黄河远上白云间， 一片孤城万仞山。
Where a yellow river climbs to the white clouds, Near the one city-wall among ten-thousand-foot mountains,
羌笛何须怨杨柳， 春风不度玉门关。
A Tartar under the willows is lamenting on his flute That spring never blows to him through the Jade Pass.


16 Apr 2015
Stranded, part II - The Easter Bunny is an arsonist!
These orthodox Greeks have their own Easter which apparently takes place a week after, well, normal Easter. Since I was going to be stuck on the island until Sunday night, I tried to see as much of the celebrations as possible. In practice, that meant three parts, starting with lots of fire on Good Friday!
After my donkey-themed excursion, the afternoon found me reading - being useless - in the hostel. The charming Finnish gentleman I had met there pointed out that the locals were famous for their Good Friday celebration in the village of Pyrgos. From Google Image Search I knew that this festivity consisted of them decorating all the roofs with candles right after dark. A procession would then head down from the church on the peak of the hill down into town.
Pyrgos was around 6km from our hostel. Of course we would have loved to walk, but with sundown approaching quickly, we’d have to take a cab. Bad luck. The Norwegian we had befriended at the hostel agreed to join us, leaving one seat in the taxi free. In the interest of saving money, we also shanghai’ed two Canadian backpackers (“Oy, there’s going to be fire on a hill. You should come!”).
Approaching Pyrgos, we immediately saw the hilltop sticking out of the landscape. Since the sun was still up and there weren’t too many people around, we decided to walk up to the peak to take a look. As most organically grown Greek towns, the area consisted of houses built on top of and into each other with tiny, narrow walkways and stairs leading through this maze. The closer we got to the peak, the more urgently we were reminded of the storm which whistled around the walls and corners of the tiny houses. Eventually we ascended a stairway and found ourselves on the flat roof right next to the main church. Here, the gusts were so strong that we had trouble standing or walking.
Thinking that maybe, just maybe the wind wasn’t strong enough were we stood, we climbed up to the flat roof of the church on the top of the hill.
I took a few pictures of the sunset but they turned out blurry, since I simply could not stand still in that wind. My Finnish friend did a little better, so I’ll just post his pictures instead (thanks, Jarno!):
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From up there, we also noticed the lights that had been placed on every wall, every roof and every pillar in town. Not candles, as we had imagined, but tin cans filled with wood shavings and candle wax. Keep this in mind, this will get important in a minute!
After sundown we headed back down into town to grab a cup of coffee and observe the procession from the comfort of a bar or restaurant. After finishing a jug of rakomelo (a hot drink made from raki and honey) we got a bit impatient and began to head back up the hill. Still, there weren’t many lights in sight, but a crowd was gathering around the church.
One by one, the lights were lit by local youngster armed with propane torches. The wind, however, had not lessened a bit. If anything, it was stronger than before. Remember those wood shavings in the cans? Soaked in candlewax? The ones set on fire by the local teenagers?
The gusts ripped the burning wood from the cans and sent them flying through the darkness, turning the night into a storm of sparks and light. Dozens, if not hundreds of those cans were lit and with each light, more sparks were sent flying.
The glowing wood was blown from the roofs down the narrow walkways and stairs. Since the wind sent them flying so fast, the sparks didn’t touch anything for long enough to pose an actual danger to anyone. They sure enough made for an amazing sight though!
After a few minutes, I braved the storm for long enough to climb back up on the roof of the main church. The experience up there was fantastic: The church bells rang out next to me, barely audible of the deafening roar of the wind. I looked down into the town with more and more spots of light appearing in the darkness below every minute. And over all of this, showers of sparks blew past me like massive waves, engulfing the church and the spot I was standing in. It was like standing in the middle of a firestorm. I remember grinning like a maniac.
Dutifully, I attempted to take a few pictures, but I don’t think they really reflect the sheer intensity of those moments up on that church roof:
Include file ‘image.html img=”pics/IMG_20150410_205155_scaled.jpg” title=”Image” caption=”” url=”http://www.escapingsloth.com/pics/fullsize/IMG_20150410_205155.jpg”’ contains invalid characters or sequences
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Eventually, I decided to climb down from there. The wind threatened to throw me on my face, off the roof or both. Instead I joined the others in front of the church and we headed back down through the town. Not before taking a few more pictures near the top though:
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Afterwards we navigated the labyrinth of passages and stairs. We also had the decidedly weird experience of walking right through a choir of priests and the congregration. As in: right between the priest and the singing congregation. “Excuse me - so sorry - my bad!”
Eventually we reached the foot of the hill. As we looked back, we saw the very image that countless photographers had captured before us: Pyrgos, on the hill, as a sea of shimmering lights in the dark.
Include file ‘image.html img=”pics/IMG_20150410_213237_scaled.jpg” title=”Image” caption=”” url=”http://www.escapingsloth.com/pics/fullsize/IMG_20150410_213237.jpg”’ contains invalid characters or sequences
It took us a while to pull ourselves away from this sight. We weaseled our way through what had become dense traffic at the foot of the hill and called a cab. After finding our cab and being stuck in traffic for the better part of 20 minutes, we finally managed to drive back to Fira, the brightly lit hill left behind us.
Until next time,
Arne


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Dietary
Bring a large pan of salted water to the boil. Add the pasta and cook according to packet instructions.
Meanwhile, bring a separate pan of salted water to the boil. Add the broccoli and boil for 2-3 minutes, until just tender. Drain the broccoli into a colander.
Heat a frying pan over a medium heat. Add the butter and fry until it melts and begins to turn golden-brown.
Add the almonds and breadcrumbs and heat until the breadcrumbs are golden-brown.
Add the broccoli and stir well to coat in the almonds and breadcrumbs.
Add the lemon juice and season, to taste, with salt and freshly ground black pepper.
Add the cooked penne pasta and mix together well.
To serve, spoon equal portions of the pasta and broccoli into bowls and garnish with freshly grated parmesan.


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Abyssal Saintess Elcadia:
I'm suprised, and not in a good way. What happened to you? Are you better now? Ready to show me your true skills?
I'm always ready. I had something in my eye last time.


Bootstrap is the most popular HTML, CSS, and JavaScript framework for developing responsive, mobile-first websites. Bootstrap is completely free to download and use!
A lightweight, flexible component that can optionally extend the entire viewport to showcase key marketing messages on your site.
A lightweight, flexible component that can optionally extend the entire viewport to showcase key marketing messages on your site.
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Assigned to: {{referral.assigned}}
Location: {{referral.locate}}
Date and Time of Appointment: {{referral.dateVisit}}
Patient Contact Info: {{referral.contactClient}}
Description/Background of Patient: {{referral.description}}
History of Patient: {{referral.history}}
Comments: {{referral.comments}}
Done


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I'm a self-proclaimed geek, but I still know how to have a good time. When I'm not writing code or doing school work, I enjoy playing tennis, reading articles, spending time with friends, and listening and/or dancing to music.
Winner at PilotPhilly hackathon at UPenn (Fall 2013). Subsequently, invited on all expenses paid trips to various other intercollegiate hackathons, including MHacks, HackTech, PennApps, BoilerMake, HackBCA, and more. You'll often find me rapidly writing programs to make life easier.
Captain of Math Team at my high school; President of Math Honors Society; Top Scorer at various math and logic based competitions. I'm a math geek - this year I am taking AP Calculus BC and am especially looking forward to the math courses I'll be taking next year - Linear Algebra and Multivariable Calc.
Winner of science fair for Mathematic Modeling of Effect of 2008 Downturn in Economy on the Average Retirement Plan. National winner two years in a row of National Mergers and Acquisitions Competition. I'm also an avid investor - my favorite sectors in the market for 2013-2014 are finance, industrials, and energy.
Region 9 President of the 12 major high school FBLA Chapters in Chester County, PA. Invited to State Regional Conference for the past 2 years, placing highly in Business Math and Business Calculations. This year, I was once again invited for Business Presentations. Startups fascinate me.


There are many areas where this implementation can be improved.
If you have any questions or suggestions, please comment in the G+ community or contact<EMAIL_ADDRESS>One more page and you're done!
There are many areas where this implementation can be improved.
If you have any questions or suggestions, please comment in the G+ community or contact<EMAIL_ADDRESS>One more page and you're done!


This months scheduled activities. If you have qustions please call.
Events Planner<PHONE_NUMBER>
50 N Medical Drive Street, Salt Lake City, UT 84112
(800)555-1212
Please contact us with any questions you might have about upcoming events, our hospitals, or our treatment solutions.
Email Us<EMAIL_ADDRESS>hospital replacement project at Utah Valley Hospital (formerly Utah Valley Regional Medical Center) is a major construction project to replace more than half of the building space on the current campus.
These buildings, which are in use during all hours each day of the year, are nearing the end of their use and will be replaced by two large buildings — a new patient tower and an outpatient building. Once completed, patients will receive treatment in one of the most technologically advanced and modern hospitals in the country.
The project, which is expected to be completed in 2019, will revitalize the look of the campus and will allow for improvements in technology, the progression of patient treatment from one care area to another, increases in patient room size and much more.
1034 N 500 W, UT 84604<PHONE_NUMBER>
The cranes and construction crews are gone, and in their place is the new, Memorial Hermann Pearland Hospital – a 250,000 square-foot, state-of-the-art healthcare facility that ushers in a higher level of quality and safe care to the Pearland community.
The hospital, along with the Convenient Care Center and adjoining medical office buildings, make up a 40-acre, comprehensive medical campus. Memorial Hermann Pearland becomes the 14th hospital in the Memorial Hermann Health System.
“This is an exciting time for us as we open our hospital and I say our hospital because many of our employees, including myself, live in Pearland,” says Mario Garner, Sr. Vice President and CEO, Memorial Hermann Pearland. “We want Memorial Hermann Pearland to quickly become the hospital of choice for the residents of Pearland, Alvin, Angleton, Manvel and surrounding communities.”
With its 64 beds, Memorial Hermann Pearland offers a number of high-quality services and specialties, including orthopedics and sports medicine, neurology, general surgery, heart and vascular, labor and delivery, gastroenterology and urology.
As an added amenity, Pearland Café, located inside Memorial Hermann Pearland, is open to the public serving breakfast from 7:00 a.m. until 9:30 a.m. and lunch from 11:00 a.m. until 2:00 p.m. daily. While at the hospital, patients and guests can also view Pearland’s historical timeline located just off the hospital’s main lobby. The timeline, which was developed in coordination with the Pearland Historical Society, illustrates the history of Pearland dating back to the early 1800s.


My name is Gregg von Bushberger. I am a Baltimore-based film editor with over 20 years of experience in the Advertising/Marketing field. I am trained in Final Cut Pro, Adobe Premiere, and Adobe After Effects
I began learning to code in 2019 in an effort to broaden my skills and add more value to my existing clients while also using my new skills to accumulate more business.
My goal is to work with a team of great people that want to create unique content accross all fields of multi-media.


LDD
Section: Linux Programmer's Manual (1)Updated: 2000-10-30
Index Return to Main Contents
NAME
ldd - print shared library dependenciesSYNOPSIS
ldd [OPTION]... FILE...DESCRIPTION
ldd prints the shared libraries required by each program or shared library specified on the command line.OPTIONS
- --version
- Print the version number of ldd.
- -v --verbose
- Print all information, including, for example, symbol versioning information.
- -u --unused
- Print unused direct dependencies. (Since glibc 2.3.4.)
- -d --data-relocs
- Perform relocations and report any missing objects (ELF only).
- -r --function-relocs
- Perform relocations for both data objects and functions, and report any missing objects or functions (ELF only).
- --help
- Usage information.
NOTES
The standard version of ldd comes with glibc2. Libc5 came with an older version, still present on some systems. The long options are not supported by the libc5 version. On the other hand, the glibc2 version does not support -V and only has the equivalent --version.The libc5 version of this program will use the name of a library given on the command line as-is when it contains a aq/aq; otherwise it searches for the library in the standard locations. To run it on a shared library in the current directory, prefix the name with "./".
BUGS
ldd does not work on a.out shared libraries.ldd does not work with some extremely old a.out programs which were built before ldd support was added to the compiler releases. If you use ldd on one of these programs, the program will attempt to run with argc = 0 and the results will be unpredictable.
SEE ALSO
ld.so(8), ldconfig(8)COLOPHON
This page is part of release 3.22 of the Linux man-pages project. A description of the project, and information about reporting bugs, can be found at http://www.kernel.org/doc/man-pages/.
Index
This document was created by man2html, using the manual pages.
Time: 05:29:05 GMT, December 24, 2015


This chapter presents the instructions to install a complete GNOME-3.12 desktop environment. The order of the installed packages follows the build order defined by the GNOME development team and has been thoroughly tested by the BLFS team. You need to be building GNOME-3.12 on top of a system running Systemd.
The installation of GNOME-3.12 is a large undertaking and one we would like to see you complete with the least amount of stress.
To install GNOME as your desktop of choice, it is recommended that
you install using --prefix=/usr
.
If your system was completely built per LFS and BLFS instructions, you have a very good chance of using GNOME-3.12 after your first installation. If you are a typical LFS user, you have made modifications to the instructions along the way knowing that you have to take those modifications into account on future installations. You should have no problems integrating GNOME-3.12 into your unique setup, but you will have to install well over 50 packages before you can run GNOME through any testing (assuming your windowing system is preinstalled and tested). You should anticipate that you will be rebuilding GNOME at least once to make adjustments for your setup.
Last updated on 2014-07-22 07:44:40 -0700


About: The story of a cyborg sent past in time.
Duration: 1 hour 48 minutes
Genre: Sci-fi, Action
Release Date: 26 October 1984
IMDb: 8.0
About: A marine on an alien planet.
Duration: 2 hours 42 minutes
Genre: Action, Adventure, Sci-fi, Fantasy
Release Date: 18 December 2009
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About: Avengers assemble to defeat Thanos.
Duration: 2 hours 36 minutes
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Duration: 2 hours 13 minutes
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About: Thor fights his evil sister, Hela, and protects Asgard from her.
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About: The Justice League assembles to defeat Darkseid.
Duration: 2 hours
Genre: Action, Sci-Fi, Fantasy
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IMDb: 6.8


My Favorite Places
Backpacking Destinations
The Sawtooth Mountain Range
The Wind River Range
The Beartooth Mountains
Paria River Canyon
Sierra Nevada Mountains


My work so far
The basics
I know it may seem empty but part of my work is the website you have been navigating! I am in the process of becoming a computer software engineer. I have only have learned a few skills so far but I am going to eventually have seven programming languages when I am done.
Here is my skills list
- The command line
- HTML (Hypertext Markup Language)
- Git (Version control)
- CSS (Cascading style sheet)
- Javascript
- SQL
- Python
All of the skills I learned went in a step format
- Theory
- Basic commands
- practice and hands on
- Project
I am in a class called CSET at Thaddeus Stevens College of technology. The class teaches web develpment, code, and much more. For all the projects referenced below check them out on my github here for my github
Command-Line
The Command-Line is the first basic skill I adopted as a software engineer. I learned how to navigate my computer to the fullest extent. File management and a plethora of command-line commands were the bulk of my command line experience. Other skills include practice with file paths navigation, bug fixing, and proper storage habits.
HTML and CSS
Html was the first web-based skill I learned in my software development education. Shortly after my professor introduced HTML, CSS was the next step. I was assigned various exercises such as a remix meaning merging several websites to create a completely different website. Some of the HTML projects I completed include semantic and syntax tests and labs which have given me some insight into the flow of HTML. In addition to my experience with tests and exercises, I have created two websites from scratch. One is the the website you are one and another an art website.
Git Version Control
Another skill I have learned is Git version control. I was taught Git due to its prominent popularity and uses in the workforce. Git practice with merge conflicts, branches, basic commands, GitHub, and many more practical skills. Every project that I work on to this day includes git and the web platform GitHub.
JavaScript
JavaScript was my initial web development language. I was taught based on the eloquent JavaScript book. I learned valuable skills such as data types, operators, functions, practical uses and finally the document object model (DOM). The knowledge I gathered allowed me to create a JavaScript maze game with another peer. Some other projects I have worked on include exercises and quizzes. For example, we completed popular software problems such as looping a triangle, bean-counting and recreating math minimum. In addition, I have also begun to learn JSON and higher operations with JavaScript like higher-order functions or animations.
Python
The second language I am currently learning is Python. Since I have software language experience the basics of Python were easily surpassed. As of today I am being taught classes in Python. Some of the projects I have already completed include function practice, importing files, entry skills with operators, data types and a start to my own python command-line game. In the upcoming weeks, I will be taught much more complex skills with Python and will update this website accordingly.
SQL
SQL is a database language for managing tasks on the 'backend' of development. For the most part, SQL is my first backend language. I am absorbing skills like table creation, database management system practice and detailed exercises with SQL commands. However, I have just scratched the surface with SQL, my class has much more to teach me in the upcoming months.
Other Works
Not only am I learning to become a software engineer, I am being taught other valuable skills along with development. The skills include microsoft office, public speaking, proffessional wrinting, and necessary mathamatics. Moreover, I know how to use and manage window, mac and linux computers. I know how to create proffessional documents such as memos, essays, speeches, and evaluations. My classes have taught me to be comfortable around a crowd as well as to work with teams.
Upcoming
Upcoming projects include more detail into Python and SQL. To build a massive interactive website with 3 to 4 other peers, based on our school portal. Furthermore, I will also have security experience which will teach me to have secure habits and to seek as well as fix any bugs or security risks I can find. The upcoming class will assist me in spotting weaknesses in website security and improve over bug fix performance.


twilio.rest.insights.v1.call package¶
Submodules¶
twilio.rest.insights.v1.call.event module¶
This code was generated by / _ _ _| _ _
(_)/(_)(_|/| |(/_ v1.0.0 / /
-
class
twilio.rest.insights.v1.call.event.
EventInstance
(version, payload, call_sid)[source]¶ Bases:
twilio.base.instance_resource.InstanceResource
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
class
Level
[source]¶ Bases:
object
-
DEBUG
= 'DEBUG'¶
-
ERROR
= 'ERROR'¶
-
INFO
= 'INFO'¶
-
UNKNOWN
= 'UNKNOWN'¶
-
WARNING
= 'WARNING'¶
-
-
class
TwilioEdge
[source]¶ Bases:
object
-
CARRIER_EDGE
= 'carrier_edge'¶
-
CLIENT_EDGE
= 'client_edge'¶
-
SDK_EDGE
= 'sdk_edge'¶
-
SIP_EDGE
= 'sip_edge'¶
-
UNKNOWN_EDGE
= 'unknown_edge'¶
-
-
account_sid
¶ Returns: The account_sid Return type: unicode
-
call_sid
¶ Returns: The call_sid Return type: unicode
-
edge
¶ Returns: The edge Return type: EventInstance.TwilioEdge
-
group
¶ Returns: The group Return type: unicode
-
level
¶ Returns: The level Return type: EventInstance.Level
-
name
¶ Returns: The name Return type: unicode
-
timestamp
¶ Returns: The timestamp Return type: unicode
-
class
-
class
twilio.rest.insights.v1.call.event.
EventList
(version, call_sid)[source]¶ Bases:
twilio.base.list_resource.ListResource
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
get_page
(target_url)[source]¶ Retrieve a specific page of EventInstance records from the API. Request is executed immediately
Parameters: target_url (str) – API-generated URL for the requested results page Returns: Page of EventInstance Return type: twilio.rest.insights.v1.call.event.EventPage
-
list
(edge=<object object>, limit=None, page_size=None)[source]¶ Lists EventInstance records from the API as a list. Unlike stream(), this operation is eager and will load limit records into memory before returning.
Parameters: - edge (EventInstance.TwilioEdge) – The edge
- limit (int) – Upper limit for the number of records to return. list() guarantees never to return more than limit. Default is no limit
- page_size (int) – Number of records to fetch per request, when not set will use the default value of 50 records. If no page_size is defined but a limit is defined, list() will attempt to read the limit with the most efficient page size, i.e. min(limit, 1000)
Returns: Generator that will yield up to limit results
Return type:
-
page
(edge=<object object>, page_token=<object object>, page_number=<object object>, page_size=<object object>)[source]¶ Retrieve a single page of EventInstance records from the API. Request is executed immediately
Parameters: - edge (EventInstance.TwilioEdge) – The edge
- page_token (str) – PageToken provided by the API
- page_number (int) – Page Number, this value is simply for client state
- page_size (int) – Number of records to return, defaults to 50
Returns: Page of EventInstance
Return type:
-
stream
(edge=<object object>, limit=None, page_size=None)[source]¶ Streams EventInstance records from the API as a generator stream. This operation lazily loads records as efficiently as possible until the limit is reached. The results are returned as a generator, so this operation is memory efficient.
Parameters: - edge (EventInstance.TwilioEdge) – The edge
- limit (int) – Upper limit for the number of records to return. stream() guarantees to never return more than limit. Default is no limit
- page_size (int) – Number of records to fetch per request, when not set will use the default value of 50 records. If no page_size is defined but a limit is defined, stream() will attempt to read the limit with the most efficient page size, i.e. min(limit, 1000)
Returns: Generator that will yield up to limit results
Return type:
-
-
class
twilio.rest.insights.v1.call.event.
EventPage
(version, response, solution)[source]¶ Bases:
twilio.base.page.Page
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
get_instance
(payload)[source]¶ Build an instance of EventInstance
Parameters: payload (dict) – Payload response from the API Returns: twilio.rest.insights.v1.call.event.EventInstance Return type: twilio.rest.insights.v1.call.event.EventInstance
-
twilio.rest.insights.v1.call.metric module¶
This code was generated by / _ _ _| _ _
(_)/(_)(_|/| |(/_ v1.0.0 / /
-
class
twilio.rest.insights.v1.call.metric.
MetricInstance
(version, payload, call_sid)[source]¶ Bases:
twilio.base.instance_resource.InstanceResource
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
class
StreamDirection
[source]¶ Bases:
object
-
BOTH
= 'both'¶
-
INBOUND
= 'inbound'¶
-
OUTBOUND
= 'outbound'¶
-
UNKNOWN
= 'unknown'¶
-
-
class
TwilioEdge
[source]¶ Bases:
object
-
CARRIER_EDGE
= 'carrier_edge'¶
-
CLIENT_EDGE
= 'client_edge'¶
-
SDK_EDGE
= 'sdk_edge'¶
-
SIP_EDGE
= 'sip_edge'¶
-
UNKNOWN_EDGE
= 'unknown_edge'¶
-
-
account_sid
¶ Returns: The account_sid Return type: unicode
-
call_sid
¶ Returns: The call_sid Return type: unicode
-
direction
¶ Returns: The direction Return type: MetricInstance.StreamDirection
-
edge
¶ Returns: The edge Return type: MetricInstance.TwilioEdge
-
timestamp
¶ Returns: The timestamp Return type: unicode
-
class
-
class
twilio.rest.insights.v1.call.metric.
MetricList
(version, call_sid)[source]¶ Bases:
twilio.base.list_resource.ListResource
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
get_page
(target_url)[source]¶ Retrieve a specific page of MetricInstance records from the API. Request is executed immediately
Parameters: target_url (str) – API-generated URL for the requested results page Returns: Page of MetricInstance Return type: twilio.rest.insights.v1.call.metric.MetricPage
-
list
(edge=<object object>, direction=<object object>, limit=None, page_size=None)[source]¶ Lists MetricInstance records from the API as a list. Unlike stream(), this operation is eager and will load limit records into memory before returning.
Parameters: - edge (MetricInstance.TwilioEdge) – The edge
- direction (MetricInstance.StreamDirection) – The direction
- limit (int) – Upper limit for the number of records to return. list() guarantees never to return more than limit. Default is no limit
- page_size (int) – Number of records to fetch per request, when not set will use the default value of 50 records. If no page_size is defined but a limit is defined, list() will attempt to read the limit with the most efficient page size, i.e. min(limit, 1000)
Returns: Generator that will yield up to limit results
Return type:
-
page
(edge=<object object>, direction=<object object>, page_token=<object object>, page_number=<object object>, page_size=<object object>)[source]¶ Retrieve a single page of MetricInstance records from the API. Request is executed immediately
Parameters: - edge (MetricInstance.TwilioEdge) – The edge
- direction (MetricInstance.StreamDirection) – The direction
- page_token (str) – PageToken provided by the API
- page_number (int) – Page Number, this value is simply for client state
- page_size (int) – Number of records to return, defaults to 50
Returns: Page of MetricInstance
Return type:
-
stream
(edge=<object object>, direction=<object object>, limit=None, page_size=None)[source]¶ Streams MetricInstance records from the API as a generator stream. This operation lazily loads records as efficiently as possible until the limit is reached. The results are returned as a generator, so this operation is memory efficient.
Parameters: - edge (MetricInstance.TwilioEdge) – The edge
- direction (MetricInstance.StreamDirection) – The direction
- limit (int) – Upper limit for the number of records to return. stream() guarantees to never return more than limit. Default is no limit
- page_size (int) – Number of records to fetch per request, when not set will use the default value of 50 records. If no page_size is defined but a limit is defined, stream() will attempt to read the limit with the most efficient page size, i.e. min(limit, 1000)
Returns: Generator that will yield up to limit results
Return type:
-
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class
twilio.rest.insights.v1.call.metric.
MetricPage
(version, response, solution)[source]¶ Bases:
twilio.base.page.Page
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
get_instance
(payload)[source]¶ Build an instance of MetricInstance
Parameters: payload (dict) – Payload response from the API Returns: twilio.rest.insights.v1.call.metric.MetricInstance Return type: twilio.rest.insights.v1.call.metric.MetricInstance
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twilio.rest.insights.v1.call.summary module¶
This code was generated by / _ _ _| _ _
(_)/(_)(_|/| |(/_ v1.0.0 / /
-
class
twilio.rest.insights.v1.call.summary.
CallSummaryContext
(version, call_sid)[source]¶ Bases:
twilio.base.instance_context.InstanceContext
-
fetch
(processing_state=<object object>)[source]¶ Fetch the CallSummaryInstance
Parameters: processing_state (CallSummaryInstance.ProcessingState) – The processing_state Returns: The fetched CallSummaryInstance Return type: twilio.rest.insights.v1.call.summary.CallSummaryInstance
-
-
class
twilio.rest.insights.v1.call.summary.
CallSummaryInstance
(version, payload, call_sid)[source]¶ Bases:
twilio.base.instance_resource.InstanceResource
-
class
CallState
[source]¶ Bases:
object
-
ANSWERED
= 'answered'¶
-
BUSY
= 'busy'¶
-
CANCELED
= 'canceled'¶
-
COMPLETED
= 'completed'¶
-
FAIL
= 'fail'¶
-
NOANSWER
= 'noanswer'¶
-
RINGING
= 'ringing'¶
-
UNDIALED
= 'undialed'¶
-
-
class
CallType
[source]¶ Bases:
object
-
CARRIER
= 'carrier'¶
-
CLIENT
= 'client'¶
-
SIP
= 'sip'¶
-
TRUNKING
= 'trunking'¶
-
-
account_sid
¶ Returns: The account_sid Return type: unicode
-
call_sid
¶ Returns: The call_sid Return type: unicode
-
call_state
¶ Returns: The call_state Return type: CallSummaryInstance.CallState
-
call_type
¶ Returns: The call_type Return type: CallSummaryInstance.CallType
-
connect_duration
¶ Returns: The connect_duration Return type: unicode
-
created_time
¶ Returns: The created_time Return type: datetime
-
duration
¶ Returns: The duration Return type: unicode
-
end_time
¶ Returns: The end_time Return type: datetime
-
fetch
(processing_state=<object object>)[source]¶ Fetch the CallSummaryInstance
Parameters: processing_state (CallSummaryInstance.ProcessingState) – The processing_state Returns: The fetched CallSummaryInstance Return type: twilio.rest.insights.v1.call.summary.CallSummaryInstance
-
processing_state
¶ Returns: The processing_state Return type: CallSummaryInstance.ProcessingState
-
start_time
¶ Returns: The start_time Return type: datetime
Returns: The tags Return type: list[unicode]
-
url
¶ Returns: The url Return type: unicode
-
class
-
class
twilio.rest.insights.v1.call.summary.
CallSummaryList
(version, call_sid)[source]¶ Bases:
twilio.base.list_resource.ListResource
-
get
()[source]¶ Constructs a CallSummaryContext
Returns: twilio.rest.insights.v1.call.summary.CallSummaryContext Return type: twilio.rest.insights.v1.call.summary.CallSummaryContext
-
-
class
twilio.rest.insights.v1.call.summary.
CallSummaryPage
(version, response, solution)[source]¶ Bases:
twilio.base.page.Page
-
get_instance
(payload)[source]¶ Build an instance of CallSummaryInstance
Parameters: payload (dict) – Payload response from the API Returns: twilio.rest.insights.v1.call.summary.CallSummaryInstance Return type: twilio.rest.insights.v1.call.summary.CallSummaryInstance
-
Module contents¶
This code was generated by / _ _ _| _ _
(_)/(_)(_|/| |(/_ v1.0.0 / /
-
class
twilio.rest.insights.v1.call.
CallContext
(version, sid)[source]¶ Bases:
twilio.base.instance_context.InstanceContext
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
events
¶ Access the events
Returns: twilio.rest.insights.v1.call.event.EventList Return type: twilio.rest.insights.v1.call.event.EventList
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fetch
()[source]¶ Fetch the CallInstance
Returns: The fetched CallInstance Return type: twilio.rest.insights.v1.call.CallInstance
-
metrics
¶ Access the metrics
Returns: twilio.rest.insights.v1.call.metric.MetricList Return type: twilio.rest.insights.v1.call.metric.MetricList
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summary
¶ Access the summary
Returns: twilio.rest.insights.v1.call.summary.CallSummaryList Return type: twilio.rest.insights.v1.call.summary.CallSummaryList
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-
class
twilio.rest.insights.v1.call.
CallInstance
(version, payload, sid=None)[source]¶ Bases:
twilio.base.instance_resource.InstanceResource
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
events
¶ Access the events
Returns: twilio.rest.insights.v1.call.event.EventList Return type: twilio.rest.insights.v1.call.event.EventList
-
fetch
()[source]¶ Fetch the CallInstance
Returns: The fetched CallInstance Return type: twilio.rest.insights.v1.call.CallInstance
-
links
¶ Returns: The links Return type: unicode
-
metrics
¶ Access the metrics
Returns: twilio.rest.insights.v1.call.metric.MetricList Return type: twilio.rest.insights.v1.call.metric.MetricList
-
sid
¶ Returns: The sid Return type: unicode
-
summary
¶ Access the summary
Returns: twilio.rest.insights.v1.call.summary.CallSummaryList Return type: twilio.rest.insights.v1.call.summary.CallSummaryList
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url
¶ Returns: The url Return type: unicode
-
-
class
twilio.rest.insights.v1.call.
CallList
(version)[source]¶ Bases:
twilio.base.list_resource.ListResource
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
get
(sid)[source]¶ Constructs a CallContext
Parameters: sid – The sid Returns: twilio.rest.insights.v1.call.CallContext Return type: twilio.rest.insights.v1.call.CallContext
-
-
class
twilio.rest.insights.v1.call.
CallPage
(version, response, solution)[source]¶ Bases:
twilio.base.page.Page
PLEASE NOTE that this class contains preview products that are subject to change. Use them with caution. If you currently do not have developer preview access, please contact<EMAIL_ADDRESS>-
get_instance
(payload)[source]¶ Build an instance of CallInstance
Parameters: payload (dict) – Payload response from the API Returns: twilio.rest.insights.v1.call.CallInstance Return type: twilio.rest.insights.v1.call.CallInstance
-


Notebook version:
Authors: Vanessa Gómez Verdejo (vanessa@tsc.uc3m.es), Óscar García Hinde (oghinnde@tsc.uc3m.es), Simón Roca Sotelo (sroca@tsc.uc3m.es), Carlos Sevilla Salcedo<EMAIL_ADDRESS>Throughout this course we're going to work with data consisting of noisy signals, samples from probability distributions, etc. For example, we might need to apply different transformations to our data in order to compute a good predictor.
In this notebook we will learn to use specific tools that will let us load, generate, transform and visualise data. We will expand on the mathematical tools that numpy offers and we will introduce a new library, matplotlib, that will allow us to plot all sorts of graphs from our data.
# Let's import some libraries
import numpy as np
import matplotlib.pyplot as plt
One of the first things we need to learn is to generate random samples from a given distribution. Most things in life come muddled with random noise. A fundamental part of Detection and Estimation is finding out what the properties of this noise are in order to make better predictions. We assume that this noise can be modeled according to a specific probability distribution (i.e: nose generated by a Gaussian dastribution), which in turn allows us to make precise estimations of said distribution's parameters.
In python, random samples can be easily generated with the numpy.random
package. Inside it we can find many usefull tools to sample from the most important probability distributions.
We have common number generator functions:
rand()
: uniformily generates random samples.randn()
: returns samples from the “standard normal” distribution.Or more specific ones:
exponential([scale, size])
: draw samples from an exponential distribution with a given scale parameter.normal([loc, scale, size])
: draw random samples from a normal (Gaussian) distribution with parameters: loc (mean) and scale (standard deviation).uniform([low, high, size])
: draw samples from a uniform distribution in the range low-high.In the following examples we will look at different random generation methods and we will visualize the results. For the time being, you can ignore the visualization code. Later on we will learn how these visualization tools work.
# Random samplig examples
n = 1000 # number of samples
# Sampling from a standard uniform distribution:
x_unif = np.random.rand(n)
fig1 = plt.figure()
plt.hist(x_unif, bins=100)
plt.title('Samples from a uniform distribution between 0 and 1')
plt.show()
# Sampling from a normal distribution:
x_norm = np.random.randn(n)
fig2 = plt.figure()
plt.hist(x_norm, bins=100)
plt.title('Samples from a normal distribution with 0 mean and unity variance')
plt.show()
# Adding Gaussian noise to a linear function:
n = 30
x = np.linspace(-5, 5, n)
noise = np.random.randn(n)
y = 3*x
y_noise = y + noise
fig3 = plt.figure()
plt.plot(x, y, color='black', linestyle='--', label='Clean signal')
plt.plot(x, y_noise, color='red', label='Noisy signal')
plt.legend(loc=4, fontsize='large')
plt.title('Visualization of a noisy data-set')
plt.show()
Note that the random vectors that are being generated will be different every time we execute the code. However, we often need to make sure we obtain the exact same sequence of random numbers in order to recreate specific experimental results. There are essentially two ways of doing this:
numpy.random.seed(int)
. See for yourselves:
# Fixing the random number generator seed:
print("If we don't fix the seed, the sequence will be different each time:\n")
for i in range(3):
print('Iteration ', str(i))
print(np.random.rand(3), '\n')
print("\nHowever, if we fix the seed, we will always obtain the same sequence:\n")
for i in range(3):
print('Iteration ', str(i))
np.random.seed(0)
print(np.random.rand(3), '\n')
Now try to solve the following excersises:
# 1. Generate 1000 samples from a uniform distribution that spans from 2 to 5.
# Print the sample mean and check that it approximates its expected value.
# Hint: check out the random.uniform() function
print('Excersise 1:\n')
# n = <FILL IN>
n = 1000
# x_unif = <FILL IN>
x_unif = np.random.uniform(2, 5, n)
# print('Sample mean = ', <FILL IN>)
print('Sample mean = ', x_unif.mean())
plt.hist(x_unif, bins=100)
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Uniform distribution between 2 and 5')
plt.show()
# 2. Generate 1000 samples from a Gaussian distribution with mean 3 and variance 2.
# Print the sample mean and variance and check that they approximate their
# expected values.
# Hint: check out the random.normal() function. Also, think about the changes you
# need to apply to a standard normal distribution to modify its mean and variande
# and try to obtain the same results using the random.randn() function.
print('\nExcersise 2:\n')
# n = <FILL IN>
n = 1000
# x_gauss = <FILL IN>
x_gauss = np.random.randn(n)*np.sqrt(2) + 3
# print('Sample mean = ', <FILL IN>)
print('Sample mean = ', x_gauss.mean())
# print('Sample variance = ', <FILL IN>)
print('Sample variance = ', x_gauss.var())
plt.hist(x_gauss, bins=100)
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Gaussian distribution with mean = 3 and variance = 2')
plt.show()
# 3. Generate 100 samples of a sine signal between -5 and 5 and add uniform
# noise with mean 0 and amplitude 1.
print('\nExcersise 3:\n')
# n = <FILL IN>
n = 100
# x = <FILL IN>
x = np.linspace(-5, 5, n)
# y = <FILL IN>
y = np.sin(x)
# noise = <FILL IN>
noise = np.random.uniform(-0.5, 0.5, 100)
# y_noise = <FILL IN>
y_noise = y + noise
plt.plot(x, y_noise, color='green', label='Noisy signal')
plt.plot(x, y, color='black', linestyle='--', label='Clean signal')
plt.legend(loc=3, fontsize='large')
plt.title('Sine signal with added uniform noise')
plt.show()
# 4. Generate 1000 samples from a 2 dimensional Gaussian distribution with mean
# [2, 3] and covariance matrix [[2, 0], [0, 2]].
# Hint: check out the random.multivariate_normal() function.
print('\nExcersise 4:\n')
# n = <FILL IN>
n = 1000
# mean = <FILL IN>
mean = np.array([2, 3])
# cov = <FILL IN>
cov = np.array([[2, 0], [0, 2]])
# x_2d_gauss = <FILL IN>
x_2d_gauss = np.random.multivariate_normal(mean=mean, cov=cov, size=n)
plt.scatter(x_2d_gauss[:, 0], x_2d_gauss[:, 1], )
plt.title('2d Gaussian Scatter Plot')
plt.show()
When we work with real data, or even if we generate data following a certain function or random distribution, we often acquire a better understanding by plotting the content of a vector, instead of just looking at a bunch of real numbers. In a plot, we assign each axis a meaning (e.g., y-axis could be a probability, kilograms, euros, etc; and x-axis could be time, index of samples, etc.). It should be clear by now how important data visualization is for us and the people who receive our data. Data analysis wouldn't be Data analysis without a nice visualization.
In Python the simplest plotting library is matplotlib and its sintax is similar to Matlab plotting library. As in Matlab, we can plot any set of samples making use of a lot of features. For instance, we can model the sampling of a continuous signal, we can deal with discrete samples of a signal, or we can even plot the histogram of random samples.
Take a look at the following code we use to plot two different sinusoids:
t = np.arange(0.0, 1.0, 0.05) # Time vector, from 0s to 1s in steps of 0.05s.
a1 = np.sin(2*np.pi*t) # Samples of the first signal.
a2 = np.sin(4*np.pi*t) # Samples of the second signal.
# Visualization
# We can create a figure that will contain our plots.
plt.figure()
# We can plot the two signals in different subplots, as in Matlab.
# First signal
ax1 = plt.subplot(211)
ax1.plot(t,a1)
plt.title('First sinusoid.')
plt.xlabel('t (seconds)')
plt.ylabel('a_1(t)')
# Second signal
ax2 = plt.subplot(212)
ax2.plot(t,a2, 'r.')
plt.title('Second sinusoid.')
plt.xlabel('t (seconds)')
plt.ylabel('a_2(t)')
# We ensure the two plots won't overlap, and finally we show the results on the
# screen.
plt.tight_layout()
plt.show()
Let's analyse how we have created the previous figures and in which things they differ:
'r.'
), the first one will draw the points using the standard blue line. As in Matlab, using lines to plot samples will interpolate them by default. If we don't want Matplotlib to do so, we can specify a different symbol, like dots, squares, etc...Look at the following figure and try to catch which argument and/or piece of code is related with each feature. It's intuitive! You can modify the parameters and see what's the new outcome.
t = np.arange(0.0, 3, 0.05)
a1 = np.sin(2*np.pi*t)+t
a2 = np.ones(a1.shape)*t
plt.figure()
# We are going to plot two signals in the same figure. For each one we can
# specify colors, symbols, width, and the label to be displayed in a legend.
# Use the Matplotlib docs if you want to know all the things you can do.
plt.plot(t,a1,'r--',LineWidth=2, label='Sinusoidal')
plt.plot(t,a2, 'k:', label='Straight Line')
plt.title('Playing with different parameters')
plt.ylabel('Amplitude')
plt.xlabel('Time (seconds)')
# By default, axis limits will coincide with the highest/lowest values in our
# vectors. However, we can specify ranges for x and y.
plt.xlim((-0.5, 3))
plt.ylim((-0.5, 4))
# When plotting more than one curve in a single figure, having a legend is a
# good practice. You can ask Matplotlib to place it in the "best" position
# (trying not to overlap the lines), or you can specify positions like
# "upper left", "lower right"... check the docs!
plt.legend(loc='best')
# We can draw the origin lines, to separate the bidimensional space in four
# quadrants.
plt.axhline(0,color='black')
plt.axvline(0, color='black')
# We can also set a grid with different styles...
plt.grid(color='grey', linestyle='--', linewidth=0.8)
# And specify the "ticks", i.e., the values which are going to be specified in
# the axis, where the grid method is placing lines.
plt.xticks(np.arange(-0.5, 3, 0.5)) # In x, put a value each 0.5.
plt.yticks(np.arange(-0.5, 4, 1)) # In y, put a value each 1.
# Finally, plot all the previous elements.
plt.show()
In just a single example we have seen a lot of Matplotlib functionalities that can be easely tuned. You have all you need to draw decent figures. However, those of you who want to learn more about Matplotlib can take a look at AnatomyOfMatplotlib, a collection of notebooks in which you will explore more in depth Matplotlib.
Now, try to solve the following exercises:
# 1. Generate a random vector x, taking 200 samples of a uniform distribution, defined in the
# [-2,2] interval.
# x = <FILL IN>
x = 4*np.random.rand(200) - 2
# Create a weights vector w, in which w[0] = 2.4, w[1] = -0.8 and w[2] = 1.
# w = <FILL IN>
w = np.array([2.4,-0.8,2])
print('x shape:\n',x.shape)
print('\nw:\n', w)
print('w shape:\n', w.shape)
# 2. Obtain the vector y whose samples are obtained by the polynomial
# w_2*x^2 + w_1*x + w_0.
# y = <FILL IN>
y = w[0] + w[1]*x + w[2]*(x**2)
print('y shape:\n',y.shape)
# 3. You probably obtained the previous vector as a sum of different terms.
# If so, try to obtain y again (and name it y2) as a product of a matrix X and
#a vector w. Then, check that both methods lead to the same result (be careful
# with shapes).
# (hint: w will remain the same, but now X has to be constructed in a way that
# the dot product of X and w is consistent).
# X = <FILL IN>
X = np.array([np.ones((len(x),)), x, x**2]).T
# y2 = <FILL IN>
y2 = X.dot(w)
print('y shape:\n',y.shape)
print('y2 shape:\n',y2.shape)
if(np.array_equal(y,y2)):
print('\ny and y2 are the same, well done!')
else:
print('\nOops, something went wrong, try again!')
# 4. Define x2 as a range vector, going from -1 to 2, in steps of 0.05. Then,
# obtain y3 as w_2*x2^2 + w_1*x2 + w_0 and plot the result using a red dashed line
# (--).
x2 = np.arange(-1,2,0.05)
y3 = w[0] + w[1]*x2 + w[2]*(x2**2)
fig1 = plt.figure()
plt.plot(x2,y3,'r--')
plt.title('y3 = f(x2)')
plt.ylabel('y3')
plt.xlabel('x2')
plt.show()
In the above exercises you have plotted a few vectors which are deterministic, that is, a range or a function applied to a range.
Let's now consider the case of representing random samples and distributions.
If we have an expression to obtain the density of a given distribution, we can plot it in the same way we plotted functions before.
In a more general case, when we only have access to a limited number of samples, or we are interested in sampling them randomly, we usually make use of a histogram.
Consider x
a vector containing samples coming from a 1-dimensional random variable. A histogram is a figure in which we represent the observed frequencies of different ranges of the x
domain. We can express them as relative frequencies (summing up to 1) or absolute frequencies (counting events).
We can adapt the number and size of intervals (called bins) to directly affect the resolution of the plot.
When we have a sufficiently high number of random samples coming from the same distribution, its histogram is expected to have a similar shape to the theoretical expression corresponding to the density of this distribution.
In Matplotlib, we have already plotted histograms, with plt.hist(samples,bins=)
.
Let's see some examples:
# We take samples from a normalized gaussian distribution, and we change
# mean and variance with an operation.
sigma = 4
mn = 5
x_norm = mn + np.sqrt(sigma)*np.random.randn(5000)
# Let's obtain an histogram with high resultion, that is, a lot of bins.
fig1 = plt.figure()
plt.hist(x_norm, bins=100,label='Samples')
plt.title('Histogram with 100 bins')
# With vertical lines, we plot the mean and the intervals obtain summing one
# standard deviation to the mean.
plt.axvline(x=np.mean(x_norm),color='k',linestyle='--',label='Mean')
plt.axvline(x=np.mean(x_norm)+np.std(x_norm),color='grey',linestyle='--',label='Mean +/- std')
plt.axvline(x=np.mean(x_norm)-np.std(x_norm),color='grey',linestyle='--')
plt.legend(loc='best')
plt.show()
# We check that the mean and variance of the samples is aprox. the original one.
print('Sample mean = ', x_norm.mean())
print('Sample variance = ', x_norm.var())
# Now let's plot a low resolution histogram, with just a few bins.
fig2 = plt.figure()
# We can set weights in this way to obtain a normalized histogram, i.e.,
# expressing relative frequencies.
w_n = np.zeros_like(x_norm) + 1. / x_norm.size
plt.hist(x_norm, bins=10,label='Samples',weights=w_n)
plt.title('Histogram with 10 bins')
plt.axvline(x=np.mean(x_norm),color='k',linestyle='--',label='Mean')
plt.axvline(x=np.mean(x_norm)+np.std(x_norm),color='grey',linestyle='--',label='Mean +/- std')
plt.axvline(x=np.mean(x_norm)-np.std(x_norm),color='grey',linestyle='--')
plt.legend(loc='best')
plt.show()
# A different resolution leads to different representations, but don't forget
# that we are plotting the same samples.
print('Sample mean = ', x_norm.mean())
print('Sample variance = ', x_norm.var())
Now it's your turn!
# 1. Obtain x_exp as 1000 samples of an exponential distribution with scale
# parameter of 10.
# x_exp = <FILL IN>
x_exp = np.random.exponential(10,1000)
# 2. Plot the corresponding histogram for the previous set of samples, using
# 50 bins. Obtain the empirical mean and make it appear in the histogram legend.
# Does it coincide with the theoretical one?
#plt.hist(<FILL IN>)
plt.hist(x_exp,bins=50,label="Emp. mean: "+str(np.mean(x_exp)))
plt.legend(loc='best')
plt.show()
Taking into account that the exponential density can be expressed as:
$f(x;\beta) = \frac{1}{\beta} e^{-\frac{x}{\beta}}; x>=0$.
where $\beta$ is the scale factor.
# 3. Fill the variable density using the vector x and apply it the theoretical
# density for an exponential distribution. Then, take a look at the plot. Do the
# histogram and the density look alike? How does the number of samples affect
# the final result?
np.random.seed(4) # Keep the same result
x_exp = np.random.exponential(10,10000) # exponential samples
x = np.arange(np.min(x_exp),np.max(x_exp),0.05)
# density = <FILL IN>
density = (1/10)*np.exp(-x/10)
w_n = np.zeros_like(x_exp) + 1. / x_exp.size
plt.hist(x_exp, weights=w_n,label='Histogram.',bins=75)
plt.plot(x,density,'r--',label='Theoretical density.')
plt.legend()
plt.show()
Once we have learned to generate and plot data, the next thing we need to know is how we can store those results for future usage and, subsequently, how to load them.
Python is a programming language commonly used in the context of data analysis. This implies there is a vast number of libraries and functions to work with data. In our case, we will study how to save your data into mat
or csv
files, although there are some other methods we encourage you to take a look at (pickle
, pandas
, npz
,...).
All of these are most usually combined with dictionaries. Dictionaries are an useful data structure implemented in Python which allows to index its different elements with keys instead of with a range of numbers. This way you can access the different elements on the list using either a number or a string.
# Creating a dictionary with different keys. These keys can be either an
# integer or a string. To separate elements you have to use ','.
my_dict = {'Is she a witch?': 'If.. she... weights the same as a duck... she`s made of wood!', 42: 'Can you repeat the question?'}
print (my_dict)
It works in a similar way to lists, being capable of storing arrays, numbers and strings of diferent sizes. In the case of dictionaries, to access to a certain value you just have to use its key.
# We can add a new key to a dictionary and fill in its value.
# Let's add a list of things that float in water:
my_dict['What floats in water?'] = ['Bread','Apples','Very small rocks','Cider','Gravy','Cherries','Mud']
my_dict['What floats in water?'].append('A duck')
print (my_dict['What floats in water?'])
# Print line by line the elements on the dictionary
print('\nThese are the keys and elements on my list:\n')
for key in my_dict:
print (key,':',my_dict[key])
Let's now try to apply this knowledge about dictionaries with the following exercise:
# 1. Create a dictionary with your name and a colleage's and create a
# dictionary for each of you with what you are wearing. Then print the whole
# list to see what each of you are wearing.
# alumnos = <FILL IN>
alumnos = {'Pedro Picapiedra':{},'Clark Kent':{}}
clothes = ['Shirt','Dress','Glasses','Shoes']
for alumno in alumnos:
print(alumno)
# <SOL>
for element in clothes:
alumnos[alumno][element] = input(element+': ')
print(alumnos)
# </SOL>
Now that we know how to create and work with dictionaries we can start to save these dictionaries into different file types. In order to work with .mat
files, we need to work with the scipy.io
library, which provides us with the functions we need:
scipy.io.savemat([filename,mdict])
: stores the given dictionary in a mat
file with the given file name.
scipy.io.loadmat([filename, mdict=None])
: loads the mat
file with the given file name. If a dictionary is given, it loads the data into it.
# Saving the previous dictionary in a mat file
import scipy.io as sio
sio.savemat('dictionaries_rule.mat', alumnos)
# Load the previously stored mat file
data = sio.loadmat('dictionaries_rule.mat')
print (data.keys())
The csv
(Comma Separated Values) files are one of the most common when working with databases. As stated in its name, these format defines the sepparation between elements in the file by a delimiter, typically the comma. Nevertheless, as this files can be defined using any delimiter, it is recommendable to specify which one you would like to use to avoid errors.
In particular, we are going to work with the functions which allow us to save and load data:
csv.writer([filename, delimiter])
: creates the csv
file with the specified filename.csv.reader([filename, delimiter])
: loads the csv
file with the specified filename.# Saving a csv file with some text in it separated by sapaces
import csv
with open('eggs.csv', 'w') as csvfile:
spamwriter = csv.writer(csvfile, delimiter=' ')
spamwriter.writerow(['Spam'] * 5 + ['Baked Beans'])
spamwriter.writerow(['Spam', 'Lovely Spam', 'Wonderful Spam'])
# Loading the csv file and join the elements with commas instead of spaces
with open('eggs.csv', 'r') as csvfile:
spamreader = csv.reader(csvfile, delimiter=' ')
for row in spamreader:
print (', '.join(row))
Finally, we will see how to work with stored data in Google Colaboratory. First of all, to work with some data you have on your computer you have to upload it first to Google Colab. At the same time, after storing some data on a notebook, you have to download it into your computer before the sesssion execution time runs out or else you would lose it.
To do so, you have to access the menu on your left and go to the tab Files(Archivos)
:
Once there there is press the button Upload(Subir)
to temporarily upload the files to Google Colab:
If you want to download some of the files you have saved, just right click on the file you are interested in and click Download(Descargar)
:
Generar datos siguiendo una distribución, aplicar una trasformación de las muestras y ver la distribución que resulta
Incluir ejemplo con el caso gauss
Incluir ejemplo con dos uniformes, sumarlas y generar una triangular?
''' Summary of loading/save methods
SAVE
1. As far as we know, any Python/Numpy/etc save method will save a file in a
local google colab directory (It can be opened with the arrow at the left of
the notebook). Note that these files are not linked to your Drive account and
they should be downloaded.
2. 'from google.colab import files'. Files.download() will let us save to disk
any file which is in the Python workspace.
3. PyDrive, after authentication, will permit us to create files directly stored
in our google drive accounts.
LOAD
1. In some browsers/OS we can just right click the file in the left local
repository, the one from the first save method. This will download the file to
the user disk.
2. There is a files.upload() method which opens a system window to load files.
3. When the file is stored in Drive, we can make use of its id (how to obtain
it?) to load it using PyDrive.
from google.colab import drive
drive.mount('/gdrive')
!pip install -U -q PyDrive
from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
from google.colab import auth
from oauth2client.client import GoogleCredentials
# 1. Authenticate and create the PyDrive client.
auth.authenticate_user()
gauth = GoogleAuth()
gauth.credentials = GoogleCredentials.get_application_default()
drive = GoogleDrive(gauth)
# PyDrive reference:
# https://gsuitedevs.github.io/PyDrive/docs/build/html/index.html
# 2. Create & upload a file text file.
uploaded = drive.CreateFile()
uploaded.SetContentFile('sines.mat')
uploaded.Upload()
print('Uploaded file with ID {}'.format(uploaded.get('id')))
# 3. Load a file by ID and print its contents.
downloaded = drive.CreateFile({'id': uploaded.get('id')})
#print('Downloaded content "{}"'.format(downloaded.GetContentString()))


Waze Map Editor
Waze is one of the most popular navigation apps in the world. I joined as a contractor who’s in charge of its editor - a tool in which a community of volunteers from all around the world edit the map and provide most of the app’s map data.
Responsibilities
- Product Design
- UX Research
Key Learnings
Working on the Waze map editor was an unusual experience. It's a heavily used product with very invested power users, and in order to get things right, I had to deeply understand their biggest issues and expectations from the product team.
How to approach a redesign
When I joined Waze, it was very clear to the entire team that the editor needs a redesign. There was simply no room for any more new features, and there were many UI issues that were designed years ago and never changed.
The redesign was a big task of over 40 screens and states. We knew we need to build it if we want to be able to build new things upon it.
The initial feedback from the community was mixed. While some editors were happy that we're finally changing things, some complained about things like screen space, contrast and more.
This made us get back to the editing desk, and with a few simple changes like background-color change, spacing fixes, new features and performance improvement the new UI was finally adopted and implemented to everyone.
How to talk to the users
It took me a few months to really ‘see’ the people I’m designing for.
It really bothered me how outdated the website was, so I spent a lot of time on aesthetics. The team supported me and we shipped the redesign in 2 months, but instead of getting praises from the community, I got a lot of feedback about things I didn’t see as problems.
After this 'rough start' I started talking to the editors more regularly, read in their forums, and asked them to send me long recordings of them editing the map. This helped me really understand how they see the platform in their eyes.
For them, ‘good UX’ is a fast and functional interface, function over form.
When I changed my approach, it led to much more positive comments from our users, as I solved actual issues and designed things that saved them time and effort.
Spotlight Project #1: Lane Guidance
Collaborating with different stakeholders to map the lanes of the entire world
Lanes were one of the most requested features people wanted from Waze. To add lanes into the app, Waze needed its community to regularly fill in and maintain the lanes of each road in the world.
I worked with our developers to find the best solution, defined the right information structure of lanes as part of our existing database, and regularly asked for feedback from our power users to make sure the solution is the right one for our community.
The lanes feature in the mobile app was implemented after I no longer worked in Waze, and is slowly being rolled to more users.
The main design challenge was for the app to be able to ‘predict’ the best lane, according to the next 2-5 turns the driver needs to make. We solved it by using the junction feature that already existed.
The responses from the community were very positive.
The feature was immediately adopted by the community and even received its own documentation in the Wazeopedia.
Spotlight Project #2: Map Legend
To help the editors deal with all the changes, I’ve designed a fully responsive map legend. The legend shows all of the icons on the map, the editor symbols, road colors, and different types of map problems/update requests.


SimpleAuth - Introduction
Simpleauth is, as its name implies, a simple authentication system which is included in the Auth package. Besides being a working Auth implementation, it is also an example for other Auth drivers. You can use this as a reference when building your own driver.
Auth setup
Configuration starts with telling the Auth package that you are going to use the Simpleauth driver. This is done through the auth.php configuration file. A default file is provided in the Auth package. You should copy this file to your app/config folder before making any changes. The default file is already configured for the Simpleauth package. You will find an explaination of this config file here.
After you have done this, you can choose to autoload the package through the always_load section of the app/config/config.php.
ACL's
SimpleAuth comes with an ACL driver that supports the following ACL structure:
- Every user is a member of one, and exactly one, group
- Every group has zero or more roles assigned to it
- Every role can have zero or more rights assigned to it
When checking for access, you specify the required access as either role.right
when you want to check for
a single right, or role.[right,right]
when you want to check for multiple rights at once. This is an AND check,
so when you specify multiple rights, the user must have ALL of them assigned to be granted access.
Configuration
The Simpleauth authentication system is configured through a configuration file, not suprisingly called 'simpleauth.php'. A default file is provided in the Auth package. You should copy this file to your app/config folder before making any changes.
The following configuration values can be defined:
| Param | Type | Default | Description |
|---|---|---|---|
| db_connection | string |
|
Name of the database connection to use. This should match the definition in your applications db.php configuration file. Set it to null to use the default DB instance. |
| table_name | string |
|
Name of the users table to use. |
| table_columns | array |
|
List of columns to select from the users table, or '*' to select all columns. You have to at least include 'username', 'password', 'email', 'last_login', 'login_hash', 'group' and 'profile_fields'. |
| guest_login | boolean |
|
If true a dummy 'guest' user will be created if no one is logged in. This allows you to use the group and acl drivers even when no one is logged in. |
| remember_me | array |
|
Configuration for the Simpleauth 'remember_me' functionality |
| multiple_logins | boolean |
|
If true multiple concurrent logins of the same user are allowed. If false, when a user logs in, any previous login will be cancelled. Note that enabling this will disable some login session hijacking measures! |
| groups | array |
|
Defined groups, to be used by the SimpleAuth groups driver. See the default configuration file for an description of the groups array structure. |
| roles | array |
|
Defined roles, to be used by the SimpleAuth acl driver. See the default configuration file for an description of the roles array structure. |
| login_hash_salt | string |
|
To make the passwords used by the SimpleAuth drivers extra secure, a salt value is used when hashing the passwords to store them into the database. Make sure you change this default to a very random string! To hash passwords, SimpleAuth uses PBKDF2, a very secure hashing mechanism. |
| username_post_key | string |
|
Name of the input field on the login form that contains the username. |
| password_post_key | string |
|
Name of the input field on the login form that contains the password. |
If you want to use the 'remember-me' functionality, make sure you have a valid Crypt configuration, as it uses an encrypted cookie to store the user information to be remembered.
Database table
SimpleAuth relies on a single table. The Auth package contains the required migration files to create this table.
Just run oil refine migrate --packages=auth
to have the table created for you.
Example
This is a sample login action:
public function action_login()
{
$data = array();
// If so, you pressed the submit button. Let's go over the steps.
if (Input::post())
{
// Check the credentials. This assumes that you have the previous table created and
// you have used the table definition and configuration as mentioned above.
if (Auth::login())
{
// Credentials ok, go right in.
Response::redirect('success_page');
}
else
{
// Oops, no soup for you. Try to login again. Set some values to
// repopulate the username field and give some error text back to the view.
$data['username'] = Input::post('username');
$data['login_error'] = 'Wrong username/password combo. Try again';
}
}
// Show the login form.
echo View::forge('auth/login',$data);
}


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Arrow deserializer to deserialize arrow buffer for Scala/Java frond end The frontend will get Array of data and Array of shape and then make string based on them
An ArrowSerializer is an instance to handle Arrow serialization of a Tensor Mulitple Tensor output, aka, Table, is processed by object ArrowSerializaer which construct multiple ArrowSerializer
Wrap class ArrowDeserializer to deserialize base64 string to Array of (dataArray, shapeArray)
Object ArrowSerializer wraps the operations in class ArrowSerializer and could get either Tensor or Table and serialize it to array of byte


This is the documentation for the version of TaskForest you have
installed on this machine.
You can always access the latest version of the TaskForest
Documentation at the TaskForest
web site. You can also access the documentation for the version
you have installed by running perldoc TaskForest
on the
command line.


TSX dips as pot stocks offset lift from trade deal hopes
by ReutersCanada’s main stock index fell on Friday in contrast to its U.S. counterparts, as losses in cannabis stocks countered a broader lift to sentiment from optimistic tones on trade talks from the United States and China.
* At 09:43 a.m. ET (14:43 GMT), the Toronto Stock Exchange’s S&P/TSX composite index was down 11.85 points, or 0.07%, at 16,987.34.
* Wall Street advanced as U.S. President Donald Trump told Fox News that a trade deal with China was potentially very close.
* Beijing had said earlier it wanted to work out an initial agreement with Washington, following reports that a truce could be delayed to 2020.
* Seven of the index’s 11 major sectors were lower, led by a near 4% drop in healthcare stocks.
* Hexo Corp dropped 6.8%, the most on the TSX, while the second biggest decliner was Cronos Group Inc , down 5.7%.
* The materials sector, which includes precious and base metals miners and fertilizer companies, lost 0.1% while the industrials sector fell 0.3%.
* The energy sector climbed 0.5% as oil prices held near two-month highs.
* U.S. crude prices were down 0.2% a barrel, while Brent crude was unchanged.
* On the TSX, 133 issues were higher, while 92 issues declined for a 1.45-to-1 ratio favoring gainers, with 30.66 million shares traded.
* The largest percentage gainers on the TSX were Ballard Power Systems, which jumped 3.5% and ARC Resources Ltd , which rose 2.8%.
* The most heavily traded shares by volume were Husky Energy , Manulife Financial Corp and Aurora Cannabis Inc.
* Eight stocks on the TSX posted new 52-week highs and no new low.
* Across all Canadian issues there were 24 new 52-week highs and five new lows, with total volume of 44.49 million shares.
(Reporting by Agamoni Ghosh)


This is an example of a visualization of a network of connections. It demonstrates some of the advantages of an interactive visualization for complex data over a simple image. You will notice on the figure that indeed the regions of the brain are very well connected to each other. Although interesting, it can be difficult for a non-expert to find information on this graph. Among the interesting thing to notice:
The size of the nodes is related to the degree (number of connections). The reader can immediately spot the central regions, connected to many parts of the brain.
Additional links are provided in the following, to filtered data, with less links. Pattern can be more easily spotted.
The diffusion MRI technique is a mean to probe the quantity of neuronal fibers between different regions of the brain. These fibers, located in the white matter, are bundles of thousands of axions and are the "communication highways" between brain regions.
In the following figure, each node is a brain region of the Desikan-Killiany Atlas. Each vertex illustrates the connection between two brain regions. The node haven't been placed according to their spatial coordinates on the brain. They are free to move, providing they follow some physical rules given by the force layout.
We analyse here the brain connections provided on the website: http://pitgroup.org/connectome/.
It is based on the following work:
Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz, The Budapest Reference Connectome Server v2.0, Neuroscience Letters, Vol. 595 (2015), Pages 60-62, http://dx.doi.org/10.1016/j.neulet.2015.03.071.
Balázs Szalkai, Csaba Kerepesi, Bálint Varga, Vince Grolmusz, Parameterizable Consensus Connectomes from the Human Connectome Project: The Budapest Reference Connectome Server v3.0, , Cognitive Neurodynamics, (2016), http://dx.doi.org/10.1007/s11571-016-9407-z.
In their work the authors unified the connectomes of 477 people (computed from MRI datasets of the Human Connectome Project) into a reference brain graph.
One can drag nodes inside the application and see the recombination of the graph. In addition, putting the mouse over a node will highlight its connections. A variant of this graph were nodes can have fixed positions is available on this page. Versions of the graph with less connections are given here: 2 regions are connected if at least 400 over the 477 patients have these regions connected and here: 2 regions are connected if at least 200 over the 477 patients have these regions connected.
Color code: Right hemisphere Left hemisphere Brain stem. The orange circled nodes belongs to the subcortical area (or the brain stem) the rest is in the cortex.
The locations of the regions on the brain are given in the following image. The color code is different. The additional regions not represented in the image corresponds to the inner brain region (subcortical) and the brainstem.


Inverted Axis
Legend
Series1
Series2
Gradient
Legend Shadow
Legend at left
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Engelsk B
Ny ordning
kl. 09.00-14.00
Vejledning til opgavesættet
| Du skal besvare følgende opgaver: | |
|
|
| Tekster til assignment 5: | |
| 5A – Fiction: | “Bone Deep”, a short story by Martin Malone, 2018. |
| 5B – Non-fiction: | “Boris Johnson: First speech as PM in full”, a speech held by the new prime minister Boris Johnson, July 24, 2019. |
Vejledning og skabelon til at løse opgaven
Den samlede eksaminationstid for assignment 1-5 er 5 timer. Besvarelsen bedømmes som en helhed ud fra de faglige mål for niveauet.
Det anbefales, at du skriver din besvarelse i skabelonen, som ligger under Template i menuen til venstre. Besvarelsen afleveres i ét dokument med opgaverne i rækkefølgen 1-5.
Henvisninger til tekst, video- og lydklip
Hvis du citerer, skal du angive kilde.
Alt anvendt materiale skal være engelsksproget og angives med kildehenvisninger. Til forklaring af grammatiske opgaver kan materialerne være på dansk.
Du kan henvise til dele af video- og lydklip, f.eks. ved at angive afspillerens minut- og sekundtal for henholdsvis starten og slutningen af klippet.
Alt anvendt materiale skal være engelsksproget og angives med kildehenvisninger. Til forklaring af grammatiske opgaver kan materialerne være på dansk.
Du kan henvise til dele af video- og lydklip, f.eks. ved at angive afspillerens minut- og sekundtal for henholdsvis starten og slutningen af klippet.
|
Tekster i opgavesættet
Teksternes ortografi og tegnsætning følger forlæggene. Trykfejl er dog rettet.
Opsætningen følger ikke nødvendigvis forlæggene. Dog følges forlægget nøje, hvor opsætningen på den ene eller anden måde indgår i opgaven.
Opsætningen følger ikke nødvendigvis forlæggene. Dog følges forlægget nøje, hvor opsætningen på den ene eller anden måde indgår i opgaven.
Assignment 1
Find alle verberne (udsagnsordene) i præteritum (datid) i nedenstående tekst, og omskriv dem til præsens (nutid). Skriv hele teksten som dit svar, og markér verberne tydeligt som i eksemplet
| Eksempel: | He enjoyed getting up in the morning… He enjoys getting up in the morning… |
He enjoyed getting up in the morning and kept a woodpecker clock by the bed, a Swiss contraption that shocked him out of sleep at 5 a.m. He had leather carpet slippers ready on the floor, which he wore for the journey to the bathroom, a gleaming place where everything waited in good order, foreign soaps, tooth powder, his shaving things and a bottle of cologne. Every small element of life fascinated him and he wanted to get it right. […]
Once a swallow’s nest fell from the eaves of the house. My father gathered us together in the front room. He made us sit quietly by the window, watching the unfolding drama, seeing if the chicks inside the nest would be rescued or abandoned or stolen. In the end it was all too much for him. He brought the nest inside and taught me how to feed the chicks with a dropper. Two of them died, but one survived, and he put everything into the life of that bird. He took a pencil and pointed to the bulging purple skin that seemed to cover the bird's eyes and he showed me the place where its heart was beating.
Once a swallow’s nest fell from the eaves of the house. My father gathered us together in the front room. He made us sit quietly by the window, watching the unfolding drama, seeing if the chicks inside the nest would be rescued or abandoned or stolen. In the end it was all too much for him. He brought the nest inside and taught me how to feed the chicks with a dropper. Two of them died, but one survived, and he put everything into the life of that bird. He took a pencil and pointed to the bulging purple skin that seemed to cover the bird's eyes and he showed me the place where its heart was beating.
Andrew O’Hagan, Be Near Me, 2006
Assignment 2
Besvar opgave a., b. og c. Brug relevant grammatisk terminologi. Skriv dit svar på dansk.
- Find og skriv to eksempler på forskellige konjunktioner (bindeord) i nedenstående tekst.
- Fire verballed (udsagnsled) er understreget i nedenstående tekst. Angiv subjekt (grundled) for hvert verballed.
- Forklar kort, hvorfor der bruges comes og ikke come i linje 3.
You work in an open plan office that starts to smell like microwave food by midday. Sometimes you’re met
with a delightful aromatic curry, other times, pure bile. And then a waft of sunshine, meadows and spices
3
comes through.
It is a colleague that you don’t normally talk to but he smells like a Greek god and you hesitate to tell
him. What if he thinks you’re being too forward? What if the office judges you?  Essentially, telling someone they smell good is not weird or creepy – who doesn’t want to
know they have a pleasant fragrance?
Faima Bakar, “Is it inappropriate to tell a colleague of the opposite sex they smell good?”, 2018
Assignment 3
Lyt til klippet fra den amerikanske vicepræsident Mike Pences tale til The National Space Council.
Find og skriv fem forskellige substantiver (navneord) og tre forskellige verber (udsagnsord), som tilhører det semantiske felt military.
Mike Pence says, “time has come”
Assignment 4
Write a text (50-75 words) to match the photo.
You must include the following words. You are not allowed to change the forms of the words. You must underline the words in your text.
| attentively – elderly – even though – furthermore – which |
Assignment 5
- Answer 5A or 5B.
Assignment 5A - Fiction
- Write a short summary of Martin Malone’s short story “Bone Deep” in about 125 words.
- Write an analytical essay (600-900 words) in which you analyse and interpret the short story. Your essay must focus on the relationship between the characters.
Include the following analytical terms in your essay:
point of view, symbols, main theme
Your essay must include references to the text.
Material
Martin Malone, “Bone Deep”, 2018.
Assignment 5B - Non-fiction
- Write a short summary of Boris Johnson’s first speech as prime minister of the UK in about 125 words.
- Write an analytical essay (600-900 words) about the speech. Your essay must focus on how Boris Johnson presents his views. Discuss briefly the kind of Britain that Johnson envisions.
Include the following analytical terms in your essay:
circumstances, style, intention
Your essay must include references to the text.
Material
“Boris Johnson: First speech as PM in full”, a speech held by the new prime minister Boris Johnson, July 24, 2019.
- Transcript: “Boris Johnson: First speech as PM in full”.
- Video: “Boris Johnson: First speech as PM in full”.
Sources
Anvendt materiale (til brug for Copydan):
Andrew O’Hagan. Be Near Me. 2006. London: Faber and Faber Ltd, 2007.
Faima Bakar. “Is it inappropriate to tell a colleague of the opposite sex they smell good?”. Metro website, March 22, 2018, viewed October 2019. (www.metro.co.uk)
The Straits Times. “Mike Pence says “time has come” for US Space Force”. August 9, 2018, viewed October 2019. (www.youtube.com)
Martin Malone. “Bone Deep”. Ed. Sarah Gilmartin and Declan Meade. Stinging Fly Stories. Dublin: The Stinging Fly Press, 2018.
“Boris Johnson: First speech as PM in full”. BBC website, July 24, 2019, viewed October 2019. (www.bbc.com)
Image credit: Daily Mail. “New York in the “Swinging sixties”: Beautiful pictures capture New York City in a period of historic transition”. Daily Mail website, November 21, 2013, viewed October 2019. (www.dailymail.co.uk)


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MARS ATTACKS! A film review by Mark R. Leeper Copyright 1996 Mark R. Leeper
Capsule: There are a few nice moments of MARS ATTACKS! that remind one of the creative fun and kinky sadism of the original trading cards, but mostly we have the story lost in silliness in a vain attempt to be funny. Tim Burton had a great cast and great special effects, but little understanding of the strength of the material those bubble gum cards offered. Turning the "Mars Attacks!" cards into this film may be the biggest waste of a good idea you will see in a major film this year. Rating: low 0 (-4 to +4)
This year has reeled from two major films made that are tributes to George Pal's 1953 film THE WAR OF THE WORLDS. INDEPENDENCE DAY is, of course, already one of the most financially successful films of all time. Tim Burton's MARS ATTACKS! is just now being loosed on theaters.
Following the release of WAR OF THE WORLDS, a whole generation of fantasy film fans grew up with the images from that film engraved on their memories. The images of the planet Earth being trounced by the weapons of alien super-science inspired imitations like EARTH VS. THE FLYING SAUCERS, THE MYSTERIANS, and BATTLE IN OUTER SPACE. In another medium, Topps Bubble Gum released a series of trading cards to cash in on these images. The "Mars Attacks!" cards were an updating of the gratuitous sadism of the earlier "Horrors of War" trading cards. They added a generous injection of imaginative science fictional weapons to more effectively melt the flesh from the poor victims' bones. The most memorably card shows a pet dog being turned into a skeleton. There was not a lot of plot to the story told on the back of the cards except that the Martians came and blasted away at everything, so (if I remember correctly) we Earthlings went to Mars and blew it up. Now inspired by this rather rudimentary but image-rich story Tim Burton has made a film with his own version of the story. It seems like a natural matching since Burton films specialize in being image-rich with rudimentary stories.
This is a wedge-shaped film with its highest point in a genuinely nightmarish image before the opening credits. I was tempted to feel at this point that perhaps Burton really did understand the style and kinky imagination of the "Mars Attacks!" cards and was steeling myself for harrowing and delicious film experience. This is followed by a nearly as impressive image of a vast armada of flying saucers picking up from Mars and converging on our own green planet. Good stuff so far. From there the film introduces us to several groups of characters, a sort of cross-section of America in a sort of hideous mosaic. We see a trailer park family from some prairie state. We meet a vulgar entrepreneur wanting to build a Las Vegas casino. And as a sort of first among equals we meet the over-ripe President of the United States (Jack Nicholson) and his weird entourage. Then for a half hour the script bogs down as we meet all these people and the people around them without getting to know them very well. Then for a while the story is fun again. But only for a while.
The real problem with MARS ATTACKS! is the deterioration of the script. It starts with a serious plotline, then begins treating the plot in a tongue-in-cheek manner. From there it starts adding jokes, and finally the whole plotline turns into a joke. Eventually the film is doing anything it can to milk laughs from the material in the worst traditions of THE CANNONBALL RUN. Each step is away from the imagination that made the cards exciting to adolescents and towards a sort of smirking patronization of the spirit of the source material.
The film sports a hefty cast of familiar actors, though certainly not for the challenge of the roles. Typical is to have an actor like Rod Steiger playing a high military official who yells his strategy at the President ("Kill! Kill!! Exterminate.") Nicholson is his most overripe playing a very un-Presidential President of the United States. Also on hand are Glenn Close as the First Lady, Danny DeVito, Martin Short, Tom Jones, and Michael J. Fox. One unexpectedly creative bit involves the fate of Pierce Brosnan and Sarah Jessica Parker. But on the whole we have familiar actors standing around to wait for a screaming death scene given to them compliments of the Martian invaders who turn out to be by far the most believable characters in the film.
With a little more respect for the original material, Burton could have had a wonderful little film instead of this tiresome comedy with one or two good moments. I give it a low 0 on the -4 to +4 scale.
Mark R. Leeper<EMAIL_ADDRESS>The review above was posted to the
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DataTjej Konferens is the largest conference for women studying Software and Computer Science related fields in the Nordic Area. I had the privilege of creating the brand of the conference 2015 including logo renewal, posters, a pamflet, stickers, patches and a redesign and reimplementation of the website. I was responsible for how we appeared in social media and for organizing photographers.


Normmatt has created a way to run B9S .firm files from bootrom via a DSi Flashcard and a magnet! This works on every 3DS on any firmware version.
For installation without a PC, GBAtemp user @TheCyberQuake has created a pack which will automatically install B9S and copy over essential starter homebrew from the flashcard's SD to the 3DS's. This will mainly be used for PC-less B9S installations. If you have a PC with you, use 3ds.guide. Read more here.
This works because of a flaw in the bootrom. Before the bootrom boots the NAND, it checks to see if Start+Select+X is held down, and if the shell is closed. If these requirements are met, it will boot an NDS cartridge from the bootrom. This gives that cartridge bootrom access. You might be wondering how you'd hold down buttons while the shell is closed, and why you need a magnet. If you put a magnet in a specific spot on the 3DS, it will go into sleep mode. Using this, you can boot the NDS cartridge with the buttons held down while in sleep mode! Using a compatible flashcard, you can boot B9SInstaller using the flashcard, and easily install it on your 3DS. The 2DS does not require a magnet, as it uses a switch to sleep instead.
Q: Can Nintendo patch this?
A: Nope! Not without a new hardware revision.
Q: My flashcard is blocked by my firmware! Can I still use this?
A: Yup, the flashcard blacklist is not enabled on the bootrom.
Q: Why can't this work with my flashcard?
A: The installation requires you to flash to the flashcard's internal NAND. Most DS Flashcards have ROMs instead of NANDS.
Q: But my flashcard has a NAND! Why won't this work!
A: You can't just easily flash them, it takes time and effort. Please do not pester the devs for a release date for your card. It will be done when it is done.
Q: Do you know what flashcards are going to be supported in the future?
A: R4 SDHC Dualcore and the DSTT. Don't expect a release date, however.
Q: Will my 3DS flashcard work?
A: Sorry, the bootrom requires it to be a TWL (NDS) Cartridge
Q: I'm bricked! Can I unbrick it?
A: Yup! You can unbrick from any kind of brick as long as it isn't an MCU brick or you've taken a knife to the motherboard. You can even use this to boot EmuNAND on consoles with their NAND chip fried or even physically removed!
Q: Can I install B9S on the latest firmware with this?
A: Since the card has direct access to the bootrom, yes!
Q: Does this work on the New Nintendo 2DS XL?
A: Yup!
| Release | Guide |
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You can construct an IF statement by placing the IF block and ENDIF block. Any ELSE or ELSE IF block goes between the IF and ENDIF blocks and is lined up with them. Don't forget to indent anything inside of the IF statement over by 1. You can change the into the appropriate symbols for the operation you are attempting to perform. For this program construct an IF statement that will set min equal to the smaller of two variables a and b.


Inside city centre penthouse 24 Nov 2019, 08:00 by Briana Millett (Image: Savills) (Image: Savills) (Image: Savills) (Image: Savills) (Image: Savills) (Image: Savills) (Image: Savills) (Image: Savills) (Image: Savills)


At Cal Poly I teach Digital Printing and Variable Data Publishing, Content Management and Web Design, and the first phase of the Senior Project.
I have more than 30 years' experience in commercial, newspaper, and digital printing operations including serving as manager for regional operations of USA Today. Previously, I worked for Xerox Corporation, developing patented image analysis techniques. I'm a graduate of the Rochester Institute of Technology School of Print Media.
My published research includes work in digital printing, personalized communication, and the news media industry. At Cal Poly led a student driven project testing Adobe's PDF/VT file format, and have recently completed a study on how demographic factors affect purchasing decisions in food packaging.


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Fastest Stapling
Athletes will be timed in stapling two reams worth of paper in groups of 14 sheets of paper using a standard-issued stapler. The paper must be hand-counted and stapled using a non-automated stapler by individual. This is not a team-event. There will be age classes in this event, and medals will be awarded by age class:
- Women & Men, Ages 15-30
- Women & Men, Ages 30-45
- Women & Men, Ages 45-60


2D constant-density acoustic frequency-domain modeling, linearized modeling and imaging: Imaging
We illustrate some basic imaging capabilities on a simple layered model.
Contents
Model
We define a simple layered model:
% grid z = 0:20:1000; x = 0:20:2000; [o,d,n] = grid2odn(z,x); % velocity v = 1500*ones(n); v(z>300,:) = 2000; v(z>700,:) = 2500; % plot figure; imagesc(x,z,v);axis equal tight;colorbar; xlabel('x [km]');ylabel('z [km]');title('velocity [m/s]');
Parameters for data
% gridded slowness-squared values [km^2/s^2] m = 1e6./v(:).^2; % model grid model.o = o; model.d = d; model.n = n; % absorbing boundary model.nb = [20 20]; % source/receiver grid model.zsrc = 15; model.xsrc = 500:100:1500; model.zrec = 5; model.xrec = 0:15:2000; % frequencies model.freq = [4:2:15]; % wavelet model.f0 = 10; model.t0 = 0.01; % source matrix Q = speye(length(model.xsrc)); % make data D = F(m,Q,model);
Reverse-time-migration
We can perform RTM by applying the adjoint of the Jacobian to the data. We model data for a smooth background model:
% smoothing operator S = opKron(opSmooth(n(2),50),opSmooth(n(1),50)); % smooth model m0 = S*m; % data and Jacobian for smooth model [D0,J0] = F(m0,Q,model);
Remember, J0 is not an explicit matrix. It is simply an object that looks like a matrix to matlab. Constructing it does not require any computation. All the computations are done when multiplying it with a vector.
Now, the RTM image is given by
dm = J0'*(D-D0); % plot figure; imagesc(x,z,reshape(dm,n));axis equal tight;colormap(gray); xlabel('x [m]');ylabel('z [m]');title('RTM image');
Least-squares migration
Using the Jacobian, we can perform least-squares migration with lsqr as follows
dm = lsqr(J0,D-D0,1e-6,2); figure; imagesc(x,z,reshape(dm,n));axis equal tight;colormap(gray); xlabel('x [m]');ylabel('z [m]');title('least-squares migration image');
lsqr stopped at iteration 2 without converging to the desired tolerance 1e-06 because the maximum number of iterations was reached. The iterate returned (number 2) has relative residual 0.73.