CoryKornowicz

import mlx.core as mx
import mlx.nn as nn
import mlx.optimizers as optim
from mlx.data.datasets import load_mnist

@mx.compile
def matrix_exp(M):
    """
    Compute matrix exponential using scaling and squaring with Padé approximation.
    This implements a simplified version suitable for small matrices.

CoryKornowicz

from __future__ import division
import numpy  as np
import IPython as ip
import matplotlib.pyplot as pp
import warnings
from collections import namedtuple
import scipy.optimize

#symbolic algebra
import theano

CoryKornowicz

import math

# deltaG = -RT*ln(Kd)

def Kd_to_dG(Kd):	
	Kd = float(Kd)
  	#           R      T
	dG = -0.0019872036*298*math.log(Kd)
	print('{} Kcal/mol'.format(round(dG, 2)))
	

CoryKornowicz