generate the same RST filename. So we just add ``.rst``.
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L799-L823
train
53,339
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
AutodocIndex.write_index_and_rst_files
def write_index_and_rst_files(self, overwrite: bool = False, mock: bool = False) -> None: """ Writes both the individual RST files and the index. Args: overwrite: allow existing files to be overwritten? mock: pretend to write, but don't """ for f in self.files_to_index: if isinstance(f, FileToAutodocument): f.write_rst( prefix=self.rst_prefix, suffix=self.rst_suffix, heading_underline_char=self.source_rst_heading_underline_char, # noqa overwrite=overwrite, mock=mock, ) elif isinstance(f, AutodocIndex): f.write_index_and_rst_files(overwrite=overwrite, mock=mock) else: fail("Unknown thing in files_to_index: {!r}".format(f)) self.write_index(overwrite=overwrite, mock=mock)
python
def write_index_and_rst_files(self, overwrite: bool = False, mock: bool = False) -> None: """ Writes both the individual RST files and the index. Args: overwrite: allow existing files to be overwritten? mock: pretend to write, but don't """ for f in self.files_to_index: if isinstance(f, FileToAutodocument): f.write_rst( prefix=self.rst_prefix, suffix=self.rst_suffix, heading_underline_char=self.source_rst_heading_underline_char, # noqa overwrite=overwrite, mock=mock, ) elif isinstance(f, AutodocIndex): f.write_index_and_rst_files(overwrite=overwrite, mock=mock) else: fail("Unknown thing in files_to_index: {!r}".format(f)) self.write_index(overwrite=overwrite, mock=mock)
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L825-L847
train
53,340
RudolfCardinal/pythonlib
cardinal_pythonlib/sphinxtools.py
AutodocIndex.write_index
def write_index(self, overwrite: bool = False, mock: bool = False) -> None: """ Writes the index file, if permitted. Args: overwrite: allow existing files to be overwritten? mock: pretend to write, but don't """ write_if_allowed(self.index_filename, self.index_content(), overwrite=overwrite, mock=mock)
python
def write_index(self, overwrite: bool = False, mock: bool = False) -> None: """ Writes the index file, if permitted. Args: overwrite: allow existing files to be overwritten? mock: pretend to write, but don't """ write_if_allowed(self.index_filename, self.index_content(), overwrite=overwrite, mock=mock)
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0b84cb35f38bd7d8723958dae51b480a829b7227
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/sphinxtools.py#L923-L932
train
53,341
carpyncho/feets
doc/source/JSAnimation/examples.py
basic_animation
def basic_animation(frames=100, interval=30): """Plot a basic sine wave with oscillating amplitude""" fig = plt.figure() ax = plt.axes(xlim=(0, 10), ylim=(-2, 2)) line, = ax.plot([], [], lw=2) x = np.linspace(0, 10, 1000) def init(): line.set_data([], []) return line, def animate(i): y = np.cos(i * 0.02 * np.pi) * np.sin(x - i * 0.02 * np.pi) line.set_data(x, y) return line, return animation.FuncAnimation(fig, animate, init_func=init, frames=frames, interval=interval)
python
def basic_animation(frames=100, interval=30): """Plot a basic sine wave with oscillating amplitude""" fig = plt.figure() ax = plt.axes(xlim=(0, 10), ylim=(-2, 2)) line, = ax.plot([], [], lw=2) x = np.linspace(0, 10, 1000) def init(): line.set_data([], []) return line, def animate(i): y = np.cos(i * 0.02 * np.pi) * np.sin(x - i * 0.02 * np.pi) line.set_data(x, y) return line, return animation.FuncAnimation(fig, animate, init_func=init, frames=frames, interval=interval)
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Plot a basic sine wave with oscillating amplitude
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/doc/source/JSAnimation/examples.py#L6-L24
train
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carpyncho/feets
doc/source/JSAnimation/examples.py
lorenz_animation
def lorenz_animation(N_trajectories=20, rseed=1, frames=200, interval=30): """Plot a 3D visualization of the dynamics of the Lorenz system""" from scipy import integrate from mpl_toolkits.mplot3d import Axes3D from matplotlib.colors import cnames def lorentz_deriv(coords, t0, sigma=10., beta=8./3, rho=28.0): """Compute the time-derivative of a Lorentz system.""" x, y, z = coords return [sigma * (y - x), x * (rho - z) - y, x * y - beta * z] # Choose random starting points, uniformly distributed from -15 to 15 np.random.seed(rseed) x0 = -15 + 30 * np.random.random((N_trajectories, 3)) # Solve for the trajectories t = np.linspace(0, 2, 500) x_t = np.asarray([integrate.odeint(lorentz_deriv, x0i, t) for x0i in x0]) # Set up figure & 3D axis for animation fig = plt.figure() ax = fig.add_axes([0, 0, 1, 1], projection='3d') ax.axis('off') # choose a different color for each trajectory colors = plt.cm.jet(np.linspace(0, 1, N_trajectories)) # set up lines and points lines = sum([ax.plot([], [], [], '-', c=c) for c in colors], []) pts = sum([ax.plot([], [], [], 'o', c=c, ms=4) for c in colors], []) # prepare the axes limits ax.set_xlim((-25, 25)) ax.set_ylim((-35, 35)) ax.set_zlim((5, 55)) # set point-of-view: specified by (altitude degrees, azimuth degrees) ax.view_init(30, 0) # initialization function: plot the background of each frame def init(): for line, pt in zip(lines, pts): line.set_data([], []) line.set_3d_properties([]) pt.set_data([], []) pt.set_3d_properties([]) return lines + pts # animation function: called sequentially def animate(i): # we'll step two time-steps per frame. This leads to nice results. i = (2 * i) % x_t.shape[1] for line, pt, xi in zip(lines, pts, x_t): x, y, z = xi[:i + 1].T line.set_data(x, y) line.set_3d_properties(z) pt.set_data(x[-1:], y[-1:]) pt.set_3d_properties(z[-1:]) ax.view_init(30, 0.3 * i) fig.canvas.draw() return lines + pts return animation.FuncAnimation(fig, animate, init_func=init, frames=frames, interval=interval)
python
def lorenz_animation(N_trajectories=20, rseed=1, frames=200, interval=30): """Plot a 3D visualization of the dynamics of the Lorenz system""" from scipy import integrate from mpl_toolkits.mplot3d import Axes3D from matplotlib.colors import cnames def lorentz_deriv(coords, t0, sigma=10., beta=8./3, rho=28.0): """Compute the time-derivative of a Lorentz system.""" x, y, z = coords return [sigma * (y - x), x * (rho - z) - y, x * y - beta * z] # Choose random starting points, uniformly distributed from -15 to 15 np.random.seed(rseed) x0 = -15 + 30 * np.random.random((N_trajectories, 3)) # Solve for the trajectories t = np.linspace(0, 2, 500) x_t = np.asarray([integrate.odeint(lorentz_deriv, x0i, t) for x0i in x0]) # Set up figure & 3D axis for animation fig = plt.figure() ax = fig.add_axes([0, 0, 1, 1], projection='3d') ax.axis('off') # choose a different color for each trajectory colors = plt.cm.jet(np.linspace(0, 1, N_trajectories)) # set up lines and points lines = sum([ax.plot([], [], [], '-', c=c) for c in colors], []) pts = sum([ax.plot([], [], [], 'o', c=c, ms=4) for c in colors], []) # prepare the axes limits ax.set_xlim((-25, 25)) ax.set_ylim((-35, 35)) ax.set_zlim((5, 55)) # set point-of-view: specified by (altitude degrees, azimuth degrees) ax.view_init(30, 0) # initialization function: plot the background of each frame def init(): for line, pt in zip(lines, pts): line.set_data([], []) line.set_3d_properties([]) pt.set_data([], []) pt.set_3d_properties([]) return lines + pts # animation function: called sequentially def animate(i): # we'll step two time-steps per frame. This leads to nice results. i = (2 * i) % x_t.shape[1] for line, pt, xi in zip(lines, pts, x_t): x, y, z = xi[:i + 1].T line.set_data(x, y) line.set_3d_properties(z) pt.set_data(x[-1:], y[-1:]) pt.set_3d_properties(z[-1:]) ax.view_init(30, 0.3 * i) fig.canvas.draw() return lines + pts return animation.FuncAnimation(fig, animate, init_func=init, frames=frames, interval=interval)
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Plot a 3D visualization of the dynamics of the Lorenz system
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/doc/source/JSAnimation/examples.py#L27-L97
train
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carpyncho/feets
doc/source/JSAnimation/html_writer.py
_included_frames
def _included_frames(frame_list, frame_format): """frame_list should be a list of filenames""" return INCLUDED_FRAMES.format(Nframes=len(frame_list), frame_dir=os.path.dirname(frame_list[0]), frame_format=frame_format)
python
def _included_frames(frame_list, frame_format): """frame_list should be a list of filenames""" return INCLUDED_FRAMES.format(Nframes=len(frame_list), frame_dir=os.path.dirname(frame_list[0]), frame_format=frame_format)
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frame_list should be a list of filenames
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/doc/source/JSAnimation/html_writer.py#L222-L226
train
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carpyncho/feets
doc/source/JSAnimation/html_writer.py
_embedded_frames
def _embedded_frames(frame_list, frame_format): """frame_list should be a list of base64-encoded png files""" template = ' frames[{0}] = "data:image/{1};base64,{2}"\n' embedded = "\n" for i, frame_data in enumerate(frame_list): embedded += template.format(i, frame_format, frame_data.replace('\n', '\\\n')) return embedded
python
def _embedded_frames(frame_list, frame_format): """frame_list should be a list of base64-encoded png files""" template = ' frames[{0}] = "data:image/{1};base64,{2}"\n' embedded = "\n" for i, frame_data in enumerate(frame_list): embedded += template.format(i, frame_format, frame_data.replace('\n', '\\\n')) return embedded
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frame_list should be a list of base64-encoded png files
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/doc/source/JSAnimation/html_writer.py#L229-L236
train
53,345
carpyncho/feets
feets/preprocess.py
remove_noise
def remove_noise(time, magnitude, error, error_limit=3, std_limit=5): """Points within 'std_limit' standard deviations from the mean and with errors greater than 'error_limit' times the error mean are considered as noise and thus are eliminated. """ data, mjd = magnitude, time data_len = len(mjd) error_mean = np.mean(error) error_tolerance = error_limit * (error_mean or 1) data_mean = np.mean(data) data_std = np.std(data) mjd_out, data_out, error_out = [], [], [] for i in range(data_len): is_not_noise = ( error[i] < error_tolerance and (np.absolute(data[i] - data_mean) / data_std) < std_limit) if is_not_noise: mjd_out.append(mjd[i]) data_out.append(data[i]) error_out.append(error[i]) data_out = np.asarray(data_out) mjd_out = np.asarray(mjd_out) error_out = np.asarray(error_out) return mjd_out, data_out, error_out
python
def remove_noise(time, magnitude, error, error_limit=3, std_limit=5): """Points within 'std_limit' standard deviations from the mean and with errors greater than 'error_limit' times the error mean are considered as noise and thus are eliminated. """ data, mjd = magnitude, time data_len = len(mjd) error_mean = np.mean(error) error_tolerance = error_limit * (error_mean or 1) data_mean = np.mean(data) data_std = np.std(data) mjd_out, data_out, error_out = [], [], [] for i in range(data_len): is_not_noise = ( error[i] < error_tolerance and (np.absolute(data[i] - data_mean) / data_std) < std_limit) if is_not_noise: mjd_out.append(mjd[i]) data_out.append(data[i]) error_out.append(error[i]) data_out = np.asarray(data_out) mjd_out = np.asarray(mjd_out) error_out = np.asarray(error_out) return mjd_out, data_out, error_out
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Points within 'std_limit' standard deviations from the mean and with errors greater than 'error_limit' times the error mean are considered as noise and thus are eliminated.
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/preprocess.py#L44-L73
train
53,346
carpyncho/feets
feets/preprocess.py
align
def align(time, time2, magnitude, magnitude2, error, error2): """Synchronizes the light-curves in the two different bands. Returns ------- aligned_time aligned_magnitude aligned_magnitude2 aligned_error aligned_error2 """ error = np.zeros(time.shape) if error is None else error error2 = np.zeros(time2.shape) if error2 is None else error2 # this asume that the first series is the short one sserie = pd.DataFrame({"mag": magnitude, "error": error}, index=time) lserie = pd.DataFrame({"mag": magnitude2, "error": error2}, index=time2) # if the second serie is logest then revert if len(time) > len(time2): sserie, lserie = lserie, sserie # make the merge merged = sserie.join(lserie, how="inner", rsuffix='2') # recreate columns new_time = merged.index.values new_mag, new_mag2 = merged.mag.values, merged.mag2.values new_error, new_error2 = merged.error.values, merged.error2.values if len(time) > len(time2): new_mag, new_mag2 = new_mag2, new_mag new_error, new_error2 = new_error2, new_error return new_time, new_mag, new_mag2, new_error, new_error2
python
def align(time, time2, magnitude, magnitude2, error, error2): """Synchronizes the light-curves in the two different bands. Returns ------- aligned_time aligned_magnitude aligned_magnitude2 aligned_error aligned_error2 """ error = np.zeros(time.shape) if error is None else error error2 = np.zeros(time2.shape) if error2 is None else error2 # this asume that the first series is the short one sserie = pd.DataFrame({"mag": magnitude, "error": error}, index=time) lserie = pd.DataFrame({"mag": magnitude2, "error": error2}, index=time2) # if the second serie is logest then revert if len(time) > len(time2): sserie, lserie = lserie, sserie # make the merge merged = sserie.join(lserie, how="inner", rsuffix='2') # recreate columns new_time = merged.index.values new_mag, new_mag2 = merged.mag.values, merged.mag2.values new_error, new_error2 = merged.error.values, merged.error2.values if len(time) > len(time2): new_mag, new_mag2 = new_mag2, new_mag new_error, new_error2 = new_error2, new_error return new_time, new_mag, new_mag2, new_error, new_error2
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Synchronizes the light-curves in the two different bands. Returns ------- aligned_time aligned_magnitude aligned_magnitude2 aligned_error aligned_error2
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/preprocess.py#L76-L113
train
53,347
carpyncho/feets
feets/datasets/ogle3.py
load_OGLE3_catalog
def load_OGLE3_catalog(): """Return the full list of variables stars of OGLE-3 as a DataFrame """ with bz2.BZ2File(CATALOG_PATH) as bz2fp, warnings.catch_warnings(): warnings.simplefilter("ignore") df = pd.read_table(bz2fp, skiprows=6) df.rename(columns={"# ID": "ID"}, inplace=True) return df
python
def load_OGLE3_catalog(): """Return the full list of variables stars of OGLE-3 as a DataFrame """ with bz2.BZ2File(CATALOG_PATH) as bz2fp, warnings.catch_warnings(): warnings.simplefilter("ignore") df = pd.read_table(bz2fp, skiprows=6) df.rename(columns={"# ID": "ID"}, inplace=True) return df
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Return the full list of variables stars of OGLE-3 as a DataFrame
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/ogle3.py#L144-L152
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carpyncho/feets
feets/datasets/ogle3.py
fetch_OGLE3
def fetch_OGLE3(ogle3_id, data_home=None, metadata=None, download_if_missing=True): """Retrieve a lighte curve from OGLE-3 database Parameters ---------- ogle3_id : str The id of the source (see: ``load_OGLE3_catalog()`` for available sources. data_home : optional, default: None Specify another download and cache folder for the datasets. By default all feets data is stored in '~/feets' subfolders. metadata : bool | None If it's True, the row of the dataframe from ``load_OGLE3_catalog()`` with the metadata of the source are added to the result. download_if_missing : optional, True by default If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site. Returns ------- A Data object. Examples -------- .. code-block:: pycon >>> ds = fetch_OGLE3("OGLE-BLG-LPV-232377") >>> ds Data(id='OGLE-BLG-LPV-232377', ds_name='OGLE-III', bands=('I', 'V')) >>> ds.bands ('I', 'V') >>> ds.data.I LightCurve(time[100], magnitude[100], error[100]) >>> ds.data.I.magnitude array([ 13.816, 13.826, 13.818, 13.812, 13.8 , 13.827, 13.797, 13.82 , 13.804, 13.783, 13.823, 13.8 , 13.84 , 13.817, 13.802, 13.824, 13.822, 13.81 , 13.844, 13.848, 13.813, 13.836, 13.83 , 13.83 , 13.837, 13.811, 13.814, 13.82 , 13.826, 13.822, 13.821, 13.817, 13.813, 13.809, 13.817, 13.836, 13.804, 13.801, 13.813, 13.823, 13.818, 13.831, 13.833, 13.814, 13.814, 13.812, 13.822, 13.814, 13.818, 13.817, 13.8 , 13.804, 13.799, 13.809, 13.815, 13.846, 13.796, 13.791, 13.804, 13.853, 13.839, 13.816, 13.825, 13.81 , 13.8 , 13.807, 13.819, 13.829, 13.844, 13.84 , 13.842, 13.818, 13.801, 13.804, 13.814, 13.821, 13.821, 13.822, 13.82 , 13.803, 13.813, 13.826, 13.855, 13.865, 13.854, 13.828, 13.809, 13.828, 13.833, 13.829, 13.816, 13.82 , 13.827, 13.834, 13.811, 13.817, 13.808, 13.834, 13.814, 13.829]) """ # retrieve the data dir for ogle store_path = _get_OGLE3_data_home(data_home) # the data dir for this lightcurve file_path = os.path.join(store_path, "{}.tar".format(ogle3_id)) # members of the two bands of ogle3 members = {"I": "./{}.I.dat".format(ogle3_id), "V": "./{}.V.dat".format(ogle3_id)} # the url of the lightcurve if download_if_missing: url = URL.format(ogle3_id) base.fetch(url, file_path) bands = [] data = {} with tarfile.TarFile(file_path) as tfp: members_names = tfp.getnames() for band_name, member_name in members.items(): if member_name in members_names: member = tfp.getmember(member_name) src = tfp.extractfile(member) lc = _check_dim(np.loadtxt(src)) data[band_name] = {"time": lc[:, 0], "magnitude": lc[:, 1], "error": lc[:, 2]} bands.append(band_name) if metadata: cat = load_OGLE3_catalog() metadata = cat[cat.ID == ogle3_id].iloc[0].to_dict() del cat return Data( id=ogle3_id, metadata=metadata, ds_name="OGLE-III", description=DESCR, bands=bands, data=data)
python
def fetch_OGLE3(ogle3_id, data_home=None, metadata=None, download_if_missing=True): """Retrieve a lighte curve from OGLE-3 database Parameters ---------- ogle3_id : str The id of the source (see: ``load_OGLE3_catalog()`` for available sources. data_home : optional, default: None Specify another download and cache folder for the datasets. By default all feets data is stored in '~/feets' subfolders. metadata : bool | None If it's True, the row of the dataframe from ``load_OGLE3_catalog()`` with the metadata of the source are added to the result. download_if_missing : optional, True by default If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site. Returns ------- A Data object. Examples -------- .. code-block:: pycon >>> ds = fetch_OGLE3("OGLE-BLG-LPV-232377") >>> ds Data(id='OGLE-BLG-LPV-232377', ds_name='OGLE-III', bands=('I', 'V')) >>> ds.bands ('I', 'V') >>> ds.data.I LightCurve(time[100], magnitude[100], error[100]) >>> ds.data.I.magnitude array([ 13.816, 13.826, 13.818, 13.812, 13.8 , 13.827, 13.797, 13.82 , 13.804, 13.783, 13.823, 13.8 , 13.84 , 13.817, 13.802, 13.824, 13.822, 13.81 , 13.844, 13.848, 13.813, 13.836, 13.83 , 13.83 , 13.837, 13.811, 13.814, 13.82 , 13.826, 13.822, 13.821, 13.817, 13.813, 13.809, 13.817, 13.836, 13.804, 13.801, 13.813, 13.823, 13.818, 13.831, 13.833, 13.814, 13.814, 13.812, 13.822, 13.814, 13.818, 13.817, 13.8 , 13.804, 13.799, 13.809, 13.815, 13.846, 13.796, 13.791, 13.804, 13.853, 13.839, 13.816, 13.825, 13.81 , 13.8 , 13.807, 13.819, 13.829, 13.844, 13.84 , 13.842, 13.818, 13.801, 13.804, 13.814, 13.821, 13.821, 13.822, 13.82 , 13.803, 13.813, 13.826, 13.855, 13.865, 13.854, 13.828, 13.809, 13.828, 13.833, 13.829, 13.816, 13.82 , 13.827, 13.834, 13.811, 13.817, 13.808, 13.834, 13.814, 13.829]) """ # retrieve the data dir for ogle store_path = _get_OGLE3_data_home(data_home) # the data dir for this lightcurve file_path = os.path.join(store_path, "{}.tar".format(ogle3_id)) # members of the two bands of ogle3 members = {"I": "./{}.I.dat".format(ogle3_id), "V": "./{}.V.dat".format(ogle3_id)} # the url of the lightcurve if download_if_missing: url = URL.format(ogle3_id) base.fetch(url, file_path) bands = [] data = {} with tarfile.TarFile(file_path) as tfp: members_names = tfp.getnames() for band_name, member_name in members.items(): if member_name in members_names: member = tfp.getmember(member_name) src = tfp.extractfile(member) lc = _check_dim(np.loadtxt(src)) data[band_name] = {"time": lc[:, 0], "magnitude": lc[:, 1], "error": lc[:, 2]} bands.append(band_name) if metadata: cat = load_OGLE3_catalog() metadata = cat[cat.ID == ogle3_id].iloc[0].to_dict() del cat return Data( id=ogle3_id, metadata=metadata, ds_name="OGLE-III", description=DESCR, bands=bands, data=data)
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Retrieve a lighte curve from OGLE-3 database Parameters ---------- ogle3_id : str The id of the source (see: ``load_OGLE3_catalog()`` for available sources. data_home : optional, default: None Specify another download and cache folder for the datasets. By default all feets data is stored in '~/feets' subfolders. metadata : bool | None If it's True, the row of the dataframe from ``load_OGLE3_catalog()`` with the metadata of the source are added to the result. download_if_missing : optional, True by default If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site. Returns ------- A Data object. Examples -------- .. code-block:: pycon >>> ds = fetch_OGLE3("OGLE-BLG-LPV-232377") >>> ds Data(id='OGLE-BLG-LPV-232377', ds_name='OGLE-III', bands=('I', 'V')) >>> ds.bands ('I', 'V') >>> ds.data.I LightCurve(time[100], magnitude[100], error[100]) >>> ds.data.I.magnitude array([ 13.816, 13.826, 13.818, 13.812, 13.8 , 13.827, 13.797, 13.82 , 13.804, 13.783, 13.823, 13.8 , 13.84 , 13.817, 13.802, 13.824, 13.822, 13.81 , 13.844, 13.848, 13.813, 13.836, 13.83 , 13.83 , 13.837, 13.811, 13.814, 13.82 , 13.826, 13.822, 13.821, 13.817, 13.813, 13.809, 13.817, 13.836, 13.804, 13.801, 13.813, 13.823, 13.818, 13.831, 13.833, 13.814, 13.814, 13.812, 13.822, 13.814, 13.818, 13.817, 13.8 , 13.804, 13.799, 13.809, 13.815, 13.846, 13.796, 13.791, 13.804, 13.853, 13.839, 13.816, 13.825, 13.81 , 13.8 , 13.807, 13.819, 13.829, 13.844, 13.84 , 13.842, 13.818, 13.801, 13.804, 13.814, 13.821, 13.821, 13.822, 13.82 , 13.803, 13.813, 13.826, 13.855, 13.865, 13.854, 13.828, 13.809, 13.828, 13.833, 13.829, 13.816, 13.82 , 13.827, 13.834, 13.811, 13.817, 13.808, 13.834, 13.814, 13.829])
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/ogle3.py#L155-L246
train
53,349
carpyncho/feets
feets/extractors/__init__.py
sort_by_dependencies
def sort_by_dependencies(exts, retry=None): """Calculate the Feature Extractor Resolution Order. """ sorted_ext, features_from_sorted = [], set() pending = [(e, 0) for e in exts] retry = len(exts) * 100 if retry is None else retry while pending: ext, cnt = pending.pop(0) if not isinstance(ext, Extractor) and not issubclass(ext, Extractor): msg = "Only Extractor instances are allowed. Found {}." raise TypeError(msg.format(type(ext))) deps = ext.get_dependencies() if deps.difference(features_from_sorted): if cnt + 1 > retry: msg = "Maximun retry ({}) to sort achieved from extractor {}." raise RuntimeError(msg.format(retry, type(ext))) pending.append((ext, cnt + 1)) else: sorted_ext.append(ext) features_from_sorted.update(ext.get_features()) return tuple(sorted_ext)
python
def sort_by_dependencies(exts, retry=None): """Calculate the Feature Extractor Resolution Order. """ sorted_ext, features_from_sorted = [], set() pending = [(e, 0) for e in exts] retry = len(exts) * 100 if retry is None else retry while pending: ext, cnt = pending.pop(0) if not isinstance(ext, Extractor) and not issubclass(ext, Extractor): msg = "Only Extractor instances are allowed. Found {}." raise TypeError(msg.format(type(ext))) deps = ext.get_dependencies() if deps.difference(features_from_sorted): if cnt + 1 > retry: msg = "Maximun retry ({}) to sort achieved from extractor {}." raise RuntimeError(msg.format(retry, type(ext))) pending.append((ext, cnt + 1)) else: sorted_ext.append(ext) features_from_sorted.update(ext.get_features()) return tuple(sorted_ext)
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Calculate the Feature Extractor Resolution Order.
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/extractors/__init__.py#L98-L121
train
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carpyncho/feets
paper/reports/fats_vs_feets/lomb.py
getSignificance
def getSignificance(wk1, wk2, nout, ofac): """ returns the peak false alarm probabilities Hence the lower is the probability and the more significant is the peak """ expy = exp(-wk2) effm = 2.0*(nout)/ofac sig = effm*expy ind = (sig > 0.01).nonzero() sig[ind] = 1.0-(1.0-expy[ind])**effm return sig
python
def getSignificance(wk1, wk2, nout, ofac): """ returns the peak false alarm probabilities Hence the lower is the probability and the more significant is the peak """ expy = exp(-wk2) effm = 2.0*(nout)/ofac sig = effm*expy ind = (sig > 0.01).nonzero() sig[ind] = 1.0-(1.0-expy[ind])**effm return sig
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returns the peak false alarm probabilities Hence the lower is the probability and the more significant is the peak
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/paper/reports/fats_vs_feets/lomb.py#L200-L209
train
53,351
carpyncho/feets
feets/datasets/base.py
fetch
def fetch(url, dest, force=False): """Retrieve data from an url and store it into dest. Parameters ---------- url: str Link to the remote data dest: str Path where the file must be stored force: bool (default=False) Overwrite if the file exists Returns ------- cached: bool True if the file already exists dest: str The same string of the parameter """ cached = True if force or not os.path.exists(dest): cached = False r = requests.get(url, stream=True) if r.status_code == 200: with open(dest, 'wb') as f: for chunk in r.iter_content(1024): f.write(chunk) return cached, dest
python
def fetch(url, dest, force=False): """Retrieve data from an url and store it into dest. Parameters ---------- url: str Link to the remote data dest: str Path where the file must be stored force: bool (default=False) Overwrite if the file exists Returns ------- cached: bool True if the file already exists dest: str The same string of the parameter """ cached = True if force or not os.path.exists(dest): cached = False r = requests.get(url, stream=True) if r.status_code == 200: with open(dest, 'wb') as f: for chunk in r.iter_content(1024): f.write(chunk) return cached, dest
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Retrieve data from an url and store it into dest. Parameters ---------- url: str Link to the remote data dest: str Path where the file must be stored force: bool (default=False) Overwrite if the file exists Returns ------- cached: bool True if the file already exists dest: str The same string of the parameter
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/base.py#L99-L129
train
53,352
carpyncho/feets
feets/datasets/synthetic.py
create_random
def create_random(magf, magf_params, errf, errf_params, timef=np.linspace, timef_params=None, size=DEFAULT_SIZE, id=None, ds_name=DS_NAME, description=DESCRIPTION, bands=BANDS, metadata=METADATA): """Generate a data with any given random function. Parameters ---------- magf : callable Function to generate the magnitudes. magf_params : dict-like Parameters to feed the `magf` function. errf : callable Function to generate the magnitudes. errf_params : dict-like Parameters to feed the `errf` function. timef : callable, (default=numpy.linspace) Function to generate the times. timef_params : dict-like or None, (default={"start": 0., "stop": 1.}) Parameters to feed the `timef` callable. size : int (default=10000) Number of obervation of the light curves id : object (default=None) Id of the created data. ds_name : str (default="feets-synthetic") Name of the dataset description : str (default="Lightcurve created with random numbers") Description of the data bands : tuple of strings (default=("B", "V")) The bands to be created metadata : dict-like or None (default=None) The metadata of the created data Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> from numpy import random >>> create_random( ... magf=random.normal, magf_params={"loc": 0, "scale": 1}, ... errf=random.normal, errf_params={"loc": 0, "scale": 0.008}) Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) """ timef_params = ( {"start": 0., "stop": 1.} if timef_params is None else timef_params.copy()) timef_params.update(num=size) magf_params = magf_params.copy() magf_params.update(size=size) errf_params = errf_params.copy() errf_params.update(size=size) data = {} for band in bands: data[band] = { "time": timef(**timef_params), "magnitude": magf(**magf_params), "error": errf(**errf_params)} return Data( id=id, ds_name=ds_name, description=description, bands=bands, metadata=metadata, data=data)
python
def create_random(magf, magf_params, errf, errf_params, timef=np.linspace, timef_params=None, size=DEFAULT_SIZE, id=None, ds_name=DS_NAME, description=DESCRIPTION, bands=BANDS, metadata=METADATA): """Generate a data with any given random function. Parameters ---------- magf : callable Function to generate the magnitudes. magf_params : dict-like Parameters to feed the `magf` function. errf : callable Function to generate the magnitudes. errf_params : dict-like Parameters to feed the `errf` function. timef : callable, (default=numpy.linspace) Function to generate the times. timef_params : dict-like or None, (default={"start": 0., "stop": 1.}) Parameters to feed the `timef` callable. size : int (default=10000) Number of obervation of the light curves id : object (default=None) Id of the created data. ds_name : str (default="feets-synthetic") Name of the dataset description : str (default="Lightcurve created with random numbers") Description of the data bands : tuple of strings (default=("B", "V")) The bands to be created metadata : dict-like or None (default=None) The metadata of the created data Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> from numpy import random >>> create_random( ... magf=random.normal, magf_params={"loc": 0, "scale": 1}, ... errf=random.normal, errf_params={"loc": 0, "scale": 0.008}) Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) """ timef_params = ( {"start": 0., "stop": 1.} if timef_params is None else timef_params.copy()) timef_params.update(num=size) magf_params = magf_params.copy() magf_params.update(size=size) errf_params = errf_params.copy() errf_params.update(size=size) data = {} for band in bands: data[band] = { "time": timef(**timef_params), "magnitude": magf(**magf_params), "error": errf(**errf_params)} return Data( id=id, ds_name=ds_name, description=description, bands=bands, metadata=metadata, data=data)
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Generate a data with any given random function. Parameters ---------- magf : callable Function to generate the magnitudes. magf_params : dict-like Parameters to feed the `magf` function. errf : callable Function to generate the magnitudes. errf_params : dict-like Parameters to feed the `errf` function. timef : callable, (default=numpy.linspace) Function to generate the times. timef_params : dict-like or None, (default={"start": 0., "stop": 1.}) Parameters to feed the `timef` callable. size : int (default=10000) Number of obervation of the light curves id : object (default=None) Id of the created data. ds_name : str (default="feets-synthetic") Name of the dataset description : str (default="Lightcurve created with random numbers") Description of the data bands : tuple of strings (default=("B", "V")) The bands to be created metadata : dict-like or None (default=None) The metadata of the created data Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> from numpy import random >>> create_random( ... magf=random.normal, magf_params={"loc": 0, "scale": 1}, ... errf=random.normal, errf_params={"loc": 0, "scale": 0.008}) Data(id=None, ds_name='feets-synthetic', bands=('B', 'V'))
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/synthetic.py#L63-L135
train
53,353
carpyncho/feets
feets/datasets/synthetic.py
create_normal
def create_normal(mu=0., sigma=1., mu_err=0., sigma_err=1., seed=None, **kwargs): """Generate a data with magnitudes that follows a Gaussian distribution. Also their errors are gaussian. Parameters ---------- mu : float (default=0) Mean of the gaussian distribution of magnitudes sigma : float (default=1) Standar deviation of the gaussian distribution of magnitude errors mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = create_normal(0, 1, 0, .0008, seed=42) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) >>> ds.data.B LightCurve(time[10000], magnitude[10000], error[10000]) >>> ds.data.B.time array([ 0.00000000e+00, 1.00010001e-04, 2.00020002e-04, ..., 9.99799980e-01, 9.99899990e-01, 1.00000000e+00]) """ random = np.random.RandomState(seed) return create_random( magf=random.normal, magf_params={"loc": mu, "scale": sigma}, errf=random.normal, errf_params={"loc": mu_err, "scale": sigma_err}, **kwargs)
python
def create_normal(mu=0., sigma=1., mu_err=0., sigma_err=1., seed=None, **kwargs): """Generate a data with magnitudes that follows a Gaussian distribution. Also their errors are gaussian. Parameters ---------- mu : float (default=0) Mean of the gaussian distribution of magnitudes sigma : float (default=1) Standar deviation of the gaussian distribution of magnitude errors mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = create_normal(0, 1, 0, .0008, seed=42) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) >>> ds.data.B LightCurve(time[10000], magnitude[10000], error[10000]) >>> ds.data.B.time array([ 0.00000000e+00, 1.00010001e-04, 2.00020002e-04, ..., 9.99799980e-01, 9.99899990e-01, 1.00000000e+00]) """ random = np.random.RandomState(seed) return create_random( magf=random.normal, magf_params={"loc": mu, "scale": sigma}, errf=random.normal, errf_params={"loc": mu_err, "scale": sigma_err}, **kwargs)
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Generate a data with magnitudes that follows a Gaussian distribution. Also their errors are gaussian. Parameters ---------- mu : float (default=0) Mean of the gaussian distribution of magnitudes sigma : float (default=1) Standar deviation of the gaussian distribution of magnitude errors mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = create_normal(0, 1, 0, .0008, seed=42) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) >>> ds.data.B LightCurve(time[10000], magnitude[10000], error[10000]) >>> ds.data.B.time array([ 0.00000000e+00, 1.00010001e-04, 2.00020002e-04, ..., 9.99799980e-01, 9.99899990e-01, 1.00000000e+00])
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/synthetic.py#L138-L190
train
53,354
carpyncho/feets
feets/datasets/synthetic.py
create_uniform
def create_uniform(low=0., high=1., mu_err=0., sigma_err=1., seed=None, **kwargs): """Generate a data with magnitudes that follows a uniform distribution; the error instead are gaussian. Parameters ---------- low : float, optional Lower boundary of the output interval. All values generated will be greater than or equal to low. The default value is 0. high : float, optional Upper boundary of the output interval. All values generated will be less than high. The default value is 1.0. mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = synthetic.create_uniform(1, 2, 0, .0008, 42) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) >>> ds.data.B.magnitude array([ 1.37454012, 1.95071431, 1.73199394, ..., 1.94670792, 1.39748799, 1.2171404 ]) """ random = np.random.RandomState(seed) return create_random( magf=random.uniform, magf_params={"low": low, "high": high}, errf=random.normal, errf_params={"loc": mu_err, "scale": sigma_err}, **kwargs)
python
def create_uniform(low=0., high=1., mu_err=0., sigma_err=1., seed=None, **kwargs): """Generate a data with magnitudes that follows a uniform distribution; the error instead are gaussian. Parameters ---------- low : float, optional Lower boundary of the output interval. All values generated will be greater than or equal to low. The default value is 0. high : float, optional Upper boundary of the output interval. All values generated will be less than high. The default value is 1.0. mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = synthetic.create_uniform(1, 2, 0, .0008, 42) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) >>> ds.data.B.magnitude array([ 1.37454012, 1.95071431, 1.73199394, ..., 1.94670792, 1.39748799, 1.2171404 ]) """ random = np.random.RandomState(seed) return create_random( magf=random.uniform, magf_params={"low": low, "high": high}, errf=random.normal, errf_params={"loc": mu_err, "scale": sigma_err}, **kwargs)
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Generate a data with magnitudes that follows a uniform distribution; the error instead are gaussian. Parameters ---------- low : float, optional Lower boundary of the output interval. All values generated will be greater than or equal to low. The default value is 0. high : float, optional Upper boundary of the output interval. All values generated will be less than high. The default value is 1.0. mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = synthetic.create_uniform(1, 2, 0, .0008, 42) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('B', 'V')) >>> ds.data.B.magnitude array([ 1.37454012, 1.95071431, 1.73199394, ..., 1.94670792, 1.39748799, 1.2171404 ])
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/synthetic.py#L193-L244
train
53,355
carpyncho/feets
feets/datasets/synthetic.py
create_periodic
def create_periodic(mu_err=0., sigma_err=1., seed=None, **kwargs): """Generate a data with magnitudes with periodic variability distribution; the error instead are gaussian. Parameters ---------- mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = synthetic.create_periodic(bands=["Ks"]) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('Ks',)) >>> ds.data.Ks.magnitude array([ 0.95428053, 0.73022685, 0.03005121, ..., -0.26305297, 2.57880082, 1.03376863]) """ random = np.random.RandomState(seed) size = kwargs.get("size", DEFAULT_SIZE) times, mags, errors = [], [], [] for b in kwargs.get("bands", BANDS): time = 100 * random.rand(size) error = random.normal(size=size, loc=mu_err, scale=sigma_err) mag = np.sin(2 * np.pi * time) + error * random.randn(size) times.append(time) errors.append(error) mags.append(mag) times, mags, errors = iter(times), iter(mags), iter(errors) return create_random( magf=lambda **k: next(mags), magf_params={}, errf=lambda **k: next(errors), errf_params={}, timef=lambda **k: next(times), timef_params={}, **kwargs)
python
def create_periodic(mu_err=0., sigma_err=1., seed=None, **kwargs): """Generate a data with magnitudes with periodic variability distribution; the error instead are gaussian. Parameters ---------- mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = synthetic.create_periodic(bands=["Ks"]) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('Ks',)) >>> ds.data.Ks.magnitude array([ 0.95428053, 0.73022685, 0.03005121, ..., -0.26305297, 2.57880082, 1.03376863]) """ random = np.random.RandomState(seed) size = kwargs.get("size", DEFAULT_SIZE) times, mags, errors = [], [], [] for b in kwargs.get("bands", BANDS): time = 100 * random.rand(size) error = random.normal(size=size, loc=mu_err, scale=sigma_err) mag = np.sin(2 * np.pi * time) + error * random.randn(size) times.append(time) errors.append(error) mags.append(mag) times, mags, errors = iter(times), iter(mags), iter(errors) return create_random( magf=lambda **k: next(mags), magf_params={}, errf=lambda **k: next(errors), errf_params={}, timef=lambda **k: next(times), timef_params={}, **kwargs)
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Generate a data with magnitudes with periodic variability distribution; the error instead are gaussian. Parameters ---------- mu_err : float (default=0) Mean of the gaussian distribution of magnitudes sigma_err : float (default=1) Standar deviation of the gaussian distribution of magnitude errorrs seed : {None, int, array_like}, optional Random seed used to initialize the pseudo-random number generator. Can be any integer between 0 and 2**32 - 1 inclusive, an array (or other sequence) of such integers, or None (the default). If seed is None, then RandomState will try to read data from /dev/urandom (or the Windows analogue) if available or seed from the clock otherwise. kwargs : optional extra arguments for create_random. Returns ------- data A Data object with a random lightcurves. Examples -------- .. code-block:: pycon >>> ds = synthetic.create_periodic(bands=["Ks"]) >>> ds Data(id=None, ds_name='feets-synthetic', bands=('Ks',)) >>> ds.data.Ks.magnitude array([ 0.95428053, 0.73022685, 0.03005121, ..., -0.26305297, 2.57880082, 1.03376863])
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/datasets/synthetic.py#L247-L305
train
53,356
carpyncho/feets
feets/libs/ls_fap.py
pdf_single
def pdf_single(z, N, normalization, dH=1, dK=3): """Probability density function for Lomb-Scargle periodogram Compute the expected probability density function of the periodogram for the null hypothesis - i.e. data consisting of Gaussian noise. Parameters ---------- z : array-like the periodogram value N : int the number of data points from which the periodogram was computed normalization : string The periodogram normalization. Must be one of ['standard', 'model', 'log', 'psd'] dH, dK : integers (optional) The number of parameters in the null hypothesis and the model Returns ------- pdf : np.ndarray The expected probability density function Notes ----- For normalization='psd', the distribution can only be computed for periodograms constructed with errors specified. All expressions used here are adapted from Table 1 of Baluev 2008 [1]_. References ---------- .. [1] Baluev, R.V. MNRAS 385, 1279 (2008) """ if dK - dH != 2: raise NotImplementedError("Degrees of freedom != 2") Nk = N - dK if normalization == 'psd': return np.exp(-z) elif normalization == 'standard': return 0.5 * Nk * (1 - z) ** (0.5 * Nk - 1) elif normalization == 'model': return 0.5 * Nk * (1 + z) ** (-0.5 * Nk - 1) elif normalization == 'log': return 0.5 * Nk * np.exp(-0.5 * Nk * z) else: raise ValueError("normalization='{0}' is not recognized" "".format(normalization))
python
def pdf_single(z, N, normalization, dH=1, dK=3): """Probability density function for Lomb-Scargle periodogram Compute the expected probability density function of the periodogram for the null hypothesis - i.e. data consisting of Gaussian noise. Parameters ---------- z : array-like the periodogram value N : int the number of data points from which the periodogram was computed normalization : string The periodogram normalization. Must be one of ['standard', 'model', 'log', 'psd'] dH, dK : integers (optional) The number of parameters in the null hypothesis and the model Returns ------- pdf : np.ndarray The expected probability density function Notes ----- For normalization='psd', the distribution can only be computed for periodograms constructed with errors specified. All expressions used here are adapted from Table 1 of Baluev 2008 [1]_. References ---------- .. [1] Baluev, R.V. MNRAS 385, 1279 (2008) """ if dK - dH != 2: raise NotImplementedError("Degrees of freedom != 2") Nk = N - dK if normalization == 'psd': return np.exp(-z) elif normalization == 'standard': return 0.5 * Nk * (1 - z) ** (0.5 * Nk - 1) elif normalization == 'model': return 0.5 * Nk * (1 + z) ** (-0.5 * Nk - 1) elif normalization == 'log': return 0.5 * Nk * np.exp(-0.5 * Nk * z) else: raise ValueError("normalization='{0}' is not recognized" "".format(normalization))
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Probability density function for Lomb-Scargle periodogram Compute the expected probability density function of the periodogram for the null hypothesis - i.e. data consisting of Gaussian noise. Parameters ---------- z : array-like the periodogram value N : int the number of data points from which the periodogram was computed normalization : string The periodogram normalization. Must be one of ['standard', 'model', 'log', 'psd'] dH, dK : integers (optional) The number of parameters in the null hypothesis and the model Returns ------- pdf : np.ndarray The expected probability density function Notes ----- For normalization='psd', the distribution can only be computed for periodograms constructed with errors specified. All expressions used here are adapted from Table 1 of Baluev 2008 [1]_. References ---------- .. [1] Baluev, R.V. MNRAS 385, 1279 (2008)
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/libs/ls_fap.py#L31-L78
train
53,357
carpyncho/feets
feets/libs/ls_fap.py
cdf_single
def cdf_single(z, N, normalization, dH=1, dK=3): """Cumulative distribution for the Lomb-Scargle periodogram Compute the expected cumulative distribution of the periodogram for the null hypothesis - i.e. data consisting of Gaussian noise. Parameters ---------- z : array-like the periodogram value N : int the number of data points from which the periodogram was computed normalization : string The periodogram normalization. Must be one of ['standard', 'model', 'log', 'psd'] dH, dK : integers (optional) The number of parameters in the null hypothesis and the model Returns ------- cdf : np.ndarray The expected cumulative distribution function Notes ----- For normalization='psd', the distribution can only be computed for periodograms constructed with errors specified. All expressions used here are adapted from Table 1 of Baluev 2008 [1]_. References ---------- .. [1] Baluev, R.V. MNRAS 385, 1279 (2008) """ return 1 - fap_single(z, N, normalization=normalization, dH=dH, dK=dK)
python
def cdf_single(z, N, normalization, dH=1, dK=3): """Cumulative distribution for the Lomb-Scargle periodogram Compute the expected cumulative distribution of the periodogram for the null hypothesis - i.e. data consisting of Gaussian noise. Parameters ---------- z : array-like the periodogram value N : int the number of data points from which the periodogram was computed normalization : string The periodogram normalization. Must be one of ['standard', 'model', 'log', 'psd'] dH, dK : integers (optional) The number of parameters in the null hypothesis and the model Returns ------- cdf : np.ndarray The expected cumulative distribution function Notes ----- For normalization='psd', the distribution can only be computed for periodograms constructed with errors specified. All expressions used here are adapted from Table 1 of Baluev 2008 [1]_. References ---------- .. [1] Baluev, R.V. MNRAS 385, 1279 (2008) """ return 1 - fap_single(z, N, normalization=normalization, dH=dH, dK=dK)
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/libs/ls_fap.py#L132-L166
train
53,358
carpyncho/feets
feets/libs/ls_fap.py
fap_simple
def fap_simple(Z, fmax, t, y, dy, normalization='standard'): """False Alarm Probability based on estimated number of indep frequencies """ N = len(t) T = max(t) - min(t) N_eff = fmax * T p_s = cdf_single(Z, N, normalization=normalization) return 1 - p_s ** N_eff
python
def fap_simple(Z, fmax, t, y, dy, normalization='standard'): """False Alarm Probability based on estimated number of indep frequencies """ N = len(t) T = max(t) - min(t) N_eff = fmax * T p_s = cdf_single(Z, N, normalization=normalization) return 1 - p_s ** N_eff
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False Alarm Probability based on estimated number of indep frequencies
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/libs/ls_fap.py#L196-L204
train
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carpyncho/feets
feets/libs/ls_fap.py
fap_davies
def fap_davies(Z, fmax, t, y, dy, normalization='standard'): """Davies upper-bound to the false alarm probability (Eqn 5 of Baluev 2008) """ N = len(t) fap_s = fap_single(Z, N, normalization=normalization) tau = tau_davies(Z, fmax, t, y, dy, normalization=normalization) return fap_s + tau
python
def fap_davies(Z, fmax, t, y, dy, normalization='standard'): """Davies upper-bound to the false alarm probability (Eqn 5 of Baluev 2008) """ N = len(t) fap_s = fap_single(Z, N, normalization=normalization) tau = tau_davies(Z, fmax, t, y, dy, normalization=normalization) return fap_s + tau
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Davies upper-bound to the false alarm probability (Eqn 5 of Baluev 2008)
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/libs/ls_fap.py#L207-L215
train
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carpyncho/feets
feets/libs/ls_fap.py
fap_baluev
def fap_baluev(Z, fmax, t, y, dy, normalization='standard'): """Alias-free approximation to false alarm probability (Eqn 6 of Baluev 2008) """ cdf = cdf_single(Z, len(t), normalization) tau = tau_davies(Z, fmax, t, y, dy, normalization=normalization) return 1 - cdf * np.exp(-tau)
python
def fap_baluev(Z, fmax, t, y, dy, normalization='standard'): """Alias-free approximation to false alarm probability (Eqn 6 of Baluev 2008) """ cdf = cdf_single(Z, len(t), normalization) tau = tau_davies(Z, fmax, t, y, dy, normalization=normalization) return 1 - cdf * np.exp(-tau)
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/libs/ls_fap.py#L218-L225
train
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carpyncho/feets
feets/libs/ls_fap.py
false_alarm_probability
def false_alarm_probability(Z, fmax, t, y, dy, normalization, method='baluev', method_kwds=None): """Approximate the False Alarm Probability Parameters ---------- TODO Returns ------- TODO """ if method not in METHODS: raise ValueError("Unrecognized method: {0}".format(method)) method = METHODS[method] method_kwds = method_kwds or {} return method(Z, fmax, t, y, dy, normalization, **method_kwds)
python
def false_alarm_probability(Z, fmax, t, y, dy, normalization, method='baluev', method_kwds=None): """Approximate the False Alarm Probability Parameters ---------- TODO Returns ------- TODO """ if method not in METHODS: raise ValueError("Unrecognized method: {0}".format(method)) method = METHODS[method] method_kwds = method_kwds or {} return method(Z, fmax, t, y, dy, normalization, **method_kwds)
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Approximate the False Alarm Probability Parameters ---------- TODO Returns ------- TODO
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/libs/ls_fap.py#L250-L267
train
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carpyncho/feets
doc/source/JSAnimation/IPython_display.py
anim_to_html
def anim_to_html(anim, fps=None, embed_frames=True, default_mode='loop'): """Generate HTML representation of the animation""" if fps is None and hasattr(anim, '_interval'): # Convert interval in ms to frames per second fps = 1000. / anim._interval plt.close(anim._fig) if hasattr(anim, "_html_representation"): return anim._html_representation else: # tempfile can't be used here: we need a filename, and this # fails on windows. Instead, we use a custom filename generator #with tempfile.NamedTemporaryFile(suffix='.html') as f: with _NameOnlyTemporaryFile(suffix='.html') as f: anim.save(f.name, writer=HTMLWriter(fps=fps, embed_frames=embed_frames, default_mode=default_mode)) html = open(f.name).read() anim._html_representation = html return html
python
def anim_to_html(anim, fps=None, embed_frames=True, default_mode='loop'): """Generate HTML representation of the animation""" if fps is None and hasattr(anim, '_interval'): # Convert interval in ms to frames per second fps = 1000. / anim._interval plt.close(anim._fig) if hasattr(anim, "_html_representation"): return anim._html_representation else: # tempfile can't be used here: we need a filename, and this # fails on windows. Instead, we use a custom filename generator #with tempfile.NamedTemporaryFile(suffix='.html') as f: with _NameOnlyTemporaryFile(suffix='.html') as f: anim.save(f.name, writer=HTMLWriter(fps=fps, embed_frames=embed_frames, default_mode=default_mode)) html = open(f.name).read() anim._html_representation = html return html
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/doc/source/JSAnimation/IPython_display.py#L60-L80
train
53,363
carpyncho/feets
doc/source/JSAnimation/IPython_display.py
display_animation
def display_animation(anim, **kwargs): """Display the animation with an IPython HTML object""" from IPython.display import HTML return HTML(anim_to_html(anim, **kwargs))
python
def display_animation(anim, **kwargs): """Display the animation with an IPython HTML object""" from IPython.display import HTML return HTML(anim_to_html(anim, **kwargs))
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/doc/source/JSAnimation/IPython_display.py#L83-L86
train
53,364
carpyncho/feets
feets/utils.py
indent
def indent(s, c=" ", n=4): """Indent the string 's' with the character 'c', 'n' times. Parameters ---------- s : str String to indent c : str, default space String to use as indentation n : int, default 4 Number of chars to indent """ indentation = c * n return "\n".join([indentation + l for l in s.splitlines()])
python
def indent(s, c=" ", n=4): """Indent the string 's' with the character 'c', 'n' times. Parameters ---------- s : str String to indent c : str, default space String to use as indentation n : int, default 4 Number of chars to indent """ indentation = c * n return "\n".join([indentation + l for l in s.splitlines()])
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Indent the string 's' with the character 'c', 'n' times. Parameters ---------- s : str String to indent c : str, default space String to use as indentation n : int, default 4 Number of chars to indent
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53bdfb73b53845561914fc1f756e0c2377b9b76b
https://github.com/carpyncho/feets/blob/53bdfb73b53845561914fc1f756e0c2377b9b76b/feets/utils.py#L37-L52
train
53,365
andersinno/hayes
hayes/ext/date_tail.py
generate_date_tail_boost_queries
def generate_date_tail_boost_queries( field, timedeltas_and_boosts, relative_to=None): """ Generate a list of RangeQueries usable to boost the scores of more recent documents. Example: ``` queries = generate_date_tail_boost_queries("publish_date", { timedelta(days=90): 1, timedelta(days=30): 2, timedelta(days=10): 4, }) s = Search(BoolQuery(must=..., should=queries)) # ... ``` Refs: http://elasticsearch-users.115913.n3.nabble.com/Boost-recent-documents-td2126107.html#a2126317 :param field: field name to generate the queries against :param timedeltas_and_boosts: dictionary of timedelta instances and their boosts. Negative or zero boost values will not generate rangequeries. :type timedeltas_and_boosts: dict[timedelta, float] :param relative_to: Relative to this datetime (may be None for "now") :return: List of RangeQueries """ relative_to = relative_to or datetime.datetime.now() times = {} for timedelta, boost in timedeltas_and_boosts.items(): date = (relative_to - timedelta).date() times[date] = boost times = sorted(times.items(), key=lambda i: i[0]) queries = [] for (x, time) in enumerate(times): kwargs = {"field": field, "boost": time[1]} if x == 0: kwargs["lte"] = time[0] else: kwargs["gt"] = time[0] if x < len(times) - 1: kwargs["lte"] = times[x + 1][0] if kwargs["boost"] > 0: q = RangeQuery() q.add_range(**kwargs) queries.append(q) return queries
python
def generate_date_tail_boost_queries( field, timedeltas_and_boosts, relative_to=None): """ Generate a list of RangeQueries usable to boost the scores of more recent documents. Example: ``` queries = generate_date_tail_boost_queries("publish_date", { timedelta(days=90): 1, timedelta(days=30): 2, timedelta(days=10): 4, }) s = Search(BoolQuery(must=..., should=queries)) # ... ``` Refs: http://elasticsearch-users.115913.n3.nabble.com/Boost-recent-documents-td2126107.html#a2126317 :param field: field name to generate the queries against :param timedeltas_and_boosts: dictionary of timedelta instances and their boosts. Negative or zero boost values will not generate rangequeries. :type timedeltas_and_boosts: dict[timedelta, float] :param relative_to: Relative to this datetime (may be None for "now") :return: List of RangeQueries """ relative_to = relative_to or datetime.datetime.now() times = {} for timedelta, boost in timedeltas_and_boosts.items(): date = (relative_to - timedelta).date() times[date] = boost times = sorted(times.items(), key=lambda i: i[0]) queries = [] for (x, time) in enumerate(times): kwargs = {"field": field, "boost": time[1]} if x == 0: kwargs["lte"] = time[0] else: kwargs["gt"] = time[0] if x < len(times) - 1: kwargs["lte"] = times[x + 1][0] if kwargs["boost"] > 0: q = RangeQuery() q.add_range(**kwargs) queries.append(q) return queries
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88d1f6b3e0cd993d9d9fc136506bd01165fea64b
https://github.com/andersinno/hayes/blob/88d1f6b3e0cd993d9d9fc136506bd01165fea64b/hayes/ext/date_tail.py#L7-L58
train
53,366
andersinno/hayes
hayes/utils.py
batch_iterable
def batch_iterable(iterable, count): """ Yield batches of `count` items from the given iterable. >>> for x in batch([1, 2, 3, 4, 5, 6, 7], 3): >>> print(x) [1, 2, 3] [4, 5, 6] [7] :param iterable: An iterable :type iterable: Iterable :param count: Number of items per batch. If <= 0, nothing is yielded. :type count: int :return: Iterable of lists of items :rtype: Iterable[list[object]] """ if count <= 0: return current_batch = [] for item in iterable: if len(current_batch) == count: yield current_batch current_batch = [] current_batch.append(item) if current_batch: yield current_batch
python
def batch_iterable(iterable, count): """ Yield batches of `count` items from the given iterable. >>> for x in batch([1, 2, 3, 4, 5, 6, 7], 3): >>> print(x) [1, 2, 3] [4, 5, 6] [7] :param iterable: An iterable :type iterable: Iterable :param count: Number of items per batch. If <= 0, nothing is yielded. :type count: int :return: Iterable of lists of items :rtype: Iterable[list[object]] """ if count <= 0: return current_batch = [] for item in iterable: if len(current_batch) == count: yield current_batch current_batch = [] current_batch.append(item) if current_batch: yield current_batch
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88d1f6b3e0cd993d9d9fc136506bd01165fea64b
https://github.com/andersinno/hayes/blob/88d1f6b3e0cd993d9d9fc136506bd01165fea64b/hayes/utils.py#L31-L57
train
53,367
ipython/ipynb
ipynb/utils.py
validate_nb
def validate_nb(nb): """ Validate that given notebook JSON is importable - Check for nbformat == 4 - Check that language is python Do not re-implement nbformat here :D """ if nb['nbformat'] != 4: return False language_name = (nb.get('metadata', {}) .get('kernelspec', {}) .get('language', '').lower()) return language_name == 'python'
python
def validate_nb(nb): """ Validate that given notebook JSON is importable - Check for nbformat == 4 - Check that language is python Do not re-implement nbformat here :D """ if nb['nbformat'] != 4: return False language_name = (nb.get('metadata', {}) .get('kernelspec', {}) .get('language', '').lower()) return language_name == 'python'
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Validate that given notebook JSON is importable - Check for nbformat == 4 - Check that language is python Do not re-implement nbformat here :D
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2f1526a447104d7d7b97e2a8ab66bee8d2da90ad
https://github.com/ipython/ipynb/blob/2f1526a447104d7d7b97e2a8ab66bee8d2da90ad/ipynb/utils.py#L25-L40
train
53,368
ipython/ipynb
ipynb/utils.py
filter_ast
def filter_ast(module_ast): """ Filters a given module ast, removing non-whitelisted nodes It allows only the following top level items: - imports - function definitions - class definitions - top level assignments where all the targets on the LHS are all caps """ def node_predicate(node): """ Return true if given node is whitelisted """ for an in ALLOWED_NODES: if isinstance(node, an): return True # Recurse through Assign node LHS targets when an id is not specified, # otherwise check that the id is uppercase if isinstance(node, ast.Assign): return all([node_predicate(t) for t in node.targets if not hasattr(t, 'id')]) \ and all([t.id.isupper() for t in node.targets if hasattr(t, 'id')]) return False module_ast.body = [n for n in module_ast.body if node_predicate(n)] return module_ast
python
def filter_ast(module_ast): """ Filters a given module ast, removing non-whitelisted nodes It allows only the following top level items: - imports - function definitions - class definitions - top level assignments where all the targets on the LHS are all caps """ def node_predicate(node): """ Return true if given node is whitelisted """ for an in ALLOWED_NODES: if isinstance(node, an): return True # Recurse through Assign node LHS targets when an id is not specified, # otherwise check that the id is uppercase if isinstance(node, ast.Assign): return all([node_predicate(t) for t in node.targets if not hasattr(t, 'id')]) \ and all([t.id.isupper() for t in node.targets if hasattr(t, 'id')]) return False module_ast.body = [n for n in module_ast.body if node_predicate(n)] return module_ast
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2f1526a447104d7d7b97e2a8ab66bee8d2da90ad
https://github.com/ipython/ipynb/blob/2f1526a447104d7d7b97e2a8ab66bee8d2da90ad/ipynb/utils.py#L43-L70
train
53,369
ipython/ipynb
ipynb/utils.py
code_from_ipynb
def code_from_ipynb(nb, markdown=False): """ Get the code for a given notebook nb is passed in as a dictionary that's a parsed ipynb file """ code = PREAMBLE for cell in nb['cells']: if cell['cell_type'] == 'code': # transform the input to executable Python code += ''.join(cell['source']) if cell['cell_type'] == 'markdown': code += '\n# ' + '# '.join(cell['source']) # We want a blank newline after each cell's output. # And the last line of source doesn't have a newline usually. code += '\n\n' return code
python
def code_from_ipynb(nb, markdown=False): """ Get the code for a given notebook nb is passed in as a dictionary that's a parsed ipynb file """ code = PREAMBLE for cell in nb['cells']: if cell['cell_type'] == 'code': # transform the input to executable Python code += ''.join(cell['source']) if cell['cell_type'] == 'markdown': code += '\n# ' + '# '.join(cell['source']) # We want a blank newline after each cell's output. # And the last line of source doesn't have a newline usually. code += '\n\n' return code
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2f1526a447104d7d7b97e2a8ab66bee8d2da90ad
https://github.com/ipython/ipynb/blob/2f1526a447104d7d7b97e2a8ab66bee8d2da90ad/ipynb/utils.py#L72-L88
train
53,370
ipython/ipynb
ipynb/fs/finder.py
FSFinder._get_paths
def _get_paths(self, fullname): """ Generate ordered list of paths we should look for fullname module in """ real_path = os.path.join(*fullname[len(self.package_prefix):].split('.')) for base_path in sys.path: if base_path == '': # Empty string means process's cwd base_path = os.getcwd() path = os.path.join(base_path, real_path) yield path + '.ipynb' yield path + '.py' yield os.path.join(path, '__init__.ipynb') yield os.path.join(path, '__init__.py')
python
def _get_paths(self, fullname): """ Generate ordered list of paths we should look for fullname module in """ real_path = os.path.join(*fullname[len(self.package_prefix):].split('.')) for base_path in sys.path: if base_path == '': # Empty string means process's cwd base_path = os.getcwd() path = os.path.join(base_path, real_path) yield path + '.ipynb' yield path + '.py' yield os.path.join(path, '__init__.ipynb') yield os.path.join(path, '__init__.py')
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2f1526a447104d7d7b97e2a8ab66bee8d2da90ad
https://github.com/ipython/ipynb/blob/2f1526a447104d7d7b97e2a8ab66bee8d2da90ad/ipynb/fs/finder.py#L24-L37
train
53,371
ipython/ipynb
ipynb/fs/finder.py
FSFinder.find_spec
def find_spec(self, fullname, path, target=None): """ Claims modules that are under ipynb.fs """ if fullname.startswith(self.package_prefix): for path in self._get_paths(fullname): if os.path.exists(path): return ModuleSpec( name=fullname, loader=self.loader_class(fullname, path), origin=path, is_package=(path.endswith('__init__.ipynb') or path.endswith('__init__.py')), )
python
def find_spec(self, fullname, path, target=None): """ Claims modules that are under ipynb.fs """ if fullname.startswith(self.package_prefix): for path in self._get_paths(fullname): if os.path.exists(path): return ModuleSpec( name=fullname, loader=self.loader_class(fullname, path), origin=path, is_package=(path.endswith('__init__.ipynb') or path.endswith('__init__.py')), )
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Claims modules that are under ipynb.fs
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2f1526a447104d7d7b97e2a8ab66bee8d2da90ad
https://github.com/ipython/ipynb/blob/2f1526a447104d7d7b97e2a8ab66bee8d2da90ad/ipynb/fs/finder.py#L39-L51
train
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sixty-north/python-transducers
transducer/_util.py
coroutine
def coroutine(func): """Decorator for priming generator-based coroutines. """ @wraps(func) def start(*args, **kwargs): g = func(*args, **kwargs) next(g) return g return start
python
def coroutine(func): """Decorator for priming generator-based coroutines. """ @wraps(func) def start(*args, **kwargs): g = func(*args, **kwargs) next(g) return g return start
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/_util.py#L16-L25
train
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sixty-north/python-transducers
examples/cooperative.py
ticker
async def ticker(delay, to): """Yield numbers from 0 to `to` every `delay` seconds.""" for i in range(to): yield i await asyncio.sleep(delay)
python
async def ticker(delay, to): """Yield numbers from 0 to `to` every `delay` seconds.""" for i in range(to): yield i await asyncio.sleep(delay)
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/examples/cooperative.py#L7-L11
train
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sixty-north/python-transducers
transducer/sinks.py
rprint
def rprint(sep='\n', end='\n', file=sys.stdout, flush=False): """A coroutine sink which prints received items stdout Args: sep: Optional separator to be printed between received items. end: Optional terminator to be printed after the last item. file: Optional stream to which to print. flush: Optional flag to force flushing after each item. """ try: first_item = (yield) file.write(str(first_item)) if flush: file.flush() while True: item = (yield) file.write(sep) file.write(str(item)) if flush: file.flush() except GeneratorExit: file.write(end) if flush: file.flush()
python
def rprint(sep='\n', end='\n', file=sys.stdout, flush=False): """A coroutine sink which prints received items stdout Args: sep: Optional separator to be printed between received items. end: Optional terminator to be printed after the last item. file: Optional stream to which to print. flush: Optional flag to force flushing after each item. """ try: first_item = (yield) file.write(str(first_item)) if flush: file.flush() while True: item = (yield) file.write(sep) file.write(str(item)) if flush: file.flush() except GeneratorExit: file.write(end) if flush: file.flush()
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/sinks.py#L14-L37
train
53,375
sixty-north/python-transducers
transducer/sources.py
iterable_source
def iterable_source(iterable, target): """Convert an iterable into a stream of events. Args: iterable: A series of items which will be sent to the target one by one. target: The target coroutine or sink. Returns: An iterator over any remaining items. """ it = iter(iterable) for item in it: try: target.send(item) except StopIteration: return prepend(item, it) return empty_iter()
python
def iterable_source(iterable, target): """Convert an iterable into a stream of events. Args: iterable: A series of items which will be sent to the target one by one. target: The target coroutine or sink. Returns: An iterator over any remaining items. """ it = iter(iterable) for item in it: try: target.send(item) except StopIteration: return prepend(item, it) return empty_iter()
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/sources.py#L6-L22
train
53,376
sixty-north/python-transducers
transducer/sources.py
poisson_source
def poisson_source(rate, iterable, target): """Send events at random times with uniform probability. Args: rate: The average number of events to send per second. iterable: A series of items which will be sent to the target one by one. target: The target coroutine or sink. Returns: An iterator over any remaining items. """ if rate <= 0.0: raise ValueError("poisson_source rate {} is not positive".format(rate)) it = iter(iterable) for item in it: duration = random.expovariate(rate) sleep(duration) try: target.send(item) except StopIteration: return prepend(item, it) return empty_iter()
python
def poisson_source(rate, iterable, target): """Send events at random times with uniform probability. Args: rate: The average number of events to send per second. iterable: A series of items which will be sent to the target one by one. target: The target coroutine or sink. Returns: An iterator over any remaining items. """ if rate <= 0.0: raise ValueError("poisson_source rate {} is not positive".format(rate)) it = iter(iterable) for item in it: duration = random.expovariate(rate) sleep(duration) try: target.send(item) except StopIteration: return prepend(item, it) return empty_iter()
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Send events at random times with uniform probability. Args: rate: The average number of events to send per second. iterable: A series of items which will be sent to the target one by one. target: The target coroutine or sink. Returns: An iterator over any remaining items.
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/sources.py#L25-L47
train
53,377
sixty-north/python-transducers
transducer/functional.py
compose
def compose(f, *fs): """Compose functions right to left. compose(f, g, h)(x) -> f(g(h(x))) Args: f, *fs: The head and rest of a sequence of callables. The rightmost function passed can accept any arguments and the returned function will have the same signature as this last provided function. All preceding functions must be unary. Returns: The composition of the argument functions. The returned function will accept the same arguments as the rightmost passed in function. """ rfs = list(chain([f], fs)) rfs.reverse() def composed(*args, **kwargs): return reduce( lambda result, fn: fn(result), rfs[1:], rfs[0](*args, **kwargs)) return composed
python
def compose(f, *fs): """Compose functions right to left. compose(f, g, h)(x) -> f(g(h(x))) Args: f, *fs: The head and rest of a sequence of callables. The rightmost function passed can accept any arguments and the returned function will have the same signature as this last provided function. All preceding functions must be unary. Returns: The composition of the argument functions. The returned function will accept the same arguments as the rightmost passed in function. """ rfs = list(chain([f], fs)) rfs.reverse() def composed(*args, **kwargs): return reduce( lambda result, fn: fn(result), rfs[1:], rfs[0](*args, **kwargs)) return composed
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Compose functions right to left. compose(f, g, h)(x) -> f(g(h(x))) Args: f, *fs: The head and rest of a sequence of callables. The rightmost function passed can accept any arguments and the returned function will have the same signature as this last provided function. All preceding functions must be unary. Returns: The composition of the argument functions. The returned function will accept the same arguments as the rightmost passed in function.
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/functional.py#L5-L31
train
53,378
sixty-north/python-transducers
transducer/transducers.py
reducing
def reducing(reducer, init=UNSET): """Create a reducing transducer with the given reducer. Args: reducer: A two-argument function which will be used to combine the partial cumulative result in the first argument with the next item from the input stream in the second argument. Returns: A reducing transducer: A single argument function which, when passed a reducing function, returns a new reducing function which entirely reduces the input stream using 'reducer' before passing the result to the reducing function passed to the transducer. """ reducer2 = reducer def reducing_transducer(reducer): return Reducing(reducer, reducer2, init) return reducing_transducer
python
def reducing(reducer, init=UNSET): """Create a reducing transducer with the given reducer. Args: reducer: A two-argument function which will be used to combine the partial cumulative result in the first argument with the next item from the input stream in the second argument. Returns: A reducing transducer: A single argument function which, when passed a reducing function, returns a new reducing function which entirely reduces the input stream using 'reducer' before passing the result to the reducing function passed to the transducer. """ reducer2 = reducer def reducing_transducer(reducer): return Reducing(reducer, reducer2, init) return reducing_transducer
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Create a reducing transducer with the given reducer. Args: reducer: A two-argument function which will be used to combine the partial cumulative result in the first argument with the next item from the input stream in the second argument. Returns: A reducing transducer: A single argument function which, when passed a reducing function, returns a new reducing function which entirely reduces the input stream using 'reducer' before passing the result to the reducing function passed to the transducer.
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L99-L119
train
53,379
sixty-north/python-transducers
transducer/transducers.py
scanning
def scanning(reducer, init=UNSET): """Create a scanning reducer.""" reducer2 = reducer def scanning_transducer(reducer): return Scanning(reducer, reducer2, init) return scanning_transducer
python
def scanning(reducer, init=UNSET): """Create a scanning reducer.""" reducer2 = reducer def scanning_transducer(reducer): return Scanning(reducer, reducer2, init) return scanning_transducer
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Create a scanning reducer.
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L136-L144
train
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sixty-north/python-transducers
transducer/transducers.py
taking
def taking(n): """Create a transducer which takes the first n items""" if n < 0: raise ValueError("Cannot take fewer than zero ({}) items".format(n)) def taking_transducer(reducer): return Taking(reducer, n) return taking_transducer
python
def taking(n): """Create a transducer which takes the first n items""" if n < 0: raise ValueError("Cannot take fewer than zero ({}) items".format(n)) def taking_transducer(reducer): return Taking(reducer, n) return taking_transducer
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L207-L216
train
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sixty-north/python-transducers
transducer/transducers.py
dropping
def dropping(n): """Create a transducer which drops the first n items""" if n < 0: raise ValueError("Cannot drop fewer than zero ({}) items".format(n)) def dropping_transducer(reducer): return Dropping(reducer, n) return dropping_transducer
python
def dropping(n): """Create a transducer which drops the first n items""" if n < 0: raise ValueError("Cannot drop fewer than zero ({}) items".format(n)) def dropping_transducer(reducer): return Dropping(reducer, n) return dropping_transducer
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L255-L264
train
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sixty-north/python-transducers
transducer/transducers.py
batching
def batching(size): """Create a transducer which produces non-overlapping batches.""" if size < 1: raise ValueError("batching() size must be at least 1") def batching_transducer(reducer): return Batching(reducer, size) return batching_transducer
python
def batching(size): """Create a transducer which produces non-overlapping batches.""" if size < 1: raise ValueError("batching() size must be at least 1") def batching_transducer(reducer): return Batching(reducer, size) return batching_transducer
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Create a transducer which produces non-overlapping batches.
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L360-L369
train
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sixty-north/python-transducers
transducer/transducers.py
windowing
def windowing(size, padding=UNSET, window_type=tuple): """Create a transducer which produces a moving window over items.""" if size < 1: raise ValueError("windowing() size {} is not at least 1".format(size)) def windowing_transducer(reducer): return Windowing(reducer, size, padding, window_type) return windowing_transducer
python
def windowing(size, padding=UNSET, window_type=tuple): """Create a transducer which produces a moving window over items.""" if size < 1: raise ValueError("windowing() size {} is not at least 1".format(size)) def windowing_transducer(reducer): return Windowing(reducer, size, padding, window_type) return windowing_transducer
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L398-L407
train
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sixty-north/python-transducers
transducer/transducers.py
first
def first(predicate=None): """Create a transducer which obtains the first item, then terminates.""" predicate = true if predicate is None else predicate def first_transducer(reducer): return First(reducer, predicate) return first_transducer
python
def first(predicate=None): """Create a transducer which obtains the first item, then terminates.""" predicate = true if predicate is None else predicate def first_transducer(reducer): return First(reducer, predicate) return first_transducer
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L422-L430
train
53,385
sixty-north/python-transducers
transducer/transducers.py
last
def last(predicate=None): """Create a transducer which obtains the last item.""" predicate = true if predicate is None else predicate def last_transducer(reducer): return Last(reducer, predicate) return last_transducer
python
def last(predicate=None): """Create a transducer which obtains the last item.""" predicate = true if predicate is None else predicate def last_transducer(reducer): return Last(reducer, predicate) return last_transducer
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L453-L461
train
53,386
sixty-north/python-transducers
transducer/transducers.py
element_at
def element_at(index): """Create a transducer which obtains the item at the specified index.""" if index < 0: raise IndexError("element_at used with illegal index {}".format(index)) def element_at_transducer(reducer): return ElementAt(reducer, index) return element_at_transducer
python
def element_at(index): """Create a transducer which obtains the item at the specified index.""" if index < 0: raise IndexError("element_at used with illegal index {}".format(index)) def element_at_transducer(reducer): return ElementAt(reducer, index) return element_at_transducer
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575357e3a17ff3b4c757967afd396bf0ea042c08
https://github.com/sixty-north/python-transducers/blob/575357e3a17ff3b4c757967afd396bf0ea042c08/transducer/transducers.py#L486-L495
train
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bjodah/pycompilation
pycompilation/compilation.py
compile_sources
def compile_sources(files, CompilerRunner_=None, destdir=None, cwd=None, keep_dir_struct=False, per_file_kwargs=None, **kwargs): """ Compile source code files to object files. Parameters ---------- files: iterable of path strings source files, if cwd is given, the paths are taken as relative. CompilerRunner_: CompilerRunner instance (optional) could be e.g. pycompilation.FortranCompilerRunner Will be inferred from filename extensions if missing. destdir: path string output directory, if cwd is given, the path is taken as relative cwd: path string working directory. Specify to have compiler run in other directory. also used as root of relative paths. keep_dir_struct: bool Reproduce directory structure in `destdir`. default: False per_file_kwargs: dict dict mapping instances in `files` to keyword arguments **kwargs: dict default keyword arguments to pass to CompilerRunner_ """ _per_file_kwargs = {} if per_file_kwargs is not None: for k, v in per_file_kwargs.items(): if isinstance(k, Glob): for path in glob.glob(k.pathname): _per_file_kwargs[path] = v elif isinstance(k, ArbitraryDepthGlob): for path in glob_at_depth(k.filename, cwd): _per_file_kwargs[path] = v else: _per_file_kwargs[k] = v # Set up destination directory destdir = destdir or '.' if not os.path.isdir(destdir): if os.path.exists(destdir): raise IOError("{} is not a directory".format(destdir)) else: make_dirs(destdir) if cwd is None: cwd = '.' for f in files: copy(f, destdir, only_update=True, dest_is_dir=True) # Compile files and return list of paths to the objects dstpaths = [] for f in files: if keep_dir_struct: name, ext = os.path.splitext(f) else: name, ext = os.path.splitext(os.path.basename(f)) file_kwargs = kwargs.copy() file_kwargs.update(_per_file_kwargs.get(f, {})) dstpaths.append(src2obj( f, CompilerRunner_, cwd=cwd, **file_kwargs )) return dstpaths
python
def compile_sources(files, CompilerRunner_=None, destdir=None, cwd=None, keep_dir_struct=False, per_file_kwargs=None, **kwargs): """ Compile source code files to object files. Parameters ---------- files: iterable of path strings source files, if cwd is given, the paths are taken as relative. CompilerRunner_: CompilerRunner instance (optional) could be e.g. pycompilation.FortranCompilerRunner Will be inferred from filename extensions if missing. destdir: path string output directory, if cwd is given, the path is taken as relative cwd: path string working directory. Specify to have compiler run in other directory. also used as root of relative paths. keep_dir_struct: bool Reproduce directory structure in `destdir`. default: False per_file_kwargs: dict dict mapping instances in `files` to keyword arguments **kwargs: dict default keyword arguments to pass to CompilerRunner_ """ _per_file_kwargs = {} if per_file_kwargs is not None: for k, v in per_file_kwargs.items(): if isinstance(k, Glob): for path in glob.glob(k.pathname): _per_file_kwargs[path] = v elif isinstance(k, ArbitraryDepthGlob): for path in glob_at_depth(k.filename, cwd): _per_file_kwargs[path] = v else: _per_file_kwargs[k] = v # Set up destination directory destdir = destdir or '.' if not os.path.isdir(destdir): if os.path.exists(destdir): raise IOError("{} is not a directory".format(destdir)) else: make_dirs(destdir) if cwd is None: cwd = '.' for f in files: copy(f, destdir, only_update=True, dest_is_dir=True) # Compile files and return list of paths to the objects dstpaths = [] for f in files: if keep_dir_struct: name, ext = os.path.splitext(f) else: name, ext = os.path.splitext(os.path.basename(f)) file_kwargs = kwargs.copy() file_kwargs.update(_per_file_kwargs.get(f, {})) dstpaths.append(src2obj( f, CompilerRunner_, cwd=cwd, **file_kwargs )) return dstpaths
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Compile source code files to object files. Parameters ---------- files: iterable of path strings source files, if cwd is given, the paths are taken as relative. CompilerRunner_: CompilerRunner instance (optional) could be e.g. pycompilation.FortranCompilerRunner Will be inferred from filename extensions if missing. destdir: path string output directory, if cwd is given, the path is taken as relative cwd: path string working directory. Specify to have compiler run in other directory. also used as root of relative paths. keep_dir_struct: bool Reproduce directory structure in `destdir`. default: False per_file_kwargs: dict dict mapping instances in `files` to keyword arguments **kwargs: dict default keyword arguments to pass to CompilerRunner_
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43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18
https://github.com/bjodah/pycompilation/blob/43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18/pycompilation/compilation.py#L85-L150
train
53,388
bjodah/pycompilation
pycompilation/compilation.py
link
def link(obj_files, out_file=None, shared=False, CompilerRunner_=None, cwd=None, cplus=False, fort=False, **kwargs): """ Link object files. Parameters ---------- obj_files: iterable of path strings out_file: path string (optional) path to executable/shared library, if missing it will be deduced from the last item in obj_files. shared: bool Generate a shared library? default: False CompilerRunner_: pycompilation.CompilerRunner subclass (optional) If not given the `cplus` and `fort` flags will be inspected (fallback is the C compiler) cwd: path string root of relative paths and working directory for compiler cplus: bool C++ objects? default: False fort: bool Fortran objects? default: False **kwargs: dict keyword arguments passed onto CompilerRunner_ Returns ------- The absolute to the generated shared object / executable """ if out_file is None: out_file, ext = os.path.splitext(os.path.basename(obj_files[-1])) if shared: out_file += sharedext if not CompilerRunner_: if fort: CompilerRunner_, extra_kwargs, vendor = \ get_mixed_fort_c_linker( vendor=kwargs.get('vendor', None), metadir=kwargs.get('metadir', None), cplus=cplus, cwd=cwd, ) for k, v in extra_kwargs.items(): expand_collection_in_dict(kwargs, k, v) else: if cplus: CompilerRunner_ = CppCompilerRunner else: CompilerRunner_ = CCompilerRunner flags = kwargs.pop('flags', []) if shared: if '-shared' not in flags: flags.append('-shared') # mimic GNU linker behavior on OS X when using -shared # (otherwise likely Undefined symbol errors) dl_flag = '-undefined dynamic_lookup' if sys.platform == 'darwin' and dl_flag not in flags: flags.append(dl_flag) run_linker = kwargs.pop('run_linker', True) if not run_linker: raise ValueError("link(..., run_linker=False)!?") out_file = get_abspath(out_file, cwd=cwd) runner = CompilerRunner_( obj_files, out_file, flags, cwd=cwd, **kwargs) runner.run() return out_file
python
def link(obj_files, out_file=None, shared=False, CompilerRunner_=None, cwd=None, cplus=False, fort=False, **kwargs): """ Link object files. Parameters ---------- obj_files: iterable of path strings out_file: path string (optional) path to executable/shared library, if missing it will be deduced from the last item in obj_files. shared: bool Generate a shared library? default: False CompilerRunner_: pycompilation.CompilerRunner subclass (optional) If not given the `cplus` and `fort` flags will be inspected (fallback is the C compiler) cwd: path string root of relative paths and working directory for compiler cplus: bool C++ objects? default: False fort: bool Fortran objects? default: False **kwargs: dict keyword arguments passed onto CompilerRunner_ Returns ------- The absolute to the generated shared object / executable """ if out_file is None: out_file, ext = os.path.splitext(os.path.basename(obj_files[-1])) if shared: out_file += sharedext if not CompilerRunner_: if fort: CompilerRunner_, extra_kwargs, vendor = \ get_mixed_fort_c_linker( vendor=kwargs.get('vendor', None), metadir=kwargs.get('metadir', None), cplus=cplus, cwd=cwd, ) for k, v in extra_kwargs.items(): expand_collection_in_dict(kwargs, k, v) else: if cplus: CompilerRunner_ = CppCompilerRunner else: CompilerRunner_ = CCompilerRunner flags = kwargs.pop('flags', []) if shared: if '-shared' not in flags: flags.append('-shared') # mimic GNU linker behavior on OS X when using -shared # (otherwise likely Undefined symbol errors) dl_flag = '-undefined dynamic_lookup' if sys.platform == 'darwin' and dl_flag not in flags: flags.append(dl_flag) run_linker = kwargs.pop('run_linker', True) if not run_linker: raise ValueError("link(..., run_linker=False)!?") out_file = get_abspath(out_file, cwd=cwd) runner = CompilerRunner_( obj_files, out_file, flags, cwd=cwd, **kwargs) runner.run() return out_file
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Link object files. Parameters ---------- obj_files: iterable of path strings out_file: path string (optional) path to executable/shared library, if missing it will be deduced from the last item in obj_files. shared: bool Generate a shared library? default: False CompilerRunner_: pycompilation.CompilerRunner subclass (optional) If not given the `cplus` and `fort` flags will be inspected (fallback is the C compiler) cwd: path string root of relative paths and working directory for compiler cplus: bool C++ objects? default: False fort: bool Fortran objects? default: False **kwargs: dict keyword arguments passed onto CompilerRunner_ Returns ------- The absolute to the generated shared object / executable
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43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18
https://github.com/bjodah/pycompilation/blob/43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18/pycompilation/compilation.py#L153-L225
train
53,389
bjodah/pycompilation
pycompilation/compilation.py
simple_cythonize
def simple_cythonize(src, destdir=None, cwd=None, logger=None, full_module_name=None, only_update=False, **cy_kwargs): """ Generates a C file from a Cython source file. Parameters ---------- src: path string path to Cython source destdir: path string (optional) Path to output directory (default: '.') cwd: path string (optional) Root of relative paths (default: '.') logger: logging.Logger info level used. full_module_name: string passed to cy_compile (default: None) only_update: bool Only cythonize if source is newer. default: False **cy_kwargs: second argument passed to cy_compile. Generates a .cpp file if cplus=True in cy_kwargs, else a .c file. """ from Cython.Compiler.Main import ( default_options, CompilationOptions ) from Cython.Compiler.Main import compile as cy_compile assert src.lower().endswith('.pyx') or src.lower().endswith('.py') cwd = cwd or '.' destdir = destdir or '.' ext = '.cpp' if cy_kwargs.get('cplus', False) else '.c' c_name = os.path.splitext(os.path.basename(src))[0] + ext dstfile = os.path.join(destdir, c_name) if only_update: if not missing_or_other_newer(dstfile, src, cwd=cwd): msg = '{0} newer than {1}, did not re-cythonize.'.format( dstfile, src) if logger: logger.info(msg) else: print(msg) return dstfile if cwd: ori_dir = os.getcwd() else: ori_dir = '.' os.chdir(cwd) try: cy_options = CompilationOptions(default_options) cy_options.__dict__.update(cy_kwargs) if logger: logger.info("Cythonizing {0} to {1}".format( src, dstfile)) cy_result = cy_compile([src], cy_options, full_module_name=full_module_name) if cy_result.num_errors > 0: raise ValueError("Cython compilation failed.") if os.path.abspath(os.path.dirname( src)) != os.path.abspath(destdir): if os.path.exists(dstfile): os.unlink(dstfile) shutil.move(os.path.join(os.path.dirname(src), c_name), destdir) finally: os.chdir(ori_dir) return dstfile
python
def simple_cythonize(src, destdir=None, cwd=None, logger=None, full_module_name=None, only_update=False, **cy_kwargs): """ Generates a C file from a Cython source file. Parameters ---------- src: path string path to Cython source destdir: path string (optional) Path to output directory (default: '.') cwd: path string (optional) Root of relative paths (default: '.') logger: logging.Logger info level used. full_module_name: string passed to cy_compile (default: None) only_update: bool Only cythonize if source is newer. default: False **cy_kwargs: second argument passed to cy_compile. Generates a .cpp file if cplus=True in cy_kwargs, else a .c file. """ from Cython.Compiler.Main import ( default_options, CompilationOptions ) from Cython.Compiler.Main import compile as cy_compile assert src.lower().endswith('.pyx') or src.lower().endswith('.py') cwd = cwd or '.' destdir = destdir or '.' ext = '.cpp' if cy_kwargs.get('cplus', False) else '.c' c_name = os.path.splitext(os.path.basename(src))[0] + ext dstfile = os.path.join(destdir, c_name) if only_update: if not missing_or_other_newer(dstfile, src, cwd=cwd): msg = '{0} newer than {1}, did not re-cythonize.'.format( dstfile, src) if logger: logger.info(msg) else: print(msg) return dstfile if cwd: ori_dir = os.getcwd() else: ori_dir = '.' os.chdir(cwd) try: cy_options = CompilationOptions(default_options) cy_options.__dict__.update(cy_kwargs) if logger: logger.info("Cythonizing {0} to {1}".format( src, dstfile)) cy_result = cy_compile([src], cy_options, full_module_name=full_module_name) if cy_result.num_errors > 0: raise ValueError("Cython compilation failed.") if os.path.abspath(os.path.dirname( src)) != os.path.abspath(destdir): if os.path.exists(dstfile): os.unlink(dstfile) shutil.move(os.path.join(os.path.dirname(src), c_name), destdir) finally: os.chdir(ori_dir) return dstfile
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Generates a C file from a Cython source file. Parameters ---------- src: path string path to Cython source destdir: path string (optional) Path to output directory (default: '.') cwd: path string (optional) Root of relative paths (default: '.') logger: logging.Logger info level used. full_module_name: string passed to cy_compile (default: None) only_update: bool Only cythonize if source is newer. default: False **cy_kwargs: second argument passed to cy_compile. Generates a .cpp file if cplus=True in cy_kwargs, else a .c file.
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43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18
https://github.com/bjodah/pycompilation/blob/43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18/pycompilation/compilation.py#L311-L381
train
53,390
bjodah/pycompilation
pycompilation/compilation.py
src2obj
def src2obj(srcpath, CompilerRunner_=None, objpath=None, only_update=False, cwd=None, out_ext=None, inc_py=False, **kwargs): """ Compiles a source code file to an object file. Files ending with '.pyx' assumed to be cython files and are dispatched to pyx2obj. Parameters ---------- srcpath: path string path to source file CompilerRunner_: pycompilation.CompilerRunner subclass (optional) Default: deduced from extension of srcpath objpath: path string (optional) path to generated object. defualt: deduced from srcpath only_update: bool only compile if source is newer than objpath. default: False cwd: path string (optional) working directory and root of relative paths. default: current dir. out_ext: string set when objpath is a dir and you want to override defaults ('.o'/'.obj' for Unix/Windows). inc_py: bool add Python include path to include_dirs. default: False **kwargs: dict keyword arguments passed onto CompilerRunner_ or pyx2obj """ name, ext = os.path.splitext(os.path.basename(srcpath)) if objpath is None: if os.path.isabs(srcpath): objpath = '.' else: objpath = os.path.dirname(srcpath) objpath = objpath or '.' # avoid objpath == '' out_ext = out_ext or objext if os.path.isdir(objpath): objpath = os.path.join(objpath, name+out_ext) include_dirs = kwargs.pop('include_dirs', []) if inc_py: from distutils.sysconfig import get_python_inc py_inc_dir = get_python_inc() if py_inc_dir not in include_dirs: include_dirs.append(py_inc_dir) if ext.lower() == '.pyx': return pyx2obj(srcpath, objpath=objpath, include_dirs=include_dirs, cwd=cwd, only_update=only_update, **kwargs) if CompilerRunner_ is None: CompilerRunner_, std = extension_mapping[ext.lower()] if 'std' not in kwargs: kwargs['std'] = std # src2obj implies not running the linker... run_linker = kwargs.pop('run_linker', False) if run_linker: raise CompilationError("src2obj called with run_linker=True") if only_update: if not missing_or_other_newer(objpath, srcpath, cwd=cwd): msg = "Found {0}, did not recompile.".format(objpath) if kwargs.get('logger', None): kwargs['logger'].info(msg) else: print(msg) return objpath runner = CompilerRunner_( [srcpath], objpath, include_dirs=include_dirs, run_linker=run_linker, cwd=cwd, **kwargs) runner.run() return objpath
python
def src2obj(srcpath, CompilerRunner_=None, objpath=None, only_update=False, cwd=None, out_ext=None, inc_py=False, **kwargs): """ Compiles a source code file to an object file. Files ending with '.pyx' assumed to be cython files and are dispatched to pyx2obj. Parameters ---------- srcpath: path string path to source file CompilerRunner_: pycompilation.CompilerRunner subclass (optional) Default: deduced from extension of srcpath objpath: path string (optional) path to generated object. defualt: deduced from srcpath only_update: bool only compile if source is newer than objpath. default: False cwd: path string (optional) working directory and root of relative paths. default: current dir. out_ext: string set when objpath is a dir and you want to override defaults ('.o'/'.obj' for Unix/Windows). inc_py: bool add Python include path to include_dirs. default: False **kwargs: dict keyword arguments passed onto CompilerRunner_ or pyx2obj """ name, ext = os.path.splitext(os.path.basename(srcpath)) if objpath is None: if os.path.isabs(srcpath): objpath = '.' else: objpath = os.path.dirname(srcpath) objpath = objpath or '.' # avoid objpath == '' out_ext = out_ext or objext if os.path.isdir(objpath): objpath = os.path.join(objpath, name+out_ext) include_dirs = kwargs.pop('include_dirs', []) if inc_py: from distutils.sysconfig import get_python_inc py_inc_dir = get_python_inc() if py_inc_dir not in include_dirs: include_dirs.append(py_inc_dir) if ext.lower() == '.pyx': return pyx2obj(srcpath, objpath=objpath, include_dirs=include_dirs, cwd=cwd, only_update=only_update, **kwargs) if CompilerRunner_ is None: CompilerRunner_, std = extension_mapping[ext.lower()] if 'std' not in kwargs: kwargs['std'] = std # src2obj implies not running the linker... run_linker = kwargs.pop('run_linker', False) if run_linker: raise CompilationError("src2obj called with run_linker=True") if only_update: if not missing_or_other_newer(objpath, srcpath, cwd=cwd): msg = "Found {0}, did not recompile.".format(objpath) if kwargs.get('logger', None): kwargs['logger'].info(msg) else: print(msg) return objpath runner = CompilerRunner_( [srcpath], objpath, include_dirs=include_dirs, run_linker=run_linker, cwd=cwd, **kwargs) runner.run() return objpath
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43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18
https://github.com/bjodah/pycompilation/blob/43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18/pycompilation/compilation.py#L398-L471
train
53,391
bjodah/pycompilation
pycompilation/compilation.py
compile_link_import_strings
def compile_link_import_strings(codes, build_dir=None, **kwargs): """ Creates a temporary directory and dumps, compiles and links provided source code. Parameters ---------- codes: iterable of name/source pair tuples build_dir: string (default: None) path to cache_dir. None implies use a temporary directory. **kwargs: keyword arguments passed onto `compile_link_import_py_ext` """ build_dir = build_dir or tempfile.mkdtemp() if not os.path.isdir(build_dir): raise OSError("Non-existent directory: ", build_dir) source_files = [] if kwargs.get('logger', False) is True: import logging logging.basicConfig(level=logging.DEBUG) kwargs['logger'] = logging.getLogger() only_update = kwargs.get('only_update', True) for name, code_ in codes: dest = os.path.join(build_dir, name) differs = True md5_in_mem = md5_of_string(code_.encode('utf-8')).hexdigest() if only_update and os.path.exists(dest): if os.path.exists(dest+'.md5'): md5_on_disk = open(dest+'.md5', 'rt').read() else: md5_on_disk = md5_of_file(dest).hexdigest() differs = md5_on_disk != md5_in_mem if not only_update or differs: with open(dest, 'wt') as fh: fh.write(code_) open(dest+'.md5', 'wt').write(md5_in_mem) source_files.append(dest) return compile_link_import_py_ext( source_files, build_dir=build_dir, **kwargs)
python
def compile_link_import_strings(codes, build_dir=None, **kwargs): """ Creates a temporary directory and dumps, compiles and links provided source code. Parameters ---------- codes: iterable of name/source pair tuples build_dir: string (default: None) path to cache_dir. None implies use a temporary directory. **kwargs: keyword arguments passed onto `compile_link_import_py_ext` """ build_dir = build_dir or tempfile.mkdtemp() if not os.path.isdir(build_dir): raise OSError("Non-existent directory: ", build_dir) source_files = [] if kwargs.get('logger', False) is True: import logging logging.basicConfig(level=logging.DEBUG) kwargs['logger'] = logging.getLogger() only_update = kwargs.get('only_update', True) for name, code_ in codes: dest = os.path.join(build_dir, name) differs = True md5_in_mem = md5_of_string(code_.encode('utf-8')).hexdigest() if only_update and os.path.exists(dest): if os.path.exists(dest+'.md5'): md5_on_disk = open(dest+'.md5', 'rt').read() else: md5_on_disk = md5_of_file(dest).hexdigest() differs = md5_on_disk != md5_in_mem if not only_update or differs: with open(dest, 'wt') as fh: fh.write(code_) open(dest+'.md5', 'wt').write(md5_in_mem) source_files.append(dest) return compile_link_import_py_ext( source_files, build_dir=build_dir, **kwargs)
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43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18
https://github.com/bjodah/pycompilation/blob/43eac8d82f8258d30d4df77fd2ad3f3e4f4dca18/pycompilation/compilation.py#L676-L717
train
53,392
BlueBrain/hpcbench
hpcbench/benchmark/osu.py
OSU.arguments
def arguments(self): """Dictionary providing the list of arguments for every benchmark""" if 'arguments' in self.attributes: LOGGER.warning( "WARNING: 'arguments' use in OSU yaml configuration file is deprecated. Please use 'options'!" ) arguments = self.attributes['arguments'] if isinstance(arguments, dict): return arguments else: return {k: arguments for k in self.categories} elif 'options' in self.attributes: options = self.attributes['options'] if isinstance(options, dict): return options else: return {k: options for k in self.categories}
python
def arguments(self): """Dictionary providing the list of arguments for every benchmark""" if 'arguments' in self.attributes: LOGGER.warning( "WARNING: 'arguments' use in OSU yaml configuration file is deprecated. Please use 'options'!" ) arguments = self.attributes['arguments'] if isinstance(arguments, dict): return arguments else: return {k: arguments for k in self.categories} elif 'options' in self.attributes: options = self.attributes['options'] if isinstance(options, dict): return options else: return {k: options for k in self.categories}
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192d0ec142b897157ec25f131d1ef28f84752592
https://github.com/BlueBrain/hpcbench/blob/192d0ec142b897157ec25f131d1ef28f84752592/hpcbench/benchmark/osu.py#L289-L306
train
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portfoliome/foil
foil/serializers.py
_
def _(obj): """ISO 8601 format. Interprets naive datetime as UTC with zulu suffix.""" tz_offset = obj.utcoffset() if not tz_offset or tz_offset == UTC_ZERO: iso_datetime = obj.strftime('%Y-%m-%dT%H:%M:%S.%fZ') else: iso_datetime = obj.isoformat() return iso_datetime
python
def _(obj): """ISO 8601 format. Interprets naive datetime as UTC with zulu suffix.""" tz_offset = obj.utcoffset() if not tz_offset or tz_offset == UTC_ZERO: iso_datetime = obj.strftime('%Y-%m-%dT%H:%M:%S.%fZ') else: iso_datetime = obj.isoformat() return iso_datetime
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b66d8cf4ab048a387d8c7a033b47e922ed6917d6
https://github.com/portfoliome/foil/blob/b66d8cf4ab048a387d8c7a033b47e922ed6917d6/foil/serializers.py#L26-L36
train
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Metatab/metatab
metatab/resolver.py
WebResolver.get_row_generator
def get_row_generator(self, ref, cache=None): """Return a row generator for a reference""" from inspect import isgenerator from rowgenerators import get_generator g = get_generator(ref) if not g: raise GenerateError("Cant figure out how to generate rows from {} ref: {}".format(type(ref), ref)) else: return g
python
def get_row_generator(self, ref, cache=None): """Return a row generator for a reference""" from inspect import isgenerator from rowgenerators import get_generator g = get_generator(ref) if not g: raise GenerateError("Cant figure out how to generate rows from {} ref: {}".format(type(ref), ref)) else: return g
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8336ec3e4bd8da84a9a5cb86de1c1086e14b8b22
https://github.com/Metatab/metatab/blob/8336ec3e4bd8da84a9a5cb86de1c1086e14b8b22/metatab/resolver.py#L34-L45
train
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portfoliome/foil
foil/filters.py
create_key_filter
def create_key_filter(properties: Dict[str, list]) -> List[Tuple]: """Generate combinations of key, value pairs for each key in properties. Examples -------- properties = {'ent': ['geo_rev', 'supply_chain'], 'own', 'fi'} >> create_key_filter(properties) --> [('ent', 'geo_rev'), ('ent', 'supply_chain'), ('own', 'fi')] """ combinations = (product([k], v) for k, v in properties.items()) return chain.from_iterable(combinations)
python
def create_key_filter(properties: Dict[str, list]) -> List[Tuple]: """Generate combinations of key, value pairs for each key in properties. Examples -------- properties = {'ent': ['geo_rev', 'supply_chain'], 'own', 'fi'} >> create_key_filter(properties) --> [('ent', 'geo_rev'), ('ent', 'supply_chain'), ('own', 'fi')] """ combinations = (product([k], v) for k, v in properties.items()) return chain.from_iterable(combinations)
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Generate combinations of key, value pairs for each key in properties. Examples -------- properties = {'ent': ['geo_rev', 'supply_chain'], 'own', 'fi'} >> create_key_filter(properties) --> [('ent', 'geo_rev'), ('ent', 'supply_chain'), ('own', 'fi')]
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b66d8cf4ab048a387d8c7a033b47e922ed6917d6
https://github.com/portfoliome/foil/blob/b66d8cf4ab048a387d8c7a033b47e922ed6917d6/foil/filters.py#L38-L50
train
53,396
portfoliome/foil
foil/filters.py
create_indexer
def create_indexer(indexes: list): """Create indexer function to pluck values from list.""" if len(indexes) == 1: index = indexes[0] return lambda x: (x[index],) else: return itemgetter(*indexes)
python
def create_indexer(indexes: list): """Create indexer function to pluck values from list.""" if len(indexes) == 1: index = indexes[0] return lambda x: (x[index],) else: return itemgetter(*indexes)
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b66d8cf4ab048a387d8c7a033b47e922ed6917d6
https://github.com/portfoliome/foil/blob/b66d8cf4ab048a387d8c7a033b47e922ed6917d6/foil/filters.py#L53-L60
train
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portfoliome/foil
foil/filters.py
AttributeFilter.including
def including(self, sequence) -> Generator: """Include the sequence elements matching the filter set.""" return (element for element in sequence if self.indexer(element) in self.predicates)
python
def including(self, sequence) -> Generator: """Include the sequence elements matching the filter set.""" return (element for element in sequence if self.indexer(element) in self.predicates)
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b66d8cf4ab048a387d8c7a033b47e922ed6917d6
https://github.com/portfoliome/foil/blob/b66d8cf4ab048a387d8c7a033b47e922ed6917d6/foil/filters.py#L27-L30
train
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portfoliome/foil
foil/filters.py
AttributeFilter.excluding
def excluding(self, sequence) -> Generator: """Exclude the sequence elements matching the filter set.""" return (element for element in sequence if self.indexer(element) not in self.predicates)
python
def excluding(self, sequence) -> Generator: """Exclude the sequence elements matching the filter set.""" return (element for element in sequence if self.indexer(element) not in self.predicates)
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b66d8cf4ab048a387d8c7a033b47e922ed6917d6
https://github.com/portfoliome/foil/blob/b66d8cf4ab048a387d8c7a033b47e922ed6917d6/foil/filters.py#L32-L35
train
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