# header = pan.read_hdf(filename,'header')
#
# dataout_dict = {}
# for dtype in datatypes:
# dataout_dict[dtype] = pan.read_hdf(filename,dtype)
#
## store.close()
#
# return header, dataout_dict
if __name__=='__main__':
olddir = os.getcwd()
os.chdir('E:\CORALNet\ASCII_Files\Smoke2012\Whistler')
newdir = ltools.set_dir('Select Event Folder')
os.chdir(newdir)
PR_type = 'PR532'
BR_type = 'BR532'
MSK_type = 'PR532_msk'
#set altitude range and date step sizes
minalt = 150 # minimum altitude in meters
maxalt = 15000 # maximum altitude in meters
altstep = 30 # altitude step in meters
altrange = np.arange(minalt,maxalt+altstep,altstep)
start = []#datetime.datetime(2013,04,22,00)
end = []#datetime.datetime(2013,05,04,17)
import numpy as np
import os,sys
import LNC_tools as LNC
#----------------------------------------------------------------------------
#Uses tools created in LNC_tools to open all files in a folder and resample
#them to a regular spacing in altitude/date the concatenates them into one
#pandas dataframe and plots it using LNC_plot
#July 05, 2012
#----------------------------------------------------------------------------
olddir = os.getcwd()
#os.chdir('K:\CORALNet\Data\ASCII Files')
newdir = LNC.set_dir('Select Event Folder')
os.chdir(newdir)
files = os.listdir(newdir)
maskfiles = []
datafiles = []
procfiles = []
rawfiles = []
#set altitude range and date step sizes
altrange = np.arange(10,10010,10)#meters
timestep = '120S' #seconds
#set buffer around backscatter ratio of 1 for mask
