# 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