Remove lru_cache on LOS methods

The 'self' argument is included in the caching calculation, and the cache is kept globally with the class (not with each instance, as you might expect). One of these even has an unbound size! Finally, these don't actually provide an appreciable speedup.

paltas/Substructure/los_dg19.py

@@ -11,7 +11,6 @@
 import numpy as np
 from colossus.lss import peaks, bias
 from ..Utils import power_law, cosmology_utils
-import functools
 from . import nfw_functions
 import lenstronomy.Util.util as util
 from lenstronomy.LensModel.Profiles.nfw import NFW
@@ -121,7 +120,6 @@ def dn_dm(self,m,z):
 
 		return -1/3*nfn_eval*rho_m/m**2*d_ln_sigma_d_ln_r
 
-	@functools.lru_cache(maxsize=None)
 	def power_law_dn_dm(self,z,m_min,m_max,n_dm=100):
 		"""Returns the best fit power law parameters for the physical number
 		density at a given redshift and mass range.
@@ -192,7 +190,6 @@ def two_halo_boost(self,z,z_lens,dz,lens_m200,r_max,r_min,n_quads=100):
 			model='tinker10')
 		return 1+np.mean(xi_halo)
 
-	@functools.lru_cache(maxsize=1024)
 	def cone_angle_to_radius(self,z,z_lens,z_source,cone_angle,
 		angle_buffer=0.8):
 		"""Returns the radius in kpc at the given redshift for the given cone
@@ -228,7 +225,6 @@ def cone_angle_to_radius(self,z,z_lens,z_source,cone_angle,
 			r_los *= 1 - scal_factor
 		return r_los
 
-	@functools.lru_cache(maxsize=1024)
 	def volume_element(self,z,z_lens,z_source,dz,cone_angle,angle_buffer=0.8):
 		"""Returns the physical volume element at the given redshift