1 files changed, 0 insertions, 90 deletions

diff --git a/Metrics/Metrics-Calculation/metrics_plot/src/plot_ks_stats.py b/Metrics/Metrics-Calculation/metrics_plot/src/plot_ks_stats.py
deleted file mode 100644
index ad72a4a1..00000000
--- a/Metrics/Metrics-Calculation/metrics_plot/src/plot_ks_stats.py
+++ /dev/null
@@ -1,90 +0,0 @@
-import glob
-import random 
-from sklearn.manifold import MDS
-import matplotlib.pyplot as plt
-from scipy import stats
-import numpy as np
-from GraphType import GraphCollection
-
-def calculateKSMatrix(dists):
-    dist = []
-
-    for i in range(len(dists)):
-        dist = dist + dists[i]
-    matrix = np.empty((len(dist),len(dist)))
-
-    for i in range(len(dist)):
-        matrix[i,i] = 0
-        for j in range(i+1, len(dist)):
-            value, p = stats.ks_2samp(dist[i], dist[j])
-            matrix[i, j] = value
-            matrix[j, i] = value
-    return matrix
-
-
-def calculateMDS(dissimilarities):
-    embedding = MDS(n_components=2, dissimilarity='precomputed')
-    trans = embedding.fit_transform(X=dissimilarities)
-    return trans
-
-def plot(graphTypes, coords, title='',index = 0, savePath = ''):
-    half_length = int(coords.shape[0] / len(graphTypes))
-    color = ['blue', 'red', 'green', 'yellow']
-    lineStyle = ['', '-']
-    plt.figure(index, figsize=(7, 4))
-    plt.title(title)
-    for i in range(len(graphTypes)):
-        x = (coords[(i*half_length):((i+1)*half_length), 0].tolist())
-        y = (coords[(i*half_length):((i+1)*half_length), 1].tolist())
-        plt.plot(x, y, color=color[i], marker='o', label = graphTypes[i].name, linestyle=lineStyle[i], alpha=0.7)
-    plt.legend(loc='upper right')
-    plt.savefig(fname = savePath, dpi=150)
-    #graph.show()
-
-def mkdir_p(mypath):
-    '''Creates a directory. equivalent to using mkdir -p on the command line'''
-
-    from errno import EEXIST
-    from os import makedirs,path
-
-    try:
-        makedirs(mypath)
-    except OSError as exc: # Python >2.5
-        if exc.errno == EEXIST and path.isdir(mypath):
-            pass
-        else: raise
-
-def metricStat(graphTypes, metricName, metric, graphIndex):
-    metrics = []
-    foldName = '../output/'
-    for graph in graphTypes:
-        metrics.append(metric(graph))
-        foldName = foldName + graph.name + '-'
-    print('calculate' + metricName +' for ' + foldName)
-    mkdir_p(foldName)
-    out_d_coords = calculateMDS(calculateKSMatrix(metrics))
-    plot(graphTypes, out_d_coords, metricName, graphIndex,foldName + '/'+ metricName+'.png')
-
-def nodeActivity(graphType):
-    return graphType.nas
-
-def outDegree(graphType):
-    return graphType.out_ds
-
-def mpc(graphType):
-    return graphType.mpcs
-
-
-# read models
-human = GraphCollection('../statistics/humanOutput/', 500, 'Human')
-# viatra30 = GraphCollection('../statistics/viatraOutput30/', 500, 'Viatra (30 nodes)')
-# viatra60 = GraphCollection('../statistics/viatraOutput60/', 500, 'Viatra (60 nodes)')
-# viatra100 = GraphCollection('../statistics/viatraOutput100/', 500, 'Viatra (100 nodes)')
-# random = GraphCollection('../statistics/randomOutput/', 500, 'Random')
-# alloy = GraphCollection('../statistics/alloyOutput/', 500, 'Alloy (30 nodes)')
-viatraEvolve = GraphCollection('../statistics/viatraEvolve/', 130, 'viatraEvolve', shouldShuffle = False)
-
-#calculate metrics
-metricStat([human, viatraEvolve], 'Node Activity', nodeActivity, 0)
-metricStat([human, viatraEvolve], 'Out Degree', outDegree, 1)
-metricStat([human, viatraEvolve], 'MPC', mpc, 2)
\ No newline at end of file