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Mar 22, 2017 8:06 AM
(2484 views)

Specifically looking for a curve fitting platform for underdamped oscillation

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Mar 27, 2017 12:10 PM
(4429 views)

Are you trying to just plot an underdamped oscillator? Or are you trying to fit beta and w0? The below script will actually fit.

```
Names Default to here(1);
dt = New Table("Harmonic Oscillator",
New Table Variable("beta", .3),
New Table Variable("w0", .4),
New Column("t", set values(0::50)),
New Column("Cos t", formula(Cos(t))),
New Column("Damped Cos t", Formula(
exp(-:beta*:w0*:t)*cos(:w0*t) + random normal(0, .01) //just adding noise
)),
New Column("Predictor",
Formula(
Parameter({pbeta = .2, pw0 = .5},
exp(-pbeta*pw0*:t)*cos(pw0*t)
)
)
)
);
dt << Nonlinear( Y( :Damped Cos t ), X( :Predictor ), Newton );
```

To give you this. notice how my actual beta/w0 was .3/.4 but I started my predictor with .2/.5

Is this sort of what your'e looking for?

6 REPLIES

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Mar 22, 2017 8:32 AM
(2474 views)

In JMP 13, have you looked at

Anaylze==>Specialized Modeling==>Fit Curve

Jim

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Mar 22, 2017 8:36 AM
(2471 views)

Hacking through that now - thanks. My data should create a an exponentially decaying sinusoid. Trying to figure out how to make JMP do it.

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Mar 22, 2017 2:09 PM
(2458 views)

You can give custom equations and parameters in the nonlinear platform. Also Under specialized models.

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Mar 23, 2017 7:32 AM
(2430 views)

Thanks y'all. I appreciate the suggetions. I was able to answer my client's question by fitting an exponential decay curve through my data rather than generate the oscillating underdamped plot. I would like to figure that part out though. I need to find some examples to learn from. Thanks again.

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Mar 27, 2017 12:10 PM
(4430 views)

Are you trying to just plot an underdamped oscillator? Or are you trying to fit beta and w0? The below script will actually fit.

```
Names Default to here(1);
dt = New Table("Harmonic Oscillator",
New Table Variable("beta", .3),
New Table Variable("w0", .4),
New Column("t", set values(0::50)),
New Column("Cos t", formula(Cos(t))),
New Column("Damped Cos t", Formula(
exp(-:beta*:w0*:t)*cos(:w0*t) + random normal(0, .01) //just adding noise
)),
New Column("Predictor",
Formula(
Parameter({pbeta = .2, pw0 = .5},
exp(-pbeta*pw0*:t)*cos(pw0*t)
)
)
)
);
dt << Nonlinear( Y( :Damped Cos t ), X( :Predictor ), Newton );
```

To give you this. notice how my actual beta/w0 was .3/.4 but I started my predictor with .2/.5

Is this sort of what your'e looking for?

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Mar 27, 2017 1:18 PM
(2309 views)

Exactly!!! You hit a grand slam! Many thanks!!