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