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building_blocks.py
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building_blocks.py
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import dash
import dash_core_components as dcc
import dash_bootstrap_components as dbc
import dash_html_components as html
import dash_cytoscape as cyto
import dash_daq as daq
from dash.dependencies import Output, Input, State
import plotly.graph_objs as go
import plotly.express as px
from urllib.request import quote
import pandas as pd
import numpy as np
import os
import pickle
from tqdm import tqdm
import networkx as nx
from networkx.algorithms.community import modularity
import matplotlib.pyplot as plt
from matplotlib.colors import rgb2hex
from sklearn.cluster import KMeans
from scipy.stats import halfnorm
from app import app
loading_banner = html.Div(
html.Center(
[
html.Div(style={"height": "10vh"}),
dbc.Fade(
dbc.Jumbotron(
[
html.Center(
html.Img(
src="/assets/imgs/logo.svg",
alt="COVIDrugNet",
style={"width": "40%"},
)
),
html.Br(),
html.H2("Sorry, it's taking some time to load ..."),
html.Hr(),
html.H5("Networks are becoming more and more complex"),
html.H5(
"and the browser could take a while to render the page"
),
html.P(
[
"If it takes too long (or it doesn't load at all) please let us know"
]
),
# html.Br(),
# html.Small("A small banner could also appear on top of your window saying that a calculation is slowing down your browser")
],
style={"width": "40vw"},
),
is_in=True,
timeout=250,
),
]
),
id="page_content",
)
def common_data_generator(prefix, graph):
if prefix == "drug_projection":
with open("data/others/atc_description.pickle", "rb") as bkp:
atc_description = pickle.load(bkp)
else:
atc_description = []
graph_properties_df = pd.DataFrame(
{
node: {
prop: values[prop]
for prop in [
"Name",
"Degree",
"Closeness Centrality",
"Betweenness Centrality",
"Eigenvector Centrality",
"Clustering Coefficient",
"VoteRank Score",
]
}
for node, values in dict(graph.nodes(data=True)).items()
}
).T
maj = graph.subgraph(max(list(nx.connected_components(graph)), key=len))
print("\tCommunities Detection Data Precomputing ...")
if os.path.isfile("data/groups/" + prefix + "_communities.pickle"):
with open("data/groups/" + prefix + "_communities.pickle", "rb") as bkp:
(
girvan_newman,
girvan_newman_maj,
communities_modularity,
communities_modularity_maj,
n_comm,
n_comm_maj,
) = pickle.load(bkp)
else:
import ray
try:
ray.init()
except:
ray.shutdown()
ray.init()
def collect_GN_communities(graph, prefix):
nested_ids = [compute_GN_communities.remote(g) for g in [graph, maj]]
results, maj_results = ray.get(nested_ids)
print(
"\t\tGirvan Newman Communities Computed for %s"
% prefix.replace("_", " ").title()
)
return [r[i] for i in range(len(results)) for r in [results, maj_results]]
@ray.remote
def compute_GN_communities(graph):
girvan_newman = {
len(comm): comm for comm in nx.algorithms.community.girvan_newman(graph)
}
communities_modularity = {
modularity(graph, community): n
for n, community in girvan_newman.items()
}
n_comm = communities_modularity[max(communities_modularity)]
return girvan_newman, communities_modularity, n_comm
communities = collect_GN_communities(graph, prefix)
(
girvan_newman,
girvan_newman_maj,
communities_modularity,
communities_modularity_maj,
n_comm,
n_comm_maj,
) = communities
print("\tCommunities Computed! Saving...")
name = "data/groups/" + prefix + "_communities.pickle"
with open(name, "wb") as bkp:
pickle.dump(
[
girvan_newman,
girvan_newman_maj,
communities_modularity,
communities_modularity_maj,
n_comm,
n_comm_maj,
],
bkp,
)
if os.path.isfile(name + ".bkp"):
os.remove(name + ".bkp")
ray.shutdown()
print("\tSpectral Clustering Data Precomputing ...")
if os.path.isfile("data/groups/" + prefix + "_spectral.pickle"):
with open("data/groups/" + prefix + "_spectral.pickle", "rb") as bkp:
(
L,
evals,
evects,
n_clusters,
clusters,
L_maj,
evals_maj,
evects_maj,
n_clusters_maj,
clusters_maj,
) = pickle.load(bkp)
else:
L = nx.normalized_laplacian_matrix(graph).toarray()
evals, evects = np.linalg.eigh(L)
relevant = [
n
for n, dif in enumerate(np.diff(evals))
if dif > halfnorm.ppf(0.99, *halfnorm.fit(np.diff(evals)))
]
relevant = [
relevant[n]
for n in range(len(relevant) - 1)
if relevant[n] + 1 != relevant[n + 1]
] + [
relevant[-1]
] # keeps only the highest value if there are consecutive ones
n_clusters = (
relevant[0] + 1
if (
relevant[0] > 1
and relevant[0] + 1 != nx.number_connected_components(graph)
)
else relevant[1] + 1
)
km = KMeans(n_clusters=n_clusters, n_init=100)
clusters = km.fit_predict(evects[:, :n_clusters])
L_maj = nx.normalized_laplacian_matrix(maj).toarray()
evals_maj, evects_maj = np.linalg.eigh(L_maj)
relevant_maj = [
n
for n, dif in enumerate(np.diff(evals_maj))
if dif > halfnorm.ppf(0.99, *halfnorm.fit(np.diff(evals_maj)))
]
relevant_maj = [
relevant_maj[n]
for n in range(len(relevant_maj) - 1)
if relevant_maj[n] + 1 != relevant_maj[n + 1]
] + [
relevant_maj[-1]
] # keeps only the highest value if there are consecutive ones
n_clusters_maj = (
relevant_maj[0] + 1
if (
relevant_maj[0] > 1
and relevant_maj[0] + 1 != nx.number_connected_components(maj)
)
else relevant_maj[1] + 1
)
km_maj = KMeans(n_clusters=n_clusters_maj, n_init=100)
clusters_maj = km_maj.fit_predict(evects_maj[:, :n_clusters_maj])
name = "data/groups/" + prefix + "_spectral.pickle"
with open(name, "wb") as bkp:
pickle.dump(
[
L,
evals,
evects,
n_clusters,
clusters,
L_maj,
evals_maj,
evects_maj,
n_clusters_maj,
clusters_maj,
],
bkp,
)
if os.path.isfile(name + ".bkp"):
os.remove(name + ".bkp")
return (
graph_properties_df,
L,
evals,
evects,
n_clusters,
clusters,
L_maj,
evals_maj,
evects_maj,
n_clusters_maj,
clusters_maj,
girvan_newman,
maj,
girvan_newman_maj,
communities_modularity,
communities_modularity_maj,
n_comm,
n_comm_maj,
atc_description,
)
def headbar():
return dbc.Navbar(
dbc.Container(
[
html.A(
dbc.Row(
[
html.Img(
src=app.get_asset_url("imgs/logo_white.svg"),
style={"height": "4vh", "margin-right": "1rem"},
),
# dbc.NavbarBrand("COVIDrugNet")
],
no_gutters=True,
justify="start",
align="center",
),
href="/covidrugnet",
className="card-link",
),
dbc.NavbarToggler(id="headbar_toggler"),
dbc.Collapse(
[
dbc.Nav(
[
dbc.NavItem(
dbc.NavLink(
[
html.I(
className="fa fa-home",
style={"margin-right": "0.4rem"},
),
"Home",
],
href="/covidrugnet/home",
active=True,
className="nav-link active",
external_link=True,
),
className="nav-item",
id="home_nav",
),
dbc.Tooltip(
"COVIDrugNet Homepage",
target="home_nav",
placement="bottom",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
[
html.I(
className="fa fa-question",
style={"margin-right": "0.4rem"},
),
"Help",
],
href="/covidrugnet/help",
active=True,
className="nav-link active",
external_link=True,
),
className="nav-item",
id="help_nav",
),
dbc.Tooltip(
"Page Structure and Main Possible Interactions",
target="help_nav",
placement="bottom",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
[
html.I(
className="fa fa-info",
style={"margin-right": "0.4rem"},
),
"About",
],
href="/covidrugnet/about",
active=True,
className="nav-link active",
external_link=True,
),
className="nav-item",
id="about_nav",
),
dbc.Tooltip(
"Info About the Project",
target="about_nav",
placement="bottom",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
[
html.I(
className="fa fa-address-book",
style={"margin-right": "0.4rem"},
),
"Contacts",
],
href="/covidrugnet/contacts",
active=True,
className="nav-link active",
external_link=True,
),
className="nav-item",
id="contacts_nav",
),
dbc.Tooltip(
"Project Participant's Contacts",
target="contacts_nav",
placement="bottom",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.Nav(
[
dbc.NavLink(
html.I(className="fa fa-project-diagram"),
active=True,
className="nav-link active",
style={"margin-right": "-0.6rem"},
), # patch for graphs label icon
dbc.DropdownMenu(
[
dbc.DropdownMenuItem(
"Drug-Target Network",
href="/covidrugnet/drug_target",
className="dropdown-item",
external_link=True,
),
dbc.DropdownMenuItem(
"Drug Projection",
href="/covidrugnet/drug_projection",
className="dropdown-item",
external_link=True,
),
dbc.DropdownMenuItem(
"Target Projection",
href="/covidrugnet/target_projection",
className="dropdown-item",
external_link=True,
),
# dbc.DropdownMenuItem("Target Disease", href="/target_disease", className="dropdown-item"), # not yet available
# dbc.DropdownMenuItem("Target Interactors", href="/target_interactors", className="dropdown-item") # not yet available
],
nav=True,
in_navbar=True,
right=True,
label="Graphs ...",
className="nav-item dropdown active",
),
],
className="nav-item",
id="other_graphs_nav",
),
dbc.Tooltip(
"Browse Other Available Graphs",
target="other_graphs_nav",
placement="left",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
],
className="ml-auto",
navbar=True,
)
],
id="headbar_collapse",
navbar=True,
),
],
fluid=True,
),
color="primary",
dark=True,
sticky="top",
style={"box-shadow": "0px 2px 5px darkgrey"},
)
def sidebar(prefix):
if prefix in ["drug_target", "drug_projection", "target_projection"]:
items = [
dbc.NavItem(
dbc.NavLink(
"Graph",
href="#" + prefix + "_graph_container",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_graph_side",
),
dbc.Tooltip(
"Jump to Graph's Section",
target=prefix + "_graph_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
"Inspected Data",
href="#" + prefix + "_inspected_table",
external_link=True,
id=prefix + "_side_inspected_table",
active=False,
disabled=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_inspected_data_side",
),
dbc.Tooltip(
"Jump to Inspected Data's Section",
target=prefix + "_inspected_data_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
id=prefix + "_inspected_data_side_tooltip",
),
dbc.NavItem(
dbc.NavLink(
"Charts and Plots",
href="#" + prefix + "_plots",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_plots_side",
),
dbc.Tooltip(
"Jump to Charts and Plots' Section",
target=prefix + "_plots_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
"Graph Properties",
href="#" + prefix + "_graph_properties_table",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_graph_properties_side",
),
dbc.Tooltip(
"Jump to Graph Properties' Section",
target=prefix + "_graph_properties_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
html.Hr(),
dbc.NavItem(
dbc.NavLink(
"Clustering",
href="#" + prefix + "_clustering",
external_link=True,
active=True,
className="nav-link",
id=prefix + "_side_clustering",
),
className="nav-item",
id=prefix + "_clustering_side",
),
dbc.Tooltip(
"Jump to Clustering's Section",
target=prefix + "_clustering_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
id=prefix + "_clustering_side_tooltip",
),
]
if "projection" in prefix:
items += [
dbc.NavItem(
dbc.NavLink(
"Degree Distribution Fittings",
href="#" + prefix + "_adv_degree_distribution",
external_link=True,
active=True,
className="nav-link",
id=prefix + "_side_adv_degree_distribution",
),
className="nav-item",
id=prefix + "_adv_degree_distribution_side",
),
dbc.Tooltip(
"Jump to Advanced Degree Distribution Fittings' Section",
target=prefix + "_adv_degree_distribution_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
id=prefix + "_adv_degree_distribution_side_tooltip",
),
]
items += [
dbc.NavItem(
dbc.NavLink(
"Virus-Host-Drug Interactome",
href="#" + prefix + "_virus_host_interactome",
external_link=True,
active=True,
className="nav-link",
id=prefix + "_side_virus_host_interactome",
),
className="nav-item",
id=prefix + "_virus_host_interactome_side",
),
dbc.Tooltip(
"Jump to Virus-Host-Drug Interactome's Section Advanced Degree Distribution Fittings' Section",
target=prefix + "_virus_host_interactome_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
id=prefix + "_virus_host_interactome_side_tooltip",
),
]
return (
dbc.NavbarSimple(
[dbc.Col(items, align="center", style={"padding": "0px"}),],
expand="xl",
color="light",
className="navbar navbar-light bg-light position-sticky nav",
style={"position": "sticky", "top": "10vh"},
),
)
elif prefix == "help":
items = [
dbc.NavItem(
dbc.NavLink(
"Main",
href="#" + prefix + "_main",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_help_main_side",
),
dbc.Tooltip(
"Jump to Main Section Description",
target=prefix + "_help_main_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
"Charts and Plots",
href="#" + prefix + "_charts_and_plots",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_help_charts_and_plots_side",
),
dbc.Tooltip(
"Jump to Charts and Plots Section Description",
target=prefix + "_help_charts_and_plots_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
dbc.NavItem(
dbc.NavLink(
"Advanced Degree Distribution",
href="#" + prefix + "_advanced_degree_distribution",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_help_advanced_degree_distribution_side",
),
dbc.Tooltip(
"Jump to Advanced Degree Distribution Section Description",
target=prefix + "_help_advanced_degree_distribution_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
html.Hr(),
dbc.NavItem(
dbc.NavLink(
"Glossary",
href="#" + prefix + "_glossary",
external_link=True,
active=True,
className="nav-link",
),
className="nav-item",
id=prefix + "_help_glossary_side",
),
dbc.Tooltip(
"Jump to Glossary Section",
target=prefix + "_help_glossary_side",
placement="right",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
]
return (
dbc.NavbarSimple(
[dbc.Col(items, align="center", style={"padding": "0px"}),],
expand="xl",
color="light",
className="navbar navbar-light bg-light position-sticky nav",
style={"position": "sticky", "top": "10vh"},
),
)
else:
return []
def nodes_info(prefix):
return dbc.Container(
[
html.Div(
[
html.H4(
"Node Info", id=prefix + "_name_card", className="card-header"
),
html.Div(
html.H5(id=prefix + "_title_card", className="card-title"),
className="card-body",
),
dbc.Container(
id=prefix + "_img_card",
fluid=True,
style={"padding": "0px", "position": "relative"},
),
html.Ul(
id=prefix + "_attributes-list-card",
className="list-group list-group-flush",
),
],
className="card border-primary mb-3",
id=prefix + "_card",
),
dbc.Toast(
html.P(
[
"The node's info are locked on the selected node.",
html.Br(),
"To show those relative to the hovered ones unselect it",
]
),
header="One node selected",
id=prefix + "_selected_node_warning",
dismissable=True,
is_open=False,
duration=10000,
icon="warning",
style={
"position": "fixed",
"top": "22vh",
"left": "65vw",
"min-width": "20vw",
"max-width": "20vw",
}, # just width doesn't work
),
]
)
def graph_help(prefix):
body = [
html.P("Pan to move around"),
html.P("Scroll to zoom"),
html.P("Click to select (and lock node's info)"),
html.P("CTRL or MAIUSC + Click for multiple selection"),
html.P("CTRL + Drag for square selection"),
]
if prefix == "target_projection":
body += [
html.Center(
[
html.Hr(),
daq.BooleanSwitch(
on=False,
label="Show All Edges",
id=prefix + "_show_all_edges_help",
style={"margin-bottom": "0.5em"},
),
]
)
]
body += [
html.Hr(),
html.A(
html.Center(html.H5("Glossary")),
id=prefix + "_graph_help_glossary",
href="/covidrugnet/help#help_glossary",
target="_blank",
style={"margin-bottom": "0.5em"},
),
]
return html.Div(
[
dbc.Button(
html.I(
className="fa fa-question-circle", style={"font-size": "0.9rem"}
),
id=prefix + "_help_open",
block=True,
className="btn btn-outline-primary",
), # "Help"
dbc.Popover(
[
dbc.PopoverHeader("Instructions for Interacting with the Graph"),
dbc.PopoverBody(body),
],
id=prefix + "_help_popover",
target=prefix + "_help_open",
placement="bottom",
),
dbc.Tooltip(
"Instructions for Interacting with the Graph",
target=prefix + "_help_open",
placement="top",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
]
)
def legend(prefix):
return html.Div(
[
dbc.Button(
"Legend",
id=prefix + "_legend_open",
block=True,
className="btn btn-outline-primary",
),
dbc.Toast(
header="Graph's Legend",
id=prefix + "_legend_toast",
dismissable=True,
style={
"position": "absolute",
"top": "-4vh",
"left": "-5vw",
"width": "200%",
"z-index": "1000",
},
is_open=False,
),
dbc.Tooltip(
["Graph's Legend", html.Br(), "(when available)"],
target=prefix + "_legend_open",
placement="top",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
]
)
def save_graph(prefix):
return html.Div(
[
dbc.Button(
html.I(className="fa fa-file-download", style={"font-size": "0.9rem"}),
id=prefix + "_save_graph_open",
block=True,
className="btn btn-outline-primary",
), # "Save"
dbc.Modal(
[
dbc.ModalHeader("Save Graph"),
dbc.ModalBody(
[
html.P("Format"),
dcc.Dropdown(
id=prefix + "_save_graph",
options=[
{
"label": "Download as Adjacency List",
"value": "adjlist",
},
{"label": "Download as Pickle", "value": "gpickle"},
{
"label": "Download as Cytoscape JSON",
"value": "cyjs",
},
{
"label": "Download as GRAPHML",
"value": "graphml",
},
{"label": "Download as GEXF", "value": "gexf"},
{
"label": "Download as Edges List",
"value": "edgelist",
},
{
"label": "Download as Multiline Adjacency List",
"value": "multiline_adjlist",
},
{"label": "Download as TSV", "value": "tsv"},
# {"label":"Download as SVG", "value":"svg"}, #temporary not working (why?)
{"label": "Download as PNG", "value": "png"},
{"label": "Download as JPEG", "value": "jpg"},
],
placeholder="Download as ...",
clearable=False,
searchable=False,
className="DropdownMenu",
),
]
),
dbc.ModalFooter(
[
html.A(
dbc.Button(
"Download",
id=prefix + "_download_graph_button",
className="btn btn-outline-primary",
),
id=prefix + "_download_graph_button_href",
target="_blank",
),
dbc.Button(
"Close",
id=prefix + "_save_graph_close",
className="btn btn-outline-primary",
),
]
),
],
id=prefix + "_save_graph_modal",
),
dbc.Tooltip(
"Download Graph File",
target=prefix + "_save_graph_open",
placement="top",
hide_arrow=True,
delay={"show": 500, "hide": 250},
),
]
)
def coloring_dropdown(prefix):
if prefix == "drug_target":
options = [{"label": "Categorical", "value": "categorical"}]
value = "categorical"
if prefix == "drug_projection":
options = [
{"label": "ATC Code", "value": "atc"},
{"label": "Target Class", "value": "targetclass"},
{"label": "Clinical Trial Phase", "value": "trialphase"},
]
value = "atc"
if prefix == "target_projection":
options = [
{"label": "Protein Class", "value": "class"},
{"label": "Protein Family", "value": "family"},
{"label": "Cellular Location", "value": "location"},
]
value = "class"
options += [
{"label": "Components", "value": "components"},
{"label": "Degree", "value": "Degree"},
{"label": "Degree (Major Component)", "value": "Degree_maj"},
{"label": "Closeness Centrality", "value": "Closeness Centrality"},
{
"label": "Closeness Centrality (Major Component)",
"value": "Closeness Centrality_maj",
},
{"label": "Betweenness Centrality", "value": "Betweenness Centrality"},
{
"label": "Betweenness Centrality (Major Component)",
"value": "Betweenness Centrality_maj",
},
{"label": "Eigenvector Centrality", "value": "Eigenvector Centrality"},
{
"label": "Eigenvector Centrality (Major Component)",
"value": "Eigenvector Centrality_maj",
},
]
if prefix != "drug_target":
options += [
{"label": "Clustering Coefficient", "value": "Clustering Coefficient"},
{
"label": "Clustering Coefficient (Major Component)",
"value": "Clustering Coefficient_maj",
},
]
options += [
{"label": "VoteRank Score", "value": "VoteRank Score"},
{"label": "VoteRank Score (Major Component)", "value": "VoteRank Score_maj"},
{"label": "Spectral Clustering", "value": "spectral_group"},
{
"label": "Spectral Clustering (Major Component)",
"value": "spectral_group_maj",
},
{"label": "Girvan-Newman Communities", "value": "girvan_newman_group"},
{
"label": "Girvan-Newman Communities (Major Component)",
"value": "girvan_newman_group_maj",
},
{"label": "Greedy Modularity Communities", "value": "greedy_modularity_group"},
{
"label": "Greedy Modularity Communities (Major Component)",
"value": "greedy_modularity_group_maj",
},
{
"label": "Custom (It might take a few seconds to update...)",
"value": "custom",
},
]
return html.Div(
[
dcc.Dropdown(
id=prefix + "_coloring_dropdown",
options=options,