Package ML :: Package Cluster :: Module Murtagh

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Module Murtagh

Interface to the C++ Murtagh hierarchic clustering code

Functions

_LookupDist(dists, i, j, n)
*Internal Use Only*...

source code

_ToClusters(data, nPts, ia, ib, crit, isDistData=0)
*Internal Use Only*...

source code

ClusterData(data, nPts, method, isDistData=0)
clusters the data points passed in and returns the cluster tree **Arguments** - data: a list of lists (or array, or whatever) with the input data (see discussion of _isDistData_ argument for the exception) - nPts: the number of points to be used - method: determines which clustering algorithm should be used.

source code

Variables

WARDS = 1

SLINK = 2

CLINK = 3

UPGMA = 4

MCQUITTY = 5

GOWER = 6

CENTROID = 7

methods = [('Ward\'s Minimum Variance', 1, 'Ward\'s Minimum Va...

Complex0 = 'F'

Complex16 = 'F'

Complex32 = 'F'

Complex64 = 'D'

Complex8 = 'F'

Float0 = 'f'

Float16 = 'f'

Float32 = 'f'

Float64 = 'd'

Float8 = 'f'

Int0 = '1'

Int16 = 's'

Int32 = 'i'

Int8 = '1'

absolute = <ufunc 'absolute'>

add = <ufunc 'add'>

arccos = <ufunc 'arccos'>

arccosh = <ufunc 'arccosh'>

arcsin = <ufunc 'arcsin'>

arcsinh = <ufunc 'arcsinh'>

arctan = <ufunc 'arctan'>

arctan2 = <ufunc 'arctan2'>

arctanh = <ufunc 'arctanh'>

bitwise_and = <ufunc 'bitwise_and'>

bitwise_or = <ufunc 'bitwise_or'>

bitwise_xor = <ufunc 'bitwise_xor'>

ceil = <ufunc 'ceil'>

conjugate = <ufunc 'conjugate'>

cos = <ufunc 'cos'>

cosh = <ufunc 'cosh'>

divide = <ufunc 'divide'>

divide_safe = <ufunc 'divide_safe'>

e = 2.71828182846

equal = <ufunc 'equal'>

exp = <ufunc 'exp'>

fabs = <ufunc 'fabs'>

floor = <ufunc 'floor'>

floor_divide = <ufunc 'floor_divide'>

fmod = <ufunc 'fmod'>

greater = <ufunc 'greater'>

greater_equal = <ufunc 'greater_equal'>

hypot = <ufunc 'hypot'>

invert = <ufunc 'invert'>

left_shift = <ufunc 'left_shift'>

less = <ufunc 'less'>

less_equal = <ufunc 'less_equal'>

log = <ufunc 'log'>

log10 = <ufunc 'log10'>

logical_and = <ufunc 'logical_and'>

logical_not = <ufunc 'logical_not'>

logical_or = <ufunc 'logical_or'>

logical_xor = <ufunc 'logical_xor'>

maximum = <ufunc 'maximum'>

minimum = <ufunc 'minimum'>

multiply = <ufunc 'multiply'>

negative = <ufunc 'negative'>

not_equal = <ufunc 'not_equal'>

pi = 3.14159265359

power = <ufunc 'power'>

remainder = <ufunc 'remainder'>

right_shift = <ufunc 'right_shift'>

sin = <ufunc 'sin'>

sinh = <ufunc 'sinh'>

sqrt = <ufunc 'sqrt'>

subtract = <ufunc 'subtract'>

tan = <ufunc 'tan'>

tanh = <ufunc 'tanh'>

true_divide = <ufunc 'true_divide'>

Function Details

_LookupDist(dists, i, j, n)

*Internal Use Only*

returns the distance between points i and j in the symmetric
distance matrix _dists_

_ToClusters(data, nPts, ia, ib, crit, isDistData=0)

*Internal Use Only*

Converts the results of the Murtagh clustering code into
a cluster tree, which is returned in a single-entry list

ClusterData(data, nPts, method, isDistData=0)

clusters the data points passed in and returns the cluster tree

**Arguments**

  - data: a list of lists (or array, or whatever) with the input
    data (see discussion of _isDistData_ argument for the exception)

  - nPts: the number of points to be used

  - method: determines which clustering algorithm should be used.
      The defined constants for these are:
      'WARDS, SLINK, CLINK, UPGMA'

  - isDistData: set this toggle when the data passed in is a
      distance matrix.  The distance matrix should be stored
      symmetrically so that _LookupDist (above) can retrieve
      the results:
        for i<j: d_ij = dists[j*(j-1)/2 + i]


**Returns**

  - a single entry list with the cluster tree

Variables Details

methods

Value:

[('Ward\'s Minimum Variance', 1, 'Ward\'s Minimum Variance'),
 ('Average Linkage', 4, 'Group Average Linkage (UPGMA)'),
 ('Single Linkage', 2, 'Single Linkage (SLINK)'),
 ('Complete Linkage', 3, 'Complete Linkage (CLINK)'),
 ('Centroid', 7, 'Centroid method')]