def test_unique(self):
import numpy as np
from cykhash import unique_int64
a = np.array([1,2,3,3,2,1], dtype=np.int64)
u = np.ctypeslib.as_array(unique_int64(a)) # there will be no reallocation
print(u) # [1,2,3] or any permutation of it
self.assertTrue(True)
def test_quick_tutorial_2(self):
import numpy as np
a = np.array([1,2,3,3,2,1], dtype=np.int64)
# actual usage:
from cykhash import unique_int64
unique_buffer = unique_int64(a) # unique element are exposed via buffer-protocol
# can be converted to a numpy-array without copying via
unique_array = np.ctypeslib.as_array(unique_buffer)
self.assertTrue(True)
import numpy as np
import pandas as pd
import sys
import resource
import psutil
from cykhash import unique_int64, unique_int32
fun_name = sys.argv[1]
N = int(sys.argv[2])
a = np.arange(N, dtype=np.int64)
process = psutil.Process()
old = process.memory_info().rss
old_max = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss * 1024
if fun_name == "pandas":
b = pd.unique(a)
else:
b = np.frombuffer(memoryview(unique_int64(a)))
new_max = resource.getrusage(resource.RUSAGE_SELF).ru_maxrss * 1024
if new_max > old_max:
overhead_in_bytes = new_max - old
print(len(b), overhead_in_bytes / float(N * 8))
else:
print(len(b), "too small")
def cykhash_unique64(bufs):
unique_int64(bufs[0])