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OCA/openupgradelib | openupgradelib/openupgrade.py | update_workflow_workitems | def update_workflow_workitems(cr, pool, ref_spec_actions):
"""Find all the workflow items from the target state to set them to
the wanted state.
When a workflow action is removed, from model, the objects whose states
are in these actions need to be set to another to be able to continue the
workflow... | python | def update_workflow_workitems(cr, pool, ref_spec_actions):
"""Find all the workflow items from the target state to set them to
the wanted state.
When a workflow action is removed, from model, the objects whose states
are in these actions need to be set to another to be able to continue the
workflow... | [
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OCA/openupgradelib | openupgradelib/openupgrade.py | logged_query | def logged_query(cr, query, args=None, skip_no_result=False):
"""
Logs query and affected rows at level DEBUG.
:param query: a query string suitable to pass to cursor.execute()
:param args: a list, tuple or dictionary passed as substitution values
to cursor.execute().
:param skip_no_result: I... | python | def logged_query(cr, query, args=None, skip_no_result=False):
"""
Logs query and affected rows at level DEBUG.
:param query: a query string suitable to pass to cursor.execute()
:param args: a list, tuple or dictionary passed as substitution values
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OCA/openupgradelib | openupgradelib/openupgrade.py | update_module_names | def update_module_names(cr, namespec, merge_modules=False):
"""Deal with changed module names, making all the needed changes on the
related tables, like XML-IDs, translations, and so on.
:param namespec: list of tuples of (old name, new name)
:param merge_modules: Specify if the operation should be a m... | python | def update_module_names(cr, namespec, merge_modules=False):
"""Deal with changed module names, making all the needed changes on the
related tables, like XML-IDs, translations, and so on.
:param namespec: list of tuples of (old name, new name)
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OCA/openupgradelib | openupgradelib/openupgrade.py | add_ir_model_fields | def add_ir_model_fields(cr, columnspec):
"""
Typically, new columns on ir_model_fields need to be added in a very
early stage in the upgrade process of the base module, in raw sql
as they need to be in place before any model gets initialized.
Do not use for fields with additional SQL constraints, su... | python | def add_ir_model_fields(cr, columnspec):
"""
Typically, new columns on ir_model_fields need to be added in a very
early stage in the upgrade process of the base module, in raw sql
as they need to be in place before any model gets initialized.
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OCA/openupgradelib | openupgradelib/openupgrade.py | m2o_to_m2m | def m2o_to_m2m(cr, model, table, field, source_field):
"""
Recreate relations in many2many fields that were formerly
many2one fields. Use rename_columns in your pre-migrate
script to retain the column's old value, then call m2o_to_m2m
in your post-migrate script.
:param model: The target model ... | python | def m2o_to_m2m(cr, model, table, field, source_field):
"""
Recreate relations in many2many fields that were formerly
many2one fields. Use rename_columns in your pre-migrate
script to retain the column's old value, then call m2o_to_m2m
in your post-migrate script.
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OCA/openupgradelib | openupgradelib/openupgrade.py | message | def message(cr, module, table, column,
message, *args, **kwargs):
"""
Log handler for non-critical notifications about the upgrade.
To be extended with logging to a table for reporting purposes.
:param module: the module name that the message concerns
:param table: the model that this m... | python | def message(cr, module, table, column,
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"""
Log handler for non-critical notifications about the upgrade.
To be extended with logging to a table for reporting purposes.
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OCA/openupgradelib | openupgradelib/openupgrade.py | reactivate_workflow_transitions | def reactivate_workflow_transitions(cr, transition_conditions):
"""
Reactivate workflow transition previously deactivated by
deactivate_workflow_transitions.
:param transition_conditions: a dictionary returned by \
deactivate_workflow_transitions
.. versionadded:: 7.0
.. deprecated:: 11.0
... | python | def reactivate_workflow_transitions(cr, transition_conditions):
"""
Reactivate workflow transition previously deactivated by
deactivate_workflow_transitions.
:param transition_conditions: a dictionary returned by \
deactivate_workflow_transitions
.. versionadded:: 7.0
.. deprecated:: 11.0
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OCA/openupgradelib | openupgradelib/openupgrade.py | convert_field_to_html | def convert_field_to_html(cr, table, field_name, html_field_name):
"""
Convert field value to HTML value.
.. versionadded:: 7.0
"""
if version_info[0] < 7:
logger.error("You cannot use this method in an OpenUpgrade version "
"prior to 7.0.")
return
cr.execut... | python | def convert_field_to_html(cr, table, field_name, html_field_name):
"""
Convert field value to HTML value.
.. versionadded:: 7.0
"""
if version_info[0] < 7:
logger.error("You cannot use this method in an OpenUpgrade version "
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OCA/openupgradelib | openupgradelib/openupgrade.py | lift_constraints | def lift_constraints(cr, table, column):
"""Lift all constraints on column in table.
Typically, you use this in a pre-migrate script where you adapt references
for many2one fields with changed target objects.
If everything went right, the constraints will be recreated"""
cr.execute(
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"""Lift all constraints on column in table.
Typically, you use this in a pre-migrate script where you adapt references
for many2one fields with changed target objects.
If everything went right, the constraints will be recreated"""
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OCA/openupgradelib | openupgradelib/openupgrade.py | savepoint | def savepoint(cr):
"""return a context manager wrapping postgres savepoints"""
if hasattr(cr, 'savepoint'):
with cr.savepoint():
yield
else:
name = uuid.uuid1().hex
cr.execute('SAVEPOINT "%s"' % name)
try:
yield
cr.execute('RELEASE SAVEPOIN... | python | def savepoint(cr):
"""return a context manager wrapping postgres savepoints"""
if hasattr(cr, 'savepoint'):
with cr.savepoint():
yield
else:
name = uuid.uuid1().hex
cr.execute('SAVEPOINT "%s"' % name)
try:
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OCA/openupgradelib | openupgradelib/openupgrade.py | rename_property | def rename_property(cr, model, old_name, new_name):
"""Rename property old_name owned by model to new_name. This should happen
in a pre-migration script."""
cr.execute(
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"""Rename property old_name owned by model to new_name. This should happen
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cr.execute(
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OCA/openupgradelib | openupgradelib/openupgrade.py | delete_records_safely_by_xml_id | def delete_records_safely_by_xml_id(env, xml_ids):
"""This removes in the safest possible way the records whose XML-IDs are
passed as argument.
:param xml_ids: List of XML-ID string identifiers of the records to remove.
"""
for xml_id in xml_ids:
logger.debug('Deleting record for XML-ID %s'... | python | def delete_records_safely_by_xml_id(env, xml_ids):
"""This removes in the safest possible way the records whose XML-IDs are
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:param xml_ids: List of XML-ID string identifiers of the records to remove.
"""
for xml_id in xml_ids:
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OCA/openupgradelib | openupgradelib/openupgrade.py | chunked | def chunked(records, single=True):
""" Memory and performance friendly method to iterate over a potentially
large number of records. Yields either a whole chunk or a single record
at the time. Don't nest calls to this method. """
if version_info[0] > 10:
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""" Memory and performance friendly method to iterate over a potentially
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OCA/openupgradelib | openupgradelib/openupgrade_80.py | get_last_post_for_model | def get_last_post_for_model(cr, uid, ids, model_pool):
"""
Given a set of ids and a model pool, return a dict of each object ids with
their latest message date as a value.
To be called in post-migration scripts
:param cr: database cursor
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"""
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OCA/openupgradelib | openupgradelib/openupgrade_80.py | set_message_last_post | def set_message_last_post(cr, uid, pool, models):
"""
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To be called in post-migration scripts
:param cr: database cursor
:param uid: user id, assumed to be openerp.SUPERUSER_ID
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"""
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To be called in post-migration scripts
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OCA/openupgradelib | openupgradelib/openupgrade_tools.py | column_exists | def column_exists(cr, table, column):
""" Check whether a certain column exists """
cr.execute(
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""" Check whether a certain column exists """
cr.execute(
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crossbario/txaio | txaio/aio.py | start_logging | def start_logging(out=_stdout, level='info'):
"""
Begin logging.
:param out: if provided, a file-like object to log to. By default, this is
stdout.
:param level: the maximum log-level to emit (a string)
"""
global _log_level, _loggers, _started_logging
if level not in log_le... | python | def start_logging(out=_stdout, level='info'):
"""
Begin logging.
:param out: if provided, a file-like object to log to. By default, this is
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:param level: the maximum log-level to emit (a string)
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crossbario/txaio | txaio/aio.py | _AsyncioApi.create_failure | def create_failure(self, exception=None):
"""
This returns an object implementing IFailedFuture.
If exception is None (the default) we MUST be called within an
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"""
if exception:
ret... | python | def create_failure(self, exception=None):
"""
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crossbario/txaio | txaio/aio.py | _AsyncioApi.gather | def gather(self, futures, consume_exceptions=True):
"""
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"""
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crossbario/txaio | txaio/__init__.py | _use_framework | def _use_framework(module):
"""
Internal helper, to set this modules methods to a specified
framework helper-methods.
"""
import txaio
for method_name in __all__:
if method_name in ['use_twisted', 'use_asyncio']:
continue
setattr(txaio, method_name,
ge... | python | def _use_framework(module):
"""
Internal helper, to set this modules methods to a specified
framework helper-methods.
"""
import txaio
for method_name in __all__:
if method_name in ['use_twisted', 'use_asyncio']:
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crossbario/txaio | txaio/tx.py | start_logging | def start_logging(out=_stdout, level='info'):
"""
Start logging to the file-like object in ``out``. By default, this
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"""
global _loggers, _observer, _log_level, _started_logging
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crossbario/txaio | txaio/tx.py | Logger.set_log_level | def set_log_level(self, level, keep=True):
"""
Set the log level. If keep is True, then it will not change along with
global log changes.
"""
self._set_log_level(level)
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"""
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self._set_log_level(level)
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crossbario/txaio | txaio/tx.py | _TxApi.sleep | def sleep(self, delay):
"""
Inline sleep for use in co-routines.
:param delay: Time to sleep in seconds.
:type delay: float
"""
d = Deferred()
self._get_loop().callLater(delay, d.callback, None)
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"""
Inline sleep for use in co-routines.
:param delay: Time to sleep in seconds.
:type delay: float
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self._get_loop().callLater(delay, d.callback, None)
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crossbario/txaio | txaio/_common.py | _BatchedTimer._notify_bucket | def _notify_bucket(self, real_time):
"""
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empymod/empymod | empymod/utils.py | check_ab | def check_ab(ab, verb):
r"""Check source-receiver configuration.
This check-function is called from one of the modelling routines in
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Parameters
----------
ab : int
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r"""Check source-receiver configuration.
This check-function is called from one of the modelling routines in
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r"""Check dipole parameters.
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Parameters
----------
inp : list of floats or arrays
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empymod/empymod | empymod/utils.py | check_frequency | def check_frequency(freq, res, aniso, epermH, epermV, mpermH, mpermV, verb):
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This check-function is called from one of the modelling routines in
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This check-function is called from one of the modelling routines in
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----------
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empymod/empymod | empymod/utils.py | check_time_only | def check_time_only(time, signal, verb):
r"""Check time and signal parameters.
This check-function is called from one of the modelling routines in
:mod:`model`. Consult these modelling routines for a detailed description
of the input parameters.
Parameters
----------
time : array_like
... | python | def check_time_only(time, signal, verb):
r"""Check time and signal parameters.
This check-function is called from one of the modelling routines in
:mod:`model`. Consult these modelling routines for a detailed description
of the input parameters.
Parameters
----------
time : array_like
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empymod/empymod | empymod/utils.py | check_solution | def check_solution(solution, signal, ab, msrc, mrec):
r"""Check required solution with parameters.
This check-function is called from one of the modelling routines in
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of the input parameters.
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r"""Check required solution with parameters.
This check-function is called from one of the modelling routines in
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of the input parameters.
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empymod/empymod | empymod/utils.py | get_abs | def get_abs(msrc, mrec, srcazm, srcdip, recazm, recdip, verb):
r"""Get required ab's for given angles.
This check-function is called from one of the modelling routines in
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Parameters
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r"""Get required ab's for given angles.
This check-function is called from one of the modelling routines in
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empymod/empymod | empymod/utils.py | get_geo_fact | def get_geo_fact(ab, srcazm, srcdip, recazm, recdip, msrc, mrec):
r"""Get required geometrical scaling factor for given angles.
This check-function is called from one of the modelling routines in
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of the input parameters.
Pa... | python | def get_geo_fact(ab, srcazm, srcdip, recazm, recdip, msrc, mrec):
r"""Get required geometrical scaling factor for given angles.
This check-function is called from one of the modelling routines in
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empymod/empymod | empymod/utils.py | get_layer_nr | def get_layer_nr(inp, depth):
r"""Get number of layer in which inp resides.
Note:
If zinp is on a layer interface, the layer above the interface is chosen.
This check-function is called from one of the modelling routines in
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r"""Get number of layer in which inp resides.
Note:
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empymod/empymod | empymod/utils.py | get_off_ang | def get_off_ang(src, rec, nsrc, nrec, verb):
r"""Get depths, offsets, angles, hence spatial input parameters.
This check-function is called from one of the modelling routines in
:mod:`model`. Consult these modelling routines for a detailed description
of the input parameters.
Parameters
-----... | python | def get_off_ang(src, rec, nsrc, nrec, verb):
r"""Get depths, offsets, angles, hence spatial input parameters.
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empymod/empymod | empymod/utils.py | printstartfinish | def printstartfinish(verb, inp=None, kcount=None):
r"""Print start and finish with time measure and kernel count."""
if inp:
if verb > 1:
ttxt = str(timedelta(seconds=default_timer() - inp))
ktxt = ' '
if kcount:
ktxt += str(kcount) + ' kernel call(s)'... | python | def printstartfinish(verb, inp=None, kcount=None):
r"""Print start and finish with time measure and kernel count."""
if inp:
if verb > 1:
ttxt = str(timedelta(seconds=default_timer() - inp))
ktxt = ' '
if kcount:
ktxt += str(kcount) + ' kernel call(s)'... | [
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empymod/empymod | empymod/utils.py | set_minimum | def set_minimum(min_freq=None, min_time=None, min_off=None, min_res=None,
min_angle=None):
r"""
Set minimum values of parameters.
The given parameters are set to its minimum value if they are smaller.
Parameters
----------
min_freq : float, optional
Minimum frequency [H... | python | def set_minimum(min_freq=None, min_time=None, min_off=None, min_res=None,
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r"""
Set minimum values of parameters.
The given parameters are set to its minimum value if they are smaller.
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min_freq : float, optional
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Set minimum values of parameters.
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empymod/empymod | empymod/utils.py | get_minimum | def get_minimum():
r"""
Return the current minimum values.
Returns
-------
min_vals : dict
Dictionary of current minimum values with keys
- min_freq : float
- min_time : float
- min_off : float
- min_res : float
- min_angle : float
... | python | def get_minimum():
r"""
Return the current minimum values.
Returns
-------
min_vals : dict
Dictionary of current minimum values with keys
- min_freq : float
- min_time : float
- min_off : float
- min_res : float
- min_angle : float
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empymod/empymod | empymod/utils.py | _check_var | def _check_var(var, dtype, ndmin, name, shape=None, shape2=None):
r"""Return variable as array of dtype, ndmin; shape-checked."""
if var is None:
raise ValueError
var = np.array(var, dtype=dtype, copy=True, ndmin=ndmin)
if shape:
_check_shape(var, name, shape, shape2)
return var | python | def _check_var(var, dtype, ndmin, name, shape=None, shape2=None):
r"""Return variable as array of dtype, ndmin; shape-checked."""
if var is None:
raise ValueError
var = np.array(var, dtype=dtype, copy=True, ndmin=ndmin)
if shape:
_check_shape(var, name, shape, shape2)
return var | [
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empymod/empymod | empymod/utils.py | _strvar | def _strvar(a, prec='{:G}'):
r"""Return variable as a string to print, with given precision."""
return ' '.join([prec.format(i) for i in np.atleast_1d(a)]) | python | def _strvar(a, prec='{:G}'):
r"""Return variable as a string to print, with given precision."""
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empymod/empymod | empymod/utils.py | _check_min | def _check_min(par, minval, name, unit, verb):
r"""Check minimum value of parameter."""
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if par.shape == ():
scalar = True
par = np.atleast_1d(par)
if minval is not None:
ipar = np.where(par < minval)
par[ipar] = minval
if verb > 0 and np.size(ipar) ... | python | def _check_min(par, minval, name, unit, verb):
r"""Check minimum value of parameter."""
scalar = False
if par.shape == ():
scalar = True
par = np.atleast_1d(par)
if minval is not None:
ipar = np.where(par < minval)
par[ipar] = minval
if verb > 0 and np.size(ipar) ... | [
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empymod/empymod | empymod/utils.py | spline_backwards_hankel | def spline_backwards_hankel(ht, htarg, opt):
r"""Check opt if deprecated 'spline' is used.
Returns corrected htarg, opt.
r"""
# Ensure ht is all lowercase
ht = ht.lower()
# Only relevant for 'fht' and 'hqwe', not for 'quad'
if ht in ['fht', 'qwe', 'hqwe']:
# Get corresponding htar... | python | def spline_backwards_hankel(ht, htarg, opt):
r"""Check opt if deprecated 'spline' is used.
Returns corrected htarg, opt.
r"""
# Ensure ht is all lowercase
ht = ht.lower()
# Only relevant for 'fht' and 'hqwe', not for 'quad'
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empymod/empymod | empymod/model.py | gpr | def gpr(src, rec, depth, res, freqtime, cf, gain=None, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, xdirect=False,
ht='quad', htarg=None, ft='fft', ftarg=None, opt=None, loop=None,
verb=2):
r"""Return the Ground-Penetrating Radar signal.
THIS FUNCTION IS EXPERI... | python | def gpr(src, rec, depth, res, freqtime, cf, gain=None, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, xdirect=False,
ht='quad', htarg=None, ft='fft', ftarg=None, opt=None, loop=None,
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r"""Return the Ground-Penetrating Radar signal.
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empymod/empymod | empymod/model.py | dipole_k | def dipole_k(src, rec, depth, res, freq, wavenumber, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, verb=2):
r"""Return the electromagnetic wavenumber-domain field.
Calculate the electromagnetic wavenumber-domain field due to infinitesimal
small electric or magnetic dip... | python | def dipole_k(src, rec, depth, res, freq, wavenumber, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, verb=2):
r"""Return the electromagnetic wavenumber-domain field.
Calculate the electromagnetic wavenumber-domain field due to infinitesimal
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empymod/empymod | empymod/model.py | wavenumber | def wavenumber(src, rec, depth, res, freq, wavenumber, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, verb=2):
r"""Depreciated. Use `dipole_k` instead."""
# Issue warning
mesg = ("\n The use of `model.wavenumber` is deprecated and will " +
"be removed;\... | python | def wavenumber(src, rec, depth, res, freq, wavenumber, ab=11, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None, verb=2):
r"""Depreciated. Use `dipole_k` instead."""
# Issue warning
mesg = ("\n The use of `model.wavenumber` is deprecated and will " +
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empymod/empymod | empymod/model.py | tem | def tem(fEM, off, freq, time, signal, ft, ftarg, conv=True):
r"""Return the time-domain response of the frequency-domain response fEM.
This function is called from one of the above modelling routines. No
input-check is carried out here. See the main description of :mod:`model`
for information regarding... | python | def tem(fEM, off, freq, time, signal, ft, ftarg, conv=True):
r"""Return the time-domain response of the frequency-domain response fEM.
This function is called from one of the above modelling routines. No
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empymod/empymod | empymod/scripts/fdesign.py | save_filter | def save_filter(name, filt, full=None, path='filters'):
r"""Save DLF-filter and inversion output to plain text files."""
# First we'll save the filter using its internal routine.
# This will create the directory ./filters if it doesn't exist already.
filt.tofile(path)
# If full, we store the inver... | python | def save_filter(name, filt, full=None, path='filters'):
r"""Save DLF-filter and inversion output to plain text files."""
# First we'll save the filter using its internal routine.
# This will create the directory ./filters if it doesn't exist already.
filt.tofile(path)
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empymod/empymod | empymod/scripts/fdesign.py | load_filter | def load_filter(name, full=False, path='filters'):
r"""Load saved DLF-filter and inversion output from text files."""
# First we'll get the filter using its internal routine.
filt = DigitalFilter(name.split('.')[0])
filt.fromfile(path)
# If full, we get the inversion output
if full:
# ... | python | def load_filter(name, full=False, path='filters'):
r"""Load saved DLF-filter and inversion output from text files."""
# First we'll get the filter using its internal routine.
filt = DigitalFilter(name.split('.')[0])
filt.fromfile(path)
# If full, we get the inversion output
if full:
# ... | [
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empymod/empymod | empymod/scripts/fdesign.py | plot_result | def plot_result(filt, full, prntres=True):
r"""QC the inversion result.
Parameters
----------
- filt, full as returned from fdesign.design with full_output=True
- If prntres is True, it calls fdesign.print_result as well.
r"""
# Check matplotlib (soft dependency)
if not plt:
pr... | python | def plot_result(filt, full, prntres=True):
r"""QC the inversion result.
Parameters
----------
- filt, full as returned from fdesign.design with full_output=True
- If prntres is True, it calls fdesign.print_result as well.
r"""
# Check matplotlib (soft dependency)
if not plt:
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empymod/empymod | empymod/scripts/fdesign.py | print_result | def print_result(filt, full=None):
r"""Print best filter information.
Parameters
----------
- filt, full as returned from fdesign.design with full_output=True
"""
print(' Filter length : %d' % filt.base.size)
print(' Best filter')
if full: # If full provided, we have more infor... | python | def print_result(filt, full=None):
r"""Print best filter information.
Parameters
----------
- filt, full as returned from fdesign.design with full_output=True
"""
print(' Filter length : %d' % filt.base.size)
print(' Best filter')
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empymod/empymod | empymod/scripts/fdesign.py | _call_qc_transform_pairs | def _call_qc_transform_pairs(n, ispacing, ishift, fI, fC, r, r_def, reim):
r"""QC the input transform pairs."""
print('* QC: Input transform-pairs:')
print(' fC: x-range defined through ``n``, ``spacing``, ``shift``, and ' +
'``r``-parameters; b-range defined through ``r``-parameter.')
print(... | python | def _call_qc_transform_pairs(n, ispacing, ishift, fI, fC, r, r_def, reim):
r"""QC the input transform pairs."""
print('* QC: Input transform-pairs:')
print(' fC: x-range defined through ``n``, ``spacing``, ``shift``, and ' +
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empymod/empymod | empymod/scripts/fdesign.py | _plot_transform_pairs | def _plot_transform_pairs(fCI, r, k, axes, tit):
r"""Plot the input transform pairs."""
# Plot lhs
plt.sca(axes[0])
plt.title('|' + tit + ' lhs|')
for f in fCI:
if f.name == 'j2':
lhs = f.lhs(k)
plt.loglog(k, np.abs(lhs[0]), lw=2, label='j0')
plt.loglog(k... | python | def _plot_transform_pairs(fCI, r, k, axes, tit):
r"""Plot the input transform pairs."""
# Plot lhs
plt.sca(axes[0])
plt.title('|' + tit + ' lhs|')
for f in fCI:
if f.name == 'j2':
lhs = f.lhs(k)
plt.loglog(k, np.abs(lhs[0]), lw=2, label='j0')
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empymod/empymod | empymod/scripts/fdesign.py | _plot_inversion | def _plot_inversion(f, rhs, r, k, imin, spacing, shift, cvar):
r"""QC the resulting filter."""
# Check matplotlib (soft dependency)
if not plt:
print(plt_msg)
return
plt.figure("Inversion result "+f.name, figsize=(9.5, 4))
plt.subplots_adjust(wspace=.3, bottom=0.2)
plt.clf()
... | python | def _plot_inversion(f, rhs, r, k, imin, spacing, shift, cvar):
r"""QC the resulting filter."""
# Check matplotlib (soft dependency)
if not plt:
print(plt_msg)
return
plt.figure("Inversion result "+f.name, figsize=(9.5, 4))
plt.subplots_adjust(wspace=.3, bottom=0.2)
plt.clf()
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empymod/empymod | empymod/scripts/fdesign.py | empy_hankel | def empy_hankel(ftype, zsrc, zrec, res, freqtime, depth=None, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None,
htarg=None, verblhs=0, verbrhs=0):
r"""Numerical transform pair with empymod.
All parameters except ``ftype``, ``verblhs``, and ``verbrhs`` correspond to... | python | def empy_hankel(ftype, zsrc, zrec, res, freqtime, depth=None, aniso=None,
epermH=None, epermV=None, mpermH=None, mpermV=None,
htarg=None, verblhs=0, verbrhs=0):
r"""Numerical transform pair with empymod.
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empymod/empymod | empymod/scripts/fdesign.py | _get_min_val | def _get_min_val(spaceshift, *params):
r"""Calculate minimum resolved amplitude or maximum r."""
# Get parameters from tuples
spacing, shift = spaceshift
n, fI, fC, r, r_def, error, reim, cvar, verb, plot, log = params
# Get filter for these parameters
dlf = _calculate_filter(n, spacing, shift... | python | def _get_min_val(spaceshift, *params):
r"""Calculate minimum resolved amplitude or maximum r."""
# Get parameters from tuples
spacing, shift = spaceshift
n, fI, fC, r, r_def, error, reim, cvar, verb, plot, log = params
# Get filter for these parameters
dlf = _calculate_filter(n, spacing, shift... | [
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empymod/empymod | empymod/scripts/fdesign.py | _calculate_filter | def _calculate_filter(n, spacing, shift, fI, r_def, reim, name):
r"""Calculate filter for this spacing, shift, n."""
# Base :: For this n/spacing/shift
base = np.exp(spacing*(np.arange(n)-n//2) + shift)
# r :: Start/end is defined by base AND r_def[0]/r_def[1]
# Overdetermined system if r_def... | python | def _calculate_filter(n, spacing, shift, fI, r_def, reim, name):
r"""Calculate filter for this spacing, shift, n."""
# Base :: For this n/spacing/shift
base = np.exp(spacing*(np.arange(n)-n//2) + shift)
# r :: Start/end is defined by base AND r_def[0]/r_def[1]
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empymod/empymod | empymod/scripts/fdesign.py | _print_count | def _print_count(log):
r"""Print run-count information."""
log['cnt2'] += 1 # Current number
cp = log['cnt2']/log['totnr']*100 # Percentage
if log['cnt2'] == 0: # Not sure about this; brute seems to call the
pass # function with the first arguments twice...
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r"""Print run-count information."""
log['cnt2'] += 1 # Current number
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if log['cnt2'] == 0: # Not sure about this; brute seems to call the
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empymod/empymod | empymod/kernel.py | wavenumber | def wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV, zetaH, zetaV, lambd,
ab, xdirect, msrc, mrec, use_ne_eval):
r"""Calculate wavenumber domain solution.
Return the wavenumber domain solutions ``PJ0``, ``PJ1``, and ``PJ0b``,
which have to be transformed with a Hankel transform to the f... | python | def wavenumber(zsrc, zrec, lsrc, lrec, depth, etaH, etaV, zetaH, zetaV, lambd,
ab, xdirect, msrc, mrec, use_ne_eval):
r"""Calculate wavenumber domain solution.
Return the wavenumber domain solutions ``PJ0``, ``PJ1``, and ``PJ0b``,
which have to be transformed with a Hankel transform to the f... | [
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empymod/empymod | empymod/kernel.py | reflections | def reflections(depth, e_zH, Gam, lrec, lsrc, use_ne_eval):
r"""Calculate Rp, Rm.
.. math:: R^\pm_n, \bar{R}^\pm_n
This function corresponds to equations 64/65 and A-11/A-12 in
[HuTS15]_, and loosely to the corresponding files ``Rmin.F90`` and
``Rplus.F90``.
This function is called from the f... | python | def reflections(depth, e_zH, Gam, lrec, lsrc, use_ne_eval):
r"""Calculate Rp, Rm.
.. math:: R^\pm_n, \bar{R}^\pm_n
This function corresponds to equations 64/65 and A-11/A-12 in
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empymod/empymod | empymod/kernel.py | angle_factor | def angle_factor(angle, ab, msrc, mrec):
r"""Return the angle-dependent factor.
The whole calculation in the wavenumber domain is only a function of the
distance between the source and the receiver, it is independent of the
angel. The angle-dependency is this factor, which can be applied to the
cor... | python | def angle_factor(angle, ab, msrc, mrec):
r"""Return the angle-dependent factor.
The whole calculation in the wavenumber domain is only a function of the
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empymod/empymod | empymod/scripts/printinfo.py | versions | def versions(mode=None, add_pckg=None, ncol=4):
r"""Old func-way of class `Versions`, here for backwards compatibility.
``mode`` is not used any longer, dummy here.
"""
# Issue warning
mesg = ("\n Func `versions` is deprecated and will " +
"be removed; use Class `Versions` instead.")... | python | def versions(mode=None, add_pckg=None, ncol=4):
r"""Old func-way of class `Versions`, here for backwards compatibility.
``mode`` is not used any longer, dummy here.
"""
# Issue warning
mesg = ("\n Func `versions` is deprecated and will " +
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empymod/empymod | empymod/scripts/printinfo.py | Versions._repr_html_ | def _repr_html_(self):
"""HTML-rendered versions information."""
# Check ncol
ncol = int(self.ncol)
# Define html-styles
border = "border: 2px solid #fff;'"
def colspan(html, txt, ncol, nrow):
r"""Print txt in a row spanning whole table."""
html ... | python | def _repr_html_(self):
"""HTML-rendered versions information."""
# Check ncol
ncol = int(self.ncol)
# Define html-styles
border = "border: 2px solid #fff;'"
def colspan(html, txt, ncol, nrow):
r"""Print txt in a row spanning whole table."""
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empymod/empymod | empymod/scripts/printinfo.py | Versions._get_packages | def _get_packages(add_pckg):
r"""Create list of packages."""
# Mandatory packages
pckgs = [numpy, scipy, empymod]
# Optional packages
for module in [IPython, numexpr, matplotlib]:
if module:
pckgs += [module]
# Cast and add add_pckg
... | python | def _get_packages(add_pckg):
r"""Create list of packages."""
# Mandatory packages
pckgs = [numpy, scipy, empymod]
# Optional packages
for module in [IPython, numexpr, matplotlib]:
if module:
pckgs += [module]
# Cast and add add_pckg
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empymod/empymod | empymod/filters.py | DigitalFilter.tofile | def tofile(self, path='filters'):
r"""Save filter values to ascii-files.
Store the filter base and the filter coefficients in separate files
in the directory `path`; `path` can be a relative or absolute path.
Examples
--------
>>> import empymod
>>> # Load a fil... | python | def tofile(self, path='filters'):
r"""Save filter values to ascii-files.
Store the filter base and the filter coefficients in separate files
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empymod/empymod | empymod/filters.py | DigitalFilter.fromfile | def fromfile(self, path='filters'):
r"""Load filter values from ascii-files.
Load filter base and filter coefficients from ascii files in the
directory `path`; `path` can be a relative or absolute path.
Examples
--------
>>> import empymod
>>> # Create an empty ... | python | def fromfile(self, path='filters'):
r"""Load filter values from ascii-files.
Load filter base and filter coefficients from ascii files in the
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empymod/empymod | empymod/transform.py | fht | def fht(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab, etaH, etaV, zetaH,
zetaV, xdirect, fhtarg, use_ne_eval, msrc, mrec):
r"""Hankel Transform using the Digital Linear Filter method.
The *Digital Linear Filter* method was introduced to geophysics by
[Ghos70]_, and made popular and wide-spread b... | python | def fht(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab, etaH, etaV, zetaH,
zetaV, xdirect, fhtarg, use_ne_eval, msrc, mrec):
r"""Hankel Transform using the Digital Linear Filter method.
The *Digital Linear Filter* method was introduced to geophysics by
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empymod/empymod | empymod/transform.py | hquad | def hquad(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab, etaH, etaV, zetaH,
zetaV, xdirect, quadargs, use_ne_eval, msrc, mrec):
r"""Hankel Transform using the ``QUADPACK`` library.
This routine uses the ``scipy.integrate.quad`` module, which in turn makes
use of the Fortran library ``QUADPACK``... | python | def hquad(zsrc, zrec, lsrc, lrec, off, factAng, depth, ab, etaH, etaV, zetaH,
zetaV, xdirect, quadargs, use_ne_eval, msrc, mrec):
r"""Hankel Transform using the ``QUADPACK`` library.
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empymod/empymod | empymod/transform.py | ffht | def ffht(fEM, time, freq, ftarg):
r"""Fourier Transform using the Digital Linear Filter method.
It follows the Filter methodology [Ande75]_, using Cosine- and
Sine-filters; see ``fht`` for more information.
The function is called from one of the modelling routines in :mod:`model`.
Consult these m... | python | def ffht(fEM, time, freq, ftarg):
r"""Fourier Transform using the Digital Linear Filter method.
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empymod/empymod | empymod/transform.py | fft | def fft(fEM, time, freq, ftarg):
r"""Fourier Transform using the Fast Fourier Transform.
The function is called from one of the modelling routines in :mod:`model`.
Consult these modelling routines for a description of the input and output
parameters.
Returns
-------
tEM : array
Ret... | python | def fft(fEM, time, freq, ftarg):
r"""Fourier Transform using the Fast Fourier Transform.
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empymod/empymod | empymod/transform.py | quad | def quad(sPJ0r, sPJ0i, sPJ1r, sPJ1i, sPJ0br, sPJ0bi, ab, off, factAng, iinp):
r"""Quadrature for Hankel transform.
This is the kernel of the QUAD method, used for the Hankel transforms
``hquad`` and ``hqwe`` (where the integral is not suited for QWE).
"""
# Define the quadrature kernels
def q... | python | def quad(sPJ0r, sPJ0i, sPJ1r, sPJ1i, sPJ0br, sPJ0bi, ab, off, factAng, iinp):
r"""Quadrature for Hankel transform.
This is the kernel of the QUAD method, used for the Hankel transforms
``hquad`` and ``hqwe`` (where the integral is not suited for QWE).
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# Define the quadrature kernels
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empymod/empymod | empymod/transform.py | get_spline_values | def get_spline_values(filt, inp, nr_per_dec=None):
r"""Return required calculation points."""
# Standard DLF
if nr_per_dec == 0:
return filt.base/inp[:, None], inp
# Get min and max required out-values (depends on filter and inp-value)
outmax = filt.base[-1]/inp.min()
outmin = filt.bas... | python | def get_spline_values(filt, inp, nr_per_dec=None):
r"""Return required calculation points."""
# Standard DLF
if nr_per_dec == 0:
return filt.base/inp[:, None], inp
# Get min and max required out-values (depends on filter and inp-value)
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empymod/empymod | empymod/transform.py | fhti | def fhti(rmin, rmax, n, q, mu):
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logrc = (rmin + rmax)/2
# Central index (1/2 integral if n is even)
nc = (n + 1)/2.
# Log spacing of points
dlogr = (rmax - rmin)/n
dlnr = dlogr*np.log(10.)
... | python | def fhti(rmin, rmax, n, q, mu):
r"""Return parameters required for FFTLog."""
# Central point log10(r_c) of periodic interval
logrc = (rmin + rmax)/2
# Central index (1/2 integral if n is even)
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Warning! This function has the potential to crash the Python runtime.
Do not call it directly. Use the _get_cpu_info_from_cpuid function instead.
It will safely call this function in another process.
'''
# Pipe all output to nothing
sys.stdout = open(os.devnull, '... | python | def _actual_get_cpu_info_from_cpuid(queue):
'''
Warning! This function has the potential to crash the Python runtime.
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It will safely call this function in another process.
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workhorsy/py-cpuinfo | cpuinfo/cpuinfo.py | get_cpu_info_json | def get_cpu_info_json():
'''
Returns the CPU info by using the best sources of information for your OS.
Returns the result in a json string
'''
import json
output = None
# If running under pyinstaller, run normally
if getattr(sys, 'frozen', False):
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output = json.dumps(info... | python | def get_cpu_info_json():
'''
Returns the CPU info by using the best sources of information for your OS.
Returns the result in a json string
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import json
output = None
# If running under pyinstaller, run normally
if getattr(sys, 'frozen', False):
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Returns the CPU info by using the best sources of information for your OS.
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'''
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output = get_cpu_info_json()
# Convert JSON to Python with non unicode strings
output = json.loads(output, object_hook = _utf_to_str)
return output | python | def get_cpu_info():
'''
Returns the CPU info by using the best sources of information for your OS.
Returns the result in a dict
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import json
output = get_cpu_info_json()
# Convert JSON to Python with non unicode strings
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qmangle/qmangle/__init__.py | _verbs_with_subjects | def _verbs_with_subjects(doc):
"""Given a spacy document return the verbs that have subjects"""
# TODO: UNUSED
verb_subj = []
for possible_subject in doc:
if (possible_subject.dep_ == 'nsubj' and possible_subject.head.pos_ ==
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verb_subj.append([possible_subjec... | python | def _verbs_with_subjects(doc):
"""Given a spacy document return the verbs that have subjects"""
# TODO: UNUSED
verb_subj = []
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qmangle/qmangle/__init__.py | mangle_agreement | def mangle_agreement(correct_sentence):
"""Given a correct sentence, return a sentence or sentences with a subject
verb agreement error"""
# # Examples
#
# Back in the 1800s, people were much shorter and much stronger.
# This sentence begins with the introductory phrase, 'back in the 1800s'
... | python | def mangle_agreement(correct_sentence):
"""Given a correct sentence, return a sentence or sentences with a subject
verb agreement error"""
# # Examples
#
# Back in the 1800s, people were much shorter and much stronger.
# This sentence begins with the introductory phrase, 'back in the 1800s'
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/__init__.py | _build_trigram_indices | def _build_trigram_indices(trigram_index):
"""Build a dictionary of trigrams and their indices from a csv"""
result = {}
trigram_count = 0
for key, val in csv.reader(open(trigram_index)):
result[key] = int(val)
trigram_count += 1
return result, trigram_count | python | def _build_trigram_indices(trigram_index):
"""Build a dictionary of trigrams and their indices from a csv"""
result = {}
trigram_count = 0
for key, val in csv.reader(open(trigram_index)):
result[key] = int(val)
trigram_count += 1
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/__init__.py | _begins_with_one_of | def _begins_with_one_of(sentence, parts_of_speech):
"""Return True if the sentence or fragment begins with one of the parts of
speech in the list, else False"""
doc = nlp(sentence)
if doc[0].tag_ in parts_of_speech:
return True
return False | python | def _begins_with_one_of(sentence, parts_of_speech):
"""Return True if the sentence or fragment begins with one of the parts of
speech in the list, else False"""
doc = nlp(sentence)
if doc[0].tag_ in parts_of_speech:
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/__init__.py | get_language_tool_feedback | def get_language_tool_feedback(sentence):
"""Get matches from languagetool"""
payload = {'language':'en-US', 'text':sentence}
try:
r = requests.post(LT_SERVER, data=payload)
except requests.exceptions.ConnectionError as e:
raise requests.exceptions.ConnectionError('''The languagetool ser... | python | def get_language_tool_feedback(sentence):
"""Get matches from languagetool"""
payload = {'language':'en-US', 'text':sentence}
try:
r = requests.post(LT_SERVER, data=payload)
except requests.exceptions.ConnectionError as e:
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/__init__.py | is_participle_clause_fragment | def is_participle_clause_fragment(sentence):
"""Supply a sentence or fragment and recieve a confidence interval"""
# short circuit if sentence or fragment doesn't start with a participle
# past participles can sometimes look like adjectives -- ie, Tired
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"""Supply a sentence or fragment and recieve a confidence interval"""
# short circuit if sentence or fragment doesn't start with a participle
# past participles can sometimes look like adjectives -- ie, Tired
if not _begins_with_one_of(sentence, ['VBG', 'VBN'... | [
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/__init__.py | check | def check(sentence):
"""Supply a sentence or fragment and recieve feedback"""
# How we decide what to put as the human readable feedback
#
# Our order of prefence is,
#
# 1. Spelling errors.
# - A spelling error can change the sentence meaning
# 2. Subject-verb agreement errors
# ... | python | def check(sentence):
"""Supply a sentence or fragment and recieve feedback"""
# How we decide what to put as the human readable feedback
#
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#
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/examples/porcupine/app.py | list_submissions | def list_submissions():
"""List the past submissions with information about them"""
submissions = []
try:
submissions = session.query(Submission).all()
except SQLAlchemyError as e:
session.rollback()
return render_template('list_submissions.html', submissions=submissions) | python | def list_submissions():
"""List the past submissions with information about them"""
submissions = []
try:
submissions = session.query(Submission).all()
except SQLAlchemyError as e:
session.rollback()
return render_template('list_submissions.html', submissions=submissions) | [
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/examples/porcupine/app.py | get_submissions | def get_submissions():
"""API endpoint to get submissions in JSON format"""
print(request.args.to_dict())
print(request.args.get('search[value]'))
print(request.args.get('draw', 1))
# submissions = session.query(Submission).all()
if request.args.get('correct_filter', 'all') == 'all':
co... | python | def get_submissions():
"""API endpoint to get submissions in JSON format"""
print(request.args.to_dict())
print(request.args.get('search[value]'))
print(request.args.get('draw', 1))
# submissions = session.query(Submission).all()
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/examples/porcupine/app.py | check_sentence | def check_sentence():
"""Sole porcupine endpoint"""
text = ''
if request.method == 'POST':
text = request.form['text']
if not text:
error = 'No input'
flash_message = error
else:
fb = check(request.form['text'])
correct = False
... | python | def check_sentence():
"""Sole porcupine endpoint"""
text = ''
if request.method == 'POST':
text = request.form['text']
if not text:
error = 'No input'
flash_message = error
else:
fb = check(request.form['text'])
correct = False
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva_rb2.py | raise_double_modal_error | def raise_double_modal_error(verb_phrase_doc):
"""A modal auxilary verb should not follow another modal auxilary verb"""
prev_word = None
for word in verb_phrase:
if word.tag_ == 'MD' and prev_word.tag == 'MD':
raise('DoubleModalError')
prev_word = word | python | def raise_double_modal_error(verb_phrase_doc):
"""A modal auxilary verb should not follow another modal auxilary verb"""
prev_word = None
for word in verb_phrase:
if word.tag_ == 'MD' and prev_word.tag == 'MD':
raise('DoubleModalError')
prev_word = word | [
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva_rb2.py | raise_modal_error | def raise_modal_error(verb_phrase_doc):
"""Given a verb phrase, raise an error if the modal auxilary has an issue
with it"""
verb_phrase = verb_phrase_doc.text.lower()
bad_strings = ['should had', 'should has', 'could had', 'could has', 'would '
'had', 'would has'] ["should", "could", "would... | python | def raise_modal_error(verb_phrase_doc):
"""Given a verb phrase, raise an error if the modal auxilary has an issue
with it"""
verb_phrase = verb_phrase_doc.text.lower()
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva_rb2.py | split_infinitive_warning | def split_infinitive_warning(sentence_str):
"""Return a warning for a split infinitive, else, None"""
sent_doc = textacy.Doc(sentence_str, lang='en_core_web_lg')
inf_pattern = r'<PART><ADV><VERB>' # To aux/auxpass* csubj
infinitives = textacy.extract.pos_regex_matches(sent_doc, inf_pattern)
for inf ... | python | def split_infinitive_warning(sentence_str):
"""Return a warning for a split infinitive, else, None"""
sent_doc = textacy.Doc(sentence_str, lang='en_core_web_lg')
inf_pattern = r'<PART><ADV><VERB>' # To aux/auxpass* csubj
infinitives = textacy.extract.pos_regex_matches(sent_doc, inf_pattern)
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva_rb2.py | raise_infinitive_error | def raise_infinitive_error(sentence_str):
"""Given a string, check that all infinitives are properly formatted"""
sent_doc = textacy.Doc(sentence_str, lang='en_core_web_lg')
inf_pattern = r'<PART|ADP><VERB>' # To aux/auxpass* csubj
infinitives = textacy.extract.pos_regex_matches(sent_doc, inf_pattern)
... | python | def raise_infinitive_error(sentence_str):
"""Given a string, check that all infinitives are properly formatted"""
sent_doc = textacy.Doc(sentence_str, lang='en_core_web_lg')
inf_pattern = r'<PART|ADP><VERB>' # To aux/auxpass* csubj
infinitives = textacy.extract.pos_regex_matches(sent_doc, inf_pattern)
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva_rb2.py | drop_modifiers | def drop_modifiers(sentence_str):
"""Given a string, drop the modifiers and return a string
without them"""
tdoc = textacy.Doc(sentence_str, lang='en_core_web_lg')
new_sent = tdoc.text
unusual_char = '形'
for tag in tdoc:
if tag.dep_.endswith('mod'):
# Replace the tag
... | python | def drop_modifiers(sentence_str):
"""Given a string, drop the modifiers and return a string
without them"""
tdoc = textacy.Doc(sentence_str, lang='en_core_web_lg')
new_sent = tdoc.text
unusual_char = '形'
for tag in tdoc:
if tag.dep_.endswith('mod'):
# Replace the tag
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empirical-org/Quill-NLP-Tools-and-Datasets | quillnlp/cluster.py | cluster | def cluster(list_of_texts, num_clusters=3):
"""
Cluster a list of texts into a predefined number of clusters.
:param list_of_texts: a list of untokenized texts
:param num_clusters: the predefined number of clusters
:return: a list with the cluster id for each text, e.g. [0,1,0,0,2,2,1]
"""
... | python | def cluster(list_of_texts, num_clusters=3):
"""
Cluster a list of texts into a predefined number of clusters.
:param list_of_texts: a list of untokenized texts
:param num_clusters: the predefined number of clusters
:return: a list with the cluster id for each text, e.g. [0,1,0,0,2,2,1]
"""
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empirical-org/Quill-NLP-Tools-and-Datasets | quillnlp/topics.py | find_topics | def find_topics(token_lists, num_topics=10):
""" Find the topics in a list of texts with Latent Dirichlet Allocation. """
dictionary = Dictionary(token_lists)
print('Number of unique words in original documents:', len(dictionary))
dictionary.filter_extremes(no_below=2, no_above=0.7)
print('Number o... | python | def find_topics(token_lists, num_topics=10):
""" Find the topics in a list of texts with Latent Dirichlet Allocation. """
dictionary = Dictionary(token_lists)
print('Number of unique words in original documents:', len(dictionary))
dictionary.filter_extremes(no_below=2, no_above=0.7)
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empirical-org/Quill-NLP-Tools-and-Datasets | scrapers/gutenfetch/gutenfetch/__init__.py | fetch_bookshelf | def fetch_bookshelf(start_url, output_dir):
"""Fetch all the books off of a gutenberg project bookshelf page
example bookshelf page,
http://www.gutenberg.org/wiki/Children%27s_Fiction_(Bookshelf)
"""
# make output directory
try:
os.mkdir(OUTPUT_DIR + output_dir)
except OSError as e:... | python | def fetch_bookshelf(start_url, output_dir):
"""Fetch all the books off of a gutenberg project bookshelf page
example bookshelf page,
http://www.gutenberg.org/wiki/Children%27s_Fiction_(Bookshelf)
"""
# make output directory
try:
os.mkdir(OUTPUT_DIR + output_dir)
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empirical-org/Quill-NLP-Tools-and-Datasets | quillnlp/preprocess.py | lemmatize | def lemmatize(text, lowercase=True, remove_stopwords=True):
""" Return the lemmas of the tokens in a text. """
doc = nlp(text)
if lowercase and remove_stopwords:
lemmas = [t.lemma_.lower() for t in doc if not (t.is_stop or t.orth_.lower() in STOPWORDS)]
elif lowercase:
lemmas = [t.lemma_... | python | def lemmatize(text, lowercase=True, remove_stopwords=True):
""" Return the lemmas of the tokens in a text. """
doc = nlp(text)
if lowercase and remove_stopwords:
lemmas = [t.lemma_.lower() for t in doc if not (t.is_stop or t.orth_.lower() in STOPWORDS)]
elif lowercase:
lemmas = [t.lemma_... | [
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva.py | inflate | def inflate(deflated_vector):
"""Given a defalated vector, inflate it into a np array and return it"""
dv = json.loads(deflated_vector)
#result = np.zeros(dv['reductions']) # some claim vector length 5555, others
#5530. this could have occurred doing remote computations? or something.
# anyhow, we w... | python | def inflate(deflated_vector):
"""Given a defalated vector, inflate it into a np array and return it"""
dv = json.loads(deflated_vector)
#result = np.zeros(dv['reductions']) # some claim vector length 5555, others
#5530. this could have occurred doing remote computations? or something.
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/sva.py | text_to_vector | def text_to_vector(sent_str):
"""Given a string, get it's defalted vector, inflate it, then return the
inflated vector"""
r = requests.get("{}/sva/vector".format(VECTORIZE_API), params={'s':sent_str})
return inflate(r.text) | python | def text_to_vector(sent_str):
"""Given a string, get it's defalted vector, inflate it, then return the
inflated vector"""
r = requests.get("{}/sva/vector".format(VECTORIZE_API), params={'s':sent_str})
return inflate(r.text) | [
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/infinitive_phrase_detect.py | detect_missing_verb | def detect_missing_verb(sentence):
"""Return True if the sentence appears to be missing a main verb"""
# TODO: should this be relocated?
doc = nlp(sentence)
for w in doc:
if w.tag_.startswith('VB') and w.dep_ == 'ROOT':
return False # looks like there is at least 1 main verb
retu... | python | def detect_missing_verb(sentence):
"""Return True if the sentence appears to be missing a main verb"""
# TODO: should this be relocated?
doc = nlp(sentence)
for w in doc:
if w.tag_.startswith('VB') and w.dep_ == 'ROOT':
return False # looks like there is at least 1 main verb
retu... | [
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empirical-org/Quill-NLP-Tools-and-Datasets | utils/qfragment/qfragment/infinitive_phrase_detect.py | detect_infinitive_phrase | def detect_infinitive_phrase(sentence):
"""Given a string, return true if it is an infinitive phrase fragment"""
# eliminate sentences without to
if not 'to' in sentence.lower():
return False
doc = nlp(sentence)
prev_word = None
for w in doc:
# if statement will execute exactly... | python | def detect_infinitive_phrase(sentence):
"""Given a string, return true if it is an infinitive phrase fragment"""
# eliminate sentences without to
if not 'to' in sentence.lower():
return False
doc = nlp(sentence)
prev_word = None
for w in doc:
# if statement will execute exactly... | [
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empirical-org/Quill-NLP-Tools-and-Datasets | quillnlp/srl.py | perform_srl | def perform_srl(responses, prompt):
""" Perform semantic role labeling on a list of responses, given a prompt."""
predictor = Predictor.from_path("https://s3-us-west-2.amazonaws.com/allennlp/models/srl-model-2018.05.25.tar.gz")
sentences = [{"sentence": prompt + " " + response} for response in responses]
... | python | def perform_srl(responses, prompt):
""" Perform semantic role labeling on a list of responses, given a prompt."""
predictor = Predictor.from_path("https://s3-us-west-2.amazonaws.com/allennlp/models/srl-model-2018.05.25.tar.gz")
sentences = [{"sentence": prompt + " " + response} for response in responses]
... | [
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] | f2ff579ddf3a556d9cdc47c5f702422fa06863d9 | https://github.com/empirical-org/Quill-NLP-Tools-and-Datasets/blob/f2ff579ddf3a556d9cdc47c5f702422fa06863d9/quillnlp/srl.py#L4-L16 | train |
empirical-org/Quill-NLP-Tools-and-Datasets | quillnlp/utils.py | detokenize | def detokenize(s):
""" Detokenize a string by removing spaces before punctuation."""
print(s)
s = re.sub("\s+([;:,\.\?!])", "\\1", s)
s = re.sub("\s+(n't)", "\\1", s)
return s | python | def detokenize(s):
""" Detokenize a string by removing spaces before punctuation."""
print(s)
s = re.sub("\s+([;:,\.\?!])", "\\1", s)
s = re.sub("\s+(n't)", "\\1", s)
return s | [
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] | f2ff579ddf3a556d9cdc47c5f702422fa06863d9 | https://github.com/empirical-org/Quill-NLP-Tools-and-Datasets/blob/f2ff579ddf3a556d9cdc47c5f702422fa06863d9/quillnlp/utils.py#L4-L9 | train |
ejeschke/ginga | ginga/misc/Task.py | Task.start | def start(self):
"""This method starts a task executing and returns immediately.
Subclass should override this method, if it has an asynchronous
way to start the task and return immediately.
"""
if self.threadPool:
self.threadPool.addTask(self)
# Lets oth... | python | def start(self):
"""This method starts a task executing and returns immediately.
Subclass should override this method, if it has an asynchronous
way to start the task and return immediately.
"""
if self.threadPool:
self.threadPool.addTask(self)
# Lets oth... | [
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Subclass should override this method, if it has an asynchronous
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