示例#1
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    def refresh(self, win=None):
        self.win.clear()
        self.win.b[0] = "FrainUI"
        Item.nodes = {}

        self.FREventEmit("ListReFreshPre")

        Item.clear() # 在刷新的时候, 把旧的所有 nodes 释放掉
        self.root = node.Node("root", None, self.get_roots)

        self.root.node_open()

        if self.Title:
            self.settitle(self.Title)

        #self.LS_Refresh_Hook()
        self.FREventEmit("ListReFreshPost")
        self.nu_refresh += 1
示例#2
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    def close(self, win):  # 关闭父级目录
        node = Item.getnode()
        route = node.route()
        fa = route[-2]
        if fa == self.root:
            return # 已经是root 了, 不可以关闭

        fa._open()
        self.win.cursor = (fa.getlinenu(), 0)
示例#3
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    def update_status(self):
        node = Item.getnode()
        if not node:
            return

        route = node.route()
        if not route:
            return

        try:
            ps = route[1:-1]
            path = '/'.join([r.name for r in ps])
        except:
            path = route[1].name
        self.win.b.vars['frain_status_path'] = path
示例#4
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def build_topology(matrix_S, matrix_D, active_user, target_song):
    """
    Function that builds the topology of the network.
    Parameters
    ----------

    matrix_S: pd.DataFrame
    matrix_D: pd.DataFrame
    active_user: int
                Active user ID
    target_song: int
                Target song ID
    """

    # 1) *********************** STATIC TOPOLOGY ***********************
    # 1.a) ********************* Content based *************************

    # 1.a.1) Instantiate Acb.
    a_cb = User(active_user, cb=True)

    # 1.a.2) Instantiate songs reviewed by the active user
    item_nodes = [Item(i) for i in matrix_S.columns[1:]]

    # 1.a.3) Instantiate edges from items rated by active user to A_cb (i --> A_cb)
    i_acb_edges = [Edge(i, a_cb) for i in item_nodes]

    # 1.a.4) Instantiate features and the corresponding edges (f --> i) to their children items
    feature_nodes = [Feature(f) for f in matrix_D.columns[1:]]
    f_i_edges = get_edges(feature_nodes, item_nodes, matrix_D)

    # 1.b) ********************* Collaborative component *************************
    # 1.b.1) Instantiate Acf. Instantiate k most-similar users.
    a_cf = User(active_user, cf=True)
    user_nodes = get_users(active_user, matrix_S, k=4)

    # 1.b.2) Instantiate edges from k-most similar users to Acf.
    u_acf_edges = [Edge(u, a_cf) for u in user_nodes]

    # 1.c) ********************** Hybrid Component **************************+
    # 1.c.1) Instantiate Ah, create edges with Acf and Acb
    a_h = User(active_user, h=True)
    acf_ah_edge = Edge(a_cf, a_h)
    acb_ah_edge = Edge(a_cb, a_h)

    # 2) *********************** DYNAMIC TOPOLOGY ***********************
    # 2.a) ********************* Content based *************************
    # 2.a.1) Set target item
    target_song_node = [i for i in item_nodes if i.index == target_song][0]
    target_song_node.set_as_target()

    # 2.a.2) Instantiate edges from all features describing target item to target item.
    f_target_song_edges = get_edges(feature_nodes, [target_song_node],
                                    matrix_D)

    # 2.b) ********************* Collaborative component *************************

    # 2.b.1) From the set of k-most similar users, get those that didn't rate the target item, U_.
    u_minus = get_u_minus([u for u in user_nodes if u.index != active_user],
                          target_song_node, matrix_S)

    # 2.b.2) Instantiate edges from items rated by users in U_ to users in U_.
    i_u_minus_edges = get_edges(item_nodes, u_minus, matrix_S)

    # 3) Return graph
    nodes = [obj for obj in gc.get_objects() if isinstance(obj, Node)]

    edges = [obj for obj in gc.get_objects() if isinstance(obj, Edge)]

    graph = Graph(nodes, edges)

    return graph
示例#5
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 def delete(self, win):
     node = Item.getnode()
     if node:
         node.FREventEmit("delete")
示例#6
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 def open(self, win):
     node = Item.getnode()
     if node:
         node._open()