Rpp_num {oreo} | R Documentation |
SPP Analysis via numerical differentiation
Description
applies the SPP Analysis by means of a numerical differentiation.
Usage
Rpp_num(time_wave, resp_wave, L, k, num_mode)
Arguments
time_wave |
Lx1 vector of time at each measurement point |
resp_wave |
Lx3 matrix of the strain, rate and stress data,with each row representing a measuring point |
L |
number of measurement points in the extracted data |
k |
step size for numerical differentiation |
num_mode |
numerical method |
Value
a list with the following data frame spp_data_in= the data frame with the data spp_params=spp_params, spp_data_out= Length,frequency,harmonics,cycles,max_harmonics,step_size fsf_data_out= Tx,Ty,Tz,Nx,Ny,Nz,Bx,By,Bz coordinates of the trajectory (T=tangent,N=principal Normal,B=Binormal Vectors) ft_out=data frame with that includes time_wave,strain,rate,stress,Gp_t,Gpp_t,G_star_t,tan_delta_t,delta_t,disp_stress,eq_strain_est,Gp_t_dot,Gpp_t_dot,G_speed,delta_t_dot)
Author(s)
Simon Rogers Group for Soft Matter (matlab version), Giorgio Luciano and Serena Berretta (R version)
References
Simon A. Rogersa, M. Paul Letting, A sequence of physical processes determined and quantified in large-amplitude oscillatory shear (LAOS): Application to theoretical nonlinear models Journal of Rheology 56:1, 1-25
Examples
data(mydata)
df <- rpp_read2(mydata , selected=c(2, 3, 4, 0, 0, 1, 0, 0))
time_wave <- df$raw_time
resp_wave <- data.frame(df$strain,df$strain_rate,df$stress)
out <- Rpp_num(time_wave, resp_wave , L=1024, k=8, num_mode=1)