prepare multiply.py for release and add script for automatic calculation testing
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import multiply as mlt
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top_value = int("0b" + input("Top value (in binary): "), 2)
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m = int(input("Method: "))
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total_iterations = (top_value + 1) ** 2
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print(f"Total test amount: {top_value + 1}^2 = {total_iterations}")
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errors = []
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for x in range(top_value):
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for y in range(top_value):
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n = max([len(bin(i)[2:]) for i in (x, y)])
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expected_result = mlt.al(bin(x*y)[2:], 2*n)
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_, r = mlt.multiply(n, x, y, m)
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if r == expected_result:
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print(f"{str(x*top_value+y).rjust(len(str(total_iterations)))}/{total_iterations}", end = "\r")
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else:
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errors.append([x, y, expected_result, r])
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print(f"Failed at {x}*{y}; expected {expected_result} but got {r}!")
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if len(errors) == 0:
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print("Testing finished, no miscalculations detected.\nIt's safe to use!")
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else:
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print("Testing failed with {len(errors)} errors.")
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@ -8,52 +8,90 @@ def align_binary_to_right(value, size):
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al = align_binary_to_right
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def multiply(x, y, method):
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def multiply(n, x, y, method):
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'''
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this method can be used to:
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- get step-by-step binary multiplication data using different methods;
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- get just the end result of binary multiplication;
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it takes 4 arguments:
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n - (int) base register bit depth
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x - (int) value for X operand
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y - (int) value for Y operand
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method - (int) which method to use to perform multiplication
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it returns 2 items:
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- (list) table with step-by-step operations and descriptions
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- (str) binary representation of the result
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Methods fully supported: №4
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'''
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if method == 4:
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n = len(bin(x)[2:]) # base registry bit length, usually written as n
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# every table line has registers like so: RG1, RG3, RG2
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data_table = [[["0"*(2*n+1), "0" + bin(y)[2:] + "0"*n, bin(x)[2:], "-"]]*2]
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data_table = [[["0", "0"*(2*n+1), "0" + al(bin(y)[2:], n) + "0"*n, al(bin(x)[2:], n), "-"]]*2]
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while int('0b' + data_table[-1][-1][2], 2) != 0:
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# iteration number
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i = 0
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while int('0b' + data_table[-1][-1][3], 2) != 0:
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data_table.append([])
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i += 1
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if data_table[-2][-1][2][0] == "1":
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if data_table[-2][-1][3][0] == "1":
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data_table[-1].append([
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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
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data_table[-2][-1][1],
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i,
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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
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data_table[-2][-1][2],
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data_table[-2][-1][3],
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"RG1+RG3"
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])
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data_table[-1].append([
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data_table[-1][-1][0],
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'0' + data_table[-1][-1][1][:-1], # 0.r(RG3)
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data_table[-1][-1][2][1:] + '0', # l(RG2).0
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i,
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data_table[-1][-1][1],
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'0' + data_table[-1][-1][2][:-1], # 0.r(RG3)
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data_table[-1][-1][3][1:] + '0', # l(RG2).0
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"0.r(RG3), l(RG2).0"
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])
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else:
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data_table[-1].append([
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data_table[-2][-1][0],
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'0' + data_table[-2][-1][1][:-1], # 0.r(RG3)
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data_table[-2][-1][2][1:] + '0', # l(RG2).0
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i,
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data_table[-2][-1][1],
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'0' + data_table[-2][-1][2][:-1], # 0.r(RG3)
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data_table[-2][-1][3][1:] + '0', # l(RG2).0
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"0.r(RG3), l(RG2).0"
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])
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return data_table
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return data_table, data_table[-1][-1][1][:-1]
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if __name__ == "__main__":
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x = int("0b" + input("X: "), 2)
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y = int("0b" + input("Y: "), 2)
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# a fully functional reference
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# implementation for this library
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# is provided below
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raw_x = input("X: ")
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raw_y = input("Y: ")
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if len(raw_x) == len(raw_y):
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n = len(raw_x)
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else:
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n = int(input("n: "))
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x = int("0b" + raw_x, 2)
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y = int("0b" + raw_y, 2)
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method = int(input("Method: "))
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dt = multiply(x, y, method)
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dt, result = multiply(n, x, y, method)
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from lib.prettytable import PrettyTable
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pt = PrettyTable()
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pt.field_names = ["RG1", "RG3", "RG2", "Operations"]
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pt.field_names = ["Iteration", "RG1", "RG3", "RG2", "Operations"]
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for i in dt[1:]:
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for i in dt:
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for j in range(len(i)):
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if j+1 == len(i):
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pt.add_row(i[j], divider = True)
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pt.add_row(i[j])
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print(pt)
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print(f"Result: {result}")
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