From ff0d3a7e7e4d076d95e8aff0dbf2f1ea18473602 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C3=89tienne=20Simon?= Date: Wed, 29 Apr 2015 00:02:27 -0400 Subject: Add data converter to hdf5 --- convert_data.py | 118 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 118 insertions(+) create mode 100755 convert_data.py (limited to 'convert_data.py') diff --git a/convert_data.py b/convert_data.py new file mode 100755 index 0000000..c58de3f --- /dev/null +++ b/convert_data.py @@ -0,0 +1,118 @@ +#!/usr/bin/env python +import os, h5py, csv, sys, numpy, theano, ast +from fuel.datasets.hdf5 import H5PYDataset + +test_size = 320 # `wc -l test.csv` - 1 # Minus 1 to ignore the header +train_size = 1710670 # `wc -l train.csv` - 1 + +stands_size = 63 # `wc -l metaData_taxistandsID_name_GPSlocation.csv` - 1 +taxi_id_size = 448 # `cut -d, -f 5 train.csv test.csv | sort -u | wc -l` - 1 +origin_call_size = 57124 # `cut -d, -f 3 train.csv test.csv | sort -u | wc -l` - 3 # Minus 3 to ignore "NA", "" and the header + +Call_type = h5py.special_dtype(enum=(numpy.int8, {'CENTRAL': 0, 'STAND': 1, 'STREET': 2})) +Day_type = h5py.special_dtype(enum=(numpy.int8, {'NORMAL': 0, 'HOLYDAY': 1, 'HOLYDAY_EVE': 2})) +Polyline = h5py.special_dtype(vlen=theano.config.floatX) + +taxi_id_dict = {} +origin_call_dict = {0: 0} + +def get_unique_taxi_id(val): + if val in taxi_id_dict: + return taxi_id_dict[val] + else: + taxi_id_dict[val] = len(taxi_id_dict) + return len(taxi_id_dict) - 1 + +def get_unique_origin_call(val): + if val in origin_call_dict: + return origin_call_dict[val] + else: + origin_call_dict[val] = len(origin_call_dict) + return len(origin_call_dict) - 1 + +def read_stands(input_directory, h5file): + stands_name = h5file.create_dataset('stands_name', shape=(stands_size+1,), dtype=('a', 24)) + stands_latitude = h5file.create_dataset('stands_latitude', shape=(stands_size+1,), dtype=theano.config.floatX) + stands_longitude = h5file.create_dataset('stands_longitude', shape=(stands_size+1,), dtype=theano.config.floatX) + stands_name[0] = 'None' + stands_latitude[0] = stands_longitude[0] = 0 + with open(os.path.join(input_directory, 'metaData_taxistandsID_name_GPSlocation.csv'), 'r') as f: + reader = csv.reader(f) + reader.next() # header + for line in reader: + id = int(line[0]) + stands_name[id] = line[1] + stands_latitude[id] = float(line[2]) + stands_longitude[id] = float(line[3]) + return {'stands': {array: (0, stands_size+1) for array in ['stands_name', 'stands_latitude', 'stands_longitude' ]}} + +def read_taxis(input_directory, h5file, dataset, prefix): + print >> sys.stderr, 'read %s: begin' % dataset + size=globals()['%s_size'%dataset] + trip_id = numpy.empty(shape=(size,), dtype='S19') + call_type = numpy.empty(shape=(size,), dtype=Call_type) + origin_call = numpy.empty(shape=(size,), dtype=numpy.int32) + origin_stand = numpy.empty(shape=(size,), dtype=numpy.int8) + taxi_id = numpy.empty(shape=(size,), dtype=numpy.int16) + timestamp = numpy.empty(shape=(size,), dtype=numpy.int32) + day_type = numpy.empty(shape=(size,), dtype=Day_type) + missing_data = numpy.empty(shape=(size,), dtype=numpy.bool) + latitude = numpy.empty(shape=(size,), dtype=Polyline) + longitude = numpy.empty(shape=(size,), dtype=Polyline) + with open(os.path.join(input_directory, '%s.csv'%dataset), 'r') as f: + reader = csv.reader(f) + reader.next() # header + id=0 + for line in reader: + if id%10000==0 and id!=0: + print >> sys.stderr, 'read %s: %d done' % (dataset, id) + trip_id[id] = line[0] + call_type[id] = ord(line[1][0]) - ord('A') + origin_call[id] = 0 if line[2]=='NA' or line[2]=='' else get_unique_origin_call(int(line[2])) + origin_stand[id] = 0 if line[3]=='NA' or line[3]=='' else int(line[3]) + taxi_id[id] = get_unique_taxi_id(int(line[4])) + timestamp[id] = int(line[5]) + day_type[id] = ord(line[6][0]) - ord('A') + missing_data[id] = line[7][0] == 'T' + polyline = numpy.array(ast.literal_eval(line[8]), dtype=theano.config.floatX) + latitude[id] = polyline[:, 1] if polyline.ndim==2 else polyline + longitude[id] = polyline[:, 0] if polyline.ndim==2 else polyline + id+=1 + splits = {} + print >> sys.stderr, 'read %s: writing' % dataset + for array in ['trip_id', 'call_type', 'origin_call', 'origin_stand', 'taxi_id', 'timestamp', 'day_type', 'missing_data', 'latitude', 'longitude']: + name = '%s%s' % (prefix, array) + h5file.create_dataset(name, data=locals()[array]) + splits[name] = (0, size) + print >> sys.stderr, 'read %s: end' % dataset + return {dataset: splits} + +def unique(h5file): + unique_taxi_id = h5file.create_dataset('unique_taxi_id', shape=(taxi_id_size,), dtype=numpy.int32) + assert len(taxi_id_dict) == taxi_id_size + for k, v in taxi_id_dict.items(): + unique_taxi_id[v] = k + + unique_origin_call = h5file.create_dataset('unique_origin_call', shape=(origin_call_size+1,), dtype=numpy.int32) + assert len(origin_call_dict) == origin_call_size+1 + for k, v in origin_call_dict.items(): + unique_origin_call[v] = k + + return {'unique': {'unique_taxi_id': (0, taxi_id_size), 'unique_origin_call': (0, origin_call_size+1)}} + +def convert(input_directory, save_path): + h5file = h5py.File(save_path, 'w') + split = {} + split.update(read_stands(input_directory, h5file)) + split.update(read_taxis(input_directory, h5file, 'test', 'test_')) + split.update(read_taxis(input_directory, h5file, 'train', '')) + split.update(unique(h5file)) + h5file.attrs['split'] = H5PYDataset.create_split_array(split) + h5file.flush() + h5file.close() + +if __name__ == '__main__': + if len(sys.argv) != 3: + print >> sys.stderr, 'Usage: %s download_dir output_file' % sys.argv[0] + sys.exit(1) + convert(sys.argv[1], sys.argv[2]) -- cgit v1.2.3