Package compilator :: Module compilator
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Module compilator

source code


Version: 0.6.0

Classes [hide private]
  Compilator
Functions [hide private]
 
rand(...)
Return an array of the given dimensions which is initialized to random numbers from a uniform distribution in the range [0,1).
source code
 
randn(...)
Returns zero-mean, unit-variance Gaussian random numbers in an array of shape (d0, d1, ..., dn).
source code
Variables [hide private]
  ALLOW_THREADS = 1
  BUFSIZE = 10000
  C = <sympy.core.basic.ClassesRegistry instance at 0x9fab6cc>
  CLIP = 0
  Catalan = Catalan
  E = E
  ERR_CALL = 3
  ERR_DEFAULT = 0
  ERR_DEFAULT2 = 2084
  ERR_IGNORE = 0
  ERR_LOG = 5
  ERR_PRINT = 4
  ERR_RAISE = 2
  ERR_WARN = 1
  EulerGamma = EulerGamma
  FLOATING_POINT_SUPPORT = 1
  FPE_DIVIDEBYZERO = 1
  FPE_INVALID = 8
  FPE_OVERFLOW = 2
  FPE_UNDERFLOW = 4
  False_ = False
  GoldenRatio = GoldenRatio
  I = I
  Inf = inf
  Infinity = inf
  MAXDIMS = 32
  NAN = nan
  NINF = -inf
  NZERO = -0.0
  NaN = nan
  PINF = inf
  PZERO = 0.0
  RAISE = 2
  S = S
  SHIFT_DIVIDEBYZERO = 0
  SHIFT_INVALID = 9
  SHIFT_OVERFLOW = 3
  SHIFT_UNDERFLOW = 6
  ScalarType = (<type 'int'>, <type 'float'>, <type 'complex'>, ...
  True_ = True
  UFUNC_BUFSIZE_DEFAULT = 10000
  UFUNC_PYVALS_NAME = 'UFUNC_PYVALS'
  WRAP = 1
  absolute = <ufunc 'absolute'>
  arccosh = <ufunc 'arccosh'>
  arcsinh = <ufunc 'arcsinh'>
  arctan = <ufunc 'arctan'>
  arctan2 = <ufunc 'arctan2'>
  bitwise_and = <ufunc 'bitwise_and'>
  bitwise_not = <ufunc 'invert'>
  bitwise_or = <ufunc 'bitwise_or'>
  bitwise_xor = <ufunc 'bitwise_xor'>
  c_ = <numpy.lib.index_tricks.CClass object at 0xa3b50ec>
  cast = {<type 'numpy.int64'>: <function <lambda> at 0xa28b3ac>...
  ceil = <ufunc 'ceil'>
  conj = <ufunc 'conjugate'>
  degrees = <ufunc 'degrees'>
  divide = <ufunc 'divide'>
  e = 2.71828182846
  equal = <ufunc 'equal'>
  expm1 = <ufunc 'expm1'>
  fabs = <ufunc 'fabs'>
  floor_divide = <ufunc 'floor_divide'>
  fmod = <ufunc 'fmod'>
  frexp = <ufunc 'frexp'>
  greater = <ufunc 'greater'>
  greater_equal = <ufunc 'greater_equal'>
  hypot = <ufunc 'hypot'>
  index_exp = <numpy.lib.index_tricks.IndexExpression object at ...
  inf = inf
  infty = inf
  invert = <ufunc 'invert'>
  isfinite = <ufunc 'isfinite'>
  isinf = <ufunc 'isinf'>
  isnan = <ufunc 'isnan'>
  ldexp = <ufunc 'ldexp'>
  left_shift = <ufunc 'left_shift'>
  less = <ufunc 'less'>
  less_equal = <ufunc 'less_equal'>
  little_endian = True
  log1p = <ufunc 'log1p'>
  logical_and = <ufunc 'logical_and'>
  logical_not = <ufunc 'logical_not'>
  logical_or = <ufunc 'logical_or'>
  logical_xor = <ufunc 'logical_xor'>
  maximum = <ufunc 'maximum'>
  mgrid = <numpy.lib.index_tricks.nd_grid object at 0xa3affcc>
  minimum = <ufunc 'minimum'>
  mod = <ufunc 'remainder'>
  modf = <ufunc 'modf'>
  multiply = <ufunc 'multiply'>
  nan = nan
  nbytes = {<type 'numpy.int64'>: 8, <type 'numpy.int16'>: 2, <t...
  negative = <ufunc 'negative'>
  newaxis = None
  not_equal = <ufunc 'not_equal'>
  ogrid = <numpy.lib.index_tricks.nd_grid object at 0xa3affec>
  ones_like = <ufunc 'ones_like'>
  oo = oo
  pi = pi
  pkgload = <numpy._import_tools.PackageLoader instance at 0xa51...
  r_ = <numpy.lib.index_tricks.RClass object at 0xa3b508c>
  radians = <ufunc 'radians'>
  reciprocal = <ufunc 'reciprocal'>
  remainder = <ufunc 'remainder'>
  right_shift = <ufunc 'right_shift'>
  rint = <ufunc 'rint'>
  s_ = <numpy.lib.index_tricks.IndexExpression object at 0xa3b52ac>
  sctypeDict = {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>,...
  sctypeNA = {'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bo...
  sctypes = {'complex': [<type 'numpy.complex64'>, <type 'numpy....
  sieve = <Sieve with 6 primes sieved: 2, 3, 5, ... 11, 13>
  signbit = <ufunc 'signbit'>
  square = <ufunc 'square'>
  subtract = <ufunc 'subtract'>
  true_divide = <ufunc 'true_divide'>
  typeDict = {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>, 2...
  typeNA = {'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bool...
  typecodes = {'All': '?bhilqpBHILQPfdgFDGSUVO', 'AllFloat': 'fd...
  zoo = zoo
Function Details [hide private]

rand(...)

source code 
Return an array of the given dimensions which is initialized to
random numbers from a uniform distribution in the range [0,1).

rand(d0, d1, ..., dn) -> random values

Note:  This is a convenience function. If you want an
            interface that takes a tuple as the first argument
            use numpy.random.random_sample(shape_tuple).

randn(...)

source code 
Returns zero-mean, unit-variance Gaussian random numbers in an
array of shape (d0, d1, ..., dn).

randn(d0, d1, ..., dn) -> random values

Note:  This is a convenience function. If you want an
            interface that takes a tuple as the first argument
            use numpy.random.standard_normal(shape_tuple).


Variables Details [hide private]

ScalarType

Value:
(<type 'int'>,
 <type 'float'>,
 <type 'complex'>,
 <type 'long'>,
 <type 'bool'>,
 <type 'str'>,
 <type 'unicode'>,
 <type 'buffer'>,
...

cast

Value:
{<type 'numpy.int64'>: <function <lambda> at 0xa28b3ac>, <type 'numpy.\
int16'>: <function <lambda> at 0xa28b3e4>, <type 'numpy.float64'>: <fu\
nction <lambda> at 0xa28b614>, <type 'numpy.uint16'>: <function <lambd\
a> at 0xa28b454>, <type 'numpy.int8'>: <function <lambda> at 0xa28b48c\
>, <type 'numpy.string_'>: <function <lambda> at 0xa28b4c4>, <type 'nu\
mpy.float96'>: <function <lambda> at 0xa28b4fc>, <type 'numpy.uint32'>\
: <function <lambda> at 0xa28b534>, <type 'numpy.int32'>: <function <l\
ambda> at 0xa28b41c>, <type 'numpy.complex64'>: <function <lambda> at \
...

index_exp

Value:
<numpy.lib.index_tricks.IndexExpression object at 0xa3b526c>

nbytes

Value:
{<type 'numpy.int64'>: 8, <type 'numpy.int16'>: 2, <type 'numpy.int32'\
>: 4, <type 'numpy.uint16'>: 2, <type 'numpy.int8'>: 1, <type 'numpy.s\
tring_'>: 0, <type 'numpy.float96'>: 12, <type 'numpy.uint32'>: 4, <ty\
pe 'numpy.unicode_'>: 0, <type 'numpy.complex64'>: 8, <type 'numpy.uin\
t32'>: 4, <type 'numpy.float64'>: 8, <type 'numpy.void'>: 0, <type 'nu\
mpy.int32'>: 4, <type 'numpy.complex128'>: 16, <type 'numpy.uint64'>: \
8, <type 'numpy.complex192'>: 24, <type 'numpy.object_'>: 4, <type 'nu\
mpy.float32'>: 4, <type 'numpy.bool_'>: 1, <type 'numpy.uint8'>: 1}

pkgload

Value:
<numpy._import_tools.PackageLoader instance at 0xa519b6c>

sctypeDict

Value:
{0: <type 'numpy.bool_'>,
 1: <type 'numpy.int8'>,
 2: <type 'numpy.uint8'>,
 3: <type 'numpy.int16'>,
 4: <type 'numpy.uint16'>,
 5: <type 'numpy.int32'>,
 6: <type 'numpy.uint32'>,
 7: <type 'numpy.int32'>,
...

sctypeNA

Value:
{'?': 'Bool',
 'B': 'UInt8',
 'Bool': <type 'numpy.bool_'>,
 'Complex32': <type 'numpy.complex64'>,
 'Complex64': <type 'numpy.complex128'>,
 'Complex96': <type 'numpy.complex192'>,
 'D': 'Complex64',
 'F': 'Complex32',
...

sctypes

Value:
{'complex': [<type 'numpy.complex64'>,
             <type 'numpy.complex128'>,
             <type 'numpy.complex192'>],
 'float': [<type 'numpy.float32'>,
           <type 'numpy.float64'>,
           <type 'numpy.float96'>],
 'int': [<type 'numpy.int8'>,
         <type 'numpy.int16'>,
...

typeDict

Value:
{0: <type 'numpy.bool_'>,
 1: <type 'numpy.int8'>,
 2: <type 'numpy.uint8'>,
 3: <type 'numpy.int16'>,
 4: <type 'numpy.uint16'>,
 5: <type 'numpy.int32'>,
 6: <type 'numpy.uint32'>,
 7: <type 'numpy.int32'>,
...

typeNA

Value:
{'?': 'Bool',
 'B': 'UInt8',
 'Bool': <type 'numpy.bool_'>,
 'Complex32': <type 'numpy.complex64'>,
 'Complex64': <type 'numpy.complex128'>,
 'Complex96': <type 'numpy.complex192'>,
 'D': 'Complex64',
 'F': 'Complex32',
...

typecodes

Value:
{'All': '?bhilqpBHILQPfdgFDGSUVO',
 'AllFloat': 'fdgFDG',
 'AllInteger': 'bBhHiIlLqQpP',
 'Character': 'c',
 'Complex': 'FDG',
 'Float': 'fdg',
 'Integer': 'bhilqp',
 'UnsignedInteger': 'BHILQP'}