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SCaVis manual

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.

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Error propagation with arbitrary units

Error propagation using arbitrary units is described in Section unit_measurements.

man/meas/errorprop.txt · Last modified: 2013/05/31 16:11 (external edit)
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