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How to use _converged method in molecule

Best Python code snippet using molecule_python

_control.py

Source:_control.py

1"""Control objects for surface calculations."""2from fsc.export import export3from ..line._control import _create_line_controls4from .._control import (5    ControlContainer, DataControl, ConvergenceControl, StatefulControl,6    IterationControl, SurfaceControl, LineControl7)8from .._utils import _get_max_move9@export10class SurfaceControlContainer(ControlContainer):11    """12    Container for controls used in the surface run.13    """14    def __init__(self, controls):15        super().__init__(16            controls=controls,17            categories={18                'line': [LineControl],19                'stateful': [StatefulControl, SurfaceControl],20                'data': [DataControl, SurfaceControl],21                'convergence': [ConvergenceControl, SurfaceControl],22                'iteration': [IterationControl, SurfaceControl],23            },24            valid_type=(SurfaceControl, LineControl),25        )26@export27class MoveCheck(DataControl, ConvergenceControl, SurfaceControl):28    """29    Performs the check whether the WCC in neighbouring lines have moved too much.30    """31    def __init__(self, *, move_tol):32        self.move_tol = move_tol33        self._converged = None34    @property35    def converged(self):36        return self._converged37    def update(self, data):38        self._converged = [39            _get_max_move(l1.wcc, l2.wcc) <40            self.move_tol * min(l1.gap_size, l2.gap_size)41            for l1, l2 in zip(data.lines[:-1], data.lines[1:])42        ]43@export44class GapCheck(DataControl, ConvergenceControl, SurfaceControl):45    """46    Performs the check whether the largest gap is too close to WCC in neighbouring lines.47    """48    def __init__(self, *, gap_tol):49        self.gap_tol = gap_tol50        self._converged = None51    @property52    def converged(self):53        return self._converged54    def update(self, data):55        self._converged = [56            all(57                abs(w2 - l1.gap_pos) > self.gap_tol * l1.gap_size58                for w2 in l2.wcc59            ) and all(60                abs(w1 - l2.gap_pos) > self.gap_tol * l2.gap_size61                for w1 in l1.wcc62            ) for l1, l2 in zip(data.lines, data.lines[1:])63        ]64def _create_surface_controls(*, pos_tol, iterator, move_tol, gap_tol):65    """66    Helper function to create the control objects needed by a surface calculation.67    """68    controls = _create_line_controls(pos_tol=pos_tol, iterator=iterator)69    if move_tol is not None:70        controls.append(MoveCheck(move_tol=move_tol))71    if gap_tol is not None:72        controls.append(GapCheck(gap_tol=gap_tol))...

main.py

Source:main.py

1#!/usr/bin/env python32from __future__ import annotations3from typing import Dict, Iterable, List4class Node:5    def __init__(self, name: int):6        self.name = name7        self.score = 1.08        self._temp_score = 1.09        self._parents: List[Node] = []10        self._children: List[Node] = []11    def update(self, new_score: float, epsilon: float) -> bool:12        self._temp_score = new_score13        return abs(new_score - self.score) < epsilon14    def release(self):15        self.score = self._temp_score16    def connect(self, other: Node) -> None:17        if other not in self._children:18            self._children.append(other)19        other.add_parent(self)20    def add_parent(self, parent: Node) -> None:21        if parent not in self._parents:22            self._parents.append(parent)23    def parents(self) -> Iterable[Node]:24        return self._parents25    @property26    def outgoing(self) -> int:27        return len(self._children)28class PageRank:29    def __init__(self, damping: int = 0.7, epsilon: float = 0.001):30        self.epsilon = epsilon31        self.damping = damping32        self._jump_factor = damping33        self._converged: Dict[Node, bool] = {}34    def add(self, new_node: Node) -> None:35        self._converged[new_node] = False36        self._jump_factor = (1-self.damping)/len(self._converged)37    def print_scores(self):38        print("Scores:")39        for node in self._converged.keys():40            print(f"{node.name}: score:{node.score:.2f}")41    def run(self, max_iterations: int = 100):42        count = 043        while(count < max_iterations and not all(self._converged.values())):44            for node in self._converged.keys():45                if self._converged[node]:46                    continue47                new_score = (48                    self._jump_factor49                    + self.damping50                    * sum([n.score / n.outgoing for n in node.parents()])51                )52                stop = node.update(new_score, self.epsilon)53                self._converged[node] = stop54            for node in self._converged.keys():55                node.release()56            count += 157        self.print_scores()58        print(f"\nIterations:{count}")59def main():60    a = Node(1)61    b = Node(2)62    c = Node(3)63    d = Node(4)64    e = Node(5)65    a.connect(b)66    b.connect(c); b.connect(e)67    c.connect(a)68    d.connect(e)69    e.connect(e)70    ranker = PageRank()71    ranker.add(a); ranker.add(b); ranker.add(c); ranker.add(d); ranker.add(e)72    ranker.run()73if __name__ == "__main__":...

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