def load_data(mod_name):
#data_mod_name = 'swept_sine_amp_75_July_07_2009_avebodes'
#data_mod_name = 'swept_sine_amp_75_July_07_2009_log_downsampled'
bode_data_set = txt_data_processing.load_avebode_data_set(mod_name)
#bode_data_set.Bode_Plot2(func=rwkbode.GenBodePlot, linetype='o')
## exp_bodes = bode_data_set.avebodes[0:2]
## th_v_exp = exp_bodes[0]
## a_v_exp = exp_bodes[1]
## f = bode_data_set.f
## a_theta_exp = bode_data_set.avebodes[2]
exp_bodes = bode_data_set.avebodes
th_v_exp = bode_data_set.find_bode('theta','v')
a_v_exp = bode_data_set.find_bode('a','v')
f = bode_data_set.f
a_theta_exp = bode_data_set.find_bode('a','theta')
return f, th_v_exp, a_v_exp, a_theta_exp
from pylab import *
from scipy import *
import os
import txt_data_processing
#reload(txt_data_processing)
#from txt_data_processing import load_avebode_data_set, \
# load_time_domain_data_set, merge_trunc_ave_data_sets
data_dir = '/home/ryan/siue/Research/PSoC_Research/SLFR_RTP/SRF_2009/June_17_2009'
import sys
if data_dir not in sys.path:
sys.path.append(data_dir)
ds_name = 'closed_loop_swept_sine_no_accel_fb_avebodes'
data_set = txt_data_processing.load_avebode_data_set(ds_name)
figs = data_set.Bode_Plot2()
inds, mask, flog = data_set.Log_Compress_Data([0.5,1.5,4.0,10],[20,70,20])
data_set.Bode_Plot2(attr='compressed_avebodes', \
f_attr='compressed_f', figs=figs, \
clear=False, linetype='o')
data_set.save_as(os.path.join(data_dir, 'log_compressed_data_June_17_2009'))
show()
reload(txt_data_processing)
import rwkbode
reload(rwkbode)
from IPython.Debugger import Pdb
#from txt_data_processing import load_avebode_data_set, \
# load_time_domain_data_set, merge_trunc_ave_data_sets
data_dir = 'June_17_2009'
import sys
if data_dir not in sys.path:
sys.path.append(data_dir)
log_ds_name = 'log_compressed_data_June_17_2009'
log_data_set = txt_data_processing.load_avebode_data_set(log_ds_name)
ol_act_bode = log_data_set.find_bode('theta','v')
ol_act_bode.phase = squeeze(ol_act_bode.phase)
ol_act_bode.mag = squeeze(ol_act_bode.mag)
f = log_data_set.f
raw_name = 'closed_loop_swept_sine_no_accel_fb_avebodes'
raw_data_set = txt_data_processing.load_avebode_data_set(raw_name)
raw_act_bode = raw_data_set.find_bode('theta','v')
raw_cl_bode = raw_data_set.find_bode('theta','u')
raw_a_theta_d_bode = raw_data_set.find_bode('a','u')
f_raw = raw_data_set.f
def my_ol_model(X):
g = X[0]
def __init__(self, modname, bode_opts, label="exp."):
self.mod = TDP.load_avebode_data_set(modname)
self.bode_opts = bode_opts
self.bode_attr = self.mod
self.func = plot_exp_bode
self.label = label
from pylab import *
from scipy import *
import copy
import txt_data_processing, rwkbode, pylab_util
from systemid import Model
#load log downsampled and raw Bode data
log_ds_mod = 'swept_sine_amp_75_July_07_2009_log_downsampled'
log_ds_data = txt_data_processing.load_avebode_data_set(log_ds_mod)
log_ds_f = log_ds_data.f
a_theta_log_ds = log_ds_data.find_bode('a', 'theta')
raw_mod = 'swept_sine_amp_75_July_07_2009_avebodes'
raw_data = txt_data_processing.load_avebode_data_set(raw_mod)
raw_f = raw_data.f
a_theta_raw = raw_data.find_bode('a', 'theta')
######################
#
# Develop a model
#
######################
#both modes multiplied together
tf_c1 = Model('g*s**2*w1**2*w2**2', \
'(s**2+2*z1*w1*s+w1**2)*(s**2+2*z2*w2*s+w2**2)' , \
{'w1':2.5*2*pi,'z1':0.03,'w2':17.8*2*pi,'z2':0.01,'g':0.005}, \
'all')
model_bode_c1 = rwkbode.Bode_From_TF(tf_c1, raw_f, input='theta', output='a')
## parser.add_option("-o", "--output", dest="output", \
## help="Output name for saving the data.",\
## default="", type="str")
(options, args) = parser.parse_args()
curdir = os.getcwd()
if curdir not in sys.path:
sys.path.insert(1, curdir)
print("options=" + str(options))
print("args=" + str(args))
opts_file = args[0]
folder, opts_name = os.path.split(opts_file)
log_opt_dict = load_and_parse_opts(opts_file)
load_path = os.path.join(folder, log_opt_dict["load_name"])
data_set = txt_data_processing.load_avebode_data_set(load_path)
freqs = log_opt_dict["freqs"]
points = log_opt_dict["points"]
inds, mask, flog = data_set.Log_Compress_Data(freqs, points)
outpath = os.path.join(folder, log_opt_dict["save_name"])
data_set.save_as(outpath)
if options.plot:
figs = data_set.Bode_Plot2()
data_set.Bode_Plot2(attr="compressed_avebodes", f_attr="compressed_f", figs=figs, clear=False, linestyle="o")
show()
load_time_domain_data_set, merge_trunc_ave_data_sets
import pylab_util
import rwkbode
data_dir = rwkos.FindFullPath('siue/Research/modeling/SLFR/data/July_07_2009')
if data_dir not in sys.path:
sys.path.append(data_dir)
import SLFR_TMM
reload(SLFR_TMM)
ds_name = 'swept_sine_amp_75_July_07_2009_log_downsampled'
data_set = load_avebode_data_set(ds_name)
figs = data_set.Bode_Plot2(linetype='o')
k_spring = 1.0
c_spring = 0.1
K_act = 0.05
tau = 10.0*2*pi
xf = [k_spring, c_spring, K_act, tau, 1.5]
ol_model = SLFR_TMM.SLFR_TMM_OL_model(xf)
ol_model.IntegratedCurveFit(expmodname=data_set, prefix='log_compressed')
show()
