neurolang.utils package¶
- class neurolang.utils.NamedRelationalAlgebraFrozenSet(columns, iterable=None)¶
Bases:
RelationalAlgebraFrozenSet,NamedRelationalAlgebraFrozenSet- Attributes:
- arity
- columns
Methods
isdisjoint(other)Return True if two sets have a null intersection.
projection(*columns)Projects the set on the given list of columns.
selection(select_criteria)Select the elements based on the given selet_criteria.
selection_columns(select_criteria)Select the elements where column pairs indicated as key, value items of the select_criteria are equal.
aggregate
as_numpy_array
as_pandas_dataframe
copy
create_view_from
cross_product
dee
dum
equijoin
explode
extended_projection
fetch_one
groupby
is_dee
is_dum
is_empty
itervalues
left_naturaljoin
naturaljoin
projection_to_unnamed
rename_column
rename_columns
replace_null
to_unnamed
- aggregate(group_columns, aggregate_function)¶
- property arity¶
- property columns¶
- classmethod create_view_from(other)¶
- cross_product(other)¶
- classmethod dee()¶
- classmethod dum()¶
- equijoin(other, join_indices)¶
- explode(src_column, dst_columns)¶
- extended_projection(eval_expressions)¶
- fetch_one()¶
- groupby(columns)¶
- left_naturaljoin(other)¶
- naturaljoin(other)¶
- projection(*columns)¶
Projects the set on the given list of columns.
Examples
>>> ras = RelationalAlgebraFrozenSet( [(i % 2, i, i * 2) for i in range(5)]) >>> ras 0 1 2 0 0 0 0 1 1 1 2 2 0 2 4 3 1 3 6 4 0 4 8 >>> ras.projection(1) 0 0 0 1 1 2 2 3 3 4 4
- projection_to_unnamed(*columns)¶
- rename_column(src, dst)¶
- rename_columns(renames)¶
- replace_null(column, value)¶
- to_unnamed()¶
- class neurolang.utils.OrderedSet(iterable=None)¶
Bases:
MutableSet,SequenceMethods
add(value)Add an element.
clear()This is slow (creates N new iterators!) but effective.
count(value)discard(value)Remove an element.
index(value, [start, [stop]])Raises ValueError if the value is not present.
isdisjoint(other)Return True if two sets have a null intersection.
pop()Return the popped value.
remove(value)Remove an element.
copy
issubset
issuperset
replace
- add(value)¶
Add an element.
- copy()¶
- discard(value)¶
Remove an element. Do not raise an exception if absent.
- index(value[, start[, stop]]) integer -- return first index of value.¶
Raises ValueError if the value is not present.
Supporting start and stop arguments is optional, but recommended.
- issubset(other)¶
- issuperset(other)¶
- replace(src, dst)¶
- class neurolang.utils.RelationalAlgebraFrozenSet(iterable=None)¶
Bases:
RelationalAlgebraFrozenSetRelationalAlgebraFrozenSet implementation using in-memory pandas.DataFrame as container for the elements.
- Attributes:
- arity
- columns
Methods
isdisjoint(other)Return True if two sets have a null intersection.
projection(*columns)Projects the set on the given list of columns.
selection(select_criteria)Select the elements based on the given selet_criteria.
selection_columns(select_criteria)Select the elements where column pairs indicated as key, value items of the select_criteria are equal.
as_numpy_array
as_pandas_dataframe
copy
create_view_from
cross_product
dee
dum
equijoin
fetch_one
groupby
is_dee
is_dum
is_empty
itervalues
- property arity¶
- as_numpy_array()¶
- as_pandas_dataframe()¶
- property columns¶
- copy()¶
- classmethod create_view_from(other)¶
- cross_product(other)¶
- classmethod dee()¶
- classmethod dum()¶
- equijoin(other, join_indices)¶
- fetch_one()¶
- groupby(columns)¶
- is_empty()¶
- itervalues()¶
- projection(*columns)¶
Projects the set on the given list of columns.
Examples
>>> ras = RelationalAlgebraFrozenSet( [(i % 2, i, i * 2) for i in range(5)]) >>> ras 0 1 2 0 0 0 0 1 1 1 2 2 0 2 4 3 1 3 6 4 0 4 8 >>> ras.projection(1) 0 0 0 1 1 2 2 3 3 4 4
- selection(select_criteria: Callable | RelationalAlgebraStringExpression | Dict[int, int | Callable])¶
Select the elements based on the given selet_criteria. The select_criteria may be a callable function, a string expression or a Dict of columns -> value
- Parameters:
- select_criteriaUnion[Callable, RelationalAlgebraStringExpression,
- Dict[int, Union[int, Callable]]]
selection criteria
- Returns:
- RelationalAlgebraFrozenSet
A RelationalAlgebraFrozenSet with elements matching the criteria.
- selection_columns(select_criteria: Dict[int, int])¶
Select the elements where column pairs indicated as key, value items of the select_criteria are equal. The select_criteria must be a Dict of Int -> Int.
- Parameters:
- select_criteriaDict [Int, Int]
selection criteria
- Returns:
- RelationalAlgebraFrozenSet
A RelationalAlgebraFrozenSet with elements matching the criteria.
Examples
Select the elements where col0 == col1 and col1 == col2 >>> ras = RelationalAlgebraFrozenSet(
[(i % 2, i, i * 2) for i in range(5)])
>>> ras.selection_columns({0:1, 1: 2}) 0 1 2 0 0 0 0
- class neurolang.utils.RelationalAlgebraSet(iterable=None)¶
Bases:
RelationalAlgebraFrozenSet,RelationalAlgebraSet- Attributes:
- arity
- columns
Methods
add(value)Add an element.
clear()This is slow (creates N new iterators!) but effective.
discard(value)Remove an element.
isdisjoint(other)Return True if two sets have a null intersection.
pop()Return the popped value.
projection(*columns)Projects the set on the given list of columns.
remove(value)Remove an element.
selection(select_criteria)Select the elements based on the given selet_criteria.
selection_columns(select_criteria)Select the elements where column pairs indicated as key, value items of the select_criteria are equal.
as_numpy_array
as_pandas_dataframe
copy
create_view_from
cross_product
dee
dum
equijoin
fetch_one
groupby
is_dee
is_dum
is_empty
itervalues
- add(value)¶
Add an element.
- discard(value)¶
Remove an element. Do not raise an exception if absent.
- class neurolang.utils.RelationalAlgebraStringExpression¶
Bases:
strMethods
capitalize(/)Return a capitalized version of the string.
casefold(/)Return a version of the string suitable for caseless comparisons.
center(width[, fillchar])Return a centered string of length width.
count(sub[, start[, end]])Return the number of non-overlapping occurrences of substring sub in string S[start:end].
encode(/[, encoding, errors])Encode the string using the codec registered for encoding.
endswith(suffix[, start[, end]])Return True if S ends with the specified suffix, False otherwise.
expandtabs(/[, tabsize])Return a copy where all tab characters are expanded using spaces.
find(sub[, start[, end]])Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end].
format(*args, **kwargs)Return a formatted version of S, using substitutions from args and kwargs.
format_map(mapping)Return a formatted version of S, using substitutions from mapping.
index(sub[, start[, end]])Return the lowest index in S where substring sub is found, such that sub is contained within S[start:end].
isalnum(/)Return True if the string is an alpha-numeric string, False otherwise.
isalpha(/)Return True if the string is an alphabetic string, False otherwise.
isascii(/)Return True if all characters in the string are ASCII, False otherwise.
isdecimal(/)Return True if the string is a decimal string, False otherwise.
isdigit(/)Return True if the string is a digit string, False otherwise.
isidentifier(/)Return True if the string is a valid Python identifier, False otherwise.
islower(/)Return True if the string is a lowercase string, False otherwise.
isnumeric(/)Return True if the string is a numeric string, False otherwise.
isprintable(/)Return True if the string is printable, False otherwise.
isspace(/)Return True if the string is a whitespace string, False otherwise.
istitle(/)Return True if the string is a title-cased string, False otherwise.
isupper(/)Return True if the string is an uppercase string, False otherwise.
join(iterable, /)Concatenate any number of strings.
ljust(width[, fillchar])Return a left-justified string of length width.
lower(/)Return a copy of the string converted to lowercase.
lstrip([chars])Return a copy of the string with leading whitespace removed.
maketrans(x[, y, z])Return a translation table usable for str.translate().
partition(sep, /)Partition the string into three parts using the given separator.
replace(old, new[, count])Return a copy with all occurrences of substring old replaced by new.
rfind(sub[, start[, end]])Return the highest index in S where substring sub is found, such that sub is contained within S[start:end].
rindex(sub[, start[, end]])Return the highest index in S where substring sub is found, such that sub is contained within S[start:end].
rjust(width[, fillchar])Return a right-justified string of length width.
rpartition(sep, /)Partition the string into three parts using the given separator.
rsplit(/[, sep, maxsplit])Return a list of the words in the string, using sep as the delimiter string.
rstrip([chars])Return a copy of the string with trailing whitespace removed.
split(/[, sep, maxsplit])Return a list of the words in the string, using sep as the delimiter string.
splitlines(/[, keepends])Return a list of the lines in the string, breaking at line boundaries.
startswith(prefix[, start[, end]])Return True if S starts with the specified prefix, False otherwise.
strip([chars])Return a copy of the string with leading and trailing whitespace removed.
swapcase(/)Convert uppercase characters to lowercase and lowercase characters to uppercase.
title(/)Return a version of the string where each word is titlecased.
translate(table, /)Replace each character in the string using the given translation table.
upper(/)Return a copy of the string converted to uppercase.
zfill(width, /)Pad a numeric string with zeros on the left, to fill a field of the given width.
- neurolang.utils.log_performance(logger, init_message, init_args=None, end_message=None, end_args=None, level=20)¶
Context manager to log the performance of executed commands in the context.
- Parameters:
- loggerlogging.Logger
Logger to use for the message
- init_messagestr
Message to display before executing the code within the context.
- init_argstuple, optional
Tuple with the arguments for the init message, by default None
- end_messagestr, optional
Message to display when code has finished first parameter is the elapsed seconds, by default None
- end_argstuple, optional
more arguments for the end message, by default None
- levellogging level, optional
level to log, by default logging.INFO
- neurolang.utils.powerset(iterable)¶
Subpackages¶
- neurolang.utils.relational_algebra_set package
NamedRelationalAlgebraFrozenSetNamedRelationalAlgebraFrozenSet.aggregate()NamedRelationalAlgebraFrozenSet.arityNamedRelationalAlgebraFrozenSet.columnsNamedRelationalAlgebraFrozenSet.create_view_from()NamedRelationalAlgebraFrozenSet.cross_product()NamedRelationalAlgebraFrozenSet.dee()NamedRelationalAlgebraFrozenSet.dum()NamedRelationalAlgebraFrozenSet.equijoin()NamedRelationalAlgebraFrozenSet.explode()NamedRelationalAlgebraFrozenSet.extended_projection()NamedRelationalAlgebraFrozenSet.fetch_one()NamedRelationalAlgebraFrozenSet.groupby()NamedRelationalAlgebraFrozenSet.left_naturaljoin()NamedRelationalAlgebraFrozenSet.naturaljoin()NamedRelationalAlgebraFrozenSet.projection()NamedRelationalAlgebraFrozenSet.projection_to_unnamed()NamedRelationalAlgebraFrozenSet.rename_column()NamedRelationalAlgebraFrozenSet.rename_columns()NamedRelationalAlgebraFrozenSet.replace_null()NamedRelationalAlgebraFrozenSet.to_unnamed()
RelationalAlgebraColumnIntRelationalAlgebraColumnStrRelationalAlgebraFrozenSetRelationalAlgebraFrozenSet.arityRelationalAlgebraFrozenSet.as_numpy_array()RelationalAlgebraFrozenSet.as_pandas_dataframe()RelationalAlgebraFrozenSet.columnsRelationalAlgebraFrozenSet.copy()RelationalAlgebraFrozenSet.create_view_from()RelationalAlgebraFrozenSet.cross_product()RelationalAlgebraFrozenSet.dee()RelationalAlgebraFrozenSet.dum()RelationalAlgebraFrozenSet.equijoin()RelationalAlgebraFrozenSet.fetch_one()RelationalAlgebraFrozenSet.groupby()RelationalAlgebraFrozenSet.is_empty()RelationalAlgebraFrozenSet.itervalues()RelationalAlgebraFrozenSet.projection()RelationalAlgebraFrozenSet.selection()RelationalAlgebraFrozenSet.selection_columns()
RelationalAlgebraSetRelationalAlgebraStringExpression- Submodules
- neurolang.utils.server package
- neurolang.utils.testing package