forked from M-Labs/nac3
280 lines
7.0 KiB
Python
Executable File
280 lines
7.0 KiB
Python
Executable File
#!/usr/bin/env python3
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import sys
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import importlib.util
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import importlib.machinery
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import math
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import numpy as np
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import numpy.typing as npt
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import scipy as sp
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import pathlib
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from numpy import int32, int64, uint32, uint64
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from scipy import special
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from typing import TypeVar, Generic, Literal, Union
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T = TypeVar('T')
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class Option(Generic[T]):
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_nac3_option: T
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def __init__(self, v: T):
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self._nac3_option = v
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def is_none(self):
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return self._nac3_option is None
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def is_some(self):
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return not self.is_none()
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def unwrap(self):
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return self._nac3_option
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def __repr__(self) -> str:
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if self.is_none():
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return "none"
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else:
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return "Some({})".format(repr(self._nac3_option))
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def __str__(self) -> str:
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if self.is_none():
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return "none"
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else:
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return "Some({})".format(str(self._nac3_option))
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def Some(v: T) -> Option[T]:
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return Option(v)
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none = Option(None)
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class _ConstGenericMarker:
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pass
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def ConstGeneric(name, constraint):
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return TypeVar(name, _ConstGenericMarker, constraint)
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N = TypeVar("N", bound=np.uint64)
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class _NDArrayDummy(Generic[T, N]):
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pass
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# https://stackoverflow.com/questions/67803260/how-to-create-a-type-alias-with-a-throw-away-generic
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NDArray = Union[npt.NDArray[T], _NDArrayDummy[T, N]]
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def _bool(x):
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if isinstance(x, np.ndarray):
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return np.bool_(x)
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else:
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return bool(x)
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def _float(x):
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if isinstance(x, np.ndarray):
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return np.float_(x)
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else:
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return float(x)
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def round_away_zero(x):
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if isinstance(x, np.ndarray):
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return np.vectorize(round_away_zero)(x)
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else:
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if x >= 0.0:
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return math.floor(x + 0.5)
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else:
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return math.ceil(x - 0.5)
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def _floor(x):
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if isinstance(x, np.ndarray):
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return np.vectorize(_floor)(x)
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else:
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return math.floor(x)
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def _ceil(x):
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if isinstance(x, np.ndarray):
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return np.vectorize(_ceil)(x)
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else:
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return math.ceil(x)
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def patch(module):
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def dbl_nan():
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return np.nan
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def dbl_inf():
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return np.inf
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def output_asciiart(x):
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if x < 0:
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sys.stdout.write("\n")
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else:
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sys.stdout.write(" .,-:;i+hHM$*#@ "[x])
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def output_float(x):
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print("%f" % x)
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def output_strln(x):
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print(x, end='')
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def dbg_stack_address(_):
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return 0
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def extern(fun):
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name = fun.__name__
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if name == "dbl_nan":
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return dbl_nan
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elif name == "dbl_inf":
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return dbl_inf
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elif name == "output_asciiart":
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return output_asciiart
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elif name == "output_float64":
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return output_float
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elif name == "output_str":
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return output_strln
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elif name in {
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"output_bool",
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"output_int32",
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"output_int64",
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"output_int32_list",
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"output_uint32",
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"output_uint64",
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"output_strln",
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"output_range",
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}:
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return print
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elif name == "dbg_stack_address":
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return dbg_stack_address
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else:
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raise NotImplementedError
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module.int32 = int32
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module.int64 = int64
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module.uint32 = uint32
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module.uint64 = uint64
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module.bool = _bool
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module.float = _float
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module.TypeVar = TypeVar
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module.ConstGeneric = ConstGeneric
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module.Generic = Generic
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module.Literal = Literal
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module.extern = extern
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module.Option = Option
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module.Some = Some
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module.none = none
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# Builtin Math functions
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module.round = round_away_zero
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module.round64 = round_away_zero
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module.np_round = np.round
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module.floor = _floor
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module.floor64 = _floor
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module.np_floor = np.floor
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module.ceil = _ceil
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module.ceil64 = _ceil
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module.np_ceil = np.ceil
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# NumPy NDArray factory functions
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module.ndarray = NDArray
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module.np_ndarray = np.ndarray
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module.np_empty = np.empty
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module.np_zeros = np.zeros
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module.np_ones = np.ones
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module.np_full = np.full
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module.np_eye = np.eye
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module.np_identity = np.identity
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module.np_array = np.array
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# NumPy NDArray view functions
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module.np_transpose = np.transpose
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module.np_reshape = np.reshape
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# NumPy NDArray property getters
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module.np_shape = np.shape
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module.np_strides = lambda ndarray: ndarray.strides
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# NumPy Math functions
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module.np_isnan = np.isnan
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module.np_isinf = np.isinf
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module.np_min = np.min
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module.np_minimum = np.minimum
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module.np_argmin = np.argmin
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module.np_max = np.max
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module.np_maximum = np.maximum
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module.np_argmax = np.argmax
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module.np_sin = np.sin
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module.np_cos = np.cos
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module.np_exp = np.exp
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module.np_exp2 = np.exp2
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module.np_log = np.log
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module.np_log10 = np.log10
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module.np_log2 = np.log2
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module.np_fabs = np.fabs
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module.np_trunc = np.trunc
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module.np_sqrt = np.sqrt
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module.np_rint = np.rint
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module.np_tan = np.tan
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module.np_arcsin = np.arcsin
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module.np_arccos = np.arccos
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module.np_arctan = np.arctan
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module.np_sinh = np.sinh
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module.np_cosh = np.cosh
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module.np_tanh = np.tanh
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module.np_arcsinh = np.arcsinh
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module.np_arccosh = np.arccosh
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module.np_arctanh = np.arctanh
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module.np_expm1 = np.expm1
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module.np_cbrt = np.cbrt
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module.np_arctan2 = np.arctan2
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module.np_copysign = np.copysign
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module.np_fmax = np.fmax
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module.np_fmin = np.fmin
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module.np_ldexp = np.ldexp
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module.np_hypot = np.hypot
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module.np_nextafter = np.nextafter
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# SciPy Math functions
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module.sp_spec_erf = special.erf
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module.sp_spec_erfc = special.erfc
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module.sp_spec_gamma = special.gamma
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module.sp_spec_gammaln = special.gammaln
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module.sp_spec_j0 = special.j0
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module.sp_spec_j1 = special.j1
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# Linalg functions
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module.np_dot = np.dot
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module.np_linalg_cholesky = np.linalg.cholesky
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module.np_linalg_qr = np.linalg.qr
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module.np_linalg_svd = np.linalg.svd
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module.np_linalg_inv = np.linalg.inv
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module.np_linalg_pinv = np.linalg.pinv
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module.np_linalg_matrix_power = np.linalg.matrix_power
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module.np_linalg_det = np.linalg.det
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module.sp_linalg_lu = lambda x: sp.linalg.lu(x, True)
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module.sp_linalg_schur = sp.linalg.schur
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module.sp_linalg_hessenberg = lambda x: sp.linalg.hessenberg(x, True)
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def file_import(filename, prefix="file_import_"):
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filename = pathlib.Path(filename)
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modname = prefix + filename.stem
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path = str(filename.resolve().parent)
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sys.path.insert(0, path)
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try:
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spec = importlib.util.spec_from_loader(
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modname,
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importlib.machinery.SourceFileLoader(modname, str(filename)),
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)
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module = importlib.util.module_from_spec(spec)
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patch(module)
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spec.loader.exec_module(module)
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finally:
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sys.path.remove(path)
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return module
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def main():
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demo = file_import(sys.argv[1])
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demo.run()
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if __name__ == "__main__":
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main()
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