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Commit f672e760 authored by Bert Palm's avatar Bert Palm 🎇
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more better

parent 9b8b4c89
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2 merge requests!2Develop,!1complete rework
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dios/dios.py
+ 44
− 48
View file @ f672e760
......@@ -193,16 +193,23 @@ class DictOfSeries:
raise KeyError(key)
# all other cases
else:
keys, ixs = self._unpack_key(key)
keys, ixs, ixstype = self._unpack_key(key)
ixs = self._unpack_indexer(keys, ixs, ixstype)
new = self.copy_empty()
for i, _ in enumerate(keys):
key, ix = keys[i], ixs[i]
new._data[key] = self._get_item(key)[ix]
new._data[key] = self._get_item(key, ix, True)
return new
def _get_item(self, key):
def _get_item(self, key, ix=None, insertna=False):
"""Extract a pd.Series from self"""
return self._data[key]
if ix is None:
return self._data[key]
elif insertna:
s = self._data[key]
return s[ix].reindex_like(s)
else:
return self._data[key][ix]
def __setitem__(self, key, value):
"""
......@@ -224,11 +231,11 @@ class DictOfSeries:
self._insert(key, value)
return
else:
k, i = [key], [slice(None)]
k, i, it = [key], [slice(None)], None
# all other cases
else:
k, i = self._unpack_key(key)
k, i, it = self._unpack_key(key)
i = self._unpack_indexer(k, i, it)
gen = self._unpack_value(k, i, value)
for tup in gen:
self._set_item(*tup)
......@@ -285,29 +292,22 @@ class DictOfSeries:
Notes:
Which keys we get, may depend on the policy in dios_options
"""
err_bool = "only boolean values are allowed"
len_err_msg = "length of given column-indexer does not match length of columns"
keys = None
boolidxer = None
sliceidxer = None
haskeys = False
indexer, idxtype = None, None
# prevent consuming of a generator
key = list(key) if is_iterator(key) else key
if isinstance(key, slice):
keys = self.columns
sliceidxer = [key]
indexer, idxtype = [key], 'slice'
# list, np.arrays, ... of list, np.arrays..
elif is_nested_list_like(key):
# we only allow bool nlists
keys = self.columns
boolidxer = key
# todo ..
# elif is_bool_indexer(key):
# ...
indexer, idxtype = key, 'nlist'
# ser, df, dios
elif is_pandas_like(key):
......@@ -328,16 +328,15 @@ class DictOfSeries:
elif is_dataframe_like(key):
# we only allow bool df's
keys = key.columns.to_list()
boolidxer, haskeys= key, True
indexer, idxtype = key, 'df'
elif is_dios_like(key):
# we only allow bool dios's
keys = key.columns
boolidxer, haskeys= key, True
indexer, idxtype = key, 'dios'
# list, np.array, np.ndarray, ...
# Note: series considered list-like,
# so we handle lists last
# Note: series considered list-like, so we handle lists at last
elif is_list_like(key):
arr = np.array(key)
if is_bool_array(arr):
......@@ -347,7 +346,6 @@ class DictOfSeries:
keys = np.array(keys)[arr]
else:
keys = key
else:
raise KeyError(f"{key}")
......@@ -355,30 +353,28 @@ class DictOfSeries:
method = dios_options[OptsFields.col_indexing_method]
keys = check_keys_by_policy(keys, self.columns, method)
# check indexers
idxer = []
if sliceidxer is not None:
idxer = sliceidxer * len(keys)
elif boolidxer is not None:
if haskeys:
for k in keys:
ix = boolidxer[k]
idxer.append(ix)
if not is_bool_indexer(ix):
raise ValueError(err_bool)
else:
for i in boolidxer:
ix = np.array(i)
idxer.append(ix)
if not is_bool_array(ix):
raise ValueError(err_bool)
else:
idxer = [slice(None)] * len(keys)
assert len(idxer) == len(keys)
return keys, indexer, idxtype
# now we have a valid indexer (a slice or a bool array) for every key
return keys, idxer
def _unpack_indexer(self, keys, indexer, idxtype):
err_bool = "only boolean values are allowed"
idxerlist = []
if idxtype == 'slice':
idxerlist = indexer * len(keys)
elif idxtype in ['df', 'dios']:
for k in keys:
ix = indexer[k]
idxerlist.append(ix)
if not is_bool_indexer(ix):
raise ValueError(err_bool)
elif idxtype == 'nlist':
for i in indexer:
ix = np.array(i)
idxerlist.append(ix)
if not is_bool_array(ix):
raise ValueError(err_bool)
else:
idxerlist = [slice(None)] * len(keys)
return idxerlist
@property
def loc(self):
......@@ -606,7 +602,7 @@ class _LocIndexer(_Indexer):
rkey, cols = self._unpack_key(key)
new = self._dios.copy_empty()
for i, _ in enumerate(cols):
c,r = cols[i], rkey[i]
c, r = cols[i], rkey[i]
new[c] = self._data[c].loc[r]
return new
......@@ -637,7 +633,7 @@ class _LocIndexer(_Indexer):
else:
try:
# list and bool list like
cols, _ = self._dios._unpack_key(ckey)
cols, *_ = self._dios._unpack_key(ckey)
except Exception:
raise
......@@ -669,7 +665,7 @@ class _iLocIndexer(_Indexer):
rkey, cols = self._unpack_key(key)
new = self._dios.copy_empty()
for i, _ in enumerate(cols):
c,r = cols[i], rkey[i]
c, r = cols[i], rkey[i]
new[c] = self._data[c].iloc[r]
return new
......
dios/options.py
+ 16
− 6
View file @ f672e760
......@@ -10,16 +10,25 @@ class OptsFields:
disp_max_vars = "disp_max_vars"
"""
none_plus: none or more can be given
at_leat_one: accept if at least one column is present
all_present: all given columns must be present
all_plus: (pandas, bool-series style) all must be present but more can be given
none_plus: none or more columns, than in self, can be given
at_least_one: accept if at least one column is present in self
all_present: all given columns must be present in self
"""
col_indexing_method = "dios_to_dios_method"
col_indexing_method = "col_indexing_method"
mixed_itype_warn_policy = "mixed_itype_policy"
"""
should nans be droppend during comparision(drop),
stay nans (keep), or be compared (nplike).
nplike is quite silly as `5 < NaN` will simply evaluate to False"""
comparison_nan_policy = "comparison_nan_policy"
"""
Get item nan policy:
"""
class Opts:
none_plus = 'none_plus'
......@@ -31,7 +40,8 @@ class Opts:
itype_ignore = 'ignore'
keep_nans = 'keep'
nplike_nans = 'nplike_nans '
nplike_nans = 'nplike'
drop_nans = 'drop'
# set default values
......
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