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Unfortunately the printing instruction of a code was written without an end-of-the-line character and one every 26 numbers consists of two numbers joined together. The following is a code that shows an example of such behaviour; at the end there is a fragment of the original database.
import numpy as np
for _ in range(2):
A=np.random.rand()+np.random.randint(0,100)
B=np.random.rand()+np.random.randint(0,100)
C=np.random.rand()+np.random.randint(0,100)
D=np.random.rand()+np.random.randint(0,100)
with open('file.txt','a') as f:
f.write(f'{A},{B},{C},{D}')
And thus the output example file looks very similar to what follows:
40.63358599010553,53.86722741700399,21.800795158561158,13.95828176311762557.217562728494684,2.626308403991772,4.840593988487278,32.401778122213486
With the issue being that there are two numbers 'printed together', in the example they were as follows:
13.95828176311762557.217562728494684
So you cannot know if they should be
13.958281763117625, 57.217562728494684
or
13.9582817631176255, 7.217562728494684
Please understand that in this case they are only two options, but the problem that I want to address considers 'unbounded numbers' which are type Python's "float" (where 'unbounded' means in a range we don't know e.g. in the range +- 1E4)
Can the original numbers be reconstructed based on "some" python internal behavior I'm missing?
Actual data with periodicity 27 (i.e. the 26th number consists of 2 joined together):
0.9221878978925224, 0.9331311610066017,0.8600582424784715,0.8754578588852764,0.8738648974725404, 0.8897837559800233,0.6773502027673041,0.736325377603136,0.7956454122424133, 0.8083168444596229,0.7089031184165164, 0.7475306242508357,0.9702361286847581, 0.9900689384633811,0.7453878225174624, 0.7749000030576826,0.7743879170108678, 0.8032590543649807,0.002434,0.003673,0.004194,0.327903,11.357262,13.782266,20.14374,31.828905,33.9260060.9215201173775437, 0.9349343132442707,0.8605282244327555,0.8741626682026793,0.8742163597524663, 0.8874673376386358,0.7109322043854609,0.7376362393985332,0.796158275345
To expand my comment into an actual answer:
We do have some information - An IEEE-754 standard float only has 32 bits of precision, some of which is taken up by the mantissa (not all numbers can be represented by a float). For datasets like yours, they're brushing up against the edge of that precision.
We can make that work for us - we just need to test whether the number can, in fact, be represented by a float, at each possible split point. We can abuse strings for this, by testing num_str == str(float(num_str)) (i.e. a string remains the same after being converted to a float and back to a string)
If your number is able to be represented exactly by the IEEE float standard, then the before and after will be equal
If the number cannot be represented exactly by the IEEE float standard, it will be coerced into the nearest number that the float can represent. Obviously, if we then convert this back to a string, will not be identical to the original.
Here's a snippet, for example, that you can play around with
def parse_number(s: str) -> List[float]:
if s.count('.') == 2:
first_decimal = s.index('.')
second_decimal = s[first_decimal + 1:].index('.') + first_decimal + 1
split_idx = second_decimal - 1
for i in range(second_decimal - 1, first_decimal + 1, -1):
a, b = s[:split_idx], s[split_idx:]
if str(float(a)) == a and str(float(b)) == b:
return [float(a), float(b)]
# default to returning as large an a as possible
return [float(s[:second_decimal - 1]), float(s[second_decimal - 1:])]
else:
return [float(s)]
parse_number('33.9260060.9215201173775437')
# [33.926006, 0.9215201173775437]
# this is the only possible combination that actually works for this particular input
Obviously this isn't foolproof, and for some numbers there may not be enough information to differentiate the first number from the second. Additionally, for this to work, the tool that generated your data needs to have worked with IEEE standards-compliant floats (which does appear to be the case in this example, but may not be if the results were generated using a class like Decimal (python) or BigDecimal (java) or something else).
Some inputs might also have multiple possibilities. In the above snippet I've biased it to take the longest possible [first number], but you could modify it to go in the opposite order and instead take the shortest possible [first number].
Yes, you have one available weapon: you're using the default precision to display the numbers. In the example you cite, there are 15 digits after the decimal point, making it easy to reconstruct the original numbers.
Let's take a simple case, where you have only 3 digits after the decimal point. It's trivial to separate
13.95857.217
The formatting requires a maximum of 2 digits before the decimal point, and three after.
Any case that has five digits between the points, is trivial to split.
13.958 57.217
However, you run into the "trailing zero" problem in some cases. If you see, instead
13.9557.217
This could be either
13.950 57.217
or
13.955 07.217
Your data do not contain enough information to differentiate the two cases.
I am using Python, and I have a problem, I want to do a program tha can count from 1 to infinite, to know how much is the infinite.
Here is my code :
a=0
for i in range(1, 10e+99):
a += 1
print (a)
but it says " 'float' object cannot be interpreted as an integer "
whereas 10e+99 is not a float
help me please
Per the Python 2 documentation and Python 3 documentation, range requires integer arguments.
In IEEE-754 32-bit binary floating-point, the largest representable finite number is about 3.4028e38. When converting numerals, such as 1e99 in source code, to this format, any number greater than or equal to 2128−2104 (340,282,377,062,143,265,289,209,819,405,393,854,464) will be converted to infinity, assuming the common round-to-nearest-ties-to-even method is used. Because of this, 10e+99 (which stands for 10•1099 and hence 10100) would act like infinity. However, Python implementations more typically use IEEE-754 64-bit binary floating-point, in which the largest representable finite number is 21024−2971, and 10e99 acts as a finite number.1 Thus, to get infinity, you would need around 1e309.
It is not humanly possible to test whether a loop incrementing by 1 from 1 to 10e99 will produce infinity because the total computing power available to humans is only around 1030 additions per year (for a loose sense of “around”, some orders of magnitude). This is insufficient to count to the limit of 32-bit floating-point finite numbers, let alone that of the 64-bit floating-point numbers.
If the arithmetic were done in a floating-point format, it would never reach infinity even with unlimited computing power because, once the sum reached 253 in IEEE-754 64-bit binary, adding 1 would not change the number; 253 would be produced in each iteration. This is because IEEE-754 64-bit binary has only 53 bits available for the significand, so 253+1 is not representable. The nearest representable values are 253 and 253+2. When arithmetic is performed, the exact real-number result is by default rounded to the nearest representable value, with ties rounded to the number with the even low bit in its significand. When 1 is added to 253 the real-number result 253+1 is rounded to 253, and the sum thus stays at 253 for all future iterations.
Footnote
1 The representable value nearest 10100 is 10,000,000,000,000,000,159,028,911,097,599,180,468,360,808,563,945,281,389,781,327,557,747,838,772,170,381,060,813,469,985,856,815,104.
The problem arises because the range() function takes an int, whereas 10e+99 is indeed a float. While 10e+99 is of course not infinity, and therefore you shouldn't expect infinity to pop up anywhere during the execution of your program, if you really wanted to get your for loop to work as it is you could simply do
a=0
for i in range(1, int(10e+99)):
a += 1
print (a)
As other users have pointed out, I would however rethink your strategy entirely: using a range-based for loop to "find out" the value of infinity just doesn't work. Infinity is not a number.
Perhaps you meant your program to go on forever:
a = 0
while True:
a += 1
print(a)
In my head when I see while True: I replace it with 'forever'.
With is code you can check you variable is infinity or not.
import math
infinity = float('inf')
a = 99999999999999999999999999999999
if a > infinity:
print('Your number is an infinity number')
else:
print('Your number is not an infinity number')
#or you can check with math.isinf
print('Your number is Infinity: ',math.isinf(infinity ))
# Also infinity can be both positive and negative
Note: infinity is infinity that has no end, whatever your value or number you enter it will always return false.
Here is what is going to happen if you correct and execute your program:
a=0
for i in range(1, 10**100):
a += 1
print (a)
Suppose you have a super efficient python virtual machine (everyone knows how efficient they are...).
Suppose you have a very efficient implementation of (unbounded) large integers.
Suppose each loop takes a few machine cycles to print those numbers in decimal form (say only 1000 which is well under reality).
Suppose each cycle takes approximately 1.0e-10 s (10GHz) which means having an implementation of print taking advantage of parallelism.
With those irrealistic hypothesis, that's already 10^93 s necessary for the program to complete.
The age of universe is estimated to be less than 10^18 s. Whaouh! It gonna be long.
Now let's compute the energy it's gonna take on a base of 400W computer.
Assuming that all Sun matter (2e30 kg) can be converted into electrical power for your computer (thru E=m c^2), you are going to consume about 2 10^48 equivalent of Sun to perform this computation.
Before you hit return, I kindly ask you: think twice! Save the universe!
So I have this long number (i.e: 1081546747036327937), and when I cleaned up my data in pandas dataframe, I didn't realize Python converted it to complex number (i.e: 1.081546747036328e+18).
I saved this one as csv. The problem is, I accidentally deleted the original file, tried to recover it but no success this far, so...
is there a way to convert this complex number back to their original number?
I tried to convert it to str using str(data) but it stays the same (i.e: 1.081546747036328e+18).
As you were said in comment, this is not a complex number, but a floating point number. You can certainly convert it to a (long) integer, but you cannot be sure to get back the initial number.
In your example:
i = 1081546747036327937
f = float(i)
j = int(f)
print(i, f, j, j-i)
will display:
1081546747036327937 1.081546747036328e+18 1081546747036327936 -1
This is because floating points only have a limited accuracy and rounding errors are to be expected with large integers when the binary representation requires more than 53 bits.
As can be read here, complex numbers are a sum of a real part and an imaginary part.
3+1j is a complex number with the real value 3 and a complex value 1
You have a scientific notation (type is float), which is just an ordinary float multiplied by the specified power of 10.
1e10 equals to 1 times ten to the power of ten
To convert this to int, you can just convert with int(number). For more information about python data types, you can take a look here
I am looking for a way in python to perform right shift and bit masking on a binary number which has a fraction part as well. For e.g., if there are 1 integer and 2 fraction bits in the number, then number 0b101 corresponds to 1.25 in decimal. First, I want to know the pythonic way to represent this number in python.
Second, I want to perform 1 right shift on this number (0b101>>1) so that the resultant number will be 0b010 which will be 0.5 in decimal. Is there an intrinsic and pythonic way in python to perform this operation. Similarly, how to mask and get a specific bit from the binary number?
Presently, for shift I am multiplying the number by 2**-x, x is the number of right shifts. I cannot think a similar operation I can perform for bit mask.
If you really must get directly at the internal representation of a float you can use struct, like this:
>>> import struct
>>> a = 1.25
>>> b = struct.pack('>d',a)
>>> b
b'?\xf4\x00\x00\x00\x00\x00\x00' # the ? means \x3f, leftmost 7 bits of exponent
>>> a.hex()
'0x1.4000000000000p+0'
You can mask the bit you want out of the bytestring that struct.pack() returns.
[edit] The question mark representing \x3f is because the default output representation of a bytestring is a string and Python will where possible show an ascii character, not two hex digits.
[edit] This representation is in principle platform-dependent, but in practice it isn't, because virtually every computer (even IBM mainframes nowadays) has a floating-point processor that uses this format.
Finding out which bit you want may be something of a challenge.
>>> c = struct.pack('>d',a/2)
>>> c
b'?\xe4\x00\x00\x00\x00\x00\x00'
>>> (a/2).hex()
'0x1.4000000000000p-1'
As you can see, division by 2 is not quite the simple one-bit shift to the right that your question seems to suggest you are expecting. In this case, the division by 2 has decremented the exponent by 1 (from 0x3ff to 0x3fe; 1023 to 1022) and left the bit pattern of the fraction (0x4000) unchanged. The exponent appears large because it is biased by 1023.
The main difficulties are
Sign, exponent and fraction don't align to byte boundaries, but to nybble boundaries (sign plus exponent: 12 bits; fraction: 52 bits)
The number is normalized so that it has no leading zeroes (much as scientific notation in decimal is normalized so that it has no leading zeroes) and, since everyone knows it's there, the leading 1 is not stored.
I can recommend the Wikpedia article on this subject: it has lots of useful examples.
But I suspect that you don't really want to get at the internal representation of a float. Instead, you want a fixed-point binary class, without pesky binary exponents, that works much the same as you would do it on paper, and where division by a power of 2 really does reflect as a shift of so many bits to the right.
Depending on how much work you want to put into it, you could do this by defining a FixedBinary class as a subclass of numbers.Real, with the integer portion internally represented by one int and the fractional component by another int, and the sign by a third int, so that 1.25 would be represented as (1, int(0.25 * 65536), +1) (or some other power of 2).
This also shows you the simplest way to get a bit representation of your fraction.
[edit] I recommend storing the sign separately. You could store it in the integer portion, or the fraction, or both, but all have disadvantages.
If you store it in the sign of the fraction, the twos-complement
representation of negative integers will give you difficulty when
you want to mask your bits.
If you don't store it in the sign of the fraction there will be no way to
represent -0.5.
If you don't store it in the sign of the integer portion there will be no way to represent -1.0.
A multiplicand of 65536 will give you 4 decimal digits of accuracy. You can increase it if you want more. I also recommend that you store your fraction in the rightmost bits and simply ignore the leftmost bits. In other words, be content with the binary point being in the middle of the int, don't insist on it being on the left. That is because you will need headroom to the left of the binary point when you do multiplication.
Implementing your own numeric class is a considerable amount of work, though.
You can work using fxpmath.
Info about this package is at:
https://github.com/francof2a/fxpmath
For your example:
from fxpmath import Fxp
x = Fxp('0b0101', signed=True, n_word=4, n_frac=2)
print(x)
y = x >> 1
print(y)
# example of AND mask
z = x & Fxp('0b0110', signed=True, n_word=4, n_frac=2)
print(z.bin())
outputs:
1.25
0.5
0100
Alrighty, first post here, so please forgive and ignore if the question is not workable;
Background:
I'm in computer science 160. I haven't taken any computer related classes since high school, so joining this class was a big shift for me. It all seemed very advanced. We have been working in Python and each week we are prompted to write a program.
I have been working with this problem for over a week and am having a hard time even starting.
The prompt is to read an integer containing only 1's and 0's,
process the binary number digit by digit and report the decimal equivalent. Now, I have gotten some tips from a classmate and it sent me at least in a direction.
Set up a couple of counters;
using the % operator to check the remainder of the number divided by 2, and slicing off the last number (to the right) to move on to and process the next digit.
I am having an incredibly hard time wrapping my head around what formula to use on the binary digits themselves which will convert the number to decimal.
setbitval = 0
counter = 0
user = int(input("enter a binary value. "))
if user % 2 == 1:
user = (user/10) - .1
setbitval += 1
This is all I've got so far.. My thinking is getting in the way. I've searched and searched, even through these forums.
Any information or thoughts are extremely appreciated,
T
Edit: okay guys, everyone's help has been extremely useful but I'm having a problem checking if the user input is not a binary number.
for i in reversed(bits):
decimal += 2**counter * int(i)
counter += 1
This is the formula someone here gave me and I've been trying different iterations of "for i in bits: if i in bits: != 0 or 1" and also "if i in bits: >= 1 or <=0".
Any thoughts?
you can use this code:
binary= raw_input("Binary: ")
d= int(binary, 2)
print d
To convert binary value to decimal you need to do the following:
Take the least significant bit and multiply it by 2^0, then take the next least significant beat and multiply it by 2^1, next one by 2^2 and so on...
Let's say, for example you need to convert a number 1010 to decimal:
You would have 0*2^0 + 1*2^1 + 0*2^2 + 1*2^3 = 0 + 2 + 0 + 8 = 10
So in your python code, you need to:
read the int that the user inputted (representing the binary value).
convert that int and convert it to string, so you can break it into list of digits
make a list of digits from the string you created (a list int python can be created from a string not an int, that's why you need the conversion to string first)
go trough that list of bits in reverse and multiply every bit by 2^k, k being the counter starting from 0
Here's the code that demonstrates what I just tried to explain:
user_input = int(input("enter a binary value"))
bits = list(str(user_input))
decimal = 0
counter = 0
for i in reversed(bits):
decimal += 2**counter * int(i)
counter+=1
print 'The decimal value is: ', decimal
I'll agree this is close to the "code this for me" territory, but I'll try to answer in a way that gets you on the right track, instead of just posting a working code snippet.
A simple way of doing this is just to use int()'s base argument, but I'm guessing that is disallowed.
You already have a way of testing the current bit in your question, namely checking whether n % 2 == 1. If this is the case, we need to add a power of two.
Then, we need some way of going to the next bit. In binary, we would use bit shifts, but sadly, we don't have those. a >> b is equivalent to a // (2**b) - can you write a decimal equivalent to that?
You also need to keep a counter of which power of two the current bit represents, a loop, and some way of detecting an end condition. Those are left as exercises to the reader.
I’d recommend reading the following articles on Wikipedia:
https://en.wikipedia.org/wiki/Radix
https://en.wikipedia.org/wiki/Binary_number
The first one gives you an idea how the numeral systems work in general and the second one explains and shows the formula to convert between binary and decimal systems.
Try to implement the solution after reading this. That’s what I did when I dealt with this problem. If that doesn’t help, let me know and I’ll post the code.
Hopefully, this code clarifies things a bit.
x = input("Enter binary number: ").strip()
decimal = 0
for i in range(len(x)):
decimal += int(x[i]) * 2**abs((i - (len(x) - 1)))
print(decimal)
This code takes in a binary number as a string, converts it to a decimal number and outputs it as an integer. The procedure is the following:
1st element of binary number * 2^(length of binary number - 1)
2nd element of binary number * 2^(length of binary number - 2)
and so on till we get to the last element and ...2^0
If we take number 10011, the conversion using this formula will look like this:
1*2^4 + 0*2^3 + 0*2^2 + 1*2^1 + 1*2^0, which equals to 19.
This code, however, assumes that the binary number is valid. Let me know if it helps.
Another implementation using while loop might look like this. Maybe it'll be easier to understand than the code with the for loop.
x = input("Enter binary number: ").strip()
decimal = 0
index = 0
exp = len(x) - 1
while index != len(x):
decimal += int(x[index]) * 2**exp
index += 1
exp -= 1
print(decimal)
In this one we start from the beginning of the number with the highest power, which is length of binary number minus one, we loop through the number, lowering the power and changing index.
Regarding checking if number is binary.
Try using helper function to determine if number is binary and then insert this function inside your main function. For example:
def is_binary(x):
""" Returns True if number x is binary and False otherwise.
input: x as a string
"""
for i in list(x):
if i not in ["1", "0"]:
return False
return True
def binary_decimal(x):
""" Converts binary to decimal.
input: binary number x as a string
output: decimal number as int
"""
if not is_binary(x):
return "Number is invalid"
decimal = 0
for i in range(len(x)):
decimal += int(x[i]) * 2**abs((i - (len(x) - 1)))
return decimal
The first function checks if number consists only of ones and zeros and the second function actually converts your number only if it's binary according to the first function.
You can also try using assert statement or try / except if you'd better raise an error if number is not binary instead of simply printing the message.
Of course, you can implement this solution without any functions.