#para_name = "best_fit_exop_fake1_mod_3_1364916905.txt"
para = np.loadtxt( para_name )
num_comp = int(np.floor((para.shape[0] - 1)/5))
plt.figure(num=1, figsize=(16,12))
start_time = data[0,0]
end_time = data[data.shape[0]-1,0]
time_span = end_time - start_time
t=np.arange(start_time-0.2*time_span, end_time+0.2*time_span,0.1)
v=np.zeros(t.shape[0])
for i in range(v.shape[0]):
for j in range(num_comp):
v[i] = v[i] + kp.rad_v_pred(t[i]-data[0,0],para[j*5+0],para[j*5+1],para[j*5+2],para[j*5+3],para[j*5+4])
v[i] = v[i] + para[num_comp*5]
if num_comp == 2:
title = 'fit of star ' + star_name + ' with ' + str(num_comp) + ' comp(s)\n' + 'Period 1: ' + str(np.round(2*np.pi/para[1])) + ' d; ' + 'Period 2: ' + str(np.round(2*np.pi/para[6])) + ' d '
if num_comp == 3:
title = 'fit of star ' + star_name + ' with ' + str(num_comp) + ' comp(s)\n' + 'Period 1: ' + str(np.round(2*np.pi/para[1])) + ' d; ' + 'Period 2: ' + str(np.round(2*np.pi/para[6])) + ' d; ' + 'Period 3: ' + str(np.round(2*np.pi/para[11])) + ' d '
plt.plot(t,v,alpha=0.8,color=[0,0,1])
plt.plot(data[:,0], data[:,1], marker='+', markersize=12, linewidth=0)
plt.grid(b=True)
plt.xlabel('time '+r'$(d)$', fontsize='x-large')
plt.ylabel('radial velocity '+'$(m\,s^{-1})$', fontsize='x-large')
plt.title(title, fontsize='x-large')
plt.savefig('fit_'+star_name+'_'+str(num_comp)+'_comp'+'.png')
data_name = star_name + '.txt' data = np.loadtxt( data_name ) res = np.zeros(data.shape[0]) model_name = 'mod_1' dim = 1 time_label = '20130930' para_name = '282_mod_1_select_20130930.txt' para = np.loadtxt( para_name ) k = para.shape[0]-1 for i in range(data.shape[0]): res[i] = data[i,1] for j in range(0,dim): res[i] = res[i] - kp.rad_v_pred(data[i,0]-data[0,0],para[k,j*5+0],para[k,j*5+1],para[k,j*5+2],para[k,j*5+3],para[k,j*5+4]) res[i] = res[i] - para[k, 5*dim] start_time = data[0,0] end_time = data[data.shape[0]-1,0] time_span = end_time - start_time t = np.arange(start_time-0.1*time_span, end_time+0.1*time_span, 0.5) v = np.zeros(t.shape[0]) fig = plt.figure(num=1, figsize=(36,36)) ax = plt.subplot2grid((3,3), (2,0), colspan=3, rowspan=1) ax.errorbar(data[:,0], res[:], data[:,2], marker='o', markersize=15, markeredgewidth=3 ,linewidth=0, color=[0,0.5,0.02], markeredgecolor=[0,0.5,0.02], fmt='-', capsize=0, elinewidth=3) ax.set_xlim(t[0], t[t.shape[0]-1]) ax.tick_params(axis = 'both', which = 'major', labelsize = 60)