Module: Integrator

Included in:
AdaptiveIntegrator, Cash_Karp_RK4
Defined in:
lib/integrator/version.rb,
lib/integrator.rb

Overview

:nodoc:

Defined Under Namespace

Modules: VERSION

Instance Method Summary collapse

Instance Method Details

#integrate(y0, t_start, t_end, derivs, step_start = 0.1, step_min = 0.0001, epsilon = 0.01) ⇒ Object

Integrate from time t_start to t_end, starting from initial value y0. Use the ‘derivs’ proc to evaluate derivatives at a given point. Start by taking a step of size step_start, take steps no smaller than step_min, and attempt to keep the error per step down to a maximum of epsilon.



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# File 'lib/integrator.rb', line 54

def integrate(y0, t_start, t_end, derivs, step_start = 0.1,
              step_min = 0.0001, epsilon = 0.01)
  raise "y0 must be a vector!" unless y0.kind_of?(Vector)
  raise "Must give derivative proc!" unless derivs.kind_of?(Proc)

  adaptive_integrate(y0, t_start, t_end, epsilon,
                     step_start, step_min, derivs)
end

#Integrator_initialize ⇒ Object 



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# File 'lib/integrator.rb', line 15

def Integrator_initialize()
  @kmax = 0     # Max steps to save
  @dxsav = 0.01 # Minimum step size to save data
  @xp = nil      # Array to save X coords
  @yp = nil      # Array to save Y vectors

  # Stats from most recent integrate call
  @nok = 0
  @nbad = 0
  @count = 0
end

#set_max_samples(num_max, min_x_save = 0.01) ⇒ Object

Set sample logging. Num_max is the maximum number of samples to log, and min_x_save is the minimum distance between x samples to bother to log.



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# File 'lib/integrator.rb', line 41

def set_max_samples(num_max, min_x_save = 0.01)
  @kmax = num_max
  @xp = []
  @yp = []
  @dxsav = min_x_save
end