body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1
value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
d3554e43f4268815e372f8e942ec8a792b553cff9e485c8abc329a22de3ab8ae | def __setstate__(self, state):
'\n In order to maintain backwards compatibility and be able to unpickle a\n old pickle from ``Composition_class`` we have to override the default\n ``__setstate__``.\n\n EXAMPLES::\n\n sage: loads(b"x\\x9ck`J.NLO\\xd5K\\xce\\xcfM\\xca\\xccK,\\x0... | In order to maintain backwards compatibility and be able to unpickle a
old pickle from ``Composition_class`` we have to override the default
``__setstate__``.
EXAMPLES::
sage: loads(b"x\x9ck`J.NLO\xd5K\xce\xcfM\xca\xccK,\x011\n\xf2\x8b3K2\xf3\xf3\xb8\x9c\x11\xec\xf8\xe4\x9c\xc4\xe2b\xaeBF\xcd\xc6B\xa6\xdaBf\x8dP\... | src/sage/combinat/composition.py | __setstate__ | LaisRast/sage | 1,742 | python | def __setstate__(self, state):
'\n In order to maintain backwards compatibility and be able to unpickle a\n old pickle from ``Composition_class`` we have to override the default\n ``__setstate__``.\n\n EXAMPLES::\n\n sage: loads(b"x\\x9ck`J.NLO\\xd5K\\xce\\xcfM\\xca\\xccK,\\x0... | def __setstate__(self, state):
'\n In order to maintain backwards compatibility and be able to unpickle a\n old pickle from ``Composition_class`` we have to override the default\n ``__setstate__``.\n\n EXAMPLES::\n\n sage: loads(b"x\\x9ck`J.NLO\\xd5K\\xce\\xcfM\\xca\\xccK,\\x0... |
33fa7a4db1f431f6976c71aed0093adca7f37b868297d526618b9613edbeac46 | @combinatorial_map(order=2, name='conjugate')
def conjugate(self) -> Composition:
'\n Return the conjugate of the composition ``self``.\n\n The conjugate of a composition `I` is defined as the\n complement (see :meth:`complement`) of the reverse composition\n (see :meth:`reversed`) of `I... | Return the conjugate of the composition ``self``.
The conjugate of a composition `I` is defined as the
complement (see :meth:`complement`) of the reverse composition
(see :meth:`reversed`) of `I`.
An equivalent definition of the conjugate goes by saying that
the ribbon shape of the conjugate of a composition `I` is t... | src/sage/combinat/composition.py | conjugate | LaisRast/sage | 1,742 | python | @combinatorial_map(order=2, name='conjugate')
def conjugate(self) -> Composition:
'\n Return the conjugate of the composition ``self``.\n\n The conjugate of a composition `I` is defined as the\n complement (see :meth:`complement`) of the reverse composition\n (see :meth:`reversed`) of `I... | @combinatorial_map(order=2, name='conjugate')
def conjugate(self) -> Composition:
'\n Return the conjugate of the composition ``self``.\n\n The conjugate of a composition `I` is defined as the\n complement (see :meth:`complement`) of the reverse composition\n (see :meth:`reversed`) of `I... |
df92c5efc116f5601dae237f026eee9ca2975a7e23b6c784996e5c672ba342f5 | @combinatorial_map(order=2, name='reversed')
def reversed(self) -> Composition:
'\n Return the reverse composition of ``self``.\n\n The reverse composition of a composition `(i_1, i_2, \\ldots, i_k)`\n is defined as the composition `(i_k, i_{k-1}, \\ldots, i_1)`.\n\n EXAMPLES::\n\n ... | Return the reverse composition of ``self``.
The reverse composition of a composition `(i_1, i_2, \ldots, i_k)`
is defined as the composition `(i_k, i_{k-1}, \ldots, i_1)`.
EXAMPLES::
sage: Composition([1, 1, 3, 1, 2, 1, 3]).reversed()
[3, 1, 2, 1, 3, 1, 1] | src/sage/combinat/composition.py | reversed | LaisRast/sage | 1,742 | python | @combinatorial_map(order=2, name='reversed')
def reversed(self) -> Composition:
'\n Return the reverse composition of ``self``.\n\n The reverse composition of a composition `(i_1, i_2, \\ldots, i_k)`\n is defined as the composition `(i_k, i_{k-1}, \\ldots, i_1)`.\n\n EXAMPLES::\n\n ... | @combinatorial_map(order=2, name='reversed')
def reversed(self) -> Composition:
'\n Return the reverse composition of ``self``.\n\n The reverse composition of a composition `(i_1, i_2, \\ldots, i_k)`\n is defined as the composition `(i_k, i_{k-1}, \\ldots, i_1)`.\n\n EXAMPLES::\n\n ... |
1870a71b537c349b2086adf1f9c0bb3dbe1c7a96c28974708df5e67f05fed148 | @combinatorial_map(order=2, name='complement')
def complement(self) -> Composition:
'\n Return the complement of the composition ``self``.\n\n The complement of a composition `I` is defined as follows:\n\n If `I` is the empty composition, then the complement is the empty\n composition as... | Return the complement of the composition ``self``.
The complement of a composition `I` is defined as follows:
If `I` is the empty composition, then the complement is the empty
composition as well. Otherwise, let `S` be the descent set of `I`
(that is, the subset
`\{ i_1, i_1 + i_2, \ldots, i_1 + i_2 + \cdots + i_{k-1... | src/sage/combinat/composition.py | complement | LaisRast/sage | 1,742 | python | @combinatorial_map(order=2, name='complement')
def complement(self) -> Composition:
'\n Return the complement of the composition ``self``.\n\n The complement of a composition `I` is defined as follows:\n\n If `I` is the empty composition, then the complement is the empty\n composition as... | @combinatorial_map(order=2, name='complement')
def complement(self) -> Composition:
'\n Return the complement of the composition ``self``.\n\n The complement of a composition `I` is defined as follows:\n\n If `I` is the empty composition, then the complement is the empty\n composition as... |
2913b748ba5739bac930fa7c353a82a3ac45a36663787e080b34058f5915e454 | def __add__(self, other) -> Composition:
'\n Return the concatenation of two compositions.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3]) + Composition([4, 1, 2])\n [1, 1, 3, 4, 1, 2]\n\n TESTS::\n\n sage: Composition([]) + Composition([]) == Composition([])\n ... | Return the concatenation of two compositions.
EXAMPLES::
sage: Composition([1, 1, 3]) + Composition([4, 1, 2])
[1, 1, 3, 4, 1, 2]
TESTS::
sage: Composition([]) + Composition([]) == Composition([])
True | src/sage/combinat/composition.py | __add__ | LaisRast/sage | 1,742 | python | def __add__(self, other) -> Composition:
'\n Return the concatenation of two compositions.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3]) + Composition([4, 1, 2])\n [1, 1, 3, 4, 1, 2]\n\n TESTS::\n\n sage: Composition([]) + Composition([]) == Composition([])\n ... | def __add__(self, other) -> Composition:
'\n Return the concatenation of two compositions.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3]) + Composition([4, 1, 2])\n [1, 1, 3, 4, 1, 2]\n\n TESTS::\n\n sage: Composition([]) + Composition([]) == Composition([])\n ... |
76b5baacf076bd99b0fb222c2316b93f4be168d4b1d023e33599a1e3eff96954 | def size(self) -> int:
'\n Return the size of ``self``, that is the sum of its parts.\n\n EXAMPLES::\n\n sage: Composition([7,1,3]).size()\n 11\n '
return sum(self) | Return the size of ``self``, that is the sum of its parts.
EXAMPLES::
sage: Composition([7,1,3]).size()
11 | src/sage/combinat/composition.py | size | LaisRast/sage | 1,742 | python | def size(self) -> int:
'\n Return the size of ``self``, that is the sum of its parts.\n\n EXAMPLES::\n\n sage: Composition([7,1,3]).size()\n 11\n '
return sum(self) | def size(self) -> int:
'\n Return the size of ``self``, that is the sum of its parts.\n\n EXAMPLES::\n\n sage: Composition([7,1,3]).size()\n 11\n '
return sum(self)<|docstring|>Return the size of ``self``, that is the sum of its parts.
EXAMPLES::
sage: Compositio... |
9fe254c50c8145a1275831e7c133823b3d063b8a2b089bd42f749fad730a56b9 | @staticmethod
def sum(compositions) -> Composition:
'\n Return the concatenation of the given compositions.\n\n INPUT:\n\n - ``compositions`` -- a list (or iterable) of compositions\n\n EXAMPLES::\n\n sage: Composition.sum([Composition([1, 1, 3]), Composition([4, 1, 2]), Compo... | Return the concatenation of the given compositions.
INPUT:
- ``compositions`` -- a list (or iterable) of compositions
EXAMPLES::
sage: Composition.sum([Composition([1, 1, 3]), Composition([4, 1, 2]), Composition([3,1])])
[1, 1, 3, 4, 1, 2, 3, 1]
Any iterable can be provided as input::
sage: Compositio... | src/sage/combinat/composition.py | sum | LaisRast/sage | 1,742 | python | @staticmethod
def sum(compositions) -> Composition:
'\n Return the concatenation of the given compositions.\n\n INPUT:\n\n - ``compositions`` -- a list (or iterable) of compositions\n\n EXAMPLES::\n\n sage: Composition.sum([Composition([1, 1, 3]), Composition([4, 1, 2]), Compo... | @staticmethod
def sum(compositions) -> Composition:
'\n Return the concatenation of the given compositions.\n\n INPUT:\n\n - ``compositions`` -- a list (or iterable) of compositions\n\n EXAMPLES::\n\n sage: Composition.sum([Composition([1, 1, 3]), Composition([4, 1, 2]), Compo... |
09bf0cb0a523320a8bf93517de698c973f8a7caa92f9fab7624f213be9c94dc1 | def near_concatenation(self, other):
'\n Return the near-concatenation of two nonempty compositions\n ``self`` and ``other``.\n\n The near-concatenation `I \\odot J` of two nonempty compositions\n `I` and `J` is defined as the composition\n `(i_1, i_2, \\ldots , i_{n-1}, i_n + j_1... | Return the near-concatenation of two nonempty compositions
``self`` and ``other``.
The near-concatenation `I \odot J` of two nonempty compositions
`I` and `J` is defined as the composition
`(i_1, i_2, \ldots , i_{n-1}, i_n + j_1, j_2, j_3, \ldots , j_m)`,
where `(i_1, i_2, \ldots , i_n) = I` and
`(j_1, j_2, \ldots , j... | src/sage/combinat/composition.py | near_concatenation | LaisRast/sage | 1,742 | python | def near_concatenation(self, other):
'\n Return the near-concatenation of two nonempty compositions\n ``self`` and ``other``.\n\n The near-concatenation `I \\odot J` of two nonempty compositions\n `I` and `J` is defined as the composition\n `(i_1, i_2, \\ldots , i_{n-1}, i_n + j_1... | def near_concatenation(self, other):
'\n Return the near-concatenation of two nonempty compositions\n ``self`` and ``other``.\n\n The near-concatenation `I \\odot J` of two nonempty compositions\n `I` and `J` is defined as the composition\n `(i_1, i_2, \\ldots , i_{n-1}, i_n + j_1... |
4260f8e6c39a7f2a885b9f9795132de2f7779dbd74958b9a50317e3d86903954 | def ribbon_decomposition(self, other, check=True):
'\n Return a pair describing the ribbon decomposition of a composition\n ``self`` with respect to a composition ``other`` of the same size.\n\n If `I` and `J` are two compositions of the same nonzero size, then\n the ribbon decomposition... | Return a pair describing the ribbon decomposition of a composition
``self`` with respect to a composition ``other`` of the same size.
If `I` and `J` are two compositions of the same nonzero size, then
the ribbon decomposition of `I` with respect to `J` is defined as
follows: Write `I` and `J` as `I = (i_1, i_2, \ldots... | src/sage/combinat/composition.py | ribbon_decomposition | LaisRast/sage | 1,742 | python | def ribbon_decomposition(self, other, check=True):
'\n Return a pair describing the ribbon decomposition of a composition\n ``self`` with respect to a composition ``other`` of the same size.\n\n If `I` and `J` are two compositions of the same nonzero size, then\n the ribbon decomposition... | def ribbon_decomposition(self, other, check=True):
'\n Return a pair describing the ribbon decomposition of a composition\n ``self`` with respect to a composition ``other`` of the same size.\n\n If `I` and `J` are two compositions of the same nonzero size, then\n the ribbon decomposition... |
cff2249dc6f69381d655186355ceef66d23318f0504c7fc319909b4b4f03d131 | def join(self, other, check=True) -> Composition:
'\n Return the join of ``self`` with a composition ``other`` of the\n same size.\n\n The join of two compositions `I` and `J` of size `n` is the\n coarsest composition of `n` which refines each of `I` and `J`. It\n can be described... | Return the join of ``self`` with a composition ``other`` of the
same size.
The join of two compositions `I` and `J` of size `n` is the
coarsest composition of `n` which refines each of `I` and `J`. It
can be described as the composition whose descent set is the
union of the descent sets of `I` and `J`. It is also the
... | src/sage/combinat/composition.py | join | LaisRast/sage | 1,742 | python | def join(self, other, check=True) -> Composition:
'\n Return the join of ``self`` with a composition ``other`` of the\n same size.\n\n The join of two compositions `I` and `J` of size `n` is the\n coarsest composition of `n` which refines each of `I` and `J`. It\n can be described... | def join(self, other, check=True) -> Composition:
'\n Return the join of ``self`` with a composition ``other`` of the\n same size.\n\n The join of two compositions `I` and `J` of size `n` is the\n coarsest composition of `n` which refines each of `I` and `J`. It\n can be described... |
3d6fc6bf4419150f7719f166abf0bb986d9a6ea94fac39bbca9c2d83506b417f | def meet(self, other, check=True) -> Composition:
'\n Return the meet of ``self`` with a composition ``other`` of the\n same size.\n\n The meet of two compositions `I` and `J` of size `n` is the\n finest composition of `n` which is coarser than each of `I` and\n `J`. It can be des... | Return the meet of ``self`` with a composition ``other`` of the
same size.
The meet of two compositions `I` and `J` of size `n` is the
finest composition of `n` which is coarser than each of `I` and
`J`. It can be described as the composition whose descent set is
the intersection of the descent sets of `I` and `J`.
I... | src/sage/combinat/composition.py | meet | LaisRast/sage | 1,742 | python | def meet(self, other, check=True) -> Composition:
'\n Return the meet of ``self`` with a composition ``other`` of the\n same size.\n\n The meet of two compositions `I` and `J` of size `n` is the\n finest composition of `n` which is coarser than each of `I` and\n `J`. It can be des... | def meet(self, other, check=True) -> Composition:
'\n Return the meet of ``self`` with a composition ``other`` of the\n same size.\n\n The meet of two compositions `I` and `J` of size `n` is the\n finest composition of `n` which is coarser than each of `I` and\n `J`. It can be des... |
616603205080ec1551368cfddbb1ddad353e10b77109918e9808f195c3833514 | def finer(self):
'\n Return the set of compositions which are finer than ``self``.\n\n EXAMPLES::\n\n sage: C = Composition([3,2]).finer()\n sage: C.cardinality()\n 8\n sage: C.list()\n [[1, 1, 1, 1, 1], [1, 1, 1, 2], [1, 2, 1, 1], [1, 2, 2], [2, ... | Return the set of compositions which are finer than ``self``.
EXAMPLES::
sage: C = Composition([3,2]).finer()
sage: C.cardinality()
8
sage: C.list()
[[1, 1, 1, 1, 1], [1, 1, 1, 2], [1, 2, 1, 1], [1, 2, 2], [2, 1, 1, 1], [2, 1, 2], [3, 1, 1], [3, 2]]
sage: Composition([]).finer()
{[]} | src/sage/combinat/composition.py | finer | LaisRast/sage | 1,742 | python | def finer(self):
'\n Return the set of compositions which are finer than ``self``.\n\n EXAMPLES::\n\n sage: C = Composition([3,2]).finer()\n sage: C.cardinality()\n 8\n sage: C.list()\n [[1, 1, 1, 1, 1], [1, 1, 1, 2], [1, 2, 1, 1], [1, 2, 2], [2, ... | def finer(self):
'\n Return the set of compositions which are finer than ``self``.\n\n EXAMPLES::\n\n sage: C = Composition([3,2]).finer()\n sage: C.cardinality()\n 8\n sage: C.list()\n [[1, 1, 1, 1, 1], [1, 1, 1, 2], [1, 2, 1, 1], [1, 2, 2], [2, ... |
987a87aa61a771b224ad14ad4fa970319d5e4e9124708cefc8ef906c58938b0b | def is_finer(self, co2) -> bool:
'\n Return ``True`` if the composition ``self`` is finer than the\n composition ``co2``; otherwise, return ``False``.\n\n EXAMPLES::\n\n sage: Composition([4,1,2]).is_finer([3,1,3])\n False\n sage: Composition([3,1,3]).is_finer([... | Return ``True`` if the composition ``self`` is finer than the
composition ``co2``; otherwise, return ``False``.
EXAMPLES::
sage: Composition([4,1,2]).is_finer([3,1,3])
False
sage: Composition([3,1,3]).is_finer([4,1,2])
False
sage: Composition([1,2,2,1,1,2]).is_finer([5,1,3])
True
sage: Com... | src/sage/combinat/composition.py | is_finer | LaisRast/sage | 1,742 | python | def is_finer(self, co2) -> bool:
'\n Return ``True`` if the composition ``self`` is finer than the\n composition ``co2``; otherwise, return ``False``.\n\n EXAMPLES::\n\n sage: Composition([4,1,2]).is_finer([3,1,3])\n False\n sage: Composition([3,1,3]).is_finer([... | def is_finer(self, co2) -> bool:
'\n Return ``True`` if the composition ``self`` is finer than the\n composition ``co2``; otherwise, return ``False``.\n\n EXAMPLES::\n\n sage: Composition([4,1,2]).is_finer([3,1,3])\n False\n sage: Composition([3,1,3]).is_finer([... |
1cfd6d886af210138e2f31df1777f57a418e249adad24d7dd7971be9bfe8b9a2 | def fatten(self, grouping) -> Composition:
'\n Return the composition fatter than ``self``, obtained by grouping\n together consecutive parts according to ``grouping``.\n\n INPUT:\n\n - ``grouping`` -- a composition whose sum is the length of ``self``\n\n EXAMPLES:\n\n Let ... | Return the composition fatter than ``self``, obtained by grouping
together consecutive parts according to ``grouping``.
INPUT:
- ``grouping`` -- a composition whose sum is the length of ``self``
EXAMPLES:
Let us start with the composition::
sage: c = Composition([4,5,2,7,1])
With ``grouping`` equal to `(1, \l... | src/sage/combinat/composition.py | fatten | LaisRast/sage | 1,742 | python | def fatten(self, grouping) -> Composition:
'\n Return the composition fatter than ``self``, obtained by grouping\n together consecutive parts according to ``grouping``.\n\n INPUT:\n\n - ``grouping`` -- a composition whose sum is the length of ``self``\n\n EXAMPLES:\n\n Let ... | def fatten(self, grouping) -> Composition:
'\n Return the composition fatter than ``self``, obtained by grouping\n together consecutive parts according to ``grouping``.\n\n INPUT:\n\n - ``grouping`` -- a composition whose sum is the length of ``self``\n\n EXAMPLES:\n\n Let ... |
6db42b200621fd6ad269cc7435fca130afad5e91d85ad35b81edf22bf51ed695 | def fatter(self):
'\n Return the set of compositions which are fatter than ``self``.\n\n Complexity for generation: `O(|c|)` memory, `O(|r|)` time where `|c|`\n is the size of ``self`` and `r` is the result.\n\n EXAMPLES::\n\n sage: C = Composition([4,5,2]).fatter()\n ... | Return the set of compositions which are fatter than ``self``.
Complexity for generation: `O(|c|)` memory, `O(|r|)` time where `|c|`
is the size of ``self`` and `r` is the result.
EXAMPLES::
sage: C = Composition([4,5,2]).fatter()
sage: C.cardinality()
4
sage: list(C)
[[4, 5, 2], [4, 7], [9, 2], ... | src/sage/combinat/composition.py | fatter | LaisRast/sage | 1,742 | python | def fatter(self):
'\n Return the set of compositions which are fatter than ``self``.\n\n Complexity for generation: `O(|c|)` memory, `O(|r|)` time where `|c|`\n is the size of ``self`` and `r` is the result.\n\n EXAMPLES::\n\n sage: C = Composition([4,5,2]).fatter()\n ... | def fatter(self):
'\n Return the set of compositions which are fatter than ``self``.\n\n Complexity for generation: `O(|c|)` memory, `O(|r|)` time where `|c|`\n is the size of ``self`` and `r` is the result.\n\n EXAMPLES::\n\n sage: C = Composition([4,5,2]).fatter()\n ... |
a4b194e52d46413abdf99c9c63935d696bb0d409f25034c51f8c1ca7346f6976 | def refinement_splitting(self, J) -> list[Composition]:
'\n Return the refinement splitting of ``self`` according to ``J``.\n\n INPUT:\n\n - ``J`` -- A composition such that ``self`` is finer than ``J``\n\n OUTPUT:\n\n - the unique list of compositions `(I^{(p)})_{p=1, \\ldots , m... | Return the refinement splitting of ``self`` according to ``J``.
INPUT:
- ``J`` -- A composition such that ``self`` is finer than ``J``
OUTPUT:
- the unique list of compositions `(I^{(p)})_{p=1, \ldots , m}`,
obtained by splitting `I`, such that
`|I^{(p)}| = J_p` for all `p = 1, \ldots, m`.
.. SEEALSO::
:m... | src/sage/combinat/composition.py | refinement_splitting | LaisRast/sage | 1,742 | python | def refinement_splitting(self, J) -> list[Composition]:
'\n Return the refinement splitting of ``self`` according to ``J``.\n\n INPUT:\n\n - ``J`` -- A composition such that ``self`` is finer than ``J``\n\n OUTPUT:\n\n - the unique list of compositions `(I^{(p)})_{p=1, \\ldots , m... | def refinement_splitting(self, J) -> list[Composition]:
'\n Return the refinement splitting of ``self`` according to ``J``.\n\n INPUT:\n\n - ``J`` -- A composition such that ``self`` is finer than ``J``\n\n OUTPUT:\n\n - the unique list of compositions `(I^{(p)})_{p=1, \\ldots , m... |
75cba63aab69a2d08107e5baa63b4fe1aef1650d4ab8f51037233db24ddd7f78 | def refinement_splitting_lengths(self, J):
'\n Return the lengths of the compositions in the refinement splitting of\n ``self`` according to ``J``.\n\n .. SEEALSO::\n\n :meth:`refinement_splitting` for the definition of refinement splitting\n\n EXAMPLES::\n\n sage: ... | Return the lengths of the compositions in the refinement splitting of
``self`` according to ``J``.
.. SEEALSO::
:meth:`refinement_splitting` for the definition of refinement splitting
EXAMPLES::
sage: Composition([1,2,2,1,1,2]).refinement_splitting_lengths([5,1,3])
[3, 1, 2]
sage: Composition([]).re... | src/sage/combinat/composition.py | refinement_splitting_lengths | LaisRast/sage | 1,742 | python | def refinement_splitting_lengths(self, J):
'\n Return the lengths of the compositions in the refinement splitting of\n ``self`` according to ``J``.\n\n .. SEEALSO::\n\n :meth:`refinement_splitting` for the definition of refinement splitting\n\n EXAMPLES::\n\n sage: ... | def refinement_splitting_lengths(self, J):
'\n Return the lengths of the compositions in the refinement splitting of\n ``self`` according to ``J``.\n\n .. SEEALSO::\n\n :meth:`refinement_splitting` for the definition of refinement splitting\n\n EXAMPLES::\n\n sage: ... |
0289f3f715ddc9b6bb8a46cfd862114e5b66c0a7df93915b3d80428dbbb79a25 | def major_index(self) -> int:
'\n Return the major index of ``self``. The major index is\n defined as the sum of the descents.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3, 1, 2, 1, 3]).major_index()\n 31\n '
lv = len(self)
if (lv == 1):
return 0
... | Return the major index of ``self``. The major index is
defined as the sum of the descents.
EXAMPLES::
sage: Composition([1, 1, 3, 1, 2, 1, 3]).major_index()
31 | src/sage/combinat/composition.py | major_index | LaisRast/sage | 1,742 | python | def major_index(self) -> int:
'\n Return the major index of ``self``. The major index is\n defined as the sum of the descents.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3, 1, 2, 1, 3]).major_index()\n 31\n '
lv = len(self)
if (lv == 1):
return 0
... | def major_index(self) -> int:
'\n Return the major index of ``self``. The major index is\n defined as the sum of the descents.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3, 1, 2, 1, 3]).major_index()\n 31\n '
lv = len(self)
if (lv == 1):
return 0
... |
0fd80f9348d51637b8ae17c6dff222411cb23954109e9a51a7895f0d05698394 | def to_code(self) -> list:
'\n Return the code of the composition ``self``.\n\n The code of a composition `I` is a list of length\n `\\mathrm{size}(I)` of 1s and 0s such that there is a 1\n wherever a new part starts. (Exceptional case: When the\n composition is empty, the code is... | Return the code of the composition ``self``.
The code of a composition `I` is a list of length
`\mathrm{size}(I)` of 1s and 0s such that there is a 1
wherever a new part starts. (Exceptional case: When the
composition is empty, the code is ``[0]``.)
EXAMPLES::
sage: Composition([4,1,2,3,5]).to_code()
[1, 0, ... | src/sage/combinat/composition.py | to_code | LaisRast/sage | 1,742 | python | def to_code(self) -> list:
'\n Return the code of the composition ``self``.\n\n The code of a composition `I` is a list of length\n `\\mathrm{size}(I)` of 1s and 0s such that there is a 1\n wherever a new part starts. (Exceptional case: When the\n composition is empty, the code is... | def to_code(self) -> list:
'\n Return the code of the composition ``self``.\n\n The code of a composition `I` is a list of length\n `\\mathrm{size}(I)` of 1s and 0s such that there is a 1\n wherever a new part starts. (Exceptional case: When the\n composition is empty, the code is... |
aab0a1f5f0adb41befa2ceb8dfd332e44ce84d089789809c888c3b1051677193 | def partial_sums(self, final=True) -> list:
'\n The partial sums of the sequence defined by the entries of the\n composition.\n\n If `I = (i_1, \\ldots, i_m)` is a composition, then the partial sums of\n the entries of the composition are\n `[i_1, i_1 + i_2, \\ldots, i_1 + i_2 + \... | The partial sums of the sequence defined by the entries of the
composition.
If `I = (i_1, \ldots, i_m)` is a composition, then the partial sums of
the entries of the composition are
`[i_1, i_1 + i_2, \ldots, i_1 + i_2 + \cdots + i_m]`.
INPUT:
- ``final`` -- (default: ``True``) whether or not to include the final
p... | src/sage/combinat/composition.py | partial_sums | LaisRast/sage | 1,742 | python | def partial_sums(self, final=True) -> list:
'\n The partial sums of the sequence defined by the entries of the\n composition.\n\n If `I = (i_1, \\ldots, i_m)` is a composition, then the partial sums of\n the entries of the composition are\n `[i_1, i_1 + i_2, \\ldots, i_1 + i_2 + \... | def partial_sums(self, final=True) -> list:
'\n The partial sums of the sequence defined by the entries of the\n composition.\n\n If `I = (i_1, \\ldots, i_m)` is a composition, then the partial sums of\n the entries of the composition are\n `[i_1, i_1 + i_2, \\ldots, i_1 + i_2 + \... |
806d32ef4504789868f65be343c29ec22b1865a1ba37ed16a238c8523368e30d | def to_subset(self, final=False):
'\n The subset corresponding to ``self`` under the bijection (see below)\n between compositions of `n` and subsets of `\\{1, 2, \\ldots, n-1\\}`.\n\n The bijection maps a composition `(i_1, \\ldots, i_k)` of `n` to\n `\\{i_1, i_1 + i_2, i_1 + i_2 + i_3, ... | The subset corresponding to ``self`` under the bijection (see below)
between compositions of `n` and subsets of `\{1, 2, \ldots, n-1\}`.
The bijection maps a composition `(i_1, \ldots, i_k)` of `n` to
`\{i_1, i_1 + i_2, i_1 + i_2 + i_3, \ldots, i_1 + \cdots + i_{k-1}\}`.
INPUT:
- ``final`` -- (default: ``False``) wh... | src/sage/combinat/composition.py | to_subset | LaisRast/sage | 1,742 | python | def to_subset(self, final=False):
'\n The subset corresponding to ``self`` under the bijection (see below)\n between compositions of `n` and subsets of `\\{1, 2, \\ldots, n-1\\}`.\n\n The bijection maps a composition `(i_1, \\ldots, i_k)` of `n` to\n `\\{i_1, i_1 + i_2, i_1 + i_2 + i_3, ... | def to_subset(self, final=False):
'\n The subset corresponding to ``self`` under the bijection (see below)\n between compositions of `n` and subsets of `\\{1, 2, \\ldots, n-1\\}`.\n\n The bijection maps a composition `(i_1, \\ldots, i_k)` of `n` to\n `\\{i_1, i_1 + i_2, i_1 + i_2 + i_3, ... |
ea962cd667517df61598e239d5e89319fe6733899db1657e770dae85cfcf1b57 | def descents(self, final_descent=False) -> list:
'\n This gives one fewer than the partial sums of the composition.\n\n This is here to maintain some sort of backward compatibility, even\n through the original implementation was broken (it gave the wrong\n answer). The same information c... | This gives one fewer than the partial sums of the composition.
This is here to maintain some sort of backward compatibility, even
through the original implementation was broken (it gave the wrong
answer). The same information can be found in :meth:`partial_sums`.
.. SEEALSO::
:meth:`partial_sums`
INPUT:
- ``fi... | src/sage/combinat/composition.py | descents | LaisRast/sage | 1,742 | python | def descents(self, final_descent=False) -> list:
'\n This gives one fewer than the partial sums of the composition.\n\n This is here to maintain some sort of backward compatibility, even\n through the original implementation was broken (it gave the wrong\n answer). The same information c... | def descents(self, final_descent=False) -> list:
'\n This gives one fewer than the partial sums of the composition.\n\n This is here to maintain some sort of backward compatibility, even\n through the original implementation was broken (it gave the wrong\n answer). The same information c... |
f9b76ea1ea6c1ecc7d3f7464a89b2f5097d1865a65320f5db09bfde437419f18 | def peaks(self) -> list:
'\n Return a list of the peaks of the composition ``self``.\n\n The peaks of a composition are the descents which do not\n immediately follow another descent.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3, 1, 2, 1, 3]).peaks()\n [4, 7]\n ... | Return a list of the peaks of the composition ``self``.
The peaks of a composition are the descents which do not
immediately follow another descent.
EXAMPLES::
sage: Composition([1, 1, 3, 1, 2, 1, 3]).peaks()
[4, 7] | src/sage/combinat/composition.py | peaks | LaisRast/sage | 1,742 | python | def peaks(self) -> list:
'\n Return a list of the peaks of the composition ``self``.\n\n The peaks of a composition are the descents which do not\n immediately follow another descent.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3, 1, 2, 1, 3]).peaks()\n [4, 7]\n ... | def peaks(self) -> list:
'\n Return a list of the peaks of the composition ``self``.\n\n The peaks of a composition are the descents which do not\n immediately follow another descent.\n\n EXAMPLES::\n\n sage: Composition([1, 1, 3, 1, 2, 1, 3]).peaks()\n [4, 7]\n ... |
16459ef774a220c1e957945d857c41ab5092714fa2ef505019e99584bc43e6a2 | @combinatorial_map(name='to partition')
def to_partition(self):
'\n Return the partition obtained by sorting ``self`` into decreasing\n order.\n\n EXAMPLES::\n\n sage: Composition([2,1,3]).to_partition()\n [3, 2, 1]\n sage: Composition([4,2,2]).to_partition()\n ... | Return the partition obtained by sorting ``self`` into decreasing
order.
EXAMPLES::
sage: Composition([2,1,3]).to_partition()
[3, 2, 1]
sage: Composition([4,2,2]).to_partition()
[4, 2, 2]
sage: Composition([]).to_partition()
[] | src/sage/combinat/composition.py | to_partition | LaisRast/sage | 1,742 | python | @combinatorial_map(name='to partition')
def to_partition(self):
'\n Return the partition obtained by sorting ``self`` into decreasing\n order.\n\n EXAMPLES::\n\n sage: Composition([2,1,3]).to_partition()\n [3, 2, 1]\n sage: Composition([4,2,2]).to_partition()\n ... | @combinatorial_map(name='to partition')
def to_partition(self):
'\n Return the partition obtained by sorting ``self`` into decreasing\n order.\n\n EXAMPLES::\n\n sage: Composition([2,1,3]).to_partition()\n [3, 2, 1]\n sage: Composition([4,2,2]).to_partition()\n ... |
74af69816849f048cf0f1cdc06e6cb458060e1fcb0e8538ba3b94ba90a4116c2 | def to_skew_partition(self, overlap=1):
'\n Return the skew partition obtained from ``self``.\n\n This is a skew partition whose rows have the entries of\n ``self`` as their length, taken in reverse order (so the first\n entry of ``self`` is the length of the lowermost row,\n etc.... | Return the skew partition obtained from ``self``.
This is a skew partition whose rows have the entries of
``self`` as their length, taken in reverse order (so the first
entry of ``self`` is the length of the lowermost row,
etc.). The parameter ``overlap`` indicates the number of cells
on each row that are directly bel... | src/sage/combinat/composition.py | to_skew_partition | LaisRast/sage | 1,742 | python | def to_skew_partition(self, overlap=1):
'\n Return the skew partition obtained from ``self``.\n\n This is a skew partition whose rows have the entries of\n ``self`` as their length, taken in reverse order (so the first\n entry of ``self`` is the length of the lowermost row,\n etc.... | def to_skew_partition(self, overlap=1):
'\n Return the skew partition obtained from ``self``.\n\n This is a skew partition whose rows have the entries of\n ``self`` as their length, taken in reverse order (so the first\n entry of ``self`` is the length of the lowermost row,\n etc.... |
ddc5886b7cd295e0fae24bedb26fa9d30762e30159afb58e33d9ec93e4e0c11b | def shuffle_product(self, other, overlap=False):
'\n The (overlapping) shuffles of ``self`` and ``other``.\n\n Suppose `I = (i_1, \\ldots, i_k)` and `J = (j_1, \\ldots, j_l)` are two\n compositions. A *shuffle* of `I` and `J` is a composition of length\n `k + l` that contains both `I` an... | The (overlapping) shuffles of ``self`` and ``other``.
Suppose `I = (i_1, \ldots, i_k)` and `J = (j_1, \ldots, j_l)` are two
compositions. A *shuffle* of `I` and `J` is a composition of length
`k + l` that contains both `I` and `J` as subsequences.
More generally, an *overlapping shuffle* of `I` and `J` is obtained by... | src/sage/combinat/composition.py | shuffle_product | LaisRast/sage | 1,742 | python | def shuffle_product(self, other, overlap=False):
'\n The (overlapping) shuffles of ``self`` and ``other``.\n\n Suppose `I = (i_1, \\ldots, i_k)` and `J = (j_1, \\ldots, j_l)` are two\n compositions. A *shuffle* of `I` and `J` is a composition of length\n `k + l` that contains both `I` an... | def shuffle_product(self, other, overlap=False):
'\n The (overlapping) shuffles of ``self`` and ``other``.\n\n Suppose `I = (i_1, \\ldots, i_k)` and `J = (j_1, \\ldots, j_l)` are two\n compositions. A *shuffle* of `I` and `J` is a composition of length\n `k + l` that contains both `I` an... |
18219f00921bba4816ef657e2fafe2264bada745f2601592baa1f29d63ccb3a2 | def wll_gt(self, co2) -> bool:
'\n Return ``True`` if the composition ``self`` is greater than the\n composition ``co2`` with respect to the wll-ordering; otherwise,\n return ``False``.\n\n The wll-ordering is a total order on the set of all compositions\n defined as follows: A co... | Return ``True`` if the composition ``self`` is greater than the
composition ``co2`` with respect to the wll-ordering; otherwise,
return ``False``.
The wll-ordering is a total order on the set of all compositions
defined as follows: A composition `I` is greater than a
composition `J` if and only if one of the following... | src/sage/combinat/composition.py | wll_gt | LaisRast/sage | 1,742 | python | def wll_gt(self, co2) -> bool:
'\n Return ``True`` if the composition ``self`` is greater than the\n composition ``co2`` with respect to the wll-ordering; otherwise,\n return ``False``.\n\n The wll-ordering is a total order on the set of all compositions\n defined as follows: A co... | def wll_gt(self, co2) -> bool:
'\n Return ``True`` if the composition ``self`` is greater than the\n composition ``co2`` with respect to the wll-ordering; otherwise,\n return ``False``.\n\n The wll-ordering is a total order on the set of all compositions\n defined as follows: A co... |
358922a272f40468d20ac98d38de94db43fa1304b35d218ba7830d5e03d2cc86 | @staticmethod
def __classcall_private__(self, n=None, **kwargs):
'\n Return the correct parent based upon the input.\n\n EXAMPLES::\n\n sage: C = Compositions(3)\n sage: C2 = Compositions(int(3))\n sage: C is C2\n True\n '
if (n is None):
... | Return the correct parent based upon the input.
EXAMPLES::
sage: C = Compositions(3)
sage: C2 = Compositions(int(3))
sage: C is C2
True | src/sage/combinat/composition.py | __classcall_private__ | LaisRast/sage | 1,742 | python | @staticmethod
def __classcall_private__(self, n=None, **kwargs):
'\n Return the correct parent based upon the input.\n\n EXAMPLES::\n\n sage: C = Compositions(3)\n sage: C2 = Compositions(int(3))\n sage: C is C2\n True\n '
if (n is None):
... | @staticmethod
def __classcall_private__(self, n=None, **kwargs):
'\n Return the correct parent based upon the input.\n\n EXAMPLES::\n\n sage: C = Compositions(3)\n sage: C2 = Compositions(int(3))\n sage: C is C2\n True\n '
if (n is None):
... |
cb88cb3f85e6c3bd4d8fc8a85f2f94b95b01c446cc2b20ac246d00730f8b8a63 | def __init__(self, is_infinite=False):
'\n Initialize ``self``.\n\n EXAMPLES::\n\n sage: C = Compositions()\n sage: TestSuite(C).run()\n '
if is_infinite:
Parent.__init__(self, category=InfiniteEnumeratedSets())
else:
Parent.__init__(self, category=... | Initialize ``self``.
EXAMPLES::
sage: C = Compositions()
sage: TestSuite(C).run() | src/sage/combinat/composition.py | __init__ | LaisRast/sage | 1,742 | python | def __init__(self, is_infinite=False):
'\n Initialize ``self``.\n\n EXAMPLES::\n\n sage: C = Compositions()\n sage: TestSuite(C).run()\n '
if is_infinite:
Parent.__init__(self, category=InfiniteEnumeratedSets())
else:
Parent.__init__(self, category=... | def __init__(self, is_infinite=False):
'\n Initialize ``self``.\n\n EXAMPLES::\n\n sage: C = Compositions()\n sage: TestSuite(C).run()\n '
if is_infinite:
Parent.__init__(self, category=InfiniteEnumeratedSets())
else:
Parent.__init__(self, category=... |
ffb63191c67bef06f5752a1895816dd981a733d39b35be23b703f1234f853647 | def _element_constructor_(self, lst) -> Composition:
'\n Construct an element with ``self`` as parent.\n\n EXAMPLES::\n\n sage: P = Compositions()\n sage: P([3,3,1]) # indirect doctest\n [3, 3, 1]\n '
if isinstance(lst, Composition):
lst = list(lst)
... | Construct an element with ``self`` as parent.
EXAMPLES::
sage: P = Compositions()
sage: P([3,3,1]) # indirect doctest
[3, 3, 1] | src/sage/combinat/composition.py | _element_constructor_ | LaisRast/sage | 1,742 | python | def _element_constructor_(self, lst) -> Composition:
'\n Construct an element with ``self`` as parent.\n\n EXAMPLES::\n\n sage: P = Compositions()\n sage: P([3,3,1]) # indirect doctest\n [3, 3, 1]\n '
if isinstance(lst, Composition):
lst = list(lst)
... | def _element_constructor_(self, lst) -> Composition:
'\n Construct an element with ``self`` as parent.\n\n EXAMPLES::\n\n sage: P = Compositions()\n sage: P([3,3,1]) # indirect doctest\n [3, 3, 1]\n '
if isinstance(lst, Composition):
lst = list(lst)
... |
a11155f8ad2c6177beeff723cba792cff13019ecf7f7dd50719aa5e0c1cdb22b | def __contains__(self, x) -> bool:
'\n TESTS::\n\n sage: [2,1,3] in Compositions()\n True\n sage: [] in Compositions()\n True\n sage: [-2,-1] in Compositions()\n False\n sage: [0,0] in Compositions()\n True\n '
... | TESTS::
sage: [2,1,3] in Compositions()
True
sage: [] in Compositions()
True
sage: [-2,-1] in Compositions()
False
sage: [0,0] in Compositions()
True | src/sage/combinat/composition.py | __contains__ | LaisRast/sage | 1,742 | python | def __contains__(self, x) -> bool:
'\n TESTS::\n\n sage: [2,1,3] in Compositions()\n True\n sage: [] in Compositions()\n True\n sage: [-2,-1] in Compositions()\n False\n sage: [0,0] in Compositions()\n True\n '
... | def __contains__(self, x) -> bool:
'\n TESTS::\n\n sage: [2,1,3] in Compositions()\n True\n sage: [] in Compositions()\n True\n sage: [-2,-1] in Compositions()\n False\n sage: [0,0] in Compositions()\n True\n '
... |
a9676344390824767d9bda57bb00246883d2d94a9e0500dcce41c5d388e33dbb | def from_descents(self, descents, nps=None) -> Composition:
'\n Return a composition from the list of descents.\n\n INPUT:\n\n - ``descents`` -- an iterable\n\n - ``nps`` -- (default: ``None``) an integer or ``None``\n\n OUTPUT:\n\n - The composition of ``nps`` whose descen... | Return a composition from the list of descents.
INPUT:
- ``descents`` -- an iterable
- ``nps`` -- (default: ``None``) an integer or ``None``
OUTPUT:
- The composition of ``nps`` whose descents are listed in
``descents``, assuming that ``nps`` is not ``None`` (otherwise,
the last element of ``descents`` is remo... | src/sage/combinat/composition.py | from_descents | LaisRast/sage | 1,742 | python | def from_descents(self, descents, nps=None) -> Composition:
'\n Return a composition from the list of descents.\n\n INPUT:\n\n - ``descents`` -- an iterable\n\n - ``nps`` -- (default: ``None``) an integer or ``None``\n\n OUTPUT:\n\n - The composition of ``nps`` whose descen... | def from_descents(self, descents, nps=None) -> Composition:
'\n Return a composition from the list of descents.\n\n INPUT:\n\n - ``descents`` -- an iterable\n\n - ``nps`` -- (default: ``None``) an integer or ``None``\n\n OUTPUT:\n\n - The composition of ``nps`` whose descen... |
3e3b6d04705665ecaa047f6fe82225749509a48a01aaf622d71189dfb22e4a4e | def from_subset(self, S, n) -> Composition:
'\n The composition of `n` corresponding to the subset ``S`` of\n `\\{1, 2, \\ldots, n-1\\}` under the bijection that maps the composition\n `(i_1, i_2, \\ldots, i_k)` of `n` to the subset\n `\\{i_1, i_1 + i_2, i_1 + i_2 + i_3, \\ldots, i_1 + \... | The composition of `n` corresponding to the subset ``S`` of
`\{1, 2, \ldots, n-1\}` under the bijection that maps the composition
`(i_1, i_2, \ldots, i_k)` of `n` to the subset
`\{i_1, i_1 + i_2, i_1 + i_2 + i_3, \ldots, i_1 + \cdots + i_{k-1}\}`
(see :meth:`Composition.to_subset`).
INPUT:
- ``S`` -- an iterable, a s... | src/sage/combinat/composition.py | from_subset | LaisRast/sage | 1,742 | python | def from_subset(self, S, n) -> Composition:
'\n The composition of `n` corresponding to the subset ``S`` of\n `\\{1, 2, \\ldots, n-1\\}` under the bijection that maps the composition\n `(i_1, i_2, \\ldots, i_k)` of `n` to the subset\n `\\{i_1, i_1 + i_2, i_1 + i_2 + i_3, \\ldots, i_1 + \... | def from_subset(self, S, n) -> Composition:
'\n The composition of `n` corresponding to the subset ``S`` of\n `\\{1, 2, \\ldots, n-1\\}` under the bijection that maps the composition\n `(i_1, i_2, \\ldots, i_k)` of `n` to the subset\n `\\{i_1, i_1 + i_2, i_1 + i_2 + i_3, \\ldots, i_1 + \... |
5cb5dc5462fd0b7bc867ab3cdfbed52910c7bc2cf9ecff87dd587ce259b01e94 | def from_code(self, code) -> Composition:
'\n Return the composition from its code. The code of a composition\n `I` is a list of length `\\mathrm{size}(I)` consisting of 1s and\n 0s such that there is a 1 wherever a new part starts.\n (Exceptional case: When the composition is empty, the... | Return the composition from its code. The code of a composition
`I` is a list of length `\mathrm{size}(I)` consisting of 1s and
0s such that there is a 1 wherever a new part starts.
(Exceptional case: When the composition is empty, the code is
``[0]``.)
EXAMPLES::
sage: Composition([4,1,2,3,5]).to_code()
[1, ... | src/sage/combinat/composition.py | from_code | LaisRast/sage | 1,742 | python | def from_code(self, code) -> Composition:
'\n Return the composition from its code. The code of a composition\n `I` is a list of length `\\mathrm{size}(I)` consisting of 1s and\n 0s such that there is a 1 wherever a new part starts.\n (Exceptional case: When the composition is empty, the... | def from_code(self, code) -> Composition:
'\n Return the composition from its code. The code of a composition\n `I` is a list of length `\\mathrm{size}(I)` consisting of 1s and\n 0s such that there is a 1 wherever a new part starts.\n (Exceptional case: When the composition is empty, the... |
2987bf49abb9c4afd39408fcb9faec8edd9a8013399cf9a16a22bd3e88a4313c | def __setstate__(self, data):
"\n TESTS::\n\n # This is the unpickling sequence for Compositions(4, max_part=2) in sage <= 4.1.1\n sage: pg_Compositions_constraints = unpickle_global('sage.combinat.composition', 'Compositions_constraints')\n sage: si = unpickle_newobj(pg_Comp... | TESTS::
# This is the unpickling sequence for Compositions(4, max_part=2) in sage <= 4.1.1
sage: pg_Compositions_constraints = unpickle_global('sage.combinat.composition', 'Compositions_constraints')
sage: si = unpickle_newobj(pg_Compositions_constraints, ())
sage: pg_make_integer = unpickle_global('sa... | src/sage/combinat/composition.py | __setstate__ | LaisRast/sage | 1,742 | python | def __setstate__(self, data):
"\n TESTS::\n\n # This is the unpickling sequence for Compositions(4, max_part=2) in sage <= 4.1.1\n sage: pg_Compositions_constraints = unpickle_global('sage.combinat.composition', 'Compositions_constraints')\n sage: si = unpickle_newobj(pg_Comp... | def __setstate__(self, data):
"\n TESTS::\n\n # This is the unpickling sequence for Compositions(4, max_part=2) in sage <= 4.1.1\n sage: pg_Compositions_constraints = unpickle_global('sage.combinat.composition', 'Compositions_constraints')\n sage: si = unpickle_newobj(pg_Comp... |
54ee8eafd675bc9c96e05a9ab3590ce3a0631f79ae55ed414ddf034080a6a068 | def __init__(self):
'\n Initialize ``self``.\n\n TESTS::\n\n sage: C = Compositions()\n sage: TestSuite(C).run()\n '
Compositions.__init__(self, True) | Initialize ``self``.
TESTS::
sage: C = Compositions()
sage: TestSuite(C).run() | src/sage/combinat/composition.py | __init__ | LaisRast/sage | 1,742 | python | def __init__(self):
'\n Initialize ``self``.\n\n TESTS::\n\n sage: C = Compositions()\n sage: TestSuite(C).run()\n '
Compositions.__init__(self, True) | def __init__(self):
'\n Initialize ``self``.\n\n TESTS::\n\n sage: C = Compositions()\n sage: TestSuite(C).run()\n '
Compositions.__init__(self, True)<|docstring|>Initialize ``self``.
TESTS::
sage: C = Compositions()
sage: TestSuite(C).run()<|endoftext|> |
b37630fb79e404c148c3de7c61303cb1b798895e3ebb0089d47325a90a7c74a9 | def _repr_(self) -> str:
"\n Return a string representation of ``self``.\n\n TESTS::\n\n sage: repr(Compositions())\n 'Compositions of non-negative integers'\n "
return 'Compositions of non-negative integers' | Return a string representation of ``self``.
TESTS::
sage: repr(Compositions())
'Compositions of non-negative integers' | src/sage/combinat/composition.py | _repr_ | LaisRast/sage | 1,742 | python | def _repr_(self) -> str:
"\n Return a string representation of ``self``.\n\n TESTS::\n\n sage: repr(Compositions())\n 'Compositions of non-negative integers'\n "
return 'Compositions of non-negative integers' | def _repr_(self) -> str:
"\n Return a string representation of ``self``.\n\n TESTS::\n\n sage: repr(Compositions())\n 'Compositions of non-negative integers'\n "
return 'Compositions of non-negative integers'<|docstring|>Return a string representation of ``self``.
TES... |
c8e91563e33be33ce3de3715b303e821d313a39460493c1a25a602e317ee048a | def subset(self, size=None):
'\n Return the set of compositions of the given size.\n\n EXAMPLES::\n\n sage: C = Compositions()\n sage: C.subset(4)\n Compositions of 4\n sage: C.subset(size=3)\n Compositions of 3\n '
if (size is None):
... | Return the set of compositions of the given size.
EXAMPLES::
sage: C = Compositions()
sage: C.subset(4)
Compositions of 4
sage: C.subset(size=3)
Compositions of 3 | src/sage/combinat/composition.py | subset | LaisRast/sage | 1,742 | python | def subset(self, size=None):
'\n Return the set of compositions of the given size.\n\n EXAMPLES::\n\n sage: C = Compositions()\n sage: C.subset(4)\n Compositions of 4\n sage: C.subset(size=3)\n Compositions of 3\n '
if (size is None):
... | def subset(self, size=None):
'\n Return the set of compositions of the given size.\n\n EXAMPLES::\n\n sage: C = Compositions()\n sage: C.subset(4)\n Compositions of 4\n sage: C.subset(size=3)\n Compositions of 3\n '
if (size is None):
... |
af4e44db406c212801bf4f641a5e49c866fd294a423de31b8ed0b2295b4f9db4 | def __iter__(self):
'\n Iterate over all compositions.\n\n TESTS::\n\n sage: C = Compositions()\n sage: it = C.__iter__()\n sage: [next(it) for i in range(10)]\n [[], [1], [1, 1], [2], [1, 1, 1], [1, 2], [2, 1], [3], [1, 1, 1, 1], [1, 1, 2]]\n '
n... | Iterate over all compositions.
TESTS::
sage: C = Compositions()
sage: it = C.__iter__()
sage: [next(it) for i in range(10)]
[[], [1], [1, 1], [2], [1, 1, 1], [1, 2], [2, 1], [3], [1, 1, 1, 1], [1, 1, 2]] | src/sage/combinat/composition.py | __iter__ | LaisRast/sage | 1,742 | python | def __iter__(self):
'\n Iterate over all compositions.\n\n TESTS::\n\n sage: C = Compositions()\n sage: it = C.__iter__()\n sage: [next(it) for i in range(10)]\n [[], [1], [1, 1], [2], [1, 1, 1], [1, 2], [2, 1], [3], [1, 1, 1, 1], [1, 1, 2]]\n '
n... | def __iter__(self):
'\n Iterate over all compositions.\n\n TESTS::\n\n sage: C = Compositions()\n sage: it = C.__iter__()\n sage: [next(it) for i in range(10)]\n [[], [1], [1, 1], [2], [1, 1, 1], [1, 2], [2, 1], [3], [1, 1, 1, 1], [1, 1, 2]]\n '
n... |
980c61137b53364385ab01d313930f11ce06f2eb5020f10f51bf0f0539e89658 | @staticmethod
def __classcall_private__(cls, n):
'\n Standardize input to ensure a unique representation.\n\n EXAMPLES::\n\n sage: C = Compositions(5)\n sage: C2 = Compositions(int(5))\n sage: C3 = Compositions(ZZ(5))\n sage: C is C2\n True\n ... | Standardize input to ensure a unique representation.
EXAMPLES::
sage: C = Compositions(5)
sage: C2 = Compositions(int(5))
sage: C3 = Compositions(ZZ(5))
sage: C is C2
True
sage: C is C3
True | src/sage/combinat/composition.py | __classcall_private__ | LaisRast/sage | 1,742 | python | @staticmethod
def __classcall_private__(cls, n):
'\n Standardize input to ensure a unique representation.\n\n EXAMPLES::\n\n sage: C = Compositions(5)\n sage: C2 = Compositions(int(5))\n sage: C3 = Compositions(ZZ(5))\n sage: C is C2\n True\n ... | @staticmethod
def __classcall_private__(cls, n):
'\n Standardize input to ensure a unique representation.\n\n EXAMPLES::\n\n sage: C = Compositions(5)\n sage: C2 = Compositions(int(5))\n sage: C3 = Compositions(ZZ(5))\n sage: C is C2\n True\n ... |
25fa8005d531dfa16eda8065674c4d125be3b9621997d8330344fefb48350d9e | def __init__(self, n):
'\n TESTS::\n\n sage: C = Compositions(3)\n sage: C == loads(dumps(C))\n True\n sage: TestSuite(C).run()\n '
self.n = n
Compositions.__init__(self, False) | TESTS::
sage: C = Compositions(3)
sage: C == loads(dumps(C))
True
sage: TestSuite(C).run() | src/sage/combinat/composition.py | __init__ | LaisRast/sage | 1,742 | python | def __init__(self, n):
'\n TESTS::\n\n sage: C = Compositions(3)\n sage: C == loads(dumps(C))\n True\n sage: TestSuite(C).run()\n '
self.n = n
Compositions.__init__(self, False) | def __init__(self, n):
'\n TESTS::\n\n sage: C = Compositions(3)\n sage: C == loads(dumps(C))\n True\n sage: TestSuite(C).run()\n '
self.n = n
Compositions.__init__(self, False)<|docstring|>TESTS::
sage: C = Compositions(3)
sage: C == loads(... |
b28101881c7e4a4a81283e44d564900d91b8655fe1750cc730918931ef17c876 | def _repr_(self) -> str:
"\n Return a string representation of ``self``.\n\n TESTS::\n\n sage: repr(Compositions(3))\n 'Compositions of 3'\n "
return ('Compositions of %s' % self.n) | Return a string representation of ``self``.
TESTS::
sage: repr(Compositions(3))
'Compositions of 3' | src/sage/combinat/composition.py | _repr_ | LaisRast/sage | 1,742 | python | def _repr_(self) -> str:
"\n Return a string representation of ``self``.\n\n TESTS::\n\n sage: repr(Compositions(3))\n 'Compositions of 3'\n "
return ('Compositions of %s' % self.n) | def _repr_(self) -> str:
"\n Return a string representation of ``self``.\n\n TESTS::\n\n sage: repr(Compositions(3))\n 'Compositions of 3'\n "
return ('Compositions of %s' % self.n)<|docstring|>Return a string representation of ``self``.
TESTS::
sage: repr(Compos... |
7289e28ed2d81acc5551b23073cc743422f33b84813731366e0686f46807e221 | def __contains__(self, x) -> bool:
'\n TESTS::\n\n sage: [2,1,3] in Compositions(6)\n True\n sage: [2,1,2] in Compositions(6)\n False\n sage: [] in Compositions(0)\n True\n sage: [0] in Compositions(0)\n True\n '
... | TESTS::
sage: [2,1,3] in Compositions(6)
True
sage: [2,1,2] in Compositions(6)
False
sage: [] in Compositions(0)
True
sage: [0] in Compositions(0)
True | src/sage/combinat/composition.py | __contains__ | LaisRast/sage | 1,742 | python | def __contains__(self, x) -> bool:
'\n TESTS::\n\n sage: [2,1,3] in Compositions(6)\n True\n sage: [2,1,2] in Compositions(6)\n False\n sage: [] in Compositions(0)\n True\n sage: [0] in Compositions(0)\n True\n '
... | def __contains__(self, x) -> bool:
'\n TESTS::\n\n sage: [2,1,3] in Compositions(6)\n True\n sage: [2,1,2] in Compositions(6)\n False\n sage: [] in Compositions(0)\n True\n sage: [0] in Compositions(0)\n True\n '
... |
8e34c4a9f8728f7f53d6cc927cfe12d2c52dccd0de4df1c1151c390136ceb35f | def cardinality(self) -> Integer:
'\n Return the number of compositions of `n`.\n\n TESTS::\n\n sage: Compositions(3).cardinality()\n 4\n sage: Compositions(0).cardinality()\n 1\n '
if (self.n >= 1):
return (ZZ(2) ** (self.n - 1))
elif... | Return the number of compositions of `n`.
TESTS::
sage: Compositions(3).cardinality()
4
sage: Compositions(0).cardinality()
1 | src/sage/combinat/composition.py | cardinality | LaisRast/sage | 1,742 | python | def cardinality(self) -> Integer:
'\n Return the number of compositions of `n`.\n\n TESTS::\n\n sage: Compositions(3).cardinality()\n 4\n sage: Compositions(0).cardinality()\n 1\n '
if (self.n >= 1):
return (ZZ(2) ** (self.n - 1))
elif... | def cardinality(self) -> Integer:
'\n Return the number of compositions of `n`.\n\n TESTS::\n\n sage: Compositions(3).cardinality()\n 4\n sage: Compositions(0).cardinality()\n 1\n '
if (self.n >= 1):
return (ZZ(2) ** (self.n - 1))
elif... |
87d9422f980bc0abedd32ed8efc9d888748da3544e0623b79efe569d27ccd7f8 | def random_element(self) -> Composition:
'\n Return a random ``Composition`` with uniform probability.\n\n This method generates a random binary word starting with a 1\n and then uses the bijection between compositions and their code.\n\n EXAMPLES::\n\n sage: Compositions(5).r... | Return a random ``Composition`` with uniform probability.
This method generates a random binary word starting with a 1
and then uses the bijection between compositions and their code.
EXAMPLES::
sage: Compositions(5).random_element() # random
[2, 1, 1, 1]
sage: Compositions(0).random_element()
[]
... | src/sage/combinat/composition.py | random_element | LaisRast/sage | 1,742 | python | def random_element(self) -> Composition:
'\n Return a random ``Composition`` with uniform probability.\n\n This method generates a random binary word starting with a 1\n and then uses the bijection between compositions and their code.\n\n EXAMPLES::\n\n sage: Compositions(5).r... | def random_element(self) -> Composition:
'\n Return a random ``Composition`` with uniform probability.\n\n This method generates a random binary word starting with a 1\n and then uses the bijection between compositions and their code.\n\n EXAMPLES::\n\n sage: Compositions(5).r... |
d83f0459773b8a466b9cd598ac33f43cbe9568c4887811b1940e80d4c3e49d12 | def __iter__(self):
'\n Iterate over the compositions of `n`.\n\n TESTS::\n\n sage: Compositions(4).list()\n [[1, 1, 1, 1], [1, 1, 2], [1, 2, 1], [1, 3], [2, 1, 1], [2, 2], [3, 1], [4]]\n sage: Compositions(0).list()\n [[]]\n '
for c in compositio... | Iterate over the compositions of `n`.
TESTS::
sage: Compositions(4).list()
[[1, 1, 1, 1], [1, 1, 2], [1, 2, 1], [1, 3], [2, 1, 1], [2, 2], [3, 1], [4]]
sage: Compositions(0).list()
[[]] | src/sage/combinat/composition.py | __iter__ | LaisRast/sage | 1,742 | python | def __iter__(self):
'\n Iterate over the compositions of `n`.\n\n TESTS::\n\n sage: Compositions(4).list()\n [[1, 1, 1, 1], [1, 1, 2], [1, 2, 1], [1, 3], [2, 1, 1], [2, 2], [3, 1], [4]]\n sage: Compositions(0).list()\n [[]]\n '
for c in compositio... | def __iter__(self):
'\n Iterate over the compositions of `n`.\n\n TESTS::\n\n sage: Compositions(4).list()\n [[1, 1, 1, 1], [1, 1, 2], [1, 2, 1], [1, 3], [2, 1, 1], [2, 2], [3, 1], [4]]\n sage: Compositions(0).list()\n [[]]\n '
for c in compositio... |
9c5fd0a0fe9a14a420df25932616cabbad9e4356bb25c420cf8a21dede292401 | def imresize(D, dims, kind='cubic', use_scipy=False):
"\n Resize a floating point image\n Parameters\n ----------\n D : ndarray(M1, N1)\n Original image\n dims : tuple(M2, N2)\n The dimensions to which to resize\n kind : string\n The kind of interpolation to use\n use_scipy... | Resize a floating point image
Parameters
----------
D : ndarray(M1, N1)
Original image
dims : tuple(M2, N2)
The dimensions to which to resize
kind : string
The kind of interpolation to use
use_scipy : boolean
Fall back to scipy.misc.imresize. This is a bad idea
because it casts everything to uint8,... | CSMSSMTools.py | imresize | jagpreet1058/CoverSongIdentification | 20 | python | def imresize(D, dims, kind='cubic', use_scipy=False):
"\n Resize a floating point image\n Parameters\n ----------\n D : ndarray(M1, N1)\n Original image\n dims : tuple(M2, N2)\n The dimensions to which to resize\n kind : string\n The kind of interpolation to use\n use_scipy... | def imresize(D, dims, kind='cubic', use_scipy=False):
"\n Resize a floating point image\n Parameters\n ----------\n D : ndarray(M1, N1)\n Original image\n dims : tuple(M2, N2)\n The dimensions to which to resize\n kind : string\n The kind of interpolation to use\n use_scipy... |
a837d1974d38df51849caecefa7c84fb6f6c3f747b82cabf021f679379f81b3d | def getSSM(X, DPixels, doPlot=False):
'\n Compute a Euclidean self-similarity image between a set of points\n :param X: An Nxd matrix holding the d coordinates of N points\n :param DPixels: The image will be resized to this dimensions\n :param doPlot: If true, show a plot comparing the original/resized ... | Compute a Euclidean self-similarity image between a set of points
:param X: An Nxd matrix holding the d coordinates of N points
:param DPixels: The image will be resized to this dimensions
:param doPlot: If true, show a plot comparing the original/resized images
:return: A tuple (D, DResized) | CSMSSMTools.py | getSSM | jagpreet1058/CoverSongIdentification | 20 | python | def getSSM(X, DPixels, doPlot=False):
'\n Compute a Euclidean self-similarity image between a set of points\n :param X: An Nxd matrix holding the d coordinates of N points\n :param DPixels: The image will be resized to this dimensions\n :param doPlot: If true, show a plot comparing the original/resized ... | def getSSM(X, DPixels, doPlot=False):
'\n Compute a Euclidean self-similarity image between a set of points\n :param X: An Nxd matrix holding the d coordinates of N points\n :param DPixels: The image will be resized to this dimensions\n :param doPlot: If true, show a plot comparing the original/resized ... |
d5f3648f50a0f739bb782a69b0ea7bf03a8cac7149a4b735f31abf7dfded145a | def getSSMAltMetric(X, A, DPixels, doPlot=False):
'\n Compute a self-similarity matrix under an alternative metric specified\n by the symmetric positive definite matrix A^TA, so that the squared\n Euclidean distance under this metric between two vectors x and y is\n (x-y)^T*A^T*A*(x-y)\n :param X: An... | Compute a self-similarity matrix under an alternative metric specified
by the symmetric positive definite matrix A^TA, so that the squared
Euclidean distance under this metric between two vectors x and y is
(x-y)^T*A^T*A*(x-y)
:param X: An Nxd matrix holding the d coordinates of N points
:param DPixels: The image will ... | CSMSSMTools.py | getSSMAltMetric | jagpreet1058/CoverSongIdentification | 20 | python | def getSSMAltMetric(X, A, DPixels, doPlot=False):
'\n Compute a self-similarity matrix under an alternative metric specified\n by the symmetric positive definite matrix A^TA, so that the squared\n Euclidean distance under this metric between two vectors x and y is\n (x-y)^T*A^T*A*(x-y)\n :param X: An... | def getSSMAltMetric(X, A, DPixels, doPlot=False):
'\n Compute a self-similarity matrix under an alternative metric specified\n by the symmetric positive definite matrix A^TA, so that the squared\n Euclidean distance under this metric between two vectors x and y is\n (x-y)^T*A^T*A*(x-y)\n :param X: An... |
9f933df24164e5a8c60313168b297db0dde1e1a7a6bc42de5a7860de9961ab13 | def getCSM(X, Y):
'\n Return the Euclidean cross-similarity matrix between the M points\n in the Mxd matrix X and the N points in the Nxd matrix Y.\n :param X: An Mxd matrix holding the coordinates of M points\n :param Y: An Nxd matrix holding the coordinates of N points\n :return D: An MxN Euclidean... | Return the Euclidean cross-similarity matrix between the M points
in the Mxd matrix X and the N points in the Nxd matrix Y.
:param X: An Mxd matrix holding the coordinates of M points
:param Y: An Nxd matrix holding the coordinates of N points
:return D: An MxN Euclidean cross-similarity matrix | CSMSSMTools.py | getCSM | jagpreet1058/CoverSongIdentification | 20 | python | def getCSM(X, Y):
'\n Return the Euclidean cross-similarity matrix between the M points\n in the Mxd matrix X and the N points in the Nxd matrix Y.\n :param X: An Mxd matrix holding the coordinates of M points\n :param Y: An Nxd matrix holding the coordinates of N points\n :return D: An MxN Euclidean... | def getCSM(X, Y):
'\n Return the Euclidean cross-similarity matrix between the M points\n in the Mxd matrix X and the N points in the Nxd matrix Y.\n :param X: An Mxd matrix holding the coordinates of M points\n :param Y: An Nxd matrix holding the coordinates of N points\n :return D: An MxN Euclidean... |
5852bc37fbda92ec6378f1864ffc10e9bcb6786b7a014b1acc9482e0896958bd | def getCSMEMD1D(X, Y):
"\n Compute an approximate of the earth mover's distance\n between the M points in the Mxd matrix X and the N points\n in the Nxd matrix Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :return D: An MxN distance matrix\n "
M = X.shape[0]
N = Y.shape[0]
K = X... | Compute an approximate of the earth mover's distance
between the M points in the Mxd matrix X and the N points
in the Nxd matrix Y
:param X: Mxd matrix
:param Y: Nxd matrix
:return D: An MxN distance matrix | CSMSSMTools.py | getCSMEMD1D | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMEMD1D(X, Y):
"\n Compute an approximate of the earth mover's distance\n between the M points in the Mxd matrix X and the N points\n in the Nxd matrix Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :return D: An MxN distance matrix\n "
M = X.shape[0]
N = Y.shape[0]
K = X... | def getCSMEMD1D(X, Y):
"\n Compute an approximate of the earth mover's distance\n between the M points in the Mxd matrix X and the N points\n in the Nxd matrix Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :return D: An MxN distance matrix\n "
M = X.shape[0]
N = Y.shape[0]
K = X... |
90f98e8bf94e1477a23a68da5a9bc8ff0544d170268abc43d38fb441cd046341 | def getCSMCosine(X, Y):
'\n Return the cosine distance between all vectors in X\n and all vectors in Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :return D: An MxN distance matrix\n '
XNorm = np.sqrt(np.sum((X ** 2), 1))
XNorm[(XNorm == 0)] = 1
YNorm = np.sqrt(np.sum((Y ** 2), 1))... | Return the cosine distance between all vectors in X
and all vectors in Y
:param X: Mxd matrix
:param Y: Nxd matrix
:return D: An MxN distance matrix | CSMSSMTools.py | getCSMCosine | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMCosine(X, Y):
'\n Return the cosine distance between all vectors in X\n and all vectors in Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :return D: An MxN distance matrix\n '
XNorm = np.sqrt(np.sum((X ** 2), 1))
XNorm[(XNorm == 0)] = 1
YNorm = np.sqrt(np.sum((Y ** 2), 1))... | def getCSMCosine(X, Y):
'\n Return the cosine distance between all vectors in X\n and all vectors in Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :return D: An MxN distance matrix\n '
XNorm = np.sqrt(np.sum((X ** 2), 1))
XNorm[(XNorm == 0)] = 1
YNorm = np.sqrt(np.sum((Y ** 2), 1))... |
8085568c4eb34eda5e14eb62072764469489ddea41e056211cf9f63db5265390 | def getOTI(C1, C2, doPlot=False):
'\n Get the optimial transposition of the first chroma vector\n with respect to the second one\n :param C1: Chroma vector 1\n :param C2: Chroma vector 2\n :param doPlot: Plot the agreements over all shifts\n :returns: An index by which to rotate the first chroma v... | Get the optimial transposition of the first chroma vector
with respect to the second one
:param C1: Chroma vector 1
:param C2: Chroma vector 2
:param doPlot: Plot the agreements over all shifts
:returns: An index by which to rotate the first chroma vector
to match with the second | CSMSSMTools.py | getOTI | jagpreet1058/CoverSongIdentification | 20 | python | def getOTI(C1, C2, doPlot=False):
'\n Get the optimial transposition of the first chroma vector\n with respect to the second one\n :param C1: Chroma vector 1\n :param C2: Chroma vector 2\n :param doPlot: Plot the agreements over all shifts\n :returns: An index by which to rotate the first chroma v... | def getOTI(C1, C2, doPlot=False):
'\n Get the optimial transposition of the first chroma vector\n with respect to the second one\n :param C1: Chroma vector 1\n :param C2: Chroma vector 2\n :param doPlot: Plot the agreements over all shifts\n :returns: An index by which to rotate the first chroma v... |
242e22959e0aac9aa37af19a2e6321aefbf51b94533427f424a15d5c3ae79a6f | def getCSMCosineOTI(X, Y, C1, C2):
'\n Get the cosine distance between each row of X\n and each row of Y after doing a global optimal\n transposition change from X to Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :param C1: Global chroma vector 1\n :param C2: Global chroma vector 2\n :re... | Get the cosine distance between each row of X
and each row of Y after doing a global optimal
transposition change from X to Y
:param X: Mxd matrix
:param Y: Nxd matrix
:param C1: Global chroma vector 1
:param C2: Global chroma vector 2
:return D: An MxN distance matrix | CSMSSMTools.py | getCSMCosineOTI | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMCosineOTI(X, Y, C1, C2):
'\n Get the cosine distance between each row of X\n and each row of Y after doing a global optimal\n transposition change from X to Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :param C1: Global chroma vector 1\n :param C2: Global chroma vector 2\n :re... | def getCSMCosineOTI(X, Y, C1, C2):
'\n Get the cosine distance between each row of X\n and each row of Y after doing a global optimal\n transposition change from X to Y\n :param X: Mxd matrix\n :param Y: Nxd matrix\n :param C1: Global chroma vector 1\n :param C2: Global chroma vector 2\n :re... |
0fc3a524d1eb7da46ca2325c121322738fbd7f3b2b6dd04fe6dfa20343bf7d84 | def CSMToBinary(D, Kappa):
'\n Turn a cross-similarity matrix into a binary cross-simlarity matrix, using partitions instead of\n nearest neighbors for speed\n :param D: M x N cross-similarity matrix\n :param Kappa:\n If Kappa = 0, take all neighbors\n If Kappa < 1 it is the fraction of mu... | Turn a cross-similarity matrix into a binary cross-simlarity matrix, using partitions instead of
nearest neighbors for speed
:param D: M x N cross-similarity matrix
:param Kappa:
If Kappa = 0, take all neighbors
If Kappa < 1 it is the fraction of mutual neighbors to consider
Otherwise Kappa is the number of... | CSMSSMTools.py | CSMToBinary | jagpreet1058/CoverSongIdentification | 20 | python | def CSMToBinary(D, Kappa):
'\n Turn a cross-similarity matrix into a binary cross-simlarity matrix, using partitions instead of\n nearest neighbors for speed\n :param D: M x N cross-similarity matrix\n :param Kappa:\n If Kappa = 0, take all neighbors\n If Kappa < 1 it is the fraction of mu... | def CSMToBinary(D, Kappa):
'\n Turn a cross-similarity matrix into a binary cross-simlarity matrix, using partitions instead of\n nearest neighbors for speed\n :param D: M x N cross-similarity matrix\n :param Kappa:\n If Kappa = 0, take all neighbors\n If Kappa < 1 it is the fraction of mu... |
9ddf09de21a4a0f0b840af32209894c2bb49029a8c92d934c0b5ca5ee388dbb8 | def CSMToBinaryMutual(D, Kappa):
'\n Take the binary AND between the nearest neighbors in one\n direction and the other\n :param D: MxN cross-similarity matrix\n :param Kappa: (as in CSMToBinary)\n :returns B: MxN mutual binary cross-similarity matrix\n '
B1 = CSMToBinary(D, Kappa)
B2 = CS... | Take the binary AND between the nearest neighbors in one
direction and the other
:param D: MxN cross-similarity matrix
:param Kappa: (as in CSMToBinary)
:returns B: MxN mutual binary cross-similarity matrix | CSMSSMTools.py | CSMToBinaryMutual | jagpreet1058/CoverSongIdentification | 20 | python | def CSMToBinaryMutual(D, Kappa):
'\n Take the binary AND between the nearest neighbors in one\n direction and the other\n :param D: MxN cross-similarity matrix\n :param Kappa: (as in CSMToBinary)\n :returns B: MxN mutual binary cross-similarity matrix\n '
B1 = CSMToBinary(D, Kappa)
B2 = CS... | def CSMToBinaryMutual(D, Kappa):
'\n Take the binary AND between the nearest neighbors in one\n direction and the other\n :param D: MxN cross-similarity matrix\n :param Kappa: (as in CSMToBinary)\n :returns B: MxN mutual binary cross-similarity matrix\n '
B1 = CSMToBinary(D, Kappa)
B2 = CS... |
9d4191ef1d178ad438e411aa5b7c7e750cd00633044544668b796a2eaed44f5d | def getCSMType(Features1, O1, Features2, O2, Type):
'\n A wrapper around all of the cross-similarity functions\n which automatically determines which one to use based\n on the type passed in\n '
if (Type == 'Euclidean'):
return getCSM(Features1, Features2)
elif (Type == 'Cosine'):
... | A wrapper around all of the cross-similarity functions
which automatically determines which one to use based
on the type passed in | CSMSSMTools.py | getCSMType | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMType(Features1, O1, Features2, O2, Type):
'\n A wrapper around all of the cross-similarity functions\n which automatically determines which one to use based\n on the type passed in\n '
if (Type == 'Euclidean'):
return getCSM(Features1, Features2)
elif (Type == 'Cosine'):
... | def getCSMType(Features1, O1, Features2, O2, Type):
'\n A wrapper around all of the cross-similarity functions\n which automatically determines which one to use based\n on the type passed in\n '
if (Type == 'Euclidean'):
return getCSM(Features1, Features2)
elif (Type == 'Cosine'):
... |
57da41cf0f0ab772ede57017a52977369999f4828027ca7c8554dc775a5ed536 | def getCSMSmithWatermanScores(Features1, O1, Features2, O2, Kappa, Type, doPlot=False):
"\n Compute the Smith Waterman score between two songs\n using a single feature set\n :param Features1: Mxk matrix of features in song 1\n :param O1: Auxiliary info for song 1\n :param Features2: Nxk matrix of fea... | Compute the Smith Waterman score between two songs
using a single feature set
:param Features1: Mxk matrix of features in song 1
:param O1: Auxiliary info for song 1
:param Features2: Nxk matrix of features in song 2
:param O2: Auxiliary info for song 2
:param Kappa: Nearest neighbors param for CSM
:param Type: Type of... | CSMSSMTools.py | getCSMSmithWatermanScores | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMSmithWatermanScores(Features1, O1, Features2, O2, Kappa, Type, doPlot=False):
"\n Compute the Smith Waterman score between two songs\n using a single feature set\n :param Features1: Mxk matrix of features in song 1\n :param O1: Auxiliary info for song 1\n :param Features2: Nxk matrix of fea... | def getCSMSmithWatermanScores(Features1, O1, Features2, O2, Kappa, Type, doPlot=False):
"\n Compute the Smith Waterman score between two songs\n using a single feature set\n :param Features1: Mxk matrix of features in song 1\n :param O1: Auxiliary info for song 1\n :param Features2: Nxk matrix of fea... |
4cb8e0eebff3c603317b4b27f7c0facb7ac9e7c7f752382a0d633f9930498a8b | def getCSMSmithWatermanScoresORMerge(AllFeatures1, O1, AllFeatures2, O2, Kappa, CSMTypes, doPlot=False):
"\n Compute the Smith Waterman score between two songs\n after doing a binary OR on individual feature sets\n :param AllFeatures1: A dictionary of Mxk matric of\n features in song 1\n :param O... | Compute the Smith Waterman score between two songs
after doing a binary OR on individual feature sets
:param AllFeatures1: A dictionary of Mxk matric of
features in song 1
:param O1: Auxiliary info for song 1
:param AllFeatures2: A dictionary of Nxk matrix of
features in song 2
:param O2: Auxiliary info for son... | CSMSSMTools.py | getCSMSmithWatermanScoresORMerge | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMSmithWatermanScoresORMerge(AllFeatures1, O1, AllFeatures2, O2, Kappa, CSMTypes, doPlot=False):
"\n Compute the Smith Waterman score between two songs\n after doing a binary OR on individual feature sets\n :param AllFeatures1: A dictionary of Mxk matric of\n features in song 1\n :param O... | def getCSMSmithWatermanScoresORMerge(AllFeatures1, O1, AllFeatures2, O2, Kappa, CSMTypes, doPlot=False):
"\n Compute the Smith Waterman score between two songs\n after doing a binary OR on individual feature sets\n :param AllFeatures1: A dictionary of Mxk matric of\n features in song 1\n :param O... |
d09cef52a0f9feb2a2f2d65a54844e6b2b8a5b8cfaf7e174273e972047d4e5fd | def getCSMSmithWatermanScoresEarlyFusionFull(AllFeatures1, O1, AllFeatures2, O2, Kappa, K, NIters, CSMTypes, doPlot=False, conservative=False):
"\n Compute the Smith Waterman score between two songs\n after doing early similarity network fusion on\n individual feature sets\n :param AllFeatures1: A dicti... | Compute the Smith Waterman score between two songs
after doing early similarity network fusion on
individual feature sets
:param AllFeatures1: A dictionary of Mxk matric of
features in song 1
:param O1: Auxiliary info for song 1
:param AllFeatures2: A dictionary of Nxk matrix of
features in song 2
:param O2: Au... | CSMSSMTools.py | getCSMSmithWatermanScoresEarlyFusionFull | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMSmithWatermanScoresEarlyFusionFull(AllFeatures1, O1, AllFeatures2, O2, Kappa, K, NIters, CSMTypes, doPlot=False, conservative=False):
"\n Compute the Smith Waterman score between two songs\n after doing early similarity network fusion on\n individual feature sets\n :param AllFeatures1: A dicti... | def getCSMSmithWatermanScoresEarlyFusionFull(AllFeatures1, O1, AllFeatures2, O2, Kappa, K, NIters, CSMTypes, doPlot=False, conservative=False):
"\n Compute the Smith Waterman score between two songs\n after doing early similarity network fusion on\n individual feature sets\n :param AllFeatures1: A dicti... |
cb37c369a891bcfe32f85c7c8faa485ba6df1f6c9a15b8a081d0cbbe7ed4fcc6 | def getCSMSmithWatermanScoresEarlyFusion(AllFeatures1, O1, AllFeatures2, O2, Kappa, K, NIters, CSMTypes, doPlot=False):
'\n Just return the score from getCSMSmithWatermanScoresEarlyFusionFull,\n using the same parameters\n '
return getCSMSmithWatermanScoresEarlyFusionFull(AllFeatures1, O1, AllFeatures2... | Just return the score from getCSMSmithWatermanScoresEarlyFusionFull,
using the same parameters | CSMSSMTools.py | getCSMSmithWatermanScoresEarlyFusion | jagpreet1058/CoverSongIdentification | 20 | python | def getCSMSmithWatermanScoresEarlyFusion(AllFeatures1, O1, AllFeatures2, O2, Kappa, K, NIters, CSMTypes, doPlot=False):
'\n Just return the score from getCSMSmithWatermanScoresEarlyFusionFull,\n using the same parameters\n '
return getCSMSmithWatermanScoresEarlyFusionFull(AllFeatures1, O1, AllFeatures2... | def getCSMSmithWatermanScoresEarlyFusion(AllFeatures1, O1, AllFeatures2, O2, Kappa, K, NIters, CSMTypes, doPlot=False):
'\n Just return the score from getCSMSmithWatermanScoresEarlyFusionFull,\n using the same parameters\n '
return getCSMSmithWatermanScoresEarlyFusionFull(AllFeatures1, O1, AllFeatures2... |
37d23fe9fd4c8fd82eda7d5c758203bbc6de2ef92cc5a38f7632de0a88b6b017 | def get_event(self):
'\n Execute at the beginning of each cycle of every loop.\n '
self.event_list = pygame.event.get()
if self.match_event_type(QUIT):
' always check exit '
self._parent_game.quit_game()
self.keys_pressed = pygame.key.get_pressed()
self.mouse_button_sta... | Execute at the beginning of each cycle of every loop. | event_manager.py | get_event | Carcuis/pysnake | 2 | python | def get_event(self):
'\n \n '
self.event_list = pygame.event.get()
if self.match_event_type(QUIT):
' always check exit '
self._parent_game.quit_game()
self.keys_pressed = pygame.key.get_pressed()
self.mouse_button_status = pygame.mouse.get_pressed()
self.mouse_pos =... | def get_event(self):
'\n \n '
self.event_list = pygame.event.get()
if self.match_event_type(QUIT):
' always check exit '
self._parent_game.quit_game()
self.keys_pressed = pygame.key.get_pressed()
self.mouse_button_status = pygame.mouse.get_pressed()
self.mouse_pos =... |
adb44ff42be145ad6c1db82add7c8be6573d49b3c022dcdc56dae0d6f6bc9efc | def check_key_or_button(self, event_type, attribute):
'\n check if mouse button or keyboard key up or down\n :param event_type: mouse: MOUSEBUTTONDOWN or MOUSEBUTTONUP\n key: KEYDOWN or KEYUP\n :param attribute: (set or value) mouse: 1->left 2->middle 3->right 4->wheel... | check if mouse button or keyboard key up or down
:param event_type: mouse: MOUSEBUTTONDOWN or MOUSEBUTTONUP
key: KEYDOWN or KEYUP
:param attribute: (set or value) mouse: 1->left 2->middle 3->right 4->wheel_up 5->wheel_down / key
:return: bool: whether match event_type and button | event_manager.py | check_key_or_button | Carcuis/pysnake | 2 | python | def check_key_or_button(self, event_type, attribute):
'\n check if mouse button or keyboard key up or down\n :param event_type: mouse: MOUSEBUTTONDOWN or MOUSEBUTTONUP\n key: KEYDOWN or KEYUP\n :param attribute: (set or value) mouse: 1->left 2->middle 3->right 4->wheel... | def check_key_or_button(self, event_type, attribute):
'\n check if mouse button or keyboard key up or down\n :param event_type: mouse: MOUSEBUTTONDOWN or MOUSEBUTTONUP\n key: KEYDOWN or KEYUP\n :param attribute: (set or value) mouse: 1->left 2->middle 3->right 4->wheel... |
b57417f6a6c164558116e4b72931d2dde58ffd627fcf208350c37ee2608b11b1 | def early_stopping(self, loss: float) -> None:
'Counts how many consecutive losses are worse than current best.\n '
if (loss < self.current_best):
self.current_best = loss
self.patience_counter = 0
else:
self.patience_counter += 1 | Counts how many consecutive losses are worse than current best. | src/utils/trainer_jit.py | early_stopping | bask0/h2m | 1 | python | def early_stopping(self, loss: float) -> None:
'\n '
if (loss < self.current_best):
self.current_best = loss
self.patience_counter = 0
else:
self.patience_counter += 1 | def early_stopping(self, loss: float) -> None:
'\n '
if (loss < self.current_best):
self.current_best = loss
self.patience_counter = 0
else:
self.patience_counter += 1<|docstring|>Counts how many consecutive losses are worse than current best.<|endoftext|> |
0f1b2bb47d3f6d7e86e139ed17aff540e090f54498b1cc2c6128a383a139ce2a | def save(self, checkpoint: str) -> None:
'Saves the model at the provided checkpoint.\n\n Parameters\n ----------\n checkpoint\n Path to target checkpoint file.\n¨\n Returns\n ----------\n checkpoint\n\n '
savefile = os.path.join(checkpoint, 'chkp.pt')... | Saves the model at the provided checkpoint.
Parameters
----------
checkpoint
Path to target checkpoint file.
¨
Returns
----------
checkpoint | src/utils/trainer_jit.py | save | bask0/h2m | 1 | python | def save(self, checkpoint: str) -> None:
'Saves the model at the provided checkpoint.\n\n Parameters\n ----------\n checkpoint\n Path to target checkpoint file.\n¨\n Returns\n ----------\n checkpoint\n\n '
savefile = os.path.join(checkpoint, 'chkp.pt')... | def save(self, checkpoint: str) -> None:
'Saves the model at the provided checkpoint.\n\n Parameters\n ----------\n checkpoint\n Path to target checkpoint file.\n¨\n Returns\n ----------\n checkpoint\n\n '
savefile = os.path.join(checkpoint, 'chkp.pt')... |
c8b2e896e0484bdfbfce84883af7be5eab14ac731fd9117b48ee98a3f558d836 | def restore(self, checkpoint: str) -> None:
'Restores the model from a provided checkpoint.\n\n Parameters\n ----------\n filename\n Path to checkpoint file.\n\n '
checkpoint = torch.load(checkpoint)
self.model.load_state_dict(checkpoint['model_state_dict'])
self.m... | Restores the model from a provided checkpoint.
Parameters
----------
filename
Path to checkpoint file. | src/utils/trainer_jit.py | restore | bask0/h2m | 1 | python | def restore(self, checkpoint: str) -> None:
'Restores the model from a provided checkpoint.\n\n Parameters\n ----------\n filename\n Path to checkpoint file.\n\n '
checkpoint = torch.load(checkpoint)
self.model.load_state_dict(checkpoint['model_state_dict'])
self.m... | def restore(self, checkpoint: str) -> None:
'Restores the model from a provided checkpoint.\n\n Parameters\n ----------\n filename\n Path to checkpoint file.\n\n '
checkpoint = torch.load(checkpoint)
self.model.load_state_dict(checkpoint['model_state_dict'])
self.m... |
796d1f7cb3c1a54cd0ed568e388bc8dd83736ee0488c09f938bf658a7212c374 | def bin_reduce_(self, x: Dict[(str, torch.Tensor)], sample_set: str, fun: Callable=torch.mean) -> None:
"Inplace reduction of tensors time dimension (dim 1).\n\n Parameters\n ----------\n x\n A dict of tensors of which all items with key in ``keys`` get reduced\n in time d... | Inplace reduction of tensors time dimension (dim 1).
Parameters
----------
x
A dict of tensors of which all items with key in ``keys`` get reduced
in time dimension to match target resolution. The reduced items are added to
the passed dicts with ``key`` as key prefix. The tensors must be of shape
(batc... | src/utils/trainer_jit.py | bin_reduce_ | bask0/h2m | 1 | python | def bin_reduce_(self, x: Dict[(str, torch.Tensor)], sample_set: str, fun: Callable=torch.mean) -> None:
"Inplace reduction of tensors time dimension (dim 1).\n\n Parameters\n ----------\n x\n A dict of tensors of which all items with key in ``keys`` get reduced\n in time d... | def bin_reduce_(self, x: Dict[(str, torch.Tensor)], sample_set: str, fun: Callable=torch.mean) -> None:
"Inplace reduction of tensors time dimension (dim 1).\n\n Parameters\n ----------\n x\n A dict of tensors of which all items with key in ``keys`` get reduced\n in time d... |
d9e1820b0cc8920750f2faf6aa996e3b2949684f6480611c5e2ad9594c80ed90 | def add_lr_metrics(self, metrics: Dict[(str, Any)]) -> None:
'Add learning rate log metrics.\n\n Parameters\n ----------\n metrics\n Metrics to logg\n lr\n The current learning rate.\n '
lr = self.scheduler.get_last_lr()
if (lr is not None):
i... | Add learning rate log metrics.
Parameters
----------
metrics
Metrics to logg
lr
The current learning rate. | src/utils/trainer_jit.py | add_lr_metrics | bask0/h2m | 1 | python | def add_lr_metrics(self, metrics: Dict[(str, Any)]) -> None:
'Add learning rate log metrics.\n\n Parameters\n ----------\n metrics\n Metrics to logg\n lr\n The current learning rate.\n '
lr = self.scheduler.get_last_lr()
if (lr is not None):
i... | def add_lr_metrics(self, metrics: Dict[(str, Any)]) -> None:
'Add learning rate log metrics.\n\n Parameters\n ----------\n metrics\n Metrics to logg\n lr\n The current learning rate.\n '
lr = self.scheduler.get_last_lr()
if (lr is not None):
i... |
5973aa4e9ac97ce4df579a652e1cc40d7d19d1c696af9057c87ddb9d47096812 | def cluster_acc(y_true, y_pred):
'\n Calculate clustering accuracy. Require scikit-learn installed\n\n # Arguments\n y: true labels, numpy.array with shape `(n_samples,)`\n y_pred: predicted labels, numpy.array with shape `(n_samples,)`\n\n # Return\n accuracy, in [0,1]\n '
y_tr... | Calculate clustering accuracy. Require scikit-learn installed
# Arguments
y: true labels, numpy.array with shape `(n_samples,)`
y_pred: predicted labels, numpy.array with shape `(n_samples,)`
# Return
accuracy, in [0,1] | utils/util.py | cluster_acc | zhunzhong07/NCL | 45 | python | def cluster_acc(y_true, y_pred):
'\n Calculate clustering accuracy. Require scikit-learn installed\n\n # Arguments\n y: true labels, numpy.array with shape `(n_samples,)`\n y_pred: predicted labels, numpy.array with shape `(n_samples,)`\n\n # Return\n accuracy, in [0,1]\n '
y_tr... | def cluster_acc(y_true, y_pred):
'\n Calculate clustering accuracy. Require scikit-learn installed\n\n # Arguments\n y: true labels, numpy.array with shape `(n_samples,)`\n y_pred: predicted labels, numpy.array with shape `(n_samples,)`\n\n # Return\n accuracy, in [0,1]\n '
y_tr... |
9ac58a8c4ae439d17a2757c8892bef929aedaf58ff23f1ab2a5e08670d55f6f2 | def accuracy(output, target, topk=(1,)):
'Computes the accuracy over the k top predictions for the specified values of k'
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
(_, pred) = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(targ... | Computes the accuracy over the k top predictions for the specified values of k | utils/util.py | accuracy | zhunzhong07/NCL | 45 | python | def accuracy(output, target, topk=(1,)):
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
(_, pred) = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target.view(1, (- 1)).expand_as(pred))
res = []
for k in topk:
... | def accuracy(output, target, topk=(1,)):
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
(_, pred) = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target.view(1, (- 1)).expand_as(pred))
res = []
for k in topk:
... |
a77904ade2c9cc1ac56f9395f7ac1696fadae568568af1599d8c710d847326eb | def check_root():
'\n Check if program is lauched with root privileges\n :return:\n '
logging.info('Checking permissions...')
if (not (os.geteuid() == 0)):
logging.warning('IoT-SecurityChecker must be run as root or with sudo privileges... Exiting')
exit(1)
logging.info(((G + 'P... | Check if program is lauched with root privileges
:return: | Utils.py | check_root | c0mix/IoT-SecurityChecker | 13 | python | def check_root():
'\n Check if program is lauched with root privileges\n :return:\n '
logging.info('Checking permissions...')
if (not (os.geteuid() == 0)):
logging.warning('IoT-SecurityChecker must be run as root or with sudo privileges... Exiting')
exit(1)
logging.info(((G + 'P... | def check_root():
'\n Check if program is lauched with root privileges\n :return:\n '
logging.info('Checking permissions...')
if (not (os.geteuid() == 0)):
logging.warning('IoT-SecurityChecker must be run as root or with sudo privileges... Exiting')
exit(1)
logging.info(((G + 'P... |
ba61f062cd0fd2dcb947639f0f34f47216779f0d064a61ad0fefe1e349461731 | def check_test_args(arg, key):
'\n Check if a bruteforce can be launched or not\n :param args: list\n :param key: string\n :return: boolean\n '
if (arg == None):
return False
for i in arg[0].split(','):
if ((i.upper() == key.upper()) or (i.upper() == 'ALL')):
retur... | Check if a bruteforce can be launched or not
:param args: list
:param key: string
:return: boolean | Utils.py | check_test_args | c0mix/IoT-SecurityChecker | 13 | python | def check_test_args(arg, key):
'\n Check if a bruteforce can be launched or not\n :param args: list\n :param key: string\n :return: boolean\n '
if (arg == None):
return False
for i in arg[0].split(','):
if ((i.upper() == key.upper()) or (i.upper() == 'ALL')):
retur... | def check_test_args(arg, key):
'\n Check if a bruteforce can be launched or not\n :param args: list\n :param key: string\n :return: boolean\n '
if (arg == None):
return False
for i in arg[0].split(','):
if ((i.upper() == key.upper()) or (i.upper() == 'ALL')):
retur... |
b816f958bf248d42d8babe25392f53e8391bf8a938156994c7f8b5ad4acd698f | def check_args(args):
'\n check if important arguments are set\n :param args:\n :return:\n '
brute_choices = ['SSH', 'ALL', 'TELNET', 'FTP', 'HTTP', 'NONE']
if (args.bruteforce is not None):
for a in args.bruteforce[0].split(','):
if (a.upper() not in brute_choices):
... | check if important arguments are set
:param args:
:return: | Utils.py | check_args | c0mix/IoT-SecurityChecker | 13 | python | def check_args(args):
'\n check if important arguments are set\n :param args:\n :return:\n '
brute_choices = ['SSH', 'ALL', 'TELNET', 'FTP', 'HTTP', 'NONE']
if (args.bruteforce is not None):
for a in args.bruteforce[0].split(','):
if (a.upper() not in brute_choices):
... | def check_args(args):
'\n check if important arguments are set\n :param args:\n :return:\n '
brute_choices = ['SSH', 'ALL', 'TELNET', 'FTP', 'HTTP', 'NONE']
if (args.bruteforce is not None):
for a in args.bruteforce[0].split(','):
if (a.upper() not in brute_choices):
... |
83e848da6692380862d7d47de2aebce1ee61ffc5ba8fcc634cbb54fc931204d3 | def arg_parsing():
'\n Handle the arguments\n :return: list\n '
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('target', help='Target list compatible with masscan range or a file with targets')
parser.add_argument('-p', '--prefix', d... | Handle the arguments
:return: list | Utils.py | arg_parsing | c0mix/IoT-SecurityChecker | 13 | python | def arg_parsing():
'\n Handle the arguments\n :return: list\n '
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('target', help='Target list compatible with masscan range or a file with targets')
parser.add_argument('-p', '--prefix', d... | def arg_parsing():
'\n Handle the arguments\n :return: list\n '
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('target', help='Target list compatible with masscan range or a file with targets')
parser.add_argument('-p', '--prefix', d... |
01c49edb9ce83c666492bff3bac79ec00672ad8617f21bfc51e730b9f71de34f | def print_banner():
'\n just print banner title\n :return:\n '
os.system('cat resources/logo')
print('\n') | just print banner title
:return: | Utils.py | print_banner | c0mix/IoT-SecurityChecker | 13 | python | def print_banner():
'\n just print banner title\n :return:\n '
os.system('cat resources/logo')
print('\n') | def print_banner():
'\n just print banner title\n :return:\n '
os.system('cat resources/logo')
print('\n')<|docstring|>just print banner title
:return:<|endoftext|> |
d072032692a23bc2be264b9cea13033db120ea3b182754dcff627caafc964de1 | def reject_next_to(env, pos):
"\n Function to filter out object positions that are right next to\n the agent's starting point\n "
(sx, sy) = env.agent_pos
(x, y) = pos
d = (abs((sx - x)) + abs((sy - y)))
return (d < 2) | Function to filter out object positions that are right next to
the agent's starting point | gym_minigrid/roomgrid.py | reject_next_to | natvern/gym-minigrid | 1,475 | python | def reject_next_to(env, pos):
"\n Function to filter out object positions that are right next to\n the agent's starting point\n "
(sx, sy) = env.agent_pos
(x, y) = pos
d = (abs((sx - x)) + abs((sy - y)))
return (d < 2) | def reject_next_to(env, pos):
"\n Function to filter out object positions that are right next to\n the agent's starting point\n "
(sx, sy) = env.agent_pos
(x, y) = pos
d = (abs((sx - x)) + abs((sy - y)))
return (d < 2)<|docstring|>Function to filter out object positions that are right next ... |
5264ad79b395edd30c6bc6a437daf33538c76bf6eb6817a96a6e321adaa04dac | def pos_inside(self, x, y):
'\n Check if a position is within the bounds of this room\n '
(topX, topY) = self.top
(sizeX, sizeY) = self.size
if ((x < topX) or (y < topY)):
return False
if ((x >= (topX + sizeX)) or (y >= (topY + sizeY))):
return False
return True | Check if a position is within the bounds of this room | gym_minigrid/roomgrid.py | pos_inside | natvern/gym-minigrid | 1,475 | python | def pos_inside(self, x, y):
'\n \n '
(topX, topY) = self.top
(sizeX, sizeY) = self.size
if ((x < topX) or (y < topY)):
return False
if ((x >= (topX + sizeX)) or (y >= (topY + sizeY))):
return False
return True | def pos_inside(self, x, y):
'\n \n '
(topX, topY) = self.top
(sizeX, sizeY) = self.size
if ((x < topX) or (y < topY)):
return False
if ((x >= (topX + sizeX)) or (y >= (topY + sizeY))):
return False
return True<|docstring|>Check if a position is within the bounds of ... |
15afda9ab355cd33397530ceae341f330229df3514a0166a174af116b64db68c | def room_from_pos(self, x, y):
'Get the room a given position maps to'
assert (x >= 0)
assert (y >= 0)
i = (x // (self.room_size - 1))
j = (y // (self.room_size - 1))
assert (i < self.num_cols)
assert (j < self.num_rows)
return self.room_grid[j][i] | Get the room a given position maps to | gym_minigrid/roomgrid.py | room_from_pos | natvern/gym-minigrid | 1,475 | python | def room_from_pos(self, x, y):
assert (x >= 0)
assert (y >= 0)
i = (x // (self.room_size - 1))
j = (y // (self.room_size - 1))
assert (i < self.num_cols)
assert (j < self.num_rows)
return self.room_grid[j][i] | def room_from_pos(self, x, y):
assert (x >= 0)
assert (y >= 0)
i = (x // (self.room_size - 1))
j = (y // (self.room_size - 1))
assert (i < self.num_cols)
assert (j < self.num_rows)
return self.room_grid[j][i]<|docstring|>Get the room a given position maps to<|endoftext|> |
c330302e2e2917a5503ac9d50eea26ccb01c87134f827fcea29e4d0a2498d6f4 | def place_in_room(self, i, j, obj):
'\n Add an existing object to room (i, j)\n '
room = self.get_room(i, j)
pos = self.place_obj(obj, room.top, room.size, reject_fn=reject_next_to, max_tries=1000)
room.objs.append(obj)
return (obj, pos) | Add an existing object to room (i, j) | gym_minigrid/roomgrid.py | place_in_room | natvern/gym-minigrid | 1,475 | python | def place_in_room(self, i, j, obj):
'\n \n '
room = self.get_room(i, j)
pos = self.place_obj(obj, room.top, room.size, reject_fn=reject_next_to, max_tries=1000)
room.objs.append(obj)
return (obj, pos) | def place_in_room(self, i, j, obj):
'\n \n '
room = self.get_room(i, j)
pos = self.place_obj(obj, room.top, room.size, reject_fn=reject_next_to, max_tries=1000)
room.objs.append(obj)
return (obj, pos)<|docstring|>Add an existing object to room (i, j)<|endoftext|> |
3599c4381c3155cc285c3aa8cb12550db93121ad038301d8ff21654d3910d471 | def add_object(self, i, j, kind=None, color=None):
'\n Add a new object to room (i, j)\n '
if (kind == None):
kind = self._rand_elem(['key', 'ball', 'box'])
if (color == None):
color = self._rand_color()
assert (kind in ['key', 'ball', 'box'])
if (kind == 'key'):
... | Add a new object to room (i, j) | gym_minigrid/roomgrid.py | add_object | natvern/gym-minigrid | 1,475 | python | def add_object(self, i, j, kind=None, color=None):
'\n \n '
if (kind == None):
kind = self._rand_elem(['key', 'ball', 'box'])
if (color == None):
color = self._rand_color()
assert (kind in ['key', 'ball', 'box'])
if (kind == 'key'):
obj = Key(color)
elif (ki... | def add_object(self, i, j, kind=None, color=None):
'\n \n '
if (kind == None):
kind = self._rand_elem(['key', 'ball', 'box'])
if (color == None):
color = self._rand_color()
assert (kind in ['key', 'ball', 'box'])
if (kind == 'key'):
obj = Key(color)
elif (ki... |
46e9f26512832fb93d8e2f0d75c2e85a7697e2fc8338644ae201a46c734ae0f9 | def add_door(self, i, j, door_idx=None, color=None, locked=None):
'\n Add a door to a room, connecting it to a neighbor\n '
room = self.get_room(i, j)
if (door_idx == None):
while True:
door_idx = self._rand_int(0, 4)
if (room.neighbors[door_idx] and (room.doors... | Add a door to a room, connecting it to a neighbor | gym_minigrid/roomgrid.py | add_door | natvern/gym-minigrid | 1,475 | python | def add_door(self, i, j, door_idx=None, color=None, locked=None):
'\n \n '
room = self.get_room(i, j)
if (door_idx == None):
while True:
door_idx = self._rand_int(0, 4)
if (room.neighbors[door_idx] and (room.doors[door_idx] is None)):
break
i... | def add_door(self, i, j, door_idx=None, color=None, locked=None):
'\n \n '
room = self.get_room(i, j)
if (door_idx == None):
while True:
door_idx = self._rand_int(0, 4)
if (room.neighbors[door_idx] and (room.doors[door_idx] is None)):
break
i... |
a817f998dac256a6dd1e79d46fc492cf4c8f77d4eb63f7df6e192f0368c97009 | def remove_wall(self, i, j, wall_idx):
'\n Remove a wall between two rooms\n '
room = self.get_room(i, j)
assert ((wall_idx >= 0) and (wall_idx < 4))
assert (room.doors[wall_idx] is None), 'door exists on this wall'
assert room.neighbors[wall_idx], 'invalid wall'
neighbor = room.ne... | Remove a wall between two rooms | gym_minigrid/roomgrid.py | remove_wall | natvern/gym-minigrid | 1,475 | python | def remove_wall(self, i, j, wall_idx):
'\n \n '
room = self.get_room(i, j)
assert ((wall_idx >= 0) and (wall_idx < 4))
assert (room.doors[wall_idx] is None), 'door exists on this wall'
assert room.neighbors[wall_idx], 'invalid wall'
neighbor = room.neighbors[wall_idx]
(tx, ty) ... | def remove_wall(self, i, j, wall_idx):
'\n \n '
room = self.get_room(i, j)
assert ((wall_idx >= 0) and (wall_idx < 4))
assert (room.doors[wall_idx] is None), 'door exists on this wall'
assert room.neighbors[wall_idx], 'invalid wall'
neighbor = room.neighbors[wall_idx]
(tx, ty) ... |
106e75c77cc63326dcde5c828b7cec01ad854dff1beacfb44533cc4ec1a7d94f | def place_agent(self, i=None, j=None, rand_dir=True):
'\n Place the agent in a room\n '
if (i == None):
i = self._rand_int(0, self.num_cols)
if (j == None):
j = self._rand_int(0, self.num_rows)
room = self.room_grid[j][i]
while True:
super().place_agent(room.top... | Place the agent in a room | gym_minigrid/roomgrid.py | place_agent | natvern/gym-minigrid | 1,475 | python | def place_agent(self, i=None, j=None, rand_dir=True):
'\n \n '
if (i == None):
i = self._rand_int(0, self.num_cols)
if (j == None):
j = self._rand_int(0, self.num_rows)
room = self.room_grid[j][i]
while True:
super().place_agent(room.top, room.size, rand_dir, ma... | def place_agent(self, i=None, j=None, rand_dir=True):
'\n \n '
if (i == None):
i = self._rand_int(0, self.num_cols)
if (j == None):
j = self._rand_int(0, self.num_rows)
room = self.room_grid[j][i]
while True:
super().place_agent(room.top, room.size, rand_dir, ma... |
a0aee7634b2c79bbf88649ed3d8d7bf891f330bbd64137ddb1db26177443a287 | def connect_all(self, door_colors=COLOR_NAMES, max_itrs=5000):
'\n Make sure that all rooms are reachable by the agent from its\n starting position\n '
start_room = self.room_from_pos(*self.agent_pos)
added_doors = []
def find_reach():
reach = set()
stack = [start_r... | Make sure that all rooms are reachable by the agent from its
starting position | gym_minigrid/roomgrid.py | connect_all | natvern/gym-minigrid | 1,475 | python | def connect_all(self, door_colors=COLOR_NAMES, max_itrs=5000):
'\n Make sure that all rooms are reachable by the agent from its\n starting position\n '
start_room = self.room_from_pos(*self.agent_pos)
added_doors = []
def find_reach():
reach = set()
stack = [start_r... | def connect_all(self, door_colors=COLOR_NAMES, max_itrs=5000):
'\n Make sure that all rooms are reachable by the agent from its\n starting position\n '
start_room = self.room_from_pos(*self.agent_pos)
added_doors = []
def find_reach():
reach = set()
stack = [start_r... |
ae3fbc8da80f940cd1be2780727b0d2741346668460b2cd405dd68665ab77d3d | def add_distractors(self, i=None, j=None, num_distractors=10, all_unique=True):
'\n Add random objects that can potentially distract/confuse the agent.\n '
objs = []
for row in self.room_grid:
for room in row:
for obj in room.objs:
objs.append((obj.type, obj... | Add random objects that can potentially distract/confuse the agent. | gym_minigrid/roomgrid.py | add_distractors | natvern/gym-minigrid | 1,475 | python | def add_distractors(self, i=None, j=None, num_distractors=10, all_unique=True):
'\n \n '
objs = []
for row in self.room_grid:
for room in row:
for obj in room.objs:
objs.append((obj.type, obj.color))
dists = []
while (len(dists) < num_distractors):
... | def add_distractors(self, i=None, j=None, num_distractors=10, all_unique=True):
'\n \n '
objs = []
for row in self.room_grid:
for room in row:
for obj in room.objs:
objs.append((obj.type, obj.color))
dists = []
while (len(dists) < num_distractors):
... |
4945bd96a3df356a3fbfd38f5b27c56a1e4706bf1680cde31b9ad997bef16820 | def users_username_token_post(self, api_token, username, **kwargs):
"Generates a user API token # noqa: E501\n\n Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_USERS_UPDATE** gr... | Generates a user API token # noqa: E501
Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_USERS_UPDATE** granted, or - To have the permission **MANAGE_USERS_BU** granted. Having this permi... | iriusrisk-python-client-lib/iriusrisk_python_client_lib/api/token_api.py | users_username_token_post | iriusrisk/iriusrisk-python-client-lib | 0 | python | def users_username_token_post(self, api_token, username, **kwargs):
"Generates a user API token # noqa: E501\n\n Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_USERS_UPDATE** gr... | def users_username_token_post(self, api_token, username, **kwargs):
"Generates a user API token # noqa: E501\n\n Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_USERS_UPDATE** gr... |
eb018917793187caf66cd35d125e92ab173f7223211a7c4751ea4857c5783150 | def users_username_token_post_with_http_info(self, api_token, username, **kwargs):
"Generates a user API token # noqa: E501\n\n Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_US... | Generates a user API token # noqa: E501
Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_USERS_UPDATE** granted, or - To have the permission **MANAGE_USERS_BU** granted. Having this permi... | iriusrisk-python-client-lib/iriusrisk_python_client_lib/api/token_api.py | users_username_token_post_with_http_info | iriusrisk/iriusrisk-python-client-lib | 0 | python | def users_username_token_post_with_http_info(self, api_token, username, **kwargs):
"Generates a user API token # noqa: E501\n\n Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_US... | def users_username_token_post_with_http_info(self, api_token, username, **kwargs):
"Generates a user API token # noqa: E501\n\n Generates a new user API token. If the user already has a generated API token, generates a new one. Conditions to be able to perform the action: - To have the permission **ALL_US... |
d29a314639752e00adaba2d5c4ebad09a8ac8ac8e00cfe7a8743b0b799cb3d23 | def setupConfigFileFramework(factoryReset=False):
"\n 4 user manipulable config files can exist in the ${packages}/ShellRunner directory\n `- these are: ShellRunner.sublime-settings, Side Bar.sublime-menu\n - Context.sublime-menu, and Default (${platform}).sublime-keymap\n Each of these files has a cor... | 4 user manipulable config files can exist in the ${packages}/ShellRunner directory
`- these are: ShellRunner.sublime-settings, Side Bar.sublime-menu
- Context.sublime-menu, and Default (${platform}).sublime-keymap
Each of these files has a corresponding 'template' (blankish canvas) file,
`- and a corresponding 'exampl... | ShellRunner.py | setupConfigFileFramework | phughes3866/ShellRunner | 0 | python | def setupConfigFileFramework(factoryReset=False):
"\n 4 user manipulable config files can exist in the ${packages}/ShellRunner directory\n `- these are: ShellRunner.sublime-settings, Side Bar.sublime-menu\n - Context.sublime-menu, and Default (${platform}).sublime-keymap\n Each of these files has a cor... | def setupConfigFileFramework(factoryReset=False):
"\n 4 user manipulable config files can exist in the ${packages}/ShellRunner directory\n `- these are: ShellRunner.sublime-settings, Side Bar.sublime-menu\n - Context.sublime-menu, and Default (${platform}).sublime-keymap\n Each of these files has a cor... |
ec9fc47111dc70463631bdb85b691840da27475a89c02a40bab1fbbbad3b7583 | def settingsUpdateByProject(projectFileShellRunnerSectionDict, projectFileName):
"\n Overwrites global: activeSettings dict with entries from ShellRunner section\n `- of the active .sublime-project file.\n Note: As settings from .sublime-projects have higher priority than the\n 'ShellRunner.sublim... | Overwrites global: activeSettings dict with entries from ShellRunner section
`- of the active .sublime-project file.
Note: As settings from .sublime-projects have higher priority than the
'ShellRunner.sublime-settings' files, they can be directly written
to 'activeSettings' | ShellRunner.py | settingsUpdateByProject | phughes3866/ShellRunner | 0 | python | def settingsUpdateByProject(projectFileShellRunnerSectionDict, projectFileName):
"\n Overwrites global: activeSettings dict with entries from ShellRunner section\n `- of the active .sublime-project file.\n Note: As settings from .sublime-projects have higher priority than the\n 'ShellRunner.sublim... | def settingsUpdateByProject(projectFileShellRunnerSectionDict, projectFileName):
"\n Overwrites global: activeSettings dict with entries from ShellRunner section\n `- of the active .sublime-project file.\n Note: As settings from .sublime-projects have higher priority than the\n 'ShellRunner.sublim... |
7896894896e530a30ff1c10b39d2ded76fb318f7eada6d51c9f47ac1d3a85a80 | def plugin_loaded(factoryReset=False):
'\n 1. Sets up global: configFile dictionary + ensures necessary config files are in place\n 2. Loads initial set of ShellRunner settings into global: activeSettings dictionary\n '
global activeSettings
global srSettings
def readInUserSettings():
... | 1. Sets up global: configFile dictionary + ensures necessary config files are in place
2. Loads initial set of ShellRunner settings into global: activeSettings dictionary | ShellRunner.py | plugin_loaded | phughes3866/ShellRunner | 0 | python | def plugin_loaded(factoryReset=False):
'\n 1. Sets up global: configFile dictionary + ensures necessary config files are in place\n 2. Loads initial set of ShellRunner settings into global: activeSettings dictionary\n '
global activeSettings
global srSettings
def readInUserSettings():
... | def plugin_loaded(factoryReset=False):
'\n 1. Sets up global: configFile dictionary + ensures necessary config files are in place\n 2. Loads initial set of ShellRunner settings into global: activeSettings dictionary\n '
global activeSettings
global srSettings
def readInUserSettings():
... |
a6a630adcff075cf26bec716bab6c33f1bd9454e051496191d6695f496f58f2d | def buildPathFileDirSidebarItemStrings(argsDict):
'\n Build space separated string lists of \'files\', \'dirs\', \'paths\' from same-named lists available in args passed\n Sublime Text fills these optional sidebar menu args appropriately when they are given in a sidebar menu command:\n `- e.g. a list arg "... | Build space separated string lists of 'files', 'dirs', 'paths' from same-named lists available in args passed
Sublime Text fills these optional sidebar menu args appropriately when they are given in a sidebar menu command:
`- e.g. a list arg "dirs": [] will be filled in with a list of dirs currently selected in the sid... | ShellRunner.py | buildPathFileDirSidebarItemStrings | phughes3866/ShellRunner | 0 | python | def buildPathFileDirSidebarItemStrings(argsDict):
'\n Build space separated string lists of \'files\', \'dirs\', \'paths\' from same-named lists available in args passed\n Sublime Text fills these optional sidebar menu args appropriately when they are given in a sidebar menu command:\n `- e.g. a list arg "... | def buildPathFileDirSidebarItemStrings(argsDict):
'\n Build space separated string lists of \'files\', \'dirs\', \'paths\' from same-named lists available in args passed\n Sublime Text fills these optional sidebar menu args appropriately when they are given in a sidebar menu command:\n `- e.g. a list arg "... |
ef712a2b68ba96ef63a4d0b4bee9aeafa5f81501c798b6589b02f7ca1b62564a | def is_anagram(word1, word2):
'Receives two words and returns True/False (boolean) if word2 is\n an anagram of word1, ignore case and spacing.\n About anagrams: https://en.wikipedia.org/wiki/Anagram'
word1 = word1.strip().replace(' ', '').lower()
word2 = word2.strip().replace(' ', '').lower()
... | Receives two words and returns True/False (boolean) if word2 is
an anagram of word1, ignore case and spacing.
About anagrams: https://en.wikipedia.org/wiki/Anagram | bites/bite122.py | is_anagram | ChidinmaKO/Chobe-bitesofpy | 0 | python | def is_anagram(word1, word2):
'Receives two words and returns True/False (boolean) if word2 is\n an anagram of word1, ignore case and spacing.\n About anagrams: https://en.wikipedia.org/wiki/Anagram'
word1 = word1.strip().replace(' ', ).lower()
word2 = word2.strip().replace(' ', ).lower()
if... | def is_anagram(word1, word2):
'Receives two words and returns True/False (boolean) if word2 is\n an anagram of word1, ignore case and spacing.\n About anagrams: https://en.wikipedia.org/wiki/Anagram'
word1 = word1.strip().replace(' ', ).lower()
word2 = word2.strip().replace(' ', ).lower()
if... |
7562dffb534d7440ebc1e29d1cf23d06c9d32a71ba7a07fbd4943f067ebb1ba1 | @njit
def reservoir_step(x, dowy, Q, S, K, R_avg, S_avg):
'\n Advances reservoir storage from one timestep to the next\n\n Parameters:\n x (np.array): Reservoir rule parameters (5)\n dowy (int): Day of water year\n Q (float): Inflow, cfs\n S (float): Storage, acre-feet\n K (float): Stor... | Advances reservoir storage from one timestep to the next
Parameters:
x (np.array): Reservoir rule parameters (5)
dowy (int): Day of water year
Q (float): Inflow, cfs
S (float): Storage, acre-feet
K (float): Storage capacity, acre-feet
R_avg (float): Median release for this day of the year, cf... | model.py | reservoir_step | jdherman/ssjrb | 5 | python | @njit
def reservoir_step(x, dowy, Q, S, K, R_avg, S_avg):
'\n Advances reservoir storage from one timestep to the next\n\n Parameters:\n x (np.array): Reservoir rule parameters (5)\n dowy (int): Day of water year\n Q (float): Inflow, cfs\n S (float): Storage, acre-feet\n K (float): Stor... | @njit
def reservoir_step(x, dowy, Q, S, K, R_avg, S_avg):
'\n Advances reservoir storage from one timestep to the next\n\n Parameters:\n x (np.array): Reservoir rule parameters (5)\n dowy (int): Day of water year\n Q (float): Inflow, cfs\n S (float): Storage, acre-feet\n K (float): Stor... |
2c9a635e84ff43561feaf0c7dab016c835397dd08e12c1e1d4ac41b9985bd6f7 | @njit
def reservoir_fit(x, dowy, Q, K, Q_avg, R_avg, R_obs, S_avg, S_obs):
'\n Evaluate reservoir model against historical observations for a set of parameters \n\n Parameters:\n x (np.array): Reservoir rule parameters (5)\n dowy (np.array(int)): Day of water year over the simulation\n Q (np.arra... | Evaluate reservoir model against historical observations for a set of parameters
Parameters:
x (np.array): Reservoir rule parameters (5)
dowy (np.array(int)): Day of water year over the simulation
Q (np.array(float)): Inflow, cfs
S (np.array(float)): Storage, acre-feet
K (float): Storage capacit... | model.py | reservoir_fit | jdherman/ssjrb | 5 | python | @njit
def reservoir_fit(x, dowy, Q, K, Q_avg, R_avg, R_obs, S_avg, S_obs):
'\n Evaluate reservoir model against historical observations for a set of parameters \n\n Parameters:\n x (np.array): Reservoir rule parameters (5)\n dowy (np.array(int)): Day of water year over the simulation\n Q (np.arra... | @njit
def reservoir_fit(x, dowy, Q, K, Q_avg, R_avg, R_obs, S_avg, S_obs):
'\n Evaluate reservoir model against historical observations for a set of parameters \n\n Parameters:\n x (np.array): Reservoir rule parameters (5)\n dowy (np.array(int)): Day of water year over the simulation\n Q (np.arra... |
a8f8a8afb53e7b89288040f4baf61e8e2335ecf3ba7aa1aa7fb0066b6300cb10 | @njit
def gains_step(x, dowy, Q_total, Q_total_avg, S_total_pct, Gains_avg):
'\n Compute gains into the Delta for one timestep\n\n Parameters:\n x (np.array): Gains parameters (2)\n dowy (int): Day of water year\n Q_total (float): Total inflow to all reservoirs, cfs\n Q_total_avg (float): Av... | Compute gains into the Delta for one timestep
Parameters:
x (np.array): Gains parameters (2)
dowy (int): Day of water year
Q_total (float): Total inflow to all reservoirs, cfs
Q_total_avg (float): Average total inflow for this day of the year, cfs
S_total_pct (float): System-wide reservoir storag... | model.py | gains_step | jdherman/ssjrb | 5 | python | @njit
def gains_step(x, dowy, Q_total, Q_total_avg, S_total_pct, Gains_avg):
'\n Compute gains into the Delta for one timestep\n\n Parameters:\n x (np.array): Gains parameters (2)\n dowy (int): Day of water year\n Q_total (float): Total inflow to all reservoirs, cfs\n Q_total_avg (float): Av... | @njit
def gains_step(x, dowy, Q_total, Q_total_avg, S_total_pct, Gains_avg):
'\n Compute gains into the Delta for one timestep\n\n Parameters:\n x (np.array): Gains parameters (2)\n dowy (int): Day of water year\n Q_total (float): Total inflow to all reservoirs, cfs\n Q_total_avg (float): Av... |
e45d264a492efbee3b60a6c82969063c2819748c8e386c05463b43515effe274 | @njit
def gains_fit(x, dowy, Q_total, Q_total_avg, S_total_pct, Gains_avg, Gains_obs):
'\n Evaluate Delta gains model against historical observations for a set of parameters\n\n Parameters:\n x (np.array): Gains parameters (2)\n dowy (np.array(int)): Day of water year\n Q_total (np.array(float)):... | Evaluate Delta gains model against historical observations for a set of parameters
Parameters:
x (np.array): Gains parameters (2)
dowy (np.array(int)): Day of water year
Q_total (np.array(float)): Total inflow to all reservoirs, cfs
Q_total_avg (np.array(float)): Average total inflow
... | model.py | gains_fit | jdherman/ssjrb | 5 | python | @njit
def gains_fit(x, dowy, Q_total, Q_total_avg, S_total_pct, Gains_avg, Gains_obs):
'\n Evaluate Delta gains model against historical observations for a set of parameters\n\n Parameters:\n x (np.array): Gains parameters (2)\n dowy (np.array(int)): Day of water year\n Q_total (np.array(float)):... | @njit
def gains_fit(x, dowy, Q_total, Q_total_avg, S_total_pct, Gains_avg, Gains_obs):
'\n Evaluate Delta gains model against historical observations for a set of parameters\n\n Parameters:\n x (np.array): Gains parameters (2)\n dowy (np.array(int)): Day of water year\n Q_total (np.array(float)):... |
948ef23ca9ca572697fe5952246ef4bd7bc84cfa96a8b3de18335ec1da4b39c6 | @njit
def delta_step(x, dowy, Q_in, Pump_pct_avg, S_total_pct):
'\n Compute total Delta pumping (Banks + Tracy) for one timestep\n\n Parameters:\n x (np.array): Delta pumping parameter (1)\n dowy (int): Day of water year\n Q_in (float): Total inflow to the Delta, cfs \n (sum of... | Compute total Delta pumping (Banks + Tracy) for one timestep
Parameters:
x (np.array): Delta pumping parameter (1)
dowy (int): Day of water year
Q_in (float): Total inflow to the Delta, cfs
(sum of all reservoir outflows plus gains)
Pump_pct_avg (float): (Average pumping / Average ... | model.py | delta_step | jdherman/ssjrb | 5 | python | @njit
def delta_step(x, dowy, Q_in, Pump_pct_avg, S_total_pct):
'\n Compute total Delta pumping (Banks + Tracy) for one timestep\n\n Parameters:\n x (np.array): Delta pumping parameter (1)\n dowy (int): Day of water year\n Q_in (float): Total inflow to the Delta, cfs \n (sum of... | @njit
def delta_step(x, dowy, Q_in, Pump_pct_avg, S_total_pct):
'\n Compute total Delta pumping (Banks + Tracy) for one timestep\n\n Parameters:\n x (np.array): Delta pumping parameter (1)\n dowy (int): Day of water year\n Q_in (float): Total inflow to the Delta, cfs \n (sum of... |
a4071f49b89bc2f5cfcb13e4b2062de042c93227735e3b37fb7894e075870dd7 | @njit
def delta_fit(x, dowy, Q_in, Pump_pct_avg, S_total_pct, Pump_obs):
'\n Evaluate Delta pumping model against historical observations for a set of parameters\n\n Parameters:\n x (np.array): Delta pumping parameter (1)\n dowy (np.array(int)): Day of water year\n Q_in (np.array(float)): Total i... | Evaluate Delta pumping model against historical observations for a set of parameters
Parameters:
x (np.array): Delta pumping parameter (1)
dowy (np.array(int)): Day of water year
Q_in (np.array(float)): Total inflow to the Delta, cfs
(sum of all reservoir outflows plus gains)... | model.py | delta_fit | jdherman/ssjrb | 5 | python | @njit
def delta_fit(x, dowy, Q_in, Pump_pct_avg, S_total_pct, Pump_obs):
'\n Evaluate Delta pumping model against historical observations for a set of parameters\n\n Parameters:\n x (np.array): Delta pumping parameter (1)\n dowy (np.array(int)): Day of water year\n Q_in (np.array(float)): Total i... | @njit
def delta_fit(x, dowy, Q_in, Pump_pct_avg, S_total_pct, Pump_obs):
'\n Evaluate Delta pumping model against historical observations for a set of parameters\n\n Parameters:\n x (np.array): Delta pumping parameter (1)\n dowy (np.array(int)): Day of water year\n Q_in (np.array(float)): Total i... |
a276f5553f81eb75855b70072211361fcf5828661b5d7142f6a47797d09cd887 | @njit
def simulate(params, K, dowy, Q, Q_avg, R_avg, S_avg, Gains_avg, Pump_pct_avg, DM):
'\n Run full system simulation over a given time period.\n\n Parameters:\n params (tuple(np.array)): Parameter arrays for all reservoirs, gains, and Delta\n K (np.array(float)): Reservoir capacities, acre-feet\n ... | Run full system simulation over a given time period.
Parameters:
params (tuple(np.array)): Parameter arrays for all reservoirs, gains, and Delta
K (np.array(float)): Reservoir capacities, acre-feet
dowy (np.array(int)): Day of water year
Q (np.array(float, float)): Matrix of inflows at all reservoirs... | model.py | simulate | jdherman/ssjrb | 5 | python | @njit
def simulate(params, K, dowy, Q, Q_avg, R_avg, S_avg, Gains_avg, Pump_pct_avg, DM):
'\n Run full system simulation over a given time period.\n\n Parameters:\n params (tuple(np.array)): Parameter arrays for all reservoirs, gains, and Delta\n K (np.array(float)): Reservoir capacities, acre-feet\n ... | @njit
def simulate(params, K, dowy, Q, Q_avg, R_avg, S_avg, Gains_avg, Pump_pct_avg, DM):
'\n Run full system simulation over a given time period.\n\n Parameters:\n params (tuple(np.array)): Parameter arrays for all reservoirs, gains, and Delta\n K (np.array(float)): Reservoir capacities, acre-feet\n ... |
9f6fd5e8ebcbea1acc1705a8626a451c43222564bdf98271c4444f8dcd3a6127 | def __init__(self, db_engine, logger):
'Constructor\n\n :param DatabaseEngine db_engine: Database engine with DB connections\n :param Logger logger: Application logger\n '
self.db = db_engine.geo_db()
self.logger = logger
self.basic_info_sql = os.getenv('BASIC_INFO_SQL', self.DEFAUL... | Constructor
:param DatabaseEngine db_engine: Database engine with DB connections
:param Logger logger: Application logger | plot_info.py | __init__ | HusseinKabbout/sogis-plotinfo-service | 0 | python | def __init__(self, db_engine, logger):
'Constructor\n\n :param DatabaseEngine db_engine: Database engine with DB connections\n :param Logger logger: Application logger\n '
self.db = db_engine.geo_db()
self.logger = logger
self.basic_info_sql = os.getenv('BASIC_INFO_SQL', self.DEFAUL... | def __init__(self, db_engine, logger):
'Constructor\n\n :param DatabaseEngine db_engine: Database engine with DB connections\n :param Logger logger: Application logger\n '
self.db = db_engine.geo_db()
self.logger = logger
self.basic_info_sql = os.getenv('BASIC_INFO_SQL', self.DEFAUL... |
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