| Opcode/Instruction | Op /En | 64/32 bit Mode Support | CPUID Feature Flag | Description |
|---|---|---|---|---|
| 66 0F 3A 17 /r ib EXTRACTPS reg/m32, xmm1, imm8 | RMI | VV | SSE4_1 | Extract one single-precision floating-point value from xmm1 at the offset specified by imm8 and store the result in reg or m32. Zero extend the results in 64-bit register if applicable. |
| VEX.128.66.0F3A.WIG 17 /r ib VEXTRACTPS reg/m32, xmm1, imm8 | RMI | V/V | AVX | Extract one single-precision floating-point value from xmm1 at the offset specified by imm8 and store the result in reg or m32. Zero extend the results in 64-bit register if applicable. |
| EVEX.128.66.0F3A.WIG 17 /r ib VEXTRACTPS reg/m32, xmm1, imm8 | T1S | V/V | AVX512F | Extract one single-precision floating-point value from xmm1 at the offset specified by imm8 and store the result in reg or m32. Zero extend the results in 64-bit register if applicable. |
| Op/En | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| RMI | ModRM:r/m (w) | ModRM:reg (r) | Imm8 | NA |
| T1S | ModRM:r/m (w) | ModRM:reg (r) | Imm8 | NA |
Extracts a single-precision floating-point value from the source operand (second operand) at the 32-bit offset spec-ified from imm8. Immediate bits higher than the most significant offset for the vector length are ignored.
The extracted single-precision floating-point value is stored in the low 32-bits of the destination operand
In 64-bit mode, destination register operand has default operand size of 64 bits. The upper 32-bits of the register are filled with zero. REX.W is ignored.
VEX.128 and EVEX encoded version: When VEX.W1 or EVEX.W1 form is used in 64-bit mode with a general purpose register (GPR) as a destination operand, the packed single quantity is zero extended to 64 bits.
VEX.vvvv/EVEX.vvvv is reserved and must be 1111b otherwise instructions will #UD.
128-bit Legacy SSE version: When a REX.W prefix is used in 64-bit mode with a general purpose register (GPR) as a destination operand, the packed single quantity is zero extended to 64 bits.
The source register is an XMM register. Imm8[1:0] determine the starting DWORD offset from which to extract the 32-bit floating-point value.
If VEXTRACTPS is encoded with VEX.L= 1, an attempt to execute the instruction encoded with VEX.L= 1 will cause an #UD exception.
VEXTRACTPS (EVEX and VEX.128 encoded version)
SRC_OFFSET (cid:197) IMM8[1:0] IF (64-Bit Mode and DEST is register) DEST[31:0] (cid:197) (SRC[127:0] >> (SRC_OFFSET*32)) AND 0FFFFFFFFh DEST[63:32] (cid:197) 0 ELSE DEST[31:0] (cid:197) (SRC[127:0] >> (SRC_OFFSET*32)) AND 0FFFFFFFFh FI
EXTRACTPS (128-bit Legacy SSE version)
SRC_OFFSET (cid:197)IMM8[1:0] IF (64-Bit Mode and DEST is register) DEST[31:0] (cid:197)(SRC[127:0] >> (SRC_OFFSET*32)) AND 0FFFFFFFFh DEST[63:32] (cid:197)0 ELSE DEST[31:0] (cid:197)(SRC[127:0] >> (SRC_OFFSET*32)) AND 0FFFFFFFFh FI
EXTRACTPS int _mm_extract_ps (__m128 a, const int nidx);
None
| VEX-encoded instructions, see Exceptions Type 5; Additionally |
| EVEX-encoded instructions, see Exceptions Type E9NF. |
| IF VEX.L = 0. |
| If VEX.vvvv != 1111B or EVEX.vvvv != 1111B. |


Ogre Animation.
More...
◆ Animation() [1/2]
| Assimp::Ogre::Animation::Animation |
( |
Skeleton * |
parent | ) |
|
|
explicit |
◆ Animation() [2/2]
| Assimp::Ogre::Animation::Animation |
( |
Mesh * |
parent | ) |
|
|
explicit |
◆ AssociatedVertexData()
Returns the associated vertex data for a track in this animation.
- Note
- Only valid to call when parent Mesh is set.
◆ ConvertToAssimpAnimation()
| aiAnimation * Assimp::Ogre::Animation::ConvertToAssimpAnimation |
( |
| ) |
|
◆ baseName
| std::string Assimp::Ogre::Animation::baseName |
◆ baseTime
| float Assimp::Ogre::Animation::baseTime |
◆ length
| float Assimp::Ogre::Animation::length |
◆ name
| std::string Assimp::Ogre::Animation::name |
◆ parentMesh
| Mesh* Assimp::Ogre::Animation::parentMesh |
Parent mesh.
- Note
- Set only when animation is read from a mesh.
◆ parentSkeleton
| Skeleton* Assimp::Ogre::Animation::parentSkeleton |
Parent skeleton.
- Note
- Set only when animation is read from a skeleton.
◆ tracks
The documentation for this class was generated from the following files:


Form field is a component used to wrap several Angular Material components and apply common Text field styles such as the underline, floating label, and hint messages.
You can use form field to wrap the following material components
In the next example we will show you how you can use the mat-form-field
attributes to change the look and behavior of a form.
The example shows how you can add error messages, hint messages, prefix and suffix options to form inputs.


Building a Historical Imagery Project¶
To build a historical imagery project:
Follow the steps in Defining and Building Resources to define and build the following:
¶ Name (Resources/Imagery/…) Acquisition Date Provider Mask Source File BlueMarble Any date. The date of the base image does not affect historical imagery browsing. NASA Imagery No Mask bluemarble_4km.tif SFBayAreaLanSat_20021010 2002-10-10 USGS Imagery Auto Mask Tolerance: 2 Default for all other mask values. usgsLanSat.tif i3_15Meter_20041010 2004-10-10 i3 Auto Mask Default values. i3SF15-meter.tif SFHighResInset_20061010 2006-10-10 USGS Imagery Auto Mask Default values. usgsSFHiRes.tif Open a new Imagery Project and add each of the image resources to the project:
- Resources/Imagery/BlueMarble
- Resources/Imagery/SFBayAreaLanSat_20021010
- Resources/Imagery/i3_15Meter_20041010
- Resources/Imagery/SFHighResInset_20061010
Select the Support Historical Imagery checkbox.
Select File > Save.
Enter Projects/Imagery/SFBayAreaHistorical as the name of your project and click Save.
Build the SFBayAreaHistorical project.
Create a new Earth Database and add the SFBayAreaHistorical project.
Save the new database as Databases/SFBayAreaHistorical.
Build and push the database to GEE Server, then publish it on GEE Server to the default Publish point.
Launch Google Earth EC.
Enter or select the host name or IP address of your server in the Server field, and specify the Publish point that you selected when you published your map database.
For example, if you specify SFBayAreaHistorical-v001, it will be accessible from myserver.mydomainname.com/SFBayAreaHistorical-v001.
Zoom in to the San Francisco Bay Area.
Select the Historical Imagery toolbar button to display a time slider. The time slider allows you to move the view through time.


The principle of rhythmic consistency pertains to rhythmic ideas, but many songs also choose to integrate patterns into the choice of scale degrees that make up the melody.
The simplest technique for integrating melodic themes is simply repeating the notes in the melody from phrase to phrase. The following diagram illustrates what repetition looks like:
An example of a song that uses repetition is “You’re Beautiful” by James Blunt:
Another example of a song that uses repetition is “She Will Be Loved” by Maroon 5:
Using repetition successfully requires careful planning (or blind luck) because a repeating melody that has not been chosen with care can clash with the underlying harmony, since scale degrees that are stable over one chord are not necessarily stable over another. Songwriters often have to break some of the rules regarding stable and unstable scale degrees in order to make use of repetition. This is where breaking the rules (with artistic license!) allows for more musical creativity and inventiveness.
It turns out some rules are easier to bend than others. Certain chords, for example, are more forgiving than others when it comes to playing unstable scale degrees on strong beats that are not resolved. An unstable scale degree might sound fine over one chord, while sounding dissonant over another. IV chords, for instance, tend to be more accommodating of unstable scale degrees than iii chords (you’ll learn more about iii chords in the next chapter).
Your ear is your best guide, but we’ve devised a mnemonic that will help you discern which chords are the most accommodating of unstable scale degrees. Just remember the simple rule that chords that have more “E”’s in their name (thrEE, onE, fivE) are more pickEE when it comes to fitting scale degrees in an overlying melody!
￼Sometimes songwriters will want to use repetition in their melody but won’t be able to without some egregious rule-breaking. For example, a repeating pattern might sound great over one chord, but not work at all when repeated over the next chord in the progression due to unresolved unstable scale degrees on strong beats. A common technique to deal with this problem involves making small changes to the offending scale degrees so that they fit with the underlying harmony. The result is a melody whose theme basically repeats, but with small variations. This technique is called modified repetition. Compared to (plain) repetition it looks like this:
An example of a song that uses modified repetition is “Somebody Told Me” by The Killers:
Notice the pattern in measure 1 of the scale degrees: 1-1-1-1-6. This pattern repeats again in measure 2, but in measure 3, the final scale degree 6 would clash with the V chord. Thus the pattern is modified to: 1-1-1-1-7.
Another common melodic theme is to shift the basic melodic phrase up or down so that it starts on a scale degree more appropriate for the underlying harmony. This is known as sequence and looks like this:
Often the amount of shifting between phrases is kept the same. In other words, if the second phrase is shifted one scale degree down from the first phrase, the third idea will also be shifted one scale degree from the second phrase. An example of a song that uses a sequence is “Friends Forever” by Vitamin C. In this case, the same melodic pattern is repeated three times with each phrase starting two scale degrees below the previous one.
The three common melodic patterns discussed in this section are summarized in the following figure. These patterns are examples to be studied, not a complete set that must be selected from when writing a melody:
When writing your melodies, remember that the human mind is as eager to recognize patterns as it is to look for new ones. Our ears are trained to like what is familiar to us - what we grew up listening to, what we like, what we find interesting. But our minds also crave the original, the novel, and the surprising. If you keep this in mind not just when writing melodies, but in the other aspects of your song as well, you’ll be on your way to writing something great.


| Direct data-driven formulas for optimal and distributed control I am interested in investigating novel approaches to the design controllers for unknown systems. Traditionally, input-(state)-output data of a system is used to identify its model, which can then be used to design a controller with classical control approaches. Instead, we look into designing controllers directly from data, in a one-step solution, bypassing explicit system identification altogether. In a series of papers we show how this approach can be advantageous, depending on the problem at hand and on the type of available data. For example, we find robust closed form formulas that return optimal controllers from data, even in distributed settings, and with noisy data. |
| Bifurcation Analysis of Linear-threshold Networks for Modeling Epilepsy We show that a network of coupled oscillators with linear-threshold nonlinearities can exhibit oscillations that are characteristic of epileptic seizures, and that the transition from normal to epileptic oscillations can be modeled as a bifurcation in the parameters of the system. This model is used to gain insight into the dynamic mechanisms underlying epileptic seizures. |
| Barrier functions for deconfliction of motion paths with traffic inspired rules We make use of safety barrier certificates with a direction bias to deconflict agents’ behaviour in a near-to-collision scenario, in compliance with local traffic rules. This work is motivated by atypical driving conditions, such as parking lots, where driving rules are not as strictly enforced as on standard roads. Navigation algorithms should take into account the human drivers’ behaviors, especially if they prove to be in conflict with the common rules of the road. |
| Melting Front Evolution of Paraffin Wax Inside Metal Foams at Different Acceleration Levels (HyMPaCt) We analyze the effect of different hyper gravity levels (up to 20g) and configurations (gravity direction parallel or perpendicular to the heat flux) on the melting performance of a composite aluminum foam/paraffin wax material. The paraffin wax melting and solidification front is dynamically recorded at each acceleration levels (from normal gravity up to 20g). The average of the critical Rayleigh number for the different test cases is evaluated and discussed. |
| Upgraded Pulsating Heat pipe Only for Space (U-PHOS) U-PHOS was a successful experiment, flown as part of the payload of ESA’s REXUS 22 sounding Rocket, launched from ESRANGE Space Center in Kiruna, Sweden on March 17th, 2017. As Ground Station responsible, I developed the communication software to receive data live from the rocket as well as send commands to drive the experiment from Earth (LabVIEW, C, MATLAB); I also took part in the definition and development of the communication protocol and assisted on some minor aspects of the experiment on board software and integration. |


Welcome to the
Greek Vocabulary Tool
What can you (and will you be able to) do with this site?
To get started, browse the Lemma List or Editions List.
Acknowledgements
The texts covered here are all from the Perseus Digital Library. They were lemmatized by Giuseppe Celano and combined with short definitions from Logeion, used with the generous permission of Helma Dik.
This site is being developed by Eldarion, supported in part by the Humboldt Chair of Digital Humanities at the University of Leipzig.


Personal Thanks
I would like to thank you again, for reading this document, and for using Go2. I sincerely hope that Go2 makes your life just a tiny bit easier, and maybe makes getting things done just a little bit faster.
I thank my wife, for her support, for her encouragement, and for her understanding of why I needed to stay up to 2 A.M. writing code. Without her constantly being there for me, neither Farmdog nor Go2 would exist.
I’d like to thank Jim Turner who I met through our local CocoaHeads chapter in Des Moines. Without his expert guidance, freely and generously given for months, Go2 would not be what it is today. Although Jim has moved away to California for bigger and better things, he remains a source of encouragement and enlightenment.
Speaking of the CocoaHeads, I would like to thank them as well. I look forward to our monthly meetings, and I'm convinced that CocoaHeads is a group of the most intelligent, articulate, and interesting people in town.
Thanks to each person who helped with their time and attention during the long beta phase of Go2. Your help is immensely appreciated.
I would also like to thank Daniel Jalkut, developer of MarsEdit and founder of Red Sweater Software. He left an encouraging note on a blog post of mine. If I see you at WWDC, I’ll buy you a beer.
Design Thanks
The neat little red coffee cup icon was designed by Seanau, who went through several iterations for me at an affordable price.
The new middle information button was designed and kindly donated by Thomas Zoechling during the beta testing phase of v1.3. Thanks again!
Code Thanks
Go2 takes advantage of a few open source code libraries:
While I am extremely grateful to the developers behind each of the above projects, my goal for the next version of Go2 is to remove the need for third party libraries.
I have also benefited from the generosity of the Mac developer community, who freely share information, code, and explanations.
The Mac community is a rich and vibrant place, and I feel privileged to be a part of it.


|
Assimp
5.0.1, master @ cd42b955
|
Data structure for the MD3 main header. More...
Public Attributes | |
| int32_t | FLAGS |
| unknown More... | |
| uint32_t | IDENT |
| magic number More... | |
| char | NAME [AI_MD3_MAXQPATH] |
| original name in .pak archive More... | |
| uint32_t | NUM_FRAMES |
| number of frames in the file More... | |
| uint32_t | NUM_SKINS |
| number of skins in the file More... | |
| uint32_t | NUM_SURFACES |
| number of surfaces in the file More... | |
| uint32_t | NUM_TAGS |
| number of tags in the file More... | |
| uint32_t | OFS_EOF |
| end of file More... | |
| uint32_t | OFS_FRAMES |
| offset of the first frame More... | |
| uint32_t | OFS_SURFACES |
| offset of the first surface More... | |
| uint32_t | OFS_TAGS |
| offset of the first tag More... | |
| uint32_t | VERSION |
| file format version More... | |
Data structure for the MD3 main header.
| int32_t Assimp::MD3::Header::FLAGS |
unknown
| uint32_t Assimp::MD3::Header::IDENT |
magic number
| char Assimp::MD3::Header::NAME[AI_MD3_MAXQPATH] |
original name in .pak archive
| uint32_t Assimp::MD3::Header::NUM_FRAMES |
number of frames in the file
| uint32_t Assimp::MD3::Header::NUM_SKINS |
number of skins in the file
| uint32_t Assimp::MD3::Header::NUM_SURFACES |
number of surfaces in the file
| uint32_t Assimp::MD3::Header::NUM_TAGS |
number of tags in the file
| uint32_t Assimp::MD3::Header::OFS_EOF |
end of file
| uint32_t Assimp::MD3::Header::OFS_FRAMES |
offset of the first frame
| uint32_t Assimp::MD3::Header::OFS_SURFACES |
offset of the first surface
| uint32_t Assimp::MD3::Header::OFS_TAGS |
offset of the first tag
| uint32_t Assimp::MD3::Header::VERSION |
file format version


B’208, Kamala C.H.S, Dr. S.P.Mukharji Rd , Dombivli(E), 421201 , Mumbai
<EMAIL_ADDRESS>(+91)<PHONE_NUMBER>
To work with a progressive organization in which I contribute my technical skills and knowledge to enhance my own productivity at the same time achieving the organizational objectives with the attribute of the time, quality and discipline.
* IT Professional with skills and enormous interest in Software Architecture and Development.
* Extensively involved in analysis, design, coding and documentation of Software Development.
* Expertise in implementing changes related to Maintenance and Enhancement.
* Expertise in Object Orient Design techniques and Shell scripting.
* Helped the Project Management Team of the project worked in the Structural designing of mongodb database for a NUSSD & NROER project.
* Exposure to various flavors of GNU Linux and open source environment.
* Handled all the Releases in the Project worked and achieved Zero defects.
* Coordinated and supported the Configuration Managers of Clients in Release activities.
Programming Languages
Python, C, C++, HTML
Web Technologies
HTML,XML,Javascript,CSS
Operating systems
Windows, GNU Linux (Ubuntu 14.04 LTS)
Database
Mongodb 2.4.9
Jan 2013 – July 2013
Project Intern
This project is about to develope Language independent communication paradigm using icons. Users can create iconic messages as realization of their concepts or ideas in mind. Its Gnowsys project and this application is one of the Django App in gnowsys studio. This application consists of iconic interface. By clicking on icons automatically the interpreted sentence will generate in users own language. Users can express their concepts and ideas solely using a spatial arrangement of icons.
Aug 2013 – Jan 2014
Program Officer
Tata Institute of Social Sciences (TISS) is initiating an exciting venture to enable job-oriented training of university students. Main Objective is to develop a platform for providing foundation courses on digital literacy. It’s a Online course delivery platform, developed using FOSS (Free and Open Source) operating system GNU/Linux,It is collaborating with 9 Universities to help aspiring students gain skills that make them employable; skills that could help secure their future, and give them an equal chance at a sustainable job or livelihood.
Python | Mongodb | Git | RCS | HTML | Foundation CSS | Javascript | django-mongokit
Feb 2014 – Present
Software Developer
Initiated by the Department of School Education and Literacy, Ministry of Human Resource Development, Government of India and the Central Institute of Educational Technology, National Council of Educational Research and Training. This repository is just a collection of free and open digital resources. Categorised and made into collections the resources are mapped to concepts that will span the entire school and teacher education curricula of the country. Anyone can participate in, contribute, curate and organise resources and activities, growing it to reach every teacher and every student in all languages.
Python | Mongodb | Git | RCS | HTML | Foundation CSS | Javascript | Django 1.6 | django-mongokit
2013
M.C.A.
Institution : MET ICS
Score : 60%
2009
B.S.C.(Physics)
Institution : K.J.Somaiya College Of Science & Commerce
Score : 52%
2005
H.S.C.
Institution : Royal College Of Science & Commerce
Score : 45%
2003
S.S.C.
Institution : Tilak Nagar High School
Score : 62%
2007
Windows Basic course of Office Automation
2007
Diploma In Software Programming
Participation in College Fest
Won the Table Tennis tournament as a part of FACES 2008 –sports event
Playing for state level Table Tennis Championship
Won the Badminton tournament as a part of FACES 2007 – sports event
Tabala, Harmonium Performance in traditional event Fest
English
ADVANCED
German
MODERATE
Hindi
ADVANCED
Marathi
NATIVE LANGUAGE
Dr. Nagarjuna G
Occupation
NUSSD Project Head at (HBCSE),
Tata Institute Of Fundamental Research,
V.N. Purav Marg, Mankhurd, Mumbai, 400088 India
Founder member and current chairperson of “Free Software Foundation of India.”
Email: nagarjun@gnowledge.org


We visualize bitcoin!
- visualize value-added synergies
- strategize end-to-end action-items
- incubate wireless interfaces
- mesh impactful initiatives
- generate dot-com schemas
- enhance granular solutions
- aggregate integrated architectures
- innovate granular users
- leverage bricks-and-clicks communities
- incubate world-class applications
- productize 24/365 partnerships
- deploy B2B e-services
- matrix open-source models
- productize impactful metrics


{{ $headline := .Get "headline" | default "Use Cases" }} {{ $textLead1 := .Get "textLead1" | default "First Value!" }} {{ $textLead2 := .Get "textLead2" | default "Second Value" }} {{ $textLead3 := .Get "textLead3" | default "Third Value" }} {{ $textSub1 := .Get "textSub1" | default "At VMware, we recognize that Open Source technology produces better software. We invest in and contribute to the Open Source community. This translates into more innovative, interoperable, scalable and secure solutions for everyone." }} {{ $textSub2 := .Get "textSub2" | default "At VMware, we recognize that Open Source technology produces better software. We invest in and contribute to the Open Source community. This translates into more innovative, interoperable, scalable and secure solutions for everyone." }} {{ $textSub3 := .Get "textSub3" | default "At VMware, we recognize that Open Source technology produces better software. We invest in and contribute to the Open Source community. This translates into more innovative, interoperable, scalable and secure solutions for everyone." }} {{ $featuredImg1 := .Get "featuredImg1" | default "administration.svg" }} {{ $featuredImg2 := .Get "featuredImg2" | default "authentication.svg" }} {{ $featuredImg3 := .Get "featuredImg3" | default "security.svg" }} {{ $buttonTxt1 := .Get "buttonTxt1" | default "Use Case 1"}} {{ $buttonTxt2 := .Get "buttonTxt2" | default "Use Case 2"}} {{ $buttonTxt3 := .Get "buttonTxt3" | default "Use Case 3"}} {{ $buttonURL1 := .Get "buttonURL1" | default "/"}} {{ $buttonURL2 := .Get "buttonURL2" | default "/"}} {{ $buttonURL3 := .Get "buttonURL3" | default "/"}}


Run Artifactory inside a Docker container. This image is based on the following image: Link: mattgruter/artifactory
(this image is using the open source version of artifactory and storers data in the embedded derby database)
Artifactories data
, logs
and backup
directories are exported as volumes:
<USER_HOME>/docker/data/artifactory/data
<USER_HOME>/docker/data/artifactory/logs
<USER_HOME>/docker/data/artifactory/backup
The service is exposed through port 8081
.
To run artifactory do:
docker run -p 18081:8081 amesken/artifactory
Now point your browser to http://<IP_ADDRESS>:18081/artifactory
Administration is done by user admin
with password password
.
The artifactory servlet is available at the artifactory/
path. However a filter redirects all paths outside of artifactory/
to the artifactory servlet. Thus instead of linking to the URL http://<IP_ADDRESS>:18081/artifactory/libs-release-local you can just link to http://<IP_ADDRESS>:18081/libs-release-local (i.e. omitting the subpath artifactory/
).
Inject the environment variable RUNTIME_OPTS
when starting a container to set Tomcat's runtime options (i.e. CATALANA_OPTS
). The most common use case is to set the heap size:
docker run -e RUNTIME_OPTS="-Xms256m -Xmx512m" -P amesken/artifactory
If you are using Artifactory Pro, the artifactory war archive has to be replaced. The image tagged -onbuild
is built with an ONBUILD
trigger for this purpose. Unpack the Artifactory Pro distribution ZIP file and place the file artifactory.war
(located in the archive) in the same directory as a simple Dockerfile that extends the onbuild
image:
# Dockerfile for Artifactory Pro
FROM mattgruter/artifactory:latest-onbuild
Now build your child docker image:
docker build -t yourname/myartifactory .
The ONBUILD
trigger ensures your artifactory.war
is picked up and applied to the image upon build.
docker run -P yourname/myartifactory
This artifactory image is originally created to work with a complete Continuous Delivery tool stack which can be obtained from docker or github. The image is based on this blog article by Marcel Birkner.


{% extends "base.html" %} {% block title %}UWCS | Error 500{% endblock %} {% block content %} 500 Sorry, there seems to be an error. Please try again soon. {% endblock %}
Sorry, there seems to be an error. Please try again soon.


Hi
{{ fullname }},
Thank you for joining us on this great platform.
Please click the following button to confirm your
registration...
By the way, if the above button is not clickable, paste the
following link in your browser.
http://{{ domain }}{% url 'accounts:activate' uidb64=uid token=token %}
– Django Authentication Webmaster
|


Donec rutrum congue leo eget malesuada. Mauris blandit aliquet elit, eget
tincidunt nibh pulvinar a. Pellentesque in ipsum id orci porta dapibus. Proin eget tortor risus. Donec
sollicitudin molestie malesuada.
Retina Design
Vestibulum ac diam sit amet quam vehicula elementum sed sit amet dui. Mauris
blandit aliquet elit, eget tincidunt nibh pulvinar a.
Donec rutrum congue leo eget malesuada. Mauris blandit aliquet elit, eget tincidunt nibh pulvinar a.
Pellentesque in ipsum id orci porta dapibus. Proin eget tortor risus. Donec sollicitudin molestie
malesuada.
Meet the Team
Donec rutrum congue leo eget malesuada. Mauris blandit aliquet elit, eget
tincidunt nibh pulvinar a. Pellentesque in ipsum id orci porta dapibus. Proin eget tortor risus. Donec
sollicitudin molestie malesuada.
Luke Skywalker
“I don't understand how we got by those troops. I thought we were dead.“
Luke Skywalker
“I don't understand how we got by those troops. I thought we were dead.“
Luke Skywalker
“I don't understand how we got by those troops. I thought we were dead.“
Luke Skywalker
“I don't understand how we got by those troops. I thought we were dead.“
Start Your Project Now
Leave your description and we start the engine.Don't worry,you can cancel anytime
Read Our Blog
NEW STORIES
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tincidunt nibh pulvinar a. Pellentesque in ipsum id orci porta dapibus. Proin eget tortor risus.
Donec sollicitudin molestie malesuada.


Image Sorting
Medical images exported from an imaging system or PACS system are often saved
with filenames based upon unique identifiers for the images. The
primary goal of DICOM Sort is to reorganize and rename these images
in a more user-friendly way. The software currently supports the following:
- Multi-level sorting based upon DICOM header
- Custom configuration of default sorting options
- Recursive token-based sorting
- Custom File Naming


The angle is specified in degrees. The rotation is done in a counter-clockwise direction. The original picture is not modified by the call to Pic.Rotate and must still be freed when no longer used. The picture produced by Pic.Rotate may be a different size than the original picture.
The (x, y) point is the point around which the rotation is to take place and is relative to the picture being rotated. If it is not important to rotate the picture in place, x and y should be set to -1, which make the new picture the minimum size required to fit the rotated image.
View.Set ("graphics:200;150,nobuttonbar")
var f : int := Font.New ("Serif:36")
Font.Draw ("Hello", 10, 10, f, black)
var pic : int := Pic.New (5, 5, 120, 45)
var pic45 : int := Pic.Rotate (pic, 45, -1, -1)
var pic90 : int := Pic.Rotate (pic, 90, -1, -1)
Pic.Draw (pic45, 5, 50, picCopy)
Pic.Draw (pic90, 150, 5, picCopy)
View.Set ("graphics:300;250,nobuttonbar")
var pic : array 0 .. 35 of int
var f : int := Font.New ("Serif:36")
const CTR : int := 57
Font.Draw ("Hello", 5, 45, f, black)
Draw.FillOval (CTR, CTR, 3, 3, brightred)
pic (0) := Pic.New (0, 0, 115, 115)
cls
for angle : 1 .. 35
pic (angle) := Pic.Rotate (pic (0), angle * 10, CTR, CTR)
end for
var x : int := CTR
var y : int := CTR
var dx : int := 1
var dy : int := 1
loop
for angle : 0 .. 35
Pic.Draw (pic (angle), x - CTR, y - CTR, picCopy)
if x + dx < CTR or x + dx > maxx - CTR then
dx := dx
end if
if y + dy < CTR or y + dy > maxy - CTR then
dy := dy
end if
x += dx
y += dy
delay (50)
end for
end loop
This means that you can only call the function by calling Pic.Rotate, not by calling Rotate.


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--- layout: post title: Improve your LINQ with .Any() categories: - Developer Deep Dive - linq status: publish type: post published: true meta: _edit_last: '2' s2mail: 'yes' _aioseop_keywords: LINQ, efficient, readable, declarative _aioseop_description: ! 'With LINQ, use the Any() method instead of using the Where() and Count() methods to see if a list contains any items. ' _aioseop_title: Improve your LINQ with .Any() dsq_thread_id: '832647668' ---
LINQ's .Any()
method is under-utilized, given the benefits it brings in making your code briefer, clearer, and more efficient. LINQ in general improves the expressiveness of your collection-manipulating code by using declarative statements instead of imperative foreach
loops; .Any()
is a great tool in that regard.
Here's a representative example:
{% gist 1877234 %}
I want to determine if my to-do list has any items that are late, so I use .Where()
to filter my list of deliverables down to items with a deadline in the past; then I take a .Count()
of the resulting list, and see if that number is greater than zero. This is a plausible solution, and our years of SQL lead us to write LINQ this way. But it can be better.
Testing "count greater than zero" is a programmer's way of saying "are there any?" So let's just say any. As you might expect, .Any()
returns a Boolean indicating whether the collection contains any items. Further, you can pass a lambda expression to specify the predicate "any like this." (.Count()
takes a predicate, too, by the way, but I really have seen ".Where().Count()
" in use, so I wanted to start from there.)
Here's the new version:
{% gist 1877236 %}
In addition to being shorter, this version more directly and declaratively states my intent: "Are there any late deliverables?"
This code also executes more efficiently. For .Count()
to return a value, LINQ must iterate over all items in the collection, even though I don't care how many items there are. .Any()
will return as soon as it encounters an item that satisfies the predicate. It evaluates as few items as possible, giving me an efficient and readable solution.


Phred scores and actual error rates:
- PhiX control (provided by Illumina) was spiked in all sequencing run to monitor sequencing errors.
- Reported Phred quality correlates well with the actual error rate down to 0.1% (Q30)
- In HIV amplicons, other sources of errors, such as PCR, dominate over sequencing errors (after filtering for >Q30)


WITNESS LIST House Administration Committee March 29, 1999-8:00A SB 494 For: Covington, Sid (Old Enfield Homeowners Association) On: Crawford, Rick (State Preservation Board) Fields, Julie (State Preservation Board)


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The fieldset's title is the main title of the step and the legend is the description of it.
Default options:
backLabel: '< Back',
Change the back button label.
block: false,
* Block the next step if the current is invalid.
errorImage: false,
* If an error occurs, a image is showed in the title of the corresponding step.
finish: true,
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nextLabel: 'Next >'
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titleClick: true,
Active the back and next action in the titles.
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* Depends of jquery.validation.js.
- All public functions have a optional second parameter to specify which container will be executed;
- You can pass a ID to be the target of the action.
- If the ID is not specified, then the last element Stepy will be takes.
Public functions:
$.fn.stepy.step(2, '#default');
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My name is Olga Bogatyreva
I am a student of the Rolling Scopes School
React is a JavaScript library for building user interfaces.
React was created by Jordan Walke, a software engineer at Facebook. React is influenced by the likes of XHP which is a simple HTML component framework for PHP. It was first deployed on Facebook's newsfeed in 2011 and later on Instagram.com in 2012. It was open-sourced at JSConf US in May 2013.
Some of the major advantages of React are:
React has a small API, and you have to understand 4 concepts to get started:
Component is a JavaScript class or function that accepts inputs i.e. properties(props) and returns a React element that describes how a section of the UI (User Interface) should appear.
function Welcome(props) {
return
Hello, {props.name}

}
class Welcome extends React.Component {
render () {
return
Hello, {this.props.name}

}
}
A React Component can go through four stages of its life as follows.
JSX is a JavaScript extension that allows us to define React elements using syntax that looks similar to HTML. In JSX, an element’s type is specified with a tag. The tag’s attributes represent the properties.
const name = 'Josh Perez';
const element =
Hello, {name}
;
ReactDOM.render (
element,
document.getElementById('root')
);
State is an object.
It is mutable unlike props and creates dynamic and interactive components. it is accessed via this.state().
class Clock extends React.Component {
constructor(props) {
super(props);
this.state = {date: new Date()};
render() {
return (

Hello, world!

It is {this.state.date.toLocaleTimeString()}.

);
}
}
Props is shorthand for properties. They are read-only components which must be kept pure i.e immutable. They are data passed down from a parent component to a child component.
const BlogPostExcerpt = props => {
return (

{props.title}

{props.description}

)
}
In React world, the term "virtual DOM" is usually associated with React elements.
React maintains two Virtual DOM at each time. One contains the updated Virtual DOM and one which is the pre-update version of this updated Virtual DOM. We can compare the pre-update version with the updated Virtual DOM and find out what has changed in the DOM. This process is known as ‘diffing’.
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| It updates slow. | It updates faster. |
| Can directly update HTML. | Can't directly update HTML. |
| Creates a new DOM if element updates. | Updates the JSX if element updates. |
| DOM manipulation is very expensive. | DOM manipulation is very easy. |
In conclusion, React is changing step by step. Hooks are a new addition in React 16.8. They let you use state and other React features without writing a class.


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Try to answer the following code-related questions within the time limit. Keep in mind that incorrect answers will penalize your score/time by ten seconds! The games ends when the questions are all answer or when your timer/score is equal to 0, whichever comes first. Want to try to beat your high score? Play again!
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[1]
we paid a bit more to get the executive room etc.
[2]
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Anterior and posterior images of the chest, lower cervical region and upper abdomen were obtained following the intravenous injection of Gallium-67 citrate. Emission tomographic images of the same area were obtained.
Ga-67 citrate mCi
Scan delay hr
None.
No abnormal concentration of Gallium is demonstrated in the chest, lower neck, or upper abdomen.
Negative examination. No evidence for inflammation, infection, or tumor.


Most people vacuum their floors on a weekly basis. The weekly light vacuuming
people vacuum their floors on a weekly basis.  The weekly light vacuumin their floors on a vacuumin their floors on a weekly basis. The weekly light vacuumin
from the BLOG
Chaddha and D'Souza families have been friends for as long as they can remember celebrating Diwali and Christmas together with equal gusto.


Type some value in the inputs and some characters will be prevented depending on the restriction set in every field


[§124A-150] Provoking speeches or gestures. Any person subject to this chapter who uses provoking or reproachful words or gestures towards any other person subject to this chapter shall be punished as a court-martial may direct. [L 1982, c 171, pt of §2]


Connectivity¶
Connectivity methods classes.
-
connectivipy.conn.
spectrum
(acoef, vcoef, fs=1, resolution=100)[source]¶ Generating data point from matrix A with MVAR coefficients. Args:
- acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- Returns:
- A_z : numpy.array
- z-transformed A(f) complex matrix in shape (resolution, k, k)
- H_z : numpy.array
- inversion of A_z
- S_z : numpy.array
- spectrum matrix (resolution, k, k)
References: .. [1] K. J. Blinowska, R. Kus, M. Kaminski (2004) “Granger causality
and information flow in multivariate processes” Physical Review E 70, 050902.
-
connectivipy.conn.
spectrum
(acoef, vcoef, fs=1, resolution=100)[source] Generating data point from matrix A with MVAR coefficients. Args:
- acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- Returns:
- A_z : numpy.array
- z-transformed A(f) complex matrix in shape (resolution, k, k)
- H_z : numpy.array
- inversion of A_z
- S_z : numpy.array
- spectrum matrix (resolution, k, k)
References: .. [1] K. J. Blinowska, R. Kus, M. Kaminski (2004) “Granger causality
and information flow in multivariate processes” Physical Review E 70, 050902.
-
connectivipy.conn.
spectrum_inst
(acoef, vcoef, fs=1, resolution=100)[source]¶ Generating data point from matrix A with MVAR coefficients taking into account zero-lag effects. Args:
- acoef : numpy.array
- array of shape (k, k, p+1) where k is number of channels and p is a model order. acoef[0] - is (k, k) matrix for zero lag, acoef[1] for one data point lag and so on.
- vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- Returns:
- A_z : numpy.array
- z-transformed A(f) complex matrix in shape (resolution, k, k)
- H_z : numpy.array
- inversion of A_z
- S_z : numpy.array
- spectrum matrix (resolution, k, k)
References: .. [1] Erla S. et all, Multivariate Autoregressive Model with
Instantaneous Effects to Improve Brain Connectivity Estimation, Int. J. Bioelectromagn. 11, 74–79 (2009).
-
connectivipy.conn.
spectrum_inst
(acoef, vcoef, fs=1, resolution=100)[source] Generating data point from matrix A with MVAR coefficients taking into account zero-lag effects. Args:
- acoef : numpy.array
- array of shape (k, k, p+1) where k is number of channels and p is a model order. acoef[0] - is (k, k) matrix for zero lag, acoef[1] for one data point lag and so on.
- vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- Returns:
- A_z : numpy.array
- z-transformed A(f) complex matrix in shape (resolution, k, k)
- H_z : numpy.array
- inversion of A_z
- S_z : numpy.array
- spectrum matrix (resolution, k, k)
References: .. [1] Erla S. et all, Multivariate Autoregressive Model with
Instantaneous Effects to Improve Brain Connectivity Estimation, Int. J. Bioelectromagn. 11, 74–79 (2009).
-
class
connectivipy.conn.
Connect
[source]¶ Abstract class governing calculation of various connectivity estimators with concrete methods: short_time, significance and abstract calculate.
-
short_time
(data, nfft=None, no=None, **params)[source]¶ Short-tme version of estimator, where data is windowed into parts of length nfft and overlap no. params catch additional parameters specific for estimator. Args:
- data : numpy.array
- data matrix
- nfft = None : int
- window length (if None it’s N/5)
- no = None : int
- overlap length (if None it’s N/10)
- params :
- additional parameters specific for chosen estimator
- Returns:
- stvalues : numpy.array
- short time values (time points, frequency, k, k), where k is number of channels
-
short_time_significance
(data, Nrep=10, alpha=0.05, nfft=None, no=None, verbose=True, **params)[source]¶ Significance of short-tme versions of estimators. It base on bootstrap
Connect.bootstrap()
for multitrial case and surrogate dataConnect.surrogate()
for one trial. Args:- data : numpy.array
- data matrix
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- nfft = None : int
- window length (if None it’s N/5)
- no = None : int
- overlap length (if None it’s N/10)
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- signi_st : numpy.array
- short time significance values in shape of - (tp, k, k) for one sided estimator - (tp, 2, k, k) for two sided where k is number of channels and tp number of time points
-
significance
(data, Nrep=10, alpha=0.05, verbose=True, **params)[source]¶ Significance of connectivity estimators. It base on bootstrap
Connect.bootstrap()
for multitrial case and surrogate dataConnect.surrogate()
for one trial. Args:- data : numpy.array
- data matrix
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- signific : numpy.array
- significance values, check
Connect.levels()
-
levels
(signi, alpha, k)[source]¶ Levels of significance Args:
- signi : numpy.array
- bootstraped values of each channel
- alpha : float
- type I error rate (significance level) - from 0 to 1 - (1-alpha) for onesided estimators (e.g. class:DTF) - alpha and (1-alpha) for twosided (e.g. class:PSI)
- k : int
- number of channels
- Returns:
- ficance : numpy.array
- maximal value throughout frequency of score at percentile at level 1-alpha - (k, k) for one sided estimator - (2, k, k) for two sided
-
bootstrap
(data, Nrep=100, alpha=0.05, verbose=True, **params)[source]¶ Bootstrap - random sampling with replacement of trials. Args:
- data : numpy.array
- multichannel data matrix
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- levelsigni : numpy.array
- significance values, check
Connect.levels()
-
surrogate
(data, Nrep=100, alpha=0.05, verbose=True, **params)[source]¶ Surrogate data testing. Mixing data points in each channel. Significance level in calculated over all Nrep surrogate sets. Args:
- data : numpy.array
- multichannel data matrix
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- levelsigni : numpy.array
- significance values, check
Connect.levels()
-
-
class
connectivipy.conn.
ConnectAR
[source]¶ Inherits from Connect class and governs calculation of various connectivity estimators basing on MVAR model methods. It overloads short_time, significance methods but calculate remains abstract.
-
short_time
(data, nfft=None, no=None, mvarmethod='yw', order=None, resol=None, fs=1)[source]¶ It overloads
ConnectAR
methodConnect.short_time()
. Short-tme version of estimator, where data is windowed into parts of length nfft and overlap no. params catch additional parameters specific for estimator. Args:- data : numpy.array
- data matrix
- nfft = None : int
- window length (if None it’s N/5)
- no = None : int
- overlap length (if None it’s N/10)
- mvarmethod = ‘yw’ :
- MVAR parameters estimation method
all avaiable methods you can find in fitting_algorithms
- order = None:
- MVAR model order; it None, it is set automatically basing on default criterion.
- resol = None:
- frequency resolution; if None, it is 100.
- fs = 1 :
- sampling frequency
- Returns:
- stvalues : numpy.array
- short time values (time points, frequency, k, k), where k is number of channels
-
short_time_significance
(data, Nrep=100, alpha=0.05, method='yw', order=None, fs=1, resolution=None, nfft=None, no=None, verbose=True, **params)[source]¶ Significance of short-tme versions of estimators. It base on bootstrap
ConnectAR.bootstrap()
for multitrial case and surrogate dataConnectAR.surrogate()
for one trial. Args:- data : numpy.array
- data matrix
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- method = ‘yw’: str
- method of MVAR parameters estimation all avaiable methods you can find in fitting_algorithms
- order = None : int
- MVAR model order, if None, it’s chosen using default criterion
- fs = 1 : int
- sampling frequency
- resolution = None : int
- resolution (if None, it’s 100 points)
- nfft = None : int
- window length (if None it’s N/5)
- no = None : int
- overlap length (if None it’s N/10)
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- signi_st : numpy.array
- short time significance values in shape of - (tp, k, k) for one sided estimator - (tp, 2, k, k) for two sided where k is number of channels and tp number of time points
-
significance
(data, method, order=None, resolution=None, Nrep=10, alpha=0.05, verbose=True, **params)[source]¶ Significance of connectivity estimators. It base on bootstrap
ConnectAR.bootstrap()
for multitrial case and surrogate dataConnectAR.surrogate()
for one trial. Args:- data : numpy.array
- data matrix
- method = ‘yw’: str
- method of MVAR parametersestimation all avaiable methods you can find in fitting_algorithms
- order = None : int
- MVAR model order, if None, it’s chosen using default criterion
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- resolution = None : int
- resolution (if None, it’s 100 points)
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- signi_st : numpy.array
- significance values, check
Connect.levels()
-
bootstrap
(data, method, order=None, Nrep=10, alpha=0.05, fs=1, verbose=True, **params)[source]¶ Bootstrap - random sampling with replacement of trials for ConnectAR. Args:
- data : numpy.array
- multichannel data matrix
- method : str
- method of MVAR parametersestimation all avaiable methods you can find in fitting_algorithms
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- order = None : int
- MVAR model order, if None, it’s chosen using default criterion
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- levelsigni : numpy.array
- significance values, check
Connect.levels()
-
surrogate
(data, method, Nrep=10, alpha=0.05, order=None, fs=1, verbose=True, **params)[source]¶ Surrogate data testing for ConnectAR . Mixing data points in each channel. Significance level in calculated over all Nrep surrogate sets. Args:
- data : numpy.array
- multichannel data matrix
- method : str
- method of MVAR parameters estimation all avaiable methods you can find in fitting_algorithms
- Nrep = 100 : int
- number of resamples
- alpha = 0.05 : float
- type I error rate (significance level)
- order = None : int
- MVAR model order, if None, it’s chosen using default criterion
- verbose = True : bool
- if True it prints dot on every realization, if False it’s quiet.
- params :
- additional parameters specific for chosen estimator
- Returns:
- levelsigni : numpy.array
- significance values, check
Connect.levels()
-
-
connectivipy.conn.
dtf_fun
(Acoef, Vcoef, fs, resolution, generalized=False)[source]¶ Directed Transfer Function estimation from MVAR parameters. Args:
- Acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- Vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- generalized = False : bool
- generalized version or not
- Returns:
- DTF : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] M. Kaminski, K.J. Blinowska. A new method of the description
of the information flow. Biol.Cybern. 65:203-210, (1991).
-
connectivipy.conn.
pdc_fun
(Acoef, Vcoef, fs, resolution, generalized=False)[source]¶ Partial Directed Coherence estimation from MVAR parameters. Args:
- Acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- Vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- generalized = False : bool
- generalized version or not
- Returns:
- PDC : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] Sameshima, K., Baccala, L. A., Partial directed
coherence: a new concept in neural structure determination., 2001, Biol. Cybern. 84, 463–474.
-
class
connectivipy.conn.
PartialCoh
[source]¶ PartialCoh - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.-
calculate
(Acoef=None, Vcoef=None, fs=None, resolution=None)[source]¶ Partial Coherence estimation from MVAR parameters. Args:
- Acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- Vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- generalized = False : bool
- generalized version or not
- Returns:
- PC : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] G. M. Jenkins, D. G. Watts. Spectral Analysis and its
Applications. Holden-Day, USA, 1969
-
-
class
connectivipy.conn.
PDC
[source]¶ PDC - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.
-
class
connectivipy.conn.
gPDC
[source]¶ gPDC - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.
-
class
connectivipy.conn.
DTF
[source]¶ DTF - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.
-
class
connectivipy.conn.
gDTF
[source]¶ gDTF - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.
-
class
connectivipy.conn.
ffDTF
[source]¶ ffDTF - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.-
calculate
(Acoef=None, Vcoef=None, fs=None, resolution=100)[source]¶ full-frequency Directed Transfer Function estimation from MVAR parameters. Args:
- Acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- Vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- generalized = False : bool
- generalized version or not
- Returns:
- ffDTF : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] Korzeniewska, A.et. all. Determination of information flow direction
among brain structures by a modified directed transfer function (dDTF) method. J. Neurosci. Methods 125, 195–207 (2003).
-
-
class
connectivipy.conn.
dDTF
[source]¶ dDTF - class inherits from
ConnectAR
and overloadsConnect.calculate()
method.-
calculate
(Acoef=None, Vcoef=None, fs=None, resolution=100)[source]¶ direct Directed Transfer Function estimation from MVAR parameters. dDTF is a DTF multiplied in each frequency by Patrial Coherence. Args:
- Acoef : numpy.array
- array of shape (k, k, p) where k is number of channels and p is a model order.
- Vcoef : numpy.array
- prediction error matrix (k, k)
- fs = 1 : int
- sampling rate
- resolution = 100 : int
- number of spectrum data points
- generalized = False : bool
- generalized version or not
- Returns:
- dDTF : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] Korzeniewska, A.et. all. Determination of information flow direction
among brain structures by a modified directed transfer function (dDTF) method. J. Neurosci. Methods 125, 195–207 (2003).
-
-
class
connectivipy.conn.
Coherency
[source]¶ Coherency - class inherits from
Connect
and overloadsConnect.calculate()
method and values_range attribute.-
calculate
(data, cnfft=None, cno=None, window=<function hanning>, im=False)[source]¶ Coherency calculation using FFT mehtod. Args:
- data : numpy.array
- array of shape (k, N) where k is number of channels and N is number of data points.
- cnfft = None : int
- number of data points in window; if None, it is N/5
- cno = 0 : int
- overlap; if None, it is N/10
- window = np.hanning : <function> generating window with 1 arg n
- window function
- im = False : bool
- if False it return absolute value, otherwise complex number
- Returns:
- COH : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] M. B. Priestley Spectral Analysis and Time Series.
Academic Press Inc. (London) LTD., 1981
-
-
class
connectivipy.conn.
PSI
[source]¶ PSI - class inherits from
Connect
and overloadsConnect.calculate()
method.-
calculate
(data, band_width=4, psinfft=None, psino=0, window=<function hanning>)[source]¶ Phase Slope Index calculation using FFT mehtod. Args:
- data : numpy.array
- array of shape (k, N) where k is number of channels and N is number of data points.
- band_width = 4 : int
- width of frequency band where PSI values are summed
- psinfft = None : int
- number of data points in window; if None, it is N/5
- psino = 0 : int
- overlap; if None, it is N/10
- window = np.hanning : <function> generating window with 1 arg n
- window function
- Returns:
- COH : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] Nolte G. et all, Comparison of Granger Causality and
Phase Slope Index. 267–276 (2009).
-
-
class
connectivipy.conn.
GCI
[source]¶ GCI - class inherits from
Connect
and overloadsConnect.calculate()
method.-
calculate
(data, gcimethod='yw', gciorder=None)[source]¶ Granger Causality Index calculation from MVAR model. Args:
- data : numpy.array
- array of shape (k, N) where k is number of channels and N is number of data points.
- gcimethod = ‘yw’ : int
- MVAR parameters estimation model
- gciorder = None : int
- model order, if None appropiate value is chosen basic on default criterion
- Returns:
- gci : numpy.array
- matrix with estimation results (resolution, k, k)
References: .. [1] Nolte G. et all, Comparison of Granger Causality and
Phase Slope Index. 267–276 (2009).
-


Library: Language support
Function
Storage allocation functions implicitly called by the corresponding new expressions to allocate storage suitably aligned to construct any object of a given size
#include <new> namespace std { class bad_alloc; struct nothrow_t {}; extern const nothrow_t nothrow; typedef void (*new_handler)(); new_handler set_new_handler new_handler) throw(); } void* operator new(std::size_t) throw (std::bad_alloc); void* operator new(std::size_t, const std::nothrow_t&) throw(); void* operator new[](std::size_t) throw(std::bad_alloc); void* operator new[](std::size_t, const std::nothrow_t&) throw(); void* operator new(std::size_t, void*) throw(); void* operator new[](std::size_t, void*) throw();
The library provides definitions for six overloads of the global operator new. The functions are implicitly called as the first step during the evaluation of the corresponding new expression to allocate storage suitably aligned to construct one or more objects (for the array versions of the operator) of any type. The functions indicate failure by either throwing an exception object of type bad_alloc or by returning the null pointer. Replacements for the replaceable forms of the functions should always paired with the replacements for the corresponding overload of operator delete.
new_handler set_new_handler(new_handler handler) throw();
Establishes handler as the current new_handler. The first time set_new_handler() is called, it returns the null pointer. Subsequent calls to set_new_handler() return the previous value of new_handler.
void* operator new(std::size_t n) throw(std::bad_alloc);
Allocation function implicitly called by a new expression to allocate n bytes of storage. The function attempts to allocate storage in a loop: if the allocation is successful, a pointer to the allocated memory is returned. Otherwise, if the last argument to std::set_new_handler() was not a null pointer, the function calls the current new_handler. Otherwise it throws an exception object of type bad_alloc. The loop terminates if the allocation is successful or the current new_handler doesn't return. A C++ program may replace this function.
void* operator new(std::size_t n, const std::nothrow_t&) throw();
Allocation function similar to the one above, except that it indicates failure by returning a null pointer. A C++ program may replace this function.
void* operator new[](std::size_t n) throw(std::bad_alloc);
Allocation function implicitly called by the array form of a new expression to allocate n bytes of storage. The function returns ::operator new (n). A C++ program may replace this function.
void* operator new[](std::size_t, const std::nothrow_t&) throw();
Allocation function similar to the one above, except that it indicates failure by returning a null pointer. A C++ program may replace this function.
void* operator new(std::size_t, void *p) throw();
Allocation function implicitly called by the placement form of a new expression. Returns p. A C++ program may not replace this function.
void* operator new[](std::size_t, void *p) throw();
Allocation function implicitly called by the placement array form of a new expression. Returns p. A C++ program may not replace this function.
<new>, bad_alloc, operator delete
ISO/IEC 14882:1998 -- International Standard for Information Systems -- Programming Language C++, Section 18.4


25toLife is a joint project between Kamal Masri's SFU Beedie School of Business Project Management class and the Canadian Cancer Society (CCS).
This project aims to raise funds for cancer research and to support individuals who are affected by this disease while learning project management.
Our goal this year is to raise $30,000 for the CCS by December 5, 2016.
After meeting each other for the first time on September 12, 2016, we decided we would organize seven diverse fundraiser events.
Thank you for all of you who are joining our team in the fight for life.
And that is something we can all live for.
Our Current Progress
Number Of Events Completed
Days Left


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Live with less
- home
Clean your house
Get rid of all your clutter and decorations. We'll keep them safe and sound for you. Most people don't need 90% of their posessions. We'll make your furniture so white that when you spill your drink, it'll stain everything.
- spa
Be more mindful
Focus only on the things you really need.  You'll feel way less materialistic when you look at so few things you have.
- money
Save lots of money
Lami will get rid of all your belongings for you, leaving only the very important parts. You can live a life of minimalism that's worth your money.
Hear what people say about us
"It like, changed my life dude.   I'm a busy person and this helped me stopped smoking weed so much. 420 blaze it my homies." — Luke Walker, CEO of Blaze Inc.


About the Author
Debra Lynn is an author/illustrator who lives in the very scenic small town of Port Alice at the northern end of Vancouver Island. Her first children’s picture book, Marshmallow, about her very lazy cat who finds many creative ways to sleep, was published in 2013. Her next picture book, Macaroni and Mud, about making a play feast out of all kinds of gross and yucky stuff, is slated to come out soon.
Debra Lynn grew up in the northern farming community of Athabasca, Alberta, but has spent many years travelling around the world, including too places like China, Mexico and Europe. She has a BFA from the University of Alberta and an MA in art education from Concordia University, Montreal. Besides working as a community art instructor, she also worked 18 seasons as a forest fire lookout in Northern Alberta and the Rocky Mountains. Since moving to Port Alice in 2010, she has taken up kayaking for the first time with her partner James Moore and his cute little Chihuahua named Chloe. Debra writes about their kayaking adventures in her blog: www.chloethekayakingchihuahua.com.
Marshmallow is available at select stores around Vancouver Island. You can also order Marshmallow from Amazon, just head to this link: Marshmallow at Amazon
The writing and photography in this blog are protected by copyright. You may download the stories and photos for your own enjoyment, but you may not use them for any kind of commercial use without written permission from Debra Lynn or James Moore.


Monika Büscher, Mette Agger Eriksen, Jannie Friis Kristensen, Preben Holst Mogensen
Covers their future laboratories, in-situ prototyping and bricolage. Focus; grounding imagination within interdisciplinary participatory design. They bring in Heidegger and Gibson (1986) 'jobs-at-hand' with means and environments as points of a methodological triangle. Their focus - landscape architects.
The three methods described and exemplified above make up the
core of methods used within the WorkSpace project. In this paper
we have used triangulation as a tool to differentiate and evaluate
them. They each come into their own through combination:
approaching design challenges from various foci at different
stages of development.
Heidegger
Gibson (1986) jobs-at-hand concept in design


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Overview¶
Cloudmesh is easy to install. However we have provided a comprehensive documentation for many different deployment scenarios.
Most of our users chose option 3 as they like to further develop Cloudmesh.
See also
In case you are experienced with Python virtualenv and like to install Cloudmesh in your virtualenv, you can alse review the Quickstart guide. However we also recommend to get an overview of how to install it for your particular system.
Please read the installation section in this manual thoroughly, and understand the items explained before you install it. Do not just paste and copy the text in your terminal and execute it as it could have unexpected consequences. This also helps to decide which installation method is best suited for you.
We are providing a clickable map to help you in your decision process which version and how to install it.
Installation of Cloudmesh with Docker¶
Although cloudmesh can just be installed on containers without the use of Python, it is best if you use cmsd. This is a python program that is designed to manage the containers and makes use of cloudmesh simple form the command line.
This installation can be conducted on all OSes on which docker and python 3.8.2 or newer is installed. Cloudmesh can also be installed with a specialized cloudmesh-cmsd command that is distributed as source and on PyPi.
See Cloudmesh cmsd for more information.
Installation of Cloudmesh in Python¶
On some operating systems, you will need a number of tools installed on your computer before you can install cloudmesh. It is important to full fill these requirements. Please use the clickable map to identify the OS method you use and follow the link.
Warning
Please only continue once you have the Prerequists fulfilled.
Once you have installed the prerequisites on your computer cloudmesh is also each to install natively in your python virtual environment. Please note that we do not recommend installing it on your OS directly, but you must use a virtual environment.
Note
We recommend that you use Python venv to isolate the system Python form the user python. For simplicity we assume and document on how to set up a virtual environment in the home directory under the directory name ~/ENV3.
Anaconda and Conda¶
Cloudmesh can be installed in anaconda with pip. Please follow our pip instructions, but make sure you create your own virtualenv with conda and assure you use python at least 3.8.2.
Python Installation from python.org¶
The easiest installation of Python for cloudmesh is to use the installation from https://www.python.org/downloads. Please, visit the page and follow the instructions. After this install, you have python3 available from the command line. After the installation of Python do the following:
Linux, macOS, Windows gitbash:
$ python3.8 -m venv ~/ENV3
$ source ~/ENV3/bin/activate
$ pip install pip -U
Tip
You can add at the end of your .bashrc (ubuntu) or .bash_profile (macOS) file the line so the environment is always loaded.
source ~/ENV3/bin/activate
In Windows CMD, you can do this with
$ python -m venv ENV3
$ ENV3\Scripts\activate
$ pip install pip -U
Now you can now install cloudmesh cmsd
with
$ pip install cloudmesh-openstack
In a Linux subsystem, ~/ is the default location, assumed to be the home directory. In a windows system, this location is assumed to be under C:UsersUSERNAME.
SSH key¶
In order for you to use a cloud you will need an ssh key that you use to interact conveniently with cloud resources. This can be created from the command line with
ssh-keygen
Please make sure to use a passphrase with your key. Anyone telling you to use a passwordless key is giving you the wrong advice.
First configuration¶
Once installed, test the cloudmesh command and at the same time create
a configuration file. This is done by invoking the cms help
command the first
time. Thus, just type the command
cms help
in your terminal. It will create a directory ~/.cloudmesh in which you can find the configuration file:
~/.cloudmesh/cloudmesh.yaml
To get you started quickly, we are providing some convenient programs that help you set things up. Use the commands
cms gui
cms init
To set up a default configuration. However, you can also do this from the command line while using the config command in case the gui command is not an option for you:
.. code-block:: bash
cms config set cloudmesh.profile.user=YOURUSERNAME cms set key user=YOURUSERNAME
Alternatively, you can edit and modify the ~/.clloudmesh/cloudmesh.yaml file.
Cloudmesh comes with cloud service bundles that can be easily installed using the pip command. Examples include
pip install cloudmesh-openstack
pip install cloudmesh-aws
pip install cloudmesh-google
pip install cloudmesh-azure
pip install cloudmesh-volume
pip install cloudmesh-storage
The Directory .cloudmesh¶
All cloudmesh related configuration information is stored in the .cloudmesh directory. In case you want to start fresh, simply delete that directory and its subdirectories. However, if you need information from it, make sure you make a backup.
Please note that in this file, you have sensitive information, and it should never be backed up into GitHub, box, icloud, or other such services. Keep it on your computer or back it up on a secure encrypted external hard drive or storage media only you have access to.
Installation of MongoDB¶
Once you have installed cloudmesh it is easy to install MongoDB with the build-in MongoDB installer:
cms admin mongo install
The installation of Mongo is done on the default port, and a version of mongo is installed in your ~/.cloudmsh directory. If you have other versions of Mongo on your computer make sure it is the newer one, as Mongo states, older versions must first completely uninstalled, so Mongo works properly.


L01 Discussion Forum Introduction to Data Science
- Discuss the differences between a natural (unintentional) experiment and a randomized control trial (RCT). [see L01 (Lecture 1)]
1.a. What are the advantages of RCTs over natural experiments?
1.b. What are the advantages of natural experiments over RCTs?
1.c. Can you think of any challenges for natural experiments that were not mentioned in the lecture?
- Share at least one possible (exogenous) cause of growth rate variability in guinea pig birth weight besides litter size. See RR1 (required reading 1)


Acorn Icons (401)
Category [commerce] (47)
balance
barcode
barrel
basket
bitcoin
board-1
board-2
board-3
box
boxes
candlestick
cart
chart-1
chart-2
chart-3
chart-down
chart-up
chimney
coin
crane
credit-card
delivery-truck
diagram-1
diagram-2
diagram-3
dollar
euro
exchange
factory
gold
handbag
invoice
money-bag
money
petrol
pos
pound
safe
sale-tag
shipping
shop
sign
signboard
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startup
suitcase
wind-turbine
Category [interface] (287)
accordion
acorn
activity
air-balloon
alarm
align-center
align-justify
align-left
align-right
anchor
antenna
archive
arrow-bottom-left
arrow-bottom-right
arrow-bottom
arrow-double-bottom
arrow-double-left
arrow-double-right
arrow-double-top
arrow-end-bottom
arrow-end-left
arrow-end-right
arrow-end-top
arrow-left
arrow-right
arrow-top-left
arrow-top-right
arrow-top
at-sign
attachment
badge
banana
battery-charging
battery-empty
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bell-off
bell
bin
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bluetooth
book-open
book
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bootstrap
brush-2
brush
building-large
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building
burger
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button
calendar
camera-off
camera
car
category
chart-4
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circle
clipboard
clock
close-circle
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compass
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crosshair
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cursor-default
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dashboard-1
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destination
divide
download
dropdown
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edit
editor
electricity
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file-image
file-music
file-text
file-video
filter
flag
flash
folder
folders
form-check
form
gear
gender
gift
grid-1
grid-2
grid-3
grid-5
headset
health
heart
help
hexagon
home-garage
home
hourglass
image
inbox
info-circle
info-hexagon
input-group
input
key
keyboard
laptop
layout-1
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leaf
light-off
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like
link-broken
link
list
loaf
lock-off
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login
logout
luggage
main-course
maximize
menu-bookmark
menu-dashed
menu-dropdown
menu-left
menu-right
menu-shrink
menu
message
messages
mic-off
mic
minimize
minus
mobile
moon
more-horizontal
more-vertical
mouse
multiply
mushrooms
music
navigate-diagonal
news
next
note
notebook-1
notification
office
paint-roller
palette
pause
pear
pen
pentagon
pepper
phone-off
phone
pin
plane
play
plus
pocket-knife
power
prev
prize
puzzle
question-circle
question-hexagon
radio
radish
record
recycle
refresh-horizontal
responsive
rotate-left
rotate-right
router
save
scissors
screen
search
send
server
settings-1
settings-2
share
shield-check
shield-warning
shield
shortcut
shrink-diagonal-2
shrink-vertical
shuffle
slash
sort
speaker
spinner
square
star
stop
sun
support
swing
switch-off
switch-on
sync-horizontal
tablet
tag
tea
tent
terminal
text
tool
toy
trend-down
trend-up
triangle
tv
umbrella
unlike
upload
user
video-off
video
volume-1
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volume-off
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ambulance
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heart-line
hospital-1
hospital
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mask
mortar
pharmacy
pill
pyrometer
sperm
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stretcher
surgery
thermometer
tooth
toothbrush
urinary
vaccine
virus
weight
xray


Friends star Jennifer Aniston confesses she took neon sign from Central Perk
The actress gave the sweetest response when asked what she stole from the Friends set after being on the show for 10 years
by Brogan-Leigh HurstJennifer Aniston has confessed she stole a neon light from Central Perk on her last day of filming the hit TV show Friends.
The actress played Rachel Green for 10 years on the iconic sitcom and shared some behind the scenes gossip as she appeared on the Graham Norton Show last night.
She was joined by Reese Witherspoon to promote their new series The Morning Show, alongside British icons Sir Ian McKellen and Dame Julie Andrews.
Graham asked: "Jennifer you took a bit of Friends when you left at the end, didn't you?"
And Jennifer gushed back: "I took all five of them," as the audience burst out with "ahhh".
While it's been 25 years since Friends first hit our screens, Jennifer has maintained a close friendship with her co-stars Courteney Cox, Matt LeBlanc, Matthew Perry, Lisa Kudrow and David Schwimmer.
Jen did admit to taking the light-up neon coffee sign from Central Perk, which now sits in her office.
It comes after the 50-year-old signed up to Instagram and delighted fans with an epic Friends reunion cast snap.
The blonde star selected a selfie for her social media debut that showed her smiling alongside her Friends co-stars - the first ever full reunion snap of the six famous actors.
She playfully captioned the offering: "And now we’re Instagram FRIENDS too. HI INSTAGRAM."
Jennifer decided to write in her bio: "My friends call me Jen."
So far, the age-defying beauty is following 180 people and has racked up a massive 18.1m followers.
Fans of the former wife of Brad Pitt took to the comments to share their excitement of her finally joining the picture sharing app.
One penned: "I love this so much" alongside a crying face.
Another added: "This is a moment!."
Some gushed: "our besties all together!!!!!" and "Oh yeah mama!! Woooohooooo."
Do you have a story to sell? Get in touch with us at<EMAIL_ADDRESS>or call us direct 0207 29 33033


This loops over values. To loop over keys, use "${!array[@]}".
Plus companion warning [[SC2303]]: i is an array value, not a key. Use directly or loop over keys instead.
array=(foo bar)
for i in "${array[@]}"
do
echo "Value is ${array[$i]}"
done
Either loop over values
for i in "${array[@]}"
do
echo "Value is $i"
done
or loop over keys:
for i in "${!array[@]}"
do
echo "Key is $i"
echo "Value is ${array[$i]}"
done
ShellCheck found a for
loop over array values, where the variable is used as an array key.
In the problematic example, the loop will print Value is foo
twice. On the second iteration, i=bar
, and bar
is unset and considered zero, so ${array[$i]}
becomes ${array[bar]}
becomes ${array[0]}
becomes foo
.
If you don't care about the key, simply loop over array values and use $i
to refer to the array value, like in the first correct example.
If you do want the key, loop over array keys with "${!array[@]}"
, use $i
to refer to the array key, and ${array[$i]}
to refer to the array value.
If you do want to use values from the arrays as keys in the same array, you can [[ignore]] these messages with a directive:
declare -A fatherOf=(
["Eric Bloodaxe"]="Harald Fairhair"
["Harald Fairhair"]="Halfdan the Black"
["Halfdan the Black"]="Gudrød the Hunter"
["Gudrød the Hunter"]="Halfdan the Mild"
)
# shellcheck disable=SC2302,SC23203
for i in "${fatherOf[@]}"
do
echo "${fatherOf[$i]:-(missing)} begat $i"
done


[gecode-users] Extra information during propagation
Christian Schulte
cschulte at kth.se
Wed Jan 21 10:39:22 CET 2009
Hi Vincent,
basically you want to have equivalence (or even equality) reasoning in
Gecode. Gecode has been explicitly designed to not deal with it. Prior
systems (logic programming based systems such as SICStus, Eclipse, Mozart,
...) do have equality reasoning (but typically with lots of restrictions if
not bugs). However my own experience has been that it is not useful enough
(from a general perspective) and the chosen implementation technology
(maintaining equivalence classes) is totally ill matched to performing
propagation efficiently.
What would be possible on a general level is to use a substitution based
approach. We know how to do it but it is a lot of work.
Okay that was just the background info and the answer that there is no
general way and just fixing something in Gecode will not do the trick.
Then what you might want to do is to define a new type of variables yourself
that just extends Gecode variables by an additional level of indirection to
do equivalence reasoning.
Hope that helps
Christian
--
Christian Schulte, www.ict.kth.se/~cschulte/
-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Vincent Barichard
Sent: Tuesday, January 20, 2009 12:46 PM
To: users at gecode.org
Subject: [gecode-users] Extra information during propagation
Hi,
I try to make a propagator that needs more extra information during
propagation, but I'm not sure of how to proceed.
For example :
At the begining of the propagation I have a propagator named p2 which
reduces
domains of a,c,d:
p2(a,c,b)
After some propagation steps, a new propagator is posted (during the
propagation). This new propagator ensures that: a == b
For my problem, the equality of domains is no sufficient, I really needs to
know
in the propagation that 'a' is equivalent to 'b'.
Of course p2 is scheduled, but p2 also needs to know that 'a' and 'b' are
equals to reduce the domain of 'c'. So I want to rewrite p2 by replacing 'a'
with 'b'. It consists in subsuming p2 and posting the new propagator
p2'(b,c,b) .
I think about two ways of doing this :
First way:
When the propagator 'a == b' is posted (subscribed), it rewrites all the
propagators which can deal with the equality of two variables 'a' and 'b'.
But
I needs to know the class of the propagator (only some propagators will be
able to be rewritten). Is there a way to know (properly) the kind (class) of
a
propagator?
Second way:
A new ModEvent will be emitted during propagation when two variables are
equals. Propagators will deal with this event and will rewrite themselves
(subsume + post). But during Propagation, extra information is needed (to
know
with which variable the equality has been found). So I think about advisors
and read the article "Advisors for Incremental Propagation" but it is said
that the result of propagation is independent of the state. The problem is
that if the extra information is not provided, the result of propagation
will
be different. Indeed, if the propagator doesn't know that 'a == b', it will
lead to less reducing. Can I still use advisors?
I don't want to make a quick dirty hack (by changing the GeCode code). So
how
do you proceed if you will have to deal with it?
I hope that I made myself clear enough.
I will really appreciate any advice. Thanks.
Best regards,
Vincent Barichard
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AMISTAD (DreamWorks) Starring: Djimon Hounsou, Matthew McConaughey, Anthony Hopkins, Morgan Freeman, Nigel Hawthorne, Pete Postlethwaite, Stellan Skarsgaard. Screenplay: David Franzoni. Producers: Debbie Allen, Steven Spielberg and Colin Wilson. Director: Steven Spielberg. MPAA Rating: R (nudity, violence, adult themes) Running Time: 153 minutes. Reviewed by Scott Renshaw.
AMISTAD is no SCHINDLER'S LIST. Think it unfair if you must, but Steven Spielberg is going to face comparisons like that for the rest of his film-making career. In the case of AMISTAD, those comparisons are going to be even harder to avoid, given the proximity in time (it's Spielberg's first "serious" film since the Oscar-winning SCHINDLER in 1993), the subject matter (the trials of an oppressed people) and the situational familiarity (if it's the December after a Spielberg dinosaur movie, it must be time for a Spielberg fact-based historical epic). Spielberg may never make another SCHINDLER'S LIST -- even the most successful home run hitter isn't likely to knock _two_ World Series-winning grand slams -- but he did raise his personal bar. Now that we know what he's capable of, we're not going to let him get away with choosing less than stellar material.
AMISTAD is hardly a half-hearted effort; in fact, there are a couple of scenes which rank with Spielberg's best work as a director. It is, however, a piece of material which ends up providing far less impact than it should. The film is based on the true story of an 1840s court case involving 44 black men and women, led by Cinque (Djimon Hounsou), accused of piracy for an uprising against their capters on the Spanish slaving ship "La Amistad." Found off the coast of Long Island by a U.S. Navy ship, the blacks become the subject of an intense and controversial series of legal challenges. Are they the property of the two surviving members of the "Amistad" crew? Are they the property of Queen Isabella (Anna Paquin)? Are they the property of the naval officers who claim salvage rights? Or are they the property of no one, free men illegally captured from their homes in Africa?
It is the latter point which is argued by attorney Roger Baldwin (Matthew McConaughey), assisted by abolitionists Theodore Joadson (Morgan Freeman) and Lewis Tappan (Stellan Skarsgaard), with further assistance from former President John Quincy Adams (Anthony Hopkins). Faced with direct opposition from struggling incumbent President Martin Van Buren (Nigel Hawthorne, looking even more befuddled than he did in THE MADNESS OF KING GEORGE) as the case becomes a flashpoint for Southern grumbling over the slavery issue, Baldwin tries to overcome a profound language gap and get Cinque to tell his own story. AMISTAD is at its best when Cinque is telling his story, allowing the electrifying performance of Djimon Hounsou to take center stage. Though he utters only half a dozen English words through the entire film, Hounsou's impassioned work brings to life an intelligent man trying to understand a thoroughly perplexing new world. He is the heart and soul of AMISTAD.
If it had ever been made clear that AMISTAD is Cinque's story, the film could have been a masterpiece. Instead, David Franzoni's script allows too many characters to flirt with the impression that the story is all about them. Freeman, as a former slave turned anti-slavery advocate, somehow gets first billing despite disappearing for most of the film; McConaughey plays his noble lawyer from A TIME TO KILL with mutton chops, but without a sense of what the case means to him; Hopkins' borderline-senile Adams has little to do before delivering his oration before the Supreme Court. Franzoni also tosses off one of the story's most crucial pieces of historical trivia -- that while slavery was still legal in 1839, capturing Africans was not -- as though it were common knowledge. The "Amistad" case was a messy piece of history, but the script only serves to make it messier, obscuring the human drama in a muddle of over-plotting.
When AMISTAD does give the Africans' plight its undivided attention, it's a gripping piece of film-making. As he did with the horror of the concentration camps, Spielberg provides unflinching images of the horrors of slave ships without exploiting those horrors. He also creates a splendid sequence in which one African's Bible lesson to Cinque is cross-cut with one man's struggle of Christian conscience. If only there had been more of those moments, more singularity of purpose, more complexity of character. Spielberg brought in SCHINDLER scribe Steven Zaillian to do some doctoring on the AMISTAD script, but the doctor couldn't turn merely good into great. AMISTAD is a solidly made film. It's just no...well, you know.
On the Renshaw scale of 0 to 10 Schindler's ships: 7.
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I'm currently pursuing 3rd year Computer Science and Engineering in Shri Madhwa Vadiraja Institute of Technology and Management,Bantakal, Udupi.
My aim is to learn new technologies and apply them in real-life situations, and also to achieve skills in the respective field, thereby working for the simultaneous progression of the organization and myself.I strongly believe in accuracy and precision in whatever I do.
I personally follow the Waste Time Wisely rule,by consistently channeling time and energy towards an overarching purpose,my interests include painting
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Playing Instrument(Veena) is my most favorable.
I'm a self-motivated,curious learner,excellant team player,easily Adaptable and time-managable person with a great deal of patience.
University:Visvesvaraya Technological University
B.E in Computer Science and Engineering
July 2018 - July 2022 | CGPA: 8.08(present)
Board:Karnataka State Board of Secondary Education
12th | March 2018 | Percentage: 87%
Board:Karnataka State Board of Secondary Education
10th | March 2016 | Percentage: 82.5%
The project aimed at booking bus ticket in online mode by selecting the required seat by the customer.This was created using MySql and Java.
This project provides information to the student about the companies and training companies arriving the institution for interview,stored by department faculties having a special privilege to update,view and send a mail to any mail. This was created using html,css,js,php and mysql.
This resume is created using html,css.To check on click here


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Edit the “contents.js” file as you like. The “images” folder is referred from the “contents.js”, and you can put image files and other resources in it. The original “contents.js” file is a example of slides and functions.
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Corrupted layout. Please wait for. CSS advices are welcome.
Creator is a Mac user. Anyway, anytime.