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- """
- altgraph.GraphStat - Functions providing various graph statistics
- =================================================================
- """
- 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
- for value in values:
- try:
- if (value - min_val) >= 0:
- index = int((value - min_val) / float(bin_size))
- bins[index] += 1
- except IndexError:
- pass
- # 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
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