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Python: How to round numbers smaller than 1 adaptively with specified precision?

I usually use
x = round(x, 3)
to round a number to the precision of 3 digits. Now I have this array:
[-1.10882605e-04 -2.01874994e-05 3.24209095e-05 -1.56917988e-05
-4.61406358e-05 1.99080610e-05 7.04079594e-05 2.64600122e-05
-3.53022316e-05 1.50542793e-05]
And using the same code just flattens everything down to 0. What I would like to have though is a function that gives me the most significant 3 digits rounded like it usually works for numbers larger than 1. Like this:
special_round(0.00034567, 3)
=
0.000346
Any idea how this could be done? Thanks!

Here is a solution that figures out the order of magnitude and does an elment wise rounding.
Note that this will only work correctly for values < 1 and > -1, which I guess is a valid assumption regarding your example data.
import numpy as np
a = np.array([-1.10882605e-04, -2.01874994e-05, 3.24209095e-05, -1.56917988e-05,
-4.61406358e-05, 1.99080610e-05, 7.04079594e-05 , 2.64600122e-05,
-3.53022316e-05 , 1.50542793e-05])
def special_round(vec):
exponents = np.floor(np.log10(np.abs(vec))).astype(int)
return np.stack([np.round(v, decimals=-e+3) for v, e in zip(vec, exponents)])
b = special_round(a)
>>> array([-1.109e-04, -2.019e-05, 3.242e-05, -1.569e-05, -4.614e-05,
1.991e-05, 7.041e-05, 2.646e-05, -3.530e-05, 1.505e-05])

Problem is, numbers you provided are starting to be so small that you are approaching limit of floating point precision, thus some artifacts show up seemingly for no reason.
def special_round(number, precision):
negative = number < 0
number = abs(number)
i = 0
while number <= 1 or number >= 10:
if number <= 1:
i += 1
number *= 10
else:
i += -1
number /= 10
rounded = round(number, precision)
if negative:
rounded = -rounded
return rounded * (10 ** -i)
Output:
[-0.0001109, -2.019e-05, 3.2420000000000005e-05, -1.569e-05, -4.614e-05, 1.9910000000000004e-05, 7.041000000000001e-05, 2.646e-05, -3.5300000000000004e-05, 1.505e-05]

You can do so by creating a specific function using the math package:
from math import log10 , floor
import numpy as np
def round_it(x, sig):
return round(x, sig-int(floor(log10(abs(x))))-1)
a = np.array([-1.10882605e-04, -2.01874994e-05, 3.24209095e-05, -1.56917988e-05,
-4.61406358e-05, 1.99080610e-05, 7.04079594e-05, 2.64600122e-05,
-3.53022316e-05, 1.50542793e-05])
round_it_np = np.vectorize(round_it) # vectorize the function to apply on numpy array
round_it_np(a, 3) # 3 is rounding with 3 significant digits
This will result in
array([-1.11e-04, -2.02e-05, 3.24e-05, -1.57e-05, -4.61e-05, 1.99e-05,
7.04e-05, 2.65e-05, -3.53e-05, 1.51e-05])

Here is a solution:
from math import log10, ceil
def special_round(x, n) :
lx = log10(abs(x))
if lx >= 0 : return round(x, n)
return round(x, n-ceil(lx))
for x in [10.23456, 1.23456, 0.23456, 0.023456, 0.0023456] :
print (x, special_round(x, 3))
print (-x, special_round(-x, 3))
Output:
10.23456 10.235
-10.23456 -10.235
1.23456 1.235
-1.23456 -1.235
0.23456 0.235
-0.23456 -0.235
0.023456 0.0235
-0.023456 -0.0235
0.0023456 0.00235
-0.0023456 -0.00235

You can use the common logarithm (provided by the built-in math module) to calculate the position of the first significant digit in your number (with 2 representing the hundreds, 1 representing the tens, 0 representing the ones, -1 representing the 0.x, -2 representing the 0.0x and so on...). Knowing the position of the first significant digit, you can use it to properly round the number.
import math
def special_round(n, significant_digits=0):
first_significant_digit = math.ceil((math.log10(abs(n))))
round_digits = significant_digits - first_significant_digit
return round(n, round_digits)
>>> special_round(0.00034567, 3)
>>> 0.000346

Print pi to a number of decimal places

One of the challenges on w3resources is to print pi to 'n' decimal places. Here is my code:
from math import pi
fraser = str(pi)
length_of_pi = []
number_of_places = raw_input("Enter the number of decimal places you want to
see: ")
for number_of_places in fraser:
length_of_pi.append(str(number_of_places))
print "".join(length_of_pi)
For whatever reason, it automatically prints pi without taking into account of any inputs. Any help would be great :)

The proposed solutions using np.pi, math.pi, etc only only work to double precision (~14 digits), to get higher precision you need to use multi-precision, for example the mpmath package
>>> from mpmath import mp
>>> mp.dps = 20 # set number of digits
>>> print(mp.pi)
3.1415926535897932385
Using np.pi gives the wrong result
>>> format(np.pi, '.20f')
3.14159265358979311600
Compare to the true value:
3.14159265358979323846264338327...

Why not just format using number_of_places:
''.format(pi)
>>> format(pi, '.4f')
'3.1416'
>>> format(pi, '.14f')
'3.14159265358979'
And more generally:
>>> number_of_places = 6
>>> '{:.{}f}'.format(pi, number_of_places)
'3.141593'
In your original approach, I guess you're trying to pick a number of digits using number_of_places as the control variable of the loop, which is quite hacky but does not work in your case because the initial number_of_digits entered by the user is never used. It is instead being replaced by the iteratee values from the pi string.

For example the mpmath package
from mpmath import mp
def a(n):
mp.dps=n+1
return(mp.pi)

Great answers! there are so many ways to achieve this. Check out this method I used below, it works any number of decimal places till infinity:
#import multp-precision module
from mpmath import mp
#define PI function
def pi_func():
while True:
#request input from user
try:
entry = input("Please enter an number of decimal places to which the value of PI should be calculated\nEnter 'quit' to cancel: ")
#condition for quit
if entry == 'quit':
break
#modify input for computation
mp.dps = int(entry) +1
#condition for input error
except:
print("Looks like you did not enter an integer!")
continue
#execute and print result
else:
print(mp.pi)
continue
Good luck Pal!

Your solution appears to be looping over the wrong thing:
for number_of_places in fraser:
For 9 places, this turns out be something like:
for "9" in "3.141592653589793":
Which loops three times, one for each "9" found in the string. We can fix your code:
from math import pi
fraser = str(pi)
length_of_pi = []
number_of_places = int(raw_input("Enter the number of decimal places you want: "))
for places in range(number_of_places + 1): # +1 for decimal point
length_of_pi.append(str(fraser[places]))
print "".join(length_of_pi)
But this still limits n to be less than the len(str(math.pi)), less than 15 in Python 2. Given a serious n, it breaks:
> python test.py
Enter the number of decimal places you want to see: 100
Traceback (most recent call last):
File "test.py", line 10, in <module>
length_of_pi.append(str(fraser[places]))
IndexError: string index out of range
>
To do better, we have to calculate PI ourselves -- using a series evaluation is one approach:
# Rewrite of Henrik Johansson's (Henrik.Johansson#Nexus.Comm.SE)
# pi.c example from his bignum package for Python 3
#
# Terms based on Gauss' refinement of Machin's formula:
#
# arctan(x) = x - (x^3)/3 + (x^5)/5 - (x^7)/7 + ...
from decimal import Decimal, getcontext
TERMS = [(12, 18), (8, 57), (-5, 239)] # ala Gauss
def arctan(talj, kvot):
"""Compute arctangent using a series approximation"""
summation = 0
talj *= product
qfactor = 1
while talj:
talj //= kvot
summation += (talj // qfactor)
qfactor += 2
return summation
number_of_places = int(input("Enter the number of decimal places you want: "))
getcontext().prec = number_of_places
product = 10 ** number_of_places
result = 0
for multiplier, denominator in TERMS:
denominator = Decimal(denominator)
result += arctan(- denominator * multiplier, - (denominator ** 2))
result *= 4 # pi == atan(1) * 4
string = str(result)
# 3.14159265358979E+15 => 3.14159265358979
print(string[0:string.index("E")])
Now we can take on a large value of n:
> python3 test2.py
Enter the number of decimal places you want: 100
3.141592653589793238462643383279502884197169399375105820974944592307816406286208998628034825342117067
>

This is what I did, really elementary but works (max 15 decimal places):
pi = 22/7
while True:
n = int(input('Please enter how many decimals you want to print: '))
if n<=15:
print('The output with {} decimal places is: '.format(n))
x = str(pi)
print(x[0:n+2])
break
else:
print('Please enter a number between 0 and 15')

As this question already has useful answers, I would just like to share how i created a program for the same purpose, which is very similar to the one in the question.
from math import pi
i = int(input("Enter the number of decimal places: "))
h = 0
b = list()
for x in str(pi):
h += 1
b.append(x)
if h == i+2:
break
h = ''.join(b)
print(h)
Thanks for Reading.

Why not just use:
import numpy as np
def pidecimal(round):
print(np.round(np.pi, round))

Python setting Decimal Place range without rounding?

How can I take a float variable, and control how far out the float goes without round()? For example.
w = float(1.678)
I want to take x and make the following variables out of it.
x = 1.67
y = 1.6
z = 1
If I use the respective round methods:
x = round(w, 2) # With round I get 1.68
y = round(y, 1) # With round I get 1.7
z = round(z, 0) # With round I get 2.0
It's going to round and alter the numbers to the point where there no use to me. I understand this is the point of round and its working properly. How would I go about getting the information that I need in the x,y,z variables and still be able to use them in other equations in a float format?

You can do:
def truncate(f, n):
return math.floor(f * 10 ** n) / 10 ** n
testing:
>>> f=1.923328437452
>>> [truncate(f, n) for n in range(7)]
[1.0, 1.9, 1.92, 1.923, 1.9233, 1.92332, 1.923328]

A super simple solution is to use strings
x = float (str (w)[:-1])
y = float (str (w)[:-2])
z = float (str (w)[:-3])
Any of the floating point library solutions would require you dodge some rounding, and using floor/powers of 10 to pick out the decimals can get a little hairy by comparison to the above.

Integers are faster to manipulate than floats/doubles which are faster than strings. In this case, I tried to get time with both approach :
timeit.timeit(stmt = "float(str(math.pi)[:12])", setup = "import math", number = 1000000)
~1.1929605630000424
for :
timeit.timeit(stmt = "math.floor(math.pi * 10 ** 10) / 10 ** 10", setup = "import math", number = 1000000)
~0.3455968870000561
So it's safe to use math.floor rather than string operation on it.

If you just need to control the precision in format
pi = 3.14159265
format(pi, '.3f') #print 3.142 # 3 precision after the decimal point
format(pi, '.1f') #print 3.1
format(pi, '.10f') #print 3.1415926500, more precision than the original
If you need to control the precision in floating point arithmetic
import decimal
decimal.getcontext().prec=4 #4 precision in total
pi = decimal.Decimal(3.14159265)
pi**2 #print Decimal('9.870') whereas '3.142 squared' would be off
--edit--
Without "rounding", thus truncating the number
import decimal
from decimal import ROUND_DOWN
decimal.getcontext().prec=4
pi*1 #print Decimal('3.142')
decimal.getcontext().rounding = ROUND_DOWN
pi*1 #print Decimal('3.141')

I think the easiest answer is :
from math import trunc
w = 1.678
x = trunc(w * 100) / 100
y = trunc(w * 10) / 10
z = trunc(w)

also this:
>>> f = 1.678
>>> n = 2
>>> int(f * 10 ** n) / 10 ** n
1.67

Easiest way to get integer:
series_col.round(2).apply(lambda x: float(str(x).split(".",1)[0]))

drop trailing zeros from decimal

I have a long list of Decimals and that I have to adjust by factors of 10, 100, 1000,..... 1000000 depending on certain conditions. When I multiply them there is sometimes a useless trailing zero (though not always) that I want to get rid of. For example...
from decimal import Decimal
# outputs 25.0, PROBLEM! I would like it to output 25
print Decimal('2.5') * 10
# outputs 2567.8000, PROBLEM! I would like it to output 2567.8
print Decimal('2.5678') * 1000
Is there a function that tells the decimal object to drop these insignificant zeros? The only way I can think of doing this is to convert to a string and replace them using regular expressions.
Should probably mention that I am using python 2.6.5
EDIT
senderle's fine answer made me realize that I occasionally get a number like 250.0 which when normalized produces 2.5E+2. I guess in these cases I could try to sort them out and convert to a int

You can use the normalize method to remove extra precision.
>>> print decimal.Decimal('5.500')
5.500
>>> print decimal.Decimal('5.500').normalize()
5.5
To avoid stripping zeros to the left of the decimal point, you could do this:
def normalize_fraction(d):
normalized = d.normalize()
sign, digits, exponent = normalized.as_tuple()
if exponent > 0:
return decimal.Decimal((sign, digits + (0,) * exponent, 0))
else:
return normalized
Or more compactly, using quantize as suggested by user7116:
def normalize_fraction(d):
normalized = d.normalize()
sign, digit, exponent = normalized.as_tuple()
return normalized if exponent <= 0 else normalized.quantize(1)
You could also use to_integral() as shown here but I think using as_tuple this way is more self-documenting.
I tested these both against a few cases; please leave a comment if you find something that doesn't work.
>>> normalize_fraction(decimal.Decimal('55.5'))
Decimal('55.5')
>>> normalize_fraction(decimal.Decimal('55.500'))
Decimal('55.5')
>>> normalize_fraction(decimal.Decimal('55500'))
Decimal('55500')
>>> normalize_fraction(decimal.Decimal('555E2'))
Decimal('55500')

There's probably a better way of doing this, but you could use .rstrip('0').rstrip('.') to achieve the result that you want.
Using your numbers as an example:
>>> s = str(Decimal('2.5') * 10)
>>> print s.rstrip('0').rstrip('.') if '.' in s else s
25
>>> s = str(Decimal('2.5678') * 1000)
>>> print s.rstrip('0').rstrip('.') if '.' in s else s
2567.8
And here's the fix for the problem that #gerrit pointed out in the comments:
>>> s = str(Decimal('1500'))
>>> print s.rstrip('0').rstrip('.') if '.' in s else s
1500

Answer from the Decimal FAQ in the documentation:
>>> def remove_exponent(d):
... return d.quantize(Decimal(1)) if d == d.to_integral() else d.normalize()
>>> remove_exponent(Decimal('5.00'))
Decimal('5')
>>> remove_exponent(Decimal('5.500'))
Decimal('5.5')
>>> remove_exponent(Decimal('5E+3'))
Decimal('5000')

Answer is mentioned in FAQ (https://docs.python.org/2/library/decimal.html#decimal-faq) but does not explain things.
To drop trailing zeros for fraction part you should use normalize:
>>> Decimal('100.2000').normalize()
Decimal('100.2')
>> Decimal('0.2000').normalize()
Decimal('0.2')
But this works different for numbers with leading zeros in sharp part:
>>> Decimal('100.0000').normalize()
Decimal('1E+2')
In this case we should use `to_integral':
>>> Decimal('100.000').to_integral()
Decimal('100')
So we could check if there's a fraction part:
>>> Decimal('100.2000') == Decimal('100.2000').to_integral()
False
>>> Decimal('100.0000') == Decimal('100.0000').to_integral()
True
And use appropriate method then:
def remove_exponent(num):
return num.to_integral() if num == num.to_integral() else num.normalize()
Try it:
>>> remove_exponent(Decimal('100.2000'))
Decimal('100.2')
>>> remove_exponent(Decimal('100.0000'))
Decimal('100')
>>> remove_exponent(Decimal('0.2000'))
Decimal('0.2')
Now we're done.

Use the format specifier %g. It seems remove to trailing zeros.
>>> "%g" % (Decimal('2.5') * 10)
'25'
>>> "%g" % (Decimal('2.5678') * 1000)
'2567.8'
It also works without the Decimal function
>>> "%g" % (2.5 * 10)
'25'
>>> "%g" % (2.5678 * 1000)
'2567.8'

I ended up doing this:
import decimal
def dropzeros(number):
mynum = decimal.Decimal(number).normalize()
# e.g 22000 --> Decimal('2.2E+4')
return mynum.__trunc__() if not mynum % 1 else float(mynum)
print dropzeros(22000.000)
22000
print dropzeros(2567.8000)
2567.8
note: casting the return value as a string will limit you to 12 significant digits

Slightly modified version of A-IV's answer
NOTE that Decimal('0.99999999999999999999999999995').normalize() will round to Decimal('1')
def trailing(s: str, char="0"):
return len(s) - len(s.rstrip(char))
def decimal_to_str(value: decimal.Decimal):
"""Convert decimal to str
* Uses exponential notation when there are more than 4 trailing zeros
* Handles decimal.InvalidOperation
"""
# to_integral_value() removes decimals
if value == value.to_integral_value():
try:
value = value.quantize(decimal.Decimal(1))
except decimal.InvalidOperation:
pass
uncast = str(value)
# use exponential notation if there are more that 4 zeros
return str(value.normalize()) if trailing(uncast) > 4 else uncast
else:
# normalize values with decimal places
return str(value.normalize())
# or str(value).rstrip('0') if rounding edgecases are a concern

You could use :g to achieve this:
'{:g}'.format(3.140)
gives
'3.14'

This should work:
'{:f}'.format(decimal.Decimal('2.5') * 10).rstrip('0').rstrip('.')

Just to show a different possibility, I used to_tuple() to achieve the same result.
def my_normalize(dec):
"""
>>> my_normalize(Decimal("12.500"))
Decimal('12.5')
>>> my_normalize(Decimal("-0.12500"))
Decimal('-0.125')
>>> my_normalize(Decimal("0.125"))
Decimal('0.125')
>>> my_normalize(Decimal("0.00125"))
Decimal('0.00125')
>>> my_normalize(Decimal("125.00"))
Decimal('125')
>>> my_normalize(Decimal("12500"))
Decimal('12500')
>>> my_normalize(Decimal("0.000"))
Decimal('0')
"""
if dec is None:
return None
sign, digs, exp = dec.as_tuple()
for i in list(reversed(digs)):
if exp >= 0 or i != 0:
break
exp += 1
digs = digs[:-1]
if not digs and exp < 0:
exp = 0
return Decimal((sign, digs, exp))

Why not use modules 10 from a multiple of 10 to check if there is remainder? No remainder means you can force int()
if (x * 10) % 10 == 0:
x = int(x)
x = 2/1
Output: 2
x = 3/2
Output: 1.5

Calculating a range of an exact number of values in Python

I'm building a range between two numbers (floats) and I'd like this range to be of an exact fixed length (no more, no less). range and arange work with steps, instead. To put things into pseudo Python, this is what I'd like to achieve:
start_value = -7.5
end_value = 0.1
my_range = my_range_function(star_value, end_value, length=6)
print my_range
[-7.50,-5.98,-4.46,-2.94,-1.42,0.10]
This is essentially equivalent to the R function seq which can specify a sequence of a given length. Is this possible in Python?
Thanks.

Use linspace() from NumPy.
>>> from numpy import linspace
>>> linspace(-7.5, 0.1, 6)
array([-7.5 , -5.98, -4.46, -2.94, -1.42, 0.1])
>>> linspace(-7.5, 0.1, 6).tolist()
[-7.5, -5.9800000000000004, -4.46, -2.9399999999999995, -1.4199999999999999, 0.10000000000000001]
It should be the most efficient and accurate.

See Recipe 66472: frange(), a range function with float increments (Python) with various float implementations, their pros and cons.
Alternatively, if precision is important to you, work with decimal.Decimal instead of float (convert to and then back) as answered in Python decimal range() step value.

def my_function(start, end, length):
len = length - 1
incr = (end-start) / len
r = [ start ]
for i in range(len):
r.append ( r[i] + incr )
return r

How about this:
def my_range_function(start, end, length):
if length <= 1: return [ start ]
step = (end - start) / (length - 1)
return [(start + i * step) for i in xrange(length)]
For your sample range, it returns:
[-7.5, -5.9800000000000004, -4.46,
-2.9399999999999995, -1.4199999999999999, 0.099999999999999645]
Of course it's full of round errors, but that's what you get when working with floats.

In order to handle the rounding errors, the following code utilizes Python's decimal module. You can set the rounding; for this sample I've set it to two decimal points via round_setting = '.01'. In order to handle any rounding errors, the last step is adjusted to the remainder.
Code
#!/usr/bin/env python
# encoding: utf-8
from __future__ import print_function
import math
import decimal
start_value = -7.5
end_value = 0.1
num_of_steps = 6
def my_range(start_value, end_value, num_of_steps):
round_setting = '.01'
start_decimal = decimal.Decimal(str(start_value)).quantize(
decimal.Decimal(round_setting))
end_decimal = decimal.Decimal(str(end_value)).quantize(
decimal.Decimal(round_setting))
num_of_steps_decimal = decimal.Decimal(str(num_of_steps)).quantize(
decimal.Decimal(round_setting))
step_decimal = ((end_decimal - start_decimal) /
num_of_steps_decimal).quantize(decimal.Decimal(round_setting))
# Change the last step in case there are rounding errors
last_step_decimal = (end_decimal - ((num_of_steps - 1) * step_decimal) -
start_decimal).quantize(decimal.Decimal(round_setting))
print('Start value = ', start_decimal)
print('End value = ', end_decimal)
print('Number of steps = ', num_of_steps)
print('Normal step for range = ', step_decimal)
print('Last step used for range = ', last_step_decimal)
my_range(start_value, end_value, num_of_steps)
Output
$ ./fixed_range.py
Start value = -7.50
End value = 0.10
Number of steps = 6
Normal step for range = 1.27
Last step used for range = 1.25
From there you can use the normal step and the last step to create your list.