Metadata-Version: 2.1
Name: errorpp
Version: 0.0.1
Summary: Automatically propagate the error in an expression symbolically
Home-page: https://github.com/de0ch/errorpp
Author: Deyao Chen
Author-email: chendeyao000@gmail.com
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/de0ch/errorpp/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown

# Automatic Error Propagation

If you take a physics class, you may need to deal with error propagation, which gets really annoying as the equation gets longer. If you are using this, make sure you are actually allowed to and you understand how error propagation works. Consider using this the same way you'd use wolfram alpha -- it can get you an answer easily but it won't make you better at math.

# Installation

```bash
pip install errorpp
```

# Function and Scope 
As of the moment, the error propagation only supports expanding addition, multiplication, division and real number exponent. If you input anything else such as `sin(x)` it will throw an error. If you want see more functions implemented, open an issue, or better yet, make a pull request!

# How to use
In its core, it uses `sympy` to process the expression. the `errorpp.propagate` function will take a `sympy` expression as the argument return the `sympy` expression with the error propagated. If your variables are all positive, you can pass in `absolute=False` to prevent the program from wrapping variables in absolute sign, which makes a cleaner output as `sympy` can cancel variables more easily.

You can also use the counterpart `errorpp.propagate_latex` which takes a string of latex expression as the argument and output the latex expression with the error propagated. 

Alternatively, you directly call this from the terminal, which takes an latex equation as its first argument and print the latex expression with the error propagated to standard output. Use `--no-absolute` to prevent the program from wrapping variables in absolute sign.

Since the code base is quite small, I won't make a website with the documentation, but instead I will write the explanation in the docstring in the source code. 

# Code Example

You can use this directly in terminal
```bash
python -m errorpp '\\frac{- c_{w} m_{1} \\left(- T_{1} + T_{f}\\right) + c_{w} m_{2} \\left(T_{2} - T_{f}\\right)}{- T_{1} + T_{f}}' --no-absolute
# output
# \frac{\sqrt{\frac{c_{w}^{2} m_{1}^{2} \left(- T_{1} + T_{f}\right)^{2} \left(\frac{\Delta^{2}{\left(T_{1} \right)} + \Delta^{2}{\left(T_{f} \right)}}{\left(- T_{1} + T_{f}\right)^{2}} + \frac{\Delta^{2}{\left(m_{1} \right)}}{m_{1}^{2}} + \frac{\Delta^{2}{\left(c_{w} \right)}}{c_{w}^{2}}\right) + c_{w}^{2} m_{2}^{2} \left(T_{2} - T_{f}\right)^{2} \left(\frac{\Delta^{2}{\left(T_{2} \right)} + \Delta^{2}{\left(T_{f} \right)}}{\left(T_{2} - T_{f}\right)^{2}} + \frac{\Delta^{2}{\left(m_{2} \right)}}{m_{2}^{2}} + \frac{\Delta^{2}{\left(c_{w} \right)}}{c_{w}^{2}}\right)}{\left(- c_{w} m_{1} \left(- T_{1} + T_{f}\right) + c_{w} m_{2} \left(T_{2} - T_{f}\right)\right)^{2}} + \frac{\Delta^{2}{\left(T_{1} \right)} + \Delta^{2}{\left(T_{f} \right)}}{\left(- T_{1} + T_{f}\right)^{2}}} \left(- c_{w} m_{1} \left(- T_{1} + T_{f}\right) + c_{w} m_{2} \left(T_{2} - T_{f}\right)\right)}{- T_{1} + T_{f}}
```

Or import this as a module
```python 
import errorpp
import sympy

eq = sympy.parse_latex('\\frac{- c_{w} m_{1} \\left(- T_{1} + T_{f}\\right) + c_{w} m_{2} \\left(T_{2} - T_{f}\\right)}{- T_{1} + T_{f}}')
p = errorpp.propagate(eq, absolute=False)
print(pretty(eq, use_unicode=False))

# Output
#          _____________________________________________________________________
#         /                         /     2             2             2         
#        /     2    2             2 |Delta (T_1) + Delta (T_f)   Delta (m_1)   D
#       /   c_w *m_1 *(-T_1 + T_f) *|------------------------- + ----------- + -
#      /                            |                  2                2       
#     /                             \      (-T_1 + T_f)              m_1        
#    /      --------------------------------------------------------------------
#   /                                                                           
# \/                                                                 (-c_w*m_1*(
# ------------------------------------------------------------------------------
#                                                                               
# 
# ______________________________________________________________________________
#     2     \                          /     2             2             2      
# elta (c_w)|      2    2            2 |Delta (T_2) + Delta (T_f)   Delta (m_2) 
# ----------| + c_w *m_2 *(T_2 - T_f) *|------------------------- + ----------- 
#       2   |                          |                  2                2    
#    c_w    /                          \       (T_2 - T_f)              m_2     
# ------------------------------------------------------------------------------
#                                   2                                           
# -T_1 + T_f) + c_w*m_2*(T_2 - T_f))                                            
# ------------------------------------------------------------------------------
#                                         -T_1 + T_f                            
# 
# ___________________________________________                                   
#        2     \                                                                
#   Delta (c_w)|                                                                
# + -----------|                                                                
#          2   |        2             2                                         
#       c_w    /   Delta (T_1) + Delta (T_f)                                    
# -------------- + ------------------------- *(-c_w*m_1*(-T_1 + T_f) + c_w*m_2*(
#                                    2                                          
#                        (-T_1 + T_f)                                           
# ------------------------------------------------------------------------------
#                                                                               
# 
#            
#            
#            
#            
#            
#            
# T_2 - T_f))
#            
#            
# -----------
# 
```

