JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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Add the links to the bottom of the text def add_links(converted_text, html): """ Add the links to the bottom of the text """ soup = BeautifulSoup(html, 'html.parser') link_exceptions = [ 'footnote-reference', 'fn-backref', 'citation-reference' ] footnotes = {} ...
Load symbols data. :keyword providers: Dictionary of registered data providers. :keyword symbols: list of symbols to load. :keyword start: start date. :keyword end: end date. :keyword logger: instance of :class:`logging.Logger` or ``None``. :keyword backend: :clas...
Internal function which perform pre-conditioning on dates: :keyword start: start date. :keyword end: end date. This function makes sure the start and end date are consistent. It never fails and always return a two-element tuple containing start, end with start less or equal end and end never a...
Parse a symbol to obtain information regarding ticker, field and provider. Must return an instance of :attr:`symboldata`. :keyword symbol: string associated with market data to load. :keyword providers: dictionary of :class:`dynts.data.DataProvider` instances av...
Return an instance of symboldata containing information about the data provider, the data provider ticker name and the data provider field. def symbol_for_ticker(self, ticker, field, provider, providers): '''Return an instance of symboldata containing information about the data provider, the data provi...
Preprocess hook. This is first loading hook and it is called before requesting data from a dataprovider. It must return an instance of :attr:`TimeSerieLoader.preprocessdata`. By default it returns:: self.preprocessdata(intervals = ((start,end),)) It could be overritten to modify the intervals. If ...
Register a new data provider. provider must be an instance of DataProvider. If provider name is already available, it will be replaced. def register(self, provider): '''Register a new data provider. provider must be an instance of DataProvider. If provider name is already available, it will be r...
Unregister an existing data provider. provider must be an instance of DataProvider. If provider name is already available, it will be replaced. def unregister(self, provider): '''Unregister an existing data provider. provider must be an instance of DataProvider. If ...
Function for parsing :ref:`timeseries expressions <dsl-script>`. If succesful, it returns an instance of :class:`dynts.dsl.Expr` which can be used to to populate timeseries or scatters once data is available. Parsing is implemented using the ply_ module, an implementation of lex and yacc parsing t...
Evaluate a timeseries ``expression`` into an instance of :class:`dynts.dsl.dslresult` which can be used to obtain timeseries and/or scatters. This is probably the most used function of the library. :parameter expression: A timeseries expression string or an instance of :class:`dynts.dsl.E...
Convert Grid table to data (the kind used by Dashtable) Parameters ---------- text : str The text must be a valid rst table Returns ------- table : list of lists of str spans : list of lists of lists of int A span is a list of [row, column] pairs that define a group of ...
Returns an extended majority rule consensus tree as a Toytree object. Node labels include 'support' values showing the occurrence of clades in the consensus tree across trees in the input treelist. Clades with support below 'cutoff' are collapsed into polytomies. If you enter an option...
Draw a slice of x*y trees into a x,y grid non-overlapping. Parameters: ----------- x (int): Number of grid cells in x dimension. Default=automatically set. y (int): Number of grid cells in y dimension. Default=automatically set. start (int): ...
Draw a series of trees overlapping each other in coordinate space. The order of tip_labels is fixed in cloud trees so that trees with discordant relationships can be seen in conflict. To change the tip order use the 'fixed_order' argument in toytree.mtree() when creating the MultiTree o...
hash ladderized tree topologies def hash_trees(self): "hash ladderized tree topologies" observed = {} for idx, tree in enumerate(self.treelist): nwk = tree.write(tree_format=9) hashed = md5(nwk.encode("utf-8")).hexdigest() if hashed not in observed: ...
Count clade occurrences. def find_clades(self): "Count clade occurrences." # index names from the first tree ndict = {j: i for i, j in enumerate(self.names)} namedict = {i: j for i, j in enumerate(self.names)} # store counts clade_counts = {} for tidx, ncopies i...
Remove conflicting clades and those < cutoff to get majority rule def filter_clades(self): "Remove conflicting clades and those < cutoff to get majority rule" passed = [] carrs = np.array([list(i[0]) for i in self.clade_counts], dtype=int) freqs = np.array([i[1] for i in self.clade_coun...
Build an unrooted consensus tree from filtered clade counts. def build_trees(self): "Build an unrooted consensus tree from filtered clade counts." # storage nodes = {} idxarr = np.arange(len(self.fclade_counts[0][0])) queue = [] ## create dict of clade counts and set k...
Compare the phonetic representations of 2 words, and return a boolean value. def sounds_like(self, word1, word2): """Compare the phonetic representations of 2 words, and return a boolean value.""" return self.phonetics(word1) == self.phonetics(word2)
Get the similarity of the words, using the supported distance metrics. def distance(self, word1, word2, metric='levenshtein'): """Get the similarity of the words, using the supported distance metrics.""" if metric in self.distances: distance_func = self.distances[metric] return ...
Get the heights of the rows of the output table. Parameters ---------- table : list of lists of str spans : list of lists of int Returns ------- heights : list of int The heights of each row in the output table def get_output_row_heights(table, spans): """ Get the heights ...
Generalised media for odd and even number of samples def smedian(olist,nobs): '''Generalised media for odd and even number of samples''' if nobs: rem = nobs % 2 midpoint = nobs // 2 me = olist[midpoint] if not rem: me = 0.5 * (me + olist[midpoint-1]) ...
Apply a rolling mean function to an array. This is a simple rolling aggregation. def roll_mean(input, window): '''Apply a rolling mean function to an array. This is a simple rolling aggregation.''' nobs, i, j, sum_x = 0,0,0,0. N = len(input) if window > N: raise ValueError('Out of boun...
Apply a rolling standard deviation function to an array. This is a simple rolling aggregation of squared sums. def roll_sd(input, window, scale = 1.0, ddof = 0): '''Apply a rolling standard deviation function to an array. This is a simple rolling aggregation of squared sums.''' nobs, i, j, sx, sxx = 0,0,...
Ensure the span is valid. A span is a list of [row, column] pairs. These coordinates must form a rectangular shape. For example, this span will cause an error because it is not rectangular in shape.:: span = [[0, 1], [0, 2], [1, 0]] Spans must be * Rectanglular * A list of li...
Loop through list of cells and piece them together one by one Parameters ---------- cells : list of dashtable.data2rst.Cell Returns ------- grid_table : str The final grid table def merge_all_cells(cells): """ Loop through list of cells and piece them together one by one ...
converts bpp newick format to normal newick def bpp2newick(bppnewick): "converts bpp newick format to normal newick" regex1 = re.compile(r" #[-+]?[0-9]\.?[0-9][:]") regex2 = re.compile(r" #[-+]?[0-9]\.?[0-9][;]") regex3 = re.compile(r": ") new = regex1.sub(":", bppnewick) new = regex2.sub("...
used to produce balanced trees, returns a tip node from the smaller clade def return_small_clade(treenode): "used to produce balanced trees, returns a tip node from the smaller clade" node = treenode while 1: if node.children: c1, c2 = node.children node = sorted([c1, c2], k...
Used in multiple internal functions (e.g., .root()) and .drop_tips()) to select an internal mrca node, or multiple tipnames, using fuzzy matching so that every name does not need to be written out by hand. name: verbose list wildcard: matching unique string regex: regex expression mrca: return ...
Returns a toytree copy with all nodes scaled so that the root height equals the value entered for treeheight. def node_scale_root_height(self, treeheight=1): """ Returns a toytree copy with all nodes scaled so that the root height equals the value entered for treeheight. """ ...
Returns a toytree copy with node heights modified while retaining the same topology but not necessarily node branching order. Node heights are moved up or down uniformly between their parent and highest child node heights in 'levelorder' from root to tips. The total tree height is ret...
Returns a toytree copy with all nodes multiplied by a constant sampled uniformly between (multiplier, 1/multiplier). def node_multiplier(self, multiplier=0.5, seed=None): """ Returns a toytree copy with all nodes multiplied by a constant sampled uniformly between (multiplier, 1/multip...
Returns a tree with branch lengths transformed so that the tree is ultrametric. Strategies include (1) tip-align: extend tips to the length of the fartest tip from the root; (2) non-parametric rate-smoothing: minimize ancestor-descendant local rates on branches to align tips ( not yet ...
Returns a coalescent tree with ntips samples and waiting times between coalescent events drawn from the kingman coalescent: (4N)/(k*(k-1)), where N is population size and k is sample size. Edge lengths on the tree are in generations. If no Ne argument is entered then edge lengths are r...
Returns a random tree topology w/ N tips and a root height set to 1 or a user-entered treeheight value. Descendant nodes are evenly spaced between the root and time 0. Parameters ----------- ntips (int): The number of tips in the randomly generated tree tre...
Return an imbalanced (comb-like) tree topology. def imbtree(ntips, treeheight=1.0): """ Return an imbalanced (comb-like) tree topology. """ rtree = toytree.tree() rtree.treenode.add_child(name="0") rtree.treenode.add_child(name="1") for i in range(2, ntips): ...
Returns a balanced tree topology. def baltree(ntips, treeheight=1.0): """ Returns a balanced tree topology. """ # require even number of tips if ntips % 2: raise ToytreeError("balanced trees must have even number of tips.") # make first cherry rtree ...
Get the height of a span in the number of newlines it fills. Parameters ---------- span : list of list of int A list of [row, column] pairs that make up the span row_heights : list of int A list of the number of newlines for each row in the table Returns ------- total_heigh...
Convert an html table to a data table and spans. Parameters ---------- html_string : str The string containing the html table Returns ------- table : list of lists of str spans : list of lists of lists of int A span is a list of [row, column] pairs that define what cells ...
Returns newick represenation of the tree in its current state. def newick(self, tree_format=0): "Returns newick represenation of the tree in its current state." # checks one of root's children for features and extra feats. if self.treenode.children: features = {"name", "dist", "supp...
Returns edge values in the order they are plotted (see .get_edges()) def get_edge_values(self, feature='idx'): """ Returns edge values in the order they are plotted (see .get_edges()) """ elist = [] for cidx in self._coords.edges[:, 1]: node = self.treenode.search_no...
Enter a dictionary mapping node 'idx' or tuple of tipnames to values that you want mapped to the stem and descendant edges that node. Edge values are returned in proper plot order to be entered to the edge_colors or edge_widths arguments to draw(). To see node idx values use node_lab...
Returns the node idx label of the most recent common ancestor node for the clade that includes the selected tips. Arguments can use fuzzy name matching: a list of tip names, wildcard selector, or regex string. def get_mrca_idx_from_tip_labels(self, names=None, wildcard=None, regex=None): """ ...
Returns node values from tree object in node plot order. To modify values you must modify the .treenode object directly by setting new 'features'. For example for node in ttree.treenode.traverse(): node.add_feature("PP", 100) By default node and tip values are hidden (set t...
Return node labels as a dictionary mapping {idx: name} where idx is the order of nodes in 'preorder' traversal. Used internally by the func .get_node_values() to return values in proper order. return_internal: if True all nodes are returned, if False only tips. return_nodes: if True r...
Returns coordinates of the tip positions for a tree. If no argument for axis then a 2-d array is returned. The first column is the x coordinates the second column is the y-coordinates. If you enter an argument for axis then a 1-d array will be returned of just that axis. def get_tip_coordinat...
Returns tip labels in the order they will be plotted on the tree, i.e., starting from zero axis and counting up by units of 1 (bottom to top in right-facing trees; left to right in down-facing). If 'idx' is indicated then a list of tip labels descended from that node will be returned,...
Returns False if there is a polytomy in the tree, including if the tree is unrooted (basal polytomy), unless you use the include_root=False argument. def is_bifurcating(self, include_root=True): """ Returns False if there is a polytomy in the tree, including if the tree is unroo...
Ladderize tree (order descendants) so that top child has fewer descendants than the bottom child in a left to right tree plot. To reverse this pattern use direction=1. def ladderize(self, direction=0): """ Ladderize tree (order descendants) so that top child has fewer descend...
Returns a copy of the tree where internal nodes with dist <= min_dist are deleted, resulting in a collapsed tree. e.g.: newtre = tre.collapse_nodes(min_dist=0.001) newtre = tre.collapse_nodes(min_support=50) def collapse_nodes(self, min_dist=1e-6, min_support=0): """ Returns a ...
Returns a copy of the tree with the selected tips removed. The entered value can be a name or list of names. To prune on an internal node to create a subtree see the .prune() function instead. Parameters: tips: list of tip names. # example: ptre = tre.drop_tips(['a', 'b...
Returns a ToyTree with the selected node rotated for plotting. tip colors do not align correct currently if nodes are rotated... def rotate_node( self, names=None, wildcard=None, regex=None, idx=None, # modify_tree=False, ): """ Retur...
Returns a copy of the tree with all polytomies randomly resolved. Does not transform tree in-place. def resolve_polytomy( self, dist=1.0, support=100, recursive=True): """ Returns a copy of the tree with all polytomies randomly resolved. Does not transfor...
Returns a copy of the tree unrooted. Does not transform tree in-place. def unroot(self): """ Returns a copy of the tree unrooted. Does not transform tree in-place. """ nself = self.copy() nself.treenode.unroot() nself.treenode.ladderize() nself._coords.update() ...
(Re-)root a tree by creating selecting a existing split in the tree, or creating a new node to split an edge in the tree. Rooting location is selected by entering the tips descendant from one child of the root split (e.g., names='a' or names=['a', 'b']). You can alternatively select a li...
Plot a Toytree tree, returns a tuple of Toyplot (Canvas, Axes) objects. Parameters: ----------- tree_style: str One of several preset styles for tree plotting. The default is 'n' (normal). Other options inlude 'c' (coalescent), 'd' (dark), and 'm' (multitree)...
Determine the side of cell1 that can be merged with cell2. This is based on the location of the two cells in the table as well as the compatability of their height and width. For example these cells can merge:: cell1 cell2 merge "RIGHT" +-----+ +------+ +-----+------+ ...
NHX format: [&&NHX:prop1=value1:prop2=value2] MB format: ((a[&Z=1,Y=2], b[&Z=1,Y=2]):1.0[&L=1,W=0], ... def parse_nhx(NHX_string): """ NHX format: [&&NHX:prop1=value1:prop2=value2] MB format: ((a[&Z=1,Y=2], b[&Z=1,Y=2]):1.0[&L=1,W=0], ... """ # store features ndict = {} # parse NH...
Load data from a file or string and return as a list of strings. The data contents could be one newick string; a multiline NEXUS format for one tree; multiple newick strings on multiple lines; or multiple newick strings in a multiline NEXUS format. In any case, we will read in the data...
get newick data from NEXUS def parse_nexus(self): "get newick data from NEXUS" if self.data[0].strip().upper() == "#NEXUS": nex = NexusParser(self.data) self.data = nex.newicks self.tdict = nex.tdict
test format of intree nex/nwk, extra features def get_treenodes(self): "test format of intree nex/nwk, extra features" if not self.multitree: # get TreeNodes from Newick extractor = Newick2TreeNode(self.data[0].strip(), fmt=self.fmt) # extract one tree ...
Reads a newick string in the New Hampshire format. def newick_from_string(self): "Reads a newick string in the New Hampshire format." # split on parentheses to traverse hierarchical tree structure for chunk in self.data.split("(")[1:]: # add child to make this node a parent. ...
iterate through data file to extract trees def extract_tree_block(self): "iterate through data file to extract trees" lines = iter(self.data) while 1: try: line = next(lines).strip() except StopIteration: break # ...
Parse CLI args. def parse_command_line(): """ Parse CLI args.""" ## create the parser parser = argparse.ArgumentParser( formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" * Example command-line usage: ## push test branch to conda --label=conda-test for travis CI ./ver...
Gets git and init versions and commits since the init version def get_git_status(self): """ Gets git and init versions and commits since the init version """ ## get git branch self._get_git_branch() ## get tag in the init file self._get_init_release_tag() ...
if no conflicts then write new tag to def push_git_package(self): """ if no conflicts then write new tag to """ ## check for conflicts, then write to local files self._pull_branch_from_origin() ## log commits to releasenotes if self.deploy: self._wr...
Pulls from origin/master, if you have unmerged conflicts it will raise an exception. You will need to resolve these. def _pull_branch_from_origin(self): """ Pulls from origin/master, if you have unmerged conflicts it will raise an exception. You will need to resolve these. """ ...
parses init.py to get previous version def _get_init_release_tag(self): """ parses init.py to get previous version """ self.init_version = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", open(self.init_file, "r").read(), ...
calls git log to complile a change list def _get_log_commits(self): """ calls git log to complile a change list """ ## check if update is necessary cmd = "git log --pretty=oneline {}..".format(self.init_version) cmdlist = shlex.split(cmd) commits = subprocess.che...
writes commits to the releasenotes file by appending to the end def _write_commits_to_release_notes(self): """ writes commits to the releasenotes file by appending to the end """ with open(self.release_file, 'a') as out: out.write("==========\n{}\n".format(self.tag)) ...
Write version to __init__.py by editing in place def _write_new_tag_to_init(self): """ Write version to __init__.py by editing in place """ for line in fileinput.input(self.init_file, inplace=1): if line.strip().startswith("__version__"): line = "__version__ ...
Write branch and tag to meta.yaml by editing in place def _write_branch_and_tag_to_meta_yaml(self): """ Write branch and tag to meta.yaml by editing in place """ ## set the branch to pull source from with open(self.meta_yaml.replace("meta", "template"), 'r') as infile: ...
Write version to __init__.py by editing in place def _revert_tag_in_init(self): """ Write version to __init__.py by editing in place """ for line in fileinput.input(self.init_file, inplace=1): if line.strip().startswith("__version__"): line = "__version__ = \...
tags a new release and pushes to origin/master def _push_new_tag_to_git(self): """ tags a new release and pushes to origin/master """ print("Pushing new version to git") ## stage the releasefile and initfileb subprocess.call(["git", "add", self.release_file]...
Run the Linux build and use converter to build OSX def build_conda_packages(self): """ Run the Linux build and use converter to build OSX """ ## check if update is necessary #if self.nversion == self.pversion: # raise SystemExit("Exited: new version == existing versio...
Gets the number of rows included in a span Parameters ---------- span : list of lists of int The [row, column] pairs that make up the span Returns ------- rows : int The number of rows included in the span Example ------- Consider this table:: +--------+--...
Convert ``x`` into a ``numpy.ndarray``. def asarray(x, dtype=None): '''Convert ``x`` into a ``numpy.ndarray``.''' iterable = scalarasiter(x) if isinstance(iterable, ndarray): return iterable else: if not hasattr(iterable, '__len__'): iterable = list(iterable) ...
Convert ``x`` into a ``column``-type ``numpy.ndarray``. def ascolumn(x, dtype = None): '''Convert ``x`` into a ``column``-type ``numpy.ndarray``.''' x = asarray(x, dtype) return x if len(x.shape) >= 2 else x.reshape(len(x),1)
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 def multis_2_mono(table): """ Converts each multiline string in a table to single line. ...
Get the number of rows 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_c...
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...
Decorator which check if timeseries has a better implementation of the function. 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 fun...
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)} def ...
Rolling Percentage range. Value between 0 and 1 indicating the position in the rolling range. 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 ...
data must be numeric list with a len above 20 This function counts the number of data points in a reduced array 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)...
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 binOp(op, indx, amap, bmap, fill_vec): ''' Combines the values from two map objects using the indx values usin...
takes a single value and creates a vecotor / matrix with that value filled in it 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
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. ...
Register a function in the function registry. The function will be automatically instantiated if not already an instance. def register(self, function): """Register a function in the function registry. The function will be automatically instantiated if not already an instanc...
Unregister function by name. def unregister(self, name): """Unregister function by name. """ try: name = name.name except AttributeError: pass return self.pop(name,None)
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 def row_includes_spans(table, row, spans): """ Determine if the...
Create a StateList object from a 'states' Workflow attribute. 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( ...
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...
Decorator to declare a function as a transition implementation. 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 call...
Ensure the given function has a xworkflows_hook attribute. That attribute has the following structure: >>> { ... 'before': [('state', <TransitionHook>), ...], ... } def _make_hook_dict(fun): """Ensure the given function has a xworkflows_hook attribute. That attribute has the following str...
Checks whether a given State matches self.names. 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 Transition matches self.names. 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)
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 ...
Run the pre-transition checks. 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 availabl...
Filter a list of hooks, keeping only applicable ones. 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_t...

Add the links to the bottom of the text def add_links(converted_text, html): """ Add the links to the bottom of the text """ soup = BeautifulSoup(html, 'html.parser') link_exceptions = [ 'footnote-reference', 'fn-backref', 'citation-reference' ] footnotes = {} ...

Load symbols data. :keyword providers: Dictionary of registered data providers. :keyword symbols: list of symbols to load. :keyword start: start date. :keyword end: end date. :keyword logger: instance of :class:`logging.Logger` or ``None``. :keyword backend: :clas...

Internal function which perform pre-conditioning on dates: :keyword start: start date. :keyword end: end date. This function makes sure the *start* and *end* date are consistent. It *never fails* and always return a two-element tuple containing *start*, *end* with *start* less or equal *end* and *end* never a...

Parse a symbol to obtain information regarding ticker, field and provider. Must return an instance of :attr:`symboldata`. :keyword symbol: string associated with market data to load. :keyword providers: dictionary of :class:`dynts.data.DataProvider` instances av...

Return an instance of *symboldata* containing information about the data provider, the data provider ticker name and the data provider field. def symbol_for_ticker(self, ticker, field, provider, providers): '''Return an instance of *symboldata* containing information about the data provider, the data provi...

Preprocess **hook**. This is first loading hook and it is **called before requesting data** from a dataprovider. It must return an instance of :attr:`TimeSerieLoader.preprocessdata`. By default it returns:: self.preprocessdata(intervals = ((start,end),)) It could be overritten to modify the intervals. If ...

Register a new data provider. *provider* must be an instance of DataProvider. If provider name is already available, it will be replaced. def register(self, provider): '''Register a new data provider. *provider* must be an instance of DataProvider. If provider name is already available, it will be r...

Unregister an existing data provider. *provider* must be an instance of DataProvider. If provider name is already available, it will be replaced. def unregister(self, provider): '''Unregister an existing data provider. *provider* must be an instance of DataProvider. If ...

Function for parsing :ref:`timeseries expressions <dsl-script>`. If succesful, it returns an instance of :class:`dynts.dsl.Expr` which can be used to to populate timeseries or scatters once data is available. Parsing is implemented using the ply_ module, an implementation of lex and yacc parsing t...

Evaluate a timeseries ``expression`` into an instance of :class:`dynts.dsl.dslresult` which can be used to obtain timeseries and/or scatters. This is probably the most used function of the library. :parameter expression: A timeseries expression string or an instance of :class:`dynts.dsl.E...

Convert Grid table to data (the kind used by Dashtable) Parameters ---------- text : str The text must be a valid rst table Returns ------- table : list of lists of str spans : list of lists of lists of int A span is a list of [row, column] pairs that define a group of ...

Returns an extended majority rule consensus tree as a Toytree object. Node labels include 'support' values showing the occurrence of clades in the consensus tree across trees in the input treelist. Clades with support below 'cutoff' are collapsed into polytomies. If you enter an option...

Draw a slice of x*y trees into a x,y grid non-overlapping. Parameters: ----------- x (int): Number of grid cells in x dimension. Default=automatically set. y (int): Number of grid cells in y dimension. Default=automatically set. start (int): ...

Draw a series of trees overlapping each other in coordinate space. The order of tip_labels is fixed in cloud trees so that trees with discordant relationships can be seen in conflict. To change the tip order use the 'fixed_order' argument in toytree.mtree() when creating the MultiTree o...

hash ladderized tree topologies def hash_trees(self): "hash ladderized tree topologies" observed = {} for idx, tree in enumerate(self.treelist): nwk = tree.write(tree_format=9) hashed = md5(nwk.encode("utf-8")).hexdigest() if hashed not in observed: ...

Count clade occurrences. def find_clades(self): "Count clade occurrences." # index names from the first tree ndict = {j: i for i, j in enumerate(self.names)} namedict = {i: j for i, j in enumerate(self.names)} # store counts clade_counts = {} for tidx, ncopies i...

Remove conflicting clades and those < cutoff to get majority rule def filter_clades(self): "Remove conflicting clades and those < cutoff to get majority rule" passed = [] carrs = np.array([list(i[0]) for i in self.clade_counts], dtype=int) freqs = np.array([i[1] for i in self.clade_coun...

Build an unrooted consensus tree from filtered clade counts. def build_trees(self): "Build an unrooted consensus tree from filtered clade counts." # storage nodes = {} idxarr = np.arange(len(self.fclade_counts[0][0])) queue = [] ## create dict of clade counts and set k...

Compare the phonetic representations of 2 words, and return a boolean value. def sounds_like(self, word1, word2): """Compare the phonetic representations of 2 words, and return a boolean value.""" return self.phonetics(word1) == self.phonetics(word2)

Get the similarity of the words, using the supported distance metrics. def distance(self, word1, word2, metric='levenshtein'): """Get the similarity of the words, using the supported distance metrics.""" if metric in self.distances: distance_func = self.distances[metric] return ...

Get the heights of the rows of the output table. Parameters ---------- table : list of lists of str spans : list of lists of int Returns ------- heights : list of int The heights of each row in the output table def get_output_row_heights(table, spans): """ Get the heights ...

Generalised media for odd and even number of samples def smedian(olist,nobs): '''Generalised media for odd and even number of samples''' if nobs: rem = nobs % 2 midpoint = nobs // 2 me = olist[midpoint] if not rem: me = 0.5 * (me + olist[midpoint-1]) ...

Apply a rolling mean function to an array. This is a simple rolling aggregation. def roll_mean(input, window): '''Apply a rolling mean function to an array. This is a simple rolling aggregation.''' nobs, i, j, sum_x = 0,0,0,0. N = len(input) if window > N: raise ValueError('Out of boun...

Apply a rolling standard deviation function to an array. This is a simple rolling aggregation of squared sums. def roll_sd(input, window, scale = 1.0, ddof = 0): '''Apply a rolling standard deviation function to an array. This is a simple rolling aggregation of squared sums.''' nobs, i, j, sx, sxx = 0,0,...

Ensure the span is valid. A span is a list of [row, column] pairs. These coordinates must form a rectangular shape. For example, this span will cause an error because it is not rectangular in shape.:: span = [[0, 1], [0, 2], [1, 0]] Spans must be * Rectanglular * A list of li...

Loop through list of cells and piece them together one by one Parameters ---------- cells : list of dashtable.data2rst.Cell Returns ------- grid_table : str The final grid table def merge_all_cells(cells): """ Loop through list of cells and piece them together one by one ...

converts bpp newick format to normal newick def bpp2newick(bppnewick): "converts bpp newick format to normal newick" regex1 = re.compile(r" #[-+]?[0-9]*\.?[0-9]*[:]") regex2 = re.compile(r" #[-+]?[0-9]*\.?[0-9]*[;]") regex3 = re.compile(r": ") new = regex1.sub(":", bppnewick) new = regex2.sub("...

used to produce balanced trees, returns a tip node from the smaller clade def return_small_clade(treenode): "used to produce balanced trees, returns a tip node from the smaller clade" node = treenode while 1: if node.children: c1, c2 = node.children node = sorted([c1, c2], k...

Used in multiple internal functions (e.g., .root()) and .drop_tips()) to select an internal mrca node, or multiple tipnames, using fuzzy matching so that every name does not need to be written out by hand. name: verbose list wildcard: matching unique string regex: regex expression mrca: return ...

Returns a toytree copy with all nodes scaled so that the root height equals the value entered for treeheight. def node_scale_root_height(self, treeheight=1): """ Returns a toytree copy with all nodes scaled so that the root height equals the value entered for treeheight. """ ...

Returns a toytree copy with node heights modified while retaining the same topology but not necessarily node branching order. Node heights are moved up or down uniformly between their parent and highest child node heights in 'levelorder' from root to tips. The total tree height is ret...

Returns a toytree copy with all nodes multiplied by a constant sampled uniformly between (multiplier, 1/multiplier). def node_multiplier(self, multiplier=0.5, seed=None): """ Returns a toytree copy with all nodes multiplied by a constant sampled uniformly between (multiplier, 1/multip...

Returns a tree with branch lengths transformed so that the tree is ultrametric. Strategies include (1) tip-align: extend tips to the length of the fartest tip from the root; (2) non-parametric rate-smoothing: minimize ancestor-descendant local rates on branches to align tips ( not yet ...

Returns a coalescent tree with ntips samples and waiting times between coalescent events drawn from the kingman coalescent: (4N)/(k*(k-1)), where N is population size and k is sample size. Edge lengths on the tree are in generations. If no Ne argument is entered then edge lengths are r...

Returns a random tree topology w/ N tips and a root height set to 1 or a user-entered treeheight value. Descendant nodes are evenly spaced between the root and time 0. Parameters ----------- ntips (int): The number of tips in the randomly generated tree tre...

Return an imbalanced (comb-like) tree topology. def imbtree(ntips, treeheight=1.0): """ Return an imbalanced (comb-like) tree topology. """ rtree = toytree.tree() rtree.treenode.add_child(name="0") rtree.treenode.add_child(name="1") for i in range(2, ntips): ...

Returns a balanced tree topology. def baltree(ntips, treeheight=1.0): """ Returns a balanced tree topology. """ # require even number of tips if ntips % 2: raise ToytreeError("balanced trees must have even number of tips.") # make first cherry rtree ...

Get the height of a span in the number of newlines it fills. Parameters ---------- span : list of list of int A list of [row, column] pairs that make up the span row_heights : list of int A list of the number of newlines for each row in the table Returns ------- total_heigh...

Convert an html table to a data table and spans. Parameters ---------- html_string : str The string containing the html table Returns ------- table : list of lists of str spans : list of lists of lists of int A span is a list of [row, column] pairs that define what cells ...

Returns newick represenation of the tree in its current state. def newick(self, tree_format=0): "Returns newick represenation of the tree in its current state." # checks one of root's children for features and extra feats. if self.treenode.children: features = {"name", "dist", "supp...

Returns edge values in the order they are plotted (see .get_edges()) def get_edge_values(self, feature='idx'): """ Returns edge values in the order they are plotted (see .get_edges()) """ elist = [] for cidx in self._coords.edges[:, 1]: node = self.treenode.search_no...

Enter a dictionary mapping node 'idx' or tuple of tipnames to values that you want mapped to the stem and descendant edges that node. Edge values are returned in proper plot order to be entered to the edge_colors or edge_widths arguments to draw(). To see node idx values use node_lab...

Returns the node idx label of the most recent common ancestor node for the clade that includes the selected tips. Arguments can use fuzzy name matching: a list of tip names, wildcard selector, or regex string. def get_mrca_idx_from_tip_labels(self, names=None, wildcard=None, regex=None): """ ...

Returns node values from tree object in node plot order. To modify values you must modify the .treenode object directly by setting new 'features'. For example for node in ttree.treenode.traverse(): node.add_feature("PP", 100) By default node and tip values are hidden (set t...

Return node labels as a dictionary mapping {idx: name} where idx is the order of nodes in 'preorder' traversal. Used internally by the func .get_node_values() to return values in proper order. return_internal: if True all nodes are returned, if False only tips. return_nodes: if True r...

Returns coordinates of the tip positions for a tree. If no argument for axis then a 2-d array is returned. The first column is the x coordinates the second column is the y-coordinates. If you enter an argument for axis then a 1-d array will be returned of just that axis. def get_tip_coordinat...

Returns tip labels in the order they will be plotted on the tree, i.e., starting from zero axis and counting up by units of 1 (bottom to top in right-facing trees; left to right in down-facing). If 'idx' is indicated then a list of tip labels descended from that node will be returned,...

Returns False if there is a polytomy in the tree, including if the tree is unrooted (basal polytomy), unless you use the include_root=False argument. def is_bifurcating(self, include_root=True): """ Returns False if there is a polytomy in the tree, including if the tree is unroo...

Ladderize tree (order descendants) so that top child has fewer descendants than the bottom child in a left to right tree plot. To reverse this pattern use direction=1. def ladderize(self, direction=0): """ Ladderize tree (order descendants) so that top child has fewer descend...

Returns a copy of the tree where internal nodes with dist <= min_dist are deleted, resulting in a collapsed tree. e.g.: newtre = tre.collapse_nodes(min_dist=0.001) newtre = tre.collapse_nodes(min_support=50) def collapse_nodes(self, min_dist=1e-6, min_support=0): """ Returns a ...

Returns a copy of the tree with the selected tips removed. The entered value can be a name or list of names. To prune on an internal node to create a subtree see the .prune() function instead. Parameters: tips: list of tip names. # example: ptre = tre.drop_tips(['a', 'b...

Returns a ToyTree with the selected node rotated for plotting. tip colors do not align correct currently if nodes are rotated... def rotate_node( self, names=None, wildcard=None, regex=None, idx=None, # modify_tree=False, ): """ Retur...

Returns a copy of the tree with all polytomies randomly resolved. Does not transform tree in-place. def resolve_polytomy( self, dist=1.0, support=100, recursive=True): """ Returns a copy of the tree with all polytomies randomly resolved. Does not transfor...

Returns a copy of the tree unrooted. Does not transform tree in-place. def unroot(self): """ Returns a copy of the tree unrooted. Does not transform tree in-place. """ nself = self.copy() nself.treenode.unroot() nself.treenode.ladderize() nself._coords.update() ...

(Re-)root a tree by creating selecting a existing split in the tree, or creating a new node to split an edge in the tree. Rooting location is selected by entering the tips descendant from one child of the root split (e.g., names='a' or names=['a', 'b']). You can alternatively select a li...

Plot a Toytree tree, returns a tuple of Toyplot (Canvas, Axes) objects. Parameters: ----------- tree_style: str One of several preset styles for tree plotting. The default is 'n' (normal). Other options inlude 'c' (coalescent), 'd' (dark), and 'm' (multitree)...

Determine the side of cell1 that can be merged with cell2. This is based on the location of the two cells in the table as well as the compatability of their height and width. For example these cells can merge:: cell1 cell2 merge "RIGHT" +-----+ +------+ +-----+------+ ...

NHX format: [&&NHX:prop1=value1:prop2=value2] MB format: ((a[&Z=1,Y=2], b[&Z=1,Y=2]):1.0[&L=1,W=0], ... def parse_nhx(NHX_string): """ NHX format: [&&NHX:prop1=value1:prop2=value2] MB format: ((a[&Z=1,Y=2], b[&Z=1,Y=2]):1.0[&L=1,W=0], ... """ # store features ndict = {} # parse NH...

Load *data* from a file or string and return as a list of strings. The data contents could be one newick string; a multiline NEXUS format for one tree; multiple newick strings on multiple lines; or multiple newick strings in a multiline NEXUS format. In any case, we will read in the data...

get newick data from NEXUS def parse_nexus(self): "get newick data from NEXUS" if self.data[0].strip().upper() == "#NEXUS": nex = NexusParser(self.data) self.data = nex.newicks self.tdict = nex.tdict

test format of intree nex/nwk, extra features def get_treenodes(self): "test format of intree nex/nwk, extra features" if not self.multitree: # get TreeNodes from Newick extractor = Newick2TreeNode(self.data[0].strip(), fmt=self.fmt) # extract one tree ...

Reads a newick string in the New Hampshire format. def newick_from_string(self): "Reads a newick string in the New Hampshire format." # split on parentheses to traverse hierarchical tree structure for chunk in self.data.split("(")[1:]: # add child to make this node a parent. ...

iterate through data file to extract trees def extract_tree_block(self): "iterate through data file to extract trees" lines = iter(self.data) while 1: try: line = next(lines).strip() except StopIteration: break # ...

Parse CLI args. def parse_command_line(): """ Parse CLI args.""" ## create the parser parser = argparse.ArgumentParser( formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" * Example command-line usage: ## push test branch to conda --label=conda-test for travis CI ./ver...

Gets git and init versions and commits since the init version def get_git_status(self): """ Gets git and init versions and commits since the init version """ ## get git branch self._get_git_branch() ## get tag in the init file self._get_init_release_tag() ...

if no conflicts then write new tag to def push_git_package(self): """ if no conflicts then write new tag to """ ## check for conflicts, then write to local files self._pull_branch_from_origin() ## log commits to releasenotes if self.deploy: self._wr...

Pulls from origin/master, if you have unmerged conflicts it will raise an exception. You will need to resolve these. def _pull_branch_from_origin(self): """ Pulls from origin/master, if you have unmerged conflicts it will raise an exception. You will need to resolve these. """ ...

parses init.py to get previous version def _get_init_release_tag(self): """ parses init.py to get previous version """ self.init_version = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", open(self.init_file, "r").read(), ...

calls git log to complile a change list def _get_log_commits(self): """ calls git log to complile a change list """ ## check if update is necessary cmd = "git log --pretty=oneline {}..".format(self.init_version) cmdlist = shlex.split(cmd) commits = subprocess.che...

writes commits to the releasenotes file by appending to the end def _write_commits_to_release_notes(self): """ writes commits to the releasenotes file by appending to the end """ with open(self.release_file, 'a') as out: out.write("==========\n{}\n".format(self.tag)) ...

Write version to __init__.py by editing in place def _write_new_tag_to_init(self): """ Write version to __init__.py by editing in place """ for line in fileinput.input(self.init_file, inplace=1): if line.strip().startswith("__version__"): line = "__version__ ...

Write branch and tag to meta.yaml by editing in place def _write_branch_and_tag_to_meta_yaml(self): """ Write branch and tag to meta.yaml by editing in place """ ## set the branch to pull source from with open(self.meta_yaml.replace("meta", "template"), 'r') as infile: ...

Write version to __init__.py by editing in place def _revert_tag_in_init(self): """ Write version to __init__.py by editing in place """ for line in fileinput.input(self.init_file, inplace=1): if line.strip().startswith("__version__"): line = "__version__ = \...

tags a new release and pushes to origin/master def _push_new_tag_to_git(self): """ tags a new release and pushes to origin/master """ print("Pushing new version to git") ## stage the releasefile and initfileb subprocess.call(["git", "add", self.release_file]...

Run the Linux build and use converter to build OSX def build_conda_packages(self): """ Run the Linux build and use converter to build OSX """ ## check if update is necessary #if self.nversion == self.pversion: # raise SystemExit("Exited: new version == existing versio...

Gets the number of rows included in a span Parameters ---------- span : list of lists of int The [row, column] pairs that make up the span Returns ------- rows : int The number of rows included in the span Example ------- Consider this table:: +--------+--...

Convert ``x`` into a ``numpy.ndarray``. def asarray(x, dtype=None): '''Convert ``x`` into a ``numpy.ndarray``.''' iterable = scalarasiter(x) if isinstance(iterable, ndarray): return iterable else: if not hasattr(iterable, '__len__'): iterable = list(iterable) ...

Convert ``x`` into a ``column``-type ``numpy.ndarray``. def ascolumn(x, dtype = None): '''Convert ``x`` into a ``column``-type ``numpy.ndarray``.''' x = asarray(x, dtype) return x if len(x.shape) >= 2 else x.reshape(len(x),1)

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 def multis_2_mono(table): """ Converts each multiline string in a table to single line. ...

Get the number of rows 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_c...

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...

Decorator which check if timeseries has a better implementation of the function. 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 fun...

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)} def ...

Rolling Percentage range. Value between 0 and 1 indicating the position in the rolling range. 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 ...

data must be numeric list with a len above 20 This function counts the number of data points in a reduced array 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)...

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 binOp(op, indx, amap, bmap, fill_vec): ''' Combines the values from two map objects using the indx values usin...

takes a single value and creates a vecotor / matrix with that value filled in it 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

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. ...

Register a function in the function registry. The function will be automatically instantiated if not already an instance. def register(self, function): """Register a function in the function registry. The function will be automatically instantiated if not already an instanc...

Unregister function by name. def unregister(self, name): """Unregister function by name. """ try: name = name.name except AttributeError: pass return self.pop(name,None)

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 def row_includes_spans(table, row, spans): """ Determine if the...

Create a StateList object from a 'states' Workflow attribute. 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( ...

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...

Decorator to declare a function as a transition implementation. 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 call...

Ensure the given function has a xworkflows_hook attribute. That attribute has the following structure: >>> { ... 'before': [('state', <TransitionHook>), ...], ... } def _make_hook_dict(fun): """Ensure the given function has a xworkflows_hook attribute. That attribute has the following str...

Checks whether a given State matches self.names. 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 Transition matches self.names. 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)

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 ...

Run the pre-transition checks. 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 availabl...

Filter a list of hooks, keeping only applicable ones. 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_t...