Reactive DDD with Akka
This sample e-commerce system has a set of properties that makes it unique among similar systems. It is:
All these capabilities are obviously supported by the underlying technology stack, which includes:
Akka - actor-based, reactive middleware implemented in Scala,
Akka HTTP - HTTP server build upon Akka Stream (Akka's implementation of Reactive Streams Specification),
Akka Persistence - infrastructure for building durable (event sourced) actors, which has a pluggable journal,
Event Store - scalable, highly available event store with akka-persistence journal implementation. Provides engine for running user-defined projections (javascript functions) over single or multiple event streams. Projections allow the system to group or combine events into new event streams that can represent domain-level journals such as office journals (events grouped by emitter (Aggregate Root
) class) or business process journals (events related to concrete business process). Domain journals are topic of interest for services such as:
Akka-DDD - framework containing glue-code and all building blocks
The system currently consists of the following subsystems:
Each subsystem is divided into write and read side, each side containing back-end and front-end application:
Backend cluster node hosting Aggregate Roots
, Receptors
and Process Managers (Sagas)
.
HTTP server forwarding commands to backend cluster.
View update service that consumes events from event store and updates view store (PostgreSQL database).
HTTP server providing rest endpoint for accessing view store.
docker run --name ecommerce-event-store -d -p 2113:2113 -p 1113:1113 newion/eventstore:3.0.1
docker run --name sales-view-store -d -p 5432:5432 postgres
Postgresql console: psql -h localhost -p 5432 -U postgres
git clone https://github.com/pawelkaczor/ddd-leaven-akka-v2.git
Run enable-projections script.
sbt stage
As there are multiple applications per subsystem, running/monitoring the whole system is not straightforward. You can use run scripts (located in run-scripts directory) to quickly start the system and execute sample Reservation process (see below). However, it s recommended you configure supervisord supervisord to include supervisord-configs dir and manage (start/restart/stop) services using supervisorctrl tool.
Create reservation
http :9100/ecommerce/sales Command-Type:ecommerce.sales.CreateReservation reservationId="r1" customerId="customer-1"
Add product
echo '{"reservationId": "r1", "product": { "snapshotId": { "aggregateId": "123456789", "sequenceNr": 0 }, "name": "DDDD For Dummies - 7th Edition", "productType": 1, "price": { "doubleValue": 10.0, "currencyCode": "USD"}}, "quantity": 1}' | http :9100/ecommerce/sales Command-Type:ecommerce.sales.ReserveProduct
Confirm reservation
http :9100/ecommerce/sales Command-Type:ecommerce.sales.ConfirmReservation reservationId="r1"
Pay
echo '{"invoiceId": "{{INVOICE_ID}}", "orderId": "r1", "amount": { "doubleValue": 10.0, "currencyCode": "USD"}, "paymentId": "230982342"}' | http :9200/ecommerce/invoicing Command-Type:ecommerce.invoicing.ReceivePayment
Check read side
http :9110/ecommerce/sales/reservation/r1
http :9310/ecommerce/shipping/shipment/order/r1


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| Class | ActiveRecord::ConnectionAdapters::AbstractAdapter |
| In: |
vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb
|
| Parent: | Object |
All the concrete database adapters follow the interface laid down in this class. You can use this interface directly by borrowing the database connection from the Base with Base.connection.
Most of the methods in the adapter are useful during migrations. Most notably, SchemaStatements#create_table, SchemaStatements#drop_table, SchemaStatements#add_index, SchemaStatements#remove_index, SchemaStatements#add_column, SchemaStatements#change_column and SchemaStatements#remove_column are very useful.
Is this connection active and ready to perform queries?
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 68 68: def active? 69: @active != false 70: end
Returns the human-readable name of the adapter. Use mixed case - one can always use downcase if needed.
 If true, next_sequence_value is called before each insert to set the record’s primary key. This is false for all adapters but Firebird.
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 55 55: def prefetch_primary_key?(table_name = nil) 56: false 57: end
Provides access to the underlying database connection. Useful for when you need to call a proprietary method such as postgresql’s lo_* methods
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 95 95: def raw_connection 96: @connection 97: end
Close this connection and open a new one in its place.
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 73 73: def reconnect! 74: @active = true 75: end
Does this adapter support using DISTINCT within COUNT? This is true for all adapters except sqlite.
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 47 47: def supports_count_distinct? 48: true 49: end
Does this adapter support migrations? Backend specific, as the abstract adapter always returns false.
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 41 41: def supports_migrations? 42: false 43: end
Lazily verify this connection, calling +active?+ only if it hasn’t been called for timeout seconds.
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 84 84: def verify!(timeout) 85: now = Time.now.to_i 86: if (now - @last_verification) > timeout 87: reconnect! unless active? 88: @last_verification = now 89: end 90: end
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 136 136: def format_log_entry(message, dump = nil) 137: if ActiveRecord::Base.colorize_logging 138: if @@row_even 139: @@row_even = false 140: message_color, dump_color = "4;36;1", "0;1" 141: else 142: @@row_even = true 143: message_color, dump_color = "4;35;1", "0" 144: end 145: 146: log_entry = " \e[#{message_color}m#{message}\e[0m " 147: log_entry << "\e[#{dump_color}m%#{String === dump ? 's' : 'p'}\e[0m" % dump if dump 148: log_entry 149: else 150: "%s %s" % [message, dump] 151: end 152: end
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 100 100: def log(sql, name) 101: if block_given? 102: if @logger and @logger.level <= Logger::INFO 103: result = nil 104: seconds = Benchmark.realtime { result = yield } 105: @runtime += seconds 106: log_info(sql, name, seconds) 107: result 108: else 109: yield 110: end 111: else 112: log_info(sql, name, 0) 113: nil 114: end 115: rescue Exception => e 116: # Log message and raise exception. 117: # Set last_verfication to 0, so that connection gets verified 118: # upon reentering the request loop 119: @last_verification = 0 120: message = "#{e.class.name}: #{e.message}: #{sql}" 121: log_info(message, name, 0) 122: raise ActiveRecord::StatementInvalid, message 123: end
# File vendor/rails/activerecord/lib/active_record/connection_adapters/abstract_adapter.rb, line 125 125: def log_info(sql, name, runtime) 126: return unless @logger 127: 128: @logger.debug( 129: format_log_entry( 130: "#{name.nil? ? "SQL" : name} (#{sprintf("%f", runtime)})", 131: sql.gsub(/ +/, " ") 132: ) 133: ) 134: end


statsmodels.tsa.stattools.kpss¶
-
statsmodels.tsa.stattools.
kpss
(x, regression='c', lags=None, store=False)[source]¶ Kwiatkowski-Phillips-Schmidt-Shin test for stationarity.
Computes the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test for the null hypothesis that x is level or trend stationary.
- Parameters
- xarray_like, 1d
Data series
- regressionstr{‘c’, ‘ct’}
Indicates the null hypothesis for the KPSS test * ‘c’ : The data is stationary around a constant (default) * ‘ct’ : The data is stationary around a trend
- lags{None, str, int}, optional
Indicates the number of lags to be used. If None (default), lags is calculated using the legacy method. If ‘auto’, lags is calculated using the data-dependent method of Hobijn et al. (1998). See also Andrews (1991), Newey & West (1994), and Schwert (1989). If set to ‘legacy’, uses int(12 * (n / 100)**(1 / 4)) , as outlined in Schwert (1989).
- storebool
If True, then a result instance is returned additionally to the KPSS statistic (default is False).
- Returns
- kpss_statfloat
The KPSS test statistic
- p_valuefloat
The p-value of the test. The p-value is interpolated from Table 1 in Kwiatkowski et al. (1992), and a boundary point is returned if the test statistic is outside the table of critical values, that is, if the p-value is outside the interval (0.01, 0.1).
- lagsint
The truncation lag parameter
- critdict
The critical values at 10%, 5%, 2.5% and 1%. Based on Kwiatkowski et al. (1992).
- resstore(optional) instance of ResultStore
An instance of a dummy class with results attached as attributes
Notes
To estimate sigma^2 the Newey-West estimator is used. If lags is None, the truncation lag parameter is set to int(12 * (n / 100) ** (1 / 4)), as outlined in Schwert (1989). The p-values are interpolated from Table 1 of Kwiatkowski et al. (1992). If the computed statistic is outside the table of critical values, then a warning message is generated.
Missing values are not handled.
References
Andrews, D.W.K. (1991). Heteroskedasticity and autocorrelation consistent covariance matrix estimation. Econometrica, 59: 817-858.
Hobijn, B., Frances, B.H., & Ooms, M. (2004). Generalizations of the KPSS-test for stationarity. Statistica Neerlandica, 52: 483-502.
Kwiatkowski, D., Phillips, P.C.B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54: 159-178.
Newey, W.K., & West, K.D. (1994). Automatic lag selection in covariance matrix estimation. Review of Economic Studies, 61: 631-653.
Schwert, G. W. (1989). Tests for unit roots: A Monte Carlo investigation. Journal of Business and Economic Statistics, 7 (2): 147-159.


| Plot of
measures vs resampled time series indices
|
|
| A selection of measures computed on
resampled time series of a specific type, i.e. time series with names
containing indices after the string code of the specified resampling
type, can be plotted against the resampling indices in a figure window.
This type of figure visualizes the result of the resampling test for a
time series, comparing the measure(s) value for the original time series
at index 0 to the other values of the resampled time series at the other
indices. Further, the user is opted to select to get a graph of ordered
values and test results (p-values of a parametric test and nonparametric
test). First, the Resampling type must be chosen among the listed resampling types (RP, FT, AAFT, IAAFT, STAP, AMRB, see "Resampled Time Series" operation). Upon the selection of the resampling type the list of resampled time series is restricted to include only resampled time series of the specified type. If for example, the STAP resampling type is specified, the label on the top of the list reads Select STAP resampled time series and the list contains all the STAP surrogate time series for which measures have been computed in the last run of measures. The resampled time series in the list are identified for the specified resampling type by the time series name and the indices after the string code of the specified resampling type (if there is a string after the index this should be the same in the names of the segments). If no such resampled time series names exist the list of resampled time series is empty and this operation cannot run for this resampling type. Further, one or more measures can be selected from the measure list having the title Select one or more measures. For measures defined in terms of one or more measure specific parameters, the measure name regards a specified set of parameters (one parameter value for each name). A subset of resampled time series and measure names can be selected from the respective lists with standard use of the mouse: a click on a name and Shift^click on a another name further down in the list selects all names between the former and the latter; a click on a name and subsequent Ctrl^clicks on other names select these names including the first name; Ctrl^a selects the whole list. Tips: For the selection of a subset of resampled time series names from the list, click on the resampled time series of this subset appearing first in the list and then Shift^click at the last resampled time series in the list. In this way, all time series from the first selected to the last time series in the list will be marked and from those only the ones that have the same resampled time series name as the first one and differ only to the resampling index will be processed. |
|
| Resampling type |
|
| The user can choose one of the
following resampling types (for details of the resampling types see the
"Resampled Time Series" operation)
RP: Random Permutation, If there are time series of the selected resampling type in the list of time series names, they are displayed in the list of resampled time series. |
|
| Draw lines / points |
|
| The user can choose one of the following: Lines, Points, Both. This is the drawing type for the measure vs resampling index plot and a different drawing type is used for each measure, as explained in the legend or to "Running messages" text box (if more than 5 lines are displayed in one graph). | |
| Normalize |
|
| If this checkbox is activated, the measures are first normalized to have mean zero and standard deviation one (z-score). In this way, the user can have all selected measures at the same range, and can assess visualize whether the measure value (test statistic) for the original time series is out of the limits of null distribution. | |
| Display test |
|
| If this checkbox is activated, then one
graph for each of the selected measures will be generated (after the
user pushes the View selected plot button), and the test results will be
given in the form of p-values, provided that the original time series
name is in the list of the time series names. Each graph contains the
following: - At index value 0 the measure value for the original time series is displayed by an open circle. For index values 1 to M (the number of resampled time series), the measure values for the resampled time series are displayed (according to the Draw lines / points selection) in ascending or descending order (depending whether the measure value for the original time series is towards the left or right part of the distribution of the "resampled" values). - Two red broken horizontal lines display the critical values for the significant level á=0.05 and á=0.01 for a parametric (normal) test. Basically these two values define the tails (left or right depending on the original value) of the null distribution of the test statistic. So, the user can have a graphical representation of the test judging from the position of the original value (open circle at time index 0) with respect to these two horizontal lines. - Quantitative test results are given in the title of the graph in the form of two p-values, one for the parametric (normal) test and the other for the nonparametric test (based on rank ordering of the M+1 values, the original and the M resampled ones). Further the validity of the parametric test is examined with the Kolmogorov-Smirnov test for normality and the notification "normality accepted" is displayed along with the parametric p-value if the null hypothesis of the Kolmogorov-Smirnov test is not rejected, otherwise the notification is changed to "normality rejected". In this way, the user has evidence to whether rely or not on the parametric test result. |
|
| View selected plot |
|
| Pressing this button
will generate one or more figures in separate window(s), provided that a list of
at least two resampled time series names of the specified resampling
type and one or more measure names are selected. The generation of one
or possible more figures depends on the selection of the "Display test"
option as follows. If the "Display test" option is not selected, a single figure as the one shown below will be displayed containing lines or points (or both) of distinct type for each selected measure vs the resampling indices. When up to 5 measure names are selected, they are listed in a legend together with their corresponding drawing type, otherwise they are listed in the "Running messages" text box.
The resampling test here is for the null hypothesis of linear stochastic process using surrogate data generated by the STAP algorithm on a time series of EEG from an epileptic seizure (exhibiting rhythmic oscillations and thus expected nonlinear dynamics to be present and the null hypothesis to be rejected). We note that for two of the four measures displayed in the figure above, the cumulative bicorrelation for maximum lag 10 (blue line) and the cumulative mutual information using equiprobable binning of automatically selected number of bins and maximum lag 10 (red line), it is obvious that the original values for both measures are well above the respective values of the resampled data. The distinction is less clear for the measure of the fit with a local zero order model of 10 neighbors, lag one, embedding dimension 10 and predicting 5 time steps ahead using the direct prediction scheme (black dashed line). However, this does not mean that the rejection of the null hypothesis is less confident by this nonlinear measure. It is just that the range for this measure is much smaller, as is for the forth measure of the linear autoregressive (AR) fit for the same prediction and using AR order 10. To visualize better the graphs for the two last measures (the nonlinear and linear fit measures) we should use the option "Normalize". Moreover, to obtain quantitative results as well for these two measures, we select only these two, and activate the checkboxes "Normalize" and "Display test". By then pressing the button "View selected plot" two figures are generated in separate windows as shown below (for the test statistic of the linear fit on the first figure and the test statistic of the nonlinear fit on the second figure).
It is obvious that for the linear fit the value for the original EEG data is well within the distribution of the values from the STAP surrogate time series (the open circle is above both the two red horizontal lines and towards zero). Accordingly, the p-values of both the parametric and the nonparametric test are large (displayed at the title of the figure). We note that the set of measure values for the resampled data form a distribution that is accepted to be normal as given by the Kolmogorov-Smirnov test, and this result is displayed in the title as "normality accepted". So, we can trust the result of the parametric test. The test results for the nonlinear fit test statistic given in the second figure above, suggest that the null hypothesis for linear stochastic process should be rejected at very low significance level when using the parametric approach and at the smallest significant level of ≈0.025 when using the nonparametric approach. The Kolmogorov-Smirnov test suggests here that the test statistic values on the resampled data do not follow normal distribution (stated as "normality rejected" in the title), so we cannot trust the parametric result. |
|
Running Messages |
|
| A text box displaying messages for the running operations. | |
| Exit |
|
| By pressing this button the window of "Plot of Measures vs Resampled Time Series Indices" will disappear and the user will be moved to the "View Measures" window. Note that any created figures will remain until the user exits from the "View Measures" window. | |
| Help |
|
| This file will be shown |


ROMEO IS BLEEDING A film review by James Berardinelli Copyright 1994 James Berardinelli
Rating (Linear 0 to 10): 5.9
Date Released: 2/4/94 Running Length: 1:49 Rated: R (Violence, language, sex, nudity)
Starring: Gary Oldman, Lena Olin, Anabella Sciorra, Juliette Lewis, Roy Scheider Director: Peter Medak Producers: Hilary Henkin and Paul Webster Screenplay: Hilary Henkin Music: Mark Isham Released by Gramercy Pictures
Even though it takes place in the 90s, the atmosphere is pure 40s. The dialogue by Hilary Henkin could have been lifted from any dime store detective story, and it's almost a surprise to see Gary Oldman sauntering around instead of, say, Humphrey Bogart. But ROMEO IS BLEEDING isn't just an homage to the genre, it's a satire as well. Unfortunately, it has a tendency to take itself too seriously, which greatly limits its effectiveness.
Jack Grimaldi (Gary Oldman) is a crooked cop. Because his yearly salary is only "Forty-two and change", he has decided to enrich himself through several profitable deals with the local mob boss, Don Falcone (Roy Scheider). However, when one of those deals goes bad, he finds himself caught in an underworld power struggle between Falcone and a Russian assassin, Mona Demarkov (Lena Olin). It's not long before the shooting starts and Grimaldi finds himself and his wife (Anabella Sciorra) trapped in a no-man's land.
ROMEO IS BLEEDING certainly has all the elements: the cop who can't keep on the right side of the law, the cocktail waitress girlfriend, seedy hotel rooms, the long-suffering wife, the high body count, and the femme fatale. Then there's the dialogue, which includes some of the following "classic" lines: "Can I tell you what makes love frightening?  To the end of either their life, or yours", and "A life's a life--moral distinctions can paralyze you."
The atmosphere is black-and-white, even though the movie is in color. Dariusz Wolski's camerawork is evocative, as is the Angelo Badalamenti-like score by Mark Isham.
Unfortunately, the production runs into problems almost from the outset. While Gary Oldman is an excellent actor, either he's not right for this part, or he's not playing it the way it was meant to be played. His portrayal is unrelentingly grim, which effectively nullifies much of the satirical bent of ROMEO IS BLEEDING. Not only is Jack Grimaldi unlikable, but he's boring, and certainly not a match for the villainess.
Lena Olin gets the kind of over-the-top, totally nasty role that is normally given to a male actor. Her Mona Demarkov makes Sharon Stone's Basic Instinct character look like a girl scout. She's the kind of woman that will laugh while garroting you, take a chainsaw to her own arm, then ask if you want to make love with the prosthesis on or off. Ms. Olin steals every scene that she's in, although that isn't difficult considering how easily Mr. Oldman blends into the background.
  Anabella Sciorra fares much better as the wife whom Grimaldi professes to still love.
The voice-over is another problem. It's certainly hardboiled, which is in keeping with the overall tone, but it's also incredibly long-winded and intrusive. Whatever can be said in ten words is dragged out to twenty or thirty. It doesn't take long before the viewer begins to wish Mr. Oldman would just shut up and let the story get moving on its own.
Comparisons with Quentin Tarantino's RESERVOIR DOGS and TRUE ROMANCE are inevitable, but ROMEO IS BLEEDING comes across as an inferior product. Tarantino may operate in the same genre, and with equally bloody scripts, but his characters have greater depth and his stories are more energetic and powerful.
Without Lena Olin's performance, ROMEO IS BLEEDING could have been an ordinary, or even sub-par, film noir. However, with a villainess as fun as Mona Demarkov, it's impossible not to find some enjoyment amidst Gary Oldman's dreadful seriousness and all the bloody corpses. There are some plot twists, and a few unexpected happenings, but in the end, it's Ms. Olin's character that keeps the audience in their seats.
- James Berardinelli<EMAIL_ADDRESS>.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


This package contains the functions used to perform some confidence statistics based in population median.
| Version: | 0.1 |
| Depends: | R (≥ 2.15.0) |
| Published: | 2012-12-24 |
| Author: | Adriano Polpo, Carlos Alberto de Braganca Pereira |
| Maintainer: | Adriano Polpo <polpo at ufscar.br> |
| License: | GPL (≥ 3) |
| URL: | http://code.google.com/p/medor/ |
| NeedsCompilation: | no |
| Citation: | MedOr citation info |
| Materials: | README |
| CRAN checks: | MedOr results |
| Reference manual: | MedOr.pdf |
| Vignettes: |
NPstat |
| Package source: | MedOr_0.1.tar.gz |
| Windows binaries: | r-devel: MedOr_0.1.zip, r-release: MedOr_0.1.zip, r-oldrel: MedOr_0.1.zip |
| OS X binaries: | r-release: MedOr_0.1.tgz, r-oldrel: MedOr_0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=MedOr to link to this page.


Member of OFCS Online Film Critics Society ******************************************
LAND GIRLS
Wars, at least those, unlike our mess in VietNam, that are considered "just," have a way of uniting the population in ways that put aside race, gender and class. Everyone pitches in to help our men in battle, Long before this happened in the U.S. in WWII, in Britain, as far back as the first World War, they had the Women's Land Army, commonly known as the Land Girls, women who worked on the farms and in factories while their men were fighting the enemy. As many as 100,000 women were part of that "army" since its inception. This film is about three women in WWII and their adventures on a farm in England.
Based on a 1994 popular book by Angela Huth, it is about three pretty women with varying backgrounds and personalities. There is Stella (Catherine McCormack), a banker's daughter, whose fianc‚ is a Naval Officer. Ag (Rachel Weiss), is a graduate of Cambridge University, brainy and capricious. Rounding out the threesome is a working-class hairdresser, Prue (Anna Friel.)
The three live on a farm owned by the Lawrences, (Tom Georgeson and Maureen Obrien). Also on the farm is the Lawrences' handsome son, Joe, who wants to be a fighter pilot but has to help out his parents on the farm. Before very long the girls and Joe, with pre-war inhibitions out the window, become "good friends." Before the war's end, each has gone through some rough periods; tragedy is a great part of war. General Sherman said it better: War is hell.
As with so many films being made these days, this one runs too long. At least, the one hour and fifty minutes seems longer than that because the epilog could have been omitted. Showing what happened to each of the characters after the war's end turns out to be on the corny side and spoils what would otherwise have been a better film.
Directed by David Leland
2.5 Bytes
4 Bytes = Superb 3 Bytes = Too good to miss 2 Bytes = Average 1 Byte = Save your money
Copyright 1998 Ben Hoffman
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Here we describe the standard distribution. If the standard doesn't meet your needs, we refer you to the Lua discussion list, where any question about the package scheme will likely already have been answered.
On Unix systems, the standard distribution uses two base directories, one for system dependent files, and another for system independent files. Let's call these directories <CDIR> and <LDIR>, respectively. For example, in my laptp, Lua 5.1 is configured to use '/usr/local/lib/lua/5.1' for <CDIR> and '/usr/local/share/lua/5.1' for <LDIR>. On Windows, <CDIR> usually points to the directory where the Lua executable is found, and <LDIR> points to a lua/ directory inside <CDIR>. (These settings can be overridden by environment variables LUA_PATH and LUA_CPATH. See the Lua documentation for details.) Here is the standard LuaSocket distribution directory structure:
<LDIR>/ltn12.lua <LDIR>/socket.lua <CDIR>/socket/core.dll <LDIR>/socket/http.lua <LDIR>/socket/tp.lua <LDIR>/socket/ftp.lua <LDIR>/socket/smtp.lua <LDIR>/socket/url.lua <LDIR>/mime.lua <CDIR>/mime/core.dll
Naturally, on Unix systems, core.dll would be replaced by core.so.
With the above setup, and an interpreter with shared library support, it should be easy to use LuaSocket. Just fire the interpreter and use the require function to gain access to whatever module you need:
Lua 5.2.2 Copyright (C) 1994-2013 Lua.org, PUC-Rio > socket = require("socket") > print(socket._VERSION) --> LuaSocket 3.0-rc1
Each module loads their dependencies automatically, so you only need to load the modules you directly depend upon:
Lua 5.2.2 Copyright (C) 1994-2013 Lua.org, PUC-Rio > http = require("socket.http") > print(http.request("http://www.impa.br/~diego/software/luasocket")) --> homepage gets dumped to terminal


Starts a local single-node OpenShift cluster.
All flags of this command can also be configured by setting corresponding environment variables or persistent configuration options.
For the former prefix the flag with MINISHIFT_, uppercase characters and replace '-' with '_', for example MINISHIFT_VM_DRIVER.
For the latter see 'minishift config -h'.
minishift start [flags]
Global Flags:


Before Change
sequence_input // make sure the order is right
// 4.Define Model,compile and train
model = DeepFM({"sparse": sparse_feat_list,
"sequence": sequence_feature}, task="regression")
model.compile("adam", "mse", metrics=["mse"], )
history = model.fit(model_input, data[target].values,
After Change
varlen_feature_columns = [VarLenSparseFeat("genres", len(
key2index) + 1, max_len, "mean")] // Notice : value 0 is for padding for sequence input feature
linear_feature_columns = fixlen_feature_columns + varlen_feature_columns
dnn_feature_columns = fixlen_feature_columns + varlen_feature_columns
fixlen_feature_names = get_fixlen_feature_names(linear_feature_columns + dnn_feature_columns)
varlen_feature_names = get_varlen_feature_names(linear_feature_columns+dnn_feature_columns)
// 3.generate input data for model


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Meet the team which made this event possible through their sheer hardwork and a will to do something great.
Rahul Gupta
Nitesh
Khushboo
Ambhuj
Shahab
Rushank


For the fig-swirl: Melt butter over medium heat in a saucepan. Add brown sugar and stir to dissolve. Halve all of the figs and toss in the saucepan with water and lemon juice. Cook over medium heat, stirring frequently, until you have a chunky-jammy mixture. Add salt with one or two stirs, set aside and let cool completely.
Ice cream: In a small pot over medium heat, combine milk, and ggranulated sugar until sugar is compleatly dissolved and the milk is just barely lukewarm. Whisk in the egg yolks. Set mixture in the fridge and wit until the fig mixture is cold.
Using an ice cream machine, pour liquids into the frozen basin and process acording to manufacturer instructions, i.e., let spin and thicken for 20 minutes before adding mascarpone, fig jam mixture, and the nuts. Continue to process for +/- 10 minutes. POu semi-frozen mixture into a pyrex dish or glass tupperware. Freeze for at least two houres before serving.


The Manila Yacht Club should be contacted on arrival and they will arrange for a team of customs, immigration and quarantine officials to board the yacht. An inspection fee of varying amounts is occasionally requested by each of the officials.
The club offers members of other clubs the use of its services. Visiting yachts must pay a refundable deposit of US$300. Moorings are available with fees on a sliding scale increasing after four weeks and doubling again after eight weeks.There are good repair facilities around the yacht club as well as skilled workers to call on.


Warning: Snapshots builds on this page have been automatically generated and are not guaranteed to be stable. It is possible that these builds have major bugs and may not run at all. Be sure to check junit test results to understand what is working and what is not in these drops.


Report: Rockets C Capela evaluated for concussion
Houston Rockets center Clint Capela is expected to miss at least one game after being evaluated for a concussion, ESPN reported Thursday.
Capela bumped his head while attempting to draw a charge on the Los Angeles Clippers’ JaMychal Green during the fourth quarter of Wednesday’s 102-93 victory.
Veteran Tyson Chandler would likely get the start at center Friday against the visiting Indiana Pacers if Capela is not available.
Capela tallied 12 points on 6-of-7 shooting and grabbed 20 rebounds against the Clippers, his seventh double-double in 11 starts this season.
Capela, 25, is averaging 13.4 points and 12.5 rebounds this season and owns career averages of 12.0 points and 9.3 boards in 306 games.
—Field Level Media


Uses of Interface
org.apache.qpid.protonj2.engine.TransactionController
-
Packages that use TransactionController Package Description org.apache.qpid.protonj2.engine org.apache.qpid.protonj2.engine.impl -
-
Uses of TransactionController in org.apache.qpid.protonj2.engine
Methods in org.apache.qpid.protonj2.engine that return TransactionController Modifier and Type Method Description TransactionController
TransactionController. addCapacityAvailableHandler(EventHandler<TransactionController> handler)
Allows the caller to add anEventHandler
that will be signaled when the underlying link for thisTransactionController
has been granted credit which would then allow for transactionDeclared
andDischarge
commands to be sent to the remote Transactional Resource.TransactionController
Session. coordinator(java.lang.String name)
Create a newTransactionController
using the provided name.TransactionController
TransactionController. declare(Transaction<TransactionController> transaction)
Request that the remoteTransactionManager
declare a new transaction and respond with a new transaction Id for that transaction.TransactionController
TransactionController. declaredHandler(EventHandler<Transaction<TransactionController>> declaredEventHandler)
Called when theTransactionManager
end of the link has responded to a previousDeclare
request and the transaction can now be used to enroll deliveries into the active transaction.TransactionController
TransactionController. declareFailureHandler(EventHandler<Transaction<TransactionController>> declareFailureEventHandler)
Called when theTransactionManager
end of the link responds to aTransaction
declaration with anRejected
outcome indicating that the transaction could not be successfully declared.TransactionController
TransactionController. discharge(Transaction<TransactionController> transaction, boolean failed)
Request that the remoteTransactionManager
discharge the given transaction and with the specified failure state (true for failed).TransactionController
TransactionController. dischargedHandler(EventHandler<Transaction<TransactionController>> dischargedEventHandler)
Called when theTransactionManager
end of the link has responded to a previousdischarge(Transaction, boolean)
request and the transaction has been retired.TransactionController
TransactionController. dischargeFailureHandler(EventHandler<Transaction<TransactionController>> dischargeFailureEventHandler)
Called when theTransactionManager
end of the link has responded to a previousdischarge(Transaction, boolean)
request and the transaction discharge failed for some reason.TransactionController
TransactionController. parentEndpointClosedHandler(EventHandler<TransactionController> handler)
Sets aEventHandler
for when the parentSession
orConnection
of thisTransactionController
is locally closed.TransactionController
TransactionController. setCoordinator(Coordinator coordinator)
Sets theCoordinator
target to assign to the local end of thisTransactionController
.TransactionController
TransactionController. setSource(Source source)
Sets theSource
to assign to the local end of thisTransactionController
.Methods in org.apache.qpid.protonj2.engine that return types with arguments of type TransactionController Modifier and Type Method Description Transaction<TransactionController>
TransactionController. declare()
Request that the remoteTransactionManager
declare a new transaction and respond with a new transaction Id for that transaction.Transaction<TransactionController>
TransactionController. newTransaction()
Creates a newTransaction
instances that is returned in theTransactionState.IDLE
state which can be populated with application specific attachments or assigned a linked resource prior to calling thejava.util.Collection<Transaction<TransactionController>>
TransactionController. transactions()
Returns a list ofTransaction
objects that are active within thisTransactionController
which have not reached a terminal state meaning they have not been successfully discharged and have not failed in either theDeclare
phase or theDischarge
phase.Method parameters in org.apache.qpid.protonj2.engine with type arguments of type TransactionController Modifier and Type Method Description TransactionController
TransactionController. addCapacityAvailableHandler(EventHandler<TransactionController> handler)
Allows the caller to add anEventHandler
that will be signaled when the underlying link for thisTransactionController
has been granted credit which would then allow for transactionDeclared
andDischarge
commands to be sent to the remote Transactional Resource.TransactionController
TransactionController. declare(Transaction<TransactionController> transaction)
Request that the remoteTransactionManager
declare a new transaction and respond with a new transaction Id for that transaction.TransactionController
TransactionController. declaredHandler(EventHandler<Transaction<TransactionController>> declaredEventHandler)
Called when theTransactionManager
end of the link has responded to a previousDeclare
request and the transaction can now be used to enroll deliveries into the active transaction.TransactionController
TransactionController. declareFailureHandler(EventHandler<Transaction<TransactionController>> declareFailureEventHandler)
Called when theTransactionManager
end of the link responds to aTransaction
declaration with anRejected
outcome indicating that the transaction could not be successfully declared.TransactionController
TransactionController. discharge(Transaction<TransactionController> transaction, boolean failed)
Request that the remoteTransactionManager
discharge the given transaction and with the specified failure state (true for failed).TransactionController
TransactionController. dischargedHandler(EventHandler<Transaction<TransactionController>> dischargedEventHandler)
Called when theTransactionManager
end of the link has responded to a previousdischarge(Transaction, boolean)
request and the transaction has been retired.TransactionController
TransactionController. dischargeFailureHandler(EventHandler<Transaction<TransactionController>> dischargeFailureEventHandler)
Called when theTransactionManager
end of the link has responded to a previousdischarge(Transaction, boolean)
request and the transaction discharge failed for some reason.TransactionController
TransactionController. parentEndpointClosedHandler(EventHandler<TransactionController> handler)
Sets aEventHandler
for when the parentSession
orConnection
of thisTransactionController
is locally closed. -
Uses of TransactionController in org.apache.qpid.protonj2.engine.impl
Classes in org.apache.qpid.protonj2.engine.impl that implement TransactionController Modifier and Type Class Description class
ProtonTransactionController
TransactionController
implementation that implements the abstraction around a sender link that initiates requests toDeclare
and toDischarge
AMQPTransaction
instance.Methods in org.apache.qpid.protonj2.engine.impl that return types with arguments of type TransactionController Modifier and Type Method Description Transaction<TransactionController>
ProtonTransactionController. declare()
java.util.Collection<Transaction<TransactionController>>
ProtonTransactionController. transactions()
-


SOME LIKE IT HOT A film by Billy Wilder Starring: Marilyn Monroe, Tony Curtis, Jack Lemmon, and Joe E. Brown
A miracle of filmmaking, "Some Like It Hot" is a brilliant film, and maybe the foremost example of slapstick comedy brought to screen with clever sight gags and plot twists. It is the pinnacle of writer-director Billy Wilder's career, a stunning feat considering the vast catalogue of films he had helped make.
Jerry (Lemmon) and Joe (Curtis) are two stage musicians who go from gig to gig, trying to earn enough money to feed themselves. One night, as they're playing at a banned Prohibition speakeasy, the place is raided. As it turns out, the owner, Spats Columbo (George Raft) was ratted out by Toothpick Charlie (George E. Stone). Several weeks later, on Valentine's Day, Jerry and Joe go to a garage to pick up a car and end up witnessing a gangland murder of Charlie by Columbo in a parking garage. Eager to escape, the duo are forced to take a job in Florida with all expenses paid. The only catch..its a girls band. So Josephine (Curtis) and Daphne (Lemmon), make their way onto the train and go to Florida. On the way there, they meet Sugar Kane (Monroe), a bombshell singer who is looking for love. Jerry and Joe immediately fall for the singer, but there's two problems: 1) they're in drag, and 2) millionaire Osgood Fielding (Joe E. Brown) falls madly in love with Daphne. What follows in pure hysteria, still complicated further by the arrival of Spats Columbo to Florida for the "Italian Opera Lovers Festival".
 Marilyn Monroe, in a wonderfully comic performance, is Sugar, providing incredible timing and sex appeal, along with true sincerity. The scenes, however, are all stolen by either Brown or Lemmon. Lemmon is hysterical as Daphne. Cast as the less rational one, Lemmon's performance is ridiculously crazy, it is disorder in the style all Billy Wilder's. Brown is particularly hilarious as Osgood, as we are treated to the finest kind of comedic irony. He manages to use Lemmon's ingenious performance as a springboard for an even loonier performance as a completely eccentric millionaire.
Every set-piece is flawless, as Wilder brilliantly changes settings constantly, and uses every comic trick in the book to make his picture. Wilder's script is stunning, as he carefully combines gangsters, cross-dressing, romance, sex, music, gender roles, and social taboos in a riotous blend of wit and oddball craziness. Wilder manages to create scenes of utter hysteria, so pitch-perfect that the audience is dying of laughter with the last comic piece, the final line of this absolutely incredible film. Wilder's is dead wrong when he says nobody's perfect: Billy Wilder is, especially when he makes something this disastrously funny. Nobody's perfect but Billy Wilder. RATING: **** out of ****
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
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Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


WEEK 6 STUDY SUGGESTIONS
Here is a suggested outline for studying this weekend:
- Fill In Learning Objective Document
- first: fill out the empty LO document on your own (
LOs_empty.md
)
- then: compare your document with the filled out version (
LOs_explained.md
)
- Review Weekly Notes
- additional notes on each days’ topics can be found in the
notes
directory
- Review the practice exercises in the
practice
directory
- inside you will find a directory for each topic that contains practice exercises for each of those topics
- instructions for each can be found in their respective
README.md
files
- recommended order:
d2-promise-practice
d3-async-await-practice
d4-unit-testing-practice
- Reminder: any topics covered in my weekly notes or in the LOs are fair game for the assessment!
- 2 hours
- Mixture of multiple choice (15-20) and VSCode (3-5) problems.
- Coding problems will have specs to run (
npm test
) and check your work against
- Part of the assessment will include writing tests using either
assert
or chai.expect
(our tests will test your tests… meta)
- Standard assessment procedures
- You will be in an individual breakout room
- Use a single monitor and share your screen
- Only have open those resources needed to complete the assessment:
- Zoom
- VSCode
- Browser with AAO and Progress Tracker (to ask questions)
- Approved Resources for this assessment:
- MDN: https://developer.mozilla.org/en-US/docs/Web/JavaScript
- Node.js Documentation: https://nodejs.org/docs/latest-v12.x/api/assert.html
- Chai Documentation: https://www.chaijs.com/api/bdd/


Explore what others are discussing !
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Loneliness is a complex and usually unpleasant emotional response to isolation. Older
persons who are not in regular contact with the outside world and the community need
company to keep in touch with the outside world. Many services exist to help older
persons to socialise, but it is not always easy to access them. This topic requires a
thorough discussion on the challenges and solutions to enable social contact for older
persons and to identify who can help them fight isolation. [...]
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An eager purely functional language with records and subtypes. The language has integers, booleans, recursive functions, and immutable records.
Sub is an extension of MiniML.


HEAD
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| 1 | /* | |
| 2 | * Licensed to the Apache Software Foundation (ASF) under one or more | |
| 3 | * contributor license agreements. See the NOTICE file distributed with | |
| 4 | * this work for additional information regarding copyright ownership. | |
| 5 | * The ASF licenses this file to You under the Apache License, Version 2.0 | |
| 6 | * (the "License"); you may not use this file except in compliance with | |
| 7 | * the License. You may obtain a copy of the License at | |
| 8 | * | |
| 9 | * http://www.apache.org/licenses/LICENSE-2.0 | |
| 10 | * | |
| 11 | * Unless required by applicable law or agreed to in writing, software | |
| 12 | * distributed under the License is distributed on an "AS IS" BASIS, | |
| 13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| 14 | * See the License for the specific language governing permissions and | |
| 15 | * limitations under the License. | |
| 16 | */ | |
| 17 | package org.apache.commons.imaging.formats.tiff.taginfos; | |
| 18 | ||
| 19 | import org.apache.commons.imaging.common.ByteConversions; | |
| 20 | import org.apache.commons.imaging.common.ByteOrder; | |
| 21 | import org.apache.commons.imaging.formats.tiff.constants.TiffDirectoryType; | |
| 22 | import org.apache.commons.imaging.formats.tiff.fieldtypes.FieldType; | |
| 23 | ||
| 24 | public class TagInfoFloat extends TagInfo { | |
| 25 | public TagInfoFloat(final String name, final int tag, final int length, final TiffDirectoryType directoryType) { | |
| 26 | super(name, tag, FieldType.FLOAT, length, directoryType); | |
| 27 | } | |
| 28 | | |
| 29 | public float[] getValue(final ByteOrder byteOrder, final byte[] bytes) { | |
| 30 |
1
1. getValue : mutated return of Object value for org/apache/commons/imaging/formats/tiff/taginfos/TagInfoFloat::getValue to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return ByteConversions.toFloats(bytes, byteOrder); |
| 31 | } | |
| 32 | | |
| 33 | public byte[] encodeValue(final ByteOrder byteOrder, final float... values) { | |
| 34 |
1
1. encodeValue : mutated return of Object value for org/apache/commons/imaging/formats/tiff/taginfos/TagInfoFloat::encodeValue to ( if (x != null) null else throw new RuntimeException ) → KILLED |
return ByteConversions.toBytes(values, byteOrder); |
| 35 | } | |
| 36 | } | |
Mutations | ||
| 30 |
1.1 |
|
| 34 |
1.1 |


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| Opcode/Instruction | Op/En | 64/32 bit Mode Support | CPUID Feature Flag | Description |
|---|---|---|---|---|
| 66 0F 73 /3 ib PSRLDQ xmm1, imm8 | A | V/V | SSE2 | Shift xmm1 right by imm8 while shifting in 0s. |
| VEX.128.66.0F.WIG 73 /3 ib VPSRLDQ xmm1, xmm2, imm8 | B | V/V | AVX | Shift xmm2 right by imm8 bytes while shifting in 0s. |
| VEX.256.66.0F.WIG 73 /3 ib VPSRLDQ ymm1, ymm2, imm8 | B | V/V | AVX2 | Shift ymm1 right by imm8 bytes while shifting in 0s. |
| EVEX.128.66.0F.WIG 73 /3 ib VPSRLDQ xmm1, xmm2/m128, imm8 | C | V/V | AVX512VL AVX512BW | Shift xmm2/m128 right by imm8 bytes while shifting in 0s and store result in xmm1. |
| EVEX.256.66.0F.WIG 73 /3 ib VPSRLDQ ymm1, ymm2/m256, imm8 | C | V/V | AVX512VL AVX512BW | Shift ymm2/m256 right by imm8 bytes while shifting in 0s and store result in ymm1. |
| EVEX.512.66.0F.WIG 73 /3 ib VPSRLDQ zmm1, zmm2/m512, imm8 | C | V/V | AVX512BW | Shift zmm2/m512 right by imm8 bytes while shifting in 0s and store result in zmm1. |
| Op/En | Tuple Type | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| A | NA | ModRM:r/m (r, w) | imm8 | NA | NA |
| B | NA | VEX.vvvv (w) | ModRM:r/m (r) | imm8 | NA |
| C | Full Mem | EVEX.vvvv (w) | ModRM:r/m (R) | Imm8 | NA |
Shifts the destination operand (first operand) to the right by the number of bytes specified in the count operand (second operand). The empty high-order bytes are cleared (set to all 0s). If the value specified by the count operand is greater than 15, the destination operand is set to all 0s. The count operand is an 8-bit immediate.
In 64-bit mode and not encoded with VEX/EVEX, using a REX prefix in the form of REX.R permits this instruction to access additional registers (XMM8-XMM15).
128-bit Legacy SSE version: The source and destination operands are the same. Bits (MAXVL-1:128) of the corresponding YMM destination register remain unchanged.
VEX.128 encoded version: The source and destination operands are XMM registers. Bits (MAXVL-1:128) of the destination YMM register are zeroed.
VEX.256 encoded version: The source operand is a YMM register. The destination operand is a YMM register. The count operand applies to both the low and high 128-bit lanes.
VEX.256 encoded version: The source operand is YMM register. The destination operand is an YMM register. Bits (MAXVL-1:256) of the corresponding ZMM register are zeroed. The count operand applies to both the low and high 128-bit lanes.
EVEX encoded versions: The source operand is a ZMM/YMM/XMM register or a 512/256/128-bit memory location. The destination operand is a ZMM/YMM/XMM register. The count operand applies to each 128-bit lanes.
Note: VEX.vvvv/EVEX.vvvv encodes the destination register.
TEMP ← COUNT IF (TEMP > 15) THEN TEMP←16; FI DEST[127:0]←SRC[127:0] >> (TEMP * 8) DEST[255:128]←SRC[255:128] >> (TEMP * 8) DEST[383:256]←SRC[383:256] >> (TEMP * 8) DEST[511:384]←SRC[511:384] >> (TEMP * 8) DEST[MAXVL-1:512] ← 0;
TEMP ← COUNT IF (TEMP > 15) THEN TEMP←16; FI DEST[127:0]←SRC[127:0] >> (TEMP * 8) DEST[255:128]←SRC[255:128] >> (TEMP * 8) DEST[MAXVL-1:256] ← 0;
TEMP ← COUNT IF (TEMP > 15) THEN TEMP←16; FI DEST←SRC >> (TEMP * 8) DEST[MAXVL-1:128] ← 0;
TEMP ← COUNT IF (TEMP > 15) THEN TEMP←16; FI DEST←DEST >> (TEMP * 8) DEST[MAXVL-1:128] (Unmodified)
(V)PSRLDQ __m128i _mm_srli_si128 ( __m128i a, int imm)
VPSRLDQ __m256i _mm256_bsrli_epi128 ( __m256i, const int)
VPSRLDQ __m512i _mm512_bsrli_epi128 ( __m512i, int)
None.
None.
Non-EVEX-encoded instruction, see Exceptions Type 7.
EVEX-encoded instruction, see Exceptions Type E4NF.nb.


If you use assistive technology (such as a screen reader) and need a
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Details
The Skills Funding Agency is committed to developing ways to engage additional providers into the advanced learner loans programme.
The application process will open in mid-November 2015, with completed applications to be returned by mid-December 2015.


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West Brom Basketball Club notch opening win on third attempt
West Brom Basketball Club's premier division side secured their first win of the season - getting the better of Aston Manor Academy 69-63 in a hard fought contest.
Tim Rudge's side had started the league season with two straight defeats, but got going at the third attempt at home.
The Black Country side got off to a good start in the encounter with Captain Cash Evans leading the way in the opening period, scoring 10 of his team-high 16 points as the hosts took a hold of the game early on.
An even second quarter saw Aston Manor rally slightly, but they could only chip into West Brom's margin by a solitary point as both sides laboured into the half time break, with West Brom leading 38-32.
Following the break, Aston continued to struggle against West Brom's steadfast defence, and whilst the host's were dominating at their own end, they themselves were also failing to convert shots of their own.
They did manage to extend their lead however, going into the fourth quarter with a nine-point cushion, with the scores at 55-46 in their favour.
The visitors mounted a comeback charge as they hoped to break West Brom's resolve in the final period, but despite bringing the score to within three, Rudge's side were not to be denied as they eventually held on to secure their first win of the campaign.
Evans was delighted to secure the first win of the campaign, but admitted the focus now has to be on the next challenge:
"We showed spells of our potential throughout the game, I think." he said.
"Things are starting the click as we grow more comfortable as a unit. With some of the new additions to the team, naturally it takes some time to learn how everyone plays and can contribute.
"I think Stefan [Artzrouni] and James [Tweedale] have really helped us, and their contribution on the day was clear to see on and off the scoresheet.
"It's nice to get our first win, but for us the feeling is short-lived. We're completely focused on the next game and performance.
"Each game we play we grow as individuals and a collective. We're looking forward to the next game and the rest of the season."
West Brom's premier division side will next face a trip to Birmingham Mets on Monday November 25.


The Global Alliance for Genomics and Health (GA4GH) Genomics v0.5.1 API will allow the interoperable exchange of genomic information across multiple organizations and on multiple platforms. This is a freely available open standard for interoperability, that uses common web protocols to support serving and sharing of data on DNA sequences and genomic variation. The API is implemented as a webservice to create a data source which may be integrated into visualization software, web-based genomics portals or processed as part of genomic analysis pipelines. It overcomes the barriers of incompatible infrastructure between organizations and institutions to enable DNA data providers and consumers to better share genomic data and work together on a global scale, advancing genome research and clinical application.
This v0.5.1 of the genomics API has been developed using Apache Avro to model the data. The documentation presented here is provided as a freely available blueprint for software developers to take and implement alongside those already at the EBI, NCBI and Google.
The Avro data model comprises of 3 main resources, Reads, Variants and the Reference. The following section describes each of these aspects of the model in turn, followed by an example of using the API to search for Variants
A GAVariant represents a change in DNA sequence relative to some reference. For example, a variant could represent a SNP or an insertion. Variants belong to a GAVariantSet. This is equivalent to a row in VCF.
When implemented as a REST web service the API may be used in the standard POST GET http request pattern. Below is an example of making a POST GASearchVariantsRequest
request to query the /variants/search
endpoint which returns a list of GAVariants
matching the search criteria.
POST /variants/search
In the request body, supply data with the following structure as JSON:
{ "datasetId": string, "variantName": string, "callsetNames": [ string ], "callsetIds": [ string ], "contig": string, "startPosition": long, "endPosition": long, "pageToken": string, "maxResults": long }
| Type | Field | Default Value | Description |
|---|---|---|---|
| array<string> | variantSetIds | [] | Required. The IDs of the variant sets to search over. |
| null | string | variantName | null | Only return variants which have exactly this name. |
| array<string> | callSetIds | [] | Only return variant calls which belong to call sets with these IDs. Leaving this blank returns all variant calls. |
| string | referenceName | Required. Only return variants on this reference. |
|
| long | start | Required. The beginning of the window (0-based, inclusive) for which overlapping variants should be returned. |
|
| long | end | Required. The end of the window (0-based, exclusive) for which overlapping variants should be returned. |
|
| null | string | pageToken | null | The continuation token, which is used to page through large
result sets.
To get the next page of results, set this parameter to the value of
|
| long | maxResults | 10 | The maximum number of variants to return in each response.
If more variants match this request, the |
If successful, this method returns a response body as a GASearchVariantsResponse as JSON with the following structure:
{ "variants": [ { "datasetId": string, "id": string, "names": [ string ], "created": long, "contig": string, "position": long, "referenceBases": string, "alternateBases": [ string ], "info": { (key): [ string ] }, "calls": [ { "callsetId": string, "callsetName": string, "genotype": [ integer ], "phaseset": string, "genotypeLikelihood": [ double ], "info": { (key): [ string ] } } ] } ], "nextPageToken": string }
| Type | Field | Default Value | Description |
|---|---|---|---|
| array<GAVariant> | variants | [] | The list of matching variants.
If the |
| null | string | nextPageToken | null | The continuation token, which is used to page through large result sets. Provide this value in a subsequent request to return the next page of results. This field will be empty if there aren't any additional results. |
A full list of methods and endpoints can be found here on our v0.5.1 documentation page


Absolutely nothing! All our services are free.
Not a thing! We are completely confidential.
No, walk-ins are welcome. However, it is recommended that you call and let us know you are on your way.
Birthright uses a medical-quality test, which is the most accurate and sensitive urine pregnancy test available. Let us run our lab-quality pregnancy test for you at no charge.
Yes, we are happy to do so. We also can help you navigate the application process.
Whether your result was positive or negative, you are welcome to come in for a back-up test with our medical-quality pregnancy test—which may be more sensitive than your over-the-counter test. It’s accurate, fast, and free. Or you’re welcome to simply come in and explore how we can help you.
Call us, and we will make arrangements for a special appointment. We want you to get the help you need!
They vary from woman to woman, but the most common symptoms are:
If you suspect you might be pregnant, let us help you with the first step—a pregnancy test.
Birthright will listen to your concerns and help you overcome whatever challenges you may face. Let’s talk.
Contact our pregnancy center today. If you think you might be pregnant, do not hesitate to give us a call. Our caring staff can help guide you through every step from free testing to ongoing counseling and community resources. We are here for you.


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| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface BeanDeclaration
Definition of an interface for declaring a bean in a configuration file.
Commons Configurations allows to define beans (i.e. simple Java objects) in configuration files, which can be created at runtime. This is especially useful if you program against interfaces and want to define the concrete implementation class is a configuration file.
This interface defines methods for retrieving all information about a bean that should be created from a configuration file, e.g. the bean's properties or the factory to use for creating the instance. With different implementations different "layouts" of bean declarations can be supported. For instance if an XML configuration file is used, all features of XML (e.g. attributes, nested elements) can be used to define the bean. In a properties file the declaration format is more limited. The purpose of this interface is to abstract from the concrete declaration format.
| Method Summary | |
|---|---|
String |
getBeanClassName()
Returns the name of the bean class, from which an instance is to be created. |
String |
getBeanFactoryName()
Returns the name of the BeanFactory that should be used
for creating the bean instance. |
Object |
getBeanFactoryParameter()
Here an arbitrary object can be returned that will be passed to the bean factory. |
Map<String,Object> |
getBeanProperties()
Returns a map with properties that should be initialized on the newly created bean. |
Map<String,Object> |
getNestedBeanDeclarations()
Returns a map with declarations for beans that should be set as properties of the newly created bean. |
| Method Detail |
|---|
String getBeanFactoryName()
BeanFactory
that should be used
for creating the bean instance. This can be null, then a default
factory will be used.
Object getBeanFactoryParameter()
String getBeanClassName()
Map<String,Object> getBeanProperties()
Map<String,Object> getNestedBeanDeclarations()
BeanDeclaration
implementations or collections thereof. They will be treated like this
declaration (in a* recursive manner), and the resulting beans are
assigned to the corresponding properties.
|
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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


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Upload Form
Insert Annotation in following Box
{{form.Annotation(rows='20',cols='50')}}
Select Source for insert
{{form.Sel_Dir}}
Enter directory name if not found in selection box
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|
BitShares-Core
6.1.0
BitShares blockchain implementation and command-line interface software
|
defines vesting in terms of coin-days accrued which allows for dynamic deposit/withdraw More...
#include <vesting_balance_object.hpp>
Public Member Functions | |
| fc::uint128_t | compute_coin_seconds_earned (const vesting_policy_context &ctx) const |
| void | update_coin_seconds_earned (const vesting_policy_context &ctx) |
| asset | get_allowed_withdraw (const vesting_policy_context &ctx) const |
| bool | is_deposit_allowed (const vesting_policy_context &ctx) const |
| bool | is_deposit_vested_allowed (const vesting_policy_context &ctx) const |
| bool | is_withdraw_allowed (const vesting_policy_context &ctx) const |
| void | on_deposit (const vesting_policy_context &ctx) |
| void | on_deposit_vested (const vesting_policy_context &ctx) |
| void | on_withdraw (const vesting_policy_context &ctx) |
Public Attributes | |
| uint32_t | vesting_seconds = 0 |
| fc::uint128_t | coin_seconds_earned |
| fc::time_point_sec | start_claim |
| fc::time_point_sec | coin_seconds_earned_last_update |
defines vesting in terms of coin-days accrued which allows for dynamic deposit/withdraw
The economic effect of this vesting policy is to require a certain amount of "interest" to accrue before the full balance may be withdrawn. Interest accrues as coindays (balance * length held). If some of the balance is withdrawn, the remaining balance must be held longer.
Definition at line 89 of file vesting_balance_object.hpp.
| fc::uint128_t graphene::chain::cdd_vesting_policy::compute_coin_seconds_earned | ( | const vesting_policy_context & | ctx | ) | const |
Compute coin_seconds_earned. Used to non-destructively figure out how many coin seconds are available.
Definition at line 93 of file vesting_balance_object.cpp.
| asset graphene::chain::cdd_vesting_policy::get_allowed_withdraw | ( | const vesting_policy_context & | ctx | ) | const |
Definition at line 114 of file vesting_balance_object.cpp.
| bool graphene::chain::cdd_vesting_policy::is_deposit_allowed | ( | const vesting_policy_context & | ctx | ) | const |
Definition at line 147 of file vesting_balance_object.cpp.
| bool graphene::chain::cdd_vesting_policy::is_deposit_vested_allowed | ( | const vesting_policy_context & | ctx | ) | const |
Definition at line 153 of file vesting_balance_object.cpp.
| bool graphene::chain::cdd_vesting_policy::is_withdraw_allowed | ( | const vesting_policy_context & | ctx | ) | const |
Definition at line 158 of file vesting_balance_object.cpp.
| void graphene::chain::cdd_vesting_policy::on_deposit | ( | const vesting_policy_context & | ctx | ) |
Definition at line 124 of file vesting_balance_object.cpp.
| void graphene::chain::cdd_vesting_policy::on_deposit_vested | ( | const vesting_policy_context & | ctx | ) |
Definition at line 129 of file vesting_balance_object.cpp.
| void graphene::chain::cdd_vesting_policy::on_withdraw | ( | const vesting_policy_context & | ctx | ) |
Definition at line 135 of file vesting_balance_object.cpp.
| void graphene::chain::cdd_vesting_policy::update_coin_seconds_earned | ( | const vesting_policy_context & | ctx | ) |
Update coin_seconds_earned and coin_seconds_earned_last_update fields; called by both on_deposit() and on_withdraw().
Definition at line 108 of file vesting_balance_object.cpp.
| fc::uint128_t graphene::chain::cdd_vesting_policy::coin_seconds_earned |
Definition at line 92 of file vesting_balance_object.hpp.
| fc::time_point_sec graphene::chain::cdd_vesting_policy::coin_seconds_earned_last_update |
Definition at line 95 of file vesting_balance_object.hpp.
| fc::time_point_sec graphene::chain::cdd_vesting_policy::start_claim |
while coindays may accrue over time, none may be claimed before first_claim date
Definition at line 94 of file vesting_balance_object.hpp.
| uint32_t graphene::chain::cdd_vesting_policy::vesting_seconds = 0 |
Definition at line 91 of file vesting_balance_object.hpp.


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solos::Tec
Home
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Connections
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Games using the TAINT model can be created in whatever way you prefer, as long as they adhere to the game model and are stored as an XML file.
This means that one could potentially build games writing pure XML, although it’s probably much simpler to do it using some program with a user interface.
The XML structure is only necessary if you wish to do more advanced stuff rather than just using the given editor and interpreter.
Generally speaking, the overall idea is broken down into 3 modules: the model, the editor and the interpreter. While we provide an editor (a program that allows you to graphically create games) and two interpreters (a program that allows you to play the games), anyone is welcome to build or use their own. The only important thing is that they adhere to the model specifications as explained in the What is a TAINT game? section.
The main tag which contains all the others is the <Game> tag. It contains the <GameName> the <Author> tags which contain the name of the game (e.g. Escape from the mines) and the name of the author(s). It also contains the <StartingScene> tag which sets the starting scene by name (e.g. Cave 1).
It then contains the <GlobalResources>, <GlobalActions> and <Scenes> tags. The <GlobalResources> contains a number of <Resource> elements which represent the global resources of the game. The <GlobalActions> block contains a number of <Action> elements which represent the global actions of the game. Finally the <Scenes> block contains a block of <Scene> elements.
For example:
<Resource>
<Name>HP</Name>
<Type>Number</Type>
<Value>20</Value>
</Resource>
For example:
<Condition>
<ConditionFunction>equals</ConditionFunction>
<LeftHandSide Type="Resource">HP</LeftHandSide>
<RightHandSide Type="Number">50</RightHandSide>
</Condition>
Each <arg> element, similarly to the <LeftHandSide> and <RightHandSide> elements of a <Condition>, has a Type attribute to set the type of the argument passed to the function and of course a value of that type.
For example:
<Effect>
<EffectFunction>Tell player</EffectFunction>
<args>
<arg Type="Text">You hear a voice.</arg>
</args>
</Effect>
Simple game with 1 scene which contains 1 action and 1 resource:
<?xml version="1.0" encoding="utf-8"?>
<Game>
<GameName>Test Game</GameName>
<Author>Alex</Author>
<StartingScene>New Scene</StartingScene>
<GlobalResources>
</GlobalResources>
<GlobalActions>
</GlobalActions>
<Scenes>
<Scene>
<Name>New Scene</Name>
<Description>This is a new scene.</Description>
<Resources>
<Resource>
<Name>HP</Name>
<Type>Number</Type>
<Value>50</Value>
</Resource>
</Resources>
<Actions>
<Action>
<Name>go</Name>
<Visible>True</Visible>
<Enabled>True</Enabled>
<Active>True</Active>
<Conditions>
<Condition>
<ConditionFunction>equals</ConditionFunction>
<LeftHandSide Type="Resource">HP</LeftHandSide>
<RightHandSide Type="Number">50</RightHandSide>
</Condition>
</Conditions>
<EffectsIfTrue>
<Effect>
<EffectFunction>Tell player</EffectFunction>
<args>
<arg Type="Text">Indeed the HP is equal to 50.</arg>
</args>
</Effect>
</EffectsIfTrue>
<EffectsIfFalse/>
</Action>
</Actions>
</Scene>
</Scenes>
</Game>


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module m_KdTree !!# KdTree !!Build and search k-dimensional trees in 2, 3, and K dimensions. !!This KdTree is balanced, in that splits are made along the dimension with the largest variance. !!A quickselect is used to quickly find the median in each splitting dimension as the splitting value. !!The ends of each branch contain multiple leaves to prevent tail recursion. !!An in-depth example is given below on how to use all the aspects of the KdTree and KdTreeSearch classes. !! !!Important: Once a tree has been built with a set, do not change their values. The KdTree does NOT make !!a copy of the input values used to build it. !!Important: Generating the tree does not modify the values used to build it. !! !!## Building the KdTree !!The KdTree object can be initialized on assignment by entering point co-ordinates. !!To build a 2-D tree, you can use two 1-D arrays as the x, y, co-ordinates, and optionally a third 1-D array !!to build a 3-D tree. !!```fortran !!use m_KdTree !!type(KdTree) :: tree !!tree = KdTree(x, y, [z]) !!``` !!Or you can build a k-dimensional tree using a 2-D array, where the first dimension is the number of items, !!and the second is the number of dimensions, k. !!```fortran !!use m_KdTree !!type(KdTree) :: tree !!tree = KdTree(D) !!``` !! !!## Querying the KdTree !!After the tree is initialized, a search class can be used to perform search for the nearest neighbour, !!the k nearest neighbours, all neighbours within a radius, k nearest within a radius, and items within !!upper and lower bounds in each dimension. !!The searches are thread safe and can be used in a parallel region. !! !!After the KdTree is built, various queries can be carried out. Searches that return multiple values !!are called using the argDynamicArray within coretran. The [[m_dArgDynamicArray]] contains an integer index !!containing the indices into the co-ordinates that are closest, and a double precision that contains the !!distance from the query point to those points. !! !!```fortran !!use m_dArgDynamicArray !!use m_KdTree !!type(KdTreeSearch) :: search !!integer(i32) :: i !!type(dArgDynamicArray) :: da !!! Nearest Neighbour to (0, 0), for 3D add z, and zQuery !!i = search%nearest(tree, x, y, [z], xQuery = 0.d0, yQuery = 0.d0, [zQuery = 0.d0]) !!! K-Nearest to (0, 0), for 3D add z, and zQuery !!da = search%kNearest(tree, x, y, [z], xQuery = 0.d0, yQuery = 0.d0, [zQuery = 0.d0], k = 10) !!! Search for all points within a given distance !!da = search%kNearest(tree, x, y, [z], xQuery = 0.d0, yQuery = 0.d0, [zQuery = 0.d0], radius = 10.d0) !!! Search for all k points within a given distance !!da = search%kNearest(tree, x, y, [z], xQuery = 0.d0, yQuery = 0.d0, [zQuery = 0.d0], k = 10, radius = 10.d0) !!``` !! !!##  Create some random points in space !!N = 1d6 !!call allocate(x, N) !!call allocate(y, N) !!call rngNormal(x) !!call rngNormal(y) !!! Build the tree !!tree = KdTree(x, y) !!! Get the nearest neighbour to (0, 0) !!ia = search%kNearest(tree, x, y, xQuery = 0.d0, yQuery = 0.d0) !!write(*,'(a)') 'Nearest point to the query location: '//str(x(ia))//str(y(ia)) !!! Get the 10 nearest neighbours to the query !!da = search%kNearest(tree, x, y, xQuery = 0.d0, yQuery = 0.d0, k = 10) !!write(*,'(a)') 'The 10 nearest neighbour indices and distances:' !!call da%print() !!! Find all the points within a 1.d0 !!da = search%kNearest(tree, x, y, xQuery = 0.d0, yQuery = 0.d0, radius = 1.d0) !!write(*,'(a)') 'The points within a distance of 1.d0' !!call da%print() !!Deallocate any tree memory !!call tree%deallocate() !! !!!====================================================================! !!! 3D KdTree example !!!====================================================================! !!! Create the third dimension !!call allocate(z, N) !!call rngNormal(z) !!! Build the tree !!tree = KdTree(x, y, z) !!! Get the nearest neighbour to (0, 0, 0) !!ia = search%kNearest(tree, x, y, z, xQuery = 0.d0, yQuery = 0.d0, zQuery = 0.d0) !!write(*,'(a)')'Nearest point to the query location: '//str(x(ia))//str(y(ia))//str(z(ia)) !!! Get the 10 nearest neighbours to the query !!da = search%kNearest(tree, x, y, z, xQuery = 0.d0, yQuery = 0.d0, zQuery = 0.d0, k = 10) !!write(*,'(a)') 'The 10 nearest neighbour indices and distances:' !!call da%print() !!! Find all the points within a 1.d0 !!da = search%kNearest(tree, x, y, z, xQuery = 0.d0, yQuery = 0.d0, zQuery = 0.d0, radius = 1.d0) !!write(*,'(a)') 'The points within a distance of 1.d0' !!call da%print() !!Deallocate any tree memory !!call tree%deallocate() !! !!!====================================================================! !!! KD KdTree example !!!====================================================================! !!call allocate(D, [N, 3]) !!D(:,1) = x !!D(:,2) = y !!D(:,3) = z !!! Build the tree !!tree = KdTree(D) !!! Get the nearest neighbour to (0, 0, 0) !!ia = search%kNearest(tree, D, query = [0.d0, 0.d0, 0.d0]) !!write(*,'(a)')'Nearest point to the query location: '//str(D(ia, 1))//str(D(ia, 2))//str(D(ia, 3)) !!! Get the 10 nearest neighbours to the query !!da = search%kNearest(tree, D, query = [0.d0, 0.d0, 0.d0], k = 10) !!write(*,'(a)') 'The 10 nearest neighbour indices and distances:' !!call da%print() !!! Find all the points within a 1.d0 !!da = search%kNearest(tree, D, query = [0.d0, 0.d0, 0.d0], radius = 1.d0) !!write(*,'(a)') 'The points within a distance of 1.d0' !!call da%print() !!Deallocate any tree memory !!call tree%deallocate() !!call deallocate(x) !!call deallocate(y) !!call deallocate(z) !!call deallocate(D) !!end program !!``` use variableKind, only: i32, r64 use m_allocate, only: allocate use m_array1D, only: arange use m_deallocate, only: deallocate use m_errors, only: eMsg use m_maths, only: variance use iDynamicArray_Class, only: iDynamicArray use dArgDynamicArray_Class, only: dArgDynamicArray use m_select, only: argSelect use m_strings, only: str implicit none private public :: KdTree public :: KdTreeSearch !====================================================================! ! Type Definitions !====================================================================! !====================================================================! type, private :: KdTreebranch private !! A branch of the tree, could be a leaf, or branch integer(i32) :: splitAlong !index of median in dat d real(r64) :: median !median value in dat x integer(i32) :: left, right ! left and right indices type(KdTreeBranch), pointer :: buds(:) => null() contains procedure :: init => init_branch !! KdTreeBranch%init() - Initialize the class procedure :: deallocate => deallocate_branch !! KdTreeBranch%deallocate() - deallocate the branch end type !====================================================================! !====================================================================! type :: KdTree !!KdTree in 2, 3, or N dimensions. See [[m_KdTree]] for more information on how to use this class. private type(KdTreebranch) :: trunk integer(i32),allocatable :: indx(:) integer(i32) :: nDims integer(i32) :: N logical(i32) :: set =.false. contains procedure, public :: deallocate => deallocate_KdTree !! kdTree%deallocate() - deallocate the recursive pointers end type !====================================================================! !====================================================================! type :: KdTreeSearch !!Class to search a KdTree. See [[m_KdTree]] for more information on how to use this class. contains generic, public :: nearest => nearest2D, nearest3D, nearestKD !! KdTreeSearch%nearest() - Perform a nearest neighbour search procedure, private :: nearest2D => nearest_2D !! Overloaded type bound procedure with KdTreeSearch%nearest() procedure, private :: nearest3D => nearest_3D !! Overloaded type bound procedure with KdTreeSearch%nearest() procedure, private :: nearestKD => nearest_KD !! Overloaded type bound procedure with KdTreeSearch%nearest() generic, public :: kNearest => kNearest2D, kNearest3D, kNearestKD !! KdTreeSearch%kNearest() - Perform a k nearest neighbour search or a radius search. procedure, private :: kNearest2D => kNearest_2D !! Overloaded type bound procedure with KdTreeSearch%kNearest() procedure, private :: kNearest3D => kNearest_3D !! Overloaded type bound procedure with KdTreeSearch%kNearest() procedure, private :: kNearestKD => kNearest_KD !! Overloaded type bound procedure with KdTreeSearch%kNearest() generic, public :: rangeSearch => rangeSearch2D, rangeSearch3D, rangeSearchKD !! KdTreeSearch%rangeSearch() - Find all points within axis aligned lower and upper bounds procedure, private :: rangeSearch2D => rangeSearch_2D !! Overloaded type bound procedure with KdTreeSearch%rangeSearch() procedure, private :: rangeSearch3D => rangeSearch_3D !! Overloaded type bound procedure with KdTreeSearch%rangeSearch() procedure, private :: rangeSearchKD => rangeSearch_KD !! Overloaded type bound procedure with KdTreeSearch%rangeSearch() end type !====================================================================! !====================================================================! ! Interface definitions !====================================================================! interface !====================================================================! module subroutine init_branch(this, left,right) !! Overloaded Type bound procedure KdTreeBranch%init() !====================================================================! class(KdTreebranch) :: this !! KdTreeBranch class integer(i32), intent(in) :: left !! Left index, first call normally = 1 integer(i32), intent(in) :: right !! Right index, first call normally = size of coordinates end subroutine !====================================================================! !====================================================================! module recursive subroutine deallocate_branch(this) !====================================================================! class(KdTreebranch) :: this !! KdTreeBranch class end subroutine !====================================================================! end interface interface KdTree !!Overloaded Initializer for a KdTree. !! !!Can be used to create a 2D, 3D, or ND, KdTree class. !! !!See [[m_KdTree]] for more information on how to use this class !====================================================================! module function init2D_KdTree(x, y) result(this) !! Overloaded by interface [[KdTree(type)]] !====================================================================! type(kdTree) :: this !! KdTree Class real(r64),intent(in) :: x(:) !! x-coordinates of the points real(r64),intent(in) :: y(:) !! y-coordinates of the points end function !====================================================================! !====================================================================! module function init3D_KdTree(x, y, z) result(this) !! Overloaded by interface [[KdTree(type)]] !====================================================================! type(kdTree) :: this !! KdTree Class real(r64),intent(in) :: x(:) !! x-coordinates of the points real(r64),intent(in) :: y(:) !! y-coordinates of the points real(r64),intent(in) :: z(:) !! z-coordinates of the points end function !====================================================================! !====================================================================! module function initKD_KdTree(D) result(this) !! Overloaded by interface [[KdTree(type)]] !====================================================================! type(kdTree) :: this !! KdTree Class real(r64),intent(in) :: D(:,:) !! Coordinates of the points, the k columns contain the k dimensional values. end function !====================================================================! end interface interface !====================================================================! module subroutine deallocate_KdTree(this) !! Overloaded Type bound procedure KdTree%deallocate() !====================================================================! class(KdTree) :: this !! KdTree Class end subroutine !====================================================================! end interface interface !====================================================================! module function nearest_2D(search, tree, x, y, xQuery, yQuery) result(nearest) !! Overloaded Type bound procedure KdTreeSearch%nearest() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: x(:) !! x co-ordinates of the points real(r64),intent(in) :: y(:) !! y co-ordinates of the points real(r64),intent(in) :: xQuery !! x co-ordinate of the query location real(r64),intent(in) :: yQuery !! y co-ordinate of the query location integer(i32) :: nearest !! Index of the nearest point to the query location end function !====================================================================! !====================================================================! module function nearest_3D(search, tree, x, y, z, xQuery, yQuery, zQuery) result(nearest) !! Overloaded Type bound procedure KdTreeSearch%nearest() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: x(:) !! x co-ordinates of the points real(r64),intent(in) :: y(:) !! y co-ordinates of the points real(r64),intent(in) :: z(:) !! z co-ordinates of the points real(r64),intent(in) :: xQuery !! x co-ordinate of the query location real(r64),intent(in) :: yQuery !! y co-ordinate of the query location real(r64),intent(in) :: zQuery !! z co-ordinate of the query location integer(i32) :: nearest !! Index of the nearest point to the query location end function !====================================================================! !====================================================================! module function nearest_KD(search, tree, D, query) result(nearest) !! Overloaded Type bound procedure KdTreeSearch%nearest() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: D(:,:) !! Co-ordinates of the points, the second dimension contains the k dimensions real(r64),intent(in) :: query(:) !! C-ordinate of the query location integer(i32) :: nearest !! Index of the nearest point to the query location end function !====================================================================! end interface interface !====================================================================! module function kNearest_2D(search, tree, x, y, xQuery, yQuery, k, radius) result(kNearest) !! Overloaded Type bound procedure KdTreeSearch%kNearest() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: x(:) !! x co-ordinates of the points real(r64),intent(in) :: y(:) !! y co-ordinates of the points real(r64),intent(in) :: xQuery !! x co-ordinate of the query location real(r64),intent(in) :: yQuery !! y co-ordinate of the query location integer(i32), intent(in), optional :: k !! Number of points to find that are closest to the query real(r64), intent(in), optional :: radius !! Only find neighbours within this distance from the query type(dArgDynamicArray) :: kNearest !! Indices of the nearest points to the query location end function !====================================================================! !====================================================================! module function kNearest_3D(search, tree, x, y, z, xQuery, yQuery, zQuery, k, radius) result(kNearest) !! Overloaded Type bound procedure KdTreeSearch%kNearest() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: x(:) !! x co-ordinates of the points real(r64),intent(in) :: y(:) !! y co-ordinates of the points real(r64),intent(in) :: z(:) !! z co-ordinates of the points real(r64),intent(in) :: xQuery !! x co-ordinate of the query location real(r64),intent(in) :: yQuery !! y co-ordinate of the query location real(r64),intent(in) :: zQuery !! z co-ordinate of the query location integer(i32), intent(in), optional :: k !! Number of points to find that are closest to the query real(r64), intent(in), optional :: radius !! Only find neighbours within this distance from the query type(dArgDynamicArray) :: kNearest !! Indices of the nearest points to the query location end function !====================================================================! !====================================================================! module function kNearest_KD(search, tree, D, query, k, radius) result(kNearest) !! Overloaded Type bound procedure KdTreeSearch%kNearest() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: D(:,:) !! Co-ordinates of the points, the second dimension contains the k dimensions real(r64),intent(in) :: query(:) !! Co-ordinate of the query location integer(i32), intent(in), optional :: k !! Number of points to find that are closest to the query real(r64), intent(in), optional :: radius !! Only find neighbours within this distance from the query type(dArgDynamicArray) :: kNearest !! Indices of the nearest points to the query location end function !====================================================================! end interface interface !====================================================================! module function rangeSearch_2D(search, tree, x, y, lowerBound, upperBound) result(iPoints) !! Overloaded Type bound procedure KdTreeSearch%rangeSearch() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: x(:) !! x co-ordinates of the points. real(r64),intent(in) :: y(:) !! y co-ordinates of the points. real(r64),intent(in) :: lowerBound(2) !! Lower bounds in x and y for the range search [xLow, yLow]. real(r64),intent(in) :: upperBound(2) !! Upper bounds in x and y for the range search [xHigh, yHigh]. type(iDynamicArray) :: iPoints !! Indices of the points inside the axis aligned range. end function !====================================================================! !====================================================================! module function rangeSearch_3D(search, tree, x, y, z, lowerBound, upperBound) result(iPoints) !! Overloaded Type bound procedure KdTreeSearch%rangeSearch() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: x(:) !! x co-ordinates of the points. real(r64),intent(in) :: y(:) !! y co-ordinates of the points. real(r64),intent(in) :: z(:) !! y co-ordinates of the points. real(r64),intent(in) :: lowerBound(3) !! Lower bounds in x and y for the range search [xLow, yLow]. real(r64),intent(in) :: upperBound(3) !! Upper bounds in x and y for the range search [xHigh, yHigh]. type(iDynamicArray) :: iPoints !! Indices of the points inside the axis aligned range. end function !====================================================================! !====================================================================! module function rangeSearch_KD(search, tree, D, lowerBound, upperBound) result(iPoints) !! Overloaded Type bound procedure KdTreeSearch%rangeSearch() !====================================================================! class(KdTreeSearch), intent(inout) :: search !! KdTreeSearch class class(kdTree),intent(in) :: tree !! KdTree class real(r64),intent(in) :: D(:,:) !! Co-ordinates of the points, the second dimension contains the k dimensions real(r64),intent(in) :: lowerBound(size(D,2)) !! Lower bounds in each dimension for the range search [Low1, Low2, ..., LowK]. real(r64),intent(in) :: upperBound(size(D,2)) !! Upper bounds in each dimension for the range search [High1, High2, ..., HighK]. type(iDynamicArray) :: iPoints !! Indices of the points inside the axis aligned range. end function !====================================================================! end interface end module