def test_asin(self):
start = 0
diff = 0.00000001
for i in range(2):
for e in env:
set_posit_env(e[0], e[1])
b = Math.asin(Posit(start))
Posit(asin(float(Posit(start).get_value())))
start += diff
def test_log(self):
start = 10
diff = 0.1
for i in range(100):
for e in env:
set_posit_env(e[0], e[1])
b = Math.log(Posit(start))
self.assertEqual(Posit(log(float(Posit(start).get_value()))),
b)
start += diff
def test_large_tan(self):
start = -100
diff = 10
for i in range(100):
for e in env:
set_posit_env(e[0], e[1])
b = Math.tan(Posit(start))
self.assertEqual(Posit(tan(float(Posit(start).get_value()))),
b)
start += diff
def test_pow(self):
i = 10.0
while i < 10:
j = -10.0
while j < 10.0:
for e in env:
set_posit_env(e[0], e[1])
b = Posit(i)**Posit(j)
self.assertEqual(
Posit(
float(Posit(i).get_value())**float(
Posit(j).get_value())), b)
j += 0.1
i += 0.1
def test_small_cast(self):
ctx = shortcuts.get_context()
ctx.load_libs(['../PySigmoid/posit-javascript/js/decimallookupv2.js'])
start = 1.5
diff = 0.0001
for i in range(10000):
res = eval(ctx.run_script('convertDToP("{}")'.format(str(start))))
for j in res:
nbits = j["ps"]
es = j["es"]
set_posit_env(nbits, es)
a, b = bin(Posit(start).number)[2:], bin(int(j["posit"],
2))[2:]
self.assertEqual(a, b)
start += diff
t = deepcopy(p)
x = Posit(float(p)).get_value()
y = p
d = decacc(x, y)
xx.append(float(p))
yy.append(float(d))
p += D("1")
print(p)
# Plot
plt.plot(xx, yy, alpha=1)
plt.xlabel('x')
plt.ylabel('Decimal Accuracy of x when converting to Posit')
plt.show()
set_posit_env(8, 1)
p = Posit()
p.set_bit_pattern(p.maxpos)
p = -p
p = p.get_value()
q = Posit()
q.set_bit_pattern(q.maxpos),
q = q.get_value()
xx = []
yy = []
while p <= q:
t = deepcopy(p)
x = Posit(float(p)).get_value()
from PySigmoid import Posit as P, set_posit_env
import numpy as np
set_posit_env(64, 3)
# input matrix
reg = [
[0, 2, 3, 4],
[3, 4, 5, 6],
[1, 3, 2, 11],
[3, 5, 3, 4]
]
# functiont to cast a regular matrix to a posit matrix
posify = lambda x: [list(map(P, e)) for e in x]
pos = posify(reg) # convert to posit
b = np.matrix(pos)
a = np.matrix(pos)
# addition
print(b+b)
print(a+a)
# subtraction
print(b-b)
print(a-a)
# multiplication
print(b*b)
print(a*a)
# transpose
print(np.transpose(b))
print(np.transpose(a))
import matplotlib.pyplot as plt
from math import exp
from copy import deepcopy as dc
# 500 digits of precision
getcontext().prec = 50
def decacc(x, y):
if x == y:
return D('inf')
else:
try:
return -abs((x / y).log10()).log10()
except:
return 0
set_posit_env(8, 0)
start = -100
end = 100
xx = []
yy = []
yy2 = []
def sigmoid(x):
return 1 / (1 + exp(-x))
while start <= end:
q = Posit(start)
q = q.sigmoid()
xx.append(start)
yy.append(float(q))