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+ + + + + + + \ No newline at end of file diff --git a/pyre/graphs/graphStrongComponent9.json b/pyre/graphs/graphStrongComponent9.json new file mode 100644 index 0000000..69b8258 --- /dev/null +++ b/pyre/graphs/graphStrongComponent9.json @@ -0,0 +1 @@ +{"nodes": [{"color": "#97c2fc", "id": "build.lib.lollms.terminal.MainMenu.select_model", "label": "build.lib.lollms.terminal.MainMenu.select_model", "shape": "dot"}, {"color": "#97c2fc", "id": "build.lib.lollms.terminal.MainMenu.install_model", "label": "build.lib.lollms.terminal.MainMenu.install_model", "shape": "dot"}], "edges": [{"id": "build.lib.lollms.terminal.MainMenu.select_model_to_build.lib.lollms.terminal.MainMenu.select_model", "from": "build.lib.lollms.terminal.MainMenu.select_model", "to": "build.lib.lollms.terminal.MainMenu.select_model"}, {"id": "build.lib.lollms.terminal.MainMenu.select_model_to_build.lib.lollms.terminal.MainMenu.install_model", "from": "build.lib.lollms.terminal.MainMenu.select_model", "to": "build.lib.lollms.terminal.MainMenu.install_model"}]} \ No newline at end of file diff --git a/pyre/strong_graphs.py b/pyre/strong_graphs.py new file mode 100644 index 0000000..a03fa4e --- /dev/null +++ b/pyre/strong_graphs.py @@ -0,0 +1,284 @@ +import json +import math +from pathlib import Path +from typing import Any, Dict, List, Tuple +import csv +import matplotlib.patches as patches +import matplotlib.pyplot as plt +import networkx as nx +import numpy as np +from pyvis.network import Network +import click +import json +import networkx + +def bezier_curve( + src: np.ndarray, ctrl: List[float], dst: np.ndarray +) -> List[np.ndarray]: + """ + Generate Bézier curve points. + + Args: + - src (np.ndarray): The source point. + - ctrl (List[float]): The control point. + - dst (np.ndarray): The destination point. + + Returns: + - List[np.ndarray]: The Bézier curve points. + """ + curve = [] + for t in np.linspace(0, 1, num=100): + curve_point = ( + np.outer((1 - t) ** 2, src) + + 2 * np.outer((1 - t) * t, ctrl) + + np.outer(t**2, dst) + ) + curve.append(curve_point[0]) + return curve + + +def curved_edges( + G: nx.Graph, pos: Dict[Any, Tuple[float, float]], dist: float = 0.2 +) -> None: + """ + Draw curved edges for nodes on the same level. + + Args: + - G (Any): The graph object. + - pos (Dict[Any, Tuple[float, float]]): Dictionary with node positions. + - dist (float, optional): Distance for curvature. Defaults to 0.2. + + Returns: + - None + """ + ax = plt.gca() + for u, v, data in G.edges(data=True): + src = np.array(pos[u]) + dst = np.array(pos[v]) + + same_level = abs(src[1] - dst[1]) < 0.01 + + if same_level: + control = [(src[0] + dst[0]) / 2, src[1] + dist] + curve = bezier_curve(src, control, dst) + arrow = patches.FancyArrowPatch( + posA=curve[0], # type: ignore + posB=curve[-1], # type: ignore + connectionstyle=f"arc3,rad=0.2", + color="gray", + arrowstyle="-|>", + mutation_scale=15.0, + lw=1, + shrinkA=10, + shrinkB=10, + ) + ax.add_patch(arrow) + else: + ax.annotate( + "", + xy=dst, + xytext=src, + arrowprops=dict( + arrowstyle="-|>", color="gray", lw=1, shrinkA=10, shrinkB=10 + ), + ) + + +def tree_layout(graph: nx.DiGraph, root_node: Any) -> Dict[Any, Tuple[float, float]]: + """Compute positions as a tree layout centered on the root with alternating vertical shifts.""" + bfs_tree = nx.bfs_tree(graph, source=root_node) + levels = { + node: depth + for node, depth in nx.single_source_shortest_path_length( + bfs_tree, root_node + ).items() + } + + pos = {} + max_depth = max(levels.values()) + level_positions = {i: 0 for i in range(max_depth + 1)} # type: ignore + + # Count the number of nodes per level to compute the width + level_count: Any = {} + for node, level in levels.items(): + level_count[level] = level_count.get(level, 0) + 1 + + vertical_offset = ( + 0.07 # The amount of vertical shift per node within the same level + ) + + # Assign positions + for node, level in sorted(levels.items(), key=lambda x: x[1]): + total_nodes_in_level = level_count[level] + horizontal_spacing = 1.0 / (total_nodes_in_level + 1) + pos_x = ( + 0.5 + - (total_nodes_in_level - 1) * horizontal_spacing / 2 + + level_positions[level] * horizontal_spacing + ) + + # Alternately shift nodes up and down within the same level + pos_y = ( + -level + + (level_positions[level] % 2) * vertical_offset + - ((level_positions[level] + 1) % 2) * vertical_offset + ) + pos[node] = (pos_x, pos_y) + + level_positions[level] += 1 + + return pos + + +def graph_spring_layout( + dag: nx.DiGraph, labels: Dict[Any, str], tree: bool = True +) -> None: + num_nodes = len(dag.nodes()) + # Setting up the figure and axis + fig, ax = plt.subplots() + ax.axis("off") # Turn off the axis + + base = 3.0 + + if num_nodes > 10: + base /= 1 + math.log(num_nodes) + font_size = base * 10 + + font_size = max(10, base * 10) + node_size = max(300, base * 1000) + + if tree: + root_node = [node for node, degree in dag.in_degree() if degree == 0][0] + pos = tree_layout(dag, root_node) + else: + # Adjust k for the spring layout based on node count + k_value = 3 / math.sqrt(num_nodes) + + pos = nx.spring_layout(dag, k=k_value, iterations=50) + + # Draw nodes and labels + nx.draw_networkx_nodes(dag, pos, node_color="skyblue", node_size=int(node_size)) + nx.draw_networkx_labels(dag, pos, labels=labels, font_size=int(font_size)) + + # Draw curved edges + curved_edges(dag, pos) # type: ignore + + plt.tight_layout() + plt.show() + + +def rgb_to_hex(rgb: Tuple[float, float, float]) -> str: + return "#{:02x}{:02x}{:02x}".format( + int(rgb[0] * 255), int(rgb[1] * 255), int(rgb[2] * 255) + ) + + +def get_category_colors(categories: Dict[Any, str]) -> Dict[str, str]: + unique_categories = set(categories.values()) + colormap = plt.cm.get_cmap("tab10", len(unique_categories)) # type: ignore + return { + category: rgb_to_hex(colormap(i)[:3]) + for i, category in enumerate(unique_categories) + } + + +def graph_interactive_network( + dag: nx.DiGraph, + labels: Dict[Any, Dict[str, Any]], + html_graph_path: str = "", +) -> None: + + # now lets split + # nx. + #largest_components = sorted(nx.connected_components(dag), key=len, reverse=True)[:n] + size = 10 + #dag = dag.to_undirected() + largest_components = sorted(nx.strongly_connected_components(dag), key=len, reverse=True)[:size] + #largest_components = sorted(nx.connected_components(dag), key=len, reverse=True)[:size] + for index in range(size): + name= f'StrongComponent{index}' + component=dag.subgraph(largest_components[index]) + nt = Network(notebook=True, width="100%", height="800px", + #directed=True + ) + for edge in component.edges(): + source_id_str = edge[0] + target_id_str = edge[1] + edge_id_str = ( + f"{source_id_str}_to_{target_id_str}" # Construct a unique edge id + ) + nt.add_node(source_id_str) + nt.add_node(target_id_str) + nt.add_edge(source_id_str, target_id_str, id=edge_id_str) + hierarchical_options = { + "enabled": True, + #"levelSeparation": 200, # Increased vertical spacing between levels + #"nodeSpacing": 250, # Increased spacing between nodes on the same level + #"treeSpacing": 250, # Increased spacing between different trees (for forest) + "blockShifting": True, + # "edgeMinimization": True, + "parentCentralization": True, + #"direction": "UD", + "sortMethod": "directed", + } + physics_options = { + "stabilization": { + "enabled": True, + "iterations": 1000, # Default is often around 100 + }, + "hierarchicalRepulsion": { + "centralGravity": 0.0, + "springLength": 700, # Increased edge length + "springConstant": 0.01, + "nodeDistance": 750, # Increased minimum distance between nodes + "damping": 0.09, + }, + "solver": "hierarchicalRepulsion", + "timestep": 0.5, + } + nt.options = { + "nodes": { + "font": { + "size": 12, # Increased font size for labels + "color": "black", # Set a readable font color + }, + "shapeProperties": {"useBorderWithImage": True}, + }, + "edges": { + "length": 1050, # Increased edge length + }, + "physics": physics_options, + "layout": {"hierarchical": hierarchical_options}, + } + graph_data = {"nodes": nt.nodes, "edges": nt.edges} + json_graph = json.dumps(graph_data) + with open(f"graphs/graph{name}.json", "w") as f: + f.write(json_graph) + nt.show(f"graphs/graph{name}.html") + + +@click.command() +@click.argument('infile', type=click.File('r')) +def main(infile): + ind = csv.DictReader(infile) + dag = networkx.DiGraph() + for r in ind: + #(caller,callee) = + parts = r["name"].split("-") + caller = parts[0] + callee = parts[1] + count = int(r["count"]) + #print(caller, callee, count) + dag.add_edge(caller,callee, weight=count) + #with input ",name,count" + + #dag.add_nodes_from(self.items) + # for item in self.items: + # nodeid = clean_nodeid(item.nodeid) + # for dependency in self.dependencies[nodeid].dependencies: + # dag.add_edge(self.nodeid_to_item[dependency], item) + + labels = {} + graph_interactive_network(dag, labels, html_graph_path="") +if __name__ == "__main__": + main()