Fix imports

.github/workflows/cdci.yml

@@ -34,7 +34,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}

pyproject.toml

@@ -6,7 +6,7 @@ dynamic = ["version"]
 description = "A Python package for plotting related to multimodal molecular data. Works with acore."
 license = { text = "GNU General Public License v3" }
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.9,<3.13"
 classifiers = [
     "Development Status :: 2 - Pre-Alpha",
     "Intended Audience :: Developers",
@@ -27,12 +27,16 @@ dependencies = [
     "beautifulsoup4",
     "requests",
     "dash", # from dash import html
-    # "networkx",
+    "networkx",
     "matplotlib",
-    # "cy-jupyterlab",
-    # "nltk",
-    # "webweb"
-    # "acore",
+    "kaleido",
+    "pyvis",
+    "wordcloud",
+    "cyjupyter",
+    "nltk",
+    "webweb",
+    "acore",
+    "dash-cytoscape",
 ]
 
 [project.optional-dependencies]
@@ -64,5 +68,7 @@ Documentation = "https://analytics-core.readthedocs.io/"
 
 
 [build-system]
-requires = ["setuptools"]
+requires = ["setuptools", "setuptools_scm>=8"]
 build-backend = "setuptools.build_meta"
+
+[tool.setuptools_scm]

src/vuecore/Dendrogram.py

@@ -17,7 +17,8 @@ def plot_dendrogram(
     color_threshold=None,
 ):
     """
-    Modified version of Plotly _dendrogram.py that returns a dendrogram Plotly figure object with cutoff line.
+    Modified version of Plotly _dendrogram.py that
+    returns a dendrogram Plotly figure object with cutoff line.
 
     :param Z_dendrogram: Matrix of observations as array of arrays
     :type Z_dendrogram: ndarray

src/vuecore/linkers.py

@@ -0,0 +1,20 @@
+from io import StringIO
+
+import requests
+
+
+def get_clustergrammer_link(net, filename=None):
+    clustergrammer_url = "http://amp.pharm.mssm.edu/clustergrammer/matrix_upload/"
+    if filename is None:
+        file_string = net.write_matrix_to_tsv()
+        file_obj = StringIO(file_string)
+        if "filename" not in net.dat or net.dat["filename"] is None:
+            fake_filename = "Network.txt"
+        else:
+            fake_filename = net.dat["filename"]
+        r = requests.post(clustergrammer_url, files={"file": (fake_filename, file_obj)})
+    else:
+        file_obj = open(filename, "r")
+        r = requests.post(clustergrammer_url, files={"file": file_obj})
+    link = r.text
+    return link

src/vuecore/translate.py

@@ -0,0 +1,20 @@
+import base64
+import io
+
+from dash import html
+
+
+def hex2rgb(color):
+    _hex = color.lstrip("#")
+    rgb = tuple(int(_hex[i : i + 2], 16) for i in (0, 2, 4))
+    rgba = rgb + (0.6,)
+    return rgba
+
+
+def mpl_to_html_image(plot, width=800):
+    buf = io.BytesIO()
+    plot.savefig(buf, format="png")
+    data = base64.b64encode(buf.getbuffer()).decode("utf8")
+    figure = html.Img(src="data:image/png;base64,{}".format(data), width=f"{width}")
+
+    return figure

src/vuecore/utils.py

@@ -1,15 +1,13 @@
-import base64
-import io
 import random
 from collections import defaultdict
 from urllib import error
 
 import bs4 as bs
-import dash_html_components as html
 import networkx as nx
 import pandas as pd
 import requests
 from Bio import Entrez, Medline
+from dash import html
 from networkx.readwrite import json_graph
 
 # TODO: This should probably be changed to the email of the person installing ckg?
@@ -23,15 +21,6 @@ def check_columns(df, cols):
     return True
 
 
-def mpl_to_html_image(plot, width=800):
-    buf = io.BytesIO()
-    plot.savefig(buf, format="png")
-    data = base64.b64encode(buf.getbuffer()).decode("utf8")
-    figure = html.Img(src="data:image/png;base64,{}".format(data), width="800")
-
-    return figure
-
-
 def generate_html(network):
     """
     This method gets the data structures supporting the nodes, edges,
@@ -281,13 +270,6 @@ def __extract_style(el):
         return getattr(html, name.title())(contents, style=style)
 
 
-def hex2rgb(color):
-    hex = color.lstrip("#")
-    rgb = tuple(int(hex[i : i + 2], 16) for i in (0, 2, 4))
-    rgba = rgb + (0.6,)
-    return rgba
-
-
 def get_rgb_colors(n):
     colors = []
     r = int(random.random() * 256)

src/vuecore/viz.py

@@ -19,9 +19,7 @@
 import plotly.io as pio
 import plotly.subplots as tools
 import plotly.tools as tls
-from ckg.analytics_core import utils
-from ckg.analytics_core.analytics import analytics, wgcnaAnalysis
-from ckg.analytics_core.viz import Dendrogram, wgcnaFigures
+from acore import network_analysis, wgcna_analysis
 from cyjupyter import Cytoscape
 from dash import dash_table, dcc, html
 from networkx.readwrite import json_graph
@@ -33,6 +31,10 @@
 from webweb import Web
 from wordcloud import STOPWORDS, WordCloud
 
+from . import dendrogram, utils, wgcna
+from .linkers import get_clustergrammer_link
+from .translate import hex2rgb, mpl_to_html_image
+
 # matplotlib.use("Agg")
 
 
@@ -99,6 +101,7 @@ def get_markdown(text, args={}):
     """
     Converts a given text into a Dash Markdown component. It includes a syntax for things
     like bold text and italics, links, inline code snippets, lists, quotes, and more.
+
     For more information visit https://dash.plot.ly/dash-core-components/markdown.
 
     :param str text: markdown string (or array of strings) that adhreres to the CommonMark spec.
@@ -663,7 +666,7 @@ def get_scatterplot_matrix(data, identifier, args):
         for g in data[group].unique():
             gdata = data[data[group] == g].dropna()
             gfig = get_simple_scatterplot(gdata, identifier + "_" + str(g), args)
-            trace = gfig.figure["data"].pop()
+            trace = gfig["data"].pop()
             trace.name = g
             fig.append_trace(trace, r, c)
 
@@ -688,7 +691,7 @@ def get_scatterplot_matrix(data, identifier, args):
             dict(xref="paper", yref="paper", showarrow=False, text="")
         ]
 
-    return dcc.Graph(id=identifier, figure=fig)
+    return fig
 
 
 def get_simple_scatterplot(data, identifier, args):
@@ -779,7 +782,7 @@ def get_simple_scatterplot(data, identifier, args):
         template="plotly_white",
     )
 
-    return dcc.Graph(id=identifier, figure=figure)
+    return figure
 
 
 def get_scatterplot(data, identifier, args):
@@ -914,7 +917,7 @@ def get_scatterplot(data, identifier, args):
         template="plotly_white",
     )
 
-    return dcc.Graph(id=identifier, figure=figure)
+    return figure
 
 
 def get_density(x: np.ndarray, y: np.ndarray):
@@ -1716,7 +1719,7 @@ def get_network(data, identifier, args):
                     max_node_size = max(degrees.values())
                     nx.set_node_attributes(graph, degrees, "radius")
 
-                clusters = analytics.get_network_communities(graph, args)
+                clusters = network_analysis.get_network_communities(graph, args)
                 col = utils.get_hex_colors(len(set(clusters.values())))
                 colors = {n: col[clusters[n]] for n in clusters}
                 nx.set_node_attributes(graph, colors, "color")
@@ -1984,7 +1987,7 @@ def get_pca_plot(data, identifier, args):
     figure = {}
     traces = []
     annotations = []
-    sct = get_scatterplot(pca_data, identifier, args).figure
+    sct = get_scatterplot(pca_data, identifier, args)
     traces.extend(sct["data"])
     figure["layout"] = sct["layout"]
     factor = 50
@@ -2033,7 +2036,7 @@ def get_pca_plot(data, identifier, args):
     figure["layout"].annotations = annotations
     figure["layout"]["template"] = "plotly_white"
 
-    return dcc.Graph(id=identifier, figure=figure)
+    return figure
 
 
 def get_sankey_plot(
@@ -2128,7 +2131,7 @@ def get_sankey_plot(
                 label=nodes,
                 color=[
                     (
-                        "rgba" + str(utils.hex2rgb(node_colors[c]))
+                        "rgba" + str(hex2rgb(node_colors[c]))
                         if node_colors[c].startswith("#")
                         else node_colors[c]
                     )
@@ -2140,7 +2143,7 @@ def get_sankey_plot(
                 target=[list(nodes).index(i) for i in data[args["target"]].tolist()],
                 value=data[args["weight"]].tolist(),
                 color=[
-                    "rgba" + str(utils.hex2rgb(c)) if c.startswith("#") else c
+                    "rgba" + str(hex2rgb(c)) if c.startswith("#") else c
                     for c in data[args["source_colors"]].tolist()
                 ],
                 label=hover_data,
@@ -2413,7 +2416,7 @@ def get_clustergrammer_plot(data, identifier, args):
                 )
         clustergrammer_net.load_df(data)
 
-        link = utils.get_clustergrammer_link(clustergrammer_net, filename=None)
+        link = get_clustergrammer_link(clustergrammer_net, filename=None)
 
         iframe = html.Iframe(src=link, width=1000, height=900)
 
@@ -2510,7 +2513,7 @@ def get_WGCNAPlots(data, identifier):
         ) = data
         plots = []
         plots.append(
-            wgcnaFigures.plot_complex_dendrogram(
+            wgcna.plot_complex_dendrogram(
                 dissTOM,
                 moduleColors,
                 title="Co-expression: dendrogram and module colors",
@@ -2537,7 +2540,7 @@ def get_WGCNAPlots(data, identifier):
             )
         )
         plots.append(
-            wgcnaFigures.plot_labeled_heatmap(
+            wgcna.plot_labeled_heatmap(
                 moduleTraitCor,
                 textMatrix,
                 title="Module-Clinical variable relationships",
@@ -2547,11 +2550,11 @@ def get_WGCNAPlots(data, identifier):
                 height=800,
             )
         )
-        dendro_tree = wgcnaAnalysis.get_dendrogram(
+        dendro_tree = wgcna_analysis.get_dendrogram(
             METDiss, METDiss.index, distfun=None, linkagefun="ward", div_clusters=False
         )
         if dendro_tree is not None:
-            dendrogram = Dendrogram.plot_dendrogram(
+            dendrogram_ = dendrogram.plot_dendrogram(
                 dendro_tree, hang=0.9, cutoff_line=False
             )
 
@@ -2563,8 +2566,8 @@ def get_WGCNAPlots(data, identifier):
                 xaxis=dict(
                     domain=[0, 1],
                     range=[
-                        np.min(dendrogram["layout"]["xaxis"]["tickvals"]) - 6,
-                        np.max(dendrogram["layout"]["xaxis"]["tickvals"]) + 4,
+                        np.min(dendrogram_["layout"]["xaxis"]["tickvals"]) - 6,
+                        np.max(dendrogram_["layout"]["xaxis"]["tickvals"]) + 4,
                     ],
                     showgrid=False,
                     zeroline=True,
@@ -2611,24 +2614,24 @@ def get_WGCNAPlots(data, identifier):
                     )
                 )
             ):
-                df = wgcnaAnalysis.get_percentiles_heatmap(
+                df = wgcna_analysis.get_percentiles_heatmap(
                     METcor, dendro_tree, bydendro=True, bycols=False
                 ).T
             else:
-                df = wgcnaAnalysis.df_sort_by_dendrogram(
-                    wgcnaAnalysis.df_sort_by_dendrogram(METcor, dendro_tree).T,
+                df = wgcna_analysis.df_sort_by_dendrogram(
+                    wgcna_analysis.df_sort_by_dendrogram(METcor, dendro_tree).T,
                     dendro_tree,
                 )
 
-            heatmap = wgcnaFigures.get_heatmap(
+            heatmap = wgcna.get_heatmap(
                 df,
                 colorscale=[[0, "#67a9cf"], [0.5, "#f7f7f7"], [1, "#ef8a62"]],
                 color_missing=False,
             )
 
             figure = tools.make_subplots(rows=2, cols=1, print_grid=False)
 
-            for i in list(dendrogram["data"]):
+            for i in list(dendrogram_["data"]):
                 figure.append_trace(i, 1, 1)
             for j in list(heatmap["data"]):
                 figure.append_trace(j, 2, 1)
@@ -3271,7 +3274,7 @@ def get_km_plot(data, identifier, args):
             plot.set_xlabel(xlabel)
             plot.set_ylabel(ylabel)
             if environment == "app":
-                figure = utils.mpl_to_html_image(plot.figure, width=800)
+                figure = mpl_to_html_image(plot.figure, width=800)
                 result = html.Div(id=identifier, children=[figure])
             else:
                 result = plot.figure
@@ -3311,7 +3314,7 @@ def get_cumulative_hazard_plot(data, identifier, args):
             plot.set_xlabel(xlabel)
             plot.set_ylabel(ylabel)
             if environment == "app":
-                figure = utils.mpl_to_html_image(plot.figure, width=800)
+                figure = mpl_to_html_image(plot.figure, width=800)
                 result = html.Div(id=identifier, children=[figure])
             else:
                 result = plot.figure