Difference between revisions of "Dist range.m"
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{{DISPLAYTITLE:dist_range.m}} __NOTOC__ | {{DISPLAYTITLE:dist_range.m}} __NOTOC__ | ||
| − | + | Returns the mathematical bounds for the distance range covered by a DEER trace with the specified number of points and duration, assuming uniform time step. | |
==Syntax== | ==Syntax== | ||
| − | [rmin,rmax]=dist_range( | + | [rmin,rmax]=dist_range(dt,tmax,expt) |
| − | == | + | ==Parameters== |
| − | + | dt - interval duration of the uniform time grid | |
| − | tmax - the time (seconds) of the last | + | tmax - the time (seconds) of the last point in the |
| − | + | grid if the first point is zero | |
| − | + | ||
| + | expt - 'ridme' or 'deer' | ||
==Outputs== | ==Outputs== | ||
| Line 25: | Line 26: | ||
For a 2 microsecond DEER trace containing 512 points: | For a 2 microsecond DEER trace containing 512 points: | ||
| − | >> [rmin,rmax]=dist_range( | + | >> [rmin,rmax]=dist_range(4e-9,2e-6,'deer') |
| − | rmin = | + | rmin = 9.4078 |
rmax = 59.2655 | rmax = 59.2655 | ||
==See also== | ==See also== | ||
| − | [[deer_lib_gen.m]], [[deernet.m]], [[ | + | [[deer_lib_gen.m]], [[deernet.m]], [[elexsys2deernet.m]], [[process_using.m]], [[train_one_net.m]], [[Neural network module]], [[Built-in_experiments]] |
| − | |||
| − | ''Version 2. | + | ''Version 2.8, authors: [[Jake Keeley]], [[Ilya Kuprov]]'' |
Latest revision as of 19:36, 6 June 2026
Returns the mathematical bounds for the distance range covered by a DEER trace with the specified number of points and duration, assuming uniform time step.
Syntax
[rmin,rmax]=dist_range(dt,tmax,expt)
Parameters
dt - interval duration of the uniform time grid
tmax - the time (seconds) of the last point in the
grid if the first point is zero
expt - 'ridme' or 'deer'
Outputs
rmin - minimum distance supported by the
grid, Angstrom
rmax - maximum distance supported by the
grid, Angstrom
Examples
For a 2 microsecond DEER trace containing 512 points:
>> [rmin,rmax]=dist_range(4e-9,2e-6,'deer') rmin = 9.4078 rmax = 59.2655
See also
deer_lib_gen.m, deernet.m, elexsys2deernet.m, process_using.m, train_one_net.m, Neural network module, Built-in_experiments
Version 2.8, authors: Jake Keeley, Ilya Kuprov
