Description Usage Arguments Examples

CVSOLVE solver to solve stiff ODEs with discontinuties

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`time_vector` |
time vector |

`IC` |
Initial Conditions |

`input_function` |
Right Hand Side function of ODEs |

`Parameters` |
Parameters input to ODEs |

`Events` |
Discontinuities in the solution (a DataFrame, default value is NULL) |

`reltolerance` |
Relative Tolerance (a scalar, default value = 1e-04) |

`abstolerance` |
Absolute Tolerance (a scalar or vector with length equal to ydot, default = 1e-04) |

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# Example of solving a set of ODEs with multiple discontinuities using cvsolve
# A simple One dimensional equation, y = -0.1 * y
# ODEs described by an R function
ODE_R <- function(t, y, p){
# vector containing the right hand side gradients
ydot = vector(mode = "numeric", length = length(y))
# R indices start from 1
ydot[1] = -p[1]*y[1]
ydot
}
# R code to generate time vector, IC and solve the equations
TSAMP <- seq(from = 0, to = 100, by = 0.1) # sampling time points
IC <- c(1)
params <- c(0.1)
# A dataset describing the dosing at times at which additions to y[1] are to be done
# Names of the columns don't matter, but they MUST be in the order of state index,
# times and Values at discontinuity.
TDOSE <- data.frame(ID = 1, TIMES = c(0, 10, 20, 30, 40, 50), VAL = 100)
df1 <- cvsolve(TSAMP, c(1), ODE_R, params) # solving without any discontinuity
df2 <- cvsolve(TSAMP, c(1), ODE_R, params, TDOSE) # solving with discontinuity
``` |

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