Package reflectometry :: Package model1d :: Package tests :: Module abeles

Module abeles

source code

Optical matrix form of the reflectivity calculation.

O.S. Heavens, Optical Properties of Thin Solid Films

Version: 1.2.1

Functions

refl(Qz, depth, rho, mu=0, wavelength=1, sigma=0)
Reflectometry as a function of Qz,wavelength.

source code

calc(kz, wavelength, depth, rho, mu, sigma)
Parratt recursion

source code

Variables
	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.CClass object at 0x2086350>`
	cast = `{<type 'numpy.int64'>: <function <lambda> at 0x13df4b0>...`
	ceil = `<ufunc 'ceil'>`
	conj = `<ufunc 'conjugate'>`
	conjugate = `<ufunc 'conjugate'>`
	cos = `<ufunc 'cos'>`
	cosh = `<ufunc 'cosh'>`
	degrees = `<ufunc 'degrees'>`
	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.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`
	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 0x17efe50>`
	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 0x20805f0>`
	ones_like = `<ufunc 'ones_like'>`
	pi = `3.14159265359`
	power = `<ufunc 'power'>`
	r_ = `<numpy.lib.index_tricks.RClass object at 0x2080250>`
	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 0x2086410>`
	sctypeDict = `{0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>,...`
	sctypeNA = `{'?': 'Bool', 'B': 'UInt8', 'Bool': <type 'numpy.bo...`
	sctypes = `{'complex': [<type 'numpy.complex64'>, <type 'numpy....`
	sign = `<ufunc 'sign'>`
	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...`
	typecodes = `{'All': '?bhilqpBHILQPfdgFDGSUVO', 'AllFloat': 'fd...`

Function Details

refl(Qz, depth, rho, mu=0, wavelength=1, sigma=0)

source code

Reflectometry as a function of Qz,wavelength.

Qz (inv angstrom): Scattering vector 4*pi*sin(theta)/wavelength. This is an array.
wavelenth (angstrom): Incident wavelength. If present this is a
rho,mu (uNb): scattering length density and absorption of each layer
depth (angstrom): thickness of each layer. The thickness of the incident medium and substrate are ignored.
sigma (angstrom): interfacial roughness. This is the roughness between a layer and the subsequent layer. There is no interface associated with the substrate. The sigma array should have at least n-1 entries, though it may have n with the last entry ignored.
method (parratt | abeles | opticalmatrix): method used to compute the reflectivity

Variables Details

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 0x13df4b0>, <type 'numpy.
int16'>: <function <lambda> at 0x13df4f0>, <type 'numpy.void'>: <funct
ion <lambda> at 0x13df530>, <type 'numpy.complex128'>: <function <lamb
da> at 0x13df570>, <type 'numpy.int32'>: <function <lambda> at 0x13df5
b0>, <type 'numpy.uint32'>: <function <lambda> at 0x13df5f0>, <type 'n
umpy.unicode_'>: <function <lambda> at 0x13df630>, <type 'numpy.comple
x64'>: <function <lambda> at 0x13df670>, <type 'numpy.int32'>: <functi
on <lambda> at 0x13df6b0>, <type 'numpy.uint32'>: <function <lambda> a
...

index_exp

Value:

<numpy.lib.index_tricks.IndexExpression object at 0x20863d0>

nbytes

Value:

{<type 'numpy.int64'>: 8, <type 'numpy.int16'>: 2, <type 'numpy.void'>
: 0, <type 'numpy.complex128'>: 16, <type 'numpy.int32'>: 4, <type 'nu
mpy.uint32'>: 4, <type 'numpy.unicode_'>: 0, <type 'numpy.complex64'>:
 8, <type 'numpy.int32'>: 4, <type 'numpy.uint32'>: 4, <type 'numpy.st
ring_'>: 0, <type 'numpy.float128'>: 16, <type 'numpy.uint16'>: 2, <ty
pe 'numpy.object_'>: 4, <type 'numpy.float64'>: 8, <type 'numpy.int8'>
: 1, <type 'numpy.uint64'>: 8, <type 'numpy.uint8'>: 1, <type 'numpy.b
ool_'>: 1, <type 'numpy.float32'>: 4, <type 'numpy.complex256'>: 32}

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_'>,
 '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.int32'>,
...

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',
...

typecodes

Value:

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