From f2a7129796a75ff6d107b410f5c1b7d3326cd508 Mon Sep 17 00:00:00 2001 From: Fabian Joswig Date: Mon, 22 Nov 2021 16:09:34 +0000 Subject: [PATCH] npr module removed --- docs/pyerrors/npr.html | 747 ----------------------------------------- pyerrors/npr.py | 108 ------ 2 files changed, 855 deletions(-) delete mode 100644 docs/pyerrors/npr.html delete mode 100644 pyerrors/npr.py diff --git a/docs/pyerrors/npr.html b/docs/pyerrors/npr.html deleted file mode 100644 index 74714b92..00000000 --- a/docs/pyerrors/npr.html +++ /dev/null @@ -1,747 +0,0 @@ - - - - - - - pyerrors.npr API documentation - - - - - - - - - - - -
-
-

-pyerrors.npr

- - -
- View Source - 
import warnings
-import numpy as np
-from .linalg import inv, matmul
-from .dirac import gamma
-
-
-L = None
-T = None
-
-
-class Npr_matrix(np.ndarray):
-
-    def __new__(cls, input_array, mom_in=None, mom_out=None):
-        obj = np.asarray(input_array).view(cls)
-        obj.mom_in = mom_in
-        obj.mom_out = mom_out
-        return obj
-
-    @property
-    def g5H(self):
-        """Gamma_5 hermitean conjugate
-
-        Uses the fact that the propagator is gamma5 hermitean, so just the
-        in and out momenta of the propagator are exchanged.
-        """
-        return Npr_matrix(self,
-                          mom_in=self.mom_out,
-                          mom_out=self.mom_in)
-
-    def _propagate_mom(self, other, name):
-        s_mom = getattr(self, name, None)
-        o_mom = getattr(other, name, None)
-        if s_mom is not None and o_mom is not None:
-            if not np.allclose(s_mom, o_mom):
-                raise Exception(name + ' does not match.')
-        return o_mom if o_mom is not None else s_mom
-
-    def __matmul__(self, other):
-        return self.__new__(Npr_matrix,
-                            super().__matmul__(other),
-                            self._propagate_mom(other, 'mom_in'),
-                            self._propagate_mom(other, 'mom_out'))
-
-    def __array_finalize__(self, obj):
-        if obj is None:
-            return
-        self.mom_in = getattr(obj, 'mom_in', None)
-        self.mom_out = getattr(obj, 'mom_out', None)
-
-
-def _check_geometry():
-    if L is None:
-        raise Exception("Spatial extent 'L' not set.")
-    else:
-        if not isinstance(L, int):
-            raise Exception("Spatial extent 'L' must be an integer.")
-    if T is None:
-        raise Exception("Temporal extent 'T' not set.")
-        if not isinstance(T, int):
-            raise Exception("Temporal extent 'T' must be an integer.")
-
-
-def inv_propagator(prop):
-    """ Inverts a 12x12 quark propagator"""
-    if prop.shape != (12, 12):
-        raise Exception("Only 12x12 propagators can be inverted.")
-    return Npr_matrix(inv(prop), prop.mom_in)
-
-
-def Zq(inv_prop, fermion='Wilson'):
-    """ Calculates the quark field renormalization constant Zq
-
-        Parameters
-        ----------
-        inv_prop : array
-            Inverted 12x12 quark propagator
-        fermion : str
-            Fermion type for which the tree-level propagator is used
-                   in the calculation of Zq. Default Wilson.
-    """
-    _check_geometry()
-    mom = np.copy(inv_prop.mom_in)
-    mom[3] /= T / L
-    sin_mom = np.sin(2 * np.pi / L * mom)
-
-    if fermion == 'Wilson':
-        p_slash = -1j * (sin_mom[0] * gamma[0] + sin_mom[1] * gamma[1] + sin_mom[2] * gamma[2] + sin_mom[3] * gamma[3]) / np.sum(sin_mom ** 2)
-    elif fermion == 'Continuum':
-        p_mom = 2 * np.pi / L * mom
-        p_slash = -1j * (p_mom[0] * gamma[0] + p_mom[1] * gamma[1] + p_mom[2] * gamma[2] + p_mom[3] * gamma[3]) / np.sum(p_mom ** 2)
-    elif fermion == 'DWF':
-        W = np.sum(1 - np.cos(2 * np.pi / L * mom))
-        s2 = np.sum(sin_mom ** 2)
-        p_slash = -1j * (sin_mom[0] * gamma[0] + sin_mom[1] * gamma[1] + sin_mom[2] * gamma[2] + sin_mom[3] * gamma[3])
-        p_slash /= 2 * (W - 1 + np.sqrt((1 - W) ** 2 + s2))
-    else:
-        raise Exception("Fermion type '" + fermion + "' not implemented")
-
-    res = 1 / 12. * np.trace(matmul(inv_prop, np.kron(np.eye(3, dtype=int), p_slash)))
-    res.gamma_method()
-
-    if not res.imag.is_zero_within_error(5):
-        warnings.warn("Imaginary part of Zq is not zero within 5 sigma")
-        return res
-
-    res.real.tag = "Zq '" + fermion + "', p=" + str(inv_prop.mom_in)
-
-    return res.real
-
- -
- -
-
-
- #   - - - class - Npr_matrix(numpy.ndarray): -
- -
- View Source - 
class Npr_matrix(np.ndarray):
-
-    def __new__(cls, input_array, mom_in=None, mom_out=None):
-        obj = np.asarray(input_array).view(cls)
-        obj.mom_in = mom_in
-        obj.mom_out = mom_out
-        return obj
-
-    @property
-    def g5H(self):
-        """Gamma_5 hermitean conjugate
-
-        Uses the fact that the propagator is gamma5 hermitean, so just the
-        in and out momenta of the propagator are exchanged.
-        """
-        return Npr_matrix(self,
-                          mom_in=self.mom_out,
-                          mom_out=self.mom_in)
-
-    def _propagate_mom(self, other, name):
-        s_mom = getattr(self, name, None)
-        o_mom = getattr(other, name, None)
-        if s_mom is not None and o_mom is not None:
-            if not np.allclose(s_mom, o_mom):
-                raise Exception(name + ' does not match.')
-        return o_mom if o_mom is not None else s_mom
-
-    def __matmul__(self, other):
-        return self.__new__(Npr_matrix,
-                            super().__matmul__(other),
-                            self._propagate_mom(other, 'mom_in'),
-                            self._propagate_mom(other, 'mom_out'))
-
-    def __array_finalize__(self, obj):
-        if obj is None:
-            return
-        self.mom_in = getattr(obj, 'mom_in', None)
-        self.mom_out = getattr(obj, 'mom_out', None)
-
- -
- -

ndarray(shape, dtype=float, buffer=None, offset=0, - strides=None, order=None)

- -

An array object represents a multidimensional, homogeneous array -of fixed-size items. An associated data-type object describes the -format of each element in the array (its byte-order, how many bytes it -occupies in memory, whether it is an integer, a floating point number, -or something else, etc.)

- -

Arrays should be constructed using array, zeros or empty (refer -to the See Also section below). The parameters given here refer to -a low-level method (ndarray(...)) for instantiating an array.

- -

For more information, refer to the numpy module and examine the -methods and attributes of an array.

- -
Parameters
- -
    -
  • (for the __new__ method; see Notes below)
    • -
  • shape (tuple of ints): -Shape of created array.
    • -
  • dtype (data-type, optional): -Any object that can be interpreted as a numpy data type.
    • -
  • buffer (object exposing buffer interface, optional): -Used to fill the array with data.
    • -
  • offset (int, optional): -Offset of array data in buffer.
    • -
  • strides (tuple of ints, optional): -Strides of data in memory.
    • -
  • order ({'C', 'F'}, optional): -Row-major (C-style) or column-major (Fortran-style) order.
    • -
- -
Attributes
- -
    -
  • T (ndarray): -Transpose of the array.
    • -
  • data (buffer): -The array's elements, in memory.
    • -
  • dtype (dtype object): -Describes the format of the elements in the array.
    • -
  • flags (dict): -Dictionary containing information related to memory use, e.g., -'C_CONTIGUOUS', 'OWNDATA', 'WRITEABLE', etc.
    • -
  • flat (numpy.flatiter object): -Flattened version of the array as an iterator. The iterator -allows assignments, e.g., x.flat = 3 (See ndarray.flat for -assignment examples; TODO).
    • -
  • imag (ndarray): -Imaginary part of the array.
    • -
  • real (ndarray): -Real part of the array.
    • -
  • size (int): -Number of elements in the array.
    • -
  • itemsize (int): -The memory use of each array element in bytes.
    • -
  • nbytes (int): -The total number of bytes required to store the array data, -i.e., itemsize * size.
    • -
  • ndim (int): -The array's number of dimensions.
    • -
  • shape (tuple of ints): -Shape of the array.
    • -
  • strides (tuple of ints): -The step-size required to move from one element to the next in -memory. For example, a contiguous (3, 4) array of type -int16 in C-order has strides (8, 2). This implies that -to move from element to element in memory requires jumps of 2 bytes. -To move from row-to-row, one needs to jump 8 bytes at a time -(2 * 4).
    • -
  • ctypes (ctypes object): -Class containing properties of the array needed for interaction -with ctypes.
    • -
  • base (ndarray): -If the array is a view into another array, that array is its base -(unless that array is also a view). The base array is where the -array data is actually stored.
    • -
- -
See Also
- -

array: Construct an array.
-zeros: Create an array, each element of which is zero.
-empty: Create an array, but leave its allocated memory unchanged (i.e., -it contains "garbage").
-dtype: Create a data-type.
-numpy.typing.NDArray: A :term:generic <generic type> version -of ndarray.

- -
Notes
- -

There are two modes of creating an array using __new__:

- -
    -
  1. If buffer is None, then only shape, dtype, and order -are used.
    2. -
  2. If buffer is an object exposing the buffer interface, then -all keywords are interpreted.
    3. -
- -

No __init__ method is needed because the array is fully initialized -after the __new__ method.

- -
Examples
- -

These examples illustrate the low-level ndarray constructor. Refer -to the See Also section above for easier ways of constructing an -ndarray.

- -

First mode, buffer is None:

- -
>>> np.ndarray(shape=(2,2), dtype=float, order='F')
-array([[0.0e+000, 0.0e+000], # random
-       [     nan, 2.5e-323]])
-
- -

Second mode:

- -
>>> np.ndarray((2,), buffer=np.array([1,2,3]),
-...            offset=np.int_().itemsize,
-...            dtype=int) # offset = 1*itemsize, i.e. skip first element
-array([2, 3])
-
-
- - -
-
#   - - - Npr_matrix() -
- - - - -
-
-
#   - - g5H -
- -

Gamma_5 hermitean conjugate

- -

Uses the fact that the propagator is gamma5 hermitean, so just the -in and out momenta of the propagator are exchanged.

-
- - -
-
-
Inherited Members
-
-
numpy.ndarray
-
dumps
-
dump
-
all
-
any
-
argmax
-
argmin
-
argpartition
-
argsort
-
astype
-
byteswap
-
choose
-
clip
-
compress
-
conj
-
conjugate
-
copy
-
cumprod
-
cumsum
-
diagonal
-
dot
-
fill
-
flatten
-
getfield
-
item
-
itemset
-
max
-
mean
-
min
-
newbyteorder
-
nonzero
-
partition
-
prod
-
ptp
-
put
-
ravel
-
repeat
-
reshape
-
resize
-
round
-
searchsorted
-
setfield
-
setflags
-
sort
-
squeeze
-
std
-
sum
-
swapaxes
-
take
-
tobytes
-
tofile
-
tolist
-
tostring
-
trace
-
transpose
-
var
-
view
-
ndim
-
flags
-
shape
-
strides
-
data
-
itemsize
-
size
-
nbytes
-
base
-
dtype
-
real
-
imag
-
flat
-
ctypes
-
T
- -
-
-
-
-
-
#   - - - def - inv_propagator(prop): -
- -
- View Source - 
def inv_propagator(prop):
-    """ Inverts a 12x12 quark propagator"""
-    if prop.shape != (12, 12):
-        raise Exception("Only 12x12 propagators can be inverted.")
-    return Npr_matrix(inv(prop), prop.mom_in)
-
- -
- -

Inverts a 12x12 quark propagator

-
- - -
-
-
#   - - - def - Zq(inv_prop, fermion='Wilson'): -
- -
- View Source - 
def Zq(inv_prop, fermion='Wilson'):
-    """ Calculates the quark field renormalization constant Zq
-
-        Parameters
-        ----------
-        inv_prop : array
-            Inverted 12x12 quark propagator
-        fermion : str
-            Fermion type for which the tree-level propagator is used
-                   in the calculation of Zq. Default Wilson.
-    """
-    _check_geometry()
-    mom = np.copy(inv_prop.mom_in)
-    mom[3] /= T / L
-    sin_mom = np.sin(2 * np.pi / L * mom)
-
-    if fermion == 'Wilson':
-        p_slash = -1j * (sin_mom[0] * gamma[0] + sin_mom[1] * gamma[1] + sin_mom[2] * gamma[2] + sin_mom[3] * gamma[3]) / np.sum(sin_mom ** 2)
-    elif fermion == 'Continuum':
-        p_mom = 2 * np.pi / L * mom
-        p_slash = -1j * (p_mom[0] * gamma[0] + p_mom[1] * gamma[1] + p_mom[2] * gamma[2] + p_mom[3] * gamma[3]) / np.sum(p_mom ** 2)
-    elif fermion == 'DWF':
-        W = np.sum(1 - np.cos(2 * np.pi / L * mom))
-        s2 = np.sum(sin_mom ** 2)
-        p_slash = -1j * (sin_mom[0] * gamma[0] + sin_mom[1] * gamma[1] + sin_mom[2] * gamma[2] + sin_mom[3] * gamma[3])
-        p_slash /= 2 * (W - 1 + np.sqrt((1 - W) ** 2 + s2))
-    else:
-        raise Exception("Fermion type '" + fermion + "' not implemented")
-
-    res = 1 / 12. * np.trace(matmul(inv_prop, np.kron(np.eye(3, dtype=int), p_slash)))
-    res.gamma_method()
-
-    if not res.imag.is_zero_within_error(5):
-        warnings.warn("Imaginary part of Zq is not zero within 5 sigma")
-        return res
-
-    res.real.tag = "Zq '" + fermion + "', p=" + str(inv_prop.mom_in)
-
-    return res.real
-
- -
- -

Calculates the quark field renormalization constant Zq

- -
Parameters
- -
    -
  • inv_prop (array): -Inverted 12x12 quark propagator
    • -
  • fermion (str): -Fermion type for which the tree-level propagator is used - in the calculation of Zq. Default Wilson.
    • -
-
- - -
-
- - \ No newline at end of file diff --git a/pyerrors/npr.py b/pyerrors/npr.py deleted file mode 100644 index 5e67ce9e..00000000 --- a/pyerrors/npr.py +++ /dev/null @@ -1,108 +0,0 @@ -import warnings -import numpy as np -from .linalg import inv, matmul -from .dirac import gamma - - -L = None -T = None - - -class Npr_matrix(np.ndarray): - - def __new__(cls, input_array, mom_in=None, mom_out=None): - obj = np.asarray(input_array).view(cls) - obj.mom_in = mom_in - obj.mom_out = mom_out - return obj - - @property - def g5H(self): - """Gamma_5 hermitean conjugate - - Uses the fact that the propagator is gamma5 hermitean, so just the - in and out momenta of the propagator are exchanged. - """ - return Npr_matrix(self, - mom_in=self.mom_out, - mom_out=self.mom_in) - - def _propagate_mom(self, other, name): - s_mom = getattr(self, name, None) - o_mom = getattr(other, name, None) - if s_mom is not None and o_mom is not None: - if not np.allclose(s_mom, o_mom): - raise Exception(name + ' does not match.') - return o_mom if o_mom is not None else s_mom - - def __matmul__(self, other): - return self.__new__(Npr_matrix, - super().__matmul__(other), - self._propagate_mom(other, 'mom_in'), - self._propagate_mom(other, 'mom_out')) - - def __array_finalize__(self, obj): - if obj is None: - return - self.mom_in = getattr(obj, 'mom_in', None) - self.mom_out = getattr(obj, 'mom_out', None) - - -def _check_geometry(): - if L is None: - raise Exception("Spatial extent 'L' not set.") - else: - if not isinstance(L, int): - raise Exception("Spatial extent 'L' must be an integer.") - if T is None: - raise Exception("Temporal extent 'T' not set.") - if not isinstance(T, int): - raise Exception("Temporal extent 'T' must be an integer.") - - -def inv_propagator(prop): - """ Inverts a 12x12 quark propagator""" - if prop.shape != (12, 12): - raise Exception("Only 12x12 propagators can be inverted.") - return Npr_matrix(inv(prop), prop.mom_in) - - -def Zq(inv_prop, fermion='Wilson'): - """ Calculates the quark field renormalization constant Zq - - Parameters - ---------- - inv_prop : array - Inverted 12x12 quark propagator - fermion : str - Fermion type for which the tree-level propagator is used - in the calculation of Zq. Default Wilson. - """ - _check_geometry() - mom = np.copy(inv_prop.mom_in) - mom[3] /= T / L - sin_mom = np.sin(2 * np.pi / L * mom) - - if fermion == 'Wilson': - p_slash = -1j * (sin_mom[0] * gamma[0] + sin_mom[1] * gamma[1] + sin_mom[2] * gamma[2] + sin_mom[3] * gamma[3]) / np.sum(sin_mom ** 2) - elif fermion == 'Continuum': - p_mom = 2 * np.pi / L * mom - p_slash = -1j * (p_mom[0] * gamma[0] + p_mom[1] * gamma[1] + p_mom[2] * gamma[2] + p_mom[3] * gamma[3]) / np.sum(p_mom ** 2) - elif fermion == 'DWF': - W = np.sum(1 - np.cos(2 * np.pi / L * mom)) - s2 = np.sum(sin_mom ** 2) - p_slash = -1j * (sin_mom[0] * gamma[0] + sin_mom[1] * gamma[1] + sin_mom[2] * gamma[2] + sin_mom[3] * gamma[3]) - p_slash /= 2 * (W - 1 + np.sqrt((1 - W) ** 2 + s2)) - else: - raise Exception("Fermion type '" + fermion + "' not implemented") - - res = 1 / 12. * np.trace(matmul(inv_prop, np.kron(np.eye(3, dtype=int), p_slash))) - res.gamma_method() - - if not res.imag.is_zero_within_error(5): - warnings.warn("Imaginary part of Zq is not zero within 5 sigma") - return res - - res.real.tag = "Zq '" + fermion + "', p=" + str(inv_prop.mom_in) - - return res.real