misu 1.0.4

Demo

Most of the time you will probably work with misu interactively, and it will be most convenient to import the entire namespace:

from misu import *

mass = 100*kg
print(mass >> lb)

The symbol kg got imported from the misu package. We redefine the shift operator to perform inline conversions. The code above produces:

220.46226218487757

There are many units already defined, and it is easy to add more. Here we convert the same quantity into ounces:

print(mass >> oz)

output:

3571.4285714285716

What you see above would be useless on its own. What you really need is to be able to perform consistent calculations with quantities expressed in different, but compatible units:

mass = 10*kg + 20*lb
print(mass)

output:

19.07 kg

For addition and subtraction, misu will ensure that only consistent units can be used. Multiplication and division will produce new units:

distance = 100*metres
time = 9.2*seconds
​
speed = distance / time
print(speed)

output:

10.87 m/s

As before, it is trivially easy to express that quantity in different units of compatible dimensions:

print(speed >> km/hr)

output:

39.130434782608695

Introduction

misu is a package of handling physical quantities with dimensions. This means performing calculations with all the units being tracked correctly. It is possible to add kilograms per hour to ounces per minute, obtain the correct answer, and have that answer be reported in, say, pounds per week.

misu grew out of a personal need. I have used this code personally in a (chemical) engineering context for well over a year now (at time of writing, Feb 2015). Every feature has been added in response to a personal need.

@dimensions(x='Length', y='Mass')
def f(x, y):
    return x/y

f(2*m, 3*kg)         # Works
f(200*feet, 3*tons)  # Works

f(2*joules, 3*kelvin)  # raises AssertionError
f(2*m, 3)              # raises AssertionError

mass = 100 * kg
mass_lb = mass >> lb

duty = 50 * MW
duty_BTU_hr = duty >> BTU / hr

General usage

For speed-critical code, the application of unit operations can still be too slow. In these situations it is typical to first cast quantities into numerical values (doubles, say), perform the speed-critical calculations (perhaps call into a C-library), and then re-cast the result back into a quantity and return that from a function.

@dimensions(x='Length', y='Mass')
def f(x, y):
    x = x >> metre
    y = y >> ounces
    <code that assumes meters and ounces, returns value in BTU>
    return answer * BTU

This way you can still easily wrap performance-critical calculations with robust unit-handling.