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:1: IN THE HIGH COURT OF KARNATAKA DHARWAD BENCH Dated this the 3rd day of February, 2014 Before THE HON'BLE MR. JUSTICE ARAVIND KUMAR WRIT PETITION Nos. 84238/2013 & 84246/2013 (GM-RES) BETWEEN: 1 THE LUCKY AGENCIES REP BY ITS PROPRIETOR SMT. FATIMA SAIDANI MOHAMMED AGE: 38 YRS, SY.NO.21/4, BILAKHAND GULMI ROAD, TQ: BHATKAL DIST: UTTARA KANNADA 2 THE LUCKY A.S.FOOD PRODUCTS INDUSTRIES REP. BY ITS PROPRIETOR MOHAMMAD ALTAF AFRICA AGE: 43 YRS, SY.NO.21/4, GULMI ROAD, BILALKHAND TQ: BHATKAL DIST: UTTARA KANNADA ... PETITIONERS (By Sri F V PATIL, ADVOCATE) AND : 1 THE ASSISTANT COMMISSIONER/ SUB DIVISIONAL MAGISTRATE BHATKAL DIVISION BHATKAL, DIST: UTTARA KANNADA :2: 2 THE TAHASILDAR BHATKAL, UTTARA KANNADA 3 PANCHAYAT DEVELOPMENT OFFICER MUTTHALLI, TQ: BHATKAL DIST: UTTARA KANNADA 4 KARNATAKA STATE POLLUTION CONTROL BOARD, ENVIRONMENTAL OFFICER KSPCB, KARWAR ... RESPONDENTS (By Sri. K.S.PATIL, HCGP FOR R-1 & 2 Sri GURUDEV I GACHCHINMATH, ADV FOR R-3 & 4) ---------- THESE WRIT PETITIONS ARE FILED UNDER ARTICLES 226 & 227 OF THE CONSTITUTION OF INDIA, PRAYING TO QUASH IMPUGNED ORDER DTD. 10.06.2013 PASSED BY RESPONDENT NO.1 VIDE ANNEXURE-G AND ETC.,. THESE PETITIONS COMING ON FOR ORDERS THIS DAY, THE COURT MADE THE FOLLOWING: ORDER
Heard Sri F V Patil, learned Advocate appearing for petitioner, learned HCGP appearing for respondents-1 and 2 and Sri Gurudev I Gachinmath, learned Advocate appearing for respondents-3 & 4. :3:
2. By consent of learned Advocates appearing for the parties, writ petition is taken up for final disposal.
3. Petitioners with intention to establish two industries, claim to have obtained permissions, approvals and licences from the statutory authorities including consent as prescribed under Water (Prevention and Control of Pollution) Act, 1974 and Air (Prevention and Control of Pollution) Act, 1981 (hereinafter referred to as 'Water Act' and 'Air Act' respectively for sake of brevity) and contend that despite such consents, approvals and licences issued by the statutory authorities, Special Divisional Magistrate without there being authority of law has assumed jurisdiction under Section 133 Cr.P.C. and has passed the impugned order - Annexure-J dated 25.10.2013 and seeks for quashing of the same.
:4:
4. Learned HCGP appearing for the State would support the impugned order contending that Sub Divisional Magistrate is empowered to pass a conditional order as has been done in the instant case on 10.06.2013 - Annexure-G and on account of said order having not been complied, an order of injunction has been passed on 25.10.2013- Annexure-J which is in the interest of general public and he is yet to pass a final order and as such, this Court should not interfere with the said orders.
5. Perusal of the case papers would indicate that undisputedly petitioners have obtained sanction for discharge of effluents both under the Water Act and Air Act as per Annexures-B and B1 dated 31.03.2012 from Pollution Control Board. Said consent has been given by respondent No.4 in exercise of its power under Section 25 and 26 of the Water Act and Section 21 of :5: the Air Act subject to conditions stipulated in the schedule to said consent orders.
6. On a representation given by residents of locality where petitioners have set up their industry, Sub Divisional Magistrate has initiated proceedings against petitioners under Section 133 of Cr.P.C. alleging that public nuisance is being created by the industries run by petitioners. He is said to have conducted spot inspection on 05.06.2013 and issued notices to both petitioners and the complainant to appear before him in the enquiry to be held on 06.06.2013. Said proceedings came to be adjourned to 10.06.2013. On said date the petitioners and their advocate appeared and undertook that they would not create any public nuisance and would stop such nuisance if any. After considering the rival contentions, first respondent passed an order of injunction restraining the petitioners from running the industry within 10 days from the order dated :6: 10.06.2013 - Annexure-G. For reasons best known, consents given under the Air Act or Water Act by fourth respondent to the petitioners to run the industry were not produced before first respondent. However, undertaking was given by petitioners that effluents being discharged by the industry would be stopped. In view of this undertaking given by the learned Advocates appearing for petitioners as well as petitioners in the enquiry conducted by first respondent, order dated 10.06.2013 came to be passed by first respondent directing petitioners to stop all activities of industries run by them as noticed hereinabove. Subsequently, on 25.10.2013 petitioner No.1 has filed a memo before first respondent enclosing consent/permission granted by fourth respondent as also Safety Certificate issued by the Director of Industries and Boilers. Though said memo filed along with documents were received by first respondent, has proceeded to pass the impugned order dated 25.10.2013 - Annexure-J restraining the :7: petitioners from running the industries by issuance of injunction merely on the say of some of residents that petitioners have continued to discharge the effluents.
7. A perusal of order dated 25.10.2013 would clearly indicate that first respondent has not taken into consideration consent given by the fourth respondent as per Annexures-B and B1 under Water Act and Air Act and permission granted by the Director of Industries and Boilers which is at Annexures-C & C1 and has proceeded to direct the petitioners to stop the operation of their industries. In view of the fact that fourth respondent - State Pollution Control Board has already issued consent under the Water Act and Air Act to the petitioner to run their industry, it would be needless to state that fourth respondent and its officers would be empowered to ascertain as to whether conditions stipulated by the fourth respondent on the petitioners- industries while giving consent have been adhered to or :8: whether there is infraction of said conditions stipulated and if there is any public nuisance created, first respondent would be at liberty to proceed against the petitioners in accordance with law. There cannot be any dispute with regard to power to be exercised by fourth respondent or its officers in this regard.
8. Be that as it may. First respondent in order to prevent the breach of public nuisance would undoubtedly be empowered to exercise his powers under Section 133 Cr.P.C. The mandate of Section 133 Cr.P.C. is required to be followed which is not forthcoming from the impugned order, inasmuch as, from the perusal of impugned order at Annexure-J it would clearly indicate that first respondent has not taken into consideration the consent orders issued by the Pollution Control Board - fourth respondent to the petitioner-industries. Impugned order do not disclose as to whether petitioners have complied with the terms and :9: conditions set out in the respective consent orders issued by fourth respondent. It was incumbent upon the first respondent to examine as to whether petitioner- industries have established effluent treatment plant and complied with the conditions imposed under the relevant consent orders or not and thereafter first respondent could have passed orders in accordance with law. However, without undertaking such an exercise, first respondent has proceeded to pass virtually an order of injunction against petitioner- industries.
9. In that view of the matter, I am of the considered view that it would suffice and it would meet the ends of justice if first respondent is directed to examine the claim of petitioners in the light of memo filed by them on 25.10.2013 - Annexure-H and proceed to pass orders afresh in accordance with law after affording opportunity to all parties.
: 10 :
10. For the reasons aforestated, following order is passed:
(i) Writ petitions are hereby allowed.
(ii) Order dated 25.10.2013 vide Annexure-J is hereby quashed.
(iii) The matter is remitted back to first respondent for consideration afresh on merits in accordance with law by keeping in mind the observation made herein above, expeditiously, at any rate, within three weeks from the date of receipt of certified copy of this order.
(iv) First respondent shall not be influenced by any observations made in order dated 10.06.2013 Annexure-G and order dated 25.10.2013 - Annexure-J.
(v) It is needless to observe that fourth respondent would also be at liberty to examine as to whether terms and conditions stipulated in the consent orders given by them to petitioners as : 11 : per Annexures-B1 and C1 is complied with or not and take steps in accordance with law.
(vi) It is also made clear that no opinion is expressed on merits of the claim made in the writ petitions.
(vii) All contentions raised by the petitioners in the present writ petitions are left open.
SD/-
JUDGE *sp


{# Load bootstrap and FA locally; The CDN's not loading on gov computers; blocked? #}
Lakenheath Links
{# Optional block for a link to the home screen.#} {% block home %}{% endblock %} {% if current_user.is_authenticated() %}
Logged in as {{ current_user.email }}.
Logout
{% endif %}
{% block content %}{% endblock %}
{# Use lakenheath.herokuapp.com/admin instead of /admin for SSL workaround. #} {#
Admin
#}
Admin
{# Jquery version 1 for legacy IE support. #} {# Load bootstrap and FA locally; The CDN's not loading on gov computers; blocked? #}


You can reserve the seats for the movies that are screencasting in all the theatres in Sri Lanka. It's easy and convinient way to make your life easy. No more waiting lines, just try it today!
You can order the snack when you are reserving the tickets. You won't miss a single thing and watch the movie without worrying about buying snacks.


Table of Contents
QGraph is a visual query language designed to support knowledge discovery in large graph databases. Such databases are used to represent relational data, that is, data that explicitly represent both objects and the relationships among them.
QGraph has some important differences from standard relational database query languages such as SQL. Most obviously, QGraph is a visual query language. Queries are created by drawing the desired graph structure and adding restrictions in the form of conditions, constraints, and numeric annotations. QGraph includes a grouping and counting mechanism that lets users move beyond specifying an exact database structure in a query. Queries can contain generalized structural descriptions, enabling a single query to match a variety of database structures.
Unlike SQL, which returns individual records, QGraph queries return subgraphs, complex objects that correspond to connected sets of objects and relations in the queried database. These subgraphs retain the full details of the database objects and links rather than just providing aggregations such as count or average. Subgraphs give users access to both the content and structure of the matches when analyzing and exploring relational data.
QGraph is used in Proximity, an open-source system for relational knowledge discovery. Although QGraph is a full-fledged query and update language for graph databases, Proximity currently only implements a large subset (but not all) of QGraph functionality. This document focuses on the features of QGraph that have been implemented in Proximity. See the technical report A Visual Language for Querying and Updating Graphs [Blau, Immerman, and Jensen, 2002] for a full description of QGraph’s power, including functionality not yet available in the current Proximity implementation.[1]
QGraph is designed to work with graph databases such as those used by Proximity. Proximity databases are directed, attributed graphs where nodes correspond to objects (typically people, places, and things) and binary links represent the relationships among objects. Both objects and links can have zero or more attributes and all attributes are set valued. For example, in a database containing information about movies, an object representing an actor might have a name attribute that has multiple values for the actor’s given and stage names. Similarly, a link connecting an actor to a movie might have a role attribute that could contain multiple values when the actor plays multiple roles in a film.
QGraph queries return a collection of subgraphs from the database that match the structure specified in the query. In Proximity, this result set is called a container. A container’s subgraphs include the matching objects and links as well as all associated attributes for these elements.
To get a sense of QGraph’s power and flexibility, consider a graph database containing information on the movie industry. Such a database might represent movies, actors, directors, producers, studios, and awards as objects, with links representing the relationships among these entities. We might query such a database to identify simple subgraphs such as movies and their actors, or more complex subgraphs such as all the actors who have worked with a particular director, following links through the associated movies. The query in Figure 1.1 finds just such subgraphs.
Without explaining the query’s notation at this point, we observe
that this query finds directors connected to one or more
movies, which are in turn are connected to one or more actors. When the
query finds a match in the database, it returns the entire
matching subgraph.
Figure 1.2 shows the kind of subgraph that might get returned as a match for such a query. This subgraph shows the director Steven Spielberg and the links from him to the movies that he’s directed. Those movies are in turn linked to the actors that appeared in those movies. (Like other examples in this guide, data for this example is intended to be representative, but not necessarily complete.)
An important feature of this subgraph is that movies are linked to
different numbers of actors. We do not need to know, and the query
does not have to specify, how many actors are linked to each movie.
Similarly, we do not need to know how many movies Steven Spielberg has
directed. The matching subgraph for another director is likely to
include a different number of movies, and those movies are also likely
to be linked to varying numbers of actors. QGraph lets us create a
simple, easily understood query that matches varying graph
structures.
By returning complete subgraphs, QGraph provides results particularly well suited for use in relational knowledge discovery. Unlike query languages that require propositionalizing attribute data from related objects, QGraph preserves both the explicit relationships among objects and the specific attribute values for all objects and links in the subgraph. Simplistic approaches to propositionalizing relational data can result in bias due to hidden autocorrelation or degree disparity. By preserving the full relationship and attribute value data, QGraph facilitates the development of models that can detect and adjust for such sources of bias.
QGraph includes several mechanisms that together provide a powerful system for specifying the graph structures that match a QGraph query: These mechanisms are introduced in the following chapters:
Chapter 2, Query Basics describes the basic structure and results of a QGraph query
Chapter 3, Conditions introduces conditions, which place restrictions on the attribute values of matching objects and links.
Chapter 4, Numeric Annotations describes numeric annotations, a powerful and elegant counting feature that serves to limit and group query results.
Chapter 5, Constraints describes constraints, a global mechanism that relates one object or link to another.
Chapter 6, Subqueries describes subqueries, which enable the treatment of connected subgraphs as a logical unit in defining more complex queries.
Appendix B, XML Representation describes the Proximity XML representation for queries.
A QGraph query is a labeled graph designed to correspond to selected structures in the target database. The vertices in the query correspond to objects in the database and the edges in the query correspond to database links. This distinction in terminology is important and will be maintained throughout this guide—we use the terms object and link when referring to database entities, and the terms vertex and edge when referring to query elements.
Because QGraph is currently only implemented in Proximity, this Guide includes a discussion of how that implementation may affect the use and interpretation of QGraph queries and results. When applicable, each chapter includes a section that describes factors you should be aware of when using QGraph in Proximity, such as how query results are stored in the database, efficiency considerations, or implementation restrictions. Information presented in these sections is not part of the QGraph specification, but can be useful when understanding how QGraph works in Proximity.
An important characteristic of Proximity databases is the lack of an inherent sense of object or link types. Type information is stored as an attribute value, just like any other attribute. When we refer to an actor object or role link, we are using a convenient shorthand for “an object whose ‘type’ attribute has a value of ‘actor’ ” or “a link whose ‘kind-of’ attribute has a value of ‘role.’ ” Users are free to include or not include type information in a database’s object and link attributes and to use whatever name they chose for an attribute that stores type information. Descriptions in this document may refer to objects and links by type (e.g., an actor object or role link) or value (e.g., the Peter Sellers object) with the understanding that this is a shorthand for database objects and links containing attributes that represent this “type” information or that have the specified attribute value.
Databases, QGraph queries, and matches identified by executing those queries are all graphs. To help distinguish these items, the Guide follows the following graphic conventions:
Database fragments use shaded ovals to represent the objects in the database. Attributes are shown next to their corresponding object or link.
Queries use white circles for vertices. Query vertices and edges are labeled.
Query results use shaded ovals to represent the objects in the resulting subgraphs. Subgraph objects and links are labeled with the corresponding query labels. Because QGraph queries return complete subgraphs that include all attribute values for the component objects and links, we also show attribute values in our graphical representations of subgraphs.
The QGraph Guide is primarily intended for readers with little to no experience using QGraph. The major chapters are heavily oriented around a series of examples, making the Guide a relatively quick read. More experienced users may want to take advantage of the summary at the end of each chapter or return to the Guide to improve their understanding of specific issues.
Most of the examples
in the QGraph Guide,
including both database fragments and queries, are available in the
$PROX_HOME/doc/user/qgraph/examples
directory. When such files are
available, the figure caption includes the appropriate file name.
See the Proximity Tutorial
for complete instructions
for importing databases and running queries.
[1] How QGraph evaluates conditions and constraints on attributes with multiple values has changed since the publication of this technical report. On this issue, the Proximity QGraph Guide is definitive.


Constructor Summary
| Private Constructors | |
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| private |
CLI(options)
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Property Summary
| Private Properties | |
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| private |
analytics: Unknown
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| private |
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| private |
instrumentation: Unknown
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| private |
name: Unknown
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| private |
npmPackage: Unknown
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| private |
root: Unknown
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| private |
ui: UI
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Method Summary
| Private Methods | |
|---|---|
| private |
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| private |
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| private |
maybeMakeCommand(commandName, commandArgs): Null | CurrentCommand
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| private |
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Private Constructors
lib/cli/cli.js:15
private CLI(options)
Parameters:
| Name | Type | Attribute | Description |
|---|---|---|---|
| options | Object |
|
Private Properties
lib/cli/cli.js:35
private analytics: Unknown
lib/cli/cli.js:48
private disableDependencyChecker: Boolean
lib/cli/cli.js:67
private instrumentation: Unknown
lib/cli/cli.js:22
private name: Unknown
lib/cli/cli.js:61
private npmPackage: Unknown
lib/cli/cli.js:55
private root: Unknown
lib/cli/cli.js:41
private testing: Boolean
lib/cli/cli.js:28
private ui: UI
Private Methods
lib/cli/cli.js:262
private callHelp(options): Promise
Parameters:
| Name | Type | Attribute | Description |
|---|---|---|---|
| options | Object |
|
Return:
lib/cli/cli.js:303
private logError(error): Number
Parameters:
| Name | Type | Attribute | Description |
|---|---|---|---|
| error | Object |
|
Return:
lib/cli/cli.js:83
private maybeMakeCommand(commandName, commandArgs): Null | CurrentCommand
Return:
Null | CurrentCommand
lib/cli/cli.js:122
private run(environmentPromiseHash): Promise
Parameters:
| Name | Type | Attribute | Description |
|---|---|---|---|
| environmentPromiseHash | Promise |
|


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// NOTE This is for August 2001 XDK and used to satisfy the XDK
Build
// This doc is prior to the 4400 Complex Tree
// There was no
documentation like this in the tree
This release of the Xbox Development Kit (XDK) for the Xbox™ video game system from Microsoft updates the software on the console and the Xbox SDK on your development system. Install the updated SDK on your development system and update your console software with the Xbox console recovery disc. Please note that running the latest recovery disc is required for this release. The data that is preinstalled on the console must be updated to function with this version of the Xbox SDK. Refer to the installation instructions for complete information.
Note The console and development software included with this release of the XDK will be replaced by updated systems in subsequent releases.
For support and to send us feedback, please contact us at:
Warning: Once the August Preview release has been installed on your development console, you will not be able to downgrade the system to any of the previous releases. You can, however, switch between the Debug and Retail versions of the August Preview SDK.
The following graphics functions have had their signatures changed:
Please note that these changes will break any code that uses these functions.
Titles using Microsoft® DirectMusic® should now call DirectMusicInitialize, DirectMusicInitializeEx, or DirectMusicInitializeFixedSizeHeaps before making any DirectMusic calls. Currently, calling an initialization function is optional (DirectMusic will do it for you), but it will be required with the September release of the Xbox System Software.
Recovery now allows you to recover a console as a development kit (as it always has in the past) or as a retail console (a new option). Press the Y button on the gamepad when prompted to recover the console as a retail console. Once complete, the console will behave much like a retail Xbox console that will be sold to customers, which can be useful for testing a game title prior to sending in for certification. In this retail configuration, only 64 MB will be available, titles will need to be loaded from the disc drive, the Title Launcher and samples will not be installed, the Xbox Dashboard will be the default title, and you will not be able to use the remote debugger or use xb* tools to communicate with the console.
Changes in our August Preview 2001 XDK release are incompatible with the June and July Game Disc (DVD) Emulation software and tools.
Applied Microsystems has provided a new hardware driver for your Microsoft® Win32®–based PCI Game Disc Emulation card. We’ve fixed a handful of issues and made the driver even more stable.
All users of Game Disc Emulation must take the following steps:
"C:\Program Files\Microsoft Xbox SDK\xbox\bin\amcinfo.exe"This program will test whether the XDK-DVD PCI card on the development system is working properly.
If the revision is reported as 0x01, the PCI chip is okay and you should attach the hard drive to the XDK-DVD PCI card using the IDE cable. It is best to follow the instructions listed in the Xbox SDK Help under "How to Install the Xbox Game Disc Emulation Software for the First Time."==================================================== Xbox DVD Emulation Card Diagnostics Copyright (C) 2001 Applied Microsystems Corporation All rights reserved. ==================================================== Querying Xbox DVD Emulator card......DONE TI PCI2250 bridge chip revision = 0x01
Please upgrade to the new driver by following the instructions in the Xbox DVD Emulator Setup and Upgrade topic.
For this release, the memory clock speed (which includes the memory clock and front-side bus/processor) has been raised to one-percent higher than the final speed. This temporary adjustment has been made to increase stability on the pre-release version of development consoles. The following list defines the speed changes:
| August preview release clock speeds | |
|---|---|
| Memory clock | 202 MHz |
| Front-side bus clock | 135 MHz |
| Processor clock | 740 MHz |
| August final release clock speeds | |
|---|---|
| Memory clock | 200 MHz |
| Front-side bus clock | 133 MHz |
| Processor clock | 733 MHz |
The Japanese language version of the CertGame will not be fully localized for the August Preview release.
The old DVD Layout tool has been replaced by the Xbox Game Disc Layout tool. A shortcut to the new tool has been placed in the Start menu.
There is a bug in the Voxware codec that prevents the proper enumeration of any codecs installed after the Voxware codec. In particular, this will prevent the usage of the Xbox ADPCM codec. In order to use the Xbox ADPCM codec, you should follow the following steps:
The Xbox ADPCM codec is installed automatically when you install the XDK; however, if you want to install the codec without the XDK, go to the ADPCM directory on the installation CD, right-click xbadpcm.inf, and select Install from the context menu that pops up.
Previously, only progressive-scan modes were supported with this AV pack. The default video mode for the Xbox Dashboard and for DVD playback is now 480i. An additional video setting has been added to the Dashboard to allow a user to specify that 480p is supported by their TV. If this setting is enabled, 480p video modes will also be enabled with the HDTV AV Pack. This allows the HDTV AV Pack to be used with TVs that have component inputs but do not support progressive-scan video modes, and enables more Xbox customers to take advantage of the superior output quality of component video. It also allows games that use field-rendering to select an interlaced mode when the HDTV AV Pack is installed. 480p generally provides better output quality than 480i, so if both video modes are enabled, please select 480p unless your game requires an interlaced mode.
DirectMusic now defers to DirectSound to handle improper ADPCM loop points (not on 64 sample boundaries). Previously, DirectMusic would attempt to “fix” the loop points to legal values, which in many cases led to hard-to-debug poor loop points. Note that this change means that for debug builds, DirectMusic content authored with bad ADPCM loop points will now assert in DirectSound (just as illegally looped ADPCM wave content played directly in DirectSound does).
Loops in Xbox ADPCM files must start on a 64-sample boundary and have a length that is a multiple of 64 to make sure your content is properly aligned.
DVD Emulation does not work when a Xbox Development Kit is recovered with the Retail option on the recovery CD. It will work when the Xbox is recovered using the Dev Kit option of the recovery CD. This will be fixed in an upcoming release.
As of this release, all samples support the button configuration on the final controller. For information on the button configuration, see the SDK Help documentation. Also note that samples will continue to support the soft reset combo "Left Trigger" + "Right Trigger" + "Black". Only the CertGame will additionally support the required combo "START" + "BACK" for three seconds.
AdpcmCreateDecoder XMO has been removed, since Microsoft® DirectSound® now supports ADPCM decompression on the hardware.
All titles using 3-D sound must call either DirectSoundUseFullHRTF or DirectSoundUseLightHRTF before creating a 3-D buffer.
If you are using the network in your title, you will have to make a small change to the initialization code or you will not be able to compile.
Replace your call to XnetInitialize with:
XNetStartupParams xnsp; memset( &xnsp, 0, sizeof( xnsp ) ); xnsp.cfgSizeOfStruct = sizeof( XNetStartupParams ); xnsp.cfgFlags = XNET_STARTUP_BYPASS_SECURITY; INT err = XNetStartup( &xnsp );
This will tell the Xbox Secure Network Library to allow insecure communication with a PC in case you use the network for private game debugging or monitor purposes. For system link play when communicating with another Xbox, you should use the new secure APIs (XNetRegisterKey, XNetXnAddrToInAddr, etc.). Attempting to bypass security when linking with xnets.lib is not an error, but the flag is ignored.
Do not plug your DVD emulation hard drive into the IDE port on the emulation card. Instead, please use a free IDE port on your computer. Your software function and performance should not be impaired. Applied Microsystems is aware of this problem and is working hard to provide a fix to very soon.
This release of the Xbox SDK adds an automatic copy feature to Visual C++. Once an Xbox executable (.xbe) file is built, it is automatically copied to the console using the remote executable path (specified under Project Settings/Debug). This feature can be disabled on a per-project basis, using the check box labeled Disable automatic copy of XBE file under Project Settings/Xbox Image. However, there is a bug that prevents the user's setting from being saved with the project file (.dsp). If a user wishes to disable the automatic copy feature, this check box will need to be re-checked every time the project is opened.
DirectSoundDoWork() should be called in your main render loop. It (1) does work to make DirectSound notifications work, and (2) frees up hardware resources by LOCDEFERed buffers that have finished playing.
All games should call IDirectSound::DownloadEffectsImage() using the provided default DSP image, dsstdfx.bin. This is required if you want 3-D sounds to play properly. The default image can be found in the play3dsound\media\dsstdfx.bin directory.
The third parameter of IDirectMusicPerformance8::InitAudioX has been changed. The new parameter (dwVoiceCount) specifies the number of hardware 2-D voices allocated to DirectMusic. These voices will not be available for DirectSound. Do not include the number of 3-D buffers (3-D audiopaths) you intend to use in this count. Also, when these voices are reserved, the total number of available voices decreases accordingly.
The Microsoft® DirectPlay® and DirectPlay Voice title libraries have been temporarily removed from the XDK. They are being updated with the changes in DirectX 8.1 and our new Xbox Secure Network Library. The DirectPlay and DirectPlay Voice libraries are currently scheduled to be restored in the September release of the XDK. Please contact your account manager if this is going to impact your schedule. Titles can still use Xbox Winsock and the Xbox Secure Network Library to implement networking.
Dolby data is output on the digital output, provided you have an AV connector with optical digital out.
ADPCM data packets used for IDirectSoundStreams need to be in physically contiguous memory. Allocate packets with XPhysicalAlloc (and release with XPhysicalFree). This applies only to IDirectSoundStreams; DirectSoundBuffers do not have this restriction.
Only reverb and chorus are supported on standard audiopaths.
The values for the surface formats (D3DFORMAT) in the Microsoft® DirectX® version have been significantly modified for Xbox. See the D3DFORMAT topic in the Xbox XDK for more information on valid Xbox values.
All memory units must be formatted in the Title Launcher before use with this release of the XDK.
When an Xbox project is built for the first time (including the provided samples), a Remote Executable Path And File Name window will appear asking you to enter the remote executable path and file name. This is the location on the Xbox that you want the .xbe file copied to. For example, if you just built the Fuzzy Teapot sample, you would enter "xe:\samples\fuzzypot\fuzzypot.xbe". Samples are generally copied into their own subdirectory under xe:\samples, but you are free to specify any location on the xe:\ drive.
The XQueryValue function is no longer available for querying system settings. Instead, use the new XGetxxx settings functions. The new functions are: XGetLanguage, XGetAVPack, XGetVideoStandard, XGetVideoFlags, XGetAudioFlags, XGetParentalControlSetting, and XGetGameRegion. Refer to the xbox.h header file for function signatures and applicable flags. Full documentation will be available in a future release of the XDK.
The library is implemented as part of the normal Xbox networking and Winsock functionality. With the addition of a few extra function calls, your existing Xbox Winsock code will function with the secure library. Check the winsockx.h header for the available XNetxxx functions (including XNetStartup) that provide the Xbox Secure Network Library functionality. Full documentation and a sample will be included in a future release of the SDK. Also see the Xbox Secure Network Library section in the Xbox SDK online documention for more information.
The following changes have been made to the Xbox networking and Winsock libraries for this release:
The following functions are obsolete and will be removed in the next release:
To avoid a "No address for Xbox has been set" error message, update the development system:
The new version of the Bundler tool has a dependency on Microsoft® DirectX® 8.0. Because the media for these samples requires the bundler during compilation, you must have the DirectX 8.0 SDK on any system that builds these samples.
Save game signing has been added (using the new save game signing functions) to the LoadSave reference UI sample. The new signing mechanism on saved games means that old save games for the LoadSave sample are now invalid. If you try to load old saves, you'll see the message "Unable to load %s.".
If you have installed Visual C++ 6.0 Service Pack 5, you must install the lastest Microsoft Visual C++ Processor Pack, as the service pack overwrites changes made by any previously installed processor pack. Previous versions of the processor pack will not install on top of Service Pack 5:
Because of hardware synchronization that has to occur to eliminate hardware race conditions, when activating submixed voices the audio voice processor will slowly drift behind the ACI DMA. This will cause a recurring audio distortion. The issue will be resolved in a future release.
After installing the Xbox SDK, the library and headers paths for Visual C++ are set only for the user that performed the installation. If you log in as another user, the library and header path environment variables will not be set.
For Microsoft® Visual C++® 7.0 code optimization on an Xbox console, use -GB/-G6 (GB now maps to G6). For speed optimization, the recommended settings are -O2 -GL -Gr. For aliasing, you can use -Oa or -Ow. However, it should be noted that if your program uses a linked list, these settings should not be used. Also note that the majority of aliasing problems disappear with Link Time Code Generation.
XGraphics.lib now contains a math library (xgmath.h). This library has the same function signatures as the Direct3DX math library, but many of the functions have been optimized to use the Pentium III SSE instructions. You can immediately begin using the optimized library by specifying the following #define before including xgmath.h:
#define _USE_XGMATH
This causes the Direct3DX math function names to be aliased to xgraphics math functions. Matrices used with the XGraphics math library must be 16-byte aligned. This is normally the case if memory is allocated just for a matrix, but in the case in which a matrix might be part of a larger structure, it may not be aligned properly.
XGraphics.lib contains a new method called XGCompressRect() that can be used to compress textures into DXTn formats. This method yields better quality compression than the Direct3DX compression code.
XDxTex has been modified to generate .dds files with the correct format enumerants. This means that they are compatible with .dds files generated by the DirectX tool, DxTex. In addition, Direct3DX on Xbox has been modified to read .dds files that contain these enumerants. It will continue to read .dds files generated with the previous version of XDxTex. XDxTex uses the improved compression code in XGraphics.lib rather than the compression code in D3DX.lib.
On Xbox, the format enumerant for DXT2 and DXT3 is the same because the hardware deals with these texture formats in the same way. The same is true for DXT4 and DXT5. The difference between DXT2/DXT4 and DXT3/DXT5 is that the former formats assume that the RGB values in the texture have been multiplied by the alpha value before the compression takes place. When Direct3DX is used to compress a texture (usually by loading a texture from a non-compressed file format to a compressed texture), it previously had no way to distinguish between these formats. An application can now call the new Direct3DX method SetDXT3DXT5(TRUE) if non-premultiplied textures are desired. A value of FALSE can be passed in this function if alpha premultiplied textures are desired.
The Bundler tool does not support reading from .jpg or .dds files in this release. We plan to correct this in a later release.
Debug support for the USB keyboard has been moved out of xapilibd.lib and into an independent library: xkbd.lib (or xkbdd.lib for debug builds). This means that the debug keyboard support can be used in a release build or a debug build of a game title as opposed to requiring a debug build. The DEBUG_KEYBOARD define, which causes the keyboard support definitions to be included, is no longer turned on automatically based on the _DEBUG define. In this release, in order to use debug keyboard support, DEBUG_KEYBOARD must be defined and xkbd.lib or xkbdd.lib must be linked in. This library is not permitted to be used in shipping retail game titles.
This release of the Xbox XDK CD includes the Arial Unicode font (TTF), which includes all code pages for valid Xbox regions. Note that this font is not included in the XDK download. On the XDK CD, the font is located in the \Extras\Fonts directory.
Scheduling DirectMusic::PlaySegmentEx for the future may cause problems. When using PlaySegmentEx, do not use the API to schedule events for future playback; these should be scheduled manually.
The meaning of the mad pixel shader instruction has been changed to match the Microsoft® DirectX® 8.0 semantics. The old behavior was:
mad d, a, b, c // d = a + b * c
This has been changed to the following:
mad d, a, b, c // d = a * b + c
This change will break any pixel shader that used the mad instruction, and no compiler warning or error will be generated. It is necessary to update all pixel shaders using this instruction by moving the second parameter of any mad instruction to be the fourth parameter.
The wMemoryAllocated member of the GetCaps structure does not accurately reflect the total amount of DirectSound memory used, particularly when using SetBufferData to specify DirectSoundBuffer data pointers.
With this release, "partial downloads" are no longer supported in the Xbox libraries derived from Microsoft® DirectMusic®. This may cause problems if the DirectMusic content contains references to gm.dls, for example. Ensure that your DirectMusic content references only explicitly set DLS instruments.
The loader for DirectMusic should be explicitly released after loading content segments. Simply releasing a content segment does not actually release memory. If the loader itself is not released and new music is continuously loaded, the title could run out of memory.
There are many Xbox Title Libraries (XTL) functions that cannot be called safely from within a debug channel command handler. Any XTL function that is called that affects the value of GetLastError may cause the console to stop responding. Also, any return value of GetLastError may be incorrect. When developing a debug channel command handler, call as few XTL functions as possible. This problem will be addressed in a future release of the XDK.
The C run-time string functions that were in question in a previous release are now safe to call.
The reference material for the Xbox system level libraries may contain some links to overview information that is not yet available. When one of these links is selected, typically a "Topic Not Supported" page will be displayed.
Using stack sizes smaller than the default of 64 K currently is not recommended. Many functions have not been tested for use with smaller stack sizes. For example, playback of Microsoft® Windows Media™ Audio (WMA) files may cause a title to crash if the stack size is smaller than the default setting; on the thread that does WMA playback (if a dedicated thread was created for that purpose), make sure to use a stack of the default size or larger.
If you are installing the version of the DVD emulation software included with this release of the Xbox SDK on a Japanese development system, you must unzip either 16056_JPN_i386.zip or 16056_JPN_nec.zip to run the hot fix for a Japanese Microsoft® Windows® 2000 system. When the DVD emulation software is installed on the development system, these hot fix files are located in the following directory:
[Install Location]\DVDEmulation\Driver.
When playing DLS segments with many simultaneous notes, the audio output may clip, causing distortion. To reduce this effect, call the IDirectMusicPerformance8::SetGlobalParam() function with GUID_PerfMasterVolume and a negative value to attenuate the overall volume of DirectMusic. (See documentation for proper use of SetGlobalParam.)
You must update your console using the Xbox console recovery disc. Since the recovery image updates the ROM, it is critical that you do not power off or reboot during the recovery process.
Boot the console using the updated recovery disc and follow the on-screen instructions. The console will then be running the updated system software that is compatible with this release of the Xbox SDK.
The .iso disc image file is also available for download on the beta support Web site (https://xds.xbox.com). If you choose to download the recovery image update, use this image file to burn an updated recovery disc (see your CD image burning software documentation for details on this process). Please note that the CD image must be burned to a CD-RW disc—CD-R media is not supported.
The video mode settings can be changed using the new Xbox Controller during either the recovery process or from within the Title Launcher. The settings are now:
Left trigger + right trigger + D-pad right = NTSC-M (North America)
Left trigger + right trigger + D-pad up = PAL-I
Left trigger + right trigger + D-pad left = NTSC-J (Japan
If you encounter a hang and a white screen when using the Xbox console, power off the console for at least five seconds, and then restore power. Please report occurrences of this problem to Xbox support.
The first time a file transfer occurs from your Microsoft® Windows® 2000 development machine to the Xbox console, the time setting on the console is updated to match the development machine. In a future version of the Xbox System Software you will be able to change the settings through the Xbox Dashboard.
The video mode on the Xbox console is set to NTSC by default. To change this setting, you can either use the controller shortcuts specified in section 5.2 of this document, or you can change the settings on the Settings screen of the Xbox Dashboard.
The controller configuration has been updated. Please use only the controller supplied with this release of the Xbox XDK. In addition, this release includes only one controller. Future releases will include two. Please contact Xbox support for information on returning previous controllers.
In this beta release, the console CPU is running at approximately 715 MHz, and the GPU is running at approximately 210 MHz. This will be addressed in a future release.
When using Xbox Controllers with the new hardware, a deadband will no longer be enforced on the device. Developers will likely experience a rise in thumbstick resolution, but will need to enforce their own deadband. Specific details concerning the manufacturing tolerances and distribution of values for all buttons and thumbsticks will be provided in an upcoming XDK release.
Do not discard previous target systems or the Xbox console shipped with this release. Do not discard packing materials shipped with previous target systems or the Xbox console. Previous target systems and consoles will need to be returned to Microsoft when requested, as new versions become available.
The xbexplorer tool is a preview of a new tool that will be included in a future release of the XDK. It provides a GUI front end for the remote tools (such as xbcopy and xbdir) and supports drag-and-drop file transfers, viewing any mapped console drive, renaming files, rebooting your console, and viewing the properties of a remote console file.
You can now specify the default save image using imagebld. The switch is: /DEFAULTSAVEIMAGE. The image will be stored in the XBE file and will be automatically copied to the root of the U:\ drive and every memory unit (MU) mounted by the title. This image will be used by the Xbox Dashboard when displaying a save game that doesn't contain a unique save image in its directory.
The unique save game image stored within a save game directory should no longer be named Image.xbx. Instead, it should now be called SaveImage.xbx.


Frequently Asked Questions
- Is Eventor really free?
- Yes. Eventor is free in the sense that you don't have to pay me any money at all.
- So, what license comes with Eventor?
- Short answer: none. It comes as-is. Long answer: It comes as-is. If it breaks you get to keep both pieces. Ok? The license is based on GNU GPL v2.
- Is the source code for Eventor available?
- Depends. I have not uploaded the source code for public inspection. It is available on request.
- What about a desktop version of Eventor?
- It is on my Todo-list. But it has been down-prioritized at the moment ... I have too many other projects on my hand. And I need to sort out whether I will create it in C++, Java or C#
- What is this Eventor Conduit I've been hearing so much about?
- The Eventor Conduit is a dll for Microsoft Windows which gets called as a part of the HotSync synchronization. It downloads data from the Eventor application to your desktop PC.
- Come on! The backup manager in HotSync takes care of that!
- Yes - that is absolutely true.
- Do I need it then?
- No - not at the moment. But when the Eventor desktop application is a reality you will be needing it. At the moment, I am happy if people downloads and uses the conduit. That way, all bugs will hopefully be squashed when the Eventor desktop application sees the light.
- Help! I have a lot of events to enter - is there a quick way to do it?
- Yes. Use Palm OS Emulator to enter your data, then export the database and install it on your handheld. Or, if you have installed the conduit, you can do a bit of cheating ...
- This one from Glen Brooksby - thanks Glen!
- When selecting the year of an event, if you place your stylus on the forward or backward button for the year and hold the stylus down, the years scroll by very quickly. I found this was perfectly adequate for entering 'old' events. This works on my Handpring Visor Deluxe, Palm OS v3.0.
Home


Matt Donne
Matt is a 4th year graduate student in the Dr. Jason Rock's lab focusing on adult lung regeneration. The Cell Hackers club had its humble beginnings inside Matt's brain. He has been thrilled with its manifestation into reality. His interest in coding came about through both necessity and curiosity.
Melissa Quino McCreery
Melissa is a 3rd year BMS graduate student in Allan Balmain's lab, focusing on cancer genetics and the clonality and evolution of tumors. She was previously founder of and a developer at The Muse, where she taught herself to code, and is now excited to be applying those skills to computational biology.
Nicolas Strauli
Nicolas is a 4th year graduate student in Ryan Hernandez's lab. He is investigating the evolutionary interaction between a host's population of antibodies and infectious pathogens during an infection. To do this he is using ultra-deep sequencing of these two populations, and using Python and R to sift through the data.
Bryne Ulmschneider
Bryne is a 4th year graduate student in Todd Nystul's lab studying stem cell biology with a focus on quantitative microscopy to measure pH inside of cells. She taught herself to code in R because she could make prettier graphs in R than in excel. She is excited about learning more R and Python.
Ian Driver
Ian is a postdoctoral scholar in Jason Rock's lab, focusing on profiling the adult lung stem cell niche during injury and regeneration using single cell RNA-sequencing. Ian started programming in Matlab while studying Chemical Engineering at MIT and became a self-taught Python devotee during his graduate work at Columbia University, while researching intestinal stem cells in Drosophila.


Use the .badge
class, followed by.rounded-pill
with
.bg-{color}
class within element to create contextual pill badge.
Use class .badge-glow
to add glow effect to contextual badge.
Use class .rounded-pill
class with .badge.badge-light-{color}
to add
light effect to your badge.
Use .badge-up
to set pill badge to higher than other text. So that it can work with
notifications also.
Use class .badge.rounded-pill
with <a>
tag to make your badge a link.
Use .d-block
with .rounded-pill
to display your badge as block level element.


16.3.49 one-way ANOVA test
To see how much difference time of day made on the speed at which he could download files, a college sophomore placed a file on a remote server, then proceeded to download it at three different time periods of the day. He downloaded the file 18 times in all, 6 times at each time of day, and recorded the time in seconds that the download took. At the 5% significance level, do the data provide sufficient evidence to conclude that a difference exists in mean download speed?
Notation in one-way ANOVA:
k = number of populations
n = total number of observations
\(\bar x\) = mean of all n observations
\(n_j\) = size of sample from Population j
\(\bar{x_j}\) = mean of sample from Population j
\(s_j^2\) = variance of sample from Population j
\(T_j\) = sum of sample data from Population j
Defining formulas from sums of squares in one-way ANOVA:
SST = \(\sum (x_i - \bar x)^2\)
SSTR = \(\sum n_j(\bar{x_j} - \bar{x})^2\)
SSE = \(\sum (n_j-1)s_j^2\)
One-way ANOVA identity: SST = SSTR + SSE
Computing formulas from sums of squares in one-way ANOVA:
SST = \(\sum x_i^2 - (\sum x_i)^2/n\)
SSTR = \(\sum (T_j^2/n_j) - (\sum x_i)^2/n\)
SSE = SST - SSTR
Mean squares in one-way ANOVA:
MSTR = \(\frac{SSTR}{k-1}\)
MSE = \(\frac{SSE}{n-k}\)
SSE = SST - SSTR
Test statistic for one-way ANOVAA (independent samples, normal populations, and equal population standard deviations):
- F = \(\frac{MSTR}{MSE}\)
with df = (k - 1, n - k)
Confidence interval for \(\mu_i - \mu_j\) in the Tukey multiple-comparison method (independent samples, normal populations, and equal population sstandard deviations):
- \((\bar{x_i} - \bar{x_j}) \pm \frac{q_{\alpha}}{\sqrt{2}}.s\sqrt{\frac{1}{n_i} + \frac{1}{n_j}}\)
where s = \(\sqrt{MSE}\) and \(q_{\alpha}\) is obtained for a q-curve with parameters k and n - k
Test statistic for a Kruskal-Wallis test (independent samples, same-shape populations, all sample sizes 5 or greater):
\(K=\frac{SSTR}{SST/(n-1)}\) or
\(K=\frac{12}{n(n+1)}\sum_{j=1}^{k} \frac{R_j^2}{n_j} - 3(n+1)\)
where SSTR and SST are computed for the ranks of the data, and \(R_j\) denotes the sum of the ranks for the sample data from Population j. K has approximately a chi-square distribution with df = k -1
First, let \(\mu_1, \mu_2,\) and \(\mu_3\) be the population means times for 7 a.m., 5 p.m., and 12 a.m., respectively. What are the correct hypotheses for a one-way ANOVA test?
Since the question asks “At the 5% significance level, do the data provide sufficient evidence to conclude that a difference exists in mean download speed?.” the correct hypothesis is.
\(H_0: \mu_1 = \mu_2 = \mu_3\)
\(H_a:\) Not all the means are equal.Now conduct a one-way ANOVA test on the data. What is the F-statistic?
First we need to get the data from the question. (We can import it from Excel)
<- read.csv("https://raw.githubusercontent.com/sileaderwt/MTH1320-UMSL/main/Image%2BData/16.3.49/16.3.49.csv")
data data
## Early Evening Late
## 1 70 206 217
## 2 140 293 177
## 3 86 251 176
## 4 209 308 222
## 5 109 237 212
## 6 76 209 164
The type of data is tibble in R. To avoid confusion when working with other question, we should create a data frame.
= data.frame(data)
dframe dframe
## Early Evening Late
## 1 70 206 217
## 2 140 293 177
## 3 86 251 176
## 4 209 308 222
## 5 109 237 212
## 6 76 209 164
First approach: using anova() in R which Professor Covert introduces in the video lectures (recommended)
<- c()
X <- c()
len for(item in dframe){
<- c(X, item[!is.na(item)])
X <- c(len, length(item[!is.na(item)]))
len
} X
## [1] 70 140 86 209 109 76 206 293 251 308 237 209 217 177 176 222 212 164
len
## [1] 6 6 6
We import name of our data.
= rep(names(dframe), times = len)
Y Y
## [1] "Early" "Early" "Early" "Early" "Early" "Early" "Evening"
## [8] "Evening" "Evening" "Evening" "Evening" "Evening" "Late" "Late"
## [15] "Late" "Late" "Late" "Late"
= data.frame(X,Y)
dframe2 dframe2
## X Y
## 1 70 Early
## 2 140 Early
## 3 86 Early
## 4 209 Early
## 5 109 Early
## 6 76 Early
## 7 206 Evening
## 8 293 Evening
## 9 251 Evening
## 10 308 Evening
## 11 237 Evening
## 12 209 Evening
## 13 217 Late
## 14 177 Late
## 15 176 Late
## 16 222 Late
## 17 212 Late
## 18 164 Late
We run anova()
= aov(X~Y, data=dframe2)
fm1 fm1
## Call:
## aov(formula = X ~ Y, data = dframe2)
##
## Terms:
## Y Residuals
## Sum of Squares 55776.44 26028.67
## Deg. of Freedom 2 15
##
## Residual standard error: 41.65627
## Estimated effects may be unbalanced
anova(fm1)
## Analysis of Variance Table
##
## Response: X
## Df Sum Sq Mean Sq F value Pr(>F)
## Y 2 55776 27888.2 16.072 0.0001862 ***
## Residuals 15 26029 1735.2
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
We can run str() to see structure of our data. We can extract any data from the frame.
str(anova(fm1))
## Classes 'anova' and 'data.frame': 2 obs. of 5 variables:
## $ Df : int 2 15
## $ Sum Sq : num 55776 26029
## $ Mean Sq: num 27888 1735
## $ F value: num 16.1 NA
## $ Pr(>F) : num 0.000186 NA
## - attr(*, "heading")= chr [1:2] "Analysis of Variance Table\n" "Response: X"
Round to 2 decimal places
print((anova(fm1)$`F value`), 4)
## [1] 16.07 NA
Now determine the critical value \(F_{\alpha}\)
Since \(\alpha = .05\), df(2,15)
qf(1-.05, 2, 15)
## [1] 3.68232
Round to decimal places
round(qf(1-.05, 2, 15), 2)
## [1] 3.68
Since our test statistic = 16.07 > our critical value \(F_{\alpha}=3.68\) and it is a right-tailed test, we have enough evidence to reject the hypothesis.
Second approach: using the formula from the book
The same approach with question 16.3.43, we could see that two approaches have the same answer
(a) Compute SST, SSTR, and SSE using the following computing formulas, where xi is the ith observation, n is the total number of observations, nj is the sample size for population j, and Tj is the sum of the sample data from population j.
Names of variables
\(\sum{x}: Sx\)
\(\sum x^2: Sxx\) \(\sum (T_j^2/n_j)\): T
n = total number of observations: n
To make it easy to find \(\sum x\), we store all data into a variable x
<- c()
x for(item in dframe){
<- c(x, item[!is.na(item)])
x
} x
## [1] 70 140 86 209 109 76 206 293 251 308 237 209 217 177 176 222 212 164
= length(x)
n n
## [1] 18
Find \(\sum x_i\)
sum(x)
## [1] 3362
Find \(\sum x_i^2\)
sum(x*x)
## [1] 709752
Find SST
To find SST, we use formula SST = \(\sum x_i^2 - (\sum x_i)^2/n\)
= sum(x*x) - (sum(x))^2/n
SST SST
## [1] 81805.11
Find \(\sum (T_j^2/n_j)\)
= 0
T for(item in dframe){
= item[!is.na(item)]
t = T + sum(t)^2/length(t)
T
} T
## [1] 683723.3
Find SSTR, we use formula SSTR = \(\sum (T_j^2/n_j) - (\sum x_i)^2/n\)
= T - sum(x)^2/n
SSTR SSTR
## [1] 55776.44
Find SSE, we use formula SSE = SST - SSTR
= SST - SSTR
SSE SSE
## [1] 26028.67
(b). Compare your results in part (a) for SSTR and SSE with the following results from the defining formulas.
We find SSTR, SSE, SST by using defining formula
Find SST using the formula SST = \(\sum (x_i - \bar x)^2\)
= sum(x*x) - (sum(x))^2/n
SST SST
## [1] 81805.11
Find SSTR using the formula SSTR = \(\sum n_j(\bar{x_j} - \bar{x})^2\)
= 0
SSTR for(item in dframe){
= item[!is.na(item)]
t = SSTR + length(t)*(mean(t) - mean(x))^2
SSTR
} SSTR
## [1] 55776.44
Find SSE using the formula SSE = \(\sum (n_j-1)s_j^2\)
= 0
SSE for(item in dframe){
= item[!is.na(item)]
t = SSE + (length(t)-1)*sd(t)^2
SSE
} SSE
## [1] 26028.67
We have the same answer by using two different formulas.
(c) Construct a one-way ANOVA table.
Find df treatment
= length(dframe)
k -1 k
## [1] 2
Find SS treatment
SSTR
## [1] 55776.44
Find MS treatment
= SSTR/(k-1)
MSTR MSTR
## [1] 27888.22
Find Error df
- k n
## [1] 15
Find Error SS
SSE
## [1] 26028.67
Find Error MS
= SSE / (n - k)
MSE MSE
## [1] 1735.244
Find F-statistic treatment
/ MSE MSTR
## [1] 16.07164
Find df total
- 1 n
## [1] 17
Find SS total
SST
## [1] 81805.11
Now determine the critical value \(F_{\alpha}\)
Since \(\alpha = .05\)
= 0.05
alpha qf(1-alpha, k-1, n-k)
## [1] 3.68232
Round to decimal places
round(qf(1-alpha, k-1, n-k), 2)
## [1] 3.68
Hope that helps!


Picker
You can include any content you want here.
Pick
Pass
Undo
Redo
Found favorites
Games to include :
Danganronpa 1 : Trigger Happy Havoc
Danganronpa 2 : Goodbye Despair


qTracker
A collaboration with Kent Odde and Tarald Vestbøstad.
The tracker has common private tracker functionalities such as ratio, hit and runs,
personal passkeys and bonus points.
The client is made with Qt (C++ and QML) whereas the tracker and server are made in C++.
Made in the spring of 2020.
Torrents Page
Upload Page
Hit and Run Page
Source: Client
Source: Tracker
Source: Server


Content
Function Definition and plotting
Taylor Polynomials
Parametric Curves plotting
Polar Curves
Plotting Vector Fields in Python
Vector field integration
Author:
Ajit Kumar
Essential Sympy tutorial for a multivariable calculus course
Function Definition and plotting
Taylor Polynomials
Parametric Curves plotting
Polar Curves
Plotting Vector Fields in Python
Vector field integration


Dusty Trails Adventure Game
{% block content %}
This game your goal is to go on an adventure, and make it as far as you can. Enjoy!
Click to play!
{% endblock %}


FirstBuild GreenBean + MeshBlue Demo
open the developer console and type sendCookCommandToOven() to send a default cook cycle (see code)


Imports an XML configuration from file
Export an XML configuration to file
Export an XML configuration per flow to file. Select a integration to see the flows.
No flows yet. Start creating new flows by going to the flows page.


--- title: JCM Music subtitle: Thank you for contacting us - we will start producing your music ASAP layout: page show_sidebar: true permalink: /thanks/ ---
We have received your message, we will back to you as soon as possible.
You are one step closer to take your project audio to the next level!


--- title: "Week 4 Lab" author: "Drew Tyre" date: "2017-08-01" output: html_document weight: 803041 ---
We’re going to use the same dataset that you generated last week for this week’s exercise. Last week we looked at choosing a best model. This week we’re going to model average the coefficients and predictions from the models, and make “partial dependence plots”. As before, we’ll first do each step by hand, then with AICcmodavg. Below I’ve assumed you still have all the objects created in week 3 lab. You can ensure this by simply using the same RStudio project you created for the week 3 lab. Then you need to include code from Lab 3 in your Rmd file for lab 4. There are 3 options in increasing order of sophistication:
Open yourname_lab3.Rmd (or whatever you called it). Save it as yourname_lab4.Rmd. Continue working at the end of the file, making one big document. This is entirely fine.
Copy the code chunks out of your lab3 Rmd file into a code chunk at the top of a new lab 4 Rmd file. You can leave out code that makes plots and tables. All you need is code that assigns operations to objects using <-
. This one is tedious and subject to making alot of mistakes.
Include the following line in your first code chunk, before you run anything else.
source(knitr::purl("yourname_lab3.rmd", output = tempfile()))
The function knitr::purl() pulls all the code chunks out of the Rmd file and puts them in an R script. source() then runs that script.
To be super clean, add include = FALSE, echo=FALSE to the code chunk options, which go at the start of the code chunk like this
```{r}
change to
```{r , include = FALSE, echo=FALSE}
that will not show the code or results in the output document.
As before, answer the numbered questions in the regular text section of your R markdown file.
First let’s look at the intercept. We need to get a vector of the estimated intercepts from each model:
library(broom) # for tidy
library(tidyverse) # for map_chr(), map_df(), filter(), mutate()
# old way intercepts = sapply(fits,function(mm)coef(mm)[1])
# new way apply tidy() to each element of the list
intercepts <- map_df(fits, tidy) %>% filter(term == "(Intercept)") %>%
mutate(models = modnames)
The estimated intercepts are stored in the list object fits
, and we use the function tidy()
to pull them out into a dataframe. tidy()
only works on a single model object, so we use map_df()
to apply tidy to each object in the list, and pull all the results into a data.frame. Then we use filter()
to keep just the rows with estimated intercepts. Explore this code a bit by using the individual functions, and looking carefully at the returned results, including the new dataframe intercepts
. Do not include these interactive explorations in your submitted R markdown file.
I left the “old way” of extracting these estimates in there for you to compare. Notice that the result is a single vector of the estimates, not a data.frame. Although the tidyverse approach looks more complex, with a couple of lines of code we’ve made several subsequent steps of the old way completely obsolete!
Now we need to calculate the weighted average of the intercepts, using the AIC weights. There are at least two ways to do this – but in the spirit of KISS we’ll use the brute force option:
mavg.intercept <- sum(weights * intercepts$estimate)
Here we’ve multiplied each element of the vector weights with its corresponding element in intercepts and then used the function sum() to add up the results.
Next we need to calculate the variance of our model averaged estimate. Variances can be added together, so first square our standard errors to get the variance of each estimate.
intercepts <- intercepts %>% mutate(var_est = std.error^2)
Now we calculate a weighted average of the variances, but we also have to include a component of how different the estimates are between models (see page 111 in MBILS). Vectorized calculations are our friend here:
sum(weights * (intercepts$var_est + (intercepts$estimate - mavg.intercept)^2))
The intercept was easy because it occurs in every model. What if we want to model average a parameter that does not occur in every model, such as Amount? There are two problems to solve – how to extract the coefficients from the models that have Amount, and what to do with the models Amount does not occur in. The first is actually pretty easy – we just change the filter()
condition above. For convienence later on, I’m going to add the modnames to the list fits
. Then map_df()
will use the names of the list to create a variable in the result indicating which list item the row comes from.
names(fits) <- modnames
amount <- map_df(fits, tidy, .id = "modname") %>% filter(term ==
"Amount")
If you look at the data.frame Amount you can see that it has fewer rows than the number of models. That is because the covariate Amount only appears in some of the models. We have two choices about how to deal with this fact. The first option just uses the weights from the models with Amount in them, re-normalizing the weights to add to 1. The other option is to assume the models without Amount have an estimated value of zero. We’ll try both.
We have to do two things: match the weights up to the smaller dataframe, and then change them to sum to one. The first task is solved handily by using a join operation. I will first add the modnames column to the dataframe with all the AIC statistics, then join the two tables together.
# have to add modnames to aic.table too!
aic.table$modname <- modnames
# we want all the rows in Amount, and all columns in both
# that is a left join in database speak. see ?join in dplyr
# for all the options
amount <- left_join(amount, aic.table, by = "modname")
names(amount)
As you can see, we now have added the aic.table
columns to the Amount
data.frame. Manually compare a couple of rows from Amount
with the values in aic.table
to convince yourself this magic actually works. Now we renormalize the weights to 1
sum(amount$weights) # less than 1 but not by much
amount$weights <- amount$weights/sum(amount$weights)
and then do the model averaging calculations:
# use with() to make code shorter -- looks for objects in
# Amount first.
mavg.amount <- with(amount, sum(weights * estimate))
amount$var_est <- amount$std.error^2
mavg.var.amount <- with(amount, sum(weights * (var_est + (estimate -
mavg.amount)^2)))
The other way to do model averaging, which I prefer, is to assume the estimate is zero for those models in which it doesn’t appear. This “shrinks” the estimate towards zero, and by a greater amount if models without Amount have substantial weight on them. The trick is to use a different join operation, one that “fills in” with missing values rows that are missing in the lefthand table.
# remake the Amount table
amount <- map_df(fits, tidy, .id = "modname") %>% filter(term ==
"Amount")
amount_allrows <- full_join(amount, aic.table, by = "modname")
Notice that the last 8 rows have values from aic.table
, but NA
for all the columns in Amount. We want to set the estimates and standard errors for those rows to zero.
# create a logical vector -- avoid relying on order
pick <- is.na(amount_allrows$estimate)
amount_allrows[pick, c("estimate", "std.error")] <- 0
And now we can use exactly the same code to get the model averaged estimates.
mavg.amount2 <- with(amount_allrows, sum(weights * estimate))
amount_allrows$var_est <- amount_allrows$std.error^2
mavg.var.amount2 <- with(amount_allrows, sum(weights * (var_est +
(estimate - mavg.amount2)^2)))
Compare those model averaged estimates with the ones from the conditional average. Again, does changing the method change your conclusion about the effect of Amount on the response?
Recall from Week 3 that we actually know the true coefficients; Amount should be 2. Compare the top models and model averaged coefficients with the true value.
Ideally we want to get a table with the model averaged coefficients for every parameter in the model. We could copy and paste the calculations above for each parameter, then bind them all together into a data.frame. Or we could do all the calculations at once. We start by simply not filtering when we create our table of parameter estimates.
# get all the things
estimates <- map_df(fits, tidy, .id = "modname")
Start with the version that conditions the weights on the models containing each parameter. First we need to get the weights associated with each model attached to the right rows. Back to left_join()
estimates1 <- left_join(estimates, aic.table[, c("weights", "modname")],
by = "modname")
head(estimates1)
We have multiple rows for each model, one for every parameter in the model. I restricted the columns of aic.table
just for simplicity. Now we are going to repeat all the calculations above for each value of term
, and summarize the result into a single data.frame.
estimates1 %>% group_by(term) %>% mutate(wnorm = weights/sum(weights),
var_est = std.error^2) %>%
summarize(avg_est = sum(estimate * wnorm), avg_var = sum(wnorm *
(var_est + (estimate - avg_est)^2)))
Now that’s pretty nice! We did everything in about 7 lines of code.
Now we want to create a dataframe with the model averaged estimate, standard error, and a t-test comparing the estimate against the known true value and turn it into a nice output table using package pander.
# repeat code from above but save to object
coef_table1 <- estimates1 %>% group_by(term) %>% mutate(wnorm = weights/sum(weights),
var_est = std.error^2) %>%
summarize(avg_est = sum(estimate * wnorm), avg_var = sum(wnorm *
(var_est + (estimate - avg_est)^2)))
coef_table1$avg_SE <- sqrt(coef_table1$avg_var)
# to get the t statistics we need a bit more information,
# what are the true parameter values
coef_table1$true_parms <- c(0, 2, -2, 2, 0)
coef_table1$t_value <- (coef_table1$avg_est - coef_table1$true_parms)/coef_table1$avg_SE
coef_table1$p_value <- 2 * (1 - pt(abs(coef_table1$t_value),
df = 350 - 5))
# print while removing variance column pander(coef_table1[, -
# 3]) # broken!
knitr::kable(coef_table1[, -3], digits = 2)
tidy(fits[[12]])
). Compare the conclusions you make about each effect in the model by using the top model or the model averaged coefficients.Now let’s do it with the other option, assuming the estimates are zero when a parameter isn’t present in the model. We need to flesh out our dataframe estimates
with the rows that are missing. A full join will do this, but first we need a table with all the coefficients and all the model names in it.
parms <- crossing(term = c("(Intercept)", "Amount", "Edge", "Hetero",
"MnPatch"), modname = modnames)
# if no by = argument, uses all columns with identical names
estimates2 <- full_join(estimates, parms)
Now we have a table with 5 parameters x 16 models = 80 rows. We can use nearly the same code as before, just skipping the normalization of the weights.
# don't forget to add the model weights!
estimates2 <- left_join(estimates2, aic.table[, c("weights",
"modname")], by = "modname")
estimates2 %>% group_by(term) %>% mutate(estimate = if_else(is.na(estimate),
0, estimate), std.error = if_else(is.na(std.error), 0, std.error),
var_est = std.error^2) %>% summarize(avg_est = sum(estimate *
weights), avg_var = sum(weights * (var_est + (estimate -
avg_est)^2)))
All those calculations can be done for you by package AICcmodavg.
library(AICcmodavg)
# conditional on inclusion in a model
modavg(fits, "Amount", modnames = modnames)
# with all the models
modavgShrink(fits, "Amount", modnames = modnames)
So that was less code, but pulling it all out into a table for all parameters would be more painful than the dplyr
based manual code above. You have to do each parameter individually.
Finally, let’s make a plot. The design of the plot below was suggested by Shivani Jadeja a couple of years ago.
gg1 <- ggplot(smithsim, aes(x = Edge, y = Y, color = Amount)) +
geom_point()
# make prediction data
nd <- expand.grid(Edge = -3:3, Amount = quantile(smithsim$Amount,
p = c(0, 0.5, 1)), Hetero = median(smithsim$Hetero), MnPatch = median(smithsim$MnPatch))
nd <- augment(fits[[12]], newdata = nd)
gg1 + geom_line(aes(y = .fitted, group = Amount), data = nd)
The color shows the value of amount for each point, a third dimension. The lines are the prediction from the top model, and automatically are colored to match the points so you can see the value of Amount that gives you that prediction. The lines are parallel because there is no interaction term.


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Rod Stewart is unrecognisable as he cuts a low-key figure during shopping trip
The rocker ensured he was not spotted by fans as he hit high street store Zara in Italy
by Sara-Aisha Kent, https://www.mirror.co.uk/authors/sara-aisha-kent/Rod Stewart has a face recognised around the globe and millions in the bank.
However, the rocker appears to enjoy incognito outings as he cut a low-key figure that made him totally unrecognisable in the Italian capital of Rome on Tuesday.
The Maggie May hitmaker, 74, ensured he was not mobbed by fans by concealing his famous features.
He sported a tweed flat-cap atop of his trademark mullet and wrapped a silk scarf - decorated with a paisley leaf design - around his neck.
Rod seems to like to stay down - to - earth as he was spotted shopping in high street retailer Zara during his solo shopping trip where he examined different jeans and chinos for sale and tried on a coat.
Inside the store he was helped by an assistant and at one point he took off his outdoor accessories which allowed his face to been seen.
Continuing his trendy display, under his coat her wore a white shirt - which was partially unbuttoned - and decorated his neck with a silver chain and large pendant and gem-encrusted cross.
It comes after the Grammy Award winner shared the secret to his and his wife’s 12-year marriage is never seeing each other.
The pop legend, who married model and Loose Women panellist Penny Lancaster in 2007, said: “Penny and I like our silence. We live in a very big house and we don’t bump into each other for hours on end.”
Rod is father to eight children, six of which are from previous relationships.
He has two children with 48-year-old Penny - Alastair, 13, and Aiden, seven.
He was previously married to Rachel Hunter, and Alana Hamilton.
The singer recently revealed last he had won a battle with prostate cancer.
He told how he was diagnosed with the disease in February 2016 during a routine checkup and secretly fought it for three years.
Sir Rod opened up about his prostate cancer during a fundraising evening with former Faces bandmates Kenney Jones and Ronnie Wood.
He said: “No one knows this, but I thought this was about time I told everybody. I’m in the clear, now, simply because I caught it early. I have so many tests.”
Addressing the men directly, he pleaded: “Guys, you’ve got to really go to the doctor.”
And he had the crowd in stitches when he said of the physical examination for the disease: “Finger up the bum, no harm done.”
He said: “If you’re positive, and you work through it and you keep a smile on your face...I’ve worked for two years and I’ve just been happy, and the good Lord looked after me.”


IgeTiledComponent CLASS
Declared in IgeTiledComponent.js
Loads slightly modified Tiled-format json map data into the Isogenic Engine.
Methods
init
init({} entity, {} options)
loadJson
Loads a .js Tiled json-format file and converts to IGE format, then calls the callback with the newly created scene and the various layers as IgeTextureMap instances.
loadJson({} url, {} callback)


There is a vast amount of alternative data available that we can use for developing signals in our Alphas. This allows us to create many unique hypotheses about the relationships between our data sources and the market, such as creating NLP models from twitter data to determine market sentiment or using Federal Reserve data to rebalance a portfolio.
QuantConnect provides a large library of alternative data sources. This includes free data sources like SEC filings, Federal Reserve data, and also paid sources like new data from Tiingo. You can find a complete list of alternative data sources in Alternative Data documentation. Most of the alternative data sources are also available in the research environment. This allows us to directly analyze a wide variety of data.


Mesh(ID)
Mesh Data
网格数据以对象模式访问, 它用于紧凑存储, Python中更为灵活的网格编辑见bmesh
The mesh data is accessed in object mode and intended for compact storage, for more flexible mesh editing from python see bmesh.
Blender存储4个主要数组用来定义网格几何.
- Mesh.vertices (顶点集, 3 points in space)
- Mesh.edges (边集, 引用2个顶点, reference 2 vertices)
- Mesh.loops (面循环, 多边形角点. Loops of the mesh (polygon corners))
- Mesh.polygons (loops一部分的引用, reference a range of loops)
每个多边形在loop数组中引用一个切片，这样，多边形不直接存储诸如UV之类的顶点或角数据，只是对多边形使用的loop的引用
Each polygon reference a slice in the loop array, this way, polygons do not store vertices or corner data such as UV’s directly, only a reference to loops that the polygon uses.
Mesh.loops, Mesh.uv_layers Mesh.vertex_colors are all aligned so the same polygon loop indices can be used to find the UV’s and vertex colors as with as the vertices.
This example script prints the vertices and UV’s for each polygon, assumes the active object is a mesh with UVs.
import bpy
me = bpy.context.object.data
uv_layer = me.uv_layers.active.data
for poly in me.polygons:
print("Polygon index: %d, length: %d" % (poly.index, poly.loop_total))
# range is used here to show how the polygons reference loops,
# for convenience 'poly.loop_indices' can be used instead.
for loop_index in range(poly.loop_start, poly.loop_start + poly.loop_total):
print(" Vertex: %d" % me.loops[loop_index].vertex_index)
print(" UV: %r" % uv_layer[loop_index].uv)
Mesh(ID)¶
Mesh Data¶
The mesh data is accessed in object mode and intended for compact storage,
for more flexible mesh editing from python see bmesh
.
Blender stores 4 main arrays to define mesh geometry.
Mesh.vertices
(3 points in space)Mesh.edges
(reference 2 vertices)Mesh.loops
(reference a single vertex and edge)Mesh.polygons
: (reference a range of loops)
Each polygon reference a slice in the loop array, this way, polygons do not store vertices or corner data such as UV’s directly, only a reference to loops that the polygon uses.
Mesh.loops
, Mesh.uv_layers
Mesh.vertex_colors
are all aligned so the same polygon loop
indices can be used to find the UV’s and vertex colors as with as the vertices.
To compare mesh API options see: NGons and Tessellation Faces
This example script prints the vertices and UV’s for each polygon, assumes the active object is a mesh with UVs.
import bpy
me = bpy.context.object.data
uv_layer = me.uv_layers.active.data
for poly in me.polygons:
print("Polygon index: %d, length: %d" % (poly.index, poly.loop_total))
# range is used here to show how the polygons reference loops,
# for convenience 'poly.loop_indices' can be used instead.
for loop_index in range(poly.loop_start, poly.loop_start + poly.loop_total):
print(" Vertex: %d" % me.loops[loop_index].vertex_index)
print(" UV: %r" % uv_layer[loop_index].uv)
base classes — bpy_struct
, ID
-
class
bpy.types.
Mesh
(ID)¶ Mesh data-block defining geometric surfaces
-
auto_smooth_angle
¶ Maximum angle between face normals that will be considered as smooth (unused if custom split normals data are available)
Type: float in [0, 3.14159], default 3.14159
-
auto_texspace
¶ Adjust active object’s texture space automatically when transforming object
Type: boolean, default False
-
cycles
¶ Cycles mesh settings
Type: CyclesMeshSettings
, (readonly)
-
edges
¶ Edges of the mesh
Type: MeshEdges
bpy_prop_collection
ofMeshEdge
, (readonly)
-
has_custom_normals
¶ True if there are custom split normals data in this mesh
Type: boolean, default False, (readonly)
-
is_editmode
¶ True when used in editmode
Type: boolean, default False, (readonly)
-
loops
¶ Loops of the mesh (polygon corners)
Type: MeshLoops
bpy_prop_collection
ofMeshLoop
, (readonly)
-
materials
¶ Type: IDMaterials
bpy_prop_collection
ofMaterial
, (readonly)
-
polygon_layers_float
¶ Type: PolygonFloatProperties
bpy_prop_collection
ofMeshPolygonFloatPropertyLayer
, (readonly)
-
polygon_layers_int
¶ Type: PolygonIntProperties
bpy_prop_collection
ofMeshPolygonIntPropertyLayer
, (readonly)
-
polygon_layers_string
¶ Type: PolygonStringProperties
bpy_prop_collection
ofMeshPolygonStringPropertyLayer
, (readonly)
-
polygons
¶ Polygons of the mesh
Type: MeshPolygons
bpy_prop_collection
ofMeshPolygon
, (readonly)
-
show_double_sided
¶ Display the mesh with double or single sided lighting (OpenGL only)
Type: boolean, default False
-
show_edge_bevel_weight
¶ Display weights created for the Bevel modifier
Type: boolean, default False
-
show_edge_crease
¶ Display creases created for subsurf weighting
Type: boolean, default False
-
show_edge_seams
¶ Display UV unwrapping seams
Type: boolean, default False
-
show_edge_sharp
¶ Display sharp edges, used with the EdgeSplit modifier
Type: boolean, default False
-
show_edges
¶ Display selected edges using highlights in the 3D view and UV editor
Type: boolean, default False
-
show_extra_edge_angle
¶ Display selected edge angle, using global values when set in the transform panel
Type: boolean, default False
-
show_extra_edge_length
¶ Display selected edge lengths, using global values when set in the transform panel
Type: boolean, default False
-
show_extra_face_angle
¶ Display the angles in the selected edges, using global values when set in the transform panel
Type: boolean, default False
-
show_extra_face_area
¶ Display the area of selected faces, using global values when set in the transform panel
Type: boolean, default False
-
show_extra_indices
¶ Display the index numbers of selected vertices, edges, and faces
Type: boolean, default False
-
show_faces
¶ Display all faces as shades in the 3D view and UV editor
Type: boolean, default False
-
show_freestyle_edge_marks
¶ Display Freestyle edge marks, used with the Freestyle renderer
Type: boolean, default False
-
show_freestyle_face_marks
¶ Display Freestyle face marks, used with the Freestyle renderer
Type: boolean, default False
-
show_normal_face
¶ Display face normals as lines
Type: boolean, default False
-
show_normal_loop
¶ Display vertex-per-face normals as lines
Type: boolean, default False
-
show_normal_vertex
¶ Display vertex normals as lines
Type: boolean, default False
-
show_statvis
¶ Display statistical information about the mesh
Type: boolean, default False
-
show_weight
¶ Draw weights in editmode
Type: boolean, default False
-
skin_vertices
¶ All skin vertices
Type: bpy_prop_collection
ofMeshSkinVertexLayer
, (readonly)
-
tessface_uv_textures
¶ All UV maps for tessellated faces (read-only, for use by renderers)
Type: TessfaceUVTextures
bpy_prop_collection
ofMeshTextureFaceLayer
, (readonly)
-
tessface_vertex_colors
¶ All tessellated face colors (read-only, for use by renderers)
Type: VertexColors
bpy_prop_collection
ofMeshColorLayer
, (readonly)
-
tessfaces
¶ Tessellated faces of the mesh (derived from polygons)
Type: MeshTessFaces
bpy_prop_collection
ofMeshTessFace
, (readonly)
-
texspace_location
¶ Texture space location
Type: float array of 3 items in [-inf, inf], default (0.0, 0.0, 0.0)
-
texspace_size
¶ Texture space size
Type: float array of 3 items in [-inf, inf], default (0.0, 0.0, 0.0)
-
total_edge_sel
¶ Selected edge count in editmode
Type: int in [0, inf], default 0, (readonly)
-
total_face_sel
¶ Selected face count in editmode
Type: int in [0, inf], default 0, (readonly)
-
total_vert_sel
¶ Selected vertex count in editmode
Type: int in [0, inf], default 0, (readonly)
-
use_auto_smooth
¶ Auto smooth (based on smooth/sharp faces/edges and angle between faces), or use custom split normals data if available
Type: boolean, default False
-
use_auto_texspace
¶ Adjust active object’s texture space automatically when transforming object
Type: boolean, default False
-
use_customdata_edge_bevel
¶ Type: boolean, default False
-
use_customdata_edge_crease
¶ Type: boolean, default False
-
use_customdata_vertex_bevel
¶ Type: boolean, default False
-
use_mirror_topology
¶ Use topology based mirroring (for when both sides of mesh have matching, unique topology)
Type: boolean, default False
-
use_mirror_x
¶ X Axis mirror editing
Type: boolean, default False
-
use_paint_mask
¶ Face selection masking for painting
Type: boolean, default False
-
use_paint_mask_vertex
¶ Vertex selection masking for painting (weight paint only)
Type: boolean, default False
-
uv_layer_clone
¶ UV loop layer to be used as cloning source
Type: MeshUVLoopLayer
-
uv_layer_clone_index
¶ Clone UV loop layer index
Type: int in [0, inf], default 0
-
uv_layer_stencil
¶ UV loop layer to mask the painted area
Type: MeshUVLoopLayer
-
uv_layer_stencil_index
¶ Mask UV loop layer index
Type: int in [0, inf], default 0
-
uv_layers
¶ All UV loop layers
Type: UVLoopLayers
bpy_prop_collection
ofMeshUVLoopLayer
, (readonly)
-
uv_texture_clone
¶ UV map to be used as cloning source
Type: MeshTexturePolyLayer
-
uv_texture_clone_index
¶ Clone UV map index
Type: int in [0, inf], default 0
-
uv_texture_stencil
¶ UV map to mask the painted area
Type: MeshTexturePolyLayer
-
uv_texture_stencil_index
¶ Mask UV map index
Type: int in [0, inf], default 0
-
uv_textures
¶ All UV maps
Type: UVTextures
bpy_prop_collection
ofMeshTexturePolyLayer
, (readonly)
-
vertex_colors
¶ All vertex colors
Type: LoopColors
bpy_prop_collection
ofMeshLoopColorLayer
, (readonly)
-
vertex_layers_float
¶ Type: VertexFloatProperties
bpy_prop_collection
ofMeshVertexFloatPropertyLayer
, (readonly)
-
vertex_layers_int
¶ Type: VertexIntProperties
bpy_prop_collection
ofMeshVertexIntPropertyLayer
, (readonly)
-
vertex_layers_string
¶ Type: VertexStringProperties
bpy_prop_collection
ofMeshVertexStringPropertyLayer
, (readonly)
-
vertex_paint_masks
¶ Vertex paint mask
Type: bpy_prop_collection
ofMeshPaintMaskLayer
, (readonly)
-
vertices
¶ Vertices of the mesh
Type: MeshVertices
bpy_prop_collection
ofMeshVertex
, (readonly)
-
edge_keys
¶ (readonly)
-
transform
(matrix, shape_keys=False)¶ Transform mesh vertices by a matrix (Warning: inverts normals if matrix is negative)
Parameters: - matrix (float array of 16 items in [-inf, inf]) – Matrix
- shape_keys (boolean, (optional)) – Transform Shape Keys
-
flip_normals
()¶ Invert winding of all polygons (clears tessellation, does not handle custom normals)
-
calc_normals
()¶ Calculate vertex normals
-
create_normals_split
()¶ Empty split vertex normals
-
calc_normals_split
()¶ Calculate split vertex normals, which preserve sharp edges
-
free_normals_split
()¶ Free split vertex normals
-
calc_tangents
(uvmap="")¶ Compute tangents and bitangent signs, to be used together with the split normals to get a complete tangent space for normal mapping (split normals are also computed if not yet present)
Parameters: uvmap (string, (optional, never None)) – Name of the UV map to use for tangent space computation
-
free_tangents
()¶ Free tangents
-
calc_tessface
(free_mpoly=False)¶ Calculate face tessellation (supports editmode too)
Parameters: free_mpoly (boolean, (optional)) – Free MPoly, Free data used by polygons and loops. WARNING: This destructive operation removes regular faces, only used on temporary mesh data-blocks to reduce memory footprint of render engines and export scripts
-
calc_smooth_groups
(use_bitflags=False)¶ Calculate smooth groups from sharp edges
Parameters: use_bitflags (boolean, (optional)) – Produce bitflags groups instead of simple numeric values
Return (poly_groups, groups): poly_groups, Smooth Groups, int array of 1 items in [-inf, inf]
groups, Total number of groups, int in [0, inf]
-
normals_split_custom_set
(normals)¶ Define custom split normals of this mesh (use zero-vectors to keep auto ones)
Parameters: normals (float array of 3 items in [-1, 1]) – Normals
-
normals_split_custom_set_from_vertices
(normals)¶ Define custom split normals of this mesh, from vertices’ normals (use zero-vectors to keep auto ones)
Parameters: normals (float array of 3 items in [-1, 1]) – Normals
-
update
(calc_edges=False, calc_tessface=False)¶ update
Parameters: - calc_edges (boolean, (optional)) – Calculate Edges, Force recalculation of edges
- calc_tessface (boolean, (optional)) – Calculate Tessellation, Force recalculation of tessellation faces
-
unit_test_compare
(mesh=None)¶ unit_test_compare
Parameters: mesh ( Mesh
, (optional)) – Mesh to compare toReturns: Return value, String description of result of comparison Return type: string, (never None)
-
validate
(verbose=False, clean_customdata=True)¶ Validate geometry, return True when the mesh has had invalid geometry corrected/removed
Parameters: - verbose (boolean, (optional)) – Verbose, Output information about the errors found
- clean_customdata (boolean, (optional)) – Clean Custom Data, Remove temp/cached custom-data layers, like e.g. normals...
Returns: Result
Return type: boolean
-
validate_material_indices
()¶ Validate material indices of polygons, return True when the mesh has had invalid indices corrected (to default 0)
Returns: Result Return type: boolean
-
from_pydata
(vertices, edges, faces)¶ Make a mesh from a list of vertices/edges/faces Until we have a nicer way to make geometry, use this.
Parameters: - vertices (iterable object) – float triplets each representing (X, Y, Z) eg: [(0.0, 1.0, 0.5), ...].
- edges (iterable object) – int pairs, each pair contains two indices to the vertices argument. eg: [(1, 2), ...]
- faces (iterable object) – iterator of faces, each faces contains three or more indices to the vertices argument. eg: [(5, 6, 8, 9), (1, 2, 3), ...]
Warning
Invalid mesh data (out of range indices, edges with matching indices, 2 sided faces... etc) are not prevented. If the data used for mesh creation isn’t known to be valid, run
Mesh.validate
after this function.
-
Inherited Properties
Inherited Functions
References


1. What is Freshchery?
Freshchery delivers groceries from the stores you love to your doorstep in as little as one hour! We empower you to shop at your trusted stores using our own trained and experienced Personal Shoppers, and then ensure a safe delivery to you.
2. What stores are supported?
We support a selected number of stores in your area including Ranch Market, Farmers Market, Lotte Mart, Transmart Carrefour, Super Indo, Grand Lucky, Red&White and LOKA Lifestyle Supermarket. We are constantly adding new stores from your area, empowering you to shop from those stores. The stores that serve you are based on your location, and the availability of stores in your proximity.
3. Do you serve my area?
Currently we serve the Greater Jakarta area, including Tangeran, BSD, Bekasi and Depok as well as Surabaya and Bandung central areas. Check if we deliver to your area by downloading the App or using our Website. You can type your address and see the list of stores available. We keep adding stores on a regular basis! If your favorite store is not listed you can suggest it to us via the “Request New Stores” button at the bottom of the supermarkets list.
4. How fast do you deliver?
We deliver to you in the next hour, or at any other one-hour time-slot today and in the next 6 days.
5. How much does delivery cost?
It costs IDR20,000 for the delivery on all delivery slots. And FREE DELIVERY for order placed above IDR500,000 in May 2017 only
6. What are the delivery hours?
Our delivery hours are based on the opening hours of the stores we work with. Usually between 10am and 10pm. You can place your orders at any time of the day.
7. Can I collect any kinds of club points from the supermarkets?
Currently we do not support the collection of membership points or other savings from stores. Be sure to keep an eye on email and social media updates for updates on how we’re expanding to improve this functionality.
8. What happens if any of my items are out of stock?
We receive price and stock updates on a daily base from our retail partners. After placing your order, you will be asked what our Personal Shopper should do in case one of more of your items are out of stock. You can select for the whole order or for each unique product the following actions: choose “let shopper pick” if you want our shoppers to pick the most suitable replacement for you or “call me” if you prefer to receive a phone call. Alternatively, you can also select “do not replace”.
9. Are there price differences from the store?
For some stores, we may add a small service charge on top of the store price. If you notice an item that you think is priced incorrectly, please reach out to us! We reserve the right to cancel items that are priced incorrectly due to error.
10. How do you treat items that are non-Halal?
We allow you to buy non-Halal items using Freshchery, and are very careful to ensure that at no point during checkout, delivery, or any other time, non-Halal and Halal items get in contact with each other. To ensure that, we use different bags and clearly separated parts of the box for the transport of non-Halal items.
11. Would I get the Freshchery shopping bag for my order?
As long as the stocks are available, our Driver will put your order on our very own reuseable shopping bag. If you don’t get the shopping bag, it could be happened because the stocks are empty. But we will restock our shopping bag in the stores maximum at 1 week, don’t worry.
12. Can you assure the quality of the products that I bought?
Of course! We can assure the quality of the items for you, our beloved customer. If you found any bad quality items, you can contact our Customer Service and we will replace it.
13. How do I check the status of my order?
You will get notified when your order is packed, order is on its way and has almost arrived. Remember to turn on your push notification in your phone settings. You can also go on “My Orders” section in the app to check live-time status.
14. How do I edit or cancel my order?
You can edit your order until the shopper starts picking your items. Go to “My Orders” section in the app and select the order you want to edit. Click on “Edit Order” to change one of the following:
- Add or remove items
- Change delivery slot
- Change payment method
- Change address
- Cancel order
15. How do I report a problem with my order?
You can contact us following the “Help” button in the app and selecting “Contact Us”. We respond very quickly!
16. When will I receive my refund?
Payment will be made within 14 days by crediting your credit card.
17. How do I review my receipt?
You will receive an electronic receipt via e-mail after your order is delivered.
18. How do I return my Freshchery bags?
We encourage you to return your Freshchery bags that are still in good condition to your next Freshchery shopper for reuse. Feel free to use them for your own errands too.
19. How do I return items?
If something seems to be wrong with your order, such as a missing item or an incorrect item, you can reject the items when our rider arrives at your doorstep. We will charge you only for the delivered items. Once an item is accepted by you, it cannot be returned. We do not currently support a return process for any items you may have accidentally purchased via Freshchery. You are more than welcome to coordinate returns directly with your store. Keep in mind that we do keep the in-store receipts for accounting purposes.
20. Why is my card authorized for more than my order total?
Like a restaurant or a bar, Freshchery temporarily authorizes your card for slightly more than your order total. As soon as your order is complete, we charge your card for exactly what was delivered. Your bank will update the final charge on your statement in 3 – 7 business days after delivery. The temporary authorization can be for up to Rp 100,000 more than the order total. It helps account for charges like items sold by weight. If your final order total exceeds the authorization amount, there may be a second charge for the difference. You can see all charges reflected at the bottom of your receipt, which is available after delivery.
21. Who will select my items?
All our Personal Shoppers and Drivers are highly trained at selecting the best groceries for you. We employ Personal Shoppers that pick grocery and Drivers to deliver to your doorstep; in some stores, we may rely directly on Drivers to deliver your grocery.
22. Who will deliver my order?
Your orders will be delivered by specially trained and screened Drivers.
23. What if all Personal Shoppers are busy?
Occasionally our Personal Shoppers get overwhelmed with orders. During these times, the next available delivery slot may be later in the day. Use the delivery checker in the app to see the next available delivery for your order.
24. I have many more questions for you!
Contact us! We will be there at support.indonesia@Freshchery.com.


Welcome to DateNight!
The website that makes your date night more convenient.
Let's assume that you and your "SO (aka Significant Other)" would like to go out for a date night, however, you have to continually switch back and forth between websites looking at showtimes and trying to find a place to eat beforehand. Well, that's where DateNight comes in! We take your location, movie you're interested in seeing, , and show you theaters that are showing your movie, and a list of restaurants nearby. Sound Convenient to you? Enter your info below to get started!


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