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JPIPKAK - JPIP Streaming
Driver short name
JPIPKAK
Build dependencies
Kakadu library
JPEG 2000 Interactive Protocol (JPIP) flexibility with respect to random access, code stream reordering and incremental decoding is highly exploitable in a networked environment allowing access to remote large files using limited bandwidth connections or high contention networks.
Driver capabilities
Supports Georeferencing
This driver supports georeferencing
JPIPKAK - JPIP Overview
A brief overview of the JPIP event sequence is presented in this section, more information can be found at JPEG 2000 Interactive Protocol (Part 9 – JPIP) and the specification can (and should) be purchased from ISO.
An earlier version of JPEG 2000 Part 9 is available here http://www.jpeg.org/public/fcd15444-9v2.pdf, noting the ISO copyright, diagrams are not replicated in this documentation.
The JPIP protocol has been abstracted in this format driver, requests are made at the 1:1 resolution level.
Initial JPIP request for a target image, a target id, a session over http, data to be returned as a jpp-stream are requested and a maximum length is put on the response. In this case no initial window is requested, though it can be. Server responds with a target identifier that can be used to identify the image on the server and a JPIP-cnew response header which includes the path to the JPIP server which will handle all future requests and a cid session identifier. A session is required so that that the server can model the state of the client connection, only sending the data that is required.
Client requests particular view windows on the target image with a maximum response length and includes the session identifier established in the previous communication. 'fsiz' is used to identify the resolution associated with the requested view-window. The values 'fx' and 'fy' specify the dimensions of the desired image resolution. 'roff' is used to identify the upper left hand corner off the spatial region associated with the requested view-windw. 'rsiz' is used to identify the horizontal and vertical extents of the spatial region associated with the requested view-window.
JPIPKAK -approach
The JPIPKAK driver uses an approach that was first demonstrated here, J2KViewer, by Juan Pablo Garcia Ortiz of separating the communication layer (socket / http) from the Kakadu kdu_cache object. Separating the communication layer from the data object is desirable since it allows the use of optimized http client libraries such as libcurl, Apache HttpClient (note that jportiz used a plain Java socket) and allows SSL communication between the client and server.
Kakadu's implementation of client communication with a JPIP server uses a socket, and this socket connection holds the state for this client session. A client session with Kakadu can be recreated using the JPIP cache operations between client and server, but no use of traditional HTTP cookies is supported since JPIP is neutral to the transport layer.
The JPIPKAK driver is written using a HTTP client library with the Kakadu cache object and supports optimized communication with a JPIP server (which may or may not support HTTP sessions) and the high performance of the kakadu kdu_region_decompressor.
JPIPKAK - implementation
The implementation supports the GDAL C++ and C API, and provides an initial SWIG wrapper for this driver with a Java ImageIO example (TODO - qGIS Example).
The driver uses a simple threading model to support requesting reads of the data and remote fetching. This threading model supports two separate client windows, with just one connection to the server. Requests to the server are multiplexed to utilize available bandwidth efficiently. The client identifies these windows by using “0” (low) or “1” (high) values to a “PRIORITY” metadata request option.
Note: SSL support
If the client is built with support for SSL, then driver determines whether to use SSL if the request is a jpips:// protocol as opposed to jpip:// . Note that the driver does not verify server certificates using the Curl certificate bundle and is currently set to accept all SSL server certificates.
Note: libCurl
JPIP sets client/server values using HTTP headers, modifications have been made to the GDAL HTTP portability library to support this.
GDALGetDatasetDriver
Fetch the driver to which this dataset relates.
Open
If the filename contained in the
GDALOpenInfo
object has a case insensitive URI scheme of JPIP or JPIPS theJPIPKAKDataset
is created and initialized, otherwise NULL is returned.Initialize
Initialization involves making an initial connection to the JPIP Server to establish a session and to retrieve the initial metadata about the image (ref. JPIP Sequence Diagram).
If the connection fails, the function returns false and the
Open
function returns NULL indicating that opening the dataset with this driver failed.If the connection is successful, then subsequent requests to the JPIP server are made to retrieve all the available metadata about the image. Metadata items are set using the
GDALMajorObject->SetMetadataItem
in the "JPIP" domain.If the metadata returned from the server includes GeoJP2 UUID box, or a GMLJP2 XML box then this metadata is parsed and sets the geographic metadata of this dataset.
GDALGetMetadata
C API to
JPIPKAKDataset->GetMetadata
GetMetadata
returns metadata for the "JPIP" domain, keys are "JPIP_NQUALITYLAYERS", "JPIP_NRESOLUTIONLEVELS", "JPIP_NCOMPS" and "JPIP_SPRECISION"
GDALEndAsyncRasterIO
If the asynchronous raster IO is active and not required, the C API calls
JPIPKAKDataset->EndAsyncRasterIO
EndAsyncRasterIO
The JPIPKAKAsyncRasterIO object is deleted
delete
GDALBeginAsyncRasterIO
C API to
JPIPKAKDataset->BeginAsyncRasterIO
BeginAsyncRasterIO
The client has set the requested view window at 1:1 and have optionally set the discard level, quality layers and thread priority metadata items.
Create
Creates a JPIPKAKAsyncRasterIO Object
Start
Configures the kakadu machinery and starts a background thread (if not already running) to communicate to the server the current view window request. The background thread results in the
kdu_cache
object being updated until the JPIP server sends an "End Of Response" (EOR) message for the current view window request.GDALLockBuffer
C API to LockBuffer
LockBuffer
Not implemented in
JPIPKAKAsyncRasterIO
, a lock is acquired inJPIPKAKAsyncRasterIO->GetNextUpdatedRegion
GDALGetNextUpdatedRegion
C API to GetNextUpdatedRegion
GetNextUpdatedRegion
The function decompresses the available data to generate an image (according to the dataset buffer type set in
JPIPKAKDataset->BeginAsyncRasterIO
) The window width, height (at the requested discard level) decompressed is returned in the region pointer and can be rendered by the client. The status of the rendering operation is one ofGARIO_PENDING, GARIO_UPDATE, GARIO_ERROR, GARIO_COMPLETE
from theGDALAsyncStatusType
structure.GARIO_UPDATE, GARIO_PENDING
require more reads of GetNextUpdatedRegion to get the full image data, this is the progressive rendering of JPIP.GARIO_COMPLETE
indicates the window is complete.GDALAsyncStatusType
is a structure used byGetNextUpdatedRegion
to indicate whether the function should be called again when either kakadu has more data in its cache to decompress, or the server has not sent an End Of Response (EOR) message to indicate the request window is complete.The region passed into this function is passed by reference, and the caller can read this region when the result returns to find the region that has been decompressed. The image data is packed into the buffer, e.g. RGB if the region requested has 3 components.
GDALUnlockBuffer
C Api to UnlockBuffer
UnlockBuffer
Not implemented in
JPIPKAKAsyncRasterIO
, a lock is acquired inJPIPKAKAsyncRasterIO->GetNextUpdatedRegion
Draw
Client renders image data
JPIPKAK - installation requirements
OpenSSL 0.9.8K (if SSL is required, a JPIPS connection)
Kakadu (tested with v5.2.6 and v6)
Currently only a Windows makefile is provided, however this should compile on Linux as well as there are no Windows dependencies.
See Also
NOTES
Driver originally developed by ITT VIS and donated to GDAL to enable SSL enabled JPIP client streaming of remote JPEG 2000 datasets.


Here is the big boy font.
Maybe a list should be below this:
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1) butter
2) eggs
3) water
Some title
some words in here
Some other title
some words in here2
[
Some title
some words in here
] [
Some other title
some words in here2
] :2col:END


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iterami
/
Guides.htm
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EVE Online
/Gnosis
Fittings:
DRONES-RANGE
Fittings
Code
Notes
Drone Control Range
[Gnosis, DRONES-RANGE] Co-Processor II Co-Processor II Drone Damage Amplifier II Drone Damage Amplifier II Drone Damage Amplifier II Drone Damage Amplifier II F-90 Compact Sensor Booster F-90 Compact Sensor Booster F-90 Compact Sensor Booster F-90 Compact Sensor Booster F-90 Compact Sensor Booster F-90 Compact Sensor Booster Drone Link Augmentor II Drone Link Augmentor II Drone Link Augmentor II Drone Link Augmentor II Drone Link Augmentor II Drone Link Augmentor II Medium Drone Control Range Augmentor I Medium Drone Control Range Augmentor II Medium Drone Control Range Augmentor II Federation Navy Hammerhead x5 Federation Navy Hobgoblin x5 Targeting Range Script x6


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Using
<script>
directly in the template.
Although the contents can be reactive, the
<script>
tag is only executed once. Basically you want to use
v-once
with it, to avoid unnecessary updating.
alert("{{ alertMessage }}");
You should see an alert box.


WITNESS LIST Licensing & Administrative Procedures Committee March 30, 2005-10:30A HB 2179 For: Smith, Patrick (Self and Texas Society of Professional Surveyors) HB 2533 Against: Furey, Robert (W.F.K.R.)


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Holmes, E.E.. 2018. Fish Catch Forecasting with R. Online text for short course (see teaching tab). Online
Ward, E. J., K. Oken, K. A. Rose, S. Sable, K. Watkins, E. E. Holmes, and M. D. Scheuerell. 2018. Applying spatiotemporal models to monitoring data to quantify fish responses to the Deepwater Horizon oil spill in the Gulf of Mexico. In press in Environmental Monitoring and Assessment.
Holmes, E. E., E. J. Ward and M. D. Scheuerell. 2018. Analysis of multivariate time series using the MARSS package PDF. User Guide for the MARSS R package 3.10.8
Holmes, E.E., M. D. Scheuerell, and E. J. Ward. 2017. Applied Time Series Analysis for Fisheries and Environmental Sciences. Online text for our course at University of Washington. Online
Ferguson, L., M. Srinivasan, E. Oleson, S. Hayes, S.K. Brown, R. Angliss, J. Carretta, E. Holmes, E. Ward, J. Kocik, K. Mullin, R. Dean, and J. Davis (eds.). 2017. Proceedings of the First National Protected Species Assessment Workshop. U.S. Dept. of Commer., NOAA. NOAA Technical Memorandum NMFS-F/SPO-172, 92 p. PDF
Tolimieri, N., E. E. Holmes, G. D. Williams, R. Pacunski, and D. Lowry. 2017. Population assessment using multivariate time-series analysis: A case study of rockfishes in Puget Sound. Ecology and Evolution 7(8): 2045-7758.  Status Review Update for Pacific Salmon and Steelhead Listed under the Endangered Species Act: Pacific Northwest. Nationa Marine Fisheries Service, Northwest Fisheries Science Center. PDF
Keith, D.M., H.R. Akcakaya, S.H.M. Butchart, B. Collen, N. K. Dulvy, E. E. Holmes, J. A. Hutchings, D. Keinath, M. K. Schwartz, A. O. Shelton, and R. S. Waples. 2015. Temporal correlations in population trends: Conservation implications from time-series analysis of diverse animal taxa. Biological Conservation 192:247-257. Selected for Editor’s Choice December 2015 PDF
See, K. E. and E. E. Holmes. 2015. Reducing bias and improving precision in species extinction forecasts. Ecological Applications 25: 1157-1165. PDF
Ruhi, A., E. E. Holmes, J. N. Rinne, and J. L. Sabo. 2015. Anomalous droughts, not invasion, decrease persistence of native fishes in a desert river. Global Change Biology 21:1482-1496. html PDF
Francis, T. B., E. M. Wolkovich, M. D. Scheuerell, S. L. Katz, E. E. Holmes, and S. E. Hampton. 2014. Shifting Regimes and Changing Interactions in the Lake Washington, USA, Plankton Community from 1962-1994. PlosOne e110363. PDF
Holmes, E. E. 2014. Computation of standardized residuals for (MARSS) models. Technical Report. arXiv:1411.0045 PDF
Ward, E.J., E.E. Holmes, J.T. Thorson, and B. Collen. 2014. Complexity is costly: a meta-analysis of parametric and non-parametric methods for short-term population forecasting. Oikos, 123(6): 652-661. Selected for Editor’s Choice June 2014. PDF
Hampton, S.E., E.E. Holmes, D.E. Pendleton, L.P. Scheef, M.D. Scheuerell, and E.J. Ward. 2013. Quantifying effects of abiotic and biotic drivers on community dynamics with multivariate autoregressive (MAR) models. Ecology 94(12): 2663-2669. Recommended by Faculty of 1000 Biology PDF
Holmes, E. E. 2013. Derivation of the EM algorithm for constrained and unconstrained multivariate autoregressive state-space (MARSS) models. Technical Report. arXiv:1302.3919 PDF Multivariate autoregressive state-space models go by different names in different fields. Dynamic linear models,vector autoregressive models, dynamic factor analysis models, multivariate discrete time Gompertz models and multivariate regression models with ARMA errors, are some of the many types of discrete time multivariate time-series models that can be written in MARSS form.
Mongillo, T. M., E. E. Holmes, D. P. Noren, G. R. VanBlaricom, A. E. Punt, S. M. O’Neill, G. M. Ylitalo, M. B. Hanson, P. S. Ross. 2012. Predicted polybrominated diphenyl ether (PBDE) and polychlorinated biphenyl (PCB) accumulation in southern resident killer whales. Marine Ecology Progress Series 453:263-277. PDF
Holmes, E.E., E.J. Ward, and K. Wills. 2012. MARSS: multivariate autoregressive state-space models for analyzing time series data. R Journal 4(1): 11-19. PDF
Scheef, L. P., D. E. Pendleton, S. E. Hampton, S. L. Katz, E. E. Holmes, M. D. Scheuerell, and D.G. Johns. 2012. Assessing marine plankton community structure from long-term monitoring data with multivariate autoregressive (MAR) models: a comparison of fixed station vs. spatially distributed sampling data. Limnology & Oceanography: Methods 10: 54-64. PDF
Ward, E.J., Semmens, B.X., Holmes, E.E., and K.C. Balcomb. 2011. Effects of multiple levels of social organization on survival and abundance. Conservation Biology 25(2): 350-355. PDF
Pattengill-Semmens, C. V., Semmens, B. X., E. E. Holmes, E. J. Ward, and B. I. Ruttenberg. 2011. Integrating time-series of community monitoring data. Proceedings of the Gulf and Caribbean Fisheries Institute 63: 214-216. PDF
Drake, J., E. A. Berntson, J. M. Cope, R. G. Gustafson, E. E. Holmes, P. S. Levin, N. Tolimieri, R. S. Waples, S. Sogard, G. D. Williams. 2010. Status review of five rockfish species in Puget Sound, Washington: Bocaccio (Sebastes paucispinis), canary rockfish (S. pinniger), yelloweye rockfish (S. ruberrimus), greenstriped rockfish (S. elongatus), and redstripe rockfish (S. proriger). U.S. Dept. of Commerce, NOAA Tech. Memo., NMFS-NWFSC-108. PDF
Ward, E.J., H. Chirrakal, M. Gonzalez-Suarez, D. Aurioles-Gamboa, E.E. Holmes, L. Gerber. 2010. Inferring spatial structure from time-series data: using multivariate state-space models to detect metapopulation structure of California sea lions in the Gulf of California, Mexico. Journal of Applied Ecology 47: 47-56. Recommended by Faculty of 1000 Biology PDF
Holmes, E. E. and E. J. Ward. 2010. Analysis of multivariate time series using the MARSS package. User Guide for the MARSS R package version 1.0. Now outdated and replaced by more recent editions.
Viscido, S. V. and E. E. Holmes. 2010. Statistical modelling of communities and ecosystems using the LAMDA software tool. Environmental Modelling and Software 25(12): 1905-1908. PDF
Ward, E.J., E. E. Holmes, and K. C. Balcomb. 2009. Quantifying the effects of prey abundance on killer whale reproduction. Journal of Applied Ecology 46(3): 632-64* PDF
Ward, E. J., E.E. Holmes, K. Parsons, K. C. Balcomb, and J. K. B. Ford. 2009. The role of menopause and reproductive senescence in a long-lived social mammal. Frontiers in Zoology 6(4). PDF
Ellner, S. P. and E. E. Holmes. 2008. Resolving the debate on when extinction risk is predictable. Ecology Letters 11: E1-E5. PDF
Hauser, D. D. W., M. G. Logsdon, E. E. Holmes, G. R. VanBlaricom, R. W. Osborne. 2007. Summer distribution patterns of Southern Resident killer whales (Orcinus orca): core areas and spatial segregation of social groups. Marine Ecology Progress Series 351: 301-31* Abstract
Holmes, E. E., J. L. Sabo, S. V. Viscido, and W. Fagan. 2007. A statistical approach to quasi-extinction forecasting. Ecology Letters 10:1182-1198 PDF List of data sets used
Holmes, E. E., L. Fritz, A. York and K. Sweeney. 2007. Age-structured modeling reveals long-term declines in the natality of western Steller sea lions. Ecological Applications 17:2214-2232. PDF Appendices In earlier versions of this paper, we had longer appendices which discussed why we feel that sightability and sex-ratios have not changed sufficiently to explain the dropping pup to nonpup ratio. This was cut during the 2nd revision process. Early draft of appendices Code to get lambda and scaled Leslie matrices
Hauser, D., G. VanBlaricom, E. Holmes, and R. Osbourne. 2006. Evaluating the use of whalewatch data in determining killer whale (Orcinus orca) distribution patterns. Journal of Cetacean Research and Management 8: 273-281. PDF
Gustafson,R. G., J. Drake, M. J. Ford, J. M. Myers, E. E. Holmes, and R. S. Waples. 2006. Status Review of Cherry Point Pacific Herring (Clupea pallasii) and Update of the Status Review of the Georgia Basin Distinct Population Segment of Pacific Herring Under the U.S. Endangered Species Act. U.S. Dept. Commer., NOAA Tech. Memo.NMFS-NWFSC-76, 182pp. PDF
Levin, P., E. E. Holmes, K. Piner and C. Harvey. 2006. Shifts in a Pacific Ocean fish assemblage: the potential influence of exploitation. Conservation Biology 20: 1181-119* PDF
Fagan, W. F and E. E. Holmes. 2006. Quantifying the extinction vortex. Ecology Letters 9:51-6* PDF
Holmes, E. E. 2004. Beyond theory to application and evaluation: diffusion approximations for population viability analysis. Ecological Applications 14: 1272-1293. PDF
Holmes, E. E. and B. Semmens. 2004. Population viability analysis for metapopulations: a diffusion approximation approach. Pp. 565-598 in Ecology, Genetics, and Evolution of Metapopulations, editors Illka Hanski and Oscar E. Gaggiotti. Elsevier Press. PDF
Sabo, J. L., E. E. Holmes, and P. Kareiva. 2004. The efficacy of simple viability models in ecological risk assessment: Does density dependence matter? Ecology 85: 328-341. PDF
Holmes, E. E. and A. E. York. 2003. Using age structure to detect impacts on threatened populations: a case study using Steller Sea Lions. Conservation Biology 17:1794-1806. PDF
McClure, M. M., E. E. Holmes, B. L. Sanderson, and C. E. Jordan. 2003. A large-scale, multi-species risk assessment: anadromous salmonids in the Columbia River Basin. Ecological Applications 13(4):964-989. PDF
Holmes, E. E. and W. F. Fagan. 2002. Validating population viability analysis for corrupted data sets. Ecology 83: 2379-2386. PDF
Holmes, E. E. 2001. Estimating risks in declining populations with poor data. Proceedings of the National Academy of Science 98: 5072-5077. PDF
Holmes, E. E. and P. M. Kareiva. 2000. Using single-species measurements to anticipate community level effects of environmental contaminants. In Environmental Contaminants and Terrestrial Vertebrates: Effects on Populations, Communities, and Ecosystems, P.H. Albers, G.H. Heinz, and H.M. Ohlendorf, editors. Published by the Society of Environmental Toxicology and Chemistry (SETAC), 315 pp. Link to book
Holmes, E. E. and H.B. Wilson. 1998. Running from trouble: long distance dispersal and the competitive coexistence of inferior species. American Naturalist 151: 578-586. PDF
Holmes, E. E. 1997. Basic epidemiological concepts in a spatial context. In Spatial Ecology (editors, D. Tilman and P. Kareiva). Princeton University Press. PDF
Holmes, E. E. 1995. Spatial models in ecology: explorations into the impact of spatial behavior on population dynamics. Dissertation. University of Washington.
Holmes, E. E., M.A. Lewis, J. Banks, and R. Veit. 1994. Partial differential equation models in ecology. Ecology 75: 17-29. PDF
Holmes, E. E. 1993. Is diffusion too simple? Comparisons with a telegraph model of dispersal. American Naturalist 142: 779-796. PDF
Holmes, E., W. L. Sibbitt Jr., and A. D. Bankhurst. 1986. Serum factors which suppress natural cytotoxicity in cancer patients. Int. Archives of Allergy and Applied Immunology 80(1): 39-43. Abstract


---
layout: post
title: conclusion about assembly book
date: '2009-12-14T12:47:00.000-08:00'
author: Daniel Hilst
blogger: true
tags:
modified_time: '2009-12-14T12:50:01.237-08:00'
blogger_id: tag:blogger.com,1999:blog-8785437776394405849.post-5545050478994837565
blogger_orig_url: http://gkos-hw.blogspot.com/2009/12/conclusion-about-assembly-book.html
---
It's unreadable
It's error prone
It's complicated
and is all about how computer works.. so
for this propose is the best, but
for real programming is sux
I still intent to lear more... about arrays, stack
and a lot of instructions .. my main goal is grasp
memory allocation, and afterward hardware manipulation
here is the link:
http://www.drpaulcarter.com/pcasm/
search below of "English:" keyword


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Qpid Dispatch 1.18.0 Release Notes
Dispatch is a lightweight AMQP 1.0 message router. More about
Qpid
Dispatch.
For more information about this release, including download links and
documentation, see the release overview.
New features and improvements
- DISPATCH-2223 - Incorporate pythoncapi_compat.h to keep up with CPython development
- DISPATCH-2225 - [http2] Remove the qdr_http2_session_data_t object and move its contents to qdr_http2_connection_t
- DISPATCH-2236 - Avoid freeing delivery state while holding the delivery lock
- DISPATCH-2238 - Avoid holding the core action lock when waking the core thread
- DISPATCH-2247 - "Received MAU from an unknown router" error message must include unknown router id
- DISPATCH-2250 - Add extra poll of pending output work on I/O thread
- DISPATCH-2251 - optimize qd_compose_insert_string_iterator
- DISPATCH-2273 - Remove support for Proton < 0.33 SASL extension API
Bugs fixed
- DISPATCH-413 - Improve the qdmanage man page
- DISPATCH-840 - "schema.adoc" contains invalid asciidoc
- DISPATCH-1958 - Qdstat throws exception when router compiled with
DQD_MEMORY_STATS=OFF
- DISPATCH-2109 - Shutdown crash: member access within null pointer of type 'struct qdr_node_t'
- DISPATCH-2218 - [http2] Remove use of variable length arrays in snd_data_callback()
- DISPATCH-2219 - Routing protocol messages can be starved by high priority user traffic
- DISPATCH-2222 - Avoid cpu-intensive message string-ify of every received AMQP message
- DISPATCH-2230 - Review callback action functions and fix all those that don't check the
discard
flag
- DISPATCH-2232 - [http2] http response is fragmented across many TCP packets thus increasing latency
- DISPATCH-2240 - Properly set default value for message annotation strip flag
- DISPATCH-2248 - link_work item leak due to improper delivery reference drop
- DISPATCH-2262 - Edge/Interior connections can half-fail in real multi-cloud environments
- DISPATCH-2268 - HTTP/1.x: incorrectly logs connection close as an error
- DISPATCH-2269 - warning: 'PN_VERSON_MINOR' is not defined, evaluates to 0 [-Wundef]
- DISPATCH-2274 - system_tests_router_mesh: ERROR: AddressSanitizer: use-after-poison in qd_link_pn container.c:1029
- DISPATCH-2283 - heap-use-after-free in system_tests_policy_oversize_compound during qdrc_endpoint_delivery_CT
- DISPATCH-2286 - Segfault while running iperf3 tests due to null raw connection pointer
- DISPATCH-2289 - use-after-free of streaming data causes crash in tcp adaptor
Tasks
Apache Qpid, Messaging built on AMQP; Copyright © 2015
The Apache Software Foundation; Licensed under
the Apache
License, Version 2.0; Apache Qpid, Qpid, Qpid Proton,
Proton, Apache, the Apache feather logo, and the Apache Qpid
project logo are trademarks of The Apache Software
Foundation; All other marks mentioned may be trademarks or
registered trademarks of their respective owners


#include <stGenericPriorityQueue.h>
Public Types | |
| typedef ObjectType | tObject |
| typedef stGenericEntry< ObjectType > | tGenericEntry |
Public Member Functions | |
| stGenericPriorityQueue () | |
| ~stGenericPriorityQueue () | |
| void | Add (tObject *object, stPageID pageID, stDistance distanceRepQuery, stDistance distanceRep, stDistance radius, int type) |
| void | Add (tObject *object, stPageID pageID, stDistance distanceQuery, stDistance radius, int type) |
| void | Add (tObject *object, stDistance distanceRep, stDistance distanceRepQuery, int type) |
| void | Add (tObject *object, stDistance distanceQuery, int type) |
| tGenericEntry * | Get () |
| stCount | GetSize () |
| bool | IsEmpty () |
This priority queue is implemented using a simple chained list. This implementation of priority queue is based on the paper "Incremental Similarity Search in Multimedia Databases" - G. R. Hjaltason & Hanan Samet - 2000.
Definition at line 342 of file stGenericPriorityQueue.h.
|
|
This type defines the stGenericEntry used by this class. Definition at line 353 of file stGenericPriorityQueue.h. |
|
|
Type of the object. Definition at line 348 of file stGenericPriorityQueue.h. |
|
|
Creates a new priority queue. Definition at line 358 of file stGenericPriorityQueue.h. |
|
|
Disposes this queue. |
|
|
Adds a new object to the queue.
|
|
|
Adds a new approximate object to the queue.
|
|
|
Adds a new node to the queue.
|
|
|
Adds a new approximate node to the queue.
|
|
|
Gets the next node. This node is removed from the queue.
|
|
|
Returns the size of this queue. Definition at line 423 of file stGenericPriorityQueue.h. References stCount. |
|
|
Returns if this queue is empty. Definition at line 430 of file stGenericPriorityQueue.h. |


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1.Introduce it is so funny about python,and all of our love it,so i hope you can love it also.best wishes to you. maybe i am not good boy ,and i want to a good man.
2.content you can not known what you see.but it is not important.i only write a txt and no fix up content what it say.so do not say again about plain. hope have a good girl to be my girlfriend.
this is test about list:


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Open AWS CloudFormation✓ Appointment Management with EHR Integration Application is Ready for Integration
In order to complete the EHR integration, you'll need to provide the following information to your EHR integration implementor. For more details, please refer to EHR Integration Guide.
| Name | Value (where to find) |
|---|---|
| Twilio Studio Flow Endpoint URL | Note the FLOW REST API URL above. |
| Twilio Account SID | Find in Environment Variables in Functions Settings |
| Twilio Auth Token for SID | Find in Environment Variables in Functions Settings |
| Twilio Phone Number | Find in Environment Variables in Functions Settings |
Once integration is in place with your EHR, appointment events will start sending to this application.
Once you have some appointment data, you can query appointment data.
Appointment State data is being prepared.
Please wait, this may take up some time.
Appointment History data is being prepared.
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Player 1
43
Current
11
Player 2
72
Current
0
Player 1 Wins
Player 2 Wins
New game
Roll dice
Hold
PIGAME


- declare an url rule for a form process with three steps: input, confirm and complete.
- share form html definition between step pages by embedding
- use static option data embed in html file rather than rendering by snippet
- form data display mode
- automatically generated display DOM at confirm page
- custom predefined display DOM at complete page
- define a common parent class to configure the common actions of form flow process
- customized validation message generation
- customized validation message DOM in html
- specify message by form field annotation
- extend TypeUnMatchValidator(retrieve message from resource bundle)
- extend JsrValueValidator and customized bean validation initialization(custom message file)
- output update success message to a specified DOM rather than the global message bar


VR on the web
AFrame is an extention to HTML
Here I try to do some live AFrame coding
More than cubes and spheres
From VR to AR
AR.js is a javascript library for doing marker based augmented reality applications for smartphones.
AR.js uses the camera to find a special marker in the video feed and maps the scene coordinates to marker.
More live coding
Time for a smart phone demo! Go to
https://cincynkyartandcode.github.io/
demos/aframear/augdemo.html
Creating your own models
Thanks!
Presentation created with reveal.js


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Select number of pocket/hole cards each player holds


Getting Started¶
This guide will step you through installing AerisCloud on your computer, then starting a new project.
Dependencies¶
- A UNIX-based operating systems, OSX and Linux are both supported
- Python 2.7
- python-virtualenv
- Virtualbox
- Vagrant 1.7+
- git
- rsync
When using Linux, also make sure to have the a working NFS server installed.
Manual Installation¶
If you already have all the dependencies installed, the first step is to clone
the AerisCloud repository where you want it to be installed (something like
/opt/aeriscloud
is a good idea):
git clone https://github.com/aeriscloud/aeriscloud.git
cd aeriscloud
Then run make install
to install all the necessary python dependencies in the
current folder and generate the auto-completion.
When updating, just enter the AerisCloud folder, then just pull the latest
version before running make install
.
Setting up AerisCloud¶
Once AerisCloud is installed, the first step is to create a new organization. Organizations are AerisCloud’s way to store your custom playbooks, roles and anything that might be private to your company, to do so run:
cloud organization init my-org
If it is your first time launching an AerisCloud command, you should be greeted by a short assistant to set the global configuration of the tool. Just answer each step as they are presented to you and if you do not know the answer/right configuration at that time, feel free to skip that step as you can always make changes later.
You terminal will then be moved to the folder containing my-org
, where the
structure of files should look like:
├── README.md
├── env_dev.yml
├── env_production.yml
└── roles
├── aeriscloud.disk
├── aeriscloud.dotdeb
├── aeriscloud.elasticsearch
├── ... more roles
└── dependencies.txt
The default generated organization should have several general purpose ansible
roles already installed to allow you to start hacking as soon as possible, but if
anything is missing then dependencies.txt
and env_production.yml
are the
two files to take a look at, more on that in Organization.
You are now ready to start using AerisCloud. For more details on the available configuration options provided by the tool, just jump to Configuration.
Starting a New Project¶
Now that everything is up and ready, it is time to start a new project, type:
aeris init my-project --up
A short assistant will ask for your project name, services you wish to enable
and vagrant basebox, the default chef/centos-7.0
basebox should be a safe
starting box but feel free to use your favorite box from Atlas. Just keep in
mind that AerisCloud roles are mainly
designed around CentOS and might not work on other distributions.
The box should start booting up right after that and the provisioning should start. It will take some time for the provisioning to finish the first time so you can go a grab a coffee, read your mails, build that treehouse you promised your kids last summer, etc...
If you want to set some custom variables or edit the virtual machine in any way
before starting it up, remove the --up
flag and take a look at the
.aeriscloud.yml file.
Your code is mounted to /home/vagrant/my-project
, one can use their favorite
language, provided that the proper roles have been installed. The recommended
way to manage dependencies, builds, etc... is through makefiles, the format is
relatively simple though maybe limited. The recommended way to run your make
commands is either via aeris ssh
or the aeris make
shortcut.
Here is a sample Makefile
for a tentative node.js app:
.PHONY: all deps build run
all: build
node_modules:
npm install
deps: node_modules
build: deps
gulp assets
run:
node .
What’s Next?¶
At this point you can already work on your application and test it in a contained environment, but the whole point of AerisCloud is to be able to run the same provisioning scripts on both your local box and your online servers. To learn how to do so, proceed to Cloud Command for more details on how ansible is used and how to write proper roles for your organization.


Expose model to view
Expose functions to handle user interaction
Update model to change the view
But also:
Instantiated once per use in your template


In the previous chapters we learned that an aggregate protects invariants and records an event for each state transition. It then applies recorded events to its internal state and uses the state to validate if the next state transition can take place.
But an aggregate cannot always rely solely on its internal state. Sometimes the aggregate needs to get information from somewhere else to make a decision. In this case the aggregate has a dependency to an external service and in this chapter we will learn how to give access to such a service and, of course, how to test it.
You may have noticed that we left a @TODO Check stock
in the Basket::addProduct()
method. Products are handled
in an external ERP system and we can request current stock of a product from that system. When implementing Domain-Driven Design,
it is a common approach to integrate an external system by defining an interface for it in the domain model but move
the implementation to the infrastucture
layer. A good example of such an integration is shown in the PHP DDD Cargo Sample¹,
where the Cargo domain makes use of an external GraphTraversalService. This is called Hexagonal Architecture or Ports & Adapters².
We want to use the same approach for the ERP system but limit the implementation to the interface only, as we don't have access to the ERP system right now and only know the interface specification. That's enough, though, because we can easily mock the ERP and use the interface to decouple our domain model from it.
File: ./Basket/src/Model/ERP/ERP.php
<?php
declare(strict_types=1);
namespace App\Basket\Model\ERP;
use App\Basket\Model\Exception\UnknownProduct;
interface ERP
{
/**
* Get stock information for given product
*
* If stock information cannot be fetched from the ERP system
* this method returns null.
*
* If product is not known by the ERP system this method must throw an UnknownProduct exception
*
* @param ProductId $productId
* @return ProductStock|null
* @throws UnknownProduct
*/
public function getProductStock(ProductId $productId): ?ProductStock;
}
The ERP
interface defines a method getProductStock
which takes a ProductId
as an argument and returns a
ProductStock
value object or null in case the request failed. You may have noticed that we use value objects a lot. In fact everything except our Basket
aggregate is modeled as a value object so far. It is a rule of thumb to model everything as value objects and only
use an aggregate if the object really has a lifecycle in YOUR domain. Products have a lifecycle but in
the ERP system and not in our basket domain. We only consume product data as read-only information. Hence, we are better
off using value objects to represent different aspects of a product like its stock information.
Having said this, let's add the value object.
File: ./Basket/src/Model/ERP/ProductStock.php
<?php
declare(strict_types=1);
namespace App\Basket\Model\ERP;
final class ProductStock
{
/**
* @var ProductId
*/
private $productId;
/**
* @var int
*/
private $quantity;
/**
* @var int
*/
private $version;
public static function fromArray(array $data): self
{
return new self(
ProductId::fromString($data['product_id'] ?? ''),
$data['quantity'] ?? 0,
$data['version'] ?? 0
);
}
private function __construct(ProductId $productId, int $quantity, int $version)
{
$this->productId = $productId;
$this->quantity = $quantity;
$this->version = $version;
}
/**
* @return ProductId
*/
public function productId(): ProductId
{
return $this->productId;
}
/**
* @return int
*/
public function quantity(): int
{
return $this->quantity;
}
/**
* @return int
*/
public function version(): int
{
return $this->version;
}
public function toArray(): array
{
return [
'product_id' => $this->productId->toString(),
'quantity' => $this->quantity,
'version' => $this->version
];
}
public function equals($other): bool
{
if(!$other instanceof self) {
return false;
}
return $this->toArray() === $other->toArray();
}
public function __toString(): string
{
return json_encode($this->toArray());
}
}
ProductStock
gives us two important pieces of information:
Stock quantity is self-explanatory, and the version is related to that quantity. Whenever stock quantity of a product changes, the version is increased by one. We can use the version during checkout to verify if the last known quantity of the product is still valid or if the quantity known by the basket is out-of-date.
We also need a new UnknownProduct
exception which is thrown by the ERP
adapter in case the ERP system returns a not found response.
File: ./Basket/src/Model/Exception/UnknownProduct.php
<?php
declare(strict_types=1);
namespace App\Basket\Model\Exception;
use App\Basket\Model\ERP\ProductId;
final class UnknownProduct extends \InvalidArgumentException
{
public static function withProductId(ProductId $productId): self
{
return new self(sprintf(
'Product with %s is unknown.',
$productId->toString()
));
}
}
The Basket
aggregate should use the ERP
system to request stock information before adding a product to the basket.
The aggregate should reject the product if it is out of stock.
Note: We keep the example simple. In a real world system this stock check would include many more variants, for example permanent or temporarily out of stock products, checkout even if a product is out of stock, and so on.
But how do we get the ERP
adapter into the aggregate? The answer is Method Injection. The Basket::addProduct
defines
the ERP
system as a dependency for that method, and the caller of the method is responsible for providing an implementation.
We will see that in action when we look at command handlers. For now, we align the method and update our test case.
File: ./Basket/src/Model/Basket.php
<?php
declare(strict_types=1);
namespace App\Basket\Model;
//...
use App\Basket\Model\ERP\ERP;
use App\Basket\Model\Exception\ProductOutOfStock;
final class Basket extends AggregateRoot
{
//...
public function addProduct(ProductId $productId, ERP $ERP): void
{
if(array_key_exists($productId->toString(), $this->products)) {
throw ProductAddedTwice::toBasket($this->basketId, $productId);
}
//If the ERP system does not know the product an exception will be thrown here
//which will stop the operation. The aggregate can not deal with that situation
//as this is one of these "this should never happen" situations
//If we want an unbreakable domain model we would need to talk to the business
//and work out a failover plan triggered by a UnknownProductAddedToBasket event.
$productStock = $ERP->getProductStock($productId);
if(!$productStock) {
$this->recordThat(ProductAddedToBasket::occur($this->basketId->toString(), [
'product_id' => $productId->toString(),
//If we did not get a response, we add the product and check stock later again
//the shopping session should not be blocked by a temporarily unavailable ERP system
'stock_version' => null,
'stock_quantity'=> null,
'quantity' => 1,
]));
return;
}
if($productStock->quantity() === 0) {
throw ProductOutOfStock::withProductId($productId);
}
$this->recordThat(ProductAddedToBasket::occur($this->basketId->toString(), [
'product_id' => $productId->toString(),
'stock_version' => $productStock->version(),
'stock_quantity' => $productStock->quantity(),
'quantity' => 1,
]));
}
/**
* Apply given event
*/
protected function apply(AggregateChanged $event): void
{
switch ($event->messageName()) {
case ShoppingSessionStarted::class:
//...
case ProductAddedToBasket::class:
/** @var $event ProductAddedToBasket */
//Use ProductId as index to avoid adding a product twice
$this->products[$event->productId()->toString()] = [
'stock_quantity' => $event->stockQuantity(),
'stock_version' => $event->stockVersion(),
'quantity' => $event->quantity()
];
break;
}
}
}
Basket::addProduct()
has quite a bit of logic now and uses an external ERP
system to request stock information of the product.
In case the ERP system is temporarily unavailable the Basket
aggregate accepts the product without a stock quantity
check. Later in the checkout process we need to take care of this situation and check stock again. If we have
a quantity stock conflict during checkout the order is routed to a support team who needs to contact the customer and
offer an alternative.
If we got stock information from the ERP system we check quantity and throw a ProductOutOfStock
exception if it is zero.
File: ./Basket/src/Model/Exception/ProductOutOfStock.php
<?php
declare(strict_types=1);
namespace App\Basket\Model\Exception;
use App\Basket\Model\ERP\ProductId;
final class ProductOutOfStock extends \RuntimeException
{
public static function withProductId(ProductId $productId): self
{
return new self(sprintf(
'Product with %s is out of stock.',
$productId->toString()
));
}
}
If everything is ok the Basket
aggregate accepts the product and records the ProductAddedToBasket
event but now
with additional information, so we need to add new getter methods to the event.
File: ./Baset/src/Model/Event/ProductAddedToBasket.php
<?php
declare(strict_types=1);
namespace App\Basket\Model\Event;
use App\Basket\Model\Basket\BasketId;
use App\Basket\Model\ERP\ProductId;
use Prooph\EventSourcing\AggregateChanged;
final class ProductAddedToBasket extends AggregateChanged
{
public function basketId(): BasketId
{
return BasketId::fromString($this->aggregateId());
}
public function productId(): ProductId
{
return ProductId::fromString($this->payload()['product_id']);
}
public function stockQuantity(): ?int
{
return $this->payload()['stock_quantity'];
}
public function stockVersion(): ?int
{
return $this->payload()['stock_version'];
}
public function quantity(): int
{
return $this->payload()['quantity'];
}
}
In the apply
method of the Basket
aggregate this additional information is added to the internal state
so that we have access to it later.
Testing the expanded version of Basket::addProduct()
is still relatively simple but we end up with a lot more test methods
to cover the different results of the method call. Check the additions below to see how we can use PHPUnit's prophecy
integration to mock the ERP system and simulate different situations.
File: ./Basket/tests/Model/BasketTest.php
<?php
declare(strict_types=1);
namespace App\BasketTest\Model;
use App\Basket\Model\Basket;
use App\Basket\Model\ERP\ERP;
use App\Basket\Model\ERP\ProductId;
use App\Basket\Model\ERP\ProductStock;
use App\Basket\Model\Event\ProductAddedToBasket;
use App\Basket\Model\Event\ShoppingSessionStarted;
use App\Basket\Model\Basket\BasketId;
use App\Basket\Model\Basket\ShoppingSession;
use App\Basket\Model\Exception\UnknownProduct;
use App\BasketTest\TestCase;
use Prooph\EventSourcing\AggregateChanged;
use Prophecy\Argument;
use Ramsey\Uuid\Uuid;
class BasketTest extends TestCase
{
/**
* @var ShoppingSession
*/
private $shoppingSession;
/**
* @var BasketId
*/
private $basketId;
/**
* @var ProductId
*/
private $product1;
protected function setUp()
{
$this->shoppingSession = ShoppingSession::fromString('123');
$this->basketId = BasketId::fromString(Uuid::uuid4()->toString());
$this->product1 = ProductId::fromString('A1');
}
/**
* @test
*/
public function it_starts_a_shopping_session()
{
$basket = Basket::startShoppingSession($this->shoppingSession, $this->basketId);
/** @var AggregateChanged[] $events */
$events = $this->popRecordedEvents($basket);
$this->assertCount(1, $events);
/** @var ShoppingSessionStarted $event */
$event = $events[0];
$this->assertSame(ShoppingSessionStarted::class, $event->messageName());
$this->assertTrue($this->basketId->equals($event->basketId()));
$this->assertTrue($this->shoppingSession->equals($event->shoppingSession()));
}
/**
* @test
*/
public function it_adds_a_product_if_stock_quantity_is_greater_than_zero()
{
$basket = $this->reconstituteBasketFromHistory(
$this->shoppingSessionStarted()
);
$basket->addProduct($this->product1, $this->product1ERP());
/** @var AggregateChanged[] $events */
$events = $this->popRecordedEvents($basket);
$this->assertCount(1, $events);
/** @var ProductAddedToBasket $event */
$event = $events[0];
$this->assertSame(ProductAddedToBasket::class, $event->messageName());
$this->assertTrue($this->basketId->equals($event->basketId()));
$this->assertTrue($this->product1->equals($event->productId()));
$this->assertSame(5, $event->payload()['stock_quantity']);
$this->assertSame(1, $event->payload()['stock_version']);
$this->assertSame(1, $event->payload()['quantity']);
}
/**
* @test
* @expectedException \App\Basket\Model\Exception\ProductAddedTwice
*/
public function it_throws_exception_if_product_is_added_twice()
{
$basket = $this->reconstituteBasketFromHistory(
$this->shoppingSessionStarted(),
$this->product1Added()
);
//Add same product again
$basket->addProduct($this->product1, $this->product1ERP());
}
/**
* @test
* @expectedException \App\Basket\Model\Exception\UnknownProduct
*/
public function it_stops_operation_if_product_is_unknown()
{
$basket = $this->reconstituteBasketFromHistory(
$this->shoppingSessionStarted()
);
$ERP = $this->prophesize(ERP::class);
//This ERP mock knows no product
$ERP->getProductStock($this->product1)->willThrow(UnknownProduct::withProductId($this->product1));
$basket->addProduct($this->product1, $ERP->reveal());
}
/**
* @test
*/
public function it_adds_product_without_stock_info_if_ERP_is_unavailable()
{
$basket = $this->reconstituteBasketFromHistory(
$this->shoppingSessionStarted()
);
$ERP = $this->prophesize(ERP::class);
//This ERP is unavailable
$ERP->getProductStock($this->product1)->willReturn(null);
$basket->addProduct($this->product1, $ERP->reveal());
/** @var AggregateChanged[] $events */
$events = $this->popRecordedEvents($basket);
$this->assertCount(1, $events);
/** @var ProductAddedToBasket $event */
$event = $events[0];
$this->assertSame(ProductAddedToBasket::class, $event->messageName());
$this->assertTrue($this->basketId->equals($event->basketId()));
$this->assertTrue($this->product1->equals($event->productId()));
$this->assertSame(1, $event->payload()['quantity']);
//No stock info present
$this->assertSame(null, $event->payload()['stock_quantity']);
$this->assertSame(null, $event->payload()['stock_version']);
}
/**
* @test
* @expectedException \App\Basket\Model\Exception\ProductOutOfStock
*/
public function it_does_not_add_product_if_product_is_out_of_stock()
{
$basket = $this->reconstituteBasketFromHistory(
$this->shoppingSessionStarted()
);
//Set stock quantity to zero in the ERP mock
$basket->addProduct($this->product1, $this->product1ERP(0));
}
/**
* Helper method to reconstitute a Basket from history
*
* With this helper we get better type hinting in the test methods
* because type hint for reconstituteAggregateFromHistory() is only AggregateRoot
*
* @param AggregateChanged[] ...$events
* @return Basket
*/
private function reconstituteBasketFromHistory(AggregateChanged ...$events): Basket
{
return $this->reconstituteAggregateFromHistory(
Basket::class,
$events
);
}
/**
* Test helper to create a ShoppingSessionStarted event
*
* If we need to change signature of the event later, we have a central place in the test case
* where we can align the creation.
*
* @return ShoppingSessionStarted
*/
private function shoppingSessionStarted(): ShoppingSessionStarted
{
return ShoppingSessionStarted::occur($this->basketId->toString(), [
'shopping_session' => $this->shoppingSession->toString()
]);
}
/**
* Test helper to create a ProductAddedToBasket event
*
* If we need to change signature of the event later, we have a central place in the test case
* where we can align the creation.
*
* @return ProductAddedToBasket
*/
private function product1Added(): ProductAddedToBasket
{
return ProductAddedToBasket::occur($this->basketId->toString(), [
'product_id' => $this->product1->toString(),
'stock_quantity' => 5,
'stock_version' => 1,
'quantity' => 1,
]);
}
private function product1ERP(int $stockQuantity = 5): ERP
{
//Create a Mock of the ERP interface
$ERP = $this->prophesize(ERP::class);
$ERP->getProductStock($this->product1)->willReturn(ProductStock::fromArray(
[
'product_id' => $this->product1->toString(),
'quantity' => $stockQuantity,
'version' => 1
]
));
return $ERP->reveal();
}
}
$ php vendor/bin/phpunit
PHPUnit 6.3.1 by Sebastian Bergmann and contributors.
...... 6 / 6 (100%)
Time: 27 ms, Memory: 4.00MB
OK (6 tests, 21 assertions)
You need to be careful when using dependency injection in an aggregate method. In the example shown above, we only read data from an external system, and we can handle the cases when communication goes wrong, be it that the product could not be found or the external system is unavailable.
Things get more complex when you want to write data to an external system. Let's say we want to update stock quantity for a product instead of requesting it. Such write operations should not be performed by the aggregate itself but instead by a process manager or a saga. In the next two chapters we're going to learn more about process managers and sagas and the difference between the two.


We are getting married!
At the UBC Boathouse in Richmond, B.C.
The John M.S. Lecky UBC Boathouse is in Richmond, B.C. (not at the university).
Parking:Parking is free along River Road. Please ignore the 3-hour parking signs. They were put in for the 2010 Olympics and never removed. The time limits are not enforced.
Transit: The venue is a 10 minute walk from Aberdeen Station along the Canada Line Skytrain.
Taxi: We care about you, please do not drink and drive. Here are some numbers for local taxis:
Welcome children of all ages!
Please no nuts! One of our guests has a severe tree nut allergy. While you are welcome to bring snacks for your kids, please make them nut-free.
We will be serving a buffet with prosciutto-wrapped chicken, ravioli, roasted veggies, garlic-mashed potatoes and salads. For less discerning palettes, we will also have chicken fingers and fries.
There is a tugboat playground right outside the venue on the River Road seawall.
If you would like to provide a gift, may we suggest the following:
Gifts are not expected, nor necessary. No one will be judged for lack of gifts!


lnd¶
lnd: Gurobi models for logistic network design
There are two models:
lnd_ms, for multiple-source supply
lnd_ss, for single-source supply
The aim is to select a predefined number of places for implementing a distribution center. Data are:
customer locations
potential distribution center locations
plant locations
demand, bounds and costs
See TestSolving below for examples of usage.
Functions
|
Logistics network design, multiple source |
|
Logistics network design, single source |
|
Instantiate costs to a given set of plants, dc’s and customers |
Classes
|
-
lnd.
lnd_ms
(weight, cust, dc, dc_lb, dc_ub, plnt, plnt_ub, demand, tp_cost, del_cost, dc_fc, dc_vc, dc_num)[source]¶ Logistics network design, multiple source
Gurobi model for multiple-source LND
- Return type
object of class Model, as defined in gurobipy
- Weight
weight[p] -> unit weight for product p
- Cust
dict associating a customer id to its location as (latitute, longitude)
- Dc
dict associating a distribution center id to its (latitute, longitude)
- Dc_lb
dc_lb[k] -> lower bound for distribution center k [not used]
- Dc_ub
dc_ub[k] -> upper bound for distribution center k
- Plnt
dict associating a plant id to its (latitute, longitude)
- Plnt_ub
plnt_ub[k] -> upper bound for plant k
- Demand
demand[k,p] -> units of p demanded by customer k
- Tp_cost
unit transportation cost (from the plant)
- Del_cost
unit delivery cost (from a dc)
- Dc_fc
fixed cost for opening a dc
- Dc_vc
unit (variable) cost for operating a dc
- Dc_num
(maximum) number of distribution centers to open
-
lnd.
lnd_ss
(weight, cust, dc, dc_lb, dc_ub, plnt, plnt_ub, demand, tp_cost, del_cost, dc_fc, dc_vc, dc_num)[source]¶ Logistics network design, single source
Gurobi model for single-source LND
- Return type
object of class Model, as defined in gurobipy
- Weight
weight[p] -> unit weight for product p
- Cust
dict associating a customer id to its location as (latitute, longitude)
- Dc
dict associating a distribution center id to its (latitute, longitude)
- Dc_lb
dc_lb[k] -> lower bound for distribution center k [not used]
- Dc_ub
dc_ub[k] -> upper bound for distribution center k
- Plnt
dict associating a plant id to its (latitute, longitude)
- Plnt_ub
plnt_ub[k] -> upper bound for plant k
- Demand
demand[k,p] -> units of p demanded by customer k
- Tp_cost
unit transportation cost (from the plant)
- Del_cost
unit delivery cost (from a dc)
- Dc_fc
fixed cost for opening a dc
- Dc_vc
unit (variable) cost for operating a dc
- Dc_num
(maximum) number of distribution centers to open
-
lnd.
mk_costs
(plnt, dc, cust)[source]¶ Instantiate costs to a given set of plants, dc’s and customers
To be adpted to more realistic settings
- Return type
tuple with transportation costs
- Plnt
dict associating a plant id to its (latitute, longitude)
- Dc
dict associating a distribution center id to its (latitute, longitude)


$026D/621: Error LED ROM-Reference: EOR $026D : $EC90 LDA $026D : $D6AB $D6C5 STA $026D : $C128 $C139 $D5D6 Previous Page / Next Page


Dungeons & Dragons (commonly abbreviated as D&D or DnD) is a fantasy tabletop role-playing game (RPG) originally designed by Gary Gygax and Dave Arneson. It was first published in 1974 by Tactical Studies Rules, Inc. (TSR). The game has been published by Wizards of the Coast (now a subsidiary of Hasbro) since 1997. It was derived from miniature wargames, with a variation of the 1971 game Chainmail serving as the initial rule system. D&D's publication is commonly recognized as the beginning of modern role-playing games and the role-playing game industry.
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{{ monster['meta'] }}
{{ monster['Armor Class'] }}
{{ monster['Hit Points'] }}
{{ monster['Speed'] }}
| Attribute | Points |
|---|---|
STR |
{{ monster['STR'] }} |
DEX |
{{ monster['DEX'] }} |
CON |
{{ monster['CON'] }} |
INT |
{{ monster['INT'] }} |
WIS |
{{ monster['WIS'] }} |
CHA |
{{ monster['CHA'] }} |
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{{ monster['Languages']}}
{{ monster['Traits']| safe }}
{{ monster['Actions']| safe}}
{{ monster['Legendary Actions']| safe}}


{% include "Partials/_Header.html" %}
{% include "Partials/_Nav_Bar.html" %}
Time Domain
| Indice |
Measurement |
| SDNN |
35 |
| ASDNN |
31 |
| SDANN |
16 |
| NN50 |
116 |
| pNN50 |
5% |
| rMSSD |
27 |
Frequency Domain
| Indice |
Measurement |
| ULF (0-0.333) |
4 |
| VLF (0.333-0.04) |
200 |
| LF (0.04-0.15) |
82 |
| HF (0.15-0.4) |
521 |
| LF/HF |
0.157 |
| Total Power |
809 |
Nonlinear Measurements
| Indice |
Measurement |
| SD1 |
45 |
| SD2 |
53 |
| SD1/SD2 |
0.857 |
| Ellipse Area |
7672 |
| DFA Alpha 1 |
0.676 |
| DFA Alpha 2 |
0.846 |
{% include "Partials/_Footer.html" %}
{% include "Partials/_Scripts.html" %}


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B-Scene is a hub for industry professionals events and workshops. You can create an account to publish your own or your organization events. You can search for events, add them to your calender and share them on your social websites.

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@()(implicit user: models.user.User, session: play.api.db.slick.Config.driver.simple.Session)
Welcome to the Math 10A CalcTutor course, please take the follow steps to complete the homework assignment:
- Start by taking the "Pre-quiz"
- Play three game rounds (click the "new game" button below, or check the panel to the right to see if someone has already requested to play with you)
- Then take the "Post-quiz"
- Finish by letting us know what you think by taking this survey


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Checklists can start empty, or they can use one of the following templates.
To create a new template, create a checklist and choose "Save as template"
- ✎ ❌
Visit /checklist/<some name> to start checklisting.
Checklists can start empty, or they can use one of the following templates.
To create a new template, create a checklist and choose "Save as template"


Before Change
Same thing as prepare_model_outputs, but for an `a_shadows_b` model.
TODO(future PR): real docblock
matched_subgraph_pairs = get_matching_subgraph_pairs(gm_a, gm_b)
gm_a_shadows_b = create_a_shadows_b(
name_a, gm_a, name_b, gm_b, matched_subgraph_pairs, logger_cls)
return gm_a_shadows_b
// Note: this is not a user facing API
// TODO(future PR): wrap this in a user facing API which does not
After Change
Same thing as prepare_model_outputs, but for an `a_shadows_b` model.
TODO(future PR): real docblock
tracer_a, tracer_b = NSTracer(), NSTracer()
gm_a = GraphModule(model_a, tracer_a.trace(model_a))
gm_b = GraphModule(model_b, tracer_b.trace(model_b))
return _prepare_model_with_stubs_impl(name_a, gm_a, name_b, gm_b, logger_cls)
// TODO(future PR): align on naming
// this is equivalent of just the comparison extraction part of `ns.compare_model_stub`


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- NAME
- dict - Manipulate dictionaries
- SYNOPSIS
- DESCRIPTION
- dict append dictionaryVariable key ?string ...?
- dict create ?key value ...?
- dict exists dictionaryValue key ?key ...?
- dict filter dictionaryValue filterType arg ?arg ...?
- dict filter dictionaryValue key globPattern
- dict filter dictionaryValue script {keyVar valueVar} script
- dict filter dictionaryValue value globPattern
- dict for {keyVar valueVar} dictionaryValue body
- dict get dictionaryValue ?key ...?
- dict incr dictionaryVariable key ?increment?
- dict info dictionaryValue
- dict keys dictionaryValue ?globPattern?
- dict lappend dictionaryVariable key ?value ...?
- dict merge ?dictionaryValue ...?
- dict remove dictionaryValue ?key ...?
- dict replace dictionaryValue ?key value ...?
- dict set dictionaryVariable key ?key ...? value
- dict size dictionaryValue
- dict unset dictionaryVariable key ?key ...?
- dict update dictionaryVariable key varName ?key varName ...? body
- dict values dictionaryValue ?globPattern?
- dict with dictionaryVariable ?key ...? body
- DICTIONARY VALUES
- EXAMPLES
- SEE ALSO
- KEYWORDS
dict - Manipulate dictionaries
dict option arg ?arg ...?
Performs one of several operations on dictionary values or variables
containing dictionary values (see the DICTIONARY VALUES section
below for a description), depending on option. The legal
options (which may be abbreviated) are:
- dict append dictionaryVariable key ?string ...?
-
This appends the given string (or strings) to the value that the given
key maps to in the dictionary value contained in the given variable,
writing the resulting dictionary value back to that variable.
Non-existent keys are treated as if they map to an empty string.
- dict create ?key value ...?
-
Create a new dictionary that contains each of the key/value mappings
listed as arguments (keys and values alternating, with each key being
followed by its associated value.)
- dict exists dictionaryValue key ?key ...?
-
This returns a boolean value indicating whether the given key (or path
of keys through a set of nested dictionaries) exists in the given
dictionary value. This returns a true value exactly when dict
get on that path will succeed.
- dict filter dictionaryValue filterType arg ?arg ...?
-
This takes a dictionary value and returns a new dictionary that
contains just those key/value pairs that match the specified filter
type (which may be abbreviated.) Supported filter types are:
- dict filter dictionaryValue key globPattern
-
The key rule only matches those key/value pairs whose keys match the
given pattern (in the style of string match.)
- dict filter dictionaryValue script {keyVar valueVar} script
-
The script rule tests for matching by assigning the key to the
keyVar and the value to the valueVar, and then evaluating
the given script which should return a boolean value (with the
key/value pair only being included in the result of the dict
filter when a true value is returned.) Note that the first
argument after the rule selection word is a two-element list. If the
script returns with a condition of TCL_BREAK, no further
key/value pairs are considered for inclusion in the resulting
dictionary, and a condition of TCL_CONTINUE is equivalent to a false
result. The key/value pairs are tested in the order in which the keys
were inserted into the dictionary.
- dict filter dictionaryValue value globPattern
-
The value rule only matches those key/value pairs whose values match
the given pattern (in the style of string match.)
- dict for {keyVar valueVar} dictionaryValue body
-
This command takes three arguments, the first a two-element list of
variable names (for the key and value respectively of each mapping in
the dictionary), the second the dictionary value to iterate across,
and the third a script to be evaluated for each mapping with the key
and value variables set appropriately (in the manner of foreach.)
The result of the command is an empty string. If any evaluation of the
body generates a TCL_BREAK result, no further pairs from the
dictionary will be iterated over and the dict for command will
terminate successfully immediately. If any evaluation of the body
generates a TCL_CONTINUE result, this shall be treated exactly like a
normal TCL_OK result. The order of iteration is the order in
which the keys were inserted into the dictionary.
- dict get dictionaryValue ?key ...?
-
Given a dictionary value (first argument) and a key (second argument),
this will retrieve the value for that key. Where several keys are
supplied, the behaviour of the command shall be as if the result of
dict get $dictVal $key was passed as the first argument to
dict get with the remaining arguments as second (and possibly
subsequent) arguments. This facilitates lookups in nested
dictionaries. For example, the following two commands are equivalent:
dict get $dict foo bar spong
dict get [dict get [dict get $dict foo] bar] spong
If no keys are provided, dict get will return a list containing pairs of
elements in a manner similar to array get. That is, the first
element of each pair would be the key and the second element would be
the value for that key.
It is an error to attempt to retrieve a value for a key that is not
present in the dictionary.
- dict incr dictionaryVariable key ?increment?
-
This adds the given increment value (an integer that defaults to 1 if
not specified) to the value that the given key maps to in the
dictionary value contained in the given variable, writing the
resulting dictionary value back to that variable. Non-existent keys
are treated as if they map to 0. It is an error to increment a value
for an existing key if that value is not an integer.
- dict info dictionaryValue
-
This returns information (intended for display to people) about the
given dictionary though the format of this data is dependent on the
implementation of the dictionary. For dictionaries that are
implemented by hash tables, it is expected that this will return the
string produced by Tcl_HashStats, similar to array statistics.
- dict keys dictionaryValue ?globPattern?
-
Return a list of all keys in the given dictionary value. If a pattern
is supplied, only those keys that match it (according to the rules of
string match) will be returned. The returned keys will be in the
order that they were inserted into the dictionary.
- dict lappend dictionaryVariable key ?value ...?
-
This appends the given items to the list value that the given key maps
to in the dictionary value contained in the given variable, writing
the resulting dictionary value back to that variable. Non-existent
keys are treated as if they map to an empty list, and it is legal for
there to be no items to append to the list. It is an error for the
value that the key maps to to not be representable as a list.
- dict merge ?dictionaryValue ...?
-
Return a dictionary that contains the contents of each of the
dictionaryValue arguments. Where two (or more) dictionaries
contain a mapping for the same key, the resulting dictionary maps that
key to the value according to the last dictionary on the command line
containing a mapping for that key.
- dict remove dictionaryValue ?key ...?
-
Return a new dictionary that is a copy of an old one passed in as
first argument except without mappings for each of the keys listed.
It is legal for there to be no keys to remove, and it also legal for
any of the keys to be removed to not be present in the input
dictionary in the first place.
- dict replace dictionaryValue ?key value ...?
-
Return a new dictionary that is a copy of an old one passed in as
first argument except with some values different or some extra
key/value pairs added. It is legal for this command to be called with
no key/value pairs, but illegal for this command to be called with a
key but no value.
- dict set dictionaryVariable key ?key ...? value
-
This operation takes the name of a variable containing a dictionary
value and places an updated dictionary value in that variable
containing a mapping from the given key to the given value. When
multiple keys are present, this operation creates or updates a chain
of nested dictionaries.
- dict size dictionaryValue
-
Return the number of key/value mappings in the given dictionary value.
- dict unset dictionaryVariable key ?key ...?
-
This operation (the companion to dict set) takes the name of a
variable containing a dictionary value and places an updated
dictionary value in that variable that does not contain a mapping for
the given key. Where multiple keys are present, this describes a path
through nested dictionaries to the mapping to remove. At least one key
must be specified, but the last key on the key-path need not exist.
All other components on the path must exist.
- dict update dictionaryVariable key varName ?key varName ...? body
-
Execute the Tcl script in body with the value for each key
(as found by reading the dictionary value in dictionaryVariable)
mapped to the variable varName. There may be multiple
key/varName pairs. If a key does not have a mapping,
that corresponds to an unset varName. When body
terminates, any changes made to the varNames is reflected back
to the dictionary within dictionaryVariable (unless
dictionaryVariable itself becomes unreadable, when all updates
are silently discarded), even if the result of body is an error
or some other kind of exceptional exit. The result of dict
update is (unless some kind of error occurs) the result of the
evaluation of body.
Each varName is mapped in the scope enclosing the dict update;
it is recommended that this command only be used in a local scope
(procedure or lambda term for apply). Because of
this, the variables set by dict update will continue to
exist after the command finishes (unless explicitly unset).
Note that the mapping of values to variables
does not use traces; changes to the dictionaryVariable's
contents only happen when body terminates.
- dict values dictionaryValue ?globPattern?
-
Return a list of all values in the given dictionary value. If a
pattern is supplied, only those values that match it (according to the
rules of string match) will be returned. The returned values
will be in the order of that the keys associated with those values
were inserted into the dictionary.
- dict with dictionaryVariable ?key ...? body
-
Execute the Tcl script in body with the value for each key in
dictionaryVariable mapped (in a manner similarly to dict
update) to a variable with the same name. Where one or more
keys are available, these indicate a chain of nested
dictionaries, with the innermost dictionary being the one opened out
for the execution of body. As with dict update, making
dictionaryVariable unreadable will make the updates to the
dictionary be discarded, and this also happens if the contents of
dictionaryVariable are adjusted so that the chain of
dictionaries no longer exists. The result of dict with is
(unless some kind of error occurs) the result of the evaluation of
body.
The variables are mapped in the scope enclosing the dict with;
it is recommended that this command only be used in a local scope
(procedure or lambda term for apply). Because of
this, the variables set by dict with will continue to
exist after the command finishes (unless explicitly unset).
Note that the mapping of values to variables does not use
traces; changes to the dictionaryVariable's contents only happen
when body terminates.
Dictionaries are values that contain an efficient, order-preserving
mapping from arbitrary keys to arbitrary values.
Each key in the dictionary maps to a single value.
They have a textual format that is exactly that of any list with an
even number of elements, with each mapping in the dictionary being
represented as two items in the list. When a command takes a
dictionary and produces a new dictionary based on it (either returning
it or writing it back into the variable that the starting dictionary
was read from) the new dictionary will have the same order of keys,
modulo any deleted keys and with new keys added on to the end.
When a string is interpreted as a dictionary and it would otherwise
have duplicate keys, only the last value for a particular key is used;
the others are ignored, meaning that,
“apple banana”
and
“apple carrot apple banana”
are equivalent dictionaries (with different string representations).
Operations that derive a new dictionary from an old one (e.g., updates
like dict set and dict unset) preserve the order of keys
in the dictionary. The exceptions to this are for any new keys they
add, which are appended to the sequence, and any keys that are
removed, which are excised from the order.
Basic dictionary usage:
# Make a dictionary to map extensions to descriptions
set filetypes [dict create .txt "Text File" .tcl "Tcl File"]
# Add/update the dictionary
dict set filetypes .tcl "Tcl Script"
dict set filetypes .tm "Tcl Module"
dict set filetypes .gif "GIF Image"
dict set filetypes .png "PNG Image"
# Simple read from the dictionary
set ext ".tcl"
set desc [dict get $filetypes $ext]
puts "$ext is for a $desc"
# Somewhat more complex, with existence test
foreach filename [glob *] {
set ext [file extension $filename]
if {[dict exists $filetypes $ext]} {
puts "$filename is a [dict get $filetypes $ext]"
}
}
Constructing and using nested dictionaries:
# Data for one employee
dict set employeeInfo 12345-A forenames "Joe"
dict set employeeInfo 12345-A surname "Schmoe"
dict set employeeInfo 12345-A street "147 Short Street"
dict set employeeInfo 12345-A city "Springfield"
dict set employeeInfo 12345-A phone "555-1234"
# Data for another employee
dict set employeeInfo 98372-J forenames "Anne"
dict set employeeInfo 98372-J surname "Other"
dict set employeeInfo 98372-J street "32995 Oakdale Way"
dict set employeeInfo 98372-J city "Springfield"
dict set employeeInfo 98372-J phone "555-8765"
# The above data probably ought to come from a database...
# Print out some employee info
set i 0
puts "There are [dict size $employeeInfo] employees"
dict for {id info} $employeeInfo {
puts "Employee #[incr i]: $id"
dict with info {
puts " Name: $forenames $surname"
puts " Address: $street, $city"
puts " Telephone: $phone"
}
}
# Another way to iterate and pick out names...
foreach id [dict keys $employeeInfo] {
puts "Hello, [dict get $employeeInfo $id forenames]!"
}
A localizable version of string toupper:
# Set up the basic C locale
set capital [dict create C [dict create]]
foreach c [split {abcdefghijklmnopqrstuvwxyz} ""] {
dict set capital C $c [string toupper $c]
}
# English locales can luckily share the "C" locale
dict set capital en [dict get $capital C]
dict set capital en_US [dict get $capital C]
dict set capital en_GB [dict get $capital C]
# ... and so on for other supported languages ...
# Now get the mapping for the current locale and use it.
set upperCaseMap [dict get $capital $env(LANG)]
set upperCase [string map $upperCaseMap $string]
Showing the detail of dict with:
proc sumDictionary {varName} {
upvar 1 $varName vbl
foreach key [dict keys $vbl] {
# Manufacture an entry in the subdictionary
dict set vbl $key total 0
# Add the values and remove the old
dict with vbl $key {
set total [expr {$x + $y + $z}]
unset x y z
}
}
puts "last total was $total, for key $key"
}
set myDict {
a {x 1 y 2 z 3}
b {x 6 y 5 z 4}
}
sumDictionary myDict
# prints: last total was 15, for key b
puts "dictionary is now \"$myDict\""
# prints: dictionary is now "a {total 6} b {total 15}"
append, array, foreach, incr, list, lappend, set
dictionary, create, update, lookup, iterate, filter
Copyright © 1995-1997 Roger E. Critchlow Jr.
Copyright © 2003 Donal K. Fellows


{{ time['timestamp'] }}
{{var2}}
Load a different dataset as your source file
Generate a similarity score
View the current pipeline and run it


Addred/Transaction details (hover over nodes)
About: Visualization of bitcoin transactions (unconfirmed ones).
Node size scale:
LEGEND:
Green = input,
Red = output,
Yellow = input+output,
Blue = transaction
NAVIGATION: mouse + scroll = pan/zoom, SPACE = run/pause
This visualisation was possible thanks to blockchain.info api and vivagraph.js library.


Please use another device
This device is too small for this website..
Varun Engineering Work
Loading . . .
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Diameter range |
10 to 100 |
50 to 200 |
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Width of V-Blocks |
100 |
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Centre height |
155 |
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Weight (approx) |
50 kgs |
75 kgs |
Tel. :-<PHONE_NUMBER>1,
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I've been meaning to write something cohesive about my thoughts post-attempted coup in Turkey, instead of having a half-dozen status updates with cryptic captions that, when analysed together, gives someone an idea of where I stand on the issue.
Writing for Foreign Policy, retired American 4-star admiral and supreme NATO commander James Stavridis says:
The highly unstable geopolitics of the Levant and NATO’s expanding security needs come together at a crossroads in Turkey. It is not only a nation, but a civilization as well, one that has an acute sense of its importance and history in the region.
The Ottoman Empire came to an end after the Great War, and the Turkish republic rose from its ashes - led by a man whose legacy has played a significant part of its landscape since: Mustafa Kemal Ataturk. Ataturk came to power in a defeated nation that was about to be partitioned among foreign powers, and led it on a path of modernisation that made it an important regional power and (long after his death) an important NATO member.
It is Ataturk's policies of secularism and democracy that the Turkish Army vows to uphold whenever it takes power:
Since the Turkish republic was founded, in 1923, the county’s generals have imagined themselves the ultimate arbiters of its politics, stepping into power—sometimes savagely—whenever they felt the government had become either too leftist or too Islamic.
Whether it succeeds or fails in this endeavour depends on who you're asking. For example, the biography of 1980s coup leader Kenan Evren reads:
He professed great admiration for the founder of the Republic of Turkey, Mustafa Kemal Atatürk; however, he shut down many institutions founded by Atatürk and is often accused of deforming the country's legal system against Atatürk's principles.
Erdogan
Recep Tayyip Erdogan was elected PM in 2003. His Justice and Development Party (AKP) embodies liberal economics and conservative social values. He was mayor of Istanbul (1994 - 1998) running on an Islamist platform, but was stripped of his office and imprisoned for "incitement to violence and religious or racial hatred". When he became PM in 2003, he was hailed as some Islamist democrat messiah:
When Erdoğan first became Prime Minister, in 2003, he was the Islamic world’s great democratic hope, a leader of enormous vitality who would show the world that an avowedly Islamist politician could lead a stable democracy and carry on as a member of NATO, too.
Erdogan's "Neo-Ottomanism" and other policies are a fascinating discussion in and of themselves, but I'll leave those out of this post. What we need to understand though is that Erdogan does not trust the military to not topple him, which led in the late 2000s to a series of investigations and trials pertaining to an alleged coup plan called "Operation Sledgehammer". From the earlier FP article:
Hundreds of senior admirals and generals were charged and jailed on suspect charges in the so-called Sledgehammer scandals of the 2000s, and the seeds of the current coup were planted when bitter military leaders watched their commanders and mentors be taken to prison in handcuffs.
Some of the evidence was flimsy at best:
All these documents carry last-saved dates from 2002-2003, appear to have been authored by officers on duty at the time, and were burned on CDs that were apparently finalized in March 2003.
Yet when forensic experts looked more closely at the document with a Hex editor, which shows all the binary information on the file, they made a discovery that revealed that the metadata had been tampered with. In plain sight on the raw file was a reference to “Calibri,” a font that Microsoft introduced with Office 2007 as the new default font for Word, and was first released to the public in mid-2006. The only explanation for this anachronistic reference was that the file had been worked on with Office 2007 before it was ultimately saved in an earlier version of Word.
In the aftermath of the coup attempt last week, there'll no doubt be more generals dragged away in chains, and more institutions falling under Erdogan's command in his mad rush for dictatorial powers.
All this could lead to rocky times for NATO ahead. Of particular concern are the nuclear weapons stored at Incirlik, 70 miles from the Syrian border:
Security concerns at Incirlik Airbase recently prompted a major upgrade of the perimeter fence that surrounds its nuclear-weapons storage area. Incirlik is about seventy miles from the Syrian border, and since last October American aircraft and drones based there have been attacking ISIS forces. Its proximity to rebel-controlled areas in Syria and the rash of terrorist acts in Turkey led the Pentagon, a few months ago, to issue an “ordered departure” of all the family members of American troops at Incirlik.
Final Thoughts
This post came out shorter than expected, because I skipped the bit I really wanted to talk about - Erdogan and his politics. I'll hopefully have time (lol) to write in more depth about what the last 13 years have looked like for Turkey under Erdogan, and what his potential endgame might be - for both Turkey and the Middle East.


{# planet/suggest.html ~~~~~~~~~~~~~~~~~~~ On this page the user can suggest a new blog for the planet. :copyright: (c) 2013-2019 by the Inyoka Team, see AUTHORS for more details. :license: BSD, see LICENSE for more details. #} {% extends 'planet/base.html' %} {% block title %} {% trans %}Suggest blog{% endtrans %} – {{ super() }} {% endblock %} {% block breadcrumb %} {{ super() }} {{ macros.breadcrumb_item(_('Suggest blog')) }} {% endblock %} {% block content %}
{% trans %}Please be patient. It could take a while, until we approve your suggestion.{% endtrans %}
{{ macros.outer_form(csrf_token(), form, action=href('planet', 'suggest')) }} {% endblock %}


Tesla on Autopilot swerves to narrowly avoid family of ducks crossing the road
The Tesla Model 3, which was being driven in Gisborne, was in Autopilot Mode during the incident - a feature that enables the car to steer, accelerate and brake on its own
by Shivali Best, https://www.facebook.com/shivalibestjournalist/A family of ducks in New Zealand had a lucky escape last week, after a Tesla car swerved out of its way at the last minute.
The Tesla Model 3, which was being driven in Gisborne, was in Autopilot Mode during the incident - a feature that enables the car to steer, accelerate and brake on its own.
During the incident, a family of ducks started crossing the road, just as the car came down the road.
The driver, who remains unnamed, has admitted that he didn’t notice the ducks because of a shadow on the road.
However, using one of its eight cameras, the car itself detected the ducks, and quickly swerved out of the way to avoid them.
The driver said: “If it wasn't for the Autopilot function, I think the ducks would not have survived.”
While Autopilot may have saved the ducks this time, the feature has been blamed for other collisions in the past.
For example, Tesla hit the headlines back in March after one of its cars was involved in a fatal collision in Florida.
The incident saw a Tesla Model 3 crash into a semi-truck, sadly killing the driver in the process.
A follow-up report by the National Transportation Safety Board revealed that the Tesla had Autopilot mode activated seconds before the crash.
Jeremy Banner was behind the wheel of the Tesla on a four-lane highway in Palm Beach County, when the semi-truck pulled out in front of him.
Despite having Autopilot mode activated, the Tesla slid under the truck’s trailer, cutting off the top of the car, and killing Mr Banner.


Before Change
if checkpoint_dir is None:
checkpoint_dir = self.config["checkpoint_dir"]
print("[*] Loading checkpoint...")
checkpoint_path = tf.train.latest_checkpoint(checkpoint_dir)
if checkpoint_path is None:
raise ValueError("Checkpoint not found")
self.saver.restore(self.sess, checkpoint_path)
After Change
if checkpoint_dir is None:
checkpoint_dir = self.config["checkpoint_dir"]
print("[*] Loading checkpoint...")
with open(os.path.join(checkpoint_dir, "checkpoint")) as f:
checkpoint_name = os.path.basename(f.readline().split()[1])
checkpoint_path = os.path.join(checkpoint_dir, checkpoint_name)
if checkpoint_path is None:


Check this link to see <script type="module"> compatibility.
Good page about modules
Another in deep analysis of modules


DROP
- Each player drops a stone on an empty cell.
The
gravitation of the board pulls the stone towards the edges
(check examples), until it reaches an edge or an already
occupied cell.
GOAL - A player wins when he makes an
orthogonal or diagonal 4 in-a-row.
Some
attractions...
If a stone
at cell [1] will be moved towards left, until cell a5.
If a stone at cell [2] will be moved towards the top, until cell d8.
If a stone at cell [3] will be moved towards top-left, until cell c6.
If a stone at cell [4] will be moved towards top-right, until cell h8.


{% extends "main.html" %} {% block content %}
Here you can find a variety of music spanning a wide variety of genres and themes. Feel free to login and post your own!


This is an example of how to use the esri.core module to create your own custom map directive that you can reuse throughout your application. View the page source to see how the directive is implemented.
esri.core
Based on this sample.


The Gaussian integral is probably one of the most important integrals in math, physics and of late computer science too.
So, today I was reading about random variables with a normal distribution and I came across this not so obvious integral . Obviously, out of curiosity, I tried verifying the results by an unsuccessful attempt at integrating it. I tried several alternatives including integration by parts and various substitutions. Sadly, I could not even simplify it further. The integral only got more complex as I tried to simplify. So, I finally gave up and thought of reverse engineering the solution. So, I went to Wolfram Alpha and inquired about the solution and to my relief, this is what came out :
On further investigation I found out that represents the error function and it is quite complicated in nature. The Risch algorithm proves that no elementary function exists for the error function. This means that it cannot be represented as some simple arithmetic combination of our common functions. Mathematically, the is defined as follows:
Now, since the hopes of finding the indefinite integral were shattered. I went on to explore the methods of finding the original integral and came across a very elegant solution. The integral can be calculated as follows :
Now consider,
Looking at the form obtained, polar coordinate substitutions appear to be inevitable. So we substitute as follows:
Substituting it back in the integral we get
On substituting we have
So, finally we get the following result :