#!/usr/bin/env python 


from scipy import io
import numpy as np
import csv
import matplotlib as mp
import matplotlib.pyplot as plt
import os, glob
from matplotlib.font_manager import FontProperties

#path = 'C:\Users\c\Desktop\import'
#for f in glob.glob( os.path.join(path, '*.mat')):
#    matfile = scipy.io.loadmat(f, struct_as_record=True)
    

flight_number = '653201001031841'
inMATFile = flight_number + '.mat'
raw_data = io.loadmat(inMATFile, struct_as_record=True, squeeze_me=False) # dict
test_matrix = np.array(raw_data) # ndarray


file = open(flight_number+'-retinax-parameters.txt','w')
mywriter = csv.writer(file)
parameter_headings = "#, description, short name (aka alpha), size (X by 1), rate, dtype, units, example value"
mywriter.writerow([parameter_headings])

#counter
i = 1

#looping through the parameter matrices in 1 .mat file. There are a total of 189 parameters in a .mat file.
for j in raw_data.keys(): 
    
    #there are a few meta parameters that trip up to loop, so we blank them but still count them, e.g. #162 
    if j[0] == '_':
        #print i
        line = "%3s, %s" %(i,j)
        mywriter.writerow([line])
        i += 1
        continue
    
    #for each of the valid parameter matrices, we pull out the relevant meta data
    
    #rate: sampling frequency [Hz]
    rate = raw_data[j]['Rate'][0][0]
    
    #units: unit of the parameter
    try:
        units = raw_data[j]['Units'][0][0][0]
    except IndexError:
        units =  " "
    
    #description: long form description of the parameter
    description = raw_data[j]['Description'][0][0][0]
    
    #alpha: short form description of the parameter
    alpha = raw_data[j]['Alpha'][0][0][0]
    
    #data: this is the matrix holding the values of the parameter. the length of this matrix correlates to the 
    #frequency of the sampling rate.
    data = raw_data[j]['data'][0][0]
    shape = data.shape
    size = data.size
    dtype = data.dtype
    value_lookahead = data[size-1]
    
    #create a line per parameter and write to file
    line = "%3s, %35s, %-20s, %5i, %5i, %10s, %15s, %s" %(i, description, alpha, size, rate, dtype, units, value_lookahead)
    #print line
    mywriter.writerow([line])
    
    #increment counter
    i += 1

#close file
file.close()

#some other test stuff to easily print to the stout.
abrk_raw = raw_data['ABRK']
abrk = raw_data['ABRK']['data'][0][0]
size = abrk.size
if (len(raw_data) == 189):
    print 'SUCCESS'


# playing around with printing the graphs to images

font0 = FontProperties()
font0.set_style('italic')
font0.set_weight('bold')
font0.set_size('x-small')


time = np.linspace(0,1,size)

b1 = raw_data['ALT']['data'][0][0]
b1 = b1[0:b1.size:4]

b2 = raw_data['AOAI']['data'][0][0]
b2 = b2[0:b2.size:4]

b3 = raw_data['TAS']['data'][0][0]
b3 = b3[0:b3.size:4]

b4 = raw_data['WOW']['data'][0][0]

plt.title(flight_number)

plt.subplot(4,1,1)
plt.plot(time,b1,'r')
plt.ylabel('Pressure Altitude (ALT)')

plt.subplot(4,1,2)
plt.plot(time,b2,'b')
plt.ylabel('Angle of Attack (IAOA)')

plt.subplot(4,1,3)
plt.plot(time,b3,'g')
plt.ylabel('True Air Speed (TAS)')

plt.subplot(4,1,4)
plt.plot(time,b4,'g')
plt.ylabel('Weight On Wheels (WOW)')
plt.xlabel('time (normalized)')

plt.savefig('test.png')
plt.show()