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Voronoi Diagram
A Voronoi
diagram is the computational geometry concept that represents partition
of the given space onto regions, with bounds determined by distances to
a
specified family of objects. The application area of this concept
varies from
Archaeology to Zoology. The Boost.Polygon Voronoi extension
provides
implementation of
the Voronoi diagram data structure in the 2D space. The internal
representation
consists of the three arrays, that respectively contain: Voronoi cells
(represent the area around the input sites bounded by the Voronoi
edges), Voronoi vertices
(points where three or more Voronoi edges intersect), Voronoi edges
(one dimensional curves containing points equidistant from the two
closest input sites). Each of the primitives (cell, vertex, edge)
contains pointers to the other linked primitives, so that it's always
possible to efficiently traverse the Voronoi graph. The picture below
shows
the Voronoi vertices in red, Voronoi edges in black, input sites that
correspond to the Voronoi cells in blue. It is considered, that each
input segment consists of the three sites: segment itself and its
endpoints. As the result, two additional Voronoi edges are constructed
per each input segment. This is made to
simplify the representation of the Voronoi diagram and Voronoi edges in
particular.
Important
All
the Voronoi primitive data structures (edge, vertex, cell) contain
mutable color member. Color type is equivalent to the std::size_t type,
except that the upper five bits are reserved for the internal usage.
That means, that the maximum supported value by the color member is 32
times less than the one supported by std::size_t.
Declaration
Header: boost/polygon/voronoi_diagram.hpp
template
<typename T, typename TRAITS = voronoi_diagram_traits<T> >
class
voronoi_diagram;
T
- the coordinate type of the Voronoi vertices.
TRAITS
- the Voronoi diagram traits.
Member Functions
| voronoi_diagram() |
Default constructor. |
| void
clear() |
Removes all primitives from the Voronoi diagram. |
| const
cell_container_type& cells()
const |
Returns the const
reference to the cell container. |
| const
vertex_container_type& vertices()
const |
Returns the const
reference to the vertex container. |
| const
edge_container_type& edges()
const |
Returns the const
reference to the edge container. |
| size_t
num_cells() const |
Returns the number of the Voronoi
cells in the Voronoi diagram. |
| size_t
num_edges() const |
Returns the number of the
Voronoi edges (half-edges) in the Voronoi diagram. |
| size_t
num_vertices()
const |
Returns the number of the
Voronoi vertices in the Voronoi diagram. |
Member Types
| coordinate_type |
Coordinate type. |
| cell_type |
Voronoi cell. |
| vertex_type |
Voronoi vertex. |
| edge_type |
Voronoi edge. |
| cell_container_type |
Container of the Voronoi cells. |
| const_cell_iterator |
Const cell container iterator. |
| vertex_container_type |
Container of the Voronoi vertices. |
| const_vertex_iterator |
Const vertex container iterator. |
| edge_container_type |
Container of the Voronoi edges. |
| const_edge_iterator |
Const edge container iterator. |
Voronoi Geometry Type
The Voronoi
diagram data structure doesn't embed coordinates of the input
geometries.
Instead it links with those via source index and source category
methods
of the Voronoi cell primitive. Source index is incrementally given
(starting from zero) to each input site inserted into the Voronoi
builder.
Considering the fact, that each input segment is splitted onto three
separate sites with the same index, we distinguish between those using
source category. For more examples check the Voronoi basic tutorial.
GeometryCategory
Defines geometric category of the input object.
Header: boost/polygon/voronoi_geometry_type.hpp
enum
GeometryCategory {
GEOMETRY_CATEGORY_POINT = 0x0,
GEOMETRY_CATEGORY_SEGMENT = 0x1
};
SourceCategory
Defines semantic category of the input site.
Header: boost/polygon/voronoi_geometry_type.hpp
enum
SourceCategory {
// Point subtypes.
SOURCE_CATEGORY_SINGLE_POINT = 0x0,
SOURCE_CATEGORY_SEGMENT_START_POINT = 0x1,
SOURCE_CATEGORY_SEGMENT_END_POINT = 0x2,
// Segment subtypes.
SOURCE_CATEGORY_INITIAL_SEGMENT = 0x8,
SOURCE_CATEGORY_REVERSE_SEGMENT = 0x9,
SOURCE_CATEGORY_GEOMETRY_SHIFT = 0x3,
SOURCE_CATEGORY_BITMASK = 0x1F
};
Member Functions
bool belongs(
SourceCategory source_category,
GeometryCategory geometry_category) |
Returns true if the
given source
category belongs to the given geometry category.
Returns false otherwise. |
Voronoi Edge
A Voronoi edge is a one-dimenstion curve, that contains points
equidistant from the two closest input geometries. The Voronoi edge
data structure is implemented as the enhanced classical half-edge
data structure. On the image below, the Voronoi edges are drawn as
directed linear (e.g. AE) or curved (e.g. DE) dashed lines of either
green (e.g. AE) or black (e.g DE) color. The green edges are considered
to be secondary, as they are generated by an input segment and its
endpoint (e.g. edge EA, made by segment MN and its endpoint M). All the
other edges are considered to be primary (e.g. curved edge CD, made by
segment KL and point N). Apart from that, each edge can be finite (e.g.
ED) or infinite (e.g. edge starting at point B and going in the east
direction).
Each Voronoi edge (consider directed edge BA) provides efficient access
to the following primitives:
- Cell the edge belongs to (Voronoi cell P, with source
segment MN)
- Start point of the edge (Voronoi vertex B, that is
equidistant from the following input sites: O, L, MN)
- End point of the edge (Voronoi vertex A, that is
equidistant from the following input sites: O, M, MN)
- Twin edge (Voronoi edge AB)
- CCW next edge inside the Voronoi cell, that the edge
belongs to (green Voronoi edge AE)
- CCW previous edge inside the Voronoi cell, that the edge
belongs to (Voronoi edge CB)
- CCW rotated next edge around the start point of the edge
(Voronoi edge BC)
- CCW rotated previous edge around the start point of the
edge (infinite Voronoi edge starting at the Voronoi vertex B and going
in the east direction)
Declaration
Header: boost/polygon/voronoi_diagram.hpp
template
<typename T>
class
voronoi_edge;
T - coordinate type.
Member Functions
| voronoi_edge(bool is_linear, bool
is_primary) |
Voronoi edge constructor. |
| voronoi_cell_type*
cell() |
Returns the pointer to the
Voronoi cell
that the edge belongs to. |
| const
voronoi_cell_type* cell()
const |
Returns the const pointer
to the Voronoi cell that the edge belongs to. |
| void
cell(voronoi_cell_type*
c) |
Sets the Voronoi cell
pointer to the cell the current edge belongs to. |
| voronoi_vertex_type*
vertex0() |
Returns the pointer to the
start point of the edge.
If the edge is infinite in that direction returns NULL. |
| const
voronoi_vertex_type* vertex0()
const |
Returns the const pointer
to the start point vertex of the edge.
If the edge is infinite in that direction returns NULL. |
| void
vertex0(voronoi_vertex_type*
v) |
Sets the start point
pointer of the edge. |
| voronoi_vertex_type*
vertex1() |
Returns the pointer to the
end point of the edge.
If the edge is infinite in that direction returns NULL. |
| const
voronoi_vertex_type* vertex1()
const |
Returns the const pointer
to the end point of the edge.
If the edge is infinite in that direction returns NULL. |
| voronoi_edge_type*
twin() |
Returns the pointer to the
twin edge. |
| const
voronoi_edge_type* twin()
const |
Returns the const pointer
to the twin edge. |
| void
twin(voronoi_edge_type*
e) |
Sets the twin edge pointer
of the edge. |
| voronoi_edge_type*
next() |
Returns the pointer to the
CCW next edge within the corresponding Voronoi cell.
Edges not necessarily share a common vertex (e.g. infinite edges). |
| const
voronoi_edge_type* next()
const |
Returns the const pointer
to the CCW next edge within the corresponding Voronoi cell.
Edges not necessarily share a common vertex (e.g. infinite edges). |
| void
next(voronoi_edge_type*
e) |
Sets the CCW next edge
pointer of the edge. |
| voronoi_edge_type*
prev() |
Returns the pointer to the
CCW prev edge within the corresponding Voronoi cell.
Edges not necessarily share a common vertex (e.g. infinite edges). |
| const
voronoi_edge_type* prev()
const |
Returns the const pointer
to the CCW prev edge within the corresponding Voronoi cell.
Edges not necessarily share a common vertex (e.g. infinite edges). |
| void
prev(voronoi_edge_type*
e) |
Sets the CCW prev edge
pointer of the edge. |
| color_type
color() const |
Returns the color value. |
| void
color(color_type
color) const |
Sets the color of
the edge.
Allows to associate the user provided data with the primitive. |
| voronoi_edge_type*
rot_next() |
Returns the pointer to the
CCW next edge rotated around the edge start point.
Works for infinite edges as well. |
| const
voronoi_edge_type* rot_next()
const |
Returns the const pointer
to the CCW next edge rotated around the edge start point.
Works for infinite edges as well. |
| voronoi_edge_type*
rot_prev() |
Returns the pointer to the
CCW prev edge rotated around the edge start point.
Works for infinite edges as well. |
| const
voronoi_edge_type* rot_prev()
const |
Returns the const pointer
to the CCW prev edge rotated around the edge start point.
Works for infinite edges as well. |
| bool
is_finite() const |
Returns true if the both
end points of the edge are finite, else false. |
| bool
is_infinite() const |
Returns true if one of the
end points of the edge is infinite, else false. |
| bool
is_linear() const |
Returns true if the edge
is linear (segment, ray, line), else false. |
| bool
is_curved() const |
Returns true if the edge
is curved (parabolic arc), else false. |
| bool
is_primary() const |
Returns false if the edge
goes through the endpoint of the segment site, else true. |
| bool
is_secondary() const |
Returns true if the edge
goes through the endpoint of the segment site, else false. |
All
the above methods have O(1) complexity. The size of
the Voronoi edge structure is equal to: 5 * sizeof(void *) +
sizeof(size_t).
Member Types
| coordinate_type |
Coordinate type. |
| voronoi_cell_type |
Voronoi cell type. |
| voronoi_vertex_type |
Voronoi vertex type. |
| voronoi_edge_type |
Voronoi edge type. |
| color_type
|
Color type (check the
Important section). |
Voronoi Cell
A Voronoi cell represents a region of the Voronoi diagram bounded by
the Voronoi edges. On the image below, there are 7 such regions: P, Q,
R, S, T, U, V. Each Voronoi cell can contain a point (e.g. cells Q, S,
T, U, V with corresponding input sources N, K, L, O, M respectively) or
a segment
(e.g. cells P and R with corresponding input sources MN and KL
respectively) as its
source. The Voronoi cell primitive doesn't contain coordinates of the
source geometry, instead it stores the index and category of the source
geometry. Source index corresponds to the unique id, issued to each
input geometry (e.g. incremental counter, used by the Voronoi builder).
Such an index uniquely identifies any input point (e.g. O), however
doesn't make any distinction between segment (e.g. MN) and both its end
points (e.g. M, N). In order to resolve possible ambiguity, the source
category is used, that specifies the semantic topology of the input
object (e.g. segment's startpoint, segment's endpoint or segment
itself). The Voronoi cell data structure also provides access to a
random Voronoi edge, located on the boundary of the cell (e.g. edge AE
for
the cell P).
Declaration
Header: boost/polygon/voronoi_diagram.hpp
template
<typename T>
class voronoi_cell;
T
- coordinate type.
Member Functions
voronoi_cell(source_index_type
source_index,
source_category_type source_category) |
Voronoi cell constructor. |
| source_index_type
source_index()
const |
Returns input site index among the other sites.
Both segment and its end points will have the same index. |
| source_category_type
source_category()
const |
Returns input site category among the other sites.
Allows to distinguish between segment site and its endpoints. |
| voronoi_edge_type*
incident_edge() |
Returns the pointer to the
one of the boundary edges. |
| const
voronoi_edge_type* incident_edge()
const |
Returns the const pointer
to the one of the boundary edges. |
| void
incident_edge(voronoi_edge_type*
e) |
Sets the incident boundary
edge pointer of the cell. |
| color_type
color() const |
Returns the color associated with the cell. |
| void
color(color_type
color) const |
Sets the color of
the cell.
Allows to associate the user provided data with the primitive. |
| bool
contains_point()
const |
Returns true if the cell
contains a point site, else false. |
| bool
contains_segment()
const |
Returns true if the cell
contains a segment site, else false. |
| bool
is_degenerate()
const |
Returns true if the cell
doesn't have an incident edge.
Can happen if a few input segments share a common endpoint. |
All
the above methods have O(1) complexity. The size of
the Voronoi cell structure is equal to: sizeof(void *) + 2 *
sizeof(size_t).
Member Types
| coordinate_type |
Coordinate type. |
| source_index_type |
Source index type. |
| source_category_type
|
Source category type. |
| voronoi_edge_type
|
Voronoi edge type. |
| color_type |
Color type (check the Important section). |
Miscellaneous
The following code snippet effectively traverses the Voronoi edges
around the
Voronoi cell:
const
voronoi_edge<double>* edge = cell->incident_edge();
do {
edge = edge->next();
// Do smth. with edge.
} while
(edge != cell->incident_edge());
Voronoi Vertex
A Voronoi vertex represents a point, that is equidistant from the three
or more input geometries. As a consequence, it corresponds to the point
of the intersection of the three or more Voronoi edges. On the image
below, there are 5 such vertices: A, B, C, D, E. The Voronoi vertex
data structure embeds the coordinates of the underlying point and
provides access to a random Voronoi edge originating from the vertex
(e.g. edge
BC for the vertex B).
Declaration
Header: boost/polygon/voronoi_diagram.hpp
template
<typename T>
class
voronoi_vertex;
T
- coordinate type.
Member Functions
voronoi_vertex(const
coordinate_type& x,
const coordinate_type& y) |
Voronoi vertex constructor. |
| const
coordinate_type& x() const |
Returns the x-coordinate of the point that represents
the vertex. |
| const
coordinate_type& y() const |
Returns the y-coordinate of the point that represents
the vertex. |
| voronoi_edge_type*
incident_edge() |
Returns the incident edge
pointer. |
| const
voronoi_edge_type* incident_edge()
const |
Returns the const pointer
to the incident edge. |
| void
incident_edge(voronoi_edge_type*
e) |
Sets the incident edge
pointer. |
| color_type
color() const |
Returns the color associated with the vertex. |
| void
color(color_type
color) const |
Sets the color of
the vertex.
Allows to associate the user provided data with the primitive. |
All
the above methods have O(1) complexity. The size of
the Voronoi vertex structure is equal to: sizeof(void *) +
sizeof(size_t) + 2 *
sizeof(coordinate_type).
Member Types
| coordinate_type |
Coordainte type. |
| voronoi_edge_type
|
Voronoi edge type. |
| color_type |
Color type (check the Important section). |
Miscellaneous
The following code snippet effectively traverses the Voronoi edges
around the
Voronoi vertex:
const
voronoi_edge<double>* edge = vertex->incident_edge();
do {
edge = edge->next();
// Do smth. with edge.
} while
(edge != vertex->incident_edge());
Voronoi Diagram Traits
The Voronoi diagram traits are used to configure the Voronoi primitive
types and predicates, used by the Voronoi diagram
data
structure.
The implementation includes default traits specialization for the
double output coordinate type.
Declaration
Header: boost/polygon/voronoi_diagram.hpp
template
<typename T>
struct
voronoi_diagram_traits;
T
- coordinate type.
Member Types
| coordinate_type
|
Coordinate type
of the Voronoi diagram primitives. |
| cell_type
|
Voronoi cell type. |
| vertex_type
|
Voronoi vertex type. |
| edge_type
|
Voronoi edge type. |
| vertex_equality_predicate_type
|
Predicate that returns
true if the two points are considered to be equal.
False otherwise. It is used to unite nearby Voronoi vertices. |
|


| Figure 1 |
Climatology (2003–2015) of the frequency of dust events. Bla ... |
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| Figure 3 |
Dominant contributors to the variations of dust event freque ... |
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Case studies of two dry years in the southern Great Plains. ... |
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Changes of dust event frequency in the late half of the twen ... |


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Adapted from here.
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Priithon # modified version of http://wiki.wxpython.org/AsynchronousSockets # by Josiah Carlson # # seb: what does this mean: # remember to validate any possible # socket objects recieved from the GUI, # they could already be closed # this is somehow related to the **kwarg sock=self - but otherwise unused
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to_network = Queue.Queue()
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_pollers =
class CustomConnection(DispatcherConnection): #inc_buffer = '' |
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EVT_LOG_EVENT = <wx._core.PyEventBinder object at 0x80cce50>
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install a server to listen on given `port` on given `host` onRead is a handler function that is being called with a asyncore.dispatcher_with_send object as argument (`asynDisp`) (its type is really a DispatcherConnection, which is derived of that) if `linewise`: `onRead` is called for each completed line an `line` is an extra first(!) argument (' ' is truncated) (`asynDisp.recv(512)` is called for you as needed!) otherwise, `onRead` has to do the `asynDisp`.recv(512) calls itself `host`='' means "all IPs of local host" (<IP_ADDRESS> + external IP(s)) `logFcn`: if None no logging done, otherwise `logFcn` called for each log-print with string message as argument if `threaded` is False, a timer event is connected to `wxEvtFrame` `wxEvtFrame` None means, find and use "first" toplevel parent |
|
_pollersclass CustomConnection(DispatcherConnection): #inc_buffer = '' # def __init__(self, connection, logFcn, handle_read): # self.hr = handle_read # DispatcherConnection.__init__(self, connection, logFcn) def handle_read(self): self.hr(self) # self.inc_buffer += self.recv(512) # while ' ' in self.inc_buffer: # snd, self.inc_buffer = self.inc_buffer.split(' ', 1) # snd += ' ' # self.log("Line from %s: %r"%(self.addr, snd)) # self.send(snd)
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We did most of the heavy lisfting. Using the API Jikan, Anilist provides you with a simple genre selection to find whatever show you might watch next
By utilizing elements and principles of community building, Anilist strives to build a strong and warm community for all anime watchers alike, avid or not. Watched an anime and have thoughts on it? Share it with the write a review button at the top right!
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This is a complete review after watching all 12 episodes of One Punch Man. I remember when I was 8 years old, I used to be excited for a new Pokemon episode everyday. I used to run from school to my house so that I wouldn’t miss any single moment. Then as you grow up, such excitement starts to fade away. No matter how good a show is, only a few shows can generate such an excitement for a viewer. I never would’ve imagined that an anime would make me feel that excitement again at 20 yrs. And lucky for me, it aired on Sundays!
One Piece is by far the best shounen anime out there that I have watched. But not all share the same views as I do, lets remedy that, shall we? A long time ago, there live a fearsome pirate king who goes by the name of Gold D. Roger. He was able to attain everything. But alas he was captured and sentenced to execution. In the brink of death, he proclaimed that he left the great treasure, One Piece, somewhere in the Grand Line and it is for anyone to claim. This event ignited the Great Pirate Age.
Bleach had great potential, but became annoying with poor character development and random powers. Bleach has one of my favorite concepts ever. The Soul Society is awesome and the Gotei 13 are probably the best part of the show. They are squads composed of a multitude of Shinigami(Soul Reapers) and the show focuses more on the Captains and Lieutenants of those squads that are the most interesting characters in the show. Although, their could have been less squads(like 6) with less members in them(like 5) to have a more focused cast of characters that get more development.


This page tracks the new paper links made to my list of NPAR 2012 papers.
Page maintained by Ke-Sen Huang.
If you have additions or changes, send an e-mail.
June 21, 2012
- Combining Sketch and Tone for Pencil Drawing Production
- No Photos Harmed / Growing Paths from Seed: An Exhibition
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June 16, 2012
- Texture-Preserving Abstraction
- Consistent Stylization and Painterly Rendering of Stereoscopic 3D Images
- Pixelated Image Abstraction
June 4, 2012
May 23, 2012
- Active Strokes: Coherent Line Stylization for Animated 3D Models
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This chapter introduces the module system of Objective Caml.
A primary motivation for modules is to package together related definitions (such as the definitions of a data type and associated operations over that type) and enforce a consistent naming scheme for these definitions. This avoids running out of names or accidentally confusing names. Such a package is called a structure and is introduced by the struct…end construct, which contains an arbitrary sequence of definitions. The structure is usually given a name with the module binding. Here is for instance a structure packaging together a type of priority queues and their operations:
#module PrioQueue = struct type priority = int type ’a queue = Empty | Node of priority * ’a * ’a queue * ’a queue let empty = Empty let rec insert queue prio elt = match queue with Empty -> Node(prio, elt, Empty, Empty) | Node(p, e, left, right) -> if prio <= p then Node(prio, elt, insert right p e, left) else Node(p, e, insert right prio elt, left) exception Queue_is_empty let rec remove_top = function Empty -> raise Queue_is_empty | Node(prio, elt, left, Empty) -> left | Node(prio, elt, Empty, right) -> right | Node(prio, elt, (Node(lprio, lelt, _, _) as left), (Node(rprio, relt, _, _) as right)) -> if lprio <= rprio then Node(lprio, lelt, remove_top left, right) else Node(rprio, relt, left, remove_top right) let extract = function Empty -> raise Queue_is_empty | Node(prio, elt, _, _) as queue -> (prio, elt, remove_top queue) end;; module PrioQueue : sig type priority = int type ’a queue = Empty | Node of priority * ’a * ’a queue * ’a queue val empty : ’a queue val insert : ’a queue -> priority -> ’a -> ’a queue exception Queue_is_empty val remove_top : ’a queue -> ’a queue val extract : ’a queue -> priority * ’a * ’a queue end
Outside the structure, its components can be referred to using the “dot notation”, that is, identifiers qualified by a structure name. For instance, PrioQueue.insert in a value context is the function insert defined inside the structure PrioQueue. Similarly, PrioQueue.queue in a type context is the type queue defined in PrioQueue.
#PrioQueue.insert PrioQueue.empty 1 "hello";; - : string PrioQueue.queue = PrioQueue.Node (1, "hello", PrioQueue.Empty, PrioQueue.Empty)
Signatures are interfaces for structures. A signature specifies which components of a structure are accessible from the outside, and with which type. It can be used to hide some components of a structure (e.g. local function definitions) or export some components with a restricted type. For instance, the signature below specifies the three priority queue operations empty, insert and extract, but not the auxiliary function remove_top. Similarly, it makes the queue type abstract (by not providing its actual representation as a concrete type).
#module type PRIOQUEUE = sig type priority = int (* still concrete *) type ’a queue (* now abstract *) val empty : ’a queue val insert : ’a queue -> int -> ’a -> ’a queue val extract : ’a queue -> int * ’a * ’a queue exception Queue_is_empty end;; module type PRIOQUEUE = sig type priority = int type ’a queue val empty : ’a queue val insert : ’a queue -> int -> ’a -> ’a queue val extract : ’a queue -> int * ’a * ’a queue exception Queue_is_empty end
Restricting the PrioQueue structure by this signature results in another view of the PrioQueue structure where the remove_top function is not accessible and the actual representation of priority queues is hidden:
#module AbstractPrioQueue = (PrioQueue : PRIOQUEUE);; module AbstractPrioQueue : PRIOQUEUE #AbstractPrioQueue.remove_top;; Error: Unbound value AbstractPrioQueue.remove_top #AbstractPrioQueue.insert AbstractPrioQueue.empty 1 "hello";; - : string AbstractPrioQueue.queue = <abstr>
The restriction can also be performed during the definition of the structure, as in
module PrioQueue = (struct ... end : PRIOQUEUE);;
An alternate syntax is provided for the above:
module PrioQueue : PRIOQUEUE = struct ... end;;
Functors are “functions” from structures to structures. They are used to express parameterized structures: a structure A parameterized by a structure B is simply a functor F with a formal parameter B (along with the expected signature for B) which returns the actual structure A itself. The functor F can then be applied to one or several implementations B1 …Bn of B, yielding the corresponding structures A1 …An.
For instance, here is a structure implementing sets as sorted lists, parameterized by a structure providing the type of the set elements and an ordering function over this type (used to keep the sets sorted):
#type comparison = Less | Equal | Greater;; type comparison = Less | Equal | Greater #module type ORDERED_TYPE = sig type t val compare: t -> t -> comparison end;; module type ORDERED_TYPE = sig type t val compare : t -> t -> comparison end #module Set = functor (Elt: ORDERED_TYPE) -> struct type element = Elt.t type set = element list let empty = [] let rec add x s = match s with [] -> [x] | hd::tl -> match Elt.compare x hd with Equal -> s (* x is already in s *) | Less -> x :: s (* x is smaller than all elements of s *) | Greater -> hd :: add x tl let rec member x s = match s with [] -> false | hd::tl -> match Elt.compare x hd with Equal -> true (* x belongs to s *) | Less -> false (* x is smaller than all elements of s *) | Greater -> member x tl end;; module Set : functor (Elt : ORDERED_TYPE) -> sig type element = Elt.t type set = element list val empty : ’a list val add : Elt.t -> Elt.t list -> Elt.t list val member : Elt.t -> Elt.t list -> bool end
By applying the Set functor to a structure implementing an ordered type, we obtain set operations for this type:
#module OrderedString = struct type t = string let compare x y = if x = y then Equal else if x < y then Less else Greater end;; module OrderedString : sig type t = string val compare : ’a -> ’a -> comparison end #module StringSet = Set(OrderedString);; module StringSet : sig type element = OrderedString.t type set = element list val empty : ’a list val add : OrderedString.t -> OrderedString.t list -> OrderedString.t list val member : OrderedString.t -> OrderedString.t list -> bool end #StringSet.member "bar" (StringSet.add "foo" StringSet.empty);; - : bool = false
As in the PrioQueue example, it would be good style to hide the actual implementation of the type set, so that users of the structure will not rely on sets being lists, and we can switch later to another, more efficient representation of sets without breaking their code. This can be achieved by restricting Set by a suitable functor signature:
#module type SETFUNCTOR = functor (Elt: ORDERED_TYPE) -> sig type element = Elt.t (* concrete *) type set (* abstract *) val empty : set val add : element -> set -> set val member : element -> set -> bool end;; module type SETFUNCTOR = functor (Elt : ORDERED_TYPE) -> sig type element = Elt.t type set val empty : set val add : element -> set -> set val member : element -> set -> bool end #module AbstractSet = (Set : SETFUNCTOR);; module AbstractSet : SETFUNCTOR #module AbstractStringSet = AbstractSet(OrderedString);; module AbstractStringSet : sig type element = OrderedString.t type set = AbstractSet(OrderedString).set val empty : set val add : element -> set -> set val member : element -> set -> bool end #AbstractStringSet.add "gee" AbstractStringSet.empty;; - : AbstractStringSet.set = <abstr>
In an attempt to write the type constraint above more elegantly, one may wish to name the signature of the structure returned by the functor, then use that signature in the constraint:
#module type SET = sig type element type set val empty : set val add : element -> set -> set val member : element -> set -> bool end;; module type SET = sig type element type set val empty : set val add : element -> set -> set val member : element -> set -> bool end #module WrongSet = (Set : functor(Elt: ORDERED_TYPE) -> SET);; module WrongSet : functor (Elt : ORDERED_TYPE) -> SET #module WrongStringSet = WrongSet(OrderedString);; module WrongStringSet : sig type element = WrongSet(OrderedString).element type set = WrongSet(OrderedString).set val empty : set val add : element -> set -> set val member : element -> set -> bool end #WrongStringSet.add "gee" WrongStringSet.empty;; Error: This expression has type string but an expression was expected of type WrongStringSet.element = WrongSet(OrderedString).element
The problem here is that SET specifies the type element abstractly, so that the type equality between element in the result of the functor and t in its argument is forgotten. Consequently, WrongStringSet.element is not the same type as string, and the operations of WrongStringSet cannot be applied to strings. As demonstrated above, it is important that the type element in the signature SET be declared equal to Elt.t; unfortunately, this is impossible above since SET is defined in a context where Elt does not exist. To overcome this difficulty, Objective Caml provides a with type construct over signatures that allows to enrich a signature with extra type equalities:
#module AbstractSet = (Set : functor(Elt: ORDERED_TYPE) -> (SET with type element = Elt.t));; module AbstractSet : functor (Elt : ORDERED_TYPE) -> sig type element = Elt.t type set val empty : set val add : element -> set -> set val member : element -> set -> bool end
As in the case of simple structures, an alternate syntax is provided for defining functors and restricting their result:
module AbstractSet(Elt: ORDERED_TYPE) : (SET with type element = Elt.t) = struct ... end;;
Abstracting a type component in a functor result is a powerful technique that provides a high degree of type safety, as we now illustrate. Consider an ordering over character strings that is different from the standard ordering implemented in the OrderedString structure. For instance, we compare strings without distinguishing upper and lower case.
#module NoCaseString = struct type t = string let compare s1 s2 = OrderedString.compare (String.lowercase s1) (String.lowercase s2) end;; module NoCaseString : sig type t = string val compare : string -> string -> comparison end #module NoCaseStringSet = AbstractSet(NoCaseString);; module NoCaseStringSet : sig type element = NoCaseString.t type set = AbstractSet(NoCaseString).set val empty : set val add : element -> set -> set val member : element -> set -> bool end #NoCaseStringSet.add "FOO" AbstractStringSet.empty;; Error: This expression has type AbstractStringSet.set = AbstractSet(OrderedString).set but an expression was expected of type NoCaseStringSet.set = AbstractSet(NoCaseString).set
Notice that the two types AbstractStringSet.set and NoCaseStringSet.set are not compatible, and values of these two types do not match. This is the correct behavior: even though both set types contain elements of the same type (strings), both are built upon different orderings of that type, and different invariants need to be maintained by the operations (being strictly increasing for the standard ordering and for the case-insensitive ordering). Applying operations from AbstractStringSet to values of type NoCaseStringSet.set could give incorrect results, or build lists that violate the invariants of NoCaseStringSet.
All examples of modules so far have been given in the context of the interactive system. However, modules are most useful for large, batch-compiled programs. For these programs, it is a practical necessity to split the source into several files, called compilation units, that can be compiled separately, thus minimizing recompilation after changes.
In Objective Caml, compilation units are special cases of structures and signatures, and the relationship between the units can be explained easily in terms of the module system. A compilation unit A comprises two files:
Both files define a structure named A as if the following definition was entered at top-level:
module A: sig (* contents of file A.mli *) end = struct (* contents of file A.ml *) end;;
The files defining the compilation units can be compiled separately using the ocamlc -c command (the -c option means “compile only, do not try to link”); this produces compiled interface files (with extension .cmi) and compiled object code files (with extension .cmo). When all units have been compiled, their .cmo files are linked together using the ocaml command. For instance, the following commands compile and link a program composed of two compilation units Aux and Main:
$ ocamlc -c Aux.mli # produces aux.cmi $ ocamlc -c Aux.ml # produces aux.cmo $ ocamlc -c Main.mli # produces main.cmi $ ocamlc -c Main.ml # produces main.cmo $ ocamlc -o theprogram Aux.cmo Main.cmo
The program behaves exactly as if the following phrases were entered at top-level:
module Aux: sig (* contents of Aux.mli *) end = struct (* contents of Aux.ml *) end;; module Main: sig (* contents of Main.mli *) end = struct (* contents of Main.ml *) end;;
In particular, Main can refer to Aux: the definitions and declarations contained in Main.ml and Main.mli can refer to definition in Aux.ml, using the Aux.ident notation, provided these definitions are exported in Aux.mli.
The order in which the .cmo files are given to ocaml during the linking phase determines the order in which the module definitions occur. Hence, in the example above, Aux appears first and Main can refer to it, but Aux cannot refer to Main.
Notice that only top-level structures can be mapped to separately-compiled files, but not functors nor module types. However, all module-class objects can appear as components of a structure, so the solution is to put the functor or module type inside a structure, which can then be mapped to a file.


This site is an example of how one can implement role based authentication in Angular applications as outlined in this blogpost. All the code can be found in this GitHub repository. You can either register a new user, log in with one of the two predefined users...
... or use one of them fancy social logins:


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Reports
switch
statements that are nested inside other
switch
statements. Such nested switch statements are confusing, and may result in unexpected behaviour.


The use of Redis persistence with EC2 EBS volumes is discouraged since EBS performance is usually poor. Use ephemeral storage to persist and then move your persistence files to EBS when possible.
Even if you have persistence disabled, Redis will need to perform RDB saves if you use replication.
Rails cache has his own server now.
# cat config/initializers/redis.rb
$redis = Redis.new host: 'ec2-xxx...', port: 6379, driver: :hiredis
$redis_rails_cache = Redis.new host: 'ec2-yyy...', port: 6379, driver: :hiredis
App response time over 3 days.
Response time and throughput over 3 days.
CPU load over 3 days.
Rails cache server CPU is overloaded
The MONITOR command in redis is showing very slow requests, expiring keys with a wildcard.
KEYS (...) should only be used in production environments with extreme care. It may ruin performance when it is executed against large databases.
Stopping using the wildcard expiration, we now increment the namespace of the cached value.
Data will expire 14 days after creation.
Error rate and CPU load around the fix.
The rails cache server after the storm.
The rails cache server after the storm.


@since Oak 1.7.0
Work in progress. Not to be used on production setups
With Oak 1.7 we have added some tooling as part of oak-run index command. Below are details around various operations supported by this command.
The index command supports connecting to different NodeStores via various options which are documented here. Example below assume a setup consisting of SegmentNodeStore and FileDataStore. Depending on setup use the appropriate connection options.
By default the tool would generate output file in directory indexing-result which is referred to as output directory.
Unless specified all operations connect to the repository in read only mode
All the commands support following common options
Also refer to help output via -h command for some other options
java -jar oak-run*.jar index --fds-path=/path/to/datastore /path/to/segmentstore/ --index-info
Generates a report consisting of various stats related to indexes present in the given repository. The generated report is stored by default in <output dir>/index-info.txt
Supported for all index types
java -jar oak-run*.jar index --fds-path=/path/to/datastore /path/to/segmentstore/ --index-definitions
--index-definitions operation dumps the index definition in json format to a file <output dir>/index-definitions.json. The json file contains index definitions keyed against the index paths
Supported for all index types
java -jar oak-run*.jar index --fds-path=/path/to/datastore /path/to/segmentstore/ --index-dump
--index-dump operation dumps the index content in output directory. The output directory would contain one folder for each index. Each folder would have a property file index-details.txt which contains indexPath
Supported for only Lucene indexes.
java -jar oak-run*.jar index --fds-path=/path/to/datastore /path/to/segmentstore/ --index-consistency-check
--index-consistency-check operation performs index consistency check against various indexes. It supports 2 level
It would generate a report in <output dir>/index-consistency-check-report.txt
Supported for only Lucene indexes.
The reindex operation supports 2 modes of index
Supported for only Lucene indexes.
If the indexes being reindex have fulltext indexing enabled then refer to Tika Setup for steps on how to adapt the command to include Tika support for text extraction
Out of band indexing has following phases
If the index being reindexed involves fulltext index and the repository has binary content then its recommended that first text pre-extraction is performed. This ensures that costly operation around text extraction is done prior to actual indexing so that actual indexing does not do text extraction in critical path
Go to CheckpointMBean and create a checkpoint with a long enough lifetime like 10 days. For this invoke CheckpointMBean#createCheckpoint with 864000000 as argument for lifetime
In this step we perform the actual indexing via oak-run where it connects to repository in read only mode.
java -jar oak-run*.jar index --reindex \ --index-paths=/oak:index/indexName \ --checkpoint=0fd2a388-de87-47d3-8f30-e86b1cf0a081 \ --fds-path=/path/to/datastore /path/to/segmentstore/
Here following options can be used
If the index does not support fulltext indexing then you can omit providing BlobStore details
As a last step we need to import the index back in the repository. This can be done in one of the following ways
In this mode we import the index using oak-run
java -jar oak-run*.jar index --index-import --read-write \ --index-import-dir=<index dir> \ --fds-path=/path/to/datastore /path/to/segmentstore
Here “index dir” is the directory which contains the index files created in step #3. Check the logs from previous command for the directory path.
This mode should only be used when repository is from Oak version 1.7+ as oak-run connects to the repository in read-write mode.
Online indexing automates some of the manual steps which are required for out-of-band indexing.
This mode should only be used when repository is from Oak version 1.7+ as oak-run connects to the repository in read-write mode.
In this step we configure oak-run to connect to repository in read-write mode and let it perform all other steps i.e checkpoint creation, indexing and import
java -jar oak-run*.jar index --reindex --index-paths=/oak:index/lucene --read-write --fds-path=/path/to/datastore /path/to/segmentstore
@since Oak 1.7.5
Index tooling support updating and adding new index definitions to existing setups. This can be done by passing in path of a json file which contains index definitions
java -jar oak-run*.jar index --reindex --index-paths=/oak:index/newAssetIndex \ --index-definitions-file=index-definitions.json \ --fds-path=/path/to/datastore /path/to/segmentstore
Where index-definitions.json has following structure
{ "/oak:index/newAssetIndex": { "evaluatePathRestrictions": true, "compatVersion": 2, "type": "lucene", "async": "async", "jcr:primaryType": "oak:QueryIndexDefinition", "indexRules": { "jcr:primaryType": "nt:unstructured", "dam:Asset": { "jcr:primaryType": "nt:unstructured", "properties": { "jcr:primaryType": "nt:unstructured", "valid": { "name": "valid", "propertyIndex": true, "jcr:primaryType": "nt:unstructured", "notNullCheckEnabled": true }, "mimetype": { "name": "mimetype", "analyzed": true, "jcr:primaryType": "nt:unstructured" } } } } } }
Some points to note about this json file * Each key of top level object refers to the index path * The value of each such key refers to complete index definition * If the index path is not present in existing repository then it would result in a new index being created * In case of new index it must be ensured that parent path structure must already exist in repository. So if a new index is being created at /content/en/oak:index/contentIndex then path upto /content/en/oak:index should already exist in repository * If this option is used with online indexing then do ensure that oak-run version matches with the Oak version used by target repository
You can also use the json file generated from Oakutils. It needs to be modified to confirm to above structure i.e. enclose the whole definition under the intended index path key.
In general the index definitions does not need any special encoding of values as Index definitions in Oak use only String, Long and Double types mostly. However if the index refers to binary config like Tika config then the binary data would need to encoded. Refer to next section for more details.
This option is supported in both online and out-of-band indexing.
For more details refer to OAK-6471
Some of the standard types used in Oak are not supported directly by JSON like names, blobs etc. Those would need to be encoded in a specific format.
Below are the encoding rules
If the indexes being reindex have fulltext indexing enabled then you need to include Tika library in classpath. This is required even if pre extraction is used so as to ensure that any new binary added after pre-extraction is done can be indexed.
First download the tika-app jar from Tika downloads. You should be able to use 1.15 version with Oak 1.7.4 jar.
Then modify the index command like below. The rest of arguments remain same as documented before.
java -cp oak-run.jar:tika-app-1.15.jar org.apache.jackrabbit.oak.run.Main index


| Module | OpenID::Yadis::XRI |
| In: |
lib/openid/yadis/xri.rb
lib/openid/yadis/xrires.rb |
| XRI_AUTHORITIES | = | ["!", "=", "@", "+", "$", "("] | The ’(’ is for cross-reference authorities, and hopefully has a matching ’)’ somewhere. |
Note this is not not idempotent, so do not apply this more than once. XRI Syntax section 2.3.2


Preview all the available experiments in the experiment factory, right in your browser.
A "battery" is a collection of experiments that are presented together using psiturk. You can deploy to a local folder, or a vagrant virtual machine, either local or for Amazon Web Services.
Our experiments are available programatically via an Application Program Interface (API). See our documentation for details. You can also download static data, for offline use.
You can use our experiment robot and validation functions to test new experiments.
We will potentially be offering experiment deployment as a service. Sign up to be notified.
All of our code for experiments, virtual machines, psiturk battery generation, and this application are available on Github, and we are excited for your help and feedback.


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As the new fall semester begins, so to does the yearly drudge and tiring exhalations of students and faculty heard through out the halls like background noise to a horror film. It is not pretty. The pursuit of pure knowledge, degrees, and ultimately a higher position in society were never designed to be an aesthetically pleasing journey.
But this is fall. I am about to begin the final year of a four year journey and in a few short months, receive a Bachelors Degree in Computer Science (hopefully with honors if nothing to dramatically terrible happens to my GPA) and begin my career in the tech field. I wanted to share some professional lessons I’ve learned as a student, a computer scientist, and a human being. Please enjoy.
A Student
There is something to say about the life of an engineering student that would put a lot of people on edge. Classes including Differential Equations, MultiVariable Calculus, and multiple physics courses, are basic requirements for most engineering degrees. So, as an engineering student, you have willing signed up for the hardest courses offered at the undergraduate level. These courses can be daunting hurdles to overcome, but not impossible.
Many people want to be engineering students for many reasons: some are sadist who enjoy the extraneous pain of never ending calculations, some have careers goals that require a great amount of quantitative skill, and others are simply here because they want to prove themselves to world. Whatever your reason, it’s very important to keep this in mind throughout your university experience. This is your driving force as to why your putting yourself through such leaps and hurdles, taking classes that turn you from dunce to genius, and putting up with a workload that is unheard of in any other college in your university.
Whatever your underlining reason for doing something as bold and brash as becoming an engineering major, strive hard and long towards the end. Rage, rage straight into the light.
A Computer Scientist
As a student, especially one pursing a Bachelor’s of Science rather than a Bachelor’s of Arts, it’s important to remember that there are hundreds of other people taking the exact same courses as you, and thus, doing the exact same assignments. Whether you plan to start a business, start a career, or start a graduate level degree after your Bachelors, you’re going to need to distinguish yourself from the pack. In the field of computer science, the best way to distinguish yourself is to be a scientist not only for a grade but as a life style.
A scientist, conducts extensive research, creates experiments, solves problems, optimizes, re-thinks old solutions, and replaces fear of the unknown with curiosity. When it comes to computers, there is no compromise on what it means to be a scientist. So when your mind is itching on a subject missing from your curriculum, you must put it on yourself to learn and master this new curiosity of yours.
I layman terms, start a project; but more importantly, FINISH the project.
A Human
Don’t take it so seriously.
That’s the best advice I can give to as to not lose your mind. If the student part of your psyche is an uptight and studious prince/princess that accepts nothing else but the purest of logic and theory, and the scientist part of your psyche is a raging lunatic that spends hours in a lab performing unholy experiments, then the human part of your psyche is a smoke-totting hippy that just got back from burning man.
Life comes at us hard. You might fail a class or two. An experiment that you’ve put a lot of blood and sweat into might turn out to be for nothing. It’s okay. These things happen. It’s important to not take it too personally or too seriously. So do what ever makes you relax: hang with friends, go for a jog, eat good food, play lots of games, find a hobby outside of computers, and go on dates. Just like you, I want to have a great impact on the world and society; I want my engineering to better the lives of not only me, but everyone around me. But, in all honesty, it’s not worth losing your mind over.
Thank you. I hope you’ve enjoyed.


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