Delete tools/telemetry.

tools/telemetry/third_party/altgraph/altgraph/GraphStat.py

Index: tools/telemetry/third_party/altgraph/altgraph/GraphStat.py
diff --git a/tools/telemetry/third_party/altgraph/altgraph/GraphStat.py b/tools/telemetry/third_party/altgraph/altgraph/GraphStat.py
deleted file mode 100644
index 25fc46c2de66e8e2f3def765e17766cc1188f6fb..0000000000000000000000000000000000000000
--- a/tools/telemetry/third_party/altgraph/altgraph/GraphStat.py
+++ /dev/null
@@ -1,73 +0,0 @@
-'''
-altgraph.GraphStat - Functions providing various graph statistics
-=================================================================
-'''
-import sys
-
-def degree_dist(graph, limits=(0,0), bin_num=10, mode='out'):
-    '''
-    Computes the degree distribution for a graph.
-
-    Returns a list of tuples where the first element of the tuple is the center of the bin
-    representing a range of degrees and the second element of the tuple are the number of nodes
-    with the degree falling in the range.
-
-    Example::
-
-        ....
-    '''
-
-    deg = []
-    if mode == 'inc':
-        get_deg = graph.inc_degree
-    else:
-        get_deg = graph.out_degree
-
-    for node in graph:
-        deg.append( get_deg(node) )
-
-    if not deg:
-        return []
-
-    results = _binning(values=deg, limits=limits, bin_num=bin_num)
-
-    return results
-
-_EPS = 1.0/(2.0**32)
-def _binning(values, limits=(0,0), bin_num=10):
-    '''
-    Bins data that falls between certain limits, if the limits are (0, 0) the
-    minimum and maximum values are used.
-
-    Returns a list of tuples where the first element of the tuple is the center of the bin
-    and the second element of the tuple are the counts.
-    '''
-    if limits == (0, 0):
-        min_val, max_val = min(values) - _EPS, max(values) + _EPS
-    else:
-        min_val, max_val = limits
-
-    # get bin size
-    bin_size = (max_val - min_val)/float(bin_num)
-    bins = [0] * (bin_num)
-
-    # will ignore these outliers for now
-    out_points = 0
-    for value in values:
-        try:
-            if (value - min_val) < 0:
-                out_points += 1
-            else:
-                index = int((value - min_val)/float(bin_size))
-                bins[index] += 1
-        except IndexError:
-            out_points += 1
-
-    # make it ready for an x,y plot
-    result = []
-    center = (bin_size/2) + min_val
-    for i, y in enumerate(bins):
-        x = center + bin_size * i
-        result.append( (x,y) )
-
-    return result