§663-4 Actions which survive death of wrongdoer or other person liable. All rights of action arising out of physical injury to the person or out of the death of a person as provided by section 663-3, shall survive, notwithstanding the death of the wrongdoer or any other persons who may be liable for damages for such physical injury or death. [L 1953, c 206, pt of §1; am L 1955, c 205, pt of §3; RL 1955, §246-3; HRS §663-4]
Cross References
Abatement and revival, see chapter 634, pt V.
Probate, claims, see chapter 560.
Rules of Court
Substitution of parties, see HRCP rule 25.
Case Notes
Does not provide for survival of defamation actions. 1 H. App. 517, 620 P.2d 771 (1980).
Judgments for punitive damages may be entered against the estate of a deceased tortfeasor. 104 H. 241 (App.), 87 P.3d 910 (2003).
Cited: 45 H. 373, 383, 369 P.2d 96 (1961).


Safeguarding biodiversity calls for the active involvement of all citizens, businesses, governments and organizations. Collectively, we need to build a vast network to communicate the importance of biodiversity with the rest of world. Very substantial changes from business-as-usual trends are needed in order to address the challenges we face: to slow and stop the loss of biodiversity.
The map below and the calendar give an overview of the work being done around the world in the context of the United Nations Decade on Biodiversity. Actions include specific programmes and projects, policy changes, activities, events and more. If you would like your action included, please register it by filling the form or contact us.
Beginning at the UN Biodiversity Conference in Cancun, in 2016, Parties and other Governments, in concert with partner organizations and other entities, are invited to announce commitments or actions in support of the Convention, the Strategic Plan for Biodiversity 2011-2020, and the Aichi Biodiversity Targets. Read more >
The following Actions are relevant for all countries. For Actions at the national level click on the map or go to the country profiles >


Striking, bright photographs of art and valuable treasures for sale at auction greet the user in a large carousel that takes up 80% of the page. The carousel automatically scrolls through the photographs prompting the user to click on one of the diverse auctions. Above and below the carousel there are horizontal menus that pop up to larger menus when hovered over by the cursor. This is a very efficient and pleasing design solution that allows for an emphasis on the central aspect of Christies: the beautiful items that are on sale.
A smaller carousel greets the user's eye. Scrolling down brings a diverse aray of images of paintings, furniture, and other mediums of art. Unlike Christies, where the auctions for much more expensive pieces of artwork will be taking place mostly off site, the goal for Paddle8 is to show as many pieces as possible that might interest the visitor. Entreaties to become a member and learn how the site works follow naturally in the flow after the main carousel. The bright photo focused design allows the user to explore new artworks and rapidly access the bidding page when he/she finds something to bid on.
The site uses a more subtle approach to displaying a number of products. There is very little text on the page outside of the menus: the prices and descriptions are hidden until the mouse hovers over them. Each piece is given equal weight in terms of visual space. Overall the site has a minimalist style avoiding boxes and maximizing white space, giving more of a contrast to the pictures of the products.


This app shows the motion of a classical single degree of freedom system, consisting out of a discrete mass, a spring, and a damper element. A harmonic force can also be applied to the system. By starting the oscillation, the system oscillates around the static equilibrium position at $u = 0$. The displacement plot is normalized with the spring stiffness. No gravity is acting on the system.
The interactivity parameters are
For high values of damping, the oscillation amplitude decays quickly and the system reaches its static equilibrium. Zero initial velocity means that the displacement starts with a horizontal tangent.
If the system is subjected to a harmonic load, the solution consists out of two main parts: the homogeneous and the particular part. While the homogeneous part is transient and decays, if damping is present, the particular part is driven by the harmonic load and does not decay. For the case of a damped system, the total solution and the particular solution coincide after the homogeneous part has decayed completely.
The diagrams on the far right show the amplification function and the phase angle of the system subjected to harmonic loading. The dot marks the current frequency ratio.
At the right-top corner of the displacement plot, several tools allow to zoom in or to scroll forward in time. The Pause button pauses the playback, the Stop button clears all time data and enables the sliders. By pressing the Reset button, all settings are restored.


Canadian Imperial Bank Of Commerce: Stable And Safe With A 5% Yield
by Canadian Dividend Growth InvestorSummary
- CIBC's 5% yield is safe.
- Its dividend is supported by stable earnings and a sustainable payout ratio.
- Other big Canadian banks offer greater earnings growth over the next few years. So, unless you only care about the income, you should consider the other banks first.
- The Big Six Canadian banks will be reporting earnings November 26-December 5.
Canadian Imperial Bank of Commerce (CM, TSX:CM) generates stable earnings, which translates to a stable stock most of the time. Stable earnings coupled with a sustainable payout ratio makes CIBC's current yield of 5% solid.
In other words, it's a better income generator than GICs in Canada or CDs in the U.S. which offer interest rates of roughly 2.4% or 2.1%, respectively, on a one-year term.
CIBC's stock often gives the notion that it underperforms the other Big Six Canadian banks, but as we shall see, that's not always the case.
Source: Author - CIBC building in Toronto
Recent News
Year-to-date results
In the first nine months of the fiscal year, CIBC reported adjusted earnings per share ("EPS") of C$9.07, down 1.5% against the comparable period a year ago. These are stable enough earnings and led to a payout ratio of just under 46%. As well, its return on equity fell 2% to 15.8% year over year.
Fiscal Q3 results
In the last reported quarter, its Canadian Personal and Small Business Banking segment and U.S. Commercial Banking and Wealth Management segment, together making up 59% of the quarter's net earnings experienced growth of 3% and 6%, respectively, year over year.
However, its remaining segments, Canadian Commercial Banking and Wealth Management, and Capital Markets experienced earnings that fell 1% and 13%, respectively. Although earnings from Capital Markets are more volatile in general, it only made up 2.4% of earnings.
Sale of a majority stake in CIBC FirstCaribbean
Earlier this month, CIBC agreed to sell a majority stake, 66.73%, of CIBC FirstCaribbean for about US$797 million to GNB Financial Group, and it'll maintain a minority 24.9% interest in FirstCaribbean and act in a supporting role. FirstCaribbean had US$12 billion of assets at the end of 2018. So, the sale will have a negligible impact on CIBC's earnings.
As a result of this transaction, CIBC's Common Equity Tier 1 capital ratio is expected to improve by about 0.40% to roughly 11.8%. Additionally, it'll result in an after-tax loss of about C$135 million that'll be recognized in fiscal Q4. Thankfully, the loss will be offset by a favourable foreign currency exchange, translating to gains of roughly C$280 million.
CIBC vs. The Big Six Banks: Dividend, Earnings Growth, & Total Returns
Let's compare the dividend, earnings growth, and total returns of the Big Six Canadian Banks over about 10 years, coming out of the financial crisis from fiscal 2009.
Notably, CIBC and BMO had the biggest hit on their earnings during the last recession triggered by a financial crisis. Therefore, they had more room for recovery when they right the ship. We were surprised to see how stable National Bank of Canada's (OTCPK:NTIOF, TSX:NA) earnings were - even during the recession, its adjusted EPS increased every year.
| Company | Earnings Growth [1] | Dividend Growth [1] | Dividends Received (CAD$) [2] | Total Returns [1] |
| Royal Bank of Canada (RY, TSX:RY) | 7.4% | 7.4% | $5,405 | 9.7% |
| Toronto-Dominion Bank (TD, TSX:TD) | 9.8% | 9% | $6,363 | 12.1% |
| Bank of Nova Scotia (BNS, TSX:BNS) | 6.1% | 5.9% | $5,920 | 8.5% |
| Bank of Montreal (BMO, TSX:BMO) | 7% | 3.8% | $6,539 | 10.3% |
| CIBC | 7.5% | 4.9% | $7,059 | 9.8% |
| National Bank of Canada | 7.2% | 7.9% | $6,915 | 12.2% |
- Annualized
- Based on C$10,000 of initial investment
Here's the same type of comparison over a five-year period.
| Ticker | Earnings Growth [1] | Dividend Growth [1] | Dividends Received (C$) [2] | Total Returns [1] |
| RY | 8% | 7.5% | $2,235 | 9.6% |
| TD | 9.9% | 9.5% | $2,197 | 9.9% |
| BNS | 5.6% | 6.4% | $2,264 | 5.8% |
| BMO | 7.4% | 5.7% | $2,237 | 7.8% |
| CM | 6.3% | 7.3% | $2,467 | 6.3% |
| NA | 7% | 7.2% | $2,232 | 9.2% |
- Annualized
- Based on C$10,000 of initial investment
The total returns in the tables above indicate only how well (or not) the stocks performed in that period, which will be skewed by the valuations of the stocks at the start of the period and the valuations they have today.
If anything, CIBC isn't the worst performer. Moreover, in both the ten-year and five-year periods, it delivered the most income - if that's what certain investors seek.
Other than valuation, earnings growth is also a driver for price appreciation. Moreover, it's a driver for dividend growth.
Is CIBC a Buy?
Over the next three to five years, the other Big Six Canadian banks are estimated to experience EPS growth that will be more than twice as fast as CIBC's estimated EPS growth of 2.2%. Therefore, the stock trades at the lowest P/E among the banks for a reason.
It's best to consider names like TD or National Bank for long-term investment, especially on dips.
However, we'd consider buying CIBC as a trade for capital gains in the short term (and get the dividend in the interim) whenever it's too cheap to ignore. At a P/E of ~9.5, we don't think it's at that level. (We did buy CIBC in our DGI Across North America service when it fell below C$100 for a quick profit.)
Income investors who care more about income than total returns might also choose CIBC over the others. Here are a few 5-6% yielders that offer safe dividends and better upside potential.
The Big Six Canadian banks are set to report their fiscal Q4 and full-year results starting with Scotiabank on November 26th through to TD and CIBC on December 5th. Cautious investors can wait for the earnings results to get better clarity on the banks' outlooks for the future.
DGI Across North America subscribers get a range of dividend ideas - some are core holdings and some are mispriced stocks to trade for outsized gains.
It is your opportunity to get weekly dividend ideas to build your own portfolio, with guidance from a dedicated dividend growth investor. Go here to start a two-week free trial!
Disclosure: I am/we are long TD, BNS. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.
Additional disclosure: We're long on the TSX: TD and BNS. This article consists of my opinions and is for educational purposes only. Please do your own research and due diligence and consult a financial advisor and or tax professional if necessary before making any investment decisions.


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Three cases of probable vaping-related illness in B.C.: Health Canada
There are seven cases Canada-wide
by Katya SlepianThere are now three probable cases of vaping-related illness in B.C., according to Health Canada.
In a bulletin issued this week, the agency said there are now seven cases of vaping-related illnesses across Canada.
Of those, two are confirmed cases in Quebec, with two probable cases in New Brunswick and two in B.C.
Earlier this fall, Health Canada directed medical professionals across the country to report any vaping-related pulmonary illnesses. B.C. saw its first case reported on Oct. 16.
READ MORE: First case of ‘probable’ vaping-related illness in B.C. ‘not surprising’: UBC prof
Doctors of BC president Kathleen Ross said the rise in vaping-related illness is worrying, as statistics show nearly one in five youths have taken up vaping.
“Certainly it’s a big step backwards in our anti-smoking efforts,” Ross said in an interview with Black Press Media in October.
“This is definitely going to contribute to a new generation of people addicted to nicotine, and potentially exposed to other forms of smoking that we were successfully battling.”
Ross said the directive from Health Canada to report vaping-related illness is helping, as will more research on the subject. Education, she said, will be key in slowing down the growth of vaping among young people.
“Teens are under the impression that beeping is not harmful,” she said. “And they’re asking us to show us the facts.”
READ MORE: B.C. men seek to open class action against e-cigarette giant Juul
Ross is worried that although the severe, acute symptoms of vaping are being looked at seriously now, it’s impossible to know the longterm effects right now.
“We really don’t have a clear picture of this full spectrum of the illnesses associated with vaping, she said. “We see symptoms starting with nausea or vomiting, stomach upset… if the symptoms were relatively minor, they may well not come to the attention of a physician.”
READ MORE: Health Canada ‘actively monitoring’ U.S. vaping illness breakthrough


--- layout: default ---
d3.js visualization of gram graphs
(a:A)-->(b:B)<--(c:C)-->(a), (c)-->(d), (c)-->(e)


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Source code for pybert.pybert_cfg
"""
Simulation configuration data encapsulation, for PyBERT.
Original Author: David Banas<EMAIL_ADDRESS>Original Date: 5 May 2017
This Python script provides a data structure for encapsulating the
simulation configuration data of a PyBERT instance. It was first
created, as a way to facilitate easier pickling, so that a particular
configuration could be saved and later restored.
Copyright (c) 2017 by David Banas; All rights reserved World wide.
"""
[docs]class PyBertCfg:
"""
PyBERT simulation configuration data encapsulation class.
This class is used to encapsulate that subset of the configuration
data for a PyBERT instance, which is to be saved when the user
clicks the "Save Config." button.
"""
def __init__(self, the_PyBERT):
"""
Copy just that subset of the supplied PyBERT instance's
__dict__, which should be saved during pickling.
"""
# Simulation Control
self.bit_rate = the_PyBERT.bit_rate
self.nbits = the_PyBERT.nbits
self.pattern_len = the_PyBERT.pattern_len
self.nspb = the_PyBERT.nspb
self.eye_bits = the_PyBERT.eye_bits
self.mod_type = the_PyBERT.mod_type
self.num_sweeps = the_PyBERT.num_sweeps
self.sweep_num = the_PyBERT.sweep_num
self.sweep_aves = the_PyBERT.sweep_aves
self.do_sweep = the_PyBERT.do_sweep
# Channel Control
self.use_ch_file = the_PyBERT.use_ch_file
self.ch_file = the_PyBERT.ch_file
self.impulse_length = the_PyBERT.impulse_length
self.f_step = the_PyBERT.f_step
self.Rdc = the_PyBERT.Rdc
self.w0 = the_PyBERT.w0
self.R0 = the_PyBERT.R0
self.Theta0 = the_PyBERT.Theta0
self.Z0 = the_PyBERT.Z0
self.v0 = the_PyBERT.v0
self.l_ch = the_PyBERT.l_ch
# Tx
self.vod = the_PyBERT.vod
self.rs = the_PyBERT.rs
self.cout = the_PyBERT.cout
self.pn_mag = the_PyBERT.pn_mag
self.pn_freq = the_PyBERT.pn_freq
self.rn = the_PyBERT.rn
tx_taps = []
for tap in the_PyBERT.tx_taps:
tx_taps.append((tap.enabled, tap.value))
self.tx_taps = tx_taps
self.tx_tap_tuners = []
for tap in the_PyBERT.tx_tap_tuners:
self.tx_tap_tuners.append((tap.enabled, tap.value))
self.tx_use_ami = the_PyBERT.tx_use_ami
self.tx_use_getwave = the_PyBERT.tx_use_getwave
self.tx_ami_file = the_PyBERT.tx_ami_file
self.tx_dll_file = the_PyBERT.tx_dll_file
# Rx
self.rin = the_PyBERT.rin
self.cin = the_PyBERT.cin
self.cac = the_PyBERT.cac
self.use_ctle_file = the_PyBERT.use_ctle_file
self.ctle_file = the_PyBERT.ctle_file
self.rx_bw = the_PyBERT.rx_bw
self.peak_freq = the_PyBERT.peak_freq
self.peak_mag = the_PyBERT.peak_mag
self.ctle_offset = the_PyBERT.ctle_offset
self.ctle_mode = the_PyBERT.ctle_mode
self.ctle_mode_tune = the_PyBERT.ctle_mode_tune
self.ctle_offset_tune = the_PyBERT.ctle_offset_tune
self.rx_use_ami = the_PyBERT.rx_use_ami
self.rx_use_getwave = the_PyBERT.rx_use_getwave
self.rx_ami_file = the_PyBERT.rx_ami_file
self.rx_dll_file = the_PyBERT.rx_dll_file
# DFE
self.use_dfe = the_PyBERT.use_dfe
self.use_dfe_tune = the_PyBERT.use_dfe_tune
self.sum_ideal = the_PyBERT.sum_ideal
self.decision_scaler = the_PyBERT.decision_scaler
self.gain = the_PyBERT.gain
self.n_ave = the_PyBERT.n_ave
self.n_taps = the_PyBERT.n_taps
self.sum_bw = the_PyBERT.sum_bw
# CDR
self.delta_t = the_PyBERT.delta_t
self.alpha = the_PyBERT.alpha
self.n_lock_ave = the_PyBERT.n_lock_ave
self.rel_lock_tol = the_PyBERT.rel_lock_tol
self.lock_sustain = the_PyBERT.lock_sustain
# Analysis
self.thresh = the_PyBERT.thresh


Here, you can analyze the number of lines of code (in percentage) written in various programming languages in a choosen country. To do this, we go through our personal server which will go through the github API and perform the analysis before sending us back the data. Below you can select a country and see the magic work.


--- title: Giant Reports subtitle: layout: capital herotype: title grid: 2-col breadcrumb: [{"name":"Home", "url":"/mbs/security-data/giant-reports.html"},{"name":"PC Reports","url":"/mbs/security-data/giant-reports.html"},{"name":"Giant Reports"}] onload: formSetup navLevel1: 'section-mbs' navLevel2: 'subnav-mbs-data' ---
For information about the files listed on this page go to Product Specific Reports File Help.
(Monthly) Gold and 75 day Giant PC schedules, available 2nd business day.
(Monthly) GNMA Giant PC schedules, available 2nd business day.
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{title:'Encoders', created:'9.0.0'}
The {@link oaj.encoders} package defines an API for handling encoding-based matching
of
The {@link oaj.encoders.EncoderSet} class represents the set of {@link oaj.encoders.Encoder encoders} keyed by codings.
It maintains a set of encoders and the codings that they can handle.
The {@link oaj.encoders.EncoderSet#getEncoderMatch(String) getEncoderMatch(String)} and {@link oaj.encoders.EncoderSet#getEncoder(String)}
methods are then used to find appropriate encoders for specific
Encoders are tried in the order they appear in the set. The {@link oaj.encoders.EncoderSet.Builder#add(Class...)} / {@link oaj.encoders.EncoderSet.Builder#add(Encoder...)} methods prepend the values to the list to allow them the opportunity to override encoders already in the list.
For example, calling builder.add(E1.
will result in the order
|
The {@link oaj.encoders.Encoder} interface is used for enabling decompression on requests and compression on responses, such as support for GZIP compression. It is used to wrap input and output streams within compression/decompression streams.
Encoders are registered with


{% extends 'nt_training/base.html' %} {% load nt_training_sessions %} {% load nt_spec %} {% block title %}{{ person }}{% endblock %} {% block content %}
{{ person.first_name|title }} has received no training.
{% endif %}{{ person.first_name|title }} has given no training.
{% endif %}


Giannis makes history in Bucks win, Pelicans eclipse Suns
by OmnisportGiannis Antetokounmpo enjoyed an historic performance as the Milwaukee Bucks outlasted the Portland Trail Blazers 137-129 in the NBA.
Reigning MVP Antetokounmpo posted his second triple-double of the season via 24 points, 19 rebounds and a career-high 15 assists on Thursday.
Antetokounmpo became the first Bucks player with a 20-point, 15-rebound and 15-assist game.
Bucks team-mate Eric Bledsoe added 30 points and six assists as Milwaukee improved to 12-3 for the season following six straight wins.
The Trail Blazers – playing without Damian Lillard – lost their third consecutive game, despite a game-high 37 points from CJ McCollum.
After scoring 10 points on debut, 10-time All-Star Carmelo Anthony finished with 18 points and seven rebounds.
Meanwhile, the New Orleans Pelicans upstaged the Phoenix Suns 124-121 on the road.
Brandon Ingram (28), JJ Redick (26) and Jrue Holiday (23) combined for 77 points in Phoenix, where the Pelicans extended their winning streak to three games.
Kelly Oubre Jr. led the Suns with 25 points, while Devin Booker had 19 of his own.
Rockets at Clippers
On a day the Los Angeles Lakers travel to the Oklahoma City Thunder, the Boston Celtics take on the Denver Nuggets and the Philadelphia 76ers host the slumping San Antonio Spurs, Friday's showdown in Los Angeles stands out. Barring anymore load management, it will be the Clippers' Kawhi Leonard and Paul George against Houston Rockets pair James Harden and Russell Westbrook.


Plugins
Sangoma is a beautifully minimalistic HTML5 template for any backend, user interface or administration, both for desktop and mobile users. Built on latest Twitter Bootstrap and powered with LESS, Sangoma will save you hours in developing your project.
Template is available in 4 default colors and packed with basic and popular user interface elements and widgets. Built on Twitter Bootstrap Bootstrap is one of the most complete front-end toolkits over the internet. Thats why we decided to use it as our skeleton framework for all upcoming templates. Maintaining native Bootstrap functionality, enriched of pleasing design and tons of new template features, makes it very powerful UI kit for rapid development.


Try out our Premium Member services: Virtual Legal Assistant, Query Alert Service and an ad-free experience. Free for one month and pay only if you like it.
IN THE HIGH COURT OF KERALA AT ERNAKULAM WP(C).No. 20991 of 2007(Y) 1. K.RAHMATHULLA, S/O.KUNHALANKUTTY HAJI, ... Petitioner Vs 1. THE CHERUKAVU GRAMA PANCHAYATH ... Respondent 2. THE SENIOR ENVIRONMENTAL ENGINEER 3. THE DISTRICT MEDICAL OFFICER 4. PALAPATTA MUHAMMED,S/O.ALAVI, For Petitioner :SRI.BABU S. NAIR For Respondent :SRI.K.M.SATHYANATHA MENON The Hon'ble MR. Justice ANTONY DOMINIC Dated :15/07/2008 O R D E R ANTONY DOMINIC, J. -------------------------------------------------------- W.P.(C) 20991 of 2007 -------------------------------------------------------- Dated: JULY 15, 2008 JUDGMENT
The prayers sought in this writ petition are against the 4th respondent. It is on the allegation that by running the ice plant, the 4th respondent is polluting the well water in the petitioner's premises. On that basis petitioner seeks directions commanding the 1st respondent to cancel the licence of the 4th respondent and also to respondents 1 to 3 not to permit the 4th respondent to run the ice plant causing pollution to the drinking water in the nearby locality.
2. Learned counsel for the petitioner submits that the petitioner's well is situated at a distance of 45 metres from the ice plant and that the well water has been analysed on different occasions. Petitioner submits that Exts.P3 to P5 are the analysis reports which indicate that the water in the well in his premises is unfit for drinking purposes. According to him, it is therefore evident that the 4th respondent unit is contaminating the well water and therefore the unit is liable to be closed down for that reason.
WP(C) 20991/07 2
3. A statement has been filed by the 2nd respondent. According to the 2nd respondent, on receipt of complaint from the residents of the locality, they had issued directions to the 4th respondent to stop discharge of waste water to public drain and also to apply and obtain consent of the Pollution Control Board. It is stated that accordingly an application was made by the 4th respondent on 17.7.2006. Thereafter, complaints were again received and the well water was analysed which showed that the chlorine content was slightly in excess of the limits.
4. It is stated that at that stage the 4th respondent had produced Ext.R2(1), an agreement entered into by the 4th respondent with the earlier owner of the petitioner's property and also another neighbouring resident. It is stated that in terms of the said agreement, petitioner had agreed to provide a bore well to the house of one Mr.Veeran Kutty and pipe connection to the residential premises which is occupied by the petitioner. According to the Pollution Control Board, considering all these, consent to operate was issued on certain conditions as envisaged in Water (Prevention and Control of Pollution) Act, 1974. The Pollution Control Board again submits WP(C) 20991/07 3 that even subsequent to the grant of consent, inspections were conducted on 2.4.2007 and 25.7.2007 and that the 4th respondent is operating the unit in terms of the conditions of the consent that has been granted.
5. Despite the assertions made by the Pollution Control Board in its statement and the 4th respondent in his counter affidavit, the learned counsel for the petitioner submits that waste water is being discharged from the 4th respondent's premises into the public drain and also into the neighbouring properties leading contamination of the well water. It is stated that as a result of this, his well water is saline and is unfit for potable purposes.
6. If the 4th respondent is complying with the conditions of the consent to operate, granted by the Pollution Control Board, the petitioner can have no complaint. Any way, it is a matter for the Pollution Control Board to ensure that the 4th respondent is operating his industrial unit strictly in terms of the consent to operate granted by them.
7. In view of the complaint raised by the petitioner, I direct that the Pollution Control Board shall conduct periodical WP(C) 20991/07 4 inspection of the premises of the 4th respondent and ensure compliance of the conditions of consent to operate. It is directed that in case violation of the consent is found, the Pollution Control Board shall take appropriate action to remedy the situation.
With these directions the writ petition is disposed of.
ANTONY DOMINIC JUDGE mt/-


@Alexfrog
I hate BTC more than ComputerGenie does. Thats why I want KMD to surpass BTC, but he just doesnt care what BTC does, he only cares about KMD vs USD.
1) the 1st part of that is impossible
2) so do I
3) the last half of that shows that you actively refuse to read the actual words I type


The paper proposes parameter-reduction techniques to lower the memory consumption (and improve training speed) of BERT.
It also proposes to use a self-supervised loss (based on inter-sentence coherence) and argues that this loss is better than the NSP loss used by BERT.
ALBERT architecture is similar to that of BERT with three major differences.
Factorized Embedding Parameterization
In BERT and followup works, the embedding size was tied to the size of the context vector.
Since context vector is expected to encoder the entire context, it needs to have a large dimensionality.
One consequence of this choice is that even the embedding layer (which encodes the representation for each token) has a large size. This increases the overall memory footprint of the model.
The paper proposed to factorize the embedding parameters into two smaller matrics.
The embedding layer learns a low dimensional representation of the tokens and this representation is projected into a high dimensional space.
Cross-layer parameter sharing
Inter-sentence coherence loss
BERT uses two losses - Masked Language Modeling loss (MLM) and Next Sentence Prediction (NSP).
In the NSP task, the model is provided a pair of sentences and it has to predict if the two sentences appear consecutively in the same document or not. Negative samples are created by sampling sentences from different documents.
The paper argues that NSP is not effective as a loss function as it merges topic prediction and coherence prediction into one task (as the two sentences come from different documents). The topic prediction is an easier task as compared to coherence prediction.
Hence the paper proposes to use the Sentence Order Prediction task where the model has to predict which of the two sentences comes first in a document. The negative samples are created by simply swapping the order in the positive samples. Hence both the sentences come from the same document and topic prediction alone can not be used to solve the task.
Different variants (in terms of size) of ALBERT and BERT models are compared (eg ALBERT, ALBERT-x, BERT-x, etc).
In general, ALBERT models have many-times fewer parameters as compared to the BERT models.
Datasets - BookCorpus, English Wikipedia.
ALBERT-xxlarge significantly outperforms the BERT-large model even though it has around 70% parameters as the BERT-large model.
BERT-xlarge performs worse than BERT-base hinting that it is difficult to train such large models.
ALBERT models also have better data throughput as compared to BERT models.
For the ALBERT models, an embedding size of 128 performs the best.
As the hidden dimension is increased, the model obtains better performance, but with diminishing returns.
Very wide ALBERT models (say with a context size of 1024) do not benefit much from depth.
Using additional training data boosts the performance for most of the downstream tasks.
The paper empirically shows that using dropout could hurt the performance of the ALBERT models. This observation may not hold for BERT as it does not share parameters across layers and hence may need regularization via dropout.
ALBERT also improves the state of the art performance on GLUE, SQuAD and RACE benchmarks, for both single-model and ensemble setup.


Aaron Smith
I am a programmer based in Manhattan. If you would like to get in touch, please email me at
<EMAIL_ADDRESS>.
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Page 2 of 3
Posted:
Mon Jan 22, 2007 1:32 pm
by Karl G.
monkeys. How can
Posted:
Sat Jan 27, 2007 10:33 pm
by Cletus
a monkey run
Posted:
Sun Jan 28, 2007 11:28 am
by Karl G.
so fast that
Posted:
Sun Jan 28, 2007 12:14 pm
by David T.
it would have
Posted:
Tue Jan 30, 2007 3:40 pm
by figgles
fiery feet and
Posted:
Thu Feb 01, 2007 2:07 am
by silvert0384
a large, red
Posted:
Thu Feb 01, 2007 7:54 pm
by Serenity
shiny bum, for
Posted:
Thu Feb 08, 2007 11:02 pm
by logitech
my eyes to
Posted:
Sun Feb 18, 2007 3:20 pm
by Morn
check the merchandise
Posted:
Tue Feb 20, 2007 6:40 pm
by Liberate My Sadness
so i took
Posted:
Tue Feb 20, 2007 10:52 pm
by Serenity
some viagra, and
Posted:
Fri Feb 23, 2007 3:46 pm
by secretrk1313
my clock radio
Posted:
Fri Feb 23, 2007 4:52 pm
by Karl G.
exploded. I hope
Posted:
Sun Feb 25, 2007 12:23 am
by Liberate My Sadness
she finds out
Posted:
Sun Feb 25, 2007 9:46 pm
by Liberate My Madness
my hairy grandma
Posted:
Wed Feb 28, 2007 8:40 pm
by Liberate My Sadness
shoved her fingers
Posted:
Wed Feb 28, 2007 10:04 pm
by Liberate My Madness
under the sky
Posted:
Thu Mar 29, 2007 4:25 pm
by Old Crowe
and in my
Posted:
Fri Mar 30, 2007 12:34 pm
by figgles
portable finger grinder
Posted:
Sat Mar 31, 2007 12:50 am
by Thunderhorse8128
she screamed F*ck
Posted:
Sat Mar 31, 2007 12:51 am
by Thunderhorse8128
me in the
Posted:
Sun Apr 01, 2007 3:37 pm
by Liberate My Sadness
boobies because it
Posted:
Wed Apr 04, 2007 7:59 pm
by Liberate My Madness
took my money
Posted:
Thu Apr 05, 2007 10:53 am
by Karl G.
and wouldn't give
Posted:
Thu Apr 12, 2007 11:36 am
by Liberate My Madness
her fingers back


Easy to Git is an open-source project that offers many ways to get started with Git and GitHub
We aim to cultivate a community that supports one another in learning how to collaborate with version control
Challenge One
Challenge Two
Quiz
Useful Links


Tree module Module that handles trees
Adds a node as a child of another one
- Parameters
-
| [in] | _pstRefNode | Reference node (add as a child of this one) |
| [in] | _pstNode | Node to add |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE
Adds a node as a parent of another one
- Parameters
-
| [in] | _pstRefNode | Reference node (add as a parent of this one) |
| [in] | _pstNode | Node to add |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE
Adds a node at the root of a tree
- Parameters
-
| [in] | _pstTree | Concerned tree |
| [in] | _pstNode | Node to add |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE
Adds a node as a sibling of another one
- Parameters
-
| [in] | _pstRefNode | Reference node (add as a sibling of this one) |
| [in] | _pstNode | Node to add |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE
Cleans a tree
- Parameters
-
| [in] | _pstTree | Concerned tree |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE
Gets first child node
- Parameters
-
| [in] | _pstNode | Concerned node |
- Returns
- orxTREE_NODE / orxNULL
Definition at line 155 of file orxTree.h.
| static orxINLINE orxU32 orxTree_GetCount |
( |
const orxTREE * |
_pstTree | ) |
|
|
static |
Gets a tree count
- Parameters
-
| [in] | _pstTree | Concerned tree |
- Returns
- Number of nodes in tree
Definition at line 208 of file orxTree.h.
Gets parent node
- Parameters
-
| [in] | _pstNode | Concerned node |
- Returns
- orxTREE_NODE / orxNULL
Definition at line 142 of file orxTree.h.
Gets previous sibling node
- Parameters
-
| [in] | _pstNode | Concerned node |
- Returns
- orxTREE_NODE / orxNULL
Definition at line 181 of file orxTree.h.
Gets a tree root
- Parameters
-
| [in] | _pstTree | Concerned tree |
- Returns
- orxTREE_NODE / orxNULL
Definition at line 195 of file orxTree.h.
Gets (next) sibling node
- Parameters
-
| [in] | _pstNode | Concerned node |
- Returns
- orxTREE_NODE / orxNULL
Definition at line 168 of file orxTree.h.
Gets a node tree
- Parameters
-
| [in] | _pstNode | Concerned node |
- Returns
- orxTREE / orxNULL
Definition at line 129 of file orxTree.h.
Moves a node as a child of another one of the same tree
- Parameters
-
| [in] | _pstRefNode | Reference node (move as a child of this one) |
| [in] | _pstNode | Node to move |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE
Removes a node from its tree
- Parameters
-
| [in] | _pstNode | Concerned node |
- Returns
- orxSTATUS_SUCCESS / orxSTATUS_FAILURE


| 2281 | U+1F1F2 U+1F1F0 | Macedonia | |
| 2282 | U+1F1F2 U+1F1F1 | Mali | |
| 2283 | U+1F1F2 U+1F1F2 | Myanmar (Burma) | |
| 2284 | U+1F1F2 U+1F1F3 | Mongolia | |
| 2285 | U+1F1F2 U+1F1F4 | Macau SAR China | |
| 2286 | U+1F1F2 U+1F1F5 | Northern Mariana Islands | |
| 2287 | U+1F1F2 U+1F1F6 | Martinique | |
| 2288 | U+1F1F2 U+1F1F7 | Mauritania | |
| 2289 | U+1F1F2 U+1F1F8 | Montserrat | |
| 2290 | U+1F1F2 U+1F1F9 | Malta | |
| 2291 | U+1F1F2 U+1F1FA | Mauritius | |
| № | Code | Sample | Name |
| 2292 | U+1F1F2 U+1F1FB | Maldives | |
| 2293 | U+1F1F2 U+1F1FC | Malawi | |
| 2294 | U+1F1F2 U+1F1FD | Mexico | |
| 2295 | U+1F1F2 U+1F1FE | Malaysia | |
| 2296 | U+1F1F2 U+1F1FF | Mozambique | |
| 2297 | U+1F1F3 U+1F1E6 | Namibia | |
| 2298 | U+1F1F3 U+1F1E8 | New Caledonia | |
| 2299 | U+1F1F3 U+1F1EA | Niger | |
| 2300 | U+1F1F3 U+1F1EB | Norfolk Island | |
| 2301 | U+1F1F3 U+1F1EC | Nigeria | |
| 2302 | U+1F1F3 U+1F1EE | Nicaragua | |
| 2303 | U+1F1F3 U+1F1F1 | Netherlands | |
| 2304 | U+1F1F3 U+1F1F4 | Norway | |
| 2305 | U+1F1F3 U+1F1F5 | Nepal | |
| 2306 | U+1F1F3 U+1F1F7 | Nauru | |
| 2307 | U+1F1F3 U+1F1FA | Niue | |
| 2308 | U+1F1F3 U+1F1FF | New Zealand | |
| 2309 | U+1F1F4 U+1F1F2 | Oman | |
| 2310 | U+1F1F5 U+1F1E6 | Panama | |
| 2311 | U+1F1F5 U+1F1EA | Peru | |
| № | Code | Sample | Name |
| 2312 | U+1F1F5 U+1F1EB | French Polynesia | |
| 2313 | U+1F1F5 U+1F1EC | Papua New Guinea | |
| 2314 | U+1F1F5 U+1F1ED | Philippines | |
| 2315 | U+1F1F5 U+1F1F0 | Pakistan | |
| 2316 | U+1F1F5 U+1F1F1 | Poland | |
| 2317 | U+1F1F5 U+1F1F2 | St. Pierre & Miquelon | |
| 2318 | U+1F1F5 U+1F1F3 | Pitcairn Islands | |
| 2319 | U+1F1F5 U+1F1F7 | Puerto Rico | |
| 2320 | U+1F1F5 U+1F1F8 | Palestinian Territories | |
| 2321 | U+1F1F5 U+1F1F9 | Portugal | |
| 2322 | U+1F1F5 U+1F1FC | Palau | |
| 2323 | U+1F1F5 U+1F1FE | Paraguay | |
| 2324 | U+1F1F6 U+1F1E6 | Qatar | |
| 2325 | U+1F1F7 U+1F1EA | Réunion | |
| 2326 | U+1F1F7 U+1F1F4 | Romania | |
| 2327 | U+1F1F7 U+1F1F8 | Serbia | |
| 2328 | U+1F1F7 U+1F1FA | Russia | |
| 2329 | U+1F1F7 U+1F1FC | Rwanda | |
| 2330 | U+1F1F8 U+1F1E6 | Saudi Arabia | |
| 2331 | U+1F1F8 U+1F1E7 | Solomon Islands | |
| № | Code | Sample | Name |
| 2332 | U+1F1F8 U+1F1E8 | Seychelles | |
| 2333 | U+1F1F8 U+1F1E9 | Sudan | |
| 2334 | U+1F1F8 U+1F1EA | Sweden | |
| 2335 | U+1F1F8 U+1F1EC | Singapore | |
| 2336 | U+1F1F8 U+1F1ED | St. Helena | |
| 2337 | U+1F1F8 U+1F1EE | Slovenia | |
| 2338 | U+1F1F8 U+1F1EF | Svalbard & Jan Mayen | |
| 2339 | U+1F1F8 U+1F1F0 | Slovakia | |
| 2340 | U+1F1F8 U+1F1F1 | Sierra Leone | |
| 2341 | U+1F1F8 U+1F1F2 | San Marino | |
| 2342 | U+1F1F8 U+1F1F3 | Senegal | |
| 2343 | U+1F1F8 U+1F1F4 | Somalia | |
| 2344 | U+1F1F8 U+1F1F7 | Suriname | |
| 2345 | U+1F1F8 U+1F1F8 | South Sudan | |
| 2346 | U+1F1F8 U+1F1F9 | São Tomé & Príncipe | |
| 2347 | U+1F1F8 U+1F1FB | El Salvador | |
| 2348 | U+1F1F8 U+1F1FD | Sint Maarten | |
| 2349 | U+1F1F8 U+1F1FE | Syria | |
| 2350 | U+1F1F8 U+1F1FF | Swaziland | |
| 2351 | U+1F1F9 U+1F1E6 | Tristan da Cunha | |
| № | Code | Sample | Name |
| 2352 | U+1F1F9 U+1F1E8 | Turks & Caicos Islands | |
| 2353 | U+1F1F9 U+1F1E9 | Chad | |
| 2354 | U+1F1F9 U+1F1EB | French Southern Territories | |
| 2355 | U+1F1F9 U+1F1EC | Togo | |
| 2356 | U+1F1F9 U+1F1ED | Thailand | |
| 2357 | U+1F1F9 U+1F1EF | Tajikistan | |
| 2358 | U+1F1F9 U+1F1F0 | Tokelau | |
| 2359 | U+1F1F9 U+1F1F1 | Timor-Leste | |
| 2360 | U+1F1F9 U+1F1F2 | Turkmenistan | |
| 2361 | U+1F1F9 U+1F1F3 | Tunisia | |
| 2362 | U+1F1F9 U+1F1F4 | Tonga | |
| 2363 | U+1F1F9 U+1F1F7 | Turkey | |
| 2364 | U+1F1F9 U+1F1F9 | Trinidad & Tobago | |
| 2365 | U+1F1F9 U+1F1FB | Tuvalu | |
| 2366 | U+1F1F9 U+1F1FC | Taiwan | |
| 2367 | U+1F1F9 U+1F1FF | Tanzania | |
| 2368 | U+1F1FA U+1F1E6 | Ukraine | |
| 2369 | U+1F1FA U+1F1EC | Uganda | |
| 2370 | U+1F1FA U+1F1F2 | U.S. Outlying Islands | |
| 2371 | U+1F1FA U+1F1F3 | United Nations | |
| № | Code | Sample | Name |
| 2372 | U+1F1FA U+1F1F8 | United States | |
| 2373 | U+1F1FA U+1F1FE | Uruguay | |
| 2374 | U+1F1FA U+1F1FF | Uzbekistan | |
| 2375 | U+1F1FB U+1F1E6 | Vatican City | |
| 2376 | U+1F1FB U+1F1E8 | St. Vincent & Grenadines | |
| 2377 | U+1F1FB U+1F1EA | Venezuela | |
| 2378 | U+1F1FB U+1F1EC | British Virgin Islands | |
| 2379 | U+1F1FB U+1F1EE | U.S. Virgin Islands | |
| 2380 | U+1F1FB U+1F1F3 | Vietnam | |
| 2381 | U+1F1FB U+1F1FA | Vanuatu | |
| 2382 | U+1F1FC U+1F1EB | Wallis & Futuna | |
| 2383 | U+1F1FC U+1F1F8 | Samoa | |
| 2384 | U+1F1FD U+1F1F0 | Kosovo | |
| 2385 | U+1F1FE U+1F1EA | Yemen | |
| 2386 | U+1F1FE U+1F1F9 | Mayotte | |
| 2387 | U+1F1FF U+1F1E6 | South Africa | |
| 2388 | U+1F1FF U+1F1F2 | Zambia | |
| 2389 | U+1F1FF U+1F1FC | Zimbabwe |


{% comment %} Use this template for subcategories which themselves have subcategories again and for these sub-subcategories as well. The top subcategory renders the


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date map view to show all matching date points
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--- title: Using a custom library in R author: Zhian N. Kamvar date: '2017-11-18' slug: using-a-custom-library-in-r categories: - R - example tags: - library - .libPaths() - .Renviron - environment variable - R image: placement: 2 focal_point: "center" preview_only: true ---
I’ve been using a custom library for R since 2012 and I’ve never looked back. I’ve not seen many tutorials for people do do this through R, so I figured I’d write a quick one.
You can usually find this out by typing .libPaths()
in your R console. If you have an out-of-the-box installation, it will generally be somewhere like:
C:/Program Files/R/R-3.4.2/library
or
/Library/Frameworks/R.framework/Versions/3.4/Resources/library
This is the place on your computer where R will put any packages you attempt to install with install.packages()
. However, you might notice one problem: this library is version-specific, which means that when you update R, you will also have to migrate your existing library. Moreover, if you’re on Windows, you may not have permissions to write to the library path 🙀.
The solution to avoid the hassle of constant library migration is to make a custom library folder1 and set the environmental variable R_LIBS
to point to that folder 👍.
Now, this has been touched on before, but when it comes to explaining HOW to set that environment variable, something is always missing2 🤷♂. This short post will demonstrate how to persistently set the variable without ever having to leave R 😎.
.Renviron
file and setting R_LIBS
The .Renviron
file is where you can store environment variables that R uses to gather specific information about your particular computer. In this case, we are going to use it to tell R where your R library lives using the R_LIBS
environment variable.
What we are going to do is:
~/.Renviron
3R_LIBS=~/R/library
to the ~/.Renviron
fileFor this tutorial, I’m using ~/R/library for the custom library, but you can set it to any folder you wish.
The first step, create the directory. Note that this will give you a warning message if the directory already exists.
dir.create("~/R/library", recursive = TRUE)
Now we can create our ~/.Renviron
file. This is a part we need to be careful. If there already is a .Renviron
file, we don’t want to accidentally clobber it. To help with that, we will use file.exists()
with an if
statement to tell us whether or not to create the file:
if (file.exists("~/.Renviron")) {
message("~/.Renviron already exists!")
} else {
file.create("~/.Renviron")
message("created ~/.Renviron")
}
## created ~/.Renviron
Now we can write R_LIBS=~/R/library
to the ~/.Renviron
file:
cat("R_LIBS=~/R/library", file = "~/.Renviron", append = TRUE)
Now after you’ve restarted R, your library will appear:
.libPaths()
## [1] "/Users/zhian/R/library"
## [2] "/Library/Frameworks/R.framework/Versions/3.4/Resources/library"
Now you can feel free to update your version of R without having to go through the hassle of migrating your library. Even better, you can take advantage of update.packages()
to auto-update packages in your R library like so:
update.packages(ask = FALSE, checkBuilt = TRUE)
Note: I am using the word “folder” here to mean “directory”.↩
Please do not take this to mean that these are bad resources. I’m just picking nits here 😄.↩
Two things: 1) The ~/ denotes the home folder. All of your documents are nested in this folder. 2) .Renviron
starts with a dot, which hides it from your file browser by default.↩


--- layout: page title: About header-img: "img/about-bg.png" ---
I am a teacher and part-time musician from the Washington D.C. area.


System Architect Picture "Identifier In Domain"
Parent Diagram:
Subject Identifier
(OMT Object Model)


{# Load the tag library #} {% load bootstrap3 %} {% load static %} {# Load CSS and JavaScript #} {% bootstrap_css %} {% bootstrap_javascript %} {# Display django.contrib.messages as Bootstrap alerts #} {% bootstrap_messages %}
Are You sure you want to delete this design?


--- layout: work title: "Fountains" description: image: /assets/images/work/bamboo-forest.jpg order: 2 link_description: "Developed Laser fountain for organization of Tehran beautification" link_image: /assets/images/work/laser-fountain/concept.jpg link_video: ---
Laser fountain was designed for organization of Tehran beautification as an urban element. It was a recirculating fountain that sent water jet w through some nozzle into a basin. The trick is to arrange a laser to shoot out through each nozzle. Because of total internal reflection, the laser light will follow the arc of the water stream.
The long collimating nozzle helps generate a smooth unbroken jet of water. A simulator based on the beam tracing method is developed for this fountain in MATLAB by a group of engineers to proof the laser propagation into nozzle with arbitrary situations such as different materials, nozzle length and curves and laser wavelengths (color).
If you cup your hands under the stream, you are rewarded with a pretty handful of wet green, red or blue lights. I underestimated its attraction for hand washing, urban beautification, children playgrounds, Amusement park, museum, musical fountains and hotels.
A bamboo fountain was designed for organization of Tehran beautification, which was inspired from large bamboo. The nozzle was designed to out the water as bamboo leafs. Similar to the water maze, the design was modular and the parts was prefabricated. This fountain can be made in different size and dimensions according to the order of customers.
This design was the result of a class project about urban furniture and introduced to organization of Tehran beautification. In fact, it was inspired by the green mazes for hot countries to make cool places for different applications such as children playgrounds, parks, libraries, hotels, Official welcoming ceremonies, places for worship and etc. The water maze design is modular and the parts was prefabricated. The fountain can be made in different size and dimensions according to the order of customers. Quick and easy installation, development ability and ability to change the maze’s form are the special characteristics of this design


-nCoV pangolin coronavirus pangolins related coronaviruses samples using sequence genome sequences View Guangdong virus Figure bat Table human viral Data Guangxi analysis obtained phylogenetic shown Extended amino animals indicated sequencing similarity -nCoV, China different estimated outbreak recombination red Download OpenUrl SARS-CoV alignment associated data genomes including lineages lung novel performed reads reference used (B) GD/PL RBD RNA S). acid animal anti-smuggling assembly market new qPCR regions (A) -nCoV. GenBank Phylogenetic RaTG Vero accession bootstrap closely collected consensus genomic inline intestine multiple nucleotide popup raw residues scale study. table: thank tissue trees Branch China. CoV CrossRef Customs Dr. GD/PS Guangzhou Malayan Note ORFs able analysis. archived blue boxes, cell coronaviruses, coronaviruses. denoted designed detection effect hosts identified indicate likelihood likely line merged number operations predicted receptor-binding revealed sample source study, suggests viruses wild window zoonotic


PART III. SPECIAL FACILITY REVENUE BONDS
Revision Note
Enacted as part II, this part was renumbered as part III pursuant to §23G-15.
§206M-41 Definitions. As used in this part, unless the context clearly requires otherwise:
"Special facility" means one or more buildings, structures, or facilities and the land thereof located in an industrial park for the technology industry, including, without limitation, facilities for technology research, development, support, processing, and manufacturing, which are the subject of a special facility lease.
"Special facility lease" includes a contract, lease, or other agreement, or any combination thereof, the subject matter of which is the same special facility.
"Special facility revenue bonds" means all bonds, notes, and other instruments of indebtedness of the State issued pursuant to this part and part III of chapter 39. [L 2000, c 72, pt of §1; am L 2017, c 69, §5]


MR. HOLLAND'S OPUS A film review by Michael John Legeros Copyright 1996 Michael John Legeros
Of Maestros and Men
(Buena Vista) Directed by Stephen Herek Written by Patrick Sheane Duncan Cast Richard Dreyfuss, Glenne Headly, Olympia Dukakis, W.H. Macy, Jay Thomas MPAA Rating "PG" Running Time 144 minutes Reviewed at General Cinemas at Pleasant Valley, Raleigh, NC (21JAN96)
==
Any motion picture that promotes music appreciation is well-deserv- ing of a look, arguably even one as excruciatingly slow and predictably dopey as MR. HOLLAND'S OPUS. Agony is the best word to describe sitting through Stephen Herek's 144-minute epic of a minor scale. The story charts 30 years in the life of high-school music teacher Glenn Holland (Richard Dreyfuss), from the inevitable first-year frustrations right on up to the only-in-the-movies appreciation-at-retirement rally. Though credible as a honest-- if rather tidy-- portrait of the educational process, the movie goes flat when scoring the weepy melodrama of Hol- land's family life. (The ads reveal a son who's born deaf and you can take it from there.)
Ignoring the deeper issues in Patrick Sheane Duncan's script, Herek opts for an OPUS that's part fantasy. Such as a school orchestra that sounds like seasoned studio players, or the magical acceptance of a teenaged son who has been terribly ignored through his life by his father. (Or even the small fact that we never see much evidence of *Holland's* impact on his student's lives. We only see how they affect *him*. How selfish.) And it only gets worse, quickly proving that more than just fairy dust is missing here.
The integration of the music is particularly horrid. Instead of a *real* review of the classics, we get a bit of Bach, a handful of old- ies, and an overdose of overblown orchestrations from composer Michael Kamen. Ugh. The lack of snap is equally abominable. Even the most patient for a good cry will likely find their bottoms growing sore long before their tear ducts do. Thank goodness for the solid work of Richard Dreyfuss. Wearing a great make-up job that successfully spans three decades, Dreyfuss gives a workmanlike performance that even survives him having to sing "Beautiful Boy." Who knows, he may just win a nomination.
Slow, sappy, and shameless, MR. HOLLAND'S OPUS is Hollywood happily- ever-after as only Hollywood can make it. The masses will probably eat this stuff up and, judging from the weekend grosses, they already have.
Grade: C+
--
Mike Legeros - Raleigh, NC
<EMAIL_ADDRESS>(h) -<EMAIL_ADDRESS>(w)
Visit the MOVIE HELL site
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rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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"""ARMA process and estimation with scipy.signal.lfilter
Notes
-----
* written without textbook, works but not sure about everything
briefly checked and it looks to be standard least squares, see below
* theoretical autocorrelation function of general ARMA
Done, relatively easy to guess solution, time consuming to get
theoretical test cases, example file contains explicit formulas for
acovf of MA(1), MA(2) and ARMA(1,1)
Properties:
Judge, ... (1985): The Theory and Practise of Econometrics
Author: josefpktd
License: BSD
"""
from statsmodels.compat.python import range
import numpy as np
from scipy import signal, optimize, linalg
__all__ = ['arma_acf', 'arma_acovf', 'arma_generate_sample',
'arma_impulse_response', 'arma2ar', 'arma2ma', 'deconvolve',
'lpol2index', 'index2lpol']
[docs]def arma_generate_sample(ar, ma, nsample, sigma=1, distrvs=np.random.randn,
burnin=0):
"""
Generate a random sample of an ARMA process
Parameters
----------
ar : array_like, 1d
coefficient for autoregressive lag polynomial, including zero lag
ma : array_like, 1d
coefficient for moving-average lag polynomial, including zero lag
nsample : int
length of simulated time series
sigma : float
standard deviation of noise
distrvs : function, random number generator
function that generates the random numbers, and takes sample size
as argument
default: np.random.randn
TODO: change to size argument
burnin : integer
Burn in observations at the generated and dropped from the beginning of
the sample
Returns
-------
sample : array
sample of ARMA process given by ar, ma of length nsample
Notes
-----
As mentioned above, both the AR and MA components should include the
coefficient on the zero-lag. This is typically 1. Further, due to the
conventions used in signal processing used in signal.lfilter vs.
conventions in statistics for ARMA processes, the AR parameters should
have the opposite sign of what you might expect. See the examples below.
Examples
--------
>>> import numpy as np
>>> np.random.seed(12345)
>>> arparams = np.array([.75, -.25])
>>> maparams = np.array([.65, .35])
>>> ar = np.r_[1, -arparams] # add zero-lag and negate
>>> ma = np.r_[1, maparams] # add zero-lag
>>> y = sm.tsa.arma_generate_sample(ar, ma, 250)
>>> model = sm.tsa.ARMA(y, (2, 2)).fit(trend='nc', disp=0)
>>> model.params
array([ 0.79044189, -0.23140636, 0.70072904, 0.40608028])
"""
# TODO: unify with ArmaProcess method
eta = sigma * distrvs(nsample + burnin)
return signal.lfilter(ma, ar, eta)[burnin:]
[docs]def arma_acovf(ar, ma, nobs=10, sigma2=1, dtype=None):
"""
Theoretical autocovariance function of ARMA process
Parameters
----------
ar : array_like, 1d
coefficient for autoregressive lag polynomial, including zero lag
ma : array_like, 1d
coefficient for moving-average lag polynomial, including zero lag
nobs : int
number of terms (lags plus zero lag) to include in returned acovf
sigma2 : float
Variance of the innovation term.
Returns
-------
acovf : array
autocovariance of ARMA process given by ar, ma
See Also
--------
arma_acf
acovf
References
----------
.. [*] Brockwell, Peter J., and Richard A. Davis. 2009. Time Series:
Theory and Methods. 2nd ed. 1991. New York, NY: Springer.
"""
if dtype is None:
dtype = np.common_type(np.array(ar), np.array(ma), np.array(sigma2))
p = len(ar) - 1
q = len(ma) - 1
m = max(p, q) + 1
if sigma2.real < 0:
raise ValueError('Must have positive innovation variance.')
# Short-circuit for trivial corner-case
if p == q == 0:
out = np.zeros(nobs, dtype=dtype)
out[0] = sigma2
return out
# Get the moving average representation coefficients that we need
ma_coeffs = arma2ma(ar, ma, lags=m)
# Solve for the first m autocovariances via the linear system
# described by (BD, eq. 3.3.8)
A = np.zeros((m, m), dtype=dtype)
b = np.zeros((m, 1), dtype=dtype)
# We need a zero-right-padded version of ar params
tmp_ar = np.zeros(m, dtype=dtype)
tmp_ar[:p + 1] = ar
for k in range(m):
A[k, :(k + 1)] = tmp_ar[:(k + 1)][::-1]
A[k, 1:m - k] += tmp_ar[(k + 1):m]
b[k] = sigma2 * np.dot(ma[k:q + 1], ma_coeffs[:max((q + 1 - k), 0)])
acovf = np.zeros(max(nobs, m), dtype=dtype)
acovf[:m] = np.linalg.solve(A, b)[:, 0]
# Iteratively apply (BD, eq. 3.3.9) to solve for remaining autocovariances
if nobs > m:
zi = signal.lfiltic([1], ar, acovf[:m:][::-1])
acovf[m:] = signal.lfilter([1], ar, np.zeros(nobs - m, dtype=dtype),
zi=zi)[0]
return acovf[:nobs]
[docs]def arma_acf(ar, ma, lags=10, **kwargs):
"""
Theoretical autocorrelation function of an ARMA process
Parameters
----------
ar : array_like, 1d
coefficient for autoregressive lag polynomial, including zero lag
ma : array_like, 1d
coefficient for moving-average lag polynomial, including zero lag
lags : int
number of terms (lags plus zero lag) to include in returned acf
Returns
-------
acf : array
autocorrelation of ARMA process given by ar, ma
See Also
--------
arma_acovf
acf
acovf
"""
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)
acovf = arma_acovf(ar, ma, lags)
return acovf / acovf[0]
[docs]def arma_pacf(ar, ma, lags=10, **kwargs):
"""
Partial autocorrelation function of an ARMA process
Parameters
----------
ar : array_like, 1d
coefficient for autoregressive lag polynomial, including zero lag
ma : array_like, 1d
coefficient for moving-average lag polynomial, including zero lag
lags : int
number of terms (lags plus zero lag) to include in returned pacf
Returns
-------
pacf : array
partial autocorrelation of ARMA process given by ar, ma
Notes
-----
solves yule-walker equation for each lag order up to nobs lags
not tested/checked yet
"""
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)
# TODO: Should use rank 1 inverse update
apacf = np.zeros(lags)
acov = arma_acf(ar, ma, lags=lags + 1)
apacf[0] = 1.
for k in range(2, lags + 1):
r = acov[:k]
apacf[k - 1] = linalg.solve(linalg.toeplitz(r[:-1]), r[1:])[-1]
return apacf
[docs]def arma_periodogram(ar, ma, worN=None, whole=0):
"""
Periodogram for ARMA process given by lag-polynomials ar and ma
Parameters
----------
ar : array_like
autoregressive lag-polynomial with leading 1 and lhs sign
ma : array_like
moving average lag-polynomial with leading 1
worN : {None, int}, optional
option for scipy.signal.freqz (read "w or N")
If None, then compute at 512 frequencies around the unit circle.
If a single integer, the compute at that many frequencies.
Otherwise, compute the response at frequencies given in worN
whole : {0,1}, optional
options for scipy.signal.freqz
Normally, frequencies are computed from 0 to pi (upper-half of
unit-circle. If whole is non-zero compute frequencies from 0 to 2*pi.
Returns
-------
w : array
frequencies
sd : array
periodogram, spectral density
Notes
-----
Normalization ?
This uses signal.freqz, which does not use fft. There is a fft version
somewhere.
"""
w, h = signal.freqz(ma, ar, worN=worN, whole=whole)
sd = np.abs(h) ** 2 / np.sqrt(2 * np.pi)
if np.any(np.isnan(h)):
# this happens with unit root or seasonal unit root'
import warnings
warnings.warn('Warning: nan in frequency response h, maybe a unit '
'root', RuntimeWarning)
return w, sd
[docs]def arma_impulse_response(ar, ma, leads=100, **kwargs):
"""
Get the impulse response function (MA representation) for ARMA process
Parameters
----------
ma : array_like, 1d
moving average lag polynomial
ar : array_like, 1d
auto regressive lag polynomial
leads : int
number of observations to calculate
Returns
-------
ir : array, 1d
impulse response function with nobs elements
Notes
-----
This is the same as finding the MA representation of an ARMA(p,q).
By reversing the role of ar and ma in the function arguments, the
returned result is the AR representation of an ARMA(p,q), i.e
ma_representation = arma_impulse_response(ar, ma, leads=100)
ar_representation = arma_impulse_response(ma, ar, leads=100)
Fully tested against matlab
Examples
--------
AR(1)
>>> arma_impulse_response([1.0, -0.8], [1.], leads=10)
array([ 1. , 0.8 , 0.64 , 0.512 , 0.4096 ,
0.32768 , 0.262144 , 0.2097152 , 0.16777216, 0.13421773])
this is the same as
>>> 0.8**np.arange(10)
array([ 1. , 0.8 , 0.64 , 0.512 , 0.4096 ,
0.32768 , 0.262144 , 0.2097152 , 0.16777216, 0.13421773])
MA(2)
>>> arma_impulse_response([1.0], [1., 0.5, 0.2], leads=10)
array([ 1. , 0.5, 0.2, 0. , 0. , 0. , 0. , 0. , 0. , 0. ])
ARMA(1,2)
>>> arma_impulse_response([1.0, -0.8], [1., 0.5, 0.2], leads=10)
array([ 1. , 1.3 , 1.24 , 0.992 , 0.7936 ,
0.63488 , 0.507904 , 0.4063232 , 0.32505856, 0.26004685])
"""
if 'nobs' in kwargs:
leads = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of leads',
DeprecationWarning)
impulse = np.zeros(leads)
impulse[0] = 1.
return signal.lfilter(ma, ar, impulse)
[docs]def arma2ma(ar, ma, lags=100, **kwargs):
"""
Get the MA representation of an ARMA process
Parameters
----------
ar : array_like, 1d
auto regressive lag polynomial
ma : array_like, 1d
moving average lag polynomial
lags : int
number of coefficients to calculate
Returns
-------
ar : array, 1d
coefficients of AR lag polynomial with nobs elements
Notes
-----
Equivalent to ``arma_impulse_response(ma, ar, leads=100)``
Examples
--------
"""
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)
return arma_impulse_response(ar, ma, leads=lags)
[docs]def arma2ar(ar, ma, lags=100, **kwargs):
"""
Get the AR representation of an ARMA process
Parameters
----------
ar : array_like, 1d
auto regressive lag polynomial
ma : array_like, 1d
moving average lag polynomial
lags : int
number of coefficients to calculate
Returns
-------
ar : array, 1d
coefficients of AR lag polynomial with nobs elements
Notes
-----
Equivalent to ``arma_impulse_response(ma, ar, leads=100)``
Examples
--------
"""
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)
return arma_impulse_response(ma, ar, leads=lags)
# moved from sandbox.tsa.try_fi
[docs]def ar2arma(ar_des, p, q, n=20, mse='ar', start=None):
"""
Find arma approximation to ar process
This finds the ARMA(p,q) coefficients that minimize the integrated
squared difference between the impulse_response functions (MA
representation) of the AR and the ARMA process. This does not check
whether the MA lag polynomial of the ARMA process is invertible, neither
does it check the roots of the AR lag polynomial.
Parameters
----------
ar_des : array_like
coefficients of original AR lag polynomial, including lag zero
p : int
length of desired AR lag polynomials
q : int
length of desired MA lag polynomials
n : int
number of terms of the impulse_response function to include in the
objective function for the approximation
mse : string, 'ar'
not used yet,
Returns
-------
ar_app, ma_app : arrays
coefficients of the AR and MA lag polynomials of the approximation
res : tuple
result of optimize.leastsq
Notes
-----
Extension is possible if we want to match autocovariance instead
of impulse response function.
"""
# TODO: convert MA lag polynomial, ma_app, to be invertible, by mirroring
# TODO: roots outside the unit interval to ones that are inside. How to do
# TODO: this?
# p,q = pq
def msear_err(arma, ar_des):
ar, ma = np.r_[1, arma[:p - 1]], np.r_[1, arma[p - 1:]]
ar_approx = arma_impulse_response(ma, ar, n)
return (ar_des - ar_approx) # ((ar - ar_approx)**2).sum()
if start is None:
arma0 = np.r_[-0.9 * np.ones(p - 1), np.zeros(q - 1)]
else:
arma0 = start
res = optimize.leastsq(msear_err, arma0, ar_des, maxfev=5000)
arma_app = np.atleast_1d(res[0])
ar_app = np.r_[1, arma_app[:p - 1]],
ma_app = np.r_[1, arma_app[p - 1:]]
return ar_app, ma_app, res
_arma_docs = {'ar': arma2ar.__doc__,
'ma': arma2ma.__doc__}
[docs]def lpol2index(ar):
"""
Remove zeros from lag polynomial
Parameters
----------
ar : array_like
coefficients of lag polynomial
Returns
-------
coeffs : array
non-zero coefficients of lag polynomial
index : array
index (lags) of lag polynomial with non-zero elements
"""
ar = np.asarray(ar)
index = np.nonzero(ar)[0]
coeffs = ar[index]
return coeffs, index
[docs]def index2lpol(coeffs, index):
"""
Expand coefficients to lag poly
Parameters
----------
coeffs : array
non-zero coefficients of lag polynomial
index : array
index (lags) of lag polynomial with non-zero elements
Returns
-------
ar : array_like
coefficients of lag polynomial
"""
n = max(index)
ar = np.zeros(n + 1)
ar[index] = coeffs
return ar
[docs]def lpol_fima(d, n=20):
"""MA representation of fractional integration
.. math:: (1-L)^{-d} for |d|<0.5 or |d|<1 (?)
Parameters
----------
d : float
fractional power
n : int
number of terms to calculate, including lag zero
Returns
-------
ma : array
coefficients of lag polynomial
"""
# hide import inside function until we use this heavily
from scipy.special import gammaln
j = np.arange(n)
return np.exp(gammaln(d + j) - gammaln(j + 1) - gammaln(d))
# moved from sandbox.tsa.try_fi
[docs]def lpol_fiar(d, n=20):
"""AR representation of fractional integration
.. math:: (1-L)^{d} for |d|<0.5 or |d|<1 (?)
Parameters
----------
d : float
fractional power
n : int
number of terms to calculate, including lag zero
Returns
-------
ar : array
coefficients of lag polynomial
Notes:
first coefficient is 1, negative signs except for first term,
ar(L)*x_t
"""
# hide import inside function until we use this heavily
from scipy.special import gammaln
j = np.arange(n)
ar = - np.exp(gammaln(-d + j) - gammaln(j + 1) - gammaln(-d))
ar[0] = 1
return ar
# moved from sandbox.tsa.try_fi
[docs]def lpol_sdiff(s):
"""return coefficients for seasonal difference (1-L^s)
just a trivial convenience function
Parameters
----------
s : int
number of periods in season
Returns
-------
sdiff : list, length s+1
"""
return [1] + [0] * (s - 1) + [-1]
[docs]def deconvolve(num, den, n=None):
"""Deconvolves divisor out of signal, division of polynomials for n terms
calculates den^{-1} * num
Parameters
----------
num : array_like
signal or lag polynomial
denom : array_like
coefficients of lag polynomial (linear filter)
n : None or int
number of terms of quotient
Returns
-------
quot : array
quotient or filtered series
rem : array
remainder
Notes
-----
If num is a time series, then this applies the linear filter den^{-1}.
If both num and den are both lag polynomials, then this calculates the
quotient polynomial for n terms and also returns the remainder.
This is copied from scipy.signal.signaltools and added n as optional
parameter.
"""
num = np.atleast_1d(num)
den = np.atleast_1d(den)
N = len(num)
D = len(den)
if D > N and n is None:
quot = []
rem = num
else:
if n is None:
n = N - D + 1
input = np.zeros(n, float)
input[0] = 1
quot = signal.lfilter(num, den, input)
num_approx = signal.convolve(den, quot, mode='full')
if len(num) < len(num_approx): # 1d only ?
num = np.concatenate((num, np.zeros(len(num_approx) - len(num))))
rem = num - num_approx
return quot, rem
[docs]class ArmaProcess(object):
r"""
Theoretical properties of an ARMA process for specified lag-polynomials
Parameters
----------
ar : array_like, 1d, optional
Coefficient for autoregressive lag polynomial, including zero lag.
See the notes for some information about the sign.
ma : array_like, 1d, optional
Coefficient for moving-average lag polynomial, including zero lag
nobs : int, optional
Length of simulated time series. Used, for example, if a sample is
generated. See example.
Notes
-----
Both the AR and MA components must include the coefficient on the
zero-lag. In almost all cases these values should be 1. Further, due to
using the lag-polynomial representation, the AR parameters should
have the opposite sign of what one would write in the ARMA representation.
See the examples below.
The ARMA(p,q) process is described by
.. math::
y_{t}=\phi_{1}y_{t-1}+\ldots+\phi_{p}y_{t-p}+\theta_{1}\epsilon_{t-1}
+\ldots+\theta_{q}\epsilon_{t-q}+\epsilon_{t}
and the parameterization used in this function uses the lag-polynomial
representation,
.. math::
\left(1-\phi_{1}L-\ldots-\phi_{p}L^{p}\right)y_{t} =
\left(1-\theta_{1}L-\ldots-\theta_{q}L^{q}\right)
Examples
--------
>>> import numpy as np
>>> np.random.seed(12345)
>>> arparams = np.array([.75, -.25])
>>> maparams = np.array([.65, .35])
>>> ar = np.r_[1, -arparams] # add zero-lag and negate
>>> ma = np.r_[1, maparams] # add zero-lag
>>> arma_process = sm.tsa.ArmaProcess(ar, ma)
>>> arma_process.isstationary
True
>>> arma_process.isinvertible
True
>>> y = arma_process.generate_sample(250)
>>> model = sm.tsa.ARMA(y, (2, 2)).fit(trend='nc', disp=0)
>>> model.params
array([ 0.79044189, -0.23140636, 0.70072904, 0.40608028])
"""
# TODO: Check unit root behavior
def __init__(self, ar=None, ma=None, nobs=100):
if ar is None:
ar = np.array([1.])
if ma is None:
ma = np.array([1.])
self.ar = np.asarray(ar)
self.ma = np.asarray(ma)
self.arcoefs = -self.ar[1:]
self.macoefs = self.ma[1:]
self.arpoly = np.polynomial.Polynomial(self.ar)
self.mapoly = np.polynomial.Polynomial(self.ma)
self.nobs = nobs
[docs] @classmethod
def from_coeffs(cls, arcoefs=None, macoefs=None, nobs=100):
"""
Convenience function to create ArmaProcess from ARMA representation
Parameters
----------
arcoefs : array-like, optional
Coefficient for autoregressive lag polynomial, not including zero
lag. The sign is inverted to conform to the usual time series
representation of an ARMA process in statistics. See the class
docstring for more information.
macoefs : array-like, optional
Coefficient for moving-average lag polynomial, excluding zero lag
nobs : int, optional
Length of simulated time series. Used, for example, if a sample
is generated.
Examples
--------
>>> arparams = [.75, -.25]
>>> maparams = [.65, .35]
>>> arma_process = sm.tsa.ArmaProcess.from_coeffs(ar, ma)
>>> arma_process.isstationary
True
>>> arma_process.isinvertible
True
"""
arcoefs = [] if arcoefs is None else arcoefs
macoefs = [] if macoefs is None else macoefs
return cls(np.r_[1, -np.asarray(arcoefs)],
np.r_[1, np.asarray(macoefs)],
nobs=nobs)
[docs] @classmethod
def from_estimation(cls, model_results, nobs=None):
"""
Convenience function to create an ArmaProcess from the results
of an ARMA estimation
Parameters
----------
model_results : ARMAResults instance
A fitted model
nobs : int, optional
If None, nobs is taken from the results
"""
arcoefs = model_results.arparams
macoefs = model_results.maparams
nobs = nobs or model_results.nobs
return cls(np.r_[1, -arcoefs], np.r_[1, macoefs], nobs=nobs)
def __mul__(self, oth):
if isinstance(oth, self.__class__):
ar = (self.arpoly * oth.arpoly).coef
ma = (self.mapoly * oth.mapoly).coef
else:
try:
aroth, maoth = oth
arpolyoth = np.polynomial.Polynomial(aroth)
mapolyoth = np.polynomial.Polynomial(maoth)
ar = (self.arpoly * arpolyoth).coef
ma = (self.mapoly * mapolyoth).coef
except:
raise TypeError('Other type is not a valid type')
return self.__class__(ar, ma, nobs=self.nobs)
def __repr__(self):
msg = 'ArmaProcess({0}, {1}, nobs={2}) at {3}'
return msg.format(self.ar.tolist(), self.ma.tolist(),
self.nobs, hex(id(self)))
def __str__(self):
return 'ArmaProcess\nAR: {0}\nMA: {1}'.format(self.ar.tolist(),
self.ma.tolist())
[docs] def acovf(self, nobs=None):
nobs = nobs or self.nobs
return arma_acovf(self.ar, self.ma, nobs=nobs)
acovf.__doc__ = arma_acovf.__doc__
[docs] def acf(self, lags=None):
lags = lags or self.nobs
return arma_acf(self.ar, self.ma, lags=lags)
acf.__doc__ = arma_acf.__doc__
[docs] def pacf(self, lags=None):
lags = lags or self.nobs
return arma_pacf(self.ar, self.ma, lags=lags)
pacf.__doc__ = arma_pacf.__doc__
[docs] def periodogram(self, nobs=None):
nobs = nobs or self.nobs
return arma_periodogram(self.ar, self.ma, worN=nobs)
periodogram.__doc__ = arma_periodogram.__doc__
[docs] def impulse_response(self, leads=None):
leads = leads or self.nobs
return arma_impulse_response(self.ar, self.ma, leads=leads)
impulse_response.__doc__ = arma_impulse_response.__doc__
[docs] def arma2ma(self, lags=None):
lags = lags or self.lags
return arma2ma(self.ar, self.ma, lags=lags)
arma2ma.__doc__ = _arma_docs['ma']
[docs] def arma2ar(self, lags=None):
lags = lags or self.lags
return arma2ar(self.ar, self.ma, lags=lags)
arma2ar.__doc__ = _arma_docs['ar']
@property
def arroots(self):
"""Roots of autoregressive lag-polynomial"""
return self.arpoly.roots()
@property
def maroots(self):
"""Roots of moving average lag-polynomial"""
return self.mapoly.roots()
@property
def isstationary(self):
"""
Arma process is stationary if AR roots are outside unit circle
Returns
-------
isstationary : boolean
True if autoregressive roots are outside unit circle
"""
if np.all(np.abs(self.arroots) > 1.0):
return True
else:
return False
@property
def isinvertible(self):
"""
Arma process is invertible if MA roots are outside unit circle
Returns
-------
isinvertible : boolean
True if moving average roots are outside unit circle
"""
if np.all(np.abs(self.maroots) > 1):
return True
else:
return False
[docs] def invertroots(self, retnew=False):
"""
Make MA polynomial invertible by inverting roots inside unit circle
Parameters
----------
retnew : boolean
If False (default), then return the lag-polynomial as array.
If True, then return a new instance with invertible MA-polynomial
Returns
-------
manew : array
new invertible MA lag-polynomial, returned if retnew is false.
wasinvertible : boolean
True if the MA lag-polynomial was already invertible, returned if
retnew is false.
armaprocess : new instance of class
If retnew is true, then return a new instance with invertible
MA-polynomial
"""
# TODO: variable returns like this?
pr = self.maroots
mainv = self.ma
invertible = self.isinvertible
if not invertible:
pr[np.abs(pr) < 1] = 1. / pr[np.abs(pr) < 1]
pnew = np.polynomial.Polynomial.fromroots(pr)
mainv = pnew.coef / pnew.coef[0]
if retnew:
return self.__class__(self.ar, mainv, nobs=self.nobs)
else:
return mainv, invertible
[docs] def generate_sample(self, nsample=100, scale=1., distrvs=None, axis=0,
burnin=0):
"""
Simulate an ARMA
Parameters
----------
nsample : int or tuple of ints
If nsample is an integer, then this creates a 1d timeseries of
length size. If nsample is a tuple, creates a len(nsample)
dimensional time series where time is indexed along the input
variable ``axis``. All series are unless ``distrvs`` generates
dependent data.
scale : float
standard deviation of noise
distrvs : function, random number generator
function that generates the random numbers, and takes sample size
as argument
default: np.random.randn
TODO: change to size argument
burnin : integer (default: 0)
to reduce the effect of initial conditions, burnin observations
at the beginning of the sample are dropped
axis : int
See nsample.
Returns
-------
rvs : ndarray
random sample(s) of arma process
Notes
-----
Should work for n-dimensional with time series along axis, but not
tested yet. Processes are sampled independently.
"""
if distrvs is None:
distrvs = np.random.normal
if np.ndim(nsample) == 0:
nsample = [nsample]
if burnin:
# handle burin time for nd arrays
# maybe there is a better trick in scipy.fft code
newsize = list(nsample)
newsize[axis] += burnin
newsize = tuple(newsize)
fslice = [slice(None)] * len(newsize)
fslice[axis] = slice(burnin, None, None)
fslice = tuple(fslice)
else:
newsize = tuple(nsample)
fslice = tuple([slice(None)] * np.ndim(newsize))
eta = scale * distrvs(size=newsize)
return signal.lfilter(self.ma, self.ar, eta, axis=axis)[fslice]


"Some writers enjoy writing, I am told. Not me. I enjoy having written." George R.R. Martin, http://grrm.livejournal.com/69850.html
2/4/2009, 4:54:35 PM
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link--- layout: tweet ---
"Some writers enjoy writing, I am told. Not me. I enjoy having written." George R.R. Martin, http://grrm.livejournal.com/69850.html
2/4/2009, 4:54:35 PM
Favs: 0
Retweets: 0
link


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BJP govt to protect Jharkhand’s ‘jal, jungle, jameen’, says Modi
The Prime Minister congratulated the Raghubar Das-led State government for completing his five-year term, a first in Jharkhand since it attained statehood.
by PTIPrime Minister Narendra Modi on November 25 asserted that the BJP governments at the Centre and the State would continue to protect Jharkhand’s ‘jal, jungle and jameen’ (water, forest and land).
Addressing a poll meeting here, the Prime Minister congratulated the Raghubar Das-led State government for completing his five-year term, a first in Jharkhand since it attained statehood.
Condemning last week’s Naxal violence in the poll-bound State, the PM also paid tribute to the four policemen who were killed in the attack.
“The BJP govt has provided good governance in Jharkhand over the past five years. That is why, for the first time in the State’s history, a chief minister completed his five-year term,” he noted.
Mr. Modi insisted that the Jharkhand government has worked day and night to end corruption in the last five years.
“The BJP governments at the Centre and the state would continue to protect Jharkhand’s ‘jal’, jungle and ‘jameen’ (water, forest and land), no matter what the opposition parties say. The State has made efforts to curb naxalism in the state and would continue to fight against the menace,” he added.


Let's start with some data that we want to get from API and render to the screen
Let's say we get data of football competitions of last year:
We're gonna use couple of things for that
We use difrectives for that in Angular
<champ-list competitions="competitions">
To Fetch the data from third-party API
CompetitionsService.fetchCompetitions(year)
Then we should have this:


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--- layout: page title: About header-img: "img/about-bg.png" ---
A proponent of the precise, efficient nature of coding while also craving to go snowboarding every chance that I possibly can. Keep life simple. Keep life balanced.


You're moving to the valley...
You’ve inherited your grandfather’s old farm plot in Stardew Valley. Armed with hand-me-down tools and a few coins, you set out to begin your new life. Can you learn to live off the land and turn these overgrown fields into a thriving home? It won’t be easy. Ever since Joja Corporation came to town, the old ways of life have all but disappeared. The community center, once the town’s most vibrant hub of activity, now lies in shambles. But the valley seems full of opportunity. With a little dedication, you might just be the one to restore Stardew Valley to greatness!
Now with Multiplayer! Invite 1-3 players to join you in the valley! Players can work together to build a thriving farm, share resources, and build relationships with townspeople or each other. As more hands are better than one, players have the option to scale profit margin on produce sold for a more challenging experience.
| Release date: October 05, 2017 | Developer: ConcernedApe |
|---|---|
| Players: up to 4 players | Game file size: 1.5 GB |
| Genre: Indie, Simulation, Role-Playings | Supported Languages: Japanese, French, German, Italian, Spanish, Korean, Portuguese, Russian, Chinese, English |
| Publisher: ConcernedApe | |
|
Supported Play Modes:
Software compatibility and play experience may differ on Nintendo Switch Lite. Additional accessories may be required (sold separately). See support for details. |
Pegi Rating:
Simulated Gambling, Use of Alcohol, Fantasy Violence, Use of Tobacco, Mild Blood, Mild Language |
|
Play online, access classic Super NES™ games, and more with a Nintendo Switch Online membership.Learn More > This game supports: |
Nintendo Switch Online membership (sold separately) and Nintendo Account required for online play. Not available in all countries. Internet access required for online features. Terms apply nintendo.com/switch-online
Stardew Valley © ConcernedApe LLC 2016-2020. All rights reserved.
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UN says G5 Sahel force needs more support in anti-militant fight
UNITED NATIONS: The five-nation G5 military task force in the Sahel faces persistent training and equipment shortfalls at a time of spiralling violence in the war against armed Islamist groups in the region, according to a UN report on Tuesday (Nov 12).
The force was set up in 2014 to tackle the militant threat in the Sahel region of Africa, and is made up of troops from Burkina Faso, Mali, Mauritania, Niger and Chad.
Supported by France, the G5 Sahel could eventually replace soldiers from France's 4,500-strong Barkhane force, deployed in the Sahel region of Africa since 2014.
"The security situation continued to deteriorate across the Sahel region, with attacks by terrorist groups against civilians and security forces and persistent violence along community lines," the UN report, submitted to the UN Security Council by Secretary General Antonio Guterres, said.
The period covered by the report, between May and October 2019, "was marked by low-intensity activity" by the Sahel force due to the rainy season "and the impact of persistent equipment and training shortfalls on its operations," Guterres said.
"I remain deeply concerned about the spiralling violence in the Sahel, which has spread to coastal States of West Africa, along the Gulf of Guinea," the document read.
"Terrorist groups have strengthened their foothold across the Sahel region, making large swaths of territory unstable and stoking ethnic violence, especially in Burkina Faso and Mali."
Since January more than 1,500 civilians have been killed in Burkina Faso and Mali, and more than one million people have been internally displaced across the five countries - more than twice the number of persons displaced in 2018.
"To fully play its role and yield more tangible results, the Joint Force will need more support," Guterres said.
The Sahel countries have called for a stronger UN mandate for the force and more funds, Guterres said.
However, this does not have US support at the United Nations, as Washington prefers to offer bilateral assistance to the affected countries.


|
|
void | printTab () |
| | Prints spaces depending on the tab size.
|
| |
|
void | dealWithDocPropertyErrors () |
| | Checks for all possible errors in document properties.
|
| |
| void | validateInteger (const int toValidate, const char description[], const int lowerLimit, const int upperLimit) |
| | Validates the integer passed in as one the arguments Validates the integer passed in as an argument against the limits provided. Uses the description argument to print an error. More...
|
| |
| int | numberOfDigits (const int num) |
| | Returns the number of digits of the integer passed in. More...
|
| |
| void | printPageNumber () |
| | Prints the page number center-aligned. More...
|
| |
|
void | actionIfReachedEndOfPage () |
| | Called when we reach the end of a page Prints the page number, increments it and resets the line number.
|
| |
| void | removeFirstAndLastChar (char **string) |
| | Removes first and last character of the string passed "by reference". More...
|
| |
| void | capitalize (char **string) |
| | Capitalizes the string passed "by reference". More...
|
| |
| int | charArraySize (const char *str) |
| | Returns the size of the character array argument. More...
|
| |
|
void | newLineActions () |
| | Called on a new line Prints a new line, increments the number of lines on current page, performs appropriate action if the end of page has been reached.
|
| |
| void | printCenterAligned (const char *s) |
| | Prints the string inserted as an argument in the output file center-aligned. More...
|
| |
| void | printLeftAligned (const char *s, const int charsUsed) |
| | Prints the string argument left-aligned. More...
|
| |
| void | printDocumentProperties () |
| | Prints the title, author and date in the center by calling. More...
|
| |
|
void | addLineNumberToLastPage () |
| | Prints new lines until we are at the end of the page and then prints the line number in the center.
|
| |
| void | freeMemory () |
| | Frees memory created by. More...
|
| |
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void | yyerror (const char *) |
| |
|
int | yylex (void) |
| |
|
| validateInteger ($5, "characters per line", MIN_CHARS_PER_LINE, INT_MAX) |
| |
|
| fprintf (yyout, "%d. ", sectionCount) |
| |
|
| printLeftAligned (sectionName, usedCharsOnLine) |
| |
|
| printLeftAligned (paragraphName, tabSize) |
| |
|
| if (enumerateFlag) fprintf(yyout |
| |
|
else | fprintf (yyout, "* ") |
| |
|
| if (tabSize > 5) for(int i=0 |
| |
|
| int | linesPerPage |
| |
|
int | charsPerLine = $5 |
| |
|
int | lineNumberOnPage = 1 |
| |
|
int | pageNumber = 1 |
| |
|
int | sectionCount = 1 |
| |
|
int | currentEnumeratedListItem = 1 |
| |
|
bool | enumerateFlag |
| | Flag for enumeration/bullet points mode When this is true, we are in enumeration mode and any list items will be considered as an enumerate list instead of bullet points.
|
| |
|
int | docPropertyCounters [NUMBER_OF_DOC_PROPERTIES] |
| | An array of the document property counters An array with counters of how many times each of the document properties appears in the input file. The order of the properties is defined in the enum below.
|
| |
|
FILE * | yyout |
| |
|
int | yylineno |
| |
|
int | tabSize = $3 |
| |
|
union { |
|
int iValue |
| |
|
char * sValue |
| |
| }; | |
| |
|
error verbose start file token LBRACE RBRACE LPAREN RPAREN COMMA token DOCUMENT ITEMIZE ENUMERATE token BEGIN_ END token PAGESETUP TABSIZE TITLE AUTHOR DATE token SECTION PARAGRAPH ITEM NEWLINE token< iValue > INTEGER token< sValue > DDMMYYYYDATE STRING | file |
| |
|
beginDocument | __pad0__ |
| |
|
docProperties | __pad1__ |
| |
|
pageSetupProperty | __pad2__ |
| |
|
pageSetupProperty lines per | page |
| |
|
pageSetupProperty lines per | INT_MAX |
| |
|
tabSizeProperty | __pad3__ |
| |
|
tabSizeProperty tab | size |
| |
|
titleProperty | __pad4__ |
| |
|
authorProperty | __pad5__ |
| |
|
dateProperty | __pad6__ |
| |
|
textProperties | __pad7__ |
| |
|
textProperty | __pad8__ |
| |
|
sectionProperty | __pad9__ |
| |
|
char * | sectionName = $3 |
| |
|
int | usedCharsOnLine = numberOfDigits(sectionCount++) + 2 |
| |
|
paragraphProperty | __pad10__ |
| |
|
removeFirstAndLastChar & | paragraphName |
| |
|
itemizeProperty | __pad11__ |
| |
|
enumerateProperty | __pad12__ |
| |
|
beginItemize | __pad13__ |
| |
|
endItemize | __pad14__ |
| |
|
beginEnumerate | __pad15__ |
| |
|
endEnumerate | __pad16__ |
| |
|
itemProperties | __pad17__ |
| |
|
itemProperty | __pad18__ |
| |
|
removeFirstAndLastChar & | itemName |
| |
|
| d |
| |
|
|
const int | MIN_TAB_SIZE = 0 |
| |
|
const int | MAX_TAB_SIZE = 7 |
| |
|
const int | MIN_LINES_PER_PAGE = 1 |
| |
|
const int | MIN_CHARS_PER_LINE = 20 |
| |
|
|
char * | title = temp |
| |
|
char * | author = temp |
| |
|
char * | date |
| |
yacc source file for miniTeX
- Author
- hb20007


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