Examples - Orthogonal Devices ER-102 User Manual

Examples

Set parameters to a specific value:
To achieve the affect of an assignment operation, just set G = 0 and set A to the
desired value. Typically you would do this when you want to simultaneously set a
particular parameter of many steps to a desired value (e.g. set the DURATION of all
steps in a pattern to 16 clock pulses). Additionally, you can use the JITTER(Jt) param-
eter to add a bit of zero-centered random noise to the parameter. This is especially
useful for velocity CVs and gate lengths.
Generate random parameter values in a given range:
The RANDOM operation produces random integers between 0 and Rd. If you want
random numbers between L and H, then just set A = L and Rd = H-L. For example,
to get random values between 12 and 19, set A = 12 and Rd = 7. This is often done
when producing random pitch values that are within a restricted range.
Generate random pitches separated by a given fixed interval:
To generate random multiples of a given number just set Rd and A as you would for
producing random numbers in a range but also set G to the desired interval size. For
example, to produce random pitch values from one octave of the whole tone series
then set G=2, Rd=6, and set A to the root pitch. Alternatively, you can use RANDOM
with the QUANTIZE operation: Rd=12 and Qt=2.
Generate random rhythms with customized probabilities:
Start with a simple sequence of steps with all the GATE parameters set to zero. If
you apply a MATH transform of [GATE+RANDOM(4)]/3 to the entire track then you
will get random sample of steps with a GATE parameter of 1 and the rest will be zero.
Furthermore, if you start with a sequence of steps where some of the steps have a
GATE parameter of 1, 2 or 3 (rather than just zero) then these steps will have a pro-
gressively higher probability of being assigned a non-zero GATE after you apply the
MATH transform. This way you can sculpt the resulting random rhythm lightly by
biasing the randomization. For example, this is great for producing random rhythms
that have a higher probability of triggering on the strong beats then on the weak
beats.
This example works especially well with the HIGH/LOW transforms (see Groups)
because the initial probability contour is not overwritten by the application of these
non-destructive transform, and, the HIGH/LOW transforms get re-evaluated every-
time a step is played, thus producing a continually evolving rhythm that neverthe-
less adheres to the user's specified probability contour.
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