{{#markdown}}
The default font used throughout the page is Helvetica Neue, and is implement through a web font loaded by fonts.css
. This is done to reflect EMBL-wide branding.
Sizing of default text is done with rem
; equivlent to 16px on 24px leading, or 12pt on 16pt leading. Note that these sizes are for desktop-class browser widths, tablet and mobile sized screens are scaled.


"Christian Schulte" <schulte at imit.kth.se> writes: > doing, I also have no clue how I can look at what is going on (I cannot even > build .s files with the nonsense Makefiles). can't you somehow add a -save-temps option -- Denys Duchier - Équipe Calligramme - LORIA, Nancy, France AIM: duchierdenys


--- layout: post title: Hummus-coated Pasta with Crispy Sautéed Kale date: 2012-01-18 02:12:14.000000000 -05:00 type: post published: true status: publish categories: - dinner - recipes - savory - vegan tags: - easy - hummus - kale - pasta - vegan - whole wheat meta: _edit_last: '1' author: login: sophie email<EMAIL_ADDRESS>display_name: Pika first_name: '' last_name: '' ---
Sorry about the blog disappearance! Between vacation and packing and moving back in to school, not to mention internship applications and reunions with old friends, it’s been crazy busy around these parts. I promise to start posting regularly as soon as I get back into the swing of things.
Anyways, enough talk! Here’s a quick (took me only about 15 min from start to finish!), healthy, and comforting meal, perfect for the first day of classes in a brand new semester. Enjoy!
Hummus-coated Pasta with Crispy Sautéed Kale
makes 2 servings (one for dinner, one for lunch tomorrow!)
Kale is one of my absolute favorite winter veggies--if you haven't tried it, you're missing out! Kale chips are another great way to enjoy them. All you busy bees out there: any other suggestions for quick & easy pasta meals?


To start your order , you need to sign in with your account. Afterwards, on the user's page ,
press the button ORDER NOW to start your order.
After starting your order , you will be redirected to the menu page, where you can choose meals from various categories.
Before you add the meal to your user basket,you are able to choose additional materials that you can add to your selected meal.
After choosing the materials ,click ADD to add the meal to your basket.
After you are done with picking meals, you need to proceed to the order's next step, verifying payment method specifying time of delivery as well as adding any comments
that our eatery should keep in mind.
Things here work really simply.If you change your mind in time , you need to call to the the restaurant that received the order and ask for a change or cancel your order.
Note that the orders that are on the way to be delivered ,cannot be canceled or modified.
Absolutely not.The catalogue prices are the same on our webpage.Moreover , for users that are ordering online ,there's a 5% discount on their next order!
Not necessarily. There are three payment methods. Credit card , PayPal and paying the delivery man with cash.For more info check the Payment Methods section.
All order go through the same process. Once you confirm your order , our system inserts it on queue for processing ,and after the restaurant verifies the order,the order is fully processed.
You can check your order's status on your personal user page.
In case there is anything wrong with your order, calling the correspondent restaurant is the best option.


Server config site and server link
cd server
==> make sure that path ends with 13\server
, or 13/server
on UNIX
npm install
npm run watch-node
npm install
npm run watch-node
everytime you want to reset the game (will be changed in future)13\server
, run npx typedoc --out ../docs/server-docs *.ts src/*.ts
.13\docs\server-docs
.13\server
, run npm test
.WARNING: when debugging, I highly highly recommend stopping both Unity clients AND the server between each test. Unity networking is kind of wonky + also if you don't stop it, your computer might become super slow (running 2 Unitys) + how server is set up right now.
Note: Unity clients often connect and disconnect (dw it's normal). We can live with it, or we can figure out fixes/optimizations in future.
followed https://blog.logrocket.com/typescript-with-node-js-and-express/
npm install express-generator -g
express server
Generated using TypeDoc


Explore
Find the projects you’re looking for. Filter by sector, region, or year.
Rate
Give feedback on projects by rating them or leaving comments.
Contribute
Help locate projects by pinning them on a map, and report discrepancies.
@(currentUser: budget.models.User)
@main("about", currentUser){
Dig deep into the government’s budget, releases, projects, and works! Find the projects you’re looking for. Filter by sector, region, or year. Give feedback on projects by rating them or leaving comments. Help locate projects by pinning them on a map, and report discrepancies.
Budget
Badger
Learn where your taxes go, explore projects near you, and leave feedback.
Explore
Rate
Contribute
Budget Badger was built by Daniel Fordan, Pepe Bawagan, Philip Cheang, and Levi Tan Ong. Please follow us and all that. Kthnx.
Because transparency is good, silly. But seriously, Budget Badger was a product of the first #KabantayNgBayan hackathon, which made government budget data available. It's part of an initiative to make Open Data available across Philippine agencies.
The first version was built in 24 hours (ish), and won first place. (Yay!)
No, but we believe strongly in engaging with government and doing our own small part to help out. It so happens that we like building apps and making pretty things.
If you'd like to see the data for yourself, or build your own apps that take advantage of this data, head on over to the Data.gov.ph portal.
We're part of By Implication, an independent, award-winning software and game design studio.
Some of our cooler projects include Storylark (helping awesome local indie comics) and Sari Software (our partner-clients, building tech for sari-sari stores and micro-entrepreneurs.)
(Do you need a game, web platform, or mobile app built? Want to collaborate on a technology or design project? Just fancy a chat? ! :)
Hopefully. We're looking forward to more data sets and feeds to play with.
In the meantime, you can check out Sakay.ph (like Google Maps for commuting! It uses open data from DOTC, MMDA, etc.) and RollCall.ph (Side project by Levi + Pepe. Lets you visualize congress attendance data!)
Please let us know! Alternatively, if you'd like to contribute by fixing bugs, reporting issues, or submitting patches — check out the project on GitHub.
If you want to run your own instance, please feel free! We just ask for attribution if you redistribute it, or maintain your own deployment.
Sure! You can hit us up on Twitter or Facebook (see links above), or email us at .


weigh
ME
We would love to hear from you!
weigh
ME!
is a weight tracking application that is designed to help individuals pursue a healthier lifestyle built by Michigan State Spartans.
Please do not hesitate to contact us at<EMAIL_ADDRESS>Weigh me
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About
Created by
Paul Guevarra, July 21, 2017
GitHub Username/URL:
paulguevarra
Objectives
- Code meets standards from previous weeks
- Use HTML tags: p, h, ul, ol, li, em, strong, a, img, div, span
- Proper usage of Bootstrap and jQuery
- Indentation and spacing is accurate
- JavaScript business logic and user interface logic are separate
- Objects drive business logic (in JavaScript, not jQuery)
- Constructors and prototypes are used successfully
- Application works as expected
- Plain English specs are included in my README
- Project is in a polished, portfolio-quality state
- Project demonstrates an understanding of this week's concepts


Anvee Bhutani
Anvee Bhutani is currently a sophomore at Archbishop Mitty High School.  In her free time, Anvee likes cooking, reading, and jump roping. In the future, Anvee hopes to enter the medical field to become a pediatrician.Lipika Chatur
Lipika Chatur is thirteen years old and will be going to eighth grade. In her free time, she enjoys drawing(photoshop) and playing her instrument(viola). She plans to get a job in Pixar and make cool animated movies such as Finding Dory.Ria Nawathe
Ria Nawathe attends Presentation High School in San Jose as a freshman. She has an interest in all STEM subjects, especially biology and computer programming. In her free time, she swims competitively, plays the piano, oil paints, and reads.Narahari Rao
Narahari Rao is a 10th grader at Archbishop Mitty. He likes coding and has done a lot of work with HTML in the past. He hopes to work with software in the future at a company like Apple or Google.Shaunak Panda
Shaunak Panda is currently a 6th grader at Lawson Middle School.  His goals for the future are to become a businessman and to produce a successful business.Saanvi Mantripragada
Saanvi Mantripragada is currently starting her first year of middle school at the age of 10. Some of her interests include reading, coding, playing sports, cooking, and drawing. She is very creative and open to new ideas.


Some things to remember
Make sure to always include your full name and address on the communication. First of all, this helps them to answer your letter. Secondly, they want to know you’re a constituent. Of course as an American Citizen you can write to ANY Congressperson or Senator, as well as the President, at any time. However, it will make more of an impact on elected officials if you are a voter from their particular district.
It is MUCH more effective to use your own words and not just to sign a form letter, a petition or a preprinted card. You want to send a thoughtful, respectful and well-reasoned letter. Do make sure you write BEFORE the bill you’re writing about goes to the House or Senate floor-timing is everything. Make sure you identify the bill you’re writing about. Use the number- i.e. H.R. 2454- or the popular title, such as “Cap & Trade”.
Be brief. Be well-reasoned. Don’t rant. Present your opinion, your facts and arguments succinctly. The sooner you get to the point, the more likely it is that the politician will read through your message. Tell them how you feel this bill will affect you, or your state, or the country. Give your reasoning. Feel free to offer suggestions on how to solve the problem that the bill is being written to solve. There are only 535 congressmen and millions of us. Perhaps we will suggest something they haven’t thought of!
Don’t expect to get a response quickly-or at all! Politicians get hundreds of letters, emails and communications every day. If you do not get a reply, do not take it personally, but keep attempting to send correspondence in order to reach your representative. Most of all, DO WRITE! Sending a letter by U.S. Mail is much more effective than by email when contacting politicians.
You can also call your congressperson or senator by dialing the U.S. Capital Building at<PHONE_NUMBER>. The switchboard can connect you to the office you request. To call the White House dial<PHONE_NUMBER>.
The President The White House 1600 Pennsylvania Avenue NW Washington, DC 20500 Dear Mr. President:
The Honorable (Your Congressperson’s Full Name i.e. The Honorable Sally Jones) United States House of Representatives Washington, D.C. 20515 Dear Congressperson (Last Name):
The Honorable (Your Senator’s Full Name i.e. The Honorable John Smith) United States Senator United States Senate Washington, D.C. 20510 Dear Senator (Last Name):
Personal meetings with a politician and/or relevant staff member are the most effective means of communication. A meeting needs to be arranged well in advance. Be flexible with meeting times, and ask when best suits them – don’t tell them when best suits you! Be punctual, well-dressed, and neatly presented. Don’t be disappointed if you meet with a staff member. These are the people you will work with over time, and it helps to build a good relationship from day one. Take your notes with you, and refer to them if necessary. This shows you’ve made an effort, and are serious about the issue. Don’t be afraid to say ‘I don’t know’, but always offer to find out. Follow up as quickly as possible with accurate information. Don’t ever pretend to know something if you really don’t. Politicians are humans, too. They have their own views and opinions, and if you want them to listen to you, you need to listen to them. Always be respectful, calm, and courteous. Send a follow-up letter thanking them for taking the time to meet with you.
How was your experience?
I would like to thank Politicious for helping me get in touch with Mike Honda, my state's Congressman. I was able to write to him with some questions about a recent bill that had been proposed, and he wrote back a very thoughtful response. I am so glad to be able to contact politicians!


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--- layout: single ---
Hello. Mark Ruddy here.
I like to work in lots of different areas: data science, writing about science-related things, and investigating recent Earth history. I live in London, with my wife and two children, and am often to be seen riding bicycles, because they're fun and solve most of the world's problems.
In the past you might have found me drilling holes in the ground to find out about Earth history, or measuring the teeth of small mammals and thinking about evolution.
Read a blog.
Download data and other goodies.
Wondering why stage5e?


pyrad.proc.
process_spectral_reflectivity
(procstatus, dscfg, radar_list=None)[source]¶ Computes spectral reflectivity
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted configuration keywords:
- datatype : list of string. Dataset keyword
The input data types
- subtract_noise : Bool
If True noise will be subtracted from the signal
- smooth_window : int or None
Size of the moving Gaussian smoothing window. If none no smoothing will be applied
- radar_list : list of spectra objects
Optional. list of spectra objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_spectral_rhohv
(procstatus, dscfg, radar_list=None)[source]¶ Computes the spectral RhoHV
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted configuration keywords:
- datatype : list of string. Dataset keyword
The input data types
- subtract_noise : Bool
If True noise will be subtracted from the signal
- radar_list : list of spectra objects
Optional. list of spectra objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_st1_iq
(procstatus, dscfg, radar_list=None)[source]¶ Computes the statistical test one lag fluctuation from the horizontal or vertical IQ data
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted configuration keywords:
- datatype : list of string. Dataset keyword
The input data types
- radar_list : list of spectra objects
Optional. list of spectra objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_st2_iq
(procstatus, dscfg, radar_list=None)[source]¶ Computes the statistical test two lag fluctuation from the horizontal or vertical IQ data
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted configuration keywords:
- datatype : list of string. Dataset keyword
The input data types
- radar_list : list of spectra objects
Optional. list of spectra objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_sun_hits
(procstatus, dscfg, radar_list=None)[source]¶ monitoring of the radar using sun hits
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- delev_max : float. Dataset keyword
maximum elevation distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5
- dazim_max : float. Dataset keyword
maximum azimuth distance from nominal radar elevation where to look for a sun hit signal [deg]. Default 1.5
- elmin : float. Dataset keyword
minimum radar elevation where to look for sun hits [deg]. Default 1.
- attg : float. Dataset keyword
gaseous attenuation. Default None
- sun_position : string. Datset keyword
The function to compute the sun position to use. Can be ‘MF’ or ‘pysolar’
- sun_hit_method : str. Dataset keyword
Method used to estimate the power of the sun hit. Can be HS (Hildebrand and Sekhon 1974) or Ivic (Ivic 2013)
- rmin : float. Dataset keyword
minimum range where to look for a sun hit signal [m]. Used in HS method. Default 50000.
- hmin : float. Dataset keyword
minimum altitude where to look for a sun hit signal [m MSL]. Default 10000. The actual range from which a sun hit signal will be search will be the minimum between rmin and the range from which the altitude is higher than hmin. Used in HS method. Default 10000.
- nbins_min : int. Dataset keyword.
minimum number of range bins that have to contain signal to consider the ray a potential sun hit. Default 20 for HS and 8000 for Ivic.
- npulses_ray : int
Default number of pulses used in the computation of the ray. If the number of pulses is not in radar.instrument_parameters this will be used instead. Used in Ivic method. Default 30
- flat_reg_wlen : int
Length of the flat region window [m]. Used in Ivic method. Default 8000.
- iterations: int
number of iterations in step 7 of Ivic method. Default 10.
- max_std_pwr : float. Dataset keyword
maximum standard deviation of the signal power to consider the data a sun hit [dB]. Default 2. Used in HS method
- max_std_zdr : float. Dataset keyword
maximum standard deviation of the ZDR to consider the data a sun hit [dB]. Default 2.
- az_width_co : float. Dataset keyword
co-polar antenna azimuth width (convoluted with sun width) [deg]. Default None
- el_width_co : float. Dataset keyword
co-polar antenna elevation width (convoluted with sun width) [deg]. Default None
- az_width_cross : float. Dataset keyword
cross-polar antenna azimuth width (convoluted with sun width) [deg]. Default None
- el_width_cross : float. Dataset keyword
cross-polar antenna elevation width (convoluted with sun width) [deg]. Default None
- ndays : int. Dataset keyword
number of days used in sun retrieval. Default 1
- coeff_band : float. Dataset keyword
multiplicate coefficient to transform pulse width into receiver bandwidth
- frequency : float. Dataset keyword
the radar frequency [Hz]. If None that of the key frequency in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present frequency dependent parameters will not be computed
- beamwidth : float. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth dependent parameters will not be computed
- pulse_width : float. Dataset keyword
the pulse width [s]. If None that of the key pulse_width in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the pulse width dependent parameters will not be computed
- ray_angle_res : float. Dataset keyword
the ray angle resolution [deg]. If None that of the key ray_angle_res in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed
- AntennaGainH, AntennaGainV : float. Dataset keyword
the horizontal (vertical) polarization antenna gain [dB]. If None that of the attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the ray angle resolution parameters will not be computed
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - sun_hits_dict : dict
dictionary containing a radar object, a sun_hits dict and a sun_retrieval dictionary
- ind_rad : int
radar index
-
pyrad.proc.
process_svp
(procstatus, dscfg, radar_list=None)[source]¶ Computes slanted vertical profiles, by averaging over height levels PPI data.
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The data type where we want to extract the point measurement
- angle : int or float
If the radar object contains a PPI volume, the sweep number to use, if it contains an RHI volume the elevation angle. Default 0.
- ang_tol : float
If the radar object contains an RHI volume, the tolerance in the elevation angle for the conversion into PPI. Default 1.
- lat, lon : float
latitude and longitude of the point of interest [deg]
- latlon_tol : float
tolerance in latitude and longitude in deg. Default 0.0005
- delta_rng, delta_azi : float
maximum range distance [m] and azimuth distance [degree] from the central point of the svp containing data to average. Default 5000. and 10.
- hmax : float
The maximum height to plot [m]. Default 10000.
- hres : float
The height resolution [m]. Default 250.
- avg_type : str
The type of averaging to perform. Can be either “mean” or “median” Default “mean”
- nvalid_min : int
Minimum number of valid points to consider the data valid when performing the averaging. Default 1
- interp_kind : str
type of interpolation when projecting to vertical grid: ‘none’, or ‘nearest’, etc. Default ‘none’ ‘none’ will select from all data points within the regular grid height bin the closest to the center of the bin. ‘nearest’ will select the closest data point to the center of the height bin regardless if it is within the height bin or not. Data points can be masked values If another type of interpolation is selected masked values will be eliminated from the data points before the interpolation
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the svp and a keyboard stating whether the processing has finished or not.
- ind_rad : int
radar index
-
pyrad.proc.
process_time_avg
(procstatus, dscfg, radar_list=None)[source]¶ computes the temporal mean of a field
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- period : float. Dataset keyword
the period to average [s]. Default 3600.
- start_average : float. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- lin_trans: int. Dataset keyword
If 1 apply linear transformation before averaging
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_time_avg_flag
(procstatus, dscfg, radar_list=None)[source]¶ computes a flag field describing the conditions of the data used while averaging
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- period : float. Dataset keyword
the period to average [s]. Default 3600.
- start_average : float. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- phidpmax: float. Dataset keyword
maximum PhiDP
- beamwidth : float. Dataset keyword
the antenna beamwidth [deg]. If None that of the keys radar_beam_width_h or radar_beam_width_v in attribute instrument_parameters of the radar object will be used. If the key or the attribute are not present the beamwidth will be set to None
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : Radar
radar object
- ind_rad : int
radar index
-
pyrad.proc.
process_time_avg_std
(procstatus, dscfg, radar_list=None)[source]¶ computes the average and standard deviation of data. It looks only for gates where data is present.
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- regular_grid : Boolean. Dataset keyword
Whether the radar has a Boolean grid or not. Default False
- rmin, rmax : float. Dataset keyword
minimum and maximum ranges where the computation takes place. If -1 the whole range is considered. Default is -1
- val_min : Float. Dataset keyword
Minimum reflectivity value to consider that the gate has signal. Default None
- filter_prec : str. Dataset keyword
Give which type of volume should be filtered. None, no filtering; keep_wet, keep wet volumes; keep_dry, keep dry volumes.
- rmax_prec : float. Dataset keyword
Maximum range to consider when looking for wet gates [m]
- percent_prec_max : float. Dataset keyword
Maxim percentage of wet gates to consider the volume dry
- lin_trans : Boolean. Dataset keyword
If True the data will be transformed into linear units. Default False
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_time_height
(procstatus, dscfg, radar_list=None)[source]¶ Produces time height radar objects at a point of interest defined by latitude and longitude. A time-height contains the evolution of the vertical structure of radar measurements above the location of interest.
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The data type where we want to extract the point measurement
- lat, lon : float
latitude and longitude of the point of interest [deg]
- latlon_tol : float
tolerance in latitude and longitude in deg. Default 0.0005
- hmax : float
The maximum height to plot [m]. Default 10000.
- hres : float
The height resolution [m]. Default 50
- interp_kind : str
type of interpolation when projecting to vertical grid: ‘none’, or ‘nearest’, etc. Default ‘none’ ‘none’ will select from all data points within the regular grid height bin the closest to the center of the bin. ‘nearest’ will select the closest data point to the center of the height bin regardless if it is within the height bin or not. Data points can be masked values If another type of interpolation is selected masked values will be eliminated from the data points before the interpolation
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the QVP and a keyboard stating whether the processing has finished or not.
- ind_rad : int
radar index
-
pyrad.proc.
process_time_stats
(procstatus, dscfg, radar_list=None)[source]¶ computes the temporal statistics of a field
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- period : float. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_average : float. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- lin_trans: int. Dataset keyword
If 1 apply linear transformation before averaging
- use_nan : bool. Dataset keyword
If true non valid data will be used
- nan_value : float. Dataset keyword
The value of the non valid data. Default 0
- stat: string. Dataset keyword
Statistic to compute: Can be mean, std, cov, min, max. Default mean
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_time_stats2
(procstatus, dscfg, radar_list=None)[source]¶ computes the temporal mean of a field
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- period : float. Dataset keyword
the period to average [s]. If -1 the statistics are going to be performed over the entire data. Default 3600.
- start_average : float. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- stat: string. Dataset keyword
Statistic to compute: Can be median, mode, percentileXX
- use_nan : bool. Dataset keyword
If true non valid data will be used
- nan_value : float. Dataset keyword
The value of the non valid data. Default 0
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_traj_antenna_pattern
(procstatus, dscfg, radar_list=None, trajectory=None)[source]¶ Process a new array of data volumes considering a plane trajectory. As result a timeseries with the values transposed for a given antenna pattern is created. The result is created when the LAST flag is set.
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
- datatype : list of string. Dataset keyword
The input data types
- antennaType : str. Dataset keyword
Type of antenna of the radar we want to get the view from. Can be AZIMUTH, ELEVATION, LOWBEAM, HIGHBEAM
- par_azimuth_antenna : dict. Global ekyword
Dictionary containing the parameters of the PAR azimuth antenna, i.e. name of the file with the antenna elevation pattern and fixed antenna angle
- par_elevation_antenna : dict. Global keyword
Dictionary containing the parameters of the PAR elevation antenna, i.e. name of the file with the antenna azimuth pattern and fixed antenna angle
- asr_lowbeam_antenna : dict. Global keyword
Dictionary containing the parameters of the ASR low beam antenna, i.e. name of the file with the antenna elevation pattern and fixed antenna angle
- asr_highbeam_antenna : dict. Global keyword
Dictionary containing the parameters of the ASR high beam antenna, i.e. name of the file with the antenna elevation pattern and fixed antenna angle
- target_radar_pos : dict. Global keyword
Dictionary containing the latitude, longitude and altitude of the radar we want to get the view from. If not specifying it will assume the radar is collocated
- range_all : Bool. Dataset keyword
If the real radar and the synthetic radar are co-located and this parameter is true the statistics are going to be computed using all the data from range 0 to the position of the plane. Default False
- rhi_resolution : Bool. Dataset keyword
Resolution of the synthetic RHI used to compute the data as viewed from the synthetic radar [deg]. Default 0.5
- max_altitude : float. Dataset keyword
Max altitude of the data to use when computing the view from the synthetic radar [m MSL]. Default 12000.
- latlon_tol : float. Dataset keyword
The tolerance in latitude and longitude to determine which synthetic radar gates are co-located with real radar gates [deg]. Default 0.04
- alt_tol : float. Datset keyword
The tolerance in altitude to determine which synthetic radar gates are co-located with real radar gates [m]. Default 1000.
- pattern_thres : float. Dataset keyword
The minimum of the sum of the weights given to each value in order to consider the weighted quantile valid. It is related to the number of valid data points
- data_is_log : dict. Dataset keyword
Dictionary specifying for each field if it is in log (True) or linear units (False). Default False
- use_nans : dict. Dataset keyword
Dictionary specyfing whether the nans have to be used in the computation of the statistics for each field. Default False
- nan_value : dict. Dataset keyword
Dictionary with the value to use to substitute the NaN values when computing the statistics of each field. Default 0
- radar_list : list of Radar objects
Optional. list of radar objects
- trajectory : Trajectory object
containing trajectory samples
Returns: - trajectory : Trajectory object
Object holding time series
- ind_rad : int
radar index
-
pyrad.proc.
process_traj_atplane
(procstatus, dscfg, radar_list=None, trajectory=None)[source]¶ Return time series according to trajectory
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- data_is_log : dict. Dataset keyword
Dictionary specifying for each field if it is in log (True) or linear units (False). Default False
- ang_tol : float. Dataset keyword
Factor that multiplies the angle resolution. Used when determining the neighbouring rays. Default 1.2
- radar_list : list of Radar objects
Optional. list of radar objects
- trajectory : Trajectory object
containing trajectory samples
Returns: - trajectory : Trajectory object
Object holding time series
- ind_rad : int
radar index
-
pyrad.proc.
process_traj_lightning
(procstatus, dscfg, radar_list=None, trajectory=None)[source]¶ Return time series according to lightning trajectory
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- data_is_log : dict. Dataset keyword
Dictionary specifying for each field if it is in log (True) or linear units (False). Default False
- ang_tol : float. Dataset keyword
Factor that multiplies the angle resolution. Used when determining the neighbouring rays. Default 1.2
- radar_list : list of Radar objects
Optional. list of radar objects
- trajectory : Trajectory object
containing trajectory samples
Returns: - trajectory : Trajectory object
Object holding time series
- ind_rad : int
radar index
-
pyrad.proc.
process_traj_trt
(procstatus, dscfg, radar_list=None, trajectory=None)[source]¶ Processes data according to TRT trajectory
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- time_tol : float. Dataset keyword
tolerance between reference time of the radar volume and that of the TRT cell [s]. Default 100.
- alt_min, alt_max : float. Dataset keyword
Minimum and maximum altitude of the data inside the TRT cell to retrieve [m MSL]. Default None
- cell_center : Bool. Dataset keyword
If True only the range gate closest to the center of the cell is extracted. Default False
- latlon_tol : Float. Dataset keyword
Tolerance in lat/lon when extracting data only from the center of the TRT cell. Default 0.01
- radar_list : list of Radar objects
Optional. list of radar objects
- trajectory : Trajectory object
containing trajectory samples
Returns: - new_dataset : dictionary
Dictionary containing radar_out, a radar object containing only data from inside the TRT cell
- ind_rad : int
radar index
-
pyrad.proc.
process_traj_trt_contour
(procstatus, dscfg, radar_list=None, trajectory=None)[source]¶ Gets the TRT cell contour corresponding to each radar volume
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- time_tol : float. Dataset keyword
tolerance between reference time of the radar volume and that of the TRT cell [s]. Default 100.
- radar_list : list of Radar objects
Optional. list of radar objects
- trajectory : Trajectory object
containing trajectory samples
Returns: - new_dataset : dict
Dictionary containing radar_out and roi_dict. Radar out is the current radar object. roi_dict contains the positions defining the TRT cell contour
- ind_rad : int
radar index
-
pyrad.proc.
process_trajectory
(procstatus, dscfg, radar_list=None, trajectory=None)[source]¶ Return trajectory
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- radar_list : list of Radar objects
Optional. list of radar objects
- trajectory : Trajectory object
containing trajectory samples
Returns: - new_dataset : Trajectory object
radar object
- ind_rad : int
None
-
pyrad.proc.
process_ts_along_coord
(procstatus, dscfg, radar_list=None)[source]¶ Produces time series along a particular antenna coordinate
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The data type where we want to extract the time series
- mode : str
coordinate to extract data along. Can be ALONG_AZI, ALONG_ELE or ALONG_RNG
- fixed_range, fixed_azimuth, fixed_elevation : float
The fixed range [m], azimuth [deg] or elevation [deg] to extract. In each mode two of these parameters have to be defined. If they are not defined they default to 0.
- ang_tol, rng_tol : float
The angle tolerance [deg] and range tolerance [m] around the fixed range or azimuth/elevation
- value_start, value_stop : float
The minimum and maximum value at which the data along a coordinate start and stop
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the data and a keyboard stating whether the processing has finished or not.
- ind_rad : int
radar index
-
pyrad.proc.
process_turbulence
(procstatus, dscfg, radar_list=None)[source]¶ Computes turbulence from the Doppler spectrum width and reflectivity using the PyTDA package
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The input data type
- radius : float. Dataset keyword
Search radius for calculating Eddy Dissipation Rate (EDR). Default 2
- split_cut : Bool. Dataset keyword
Set to True for split-cut volumes. Default False
- max_split_cut : Int. Dataset keyword
Total number of tilts that are affected by split cuts. Only relevant if split_cut=True. Default 2
- xran, yran : float array. Dataset keyword
Spatial range in X,Y to consider. Default [-100, 100] for both X and Y
- beamwidth : Float. Dataset keyword
Radar beamwidth. Default None. If None it will be obtained from the radar object metadata. If cannot be obtained defaults to 1 deg.
- compute_gate_pos : Bool. Dataset keyword
If True the gate position is going to be computed in PyTDA. Otherwise the position from the radar object is used. Default False
- verbose : Bool. Dataset keyword
True for verbose output. Default False
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_vad
(procstatus, dscfg, radar_list=None)[source]¶ Estimates vertical wind profile using the VAD (velocity Azimuth Display) technique
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The input data type
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_visibility
(procstatus, dscfg, radar_list=None)[source]¶ Gets the visibility in percentage from the minimum visible elevation. Anything with elevation lower than the minimum visible elevation plus and offset is set to 0 while above is set to 100.
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
arbitrary data type
- offset : float. Dataset keyword
The offset above the minimum visibility that must be filtered
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_vol_refl
(procstatus, dscfg, radar_list=None)[source]¶ Computes the volumetric reflectivity in 10log10(cm^2 km^-3)
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- freq : float. Dataset keyword
The radar frequency
- kw : float. Dataset keyword
The water constant
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_wbn_iq
(procstatus, dscfg, radar_list=None)[source]¶ Computes the wide band noise from the horizontal or vertical IQ data
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted configuration keywords:
- datatype : list of string. Dataset keyword
The input data types
- radar_list : list of spectra objects
Optional. list of spectra objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_weighted_time_avg
(procstatus, dscfg, radar_list=None)[source]¶ computes the temporal mean of a field weighted by the reflectivity
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- period : float. Dataset keyword
the period to average [s]. Default 3600.
- start_average : float. Dataset keyword
when to start the average [s from midnight UTC]. Default 0.
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : Radar
radar object
- ind_rad : int
radar index
-
pyrad.proc.
process_wind_vel
(procstatus, dscfg, radar_list=None)[source]¶ Estimates the horizontal or vertical component of the wind from the radial velocity
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The input data type
- vert_proj : Boolean
If true the vertical projection is computed. Otherwise the horizontal projection is computed
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_windshear
(procstatus, dscfg, radar_list=None)[source]¶ Estimates the wind shear from the wind velocity
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : string. Dataset keyword
The input data type
- az_tol : float
The tolerance in azimuth when looking for gates on top of the gate when computation is performed
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_zdr_column
(procstatus, dscfg, radar_list=None)[source]¶ Detects ZDR columns
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_zdr_precip
(procstatus, dscfg, radar_list=None)[source]¶ Keeps only suitable data to evaluate the differential reflectivity in moderate rain or precipitation (for vertical scans)
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- ml_filter : boolean. Dataset keyword
indicates if a filter on data in and above the melting layer is applied. Default True.
- rmin : float. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
- rmax : float. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
- Zmin : float. Dataset keyword
minimum reflectivity to consider the bin as precipitation [dBZ]. Default 20.
- Zmax : float. Dataset keyword
maximum reflectivity to consider the bin as precipitation [dBZ] Default 22.
- RhoHVmin : float. Dataset keyword
minimum RhoHV to consider the bin as precipitation Default 0.97
- PhiDPmax : float. Dataset keyword
maximum PhiDP to consider the bin as precipitation [deg] Default 10.
- elmax : float. Dataset keyword
maximum elevation angle where to look for precipitation [deg] Default None.
- ml_thickness : float. Dataset keyword
assumed thickness of the melting layer. Default 700.
- fzl : float. Dataset keyword
The default freezing level height. It will be used if no temperature field name is specified or the temperature field is not in the radar object. Default 2000.
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index
-
pyrad.proc.
process_zdr_snow
(procstatus, dscfg, radar_list=None)[source]¶ Keeps only suitable data to evaluate the differential reflectivity in snow
Parameters: - procstatus : int
Processing status: 0 initializing, 1 processing volume, 2 post-processing
- dscfg : dictionary of dictionaries
data set configuration. Accepted Configuration Keywords:
- datatype : list of string. Dataset keyword
The input data types
- rmin : float. Dataset keyword
minimum range where to look for rain [m]. Default 1000.
- rmax : float. Dataset keyword
maximum range where to look for rain [m]. Default 50000.
- Zmin : float. Dataset keyword
minimum reflectivity to consider the bin as snow [dBZ]. Default 0.
- Zmax : float. Dataset keyword
maximum reflectivity to consider the bin as snow [dBZ] Default 30.
- SNRmin : float. Dataset keyword
minimum SNR to consider the bin as snow [dB]. Default 10.
- SNRmax : float. Dataset keyword
maximum SNR to consider the bin as snow [dB] Default 50.
- RhoHVmin : float. Dataset keyword
minimum RhoHV to consider the bin as snow Default 0.97
- PhiDPmax : float. Dataset keyword
maximum PhiDP to consider the bin as snow [deg] Default 10.
- elmax : float. Dataset keyword
maximum elevation angle where to look for snow [deg] Default None.
- KDPmax : float. Dataset keyword
maximum KDP to consider the bin as snow [deg] Default None
- TEMPmin : float. Dataset keyword
minimum temperature to consider the bin as snow [deg C]. Default None
- TEMPmax : float. Dataset keyword
maximum temperature to consider the bin as snow [deg C] Default None
- hydroclass : list of ints. Dataset keyword
list of hydrometeor classes to keep for the analysis Default [2] (dry snow)
- radar_list : list of Radar objects
Optional. list of radar objects
Returns: - new_dataset : dict
dictionary containing the output
- ind_rad : int
radar index


|
BiriBiriBeat
An Arduboy Otoge/Rhythm Game
|
A class for the state in which the game displays the config menu. More...
#include <gamestates.h>
Public Member Functions | |
| virtual void | on_entry () override |
| The entry function of a state. More... | |
| virtual void | on_exit () override |
| The exit function of a state. More... | |
| virtual gamestate_e | on_loop () override |
| The loop function of a state. More... | |
| Public Member Functions inherited from base_state | |
| virtual bool | next_frame () |
| Determines if it's time to draw the next frame. More... | |
A class for the state in which the game displays the config menu.
Definition at line 142 of file gamestates.h.
|
overridevirtual |
The entry function of a state.
This function is part of the enter->loop->exit method of handling states and transitions. It should be run when entering a new state before calling the looping method.
Implements base_state.
Definition at line 238 of file gamestates.cpp.
|
overridevirtual |
The exit function of a state.
This function is part of the enter->loop->exit method of handling states and transitions. It should be run when exiting a current state before entering a different state.
Implements base_state.
Definition at line 328 of file gamestates.cpp.
|
overridevirtual |
The loop function of a state.
This function is part of the enter->loop->exit method of handling states and transitions. It should be run for the current state every game loop.
Implements base_state.
Definition at line 243 of file gamestates.cpp.


Server Options
Options in this panel are used to set up a connection to a Blog server and fine tune how Blog Links are handled when collected from a server.
Server Options
- Web Server Name:
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- CGI-BIN Path:
- Enter the path and file name to your XML-RPC module. For MT users, this file is named mt-xmlrpc.cgi and will be located in your CGI-BIN directory. For example, if your link to access your server-based Blog settings is http://www.hostname.com/cgi-bin/mt.cgi then your CGI-BIN path is: /cgi-bin/mt-xmlrpc.cgi
- User Name:
- Enter the user name that you use to access your Blog's settings.
- Password:
- Enter the password that you use to access your Blog's settings.
- Blog List:
- If you click Refresh now, you will see a list of your Blogs appear in this list.
- Refresh
- Press this button to refresh your Blog-based settings from your server. You should refresh whenever you've changed your server name, Blog published, Categories, Text Filters, or anything else that is defined by the server.
Blog Links Options
- When Updating Links...
- Because SharpMT keeps list of Blog posts that have already been posted to the Blog server, these options will tell SharpMT how to handle the information sent from the server when you click "Update Blog Links" on the main window. If you want to replace the existing Blog Links list with a new list from the server, select "Replace old links with new links" - if you want new links to be appended to the end of the existing list select "Add newer links to list". Either way, "Posts to Retrieve" will cap the number of entries retrieved to a fixed number. These options will be used the next time you click "Update Blog Links" from the main menu or toolbar.
When you click OK on this dialog, SharpMT will automatically download a list of Categories and Text Filters from your Blog server as those are also required to effectively work offline and when posting new drafts. Once that is completed you are now ready to Blog writing while offline.


SIX DEGREES OF SEPARATION A film review by Mark R. Leeper Copyright 1994 Mark R. Leeper
Capsule review: This adaptation of the Broadway play is diverting but eventually doesn't tell very much story and left this viewer with the vague feeling that he missed some of the point.  When you find out what is really going on, you also find it very unlikely. Rating low +1 (-4 to +4)
BACKGROUND: Humanity is like a group of people walking around in a fog. Nobody is very far from anyone else, but you can see only the people nearest to you. And they can see only the people immediately around them. So everybody sees just a small part of the crowd. People drift closer in the fog and you see them for a while, then they move further away and cannot be traced.  That is not a lot for a film to be about, but an odd and convoluted mode of storytelling makes this film entertaining and at the same time enigmatic. Whatever else the film is about is really in the eye of the beholder.
Our story is told in large part through flashbacks as several groups of friends, families, and acquaintances tell each other about a mysterious young black man Paul (played by Will Smith) who has insinuated himself into their lives and then has gone back out of it. Primarily we see the stories through the eyes of Ouisa and Flan Kittredge (Stockard Channing and Donald Sutherland). They are wealthy pseudo-intellectual members of the upper crust. Flan makes his money through dubious trading in fine art. On a night that they are having an important dinner with a friend who might finance their next big deal, Paul shows up on their doorstep claiming to be the a friend of the Kittredge children and the son of Sidney Portier. The refined Paul makes an immediate hit and helps Flan to swing his deal. They invite Paul to stay the night only to have him hire a male hustler and bring him to the house. They throw Paul out. Almost immediately they start hearing that others of their friends have had run-ins with the same person. Soon they decide that they have to learn more about this young man who seems to know so much more about them than they know about him.
The people in this film are much like adult versions of the young people in METROPOLITAN. The have superficial conversations on profound subjects. While what they are saying seems erudite, it is only banality phrased well. What Paul says to keep up his end of the conversation occasionally does border on profundity, which makes him all the more enigmatic to the people he visits. Conversation and how things are expressed is very important to this film since so much of it is carried on by social conversations, often recounting other conversations. This slows down the plot development, but eventually this 111-minute film tells a nearly complete story that could have been told in twenty or thirty minutes. In the final analysis film is a light fantasy. The story is contrived and very unlikely to occur in the way it was told. I think that credibility is not the point here. Even the title is never clearly explained; it seems to refer to some idea that there are at most six intermediate people between anybody and anybody else in the world. Considering how isolated some tribes are to this day in the Amazon and other parts of the world, it seems very unlikely. Also it is not clear what counts as a direct adjacency.
This is a film with a terrific cast and a lack of characters. Will Smith is actually fairly charismatic as Paul, but the characters played by Channing, Sutherland, Ian McKellan, Mary Beth Hurt, Bruce Davison, Richard Masur, and Anthony Michael Hall are all quickly forgettable as indeed John Guare's screenplay based on his Broadway play would have them be. Perhaps like "Cats," this is just a play that cannot be done on the screen."
The film is a departure for director Fred Schepisi, but will not be one of his more memorable accomplishments. I give it a low +1 on the -4 to +4 scale.
Mark R. Leeper att!mtgzfs3!leeper<EMAIL_ADDRESS>.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
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Related links: index of all rec.arts.movies.reviews reviews


--- layout: post title: 'Consul: Service Discovery and Failure Detection' author: vcomposieux date: '2017-02-22 10:50:16 +0100' date_gmt: '2017-02-22 09:50:16 +0100' categories: - Non classé tags: [] --- {% raw %}
Consul is a product developed in Go language by the HashiCorp company and was born in 2013.
Consul has multiple components but its main goal is to manage the services knowledge in an architecture (which is service discovery) and also allows to ensure that all contacted services are always available by adding health checks on them.
Basically, Consul will bring us a DNS server that will resolve IP addresses of a host's services, depending on which one will be healthy.
This method also allows to do load balancing even if we will see in this blog post that it's actually not possible to distribute priorities between services.
Another Consul service we'll use in this article is key/value storage because we'll create a Docker Swarm cluster and will use Consul as the discovery/storage for Docker Swarm.
In order to clarify the rest of the article, here are the ports used by Consul:
Next, we'll focus on service discovery and failure detection. To do that, we'll create a Docker Swarm cluster with the following architecture:
As you can see, we'll have 3 Docker machines:
We'll also add on our two nodes a Docker container with Registrator image that will facilitate the discovery of Docker containers into Consul.
For more information about Registrator, you can visit: https://gliderlabs.com/registrator/.
Let's start to install our architecture!
We'll start by creating our first machine: Consul
To do that, just type:
$ docker-machine create -d virtualbox consul
Once the machine is fully ready, prepare your environment to use this Docker machine and launch a Consul container:
$ eval $(docker-machine env consul) $ docker run -d \ -p 8301:8301 \ -p 8302:8302 \ -p 8400:8400 \ -p 8500:8500 \ -p 53:8600/udp \ consul
Well, your Consul is ready to receive your services and also our Docker Swarm nodes!
By the way, you can open the web interface by obtaining the Consul machine IP address:
$ docker-machine ip consul <obtained-ip>
Then, open in your browser the following URL: http://<obtained-ip>:8500 .
Now, it's time to create the machine that corresponds to our first Docker Swarm cluster node and that will also receive the master role for our cluster (we need one...):
$ docker-machine create -d virtualbox \ --swarm \ --swarm-master \ --swarm-discovery="consul://$(docker-machine ip consul):8500" \ --engine-opt="cluster-store=consul://$(docker-machine ip consul):8500" \ --engine-opt="cluster-advertise=eth1:2376" swarm-node-01
As you can see, we've added the --swarm-discovery option with our Consul machine IP address and port 8500 that corresponds to the Consul API. This way, Docker Swarm will use the Consul API to store machine information with the rest of the cluster.
We'll now configure our environment to use this machine and install a Registrator container on top of it in order to auto-register our new services (Docker containers).
To do that, type the following:
$ eval $(docker-machine env swarm-node-01)
Then:
$ docker run -d \ --volume=/var/run/docker.sock:/tmp/docker.sock \ gliderlabs/registrator \ -ip $(docker-machine ip swarm-node-01) \ consul://$(docker-machine ip consul):8500
Here, you can notice that we share the host Docker socket in the container. This solution could be a controversial solution but in our example case, forgive me about that ;)
If you want to register services to Consul I recommend to register them using the Consul API in order to keep control on what's added in your Consul.
The -ip option allows to precise to Registrator that we want to register our services with the given IP address: so here the Docker machine IP address and not the Docker container internal IP address.
We are now ready to start our HTTP service. This one is located under the "ekofr/http-ip" Docker image which is a simple Go HTTP application that renders "hello, <ip>" with the IP address of the current container.
In order to fit this article needs, we will also create a different network for the two Docker machines in order to clearly identify IP addresses for our two services.
Let's create a new network concerning our first node:
$ docker network create \ --subnet=<IP_ADDRESS>/16 network-node-01
then you can use the newly created network to be used with your HTTP service container:
$ docker run -d \ --net network-node-01 \ -p 80:8080 \ ekofr/http-ip
Before executing the same steps for our second node, we will ensure that our HTTP service works:
$ curl http://localhost:80 hello from 172.18.0.X
We'll now repeat most steps we've ran for our first node but we'll change some values.  We can now discover what Consul brings to us.
Indeed, you can now resolve your service hostname `http-ip.service.consul` by using the DNS server brought by Consul and you should see your two services appearing as a DNS record:
$ dig @$(docker-machine ip consul) http-ip.service.consul ;; QUESTION SECTION: ;http-ip.service.consul. IN A ;; ANSWER SECTION: http-ip.service.consul. 0 IN A <IP_ADDRESS> http-ip.service.consul. 0 IN A <IP_ADDRESS>
In other words, a kind of load balancing will be done on one of these services when you'll try to join them http://http-ip.service.consul .
Ok, but what about the load balancing repartition? Are we able to define a priority and/or weight for each services?
Sadly, the answer is no, actually. An issue is currently opened about that on Github in order to bring this support. You can find it here: https://github.com/hashicorp/consul/issues/1088.
Indeed, if we look in details about SRV DNS record type, here is what we get:
$ dig @$(docker-machine ip consul) http-ip.service.consul SRV ;; ANSWER SECTION: http-ip.service.consul. 0 IN SRV 1 1 80 c0a86366.addr.dc1.consul. http-ip.service.consul. 0 IN SRV 1 1 80 c0a86364.addr.dc1.consul.
As you can see here, priority and weight are both defined to value 1 so the load balancing will be equal between all services.
If you add the Consul Docker machine IP address as a DNS server on your operating system, you'll be able to perform HTTP calls and see more easily what's happening on load balancing:
$ curl http://http-ip.service.consul hello from <IP_ADDRESS> $ curl http://http-ip.service.consul hello from <IP_ADDRESS>
Here, we have an IP address that corresponds to each HTTP service that we have registered so we can clearly see that we are load balanced between our two containers.
We'll now add a Health Check to our service in order to ensure that it can be use safely by our users.
In this case we'll start to return on our node 01 and suppress the container named ekofr/http-ip in order to recreate it with a Health Check:
$ eval $(docker-machine env swarm-node-01)
$ docker kill \ $(docker ps -q --filter='ancestor=ekofr/http-ip')
Registrator brings us some environment variables in order to add some Health Check for our containers into Consul and you can see the full list here: http://gliderlabs.com/registrator/latest/user/backends/#consul.
Idea here is to verify that port 80 is opened and application answers correctly so we'll add a script that simply executes a curl command:
$ docker run -d \ --net network-node-01 -p 80:8080 \ -e SERVICE_CHECK_SCRIPT="curl -s -f http://$(docker-machine ip swarm-node-01)" \ -e SERVICE_CHECK_INTERVAL=5s \ -e SERVICE_CHECK_TIMEOUT=1s \ ekofr/http-ip
You can do the same thing on your node 02 (by paying attention to modify the node-01 values to node-02 ) and you should now visualize these checks on the Consul web UI:
You can also use the Consul API in order to verify the good health of your services:
$ curl http://$(docker-machine ip consul):8500/v1/health/checks/http-ip .. [ { "Status": "passing", "Output": "hello from <IP_ADDRESS>", "ServiceName": "http-ip", }, ... ]
You are now able to install Consul on your projects architectures in order to ensure that services you contact are available and also be able to identify eventual issues that can occur on your services.
It's important to add a maximum of checks on elements that can make your services become unavailable (ensure that this one can be contacted and answer, ensure that remaining available disk space is sufficient, etc...).
Consul is a tool that integrates well in your architectures by its simplicity of use and its powerful API.
{% endraw %}


{% extends "global/Page.html" %} {% load static otree %} {% block title %} Round {{ player.round_number }} of {{ Constants.num_rounds }} {% endblock %} {% block content %}
In this period, you are matched with a random worker. You will select a wage offer for a worker by drawing a ball from the jar below. But before you draw the ball, please state the wage that you would have offered to the worker if you could offer any wage of your choice;
You proposed a wage of {{ group.proposed_wage }}. The selected wage for worker in this period is {{ group.random_wage }} points {% formfield group.expected_effort label="Based on the selected wage, what effort do you expect the worker to choose." %} {% next_button %} {% if player.id_in_group == 1 %} {% include 'gift_exchange/InstructionsForEmployerBaseline.html' %} {% endif %} {% if player.id_in_group == 2 %} {% include 'gift_exchange/InstructionsForWorkerBaseline.html' %} {% endif %} {% endblock %}


{% extends "secondary.html" %} {% block content %}
Uploading file... Please be patient as this may take a little while. In the meantime, enjoy a fortune: {{ witty_saying }}


Submit indemnity bond and take Nawaz, Awan tells PML-N
by Our CorrespondentISLAMABAD: Special Assistant to Prime Minister Imran Khan on Information and Broadcasting Firdous Ashiq Awan asked Pakistan Muslim League-Nawaz (PML-N) on Thursday not to do politics on the health of former premier Nawaz Sharif, according to Radio Pakistan.
Speaking to the media in Islamabad, she said PML-N should act responsibly and take advantage of the facility extended by the government for Nawaz’s treatment abroad.
“The government has demonstrated flexibility and gave him out-of-the-box one-time waiver to get the treatment abroad,” said Awan.
The minister added, “As per law, names of the convicted persons are not removed from the Exit Control List (ECL).”
Awan said the government only sought guarantee in the form of an indemnity bond which she termed “a legal requirement”.
“The PML-N should not make it a matter of its ego. Submit the indemnity bond and take Nawaz Sharif abroad for the treatment,” she maintained.
According to Awan, Prime Minister Imran had directed his team to refrain from doing any politics on the health of the PML-N supremo.
She also invited opposition parties to sit with the government for the resolution of problems faced by the masses.
“The parliament is functional and the opposition should cooperate with the government for the passage of people-friendly legislation.”
Awan said, “The government has put the country on the right track and the economy is heading towards stability.”
Commenting on Jamiat Ulema-e-Islam-Fazl’s (JUI-F) ‘Azadi March’, she said the people would not support the elements bent upon stoking instability in the country.
“JUI-F’s plan B will also flop like his Plan A. People fully understand the motives behind party chief Maulana Fazlur Rehman’s move.
‘Nawaz, Zardari old stories now’
Minister for Science and Technology Fawad Chaudhry termed Nawaz Sharif and Asif Ali Zardari as characters of the past in Pakistani politics.
“Shakespeare has written that the world is a stage. People come here, play their character and go. In the play of Pakistani politics, the role of Nawaz Sharif and [Asif Ali] Zardari has ended. New characters don’t give them any importance now other than using them to increase their roles,” said the minister in a tweet while criticising the PML-N and Pakistan People’s Party (PPP).


I am 23 years old I studied at AL Balqa Applied University in Salt, Jordan,from oct 2017 to jun 2021 i have a Bachelor's degree in Software engineering ,I want to become a web developer developer
I am 23 years old I studied at AL Balqa Applied University in Salt, Jordan,from oct 2017 to jun 2021 i have a Bachelor's degree in Software engineering ,I want to become a web developer developer


HTML & CSS Extras
First, please fill out this attendance sheet, and complete a few surveys.
Attendance Sheet
Surveys
Our first extra is going to be about floats, a useful layout tool.
This webpage has a bunch of challenges I want you to work on with the person next to you. Both of you should code everything. Don't move on until your partner understands what's going on.
Next, I'm going to do a few demos for everyone.
- FileZilla Site Manager
- How multiple files work
- IDs vs Classes
- Children vs parents
- Display: none & visibility: hidden
- Browser testing - Browserling
- The hr and br tag
- Commenting trick
- Why is CSS called CSS
- Separate stylesheet
- In the head of the HTML
- Inline styles
One more challenge!
There are a lot of ways you can select elements on a page to edit with CSS. This game helps you practice them. It gets really advanced, but the first half or so you should be able to get under your belt. Work on this together with someone next to you.


--- layout: post title: '2013 MySQL Conference and Expo -- a #DBHangOps Review' categories: - computing - database - linux - mysql tags: - '#DBHangOps' - computing - database - HangOps - mysql - mysql_planet status: publish type: post published: true meta: _edit_last: '1' _wpas_done_all: '1' _wpas_skip_3039720: '1' _wpas_skip_3039727: '1' _wpas_skip_3039731: '1' _wpas_skip_3039741: '1' --- Hey everybody! The Percona Live MySQL Conference and Expo just wrapped up last week and we're looking to get some conference in review talk from everyone! Talk about your favorite sessions, new things you learned, and your overall opinion of the conference! Hop online Wednesday at 12:00pm PDT (19:00 GMT) to join the discussion and share your experience from the 2013 Percona Live: MySQL Conference and Expo. Be sure to watch this twitter search or this blog post get a link for the google hangout tomorrow! Some talks that were specifically called out:


This is just a test to see if you are keeping up with Git and GitHub. If you can get to this page, then you are retaining the information pretty well.
For now, we will keep this short and simple. We will expand on this document in the future.


Hi there! I'm a 26 year old software engineer who specializes in a few languages such as Node.JS, HTML5, CSS3, Python, Visual Basic and am in the process of learning C#, C++ and Elixir and Golang. I am a simple guy who is a bit reserved and to myself more times than not and that is just about all I have to say on the matter.
I like to create things and resources that people can use. Check out some of them below!
{{ project.description }}
Here are the latest posts I've made about various things
{{ post.summary }}
These are my signature colors across my products!
HEX: #DB4343
RGB: rgb(219, 67, 67)
HSLA: hsla(0, 68%, 56%)
HEX: #394281
RGB: rgb(57, 66, 129)
HSLA: hsla(233, 39%, 36%)
HEX: #292152
RGB: rgb(41, 33, 82)
HSLA: hsla(250, 43%, 23%)
HEX: #181029
RGB: rgb(24, 16, 41)
HSLA: hsla(259, 44%, 11%)
I don't know why you are even reading this section honestly! But if you are then I thank you for even that much! It means a lot to me when people consider supporting independant businesses, projects and services. I have nothing but respect for them and I'm glad you have enough to read this.
I'm working on a form of perk for users on my Discord Server such as advanced feeds on updates, personal project requests and various other things. This is just my way of saying thank you.


anyone came up or have good sugestions for a melee build that would use pale master as a class? I saw some using either bard and fighter with if anybody has an idea that would add some flavor or an interesting twist to the build I would like to know. Thx all _________________ K.M. aka Chillychill
"Y'a pire que ne pas pouvoir, y'a savoir qu'on peut et ne jamais tenter"
try http://web1.vattnet.com/staffan/search/builds.htm there are 60 PM builds listed so 1 of them should meet your requirements _________________ Teaching men a lesson in combat etiquette.


25 Feb 2016
Time Reversal and PAT
The time reversal method works well when the wave speed is known and no attenuation is present, but it requires a long time observation on $\partial\Omega$.
However, it is already known that the observation time must be larger than a minimum $T$, to let all information pass through. And in 2D, the waiting time is much longer than odd dimension due to $\mathcal{O}(t^{1-d})$ decay rate of energy. Thus we do not have enough resources to wait such a long time.
The ending solution does not vanish $u(T, x)\neq 0$, not even close to $0$ maybe. The Neumann series method works here, using an "error" operator.
Take pressure field mapping to measurement as $A:f\to u(t, \partial\Omega)$, and take time reversal operator $Q: u(t,\partial\Omega)\to u(0, x)$. The error operator is defined as
$$Kf = f - Q(Af)$$
if we take $Af = h$ which is known measurement, then
$$Qh = (I - K)f$$
when $T>T_0$, it is possible to show that $|K|<1$, therefore,
$$f = (I-K)^{-1}(Qh) = \sum K^m (Qh)$$
The algorithm is trivial here.
- calculate time reversal $Qh$ as an initial guess of $f$, let $v = Qh$, $r = Qh$.
- calculate $w = v - Q A(v)$, $r = r + w$
- $v = w$ and repeat step 2.
We must see that each iteration consists of one forward and one backward propagation. It will take $\mathcal{O}(T)$ time for each. That is the sketchy outline of this method.
This is the reconstruction image for initial condition. There is larger errors on jumps around phantom (WF set), for smooth bumps at corners, the reconstruction is accurate (w.r.t to the spatial discretization).
Now let's look at the implementation.
forward model, namely operator $A$, it is to solve a wave equation in $\Omega\times[0, T]$, the wave equation lives in $\mathbb{R}^3$, thus finite domain has to deal with some absorption boundary, using PML or sufficient large domain would help.
The PML method sets the absorption layer around $\Omega$, we will solve an equation like
$$ \begin{equation} \frac{d}{dt}\pmatrix{u\\u_t\\p\\q} = F(u, u_t, p ,q) \end{equation} $$
any solver for first order ODE will work here, the forward model should be solved with high accuracy, thus a fine mesh will be necessary.
backward model, iteratively, calculate
$$K^m Qh = K(K^{m-1}Qh) = K^{m-1}Qh - QAK^{m-1}Qh$$
The first term was stored from last step, the second term will need a forward plus a reversal.


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The Psychic Game
Guess what letter I'm thinking of
Wins:
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Guesses left:
9
You guessed so far:


|
A Biochemical Simulation Model of Photosynthesis and Transpiration
1.0
C++ code that can be incorporated into modes to simulate photosynthesis
|
Contains code to simulate gas exchange. More...
Go to the source code of this file.
Namespaces | |
| photomod | |
Macros | |
| #define | R 8.314 |
| R idealgasconstant More... | |
| #define | maxiter 200 |
| maxiter maximum number of iterations More... | |
| #define | epsilon 0.97 |
| epsilon emissivity See Campbell and Norman, 1998, page 163 (CHECK) More... | |
| #define | sbc 5.6697e-8 |
| stefan-Boltzmann constant Wm-2 k-4. More... | |
| #define | scatt 0.15 |
| leaf reflectance + transmittance More... | |
| #define | f 0.15 |
| spectral correction More... | |
| #define | O 205.0 |
| Oxygen partial pressure gas units are mbar. More... | |
| #define | Q10 2.0 |
| Q10 factor. More... | |
Contains code to simulate gas exchange.
Definition in file gas_exchange.cpp.
| #define epsilon 0.97 |
epsilon emissivity See Campbell and Norman, 1998, page 163 (CHECK)
Definition at line 21 of file gas_exchange.cpp.
| #define f 0.15 |
spectral correction
Definition at line 24 of file gas_exchange.cpp.
| #define maxiter 200 |
maxiter maximum number of iterations
Definition at line 20 of file gas_exchange.cpp.
| #define O 205.0 |
Oxygen partial pressure gas units are mbar.
Definition at line 25 of file gas_exchange.cpp.
| #define Q10 2.0 |
Q10 factor.
Definition at line 26 of file gas_exchange.cpp.
| #define R 8.314 |
R idealgasconstant
Definition at line 19 of file gas_exchange.cpp.
| #define sbc 5.6697e-8 |
stefan-Boltzmann constant Wm-2 k-4.
Actually varies somewhat with temperature
Definition at line 22 of file gas_exchange.cpp.
| #define scatt 0.15 |
leaf reflectance + transmittance
Definition at line 23 of file gas_exchange.cpp.


PLEASE WAIT:
The lid is heating to {{experiment.protocol.lid_temperature | round: 1}}°C
This will take about one minute
Warming the instrument at {{getBlockHeat() | round: 1}}°C
Estimated remaining time {{ timeRemaining | secondsDisplay: 'display2'}}
Please don't open the machine during this step.


Status
Server status:
Active-
Characters
== 100
-
Episodes
== 80
-
Locations
== 40
-
Cities
== 10
What is this?
The simpsons Api is a service that icludes all the data in the simpsons universe.
Most the people have seen the simpsons and really enjoy each chapter, doesn't matter if is the fourth or fifth time that you whatch it. Also we know there are a lot of companies, insitutions and programmers that test apps even web apps or local programms with data that they have to fill or request. For those reasons, we present to you all the Characters, Episodes, Locations and Cities of the simpsons Universe.
We have formatted this data in JSON and exposed it to you with a RESTful app.
Check out the documentation to get started consuming the simpsons data
What can I use this for?
Even if you are a company or just someone that recenty started to learn programming you all can use this api to test your apps or make and app that is related with or needs this data for a long time you won't spend time making an Api or searching all the information about characters or other series, you are going to have all the information just with one consult of distance.
Who are you?
We are Sergio bustos, a guy who likes to develop anykind of app and Jair Ayala, the person in charge of maintain the "Simpsons Api" database updated. We both love the simpsons and whe know there are a lot of people that love them too.
Technical stuff?
We use Flask and sqlite to serve the API. All the data is formatted in JSON and the entire project is hosted on pythonanywhere. However in order to optimize the Api the images are located into a especial server for images.
How can i contribute to the project?
you can help us to keep the project alive with any donation or you can also contribute on Github.
Copyright?
The simpsons API was created by Sergio Bustos and Jair Ayala. The data and images are used without claim of ownership and belong to the respective ownership.
This Api is open source and uses a MIT license.


CLOUD 360°
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Team!
Let's improve our
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Join Us!
Jonatas Emidio
Github
Igor Costa
Github
Gabriel Lima
Github


For the XSFoundation project, I've coded an integrated debugger, that signals memory faults.
On Mac OS X or Unix-like system, I can use the backtrace() function, from execinfo.h to retrieve a function call stack, when necessary.
This way, when a fault occurs, the debugger can show you where the fault occurred.
As XSFoundation is a portable library, I had to do the same thing on Windows.
I first try using the StackWalk64 function, with no luck.
At last, I found a solution using the CaptureBackTrace function, from the MS API.
The output will be the following:
6: printStack - 0xD2430 5: wmain - 0xD28F0 4: __tmainCRTStartup - 0xE5010 3: wmainCRTStartup - 0xE4FF0 2: BaseThreadInitThunk - 0x75BE3665 1: RtlInitializeExceptionChain - 0x770F9D0F 0: RtlInitializeExceptionChain - 0x770F9D0F
Here's the actual code to achieve this:
void printStack( void ); void printStack( void ) { unsigned int i; void * stack[ 100 ]; unsigned short frames; SYMBOL_INFO * symbol; HANDLE process; process = GetCurrentProcess(); SymInitialize( process, NULL, TRUE ); frames = CaptureStackBackTrace( 0, 100, stack, NULL ); symbol = ( SYMBOL_INFO * )calloc( sizeof( SYMBOL_INFO ) + 256 * sizeof( char ), 1 ); symbol->MaxNameLen = 255; symbol->SizeOfStruct = sizeof( SYMBOL_INFO ); for( i = 0; i < frames; i++ ) { SymFromAddr( process, ( DWORD64 )( stack[ i ] ), 0, symbol ); printf( "%i: %s - 0x%0X\n", frames - i - 1, symbol->Name, symbol->Address ); } free( symbol ); }


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QRBucks
- Class in
com.example.zoomwroom.Entities
This class represents the QRBucks in the form of IOUs.
QRBucks()
- Constructor for class com.example.zoomwroom.Entities.
QRBucks
QRBucks(String, String, float)
- Constructor for class com.example.zoomwroom.Entities.
QRBucks
QRBucks(String)
- Constructor for class com.example.zoomwroom.Entities.
QRBucks
Constructor to use when scanning in a QR Code as it will do all the parsing QR Code should be code like this: Rider'sFullName-driveRequestID-offeredfare
QRBucks.StatusQRBucks
- Class in
com.example.zoomwroom.Entities
QRBucksAdapter
- Class in
com.example.zoomwroom
QRBucksAdapter(Context, ArrayList<QRBucks>, QRBucksAdapter.OnQRBucksClickListener)
- Constructor for class com.example.zoomwroom.
QRBucksAdapter
QRBucksAdapter.OnQRBucksClickListener
- Interface in
com.example.zoomwroom
QRCode
- Class in
com.example.zoomwroom.Entities
QRCode(String)
- Constructor for class com.example.zoomwroom.Entities.
QRCode
Deprecated.
QRCode(String, int)
- Constructor for class com.example.zoomwroom.Entities.
QRCode
Deprecated.
might cause errors
QRDisplayFragment
- Class in
com.example.zoomwroom
QRDisplayFragment(String)
- Constructor for class com.example.zoomwroom.
QRDisplayFragment
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BFO_0000029 - site
Label
site
Sub class of
Definition
B is a site means: b is a three-dimensional immaterial entity that is (partially or wholly) bounded by a material entity or it is a three-dimensional immaterial part thereof. (axiom label in BFO2 Reference: [034-002])
Example
the interior of a kangaroo pouch
the interior of your refrigerator
Manhattan Canyon)
your left nostril (a fiat part – the opening – of your left nasal cavity)
the interior of your bedroom
the interior of the trunk of your car
a rabbit hole
the Grand Canyon
the interior of your office
the Piazza San Marco
the cockpit of an aircraft
the hold of a ship
a hole in the interior of a portion of cheese
an air traffic control region defined in the airspace above an airport
the lumen of your gut
Imported from


Prime Calculator
Input a number and this page will calculate all prime numbers lower than your number!
Submit!


block
block(g: GeneratorFunction, m?: string): Parser
Executes a generator function that can yield to parsers in its body.
block
is the most versatile parser in the entire library and provides a way to parse pretty much anything without having to write a custom parser. It corresponds to using do-notation blocks in Haskell (hence the name block
).
The generator function can do anything that any function could do. In addition, it can have yield
expressions that yield any parser. That parser will be applied at that point, and if it's successful, its result will be fed back into the generator function, able to be used as needed (for example, in const number = yield join(many1(digit()))
in the example, the result of the join
parser is assigned to the variable number
). When the generator function returns, its return value becomes the value returned by the block
parser.
If any of the parsers fail when yielded, then block
will fail. If any input was consumed before the failure, that failure will be fatal.
block
can be used to implement pretty much any other combinator. It, in conjunction with any
, could be used to implement any other parser in this library. However, if there is a parser that already does what needs to be done, it's sure to be more efficient than just shoving everything into a block
.
This is most notable with sequences. A block
parser that discards a number of parser results and keeps one, returning that result, can very often be implemented as a seq
wrapped in nth
. This is a fairly common use case.
Example
const parser = block(function *() {
yield spaces()
const sign = yield opt(alt(char('+'), char('-')))
const number = yield join(many1(digit()))
yield spaces()
const result = parseInt(number) * (sign === '-' ? -1 : 1)
return result
})
const s = parse(parser, ' 1729 ')
console.log(status(s)) // "ok"
console.log(success(s)) // 1729
const f = parse(parser, 'abcd')
console.log(status(f)) // "fail"
console.log(failure(f)) // Parse error at (line 1, column 1):
//
// abcd
// ^
// Expected a digit
const t = parse(parser, '-abcd')
console.log(status(t)) // "fatal"
console.log(failure(t)) // Parse error at (line 1, column 2):
//
// -abcd
// ^
// Expected a digit
The first yielded parser here is spaces
. This skips zero or more whitespace characters. Its result is discarded as it is not assigned to anything (besides, spaces
only returns null
so its result isn't useful).
The second yielded parser is opt(alt(char('+'), char('-')))
. This will match either a '+'
or '-'
if it's there, or return null
if the next character is neither of those (without opt
it would fail, and we don't want that because it's okay for a number to have no sign). This value (either '+'
, '-'
, or null
) is assigned to the variable sign
.
The third yielded parser is join(many1(digit()))
. This simply matches a series of one or more digit characters (0-9
), returning them as a single string instead of an array of characters (because of join
). This parses a natural number, assigning the result to number
. (When combined with sign
, this could be a negative number as well, so the two together parse an integer.)
The fourth yielded parser skips whitespace at the end, similar to the first parser.
After the parsing is done, sign
and number
are used in a calculation that turns them into an integer of the JavaScript number
type. This number is returned at the end, so the block
parser in total results in this number. Note that it isn't a string, like most parsers return; block
can return anything that its function can return.
The first case (s
) shows success. Whitespace was skipped before and after the number, an optional sign was parsed (which was not present), and then the string '1729'
was parsed. The calculation turned this into the number 1729
, which was returned.
The second case (f
) fails because the first character is not a digit. It does not have to be whitespace (spaces
can match zero spaces) and it does not have to be a sign (that parser is optional), but the digit
part of the third parser has to be matched. No input was consumed before this failure, so it is not a fatal failure.
The third case (t
) fails because, while the whitespace was ignored and the optional sign was parsed, the third parser fails against the non-digit 'a'
. Since input was consumed (the negative sign) before this failure, it is fatal.
Parameters
g
: A generator function that provides the body of theblock
parser. This generator function canyield
parsers, which will have those parsers' results fed back into the function when it's restarted (so that they can be assigned to variables, used in calculations, etc.). The return value of this generator function becomes the result of theblock
parser.m
: The optional expected error message that will take the place of the default error message.
Success
- Succeeds if every parser that is applied in the generator function succeeds. (Not all parsers need be applied; those that are skipped by conditional statements, for instance, will never execute.) Returns the return value of the generator function.
Failure
- Fails if any yielded parser fails before any input is consumed.
Fatal Failure
- Fails fatally if any yielded parser fails fatally.
- Fails fatally if any yielded parser fails non-fatally after some input was consumed.
Throws
- Throws an error if
g
is not a generator function. - Throws an error if
m
exists and is not a string. - Throws an error if any
yield
statement is executed and the value that is yielded is not a parser.


An Open-Source, Community-Maintained Database ofWeb Standards & Related References.
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Address Validation
Line 1
Line 2
City
State
Postcode
Validate Address
`
×
Address Validation Results
×
Please Provide: Street City and State


Background: I am a 19 year-old male college student, 5 ft. 10 in. tall, and weighing in at 145 lbs. I am a regular Cannabis and Tobacco user. I have used on multiple past occasions: Dextromethorphan, Opiate painkillers, JWH-018, and Alprazolam (Xanax). I have also experienced 'Shrooms' three times, LSD (1 potent tab) once, LSA (Morning Glory tea) about 5 times, and one nightmarish Salvia breakthrough in which I ran around the yard slamming into fences. I used Adderall XR 20mg for ADHD on and off throughout my childhood (6 years+) and it now causes me to fear for the health of my heart. Also, I have been having mild/moderate panic attacks almost daily for about 2 weeks, a recently developed 'panic disorder.'
Preparation: 1000 mgs of 5-MEO-DALT are mixed with 100 ml of 89% Ethanol in a VERY flat, square glass (Pyrex) baking tray. The powder seems to be insoluble in this solution, so I stir it vigorously for 10 minutes. The clumps now seem broken down fairly well, and I place the tray across a stove burner on low to evaporate the ethanol, once again, making sure that the pan is flat and level. Once the ethanol has evaporated completely I was left with a fairly consistent powder layer on the bottom of the tray.
(WARNING: I do not recommend using this method of measuring out dosages in MG! The solvent used in the situation was not appropriate and even if you are working with a solvent that works for your substance(s), the baking tray must be COMPLETELY flat and level, as to avoid higher concentrations of your chem on one side or in random places on your glass tray due to pooling solvent.)
Using a ruler, I measure 10x10 (100) even squares and mark them out with a razor blade, carefully making a grid out of the powder in the baking tray. Paper Towel squares (100) were cut to the size of each square in the grid now cut into the powder on the baking pan. Each square of paper towel (about 1'x1') is wet with a spray of vegetable oil, and placed on top of a square of the grid in the pan, then slid outward to the edge of the pan while pressing down, to capture the powdered DALT.
Finally, each paper towel square was folded shut, and stuffed into an empty size 00 gel capsule. This was repeated for the remaining 99 squares of paper towel.
Experience: T+00:00- One gel capsule containing assumably ~10mgs (+/- ~5mg) of 5-MEO-DALT was taken orally, with a glass of root beer and some grilled chicken. Freaknik: The Musical was on TV. A friend, who I will call 'A', came over to 'trip sit.'
T+00:15- I am feeling slightly altered, but not enough to know in what way. A and I pack a bowl of some high-grade Cannabis.
T+00:20-A asks me how I'm feeling. I answer that I'm feeling it, but that right now it's just a tingling in the body. On the come-up I was quite cautious, enough to have killed the fun of the experience but it's ok. I was constantly trying to differentiate normal bodily functions from drug side effects and watch out for panic attack symptoms (I actually didn't have any of these!). A and I finish smoking our bowl in the meantime and about 30 minutes after dosing-
T+00:30- I am definitely 'feeling it.' My body is buzzing hard, and for the very few seconds I can stop worrying about watching out for side effects and checking my pulse (which seemed steady, with a rate within normal limits, but strong), I am in a wonderful mood. It's very hard to define this feeling. I feel as though it was only a glimpse of what this drug can do, as even though it seemed 'intense' in a way, it was faint and indefinable. I couldn't put words on how I felt altered at all, other than 'My body is buzzing... or tingling a little, like when you're on shrooms but it doesn't feel as much like sex.'
T+00:45 I am peaked, and have been for a few minutes. Same feeling as before, just stronger slightly. I am in a great mood when I'm not worrying about a panic/heart attack. It is interesting to note that at this point, Freaknik: The Musical had to be turned off, because it was 'too much' for me to watch. It felt as if all the colors and sounds and seas O' booty-shakin' was an overload of nonsensical information. My head started to hurt and I changed the channel to King of the Hill. This was the only moment like it throughout the 'trip.' A and I go outside to pack another bowl now.
I started to come down at about T+01:00. At T+2:00 I am no longer feeling the DALT, or much of the weed, but I've got the munchies real bad, and like another user has reported, my munchies seemed logical and almost healthy compared to the stupidly sugary foods I get the munchies for on weed alone. I was craving burgers and steak, real foods I rarely have an appetite for.
Summary: I'm definitely interested in trying this substances in increasing dosages, but next time, I will try smoking the same amount. Thus far, it SEEMS fairly safe in small doses, my heart did not race, and though my breathing became deeper (that's a personal side effect of any psychedelic on me, because breathing deep while tripping feels wonderful), and my pupils were very dilated, no other obvious physical side effects were noted. Also, there were no negative emotional side effects. I felt uplifted and if anything, and more relaxed, though the relaxed feeling is what we call 'stoned.' Until next time, stay safe, stay educated.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Persons archive
Simple REST application to create, delete and display instances of persons (see class PersonPojo).
Add a person
Name
Email
Password
×
Create new person
Name
Email
*
Password
*The email will be validated.


CU POP BUS
APPLICATION BY THINC.
Even more convenient using
CU POP BUS application by Thinc. to aid you to keep track of
CU POP BUS
CU POP BUS application by Thinc. to aid you to keep track of
CU POP BUS


index.html to demo loading bundled JS into browser Using the UMD build, the `hello` function is exposed as `window.hello`


---
layout: default
title: Contact Us
class: contact
parent: Contact
---
Michael Goffredo Foundation
michaelgoffredofoundation.org
Donations (tax deductable 501c3)
Tax ID # 27-1456756
Make checks payable to:
Michael Goffredo Foundation
1271 S Vine St
Denver, CO 80210-1819
For additional information regarding the Michael Goffredo Foundation:


{% extends "_layouts/default.html" %} {% block custom_head %} {% endblock %} {% block content %}
A Maximum of 1000 variants or 100kb will be queried and returned. Heterozygous calls are likely errors. When rows are yellow, it indicates the entire variant failed QC.
Hovering over a failing genotype will list the filter applied. Genotypes are shown as follows:| CHROM:POS | REF / ALT | Filter | AF | Gene Name | WormBase ID | Sequence | Coding Change | Biotype | Annotation | Impact |
|---|