sentence1 stringlengths 52 3.87M | sentence2 stringlengths 1 47.2k | label stringclasses 1
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|---|---|---|
def multis_2_mono(table):
"""
Converts each multiline string in a table to single line.
Parameters
----------
table : list of list of str
A list of rows containing strings
Returns
-------
table : list of lists of str
"""
for row in range(len(table)):
for column ... | Converts each multiline string in a table to single line.
Parameters
----------
table : list of list of str
A list of rows containing strings
Returns
-------
table : list of lists of str | entailment |
def get_html_row_count(spans):
"""Get the number of rows"""
if spans == []:
return 0
row_counts = {}
for span in spans:
span = sorted(span)
try:
row_counts[str(span[0][1])] += get_span_row_count(span)
except KeyError:
row_counts[str(span[0][1])] =... | Get the number of rows | entailment |
def levenshtein_distance(word1, word2):
"""
Computes the Levenshtein distance.
[Reference]: https://en.wikipedia.org/wiki/Levenshtein_distance
[Article]: Levenshtein, Vladimir I. (February 1966). "Binary codes capable of correcting deletions,
insertions,and reversals". Soviet Physics Doklady 10... | Computes the Levenshtein distance.
[Reference]: https://en.wikipedia.org/wiki/Levenshtein_distance
[Article]: Levenshtein, Vladimir I. (February 1966). "Binary codes capable of correcting deletions,
insertions,and reversals". Soviet Physics Doklady 10 (8): 707–710.
[Implementation]: https://en.wiki... | entailment |
def better_ts_function(f):
'''Decorator which check if timeseries has a better
implementation of the function.'''
fname = f.__name__
def _(ts, *args, **kwargs):
func = getattr(ts, fname, None)
if func:
return func(*args, **kwargs)
else:
return f(ts... | Decorator which check if timeseries has a better
implementation of the function. | entailment |
def zscore(ts, **kwargs):
'''Rolling Z-Score statistics.
The Z-score is more formally known as ``standardised residuals``.
To calculate the standardised residuals of a data set,
the average value and the standard deviation of the data value
have to be estimated.
.. math::
z = ... | Rolling Z-Score statistics.
The Z-score is more formally known as ``standardised residuals``.
To calculate the standardised residuals of a data set,
the average value and the standard deviation of the data value
have to be estimated.
.. math::
z = \frac{x - \mu(x)}{\sigma(x)} | entailment |
def prange(ts, **kwargs):
'''Rolling Percentage range.
Value between 0 and 1 indicating the position in the rolling range.
'''
mi = ts.rollmin(**kwargs)
ma = ts.rollmax(**kwargs)
return (ts - mi)/(ma - mi) | Rolling Percentage range.
Value between 0 and 1 indicating the position in the rolling range. | entailment |
def bindata(data, maxbins = 30, reduction = 0.1):
'''
data must be numeric list with a len above 20
This function counts the number of data points in a reduced array
'''
tole = 0.01
N = len(data)
assert N > 20
vmin = min(data)
vmax = max(data)
DV = vmax - vmin
tol = tole*DV
vmax += t... | data must be numeric list with a len above 20
This function counts the number of data points in a reduced array | entailment |
def binOp(op, indx, amap, bmap, fill_vec):
'''
Combines the values from two map objects using the indx values
using the op operator. In situations where there is a missing value
it will use the callable function handle_missing
'''
def op_or_missing(id):
va = amap.get(id, None)
... | Combines the values from two map objects using the indx values
using the op operator. In situations where there is a missing value
it will use the callable function handle_missing | entailment |
def _toVec(shape, val):
'''
takes a single value and creates a vecotor / matrix with that value filled
in it
'''
mat = np.empty(shape)
mat.fill(val)
return mat | takes a single value and creates a vecotor / matrix with that value filled
in it | entailment |
def center_line(space, line):
"""
Add leading & trailing space to text to center it within an allowed
width
Parameters
----------
space : int
The maximum character width allowed for the text. If the length
of text is more than this value, no space will be added.\
line : str
... | Add leading & trailing space to text to center it within an allowed
width
Parameters
----------
space : int
The maximum character width allowed for the text. If the length
of text is more than this value, no space will be added.\
line : str
The text that will be centered.
... | entailment |
def register(self, function):
"""Register a function in the function registry.
The function will be automatically instantiated if not already an
instance.
"""
function = inspect.isclass(function) and function() or function
name = function.name
self[name] = ... | Register a function in the function registry.
The function will be automatically instantiated if not already an
instance. | entailment |
def unregister(self, name):
"""Unregister function by name.
"""
try:
name = name.name
except AttributeError:
pass
return self.pop(name,None) | Unregister function by name. | entailment |
def row_includes_spans(table, row, spans):
"""
Determine if there are spans within a row
Parameters
----------
table : list of lists of str
row : int
spans : list of lists of lists of int
Returns
-------
bool
Whether or not a table's row includes spans
"""
for c... | Determine if there are spans within a row
Parameters
----------
table : list of lists of str
row : int
spans : list of lists of lists of int
Returns
-------
bool
Whether or not a table's row includes spans | entailment |
def _setup_states(state_definitions, prev=()):
"""Create a StateList object from a 'states' Workflow attribute."""
states = list(prev)
for state_def in state_definitions:
if len(state_def) != 2:
raise TypeError(
"The 'state' attribute of a workflow should be "
... | Create a StateList object from a 'states' Workflow attribute. | entailment |
def _setup_transitions(tdef, states, prev=()):
"""Create a TransitionList object from a 'transitions' Workflow attribute.
Args:
tdef: list of transition definitions
states (StateList): already parsed state definitions.
prev (TransitionList): transition definitions from a parent.
Re... | Create a TransitionList object from a 'transitions' Workflow attribute.
Args:
tdef: list of transition definitions
states (StateList): already parsed state definitions.
prev (TransitionList): transition definitions from a parent.
Returns:
TransitionList: the list of transitions... | entailment |
def transition(trname='', field='', check=None, before=None, after=None):
"""Decorator to declare a function as a transition implementation."""
if is_callable(trname):
raise ValueError(
"The @transition decorator should be called as "
"@transition(['transition_name'], **kwargs)")... | Decorator to declare a function as a transition implementation. | entailment |
def _make_hook_dict(fun):
"""Ensure the given function has a xworkflows_hook attribute.
That attribute has the following structure:
>>> {
... 'before': [('state', <TransitionHook>), ...],
... }
"""
if not hasattr(fun, 'xworkflows_hook'):
fun.xworkflows_hook = {
HOOK_... | Ensure the given function has a xworkflows_hook attribute.
That attribute has the following structure:
>>> {
... 'before': [('state', <TransitionHook>), ...],
... } | entailment |
def _match_state(self, state):
"""Checks whether a given State matches self.names."""
return (self.names == '*'
or state in self.names
or state.name in self.names) | Checks whether a given State matches self.names. | entailment |
def _match_transition(self, transition):
"""Checks whether a given Transition matches self.names."""
return (self.names == '*'
or transition in self.names
or transition.name in self.names) | Checks whether a given Transition matches self.names. | entailment |
def applies_to(self, transition, from_state=None):
"""Whether this hook applies to the given transition/state.
Args:
transition (Transition): the transition to check
from_state (State or None): the state to check. If absent, the check
is 'might this hook apply to... | Whether this hook applies to the given transition/state.
Args:
transition (Transition): the transition to check
from_state (State or None): the state to check. If absent, the check
is 'might this hook apply to the related transition, given a
valid source ... | entailment |
def _pre_transition_checks(self):
"""Run the pre-transition checks."""
current_state = getattr(self.instance, self.field_name)
if current_state not in self.transition.source:
raise InvalidTransitionError(
"Transition '%s' isn't available from state '%s'." %
... | Run the pre-transition checks. | entailment |
def _filter_hooks(self, *hook_kinds):
"""Filter a list of hooks, keeping only applicable ones."""
hooks = sum((self.hooks.get(kind, []) for kind in hook_kinds), [])
return sorted(hook for hook in hooks
if hook.applies_to(self.transition, self.current_state)) | Filter a list of hooks, keeping only applicable ones. | entailment |
def _post_transition(self, result, *args, **kwargs):
"""Performs post-transition actions."""
for hook in self._filter_hooks(HOOK_AFTER, HOOK_ON_ENTER):
hook(self.instance, result, *args, **kwargs) | Performs post-transition actions. | entailment |
def load_parent_implems(self, parent_implems):
"""Import previously defined implementations.
Args:
parent_implems (ImplementationList): List of implementations defined
in a parent class.
"""
for trname, attr, implem in parent_implems.get_custom_implementation... | Import previously defined implementations.
Args:
parent_implems (ImplementationList): List of implementations defined
in a parent class. | entailment |
def add_implem(self, transition, attribute, function, **kwargs):
"""Add an implementation.
Args:
transition (Transition): the transition for which the implementation
is added
attribute (str): the name of the attribute where the implementation
will... | Add an implementation.
Args:
transition (Transition): the transition for which the implementation
is added
attribute (str): the name of the attribute where the implementation
will be available
function (callable): the actual implementation fun... | entailment |
def should_collect(self, value):
"""Decide whether a given value should be collected."""
return (
# decorated with @transition
isinstance(value, TransitionWrapper)
# Relates to a compatible transition
and value.trname in self.workflow.transitions
... | Decide whether a given value should be collected. | entailment |
def collect(self, attrs):
"""Collect the implementations from a given attributes dict."""
for name, value in attrs.items():
if self.should_collect(value):
transition = self.workflow.transitions[value.trname]
if (
value.trname in self.... | Collect the implementations from a given attributes dict. | entailment |
def get_custom_implementations(self):
"""Retrieve a list of cutom implementations.
Yields:
(str, str, ImplementationProperty) tuples: The name of the attribute
an implementation lives at, the name of the related transition,
and the related implementation.
... | Retrieve a list of cutom implementations.
Yields:
(str, str, ImplementationProperty) tuples: The name of the attribute
an implementation lives at, the name of the related transition,
and the related implementation. | entailment |
def register_function_hooks(self, func):
"""Looks at an object method and registers it for relevent transitions."""
for hook_kind, hooks in func.xworkflows_hook.items():
for field_name, hook in hooks:
if field_name and field_name != self.state_field:
conti... | Looks at an object method and registers it for relevent transitions. | entailment |
def _may_override(self, implem, other):
"""Checks whether an ImplementationProperty may override an attribute."""
if isinstance(other, ImplementationProperty):
# Overriding another custom implementation for the same transition
# and field
return (other.transition == i... | Checks whether an ImplementationProperty may override an attribute. | entailment |
def fill_attrs(self, attrs):
"""Update the 'attrs' dict with generated ImplementationProperty."""
for trname, attrname in self.transitions_at.items():
implem = self.implementations[trname]
if attrname in attrs:
conflicting = attrs[attrname]
if no... | Update the 'attrs' dict with generated ImplementationProperty. | entailment |
def transform(self, attrs):
"""Perform all actions on a given attribute dict."""
self.collect(attrs)
self.add_missing_implementations()
self.fill_attrs(attrs) | Perform all actions on a given attribute dict. | entailment |
def log_transition(self, transition, from_state, instance, *args, **kwargs):
"""Log a transition.
Args:
transition (Transition): the name of the performed transition
from_state (State): the source state
instance (object): the modified object
Kwargs:
... | Log a transition.
Args:
transition (Transition): the name of the performed transition
from_state (State): the source state
instance (object): the modified object
Kwargs:
Any passed when calling the transition | entailment |
def _add_workflow(mcs, field_name, state_field, attrs):
"""Attach a workflow to the attribute list (create a StateProperty)."""
attrs[field_name] = StateProperty(state_field.workflow, field_name) | Attach a workflow to the attribute list (create a StateProperty). | entailment |
def _find_workflows(mcs, attrs):
"""Finds all occurrences of a workflow in the attributes definitions.
Returns:
dict(str => StateField): maps an attribute name to a StateField
describing the related Workflow.
"""
workflows = {}
for attribute, value in... | Finds all occurrences of a workflow in the attributes definitions.
Returns:
dict(str => StateField): maps an attribute name to a StateField
describing the related Workflow. | entailment |
def _add_transitions(mcs, field_name, workflow, attrs, implems=None):
"""Collect and enhance transition definitions to a workflow.
Modifies the 'attrs' dict in-place.
Args:
field_name (str): name of the field transitions should update
workflow (Workflow): workflow we're... | Collect and enhance transition definitions to a workflow.
Modifies the 'attrs' dict in-place.
Args:
field_name (str): name of the field transitions should update
workflow (Workflow): workflow we're working on
attrs (dict): dictionary of attributes to be updated.
... | entailment |
def update(self):
"Updates cartesian coordinates for drawing tree graph"
# get new shape and clear for attrs
self.edges = np.zeros((self.ttree.nnodes - 1, 2), dtype=int)
self.verts = np.zeros((self.ttree.nnodes, 2), dtype=float)
self.lines = []
self.coords =... | Updates cartesian coordinates for drawing tree graph | entailment |
def update_idxs(self):
"set root idx highest, tip idxs lowest ordered as ladderized"
# internal nodes: root is highest idx
idx = self.ttree.nnodes - 1
for node in self.ttree.treenode.traverse("levelorder"):
if not node.is_leaf():
node.add_feature("idx", idx)
... | set root idx highest, tip idxs lowest ordered as ladderized | entailment |
def update_fixed_order(self):
"after pruning fixed order needs update to match new nnodes/ntips."
# set tips order if fixing for multi-tree plotting (default None)
fixed_order = self.ttree._fixed_order
self.ttree_fixed_order = None
self.ttree_fixed_idx = list(range(self.ttree.nti... | after pruning fixed order needs update to match new nnodes/ntips. | entailment |
def assign_vertices(self):
"""
Sets .edges, .verts for node positions.
X and Y positions here refer to base assumption that tree is right
facing, reorient_coordinates() will handle re-translating this.
"""
# shortname
uselen = bool(self.ttree.style.use_e... | Sets .edges, .verts for node positions.
X and Y positions here refer to base assumption that tree is right
facing, reorient_coordinates() will handle re-translating this. | entailment |
def reorient_coordinates(self):
"""
Returns a modified .verts array with new coordinates for nodes.
This does not need to modify .edges. The order of nodes, and therefore
of verts rows is still the same because it is still based on the tree
branching order (ladderized usually). ... | Returns a modified .verts array with new coordinates for nodes.
This does not need to modify .edges. The order of nodes, and therefore
of verts rows is still the same because it is still based on the tree
branching order (ladderized usually). | entailment |
def tsiterator(ts, dateconverter=None, desc=None,
clean=False, start_value=None, **kwargs):
'''An iterator of timeseries as tuples.'''
dateconverter = dateconverter or default_converter
yield ['Date'] + ts.names()
if clean == 'full':
for dt, value in full_clean(ts, dateconverter, ... | An iterator of timeseries as tuples. | entailment |
def set_baselines(self):
"""
Modify coords to shift tree position for x,y baseline arguments. This
is useful for arrangeing trees onto a Canvas with other plots, but
still sharing a common cartesian axes coordinates.
"""
if self.style.xbaseline:
if self.styl... | Modify coords to shift tree position for x,y baseline arguments. This
is useful for arrangeing trees onto a Canvas with other plots, but
still sharing a common cartesian axes coordinates. | entailment |
def add_tip_labels_to_axes(self):
"""
Add text offset from tips of tree with correction for orientation,
and fixed_order which is usually used in multitree plotting.
"""
# get tip-coords and replace if using fixed_order
xpos = self.ttree.get_tip_coordinates('x')
... | Add text offset from tips of tree with correction for orientation,
and fixed_order which is usually used in multitree plotting. | entailment |
def add_tip_lines_to_axes(self):
"add lines to connect tips to zero axis for tip_labels_align=True"
# get tip-coords and align-coords from verts
xpos, ypos, aedges, averts = self.get_tip_label_coords()
if self.style.tip_labels_align:
self.axes.graph(
aedges,... | add lines to connect tips to zero axis for tip_labels_align=True | entailment |
def fit_tip_labels(self):
"""
Modifies display range to ensure tip labels fit. This is a bit hackish
still. The problem is that the 'extents' range of the rendered text
is totally correct. So we add a little buffer here. Should add for
user to be able to modify this if needed. I... | Modifies display range to ensure tip labels fit. This is a bit hackish
still. The problem is that the 'extents' range of the rendered text
is totally correct. So we add a little buffer here. Should add for
user to be able to modify this if needed. If not using edge lengths
then need to ... | entailment |
def assign_node_colors_and_style(self):
"""
Resolve conflict of 'node_color' and 'node_style['fill'] args which are
redundant. Default is node_style.fill unless user entered node_color.
To enter multiple colors user must use node_color not style fill.
Either way, we build a list... | Resolve conflict of 'node_color' and 'node_style['fill'] args which are
redundant. Default is node_style.fill unless user entered node_color.
To enter multiple colors user must use node_color not style fill.
Either way, we build a list of colors to pass to Drawing.node_colors
which is ... | entailment |
def assign_node_labels_and_sizes(self):
"assign features of nodes to be plotted based on user kwargs"
# shorthand
nvals = self.ttree.get_node_values()
# False == Hide nodes and labels unless user entered size
if self.style.node_labels is False:
self.node_labels = [... | assign features of nodes to be plotted based on user kwargs | entailment |
def assign_tip_labels_and_colors(self):
"assign tip labels based on user provided kwargs"
# COLOR
# tip color overrides tipstyle.fill
if self.style.tip_labels_colors:
#if self.style.tip_labels_style.fill:
# self.style.tip_labels_style.fill = None
if... | assign tip labels based on user provided kwargs | entailment |
def assign_edge_colors_and_widths(self):
"""
Resolve conflict of 'node_color' and 'node_style['fill'] args which are
redundant. Default is node_style.fill unless user entered node_color.
To enter multiple colors user must use node_color not style fill.
Either way, we build a lis... | Resolve conflict of 'node_color' and 'node_style['fill'] args which are
redundant. Default is node_style.fill unless user entered node_color.
To enter multiple colors user must use node_color not style fill.
Either way, we build a list of colors to pass to Drawing.node_colors
which is ... | entailment |
def add_nodes_to_axes(self):
"""
Creates a new marker for every node from idx indexes and lists of
node_values, node_colors, node_sizes, node_style, node_labels_style.
Pulls from node_color and adds to a copy of the style dict for each
node to create marker.
Node_color... | Creates a new marker for every node from idx indexes and lists of
node_values, node_colors, node_sizes, node_style, node_labels_style.
Pulls from node_color and adds to a copy of the style dict for each
node to create marker.
Node_colors has priority to overwrite node_style['fill'] | entailment |
def get_tip_label_coords(self):
"""
Get starting position of tip labels text based on locations of the
leaf nodes on the tree and style offset and align options. Node
positions are found using the .verts attribute of coords and is
already oriented for the tree face direction.
... | Get starting position of tip labels text based on locations of the
leaf nodes on the tree and style offset and align options. Node
positions are found using the .verts attribute of coords and is
already oriented for the tree face direction. | entailment |
def get_dims_from_tree_size(self):
"Calculate reasonable canvas height and width for tree given N tips"
ntips = len(self.ttree)
if self.style.orient in ("right", "left"):
# height is long tip-wise dimension
if not self.style.height:
self.style.height = ma... | Calculate reasonable canvas height and width for tree given N tips | entailment |
def get_longest_line_length(text):
"""Get the length longest line in a paragraph"""
lines = text.split("\n")
length = 0
for i in range(len(lines)):
if len(lines[i]) > length:
length = len(lines[i])
return length | Get the length longest line in a paragraph | entailment |
def isnumeric(obj):
'''
Return true if obj is a numeric value
'''
from decimal import Decimal
if type(obj) == Decimal:
return True
else:
try:
float(obj)
except:
return False
return True | Return true if obj is a numeric value | entailment |
def significant_format(number, decimal_sep='.', thousand_sep=',', n=3):
"""Format a number according to a given number of significant figures.
"""
str_number = significant(number, n)
# sign
if float(number) < 0:
sign = '-'
else:
sign = ''
if str_number[0] == '-':... | Format a number according to a given number of significant figures. | entailment |
def to_text_string(obj, encoding=None):
"""Convert `obj` to (unicode) text string"""
if PY2:
# Python 2
if encoding is None:
return unicode(obj)
else:
return unicode(obj, encoding)
else:
# Python 3
if encoding is None:
return str(ob... | Convert `obj` to (unicode) text string | entailment |
def text_to_qcolor(text):
"""
Create a QColor from specified string
Avoid warning from Qt when an invalid QColor is instantiated
"""
color = QColor()
if not is_string(text): # testing for QString (PyQt API#1)
text = str(text)
if not is_text_string(text):
return color
if t... | Create a QColor from specified string
Avoid warning from Qt when an invalid QColor is instantiated | entailment |
def tuple_to_qfont(tup):
"""
Create a QFont from tuple:
(family [string], size [int], italic [bool], bold [bool])
"""
if not isinstance(tup, tuple) or len(tup) != 4 \
or not is_text_string(tup[0]) \
or not isinstance(tup[1], int) \
or not isinstance(tup[2], bool) \
or... | Create a QFont from tuple:
(family [string], size [int], italic [bool], bold [bool]) | entailment |
def fedit(data, title="", comment="", icon=None, parent=None, apply=None,
ok=True, cancel=True, result='list', outfile=None, type='form',
scrollbar=False, background_color=None, widget_color=None):
"""
Create form dialog and return result
(if Cancel button is pressed, return None)
:... | Create form dialog and return result
(if Cancel button is pressed, return None)
:param tuple data: datalist, datagroup (see below)
:param str title: form title
:param str comment: header comment
:param QIcon icon: dialog box icon
:param QWidget parent: parent widget
:param str ok: customize... | entailment |
def get_dialog(self):
"""Return FormDialog instance"""
dialog = self.parent()
while not isinstance(dialog, QDialog):
dialog = dialog.parent()
return dialog | Return FormDialog instance | entailment |
def get(self):
"""Return form result"""
# It is import to avoid accessing Qt C++ object as it has probably
# already been destroyed, due to the Qt.WA_DeleteOnClose attribute
if self.outfile:
if self.result in ['list', 'dict', 'OrderedDict']:
fd = open(self.out... | Return form result | entailment |
def ts_merge(series):
'''Merge timeseries into a new :class:`~.TimeSeries` instance.
:parameter series: an iterable over :class:`~.TimeSeries`.
'''
series = iter(series)
ts = next(series)
return ts.merge(series) | Merge timeseries into a new :class:`~.TimeSeries` instance.
:parameter series: an iterable over :class:`~.TimeSeries`. | entailment |
def ts_bin_op(op_name, ts1, ts2, all=True, fill=None, name=None):
'''Entry point for any arithmetic type function performed on a timeseries
and/or a scalar.
op_name - name of the function to be performed
ts1, ts2 - timeseries or scalars that the function is to performed over
all - whether all d... | Entry point for any arithmetic type function performed on a timeseries
and/or a scalar.
op_name - name of the function to be performed
ts1, ts2 - timeseries or scalars that the function is to performed over
all - whether all dates should be included in the result
fill - the value that should be... | entailment |
def getalgo(self, operation, name):
'''Return the algorithm for *operation* named *name*'''
if operation not in self._algorithms:
raise NotAvailable('{0} not registered.'.format(operation))
oper = self._algorithms[operation]
try:
return oper[name]
e... | Return the algorithm for *operation* named *name* | entailment |
def dates(self, desc=None):
'''Returns an iterable over ``datetime.date`` instances
in the timeseries.'''
c = self.dateinverse
for key in self.keys(desc=desc):
yield c(key) | Returns an iterable over ``datetime.date`` instances
in the timeseries. | entailment |
def items(self, desc=None, start_value=None, shift_by=None):
'''Returns a python ``generator`` which can be used to iterate over
:func:`dynts.TimeSeries.dates` and :func:`dynts.TimeSeries.values`
returning a two dimensional
tuple ``(date,value)`` in each iteration.
Similar t... | Returns a python ``generator`` which can be used to iterate over
:func:`dynts.TimeSeries.dates` and :func:`dynts.TimeSeries.values`
returning a two dimensional
tuple ``(date,value)`` in each iteration.
Similar to the python dictionary items
function.
:parameter de... | entailment |
def series(self):
'''Generator of single series data (no dates are included).'''
data = self.values()
if len(data):
for c in range(self.count()):
yield data[:, c]
else:
raise StopIteration | Generator of single series data (no dates are included). | entailment |
def named_series(self, ordering=None):
'''Generator of tuples with name and serie data.'''
series = self.series()
if ordering:
series = list(series)
todo = dict(((n, idx) for idx, n in enumerate(self.names())))
for name in ordering:
if n... | Generator of tuples with name and serie data. | entailment |
def clone(self, date=None, data=None, name=None):
'''Create a clone of timeseries'''
name = name or self.name
data = data if data is not None else self.values()
ts = self.__class__(name)
ts._dtype = self._dtype
if date is None:
# dates not provided
... | Create a clone of timeseries | entailment |
def reduce(self, size, method='simple', **kwargs):
'''Trim :class:`Timeseries` to a new *size* using the algorithm
*method*. If *size* is greater or equal than len(self) it does nothing.'''
if size >= len(self):
return self
return self.getalgo('reduce', method)(self, size, **kwa... | Trim :class:`Timeseries` to a new *size* using the algorithm
*method*. If *size* is greater or equal than len(self) it does nothing. | entailment |
def clean(self, algorithm=None):
'''Create a new :class:`TimeSeries` with missing data removed or
replaced by the *algorithm* provided'''
# all dates
original_dates = list(self.dates())
series = []
all_dates = set()
for serie in self.series():
dstart, ... | Create a new :class:`TimeSeries` with missing data removed or
replaced by the *algorithm* provided | entailment |
def isconsistent(self):
'''Check if the timeseries is consistent'''
for dt1, dt0 in laggeddates(self):
if dt1 <= dt0:
return False
return True | Check if the timeseries is consistent | entailment |
def var(self, ddof=0):
'''Calculate variance of timeseries. Return a vector containing
the variances of each series in the timeseries.
:parameter ddof: delta degree of freedom, the divisor used in the calculation
is given by ``N - ddof`` where ``N`` represents the length
... | Calculate variance of timeseries. Return a vector containing
the variances of each series in the timeseries.
:parameter ddof: delta degree of freedom, the divisor used in the calculation
is given by ``N - ddof`` where ``N`` represents the length
of timeseries. Default ``0``.
.... | entailment |
def sd(self):
'''Calculate standard deviation of timeseries'''
v = self.var()
if len(v):
return np.sqrt(v)
else:
return None | Calculate standard deviation of timeseries | entailment |
def apply(self, func, window=None, bycolumn=True, align=None, **kwargs):
'''Apply function ``func`` to the timeseries.
:keyword func: string indicating function to apply
:keyword window: Rolling window, If not defined ``func`` is applied on
the whole dataset. Default ``None``.
... | Apply function ``func`` to the timeseries.
:keyword func: string indicating function to apply
:keyword window: Rolling window, If not defined ``func`` is applied on
the whole dataset. Default ``None``.
:keyword bycolumn: If ``True``, function ``func`` is applied on
... | entailment |
def rollapply(self, func, window=20, **kwargs):
'''A generic :ref:`rolling function <rolling-function>`
for function *func*.
Same construct as :meth:`dynts.TimeSeries.apply` but with default
``window`` set to ``20``.
'''
return self.apply(func, window=window, **kwar... | A generic :ref:`rolling function <rolling-function>`
for function *func*.
Same construct as :meth:`dynts.TimeSeries.apply` but with default
``window`` set to ``20``. | entailment |
def rollsd(self, scale=1, **kwargs):
'''A :ref:`rolling function <rolling-function>` for
stadard-deviation values:
Same as::
self.rollapply('sd', **kwargs)
'''
ts = self.rollapply('sd', **kwargs)
if scale != 1:
ts *= scale
return... | A :ref:`rolling function <rolling-function>` for
stadard-deviation values:
Same as::
self.rollapply('sd', **kwargs) | entailment |
def unwind(self, values, backend, **kwargs):
'''Unwind expression by applying *values* to the abstract nodes.
The ``kwargs`` dictionary can contain data which can be used
to override values
'''
if not hasattr(self, "_unwind_value"):
self._unwind_value = self._... | Unwind expression by applying *values* to the abstract nodes.
The ``kwargs`` dictionary can contain data which can be used
to override values | entailment |
def removeduplicates(self, entries = None):
'''
Loop over children a remove duplicate entries.
@return - a list of removed entries
'''
removed = []
if entries == None:
entries = {}
new_children = []
for c in self.children:
... | Loop over children a remove duplicate entries.
@return - a list of removed entries | entailment |
def html2md(html_string):
"""
Convert a string or html file to a markdown table string.
Parameters
----------
html_string : str
Either the html string, or the filepath to the html
Returns
-------
str
The html table converted to a Markdown table
Notes
-----
... | Convert a string or html file to a markdown table string.
Parameters
----------
html_string : str
Either the html string, or the filepath to the html
Returns
-------
str
The html table converted to a Markdown table
Notes
-----
This function requires BeautifulSoup_ ... | entailment |
def table_cells_2_spans(table, spans):
"""
Converts the table to a list of spans, for consistency.
This method combines the table data with the span data into a
single, more consistent type. Any normal cell will become a span
of just 1 column and 1 row.
Parameters
----------
table : li... | Converts the table to a list of spans, for consistency.
This method combines the table data with the span data into a
single, more consistent type. Any normal cell will become a span
of just 1 column and 1 row.
Parameters
----------
table : list of lists of str
spans : list of lists of int... | entailment |
def keys(self, desc = None):
'''numpy asarray does not copy data'''
res = asarray(self.rc('index'))
if desc == True:
return reversed(res)
else:
return res | numpy asarray does not copy data | entailment |
def values(self, desc = None):
'''numpy asarray does not copy data'''
if self._ts:
res = asarray(self._ts)
if desc == True:
return reversed(res)
else:
return res
else:
return ndarray([0,0]) | numpy asarray does not copy data | entailment |
def rcts(self, command, *args, **kwargs):
'''General function for applying a rolling R function to a timeserie'''
cls = self.__class__
name = kwargs.pop('name','')
date = kwargs.pop('date',None)
data = kwargs.pop('data',None)
kwargs.pop('bycolumn',None)
ts ... | General function for applying a rolling R function to a timeserie | entailment |
def get_html_column_count(html_string):
"""
Gets the number of columns in an html table.
Paramters
---------
html_string : str
Returns
-------
int
The number of columns in the table
"""
try:
from bs4 import BeautifulSoup
except ImportError:
print("ER... | Gets the number of columns in an html table.
Paramters
---------
html_string : str
Returns
-------
int
The number of columns in the table | entailment |
def add_cushions(table):
"""
Add space to start and end of each string in a list of lists
Parameters
----------
table : list of lists of str
A table of rows of strings. For example::
[
['dog', 'cat', 'bicycle'],
['mouse', trumpet', '']
... | Add space to start and end of each string in a list of lists
Parameters
----------
table : list of lists of str
A table of rows of strings. For example::
[
['dog', 'cat', 'bicycle'],
['mouse', trumpet', '']
]
Returns
-------
tabl... | entailment |
def rollsingle(self, func, window=20, name=None, fallback=False,
align='right', **kwargs):
'''Efficient rolling window calculation for min, max type functions
'''
rname = 'roll_{0}'.format(func)
if fallback:
rfunc = getattr(lib.fallback, rname)
else:
rfunc = getattr(li... | Efficient rolling window calculation for min, max type functions | entailment |
def find_ge(self, dt):
'''Building block of all searches. Find the index
corresponding to the leftmost value greater or equal to *dt*.
If *dt* is greater than the
:func:`dynts.TimeSeries.end` a :class:`dynts.exceptions.RightOutOfBound`
exception will raise.
*dt* must be a python datetime.date instance.'... | Building block of all searches. Find the index
corresponding to the leftmost value greater or equal to *dt*.
If *dt* is greater than the
:func:`dynts.TimeSeries.end` a :class:`dynts.exceptions.RightOutOfBound`
exception will raise.
*dt* must be a python datetime.date instance. | entailment |
def find_le(self, dt):
'''Find the index corresponding to the rightmost
value less than or equal to *dt*.
If *dt* is less than :func:`dynts.TimeSeries.end`
a :class:`dynts.exceptions.LeftOutOfBound`
exception will raise.
*dt* must be a python datetime.date instance.'''
i = bisect_right(self.dat... | Find the index corresponding to the rightmost
value less than or equal to *dt*.
If *dt* is less than :func:`dynts.TimeSeries.end`
a :class:`dynts.exceptions.LeftOutOfBound`
exception will raise.
*dt* must be a python datetime.date instance. | entailment |
def upgrade():
"""Update database."""
op.create_table(
'transaction',
sa.Column('issued_at', sa.DateTime(), nullable=True),
sa.Column('id', sa.BigInteger(), nullable=False),
sa.Column('remote_addr', sa.String(length=50), nullable=True),
)
op.create_primary_key('pk_transac... | Update database. | entailment |
def downgrade():
"""Downgrade database."""
op.drop_table('transaction')
if op._proxy.migration_context.dialect.supports_sequences:
op.execute(DropSequence(Sequence('transaction_id_seq'))) | Downgrade database. | entailment |
def t_NUMBER(self, t):
r'([0-9]+\.?[0-9]*|\.[0-9]+)([eE](\+|-)?[0-9]+)?'
try:
sv = t.value
v = float(sv)
iv = int(v)
t.value = (iv if iv == v else v, sv)
except ValueError:
print("Number %s is too large!" % t.value)
... | r'([0-9]+\.?[0-9]*|\.[0-9]+)([eE](\+|-)?[0-9]+)? | entailment |
def t_ID(self, t):
r'`[^`]*`|[a-zA-Z_][a-zA-Z_0-9:@]*'
res = self.oper.get(t.value, None) # Check for reserved words
if res is None:
res = t.value.upper()
if res == 'FALSE':
t.type = 'BOOL'
t.value = False
elif res == '... | r'`[^`]*`|[a-zA-Z_][a-zA-Z_0-9:@]* | entailment |
def read_newick(newick, root_node=None, format=0):
"""
Reads a newick tree from either a string or a file, and returns
an ETE tree structure.
A previously existent node object can be passed as the root of the
tree, which means that all its new children will belong to the same
class as the root... | Reads a newick tree from either a string or a file, and returns
an ETE tree structure.
A previously existent node object can be passed as the root of the
tree, which means that all its new children will belong to the same
class as the root (This allows to work with custom TreeNode objects).
You ca... | entailment |
def _read_newick_from_string(nw, root_node, matcher, formatcode):
""" Reads a newick string in the New Hampshire format. """
if nw.count('(') != nw.count(')'):
raise NewickError('Parentheses do not match. Broken tree structure?')
# white spaces and separators are removed
nw = re.sub("[\n\r\t]+"... | Reads a newick string in the New Hampshire format. | entailment |
def _parse_extra_features(node, NHX_string):
"""
Reads node's extra data form its NHX string. NHX uses this
format: [&&NHX:prop1=value1:prop2=value2]
"""
NHX_string = NHX_string.replace("[&&NHX:", "")
NHX_string = NHX_string.replace("]", "")
for field in NHX_string.split(":"):
try... | Reads node's extra data form its NHX string. NHX uses this
format: [&&NHX:prop1=value1:prop2=value2] | entailment |
def compile_matchers(formatcode):
"""
Tests newick string against format types? and makes a re.compile
"""
matchers = {}
for node_type in ["leaf", "single", "internal"]:
if node_type == "leaf" or node_type == "single":
container1 = NW_FORMAT[formatcode][0][0]
containe... | Tests newick string against format types? and makes a re.compile | entailment |
def _read_node_data(subnw, current_node, node_type, matcher, formatcode):
"""
Reads a leaf node from a subpart of the original newicktree
"""
if node_type == "leaf" or node_type == "single":
if node_type == "leaf":
node = current_node.add_child()
else:
node = cu... | Reads a leaf node from a subpart of the original newicktree | entailment |
def write_newick(rootnode,
features=None,
format=1,
format_root_node=True,
is_leaf_fn=None,
dist_formatter=None,
support_formatter=None,
name_formatter=None):
"""
Iteratively export a tree structure and returns its NHX
representation.
"""
newick = []
leaf = is_leaf_fn if... | Iteratively export a tree structure and returns its NHX
representation. | entailment |
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