import vaex as vx
import sys
import timeit
import numpy as np
import argparse

subspace, dataset, limits = None, None, None

def main(argv):
	global subspace, dataset, limits
	parser = argparse.ArgumentParser(argv[0])
	parser.add_argument("-N", help="run each batch N times (default: %(default)s)", type=int, default=5)
	parser.add_argument("-f", "--fraction", help="fraction of dataset to use (default: %(default)s)", default=1., type=float)
	parser.add_argument("-b", "--buffer-size", default=vx.execution.buffer_size_default, help="buffer size per thread (default: %(default)s)", type=int)
	parser.add_argument("-r", "--repeat", default=5, help="repeat benchmark X times (default: %(default)s)", type=int)
	parser.add_argument("-c", "--cpu-count", default=vx.multithreading.thread_count_default, help="thread count/cpu count (default: %(default)s)", type=int)
	parser.add_argument("filename", help="filename of dataset to use")
	parser.add_argument("expressions", help="list of expressions to export (or all when empty)", nargs="*")

	args = parser.parse_args(argv[1:])
	vx.execution.buffer_size_default = args.buffer_size
	vx.multithreading.thread_count_default = args.cpu_count

	progressbar = False
	fn = args.filename
	#print(("opening", fn))
	dataset = vx.open(fn)
	dataset.set_active_fraction(args.fraction)
	#dataset = vx.open_many(fn)

	expressions = args.expressions
	#print "subspace", expressions
	subspace = dataset(*expressions)
	byte_size = len(dataset) * len(expressions) * 8
	#sums = subspace.sum()

	limits = subspace.minmax()
	print(limits)

	N = args.N
	print("benchmarking minmax")
	expr = "subspace.minmax()"
	times = timeit.repeat(expr, setup="from vaex.benchmark import subspace, dataset, np", repeat=args.repeat, number=N)
	print("minimum time", min(times)/N)
	bandwidth = [byte_size/1024.**3/(time/N) for time in times]
	print("%f GiB/s" % max(bandwidth))

	speed = [len(dataset)/(time/N)/1e9 for time in times]
	print("%f billion rows/s " % max(speed))

	print()
	print("benchmarking histogram")
	expr = "subspace.histogram(limits, 256)"
	times = timeit.repeat(expr, setup="from vaex.benchmark import subspace, dataset, np, limits", repeat=args.repeat, number=N)
	print("minimum time", min(times)/N)
	bandwidth = [byte_size/1024.**3/(time/N) for time in times]
	print("%f GiB/s" % max(bandwidth))

	speed = [len(dataset)/(time/N)/1e9 for time in times]
	print("%f billion rows/s " % max(speed))
	print()

	#expr = "np.nansum(dataset.columns['x'])"
	print("sum=", subspace.sum())
	print("benchmarking sum")
	expr = "subspace.sum()"
	times = timeit.repeat(expr, setup="from vaex.benchmark import subspace, dataset, np", repeat=args.repeat, number=N)
	print("minimum time", min(times)/N)
	bandwidth = [byte_size/1024.**3/(time/N) for time in times]
	print("%f GiB/s" % max(bandwidth))


import vaex as vx
import sys
import timeit
import numpy as np
import argparse

subspace, dataset, limits = None, None, None

def main(argv):
	global subspace, dataset, limits
	parser = argparse.ArgumentParser(argv[0])
	parser.add_argument("-N", help="run each batch N times (default: %(default)s)", type=int, default=5)
	parser.add_argument("-f", "--fraction", help="fraction of dataset to use (default: %(default)s)", default=1., type=float)
	parser.add_argument("-b", "--buffer-size", default=vx.execution.buffer_size_default, help="buffer size per thread (default: %(default)s)", type=int)
	parser.add_argument("-r", "--repeat", default=5, help="repeat benchmark X times (default: %(default)s)", type=int)
	parser.add_argument("-c", "--cpu-count", default=vx.multithreading.thread_count_default, help="thread count/cpu count (default: %(default)s)", type=int)
	parser.add_argument("filename", help="filename of dataset to use")
	parser.add_argument("expressions", help="list of expressions to export (or all when empty)", nargs="*")

	args = parser.parse_args(argv[1:])
	vx.execution.buffer_size_default = args.buffer_size
	vx.multithreading.thread_count_default = args.cpu_count

	progressbar = False
	fn = args.filename
	#print(("opening", fn))
	dataset = vx.open(fn)
	dataset.set_active_fraction(args.fraction)
	#dataset = vx.open_many(fn)

	expressions = args.expressions
	#print "subspace", expressions
	subspace = dataset(*expressions)
	byte_size = len(dataset) * len(expressions) * 8
	#sums = subspace.sum()

	limits = subspace.minmax()
	print(limits)

	N = args.N
	print("benchmarking minmax")
	expr = "subspace.minmax()"
	times = timeit.repeat(expr, setup="from vaex.benchmark import subspace, dataset, np", repeat=args.repeat, number=N)
	print("minimum time", min(times)/N)
	bandwidth = [byte_size/1024.**3/(time/N) for time in times]
	print("%f GiB/s" % max(bandwidth))

	speed = [len(dataset)/(time/N)/1e9 for time in times]
	print("%f billion rows/s " % max(speed))

	print()
	print("benchmarking histogram")
	expr = "dataset.count(binby=['{}', '{}'])".format(*expressions)
	times = timeit.repeat(expr, setup="from vaex.benchmark import subspace, dataset, np, limits", repeat=args.repeat, number=N)
	print("minimum time", min(times)/N)
	bandwidth = [byte_size/1024.**3/(time/N) for time in times]
	print("%f GiB/s" % max(bandwidth))

	speed = [len(dataset)/(time/N)/1e9 for time in times]
	print("%f billion rows/s " % max(speed))
	print()

	#expr = "np.nansum(dataset.columns['x'])"
	print("sum=", subspace.sum())
	print("benchmarking sum")
	expr = "subspace.sum()"
	times = timeit.repeat(expr, setup="from vaex.benchmark import subspace, dataset, np", repeat=args.repeat, number=N)
	print("minimum time", min(times)/N)
	bandwidth = [byte_size/1024.**3/(time/N) for time in times]
	print("%f GiB/s" % max(bandwidth))


use newstyle histogram