import mathutils
from mathutils import *
from plotutils import *

#f = "2018/03/12/20180312_231754_WireScan.h5|"
#f = "2018/03/12/20180312_233008_WireScan.h5|"
f = "2018/03/12/20180312_234230_WireScan.h5|"
#p = f + "/x_000"
p = f + "/y_000"

def gd(i):
    global p
    return load_data(p+str(i)+"/blm1")

def gt(i):
    global p
    return load_data(p+str(i)+"/Time")
def gp(i):
    global p
    return load_data(p+str(i)+"/w_pos")

def bg(i):
    global f
    return load_data(f+"/background/blm" + str(i))

def bga(blm):
    global f
    return get_attributes(f+"/background/blm" + str(blm))["Mean"]

def sig(i):
    bg = bga(1)
    ret = gd(i)
    #ret = blm_remove_spikes(ret)
    ret =  [v-bg for v in ret]   
    return ret


epsilon = 1e-10
def make_monotonic(x):
    for i in range(len(x)-1):
        if x[i+1]<= x[i]:
            x[i+1] = x[i] + epsilon
    return x
    
x = [x1,x2,x3,x4,x5,x6]= [gp(1), gp(2), gp(3), gp(4), gp(5), gp(6)]

#plot(x, ["1", "2", "3", "4", "5", "6"], xdata = x)



s = [s1, s1, s3, s4, s5, s6] = [sig(1), sig(2), sig(3), sig(4), sig(5), sig(6)]

p=plot(s, ["1", "2", "3", "4", "5", "6"], xdata = x)
#print call_jep(MODULE, "profile_rms_stats", [to_npa(x), to_npa(y), 0, 3.5])

run("Diagnostics/sig_process_wrapper")


print "------------------ Gauss ---------------------------"
sum_mean=0.0
sum_sigma=0.0
sum_norm=0.0
mathutils.MAX_EVALUATIONS = mathutils.MAX_EVALUATIONS*10
for i in range(6):
    [off, amp, com, sigma] = profile_gauss_stats(x[i], s[i], off=None, amp=None, com=None, sigma=None)    
    #[amp, com, sigma] = profile_gauss_stats(x[i], s[i], off=None, amp=None, com=None, sigma=None, with_offset=False)    
    """
    if i%2 == 0:
        (amp, com, sigma) = fit_gaussian(s[i], make_monotonic(x[i]))
    else :
        (amp, com, sigma) = fit_gaussian(s[i][::-1], make_monotonic(x[i][::-1]))    
    """
    #print "Pass " , (i+1) ,": " , [off, amp, com, sigma]
    sum_mean = sum_mean + com
    sum_sigma = sum_sigma + sigma
    sum_norm = sum_norm + amp

    plot_function(p[i], Gaussian(amp, com, sigma), "Fit",x[i], show_points = False, show_lines = True, color = Color.BLUE)


ave_mean, ave_sigma = sum_mean/6, sum_sigma/6
print "Average: mean=" , ave_mean, ave_sigma



    
print "------------------ RMS ---------------------------"
sum_com=0.0
sum_sigma=0.0
for i in range(6):
    #[rms_com, rms_sigma] =  profile_rms_stats(x[i], s[i],noise_std=0, n_sigma=3.5)
    [off, amp, com, sigma] = profile_gauss_stats(x[i], s[i], off=None, amp=None, com=None, sigma=None)    
    [rms_com, rms_sigma] =  profile_rms_stats_with_estimate(x[i], s[i], com_estimate = com, window_size = sigma *3.5)
    print "Pass " , (i+1) ,": " , [rms_com, rms_sigma]
    sum_com = sum_com+ rms_com
    sum_sigma = sum_sigma + rms_sigma    
print "Average: mean=" , sum_com/6, " sigma=", sum_sigma/6