def benchmark_test(minsize, maxsize, step, repeat):
plot_data = []
y_sp = []
y_block = []
y_no = []
for i in range(minsize, maxsize, step):
test_sp = []
test_no = []
test_partial = []
test_complete = []
test_rook = []
test_block = []
for j in range(repeat):
# pos_def = tests.generate_pos_dif(i, 1, 1000)
A = np.random.randint(-1000, 1000, size=(i, i)) # change
# Ab = np.random.randint(-1000, 1000, size=(i, 1)) # change
time_start = time.clock()
sp.lu(A)
test_sp += [time.clock() - time_start]
time_start = time.clock()
lu.lu_in_place(A)
test_no += [time.clock() - time_start]
time_start = time.clock()
lu.lu_partial_pivot(A)
test_partial += [time.clock() - time_start]
time_start = time.clock()
lu.lu_complete_pivot(A)
test_complete += [time.clock() - time_start]
time_start = time.clock()
lu.lu_rook_pivot(A)
test_rook += [time.clock() - time_start]
time_start = time.clock()
lu_block.lu_partial_block(A, 32)
test_block += [time.clock() - time_start]
# time_start = time.clock()
# lu.lu_partial_pivot(A)
# test_no += [time.clock() - time_start]
print i, j
plot_data += [{
'y': test_sp,
'type':'box',
'marker':{'color': 'black'},
'name': str(i) + 'x' + str(i),
'boxpoints': False
}]
plot_data += [{
'y': test_no,
'type':'box',
'marker':{'color': 'grey'},
'name': str(i) + 'x' + str(i),
'boxpoints': False
}]
plot_data += [{
'y': test_partial,
'type':'box',
'marker':{'color': 'blue'},
'name': str(i) + 'x' + str(i),
'boxpoints': False
}]
plot_data += [{
'y': test_complete,
'type':'box',
'marker':{'color': 'red'},
'name': str(i) + 'x' + str(i),
'boxpoints': False
}]
plot_data += [{
'y': test_rook,
'type':'box',
'marker':{'color': 'green'},
'name': str(i) + 'x' + str(i),
'boxpoints': False
}]
plot_data += [{
'y': test_block,
'type':'box',
'marker':{'color': 'purple'},
'name': str(i) + 'x' + str(i),
'boxpoints': False
}]
# plot_data += [{
# 'y': test_no,
# 'type':'box',
# 'marker':{'color': 'blue'},
# 'name': str(i) + 'x' + str(i),
# 'boxpoints': False
# }]
#
# y_sp += [np.sum(test_sp) / len(test_sp)]
# y_block += [np.sum(test_block) / len(test_block)]
# y_no += [np.sum(test_no) / len(test_no)]
# print np.polyfit(range(len(y_sp)), y_sp, 1, full=True)
# print np.polyfit(range(len(y_sp)), y_sp, 2, full=True)
# print np.polyfit(range(len(y_block)), y_block, 1, full=True)
# print np.polyfit(range(len(y_block)), y_block, 2, full=True)
# print np.polyfit(range(len(y_no)), y_no, 1, full=True)
# print np.polyfit(range(len(y_no)), y_no, 2, full=True)
url = py.plot(plot_data, filename='Benchmark')
def test_lu_inplace(self):
rand_int_matrix = np.random.randint(-1000, 1000, size=(1000, 1000))
np.array_equal(lu.lu_in_place(rand_int_matrix)[0], lu.lu_inplace_with_dot(rand_int_matrix)[0])
np.array_equal(lu.lu_in_place(rand_int_matrix)[1], lu.lu_inplace_with_dot(rand_int_matrix)[1])