import numpy as np def convert_to_fixed(floating_point): # convert floating_point to fixed-point format # return fixed_point as a string of the binary representation of this converted number fin_int = int(floating_point*2**5) b = bin(fin_int) fixed_point = '' i = len(b) - 2 if fin_int > 0: fixed_point += '0' else: fixed_point += '1' while i < 8: fixed_point += '0' i += 1 for i in range(2, len(b)): fixed_point += b[i] return fixed_point print(convert_to_fixed(3.013)) and you want to store this number using the format. This will require bits. The process to convert a floating-point number into a fixed-point number can be described by the following steps: Multiply the float by : Round the result to the nearest integer. Your result should be . Convert this integer to binary representation, where the binary representation is stored as a string. You can use the bin() function. Just be aware that the format returned by bin() is not exactly the binary representation. For example, bin(24) = '0b11000' and bin(-24) = '-0b11000', but the binary representation of the number 24 is '11000'. If this string has less than bits, then pad the left with zeros: '11000' -> '00011000'. Else, store the right-most bits. Add the sign bit ('0' or '1') to the binary number on the left: '00011000'->'000011000' Task: Write a function that takes a floating-point number, converts it to fixed-point and returns a string containing the 9-bit binary representation of the fixed-point number in Q(3.5) format. Your code snippet should define the following function:
Question
import numpy as np
def convert_to_fixed(floating_point): # convert floating_point to fixed-point format # return fixed_point as a string of the binary representation of this converted number fin_int = int(floating_point*2**5) b = bin(fin_int) fixed_point = '' i = len(b) - 2 if fin_int > 0: fixed_point += '0' else: fixed_point += '1' while i < 8: fixed_point += '0' i += 1 for i in range(2, len(b)): fixed_point += b[i]
return fixed_point
print(convert_to_fixed(3.013))
and you want to store this number using the format. This will require bits. The process to convert a floating-point number into a fixed-point number can be described by the following steps:
Multiply the float by : Round the result to the nearest integer. Your result should be . Convert this integer to binary representation, where the binary representation is stored as a string. You can use the bin() function. Just be aware that the format returned by bin() is not exactly the binary representation. For example, bin(24) = '0b11000' and bin(-24) = '-0b11000', but the binary representation of the number 24 is '11000'. If this string has less than bits, then pad the left with zeros: '11000' -> '00011000'. Else, store the right-most bits. Add the sign bit ('0' or '1') to the binary number on the left: '00011000'->'000011000' Task: Write a function that takes a floating-point number, converts it to fixed-point and returns a string containing the 9-bit binary representation of the fixed-point number in Q(3.5) format.
Your code snippet should define the following function:
Solution
The text is written in Python language. Here is the function that converts a floating-point number to a fixed-point number in Q(3.5) format:
def float_to_fixed(floating_point):
# Step 1: Multiply the float by 2^5
multiplied = floating_point * (2**5)
# Step 2: Round the result to the nearest integer
rounded = round(multiplied)
# Step 3: Convert this integer to binary representation
binary = bin(rounded)[2:] # remove '0b' from the start
# Step 4: If this string has less than 8 bits, then pad the left with zeros
while len(binary) < 8:
binary = '0' + binary
# Step 5: Add the sign bit ('0' or '1') to the binary number on the left
if floating_point < 0:
binary = '1' + binary
else:
binary = '0' + binary
return binary
This function takes a floating-point number as input, converts it to a fixed-point number in Q(3.5) format, and returns a string containing the 9-bit binary representation of the fixed-point number.
Similar Questions
import numpy as np def convert_to_fixed(floating_point): # convert floating_point to fixed-point format # return fixed_point as a string of the binary representation of this converted number fin_int = int(floating_point*2**5) b = bin(fin_int) fixed_point = '' i = len(b) - 2 if fin_int > 0: fixed_point += '0' else: fixed_point += '1' while i < 8: fixed_point += '0' i += 1 for i in range(2, len(b)): fixed_point += b[i] return fixed_point print(convert_to_fixed(3.013)) and you want to store this number using the format. This will require bits. The process to convert a floating-point number into a fixed-point number can be described by the following steps: Multiply the float by : Round the result to the nearest integer. Your result should be . Convert this integer to binary representation, where the binary representation is stored as a string. You can use the bin() function. Just be aware that the format returned by bin() is not exactly the binary representation. For example, bin(24) = '0b11000' and bin(-24) = '-0b11000', but the binary representation of the number 24 is '11000'. If this string has less than bits, then pad the left with zeros: '11000' -> '00011000'. Else, store the right-most bits. Add the sign bit ('0' or '1') to the binary number on the left: '00011000'->'000011000' Task: Write a function that takes a floating-point number, converts it to fixed-point and returns a string containing the 9-bit binary representation of the fixed-point number in Q(3.5) format. Your code snippet should define the following function:
What is a correct method to round decimals in NumPy?np.fix()np.trunc()np.around()All the other 3 are rounding methods in NumPyNext ❯
How do you define a floating-point number in Python?
What is the purpose of NumPy in Python?BothTo do numerical calculationsTo do scientific computingNone of the above
What is the purpose of the np.random.rand() function in NumPy?To generate random complex numbersTo generate a sequence of evenly spaced numbersTo generate random floats between 0 and 1To generate random integers
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