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ffa_stages.py
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import ffa_tools as f
import FFA_cy as FFA
import numpy as np
import matplotlib.pyplot as plt
import math
import time
from scipy import *
import scipy.signal
import inspect
import sys
import os
"""
Make histogram
check for why sigma isnt sig*sqrt{dwn}
"""
def ffa_code_stage1(data ,dt , T , sigma_total,p_min, p_max, count_lim, name):
"""
ffa_code_stage1 (data , dt , T, period , N , p_min , p_max , count_lim , name):
- data : Time series
- dt : Sampling interval (s)
- T : Total observative time (s)
- p_min : Minimum period in the subset of trial periods (s)
- p_max : Maximum period in the subset of trial periods (s)
- count_lim : int 1 or 2, used in stage2 and stage 3
if count_lim =1, goes to 4*dt and 9*dt
if count_lim =2, goes to 8*dt and 27*dt
- name : Name of the beam (without the extension)
Returns
"""
# -------------------- FFA Stage 1 ----------------------
fill_value = np.median(data)
N = T/dt
P0_start, P0_end = np.floor(p_min/dt), np.ceil(p_max/dt)
P0s = np.arange(P0_start,P0_end,1)
SNs1 = []
all_Ps1 = []
for p0 in P0s:
p0 = int(p0)
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin'
continue
p0_sec = p0*dt
xwrap = FFA.XWrap2(data,p0, fill_value=fill_value, pow2=True)
folds = FFA.FFA(xwrap)
M = folds.shape[0]
SN = f.simple_SNR(folds, sigma_total ,added_profs)
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec=P*dt
SNs1.append(SN)
all_Ps1.extend(Psec)
SNs1 = np.concatenate(SNs1)
dts = [dt]*len(SNs1)
return np.array([SNs1]),np.array([all_Ps1]), dts
#______________________________________________________________________
# -------------------- FFA Stage 2 ------------------------------
# -------------------- Extra downsampling : 2 ----------------------
def ffa_code_stage2(data ,dt , T , sigma_total,p_min, p_max, count_lim, name):
"""
ffa_code_stage2 (data , dt , T, period , N , p_min , p_max , count_lim , name):
- data : Time series
- dt : Sampling interval (s)
- T : Total observative time (s)
- p_min : Minimum period in the subset of trial periods (s)
- p_max : Maximum period in the subset of trial periods (s)
- count_lim : int 1 or 2, used in stage2 and stage 3
if count_lim =1, goes to 4*dt and 9*dt
if count_lim =2, goes to 8*dt and 27*dt
- name : Name of the beam (without the extension)
Returns
"""
fill_value = np.median(data)
P0_start, P0_end = np.floor(p_min/dt), np.ceil(p_max/dt)
P0s = np.arange(P0_start,P0_end,1)
count=0
sigma_total = sigma_total*np.sqrt(2)
while count<=count_lim:
if count==0:
data_1,data_2 = f.forced_dws_2phase(data)
new_dt2 = dt*2
dt2 = new_dt2
all_Ps2 = []
N = T/(new_dt2)
P0_start, P0_end = np.floor(p_min/new_dt2), np.ceil(p_max/new_dt2)
P0s2=np.arange(P0_start,P0_end,1)
time_stage2_1=time.time()
SNs2_1, SNs2_2 = [], []
for p0 in P0s2:
p0=int(p0)
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin','\n'
continue
p0_sec = p0*new_dt2
time_stage2_1=time.time()
xwrap_1 = FFA.XWrap2(data_1,p0, fill_value=fill_value, pow2=True)
xwrap_2 = FFA.XWrap2(data_2,p0, fill_value=fill_value, pow2=True)
folds_1 = FFA.FFA(xwrap_1)
folds_2 = FFA.FFA(xwrap_2)
SN_1 = f.simple_SNR(folds_1, sigma_total, added_profs)
SN_2 = f.simple_SNR(folds_2, sigma_total , added_profs)
M = folds_1.shape[0]
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec = P *new_dt2
SNs2_1.append(SN_1)
SNs2_2.append(SN_2)
all_Ps2.extend(Psec)
SNs2_1=np.concatenate(SNs2_1)
SNs2_2=np.concatenate(SNs2_2)
dt2s = [dt2]*len(SNs2_1)
if count == 1:
data_11, data_12 = f.forced_dws_2phase(data_1)
data_21, data_22 = f.forced_dws_2phase(data_2)
new_dt2 = new_dt2*2
dt4 = new_dt2
N = T/(new_dt2)
all_Ps4 = []
SNs4_11, SNs4_12, SNs4_21, SNs4_22 = [],[],[],[]
P0_start, P0_end = np.floor(p_min/new_dt2), np.ceil(p_max/new_dt2)
P0s2=np.arange(P0_start,P0_end,1)
sigma_total = sigma_total*np.sqrt(2)
for p0 in P0s2:
p0=int(p0)
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin'
continue
p0_sec = p0*new_dt2
xwrap_11 = FFA.XWrap2(data_11,p0, fill_value=fill_value, pow2=True)
xwrap_12 = FFA.XWrap2(data_12,p0, fill_value=fill_value, pow2=True)
xwrap_21 = FFA.XWrap2(data_21,p0, fill_value=fill_value, pow2=True)
xwrap_22 = FFA.XWrap2(data_22,p0, fill_value=fill_value, pow2=True)
folds_11 = FFA.FFA(xwrap_11)
folds_12 = FFA.FFA(xwrap_12)
folds_21 = FFA.FFA(xwrap_21)
folds_22 = FFA.FFA(xwrap_22)
SN_11 = f.simple_SNR(folds_11, sigma_total , added_profs)
SN_12 = f.simple_SNR(folds_12, sigma_total , added_profs)
SN_21 = f.simple_SNR(folds_21, sigma_total , added_profs)
SN_22 = f.simple_SNR(folds_22, sigma_total , added_profs)
M = folds_11.shape[0]
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec = P *new_dt2
SNs4_11.append(SN_11)
SNs4_12.append(SN_12)
SNs4_21.append(SN_21)
SNs4_22.append(SN_22)
all_Ps4.extend(Psec)
SNs4_11=np.concatenate(SNs4_11)
SNs4_12=np.concatenate(SNs4_12)
SNs4_21=np.concatenate(SNs4_21)
SNs4_22=np.concatenate(SNs4_22)
dt4s = [dt4]*len(SNs4_11)
if count == 2:
data_111, data_112 = f.forced_dws_2phase(data_11)
data_121, data_122 = f.forced_dws_2phase(data_12)
data_211, data_212 = f.forced_dws_2phase(data_21)
data_221, data_222 = f.forced_dws_2phase(data_22)
new_dt2 = new_dt2*2
dt8 = new_dt2
all_Ps8 = []
N = T/(new_dt2)
SNs8_111 , SNs8_112 ,SNs8_121 ,SNs8_122 =[],[],[],[]
SNs8_211 ,SNs8_212 ,SNs8_221 ,SNs8_222 =[],[],[],[]
P0_start, P0_end = np.floor(p_min/new_dt2), np.ceil(p_max/new_dt2)
P0s2=np.arange(P0_start,P0_end,1)
sigma_total = sigma_total*np.sqrt(2)
for p0 in P0s2:
p0=int(p0)
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin'
continue
p0_sec = p0*new_dt2
xwrap_111 = FFA.XWrap2(data_111,p0, fill_value=fill_value, pow2=True)
xwrap_121 = FFA.XWrap2(data_121,p0, fill_value=fill_value, pow2=True)
xwrap_211 = FFA.XWrap2(data_211,p0, fill_value=fill_value, pow2=True)
xwrap_221 = FFA.XWrap2(data_221,p0, fill_value=fill_value, pow2=True)
xwrap_112 = FFA.XWrap2(data_112,p0, fill_value=fill_value, pow2=True)
xwrap_122 = FFA.XWrap2(data_122,p0, fill_value=fill_value, pow2=True)
xwrap_212 = FFA.XWrap2(data_212,p0, fill_value=fill_value, pow2=True)
xwrap_222 = FFA.XWrap2(data_222,p0, fill_value=fill_value, pow2=True)
folds_111 = FFA.FFA(xwrap_111)
folds_121 = FFA.FFA(xwrap_121)
folds_211 = FFA.FFA(xwrap_211)
folds_221 = FFA.FFA(xwrap_221)
folds_112 = FFA.FFA(xwrap_112)
folds_122 = FFA.FFA(xwrap_122)
folds_212 = FFA.FFA(xwrap_212)
folds_222 = FFA.FFA(xwrap_222)
SN_111 = f.simple_SNR(folds_111, sigma_total , added_profs)
SN_121 = f.simple_SNR(folds_121, sigma_total , added_profs)
SN_211 = f.simple_SNR(folds_211, sigma_total , added_profs)
SN_221 = f.simple_SNR(folds_221, sigma_total , added_profs)
SN_112 = f.simple_SNR(folds_112, sigma_total , added_profs)
SN_122 = f.simple_SNR(folds_122, sigma_total , added_profs)
SN_212 = f.simple_SNR(folds_212, sigma_total , added_profs)
SN_222 = f.simple_SNR(folds_222, sigma_total , added_profs)
M = folds_111.shape[0]
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec = P *new_dt2
SNs8_111.append(SN_111)
SNs8_121.append(SN_121)
SNs8_211.append(SN_211)
SNs8_221.append(SN_221)
SNs8_112.append(SN_112)
SNs8_122.append(SN_122)
SNs8_212.append(SN_212)
SNs8_222.append(SN_222)
all_Ps8.extend(Psec)
SNs8_111 = np.concatenate(SNs8_111)
SNs8_121 = np.concatenate(SNs8_121)
SNs8_211 = np.concatenate(SNs8_211)
SNs8_221 = np.concatenate(SNs8_221)
SNs8_112 = np.concatenate(SNs8_112)
SNs8_122 = np.concatenate(SNs8_122)
SNs8_212 = np.concatenate(SNs8_212)
SNs8_222 = np.concatenate(SNs8_222)
dt8s = [dt8]*len(SNs8_111)
count+=1
if count_lim == 1:
return np.array([SNs2_1,SNs2_2, SNs4_11 , SNs4_12 , SNs4_21 , SNs4_22]), np.array([all_Ps2, all_Ps4]), [dt2s,dt4s]
if count_lim == 2:
return np.array([SNs2_1,SNs2_2, SNs4_11 , SNs4_12 , SNs4_21 , SNs4_22, SNs8_111 , SNs8_121 , SNs8_211 , SNs8_221 , SNs8_112 , SNs8_122 , SNs8_212 , SNs8_222 ]), np.array([all_Ps2, all_Ps4, all_Ps8]), [dt2s,dt4s,dt8s]
# -------------------- FFA Stage 3 ----------------------
# -------------------- - Extra downsampling : 3 ----------------------
def ffa_code_stage3(data ,dt ,T,sigma_total,p_min,p_max, count_lim,name):
"""
ffa_code_stage3 (data , dt , T, period , N , p_min , p_max , count_lim , name):
- data : Time series
- dt : Sampling interval (s)
- T : Total observative time (s)
- p_min : Minimum period in the subset of trial periods (s)
- p_max : Maximum period in the subset of trial periods (s)
- count_lim : int 1 or 2, used in stage2 and stage 3
if count_lim =1, goes to 4*dt and 9*dt
if count_lim =2, goes to 8*dt and 27*dt
- name : Name of the beam (without the extension)
Returns
"""
fill_value = np.median(data)
P0_start, P0_end = np.floor(p_min/dt), np.ceil(p_max/dt)
P0s = np.arange(P0_start,P0_end,1)
time_ffa3=time.time()
count=0
plot_num=311
larges_dt3=[]
w=int(3)
sigma_total = sigma_total*np.sqrt(3)
while count<=count_lim:
if count==0:
data_1,data_2,data_3=f.forced_dws_3phase(data)
new_dt3 = dt*3
dt3 = new_dt3
N = T/(new_dt3)
P0_start, P0_end = np.floor(p_min/new_dt3), np.ceil(p_max/new_dt3)
P0s3=np.arange(P0_start,P0_end,1)
all_Ps3 = []
SNs3_1, SNs3_2, SNs3_3 = [], [], []
for p0 in P0s3:
p0=int(p0)
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin'
continue
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
p0_sec = p0*new_dt3
xwrap_1 = FFA.XWrap2(data_1,p0, fill_value=fill_value, pow2=True)
xwrap_2 = FFA.XWrap2(data_2,p0, fill_value=fill_value, pow2=True)
xwrap_3 = FFA.XWrap2(data_3,p0, fill_value=fill_value, pow2=True)
folds_1 = FFA.FFA(xwrap_1)
folds_2 = FFA.FFA(xwrap_2)
folds_3 = FFA.FFA(xwrap_3)
SN_1 = f.simple_SNR(folds_1, sigma_total , added_profs)
SN_2 = f.simple_SNR(folds_2, sigma_total , added_profs)
SN_3 = f.simple_SNR(folds_3, sigma_total , added_profs)
M = folds_1.shape[0]
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec = P *new_dt3
all_Ps3.extend(Psec)
SNs3_1.append(SN_1)
SNs3_2.append(SN_2)
SNs3_3.append(SN_3)
SNs3_1 = np.concatenate(SNs3_1)
SNs3_2 = np.concatenate(SNs3_2)
SNs3_3 = np.concatenate(SNs3_3)
dt3s = [dt3]*len(SNs3_1)
if count==1:
w=int(w*3)
new_dt3 = new_dt3*3
dt9 = new_dt3
all_Ps9 = []
data_11, data_12, data_13 = f.forced_dws_3phase(data_1)
data_21, data_22, data_23 = f.forced_dws_3phase(data_2)
data_31, data_32, data_33 = f.forced_dws_3phase(data_3)
N = T/(new_dt3)
P0_start, P0_end = np.floor(p_min/new_dt3), np.ceil(p_max/new_dt3)
P0s3=np.arange(P0_start,P0_end,1)
SNs9_11 ,SNs9_12 ,SNs9_13 ,SNs9_21 ,SNs9_22 = [],[],[],[],[]
SNs9_23 ,SNs9_31 ,SNs9_32 ,SNs9_33 = [],[],[],[]
sigma_total = sigma_total*np.sqrt(3)
for p0 in P0s3:
p0=int(p0)
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin'
continue
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
p0_sec = p0*new_dt3
xwrap_11 = FFA.XWrap2(data_11,p0, fill_value=fill_value, pow2=True)
xwrap_21 = FFA.XWrap2(data_21,p0, fill_value=fill_value, pow2=True)
xwrap_31 = FFA.XWrap2(data_31,p0, fill_value=fill_value, pow2=True)
xwrap_12 = FFA.XWrap2(data_12,p0, fill_value=fill_value, pow2=True)
xwrap_22 = FFA.XWrap2(data_22,p0, fill_value=fill_value, pow2=True)
xwrap_32 = FFA.XWrap2(data_32,p0, fill_value=fill_value, pow2=True)
xwrap_13 = FFA.XWrap2(data_13,p0, fill_value=fill_value, pow2=True)
xwrap_23 = FFA.XWrap2(data_23,p0, fill_value=fill_value, pow2=True)
xwrap_33 = FFA.XWrap2(data_33,p0, fill_value=fill_value, pow2=True)
folds_11 = FFA.FFA(xwrap_11)
folds_21 = FFA.FFA(xwrap_21)
folds_31 = FFA.FFA(xwrap_31)
folds_12 = FFA.FFA(xwrap_12)
folds_22 = FFA.FFA(xwrap_22)
folds_32 = FFA.FFA(xwrap_32)
folds_13 = FFA.FFA(xwrap_13)
folds_23 = FFA.FFA(xwrap_23)
folds_33 = FFA.FFA(xwrap_33)
SN_11 = f.simple_SNR(folds_11, sigma_total , added_profs)
SN_21 = f.simple_SNR(folds_21, sigma_total , added_profs)
SN_31 = f.simple_SNR(folds_31, sigma_total , added_profs)
SN_12 = f.simple_SNR(folds_12, sigma_total , added_profs)
SN_22 = f.simple_SNR(folds_22, sigma_total , added_profs)
SN_32 = f.simple_SNR(folds_32, sigma_total , added_profs)
SN_13 = f.simple_SNR(folds_13, sigma_total , added_profs)
SN_23 = f.simple_SNR(folds_23, sigma_total , added_profs)
SN_33 = f.simple_SNR(folds_33, sigma_total , added_profs)
M = folds_11.shape[0]
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec = P *new_dt3
SNs9_11.append(SN_11)
SNs9_12.append(SN_12)
SNs9_13.append(SN_13)
SNs9_21.append(SN_21)
SNs9_22.append(SN_22)
SNs9_23.append(SN_23)
SNs9_31.append(SN_31)
SNs9_32.append(SN_32)
SNs9_33.append(SN_33)
all_Ps9.extend(Psec)
try:
SNs9_11 = np.concatenate(SNs9_11)
SNs9_12 = np.concatenate(SNs9_12)
SNs9_13 = np.concatenate(SNs9_13)
SNs9_21 = np.concatenate(SNs9_21)
SNs9_22 = np.concatenate(SNs9_22)
SNs9_23 = np.concatenate(SNs9_23)
SNs9_31 = np.concatenate(SNs9_31)
SNs9_32 = np.concatenate(SNs9_32)
SNs9_33 = np.concatenate(SNs9_33)
except :
continue
dt9s = [dt9]*len(SNs9_11)
if count==2 :
new_dt3 = new_dt3*3
dt27 = new_dt3
w=int(w*3)
data_111, data_112, data_113 = f.forced_dws_3phase(data_11)
data_211, data_212, data_213 = f.forced_dws_3phase(data_21)
data_311, data_312, data_313 = f.forced_dws_3phase(data_31)
data_121, data_122, data_123 = f.forced_dws_3phase(data_12)
data_221, data_222, data_223 = f.forced_dws_3phase(data_22)
data_321, data_322, data_323 = f.forced_dws_3phase(data_32)
data_131, data_132, data_133 = f.forced_dws_3phase(data_13)
data_231, data_232, data_233 = f.forced_dws_3phase(data_23)
data_331, data_332, data_333 = f.forced_dws_3phase(data_33)
all_Ps27 = []
N = T/(new_dt3)
P0_start, P0_end = np.floor(p_min/new_dt3), np.ceil(p_max/new_dt3)
P0s3=np.arange(P0_start,P0_end,1)
SNs27_111, SNs27_211, SNs27_311, SNs27_121 = [], [], [], []
SNs27_221, SNs27_321, SNs27_131, SNs27_231 = [], [], [], []
SNs27_331, SNs27_112, SNs27_212, SNs27_312 = [], [], [], []
SNs27_122, SNs27_222, SNs27_322, SNs27_132 = [], [], [], []
SNs27_232, SNs27_332, SNs27_113, SNs27_213 = [], [], [], []
SNs27_313, SNs27_123, SNs27_223, SNs27_323 = [], [], [], []
SNs27_133,SNs27_233,SNs27_333 = [], [], []
sigma_total = sigma_total*np.sqrt(3)
for p0 in P0s3:
p0=int(p0)
if p0==0 or p0 ==1:
print ' It tried to fold with period = 0 or 1 bin'
continue
M_real = float(float(N)/p0)
added_profs = 2**(int(math.floor(math.log(M_real,2)) + 1)) - M_real
p0_sec = p0*new_dt3
xwrap_111 = FFA.XWrap2(data_111,p0, fill_value=fill_value, pow2=True)
xwrap_112 = FFA.XWrap2(data_112,p0, fill_value=fill_value, pow2=True)
xwrap_113 = FFA.XWrap2(data_113,p0, fill_value=fill_value, pow2=True)
xwrap_121 = FFA.XWrap2(data_121,p0, fill_value=fill_value, pow2=True)
xwrap_122 = FFA.XWrap2(data_122,p0, fill_value=fill_value, pow2=True)
xwrap_123 = FFA.XWrap2(data_123,p0, fill_value=fill_value, pow2=True)
xwrap_131 = FFA.XWrap2(data_131,p0, fill_value=fill_value, pow2=True)
xwrap_132 = FFA.XWrap2(data_132,p0, fill_value=fill_value, pow2=True)
xwrap_133 = FFA.XWrap2(data_133,p0, fill_value=fill_value, pow2=True)
xwrap_211 = FFA.XWrap2(data_211,p0, fill_value=fill_value, pow2=True)
xwrap_212 = FFA.XWrap2(data_212,p0, fill_value=fill_value, pow2=True)
xwrap_213 = FFA.XWrap2(data_213,p0, fill_value=fill_value, pow2=True)
xwrap_221 = FFA.XWrap2(data_221,p0, fill_value=fill_value, pow2=True)
xwrap_222 = FFA.XWrap2(data_222,p0, fill_value=fill_value, pow2=True)
xwrap_223 = FFA.XWrap2(data_223,p0, fill_value=fill_value, pow2=True)
xwrap_231 = FFA.XWrap2(data_231,p0, fill_value=fill_value, pow2=True)
xwrap_232 = FFA.XWrap2(data_232,p0, fill_value=fill_value, pow2=True)
xwrap_233 = FFA.XWrap2(data_233,p0, fill_value=fill_value, pow2=True)
xwrap_311 = FFA.XWrap2(data_311,p0, fill_value=fill_value, pow2=True)
xwrap_312 = FFA.XWrap2(data_312,p0, fill_value=fill_value, pow2=True)
xwrap_313 = FFA.XWrap2(data_313,p0, fill_value=fill_value, pow2=True)
xwrap_321 = FFA.XWrap2(data_321,p0, fill_value=fill_value, pow2=True)
xwrap_322 = FFA.XWrap2(data_322,p0, fill_value=fill_value, pow2=True)
xwrap_323 = FFA.XWrap2(data_323,p0, fill_value=fill_value, pow2=True)
xwrap_331 = FFA.XWrap2(data_331,p0, fill_value=fill_value, pow2=True)
xwrap_332 = FFA.XWrap2(data_332,p0, fill_value=fill_value, pow2=True)
xwrap_333 = FFA.XWrap2(data_333,p0, fill_value=fill_value, pow2=True)
folds_111 = FFA.FFA(xwrap_111)
folds_112 = FFA.FFA(xwrap_112)
folds_113 = FFA.FFA(xwrap_113)
folds_211 = FFA.FFA(xwrap_211)
folds_212 = FFA.FFA(xwrap_212)
folds_213 = FFA.FFA(xwrap_213)
folds_311 = FFA.FFA(xwrap_311)
folds_312 = FFA.FFA(xwrap_312)
folds_313 = FFA.FFA(xwrap_313)
folds_121 = FFA.FFA(xwrap_121)
folds_122 = FFA.FFA(xwrap_122)
folds_123 = FFA.FFA(xwrap_123)
folds_221 = FFA.FFA(xwrap_221)
folds_222 = FFA.FFA(xwrap_222)
folds_223 = FFA.FFA(xwrap_223)
folds_321 = FFA.FFA(xwrap_321)
folds_322 = FFA.FFA(xwrap_322)
folds_323 = FFA.FFA(xwrap_323)
folds_131 = FFA.FFA(xwrap_131)
folds_132 = FFA.FFA(xwrap_132)
folds_133 = FFA.FFA(xwrap_133)
folds_231 = FFA.FFA(xwrap_231)
folds_232 = FFA.FFA(xwrap_232)
folds_233 = FFA.FFA(xwrap_233)
folds_331 = FFA.FFA(xwrap_331)
folds_332 = FFA.FFA(xwrap_332)
folds_333 = FFA.FFA(xwrap_333)
SN_111 = f.simple_SNR(folds_111, sigma_total , added_profs)
SN_211 = f.simple_SNR(folds_211, sigma_total , added_profs)
SN_311 = f.simple_SNR(folds_311, sigma_total , added_profs)
SN_121 = f.simple_SNR(folds_121, sigma_total , added_profs)
SN_221 = f.simple_SNR(folds_221, sigma_total , added_profs)
SN_321 = f.simple_SNR(folds_321, sigma_total , added_profs)
SN_131 = f.simple_SNR(folds_131, sigma_total , added_profs)
SN_231 = f.simple_SNR(folds_231, sigma_total , added_profs)
SN_331 = f.simple_SNR(folds_331, sigma_total , added_profs)
SN_112 = f.simple_SNR(folds_112, sigma_total , added_profs)
SN_212 = f.simple_SNR(folds_212, sigma_total , added_profs)
SN_312 = f.simple_SNR(folds_312, sigma_total , added_profs)
SN_122 = f.simple_SNR(folds_122, sigma_total , added_profs)
SN_222 = f.simple_SNR(folds_222, sigma_total , added_profs)
SN_322 = f.simple_SNR(folds_322, sigma_total , added_profs)
SN_132 = f.simple_SNR(folds_132, sigma_total , added_profs)
SN_232 = f.simple_SNR(folds_232, sigma_total , added_profs)
SN_332 = f.simple_SNR(folds_332, sigma_total , added_profs)
SN_113 = f.simple_SNR(folds_113, sigma_total , added_profs)
SN_213 = f.simple_SNR(folds_213, sigma_total , added_profs)
SN_313 = f.simple_SNR(folds_313, sigma_total , added_profs)
SN_123 = f.simple_SNR(folds_123, sigma_total , added_profs)
SN_223 = f.simple_SNR(folds_223, sigma_total , added_profs)
SN_323 = f.simple_SNR(folds_323, sigma_total , added_profs)
SN_133 = f.simple_SNR(folds_133, sigma_total , added_profs)
SN_233 = f.simple_SNR(folds_233, sigma_total , added_profs)
SN_333 = f.simple_SNR(folds_333, sigma_total , added_profs)
M = folds_111.shape[0]
P = p0 + (np.arange(M, dtype=np.float) / (M-1))
Psec = P *new_dt3
SNs27_111.append(SN_111)
SNs27_211.append(SN_211)
SNs27_311.append(SN_311)
SNs27_121.append(SN_121)
SNs27_221.append(SN_221)
SNs27_321.append(SN_321)
SNs27_131.append(SN_131)
SNs27_231.append(SN_231)
SNs27_331.append(SN_331)
SNs27_112.append(SN_112)
SNs27_212.append(SN_212)
SNs27_312.append(SN_312)
SNs27_122.append(SN_122)
SNs27_222.append(SN_222)
SNs27_322.append(SN_322)
SNs27_132.append(SN_132)
SNs27_232.append(SN_232)
SNs27_332.append(SN_332)
SNs27_113.append(SN_113)
SNs27_213.append(SN_213)
SNs27_313.append(SN_313)
SNs27_123.append(SN_123)
SNs27_223.append(SN_223)
SNs27_323.append(SN_323)
SNs27_133.append(SN_133)
SNs27_233.append(SN_233)
SNs27_333.append(SN_333)
all_Ps27.extend(Psec)
SNs27_111 = np.concatenate(SNs27_111)
SNs27_211 = np.concatenate(SNs27_211)
SNs27_311 = np.concatenate(SNs27_311)
SNs27_121 = np.concatenate(SNs27_121)
SNs27_221 = np.concatenate(SNs27_221)
SNs27_321 = np.concatenate(SNs27_321)
SNs27_131 = np.concatenate(SNs27_131)
SNs27_231 = np.concatenate(SNs27_231)
SNs27_331 = np.concatenate(SNs27_331)
SNs27_112 = np.concatenate(SNs27_112)
SNs27_212 = np.concatenate(SNs27_212)
SNs27_312 = np.concatenate(SNs27_312)
SNs27_122 = np.concatenate(SNs27_122)
SNs27_222 = np.concatenate(SNs27_222)
SNs27_322 = np.concatenate(SNs27_322)
SNs27_132 = np.concatenate(SNs27_132)
SNs27_232 = np.concatenate(SNs27_232)
SNs27_332 = np.concatenate(SNs27_332)
SNs27_113 = np.concatenate(SNs27_113)
SNs27_213 = np.concatenate(SNs27_213)
SNs27_313 = np.concatenate(SNs27_313)
SNs27_123 = np.concatenate(SNs27_123)
SNs27_223 = np.concatenate(SNs27_223)
SNs27_323 = np.concatenate(SNs27_323)
SNs27_133 = np.concatenate(SNs27_133)
SNs27_233 = np.concatenate(SNs27_233)
SNs27_333 = np.concatenate(SNs27_333)
dt27s = [dt27]*len(SNs27_111)
count+=1
if count_lim ==1:
return np.array([SNs3_1 , SNs3_2 , SNs3_3 , SNs9_11, SNs9_12, SNs9_13, SNs9_21, SNs9_22, SNs9_23, SNs9_31, SNs9_32,SNs9_33]), np.array([all_Ps3,all_Ps9]), [dt3s,dt9s]
if count_lim ==2:
return np.array([SNs3_1 , SNs3_2 , SNs3_3 , SNs9_11, SNs9_12, SNs9_13, SNs9_21, SNs9_22, SNs9_23, SNs9_31, SNs9_32,SNs9_33, SNs27_111 ,SNs27_211 ,SNs27_311 ,SNs27_121 ,SNs27_221 ,SNs27_321 ,
SNs27_131 ,SNs27_231 ,SNs27_331 ,SNs27_112 ,SNs27_212 ,SNs27_312 ,SNs27_122 ,SNs27_222 ,
SNs27_322 ,SNs27_132 ,SNs27_232 ,SNs27_332 ,SNs27_113 ,SNs27_213 ,SNs27_313 ,SNs27_123 ,
SNs27_223 ,SNs27_323 ,SNs27_133 ,SNs27_233 ,SNs27_333 ]), np.array([all_Ps3,all_Ps9, all_Ps27]), [dt3s,dt9s,dt27s]