prepare multiply.py for release and add script for automatic calculation testing

This commit is contained in:
dymik739 2023-04-01 20:53:36 +03:00
parent 6cda8bcfa0
commit 1ab5b67c77
2 changed files with 86 additions and 20 deletions

27
src/mult-test.py Normal file
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@ -0,0 +1,27 @@
import multiply as mlt
top_value = int("0b" + input("Top value (in binary): "), 2)
m = int(input("Method: "))
total_iterations = (top_value + 1) ** 2
print(f"Total test amount: {top_value + 1}^2 = {total_iterations}")
errors = []
for x in range(top_value):
for y in range(top_value):
n = max([len(bin(i)[2:]) for i in (x, y)])
expected_result = mlt.al(bin(x*y)[2:], 2*n)
_, r = mlt.multiply(n, x, y, m)
if r == expected_result:
print(f"{str(x*top_value+y).rjust(len(str(total_iterations)))}/{total_iterations}", end = "\r")
else:
errors.append([x, y, expected_result, r])
print(f"Failed at {x}*{y}; expected {expected_result} but got {r}!")
if len(errors) == 0:
print("Testing finished, no miscalculations detected.\nIt's safe to use!")
else:
print("Testing failed with {len(errors)} errors.")

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@ -8,52 +8,90 @@ def align_binary_to_right(value, size):
al = align_binary_to_right
def multiply(x, y, method):
def multiply(n, x, y, method):
'''
this method can be used to:
- get step-by-step binary multiplication data using different methods;
- get just the end result of binary multiplication;
it takes 4 arguments:
n - (int) base register bit depth
x - (int) value for X operand
y - (int) value for Y operand
method - (int) which method to use to perform multiplication
it returns 2 items:
- (list) table with step-by-step operations and descriptions
- (str) binary representation of the result
Methods fully supported: 4
'''
if method == 4:
n = len(bin(x)[2:]) # base registry bit length, usually written as n
# every table line has registers like so: RG1, RG3, RG2
data_table = [[["0"*(2*n+1), "0" + bin(y)[2:] + "0"*n, bin(x)[2:], "-"]]*2]
data_table = [[["0", "0"*(2*n+1), "0" + al(bin(y)[2:], n) + "0"*n, al(bin(x)[2:], n), "-"]]*2]
while int('0b' + data_table[-1][-1][2], 2) != 0:
# iteration number
i = 0
while int('0b' + data_table[-1][-1][3], 2) != 0:
data_table.append([])
i += 1
if data_table[-2][-1][2][0] == "1":
if data_table[-2][-1][3][0] == "1":
data_table[-1].append([
al(bin(int("0b"+data_table[-2][-1][0], 2) + int("0b"+data_table[-2][-1][1], 2))[-(2*n+1):], 2*n+1), # RG1 + RG3
data_table[-2][-1][1],
i,
al(bin(int("0b"+data_table[-2][-1][1], 2) + int("0b"+data_table[-2][-1][2], 2))[-(2*n+1):], 2*n+1), # RG1 + RG3
data_table[-2][-1][2],
data_table[-2][-1][3],
"RG1+RG3"
])
data_table[-1].append([
data_table[-1][-1][0],
'0' + data_table[-1][-1][1][:-1], # 0.r(RG3)
data_table[-1][-1][2][1:] + '0', # l(RG2).0
i,
data_table[-1][-1][1],
'0' + data_table[-1][-1][2][:-1], # 0.r(RG3)
data_table[-1][-1][3][1:] + '0', # l(RG2).0
"0.r(RG3), l(RG2).0"
])
else:
data_table[-1].append([
data_table[-2][-1][0],
'0' + data_table[-2][-1][1][:-1], # 0.r(RG3)
data_table[-2][-1][2][1:] + '0', # l(RG2).0
i,
data_table[-2][-1][1],
'0' + data_table[-2][-1][2][:-1], # 0.r(RG3)
data_table[-2][-1][3][1:] + '0', # l(RG2).0
"0.r(RG3), l(RG2).0"
])
return data_table
return data_table, data_table[-1][-1][1][:-1]
if __name__ == "__main__":
x = int("0b" + input("X: "), 2)
y = int("0b" + input("Y: "), 2)
# a fully functional reference
# implementation for this library
# is provided below
raw_x = input("X: ")
raw_y = input("Y: ")
if len(raw_x) == len(raw_y):
n = len(raw_x)
else:
n = int(input("n: "))
x = int("0b" + raw_x, 2)
y = int("0b" + raw_y, 2)
method = int(input("Method: "))
dt = multiply(x, y, method)
dt, result = multiply(n, x, y, method)
from lib.prettytable import PrettyTable
pt = PrettyTable()
pt.field_names = ["RG1", "RG3", "RG2", "Operations"]
pt.field_names = ["Iteration", "RG1", "RG3", "RG2", "Operations"]
for i in dt[1:]:
for i in dt:
for j in range(len(i)):
if j+1 == len(i):
pt.add_row(i[j], divider = True)
@ -61,3 +99,4 @@ if __name__ == "__main__":
pt.add_row(i[j])
print(pt)
print(f"Result: {result}")