import os

from sys import exit

from pylab import *

import question

from query_yes_no import query_yes_no

from down_data_in_parts_tot import down_data_in_parts

from kind_of_data import kind_of_data

from choose_variables_for_correlation import choose_variables_for_correlation

from search_operational_stations import search_operational_stations

from show_downloaded_file_names import show_downloaded_file_names

from interpolate_and_create_new_pytable import interpolate

from least_squares_fit import least_squares_fit

from get_station_ID_from_filename import get_station_ID_from_filename

from choose_one_variable import choose_one_variable

from plot_data import plot_data

from get_corresponding_values_MPV import get_corresponding_values_MPV

from get_corresponding_values_selection import get_corresponding_values_selection

from create_correlation_table import create_correlation_table

from interpolate_selection import interpolate_selection

print ''

print 'HH HH iii SSSS PPPPPPP A RRRRRRR CCCCCC

print 'HH HH iii SSSSSSSS PPPPPPPPP AAA RRRRRRRRRR CCC CCC

print 'HH HH SSS SSS PPP PPP AAAAA RRR RRR CCC CCC

print 'HH HH iii SSSSS PPP PPP AAA AAA RRR RRR CCC

print 'HHHHHHHHH iii SSSSSS PPPPPPPPP AAA AAA RRRRRRRR CCC

print 'HH HH iii SSS PPP AAAAAAAAAAA RRR RRR CCC CCC

print 'HH HH iii SSS SSS PPP AAA AAA RRR RRR CCC CCC

print 'HH HH iii SSSSSSSS PPP AAA AAA RRR RRR CCCCCC

print ''

print ''

print 'Welcome to HiSPARC download and correlation software!'

print ''

print 'With this program you can download HiSPARC data, plot data and search for a correlation between HiSPARC shower and/or weather variables.'

print ''

download_question = query_yes_no('Do you want to download DATA? (if not, then you must already have a datafile on your pc)')

stations = []

plot_variable1 = []

plot_variable2 = []

if download_question == True:

show_operational_stations = query_yes_no('Do you want to see a list with operational HiSPARC and WEATHER stations?')

if show_operational_stations == True:

search_operational_stations()

user_hisparc_station_id_1 = question.digit('Enter the HiSPARC STATION ID from which you want to download data ( e.g. 501 ): ')

stations.append(user_hisparc_station_id_1)

user_start_date_data_interval = question.digit_and_date('Enter START date data interval ( e.g. 2011,7,21 ) : ')

user_stop_date_data_interval = question.digit_and_date('Enter STOP date data interval ( e.g. 2011,7,22 ) : ')

list_file_names_station_1 = down_data_in_parts(user_hisparc_station_id_1, user_start_date_data_interval, user_stop_date_data_interval)

if not list_file_names_station_1:

sys.exit()

kind_of_data_in_table = kind_of_data(list_file_names_station_1)

show_downloaded_file_names(kind_of_data_in_table)

print ''

down_data_another_station = query_yes_no('Do you want to download data from another station?')

if down_data_another_station == True:

user_hisparc_station_id_2 = question.digit('Enter the HiSPARC STATION ID from which you want to download data ( e.g. 501 ): ')

stations.append(user_hisparc_station_id_2)

print ''

same_dates = query_yes_no('Do you want to use the SAME DATE INTERVAL you entered earlier?')

if same_dates == True:

list_file_names_station_2 = down_data_in_parts(user_hisparc_station_id_2, user_start_date_data_interval, user_stop_date_data_interval)

if not list_file_names_station_2:

sys.exit()

kind_of_data_in_station_2 = kind_of_data(list_file_names_station_2)

kind_of_data_in_table.extend(kind_of_data_in_station_2)

show_downloaded_file_names(kind_of_data_in_table)

elif same_dates == False:

user_start_date_data_interval = question.digit_and_date('Enter START date data interval as yyyy,mm,dd ( e.g. 2011,7,21 ) : ')

user_stop_date_data_interval = question.digit_and_date('Enter STOP date data interval ( e.g. 2011,7,22 ) : ')

list_file_names_station_2 = down_data_in_parts(user_hisparc_station_id_2, user_start_date_data_interval, user_stop_date_data_interval)

if not list_file_names_station_2:

sys.exit()

kind_of_data_in_station_2 = kind_of_data(list_file_names_station_2)

kind_of_data_in_table.extend(kind_of_data_in_station_2)

show_downloaded_file_names(kind_of_data_in_table)

print ''

plot_question = query_yes_no('Do you want to see a PLOT of your data (variable against timestamp)?')

if plot_question == True and download_question == False:

use_downloaded_files = False

print ''

print 'If you want to analyze data you must already have a data set on your pc.'

print 'Make sure it is located in: ' + os.getcwd()

elif plot_question == True and download_question == True:

use_downloaded_files = query_yes_no('Do you want to use the data you downloaded earlier?')

if plot_question == True and use_downloaded_files == True:

plot_variable1 = choose_one_variable(kind_of_data_in_table, stations) # e.g. plot_variable = [('event_rate','data_s501_2011,12,7_2011,12,8.h5','501','events','')]

values1, times, returntype = plot_data(plot_variable1)

if plot_question == True and use_downloaded_files == False:

list_files = []

stations = []

print ''

station_ID = question.digit("Enter the station ID that you want to use in your analysis ( e.g. 501 ) ")

stations.append(station_ID)

print ''

number_of_files = question.digit("Enter the NUMBER of FILENAMES for station %s that you want to use in your analysis ( e.g. 6 ): " % station_ID)

print ''

print "You are going to enter filenames ( e.g. data_s501_2011,7,21_2011,7,22.h5 )"

print 'Enter the filenames in CHRONOLOGICAL ORDER. '

print ''

for j in range(1, int(number_of_files) + 1):

while True:

filename = raw_input('For station %s enter filename number %d: ' % (station_ID, j))

ID = get_station_ID_from_filename(filename)

if ID in stations:

list_files.append(filename) # pas 'kind of data' aan zodat kijkt of hetzelfde station

break

else:

print "Oops! The filename you entered does not match the station ID you entered earlier. Try again..."

kind_of_data_in_table = kind_of_data(list_files) # e.g. [('data_s501_2011,6,30_2011,6,30.h5', True, True), ('data_s502_2011,6,30_2011,6,30.h5', True, False)]

plot_variable1 = choose_one_variable(kind_of_data_in_table, stations) #e.g. plot_variable = [('event_rate','data_s501_2011,12,7_2011,12,8.h5','501','events','')]

values1, times, returntype = plot_data(plot_variable1)

print ''

correlate_question = query_yes_no('Do you want to CORRELATE data?')

use_plotted_files = False

if plot_question == True and correlate_question == True:

use_plotted_files = query_yes_no('Do you want to use the data you plotted earlier?')

if use_plotted_files == True:

print ''

print 'You are going to enter the specifications for the OTHER variable for correlation'

print ''

list_files = []

stations = []

print ''

station_ID = question.digit("Enter the station ID that you want to use in your analysis ( e.g. 501 ) ")

stations.append(station_ID)

print ''

number_of_files = question.digit("Enter the NUMBER of FILENAMES for station %s that you want to use in your analysis ( e.g. 6 ): " % station_ID)

print ''

print "You are going to enter filenames ( e.g. data_s501_2011,7,21_2011,7,21.h5 )"

print 'Enter the filenames in CHRONOLOGICAL ORDER. '

print ''

for j in range(1, int(number_of_files) + 1):

while True:

filename = raw_input('For station %s enter filename number %d: ' % (station_ID, j))

if os.path.exists(filename):

ID = get_station_ID_from_filename(filename)

print stations

if ID in stations:

list_files.append(filename)

break

else:

print "Oops! The filename you entered does not match the station ID you entered earlier. Try again..."

else:

print "Oops! The filename you entered does not exist. Try again..."

kind_of_data_in_table = kind_of_data(list_files) # e.g. [('data_s501_2011,6,30_2011,6,30.h5', True, True), ('data_s502_2011,6,30_2011,6,30.h5', True, False)]

plot_variable2 = choose_one_variable(kind_of_data_in_table, stations) #e.g. plot_variable = [('event_rate','data_s501_2011,12,7_2011,12,8.h5','501','events')]

if returntype == 'MPV':

if len(times) > 1:

mean_variable_list = get_corresponding_values_MPV(plot_variable2, times)

filen = create_correlation_table(plot_variable1, plot_variable2, values1, mean_variable_list, int(times[1] - times[0]))

least_squares_fit(filen, plot_variable1, plot_variable2)

else:

print 'Correlation is not possible with one data point.'

elif returntype == 'whole':

print 'b'

filen = interpolate(plot_variable1, plot_variable2) # e.g. cor_data_barometer_501_event_rate_502.h5

least_squares_fit(filen, plot_variable1, plot_variable2)

elif returntype == 'part':

complementary_variable2_list = get_corresponding_values_selection(plot_variable2, times)

filen = interpolate_selection(array(zip(times, values1)), complementary_variable2_list)

least_squares_fit(filen, plot_variable1, plot_variable2)

else:

print 'problem'

print ''

if correlate_question == True and download_question == False and use_plotted_files == False:

use_downloaded_files = False

print 'If you want to analyze data you must already have a data set on your pc.'

print 'Make sure it is located at: ' + os.getcwd()

elif correlate_question == True and download_question == True and use_plotted_files == False:

use_downloaded_files = query_yes_no('Do you want to use the data you downloaded earlier?')

if correlate_question == True and use_downloaded_files == True and use_plotted_files == False:

#e.g. variable1 = [('event_rate','data_s501_2011,12,7_2011,12,8.h5','501','events')]

variable1, variable2 = choose_variables_for_correlation(kind_of_data_in_table, stations)

filen = interpolate(variable1, variable2) # e.g. cor_data_barometer_501_event_rate_502.h5

least_squares_fit(filen, variable1, variable2)

if correlate_question == True and use_downloaded_files == False and use_plotted_files == False:

print ''

number_of_stations = question.digit_with_constraint("Enter the NUMBER of STATION IDs that you want to use in your analysis ( e.g. 2 ): ")

list_files = []

stations = []

for i in range(1, int(number_of_stations) + 1):

print ''

station_ID = question.digit("Enter the station ID for station %d: " % i)

stations.append(station_ID)

print ''

number_of_files = question.digit("Enter the NUMBER of FILENAMES for station %s that you want to use in your analysis ( e.g. 6 ): " % station_ID)

print ''

print "You are going to enter filenames ( e.g. data_s501_2011,7,21_2011,7,21.h5 )"

print 'Enter the filenames in CHRONOLOGICAL ORDER. '

print ''

for j in range(1, int(number_of_files) + 1):

while True:

filename = raw_input('For station %d enter filename number %d: ' % (station_ID, j))

ID = get_station_ID_from_filename(filename)

if ID in stations:

list_files.append(filename) # pas 'kind of data' aan zodat kijkt of hetzelfde station

break

else:

print "Oops! The filename you entered does not match the station ID you entered earlier. Try again..."

kind_of_data_in_table = kind_of_data(list_files) # e.g. [('data_s501_2011,6,30_2011,6,30.h5', True, True), ('data_s502_2011,6,30_2011,6,30.h5', True, False)]

variable1, variable2 = choose_variables_for_correlation(kind_of_data_in_table, stations) # e.g. [('barometer', 'data_s501_2011,6,30_2011,6,30.h5', '501', 'weather')], [('event_rate', 'data_s502_2011,6,30_2011,6,30.h5', '502', 'events')]

filen = interpolate(variable1, variable2) # e.g. cor_data_barometer_501_event_rate_502.h5

least_squares_fit(filen, variable1, variable2)