You are a guest. Restricted access. Read more.

### Table of Contents

# Error propagation

## Error propagation using P1D

A typical measurement contains an uncertainty. A convenient way to keep data with errors is to use the P1D data container.

from jhplot import * p=P1D("data with errors") p.add(1, 2, 0.5) # error on Y=2 is 0.5 p.add(2, 5, 0.9) # error on Y=5 is 0.9

See the discussion of P1D in data_structures. When you are using the method “oper()” of this class, the errors are automatically propagated. This applies for subtraction, division, multiplication and addition.

## Error propagation for arbitrary functions

In this section section we describe error propagation for an arbitrary transformation.

You are not full member and have a limited access to this section.
One can unlock this part after becoming a full member.

## Error propagation with arbitrary units

Error propagation using arbitrary units is described in Section unit_measurements.