Pygromos: OOP in python 3¶
__ This Jupyter Notebook is giving you a codification of a Talk I gave in the IGC Seminar __
Underlying Idea PyGromos:
Started during writing the RE-EDS pipeline
Try to making all Gromos operations possible from python
Sometimes implements the functionally, sometimes hides it
Goals:
Make code easy to read
Provide easy access to gromos functions and file modifications (especially in IDEs)
Faster adding new features to the code base
Add safety functionality/errors to functions
increase shareability, reusage of code
In this talk I want to introduce you to Pygromos and look at some aspects of OOP in python3. Pleas keep in mind that Pygromos right now is an idea not a perfect package, it’s under development.
[ ]:
import os, sys
root_dir = os.getcwd()
#if package is not installed and path not set correct - this helps you out :)
sys.path.append(root_dir+"/..")
Implementations of OOP in Python3¶
Definition of a Class¶
This is the basic definition of a class in python3
Magic functions (****)¶
Are functions having two underscores after and before their name.
These functions do stuff "under the hood" like for example if you interact with an operator.
Similar to overloadings in C++/Java.
e.g.: __init__, __str__, __append__, etc.
More: https://realpython.com/operator-function-overloading/
[3]:
class treasure_island():
## Constructor
def __init__(self, n_treasures:int):
self.n_treasures = n_treasures
## Other magic function
def __str__(self)->str:
return "nice Island with "+str(self.n_treasures)+" treasures"
#MAIN
islandA = treasure_island(n_treasures=2)
print(str(islandA))
nice Island with 2 treasures
Class Attributes¶
Accessibility¶
There is no such thing as strict accessiblitiy in python OOP. The only thing comming close to it, are the naming conventions and name mangling.
[ ]:
class treasure_island():
fun:int = 1 #Class Variable ~ static
fun_annotation:str # just an annotation (for example for IDE)
## Constructor
def __init__(self, n_treasures:int, secret_treasure:str="beneath the palm"):
self.n_treasures = n_treasures
self._secret_treasure = secret_treasure
self.__really_secret_treasure = "in the rum barrel"
#MAIN
islandA = treasure_island(2)
print(islandA.n_treasures)
print("Treasure 1 Location: ", islandA._secret_treasure)
#print("Treasure 2 Location: ",islandA.__really_secret_treasure) #throws: treasure_island' object has no attribute '__really_secret_treasure'
print("Treasure 2 Location: ",islandA._treasure_island__really_secret_treasure)
Properties¶
Class Properties are generated via Decorators “@property”. They allow to implement getters and setters in python OOP and even allow preventing setting a variable directly if a setter is missing.
[ ]:
class treasure_island():
## Constructor
def __init__(self, n_treasures:int, secret_treasure:str="beneath the palm"):
self.n_treasures = n_treasures
self._secret_treasure = secret_treasure
@property #getter
def treasure(self)->str:
self.n_treasures -= 1
return self._secret_treasure
@treasure.setter #setter
def treasure(self, treasure_location:str):
self.n_treasures += 1
self._secret_treasure = treasure_location
#MAIN
islandA = treasure_island(1)
print(islandA.treasure, islandA.n_treasures)
islandA.treasure = "under stone" #Throws an error if @treasure.setter is missing!
print(islandA.n_treasures,islandA.treasure)
Mutability of Class Attributes¶
A very pythonic way of coding is that attributes can be set on the fly(runtime) of a class. This is nice in small approaches, but be careful with this feature, it’s dangerous!
key functionality: * setattr(obj, key, value) * hasattr(obj, key) -> bool * getattr(obj, key) -> value
this is also possibile with functions!
[ ]:
class cnf():
def __init__(self, content_dict):
for key, value in content_dict.items():
setattr(self, key, value)
def __str__(self)->str:
#Here you see a list comprehension - that is a functional element.
return "\n".join([str(key)+"\t"+str(getattr(self, key)) for key in vars(self)])
#MAIN
content_dict = {"POSITION": [1,2,3], "VELOCITY":[4,5,6]}
c = cnf(content_dict)
print("Manual:\n is there a POSITION attribute?\n\t", hasattr(c, "POSITION"), c.POSITION)
print(str(c))
Methods¶
Levels¶
there are three types of methods to my knowledge in python: * instance methods * class methods * static methods
[ ]:
class counter():
class_counter: int = 1
def __init__(self):
self.counter: int = 2
def add_1(self):
self.counter += 1
@classmethod
def class_add_1(cls):
cls.class_counter += 1
@staticmethod
def static_add_1(arg):
return arg + 1
#MAIN
print(counter.static_add_1(2))
# classmethods
print("Class Var: ", counter.class_counter)
counter.class_add_1()
print("Class Var: ", counter.class_counter)
# normal method:
c = counter()
c.add_1()
print("instance ", c.counter)
Overwriting methods on Runtime¶
In python one can overwrite methods of a class with new function definitions during runtime!
[13]:
class counter():
def __init__(self):
self.counter: int = 2
def add_1(self):
self.counter += 1
def add_1_modulo(self):
self.counter = (self.counter + 1) % 2
#MAIN
c = counter()
c.add_1()
print("Normal", c.counter)
c.add_1 = c.add_1_modulo
c.add_1()
print("\"Normal\"", c.counter)
Normal 3
"Normal" 0
Inheritance¶
This is a simple inheritance example. There are no multi-inheritances possible (like in Java, not like in C++). The super constructor can be called any time in the init functions (recommendation: call IT!).
[ ]:
class islands():
island_name:str
def __init__(self, island_name):
self.island_name = island_name
class treasure_island(islands):
## Constructor
def __init__(self, n_treasures:int,
secret_treasure:str="beneath the palm"):
self.n_treasures = n_treasures
self._secret_treasure = secret_treasure
super().__init__(island_name="treasure island")
islandA = treasure_island(1)
print(islandA.island_name, islandA.n_treasures)
Type Testing & implicit Polymorphism¶
as python is not type save, polymorphism is implicitly given. To ensure that you really encouter a certain class on runtime, one can use the isinstance or issubclass functions.
[ ]:
class islands():
island_name:str
def __init__(self, island_name):
self.island_name = island_name
class treasure_island(islands):
## Constructor
def __init__(self, n_treasures:int,
secret_treasure:str="beneath the palm"):
self.n_treasures = n_treasures
self._secret_treasure = secret_treasure
super().__init__(island_name="treasure island")
islandA = treasure_island(1)
boringIsland = islands("nothing here")
#Check
print("the obj boringIsland ..."
"\n is a treasure_island:", isinstance(boringIsland, treasure_island),
"\n is an island:",isinstance(boringIsland, islands),
"\n is an int:", isinstance(boringIsland, int))
print("the class of boringIsland ..."
"\n is a subclass of treasure_island:", issubclass(type(boringIsland), treasure_island),
"\n is an island:",issubclass(type(boringIsland), islands),
"\n is an int:", issubclass(type(boringIsland), int))
print()
print("the obj islandA ..."
"\n is a treasure_island:", isinstance(islandA, treasure_island),
"\n is an island:",isinstance(islandA, islands),
"\n is an int:", isinstance(islandA, int))
print("the class of islandA ..."
"\n is a subclass of treasure_island:", issubclass(type(islandA), treasure_island),
"\n is an island:",issubclass(type(islandA), islands),
"\n is an int:", issubclass(type(islandA), int))
Using Pygromos¶
PyGromos Wrapper:¶
Example gromosPP:¶
[ ]:
from pygromos.gromos.gromosPP import GromosPP
from pygromos.data.ff import Gromos54A7
gromPP = GromosPP()
## Make Peptide
sequence = "NH3+ VAL TYR ARG LYSH GLN COO-"
solvent = "H2O"
out_top_peptide = "example_files/topo/peptide.top"
gromPP.make_top(in_building_block_lib_path=Gromos54A7.mtb,
in_parameter_lib_path=Gromos54A7.ifp,
in_sequence=sequence, in_solvent="",
out_top_path= out_top_peptide)
Example for gromosXX:¶
[ ]:
gromXX = GromosXX()
# file paths
imd_emin_vacuum = "myPath.imd"
cnf_hpeptide = "myCnf.cnf"
top_vacuum_system = "myTop.top"
out_prefix = "emin_out"
#run emin
gromXX.md_run(in_coord_path=cnf_hpeptide,
in_topo_path=top_vacuum_system,
in_imd_path=imd_emin_vacuum,
out_prefix=out_prefix)
PyGromos Files:¶
[ ]:
from pygromos.files import imd, Cnf
from pygromos.data.imd_templates import template_emin
from pygromos.data.solvents import spc
cnf_file = Cnf(spc)
residues = cnf_file.get_residues()
[ ]:
#IMD Handling
emin_imd = imd.Imd(template_emin)
emin_imd.SYSTEM.NSM = int(residues["SOLV"]/3)
emin_imd.FORCE.adapt_energy_groups(residues)
emin_imd.edit_EDS(NUMSTATES=len(residues)-1,
S = 1.0, EIR=[0.0 for x in range(lig_num)])
emin_imd.write(emin_imd_template_path)
Additional: functional programming¶
Functional programming is yet another programming paradigm. In this style you try not to think in objects, but everything in functions. A pure functional program is not containing any stored values!
Lambda functions¶
are one line functions, some kind of lazy function definition
Note the functions are written into variables, which behave like “normal” variables and can be overwritten. This can happen with any function in python.
[ ]:
# a function
add = lambda x,y: x+y
print("add: ", add(1,2))
# another function
add_modulo = lambda x,y: (x+y)%2
print("add modulo 2: ", add_modulo(1,2))
#override first function (also possible in classes! see next example)
add = add_modulo
print("the new add: ", add(1,2))
preimplemented functions¶
There are the standard functional functions pre implemented in gromos. * MAP * ZIP * FILTER
[34]:
# MAP
int_list = [1,2,3,4,5]
new_list = list(map(lambda x: x+1, int_list))
print("Map: Add to all elements of the list +1\n ", int_list, "\n ", new_list,"\n")
# ZIP
int_list = [1,2,3,4,5]
letter_list = ["a", "b", "c", "d", "e"]
combination = list(zip(letter_list, int_list))
print("Zip: combined lists: \n ", combination,"\n")
# FILTER
int_list = [1,2,3,4,5]
odd_list = list(filter(lambda x: x%2!=0, int_list))
print("Filter: a list with only odd numbers: \n ", odd_list,"\n")
Map: Add to all elements of the list +1
[1, 2, 3, 4, 5]
[2, 3, 4, 5, 6]
Zip: combined lists:
[('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5)]
Filter: a list with only odd numbers:
[1, 3, 5]
list/dict - comprehensions¶
can be used to bring a for loop into one line.
[40]:
# list comprehension
int_list = [1,2,3,4,5]
odd_list = [x for x in int_list if(x%2!=0)]
odd_replace_list = [x if(x%2!=0) else 0 for x in int_list]
print("list comprehension")
print("exclude odds: ", odd_list)
print("replace odds: ", odd_replace_list)
print()
#dict comprehension
int_list = [1,2,3,4,5]
letter_list = ["a", "b", "c", "d", "e"]
combination_dict = {key: value for key, value in zip(letter_list, int_list)}
combination_list = list(combination_dict.items()) #if it needs to be a list
print("dict comprehension")
print("combinatinos dict: ", combination_dict)
print("combinatinos list: ", combination_list)
print()
list comprehension
exclude odds: [1, 3, 5]
replace odds: [1, 0, 3, 0, 5]
dict comprehension
combinatinos dict: {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}
combinatinos list: [('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5)]
decorators - how they work¶
Decorators are actually function wrapping a function, that builds a new function! :) This is part of higher order functional programming and therefore for the pros.
[48]:
#Our nice Decorator
def secret(function:callable):
def disclosure(): #the "final" function
print("don't tell about the island\n")
function() #the decorated function
print("\nDamn!\n")
return disclosure
#Our Application
@secret
def treasure_island_location():
print("\tnice island, with two mountains and train traffic")
treasure_island_location()
don't tell about the island
nice island, with two mountains and train traffic
Damn!
I hope you liked the talk. Thanks to:
Sereina, Phil
Salome, Marc, Candide
and all the IGC Group Members!


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Since the advent of the RGraph.text
function, which saves the
coordinates of the text that is added to the canvas
, you have been able to use
those coordinates to draw an image onto the canvas
. You could even use the coordinates
of the bar itself if you wished (if you wanted to add an image above the bar for
example)
You might find that using images (eg faces) may make your charts more instantly recognisable.
The code below first creates an array of the image URLs, then creates the chart and then adds the images. The configuration is quite straightforward.
The next bit of code is where the coordinates of the text are looped through and the images are
added in place of the text. With canvas
charts, the coordinates of the text that's added to the canvas
are saved in the
obj.coordsText
variable so you can use them to add the images in place of the text.
Remember that the text labels are actually just empty strings - this is so that the coordinates of
where the text should be are stored in the obj.coordsText
variable.
Instead of just using the canvas
API
function drawImage
-
drawing API Image objects
are used to place the images. This means that if you need to you can add tooltips to the
images or add event listeners (eg click
, mousemove
, mouseover
and mouseout
.
<script src="RGraph.common.core.js"></script> <script src="RGraph.drawing.image.js"></script> <script src="RGraph.bar.js"></script>Put this where you want the chart to show up:
<canvas id="cvs" width="400" height="250" style="float: right">[No canvas support]</canvas>This is the code that generates the chart - it should be placed AFTER the
canvas
tag(s):


Summary
Web development fuses together my aptitude for math and science with my love of languages, while simultaneously satisfying my urge to create beautiful things. Below is barebones, check my LinkedIn profile for the fleshed out version.
Languages
- Programming Languages and Frameworks: Ruby (plus Rails), JavaScript (including Backbone.js, AngularJS, and D3), HTML5, CSS3 (LESS and Sass too), SQL, Bootstrap, and Java (reading only)
- Natural Languages: English, Russian, Polish, Old Church Slavonic and French (reading only)
Work Experience
- BenchPrep (February 2016 – Present)
- Junior Software Engineer
- WJL Communications (March 2011 – June 2015)
- Freelance Translator, Private Tutor, and Editor
- Loyola University Maryland (Feb 2015 – June 2015)
- Program Assistant, Office of International Student Services
- University of Virginia (Aug 2013 – Dec 2013)
- Lecturer, Russian and Polish Language Courses
- Stanford University (Sept 2007 – Dec 2012)
- Teaching Fellow and Teaching Assistant, Courses on Russian Language and Literature
- Countercultural Newspaper in Moscow, Russia (Jan 2005 – Aug 2005)
- Assistant Editor, Writer, and Copy Editor
- University of Rochester (June 2003 – Aug 2003)
- Undergraduate Researcher, Chemistry Lab
Education
- Dev Bootcamp (June 2015 – Oct 2015)
- Stanford University (Sept 2005 – Dec 2012)
- Doctor of Philosophy in Slavic Languages and Literatures
- University of Rochester (Sept 2000 – May 2004)
- Bachelor of Arts in Chemistry and Russian


Introduction
The CMSIS System View Description format(CMSIS-SVD) formalizes the description of the system contained in ARM Cortex-M processor-based microcontrollers, in particular, the memory mapped registers of peripherals. The detail contained in system view descriptions is comparable to the data in device reference manuals. The information ranges from high level functional descriptions of a peripheral all the way down to the definition and purpose of an individual bit field in a memory mapped register.
CMSIS-SVD files are developed and maintained by silicon vendors. Silicon vendors distribute their descriptions as part of CMSIS Device Family Packs. Tool vendors use CMSIS-SVD files for providing device-specific debug views of peripherals in their debugger. Last but not least, CMSIS-compliant device header files are generated from CMSIS-SVD files.
CMSIS-SVD Benefits
- For Software Developers:
- Consistency between device header file and what is being displayed by the debugger.
- Detailed information about peripherals, registers, fields, and bit values as well as named interrupts from within the debugger, without the need to reference device documentation.
- Convenient access to new and updated descriptions as part of the silicon vendor's CMSIS Device Family Packs as the packs are made availabl by silicon vendors.
- Improved software development efficiency.
- For Silicon Vendors:
- A tool vendor independent file format enables early device support by a wide range of toolchains with limited effort.
- The XML-based format helps ease the integration into in-house design flows.
- Automated generation of CMSIS compliant device header files.
- Full control throughout the life cycle of the CMSIS-SVD files from creation to maintenance.
- For Tool Vendors:
- Unified file format across silicon vendors helps the efficiency of supporting a wide range of devices in a timely manner.
- Silicon vendors can provide early review access to the device support via restricted access to CMSIS Device Family Packs.
- Updated descriptions are available over the web simplifying the maintenance of device support.
Language Specification and Conventions
CMSIS-SVD in ARM::CMSIS Pack
The following files relevant to CMSIS-SVD are present in the ARM::CMSIS Pack directories:
| File/Folder | Content |
| CMSIS\Documentation\SVD | This documentation |
| CMSIS\Utilities | Exemplary SVD file (ARM_Example.svd) and generated header file (ARM_Example.h). |


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The next Stavanger monthly meeting will be at 11:00 on Wednesday the 2nd of October, 2019, at the Solastranden Gård.


--- layout: post title: Looking ahead date: '2015-03-31T07:31:15+02:00' categories: - Storyboards picture_url: https://film-Storyboards.tumblr.com/post/115115662376/what-is-the-future-of-storyboarding ---
What is the future of storyboarding?


A simple and easy way to visualise Travelport's Hotel Trip Services. Draw and customise your own API Sequence Diagrams. It's fun and it's free.
JSON Files:
{{jsonObj.shop.name}} {{jsonObj.details.name}} {{jsonObj.avail.name}}
SVG File:
Generating SVG
{{svgObj.name}}
Time Taken:
{{timeSecs}} secs
{{i}}
{{codeErrorMsg}}
Made with ❤ in Hong Kong


{% extends 'bases/auth_base.html' %} {% block title %}Home{% endblock %} {% block body %}
Interactive Tic Tac Toe game where the user can choose to either play against other human players or choose to play against the UNBEATABLE computer player! Learn more about Tic Tac Toe game in the "About" page.
Interactive Sudoku game where the user can play various levels of difficulty of Sudoku puzzles with various game stats that keeps track of how the players are doing. Learn more about Sudoku game in the "About" page.
Interactive Blackjack game where the user can choose to either play against other human players or choose to play against a simple computer player who is also the host of the game!. Learn more about Blackjack game in the "About" page.
Interactive 2048 game that allows the user to experience the exciting puzzle of 2048. Learn more about 2048 game in the "About" page.


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Methods
attrs (RedisRecord::Base)
destroy (RedisRecord::Base)
dirty? (RedisRecord::Base)
find (RedisRecord::Base)
inherited (RedisRecord::Base)
new (RedisRecord::Base)
new_record? (RedisRecord::Base)
populate_from_yaml (RedisRecord::Base)
save (RedisRecord::Base)
search (RedisRecord::Base)
sort_by (RedisRecord::Base)
sphinx_export (RedisRecord::Base)


To be accepted into the gang, teens often have to commit some sort of crime or go through hazing.Hazing is usually considered forcing a new member of a group, such as a fraternity, sorority, or a gang, to perform an embarrassing or illegal act to be accepted into the group


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/simp.20list.2Emap.20id.html ---
Interesting that simp
doesn't solve list.map (λ t, t) l = l
.
I suppose I could add this to the simp
:
theorem map_id' {f : α → α} (h : ∀ x, f x = x) (l : list α) : map f l = l
Yep, simp [list.map_id']
does the job.
Last updated: Apr 24 2020 at 19:02 UTC


Abyssal Saintess Elcadia:
You think the book where Embryo is mentioned is in the Rune Library? Hmm... I see. Well, that was easier than I thought it would be, but don't worry. This is just the beginning.


Budgeted and proposed numbers are for fiscal years, which begin on October 1 of the preceding calendar year and end on September 30.
{{ item.cpi_description | smartQuotes }} — {{item.description_source_text}}
{{ item.cpi_obama_reason | smartQuotes }} — {{item.obama_reason_source_text}}
{{ item.cpi_trump_reason | smartQuotes }} — budget blueprint


Every transaction is secured with robust cryptography, distributed though the global peer-to-peer consensus network.
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Before Change
self.lock = threading.Lock()
// Load config
for dev_id, device_dict in config.items():
dev_id = str(dev_id)
device_dict = device_dict or {}
away_hide = device_dict.get(CONF_AWAY_HIDE, False)
device = Device(
hass, self.consider_home, device_dict.get("track", False),
dev_id, device_dict.get("mac"), device_dict.get("name"),
device_dict.get("picture"), away_hide)
if device.mac:
self.mac_to_dev[device.mac] = device
self.devices[dev_id] = device
// pylint: disable=too-many-arguments
def see(self, mac=None, dev_id=None, host_name=None, location_name=None,
gps=None):
Notify device tracker that you see a device.
with self.lock:
After Change
Track devices
def __init__(self, hass, consider_home, track_new, devices):
self.hass = hass
self.devices = {dev.dev_id: dev for dev in devices}
self.mac_to_dev = {dev.mac: dev for dev in devices if dev.mac}
self.consider_home = timedelta(seconds=consider_home)
self.track_new = track_new
self.lock = threading.Lock()


# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Schemas for anything related to project routes, database models, and workers
"""
from marshmallow import Schema, fields, validate
from sparsify.schemas.projects_data import ProjectDataSchema
from sparsify.schemas.projects_model import ProjectModelSchema
__all__ = [
"ProjectSchema",
"ProjectExtSchema",
"ResponseProjectSchema",
"ResponseProjectExtSchema",
"ResponseProjectsSchema",
"ResponseProjectDeletedSchema",
"SearchProjectsSchema",
"CreateUpdateProjectSchema",
"DeleteProjectSchema",
]
[docs]class ProjectSchema(Schema):
"""
Schema for a project object as stored in the DB and returned in the server routes
"""
project_id = fields.Str(required=True)
name = fields.Str(required=True)
description = fields.Str(required=True)
created = fields.DateTime(required=True)
modified = fields.DateTime(required=True)
training_optimizer = fields.Str(required=True, allow_none=True)
training_epochs = fields.Int(required=True, allow_none=True)
training_lr_init = fields.Float(required=True, allow_none=True)
training_lr_final = fields.Float(required=True, allow_none=True)
dir_path = fields.Str(required=True)
dir_size = fields.Int(required=True)
[docs]class ProjectExtSchema(ProjectSchema):
"""
Schema for a project object including model and data
as stored in the DB and returned in the server routes
"""
model = fields.Nested(
ProjectModelSchema,
required=False,
default=None,
missing=None,
allow_none=True,
)
data = fields.Nested(
ProjectDataSchema,
many=True,
required=False,
default=None,
missing=None,
allow_none=True,
)
[docs]class ResponseProjectSchema(Schema):
"""
Schema for returning a response with a single project
"""
project = fields.Nested(ProjectSchema, required=True)
[docs]class ResponseProjectExtSchema(Schema):
"""
Schema for returning a response with a single project and its
associated model and data
"""
project = fields.Nested(ProjectExtSchema, required=True)
[docs]class ResponseProjectsSchema(Schema):
"""
Schema for returning a response with multiple project
"""
projects = fields.Nested(ProjectSchema, many=True, required=True)
[docs]class ResponseProjectDeletedSchema(Schema):
"""
Schema for returning a response after deleting a project
"""
success = fields.Bool(required=False, default=True, missing=True)
project_id = fields.Str(required=True)
[docs]class SearchProjectsSchema(Schema):
"""
Expected schema to use for querying projects
"""
order_by = fields.Str(
default="modified",
missing="modified",
validate=validate.OneOf(["name", "created", "modified"]),
required=False,
)
order_desc = fields.Bool(default=True, missing=True, required=False)
page = fields.Int(
default=1,
missing=1,
validate=validate.Range(min=1, min_inclusive=True),
required=False,
)
page_length = fields.Int(
default=20,
missing=20,
validate=validate.Range(min=1, min_inclusive=True),
required=False,
)
[docs]class CreateUpdateProjectSchema(Schema):
"""
Expected schema to use for creating or updating a project
"""
name = fields.Str(required=False)
description = fields.Str(required=False)
training_optimizer = fields.Str(required=False, allow_none=True)
training_epochs = fields.Int(required=False, allow_none=True)
training_lr_init = fields.Float(required=False, allow_none=True)
training_lr_final = fields.Float(required=False, allow_none=True)
[docs]class DeleteProjectSchema(Schema):
"""
Expected schema to use for deleting a project
"""
force = fields.Bool(required=False, default=False, missing=False)


Hi! My name is Darrell and I have been a trainer/ instructional designer in the museum industry for the last eight years. I have a background in education and digital design, but have always been interested in computer programming since I was a teenager.
I'm excited to be a part of DBC Chicago and begin my career as a developer.
I'm originally from Pittsburgh, PA but have lived in Chicago for the last eleven years. I have been married to my beautiful wife, Shannon for ten years and have an American Bulldog named Oliver.


Frank Sinatra was born in an upstairs tenement at 415 Monroe Street in Hoboken, New Jersey, the only child of Italian immigrants Natalina "Dolly" Garaventa and Antonino Martino "Marty" Sinatra. Sinatra weighed 13.5 pounds (6.1 kg) at birth and had to be delivered with the aid of forceps, which caused severe scarring to his left cheek, neck, and ear, and perforated his eardrum—damage that remained for life. Due to his injuries at birth, his baptism at St. Francis Church in Hoboken was delayed until April 2, 1916. A childhood operation on his mastoid bone left major scarring on his neck, and during adolescence he suffered from cystic acne that further scarred his face and neck. (wiki)
By May 1941, Sinatra topped the male singer polls in Billboard and DownBeat magazines.His appeal to bobby soxers, as teenage girls of that time were called, revealed a whole new audience for popular music, which had been recorded mainly for adults up to that time. The phenomenon became officially known as "Sinatramania" after his "legendary opening" at the Paramount Theatre in New York on December 30, 1942. According to Nancy Sinatra, Jack Benny later said, "I thought the goddamned building was going to cave in. I never heard such a commotion ... All this for a fellow I never heard of. (wiki)
Despite Being Born in Hoboken, one of Sinatra's debatably most influential song is about New York. The song is the theme song from the Martin Scorsese film New York, New York (1977), composed by John Kander, with lyrics by Fred Ebb. It was written for and performed in the film by Liza Minnelli. In 1980, Sinatra recorded it for his album, "Trilogy: Past Present Future", and his recording has become one of the most iconic symbols of Sinatra, and New York City. This song is still played, to this day, at Yankee Stadium!wiki
Start spreading the news, I'm leaving today
I want to be a part of it: New York, New York
These vagabond shoes, are longing to stray
Right through the very heart of it: New York, New York
I wanna wake up in a city that doesn't sleep
And find I'm king of the hill, top of the heap
These little town blues, are melting away
I'll make a brand new start of it in old New York
If I can make it there, I'll make it anywhere
It's up to you, New York, New York
New York, New York
I want to wake up in a city that never sleeps
And find I'm a number one, top of the list
King of the hill, a number one
These little town blues, oh, are melting away
I'm gonna make a brand new start of it in old New York
And if I can make it there, I'm gonna make it anywhere
It's up to you, New York, New York
The song you're listening to right now. It was written for Tony Bennet in 1959. Sinatra recorded it on June 9th, 1964, and released in August of the same year. This song was played as a wake-up call for the crew of the Apollo 10 mission (the one before we landed on the moon).
Out of the tree of life I just picked me a plum
You came along and everything's startin' to hum
Still, it's a real good bet, the best is yet to come
Best is yet to come and babe, won't that be fine?

Best is yet to come, come the day you're mine
Come the day you're mine
I'm gonna teach you to fly
We've only tasted the wine
We're gonna drain the cup dry
Wait till your charms are right for these arms to surround
You think you've flown before, but baby, you ain't left the ground
A-Wait till you're locked in my embrace
Wait till I draw you near
A-Wait till you see that sunshine place
Ain't nothin' like it here
The best is yet to come and babe, won't it be fine?
The best is yet to come, come the day you're mine
Come the day you're mine
And you're gonna be mine
That's Life" is a popular song written by Dean Kay and Kelly Gordon and first recorded in 1963 by Marion Montgomery. The most famous version is by Frank Sinatra, released on his 1966 album of the same name. Sinatra recorded the song after hearing an earlier cover of it by O.C. Smith; the song proved successful and reached the fourth spot on the Billboard Hot 100 singles chart. Following the success of Sinatra's version, it was subsequently recorded by a number of artists including Aretha Franklin, James Booker, Shirley Bassey, James Brown, Van Morrison, David Lee Roth, Michael Bolton, Michael Bublé, Russell Watson, Deana Martin and Holt McCallany.
Sinatra's version appeared in the 1993 film A Bronx Tale, the theme song of the 2019 film Joker, the 2004 video game Tony Hawk's Underground 2, and in the sixth season finale of Brooklyn Nine-Nine while a cover by Bono was on the soundtrack of The Good Thief. wiki
That's life (that's life), that's what all the people say
You're ridin' high in April, shot down in May
But I know I'm gonna change that tune
When I'm back on top, back on top in June
I said that's life (that's life), and as funny as it may seem
Some people get their kicks stompin' on a dream
But I don't let it, let it get me down
'cause this fine old world, it keeps spinnin' around
I've been a puppet, a pauper, a pirate, a poet, a pawn and a king
I've been up and down and over and out and I know one thing
Each time I find myself flat on my face
I pick myself up and get back in the race
That's life (that's life), I tell you I can't deny it
I thought of quitting, baby, but my heart just ain't gonna buy it
And if I didn't think it was worth one single try
I'd jump right on a big bird and then I'd fly
I've been a puppet, a pauper, a pirate, a poet, a pawn and a king
I've been up and down and over and out and I know one thing
Each time I find myself layin' flat on my face
I just pick myself up and get back in the race
That's life (that's life), that's life and I can't deny it
Many times I thought of cuttin' out but my heart won't buy it
But if there's nothin' shakin' come this here July
I'm gonna roll myself up in a big ball a-and die
My, my!


{% block head %}
In tink head (displaces text of inherited head)
{% endblock %}
{% block content %}
In tink content (displaces content tag but not parent main it's nested in)
{% endblock %}
{% block container %}
in tink block container (also displaces child nested blocks)


Join Fresh4Less this holiday season for the semi-annual Solstice Jam! Make something interactive in 24 hours and share it for a chance to win SWEET PRIZES.
Updates:
The votes are in!
The winner is Caius Worthen!
The runner up is RORYYY TARIIIIICS!
Thanks for participating in the jam everyone!
| Name | Votes |
|---|---|
| Caius Worthen | 8 |
| RORYYY TARIIIIICS | 3 |
| Brandon Walker | 2 |
| Samuel Davidson | 2 |
| Yaroslav Berejnoi | 2 |
| Elliot Hatch | 1 |
The jam has been extended. Entries will be accepted until .
What is the Fresh4Less Winter Solstice Jam?
The Winter Solstice Jam is a competition to create an interactive project from scratch in 24 hours, based on a given theme. You get to choose when you begin your 24 hour entry, so you can fit it into your schedule.
Everyone who participates must judge every other entry and vote for their favorite. The winner and runner-up will both win a prize. Collaboration is not allowed.
The jam ends and voting begins on January 18 at 12:00am MST. Voting ends February 1 12:00am MST.
What can I enter?
Anything interactive. It's up to you what interactive means. Your entry doesn't necessarily need to require a computer to be experienced, but it does need to be submitted on this webpage so anyone in the world can experience it for themself. Your entry should be related to the theme in some way.
The majority of your entry should be designed and created during the 24 hours you participate in the jam. It's okay to use frameworks, templates, and some art and audio assets not created during the jam.
How does it work?
Whenever you're ready, click the button above to join the jam. Enter your name and you'll be given a secret code. Once you enter, the 24 hour timer starts ticking down. You can submit files by finding your name in the submission list below and entering your secret code. You may submit as many times as you would like before the countdown reaches zero. Once it hits zero, you will not be able to upload any more files. Your most recent upload will be downloadable by other participants after your entry time has expired.
How do I vote?
When the jam ends, the two week voting period will begin. If you made a submission, you can visit this page and vote on entries, using your secret code. You can give your favorite entry two votes, and your second favorite entry one vote.
When the voting period ends, the winner and runner-up will be announced and awarded their prizes. As a participant in the jam, you are required to try every entry and cast a vote. If you do not vote, you will not receive any prizes.
What can I win?
The first place prize is a Fresh4Less Winter Jam 2016 Winner Congratulatory Mug.
The runner-up will receive three, count 'em, three Fresh4Less Winter Jam 2016 Magnets, to decorate their refrigerator. Additionally, every participant will receive one Fresh4Less Winter Jam 2016 Magnet.
What if I have more questions?
You can contact Elliot at<EMAIL_ADDRESS>Participants
| Name | Time remaining |
|---|


Vanilla
vanilla.html
Local
local.html
Local (w/o painting)
local-no-paint.html
Server (w/ WebWorker)
server-worker.html
Server (w/o WebWorker)
server-no-worker.html
Server (w/o WebWorker and painting)
server-no-worker-no-paint.html
Direct Vanilla
direct-vanilla.html
Direct Local
direct-local.html
Direct Local (w/o)
direct-local-no-paint.html
Direct Server (w/ WebWorker)
direct-server-worker.html
Direct Server (w/o WebWorker)
direct-server-no-worker.html
Direct Server (w/o WebWorker and painting)
direct-server-no-worker-no-paint.html


Functions for inference in generalised linear spatial models. The posterior and predictive inference is based on Markov chain Monte Carlo methods. Package geoRglm is an extension to the package geoR, which must be installed first.
| Version: | 0.9-11 |
| Depends: | R (≥ 3.0.0), geoR (≥ 1.7-5), stats |
| Imports: | sp |
| Suggests: | coda |
| Published: | 2017-10-18 |
| Author: | Ole F. Christensen [aut, cre], Paulo J. Ribeiro Jr [aut] |
| Maintainer: | Ole F. Christensen <OleF.Christensen at mbg.au.dk> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | http://gbi.agrsci.dk/~ofch/geoRglm |
| NeedsCompilation: | yes |
| Citation: | geoRglm citation info |
| In views: | Bayesian, Spatial |
| CRAN checks: | geoRglm results |
| Reference manual: | geoRglm.pdf |
| Vignettes: |
An introduction to the package geoRglm |
| Package source: | geoRglm_0.9-11.tar.gz |
| Windows binaries: | r-devel: geoRglm_0.9-11.zip, r-release: geoRglm_0.9-11.zip, r-oldrel: geoRglm_0.9-11.zip |
| OS X binaries: | r-release: geoRglm_0.9-11.tgz, r-oldrel: geoRglm_0.9-11.tgz |
| Old sources: | geoRglm archive |
| Reverse suggests: | geoR |
| Reverse enhances: | glmmBUGS |
Please use the canonical form https://CRAN.R-project.org/package=geoRglm to link to this page.


employment
2015-current Assistant Professor, Department of Environmental Science, Policy and Management, University of California, Berkeley.
2013-2015 NSF Post-doctoral Scholar in the Department of Applied Mathematics and Statistics, University of California, Santa Cruz. Mentors: Marc Mangel, Stephan Munch
education
2012 Ph.D Population Biology, University of California, Davis. Mentor: Alan Hastings
2007 A.B in Physics, Princeton University, with honors and certificates in biophysics and applied and computational mathematics.
publications
Karthik Ram, Carl Boettiger, Scott Chamberlain, Noam Ross, Maelle Salmon, & Stephanie Butland. (2018). A Community of Practice Around Peer-review for Long-term Research Software Sustainability. Computing in Science & Engineering, 9615(c), 1–1. doi:10.1109/MCSE.2018.2882753
Carl Boettiger, (2018). Managing Larger Data on a GitHub Repository. Journal of Open Source Software, 3(29), 971, doi:10.21105/joss.00971. (software).
Milad Memarzadeh, Carl Boettiger (2018). Adaptive management of ecological systems under partial observability. Biological Conservation. 224, 9-15. doi:10.1016/j.biocon.2018.05.009. (software)
Carl Boettiger (2018). From noise to knowledge: how randomness generates novel phenomena and reveals information. Ecology Letters. doi:10.1111/ele.13085 (oa, code, data)
Carl Boettiger, Dirk Eddelbuettel (2018). An Introduction to Rocker: Docker Containers for R. The R Journal. https://journal.r-project.org/archive/2017/RJ-2017-065/index.html.
Carl Boettiger (2017). Generating Codemeta Metadata for R Packages.
The Journal of Open Source Software 2 (19), 454, doi:10.21105/joss.00454Getz, Marshall, Carlson, Giuggioli, Ryan, Romañach, Boettiger, Chamberlain, Larsen, D'Odorico, O'Sullivan, D. (2017). Making ecological models adequate. Ecology Letters. doi:10.1111/ele.12893
Ben Marwick, Carl Boettiger, Lincoln Mullen (2017). Packaging data analytical work reproducibly using R (and friends). The American Statistician. doi:10.1080/00031305.2017.1375986. (oa)
Hampton, Jones, Wasser, Schuldhauer, Supp, Brun, Herandez, Boettiger, Collins, Gross, Fernandez, Budden, White, Teal, Labou & Aukema. (2017) Skills and Knowledge for Data Intensive Research. BioScience. doi:10.1093/biosci/bix025. (oa)
T Alex Perkins, Carl Boettiger, Benjamin L. Philips. (2016) After the games are over: life-history trade-offs drive dispersal attenuation following range expansion. Ecology and Evolution 6 (18) 6425-6434. doi:10.1002/ece3.2314. (oa, code)
Carl Boettiger, Michael Bode, James N. Sanchirico, Jacob LaRiviere, Alan Hastings, and Paul Robert Armsworth. (2016) Optimal management of a stochastically varying population when policy adjustment is costly. Ecological Applications 26 (3) 808-817. doi:10.1890/15-0236. (oa, code)
Carl Boettiger, Scott Chamberlain, Rutger Vos and Hilmar Lapp. (2016) RNeXML: a package for reading and writing richly annotated phylogenetic, character, and trait data in R. Methods in Ecology and Evolution. doi:10.1111/2041-210X.12469. (oa, code, software)
Carl Boettiger, Scott Chamberlain, Edmund Hart, Karthik Ram. (2015) Building Software, Building Community: Lessons from the rOpenSci Project. Journal of Open Research Software 3: e8, doi:10.5334/jors.bu.
Carl Boettiger. (2015) An introduction to Docker for reproducible research. ACM SIGOPS Operating Systems Review, Special Issue on Repeatability and Sharing of Experimental Artifacts. 49(1), 71-79. doi:10.1145/2723872.2723882. (oa)
Carl Boettiger, Marc Mangel, Stephan Munch. (2015) Avoiding tipping points in fisheries management through Gaussian process dynamic programming. Proceedings of the Royal Society B 282(1801), 8–11. doi:10.1098/rspb.2014.1631. (oa, code, data)
Carl Boettiger, Alan Hastings. (2013) No early warning signals for stochastic transitions: insights from large deviation theory. Proceedings of the Royal Society B. doi:10.1098/rspb.2013.1372. (oa, code)
Carl Boettiger*, Noam Ross*, Alan Hastings. (2013) Early warning signals: The charted and uncharted territories. Theoretical Ecology doi:10.1007/s12080-013-0192-6. (oa, code)
Carl Boettiger, Alan Hastings (2013). Tipping points: From patterns to predictions, Nature 493, 157–158. doi:10.1038/493157a.
Carl Boettiger, Alan Hastings (2012). Early Warning Signals and the Prosecutor’s Fallacy, Proceedings of the Royal Society B 279 (1748) 4734-4739. doi:10.1098/rspb.2012.2085. (oa, code, data)
Carl Boettiger, Duncan Temple Lang, Peter Wainwright (2012). rfishbase: exploring, manipulating and visualizing FishBase data from R, Journal of Fish Biology. 81 (6) 2030–2039. doi:10.1111/j.1095-8649.2012.03464.x. (oa, code, software)
Carl Boettiger, Duncan Temple Lang (2012). Treebase: An R package for discovery, access and manipulation of online phylogenies, Methods in Ecology and Evolution 3 (6) 1060–1066. doi:10.1111/j.2041-210X.2012.00247x. (oa, code, software)
Carl Boettiger and Alan Hastings (2012). Quantifying Limits to Detection of Early Warning for Critical Transitions, Journal of the Royal Society: Interface 9 (75) 2527-2539. doi:10.1098/rsif.2012.0125. (oa, code)
Jeremy M. Beaulieu, Dwueng-Chwuan Jhwueng, Carl Boettiger and Brian O’Meara, (2012). Modeling Stabilizing Selection: Expanding the Ornstein-Uhlenbeck Model of Adaptive Evolution, Evolution 66 (8) 2369-2383. doi:10.1111/j.1558-5646.2012.01619.x (software)
Carl Boettiger, Graham Coop, Peter Ralph (2012) Is your phylogeny informative? Measuring the power of comparative methods, Evolution 66 (7) 2240-51. doi:10.1111/j.1558-5646.2011.01574.x, (oa, code, data)
Carl Boettiger, Jonathan Dushoff, Joshua S Weitz (2010) Fluctuation domains in adaptive evolution, Theoretical Population Biology 77 (1) 6-13. doi:10.1016/j.tpb.2009.10.003. (oa, code, data)
James J. Wray, Neta A. Bahcall, Paul Bode, Carl Boettiger, Phillip Hopkins. (2006) The Shape, Multiplicity, and Evolution of Superclusters in Lambda-CDM Cosmology, The Astrophysical Journal 652 (2) 907-916. doi:10.1086/50860. (oa)
grants
The Influence of Conflicting Policies and Supply-Chain Pressures on Farmers' Decisions and Tradeoffs with Respect to Biodiversity, Profitability, and Sustainability. Timothy Bowles (PI), Alastair Iles, Claire Kremen, Carl Boettiger. (2018-2022). National Science Foundation #CNH-1824871 $1,301,737
Detecting Change in Global Biodiversity through Large Scale Network Analysis. (2018-2020) Berkeley Institute for Data Science, $67,000
Hellman Fellows Award (2018-2020) The Hellman Foundation. $37,600
Berkeley Collegium Award for Excellence in Undergraduate Education. (2018-2019) $16,867.50
Managing ecosystems under extreme uncertainty. (2016-03 - 2019-09) NSF XSEDE TG-DEB160003. NSF Estimated value of computing resources: $34,558
Reproducible and Collaborative Data Science. NSF XSEDE TG-DEB160021. NSF Estimated value of computing resources: $20,028
The rOpenSci Project (2015-2018, Co-PI). Helmsley Charitable Trust, award 2016PG-BRI004. $2,900,000
The Codemeta project (2015). National Science Foundation #ACI-1549758 165,782 USD. (proposal)
The rOpenSci Project, Phase II funding (2014, Co-PI). Alfred P. Sloan Foundation $300,000
NSF Biology Post-doc (2013-2015). National Science Foundation #DBI-1306697, $138,000 (proposal)
The rOpenSci Project Phase I funding (2013, Co-PI). Alfred P. Sloan Foundation $180,000
IIASA YSSP fellowship (2009). National Academy of Sciences, OISE-0738129, $8,000. (proposal)
Computational Science Graduate Fellowship (2008). United States Department of Energy, #DE-FG02-97ER25308, $149,000. (proposal)
book chapters
- Carl Boettiger (2017). A Reproducible R Notebook Using Docker. In J. Kitzes, D. Turek, & F. Deniz (Eds.), The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences (1st ed., pp. 109–117). Oakland, CA: UC Press. https://www.ucpress.edu/book.php?isbn=9780520294752
invited talks & workshops
2018
- NSF SI2 PIs Meeting, Washington, DC
- rOpenSci unconference, Seattle, WA
- Faculty Learning Program Fellows Workshop Berkeley, CA
- GraphXD, Berkeley, CA
- Digital Data in Biodiversity UC Berkeley. (co-organizer)
2017
- CROSS Symposium Speaker UC Santa Cruz.
- Imagining Tomorrow's University Chicago, IL.
- rOpenSci unconference, Los Angeles, CA
- Prov-a-thon: Practical Tools for Reproducible Science, Tamaya, NM.
- NSF Translational Data Science Workshop, Berkeley Institute for Data Science, Berkeley, CA.
2016
- Force16 Codemeta Workshop, Portland OR (organizer)
- CodeMeta NSF Workshop Portland, OR (organizer)
- rOpenSci unconference, San Francisco, CA
2015
- Invited Speaker, Empirical Dynamical Modeling and Forecasting in Nonlinear Systems, NTU, Taiwan.
- Moore-Sloan Data Science Environments: Second Annual Data Science Summit
- Data Intensive Training Workshop, NCEAS, Santa Barbara, CA
- NSF Big Data Hubs Design Charette, Western Region.
- rOpenSci unconference, San Francisco CA.
- Pretty Darn Good Control Working group, NIMBIOS, Knoxville TN
2014
- Invited speaker, Berkeley Initiative for Global Change Biology Workshop (student organized), UC Berkeley, CA.
- Invited speaker, DIMACS Global Change, Berkeley CA.
- Invited speaker, Zoology Seminar, University of Wisconsin, Madison, WI.
- Invited speaker, ESPM Seminar, UC Berkeley, CA.
- rOpenSci unconference, San Francisco CA.
- Reproducible Science: Curriculum & Workflow Workshop, NESCent, Durham, NC.
- WSSSPE 2.0 Meeting. New Orleans, LA.
- Workflows Working Group, NCEAS, Santa Barbara, CA.
2013 & prior
- invited speaker, MBI, Sustainable Management of Living Natural Resources, Columbus, OH.
- invited seminar speaker, WHOI, Woods Hole, MA.
- invited seminar speaker, UC Davis Dept of Environmental Resources and Economics; Davis, CA.
- invited speaker, SSB Symposium, Evolution Conference, Ottawa, CAN.
- Sustainable Management of Living Natural Resources Workshop, MBI Columbus, OH.
- Academic software & workforce development Workshop, ISEES. Oakland, CA.
- Software Lifecycle Workshop, ISEES, Santa Barbara, CA.
- Pretty Darn Good Control Working group, NIMBIOS, Knoxville, TN
- Stochastic spatial modeling in population dynamics Workshop, AIM, Palo Alto, CA.
awards
- 2011 Volterra Award (Best student talk, ESA Theory Section)
- 2007 Elected to Membership in the Society of Sigma Xi
- 2007 Allen G. Shenstone Prize in Physics, Princeton University
- 2007 The Class of 1870 Old English Prize, Princeton University
- 2006 Kusaka Memorial Prize in Physics, Princeton University
- 2006 Plasma Physics Fellow, PPPL
service
campus
- 2018 - current. Governance Committee for Data Science Programs
- 2017 - 2018. ESPM Remote Sensing Faculty Search, committee member & equity liaison
- 2017 - 2018. ad hoc Data Science Degree Proposal Committee
- 2015 - current. Berkeley Research Computing Advisory Committee
extra-campus
- NCEAS Scientific Advisory Board
- rOpenSci Leadership Team
- Jetstream Cloud Computing Stakeholder Advisory Board, XSEDE.
selected software projects
- 2012 - current: The rOpenSci Project, co-founder. https://ropensci.org
- 2014 - current: Carl Boettiger, Dirk Eddelbuettel. The Rocker Project: Docker images for the R environment. https://rocker-project.org
- 2015 - current: Carl Boettiger, Matt Jones, et al. The CodeMeta Project: Software Metadata Exchange https://codemeta.github.io
My software impact is also measured relative to other academics by depsy.org
theses
- Carl Boettiger, David Huse (2006) Clonal Interference Models in Population Genetics. Princeton Physics Dept. doi:10.6084/m9.figshare.678305.
- Carl Boettiger, Joshua Weitz, Simon Levin (2007) Adaptive Dynamics: Branching Phenomena and the Canonical Equation Princeton Physics Dept. doi:10.6084/m9.figshare.678306.
- Carl Boettiger, Stephen Pacala, David Huse (2007) Ensemble Behavior from Individual Dynamics in Multispecies Forest Populations. Princeton Physics Dept. doi:10.6084/m9.figshare.678304.
- Carl Boettiger (2012). Regime shifts in ecology and evolution (PhD Dissertation). doi:10.6084/m9.figshare.97218.
media interviews
- Seltenrich, N. (2016). "Scaling the Heights of Data Science." Breakthroughs Magazine. https://nature.berkeley.edu/breakthroughs/opensci-data
- Tachibana, C. (2014). "The paperless lab" Science 345(6195) pp. 468-470. 10.1126/science.opms.p1400087
- Mascarelli, A. (2014) "Research tools: Jump off the page." Nature 507, 523–525. doi:10.1038/nj7493-523a
- Check Hayden E (2013). "Mozilla Plan Seeks to Debug Scientific Code." Nature, 501, pp. 472-472. doi:10.1038/501472a
- Van Noorden R (2013). "Data-Sharing: Everything on Display." Nature, 500, pp. 243-245. doi:10.1038/nj7461-243a
- Gewin, Virginia (2013). "Turning Point: Carl Boettiger" Nature, 493 p 711 doi:10.1038/nj7434-711a
- Wald, Chelsea (2010). "Scientists Embrace Openness" Science. doi:10.1126/science.caredit.a1000036


portal - Domain Entity Access via the Domain Portal
This manual page describes the micca portal functions. These functions allow operations on entities with a domain from outside of the domain code itself. The primary use case for the portal functions is for bridging between domains. Portal functions are also useful for testing or for building a test framework around a micca generated domain.
When micca generates the code for a domain, it also generates an initialized, externally scoped variable containing data that can be used in conjunction with the portal functions given here to query and operate on the domain. The portal data is placed in a variable whose name is given as, <domain name>__PORTAL, where <domain name> is the name given to the generated domain.
In addition to the portal data, micca generates a set of pre-processor macros that are included in the generated header file. These macros define a set of integer encodings for the various domain elements. For example, each class in the domain has a non-negative integer value symbolically defined by a pre-processor macro. This symbol may be used as a class identifier in the portal functions to specify on which class an operation is applied. Micca supplies symbolic encodings as follows for the domain entities. In parentheses, the naming convention for the generated macro names is given.
classes (<domain name>_<class name>_CLASSID)
pre-defined instances (<domain name>_<class name>_<instance name>_INSTID)
attributes (<domain name>_<class name>_<attribute name>_ATTRID)
events (<domain name>_<class name>_<event name>_EVENT
states (<domain name>_<class name>_<state name>_STATE
the number of classes in the domain (<domain name>_CLASSCOUNT)
the number of instances of each class (<domain name>_<class name>_INSTCOUNT)
the number of attributes of each class (<domain name>_<class name>_ATTRCOUNT)
the number of events (classes with a state model) (<domain name>_<class name>_EVENTCOUNT)
the number of states (classes with a state model) (<domain name>_<class name>_STATECOUNT)
Additionally, for each event that carries supplimental event parameters, micca also places in the generated header file a structure definition for the parameters. The structure definition follows the naming convention: struct <domain name>_<class name>_<event name>__EPARAMS. Initialized values of these structures may be passed to portal functions to supply supplemental event data to signaled events.
Every portal function returns an integer value that indicates the success or failure of the operations. A non-negative return value indicates success. A negative return value indicates failure. The following pre-processor defined macros define the set of negative return values and their meaning.
There is no class in the domain with the given class identifier.
There is no instance of the class with the given instance identifier.
There is no attribute of the class with the given attribute idenifier.
The instance identifier refers to an unused instance memory slot.
The given class has no state model.
There is no event for the class with the given event number.
There is no state for the class with the given state number.
Dynamic instance creation is not allowed for the given class.
The operation is not allowed for dependent attributes.
The supplied value cannot be stored in the allocated storage space.
A function is supplied that returns a canonical string representation of an error code.
An error value as returned from a portal function.
The mrt_PortalErrorString function translates a portal error code to a human readable string. By special dispensation, a value of zero for portalErrorCode is accepted and a string reference is returned for it. The value of NULL is returned for unknown error code values or if the run time was compiled with the pre-processor macro, MRT_NO_NAMES, defined.
This section describes the set of function available through the portal to perform operations on a domain. These functions are intended primarily for use in creating bridge operations when multiple domains are used in an application. They are also useful for testing purposes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies an assigner in the domain.
A non-negative integer value that identifies an instance of an assigner.
The mrt_PortalAssignerCurrentState obtains the current state number for the instId instance of the assignerId assigner in the domain described by portal. If successful, the return value of the function is the a small non-negative number that is the encoded value of the current state. This value will match one of the pre-processor macro values defined in the generated header file of the domain. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies the event to cancel.
The mrt_PortalCancelDelayedEvent function cancels the eventNumber event to the instId instance of class, classId, in the domain described by portal. N.B. it is not an error to cancel an event that was never signaled or to cancel an event that was signaled but has already been dispatched. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A small non-negative interger that gives the initial state into which the new created instance is placed.
The mrt_PortalCreateInstance function creates an instance of classId in the domain described by portal. The instance is placed in the initialState state. If the class given by classId does not have a state model, then initialState must be given by MRT_StateCode_IG. If the class given by classId does have a state model and if initialState is given as MRT_StateCode_IG, then the new created instance is placed in the default initial state. The initialState may not be given as the pseudo-initial state for those classes that have creation events. In all cases, no state activity is executed by the new created instance. If successful, the return value of the function is the a small non-negative number that is the instance identifier for the newly created instance. Upon failure, the return value is one of the portal error codes.
N.B. the instance created by this function is not properly initialized since no attribute values have been set. It is encumbent upon the caller of this function to use the mrt_PortalUpdateAttr function to set a value for all the attributes of the newly created instance. Also note that it is not possible to create an association between class instances via the portal functions. For this reason, instance creation where the class instances participate in unconditional relationships must usually be done by constructing a domain operation in the domain containing the class. Also for this reason, instance creation via portal functions is often best accomplished asynchronously using creation events so that a state action is run to place the newly created instance into a consistent state and create any relationship linkages.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
The number of bytes pointed to by eventParameters.
A non-negative integer value that identifies the event to signal.
A pointer to an object that contains the parameters for the event.
The number of bytes pointed to by eventParameters.
The mrt_PortalCreateInstanceAsync function creates an instance of classId in the domain described by portal by signaling the creation event given by eventNumber. If the event requires any supplemental event parameters, they are given in the memory pointed to by eventParameters which is paramSize number of bytes. The new created instance is placed in its pseudo-initial state and eventNumber is signaled to it. When the event is dispatched, the state action associated with transition is executed. If successful, the return value of the function is the a small non-negative number that is the instance identifier for the newly created instance. Upon failure, the return value is one of the portal error codes.
N.B. the instance created by this function is not properly initialized since no attribute values have been set. It is encumbent upon the caller of this function to use the mrt_PortalUpdateAttr function to set a value for all the attributes of the newly created instance.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
The mrt_PortalDeleteInstance deletes the instId instance of the classId class in the domain described by portal.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies an attribute of a class.
A pointer to a memory pointer where the reference to the attribute is placed.
A pointer to an object where the number of bytes occupied by the attribute is placed.
The mrt_PortalGetAttrRef function obtains a pointer reference to an attribute value. The preferred way to access attributes is to use the mrt_PortalReadAttr or mrt_PortalUpdateAttr functions. However, for attributes values that are arrays, it is most convenient to deal with them by references rather than by value. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
char const *cycletype ; MRT_AttrSize typelen ; int pcode = mrt_PortalGetAttrRef(&wmctrl__PORTAL, WMCTRL_WASHINGCYCLE_CLASSID, WMCTRL_WASHINGCYCLE_NORMAL_INSTID, WMCTRL_WASHINGCYCLE_WASHINGCYCLE_ATTRID, (void **)&cycletype, &typelen) ; assert(pcode == 0) ; if (strcmp(cycletype, "Normal") == 0) { printf("found the normal washing cycle\n") ; }
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
The mrt_PortalInstanceCurrentState obtains the current state number for the instId instance of the classId class in the domain described by portal. If successful, the return value of the function is the a small non-negative number that is the encoded value of the current state. This value will match one of the pre-processor macro values defined in the generated header file of the domain. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies an attribute of a class.
A pointer to memory where the attribute value is placed.
The number of bytes pointed to by dst.
The mrt_PortalReadAtt function reads the value of an attribute of a class instance. The value is read from the domain described by portal, the class given by classId, the instance given by instId and the attribute given by attrId. The attribute value is copied to the memory pointed to by dst. The number of bytes pointed to by dst is given by dstSize and no more than dstSize bytes are copied to dst. If successful, the return value of the function is the number of bytes actually copied to dst. Upon failure, the return value is one of the portal error codes.
unsigned washduration ; int pcode = mrt_PortalReadAttr(&wmctrl__PORTAL, WMCTRL_WASHINGCYCLE_CLASSID, WMCTRL_WASHINGCYCLE_NORMAL_INSTID, WMCTRL_WASHINGCYCLE_WASHDURATION_ATTRID, &washduration, sizeof(washduration)) ; if (pcode == sizeof(washduration)) { printf("normal washing duration is %u\n", washduration) ; }
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies the event to signal.
A pointer to an object of type MRT_DelayTime where the remaining delay is placed.
The mrt_PortalRemainingDelayTime function returns by reference via delayRef the minimum number of milliseconds before the eventNumber is dispatched to the classId instance in the domain described by portal. If there is no event given by eventNumber for the classId instance or if the event has already been dispatched, then the returned remaining time is set to zero. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies the event to signal.
A pointer to an object that contains the parameters for the event.
The number of bytes pointed to by eventParameters.
The minimum number of milliseconds that is to elapse before the event is dispatched.
The mrt_PortalSignalDelayedEvent function signals the eventNumber event to the instId instance of class, classId, in the domain described by portal delayed in time by at least delay milliseconds. It the event carries supplimental parameters, they are supplied by reference via eventParameters which points to paramSize number of bytes. If the event requires no parameters, then eventParameters and paramSize are given as NULL and 0, respectively. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies the event to signal.
A pointer to memory from with the new attribute is retrieved.
The number of bytes pointed to by eventParameters.
The mrt_PortalSignalEvent function signals the eventNumber event to the instId instance of class, classId, in the domain described by portal. It the event carries supplimental parameters, they are supplied by reference via eventParameters which points to paramSize number of bytes. If the event requires no parameters, then eventParameters and paramSize are given as NULL and 0, respectively. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
struct wmctrl_ClothesTub_Fill__EPARAMS = { .temp = WT_Hot } ; int pcode = mrt_PortalSignalEvent(&wmctrl__PORTAL, WMCTRL_CLOTHESTUB_CLASSID, WMCTRL_CLOTHESTUB_CT1_INSTID, WMCTRL_CLOTHESTUB_FILL_EVENT, &wmctrl_ClothesTub_Fill__EPARAMS, sizeof(wmctrl_ClothesTub_Fill__EPARAMS)) ; assert(pcode == 0) ;
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an instance of a class.
A non-negative integer value that identifies an attribute of a class.
A pointer to memory from with the new attribute is retrieved.
The number of bytes pointed to by src.
The mrt_PortalUpdateAttr modifies the value of the attrId attribute of the instId instance in the classId class of the domain described by portal. The new attribute value is obtain by reference from src which points to srcSize bytes of memory. If successful, the return value of the function is the number of bytes actually copied from src. Upon failure, the return value is one of the portal error codes.
unsigned washduration = 100 ; int pcode = mrt_PortalUpdateAttr(&wmctrl__PORTAL, WMCTRL_WASHINGCYCLE_CLASSID, WMCTRL_WASHINGCYCLE_NORMAL_INSTID, WMCTRL_WASHINGCYCLE_WASHDURATION_ATTRID, &washduration, sizeof(washduration)) ; if (pcode == sizeof(washduration)) { printf("normal washing duration is now %u\n", washduration) ; }
The functions in this section return information about the domain and the elements in the domain. These functions allow programs to inquire about the domain meta-data during run time.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
The mrt_PortalClassAttributeCount function returns the number of attributes contained in the classId class in the domain described by portal. If successful, the return value of the function is a non-negative count of the number of attributes of classId. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an attribute of a class.
A pointer to a character pointer by which the attribute name is returned.
The mrt_PortalClassAttributeName function obtains the name of the attrId attribute of the classId class in the domain described by portal. The name is returned via nameRef as a pointer to a NUL terminated string. If the domain was compiled with the preprocessor symbol MRT_NO_NAMES defined, then the value placed in the location pointed to by nameRef is NULL. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
int attrCount = mrt_PortalClassAttributeCount(&wmctrl__PORTAL, WMCTRL_WASHINGCYCLE_CLASSID) ; assert(attrCount >= 0) ; for (int attrId = 0 ; attrId < attrCount ; attrId++) { char const *attrName ; int pcode = mrt_PortalClassAttributeName(&wmctrl__PORTAL, WMCTRL_WASHINGCYCLE_CLASSID, attrId, &attrName) ; if (pcode == 0) { if (attrName != NULL) { printf("attribute %d is named %s\n", attrId, attrName) ; } else { printf("no name available for attribute %d\n", attrId) ; } } else { fprintf(stderr, "failed to get attribute name, %s\n", mrt_PortalErrorString(pcode)) ; break ; } }
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an attribute of a class.
The mrt_PortalClassAttributeSize function returns the number of bytes occupied by a value of the attrId of the classId class in the domain described by portal. If successful, the return value of the function is a positive number of bytes occupied by the attribute value. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
The mrt_PortalClassEventCount function returns the number of events associated with the state model of the classId class in the domain described by portal. If successful, the return value of the function is a positive number giving the number of events in the state model. Events are numbered from 0 to the return value of the function minus one. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies an event in the class.
A pointer to a character pointer by which the event name is returned.
The mrt_PortalClassEventName function obtains the name of the eventNumber event of the classId class in the domain described by portal. The name is returned via nameRef as a pointer to a NUL terminated string. If the domain was compiled with the preprocessor symbol MRT_NO_NAMES defined, then the value placed in the location pointed to by nameRef is NULL. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
int eventCount = mrt_PortalClassEventCount(&wmctrl__PORTAL, WMCTRL_WASHINGMACHINE_CLASSID) ; assert(eventCount > 0) ; for (int eventId = 0 ; eventId < eventCount ; eventId++) { char const *eventName ; int pcode = mrt_PortalClassEventName(&wmctrl__PORTAL, WMCTRL_WASHINGMACHINE_CLASSID, eventId, &eventName) ; if (pcode == 0) { if (eventName != NULL) { printf("event %d is named %s\n", eventId, eventName) ; } else { printf("no name available for event %d\n", eventId) ; } } else { fprintf(stderr, "failed to get event name, %s\n", mrt_PortalErrorString(pcode)) ; break ; } }
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
The mrt_PortalClassInstanceCount function returns the maximum number of instances that may exist for the classId class in the domain described by portal. If successful, the return value of the function is a positive number giving the count of the instance storage slots of classId. Instances are identified via sequential integers from zero to the return value of the function minus one. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A pointer to a character pointer by which the class name is returned.
The mrt_PortalClassName function obtains the name of the classId class in the domain described by portal. The class name is returned via nameRef as a pointer to a NUL terminated string. If the domain was compiled with the preprocessor symbol MRT_NO_NAMES defined, then the value placed in the location pointed to by nameRef is NULL. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
The mrt_PortalClassStateCount function returns the number of states associated with the state model of the classId class in the domain described by portal. If successful, the return value of the function is a positive number giving the number of events in the state model. Events are numbered from 0 to the return value of the function minus one. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
A non-negative integer value that identifies a class in the domain.
A non-negative integer value that identifies a state in the class.
A pointer to a character pointer by which the state name is returned.
The mrt_PortalClassStateName function obtains the name of the stateCode state of the classId class in the domain described by portal. The name is returned via nameRef as a pointer to a NUL terminated string. If the domain was compiled with the preprocessor symbol MRT_NO_NAMES defined, then the value placed in the location pointed to by nameRef is NULL. If successful, the return value of the function is zero. Upon failure, the return value is one of the portal error codes.
A pointer to the portal data that describes a domain.
The mrt_PortalDomainClassCount function returns the number of classes defined in the domain described by portal. Classes are identified by numbers from 0 to the return value of the function minus one.
A pointer to the portal data that describes a domain.
The mrt_PortalDomainName function returns a pointer to a NUL terminated string giving the name of the domain described by portal. If the domain was compiled with the preprocessor symbol MRT_NO_NAMES defined, then the return value is NULL.
Copyright © 2015 - 2020 by G. Andrew Mangogna


Consistency in communication is key in helping citizens and governments build trust amongst each other. The following offers info about the mood and style of Code for America's communications material.
Verbiage Style
- Humanistic: We care about improving the human experience. Where possible we opt to speak in human terms rather than technical ones.
- Impactful: We use powerful and easy-to-understand words.
- Confident: We're positive but not boastful.
- Clean and crisp: We aim for simple but effective communication.
- Conversational: We're talking with people, not at them. We avoid jargon and buzzwords.
- Humorous: In the words of Stephen Colbert, "We're not just brainiacs on the nerd patrol". We try to make work civic hacking fun through humor.
- Respectful and professional: We respect the diverse experiences, skill-sets and POVs of the community and welcome respectful debate.
Consistency
Code for America generally uses America Press Style (APStyle). One exception is that we believe adamantly in the serial or Oxford comma. Beyond that, below are a few CfA-specific things to keep in mind:
- The “f” in Code for America is always lowercase. The abbreviation Code for America should read “CfA.” The single exception is when CODE FOR AMERICA is in a heading or title and the entire name is capitalized to keep style with the rest of the document.
- “Datasets” is one word.
- “Open source” is two words, “opensourcing” is one word.
- URLs do not include “www.”
- Only capitalize the word “brigade” when it refers to the Code for America Brigade program or the name of your brigade. When referring to a local brigade or collection of brigades, use lower case. Example: There is a brigade where I live. It’s called the Code for San Francisco Brigade.


[gecode-users] B&B or DFS engine ?
Christian Schulte
cschulte at kth.se
Thu Mar 31 15:17:14 CEST 2016
Hi,
Would use a BAB engine and add the external check by synchronized execution
(when some variables have been assigned), please check Section 4.5 for the
details.
Cheers
Christian
--
Christian Schulte, www.gecode.org/~schulte
Professor of Computer Science, KTH, cschulte at kth.se
Expert Researcher, SICS, cschulte at sics.se
-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Philippe
Sent: Thursday, March 31, 2016 06:15
To: users at gecode.org
Subject: [gecode-users] B&B or DFS engine ?
Hello,
I have a design problem when using a b&b engine. Here it is :
When a solution S is found I have to confirm it using an external
algorithm. It's only if S is confirmed that the next solution S '
must have a better cost than S.
For now, i use a DFS engine and i reject or accept S' myself.
Is there a better solution (using constraint(S) for instance ?).
Thanks,
Philippe
_______________________________________________
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‘Gamified learning’: Game-based pilot for young farmers launched
by Sylvester PhelanA gaming pilot programme to raise cooperative awareness among young farmers through “gamified learning” resources has been launched recently.
ICOS Skillnet, with the support of Teagasc and Kildalton Agricultural College, is engaged in the interactive pilot for young farmers.
According to the Irish Cooperative Organisation Society (ICOS), the “games” improve the students’ leadership, communication, organisational and risk assessment skills, and create discussion on how the cooperative model works for Irish farmers.
Training programme
ICOS Skillnet developed a young farmer training programme to support the young farmer at farmgate level in his/her farm business, and also introduce them to the cooperative, its values and culture, outlining the benefits of being involved in a cooperative, including generational renewal.
The modules that have been developed are under two different headings, namely ‘Basic Farm Management’, and ‘Cooperative Values and Cultures’.
Basic Farm Management:
- Decision Making;
- Markets;
- Risk Management; and
- Finance.
Co-operative Values and Cultures:
- Daily Management;
- Legal Frameworks;
- Leadership;
- Organisational Skills;
- Agricultural Policy;
- Marketing;
- Origins of Co-ops; and
- Sustainability.
Game-based learning
Under the pilot an online training platform has been developed with training materials for young farmers.
The unique point about this programme is the blended approach taken in training delivery and in particular the use of game-based learning to meet the needs of young farmers, as they don’t want to sit in a classroom all day.
There are currently six games which effectively support the training materials and bring home the practical element of learning, through ‘gamification’.
The games that have been developed include:
- Decision Making;
- Risk Management;
- Finance;
- Organisational Skills;
- Leadership and Communications; and
- Principles of co-operation.
ICOS vice-president and chairman of the ICOS Rural Business Committee, James O’Donnell, expressed his gratitude to Tony Pettit and Frank Murphy of Teagasc and Tim Ashmore and James Ryan of Kildalton College for agreeing to the pilot.
O’Donnell emphasised the importance of the co-operative model in the agriculture sector as well as the need for greater involvement by young farmers in the co-operative movement.
The vice-president added that he is optimistic that the ongoing cooperation between ICOS and Teagasc will help to ensure an upsurge in young farmer involvement with their local dairy co-operative, their co-operative livestock mart or their local Farm Relief Service.


|
GliderThrow_Meter
|
This project proposes a simple digital Angle/Throw meter and ... Differentials, using two esp32 and two MPU 6050 6 DOFFS components.
GliderThrow meter is composed by two device, each using one esp32 and one MPU 6050.
Each device can measure the deflections in degrees / millimeters with a resolution of 0.1 degrees and can measure the differential when working together with a second unit since GliderThrow is a system that comprises two sensors, one for each wing or surface of your airplane.
Using a dual system very much simplifies the throw setting of your model by having a direct view of both control surfaces at the same time.
GliderThrow is primary design for setting the control surface of a model glider but you will find that it can be used on most every airplane and for a variety of applications as Measuring a dihedral angle of a wing, Measuring Model Airplane Incidence angle , etc.
As the first device embedded a small http server, the data can be viewed through any web browser on a smartphone, Android or iOS, PC or MAC.
UI is built using bootstrap and jquery, and all the files needed are embedded in the .rodata segment of the first device.
The project is composed of two parts, the server (Esp_mad_Server directory) and the client (Esp_mad_Client directory).
Two extras libraries are used in the project : i2clibdev and MPU6050 from jrowberg (https://github.com/jrowberg/i2cdevlib).
These libraries are in the extra_components directrory of the project. Take care to update the Makefile given in Esp_mad_Client & Server regarding your own configuration.
Enjoy !


Visualboy Advance 1.7.1 tracer
Table of contents
1. Readme
1a. Memory logging file
2. Source
Thanks to romhacking.net (RHDN) for hosting.
Additional mention to Nightcrawler for the HTML suggestion.
Extra recognition towards RedComet for being a catalyst.
Contact:
Register a RHDN account.
PM user 'g8z et al'.


 We already had some cannabis and salvia, but decided now would be a good time to try 2C-B, the queen of the psychedelic amphetamines which we had heard so much about. Our dealer said that he had some extremely potent pills, so we purchased one pill between us and had half each.  I put EP7 by Autechre on the stereo. After we had finished the spliff the 2CB started to take hold. We felt something happening to ourselves, but it didn't feel like anything we were used to. I thought it would feel a bit like E when coming up, but it didn't and I started to worry that the pill might have been spiked with something other than 2CB. First I thought it was acid, the most likely contender as far as pill spiking goes. Then I thought, it must be ketamine or PCP because I couldn't feel my arms and legs getting longer like with acid.
After voicing my worries to my friend (who will be known only as Mr.X) I began to get even more worried. Mr.X started saying how warm and snuggly he felt, and I thought that the pill might have been spiked with smack. But then, it all became clear. If it was smack then I wouldn't have cared what was in it, and it certainly wasn't any other drug I had tried, so it must be 2CB. When I had the thought 'This is 2CB, this is really good' it was like I was standing on a beach and a huge wave of orgasmic pleasure hit me like a wall. I was lying on my bed panting, moaning and rubbing my hands over my whole body uncontrollably. I couldn't believe how intense it was. It made cocain look like speed.
Then after a few minutes of bliss we calmed down. I felt extremely focused. I knew exactly what reality was, there was no confusion over what was real and what wasn't. I went to the bathroom to get some water and saw some sober flatmates on the way. I spoke to them coherently and felt completely in control of what I was saying. No ecstasy rants. When I came back to the room we decided to let the effects settle in for half an hour. Then we smoked another spliff and got the salvia out.
I knew that doing bongs of salvia was going to be cool because I had done salvia and E before, and that was mind blowing. This was going to be REALLY good. After the second bong of salvia I got up and sat in my blow-up chair. I felt like I was on a magic carpet flying into infinity. But it wasn't like doing lots of salvia, because I could see my room as it really was, as well as seeing a horizon which I was flying towards. After the first two minutes of the salvia rush I focused my attention on a large psychedelic poster on my wall. The poster is trippy enough as it is, but the salvia and 2CB added a whole new dimention to it, literally. It looked like it was moving around in 3 dimentions. It kept dividing up into layers which moved foward and backward. As well as this, the pattern on the picture looked like lots of strange animals and humans joined together, and flowing through one another.
After the salvia wore off we explored the effects of the 2CB. I found 'concentration' is very important to the experience. For a start it makes you feel very concentrated on whatever you are doing. But if you actually try to concentrate on something as hard as you can, that is when the interesting things happen. Just by concentrating on a thought about how good someting is, the 2CB fills every part of your being with wave after wave of pleasure far more intense than a sober orgasm. But you can control it at will.  If you concentrate on something external to yourself then you can take pleasure in this too. You can stare at something and see it getting more and more beautiful, as the 2CB changes its colour and projects geometric shapes onto it. Music sounds like it was supposed to. Social interaction on 2CB is also very enjoyable, but you don't feel like you love everyone as with E.
On the whole, I found 2C-B a very versatile and rewarding drug. The best thing about it is that you have so much control over the effects. You can't switch it off completely, but you can easily remember what reality is. The salvia did add a very interesting aspect to the trip. But personally I think that salvia is best taken on it's own, preferable chewed, at least 3 days after taking any other drug, especially cannabis. I may well go without cannabis for a week and then try chewing 10 fresh leaves whilst on 2CB. It's a shame that GOd didn't make salvia and cannabis more compatible.
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.


---
title: Register
description: "Book your ticket, there won't be one for everyone"
i18n-key: 2019-register
permalink: /en/2019/register/
---
{% if site.tickets.selling and site.tickets.weezevent %}
All tickets available for this edition have been sold. It is possible that new places will become available in the event of withdrawal. Join the waiting list to be notified as soon as a place becomes available.Purchase a ticket
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On 23 April 2020, 10 new articles were published in 9 journals.
Governmentality and Environmental Rights: Regulatory Failure and the Volkswagen Emissions Fraud Case
Housing Ex-Offenders in the Netherlands: Balancing Neighbourhood Safety and Human Rights
Police Science As An Emerging Scientific Discipline
A Review on Privacy Preservation of Social Networks Using Graphs
How Satisfied Are Siblings of Homicide Victims With Police?
The Importation of Violent “Codes” of South Korean Inmates
Colonialism, Neo-Colonialism, and Anti-Terrorism Law in the Arab World
Racial Profiling in the Racial Welfare State: Examining the Order of Policing in the Nordic Region


Before Change
elif bands_feature is not None:
self.bands = data_source.bands()
else:
self.bands = []
if additional_data is None:
self.additional_data = []
else:
self.additional_data = list(self._parse_features(additional_data, new_names=True)())
self.all_bands = self.bands + [f_name for _, f_name, _ in self.additional_data]
self.request_types = {
api_type: [band for band in self.all_bands if band in self.API_BANDS[api_type]]
for api_type in self.API_BANDS
After Change
if additional_data is not None:
additional_features = list(self._parse_features(additional_data, new_names=True)())
requested_bands.extend(band for ftype, band, new_name in additional_features)
self.write_features = {band: (ftype, new_name) for ftype, band, new_name in additional_features}
itr = ((atype, [band for band in requested_bands if band in self.API_BANDS[atype]]) for atype in self.API_BANDS)
self.request_types = {api_type: bands for api_type, bands in itr if bands}


Code templates
The Code Templates preference panel lets you configure the format of newly generated code stubs, comments and files.
The code templates page contains templates that are used by actions that generate code and/or source files. E.g. the New Class wizard uses source and header file templates to create new files and code templates to insert generated method stubs. Templates contain variables that are substituted when the template is applied. Some variables are available in all templates, some are specific to templates.
| Options | Description |
|---|---|
| New... |
Opens the Code Template dialog to create a new file template. |
| Edit... |
Opens the Code Template dialog to edit the currently selected code template. |
| Remove |
Removes a user added file template. Predefined templates cannot be removed. |
| Import... |
Imports templates from the file system. |
| Export... |
Exports all selected templates to the file system. |
| Export All... |
Exports all templates to the file system. |
Comment Templates
| Template Name | Specifies |
|---|---|
| Files |
Header comment for new source or header files. Note that this template can be referenced in source and header file templates with ${filecomment}. |
| Types |
The comment for new types. Note that this template can be referenced in source and header file templates with ${typecomment}. |
| Fields |
The comment for new fields. |
| Constructors |
The comment for new constructors. |
| Destructors |
The comment for new destructors. |
| Methods |
The comment for new methods. |
Code Templates
| Template Name | Description |
|---|---|
| Method body |
The 'Method body' templates are used when new method is created. |
| Constructor body |
The 'Constructor body' templates are used when a constructor is created. |
| Destructor body |
The 'Destructor body' templates are used when the destructor is created. |
File Templates
File templates can not only be defined and modified for C/C++ files, but also for other content types, like Assembly files or plain text files. The New File from Template wizard can be used to create new files based on one of the templates defined in this page.| Template Name | Description |
|---|---|
| Default C++ source template |
Used by the New Class wizard and the New Source File wizard when a new C++ source file is created. The template can specify where comments are added. Note that the template can contain the variable ${typecomment} and ${filecomment} that will be substituted by the evaluation of the Types respectively Files comment template. |
| Default C++ header template |
Used by the New Class wizard and the New Header File wizard when a new C++ header file is created. The template can specify where comments are added. Note that the template can contain the variable ${typecomment} and ${filecomment} that will be substituted by the evaluation of the Types respectively Files comment template. |
| Default C source template |
Used by the New Source File wizard when a new C source file is created. The template can specify where comments are added. Note that the template can contain the variable ${typecomment} and ${filecomment} that will be substituted by the evaluation of the Types respectively Files comment template. |
| Default C header template |
Used by the New Header File wizard when a new C source file is created. The template can specify where comments are added. Note that the template can contain the variable ${typecomment} and ${filecomment} that will be substituted by the evaluation of the Types respectively Files comment template. |
| Other file templates |
File templates can be defined for other content types, e.g. Assembly or plain text. |
Edit Template dialog
The following fields and buttons appear in the dialog:
| Options |
Description |
|---|---|
| Name |
The name of the template. Only available for file templates. |
| Type |
The file type (content type) of the template. Only available for file templates. |
| Description |
A description of the template |
| Pattern |
The template pattern. |
| Insert Variables... |
Displays a list of pre-defined template specific variables. |


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| annotation_custom {ggplot2} | R Documentation |
This is a special geom intended for use as static annotations that are the same in every panel. These annotations will not affect scales (i.e. the x and y axes will not grow to cover the range of the grob, and the grob will not be modified by any ggplot settings or mappings).
annotation_custom(grob, xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf)
grob |
grob to display |
xmin, xmax |
x location (in data coordinates) giving horizontal location of raster |
ymin, ymax |
y location (in data coordinates) giving vertical location of raster |
Most useful for adding tables, inset plots, and other grid-based decorations.
annotation_custom
expects the grob to fill the entire viewport
defined by xmin, xmax, ymin, ymax. Grobs with a different (absolute) size
will be center-justified in that region.
Inf values can be used to fill the full plot panel (see examples).
# Dummy plot df <- data.frame(x = 1:10, y = 1:10) base <- ggplot(df, aes(x, y)) + geom_blank() + theme_bw() # Full panel annotation base + annotation_custom( grob = grid::roundrectGrob(), xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf ) # Inset plot df2 <- data.frame(x = 1 , y = 1) g <- ggplotGrob(ggplot(df2, aes(x, y)) + geom_point() + theme(plot.background = element_rect(colour = "black"))) base + annotation_custom(grob = g, xmin = 1, xmax = 10, ymin = 8, ymax = 10)


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