Simplify imports

barahona-research-group · Oct 16, 2023 · a853bae · a853bae
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Showing 7 changed files with 38 additions and 39 deletions.
diff --git a/examples/Example_1_undirected_sbm.ipynb b/examples/Example_1_undirected_sbm.ipynb
@@ -15,7 +15,7 @@
    "source": [
     "import networkx as nx\n",
     "\n",
-    "from pygenstability import run, plotting\n",
+    "import pygenstability as pgs\n",
     "\n",
     "import create_graph"
    ]
@@ -59,7 +59,7 @@
    ],
    "source": [
     "# run Markov Stability\n",
-    "all_results = run(adjacency, min_scale=-1, max_scale = 0.75, n_scale = 30, constructor='continuous_normalized')"
+    "all_results = pgs.run(adjacency, min_scale=-1, max_scale = 0.75, n_scale = 30, constructor='continuous_normalized')"
    ]
   },
   {
@@ -80,7 +80,7 @@
    ],
    "source": [
     "# plot the results matplotlib\n",
-    "_ = plotting.plot_scan(all_results, use_plotly=False)"
+    "_ = pgs.plot_scan(all_results, use_plotly=False)"
    ]
   },
   {
@@ -101,7 +101,7 @@
    ],
    "source": [
     "# plot partition at scale index t\n",
-    "plotting.plot_single_partition(nx_graph, all_results, scale_id=5)"
+    "pgs.plot_single_partition(nx_graph, all_results, scale_id=5)"
    ]
   },
   {
@@ -122,7 +122,7 @@
    ],
    "source": [
     "# plot optimal partitions\n",
-    "plotting.plot_optimal_partitions(nx_graph, all_results, show=True)"
+    "pgs.plot_optimal_partitions(nx_graph, all_results, show=True)"
    ]
   },
   {

diff --git a/examples/Example_2_multiscale.ipynb b/examples/Example_2_multiscale.ipynb
@@ -16,8 +16,6 @@
    "outputs": [],
    "source": [
     "import pygenstability as pgs\n",
-    "from pygenstability import plotting\n",
-    "from pygenstability.pygenstability import evaluate_NVI\n",
     "import scipy.sparse as sp\n",
     "\n",
     "import matplotlib.pyplot as plt\n",
@@ -132,7 +130,7 @@
    "source": [
     "# plots results\n",
     "plt.figure(figsize=(7, 5))\n",
-    "axes = plotting.plot_scan(results, figure_name=None)\n",
+    "axes = pgs.plot_scan(results, figure_name=None)\n",
     "axes[3].set_ylim(0, 50)\n",
     "axes[3].axhline(3, ls=\"--\", color=\"k\", zorder=-1, lw=0.5)\n",
     "axes[3].axhline(9, ls=\"--\", color=\"k\", zorder=-1, lw=0.5)\n",
@@ -160,7 +158,7 @@
     "# compare MS partitions to ground truth with NVI\n",
     "def _get_NVI(ref_ids):\n",
     "    return [\n",
-    "        evaluate_NVI([0, i + 1], [ref_ids] + results[\"community_id\"])\n",
+    "        pgs.evaluate_NVI([0, i + 1], [ref_ids] + results[\"community_id\"])\n",
     "        for i in range(len(results[\"scales\"]))\n",
     "    ]\n",
     "\n",

diff --git a/examples/Example_3_directed.ipynb b/examples/Example_3_directed.ipynb
@@ -16,8 +16,7 @@
     "import networkx as nx\n",
     "import scipy.sparse as sp\n",
     "\n",
-    "from pygenstability import run, plotting, constructors\n",
-    "from pygenstability.optimal_scales import identify_optimal_scales"
+    "import pygenstability as pgs\n"
    ]
   },
   {
@@ -49,7 +48,7 @@
    ],
    "source": [
     "# scan markov scale for communities\n",
-    "all_results = run(sp.csgraph.csgraph_from_dense(adjacency), \n",
+    "all_results = pgs.run(sp.csgraph.csgraph_from_dense(adjacency), \n",
     "                  min_scale=-1.0, \n",
     "                  max_scale=1.0, \n",
     "                  n_scale=90, \n",
@@ -76,8 +75,8 @@
    ],
    "source": [
     "# select optimal scales\n",
-    "all_results = identify_optimal_scales(all_results,kernel_size=30,window_size=10)\n",
-    "_ = plotting.plot_scan(all_results)"
+    "all_results = pgs.identify_optimal_scales(all_results,kernel_size=30,window_size=10)\n",
+    "_ = pgs.plot_scan(all_results)"
    ]
   },
   {
@@ -110,7 +109,7 @@
    ],
    "source": [
     "# plot optimal partitions\n",
-    "plotting.plot_optimal_partitions(nx_graph, all_results, show=True)"
+    "pgs.plot_optimal_partitions(nx_graph, all_results, show=True)"
    ]
   },
   {
@@ -131,7 +130,7 @@
    ],
    "source": [
     "# scan markov scale for communities using linearized directed\n",
-    "all_results = run(sp.csgraph.csgraph_from_dense(adjacency), \n",
+    "all_results = pgs.run(sp.csgraph.csgraph_from_dense(adjacency), \n",
     "                  min_scale=-1.0, \n",
     "                  max_scale=1.0, \n",
     "                  n_scale=90, \n",
@@ -158,8 +157,8 @@
    ],
    "source": [
     "# select optimal scales\n",
-    "all_results = identify_optimal_scales(all_results,kernel_size=30,window_size=10)\n",
-    "_ = plotting.plot_scan(all_results)"
+    "all_results = pgs.identify_optimal_scales(all_results,kernel_size=30,window_size=10)\n",
+    "_ = pgs.plot_scan(all_results)"
    ]
   },
   {
@@ -190,7 +189,7 @@
    ],
    "source": [
     "# plot optimal partitions\n",
-    "plotting.plot_optimal_partitions(nx_graph, all_results, show=True)"
+    "pgs.plot_optimal_partitions(nx_graph, all_results, show=True)"
    ]
   }
  ],

diff --git a/examples/Example_4_constructors.ipynb b/examples/Example_4_constructors.ipynb
@@ -17,7 +17,7 @@
    "source": [
     "import networkx as nx\n",
     "\n",
-    "from pygenstability import run, plotting\n",
+    "import pygenstability as pgs\n",
     "import create_graph"
    ]
   },
@@ -76,8 +76,8 @@
     }
    ],
    "source": [
-    "all_results = run(adjacency, min_scale=-1, max_scale=1, n_scale=30, constructor='linearized')\n",
-    "_ = plotting.plot_scan(all_results)"
+    "all_results = pgs.run(adjacency, min_scale=-1, max_scale=1, n_scale=30, constructor='linearized')\n",
+    "_ = pgs.plot_scan(all_results)"
    ]
   },
   {
@@ -113,8 +113,8 @@
     }
    ],
    "source": [
-    "all_results = run(adjacency, min_scale=-0.5, max_scale =.2, n_scale=30, constructor='continuous_combinatorial')\n",
-    "_ = plotting.plot_scan(all_results)"
+    "all_results = pgs.run(adjacency, min_scale=-0.5, max_scale =.2, n_scale=30, constructor='continuous_combinatorial')\n",
+    "_ = pgs.plot_scan(all_results)"
    ]
   },
   {
@@ -150,8 +150,8 @@
     }
    ],
    "source": [
-    "all_results = run(adjacency, min_scale=-1, max_scale=1, n_scale=30, constructor='continuous_normalized')\n",
-    "_ = plotting.plot_scan(all_results)"
+    "all_results = pgs.run(adjacency, min_scale=-1, max_scale=1, n_scale=30, constructor='continuous_normalized')\n",
+    "_ = pgs.plot_scan(all_results)"
    ]
   }
  ],

diff --git a/examples/Example_5_hypergraph.ipynb b/examples/Example_5_hypergraph.ipynb
@@ -37,7 +37,6 @@
     "import matplotlib.pyplot as plt\n",
     "\n",
     "import pygenstability as pgs\n",
-    "from pygenstability import plotting\n",
     "\n",
     "import hypernetx as hnx"
    ]
@@ -169,7 +168,7 @@
     }
    ],
    "source": [
-    "_ = plotting.plot_scan(results_hypergraph_projection)"
+    "_ = pgs.plot_scan(results_hypergraph_projection)"
    ]
   },
   {
@@ -214,7 +213,7 @@
     "# plot the partition at the optimal scale\n",
     "for scale in results_hypergraph_projection['selected_partitions']:\n",
     "    plt.figure()\n",
-    "    plotting.plot_single_partition(nx_graph, results_hypergraph_projection, scale_id=scale)"
+    "    pgs.plot_single_partition(nx_graph, results_hypergraph_projection, scale_id=scale)"
    ]
   },
   {
@@ -313,7 +312,7 @@
    ],
    "source": [
     "# note the 3-way partition that now appears\n",
-    "_ = plotting.plot_scan(results_hypergraph_ew)"
+    "_ = pgs.plot_scan(results_hypergraph_ew)"
    ]
   },
   {
@@ -368,7 +367,7 @@
     "# plot the partition at the optimal scale\n",
     "for scale in results_hypergraph_ew['selected_partitions']:\n",
     "    plt.figure()\n",
-    "    plotting.plot_single_partition(nx_graph, results_hypergraph_ew, scale_id=scale)"
+    "    pgs.plot_single_partition(nx_graph, results_hypergraph_ew, scale_id=scale)"
    ]
   }
  ],

diff --git a/examples/Example_6_signed.ipynb b/examples/Example_6_signed.ipynb
@@ -27,8 +27,7 @@
     "import numpy as np\n",
     "import scipy.sparse as sp\n",
     "\n",
-    "from pygenstability import run, plotting, constructors\n",
-    "from pygenstability.optimal_scales import identify_optimal_scales"
+    "import pygenstability as pgs\n"
    ]
   },
   {
@@ -98,7 +97,7 @@
    ],
    "source": [
     "# apply MS analysis using signed modularity\n",
-    "all_results = run(sp.csgraph.csgraph_from_dense(adjacency), \n",
+    "all_results = pgs.run(sp.csgraph.csgraph_from_dense(adjacency), \n",
     "                  min_scale=-1, \n",
     "                  max_scale=1.0, \n",
     "                  n_scale=90, \n",
@@ -123,7 +122,7 @@
    ],
    "source": [
     "# select optimal scales\n",
-    "_ = plotting.plot_scan(all_results)"
+    "_ = pgs.plot_scan(all_results)"
    ]
   },
   {
@@ -166,7 +165,7 @@
    ],
    "source": [
     "# plot optimal partitions\n",
-    "plotting.plot_optimal_partitions(nx_graph, all_results, show=True)"
+    "pgs.plot_optimal_partitions(nx_graph, all_results, show=True)"
    ]
   },
   {
@@ -210,7 +209,7 @@
    ],
    "source": [
     "# apply MS analysis using signed combinatorial Laplacian\n",
-    "all_results = run(sp.csgraph.csgraph_from_dense(adjacency), \n",
+    "all_results = pgs.run(sp.csgraph.csgraph_from_dense(adjacency), \n",
     "                  min_scale=-2.0, \n",
     "                  max_scale=1.0, \n",
     "                  n_scale=90, \n",
@@ -235,7 +234,7 @@
    ],
    "source": [
     "# select optimal scales\n",
-    "_ = plotting.plot_scan(all_results)"
+    "_ = pgs.plot_scan(all_results)"
    ]
   },
   {
@@ -276,7 +275,7 @@
    ],
    "source": [
     "# plot optimal partitions\n",
-    "plotting.plot_optimal_partitions(nx_graph, all_results, show=True)"
+    "pgs.plot_optimal_partitions(nx_graph, all_results, show=True)"
    ]
   },
   {

diff --git a/src/pygenstability/__init__.py b/src/pygenstability/__init__.py
@@ -2,3 +2,7 @@
 from pygenstability.io import load_results
 from pygenstability.io import save_results
 from pygenstability.pygenstability import run
+from pygenstability.pygenstability import evaluate_NVI
+from pygenstability.plotting import *
+from pygenstability.optimal_scales import identify_optimal_scales
+