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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 ...
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])] =...
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...
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...
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 = ...
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)
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...
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) ...
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
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 ...
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] = ...
def unregister(self, name): """Unregister function by name. """ try: name = name.name except AttributeError: pass return self.pop(name,None)
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...
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 " ...
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...
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)")...
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_...
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)
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)
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...
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'." % ...
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))
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)
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...
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...
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 ...
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....
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. ...
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...
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...
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...
def transform(self, attrs): """Perform all actions on a given attribute dict.""" self.collect(attrs) self.add_missing_implementations() self.fill_attrs(attrs)
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: ...
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)
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...
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...
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 =...
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) ...
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...
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...
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). ...
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, ...
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...
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') ...
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,...
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...
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...
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 = [...
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...
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...
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...
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. ...
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...
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
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
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] == '-':...
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...
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...
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...
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) :...
def get_dialog(self): """Return FormDialog instance""" dialog = self.parent() while not isinstance(dialog, QDialog): dialog = dialog.parent() return dialog
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...
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)
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...
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...
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)
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...
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
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...
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 ...
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...
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, ...
def isconsistent(self): '''Check if the timeseries is consistent''' for dt1, dt0 in laggeddates(self): if dt1 <= dt0: return False return True
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 ...
def sd(self): '''Calculate standard deviation of timeseries''' v = self.var() if len(v): return np.sqrt(v) else: return None
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``. ...
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...
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...
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._...
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: ...
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 ----- ...
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...
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
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])
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 ...
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...
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', ''] ...
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...
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.'...
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...
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...
def downgrade(): """Downgrade database.""" op.drop_table('transaction') if op._proxy.migration_context.dialect.supports_sequences: op.execute(DropSequence(Sequence('transaction_id_seq')))
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) ...
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 == '...
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...
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]+"...
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...
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...
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...
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...