@@ -457,42 +457,42 @@ def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
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cdef:
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int tiebreak
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Py_ssize_t i, j, N, K
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- int64_t val_start=0, grp_start=0, dups=0, sum_ranks=0, vals_seen =1
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+ int64_t val_start=0, grp_start=0, dups=0, sum_ranks=0, grp_vals_seen =1
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int64_t grp_na_count=0
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ndarray[int64_t] _as
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- ndarray[{{c_type}}] _values
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+ ndarray[{{c_type}}] masked_vals
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ndarray[uint8_t] mask
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bint pct, ascending, keep_na
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- {{c_type}} nan_value
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+ {{c_type}} nan_fill_val
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tiebreak = tiebreakers[kwargs['ties_method']]
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ascending = kwargs['ascending']
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pct = kwargs['pct']
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keep_na = kwargs['na_option'] == 'keep'
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N, K = (<object> values).shape
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- _values = np.array(values[:, 0], copy=True)
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+ masked_vals = np.array(values[:, 0], copy=True)
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{{if name=='int64'}}
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- mask = (_values == {{nan_val}}).astype(np.uint8)
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+ mask = (masked_vals == {{nan_val}}).astype(np.uint8)
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{{else}}
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- mask = np.isnan(_values ).astype(np.uint8)
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+ mask = np.isnan(masked_vals ).astype(np.uint8)
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{{endif}}
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if ascending ^ (kwargs['na_option'] == 'top'):
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{{if name == 'int64'}}
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- nan_value = np.iinfo(np.int64).max
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+ nan_fill_val = np.iinfo(np.int64).max
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{{else}}
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- nan_value = np.inf
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+ nan_fill_val = np.inf
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{{endif}}
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- order = (_values , mask, labels)
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+ order = (masked_vals , mask, labels)
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else:
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{{if name == 'int64'}}
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- nan_value = np.iinfo(np.int64).min
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+ nan_fill_val = np.iinfo(np.int64).min
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{{else}}
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- nan_value = -np.inf
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+ nan_fill_val = -np.inf
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{{endif}}
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- order = (_values , ~mask, labels)
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- np.putmask(_values , mask, nan_value )
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+ order = (masked_vals , ~mask, labels)
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+ np.putmask(masked_vals , mask, nan_fill_val )
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_as = np.lexsort(order)
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@@ -504,7 +504,7 @@ def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
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dups += 1
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sum_ranks += i - grp_start + 1
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- if keep_na and _values [_as[i]] == nan_value :
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+ if keep_na and masked_vals [_as[i]] == nan_fill_val :
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grp_na_count += 1
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out[_as[i], 0] = nan
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else:
@@ -525,24 +525,24 @@ def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
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out[_as[j], 0] = 2 * i - j - dups + 2 - grp_start
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elif tiebreak == TIEBREAK_DENSE:
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for j in range(i - dups + 1, i + 1):
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- out[_as[j], 0] = vals_seen
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+ out[_as[j], 0] = grp_vals_seen
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{{if name=='int64'}}
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if (i == N - 1 or (
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- (_values [_as[i]] != _values [_as[i+1]]) and not
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- (_values [_as[i]] == nan_value and
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- _values [_as[i+1]] == nan_value
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+ (masked_vals [_as[i]] != masked_vals [_as[i+1]]) and not
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+ (masked_vals [_as[i]] == nan_fill_val and
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+ masked_vals [_as[i+1]] == nan_fill_val
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))):
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{{else}}
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if (i == N - 1 or (
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- (_values [_as[i]] != _values [_as[i+1]]) and not
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- (isnan(_values [_as[i]]) and
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- isnan(_values [_as[i+1]])
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+ (masked_vals [_as[i]] != masked_vals [_as[i+1]]) and not
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+ (isnan(masked_vals [_as[i]]) and
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+ isnan(masked_vals [_as[i+1]])
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))):
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{{endif}}
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dups = sum_ranks = 0
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val_start = i
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- vals_seen += 1
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+ grp_vals_seen += 1
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# Move to the next group, cleaning up any values
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if i == N - 1 or labels[_as[i]] != labels[_as[i+1]]:
@@ -552,7 +552,7 @@ def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
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- grp_na_count)
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grp_na_count = 0
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grp_start = i + 1
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- vals_seen = 1
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+ grp_vals_seen = 1
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{{endfor}}
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