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infobloxopen/infoblox-client | infoblox_client/object_manager.py | InfobloxObjectManager.create_ip_range | def create_ip_range(self, network_view, start_ip, end_ip, network,
disable, range_extattrs):
"""Creates IPRange or fails if already exists."""
return obj.IPRange.create(self.connector,
network_view=network_view,
... | python | def create_ip_range(self, network_view, start_ip, end_ip, network,
disable, range_extattrs):
"""Creates IPRange or fails if already exists."""
return obj.IPRange.create(self.connector,
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infobloxopen/infoblox-client | infoblox_client/object_manager.py | InfobloxObjectManager.network_exists | def network_exists(self, network_view, cidr):
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infobloxopen/infoblox-client | infoblox_client/object_manager.py | InfobloxObjectManager.delete_objects_associated_with_a_record | def delete_objects_associated_with_a_record(self, name, view, delete_list):
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if 'record:cname' in delete_list:
search_objects['record:cname'] = 'canonical'
if 'record:txt' in delete_list:
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infobloxopen/infoblox-client | infoblox_client/connector.py | Connector._parse_options | def _parse_options(self, options):
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attributes = ('host', 'wapi_version', 'username', 'password',
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infobloxopen/infoblox-client | infoblox_client/connector.py | Connector._parse_reply | def _parse_reply(request):
"""Tries to parse reply from NIOS.
Raises exception with content if reply is not in json format
"""
try:
return jsonutils.loads(request.content)
except ValueError:
raise ib_ex.InfobloxConnectionError(reason=request.content) | python | def _parse_reply(request):
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infobloxopen/infoblox-client | infoblox_client/connector.py | Connector.get_object | def get_object(self, obj_type, payload=None, return_fields=None,
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infobloxopen/infoblox-client | infoblox_client/connector.py | Connector.create_object | def create_object(self, obj_type, payload, return_fields=None):
"""Create an Infoblox object of type 'obj_type'
Args:
obj_type (str): Infoblox object type,
e.g. 'network', 'range', etc.
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obj_type (str): Infoblox object type,
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infobloxopen/infoblox-client | infoblox_client/connector.py | Connector.update_object | def update_object(self, ref, payload, return_fields=None):
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Args:
ref (str): Infoblox object reference
payload (dict): Payload with data to send
Returns:
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infobloxopen/infoblox-client | infoblox_client/connector.py | Connector.delete_object | def delete_object(self, ref, delete_arguments=None):
"""Remove an Infoblox object
Args:
ref (str): Object reference
delete_arguments (dict): Extra delete arguments
Returns:
The object reference of the removed object
Raises:
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infobloxopen/infoblox-client | infoblox_client/objects.py | BaseObject._remap_fields | def _remap_fields(cls, kwargs):
"""Map fields from kwargs into dict acceptable by NIOS"""
mapped = {}
for key in kwargs:
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mapped[cls._remap[key]] = kwargs[key]
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infobloxopen/infoblox-client | infoblox_client/objects.py | EA.from_dict | def from_dict(cls, eas_from_nios):
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infobloxopen/infoblox-client | infoblox_client/objects.py | EA.to_dict | def to_dict(self):
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infobloxopen/infoblox-client | infoblox_client/objects.py | InfobloxObject.from_dict | def from_dict(cls, connector, ip_dict):
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infobloxopen/infoblox-client | infoblox_client/objects.py | InfobloxObject.field_to_dict | def field_to_dict(self, field):
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value = getattr(self, field)
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infobloxopen/infoblox-client | infoblox_client/objects.py | InfobloxObject.fetch | def fetch(self, only_ref=False):
"""Fetch object from NIOS by _ref or searchfields
Update existent object with fields returned from NIOS
Return True on successful object fetch
"""
if self.ref:
reply = self.connector.get_object(
self.ref, return_fields... | python | def fetch(self, only_ref=False):
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Update existent object with fields returned from NIOS
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python-beaver/python-beaver | beaver/worker/tail.py | Tail._update_file | def _update_file(self, seek_to_end=True):
"""Open the file for tailing"""
try:
self.close()
self._file = self.open()
except IOError:
pass
else:
if not self._file:
return
self.active = True
try:
... | python | def _update_file(self, seek_to_end=True):
"""Open the file for tailing"""
try:
self.close()
self._file = self.open()
except IOError:
pass
else:
if not self._file:
return
self.active = True
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raise ValueError('invalid window %r' % window)
encodings = ENCODINGS
if encoding:
encodings = [encoding] + ENCODINGS
for enc in encodings:
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"""Read last N lines from file fname."""
if window <= 0:
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encodings = ENCODINGS
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python-beaver/python-beaver | beaver/transports/__init__.py | create_transport | def create_transport(beaver_config, logger):
"""Creates and returns a transport object"""
transport_str = beaver_config.get('transport')
if '.' not in transport_str:
# allow simple names like 'redis' to load a beaver built-in transport
module_path = 'beaver.transports.%s_transport' % transpo... | python | def create_transport(beaver_config, logger):
"""Creates and returns a transport object"""
transport_str = beaver_config.get('transport')
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# allow simple names like 'redis' to load a beaver built-in transport
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python-beaver/python-beaver | beaver/worker/tail_manager.py | TailManager.listdir | def listdir(self):
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ls = os.listdir(self._folder)
return [x for x in ls if os.path.splitext(x)[1][1:] == "log"] | python | def listdir(self):
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TODO: Convert this to a glob"""
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python-beaver/python-beaver | beaver/worker/tail_manager.py | TailManager.update_files | def update_files(self):
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On non-linux platforms, it will also manually reload the file for tailing.
Note that this hack is necessary because EOF is cached on BSD systems.
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"""Ensures all files are properly loaded.
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Note that this hack is necessary because EOF is cached on BSD systems.
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python-beaver/python-beaver | beaver/worker/tail_manager.py | TailManager.close | def close(self, signalnum=None, frame=None):
self._running = False
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self._log_debug("Closing all tail objects")
self._active = False
for fid in self._tails:
self._tails[fid].close()
for n in range(0,self._number_of_c... | python | def close(self, signalnum=None, frame=None):
self._running = False
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self._log_debug("Closing all tail objects")
self._active = False
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python-beaver/python-beaver | beaver/utils.py | eglob | def eglob(path, exclude=None):
"""Like glob.glob, but supports "/path/**/{a,b,c}.txt" lookup"""
fi = itertools.chain.from_iterable
paths = list(fi(glob2.iglob(d) for d in expand_paths(path)))
if exclude:
cached_regex = cached_regices.get(exclude, None)
if not cached_regex:
ca... | python | def eglob(path, exclude=None):
"""Like glob.glob, but supports "/path/**/{a,b,c}.txt" lookup"""
fi = itertools.chain.from_iterable
paths = list(fi(glob2.iglob(d) for d in expand_paths(path)))
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python-beaver/python-beaver | beaver/utils.py | expand_paths | def expand_paths(path):
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>>> expand_paths('../{a,b}/{c,d}')
['../a/c', '../a/d', '../b/c', '../b/d']
>>> expand_paths('../{a,b}/{a,b}.py')
['../a/a.py', '.... | python | def expand_paths(path):
"""When given a path with brackets, expands it to return all permutations
of the path with expanded brackets, similar to ant.
>>> expand_paths('../{a,b}/{c,d}')
['../a/c', '../a/d', '../b/c', '../b/d']
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['../a/a.py', '.... | [
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python-beaver/python-beaver | beaver/utils.py | multiline_merge | def multiline_merge(lines, current_event, re_after, re_before):
""" Merge multi-line events based.
Some event (like Python trackback or Java stracktrace) spawn
on multiple line. This method will merge them using two
regular expression: regex_after and regex_before.
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python-beaver/python-beaver | beaver/ssh_tunnel.py | create_ssh_tunnel | def create_ssh_tunnel(beaver_config, logger=None):
"""Returns a BeaverSshTunnel object if the current config requires us to"""
if not beaver_config.use_ssh_tunnel():
return None
logger.info("Proxying transport using through local ssh tunnel")
return BeaverSshTunnel(beaver_config, logger=logger) | python | def create_ssh_tunnel(beaver_config, logger=None):
"""Returns a BeaverSshTunnel object if the current config requires us to"""
if not beaver_config.use_ssh_tunnel():
return None
logger.info("Proxying transport using through local ssh tunnel")
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python-beaver/python-beaver | beaver/ssh_tunnel.py | BeaverSubprocess.poll | def poll(self):
"""Poll attached subprocess until it is available"""
if self._subprocess is not None:
self._subprocess.poll()
time.sleep(self._beaver_config.get('subprocess_poll_sleep')) | python | def poll(self):
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self._subprocess.poll()
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python-beaver/python-beaver | beaver/ssh_tunnel.py | BeaverSubprocess.close | def close(self):
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if self._subprocess is not None:
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self._subprocess = None | python | def close(self):
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python-beaver/python-beaver | beaver/transports/mqtt_transport.py | MqttTransport.callback | def callback(self, filename, lines, **kwargs):
"""publishes lines one by one to the given topic"""
timestamp = self.get_timestamp(**kwargs)
if kwargs.get('timestamp', False):
del kwargs['timestamp']
for line in lines:
try:
import warnings
... | python | def callback(self, filename, lines, **kwargs):
"""publishes lines one by one to the given topic"""
timestamp = self.get_timestamp(**kwargs)
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del kwargs['timestamp']
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python-beaver/python-beaver | beaver/unicode_dammit.py | _to_unicode | def _to_unicode(self, data, encoding, errors='strict'):
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# strip Byte Order Mark (if present)
if (len(data) >= 4) and (data[:2] == '\xfe\xff') and (data[2:4] != '\x00\x00'):
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python-beaver/python-beaver | beaver/transports/stomp_transport.py | StompTransport.callback | def callback(self, filename, lines, **kwargs):
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if kwargs.get('timestamp', False):
del kwargs['timestamp']
for line in lines:
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python-beaver/python-beaver | beaver/transports/stomp_transport.py | StompTransport.reconnect | def reconnect(self):
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try:
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self.logger.warn(e)
self.createConnection()
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self.logger.warn(e)
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python-beaver/python-beaver | beaver/transports/redis_transport.py | RedisTransport.valid | def valid(self):
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valid_servers += 1
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python-beaver/python-beaver | beaver/transports/kafka_transport.py | KafkaTransport.callback | def callback(self, filename, lines, **kwargs):
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python-beaver/python-beaver | beaver/transports/base_transport.py | BaseTransport.format | def format(self, filename, line, timestamp, **kwargs):
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gqmelo/exec-wrappers | exec_wrappers/create_wrappers.py | _make_executable | def _make_executable(path):
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cmap/cmapPy | cmapPy/pandasGEXpress/subset.py | build_parser | def build_parser():
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parser = argparse.ArgumentParser(description=__doc__,
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cmap/cmapPy | cmapPy/math/fast_cov.py | fast_cov | def fast_cov(x, y=None, destination=None):
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cmap/cmapPy | cmapPy/set_io/gmt.py | read | def read(file_path):
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cmap/cmapPy | cmapPy/set_io/gmt.py | verify_gmt_integrity | def verify_gmt_integrity(gmt):
""" Make sure that set ids are unique.
Args:
gmt (GMT object): list of dicts
Returns:
None
"""
# Verify that set ids are unique
set_ids = [d[SET_IDENTIFIER_FIELD] for d in gmt]
assert len(set(set_ids)) == len(set_ids), (
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""" Make sure that set ids are unique.
Args:
gmt (GMT object): list of dicts
Returns:
None
"""
# Verify that set ids are unique
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cmap/cmapPy | cmapPy/set_io/gmt.py | write | def write(gmt, out_path):
""" Write a GMT to a text file.
Args:
gmt (GMT object): list of dicts
out_path (string): output path
Returns:
None
"""
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""" Write a GMT to a text file.
Args:
gmt (GMT object): list of dicts
out_path (string): output path
Returns:
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"""
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cmap/cmapPy | cmapPy/pandasGEXpress/diff_gctoo.py | diff_gctoo | def diff_gctoo(gctoo, plate_control=True, group_field='pert_type', group_val='ctl_vehicle',
diff_method="robust_z", upper_diff_thresh=10, lower_diff_thresh=-10):
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Args:
df (pandas... | python | def diff_gctoo(gctoo, plate_control=True, group_field='pert_type', group_val='ctl_vehicle',
diff_method="robust_z", upper_diff_thresh=10, lower_diff_thresh=-10):
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | parse | def parse(gctx_file_path, convert_neg_666=True, rid=None, cid=None,
ridx=None, cidx=None, row_meta_only=False, col_meta_only=False, make_multiindex=False):
"""
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Input:
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | check_and_order_id_inputs | def check_and_order_id_inputs(rid, ridx, cid, cidx, row_meta_df, col_meta_df):
"""
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Input:
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"""
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | check_id_idx_exclusivity | def check_id_idx_exclusivity(id, idx):
"""
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Input:
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Output:
- a tuple: first element is... | python | def check_id_idx_exclusivity(id, idx):
"""
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | get_ordered_idx | def get_ordered_idx(id_type, id_list, meta_df):
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | parse_metadata_df | def parse_metadata_df(dim, meta_group, convert_neg_666):
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | replace_666 | def replace_666(meta_df, convert_neg_666):
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meta_df (pandas df):
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meta_df (pandas df):
convert_neg_666 (bool):
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | parse_data_df | def parse_data_df(data_dset, ridx, cidx, row_meta, col_meta):
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | get_column_metadata | def get_column_metadata(gctx_file_path, convert_neg_666=True):
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"""
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gctx.py | get_row_metadata | def get_row_metadata(gctx_file_path, convert_neg_666=True):
"""
Opens .gctx file and returns only row metadata
Input:
Mandatory:
- gctx_file_path (str): full path to gctx file you want to parse.
Optional:
- convert_neg_666 (bool): whether to convert -666 values to num
... | python | def get_row_metadata(gctx_file_path, convert_neg_666=True):
"""
Opens .gctx file and returns only row metadata
Input:
Mandatory:
- gctx_file_path (str): full path to gctx file you want to parse.
Optional:
- convert_neg_666 (bool): whether to convert -666 values to num
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cmap/cmapPy | cmapPy/pandasGEXpress/GCToo.py | multi_index_df_to_component_dfs | def multi_index_df_to_component_dfs(multi_index_df, rid="rid", cid="cid"):
""" Convert a multi-index df into 3 component dfs. """
# Id level of the multiindex will become the index
rids = list(multi_index_df.index.get_level_values(rid))
cids = list(multi_index_df.columns.get_level_values(cid))
# I... | python | def multi_index_df_to_component_dfs(multi_index_df, rid="rid", cid="cid"):
""" Convert a multi-index df into 3 component dfs. """
# Id level of the multiindex will become the index
rids = list(multi_index_df.index.get_level_values(rid))
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cmap/cmapPy | cmapPy/pandasGEXpress/GCToo.py | GCToo.check_df | def check_df(self, df):
"""
Verifies that df is a pandas DataFrame instance and
that its index and column values are unique.
"""
if isinstance(df, pd.DataFrame):
if not df.index.is_unique:
repeats = df.index[df.index.duplicated()].values
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"""
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cmap/cmapPy | cmapPy/pandasGEXpress/GCToo.py | GCToo.id_match_check | def id_match_check(self, data_df, meta_df, dim):
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- row case: index of data_df & index of row metadata
- col case: columns of data_df & index of column metadata
"""
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cmap/cmapPy | cmapPy/pandasGEXpress/GCToo.py | GCToo.assemble_multi_index_df | def assemble_multi_index_df(self):
"""Assembles three component dataframes into a multiindex dataframe.
Sets the result to self.multi_index_df.
IMPORTANT: Cross-section ("xs") is the best command for selecting
data. Be sure to use the flag "drop_level=False" with this command,
or... | python | def assemble_multi_index_df(self):
"""Assembles three component dataframes into a multiindex dataframe.
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cmap/cmapPy | cmapPy/pandasGEXpress/parse_gct.py | parse | def parse(file_path, convert_neg_666=True, rid=None, cid=None,
ridx=None, cidx=None, row_meta_only=False, col_meta_only=False, make_multiindex=False):
"""
The main method.
Args:
- file_path (string): full path to gct(x) file you want to parse
- convert_neg_666 (bool): whether to c... | python | def parse(file_path, convert_neg_666=True, rid=None, cid=None,
ridx=None, cidx=None, row_meta_only=False, col_meta_only=False, make_multiindex=False):
"""
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cmap/cmapPy | cmapPy/clue_api_client/gene_queries.py | are_genes_in_api | def are_genes_in_api(my_clue_api_client, gene_symbols):
"""determine if genes are present in the API
Args:
my_clue_api_client:
gene_symbols: collection of gene symbols to query the API with
Returns: set of the found gene symbols
"""
if len(gene_symbols) > 0:
query_gene_sym... | python | def are_genes_in_api(my_clue_api_client, gene_symbols):
"""determine if genes are present in the API
Args:
my_clue_api_client:
gene_symbols: collection of gene symbols to query the API with
Returns: set of the found gene symbols
"""
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cmap/cmapPy | cmapPy/pandasGEXpress/write_gct.py | write | def write(gctoo, out_fname, data_null="NaN", metadata_null="-666", filler_null="-666", data_float_format="%.4f"):
"""Write a gctoo object to a gct file.
Args:
gctoo (gctoo object)
out_fname (string): filename for output gct file
data_null (string): how to represent missing values in the... | python | def write(gctoo, out_fname, data_null="NaN", metadata_null="-666", filler_null="-666", data_float_format="%.4f"):
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cmap/cmapPy | cmapPy/pandasGEXpress/write_gct.py | write_version_and_dims | def write_version_and_dims(version, dims, f):
"""Write first two lines of gct file.
Args:
version (string): 1.3 by default
dims (list of strings): length = 4
f (file handle): handle of output file
Returns:
nothing
"""
f.write(("#" + version + "\n"))
f.write((dims... | python | def write_version_and_dims(version, dims, f):
"""Write first two lines of gct file.
Args:
version (string): 1.3 by default
dims (list of strings): length = 4
f (file handle): handle of output file
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cmap/cmapPy | cmapPy/pandasGEXpress/write_gct.py | write_top_half | def write_top_half(f, row_metadata_df, col_metadata_df, metadata_null, filler_null):
""" Write the top half of the gct file: top-left filler values, row metadata
headers, and top-right column metadata.
Args:
f (file handle): handle for output file
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cmap/cmapPy | cmapPy/pandasGEXpress/write_gct.py | write_bottom_half | def write_bottom_half(f, row_metadata_df, data_df, data_null, data_float_format, metadata_null):
""" Write the bottom half of the gct file: row metadata and data.
Args:
f (file handle): handle for output file
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cmap/cmapPy | cmapPy/pandasGEXpress/write_gct.py | append_dims_and_file_extension | def append_dims_and_file_extension(fname, data_df):
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N.B. Dimensions are cols x rows.
Args:
fname (string): output filename
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cmap/cmapPy | cmapPy/math/robust_zscore.py | robust_zscore | def robust_zscore(mat, ctrl_mat=None, min_mad=0.1):
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Args:
mat (pandas df): Matrix of data that z-scoring will be applied to
ctrl_mat (pandas df): Optional matrix from which to compute medians and MADs
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min_mad (float): M... | python | def robust_zscore(mat, ctrl_mat=None, min_mad=0.1):
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mat (pandas df): Matrix of data that z-scoring will be applied to
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cmap/cmapPy | cmapPy/pandasGEXpress/gct2gctx.py | gct2gctx_main | def gct2gctx_main(args):
""" Separate from main() in order to make command-line tool. """
in_gctoo = parse_gct.parse(args.filename, convert_neg_666=False)
if args.output_filepath is None:
basename = os.path.basename(args.filename)
out_name = os.path.splitext(basename)[0] + ".gctx"
else... | python | def gct2gctx_main(args):
""" Separate from main() in order to make command-line tool. """
in_gctoo = parse_gct.parse(args.filename, convert_neg_666=False)
if args.output_filepath is None:
basename = os.path.basename(args.filename)
out_name = os.path.splitext(basename)[0] + ".gctx"
else... | [
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cmap/cmapPy | cmapPy/pandasGEXpress/parse.py | parse | def parse(file_path, convert_neg_666=True, rid=None, cid=None, ridx=None, cidx=None,
row_meta_only=False, col_meta_only=False, make_multiindex=False):
"""
Identifies whether file_path corresponds to a .gct or .gctx file and calls the
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Input:
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row_meta_only=False, col_meta_only=False, make_multiindex=False):
"""
Identifies whether file_path corresponds to a .gct or .gctx file and calls the
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cmap/cmapPy | cmapPy/math/agg_wt_avg.py | get_upper_triangle | def get_upper_triangle(correlation_matrix):
''' Extract upper triangle from a square matrix. Negative values are
set to 0.
Args:
correlation_matrix (pandas df): Correlations between all replicates
Returns:
upper_tri_df (pandas df): Upper triangle extracted from
correlation_matrix; rid ... | python | def get_upper_triangle(correlation_matrix):
''' Extract upper triangle from a square matrix. Negative values are
set to 0.
Args:
correlation_matrix (pandas df): Correlations between all replicates
Returns:
upper_tri_df (pandas df): Upper triangle extracted from
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cmap/cmapPy | cmapPy/math/agg_wt_avg.py | calculate_weights | def calculate_weights(correlation_matrix, min_wt):
''' Calculate a weight for each profile based on its correlation to other
replicates. Negative correlations are clipped to 0, and weights are clipped
to be min_wt at the least.
Args:
correlation_matrix (pandas df): Correlations between all replicat... | python | def calculate_weights(correlation_matrix, min_wt):
''' Calculate a weight for each profile based on its correlation to other
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cmap/cmapPy | cmapPy/math/agg_wt_avg.py | agg_wt_avg | def agg_wt_avg(mat, min_wt = 0.01, corr_metric='spearman'):
''' Aggregate a set of replicate profiles into a single signature using
a weighted average.
Args:
mat (pandas df): a matrix of replicate profiles, where the columns are
samples and the rows are features; columns correspond to the
... | python | def agg_wt_avg(mat, min_wt = 0.01, corr_metric='spearman'):
''' Aggregate a set of replicate profiles into a single signature using
a weighted average.
Args:
mat (pandas df): a matrix of replicate profiles, where the columns are
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cmap/cmapPy | cmapPy/pandasGEXpress/concat.py | concat_main | def concat_main(args):
""" Separate method from main() in order to make testing easier and to
enable command-line access. """
# Get files directly
if args.input_filepaths is not None:
files = args.input_filepaths
# Or find them
else:
files = get_file_list(args.file_wildcard)
... | python | def concat_main(args):
""" Separate method from main() in order to make testing easier and to
enable command-line access. """
# Get files directly
if args.input_filepaths is not None:
files = args.input_filepaths
# Or find them
else:
files = get_file_list(args.file_wildcard)
... | [
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cmap/cmapPy | cmapPy/pandasGEXpress/concat.py | get_file_list | def get_file_list(wildcard):
""" Search for files to be concatenated. Currently very basic, but could
expand to be more sophisticated.
Args:
wildcard (regular expression string)
Returns:
files (list of full file paths)
"""
files = glob.glob(os.path.expanduser(wildcard))
re... | python | def get_file_list(wildcard):
""" Search for files to be concatenated. Currently very basic, but could
expand to be more sophisticated.
Args:
wildcard (regular expression string)
Returns:
files (list of full file paths)
"""
files = glob.glob(os.path.expanduser(wildcard))
re... | [
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cmap/cmapPy | cmapPy/pandasGEXpress/concat.py | hstack | def hstack(gctoos, remove_all_metadata_fields=False, error_report_file=None, fields_to_remove=[], reset_ids=False):
""" Horizontally concatenate gctoos.
Args:
gctoos (list of gctoo objects)
remove_all_metadata_fields (bool): ignore/strip all common metadata when combining gctoos
error_... | python | def hstack(gctoos, remove_all_metadata_fields=False, error_report_file=None, fields_to_remove=[], reset_ids=False):
""" Horizontally concatenate gctoos.
Args:
gctoos (list of gctoo objects)
remove_all_metadata_fields (bool): ignore/strip all common metadata when combining gctoos
error_... | [
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cmap/cmapPy | cmapPy/pandasGEXpress/concat.py | assemble_common_meta | def assemble_common_meta(common_meta_dfs, fields_to_remove, sources, remove_all_metadata_fields, error_report_file):
""" Assemble the common metadata dfs together. Both indices are sorted.
Fields that are not in all the dfs are dropped.
Args:
common_meta_dfs (list of pandas dfs)
fields_to_r... | python | def assemble_common_meta(common_meta_dfs, fields_to_remove, sources, remove_all_metadata_fields, error_report_file):
""" Assemble the common metadata dfs together. Both indices are sorted.
Fields that are not in all the dfs are dropped.
Args:
common_meta_dfs (list of pandas dfs)
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cmap/cmapPy | cmapPy/pandasGEXpress/concat.py | build_common_all_meta_df | def build_common_all_meta_df(common_meta_dfs, fields_to_remove, remove_all_metadata_fields):
"""
concatenate the entries in common_meta_dfs, removing columns selectively (fields_to_remove) or entirely (
remove_all_metadata_fields=True; in this case, effectively just merges all the indexes in common_meta... | python | def build_common_all_meta_df(common_meta_dfs, fields_to_remove, remove_all_metadata_fields):
"""
concatenate the entries in common_meta_dfs, removing columns selectively (fields_to_remove) or entirely (
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cmap/cmapPy | cmapPy/pandasGEXpress/concat.py | build_mismatched_common_meta_report | def build_mismatched_common_meta_report(common_meta_df_shapes, sources, all_meta_df, all_meta_df_with_dups):
"""
Generate a report (dataframe) that indicates for the common metadata that does not match across the common metadata
which source file had which of the different mismatch values
Args:
... | python | def build_mismatched_common_meta_report(common_meta_df_shapes, sources, all_meta_df, all_meta_df_with_dups):
"""
Generate a report (dataframe) that indicates for the common metadata that does not match across the common metadata
which source file had which of the different mismatch values
Args:
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