Element is a 1 or 2 player game where you take control of 1 of 10 playable characters to defeat your opponent.
How To Play
Element is a turn based game that tracks multiple player statistics. On the header page, you will see a short summary of each of the different playable elements. To select one, enter its name (note: it will only work if you use capital first letter). You must do this twice, one for each player. Once you select your character, you will be accompanied by the following statistics:
-Health: Starting health of your character.
-Armor: Flat damage reduction against normal attacks.
-Speed: First attack priority. Every turn, a random number generator determines who takes their action first, there is no advantage in being player 1 or player 2.
-Agility: Percentage chance to dodge a normal attack.
-Max Damage: when attacking, a random number generator will choose a number from 0 to this number and deal damage.
-Starting Energy: Energy is used to activate abilities, this is how much you will have available at the beginning of the game. you gain 1 more every turn.
The next 3 items are your abilities, their energy cost is listed next to them and their description of what they do underneath.
the next item is a passive ability. It is a special ability that is always active and is completely free.
lastly, is the tips. Its a summary of the character, their strengths, weaknesses, and play style.
After both players have chosen their elements, they will move onto the battle phase. There is some statistical data displayed at the top, they are:
-Element Name
-[remaining health]
-[current status]
-[current energy]
*Default status is "Healthy", certain abilities change this.
Every turn, you may take 1 of 6 actions:
1) attack for a random value between 0 and maximum attack value, there is a chance to miss based on your opponents agility and will be reduced in damage by your opponent's armor.
2) defend against your opponent's attack, half incoming damage (only effects attacks, not abilities)
3 - 5) activate an ability, the energy cost is listed inside the brackets. effects vary depending on element being played
6) surrender and loose immediately.
0) ai code (disabled for Sweep mode)
The game ends when a player's health reaches 0.
After the battle, the results will be saved for future reference, if you would like to look up statistical data, enter "y" for yes on the next screen (the one with the 10x10 grid of numbers, these are the saved wins and losses for all match ups for the normal characters. If you enter y, you will be asked to enter in what match ups you would like to look up.
If the elements are different: it will look up that specific match up, wins and losses.
If you enter the same element twice: it will look up that element's win rate against all opponents
If one of the two elements entered is "All": it will look up the overall win rate of all elements and display them.
Admin Commands
On the initial screen, there are numerous commands you can enter.
FillData
Run an ai battle to determine a quick result between 2 random combatants.
FillDataFast
Run an infinite number of ai battles, use to populate data if you want statistics.
FillDataOne (use on player 2 screen)
Run an infinite number of ai battles, the first combatant will always be the same, use for statistical purposes.
SystemFill
Run an infinite number of ai battles in a specific order so each element battles each other the same amount of times. Use to populate data for statistics.
SystemFillOne
Run 2 ai battles of each matchup, useful for quick statistics.
no
Skip the battle and go directly to the statistical analysis page.
Rand
Enter a number to mix up the random number generator so you do not get repeat results
Secret
Add the 4 hidden characters to the top menu, will not reveal their codes to play them
Sweep (use on player 2 screen)
Activate special single player mode, fight each element until you win, test your skills with a given element to achieve victory over all opponents.
Changes From Version 1
-Added screen coloring to better determine whose turn it is. Red for player 1, blue for player 2.
-Changed how stats are shown on the header screen, from ambiguous phrasing to statistical bar graphs.
-Adjusted text to better align menus.
-Various AI improvements
*NEW* added 3rd and 4th new secret characters, Idler and Techmaturgy. The other two are Energy and Morphling. Figure out their secret codes to play them.
Balance Changes
Fire:
-Armor increased to 6 from 3
-Max Attack reduced to 25 from 30
-Speed increased to 55 from 50
-Dodge increased to 30 from 20
-Starting energy reduced to 3 from 4
-Flamethrower:
Damage reduced to 35 from 45
Water:
-Wave:
Cost reduced to 1 from 2
Damage reduced to 24 from 33
-Barrier:
Cost increased to 4 from 3
Static:
-Health increased to 270 from 230
-Armor increased to 8 from 2
-Dodge reduced to 15 from 25
-Shock Absorb:
Healing rate increased to double opposing damage from just the base value
Holy:
-Health increased to 250 from 170
-Armor increased to 6 from 4
-Max attack increased to 45 from 38
-Speed increased to 40 from 35
-Starting energy reduced to 4 from 5
-Divine Blessing:
Cost increased to 4 from 3
-Hinder:
Cost increased to 5 from 4
-Smite
Cost decreased to 6 from 7
Wind:
-Health increased to 170 from 150
-Max attack increased to 35 from 25
-Speed reduced to 75 from 80
-Starting energy reduced to 2 from 3
-Wind Charge:
Cost decreased to 3 from 4
Maximum damage increased to 85 from 75, still remains +50
-Tempest:
Cost increased to 7 from 6
Damage reduced to 100 from 120
Earth:
-Health increased to 350 from 300
-Armor increased to 10 from 6
-Max damage increased to 40 from 30
-Speed increased to 35 from 30
-Starting energy reduced to 2 from 3
-Boulder:
Cost reduced to 3 from 4
-Shakedown:
Cost reduced to 4 from 6
-Quake:
Cost reduced to 7 from 8
Blood:
-Armor increased to 4 from 3
-Max attack increased to 50 from 35
-Bleed:
Damage increased to 10% per turn from 5% (new maximum is 27.1% from 14.3%)
-Drain:
Cost reduced to 3 from 4
-Ravage:
Damage increased to Attack*4 + 20 from Attack*4 (keep in mind the attack buff from 35 to 50)
Cost increased to 6 from 5
Dark:
-Armor increased to 6 from 3
-Max attack decreased to 15 from 30
-Speed increased to 70 from 65
-Shadowmeld:
Now has a 1 energy penalty if it is not used to dodge an ability
Now activates passive a second time if dodge is successful against an ability
Venom:
-Health decreased to 170 from 230
-Armor increased to 3 from 2
-Max damage reduced to 15 from 30
-Hidden:
Renamed: Sneak Attack
-Piercing Shot:
Cost increased to 6 from 5
-Passive:
Venom damage per stack reduced to 3 from 5
Conclusion
I am sorry the new version took so long to come out, but I was incredibly bogged down by IRL projects. If you have any questions about the game, balance suggestions, or other ideas, PLEASE send me a message (be specific so I know what you are talking about). If it does not work initially, try creating a document called "Balance.txt", this is where all of the battle data will be saved. I wanted to get this up as soon as I got a chance to, so the code is slightly messy and un-commented, some comments are inaccurate, however, all data that is displayed within the game is up to date. Have fun with Element!
(Due to the amount of changes and additions to the game I made, I am unable to directly post the source code due to length restrictions, I'll include a .txt in case you cannot get .cpp files)
EDIT:
I went back and commented all of the code to make it more readable, all comments should be up to date now, I also noticed a few small bugs that are now fixed:
-Morphling cannot activate idler's and tech's 3rd ability now, caused major inconsistencies program-wise
-Fixed typo in earth, boulder does 20 damage, not 30
-Fixed bug that allowed Energy element's cost on 1st ability to be reimbursed if used to block an attack (not an ability)
I also added a title screen to make it a bit more game-like once it is started up.
Lastly, I am also adding match data I have gathered if you want to use that as a base, it's in the file "Balance.txt"
Attachments:
[Balance.txt]
[Element.cpp]
[Element.txt]


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In 2020 I co-founded BytePact to share my expertise and passion about software development and (STEM) education with others. At present I work remotely on the product development of MakerStudio, a 2D design and fabrication platform for people who want to create stuff even if they consider themselves unfamiliar with digital design.
Before, I was doing research on computer science and STEM education as a PhD student with Dwengo at Ghent University. I left the university due to my move to Asia in 2021. In 2017 I co-created the Co-De learning platform for teaching computational thinking in secondary education. .
I hold masters degrees in Computer Science and Musicology from the University of Leuven and have completed an Erasmus exchange at Université Paris-Sorbonne Paris IV.
I grew up on an isolated farm in Belgium that carries the name Zillekeshoeve. My maternal grandparents moved there in 1949 (after the liberation). At that time there was no electricity nor running water for several years. This is something I like to remind myself of regularly to be thankful that the digital revolution from the past decades is indeed... a revolution. The name of the farm stems from a Zil, an old, local unit for measuring farming land. One Zil measures the area of land that one farmer can plow by himself with horse and plough. In the case of my grandfather, that must have been quite a lot. In the 1980s my parents decided to stay on the farm, because they deemed living in solitude, but in the viscinity of family, a very rewarding experience. Maybe this explains why I'm so drawn to living in a mega city for now?
My father is an experienced maker and DIYer. Needless to say, I grew up in a family that encouraged me to persue a career in STEM. In fact, as a 7-year old, my dad let me sort out his diodes by colour bands in his garage lab when I was bored... I had absolutely no clue what was going on, but being surrounded by all these little components somehow triggered my curiosity. My mother introduced me to the joy of playing music and learning a new language, hence my fascination for Chinese in recent years.


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This is a public repository for my latest open source code Data Science applications in diverse topics. Each link will take you to the github repository which
contains the codes and the pdf or html file of the results. Some HTML files are to big to be display through GitHub, in consequnece, they need to be download and open by their own
- Costumer deposit prediction - Machine Learning Part I: pre-process of a dataset of a marketing
campaign in a bank to promote deposits cointining demographic information of clients,
characterization of the latest contact and previous campaigns,
information of the relationship with the client and results of the campaign. Test of different
probabilistic methods (logistic regression, shinkage methods, Bayes Classifiers and Cost-Sensitive Learning techniques)
for prediction of the clients that will make deposits
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Script
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- Costumer deposit prediction - Machine Learning Part II: test of different
Machine Learning methods (Nearest Neighbors, SVM, Decision Trees, Random Forest,
Gradient Boosting, Neural Networks, Deep Neural Networks and Ensemble Methods)
in a dataset of a Marketing Campaign in a bank to determine which
clients are more likely to perfom a deposit
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- Comparisson of unsupervised classification methods over the Aemet dataset
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- Functional Data Analysis - AEMET
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- Functional Data Analysis - Pinch Data
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- Coding - Function to estimate a regression function non-parametrically considering a local cubic estimator.
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- >Network Community Detection - Game of Thrones: A song of ice and fire
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- Reporting - Shiny App of Traffic Accidents in Madrid
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============================================================================
Description of ALICE Silicon Drift Detector (SDD) Code (Rev. 2 — May, 17th 2008 — F. Prino)
============================================================================
SDD module geometrical description
SDD module geometrical description (= anode numbering scheme, time bin definition, conversion from local coordinates to detector coordinates) is managed by the AliITSsegmentationSDD class. The detector is divided in 2 drift regions along the drift direction (horizontal in the following scheme).
Each drift region is read by 256 anodes (anode pitch = 294 micrometers).
The anode signal is sampled every 25 ns, this allows to measure the drift time of the charge produced by the crossing particle.
The memory depth (= number of time bins) is of 256 samplings per anode resulting in 6.4 microseconds of maximum drift time.
Detector size (active region) along anode axis = 256 * 294 microns = 75.264 mm
Detector size (active region) along drift axis = 2 * 35.085 mm = 70.170 mm
microcables microcables /\ /\ || || || || || || 0 256 0 0 |----------------------|---------------------| 511 | time-bins | time-bins | | a | a | | n | n | X <_|_o____________________|___________________o_|__ | d | d | | e LEFT SIDE | RIGHT SIDE e | | s CHANNEL 0 | CHANNEL 1 s | | Xlocal > 0 | Xlocal < 0 | 255 |----------------------|---------------------| 256 | | V Z
=================================================================================================================
SDD digitization is implemented in the AliITSsimulationSDD class and managed via the AliITSDetTypeSim class.
Working scheme:
1) Hits --> SDigits (AliSimulation::RunSDigitization)
-> AliITS::Hits2SDigits
-> AliITS::Hits2Predigits
-> AliITSsimulationSDD::SDigitiseModule
-> AliITSsimulationSDD::HitsToAnalogDigits
- read hits, calculate anode and time bin using drift speed from OCDB and AliITSsegmentationSDD class
- apply electron cloud diffusion (gaussian smearing) along anode and drift directions, charge loss during drift (set to zero)
-> AliITSsimulationSDD::ChargeToSignal
- apply gain (from OCDB) to signal
- sum the signal to the baseline (from OCDB) value fluctuating with the
proper noise (from OCDB)
-> AliITSsimulationSDD::WriteSDigits
- call AliITS::AddSumDigit (which calls AliITSDetTypeSim::AddSumDigit) to write SDigits (AliITSpListItem) to file
2) SDigits --> Digits (AliSimulation::RunDigitization)
-> AliITSDigitizer::Exec
- load SDigits
-> AliITSsimulationSDD::FinishSDigitiseModule
-> AliITSsimulationSDD::FinishDigits
- check zero suppression option
-> AliITSsimulationSDD::Compress2D (if zero supp is active)
- apply zero suppression
- compress signal from 10 to 8 bit
- subtract low threshold
- calculate expanded signal by converting back from 8 to 10 bit
- store digit (by calling AliITS::AddSimDigit which calls
AliITSDetTypeSim::AddSimDigit) both compressed (8 bit, low threshold subtracted) and expanded (10 bit, low threshold added)
-> AliITSsimulationSDD::StoreAllDigits (if zero supp is not active)
- compress signal from 10 to 8 bit
- calculate expanded signal by converting back from 8 to 10 bit
- store digit (by calling AliITS::AddRealDigit which calls
AliITSDetTypeSim::AddRealDigit). Only expanded (10 bit) value is stored in fSignal. TO BE CHECKED AND FIXED!!!
========================================================================================================================
Local reconstruction is implemented in AliITSClusterFinderV2SDD class and managed via the AliITSDetTypeRec class.
Working scheme:
Cluster Finding (AliReconstruction::RunLocalEventReconstruction)
-> AliITSReconstructor::Reconstruct
-> AliITSDetTypeRec::DigitsToRecPoints
- Two possibilities:
A) RECONSTRUCTION FROM DIGITS
-> AliITSClusterFinderV2SDD::FindRawClusters
- build AliBin array from digit tree
- apply gain (from OCDB) correction
B) RECONSTRUCTION FROM RAW DATA
-> AliITSClusterFinderV2SDD::RawdataToClusters
- instantiate AliITSRawStreamSDD object and set
1) ddl map
2) low threshold for zero suppression (needed to decompress raw data)
- build AliBin array from raw data
- apply gain (from OCDB) correction
-> AliITSClusterFinderV2SDD::FindClustersSDD
- loop on AliBin elements and:
1) apply noise suppression (AliITSClusterFinderV2SDD::NoiseSuppress)
2) find peaks (AliITSClusterFinderV2::FindPeaks)
3) unfold clusters (AliITSClusterFinderV2::MarkPeaks)
4) calculate coordinates (AliITSClusterFinderV2::MakeCluster)
5) calculate cluster size (TO BE REVIEWED)
6) convert from anode/time bin to local coordinates
using drift speed (from OCDB) and AliITSsegmentationSDD class
7) apply correction from laser maps (from OCDB)
8) convert cluster charge from ADC to keV (from OCDB)
9) add cluster to cluster array
===============================================================================================================================
There are 6 directories in ITS/Calib with calibration data to be used in SDD reconstruction
1) DDLMapSDD
Contains: 1 AliITSDDLModuleMapSDD object with the correspondence between hardware/online and aliroot/offline numbering scheme for SDD modules
Online numbering scheme = DDL number, Carlos Number
SDD use 23 DDL each reading up to 12 Carlos cards (=12 modules)
Details on geometrical mapping can be found here.
Update in OCDB: every time the hardware cabling on the acquisition cards is modified (practically this should occur only at the beginning of data taking periods)
Object creation: macro StoreDDLMapSDD.C
strategy for storage via preprocessor to be finalized
2) CalibSDD:
Contains: 1 TObjArray with 260 AliITSCalibrationSDD objects, i.e. 1 AliITSCalibrationSDD object for each module with:
- status (0/1) of module
- status (0/1) for the 8 chips of the module
- flag to control the use of correction maps for the module
And:
- baseline
- noise
- gain
for each of the 520 anodes of the module
+ list of bad anodes (TArrayI)
NOTE: bad anodes are tagged in 2 ways:
1) inserted in the TArrayI of bad anode numbers
2) gain set to zero
Update in OCDB: after each sequence of PEDESTAL+PULSER run and PEDESTAL run -> launch ITSSDDBASda.cxx
-> measure baselines and noise for each anode
-> produce temporary output on LDC
PULSER run -> launch ITSSDDGAINda.cxx
-> read output of PEDESTAL
-> measure gain from test pulse for each anode
-> store baselines, noise and gain on FXS
Simulated files can be produced with the macro StoreCalibSDD.C
3) DriftSpeedSDD
Contains: 1 TObjArray of 520 AliITSDriftSpeedArraySDD objects, i.e. 1 AliITSDriftSpeedArraySDD for each drift region (hybrid).
The AliITSDriftSpeedArraySDD class contains AliITSDriftSpeedSDD objects with polynomial coefficients of fit to drift speed vs. anode number together with event number and event timestamp.
It provides methods for interpolation of drift speed vs. time.
Update in OCDB: 1) after an INJECTOR run
-> launch ITSSDDINJda.cxx
-> measure drift speed for each injector pad (33 drift speed determinations for each hybrid, at every 8th anode)
2) after a PHYSICS run (if and when SDD injector triggers will be implemented in the DAQ)
Simulated files can be produced with the macro StoreDriftSpeedSDD.C
4) RespSDD
Contains: 1 AliITSresponseSDD object with calibration parameters common to all modules:
- flag for zero suppressed data
- ADC to keV conversion factor for detected signal
- time offset to account for various delays in the measurement of drift time
Update in OCDB: from offline analysis (time offset from alignemnt studies
ADC to keV from reconstructed poits of cosmic tracks)
Simulated files can be produced with the macro StoreCalibSDD.C
5) MapsAnodeSDD
Contains: 1 TObjArray of 520 AliITSMapSDD objects, i.e. 1 AliITSMapSDD for each drift region (hybrid) with systematic deviations between particle crossing positions and reconstructed coordinates along anode axis
These residuals have been measured with the laser by scanning the detector surface on a discrete 2D grid.
Update in OCDB: never updated, data have been measured in the lab during the construction phase
Simulated files can be produced with the macro StoreMapsSDD.C
6) MapsTimeSDD
Contains: 1 TObjArray of 520 AliITSMapSDD objects, i.e. 1 AliITSMapSDD for each drift region (hybrid) with systematic deviations between particle crossing positions and reconstructed coordinates along drift axis
These residuals have been measured with the laser by scanning the detector surface on a discrete 2D grid.
Update in OCDB: never updated, data have been measured in the lab during the construction phase
Simulated files can be produced with the macro StoreMapsSDD.C
========================================================================================================================
ECD Run Types and DAs
---------------------
ECS Run Types available for SDD
1) STANDALONE
- for test purposes
- no DA launched at EOR
2) PEDESTAL
- GOAL: measure baselines and noise
- JTAG configuration: zero-suppression OFF
baseline equalization OFF
testpulse OFF
prepulse OFF
- DA: ITSSDDBASda.cxx (running on LDCs)
- uses AliITSOnlineSDDBase and AliITSOnlineSDDCMN classes
- calculates baseline, noise and common mode for each anode
- tags bad (= noisy + bad baseline) anodes
2) PULSER
- GOAL: measure gain
- JTAG configuration: zero-suppression OFF
baseline equalization OFF
testpulse ON
prepulse OFF
- DA: ITSSDDGAINda.cxx (running on LDCs)
- uses AliITSOnlineSDDTP class
- read PEDESTAL DA output
- calculates gain for each anode
- sets anodes with problems of gain (dead) as bad
- stores data to FXS
3) INJECTOR
- GOAL: measure drift speed
- JTAG configuration: zero-suppression ON
baseline equalization ON
testpulse OFF
prepulse ON
- DA: ITSSDDINJda.cxx (running on LDCs)
- uses AliITSOnlineSDDInjectors class
- calculates drift speed for each of the 33 groups of injectors
fits drift speed vs. anode with a 3rd degree polynomial
stores data to FXS
4) PHYSICS
Nothing done for now.
If/when injector triggers will be implemented in DAQ, a monitoring
DA will be prepared to calculated drift speed for these triggers.
===========================================================================================================================
DCS data points are used for reference. They are needed for a possible backup
estimation of drift speed in case of injector failure.
Values monitored (and stored every 2 minutes + when out of confidence band) by SDD DCS:
- 260 HV values (1 for each module)
- 260 MV values (1 for each module)
- 520 temperature values (1 for each hybrid)
Plus:
- 260 module status bits (1 for each module)
- 520 temperature status bits (1 for each hybrid)
Data treated by AliITSDCSAnalyzerSDD class which:
- compress status bits into 1 byte
- reduce data size by saving values only if out of confidence band with
respect to last stored value
- store data into AliITSDCSDataSDD objects for each module
Data stored in Reference/ITS/DCS/DataSDD.
Object stored: 1 TClonesArray of 260 AliITSDCSDataSDD (q for each module)


Module: Mime
| Relationships & Source Files | |
| Namespace Children | |
|
Classes:
| |
| Defined in: | actionpack/lib/action_dispatch/http/mime_type.rb |
Constant Summary
-
ALL =
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 343
ALL
isn't a real MIME type, so we don't register it for lookup with the other concrete types. It's a wildcard match that we use for `respond_to` negotiation internals.AllType.instance
-
EXTENSION_LOOKUP =
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 35{}
-
LOOKUP =
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 36{}
-
SET =
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 34Mimes.new
Class Method Summary
Class Method Details
.[](type)
[ GitHub ]39 40 41 42
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 39
def [](type) return type if type.is_a?(Type) Type.lookup_by_extension(type) end
.const_defined?(sym, inherit = true) ⇒ Boolean
62 63 64 65 66 67 68 69 70 71 72 73
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 62
def const_defined?(sym, inherit = true) ext = sym.downcase if Mime[ext] ActiveSupport::Deprecation.warn(<<-MSG.squish) Accessing mime types via constants is deprecated. Please change `Mime.const_defined?(#{sym})` to `Mime[:#{ext}]`. MSG true else super end end
.const_missing(sym)
[ GitHub ]49 50 51 52 53 54 55 56 57 58 59 60
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 49
def const_missing(sym) ext = sym.downcase if Mime[ext] ActiveSupport::Deprecation.warn(<<-MSG.squish) Accessing mime types via constants is deprecated. Please change `Mime::#{sym}` to `Mime[:#{ext}]`. MSG Mime[ext] else super end end
.fetch(type)
[ GitHub ]44 45 46 47
# File 'actionpack/lib/action_dispatch/http/mime_type.rb', line 44
def fetch(type) return type if type.is_a?(Type) EXTENSION_LOOKUP.fetch(type.to_s) { |k| yield k } end


|
Contiki 2.5
|
The SLIP protocol is a very simple way to transmit IP packets over a serial line. More...
Files | |
| file | slipdev.c |
SLIP protocol implementation. | |
| file | slipdev.h |
SLIP header file. | |
Functions | |
| u8_t | slipdev_send (void) |
| Send the packet in the uip_buf and uip_appdata buffers using the SLIP protocol. | |
| u16_t | slipdev_poll (void) |
| Poll the SLIP device for an available packet. | |
| void | slipdev_init (void) |
| Initialize the SLIP module. | |
| void | slipdev_char_put (u8_t c) |
| Put a character on the serial device. | |
| u8_t | slipdev_char_poll (u8_t *c) |
| Poll the serial device for a character. |
The SLIP protocol is a very simple way to transmit IP packets over a serial line.
It does not provide any framing or error control, and is therefore not very widely used today.
This SLIP implementation requires two functions for accessing the serial device: slipdev_char_poll() and slipdev_char_put(). These must be implemented specifically for the system on which the SLIP protocol is to be run.
Poll the serial device for a character.
This function is used by the SLIP implementation to poll the serial device for a character. It must be implemented specifically for the system on which the SLIP implementation is to be run.
The function should return immediately regardless if a character is available or not. If a character is available it should be placed at the memory location pointed to by the pointer supplied by the argument c.
| c | A pointer to a byte that is filled in by the function with the received character, if available. |
| 0 | If no character is available. |
| Non-zero | If a character is available. |
Referenced by slipdev_poll().
| void slipdev_char_put | ( | u8_t | c | ) |
Put a character on the serial device.
This function is used by the SLIP implementation to put a character on the serial device. It must be implemented specifically for the system on which the SLIP implementation is to be run.
| c | The character to be put on the serial device. |
Referenced by slipdev_send().
| void slipdev_init | ( | void | ) |
| u16_t slipdev_poll | ( | void | ) |
Poll the SLIP device for an available packet.
This function will poll the SLIP device to see if a packet is available. It uses a buffer in which all avaliable bytes from the RS232 interface are read into. When a full packet has been read into the buffer, the packet is copied into the uip_buf buffer and the length of the packet is returned.
Definition at line 144 of file slipdev.c.
References slipdev_char_poll(), UIP_BUFSIZE, and UIP_LLH_LEN.
| u8_t slipdev_send | ( | void | ) |
Send the packet in the uip_buf and uip_appdata buffers using the SLIP protocol.
The first 40 bytes of the packet (the IP and TCP headers) are read from the uip_buf buffer, and the following bytes (the application data) are read from the uip_appdata buffer.
Definition at line 97 of file slipdev.c.
References slipdev_char_put(), uip_appdata, UIP_FW_OK, uip_len, and UIP_LLH_LEN.


|
BitShares-Core
6.1.0
BitShares blockchain implementation and command-line interface software
|
An ID for some votable object. More...
#include <vote.hpp>
Public Types | |
| enum | vote_type { committee, witness, worker, VOTE_TYPE_COUNT } |
Public Member Functions | |
| vote_id_type ()=default | |
| vote_id_type (vote_type type, uint32_t instance=0) | |
| Construct this vote_id_type with provided type and instance. More... | |
| vote_id_type (const std::string &serial) | |
| Construct this vote_id_type from a serial string in the form "type:instance". More... | |
| void | set_type (vote_type type) |
| Set the type of this vote_id_type. More... | |
| vote_type | type () const |
| Get the type of this vote_id_type. More... | |
| void | set_instance (uint32_t instance) |
| Set the instance of this vote_id_type. More... | |
| uint32_t | instance () const |
| Get the instance of this vote_id_type. More... | |
| vote_id_type & | operator= (vote_id_type other) |
| vote_id_type & | operator= (uint32_t instance) |
| Set the instance of this vote_id_type. More... | |
| operator uint32_t () const | |
| Get the instance of this vote_id_type. More... | |
| operator std::string () const | |
| Convert this vote_id_type to a serial string in the form "type:instance". More... | |
Public Attributes | |
| uint32_t | content = 0 |
Friends | |
| size_t | hash_value (vote_id_type v) |
An ID for some votable object.
This class stores an ID for a votable object. The ID is comprised of two fields: a type, and an instance. The type field stores which kind of object is being voted on, and the instance stores which specific object of that type is being referenced by this ID.
A value of vote_id_type is implicitly convertible to an unsigned 32-bit integer containing only the instance. It may also be implicitly assigned from a uint32_t, which will update the instance. It may not, however, be implicitly constructed from a uint32_t, as in this case, the type would be unknown.
On the wire, a vote_id_type is represented as a 32-bit integer with the type in the lower 8 bits and the instance in the upper 24 bits. This means that types may never exceed 8 bits, and instances may never exceed 24 bits.
In JSON, a vote_id_type is represented as a string "type:instance", i.e. "1:5" would be type 1 and instance 5.
|
default |
|
inlineexplicit |
Construct this vote_id_type with provided type and instance.
|
inlineexplicit |
Construct this vote_id_type from a serial string in the form "type:instance".
|
inline |
Get the instance of this vote_id_type.
|
inlineexplicit |
Convert this vote_id_type to a serial string in the form "type:instance".
|
inline |
Get the instance of this vote_id_type.
|
inline |
|
inline |
Set the instance of this vote_id_type.
|
inline |
Set the instance of this vote_id_type.
|
inline |
Set the type of this vote_id_type.
|
inline |
Get the type of this vote_id_type.
|
friend |
| uint32_t graphene::protocol::vote_id_type::content = 0 |


--- layout: post title: 'iPhones Replacing Specialized Equipment, Doing More With Less : TreeHugger' categories: [] tags: [] status: publish type: post published: true meta: _original_post_id: '' _original_import_author: John Duprey author: ---
My $100+ garmin forerunner 50 (https://buy.garmin.com/shop/shop.do?pID=10527) died recently so I'm impatiently waiting for my iPhone Runkeeper app to get ANT+ support for my gamin heart rate monitor - perhaps through the Wahoo Fisica Fitness Sensor for the iPhone: http://www.wahoofitness.com/Fisica/Wahoo-Fitness-Fisica-Fitness-Sensor-Key.asp


This screen also provides an overview of your character's current locations and the ships they're in.


{% extends "components/base.html" %} {% block content %}
Please use the links on the navbar to go somewhere else!


WITNESS LIST Criminal Jurisprudence Committee February 12, 1997-2:00P HB 312 On: Carl Reynolds (TX Board Crim Justice) Registering, but not testifying: For: Sherri Wallace (Dallas Co Dist Attorney) On: Tom Krampitz (TDCAA) Driving While Intoxicated On: Bill Lewis (MADD) Office of Prosecuting Attorney On: Jeff Van Horn (State Prosecuting Atty) Registering, but not testifying: On: Betty Marshall (State Prosecuting Atty) Status of Death Penalty Reform On: Peggy Griffey (Office of Atty General) Roy E. Greenwood (TCDLA)


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--- layout: default title: Hadia Hameed ---
When Richard Feynman explained the difference between “knowing something” and “knowing the name of something”, he presented his secret formula for effective learning. The trick was simple. When you learn a new concept and want to build a ground-up understanding of it, simply teach it to a child, review it, organize and simplify and then transmit it.
So, I am excited to try the Feynman technique and write a weekly blog post on the most interesting things I have learned during the week. There is a deluge of resources on data science and I often find myself dabbling in exploring data science blog posts, videos, and podcasts and have a hard time remembering the things I have learned.
However, lately, I have realized that writing gives me closure and helps me demystify complicated concepts. In my blog posts, I generally talk about a new thing I have learned during the week, followed by a small coding exercise and in the end, I share a useful thought of the week which I have somehow discovered serendipitously while "scrounging around in my life for things to improve". These are just informal, mini episodes summarizing my readings/research/reflections. Feel free to make them richer with relevant comments and feedback. Happy reading!
{{ post.excerpt }}


Configure > Reproxy Directives
This document describes the configuration directives of the reproxy handler.
- Description:
-
A boolean flag (
ON
orOFF
) indicating if the server should recognize theX-Reproxy-URL
header sent from upstream servers.If H2O recognizes the header, it fetches the contents of the resource specified by the header, and sends the contents as the response to the client. If the status code associated with the
X-Reproxy-URL
header is 307 or 308, then the method of the original request is used to obtain the specified resource. Otherwise, the request method is changed toGET
.For example, an upstream server may send an URL pointing to a large image using the
X-Reproxy-URL
header stored on a distributed file system, and let H2O fetch and return the content to the client, instead of fetching the image by itself. Doing so would reduce the load on the application server. - Level:
- global, host, path, extension
- Default:
reproxy: OFF