The next day,we woke up prepared our self and then we wore our swimming costume to go to the ocean.We found it was low tide.A tour gide came and gave us a tour.
We saw many animals hidding under rocks. One of the animals we saw first was called sea urchin.The female ones were brown and the male ones are black.Another animal we saw was called a stone fish.It blends with the rocks because it has the same colour with the rocks.That's how it got its name.The stone fish has a poison spikes on their scales.Another animal we saw was a sea animal.Its protection is its gum.Sea animal has sticky gum which is poisonus to other animals excpt from Humans.We came back from the ocean and we went to the swimming pool.
We ate lunch whent to the swimming.At 4 oclock,we went to drink cocoa.After that we went to the ocean the waves were big.
After the ocean we went to shower, change and went to eat supper.After supper I went with my small cousin to Coco Jambo.Coco Jambo is the room were you can play.We played and then my brother and my big cousin came to play too.Then my father came to play with me pool.We played until the place was closed.We went back home to sleep.


Activities and Groups within the Parish
Ascent Movement
One of the ‘new movements’ in the Church, for people in their middle years who are called to be Active, Spiritual, Caring, Enlightened, Needy and Thankful. The group also aims to build a link between the young and the not so young in the parish. Meetings are usually held on the first Wednesday of each month.
For further information, contact Veronica Sowerby or John Green. Visit the Hallam Ascent website for information about forthcoming meetings.
Afternoon Tea
A traditional afternoon tea is held in the Assisi Hall every second Wednesday of the month from 2pm to 4pm at a cost of £3 per person. Everyone welcome. If you need a lift or can offer lifts, please contact Anne-Marie Appleton.
Dance Club
This is a Thursday evening activity for ladies of any age and ability. Complete beginners are very welcome. It takes place in the Assisi Hall between 8 p.m. and 9 p.m. The cost is £30 for 10 sessions. The classes are led by fully-qualified dance tutors. We incorporate a wide range of dance types, with the aim of having fun and enjoyment, culminating in the staging of an annual show which raises money for charities supported by the parish. For further details, contact Grazyna Swales.
Inspir Prayer Group
The Parish Inspir Prayer Group meets monthly on Mondays from 10am until 12 noon. Contact Jacinta Campbell or Lindsay Reynolds for dates and location.
Little Fishes
Praise and Play for 0 - 5 years, with carers, monthly on Mondays from 1.45 p.m. to 3.00 p.m. Meet in the Assisi Hall and then in the Blessed Sacrament Chapel. For further information, contact Clare Byrne.
The Rosary
Friday after morning Mass. For more information, contact Elizabeth Davison or Brian Sowerby.
St. Vincent De Paul Society
The SVP was founded over 160 years ago with volunteers dedicated to helping the poor, sick and lonely and housebound, Catholic or not. Today, the society has almost a million members working in five continents for the benefit of others. Contact Kevin McHale for further details.
Welcoming of new Parishoners
A group of existing parishioners visits those new to the Parish in their homes in order to give them a formal welcome to St. Francis Parish and to outline the various activities and facilities available within the Parish.
200 Club
We run this lottery to raise money for the Parish. Membership entitles you to enter twelve draws per year. A total of £740 is paid out in prizes each year, £30 in eight months of the year and £125 each quarter. The club usually raises over £600 per year for the parish.
You can join by contacting Kevin Exell on 0114 2665375. You will need to set up a standing order of £13 a year, payable quarterly, half yearly or annually to the Club - a sum equivalent to only 25p per week! Some parishioners have two or even three tokens in each draw; there is no limit to the number of tokens you can purchase. (Registered under the Gaming Act 2005).


I am a Front End Developer with a passion for clean code, plenty of comments, and lots of commits. I am currently taking new projects and love working with clients who desire clean, elegant design and consistent communication.
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CodeNewb Meetup Every 3rd Thursday 6:30pm LVL1 HackerSpace Louisville, KY


This phone application has been prepared by Nick Evevsky and Peter Traeg for the 2014 AT&T Rochester Civic App Challenge.
Special thanks go to the City of Rochester, NY Public Market Office and the Friends of the Rochester, NY Public Market.
The software developed for this application is Open Source under the MIT license and is allowed to be freely used, modified, and shared.
For more information about this app, visit http://ptraeg.github.io/publicmarketguide/


and I'm currently studying Systems Engineering in Universidad de los Andes in Bogotá, Colombia.
I'm interested in learning and adquiring new skills, such as Web development, App development, and Machine learning.
Universidad de los Andes (2015 – Present)


Well, the Plexdata Logging Writer is nothing else but yet another implementation of a logging framework. Someone may ask “Do I need it?” For sure, the answer is “maybe”. Thus, feel invited to test it.
The whole project is split into different parts to be able to choose only the necessary logging functionality. These parts are shown in table below.
| Library | Description |
|---|---|
Plexdata.LogWriter.Abstraction.dll |
This library serves as the base of all other logging writer implementations and defines all interfaces and base implementations that are globally shared between other projects. Current target framework of this library is the .NET Standard 2.0. |
Plexdata.LogWriter.Composite.dll |
This library represents an ILogger derived implementation which supports composite logging.
This logger version is available on any platform. Current target framework of this library is the
.NET Standard 2.0.
|
Plexdata.LogWriter.Console.dll |
This library contains all ILogger derived interfaces which especially support console
logging. Other implementations, such as the settings, which refer to console logging are
also part of this library. Current target framework of this library is the .NET Standard 2.0.
|
Plexdata.LogWriter.Console.Standard.dll |
This library represents an ILogger derived implementation which supports standard console
logging. This logger version is available on any platform. Current target framework of this
library is the .NET Standard 2.0.
|
Plexdata.LogWriter.Console.Windows.dll |
This library represents an ILogger derived implementation which especially supports console
logging for Windows applications. But keep in mind, this logger version is only available on
Windows™ platforms! Current target framework of this library is the .NET Standard 2.0.
|
Plexdata.LogWriter.Mail.dll |
This library represents an ILogger derived implementation which supports mail–based
logging. This logger version is available on any platform. Current target framework of this library
is the .NET Standard 2.0.
|
Plexdata.LogWriter.Network.dll |
This library represents an ILogger derived implementation which supports network–based
logging and combined with logging type GELF it becomes possible to send logging messages to a
Graylog server. This logger version is available on any platform. Current target framework of this
library is the .NET Standard 2.0.
|
Plexdata.LogWriter.Persistent.dll
|
This library represents an ILogger derived implementation which supports persistent file logging.
This logger version is available on any platform. Current target framework of this library is the
.NET Standard 2.0.
|
Plexdata.LogWriter.Stream.dll
|
This library represents an ILogger derived implementation which supports stream–based logging.
This logger version is available on any platform. Current target framework of this library is the
.NET Standard 2.0.
|
The whole software has been published under the terms of MIT License. See section Licensing for more information.


Ariana Grande puts herself on vitamin drip after tearfully cancelling tour show
Ariana Grande has taken extreme measures to overcome her nasty illness, by hooking herself up to a vitamin IV drip hours after cancelling her latest Sweetener tour show.
The Thank U, Next singer has been battling a mystery illness since August and it got the best of her this weekend, prompting her to scrap her performance at Lexington’s Rupp Arena on Sunday evening.
In a tearful Instagram video, Ari told her followers: ‘It hurts so bad to swallow.
‘I unfortunately don’t think I’ll be able to push through tonight, and I’m so … sorry.’
Bless her heart.
Fans and Ari’s celebrity peers have been equally concerned about her wellbeing, including Barbra Streisand who tweeted some suggestions for the singer to overcome the illness once and for all.
‘Take a strong Vitamin C drink with some Manuka honey and of course get some chicken soup! Bx,’ Barbra told the popstar.
Ari was a little starstruck by the iconic singer’s kind tweet and replied: ‘My goodness. love you so so much. thank you my sweetest.’
Advertisement Advertisement
Barbra wasn’t the only celebrity dishing out advice for Ari as British singer FKA twigs provided a soup recipe.

The 26-year-old then cosied up in bed to binge on episodes of Gossip Girl.
Sounds like the perfect evening to us – nasty colds aside, of course.
On Saturday, the 7 Rings hitmaker warned fans that there was a chance she’d have to cancel her next concert, revealing her head was ‘splitting’ while performing in Charlottesville the night before.
Ariana explained: ‘So I’m still very sick.  I don’t know how it’s possible but my throat and head are still in so much pain.
‘I sound okay I’m just in a lot of pain and it’s difficult to breathe during the show. I am seeing my doctor and trying my v vest to get better for tomorrow’s show.’
She continued: ‘Please take this as a gentle heads up…
‘I don’t want anyone to feel blindsided tomorrow if God forbid I can’t make the show happen. ‘I’m on all the meds. Getting IV drips, doing everything I possibly can to pull through. Mum and friends are taking good care of me. Just a scary feeling.’
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


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THIEVES [LES VOLEURS] A film review by James Berardinelli Copyright 1997 James Berardinelli
RATING (0 TO 10): 7.5 Alternative Scale: *** out of ****
France, 1996 U.S. Release Date: varies (limited) Running Length: 1:57 MPAA Classification: R (Sex, nudity, profanity, violence, mature themes) Theatrical Aspect Ratio: 1.85:1
Cast: Catherine Deneuve, Daniel Auteuil, Laurence Cote, Fabienne Babe, Didier Bezace, Julien Riviere Director: Andre Techine Producer: Alain Sarde Screenplay: Michel Alexandre, Pascal Bonitzer, Gilles Taurand, Andre Techine Cinematography: Jeanne Lapoirie Music: Philippe Sarde U.S. Distributor: Sony Pictures Classics
THIEVES is Andre Techine's followup to his unexpectedly successful 1995 art-house entry, WILD REEDS. In fact, Techine drew so much interest for his installment of the French TV series, ALL THE BOYS AND GIRLS OF THE WORLD, that Filmopolis Pictures rushed out and acquired the distribution rights to Techine's previous film, MA SAISON PREFEREE. Now, the acclaimed director whose movies were once rarely seen beyond New York's Walter Reade Theater is reaching increasingly larger and more enthusiastic audiences.
Actually, in the wake of MA SAISON PREFEREE and WILD REEDS, THIEVES represents a slight step down. Emphasis, however, on slight. The film features riveting performances by French icons Catherine Deneuve and Daniel Auteuil as two points of a romantic triangle. The third component is essayed by the sexy Laurence Cote, who, despite ten years of French screen credits, is a virtual newcomer to U.S. viewers. The acting, a hallmark of Techine's films, has never been stronger than in THIEVES.
Auteuil plays Alex, a French cop with a chip on his shoulder and a penchant for keeping his emotions under lock and key. Auteuil, who does this kind of role so well (check out UN COUER EN HIVER for an example), is perfectly cast, and never for the briefest of moments does his portrayal ring false. Deneuve, the ageless star who is returning opposite Auteuil (the two played brother and sister in MA SAISON PREFEREE), is superlative as Marie, the fragile philosophy professor who falls in love often and easily. On the other hand, although Cote gives a strong performance, her character, Juliette, is more of a catalyst than a three-dimensional individual. Juliette's presence remains enigmatic and sketchily drawn, and is all-but-forgotten during the movie's final third.
The event that jump-starts THIEVES is the murder of Alex's criminal brother, Ivan (Didier Bezace), who was the head of a car-stealing ring. Juliette is somehow mixed up in the ring, but the situation is complicated because she's sleeping with Alex, who has been trying to gather enough evidence to put his brother behind bars. Marie, Juliette's other lover, becomes involved in the investigation when Juliette disappears and Alex approaches her to see whether she has been in touch with the young woman. Through a series of flashbacks presented from four different perspectives (Marie's, Juliette's, Alex's, and that of Alex's adolescent nephew, Justin), Techine develops both plot and characters.
The best parts of THIEVES are the beginning and end, which concentrate on Alex and Marie, both as they interact with Juliette and with each other. The middle section of the film is somewhat murky, and, with Auteuil and Deneuve largely off-screen, less compelling. Taking nothing away from Cote's performance, she doesn't hold our attention the way her co-stars do, in part because her character doesn't exhibit the same emotional depth or breadth. This segment of the movie also features the most exposition, introducing us to the inner workings of the thieves' ring. Compared with the emotional tension choreographed by Techine when he concentrates on the romantic triangle, this aspect of THIEVES seems mundane.
THIEVES' payoff occurs during the last third, when Alex and Marie, ostensibly searching for Juliette, become entwined in each others' lives. This isn't love, at least not in the conventional sense, but something that is, paradoxically, less profound and more complex. As the two of them try to establish a sense of trust, the normally-open Marie finds herself shutting down while the emotionally-closeted Alex discovers, much to his surprise, that he is capable of developing feelings for a woman whom he initially treats with contempt. Ultimately, the film's anchor is Alex, whose highest hope for life is not to feel pain, who never laughs and sees evil everywhere, and whose personality alters with brilliant-but-unmistakable subtlety.
Techine's development of Alex and Marie is masterful; Auteuil and Deneuve keep our attention riveted to the screen whenever they're on. And, while the director doesn't succeed in plumbing the emotional depths reached by MA SAISON PREFEREE, there are elements of THIEVES that touch us nearly as forcefully -- those moments just aren't as plentiful. So, although THIEVES is strong and keenly-insightful, it is the least imposing of Techine's trio of U.S. releases.
- James Berardinelli e-mail<EMAIL_ADDRESS>ReelViews web site: http://www.cybernex.net/~berardin
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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POLITICS
FACULTY:
Name:
Picture:
Dina Badie
Rob Bosco
Chelsea Ebin
Lori Hartmann
Benjamin Knoll
Chris Paskewich
Katy Schwaeble
Daniel Stroup
John Wilson
"Return to Home:"


Extract river discharges from the supplied river positions for the FVCOM grid in Mobj. get_EHYPE_rivers(Mobj, dist_thresh) DESCRIPTION: For the positions in Mobj.rivers.positions, find the nearest unstructured grid node and extract the river discharge from Mobj.rivers.river_flux. The river positions must fall within the specified distance (dist_thresh). If multiple rivers are assigned to the same node, the river with the larger of the set of discharges is used. INPUT: Mobj - MATLAB mesh object containing: * have_lonlat - boolean to check for spherical coordinates. * lon, lat - positions for the unstructured grid. * tri - triangulation table for the unstructured grid. * nVerts - number of nodes in the grid. * read_obc_nodes - open boundary node IDs. * rivers - river data struct with the following fields: - positions - river positions in lon, lat. - names - list of river names - river_flux - path to the EHYPE ASCII file data directory. dist_thresh - maximum distance away from a river node beyond which the search for an FVCOM node is abandoned. Units in degrees. model_year - [optional] when giving climatology, a year must be specified so that the time series can be anchored in time. The returned time series will be 3 years long centred on the specified year. Discharges will be repeated for the two additional years. exclude - [optional] give an array of river numbers to exclude (for example if they are particularly bad quality data or are within the threshold but otherwise should be excluded from the model). Note, these must be numbers (not strings). ceh - [optional] if set as true, then the format of the discharge data is assumed to be "time,flux" which is valid if using non-EHYPE derived flux data (e.g. CEH-derived climatology). OUTPUT: Mobj.river_flux - volume flux at the nodes within the model domain. Mobj.river_nodes - node IDs for the rivers. At the moment, these are point sources only. Eventually, some rivers may have to be split over several nodes. Mobj.river_names - river names which fall within the model domain. For rivers where the discharge has been summed, the name is compoud, with each contributing name separated by a hyphen (-). Mobj.river_time - time series for the river discharge data EXAMPLE USAGE: Mobj = get_EHYPE_rivers(Mobj, 0.15) Author(s): Pierre Cazenave (Plymouth Marine Laboratory) Revision history: 2013-10-15 - First version based on get_FVCOM_rivers.m. 2013-11-14 - Update the help to reflect the functionality. 2013-11-15 - Add support for using a river climatology from the E-HYPE time series data (must be precomputed) instead of a specified section of the E-HYPE model output. 2013-12-12 - Remove some redundant variables. 2013-12-13 - Remove the loop through the time at the end and instead use greg2mjulian to work on the whole time vector array. 2014-01-22 - For nodes with mulitple rivers assigned, use the largest of the rivers rather than summing their fluxes. Also eliminate having two adjacent river nodes (instead use the average of their flux and assign the position to the first river node). 2014-05-15 - Add option to exclude rivers by name. 2014-05-19 - Add new option to use an alternatively formatted input climatology (two columns instead of the number in the EHYPE data). 2014-05-20 - Set boolean flag to true to indicate rivers and add number of rivers to the relevant field. 2014-05-29 - Fix issues with the climatology vs. timeseries allocation of the output arrays. ==========================================================================
0001 function Mobj = get_EHYPE_rivers(Mobj, dist_thresh, varargin) 0002 % Extract river discharges from the supplied river positions for the FVCOM 0003 % grid in Mobj. 0004 % 0005 % get_EHYPE_rivers(Mobj, dist_thresh) 0006 % 0007 % DESCRIPTION: 0008 % For the positions in Mobj.rivers.positions, find the nearest 0009 % unstructured grid node and extract the river discharge from 0010 % Mobj.rivers.river_flux. The river positions must fall within the 0011 % specified distance (dist_thresh). If multiple rivers are assigned to 0012 % the same node, the river with the larger of the set of discharges is 0013 % used. 0014 % 0015 % INPUT: 0016 % Mobj - MATLAB mesh object containing: 0017 % * have_lonlat - boolean to check for spherical coordinates. 0018 % * lon, lat - positions for the unstructured grid. 0019 % * tri - triangulation table for the unstructured grid. 0020 % * nVerts - number of nodes in the grid. 0021 % * read_obc_nodes - open boundary node IDs. 0022 % * rivers - river data struct with the following fields: 0023 % - positions - river positions in lon, lat. 0024 % - names - list of river names 0025 % - river_flux - path to the EHYPE ASCII file data directory. 0026 % dist_thresh - maximum distance away from a river node beyond 0027 % which the search for an FVCOM node is abandoned. Units in degrees. 0028 % model_year - [optional] when giving climatology, a year must be 0029 % specified so that the time series can be anchored in time. The 0030 % returned time series will be 3 years long centred on the specified 0031 % year. Discharges will be repeated for the two additional years. 0032 % exclude - [optional] give an array of river numbers to exclude (for 0033 % example if they are particularly bad quality data or are within the 0034 % threshold but otherwise should be excluded from the model). Note, 0035 % these must be numbers (not strings). 0036 % ceh - [optional] if set as true, then the format of the discharge data 0037 % is assumed to be "time,flux" which is valid if using non-EHYPE 0038 % derived flux data (e.g. CEH-derived climatology). 0039 % 0040 % OUTPUT: 0041 % Mobj.river_flux - volume flux at the nodes within the model domain. 0042 % Mobj.river_nodes - node IDs for the rivers. At the moment, these are 0043 % point sources only. Eventually, some rivers may have to be split 0044 % over several nodes. 0045 % Mobj.river_names - river names which fall within the model domain. For 0046 % rivers where the discharge has been summed, the name is compoud, 0047 % with each contributing name separated by a hyphen (-). 0048 % Mobj.river_time - time series for the river discharge data 0049 % 0050 % EXAMPLE USAGE: 0051 % Mobj = get_EHYPE_rivers(Mobj, 0.15) 0052 % 0053 % Author(s): 0054 % Pierre Cazenave (Plymouth Marine Laboratory) 0055 % 0056 % Revision history: 0057 % 2013-10-15 - First version based on get_FVCOM_rivers.m. 0058 % 2013-11-14 - Update the help to reflect the functionality. 0059 % 2013-11-15 - Add support for using a river climatology from the E-HYPE 0060 % time series data (must be precomputed) instead of a specified section 0061 % of the E-HYPE model output. 0062 % 2013-12-12 - Remove some redundant variables. 0063 % 2013-12-13 - Remove the loop through the time at the end and instead 0064 % use greg2mjulian to work on the whole time vector array. 0065 % 2014-01-22 - For nodes with mulitple rivers assigned, use the largest 0066 % of the rivers rather than summing their fluxes. Also eliminate having 0067 % two adjacent river nodes (instead use the average of their flux and 0068 % assign the position to the first river node). 0069 % 2014-05-15 - Add option to exclude rivers by name. 0070 % 2014-05-19 - Add new option to use an alternatively formatted input 0071 % climatology (two columns instead of the number in the EHYPE data). 0072 % 2014-05-20 - Set boolean flag to true to indicate rivers and add number 0073 % of rivers to the relevant field. 0074 % 2014-05-29 - Fix issues with the climatology vs. timeseries allocation 0075 % of the output arrays. 0076 % 0077 %========================================================================== 0078 0079 subname = 'get_EHYPE_rivers'; 0080 0081 global ftbverbose; 0082 if ftbverbose 0083 fprintf(['\nbegin : ' subname '\n']) 0084 end 0085 0086 % Check inputs 0087 if ~Mobj.have_lonlat 0088 error('Require unstructured grid positions in lon/lat format to compare against supplied river positions.') 0089 end 0090 0091 % Default to standard EHYPE formatted data and no ignored rivers. 0092 yr = []; 0093 ignore_list = []; 0094 ceh = false; 0095 0096 % If we have only three arguments, we have to assume we've been given a 0097 % year for the climatology. Otherwise, we need to read the arguments based 0098 % on keyword-value pairs. Really, we want keyword-value pairs all the time, 0099 % so silently work when given three arguments and don't mention it in the 0100 % help. This is going to bite me at some point in the future, I'm sure. 0101 if nargin == 3 0102 yr = varargin{1}; 0103 elseif nargin > 3 0104 for aa = 1:2:length(varargin) 0105 switch varargin{aa} 0106 case 'model_year' 0107 yr = varargin{aa + 1}; 0108 case 'exclude' 0109 ignore_list = varargin{aa + 1}; 0110 case 'ceh' 0111 ceh = varargin{aa + 1}; 0112 end 0113 end 0114 end 0115 0116 if (isempty(yr) && ceh) || (~isempty(yr) && ~isnumeric(yr)) 0117 error('Trying to do climatology, but don''t have an anchor year. Supply one via the ''model_year'' keyword-value pair.') 0118 end 0119 0120 % Separate the inputs into separate arrays. 0121 ehype_name = Mobj.rivers.names; 0122 ehype_xy = Mobj.rivers.positions; 0123 ehype_flow = Mobj.rivers.river_flux; 0124 0125 % If we've been given rivers to ignore, remove them now. 0126 if ~isempty(ignore_list) 0127 ignore_mask = ehype_name ~= ignore_list; 0128 0129 ehype_name = ehype_name(ignore_mask); 0130 ehype_xy = ehype_xy(ignore_mask, :); 0131 end 0132 0133 fv_nr = length(ehype_name); 0134 0135 % Check each location in the EHYPE positions against the grid in Mobj and 0136 % for the indices within the dist_thresh, load and extract the relevant 0137 % time series data. 0138 0139 vc = 0; % valid FVCOM boundary node counter 0140 0141 % We need to find the unstructured grid boundary nodes and exclude the open 0142 % boundary nodes from them. This will be our list of potential candidates 0143 % for the river nodes (i.e. the land coastline). 0144 [~, ~, ~, bnd] = connectivity([Mobj.lon, Mobj.lat], Mobj.tri); 0145 boundary_nodes = 1:Mobj.nVerts; 0146 boundary_nodes = boundary_nodes(bnd); 0147 coast_nodes = boundary_nodes(~ismember(boundary_nodes, [Mobj.read_obc_nodes{:}])); 0148 tlon = Mobj.lon(coast_nodes); 0149 tlat = Mobj.lat(coast_nodes); 0150 0151 fv_obc = nan; 0152 fvcom_names = cell(0); 0153 0154 % Initialise the flow array with a 366 day long time series of nans. This 0155 % array will be appended to (unless all rivers are outside the domain). 0156 % Only do this if we're doing climatology (signified by a non-empty year). 0157 if ~isempty(yr) 0158 fv_flow = nan(366, 1); 0159 end 0160 for ff = 1:fv_nr 0161 % Find the coastline node closest to this river. 0162 fv_dist = sqrt( ... 0163 (ehype_xy(ff, 1) - tlon).^2 + ... 0164 (ehype_xy(ff, 2) - tlat).^2); 0165 [c, idx] = min(fv_dist); 0166 if c > dist_thresh 0167 if ftbverbose 0168 fprintf('\tskipping river %07d (%f, %f [%fdeg away])\n', ehype_name(ff), ehype_xy(ff, 1), ehype_xy(ff, 2), c) 0169 end 0170 continue 0171 else 0172 if ftbverbose 0173 fprintf('candidate river %07d found (%f, %f)... ', ehype_name(ff), ehype_xy(ff, 1), ehype_xy(ff, 2)) 0174 end 0175 end 0176 0177 vc = vc + 1; 0178 0179 % We need to make sure the element in which this node occurs does not 0180 % have two land boundaries (otherwise the model sometimes just fills up 0181 % that element without releasing the water into the adjacent element). 0182 0183 % Find the other nodes which are joined to the node we've just found. 0184 % We don't need the column to get the other nodes in the element, only 0185 % the row is required. 0186 [row, ~] = find(Mobj.tri == coast_nodes(idx)); 0187 0188 if length(row) == 1 0189 % This is a bad node because it is a part of only one element. The 0190 % rivers need two adjacent elements to work reliably (?). So, we 0191 % need to repeat the process above until we find a node that's 0192 % connected to two elements. We'll try the other nodes in the 0193 % current element before searching the rest of the coastline (which 0194 % is computationally expensive). 0195 0196 % Remove the current node index from the list of candidates (i.e. 0197 % leave only the two other nodes in the element). 0198 mask = Mobj.tri(row, :) ~= coast_nodes(idx); 0199 n_tri = Mobj.tri(row, mask); 0200 0201 % Remove values which aren't coastline values (we don't want to set 0202 % the river node to an open water node). 0203 n_tri = intersect(n_tri, coast_nodes); 0204 0205 % Of the remaining nodes in the element, find the closest one to 0206 % the original river location (in fvcom_xy). 0207 [~, n_idx] = sort(sqrt( ... 0208 (ehype_xy(ff, 1) - Mobj.lon(n_tri)).^2 ... 0209 + (ehype_xy(ff, 2) - Mobj.lon(n_tri)).^2)); 0210 0211 [row_2, ~] = find(Mobj.tri == n_tri(n_idx(1))); 0212 if length(n_idx) > 1 0213 [row_3, ~] = find(Mobj.tri == n_tri(n_idx(2))); 0214 end 0215 % Closest first 0216 if length(row_2) > 1 0217 idx = find(coast_nodes == n_tri(n_idx(1))); 0218 % The other one (only if we have more than one node to consider). 0219 elseif length(n_idx) > 1 && length(row_3) > 1 0220 idx = find(coast_nodes == n_tri(n_idx(2))); 0221 % OK, we need to search across all the other coastline nodes. 0222 else 0223 % TODO: Implement a search of all the other coastline nodes. 0224 % My testing indicates that we never get here (at least for the 0225 % grids I've tested). I'd be interested to see the mesh which 0226 % does get here... 0227 continue 0228 end 0229 if ftbverbose 0230 fprintf('alternate node ') 0231 end 0232 end 0233 0234 % Add it to the list of valid rivers 0235 fv_obc(vc) = coast_nodes(idx); 0236 0237 % We are assuming that the river discharge data array y-dimension is 0238 % ordered the same as the positions in fvcom_xy. If they are not, then 0239 % the discharges for the rivers will be incorrect (i.e. you might put 0240 % the Severn discharge somewhere in the Baltic). 0241 fvcom_names{vc} = sprintf('%07d', ehype_name(ff)); 0242 fid = fopen(fullfile(ehype_flow, [fvcom_names{vc}, '.txt'])); 0243 assert(fid >= 0, 'Failed to open E-HYPE river flow data.') 0244 if isempty(yr) && ~ceh 0245 % Time series have a 2 line header. 0246 eflow = textscan(fid, '%s %f %f %f %f %f %f %f %f %f', 'delimiter', '\t', 'HeaderLines', 2, 'MultipleDelimsAsOne', 1); 0247 elseif ~isempty(yr) && ceh 0248 eflow = textscan(fid, '%s %f', 'delimiter', ' ', 'MultipleDelimsAsOne', 1); 0249 elseif ~isempty(yr) 0250 % Climatology, so we have no header. Are we using the original 0251 % EHYPE data or some other "time,flux" data? 0252 eflow = textscan(fid, '%s %f %f %f %f %f %f %f %f %f', 'delimiter', '\t', 'MultipleDelimsAsOne', 1); 0253 else 0254 error('Incorrect time set up. Check the ''ceh'' or ''model_time'' keyword-value pairs.') 0255 end 0256 fclose(fid); 0257 % Make sure we always have the right number of time steps. Truncate the 0258 % new data to fit the existing array or wrap the start of the time 0259 % series back to the end. 0260 new_t = length(eflow{2}); 0261 % Check if we're doing climatology in which case we can have different 0262 % length time series (for CEH vs. EHYPE derived climatologies, for 0263 % example). If we're not doing climatology, we have to assume the 0264 % modelled time series are all the same length, in which case just use 0265 % the values in new_t. 0266 if ~isempty(yr) 0267 old_t = length(fv_flow(:, 1)); 0268 else 0269 old_t = new_t; 0270 end 0271 diff_t = old_t - new_t; 0272 if new_t > old_t 0273 fv_flow(:, vc) = eflow{2}(1:old_t); 0274 elseif new_t < old_t 0275 fv_flow((1:new_t), vc) = eflow{2}; 0276 fv_flow(end - diff_t + 1:end, vc) = eflow{2}(1:diff_t); 0277 else 0278 fv_flow(:, vc) = eflow{2}; 0279 end 0280 if ftbverbose 0281 fprintf('added (%f, %f)\n', Mobj.lon(fv_obc(vc)), Mobj.lat(fv_obc(vc))) 0282 end 0283 0284 end 0285 0286 % Get the length of the EHYPE time series. 0287 ehype_nt = size(fv_flow, 1); 0288 0289 % Now we've got a list and some of the nodes will be duplicates. Use the 0290 % larger of the two discharge values assigned to those nodes and ditch the 0291 % smaller one. The output is stored in a new fv_uniq_flow array (names and 0292 % nodes are similarly stored in their unique format). 0293 fv_uniq_obc = unique(fv_obc); 0294 fv_uniq_flow = nan(ehype_nt, length(fv_uniq_obc)); 0295 fv_uniq_names = cell(length(fv_uniq_obc), 1); 0296 0297 fv_idx = 1:length(fvcom_names); 0298 for nn = 1:length(fv_uniq_obc) 0299 0300 dn = fv_idx(fv_obc == fv_uniq_obc(nn)); 0301 0302 % Instead of summing the values (which causes very large discharges 0303 % because of the way the E-HYPE river mouths are determined), use the 0304 % river flux with the largest mean over the entire time series (~20 0305 % years). 0306 flow_bar = mean(fv_flow(:, dn), 1); % get a mean for each time series 0307 [~, max_idx] = max(flow_bar, [], 2); 0308 fv_uniq_flow(:, nn) = fv_flow(:, dn(max_idx)); 0309 fv_uniq_names{nn} = fvcom_names{dn(max_idx)}; 0310 0311 % % This is the old way where nodes which are grouped together are 0312 % % summed. This yielded unrealistically high discharges, particularly at 0313 % % the Fowey near Plymouth. It probably did elsewhere too. 0314 %fv_uniq_flow(:, nn) = sum(fv_flow(:, dn), 2); 0315 % % Concatenate the river names so we know at least which rivers' 0316 % % discharges have been summed. 0317 %s = fvcom_names(dn); 0318 %s = [sprintf('%s-', s{1:end-1}, s{end})]; 0319 %fv_uniq_names{nn} = s(1:end-1); % lose the trailing -. 0320 0321 end 0322 0323 % Some of the river fluxes are being assigned to adjacent coastal nodes. 0324 % This is no good because we end up putting too much water in (similar 0325 % problem to the multiple river inputs on a single node which is fixed in 0326 % the loop above). So, we need to check each node and check its neighbours 0327 % aren't also rivers. If one (or more?) is, then we need to pick the larger 0328 % discharge (as defined by the mean over the entire time series) and use 0329 % that, removing the other node from the list. 0330 0331 % Finding the neighbouring nodes is not as straightforward as it might seem 0332 % at first. Simply using poly2cw is no good because our coastline is too 0333 % complicated for that (poly2cw assumes a convex hull). So, we'll find the 0334 % 2 nearest coastline nodes to each river node. If any of those 2 is also a 0335 % river, then merge the two rivers together (use the mean discharge). 0336 0337 % This breaks down a bit when three rivers are adjacent to one another, but 0338 % most of the time that shouldn't happen... 0339 0340 % Build a list of the nodes we're considering as neighbouring in 0341 % fv_dups_idx and fv_keep_idx. Store the meaned flow in fv_dups_flow (we'll 0342 % remove the original un-meaned flows at the end). Also store the 0343 % duplicated names in fv_dups_names. All these duplicate arrays will be 0344 % sorted out after the loop to find the adjacent nodes has finished. This 0345 % is less horrible than looping through and adjusting the values in the 0346 % original arrays because the mean of a meaned value and a new value is not 0347 % the same as the mean of the three original values, that is: 0348 % mean([mean([2, 5]), 10]) ~= mean([2, 5, 10]). 0349 0350 fv_dups_obc = cell(0); 0351 fv_dups_idx = []; 0352 fv_dups_flow = fv_uniq_flow; 0353 fv_dups_names = cell(0); 0354 fv_uniq_obc_orig = fv_uniq_obc; 0355 c = 0; 0356 for nn = 1:length(fv_uniq_obc) 0357 [~, idx] = sort(sqrt(... 0358 (Mobj.x(coast_nodes) - Mobj.x(fv_uniq_obc(nn))).^2 + ... 0359 (Mobj.y(coast_nodes) - Mobj.y(fv_uniq_obc(nn))).^2)); 0360 if any(ismember(fv_uniq_obc, coast_nodes(idx(2:3)))) 0361 % Build a list of the indices which we want to merge. 0362 fv_dups_idx = [fv_dups_idx, nn]; 0363 0364 c = c + 1; 0365 % Remove the current node from the list of river nodes. 0366 fv_dups_obc{c, 1} = fv_uniq_obc(nn); 0367 fv_dups_obc{c, 2} = fv_uniq_obc(ismember(fv_uniq_obc, coast_nodes(idx(2:3)))); 0368 fv_uniq_obc(nn) = nan; 0369 0370 % We can sort out the names and discharges here too. We'll store 0371 % the modified fluxes in a copy of the flux array so we can append 0372 % them once we've cleaned out the duplicate IDs. This way we can 0373 % still get accurate means if we need to reuse a particular node's 0374 % flux. Similarly, merge river names into a separate array. 0375 fv_dups_flow(:, fv_uniq_obc_orig == fv_dups_obc{c, 1}) = mean([fv_uniq_flow(:, fv_uniq_obc_orig == fv_dups_obc{c, 1}), ... 0376 fv_uniq_flow(:, fv_uniq_obc_orig == fv_dups_obc{c, 2})], 2); 0377 fv_dups_names{c} = sprintf('%s-%s', fv_uniq_names{fv_uniq_obc_orig == fv_dups_obc{c, 1}}, ... 0378 fv_uniq_names{fv_uniq_obc_orig == fv_dups_obc{c, 2}}); 0379 end 0380 end 0381 0382 clear c idx 0383 0384 % Now we can remove the duplicate data from the names, nodes and fluxes. 0385 fv_uniq_obc(fv_dups_idx) = []; 0386 fv_uniq_flow(:, fv_dups_idx) = []; 0387 fv_uniq_names(fv_dups_idx) = []; 0388 % And append the averaged flow, names and nodes to the relevant arrays. 0389 fv_uniq_flow = cat(2, fv_uniq_flow, fv_dups_flow(:, fv_dups_idx)); 0390 fv_uniq_obc = [fv_uniq_obc, [fv_dups_obc{:, 1}]]; 0391 fv_uniq_names = [fv_uniq_names; fv_dups_names']; 0392 0393 % % Merge the river discharges for the rivers we've identified as adjacent to 0394 % % one another on the coastline. 0395 % assert(mod(numel(fv_dups_obc), 2) ~= 1, 'Odd number of river pairs.') 0396 % assert(mod(length(unique(fv_dups_obc)), 2) ~= 1, 'Duplicate river node in being removed for two separate rivers.') 0397 % nr = length(fv_dups_obc); 0398 % for nn = 1:nr 0399 % % Find the indices for the flow data for the node to keep and remove. 0400 % [~, idx1] = find(fv_uniq_obc_orig == fv_dups_obc{nn, 1}); % keep 0401 % [~, idx2] = find(fv_uniq_obc_orig == fv_dups_obc{nn, 2}); % remove 0402 % idx = [idx1, idx2]; clear idx1 idx2 0403 % % Set the first column to the mean of the two rivers and set the other 0404 % % one to NaN. We'll clear out the NaNs afterwards. 0405 % fv_uniq_flow(:, idx(1)) = mean(fv_uniq_flow(:, idx), 2); 0406 % fv_uniq_flow(:, idx(2)) = nan; 0407 % 0408 % fv_uniq_names{idx(1)} = sprintf('%s-%s', fv_uniq_names{idx(1)}, ... 0409 % fv_uniq_names{idx(2)}); 0410 % fv_uniq_names{idx(2)} = ''; 0411 % end 0412 % 0413 % % Collapse the NaNs out of the flow data; rename the rivers to be 0414 % % hyphenated based on the two source rivers that have been merged. 0415 % nanidx = 1:size(fv_uniq_flow, 2); 0416 % nanidx = nanidx(~isnan(fv_uniq_flow(1, :))); 0417 % fv_uniq_flow = fv_uniq_flow(:, nanidx); 0418 % % Clear out the empty names too. 0419 % c = 0; 0420 % names = cell(0); 0421 % for i = 1:length(fv_uniq_names) 0422 % if ~isempty(fv_uniq_names{i}) 0423 % c = c + 1; 0424 % names{c, 1} = fv_uniq_names{i}; 0425 % end 0426 % end 0427 % fv_uniq_names = names; 0428 % clear names 0429 0430 0431 % Assign the relevant arrays to the Mobj. Flux is added in the section 0432 % dealing with either climatology or time series data. 0433 Mobj.river_nodes = fv_uniq_obc; 0434 Mobj.river_names = fv_uniq_names; 0435 Mobj.have_rivers = true; 0436 Mobj.nRivers = length(fv_uniq_obc); 0437 0438 % Create a Modified Julian Day time series of the EHYPE river data. Assume 0439 % all the EHYPE model outputs are for the same period and have the same 0440 % sampling interval. If the eflow{1} data is a number below 367, assume 0441 % we've been given a climatology. In that case, find the model year we're 0442 % using and generate the time string for a year each side of that year (to 0443 % cover the period at each end of a year). For that to work, we need to be 0444 % given the model year as an optional argument to the function. 0445 checkdate = cellfun(@str2num, eflow{1}); 0446 if max(checkdate) < 367 0447 % Climatology. 0448 if isempty(yr) && ~isnumeric(yr) 0449 error('For climatology, a year must be specified for the time series to be generated.') 0450 elseif ~isempty(yr) && isnumeric(yr) 0451 % Get to Gregorian first. 0452 0453 % Make three years of data starting from the year before the 0454 % current one. Do so accounting for leap years. 0455 daysinyr = [sum(eomday(yr - 1, 1:12)), ... 0456 sum(eomday(yr, 1:12)), ... 0457 sum(eomday(yr + 1, 1:12))]; 0458 % Offset the checkdate by one to add zero for the first day. 0459 % Alternative would be to specify the day as the end of the 0460 % previous month (or a day value of zero?). 0461 offsetdays = (1:sum(daysinyr)) - 1; 0462 mtime = datevec(datenum(yr - 1, 1, 1, 0, 0, 0) + offsetdays); 0463 Mobj.river_time = greg2mjulian(mtime(:, 1), mtime(:, 2), ... 0464 mtime(:, 3), mtime(:, 4), mtime(:, 5), mtime(:, 6)); 0465 0466 % Repeat the river flux for the climatology before adding to the 0467 % Mobj. 0468 Mobj.river_flux = [... 0469 fv_uniq_flow(1:daysinyr(1), :); ... 0470 fv_uniq_flow(1:daysinyr(2), :); ... 0471 fv_uniq_flow(1:daysinyr(3), :)]; 0472 else 0473 error('Non-numeric format for the climatology anchor year.') 0474 end 0475 else 0476 % Time series. 0477 rtimes = datevec(eflow{1}); 0478 Mobj.river_time = greg2mjulian(... 0479 rtimes(:, 1), rtimes(:, 2), rtimes(:, 3), ... 0480 rtimes(:, 4), rtimes(:, 5), rtimes(:, 6) ... 0481 ); 0482 0483 % Add the river flux to the Mobj for the time series data. 0484 Mobj.river_flux = fv_uniq_flow; 0485 0486 end 0487 0488 if ftbverbose 0489 fprintf('end : %s \n', subname) 0490 end 0491 0492 % Figure to check what's going on with identifying river nodes 0493 % figure 0494 % plot(ehype_xy(:, 1), ehype_xy(:, 2), '.', 'MarkerFaceColor', 'b') 0495 % hold on 0496 % plot(Mobj.lon(bnd), Mobj.lat(bnd), 'g.', 'MarkerFaceColor', 'g') 0497 % axis('square', 'tight') 0498 % plot(Mobj.lon(coast_nodes), Mobj.lat(coast_nodes), 'r.') 0499 % plot(Mobj.lon(Mobj.river_nodes), Mobj.lat(Mobj.river_nodes), 'k.', 'MarkerFaceColor', 'k') 0500 % % text(Mobj.lon(Mobj.river_nodes) + 0.025, Mobj.lat(Mobj.river_nodes) + 0.025, Mobj.river_names) 0501 % axis([min(Mobj.lon), max(Mobj.lon), min(Mobj.lat), max(Mobj.lat)]) 0502 % legend('EHYPE nodes', 'Grid boundary', 'Land nodes', 'Selected nodes', 'Location', 'NorthOutside', 'Orientation', 'Horizontal') 0503 % legend('BoxOff')


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I have a philosophy that there is no end to what can be learned, and with that very outlook I have passionately honed my own interests in enriching personal experience and knowledge through the projects that I create and work on. The completion of those projects always demonstrate a development of improvement with previous skills, as well as expanding into newer ones, while exploring greater concepts regarding data science, machine learning and deep learning.
Currently earning a Master's Degree in Statistical Data Science, together with a Masters in Quantitative Economics simultaneously. Diligent, exceptionally focused and highly detailed, with skills only surpassed by motivation.


Before Change
assert operation_run.is_upstream_done is False
// A running upstream
OperationRunStatus.objects.create(status=OperationStatuses.RUNNING,
operation_run=upstream_run1)
assert operation_run.is_upstream_done is False
// A failed upstream
OperationRunStatus.objects.create(status=OperationStatuses.FAILED,
operation_run=upstream_run1)
assert operation_run.is_upstream_done is True
// Add skipped upstream
upstream_run2 = OperationRunFactory()
operation_run.upstream_runs.set([upstream_run2])
OperationRunStatus.objects.create(status=OperationStatuses.SKIPPED,
operation_run=upstream_run2)
assert operation_run.is_upstream_done is True
// Add succeeded upstream
upstream_run3 = OperationRunFactory()
operation_run.upstream_runs.set([upstream_run3])
OperationRunStatus.objects.create(status=OperationStatuses.SUCCEEDED,
operation_run=upstream_run3)
assert operation_run.is_upstream_done is True
// Many done upstreams
operation_run.upstream_runs.set(
After Change
assert operation_run.is_upstream_done is False
// A running upstream
upstream_run1.status = OperationStatuses.RUNNING
upstream_run1.save()
assert operation_run.is_upstream_done is False
// A failed upstream
upstream_run1.status = OperationStatuses.FAILED
upstream_run1.save()
assert operation_run.is_upstream_done is True
// Add skipped upstream
upstream_run2 = OperationRunFactory()


|
libcoap 4.3.1
|
CoAP session internal information. More...
Go to the source code of this file.
Data Structures | |
| struct | coap_addr_hash_t |
| Only used for servers for hashing incoming packets. More... | |
| struct | coap_session_t |
| Abstraction of virtual session that can be attached to coap_context_t (client) or coap_endpoint_t (server). More... | |
| struct | coap_endpoint_t |
| Abstraction of virtual endpoint that can be attached to coap_context_t. More... | |
Macros | |
| #define | COAP_DEFAULT_SESSION_TIMEOUT 300 |
| #define | COAP_PARTIAL_SESSION_TIMEOUT_TICKS (30 * COAP_TICKS_PER_SECOND) |
| #define | COAP_DEFAULT_MAX_HANDSHAKE_SESSIONS 100 |
| #define | COAP_SESSION_REF(s) ((s)->ref |
| #define | COAP_ACK_TIMEOUT(s) ((s)->ack_timeout) |
| #define | COAP_ACK_RANDOM_FACTOR(s) ((s)->ack_random_factor) |
| #define | COAP_MAX_RETRANSMIT(s) ((s)->max_retransmit) |
| #define | COAP_NSTART(s) ((s)->nstart) |
| #define | COAP_DEFAULT_LEISURE(s) ((s)->default_leisure) |
| #define | COAP_PROBING_RATE(s) ((s)->probing_rate) |
| #define | COAP_DEFAULT_LEISURE_TICKS(s) |
| The DEFAULT_LEISURE definition for the session (s). More... | |
| #define | COAP_MAX_TRANSMIT_SPAN(s) |
| The MAX_TRANSMIT_SPAN definition for the session (s). More... | |
| #define | COAP_MAX_TRANSMIT_WAIT(s) |
| The MAX_TRANSMIT_WAIT definition for the session (s). More... | |
| #define | COAP_MAX_TRANSMIT_WAIT_TICKS(s) (COAP_MAX_TRANSMIT_WAIT(s) * COAP_TICKS_PER_SECOND) |
| #define | COAP_PROCESSING_DELAY(s) |
| The PROCESSING_DELAY definition for the session (s). More... | |
| #define | COAP_MAX_RTT(s) ((2 * COAP_DEFAULT_MAX_LATENCY) + COAP_PROCESSING_DELAY(s)) |
| The MAX_RTT definition for the session (s). More... | |
| #define | COAP_EXCHANGE_LIFETIME(s) |
| The EXCHANGE_LIFETIME definition for the session (s). More... | |
| #define | COAP_NON_LIFETIME(s) (COAP_MAX_TRANSMIT_SPAN(s) + COAP_DEFAULT_MAX_LATENCY) |
| The NON_LIFETIME definition for the session (s). More... | |
| #define | SESSIONS_ADD(e, obj) HASH_ADD(hh, (e), addr_hash, sizeof((obj)->addr_hash), (obj)) |
| #define | SESSIONS_DELETE(e, obj) HASH_DELETE(hh, (e), (obj)) |
| #define | SESSIONS_ITER(e, el, rtmp) HASH_ITER(hh, (e), el, rtmp) |
| #define | SESSIONS_ITER_SAFE(e, el, rtmp) for ((el) = (e); (el) && ((rtmp) = (el)->hh.next, 1); (el) = (rtmp)) |
| #define | SESSIONS_FIND(e, k, res) |
Functions | |
| void | coap_session_send_csm (coap_session_t *session) |
| Notify session transport has just connected and CSM exchange can now start. More... | |
| void | coap_session_connected (coap_session_t *session) |
| Notify session that it has just connected or reconnected. More... | |
| int | coap_session_refresh_psk_hint (coap_session_t *session, const coap_bin_const_t *psk_hint) |
| Refresh the session's current Identity Hint (PSK). More... | |
| int | coap_session_refresh_psk_key (coap_session_t *session, const coap_bin_const_t *psk_key) |
| Refresh the session's current pre-shared key (PSK). More... | |
| int | coap_session_refresh_psk_identity (coap_session_t *session, const coap_bin_const_t *psk_identity) |
| Refresh the session's current pre-shared identity (PSK). More... | |
| coap_session_t * | coap_new_server_session (coap_context_t *ctx, coap_endpoint_t *ep) |
| Creates a new server session for the specified endpoint. More... | |
| ssize_t | coap_session_send (coap_session_t *session, const uint8_t *data, size_t datalen) |
| Function interface for datagram data transmission. More... | |
| ssize_t | coap_session_write (coap_session_t *session, const uint8_t *data, size_t datalen) |
| Function interface for stream data transmission. More... | |
| ssize_t | coap_session_send_pdu (coap_session_t *session, coap_pdu_t *pdu) |
| Send a pdu according to the session's protocol. More... | |
| ssize_t | coap_session_delay_pdu (coap_session_t *session, coap_pdu_t *pdu, coap_queue_t *node) |
| coap_session_t * | coap_endpoint_get_session (coap_endpoint_t *endpoint, const coap_packet_t *packet, coap_tick_t now) |
| Lookup the server session for the packet received on an endpoint, or create a new one. More... | |
| size_t | coap_session_max_pdu_rcv_size (const coap_session_t *session) |
| Get maximum acceptable receive PDU size. More... | |
| coap_session_t * | coap_session_new_dtls_session (coap_session_t *session, coap_tick_t now) |
Create a new DTLS session for the session . More... | |
| void | coap_session_free (coap_session_t *session) |
| void | coap_session_mfree (coap_session_t *session) |
CoAP session internal information.
Definition in file coap_session_internal.h.
| #define COAP_DEFAULT_MAX_HANDSHAKE_SESSIONS 100 |
Definition at line 26 of file coap_session_internal.h.
| #define COAP_DEFAULT_SESSION_TIMEOUT 300 |
Definition at line 24 of file coap_session_internal.h.
| #define COAP_PARTIAL_SESSION_TIMEOUT_TICKS (30 * COAP_TICKS_PER_SECOND) |
Definition at line 25 of file coap_session_internal.h.
| #define SESSIONS_ADD | ( | e, | |
| obj | |||
| ) | HASH_ADD(hh, (e), addr_hash, sizeof((obj)->addr_hash), (obj)) |
Definition at line 420 of file coap_session_internal.h.
| #define SESSIONS_DELETE | ( | e, | |
| obj | |||
| ) | HASH_DELETE(hh, (e), (obj)) |
Definition at line 423 of file coap_session_internal.h.
| #define SESSIONS_FIND | ( | e, | |
| k, | |||
| res | |||
| ) |
Definition at line 432 of file coap_session_internal.h.
| #define SESSIONS_ITER | ( | e, | |
| el, | |||
| rtmp | |||
| ) | HASH_ITER(hh, (e), el, rtmp) |
Definition at line 426 of file coap_session_internal.h.
| #define SESSIONS_ITER_SAFE | ( | e, | |
| el, | |||
| rtmp | |||
| ) | for ((el) = (e); (el) && ((rtmp) = (el)->hh.next, 1); (el) = (rtmp)) |
Definition at line 429 of file coap_session_internal.h.


Colin Kaepernick: Twenty-four NFL teams set to attend workout
More than 24 NFL teams are set to attend Colin Kaepernick's open workout in Atlanta on Saturday.
Kaepernick, the former San Francisco 49ers quarterback who began kneeling on the sideline during the national anthem to bring attention to social injustice, has not played since the 2016 season.
The NFL scheduled a workout for Kaepernick at the Atlanta Falcons' practice facility. Former Cleveland Browns head coach Hue Jackson, with the help of former Miami Dolphins head coach Joe Philbin, will direct the session.
The league earlier had announced that 11 teams - Arizona, Atlanta, Cleveland, Denver, Detroit, Miami, New England, New York Giants, New York Jets, Tampa Bay, and Washington - confirmed they will attend in some capacity.
On Friday, ESPN reported that figure could more than double. NFL Network reported teams have until Saturday to submit names of people attending. Multiple outlets reported the league will not provide Kaepernick with a list of names of those attending, despite the belief the NFL had agreed to do so.
A video of the workout, along with an interview, will be prepared and sent to every head coach and general manager in the league.
NFL Network reported the receivers at the workout will be provided by the National Football Scouting Service, which is putting on the event and runs the NFL Scouting Combine each year. The receivers are expected to be mostly players who were on teams during the preseason.
Kaepernick, 32, has played six seasons in the NFL and participated in six postseason games, including Super Bowl XLVII in 2013, when the 49ers lost 34-31 to the Baltimore Ravens. Kaepernick passed for 302 yards and one touchdown in that game.
The Nevada product, who was a second-round draft pick by the 49ers in 2011, has passed for 12,271 yards in his career with 72 TDs and 30 interceptions. He also rushed for 2,300 yards and 13 more TDs.


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FROM MRS.COMFORT SOMBA. ABIDJAN COTE D' IVOIRE WEST AFRICA. Dearest, I am Mrs Comfort Somba from India. I am married to Late Mr Daniel Somba who worked with India embassy in Ivory Coast for nine years before he died in the year 2001. We were married for eleven years without a child. He died after a brief illness that lasted for only four days. Since his death I decided not to remarry or get a child outside my matrimonial home which the Bible is against. When my late husband was alive he deposited the sum of $5.5Million (Five Million Five Hundred Thousand U.S. Dollars) in one of the Security Company here in Abidjan. Recently, my Doctor told me that I have serious sickness which is cancer problem. The one that disturbs me most is my stroke sickness. Having known my condition I decided to donate this fund to a church or individual that will utilize it the way I am going to instruct herein. I want a God fearing person that will use this fund for orphanage Homes, widows, propagating the word of God and to endeavour that the house of God is maintained. The Bible made us to understand that Blessed is the hand that gives, I took this decision because I don't have any child that will inherit this money and I don' t want my husband's efforts to be wasted or abandoned or a situation where this money will be used in an ungodly way. Due to my health conditions, I have forwarded all the necessary documents required for this fund released to the Security Company and also an Authority Letter Directing the Security Company to release this deposited family treasure to you as soon as you Identify yourself to the Security Company as the deposited family treasures recipient. Kindly contact the Security Company and request for this deposited family treasure as I have directed you. Hoping to receive your reply Immediately. Yours in Christ, Mrs Comfort Somba.


{% include disqus.html %} {% unless site.respectfully_social %} {% include facebook_like.html %} {% include google_plus_one.html %} {% include twitter_sharing.html %} {% endunless %} {% include custom/after_footer.html %}


Over the past decade, influenza surveillance has been established in several African countries including Zambia. However, information on the on data quality and reliability of established influenza surveillance systems in Africa are limited. Such information would enable countries to assess the performance of their surveillance systems, identify shortfalls for improvement and provide evidence of data reliability for policy making and public health interventions.
We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza surveillance system (ISS) in Zambia during 2011–2017 using 9 attributes: (i) data quality and completeness, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability, (viii) utility, and (ix) sustainability. Each attribute was evaluated using pre-defined indicators. For each indicator we obtained the proportion (expressed as percentage) of the outcome of interest over the total. A scale from 1 to 3 was used to provide a score for each attribute as follows: < 60% (as obtained in the calculation above) scored 1 (weak performance); 60–79% scored 2 (moderate performance); ≥80% scored 3 (good performance). An overall score for each attribute and the ISS was obtained by averaging the scores of all evaluated attributes.
The overall mean score for the ISS in Zambia was 2.6. Key strengths of the system were the quality of data generated (score: 2.9), its flexibility (score: 3.0) especially to monitor viral pathogens other than influenza viruses, its simplicity (score: 2.8), acceptability (score: 3.0) and stability (score: 2.6) over the review period and its relatively low cost ($310,000 per annum). Identified weaknesses related mainly to geographic representativeness (score: 2.0), timeliness (score: 2.5), especially in shipment of samples from remote sites, and sustainability (score: 1.0) in the absence of external funds.
The system performed moderately well in our evaluation. Key improvements would include improvements in the timeliness of samples shipments and geographical coverage. However, these improvements would result in increased cost and logistical complexity. The ISSS in Zambia is largely reliant on external funds and the acceptability of maintaining the surveillance system through national funds would require evaluation.


FlagValues
Registry of 'Flag' objects.
tf.compat.v1.app.flags.FlagValues
A 'FlagValues' can then scan command line arguments, passing flag arguments through to the 'Flag' objects that it owns. It also provides easy access to the flag values. Typically only one 'FlagValues' object is needed by an application: flags.FLAGS
This class is heavily overloaded:
'Flag' objects are registered via setitem: FLAGS['longname'] = x # register a new flag
The .value attribute of the registered 'Flag' objects can be accessed as attributes of this 'FlagValues' object, through getattr. Both the long and short name of the original 'Flag' objects can be used to access its value: FLAGS.longname # parsed flag value FLAGS.x # parsed flag value (short name)
Command line arguments are scanned and passed to the registered 'Flag' objects through the call method. Unparsed arguments, including argv[0] (e.g. the program name) are returned. argv = FLAGS(sys.argv) # scan command line arguments
The original registered Flag objects can be retrieved through the use of the dictionary-like operator, getitem: x = FLAGS['longname'] # access the registered Flag object
The str() operator of a 'FlagValues' object provides help for all of the registered 'Flag' objects.
__init__
__init__()
Initialize self. See help(type(self)) for accurate signature.
__call__
__call__( argv, known_only=False )
Parses flags from argv; stores parsed flags into this FlagValues object.
All unparsed arguments are returned.
argv
: a tuple/list of strings.known_only
: bool, if True, parse and remove known flags; return the rest
untouched. Unknown flags specified by --undefok are not returned.The list of arguments not parsed as options, including argv[0].
Error
: Raised on any parsing error.TypeError
: Raised on passing wrong type of arguments.ValueError
: Raised on flag value parsing error.__contains__
__contains__(name)
Returns True if name is a value (flag) in the dict.
__getitem__
__getitem__(name)
Returns the Flag object for the flag --name.
__iter__
__iter__()
__len__
__len__()
append_flag_values
append_flag_values(flag_values)
Appends flags registered in another FlagValues instance.
flag_values
: FlagValues, the FlagValues instance from which to copy flags.append_flags_into_file
append_flags_into_file(filename)
Appends all flags assignments from this FlagInfo object to a file.
Output will be in the format of a flagfile.
NOTE: MUST mirror the behavior of the C++ AppendFlagsIntoFile from https://github.com/gflags/gflags.
filename
: str, name of the file.find_module_defining_flag
find_module_defining_flag( flagname, default=None )
Return the name of the module defining this flag, or default.
flagname
: str, name of the flag to lookup.default
: Value to return if flagname is not defined. Defaults
to None.The name of the module which registered the flag with this name. If no such module exists (i.e. no flag with this name exists), we return default.
find_module_id_defining_flag
find_module_id_defining_flag( flagname, default=None )
Return the ID of the module defining this flag, or default.
flagname
: str, name of the flag to lookup.default
: Value to return if flagname is not defined. Defaults
to None.The ID of the module which registered the flag with this name. If no such module exists (i.e. no flag with this name exists), we return default.
flag_values_dict
flag_values_dict()
Returns a dictionary that maps flag names to flag values.
flags_by_module_dict
flags_by_module_dict()
Returns the dictionary of module_name -> list of defined flags.
A dictionary. Its keys are module names (strings). Its values are lists of Flag objects.
flags_by_module_id_dict
flags_by_module_id_dict()
Returns the dictionary of module_id -> list of defined flags.
A dictionary. Its keys are module IDs (ints). Its values are lists of Flag objects.
flags_into_string
flags_into_string()
Returns a string with the flags assignments from this FlagValues object.
This function ignores flags whose value is None. Each flag assignment is separated by a newline.
NOTE: MUST mirror the behavior of the C++ CommandlineFlagsIntoString from https://github.com/gflags/gflags.
str, the string with the flags assignments from this FlagValues object. The flags are ordered by (module_name, flag_name).
get_flag_value
get_flag_value( name, default )
Returns the value of a flag (if not None) or a default value.
name
: str, the name of a flag.default
: Default value to use if the flag value is None.Requested flag value or default.
get_help
get_help( prefix='', include_special_flags=True )
Returns a help string for all known flags.
prefix
: str, per-line output prefix.include_special_flags
: bool, whether to include description of
SPECIAL_FLAGS, i.e. --flagfile and --undefok.str, formatted help message.
get_key_flags_for_module
get_key_flags_for_module(module)
Returns the list of key flags for a module.
module
: module|str, the module to get key flags from.[Flag], a new list of Flag instances. Caller may update this list as
desired
: none of those changes will affect the internals of this
FlagValue instance.is_gnu_getopt
is_gnu_getopt()
is_parsed
is_parsed()
Returns whether flags were parsed.
key_flags_by_module_dict
key_flags_by_module_dict()
Returns the dictionary of module_name -> list of key flags.
A dictionary. Its keys are module names (strings). Its values are lists of Flag objects.
main_module_help
main_module_help()
Describes the key flags of the main module.
str, describing the key flags of the main module.
mark_as_parsed
mark_as_parsed()
Explicitly marks flags as parsed.
Use this when the caller knows that this FlagValues has been parsed as if a call() invocation has happened. This is only a public method for use by things like appcommands which do additional command like parsing.
module_help
module_help(module)
Describes the key flags of a module.
module
: module|str, the module to describe the key flags for.str, describing the key flags of a module.
read_flags_from_files
read_flags_from_files( argv, force_gnu=True )
Processes command line args, but also allow args to be read from file.
argv
: [str], a list of strings, usually sys.argv[1:], which may contain
one or more flagfile directives of the form --flagfile="./filename".
Note that the name of the program (sys.argv[0]) should be omitted.force_gnu
: bool, if False, --flagfile parsing obeys the
FLAGS.is_gnu_getopt() value. If True, ignore the value and always
follow gnu_getopt semantics.A new list which has the original list combined with what we read from any flagfile(s).
IllegalFlagValueError
: Raised when --flagfile is provided with no
argument.This function is called by FLAGS(argv).
It scans the input list for a flag that looks like:
--flagfile=
Note that your application's flags are still defined the usual way using absl.flags DEFINE_flag() type functions.
Notes (assuming we're getting a commandline of some sort as our input):
--> For duplicate flags, the last one we hit should "win".
--> Since flags that appear later win, a flagfile's settings can be "weak"
if the --flagfile comes at the beginning of the argument sequence,
and it can be "strong" if the --flagfile comes at the end.
--> A further "--flagfile=
register_flag_by_module
register_flag_by_module( module_name, flag )
Records the module that defines a specific flag.
We keep track of which flag is defined by which module so that we can later sort the flags by module.
module_name
: str, the name of a Python module.flag
: Flag, the Flag instance that is key to the module.register_flag_by_module_id
register_flag_by_module_id( module_id, flag )
Records the module that defines a specific flag.
module_id
: int, the ID of the Python module.flag
: Flag, the Flag instance that is key to the module.register_key_flag_for_module
register_key_flag_for_module( module_name, flag )
Specifies that a flag is a key flag for a module.
module_name
: str, the name of a Python module.flag
: Flag, the Flag instance that is key to the module.remove_flag_values
remove_flag_values(flag_values)
Remove flags that were previously appended from another FlagValues.
flag_values
: FlagValues, the FlagValues instance containing flags to
remove.set_default
set_default( name, value )
Changes the default value of the named flag object.
The flag's current value is also updated if the flag is currently using the default value, i.e. not specified in the command line, and not set by FLAGS.name = value.
name
: str, the name of the flag to modify.value
: The new default value.UnrecognizedFlagError
: Raised when there is no registered flag named name.IllegalFlagValueError
: Raised when value is not valid.set_gnu_getopt
set_gnu_getopt(gnu_getopt=True)
Sets whether or not to use GNU style scanning.
GNU style allows mixing of flag and non-flag arguments. See http://docs.python.org/library/getopt.html#getopt.gnu_getopt
gnu_getopt
: bool, whether or not to use GNU style scanning.unparse_flags
unparse_flags()
Unparses all flags to the point before any FLAGS(argv) was called.
write_help_in_xml_format
write_help_in_xml_format(outfile=None)
Outputs flag documentation in XML format.
NOTE: We use element names that are consistent with those used by
the C++ command-line flag library, from
https://github.com/gflags/gflags.
We also use a few new elements (e.g.,
outfile
: File object we write to. Default None means sys.stdout.


To login, you have to create a form with the following fields:
action[login]
.An example login form:
<form method="post" action="">
E-mail address: <input type="text" name="fields[e-mail-address]" />

Password: <input type="text" name="fields[password]" />

<input type="hidden" name="fields[section]" value="users" />
<input type="hidden" name="redirect" value="/" />
<input type="submit" name="action[login]" value="Login" />
</form>
When a user is logged in, there will be a extra parameter available called $fmm-(section name)-id
with the ID of the currently logged in user. You can use this parameter for example to retrieve user information from your users section.


This page is home page. You can see the rules of this game and some of the roaming paths.
You can change directories using the commands listed below.
cd [directory name]
You can see how to use this page by enter help.
Enter home to return the main screen.
Enter challenges to see a list of problem.
Enter notice to confirm the announcement.
Enter rank to see the rankings.
Enter login to perform the login.
Enter register to perform the register.
Your score : <%= score %>
↓


We are a team that strives to meet the expectations of Drew students in order to make Drew a better and more efficient school.
After returning home from his boarding school for the summer, Percy and his mother, Sally Jackson, travel to their cabin in Montauk. However, the trip is cut short and after a series of harrowing incidents such as being attacked by a minotaur, Percy finds himself at Camp Half Blood.
On a mission to rescue half-bloods Bianca and Nico di Angelo; Percy, Annabeth, Thalia and Grover are attacked by a manticore and rescued by the goddess Artemis and her Hunters. However, Annabeth falls off a cliff whilst trying to fight the manticore and is said to be captured. Later, Artemis is captured by Luke's army while on the hunt for the Ophiotaurus, a cow-serpent monster that was foretold to bring the downfall of Olympus when its entrails are sacrificed to a fire.
Copyright Line. All Rights Reserved. Date.


{% extends "layouts/layout.html" %} {% block title %}SL Questions{% endblock %} {% block content %}
Onboarding = walkthrough introducing a user to the app on first launch. and != inviting a another user.
*Problem: prayer is only sent to the requesting person if a new prayer is created. Assumes prayers have visibility/privacy features.
IMO, "Asking to Pray" should be a feature used when *inviting* external users to the app, not a feature triggered by a follow request.
For MVP, I'd suggest launching without some of these features
Are we letting users style their prayers? From meeting with camera, we decided to let users select an app “theme” which would dicate how all their incoming prayers look. Patterns? Gradients? Images?
*Current navigation works because of only 3 main views and the rest not accessible through the top nav. More main views will require a different navigation style


#include <dfs_client.h>
Inherited by DFSFileHandle, and UnixFileHandle.
|
| virtual bool | pread (void *buf, size_t size, fsize_t pos, int flags=0)=0 |
| |
| virtual void | pwrite (void *buf, size_t size, fsize_t pos, int clique=0)=0 |
| |
| virtual bool | read (void *buf, size_t size, int flags=0)=0 |
| |
| virtual void | write (void *buf, size_t size, int clique=0)=0 |
| |
| virtual off_t | seek (off_t offs, int whence)=0 |
| |
| virtual void | prefetch (off_t offs, size_t size)=0 |
| |
| virtual size_t | blockSize ()=0 |
| |
Virtual file handle allowing to work in the same way either with DFS file, either with local file system file
| virtual size_t VFileHandle::blockSize |
( |
| ) |
|
|
pure virtual |
Get block size for the underlying device (chunk size for DFS)
- Returns
- block size in bytes
| virtual bool VFileHandle::pread |
( |
void * |
buf, |
|
|
size_t |
size, |
|
|
fsize_t |
pos, |
|
|
int |
flags = 0 |
|
) |
| |
|
pure virtual |
Read data from the specified location
- Parameters
-
| buf | destination buffer |
| size | amount of bytes to read |
| pos | position in the file |
| flags | combination of V_DIRECT and V_NOWAIT flags |
- Returns
- true if specified number of bytes is successfully read, false otherwise (last one is possible only in V_NOWAIT mode)
| virtual void VFileHandle::prefetch |
( |
off_t |
offs, |
|
|
size_t |
size |
|
) |
| |
|
pure virtual |
Prefetch data in the cache
- Parameters
-
| offs | offset inn the file |
| size | size of data to be prefetched |
| virtual void VFileHandle::pwrite |
( |
void * |
buf, |
|
|
size_t |
size, |
|
|
fsize_t |
pos, |
|
|
int |
clique = 0 |
|
) |
| |
|
pure virtual |
Write data to the specified location
- Parameters
-
| buf | source buffer |
| size | amount of bytes to be written |
| pos | position in the file |
| clique | to which DFS clique data should be written (ignored in case of OS file) |
| virtual bool VFileHandle::read |
( |
void * |
buf, |
|
|
size_t |
size, |
|
|
int |
flags = 0 |
|
) |
| |
|
pure virtual |
Read data from the current position in the file
- Parameters
-
| buf | destination buffer |
| size | amount of bytes to read |
| flags | combination of V_DIRECT and V_NOWAIT flags |
- Returns
- true if specified number of bytes is successfully read, false otherwise (last one is possible only in V_NOWAIT mode)
| virtual off_t VFileHandle::seek |
( |
off_t |
offs, |
|
|
int |
whence |
|
) |
| |
|
pure virtual |
Set current position in the file
- Parameters
-
| offs | new position in the file |
| whence | SEEK_SET or SEEK_CUR |
- Returns
- absolute position in the file
| virtual void VFileHandle::write |
( |
void * |
buf, |
|
|
size_t |
size, |
|
|
int |
clique = 0 |
|
) |
| |
|
pure virtual |
Write data to the current position in the file
- Parameters
-
| buf | source buffer |
| size | amount of bytes to be written |
| clique | to which DFS clique data should be written (ignored in case of OS file) |
The documentation for this class was generated from the following file:


Week 7
Databases, SQL, and Schemas
- Technical Blog - SQL Stuff
- Cultural Blog - Affirmation and Stereotype Threat
Phew!
Databases, SQL, and Schemas
Phew!
Consolidating C#
Is that a few clicks I hear inside my own head! At last a little more understanding of all those Object Oriented Programming concepts.
Trickier C#
Creating a RPN calculator (who would have thought!) and checking on your Credit card.
A quick switch and now it is C#
A new web design. C# = {:; using.} or something like that.
JavaScript - phew something new!
Fun(?)
Exhaustion! This week is more HTML/CSS.
All completed phew!
Whoa - we are off and sprinting! This week is HTML/CSS.
Survived! But only just.


{% extends 'base.html' %} {% block title %}Stock Watcher - Search potential stocks{% endblock title %} {% block content %}
Search for potential stocks to add to your portfolio.


Enkel politik
Motions
Here you can find the most recent votings in the parlament
Choose an alternative
Political test
Parlament motions