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CLN: cleanup hashtable.pyx #10111

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May 13, 2015
Merged

CLN: cleanup hashtable.pyx #10111

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40 changes: 12 additions & 28 deletions pandas/hashtable.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -211,7 +211,6 @@ cdef class StringHashTable(HashTable):
def unique(self, ndarray[object] values):
cdef:
Py_ssize_t i, n = len(values)
Py_ssize_t idx, count = 0
int ret = 0
object val
char *buf
Expand All @@ -223,12 +222,9 @@ cdef class StringHashTable(HashTable):
buf = util.get_c_string(val)
k = kh_get_str(self.table, buf)
if k == self.table.n_buckets:
k = kh_put_str(self.table, buf, &ret)
# print 'putting %s, %s' % (val, count)
count += 1
kh_put_str(self.table, buf, &ret)
uniques.append(val)

# return None
return uniques.to_array()

def factorize(self, ndarray[object] values):
Expand Down Expand Up @@ -258,7 +254,6 @@ cdef class StringHashTable(HashTable):
labels[i] = count
count += 1

# return None
return reverse, labels

cdef class Int32HashTable(HashTable):
Expand Down Expand Up @@ -319,7 +314,6 @@ cdef class Int32HashTable(HashTable):
def lookup(self, ndarray[int32_t] values):
cdef:
Py_ssize_t i, n = len(values)
int ret = 0
int32_t val
khiter_t k
ndarray[int32_t] locs = np.empty(n, dtype=np.int64)
Expand Down Expand Up @@ -357,7 +351,6 @@ cdef class Int32HashTable(HashTable):
labels[i] = count
count += 1

# return None
return reverse, labels

cdef class Int64HashTable: #(HashTable):
Expand Down Expand Up @@ -518,7 +511,6 @@ cdef class Int64HashTable: #(HashTable):
def unique(self, ndarray[int64_t] values):
cdef:
Py_ssize_t i, n = len(values)
Py_ssize_t idx, count = 0
int ret = 0
ndarray result
int64_t val
Expand All @@ -529,9 +521,8 @@ cdef class Int64HashTable: #(HashTable):
val = values[i]
k = kh_get_int64(self.table, val)
if k == self.table.n_buckets:
k = kh_put_int64(self.table, val, &ret)
kh_put_int64(self.table, val, &ret)
uniques.append(val)
count += 1

result = uniques.to_array()

Expand Down Expand Up @@ -644,7 +635,6 @@ cdef class Float64HashTable(HashTable):
def unique(self, ndarray[float64_t] values):
cdef:
Py_ssize_t i, n = len(values)
Py_ssize_t idx, count = 0
int ret = 0
float64_t val
khiter_t k
Expand All @@ -657,9 +647,8 @@ cdef class Float64HashTable(HashTable):
if val == val:
k = kh_get_float64(self.table, val)
if k == self.table.n_buckets:
k = kh_put_float64(self.table, val, &ret)
kh_put_float64(self.table, val, &ret)
uniques.append(val)
count += 1
elif not seen_na:
seen_na = 1
uniques.append(ONAN)
Expand Down Expand Up @@ -786,7 +775,6 @@ cdef class PyObjectHashTable(HashTable):
def unique(self, ndarray[object] values):
cdef:
Py_ssize_t i, n = len(values)
Py_ssize_t idx, count = 0
int ret = 0
object val
ndarray result
Expand All @@ -800,7 +788,7 @@ cdef class PyObjectHashTable(HashTable):
if not _checknan(val):
k = kh_get_pymap(self.table, <PyObject*>val)
if k == self.table.n_buckets:
k = kh_put_pymap(self.table, <PyObject*>val, &ret)
kh_put_pymap(self.table, <PyObject*>val, &ret)
uniques.append(val)
elif not seen_na:
seen_na = 1
Expand Down Expand Up @@ -918,7 +906,7 @@ cdef class Int64Factorizer:

cdef build_count_table_int64(ndarray[int64_t] values, kh_int64_t *table):
cdef:
int k
khiter_t k
Py_ssize_t i, n = len(values)
int ret = 0

Expand All @@ -938,7 +926,6 @@ cpdef value_count_int64(ndarray[int64_t] values):
cdef:
Py_ssize_t i
kh_int64_t *table
int ret = 0
int k

table = kh_init_int64()
Expand All @@ -961,7 +948,7 @@ cdef build_count_table_object(ndarray[object] values,
ndarray[uint8_t, cast=True] mask,
kh_pymap_t *table):
cdef:
int k
khiter_t k
Py_ssize_t i, n = len(values)
int ret = 0

Expand All @@ -983,7 +970,7 @@ cdef build_count_table_object(ndarray[object] values,
cpdef value_count_object(ndarray[object] values,
ndarray[uint8_t, cast=True] mask):
cdef:
Py_ssize_t i = len(values)
Py_ssize_t i
kh_pymap_t *table
int k

Expand All @@ -1008,9 +995,7 @@ def mode_object(ndarray[object] values, ndarray[uint8_t, cast=True] mask):
int count, max_count = 2
int j = -1 # so you can do +=
int k
Py_ssize_t i, n = len(values)
kh_pymap_t *table
int ret = 0

table = kh_init_pymap()
build_count_table_object(values, mask, table)
Expand All @@ -1036,11 +1021,10 @@ def mode_object(ndarray[object] values, ndarray[uint8_t, cast=True] mask):

def mode_int64(ndarray[int64_t] values):
cdef:
int val, max_val = 2
int count, max_count = 2
int j = -1 # so you can do +=
int k
kh_int64_t *table
list uniques = []

table = kh_init_int64()

Expand All @@ -1049,12 +1033,12 @@ def mode_int64(ndarray[int64_t] values):
modes = np.empty(table.n_buckets, dtype=np.int64)
for k in range(table.n_buckets):
if kh_exist_int64(table, k):
val = table.vals[k]
count = table.vals[k]

if val == max_val:
if count == max_count:
j += 1
elif val > max_val:
max_val = val
elif count > max_count:
max_count = count
j = 0
else:
continue
Expand Down