Package PyFoam :: Package ThirdParty :: Package Gnuplot :: Module demo
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Module demo

source code

demo.py -- Demonstrate the Gnuplot python module.

Run this demo by typing 'python demo.py'. For a more complete test of the Gnuplot package, see test.py.


Version: 1.0.4

Functions [hide private]
 
demo()
Demonstrate the Gnuplot package.
source code
Variables [hide private]
  newaxis = None
  ALLOW_THREADS = 1
  BUFSIZE = 10000
  CLIP = 0
  ERR_CALL = 3
  ERR_DEFAULT = 0
  ERR_DEFAULT2 = 2084
  ERR_IGNORE = 0
  ERR_LOG = 5
  ERR_PRINT = 4
  ERR_RAISE = 2
  ERR_WARN = 1
  FLOATING_POINT_SUPPORT = 1
  FPE_DIVIDEBYZERO = 1
  FPE_INVALID = 8
  FPE_OVERFLOW = 2
  FPE_UNDERFLOW = 4
  False_ = False
  Inf = inf
  Infinity = inf
  MAXDIMS = 32
  NAN = nan
  NINF = -inf
  NZERO = -0.0
  NaN = nan
  PINF = inf
  PZERO = 0.0
  RAISE = 2
  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'>
  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_not = <ufunc 'invert'>
  bitwise_or = <ufunc 'bitwise_or'>
  bitwise_xor = <ufunc 'bitwise_xor'>
  c_ = <numpy.lib.index_tricks.c_class object at 0x2b0c49aabb90>
  cast = {<type 'numpy.int64'>: <function <lambda> at 0x2b0c4916...
  ceil = <ufunc 'ceil'>
  conj = <ufunc 'conjugate'>
  conjugate = <ufunc 'conjugate'>
  cos = <ufunc 'cos'>
  cosh = <ufunc 'cosh'>
  divide = <ufunc 'divide'>
  e = 2.71828182846
  equal = <ufunc 'equal'>
  exp = <ufunc 'exp'>
  expm1 = <ufunc 'expm1'>
  fabs = <ufunc 'fabs'>
  floor = <ufunc 'floor'>
  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._index_expression_class ob...
  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
  log = <ufunc 'log'>
  log10 = <ufunc 'log10'>
  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 0x2b0c49aaba50>
  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'>
  not_equal = <ufunc 'not_equal'>
  ogrid = <numpy.lib.index_tricks.nd_grid object at 0x2b0c49aaba90>
  ones_like = <ufunc 'ones_like'>
  pi = 3.14159265359
  power = <ufunc 'power'>
  r_ = <numpy.lib.index_tricks.r_class object at 0x2b0c49aabb10>
  reciprocal = <ufunc 'reciprocal'>
  remainder = <ufunc 'remainder'>
  right_shift = <ufunc 'right_shift'>
  rint = <ufunc 'rint'>
  s_ = <numpy.lib.index_tricks._index_expression_class object at...
  sctypeDict = {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>,...
  sctypeNA = {'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bo...
  sctypes = {'complex': [<type 'numpy.complex64'>, <type 'numpy....
  signbit = <ufunc 'signbit'>
  sin = <ufunc 'sin'>
  sinh = <ufunc 'sinh'>
  sqrt = <ufunc 'sqrt'>
  square = <ufunc 'square'>
  subtract = <ufunc 'subtract'>
  tan = <ufunc 'tan'>
  tanh = <ufunc 'tanh'>
  true_divide = <ufunc 'true_divide'>
  typeDict = {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>, 2...
  typeNA = {'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bool...

Imports: ScipyTest, PackageLoader, NumpyTest, show_config, pkgload, putmask, Unpickler, Character, arraytype, shape, LittleEndian, cumsum, choose, NewAxis, ravel, string, PyObject, ones, arrayrange, UnsignedInt32, UfuncType, dumps, convolve, indices, loads, Pickler, where, PrecisionError, dump, argmax, product, sign, Complex, arange, allclose, nonzero, asarray, sum, math, concatenate, pickle_array, vdot, transpose, array2string, diagonal, put, UInt64, StringIO, argsort, load, rank, array, UnsignedInt64, size, sometrue, cross_correlate, alltrue, zeros, identity, UnsignedInt8, empty, sort, LoadArray, cumproduct, matrixmultiply, multiarray, UInt, typecodes, copy, resize, fromfunction, argmin, Int, UInt128, UInt32, pickle, copy_reg, clip, DumpArray, ArrayType, array_constructor, innerproduct, around, reshape, UInt16, take, array_str, sarray, outerproduct, repeat, trace, UnsignedInteger, compress, UInt8, UnsignedInt128, types, UnsignedInt16, fromstring, average, Float, searchsorted, array_repr, swapaxes, dot, Gnuplot, MachAr, RankWarning, add_docstring, add_newdoc, add_newdocs, alen, all, alterdot, amax, amin, angle, any, append, apply_along_axis, apply_over_axes, argwhere, array_equal, array_equiv, array_split, asanyarray, asarray_chkfinite, ascontiguousarray, asfarray, asfortranarray, asmatrix, asscalar, atleast_1d, atleast_2d, atleast_3d, bartlett, base_repr, binary_repr, bincount, blackman, bmat, bool8, bool_, broadcast, byte, byte_bounds, can_cast, cdouble, cfloat, char, character, chararray, clongdouble, clongfloat, column_stack, common_type, compare_chararrays, complex128, complex256, complex64, complex_, complexfloating, corrcoef, correlate, cov, cross, csingle, ctypeslib, cumprod, delete, deprecate, diag, diagflat, diff, digitize, disp, double, dsplit, dstack, dtype, ediff1d, emath, empty_like, errstate, expand_dims, extract, eye, fastCopyAndTranspose, fft, finfo, fix, flatiter, flatnonzero, flexible, fliplr, flipud, float128, float32, float64, float_, floating, format_parser, frombuffer, fromfile, fromiter, frompyfunc, generic, get_array_wrap, get_include, get_numarray_include, get_numpy_include, get_printoptions, getbuffer, getbufsize, geterr, geterrcall, geterrobj, gradient, hamming, hanning, histogram, histogram2d, histogramdd, hsplit, hstack, i0, iinfo, imag, inexact, info, inner, insert, int0, int16, int32, int64, int8, int_, int_asbuffer, intc, integer, interp, intersect1d, intersect1d_nu, intp, iscomplex, iscomplexobj, isfortran, isneginf, isposinf, isreal, isrealobj, isscalar, issctype, issubclass_, issubdtype, issubsctype, iterable, ix_, kaiser, kron, lexsort, linalg, linspace, loadtxt, log2, logspace, longcomplex, longdouble, longfloat, longlong, ma, mat, matrix, maximum_sctype, may_share_memory, mean, median, memmap, meshgrid, mintypecode, msort, nan_to_num, nanargmax, nanargmin, nanmax, nanmin, nansum, ndarray, ndenumerate, ndim, ndindex, newbuffer, number, obj2sctype, object0, object_, outer, piecewise, place, poly, poly1d, polyadd, polyder, polydiv, polyfit, polyint, polymul, polysub, polyval, prod, ptp, random, real, real_if_close, rec, recarray, record, require, restoredot, roll, rollaxis, roots, rot90, round_, row_stack, savetxt, sctype2char, select, set_numeric_ops, set_printoptions, set_string_function, setbufsize, setdiff1d, seterr, seterrcall, seterrobj, setmember1d, setxor1d, short, signedinteger, sinc, single, singlecomplex, sort_complex, source, split, squeeze, std, str_, string0, string_, tensordot, test, tile, trapz, tri, tril, trim_zeros, triu, typename, ubyte, ufunc, uint, uint0, uint16, uint32, uint64, uint8, uintc, uintp, ulonglong, unicode0, unicode_, union1d, unique, unique1d, unravel_index, unsignedinteger, unwrap, ushort, vander, var, vectorize, void, void0, vsplit, vstack, who, zeros_like


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 0x2b0c49163488>, <type 'n\
umpy.int16'>: <function <lambda> at 0x2b0c49163500>, <type 'numpy.floa\
t64'>: <function <lambda> at 0x2b0c49163578>, <type 'numpy.complex128'\
>: <function <lambda> at 0x2b0c491635f0>, <type 'numpy.void'>: <functi\
on <lambda> at 0x2b0c49163668>, <type 'numpy.complex256'>: <function <\
lambda> at 0x2b0c49163c80>, <type 'numpy.uint64'>: <function <lambda> \
at 0x2b0c49163758>, <type 'numpy.unicode_'>: <function <lambda> at 0x2\
b0c49163b18>, <type 'numpy.float128'>: <function <lambda> at 0x2b0c491\
...

index_exp

Value:
<numpy.lib.index_tricks._index_expression_class object at 0x2b0c49aabc\
d0>

nbytes

Value:
{<type 'numpy.int64'>: 8, <type 'numpy.int16'>: 2, <type 'numpy.float6\
4'>: 8, <type 'numpy.complex128'>: 16, <type 'numpy.void'>: 0, <type '\
numpy.float32'>: 4, <type 'numpy.uint64'>: 8, <type 'numpy.int32'>: 4,\
 <type 'numpy.complex64'>: 8, <type 'numpy.int8'>: 1, <type 'numpy.flo\
at128'>: 16, <type 'numpy.string_'>: 0, <type 'numpy.uint32'>: 4, <typ\
e 'numpy.object_'>: 8, <type 'numpy.unicode_'>: 0, <type 'numpy.uint16\
'>: 2, <type 'numpy.bool_'>: 1, <type 'numpy.complex256'>: 32, <type '\
numpy.uint8'>: 1, <type 'numpy.uint64'>: 8, <type 'numpy.int64'>: 8}

s_

Value:
<numpy.lib.index_tricks._index_expression_class object at 0x2b0c49aabd\
10>

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.int64'>,
...

sctypeNA

Value:
{'?': 'Bool',
 'B': 'UInt8',
 'Bool': <type 'numpy.bool_'>,
 'Complex128': <type 'numpy.complex256'>,
 'Complex32': <type 'numpy.complex64'>,
 'Complex64': <type 'numpy.complex128'>,
 'D': 'Complex64',
 'F': 'Complex32',
...

sctypes

Value:
{'complex': [<type 'numpy.complex64'>,
             <type 'numpy.complex128'>,
             <type 'numpy.complex256'>],
 'float': [<type 'numpy.float32'>,
           <type 'numpy.float64'>,
           <type 'numpy.float128'>],
 '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.int64'>,
...

typeNA

Value:
{'?': 'Bool',
 'B': 'UInt8',
 'Bool': <type 'numpy.bool_'>,
 'Complex128': <type 'numpy.complex256'>,
 'Complex32': <type 'numpy.complex64'>,
 'Complex64': <type 'numpy.complex128'>,
 'D': 'Complex64',
 'F': 'Complex32',
...