HComP-Net / app.py
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import gradio as gr
import plotly.graph_objects as go
import os
from collections import defaultdict
import igraph as ig
# print(os.pwd())
species_to_imgpath = {'bird': './descendent_specific_topk_heatmap_withbb_ep=last_024+051',
'fish': './descendent_specific_topk_heatmap_withbb_ep=last_024+051',
'butterfly': './descendent_specific_topk_heatmap_withbb_ep=last_024+051',
}
# this has to be there for each species
imgname_to_filepath = {} # this ignores the extension such as .png
nodename_to_protoIDs = defaultdict(list)
for species, imgpath in species_to_imgpath.items():
for foldername in os.listdir(imgpath):
if os.path.isdir(os.path.join(imgpath, foldername)):
folderpath = os.path.join(imgpath, foldername)
for filename in os.listdir(folderpath):
if filename.endswith('png') or filename.endswith('jpg'):
filepath = os.path.join(folderpath, filename)
imgname_to_filepath[filename] = filepath
nodename = filename.split('.')[0].split('-')[0]
protoID = filename.split('.')[0].split('-')[1]
nodename_to_protoIDs[nodename].append(protoID)
class Node():
id = 0
def __init__(self, name):
self.id = Node.id
Node.id += 1
self.name = name
self.parent = None
self.children = [] # list of type Node
def add_child(child):
self.children.append(child)
name_to_node = {}
id_to_node = {}
def get_root(node):
root = node
while node:
root = node
node = node.parent
return root
def get_tree(imgpath):
for foldername in os.listdir(imgpath):
if os.path.isdir(os.path.join(imgpath, foldername)):
folderpath = os.path.join(imgpath, foldername)
node_name = foldername
child_names = list(set([filename.split('.')[0].split('-')[0] for filename in os.listdir(folderpath)]))
if node_name in name_to_node:
node = name_to_node[node_name]
else:
node = Node(node_name)
name_to_node[node_name] = node
id_to_node[node.id] = node
child_nodes = []
for child_name in child_names:
if child_name in name_to_node:
child_node = name_to_node[child_name]
else:
child_node = Node(child_name)
name_to_node[child_name] = child_node
id_to_node[child_node.id] = child_node
child_node.parent = node
child_nodes.append(child_node)
node.children = child_nodes
# To be finished
return get_root(node)
ROOT = None
def create_binary_tree_edges(root):
edges = []
prev = [root]
while len(prev) > 0:
new_prev = []
for node in prev:
# print(node.children, '\n')
edges = edges + [(node.id, child.id) for child in node.children]
new_prev = new_prev + [child for child in node.children if (len(child.children) > 0)]
prev = new_prev
# print(edges)
# print('-*'*20, '\n')
return edges
def plot_tree_using_igraph():
# Define the edges in a tree structure
# edges = [(0, 1), (0, 2), (1, 3), (1, 4), (2, 5), (2, 6)]
root = ROOT
edges = create_binary_tree_edges(root)
# edges = [(str(n1), str(n2)) for (n1, n2) in edges]
# print(edges)
# Create an igraph Graph from the edge list
g = ig.Graph(edges, directed=True)
# Validate the root index
if g.vcount() > 0: # Check if the graph has any vertices
root_vertex_id = 0 # This assumes that vertex '0' is the root
else:
print("The graph has no vertices.")
return None
# Use the Reingold-Tilford layout to position the nodes
try:
layout = g.layout_reingold_tilford(root=None) # Correct root specification
except Exception as e:
print(f"Error computing layout: {e}")
return None
# Edge traces
edge_x = []
edge_y = []
for edge in edges:
start_idx, end_idx = edge
x0, y0 = layout.coords[start_idx]
x1, y1 = layout.coords[end_idx]
edge_x.extend([x0, x1, None])
edge_y.extend([-y0, -y1, None]) # y values are inverted to make the tree top-down
edge_trace = go.Scatter(
x=edge_x, y=edge_y,
line=dict(width=0.5, color='#888'),
hoverinfo='none',
mode='lines')
# Node traces
node_x = [pos[0] for pos in layout.coords]
node_y = [-pos[1] for pos in layout.coords] # y values are inverted
node_trace = go.Scatter(
x=node_x, y=node_y,
text=[id_to_node[i].name for i in range(len(layout.coords))],
# text=["Node {}".format(i) for i in range(len(layout.coords))],
mode='markers+text',
hoverinfo='text',
marker=dict(
showscale=False,
size=10,
color='LightSkyBlue'
),
textposition="bottom center"
)
# Create a Plotly figure
fig = go.Figure(data=[edge_trace, node_trace],
layout=go.Layout(
title='<b>Tree Layout with iGraph and Plotly</b>',
titlefont_size=16,
showlegend=False,
hovermode='closest',
margin=dict(b=0, l=0, r=0, t=50),
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
# height=600,
# width=600,
annotations=[dict(
showarrow=False,
xref="paper", yref="paper",
x=0.005, y=-0.002 )]
))
return fig
def plot_tree_from_species(species_name):
# Define the edges in a tree structure
# edges = [(0, 1), (0, 2), (1, 3), (1, 4), (2, 5), (2, 6)]
imgpath = species_to_imgpath[species_name]
print(imgpath)
root = get_tree(imgpath)
# root = ROOT
edges = create_binary_tree_edges(root)
# edges = [(str(n1), str(n2)) for (n1, n2) in edges]
# print(edges)
# Create an igraph Graph from the edge list
g = ig.Graph(edges, directed=True)
# Validate the root index
if g.vcount() > 0: # Check if the graph has any vertices
root_vertex_id = 0 # This assumes that vertex '0' is the root
else:
print("The graph has no vertices.")
return None
# Use the Reingold-Tilford layout to position the nodes
try:
layout = g.layout_reingold_tilford(root=None) # Correct root specification
except Exception as e:
print(f"Error computing layout: {e}")
return None
# Edge traces
edge_x = []
edge_y = []
for edge in edges:
start_idx, end_idx = edge
x0, y0 = layout.coords[start_idx]
x1, y1 = layout.coords[end_idx]
edge_x.extend([x0, x1, None])
edge_y.extend([-y0, -y1, None]) # y values are inverted to make the tree top-down
edge_trace = go.Scatter(
x=edge_x, y=edge_y,
line=dict(width=0.5, color='#888'),
hoverinfo='none',
mode='lines')
# Node traces
node_x = [pos[0] for pos in layout.coords]
node_y = [-pos[1] for pos in layout.coords] # y values are inverted
node_trace = go.Scatter(
x=node_x, y=node_y,
text=[id_to_node[i].name for i in range(len(layout.coords))],
# text=["Node {}".format(i) for i in range(len(layout.coords))],
mode='markers+text',
hoverinfo='text',
marker=dict(
showscale=False,
size=10,
color='LightSkyBlue'
),
textposition="bottom center"
)
# Create a Plotly figure
fig = go.Figure(data=[edge_trace, node_trace],
layout=go.Layout(
title='<b>Tree Layout with iGraph and Plotly</b>',
titlefont_size=16,
showlegend=False,
hovermode='closest',
margin=dict(b=0, l=0, r=0, t=50),
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
# height=600,
# width=600,
annotations=[dict(
showarrow=False,
xref="paper", yref="paper",
x=0.005, y=-0.002 )]
))
return gr.Plot(fig)
def set_nodename_to_protoIDs(species_name):
global nodename_to_protoIDs
imgpath = species_to_imgpath[species_name]
for foldername in os.listdir(imgpath):
if os.path.isdir(os.path.join(imgpath, foldername)):
folderpath = os.path.join(imgpath, foldername)
for filename in os.listdir(folderpath):
if filename.endswith('png') or filename.endswith('jpg'):
filepath = os.path.join(folderpath, filename)
imgname_to_filepath[filename] = filepath
nodename = filename.split('.')[0].split('-')[0]
protoID = filename.split('.')[0].split('-')[1]
nodename_to_protoIDs[nodename].append(protoID)
def get_protoIDs(nodename):
return gr.Dropdown(choices=nodename_to_protoIDs[nodename], interactive=True)
def get_nodenames(species_name):
return gr.Dropdown(choices=list(nodename_to_protoIDs.keys()), interactive=True)
def get_image(nodename, protoID):
imgname = '-'.join([nodename, protoID]) + '.png'
filepath = imgname_to_filepath[imgname]
return gr.Image(filepath)
def species_change(species_name):
set_nodename_to_protoIDs(species_name)
return [plot_tree_from_species(species_name), get_nodenames(species_name), get_nodenames(species_name)]
with gr.Blocks() as demo:
imgpath = species_to_imgpath['bird']
print(imgpath)
ROOT = get_tree(imgpath)
print(ROOT.name)
gr.Markdown("## Interactive Tree and Image Display")
# with gr.Row():
# tree_output = gr.Plot(plot_tree_using_igraph) # Connect the function directly
# with gr.Row():
# with gr.Column():
# dropdown_1_nodename = gr.Dropdown(label="Select a node name", choices=list(nodename_to_protoIDs.keys()))
# dropdown_1_protos = gr.Dropdown(label="Select a prototype ID", choices=[], allow_custom_value=True)
# image_output_1 = gr.Image()
# with gr.Column():
# dropdown_2_nodename = gr.Dropdown(label="Select a node name", choices=list(nodename_to_protoIDs.keys()))
# dropdown_2_protos = gr.Dropdown(label="Select a prototype ID", choices=[], allow_custom_value=True)
# image_output_2 = gr.Image()
# dropdown_1_nodename.change(get_protoIDs, dropdown_1_nodename, dropdown_1_protos)
# dropdown_1_protos.change(get_image, [dropdown_1_nodename, dropdown_1_protos], image_output_1)
# dropdown_2_nodename.change(get_protoIDs, dropdown_2_nodename, dropdown_2_protos)
# dropdown_2_protos.change(get_image, [dropdown_2_nodename, dropdown_2_protos], image_output_2)
with gr.Row():
dropdown_species = gr.Dropdown(label="Select a species", choices=list(species_to_imgpath.keys()))
with gr.Row():
tree_output = gr.Plot() # Connect the function directly
with gr.Row():
with gr.Column():
dropdown_1_nodename = gr.Dropdown(label="Select a node name", choices=[])
dropdown_1_protos = gr.Dropdown(label="Select a prototype ID", choices=[], allow_custom_value=True)
image_output_1 = gr.Image()
with gr.Column():
dropdown_2_nodename = gr.Dropdown(label="Select a node name", choices=[])
dropdown_2_protos = gr.Dropdown(label="Select a prototype ID", choices=[], allow_custom_value=True)
image_output_2 = gr.Image()
# dropdown_species.change(plot_tree_from_species, dropdown_species, tree_output)
dropdown_species.change(species_change, dropdown_species, [tree_output, dropdown_1_nodename, dropdown_1_nodename])
# dropdown_species.change(set_nodename_to_protoIDs)
# dropdown_species.change(get_nodenames, dropdown_species, dropdown_1_nodename)
# dropdown_species.change(get_nodenames, dropdown_species, dropdown_2_nodename)
dropdown_1_nodename.change(get_protoIDs, dropdown_1_nodename, dropdown_1_protos)
dropdown_1_protos.change(get_image, [dropdown_1_nodename, dropdown_1_protos], image_output_1)
dropdown_2_nodename.change(get_protoIDs, dropdown_2_nodename, dropdown_2_protos)
dropdown_2_protos.change(get_image, [dropdown_2_nodename, dropdown_2_protos], image_output_2)
# imgpath = species_to_imgpath['bird']
# print(imgpath)
# ROOT = get_tree(imgpath)
# print(ROOT.name)
# gr.Markdown("## Interactive Tree and Image Display")
# with gr.Row():
# tree_output = gr.Plot(plot_tree_using_igraph) # Connect the function directly
# with gr.Row():
# with gr.Column():
# dropdown_3_nodename = gr.Dropdown(label="Select a node name", choices=list(nodename_to_protoIDs.keys()))
# dropdown_3_protos = gr.Dropdown(label="Select a prototype ID", choices=[], allow_custom_value=True)
# image_output_3 = gr.Image()
# with gr.Column():
# dropdown_4_nodename = gr.Dropdown(label="Select a node name", choices=list(nodename_to_protoIDs.keys()))
# dropdown_4_protos = gr.Dropdown(label="Select a prototype ID", choices=[], allow_custom_value=True)
# image_output_4 = gr.Image()
# dropdown_3_nodename.change(get_protoIDs, dropdown_3_nodename, dropdown_3_protos)
# dropdown_3_protos.change(get_image, [dropdown_3_nodename, dropdown_3_protos], image_output_3)
# dropdown_4_nodename.change(get_protoIDs, dropdown_4_nodename, dropdown_4_protos)
# dropdown_4_protos.change(get_image, [dropdown_4_nodename, dropdown_4_protos], image_output_4)
# Initialize with placeholder images
# image_output_1.update(display_image_based_on_dropdown_1)
# image_output_2.update(display_image_based_on_dropdown_2)
demo.launch()