removed np_cache

src/scgenerator/cache.py

@@ -1,77 +0,0 @@
-from collections import namedtuple
-from copy import copy
-from functools import wraps
-
-import numpy as np
-
-CacheInfo = namedtuple("CacheInfo", "hits misses size")
-
-
-def make_arg_hashable(arg):
-    if isinstance(arg, np.ndarray):
-        return arg.tobytes()
-    elif isinstance(arg, list):
-        return tuple(make_arg_hashable(a) for a in arg)
-    return arg
-
-
-def np_cache(func):
-    def new_cached_func():
-        cache = {}
-        hits = misses = 0
-
-        @wraps(func)
-        def wrapped(*args, **kwargs):
-            nonlocal cache, hits, misses
-            hashable_args = tuple(make_arg_hashable(a) for a in args)
-            hashable_kwargs = tuple({k: make_arg_hashable(a) for k, a in kwargs.items()}.items())
-            key = hash((hashable_args, hashable_kwargs))
-            if key not in cache:
-                misses += 1
-                cache[key] = func(*args, **kwargs)
-            else:
-                hits += 1
-            return copy(cache[key])
-
-        def reset():
-            nonlocal cache, hits, misses
-            cache = {}
-            hits = misses = 0
-
-        wrapped.cache_info = lambda: CacheInfo(hits, misses, len(cache))
-        wrapped.reset = reset
-
-        return wrapped
-
-    return new_cached_func()
-
-
-if __name__ == "__main__":
-    import random
-    import time
-
-    @np_cache
-    def lol(a):
-        time.sleep(random.random() * 4)
-        return a / 2
-
-    @np_cache
-    def ggg(b):
-        time.sleep(random.random() * 4)
-        return b * 2
-
-    x = np.arange(6)
-    for i in range(5):
-        print(lol.cache_info())
-        print(lol(x))
-
-    print(f"{ggg.cache_info()=}")
-    print(f"{lol.cache_info()=}")
-    lol.reset()
-
-    print(ggg(np.arange(3)))
-    print(ggg(np.arange(8)))
-    print(ggg(np.arange(3)))
-
-    print(f"{ggg.cache_info()=}")
-    print(f"{lol.cache_info()=}")

src/scgenerator/physics/__init__.py

@@ -9,7 +9,6 @@ import numpy as np
 from scipy.optimize import minimize_scalar
 
 from scgenerator import math
-from scgenerator.cache import np_cache
 from scgenerator.physics import fiber, materials, pulse, units
 
 T = TypeVar("T")
@@ -21,7 +20,6 @@ def group_delay_to_gdd(wavelength: np.ndarray, group_delay: np.ndarray) -> np.nd
     return gdd
 
 
-@np_cache
 def material_dispersion(
     wavelengths: np.ndarray,
     material: str,

src/scgenerator/physics/fiber.py

@@ -7,7 +7,6 @@ from numpy.polynomial.chebyshev import Chebyshev, cheb2poly
 from scipy.interpolate import interp1d
 
 from scgenerator import utils
-from scgenerator.cache import np_cache
 from scgenerator.math import argclosest, u_nm
 from scgenerator.physics import materials as mat
 from scgenerator.physics import units
@@ -284,7 +283,6 @@ def capillary_resonance_strengths(
     ]
 
 
-@np_cache
 def n_eff_hasan(
     wl_for_disp: np.ndarray,
     n_gas_2: np.ndarray,
@@ -548,7 +546,6 @@ def constant_effective_area_arr(l: np.ndarray, effective_area: float) -> np.ndar
     return np.ones_like(l) * effective_area
 
 
-@np_cache
 def n_eff_pcf(wl_for_disp: np.ndarray, pcf_pitch: float, pcf_pitch_ratio: float) -> np.ndarray:
     """
     semi-analytical computation of the dispersion profile of a triangular Index-guiding PCF
@@ -685,7 +682,6 @@ def load_custom_loss(l: np.ndarray, loss_file: str) -> np.ndarray:
     return interp1d(wl, loss, fill_value=0, bounds_error=False)(l)
 
 
-@np_cache
 def dispersion_coefficients(
     w_for_disp: np.ndarray,
     beta2_arr: np.ndarray,

src/scgenerator/physics/materials.py

@@ -8,7 +8,6 @@ import numpy as np
 
 import scgenerator.math as math
 from scgenerator import utils
-from scgenerator.cache import np_cache
 from scgenerator.logger import get_logger
 from scgenerator.physics import units
 from scgenerator.physics.units import NA, c, epsilon0, kB
@@ -318,7 +317,6 @@ class Gas:
         return f"{self.__class__.__name__}({self.name!r})"
 
 
-@np_cache
 def n_gas_2(wl_for_disp: np.ndarray, gas_name: str, pressure: float, temperature: float):
     """Returns the sqare of the index of refraction of the specified gas"""
     return Sellmeier.load(gas_name).n_gas_2(wl_for_disp, temperature, pressure)