Package Chem :: Package Fingerprints :: Module ClusterMols

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Module ClusterMols

utility functionality for clustering molecules using fingerprints
 includes a command line app for clustering


Sample Usage:
  python ClusterMols.py  -d data.gdb -t daylight_sig     --idName="CAS_TF" -o clust1.pkl     --actTable="dop_test" --actName="moa_quant"

Functions

GetDistanceMatrix(data, metric, isSimilarity=1)
data should be a list of tuples with fingerprints in position 1...

source code

ClusterPoints(data, metric, algorithmId, haveLabels=False, haveActs=True, returnDistances=False)

source code

ClusterFromDetails(details)
Returns the cluster tree...

source code

Variables

_cvsVersion = '$Id: ClusterMols.py 2 2006-05-06 22:54:39Z glan...

idx1 = 4

idx2 = 52

__VERSION_STRING = ' ClusterMols.py 2 2006-05-06 22:54:39Z gla...

_usageDoc = '\nUsage: ClusterMols.py [args] <fName>\n\n If <f...

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

GetDistanceMatrix(data, metric, isSimilarity=1)

data should be a list of tuples with fingerprints in position 1
(the rest of the elements of the tuple are not important)

 Returns the symmetric distance matrix
 (see ML.Cluster.Resemblance for layout documentation)

ClusterFromDetails(details)

Returns the cluster tree

Variables Details

_cvsVersion

Value:

'$Id: ClusterMols.py 2 2006-05-06 22:54:39Z glandrum $'

__VERSION_STRING

Value:

' ClusterMols.py 2 2006-05-06 22:54:39Z glandrum '

_usageDoc

Value:

'''
Usage: ClusterMols.py [args] <fName>

  If <fName> is provided and no tableName is specified (see below),
  data will be read from the text file <fName>.  Text files delimited
  with either commas (extension .csv) or tabs (extension .txt) are
  supported. 

...