The Database class encapsulates a single connection to a SQLite3 database. Its usage is very straightforward:
require 'sqlite3' SQLite3::Database.new( "data.db" ) do |db| db.execute( "select * from table" ) do |row| p row end end
It wraps the lower-level methods provides by the selected driver, and includes the Pragmas module for access to various pragma convenience methods.
The Database class provides type translation services as well, by which the SQLite3 data types (which are all represented as strings) may be converted into their corresponding types (as defined in the schemas for their tables). This translation only occurs when querying data from the database–insertions and updates are all still typeless.
Furthermore, the Database class has been designed to work well with the ArrayFields module from Ara Howard. If you require the ArrayFields module before performing a query, and if you have not enabled results as hashes, then the results will all be indexible by field name.
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| [RW] | results_as_hash | A boolean that indicates whether rows in result sets should be returned as hashes or not. By default, rows are returned as arrays. |
| [RW] | type_translation | A boolean indicating whether or not type translation is enabled for this database. |
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 366 def self.finalize( &block ) define_method(:finalize, &block) end
Create a new Database object that opens the
given file. If utf16 is true
, the filename is interpreted as a
UTF-16 encoded string.
By default, the new database will return result rows as arrays (results_as_hash) and has type translation disabled (type_translation=).
Source: show
static VALUE initialize(int argc, VALUE *argv, VALUE self) { sqlite3RubyPtr ctx; VALUE file; VALUE opts; VALUE zvfs; int status; Data_Get_Struct(self, sqlite3Ruby, ctx); rb_scan_args(argc, argv, "12", &file, &opts, &zvfs); if(NIL_P(opts)) opts = rb_hash_new(); #ifdef HAVE_RUBY_ENCODING_H if(UTF16_LE_P(file)) { status = sqlite3_open16(utf16_string_value_ptr(file), &ctx->db); } else { #endif if(Qtrue == rb_hash_aref(opts, sym_utf16)) { status = sqlite3_open16(utf16_string_value_ptr(file), &ctx->db); } else { #ifdef HAVE_RUBY_ENCODING_H if(!UTF8_P(file)) { file = rb_str_export_to_enc(file, rb_utf8_encoding()); } #endif status = sqlite3_open_v2( StringValuePtr(file), &ctx->db, SQLITE_OPEN_READWRITE | SQLITE_OPEN_CREATE, NIL_P(zvfs) ? NULL : StringValuePtr(zvfs) ); } #ifdef HAVE_RUBY_ENCODING_H } #endif CHECK(ctx->db, status) rb_iv_set(self, "@tracefunc", Qnil); rb_iv_set(self, "@authorizer", Qnil); rb_iv_set(self, "@encoding", Qnil); rb_iv_set(self, "@busy_handler", Qnil); rb_iv_set(self, "@results_as_hash", rb_hash_aref(opts, sym_results_as_hash)); rb_iv_set(self, "@type_translation", rb_hash_aref(opts, sym_type_translation)); if(rb_block_given_p()) { rb_yield(self); rb_funcall(self, rb_intern("close"), 0); } return self; }
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 444 def initialize handler @handler = handler @fp = FunctionProxy.new end
Quotes the given string, making it safe to use in an SQL statement. It replaces all instances of the single-quote character with two single-quote characters. The modified string is returned.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 45 def quote( string ) string.gsub( /'/, "''" ) end
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 362 def self.step( &block ) define_method(:step, &block) end
Installs (or removes) a block that will be invoked for every access to the
database. If the block returns 0 (or nil
), the statement is
allowed to proceed. Returning 1 causes an authorization error to occur, and
returning 2 causes the access to be silently denied.
Source: show
Set the authorizer for this database. auth
must respond to
call
, and call
must take 5 arguments.
Installs (or removes) a block that will be invoked for every access to the
database. If the block returns 0 (or true
), the statement is
allowed to proceed. Returning 1 or false causes an authorization error to
occur, and returning 2 or nil causes the access to be silently denied.
Source: show
Register a busy handler with this database instance. When a requested
resource is busy, this handler will be invoked. If the handler returns
false
, the operation will be aborted; otherwise, the resource
will be requested again.
The handler will be invoked with the name of the resource that was busy, and the number of times it has been retried.
See also the mutually exclusive busy_timeout.
Source: show
static VALUE busy_handler(int argc, VALUE *argv, VALUE self) { sqlite3RubyPtr ctx; VALUE block; int status; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); rb_scan_args(argc, argv, "01", &block); if(NIL_P(block) && rb_block_given_p()) block = rb_block_proc(); rb_iv_set(self, "@busy_handler", block); status = sqlite3_busy_handler( ctx->db, NIL_P(block) ? NULL : rb_sqlite3_busy_handler, (void *)self); CHECK(ctx->db, status); return self; }
Indicates that if a request for a resource terminates because that resource
is busy, SQLite should sleep and retry for up to the indicated number of
milliseconds. By default, SQLite does not retry busy resources. To restore
the default behavior, send 0 as the ms
parameter.
See also the mutually exclusive busy_handler.
Source: show
static VALUE set_busy_timeout(VALUE self, VALUE timeout) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); CHECK(ctx->db, sqlite3_busy_timeout(ctx->db, (int)NUM2INT(timeout))); return self; }
Returns the number of changes made to this database instance by the last operation performed. Note that a “delete from table” without a where clause will not affect this value.
Source: show
static VALUE changes(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); return INT2NUM(sqlite3_changes(ctx->db)); }
Closes this database.
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static VALUE sqlite3_rb_close(VALUE self) { sqlite3RubyPtr ctx; sqlite3 * db; Data_Get_Struct(self, sqlite3Ruby, ctx); db = ctx->db; CHECK(db, sqlite3_close(ctx->db)); ctx->db = NULL; return self; }
Returns true
if this database instance has been closed (see close).
Source: show
static VALUE closed_p(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); if(!ctx->db) return Qtrue; return Qfalse; }
Commits the current transaction. If there is no current transaction, this
will cause an error to be raised. This returns true
, in order
to allow it to be used in idioms like abort? and rollback or
commit
.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 501 def commit execute "commit transaction" @transaction_active = false true end
Return true
if the string is a valid (ie, parsable) SQL
statement, and false
otherwise.
Source: show
static VALUE complete_p(VALUE UNUSED(self), VALUE sql) { if(sqlite3_complete(StringValuePtr(sql))) return Qtrue; return Qfalse; }
Creates a new aggregate function for use in SQL statements. Aggregate functions are functions that apply over every row in the result set, instead of over just a single row. (A very common aggregate function is the “count” function, for determining the number of rows that match a query.)
The new function will be added as name
, with the given
arity
. (For variable arity functions, use -1 for the arity.)
The step
parameter must be a proc object that accepts as its
first parameter a FunctionProxy
instance (representing the function invocation), with any subsequent
parameters (up to the function’s arity). The step
callback
will be invoked once for each row of the result set.
The finalize
parameter must be a proc
object that
accepts only a single parameter, the FunctionProxy instance representing
the current function invocation. It should invoke FunctionProxy#set_result
to store the result of the function.
Example:
db.create_aggregate( "lengths", 1 ) do step do |func, value| func[ :total ] ||= 0 func[ :total ] += ( value ? value.length : 0 ) end finalize do |func| func.set_result( func[ :total ] || 0 ) end end puts db.get_first_value( "select lengths(name) from table" )
See also create_aggregate_handler for a more object-oriented approach to aggregate functions.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 358 def create_aggregate( name, arity, step=nil, finalize=nil, text_rep=Constants::TextRep::ANY, &block ) factory = Class.new do def self.step( &block ) define_method(:step, &block) end def self.finalize( &block ) define_method(:finalize, &block) end end if block_given? factory.instance_eval(&block) else factory.class_eval do define_method(:step, step) define_method(:finalize, finalize) end end proxy = factory.new proxy.extend(Module.new { attr_accessor :ctx def step( *args ) super(@ctx, *args) end def finalize super(@ctx) end }) proxy.ctx = FunctionProxy.new define_aggregator(name, proxy) end
This is another approach to creating an aggregate function (see create_aggregate). Instead of explicitly specifying the name, callbacks, arity, and type, you specify a factory object (the “handler”) that knows how to obtain all of that information. The handler should respond to the following messages:
arity
-
corresponds to the
arity
parameter of create_aggregate. This message is optional, and if the handler does not respond to it, the function will have an arity of -1. name
-
this is the name of the function. The handler must implement this message.
new
-
this must be implemented by the handler. It should return a new instance of the object that will handle a specific invocation of the function.
The handler instance (the object returned by the new
message,
described above), must respond to the following messages:
step
-
this is the method that will be called for each step of the aggregate function’s evaluation. It should implement the same signature as the
step
callback for create_aggregate. finalize
-
this is the method that will be called to finalize the aggregate function’s evaluation. It should implement the same signature as the
finalize
callback for create_aggregate.
Example:
class LengthsAggregateHandler def self.arity; 1; end def initialize @total = 0 end def step( ctx, name ) @total += ( name ? name.length : 0 ) end def finalize( ctx ) ctx.set_result( @total ) end end db.create_aggregate_handler( LengthsAggregateHandler ) puts db.get_first_value( "select lengths(name) from A" )
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 442 def create_aggregate_handler( handler ) proxy = Class.new do def initialize handler @handler = handler @fp = FunctionProxy.new end def step( *args ) @handler.step(@fp, *args) end def finalize @handler.finalize @fp @fp.result end end define_aggregator(handler.name, proxy.new(handler.new)) self end
Creates a new function for use in SQL statements. It will be added as
name
, with the given arity
. (For variable arity
functions, use -1 for the arity.)
The block should accept at least one parameter–the FunctionProxy instance that wraps this function invocation–and any other arguments it needs (up to its arity).
The block does not return a value directly. Instead, it will invoke the
FunctionProxy#set_result method on the func
parameter and
indicate the return value that way.
Example:
db.create_function( "maim", 1 ) do |func, value| if value.nil? func.result = nil else func.result = value.split(//).sort.join end end puts db.get_first_value( "select maim(name) from table" )
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 313 def create_function name, arity, text_rep=Constants::TextRep::ANY, &block define_function(name) do |*args| fp = FunctionProxy.new block.call(fp, *args) fp.result end self end
Define an aggregate function named name
using the object
aggregator
. aggregator
must respond to
step
and finalize
. step
will be
called with row information and finalize
must return the
return value for the aggregator function.
Source: show
static VALUE define_aggregator(VALUE self, VALUE name, VALUE aggregator) { sqlite3RubyPtr ctx; int arity, status; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); arity = sqlite3_obj_method_arity(aggregator, rb_intern("step")); status = sqlite3_create_function( ctx->db, StringValuePtr(name), arity, SQLITE_UTF8, (void *)aggregator, NULL, rb_sqlite3_step, rb_sqlite3_final ); rb_iv_set(self, "@agregator", aggregator); CHECK(ctx->db, status); return self; }
Define a function named name
with args
. The
arity of the block will be used as the arity for the function defined.
Source: show
static VALUE define_function(VALUE self, VALUE name) { sqlite3RubyPtr ctx; VALUE block; int status; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); block = rb_block_proc(); status = sqlite3_create_function( ctx->db, StringValuePtr(name), rb_proc_arity(block), SQLITE_UTF8, (void *)block, rb_sqlite3_func, NULL, NULL ); CHECK(ctx->db, status); return self; }
Enable or disable extension loading.
Source: show
static VALUE enable_load_extension(VALUE self, VALUE onoff) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); CHECK(ctx->db, sqlite3_enable_load_extension(ctx->db, (int)NUM2INT(onoff))); return self; }
Fetch the encoding set on this database
Source: show
static VALUE db_encoding(VALUE self) { sqlite3RubyPtr ctx; VALUE enc; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); enc = rb_iv_get(self, "@encoding"); if(NIL_P(enc)) { sqlite3_exec(ctx->db, "PRAGMA encoding", enc_cb, (void *)self, NULL); } return rb_iv_get(self, "@encoding"); }
Return an integer representing the last error to have occurred with this database.
Source: show
static VALUE errcode_(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); return INT2NUM((long)sqlite3_errcode(ctx->db)); }
Return a string describing the last error to have occurred with this database.
Source: show
static VALUE errmsg(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); return rb_str_new2(sqlite3_errmsg(ctx->db)); }
Executes the given SQL statement. If additional parameters are given, they are treated as bind variables, and are bound to the placeholders in the query.
Note that if any of the values passed to this are hashes, then the key/value pairs are each bound separately, with the key being used as the name of the placeholder to bind the value to.
The block is optional. If given, it will be invoked for each row returned by the query. Otherwise, any results are accumulated into an array and returned wholesale.
See also execute2, query, and execute_batch for additional ways of executing statements.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 107 def execute sql, bind_vars = [], *args, &block # FIXME: This is a terrible hack and should be removed but is required # for older versions of rails hack = Object.const_defined?(:ActiveRecord) && sql =~ /^PRAGMA index_list/ if bind_vars.nil? || !args.empty? if args.empty? bind_vars = [] else bind_vars = [nil] + args end warn("#{caller[0]} is calling SQLite3::Database#execute with nil or multiple bind params without using an array. Please switch to passing bind parameters as an array. ") if $VERBOSE end prepare( sql ) do |stmt| stmt.bind_params(bind_vars) if type_translation stmt = ResultSet.new(self, stmt).to_a end if block_given? stmt.each do |row| if @results_as_hash h = Hash[*stmt.columns.zip(row).flatten] row.each_with_index { |r, i| h[i] = r } yield h else yield row end end else if @results_as_hash stmt.map { |row| h = Hash[*stmt.columns.zip(row).flatten] row.each_with_index { |r, i| h[i] = r } # FIXME UGH TERRIBLE HACK! h['unique'] = h['unique'].to_s if hack h } else stmt.to_a end end end end
Executes the given SQL statement, exactly as with execute. However, the first row returned (either via the block, or in the returned array) is always the names of the columns. Subsequent rows correspond to the data from the result set.
Thus, even if the query itself returns no rows, this method will always return at least one row–the names of the columns.
See also execute, query, and execute_batch for additional ways of executing statements.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 170 def execute2( sql, *bind_vars ) prepare( sql ) do |stmt| result = stmt.execute( *bind_vars ) if block_given? yield stmt.columns result.each { |row| yield row } else return result.inject( [ stmt.columns ] ) { |arr,row| arr << row; arr } end end end
Executes all SQL statements in the given string. By contrast, the other means of executing queries will only execute the first statement in the string, ignoring all subsequent statements. This will execute each one in turn. The same bind parameters, if given, will be applied to each statement.
This always returns nil
, making it unsuitable for queries that
return rows.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 191 def execute_batch( sql, bind_vars = [], *args ) # FIXME: remove this stuff later unless [Array, Hash].include?(bind_vars.class) bind_vars = [bind_vars] warn("#{caller[0]} is calling SQLite3::Database#execute_batch with bind parameters that are not a list of a hash. Please switch to passing bind parameters as an array or hash. ") if $VERBOSE end # FIXME: remove this stuff later if bind_vars.nil? || !args.empty? if args.empty? bind_vars = [] else bind_vars = [nil] + args end warn("#{caller[0]} is calling SQLite3::Database#execute_batch with nil or multiple bind params without using an array. Please switch to passing bind parameters as an array. ") if $VERBOSE end sql = sql.strip until sql.empty? do prepare( sql ) do |stmt| # FIXME: this should probably use sqlite3's api for batch execution # This implementation requires stepping over the results. if bind_vars.length == stmt.bind_parameter_count stmt.bind_params(bind_vars) end stmt.step sql = stmt.remainder.strip end end nil end
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 388 def finalize super(@ctx) end
A convenience method for obtaining the first row of a result set, and discarding all others. It is otherwise identical to execute.
See also get_first_value.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 273 def get_first_row( sql, *bind_vars ) execute( sql, *bind_vars ) { |row| return row } nil end
A convenience method for obtaining the first value of the first row of a result set, and discarding all other values and rows. It is otherwise identical to execute.
See also get_first_row.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 283 def get_first_value( sql, *bind_vars ) execute( sql, *bind_vars ) { |row| return row[0] } nil end
Interrupts the currently executing operation, causing it to abort.
Source: show
static VALUE interrupt(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); sqlite3_interrupt(ctx->db); return self; }
Obtains the unique row ID of the last row to be inserted by this Database instance.
Source: show
static VALUE last_insert_row_id(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); return LL2NUM(sqlite3_last_insert_rowid(ctx->db)); }
Loads an SQLite extension library from the named file. Extension loading must be enabled using db.enable_load_extension(1) prior to calling this API.
Source: show
static VALUE load_extension(VALUE self, VALUE file) { sqlite3RubyPtr ctx; int status; char *errMsg; VALUE errexp; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); status = sqlite3_load_extension(ctx->db, RSTRING_PTR(file), 0, &errMsg); if (status != SQLITE_OK) { errexp = rb_exc_new2(rb_eRuntimeError, errMsg); sqlite3_free(errMsg); rb_exc_raise(errexp); } return self; }
Returns a Statement object representing the given SQL. This does not execute the statement; it merely prepares the statement for execution.
The Statement can then be executed using SQLite3::Statement#execute.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 82 def prepare sql stmt = SQLite3::Statement.new( self, sql ) return stmt unless block_given? begin yield stmt ensure stmt.close end end
This is a convenience method for creating a statement, binding paramters to it, and calling execute:
result = db.query( "select * from foo where a=?", 5 ) # is the same as result = db.prepare( "select * from foo where a=?" ).execute( 5 )
You must be sure to call close
on the ResultSet instance that is returned, or you could
have problems with locks on the table. If called with a block,
close
will be invoked implicitly when the block terminates.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 242 def query( sql, bind_vars = [], *args ) if bind_vars.nil? || !args.empty? if args.empty? bind_vars = [] else bind_vars = [nil] + args end warn("#{caller[0]} is calling SQLite3::Database#query with nil or multiple bind params without using an array. Please switch to passing bind parameters as an array. ") if $VERBOSE end result = prepare( sql ).execute( bind_vars ) if block_given? begin yield result ensure result.close end else return result end end
Rolls the current transaction back. If there is no current transaction,
this will cause an error to be raised. This returns true
, in
order to allow it to be used in idioms like abort? and rollback or
commit
.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 511 def rollback execute "rollback transaction" @transaction_active = false true end
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 384 def step( *args ) super(@ctx, *args) end
Returns the total number of changes made to this database instance since it was opened.
Source: show
static VALUE total_changes(VALUE self) { sqlite3RubyPtr ctx; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); return INT2NUM((long)sqlite3_total_changes(ctx->db)); }
Installs (or removes) a block that will be invoked for every SQL statement
executed. The block receives one parameter: the SQL statement executed. If
the block is nil
, any existing tracer will be uninstalled.
Source: show
static VALUE trace(int argc, VALUE *argv, VALUE self) { sqlite3RubyPtr ctx; VALUE block; Data_Get_Struct(self, sqlite3Ruby, ctx); REQUIRE_OPEN_DB(ctx); rb_scan_args(argc, argv, "01", &block); if(NIL_P(block) && rb_block_given_p()) block = rb_block_proc(); rb_iv_set(self, "@tracefunc", block); sqlite3_trace(ctx->db, NIL_P(block) ? NULL : tracefunc, (void *)self); return self; }
Begins a new transaction. Note that nested transactions are not allowed by SQLite, so attempting to nest a transaction will result in a runtime exception.
The mode
parameter may be either :deferred
(the
default), :immediate
, or :exclusive
.
If a block is given, the database instance is yielded to it, and the transaction is committed when the block terminates. If the block raises an exception, a rollback will be performed instead. Note that if a block is given, commit and rollback should never be called explicitly or you’ll get an error when the block terminates.
If a block is not given, it is the caller’s responsibility to end the transaction explicitly, either by calling commit, or by calling rollback.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 478 def transaction( mode = :deferred ) execute "begin #{mode.to_s} transaction" @transaction_active = true if block_given? abort = false begin yield self rescue ::Object abort = true raise ensure abort and rollback or commit end end true end
Returns true
if there is a transaction active, and
false
otherwise.
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 518 def transaction_active? @transaction_active end
Return the type translator employed by this database instance. Each database instance has its own type translator; this allows for different type handlers to be installed in each instance without affecting other instances. Furthermore, the translators are instantiated lazily, so that if a database does not use type translation, it will not be burdened by the overhead of a useless type translator. (See the Translator class.)
Source: show
# File req/sqlite3/lib/sqlite3/database.rb, line 65 def translator @translator ||= Translator.new end


About The Nath
Scott is a web developer and sometime actor living in Brooklyn.
Scott is a web developer and sometime actor living in Brooklyn.
Scott has a bunch of sites he owns. They generally look terrible and use bad code. He has allowed us to list a couple anyway.
Scott Nath had a HUGE career as an actor! You can check it out right here!


As parking always costs a lot, especially in metropolis, so people prefer riding bikes nowadays. We collected the bike rental data in Washington D.C from Kaggle and created this web page to illustrate different factors that would affect the bike rentals.
Drag the slider to view bike rentals by hour!
Change the weekdays of interest by clicking the text at the bottom!
**Specify a range of time that you are interested in(1/2011~12/2012).
Click the little circle to view count number!
Three factors are discussed here, temperature, humidity, windspeed.
To make the linear model better fit, average number of count is displayed vs the three factors.
Select the factor and visualization type you like from the drop down menu!
Apparently, people would choose to ride to work or back home in warmer season and sunny days.
To maintain good visualization, we plot both average bike rentals and the whole data.
Click the button to view the graph you prefer!


Gesaka Chacha stands out in a group of community members assembled at a chief’s camp to discuss issues about female genital mutilation (FGM).....Read More
Twelve years letter I am still learning how to live with the scars of the cut.Still fresh in my memory is that fateful day in December when it all happened....Read More
FGM- the Female Genital Mutilation Network
- tracks these dangerous acts around the world. The project helps define how much occurs in various regions by placing them on a five-point scale that ranges from low to very high.
Very low: Up to 2.8 percent of women have undergone any form of FGM
Low: Between 2.9 and 11 percent of women have undergone of FGM
Medium: Between 11.2 and 31.9 percent of women have undergone
High: Between 32.2 and 45 percent of women have undergone
Very High: Up to 76.6 percent of women have undergone.


We’ll be back soon! Sorry for the inconvenience. We're performing maintenance and should be back shortly. — BC Mine Information Team


WENDY VALLADARES
FRONT-END DEVELOPER
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Animal Trading Card
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About Site
This site is both a collection of all the work I have put into my prog 109 class, and the final form of my midterm project, which details the functions and importance of Paperclips in history.
About Me
My name is Sky Pierce, I come from a small coastal town called Gig Harbor, but moved to a dorm on campus about two months ago to hone and develop my childhood interests into a college degree.
I really hope to broaden my technological horizons, take my sloppy self taught impressions about coding and computer languages all around, and carve out a formal practiced understanding of the basics.
I enjoy the idea of everything about computer manipulation, from simple webpage design, to complex topics like machine learning, or game development.
I also enjoy watching "The Office" playing video games, writing short stories, and running.
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Week 9: Complete list of high-school football scores from around Washington
by Associated Press staffFriday’s Scores
Arlington 63, Meadowdale 42
Asotin 14, Lind-Ritzville/Sprague 13
Auburn Riverside 59, Todd Beamer 9
Ballard 54, Ingraham 3
Bellarmine Prep 31, Emerald Ridge 0
Bellevue 53, Mercer Island 14
Bonney Lake 19, Mount Tahoma 0
Camas 28, Union 14
Cascade (Leavenworth) 33, Cashmere 28
Cedar Park Christian (Bothell) 14, Sultan 7
Central Valley 51, University 0
Charles Wright Academy 42, Bellevue Christian 0
Cheney 17, Pullman 9
Chewelah 35, Davenport 15
Chiawana 34, Pasco 0
Chief Sealth 55, Nathan Hale 34
Clarkston 35, Columbia River 20
Columbia (Burbank) 51, White Swan 24
Columbia (White Salmon) 50, Stevenson 7
Colville 49, Freeman 33
Connell 30, River View 8
DeSales 64, St. John-Endicott/Lacrosse 6
Evergreen Lutheran 58, Rainier Christian 36
Fife 50, Clover Park 21
Franklin Pierce 27, Eatonville 25
Friday Harbor 42, Granite Falls 0
Gig Harbor 6, Central Kitsap 0
Glacier Peak 17, Mount Vernon 14
Interlake 36, Coupeville 7
Kalama 52, Toutle Lake 8
Kamiak 37, Jackson 7
Kamiakin 40, Hermiston, Ore. 7
Kelso 42, Hudson’s Bay 14
Kennedy 42, Federal Way 28
King’s Way Christian School 42, Seton Catholic 7
Kittitas 30, Liberty Christian 0
La Center 42, Castle Rock 39
La Salle 49, Naches Valley 7
Lake Stevens 62, Mariner 0
Lake Washington 42, Juanita 14
Lakes 55, Wilson 3
Liberty (Spangle) 61, Reardan 13
Lincoln 35, Bethel 21
Mark Morris 28, Woodland 0
Marysville-Getchell 44, Lynnwood 18
Mead 21, Ferris 16
Monroe 51, Cascade (Everett) 6
Montesano 49, Elma 7
Mt. Rainier 27, Enumclaw 6
Napavine 51, Rainier 6
Neah Bay 54, Lummi 42
Newport 21, Lakeside (Nine Mile Falls) 14
North Kitsap 28, Olympic 14
Northwest Christian (Colbert) 17, Kettle Falls 0
Oak Harbor 48, Everett 6
Olympia 7, Curtis 6
Omak 41, Okanogan 13
Pe Ell/Willapa Valley 48, Ilwaco 8
Pomeroy 62, Colton 0
Port Angeles 25, North Mason 20
Port Townsend 24, Chimacum 22
Prairie 42, Evergreen (Vancouver) 14
Puyallup 59, Rogers (Puyallup) 13
Raymond 21, Vashon Island 7
Redmond 49, Newport-Bellevue 14
Republic 52, Curlew 6
River Ridge 47, Highline 27
Riverside 28, Chelan 21
Royal 76, College Place 7
Sedro-Woolley 24, Cedarcrest 7
Sequim 36, Bremerton 21
Shelton 24, North Thurston 20
Skyview 56, Heritage 17
South Kitsap 28, Battle Ground 24
Spanaway Lake 44, Stadium 8
Springdale 42, Wellpinit 34
Squalicum 28, Edmonds-Woodway 7
Steilacoom 49, Orting 7
Tonasket 35, Oroville 16
Tri-Cities Prep 27, Dayton-Waitsburg 15
Tumwater 62, Centralia 7
W. F. West 56, Aberdeen/Wishkah Valley Co-op 28
Warden 29, Kiona-Benton 18
Washougal 51, R.A. Long 6
Wenatchee 41, Walla Walla 20
West Valley (Spokane) 55, East Valley (Spokane) 6
West Valley (Yakima) 57, Eisenhower 12
Winlock 53, Wahkiakum 7
Woodinville 21, Skyline 14
Yakama Tribal 50, Touchet 20
Thursday’s Scores
Black Hills 57, Rochester 19
Bothell 47, Eastlake 24
Gonzaga Prep 21, Lewis and Clark 20
Graham-Kapowsin 28, Sumner 14
Kentlake 58, Kent Meridian 0
Lynden Christian 42, Meridian 0
North Central 26, Rogers (Spokane) 3
Peninsula 49, Capital 7
Yelm 35, Timberline 30
Associated Press staff


This example demonstrates grouping elements into a unit. Each SMU is grouped into a unit which is then placed where needed.
Shows creation of elements within for loop, angled elements with automatic label positioning, and colors.
Internal schematic of a 741 IC.
Turn on Matplotlib's XKCD mode for some hand-drawn looks!


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Web Latency Benchmark: Hardware test
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Use any medium you want to make a card. It can be a drawing, a letter, or even a few nice words. You don't have to be Picasso or Shakespeare to send a touching message - it's the thought that counts!
Go to our Submit link in the header and fill out the fields on the page!
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Warhol & Basquiat. Buuel & Dal. Rauschenberg & Johns. There are countless examples of artists collaborating to bring a shared creative vision to life. So we wondered: Could technology help bring together two artists who might not otherwise meet? What would they createif their canvas were a spreadsheet? And how could we celebrate and share their work of art with the world?
In partnership with
Refinery29
, a lifestyle digital media company, we linked up with renowned illustrators
Marina Esmeraldo
in Barcelona, and
Mallory Heyer
in NYC. We gave them a simple creative assignmentto break the gridwhich literally can mean pushing the grid of
Google Sheets
to its limits, but also taps into the idea of supporting and celebrating women globally who break free of confined roles and ways of thinking, which is core to Refinery29's mission.
Marina and Mallory connected a handful of times on Google Hangouts to plan and sketch out ideas, and creatively hack Sheets in order to make art: resizing cells into thousands of pixel-like squares, merging cells to create color blocks, creating vibrant color gradients with
conditional formatting
and cell values, and other cool things we had no idea you could do with Sheets.
The
result
was a bright, beautiful design that celebrates the diversity and strength of women, and we wanted to share their finished project in a BIG way.
The final step was to convert Marina and Mallorys final piece from the cells of a spreadsheet to the bricks of a giant wallto go from Sheets to the streets.
After hand-mixing each of the colors and prepping the artwork for large-scale painting, Colossal spent five days painting each cell, letter, and gradient by hand, to create a 13 x 34 mural of the
spreadsheet
.
And thats how art was #madewithGoogleSheets.
To see it for yourself, check out Marina & Mallorys spreadsheet or head to
Bogart & Thames
in Brooklyn to visit the wall in person (until August 14). We're delighted by the creativity and imagination brought about by artistic collaboration, and proud to be associated with the works inspirational message supporting strong women everywhere.
Posted by Michael Bolognino, Product Marketing Manager
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8.4 Image Coordinate Transform
Image re-sampling assumes reconstruction of a continuous approximation of the original non-sampled image by means of interpolation of available image samples to obtain samples “in-between” the available ones. The most feasible is interpolation by means of digital filtering implemented as digital convolution. A number of convolutional interpolation methods are known, beginning from the simplest and the least accurate nearest neighbor and linear (bilinear, for 2D case) interpolations to more accurate cubic (bicubic, for 2D case) and higher order spline methods.
Discrete sinc-interpolation is the gold standard for re-sampling sampled data.
The nearest neighbor algorithm selects the value of the nearest point and does not consider the values of neighboring points at all, yielding a piecewise-constant interpolant. The point spread function of the nearest neighbor interpolation (in 1D):
Equation 8‑1
is illustrated at Figure 8‑1.
Figure 8‑1 Nearest Neighbor interpolation kernel
The nearest neighbor interpolation can be computed by:
Equation 8‑2
Where:
is the input signal; a discrete delta function with length of L; – is the convolution operation; – is a signal with L coefficients, all equal to 1; is the Kronecker product.
The linear interpolation algorithm uses the two nearest neighbors of the current point to calculate it value by multiplying each of those points with weights inverse proportionate to their distance from the current point. An example for linear interpolation is given at Figure 8‑2. The value of y at point x is calculated as a weighted sum of its nearest neighbors:
Equation 8‑3
Linear interpolation is special case of polynomial interpolation with n = 1.
Figure 8‑2: Linear interpulation example. The value of y at point x is calculated as a weighted sum of , where the weights are poportional to the distance of from .
The point spread function of the nearest neighbor interpolation (in 1D)
Equation 8‑4
is illustrated at Figure 8‑3:
Figure 8‑3: Linear interpolation kernel
Linear interpolation is special case of polynomial interpolation with n = 1.
The linear interpolation can be computed by:
Equation 8‑5
Where:
is the input signal; a discrete delta function with length of L; – is the convolution operation; – is a signal with L coefficients, all equal to 1; is the Kronecker product.
The Bi-cubic interpolation (aka cubic Hermite spline) is composed of piecewise cubic polynomials defined on the subintervals.
Outside this interval, the interpolation kernel is zero. As a consequence of this condition, the number of data samples used to evaluate the interposition function is 4. This condition, along with the continuous and continuous first derivative demand, the requirement of the kernel to be symmetric, and the conditions, result in a kernel on form:
Equation 8‑6
Where is the distance of the current calculated sample form its nearest neighbors.
If the interpolation function g(x) is to agree with the first three terms of the Taylor series expansion for (where is the continues function which we wish to estimate its values from a sampled version of) then the parameter must be equal to -0.5.
This leads to one of the point spread function (suggested by Keys [2]) of the bi-cubic interpolation (in 1D) is illustrated at Figure 8‑4
Equation 8‑7
Figure 8‑4 Cubic interpolation kernel
Cubic interpolation is special case of polynomial interpolation with n = 2.
The Cubic interpolation can be computed by:
Equation 8‑8
Where:
is the input signal; a discrete delta function with length of L; – is the convolution operation; – is a signal with L coefficients, all equal to 1; is the Kronecker product.
Sinc subsampling interpolation relays on the discrete frequency response of perfect shifting filter.
For zoom factor L, signal/image zooming can be implemented through generating subsequently computed L-1 signal/image copies shifted by corresponding multiple of 1/L shifts:
,
Equation 8‑9
Where is the signal sampling interval , and are direct and inverse -point Fast Fourier transforms, symbolizes component-wise (Hadamard) matrix product elements of two arrays and is the discrete frequency response coefficients of the perfect -shifting filter which is defined by:
For odd number of signal samples:
And for even number of signal samples:
Where can be: , , , each defining a different interpolation kernel.
Applying to Equation 8‑10 and Equation 8‑11 inverse discrete Fourier transform one can obtain that, for odd , point spread function of the perfect shifting filter defined by Equation 8‑10 is:
8.1.1Equation 8‑12
and for even , Case 0 and Case 2, perfect shifting filter point spread functions are
Equation 8‑13
and
Equation 8‑14
correspondingly.
Where:
is the discrete sinc-function: ,
is the general discrete sinc-function:
Case_1/2 is a combination of Case_0 and Case_2:
Equation 8‑15
Equation 8‑16
Numerical interpolation using discrete sinc-functions (sincd-functions) given by the equations above as the interpolation kernel is called discrete sinc-interpolation.
The sinc interpolation PSF is illustrated at Figure 8‑5 and Figure 8‑6.
Figure 8‑5: Sinc interpolation kernel
Figure 8‑6: Sinc interpolation kernel in the range of [-0.5:0.5]
Figure 8‑7 Frequency response comparison of nearest neighbor (FR_NN), linear (FR_lin), cubic (FR_spl), and sinc (FR_scincd) interpulations kernels.
Plots of frequency responses of the methods clearly reveal major drawback of the traditional interpolation methods: they tend to substantially attenuate high frequency signal components within the signal base band (frequency interval in Figure 8‑7 and introduce substantial aliasing frequency components outside this interval (in the case of signal sub-sampling). In imaging, this tendency results in image blurring that can heavily worsen visual image quality and its applicability for further analysis, for instance object recognition, target location and alike.
The “signal zoom” experiment compare 6 different interpolation methods applied on a 1D signal.
The methods compared are nearest neighbor, bilinear, bi-cubic, 3 variants of sinc interpolation.
Figure 8‑8: "Signal Zoom". Top plot is the input signal ( function). The black arrow illustrates the section of the signal to zoom. Second from the top is the nearest neighbor interpolation of the signal. Third from the top is the linear interpolation of the signal. Fourth from the top is the cubic interpolation of the signal. Fifth from the top is the discrete sinc interpolation of the signal using. Sixth from the top is the discrete sinc interpolation of the signal using. Seventh from the top is the discrete sinc interpolation of the signal using. Window size is 29, zoom factor is 10.
The example shown at Figure 8‑8 is the impulse response of the convolution interpolation kernels. It can be seen that the kernels are similar to kernel images presented at 9.1.1.
Figure 8‑9: "Signal Zoom" result number 2. Top plot is the input signal. The black arrow illustrates the section of the signal to zoom. Second from the top is the nearest neighbor interpolation of the signal. Third from the top is the linear interpolation of the signal. Fourth from the top is the cubic interpolation of the signal. Fifth from the top is the discrete sinc interpolation of the signal using. Sixth from the top is the discrete sinc interpolation of the signal using. Seventh from the top is the discrete sinc interpolation of the signal using. Window size is 46, zoom factor is 3.
Figure 8‑9 illustrates the disadvantages of the nearest neighbor interpolation kernel – the originally smooth signal interpreted as a stairs function for the nearest neighbor interpolation, while all the other interpolation kernels seem to give similar results.
The 2D Nearest neighbor interpolation, which Like its 1D counterpart, selects the value of the nearest point and does not consider the values of neighboring points at all, yielding a piecewise-constant interpolant.
The bilinear interpolation, which is the 2D counterpart of the 1D linear-interpolation. It calculates the current pixel value as a weighted sum of its 4 nearest neighbors, and can be calculated as a 2 passes of 1D linear interpolation – one along the y axis, and the other along the x axis of the result.
The bi-cubic interpolation, which is the 2D counterpart of the 1D cubic-interpolation. It calculates the current pixel value as a weighted sum of its 16 nearest neighbors, and can be calculated as a 2 passes of 1D cubic interpolation – one along the y axis, and the other along the x axis of the result.
And the 2D sinc interpolation, which is the 2D counterpart of the 1D sinc interpolation. It can be calculated as a 2 passes of 1D sinc interpolation – one along the y axis, and the other along the x axis of the result.
All of those kernels point spread function can be represented as multiplication of 1D version of the point spread functions.
Image zoom experiment compares 4 different 2D resampling algorithms which are 2D variants of the 1D interpolation algorithms introduced at signal zoom.
Figure 8‑10: "Image Zoom" result number 2. Top plot is the input signal. The black arrow illustrates the section of the signal to zoom. Second from the top is the nearest neighbor interpolation of the signal. Third from the top is the linear interpolation of the signal. Fourth from the top is the cubic interpolation of the signal. Fifth from the top is the discrete sinc interpolation of the signal using. Sixth from the top is the discrete sinc interpolation of the signal using. Seventh from the top is the discrete sinc interpolation of the signal using. Window size is 46, zoom factor is 3.
Figure 8‑10 is another illustration of the disadvantages of the nearest neighbor interpolation kernel in comparison to other acceptable results.
Rotation of a 2D coordinate system by an angle as a geometrical transformation of signal co-ordinates can be described as a multiplication of signal coordinate vector by a rotation matrix:
Equation 8‑17
In computers, physical coordinates are represented, given sampling intervals , by integer indices of pixels :
Equation 8‑18
and the rotation matrix is applied to the vector of indices:
Equation 8‑19 describes the resampling rule that should be applied to input image pixel indices to generate indices of its rotated copy.
In practice, the calculation of pixel values of the rotated image is calculated in using backward mapping, i.e. for each pixel coordinate (k,l) in the rotated image, its location in the original image is calculated by the inverse of rotation matrix:
Equation 8‑20
And then the neighboring pixels are used for calculation of the pixel value according to the interpolation kernel.
The three pass rotation algorithm uses factorization of the rotation matrix in order to reduce the computational complexity of the rotation transform. The rotation matrix can be factorized into a product of three matrices each of which modifies only one co-ordinate:
Equation 8‑21
It carries out, on each of three passes, only shifts along one of the co-ordinates: along rows on the first pass, along columns on the second pass and again along rows on the third pass as it is illustrated in Figure 8‑11.
Figure 8‑11 illustration of three pass rotation
Specifically, in rotation of an image of pixels (, ) around point () on the first pass -th row is shifted by , on the second pass -th column is shifted by and on the third pass again -th row is shifted by . Above described DFT or DCT based signal fractional shift algorithms are ideally suited for performing these shifts.
The “image Rotation” experiment compares 4 methods of rotations. Backward mapping using nearest neighbor interpolation, backward mapping using nearest neighbor interpolation, Backward mapping using nearest neighbor interpolation, and three pass rotation uses sinc interpolation.
The image is rotated times, where RotationAngle is a given parameter, to complete full 360 degree rotation. It does so for times, which is another given parameter.
Figure 8‑12: "Image Rotation". Top left is the test image. Top middle is nearest neighbor interpolation result of the rotation. Top right is the bilinear interpolation result of the rotation. Bottom middle is the bi-cubic interpolation result of the rotation. Bottom right is the sinc interpolation result of the rotation. Rotation angle is , and is 1 (which means each image rotated in for 20 times).
Figure 8‑12 illustrates the huge advantage of the 3-step rotation algorithm in comparison of the standard coordinate transform and then interpolation. While all of the other (nearest neighbor, bilinear, bicubic) have a strong degradation effect on the interpolated image, 1D sinc-shift with each cycle, preserve almost perfectly the original image, and if comes a need to interpolate again the result, it can be done with similar result as if the second interpolation was performed on the original image.
The “Image Coordinate Transform” experiment is an open experiment which allows warping the image according to any linear coordinate transform desired. The result of the coordinate transform in interpolated using 4 interpolation method for comparison: nearest neighbor, bi-linear, bi-cubic and sinc interpolations. The equations for coordinate transform are controlled by the user, and the center reference point is determined by clicking at the point in the test image.
Figure 8‑13: "Image Coordinate Transform". Top left is the test image. Top middle is nearest neighbor interpolation result of the coordinate transform. Top right is the bilinear interpolation result of the coordinate transform. Bottom middle is the bi-cubic interpolation result of the coordinate transform. Bottom right is the sinc interpolation result of the coordinate transform. Coordinate transformed according to
and .
The “Image Profile” experiment is an open experiment which allows examining different image profiles along a straight line. The result profile is interpolated using 4 interpolation method for comparison: nearest neighbor, bi-linear, bi-cubic and sinc interpolations.
Figure 8‑14: "Image Profile". Left is the test image. interpulated profile is marked by a red line. Top right plot is the nearest neighbor interpulation of the profile. Second from the top right plot is the bilinear interpulation of the profile. Third from the top right plot is the bi-cubic interpulation of the profile. Fourth from the top right plot is the discrete sinc interpulation of the profile. All interpulations results are 1024 length, and initial profile was from point (173, 46) to (146, 58).
|
[1] |
L. P. Yaroslavsky, "PERFECT RESAMPLING FILTER," in Theoretical Foundations of Digital Imaging Using MATLAB, CRC Press, 2012, pp. 294-310. |
|
[2] |
R. Keys, "Cubic convolution interpolation for digital image processing," IEEE Transactions on Acoustics, Speech, and Signal Processing , vol. 6, pp. 1153-1160, 1981. |


My life story? My journey has been a long one. BUT I've learned a lot. Who hasn't? I've learned that I have passion when it comes to helping people. I'm guessing it comes from being raised by the kindest mother. I want to help people. Throughout my life I've tinkered around with coding. I took several online courses to be introduced to the basics.
Most of us like to kick back and relax. Right? Well, there was a particular day where I was relaxing and I started day dreaming about being able to develop what my mind could create. I started thinking about the video games I play. I started combining all sorts of different ideas when it came to VR. I decided during the first day of day dreaming about creating whats in my head that I wanted to learn to code.
Learning is power. When I say POWER, I think about KNOWLEDGE. Nerds rule the world am I right?


Twitter Bootstrap is a website where Style sheets and more is already done for you, it makes things that are complex to some people much more easier. Twitter Bootstrap save coders alot of time by making style sheets for you because they can be very time cosuming.


CLERKS
A film review by Chad Polenz
Copyright 1997 Chad Polenz
**** 1994, R, 92 minutes [1 hour, 32 minutes] [comedy] starring: Brian O'Halloran (Dante), Jeff Anderson (Randal), Marilyn Ghiglotti (Veronica), Jason Mewes (Jay), Lisa Spoonauer (Caitlin), produced by Kevin Smith, Scott Mosier, written and directed by Kevin Smith.
"Clerks" is really a landmark in film history, although I don't think anyone will recognize it as such. This is a film that cost about $25,000 to make, yet it is much more enjoyable and better written than most commercial films costing a thousand times as much. This is a film about Generation X slackers hanging out in a convenient store talking about their lives and little idiosyncrasies in a way that is so mundane, yet so unique and sometimes vulgar, but still brilliantly hysterical.  Many non-Gen Xers may find it rather offensive and unrealistic at times, but those of us who are essentially the same as the characters in the film can relate all too well.
This is a film about two buddies hanging out in their place of employment. There is Dante (O'Halloran), the clerk who tries to do his job and get on with his life - "I don't bother them and they don't bother me." Dante hates his life but somehow finds a way to deal with it, he comes to work and does his job just hoping that tomorrow will be a better day. And then there is Randal (Anderson), the rude, but very funny slacker who represents the attitude that we Gen Xers think, but don't say aloud. He speaks his mind, he poses questions that we don't really think about (one involving an extremely detailed, but very hilarious analysis, of the "Star Wars" films), he also refuses to be nice to customers, nor swallow his pride just for the sake of etiquette and courtesy.
Dante and Randal are both 22, work full time at minimum wage jobs serving the public, are not in school and may never go back. They hate everyone and everything, and this tension is often relieved on their customers. The entire atmosphere of the film is so campy and almost "realistic" in a way, as it was shot in a very grainy black and white and does not feature a celebrity, which only makes the tone more suited for the story. These bare essentials are what force us to pay attention to the basic elements of theme, mood, and dialogue.
I can relate to this film so well because I have had experience in very similar occupations. There are conversations in this movie that are almost word-for-word duplications of conversations I have had with co-workers.  There is a very funny scene in which Randal beats a customer at their own game, as he blatantly admits that he doesn't care for them and that it feels good to point out the shortcomings of others, ahh... how true that is. Even if you are not, or never have been in a position like this, it is still hysterical because of the genius knack of dialogue that Kevin Smith has, and his sense of character for Gen Xers.
Dante and his girlfriend Veronica (Ghiglotti) constantly argue over the importance of college, the differences in the requirements to make men and women come to orgasm, and deciding who and what is most important in a relationship. Specific examples are not given, but the entire atmosphere of the film really gives one the sense of what modern relationships are based on, that is, nothing.
At some points "Clerks" can get rather crude, but the dialogue did not seem unbelievable to me. Even though the actors are not professionals, they are able to deliver a credible and very entertaining performance. There are many scenes where it is obvious that they are reading cue cards, one scene even shows the actor admitting that he messed up the line, but the improvisation is still funny and does not break our concentration at all.
I still think that "Clerks" is truly a landmark of sorts, as it is somewhat following a trend of telling funny stories about "nothing" as this story is the epitome of that idea and does not become commercial at all, as it relies upon its originality and comical genius to provide for a very funny, very entertaining, and very unique film unlike any you will ever see. Kevin Smith has basically exploited my generation, and for that I thank him. [other films by Smith: "Mallrats"] (3/19/96) (12/18/96)
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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Related links: index of all rec.arts.movies.reviews reviews


This plugin allows you to create modals dynamically, without cluttering your source with static HTML for modals. Everything is created in JavaScript and fully customizable.
Download fileCode for the example above:
$.modal({ title: "Example title", content: "Here's some important message you must read.", buttons: [ { text: "Roger that", close: true } ] }).modal('show');
$.modal()
returns the actual HTML node for created modal so you can chain it with Bootstrap's .modal()
method to manipulate it.
| Name | type | default | description |
|---|---|---|---|
| title | string | "" | Title of the modal in .modal-header . |
| content | string | "" | Content of the modal, can be a HTML string. |
| header | boolean | true | Display the .modal-header . If hidden, title and .close button are invisible |
| footer | boolean | true | Display the .modal-footer . Please note that when false buttons will also not appear. |
| dispose | boolean | true | Remove the actual HTML element with modal on close. Set to false if you want to reuse the same modal multiple times. |
| buttons | array | [] | List of buttons to create in the modal. See the table below for button specific options. |
These options apply to objects in buttons
array.
| Name | type | default | description |
|---|---|---|---|
| text | string | "" | Text visible on the button. |
| href | string | "#" | Link used in the href attribute. |
| close | boolean | false | When true , pressing the button will also close the modal. Behind the scenes it adds data-dismiss="modal" . |
| classes | string | "" |
List of classes applied to the button HTML tag. For example, if you want a button to be primary and large, set it to: btn-primary btn-large .
btn class is applied by default so you don't have to add it here.
|
| html | string | "" | Custom HTML for the button. Use it if your button tag needs more tweaking. Remember that the text , href and classes options take precedence and can still modify the custom HTML. For example additional classes will be appended to the custom element. |
| click | function | undefined | Callback function fired when a button is clicked. |
Method with all options possible:
$.modal({ title: "Full example title", content: "
Rich content with some HTML tags here and there
", header: true, footer: true, dispose: true, buttons: [ { text: "Yup, I got it", href: "#", classes: "btn-primary", click: function(e) { alert("Seriously, I got it!"); } }, { text: "Get me out of here", href: "#", close: true }, { html: "Danger, custom button", text: "Achtung!", classes: "btn-large", click: function() { alert("Custom button"); } } ] }).modal('show');


Transitions
Predefined page & section transitions.
Ready to use out of the box.
Predefined page & section transitions.
Ready to use out of the box.
Transition guidelines:
<img src="photo.jpg" transition="fold-down"/>
Also, use configuration object to:
More pens:
Narrative demo Photo gallery


In a path based access control scheme, an attacker can traverse a path by providing relative path information. Therefore an attacker can use relative paths to access files that normally are not directly accessible by anyone, or would otherwise be denied if requested directly.
The user should be able to access a file that is not in the listed directory.


Create Project
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Select Organization
Business Group:
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Select Business Group
Environments:
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Save


Generally, you can enable or disable particular projects and images for particular users, but this requires
you to
be a project coordinator.
As a project coordinator you are able to view and alter access rights to the project and each image per user
and
authorize other users as project coordinator as well.
All project users are listed in a table in the page, and a short summary is displayed right above the table.
If there is just a single project coordinator in this project, the number is replaced with the name of that
user,
otherwise, hovering the number will display all coordinators of the project (also if they are on different pages
of the
user table).
User ID: the Cytomine user ID
Last Name: the user's last name
First Name: the user's first name
Username: the user's user name
Enabled: a flag indicating whether or not the user has access to this project on this IRIS host
Coordinator: a flag indicating whether or not the user is a coordinator of this project on this
IRIS host
Actions:
: this will open a modal dialog, displaying all images in the project, where you can enable and
disable each image for the user.
Hint: always try to refresh the table before
making changes!
Project Coordinator
In order to establish a person as a coordinator, select the user's check box in the column
Coordinator.
If you authorize someone as coordinator, the project will automatically be enabled for that user.
Moreover, the user will receive an email indicating that coordinator rights are now available for that
project.
Similarly, deselect the check box, if you want to revoke the user's rights as coordinator.
Please note: You cannot remove yourself as a project
coordinator.
Project Access
Project access is granted by selecting the user's check box in the column Enabled.
Disable the project for a user by deselecting the check box.
Please note: You cannot disable the project for yourself.
Image Access
Open the images for a user by selecting
from the table. This will open a modal dialog, where you can enable and disable the images using the check
box from the rightmost column.
The summary at the top of the table will be updated accordingly.
Labeling Progress Update/Synchronization
From the tabs, select Synchronization to view the corresponding settings.
Computing the labeling progress for each user in an image is a rather expensive operation and is just
executed automatically
at very specific moments during a workflow in the application.
Nevertheless, as a coordinator, you can trigger synchronization manually either for all users (using the big
red button ;-)) or for individual users by pressing
.
While synchronization is in progress, the buttons will be deactivated and become reactivated when the
procedure is finished.
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| I l@ve RuBoard |
On to the nitty-gritty. The first object type on our tour is Python numbers. In general, Python's number types are fairly typical and will seem familiar if you've used just about any other programming language in the past. Python supports the usual numeric types (integer and floating point), constants, and expressions. In addition, Python provides more advanced numeric programming support, including a complex number type, an unlimited precision integer, and a variety of numeric tool libraries. The next few sections give an overview of the numeric support in Python.
Among its basic types, Python supports the usual suspects: both integer and floating-point numbers, and all their associated syntax and operations. Like C, Python also allows you to write integers using hexadecimal and octal constants. Unlike C, Python also has a complex number type (introduced in Python 1.4), as well as a long integer type with unlimited precision (it can grow to have as many digits as your memory space allows). Table 2.2 shows what Python's numeric types look like when written out in a program (i.e., as constants).
|
Constant |
Interpretation |
|---|---|
|
1234, -24, 0 |
Normal integers (C longs) |
|
999999999999L |
Long integers (unlimited size) |
|
1.23, 3.14e-10, 4E210, 4.0e+210 |
Floating-point (C doubles) |
|
0177, 0x9ff |
Octal and hex constants |
|
3+4j, 3.0+4.0j, 3J |
Complex number constants |
By and large, Python's numeric types are straightforward, but a few are worth highlighting here:
Integers are written as a string of decimal digits. Floating-point numbers have an embedded decimal point, and/or an optional signed exponent introduced by an e or E. If you write a number with a decimal point or exponent, Python makes it a floating-point object and uses floating-point (not integer) math when it's used in an expression. The rules for writing floating-point numbers are the same as with C.
Plain Python integers (row 1) are implemented as C longs internally (i.e., at least 32 bits), and Python floating-point numbers are implemented as C doubles; Python numbers get as much precision as the C compiler used to build the Python interpreter gives to longs and doubles. On the other hand, if an integer constant ends with an l or L, it becomes a Python long integer (not to be confused with a C long) and can grow as large as needed.
The rules for writing hexadecimal (base 16) and octal (base 8) integers are the same as in C: octal constants start with a leading zero (0), and hexadecimals start with a leading 0x or 0X. Notice that this means you can't write normal base-ten integers with a leading zero (e.g., 01); Python interprets them as octal constants, which usually don't work as you'd expect!
Python complex constants are written as real-part + imaginary-part, and terminated with a j or J. Internally, they are implemented as a pair of floating-point numbers, but all numeric operations perform complex math when applied to complex numbers.
Besides the built-in number types shown in Table 2.2, Python provides a set of tools for processing number objects:
+, *, >>, **, etc.
pow, abs, etc.
rand, math, etc.
We'll meet all of these as we go along. Finally, if you need to do serious number-crunching, an optional extension for Python called Numeric Python provides advanced numeric programming tools, such as a matrix data type and sophisticated computation libraries. Because it's so advanced, we won't say more about Numeric Python in this chapter; see the examples later in the book and Appendix A. Also note that, as of this writing, Numeric Python is an optional extension; it doesn't come with Python and must be installed separately.
Perhaps the most fundamental tool that processes numbers is the expression : a combination of numbers (or other objects) and operators that computes a value when executed by Python. In Python, expressions are written using the usual mathematical notation and operator symbols. For instance, to add two numbers X and Y, we say X + Y, which tells Python to apply the + operator to the values named by X and Y. The result of the expression is the sum of X and Y, another number object.
Table 2.3 lists all the operator expressions available in Python. Many are self-explanatory; for instance, the usual mathematical operators are supported: +, -, *, /, and so on. A few will be familiar if you've used C in the past: % computes a division remainder, << performs a bitwise left-shift, & computes a bitwise and result, etc. Others are more Python-specific, and not all are numeric in nature: the is operator tests object identity (i.e., address) equality, lambda creates unnamed functions, and so on.
|
Operators |
Description |
|---|---|
|
Logical or ( y is evaluated only if x is false), anonymous function |
|
|
x and y |
Logical and (y is evaluated only if x is true) |
|
not x |
Logical negation |
|
sequence membership |
|
|
Bitwise or |
|
|
x ^ y |
Bitwise exclusive or |
|
x & y |
Bitwise and |
|
Shift x left or right by y bits |
|
|
Addition/concatenation, subtraction |
|
|
Multiplication/repetition, division, remainder/format |
|
|
Unary negation, identity, bitwise complement |
|
|
x[i], x[i:j], x.y, x(...) |
Indexing, slicing, qualification, function calls |
|
(...), [...], {...}, `...` |
Tuple, list, dictionary, conversion to string |
Table 2.3 is mostly included for reference; since we'll see its operators in action later, we won't describe every entry here. But there are a few basic points we'd like to make about expressions before moving on.
As in most languages, more complex expressions are coded by stringing together operator expressions in the table. For instance, the sum of two multiplications might be written as: A * B + C * D. So how does Python know which operator to perform first? When you write an expression with more than one operator, Python groups its parts according to what are called precedence rules, and this grouping determines the order in which expression parts are computed. In the table, operators lower in the table have higher precedence and so bind more tightly in mixed expressions. For example, if you write X + Y * Z, Python evaluates the multiplication first (Y * Z), then adds that result to X, because * has higher precedence (is lower in the table) than +.
If the prior paragraph sounded confusing, relax: you can forget about precedence completely if you're careful to group parts of expressions with parentheses. When you parenthesize subexpressions, you override Python precedence rules; Python always evaluates parenthesized expressions first, before using their results in enclosing expressions. For instance, instead of X + Y * Z, write (X + Y) * Z, or for that matter X + (Y * Z) to force Python to evaluate the expression in the desired order. In the former case, + is applied to X and Y first; in the latter, the * is performed first (as if there were no parentheses at all). Generally speaking, adding parentheses in big expressions is a great idea; it not only forces the evaluation order you want, but it also aids readability.
Besides mixing operators in expressions, you can also mix numeric types. For instance, you can add an integer to a floating-point number, but this leads to another dilemma: what type is the result—integer or floating-point? The answer is simple, especially if you've used almost any other language before: in mixed type expressions, Python first converts operands up to the type of the most complex operand, and then performs the math on same-type operands. Python ranks the complexity of numeric types like so: integers are simpler than long integers, which are simpler than floating-point numbers, which are simpler than complex numbers. So, when an integer is mixed with a floating-point, the integer is converted up to a floating-point value first, and then floating-point math yields the floating-point result. Similarly, any mixed-type expression where one operand is a complex number results in the other operand being converted up to a complex, and yields a complex result.
Although we're focusing on built-in numbers right now, keep in mind that all Python operators may be overloaded by Python classes and C extension types, to work on objects you implement. For instance, you'll see later that objects coded with classes may be added with + expressions, indexed with [i] expressions, and so on. Furthermore, some operators are already overloaded by Python itself: they perform different actions depending on the type of built-in objects being processed. For example, the + operator performs addition when applied to numbers, but (as we'll see in a moment) performs concatenation when applied to sequence objects such as strings and lists.[2]
[2] This is usually called polymorphism—the meaning of an operation depends on the type of objects being operated on. But we're not quite ready for object-oriented ideas like this yet, so hold that thought for now.
Perhaps the best way to understand numeric objects and expressions is to see them in action.
First of all, let's exercise some basic math: addition and division. In the following interaction, we first assign two variables (a and b) to integers, so we can use them later in a larger expression. We'll say more about this later, but in Python, variables are created when first assigned; there is no need to predeclare the names a and b before using them. In other words, the assignments cause these variables to spring into existence automatically.
% python >>> a = 3 # name created >>> b = 4
We've also used a comment here. These were introduced in Chapter 1, but as a refresher: in Python code, text after a # mark and continuing to the end of the line is considered to be a comment, and is ignored by Python (it's a place for you to write human-readable documentation for your code; since code you type interactively is temporary, you won't normally write comments there, but we've added them to our examples to help explain the code). Now, let's use our integer objects in expressions; as usual, expression results are echoed back to us at the interactive prompt:
>>> b / 2 + a # same as ((4 / 2) + 3) 5 >>> b / (2.0 + a) # same as (4 / (2.0 + 3)) 0.8
In the first expression, there are no parentheses, so Python automatically groups the components according to its precedence rules; since / is lower in Table 2.3 than +, it binds more tightly, and so is evaluated first. The result is as if we had parenthesized the expression as shown in the comment to the right of the code. Also notice that all the numbers are integers in the first expression; because of that, Python performs integer division and addition.
In the second expression, we add parentheses around the + part to force Python to evaluate it first (i.e., before the / ). We also made one of the operands floating point by adding a decimal point: 2.0. Because of the mixed types, Python converts the integer referenced by a up to a floating-point value (3.0) before performing the +. It also converts b up to a floating-point value (4.0) and performs a floating-point division: (4.0 / 5.0) yields a floating-point result of 0.8. If this were integer division instead, the result would be a truncated integer zero.
Besides the normal numeric operations (addition, subtraction, and so on), Python supports most of the numeric expressions available in the C language. For instance, here it's at work performing bitwise shift and Boolean operations:
>>> x = 1 # 0001 >>> x << 2 # shift left 2 bits: 0100 4 >>> x | 2 # bitwise OR: 0011 3 >>> x & 1 # bitwise AND: 0001 1
In the first expression, a binary 1 (in base 2, 0001) is shifted left two slots to create a binary 4 (0100). The last two operations perform a binary or (0001 | 0010 = 0011), and a binary and (0001 & 0001 = 0001). We won't go into much more detail on bit-twiddling here. It's supported if you need it, but be aware that it's often not as important in a high-level language such as Python as it is in a low-level language such as C. As a rule of thumb, if you find yourself wanting to flip bits in Python, you should think long and hard about which language you're really using. In general, there are often better ways to encode information in Python than bit strings.[3]
[3] Usually. As for every rule there are exceptions. For instance, if you interface with C libraries that expect bit strings to be passed in, our preaching doesn't apply.
Now for something more exotic: here's a look at long integers in action. When an integer constant ends with an L (or lowercase l), Python creates a long integer, which can be arbitrarily big:
>>><PHONE_NUMBER>999999999999999999 + 1 OverflowError: integer literal too large >>><PHONE_NUMBER>999999999999999999L + 1<PHONE_NUMBER>0000000000000000000L
Here, the first expression fails and raises an error, because normal integers can't accommodate such a large number. On the other hand, the second works fine, because we tell Python to generate a long integer object instead.
|
C omplex numbers are a recent addition to Python. If you know what they are, you know why they are useful; if not, consider this section optional reading.[4] Complex numbers are represented as two floating-point numbers—the real and imaginary parts—and are coded by adding a j or J suffix to the imaginary part. We can also write complex numbers with a nonzero real part by adding the two parts with a +. For example, the complex number with a real part of 2 and an imaginary part of -3 is written: 2 + -3j. Some examples of complex math at work:
[4] One of your authors is quick to point out that he has never had a need for complex numbers in some 15 years of development work. The other author isn't so lucky.
>>> 1j * 1J (-1+0j) >>> 2 + 1j * 3 (2+3j) >>> (2+1j)*3 (6+3j)
Complex numbers also allow us to extract their parts as attributes, but since complex math is an advanced tool, check Python's language reference manual for additional details.
As mentioned above, Python also provides both built-in functions and built-in modules for numeric processing. Here are the built-in math module and a few built-in functions at work; we'll meet more built-ins in Chapter 8.
>>> import math >>> math.pi 3.14159265359 >>> >>> abs(-42), 2**4, pow(2, 4) (42, 16, 16)
Notice that built-in modules such as math must be imported and qualified, but built-in functions such as abs are always available without imports. Really, modules are external components, but built-in functions live in an implied namespace, which Python searches to find names used in your program. This namespace corresponds to the module called _ _builtin__. We talk about name resolution in Chapter 4; for now, when we say "module", think "import."
| I l@ve RuBoard |


Hopefully you clicked on the "Work Info" section of the image map in order to arrive at this page. Is that correct? If so, press the "BACK" button in the browser bar and try the next portion of the image map!


|
|
Development Tools Overview |
|
|
This section contains information on the tools and related programs necessary for content creation related to Level Design for Halo PC.
The tools used for creating Halo game assets are a combination of both custom created tools and commercially available tools.
See the section Creating a Development Environment for information on where these tools and exporters should be placed to allow editing for Halo.
Textures and graphics can be created using any graphics package that can export or save in the .tif graphics format (Photoshop, Paint Shop Pro, etc…).
All the levels as well as models and animation in Halo are created using 3D Studio Max and Character Studio. Plug-ins for exporting from 3D Studio Max to the data formats that get converted to Halo data “tags” are required. Exporter plug-ins exist for 3D Studio R3, 3D Studio Max 4, and 3D Studio Max 5.
The following sections give a brief overview and description of the tools and their function in the development path for Halo. |
| Blitzkrieg (blitzkrieg.dle) |
|
Blitzkrieg is the exporter plug-in for 3D Studio Max. This plug-in exports the model data (vertices, materials, smoothing group information, animations, etc...) from 3DS Max to the file formats (.jms, .jmp, .jma, .jmm, .jmt) used by tool.exe to compile a data tag that can be used by Halo.
|
| Tool (tool.exe) |
|
Tool is a multipurpose command line program that compiles and converts data that has been exported from other sources such as 3D Studio Max. The data files that are created are referred to as "tags".
Running "tool.exe" by itself with no command line parameters will display a complete list of the available command line parameters and appropriate variables and variable formats. |
| Guerilla (guerilla.exe) |
|
Guerilla has a graphical interface that is used to edit the properties and resource references in the Halo data “tags”. |
|
|
Sapien (sapien.exe) |
|
|
Sapien is used to edit or modify various aspects of a level that has already been compiled using Tool.
Sapien has a graphical interface that contains a 3D window that renders the game including the level bsp, models, and vehicles as well as playing sounds and running physics.
Sapien is used for many purposes, including the population of characters, weapons, items, scenery objects, and game play and mission objectives |


More than 17,000 companies are using Intercom to achieve their goals
{% with more_proofs_link=instance.more_proofs_link post_description=instance.post_description %}
{% for plugin in instance.child_plugin_instances %}
{% render_plugin plugin %}
{% endfor %}
{% endwith %}


int curl_multi_select ( resource $mh [, float $timeout = 1.0 ] )
Blocks until there is activity on any of the curl_multi connections.
On success, returns the number of descriptors contained in the descriptor sets. On failure, this function will return -1 on a select failure or timeout (from the underlying select system call).


Provides read and write access to data and metadata from the DataONE network of data repositories, including the KNB Data Repository, Dryad, and the NSF Arctic Data Center. Each DataONE repository implements a consistent repository application programming interface. Users call methods in R to access these remote repository functions, such as methods to query the metadata catalog, get access to metadata for particular data packages, and read the data objects from the data repository using the global identifier for each data object. Users can also insert and update data objects on repositories that support these methods. For more details, see the vignettes.
Version 2.0 of the dataone R package removes the dependency on rJava and significantly changes the base API to correspond to the published DataONE API. Previous methods for accessing DataONE will be maintained, but new methods have been added.
The dataone R package requires the R package redland. If you are installing on Ubuntu then the Redland C libraries must be installed first. If you are installing on Mac OS X or Windows then installing these libraries is not required.
On Mac OS X dataone can be installed with the following commands:
install.packages("dataone")
library(dataone)
The dataone R package should be available for use at this point.
For ubuntu, install the required Redland C libraries by entering the following commands in a terminal window:
sudo apt-get update
sudo apt-get install librdf0 librdf0-dev
Then install the R packages from the R console:
install.packages("dataone")
library(dataone)
The dataone R package should be available for use at this point
For windows, the required redland R package is distributed as a binary release, so it is not necessary to install any additional system libraries.
To install the dataone R packages from the R console:
install.packages("dataone")
library(dataone)
The dataone R package should be available for use at this point.
See the full manual (help(dataone)
) for documentation.
To search the DataONE Federation Member Node Knowledge Network for Biocomplexity (KNB) for a dataset:
library(dataone)
cn <- CNode("PROD")
mn <- getMNode(cn, "urn:node:KNB")
mySearchTerms <- list(q="abstract:salmon+AND+keywords:spawn+AND+keywords:chinook",
fl="id,title,dateUploaded,abstract,size",
fq="dateUploaded:[2017-06-01T00:00:00.000Z TO 2017-07-01T00:00:00.000Z]",
sort="dateUploaded+desc")
result <- query(mn, solrQuery=mySearchTerms, as="data.frame")
result[1,c("id", "title")]
id <- result[1,'id']
The metadata file that describes the located research can be downloaded and viewed in an XML viewer, text editor after being written to disk, or in R via the commands below:
library(XML)
metadata <- rawToChar(getObject(mn, id))
doc <- xmlRoot(xmlTreeParse(metadata, asText=TRUE, trim = TRUE, ignoreBlanks = TRUE))
tf <- tempfile()
saveXML(doc, tf)
file.show(tf)
This metadata file describes a data file (CSV) in this data collection (package) that can be obtained using the listed identifier, using the commands:
dataRaw <- getObject(mn, "urn:uuid:49d7a4bc-e4c9-4609-b9a7-9033faf575e0")
dataChar <- rawToChar(dataRaw)
theData <- textConnection(dataChar)
df <- read.csv(theData, stringsAsFactors=FALSE)
df[1,]
Uploading a CSV file to a DataONE Member Node requires user authentication. DataONE user authentication is described in the vignette dataone-federation
.
Once the authentication steps have been followed, uploading is done with:
library(datapack)
library(uuid)
d1c <- D1Client("STAGING", "urn:node:mnStageUCSB2")
id <- paste("urn:uuid:", UUIDgenerate(), sep="")
testdf <- data.frame(x=1:10,y=11:20)
csvfile <- paste(tempfile(), ".csv", sep="")
write.csv(testdf, csvfile, row.names=FALSE)
# Build a DataObject containing the csv, and upload it to the Member Node
d1Object <- new("DataObject", id, format="text/csv", filename=csvfile)
uploadDataObject(d1c, d1Object, public=TRUE)
In addition, a collection of science metadata and data can be downloaded with one command, for example:
d1c <- D1Client("PROD", "urn:node:KNB")
pkg <- getDataPackage(d1c, id="urn:uuid:04cd34fd-25d4-447f-ab6e-73a572c5d383", quiet=FALSE)
See the R vignette dataone R Package for more information.
Work on this package was supported by:
Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California.


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Imgur Screenshots & Replays & Showcases
? PageCommonHelpTopics
Why are some images not able to be deleted from imgur.com?
The 'deletehash' code for old images you uploaded to imgur.com before are not saved, so they are not able to be deleted via imgur API.
You can only send a removal request to imgur via
this page for those images.


Rent too high? Need roommates to share the cost? We help you find the best location that suits your needs.


--- title: Research Topics in Software Engineering ref: ses2023 description: Graduate seminar on the latest research trends in the field of software engineering. semester: Spring 2023 number: 263-2100-00L lecturer: Prof. Martin Vechev, Prof. Zhendong Su, Prof. Ralf Jung ta: Dimitar I. Dimitrov, Momchil Peychev, Jingxuan He, Benjamin Bichsel, Anouk Paradis, Chengyu Zhang, Shaohua Li, Yann Girsberger, Theodoros Theodoridis, Dominik Winterer, Zuming Jiang, Sverrir Thorgeirsson, Max Vistrup assistants: edoz: https://www.vorlesungen.ethz.ch/Vorlesungsverzeichnis/lerneinheit.view?lerneinheitId=168753&semkez=2023S&lang=en session-time-place: Thu 12-14, CAB G52 lecture-time-place: exercise-time-place: credits: 2 image: assets/images/orator.jpg ---
This seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research.
Each student will be asked to study some papers from the recent software engineering literature and review them. This is an exercise in critical review and analysis. Active participation is required (a presentation of a paper as well as participation in discussions).
The aim of this seminar is to introduce students to recent research results in the area of programming languages and software engineering. To accomplish that, students will study and present research papers in the area as well as participate in paper discussions. The papers will span topics in both theory and practice, including papers on program verification, program analysis, testing, programming language design, and development tools.


---
layout: theorems
---
Basis for a Direct Sum
Suppose $W=V_1\oplus\dots\oplus V_k$. If $B_i$ is a basis for $V_i$ for all $i$, the $B_1\cup\dots\cup B_k$ is a basis for $W$.
Concepts
Coming soon
Hypothesis
Coming soon
Results
Coming soon
Proof
Coming soon


--- layout: post esbma_id: 1517 title: Book Review: Coder to Developer date: 2004-04-26 14:45:05 keywords: cornsharp book_dev ---
26 Apr 2004
I recently read Coder to Developer, by Mike Gunderloy. Very good book.
Mike covers an assortment of topics, all of which are important to software development:
This is the stuff which is typically not taught. This is the stuff which people fresh out of college don't know, and everybody expects them to just learn it as they go. This is the stuff which distinguishes true developers from mere programmers.
This book mentions a lot of specific technologies and tools, and it's very current right now. However, I plan to be fussing at Mike every two years for an updated edition. Ten years from now, these important topics will still be the difference between coders and developers.
Gunderloy is a fine writer, and the book is enjoyable to read. There's an excellent foreword from Joel Spolsky as well.
I highly recommend Coder to Developer for all programmers, especially those working in a small ISV.
Disclosure: Mike Gunderloy is a fan of SourceGear Vault, and this is evident in the book. The truth is that I would recommend this book even if all mention of SourceGear were removed. However, I think it is appropriate to disclose the facts.


Fight of the Day: Heath Herring vs. Yoshihiro Nakao
by Luke Irwin
Date: December 31, 2005
Card: K-1 PREMIUM Dynamite! 2005
Championship(s):
Venue: Osaka Dome
Location: Osaka, Japan
Date: December 31, 2005
Card: K-1 PREMIUM Dynamite! 2005
Championship(s):
Venue: Osaka Dome
Location: Osaka, Japan


Package javax.measure.spi
Interface SystemOfUnitsService
public interface SystemOfUnitsService
This interface represents the service to obtain a
system
of units
.
Common systems of units are "SI" (System International) or Metric system, "Imperial" (British), or "US" (US Customary).
- Since:
- 1.0
- Version:
- 1.7, October 7, 2018
- Author:
- Jean-Marie Dautelle, Werner Keil, Martin Desruisseaux
- See Also:
- Wikipedia: International System of Units
-
Method Summary
Modifier and Type Method Description Collection<SystemOfUnits>
getAvailableSystemsOfUnits()
Gets a list with available systems for thisSystemOfUnitsService
.default <P extends Prefix>
Set<P>getPrefixes(Class<P> prefixType)
SystemOfUnits
getSystemOfUnits()
Returns the defaultsystem of units
.SystemOfUnits
getSystemOfUnits(String name)
Returns the system of units having the specified name ornull
if none is found.
-
Method Details
-
getSystemOfUnits
Returns the defaultsystem of units
. Depending on the implementation this may be the International System of Units or another default system.- Returns:
- the default system of units.
-
getSystemOfUnits
Returns the system of units having the specified name ornull
if none is found.- Parameters:
name
- the system of unit name.- Returns:
- the system of units for the given name.
-
getAvailableSystemsOfUnits
Gets a list with available systems for thisSystemOfUnitsService
.- Returns:
- list of available systems of units, never null.
-
getPrefixes
Returns aSet
containing the values of a particularPrefix
type.This method may be used to iterate over certain prefixes as follows:
The default implementation assumes that prefixes of the given type are implemented as an enumeration. This is the case of the two default prefix implementations provided in JSR 385, namelyfor(MetricPrefix mp : service.getPrefixes(MetricPrefix.class)) System.out.println(p);
MetricPrefix
andBinaryPrefix
. Implementors shall override this method if they provide prefixes implemented in a different way.- Type Parameters:
P
- compile-time value of theprefixType
argument- Parameters:
prefixType
- thePrefix
type- Returns:
- a set containing the constant values of this Prefix type, in the order they're declared
- Throws:
ClassCastException
- if the class is not compatible with the desired Prefix implementation or does not implement Prefix at all.- Since:
- 2.0
-


pg_checksums — enable, disable or check data checksums in a PostgreSQL database cluster
pg_checksums
[option
...] [[ -D
| --pgdata
] datadir
]
pg_checksums checks, enables or disables data checksums in a PostgreSQL cluster. The server must be shut down cleanly before running pg_checksums. When verifying checksums, the exit status is zero if there are no checksum errors, and nonzero if at least one checksum failure is detected. When enabling or disabling checksums, the exit status is nonzero if the operation failed.
When verifying checksums, every file in the cluster is scanned. When
enabling checksums, every file in the cluster is rewritten in-place.
Disabling checksums only updates the file pg_control
.
The following command-line options are available:
-D directory
--pgdata=directory
Specifies the directory where the database cluster is stored.
-c
--check
Checks checksums. This is the default mode if nothing else is specified.
-d
--disable
Disables checksums.
-e
--enable
Enables checksums.
-f filenode
--filenode=filenode
Only validate checksums in the relation with filenode
filenode
.
-N
--no-sync
By default, pg_checksums
will wait for all files
to be written safely to disk. This option causes
pg_checksums
to return without waiting, which is
faster, but means that a subsequent operating system crash can leave
the updated data directory corrupt. Generally, this option is useful
for testing but should not be used on a production installation.
This option has no effect when using --check
.
-P
--progress
Enable progress reporting. Turning this on will deliver a progress report while checking or enabling checksums.
-v
--verbose
Enable verbose output. Lists all checked files.
-V
--version
Print the pg_checksums version and exit.
-?
--help
Show help about pg_checksums command line arguments, and exit.
PGDATA
Specifies the directory where the database cluster is
stored; can be overridden using the -D
option.
PG_COLOR
Specifies whether to use color in diagnostic messages. Possible values
are always
, auto
and
never
.
Enabling checksums in a large cluster can potentially take a long time. During this operation, the cluster or other programs that write to the data directory must not be started or else data loss may occur.
When using a replication setup with tools which perform direct copies of relation file blocks (for example pg_rewind), enabling or disabling checksums can lead to page corruptions in the shape of incorrect checksums if the operation is not done consistently across all nodes. When enabling or disabling checksums in a replication setup, it is thus recommended to stop all the clusters before switching them all consistently. Destroying all standbys, performing the operation on the primary and finally recreating the standbys from scratch is also safe.
If pg_checksums is aborted or killed while enabling or disabling checksums, the cluster's data checksum configuration remains unchanged, and pg_checksums can be re-run to perform the same operation.


|
MOTS Finder
Find non-star-shaped MOTSs
|
Represents a sequence of multiple integration results. More...
Public Member Functions | |
| def | __init__ (self, results, info=None, sum_makes_sense=True) |
| Create a results object from given results. More... | |
| def | value (self) |
| Total value (sum of all results). More... | |
| def | error (self) |
| Total error (sum of all errors). More... | |
| def | __len__ (self) |
| Number of stored results. More... | |
| def | __getitem__ (self, key) |
| Access individual results. More... | |
| def | __iter__ (self) |
| Iterate through individual results. More... | |
| def | sum (self, indices, full_output=False) |
| Combine results (sum values and optionally errors). More... | |
| def | __repr__ (self) |
| def | all_ok (self) |
| Return whether none of the results produced a warning. More... | |
Public Attributes | |
| info | |
| Additional info supplied to the constructor. More... | |
| sum_makes_sense | |
| Whether the sum of all results is a meaningful number. More... | |
Private Attributes | |
| _results | |
Represents a sequence of multiple integration results.
This class presents convenience methods to sum individual results and errors and check whether all results were computed without any warnings.
Examples
| def __init__ | ( | self, | |
| results, | |||
info = None , |
|||
sum_makes_sense = True |
|||
| ) |
Create a results object from given results.
Positional arguments can be either the full_output=True
results of scipy.integrate.quad()
calls or IntegrationResult objects.
| *results | Results to collect. |
| info | Arbitrary info object to be stored with the results. |
| sum_makes_sense | Whether the sum of all results is a meaningful number. This controls if the total is printed in case of string conversion. |
| def __getitem__ | ( | self, | |
| key | |||
| ) |
Access individual results.
| def __iter__ | ( | self | ) |
Iterate through individual results.
| def __len__ | ( | self | ) |
Number of stored results.
| def all_ok | ( | self | ) |
Return whether none of the results produced a warning.
| def error | ( | self | ) |
Total error (sum of all errors).
| def sum | ( | self, | |
| indices, | |||
full_output = False |
|||
| ) |
Combine results (sum values and optionally errors).
| def value | ( | self | ) |
Total value (sum of all results).
| info |
Additional info supplied to the constructor.
| sum_makes_sense |
Whether the sum of all results is a meaningful number.


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enum class ContentShareStatusCode
ContentShareStatusCode indicates the reason the content share event occurred.
OK |
No failure. |
VideoServiceFailed |
Content share video connection is in an unrecoverable failed state. Restart content share connection when this error is encountered. |


Date of Table Update:201110130947
| GRIB2 Id | FNMOC id | Name | FNMOC Status1 | WMO Status2 |
|---|---|---|---|---|
| 0 | AM | unweighted mean | current | operational |
| 1 | WA | weighted mean | current | operational |
| 2 | SC | standard deviation, cluster mean | current | operational |
| 3 | SN | standard deviation, cluster mean, normalized | current | operational |
| 4 | S | spread | current | operational |
| 5 | LA | large anomaly index | current | operational |
| 6 | UC | unweighted mean, cluster | current | operational |
| 7 | IR | interquartile range | current | validation |
| 8 | MI | minimum of all members | current | validation |
| 9 | MA | maximum of all members | current | validation |
| 10-191 | 10-191 | reserved | current | operational |
| 192-253 | 192-253 | reserved local | current | operational |
| 252 | QM | quantile (percentiles), all members | current | operational |
| 253 | SM | standard deviation, all member mean | current | operational |
| 254 | PM | probability across all ensemble members | current | operational |
| 255 | M | missing | current | operational |
Date of Table Creation:200812161743
Date of Table Update:201110130947
References:
| title: | Product Name Standard Document |
|---|---|
| version: | 2.2 |
| docId: | P-3146-2.2 |
| dtg: | May 2012 |
| organization: | Fleet Numerical Meteorology and Oceanography Center |
| infoUsed: | Derived Forecast Table |
|
|
|
| title: | GRIB 2 |
| version: | 12.0.0 |
| docId: | FM 92-XII |
| organization: | World Meteorological Organization |
| infoUsed: | GRIB2 Derived Forecast, table 4.7 |
|
|
Footnotes:
| value | definition |
|---|---|
| available | Entry was used in the past, is not in production now, and could be used again. |
| current | Entry is currently in production and available to customers. |
| deprecated | Entry name is no longer to be used. Parameter may or may not be in production. |
| listed | Entry is listed in WMO documentation. Not in production with no plans to be produced. |
| obsolete | Entry is not to be used and is not in production, if it ever was. |
| pending | Entry is being prepared for production. |
| planned | Entry is being looked at for possible production. |
| value | definition |
|---|---|
| deprecated | Entry is no longer used. |
| experimental | Entry is not recommended for use outside of bi-lateral previously agreed tests. |
| operational | Entry is available for use. |
| validation | Entry is in the approval process, not recommended for use. |