In [1]:

    

import csv
import datetime
import dateutil.parser
import matplotlib.pyplot as plt
import netCDF4
import numpy
import os
%matplotlib


    

    




Using matplotlib backend: MacOSX

In [2]:

    

def get_data_from_netcdf(latitude,longitude,fire_date,window):
    # dictionary for met data
    met_data = {}
    # initialise constants
    latitude0 = -9.75
    longitude0 = 109.5
    lat_resolution = 0.75
    lon_resolution = 0.75
    nc_file_path = "/home/peter/hackfest/"
    # get the year
    year = fire_date.year
    # get the latitude and longitude indices
    lat_index = int(((latitude0-latitude)/lat_resolution)+0.5)
    lon_index = int(((longitude-longitude0)/lon_resolution)+0.5)
    # get the name of the netCDF file containing the data
    nc_file_name = str(year)+"_"+str(lat_index)+"_"+str(lon_index)+".nc"
    nc_full_name = nc_file_path+nc_file_name
    print " File name is: ",nc_full_name
    if not os.path.exists(nc_full_name):
        print " File "+nc_full_name+" not found, skipping ..."
        return met_data
    # get the data
    print " Opening file "+nc_file_name
    nc_file = netCDF4.Dataset(nc_full_name,'r')
    nc_time = nc_file.variables["time"][:]
    nc_time_units = getattr(nc_file.variables["time"],"units")
    dt_utc = netCDF4.num2date(nc_time,nc_time_units)
    start_date = fire_date - datetime.timedelta(days=window["before"])
    end_date = fire_date + datetime.timedelta(days=window["after"])
    if start_date<datetime.datetime(year,1,1,0,0,0):
        print " start_date before beginning of year, skipping ..."
        return met_data
    si = [n for n,dt in enumerate(dt_utc) if dt>start_date ][0]
    ei = [n for n,dt in enumerate(dt_utc) if dt>end_date ][0]
    met_data["DateTime"] = dt_utc[si:ei+1]
    met_data["Fsd"] = nc_file.variables["Fsd"][si:ei+1]
    met_data["Ta"] = nc_file.variables["Ta"][si:ei+1]
    met_data["RH"] = nc_file.variables["RH"][si:ei+1]
    met_data["Ws"] = nc_file.variables["Ws"][si:ei+1]
    met_data["Wd"] = nc_file.variables["Wd"][si:ei+1]
    met_data["Precip"] = nc_file.variables["Precip"][si:ei+1]
    nc_file.close()
    return met_data


    

In [3]:

    

# get the filename
file_path = "/home/peter/hackfest/"
year = 2015
csv_filename = file_path+"hotspot_"+str(year)+".csv"
erai_name = file_path+"ERAI_"+str(year)+".nc"
# sniff the file to see if we can find the dialect
csv_file = open(csv_filename,'rb')
dialect = csv.Sniffer().sniff(csv_file.readline(), [' ',',','\t'])
# rewind file
csv_file.seek(0)
csv_reader = csv.reader(csv_file,dialect)
# get the header line
header = csv_reader.next()
# close the file
csv_file.close()
# get a list of columns to be read
csv_list = ["load_dt","latitude","longitude"]
col_list = [header.index(item) for item in csv_list]
# read the csv file using numpy's genfromtxt
skip = 1
# define the missing values and the value with which to fill them
missing_values = {}
filling_values = {}
for item in col_list:
    missing_values[item] = ["NA","N/A","NAN","#NAME?","#VALUE!","#DIV/0!","#REF!"]
    filling_values[item] = float(-9999)
# read the CSV file
fire_data = numpy.genfromtxt(csv_filename,delimiter=dialect.delimiter,skip_header=skip,
                        names=header,usecols=col_list,missing_values=missing_values,
                        filling_values=filling_values,dtype=None)


    

In [2]:

    

plot_data = True
window = {"before":5,"after":0}
nrecs = len(fire_data["latitude"])
# test with first 5
# normal operation would use nrecs
nplots = 0
for i in range(nrecs):
    latitude = fire_data["latitude"][i]
    longitude = fire_data["longitude"][i]
    fire_date = dateutil.parser.parse(fire_data["load_dt"][i])
    met_data = get_data_from_netcdf(latitude,longitude,fire_date,window)
    if "DateTime" not in met_data: continue
    if plot_data and nplots<10:
        nplots = nplots+1
        fig = plt.figure()
        plt.subplot(311)
        plt.plot(met_data["DateTime"],met_data["Fsd"])
        plt.subplot(312)
        plt.plot(met_data["DateTime"],met_data["Ta"])
        plt.subplot(313)
        plt.plot(met_data["DateTime"],met_data["RH"])
        plt.show()


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-2-e6852d105a31> in <module>()
      1 plot_data = True
      2 window = {"before":5,"after":0}
----> 3 nrecs = len(fire_data["latitude"])
      4 # test with first 5
      5 # normal operation would use nrecs

NameError: name 'fire_data' is not defined

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