In css there are 4 types of positioning. There's static, or the default positioning, relative positioning, fixed positioning, and absolute positioning. They're all extremely useful in their own ways in making quality websites in css.
Static positioning is the easiest to understand of the 4. It's the default positioning, meaning that static objects are simply placed under each other in a website. Object 1 will be on top of object 2, and so on.
Relative positioning is just like static positioning, if no modifiers are applied. However, elements with relative positioning can be moved from their original location. They can be moved up, down left, or right depending on what is specified after declaring that the elemnt has relative positioning.
Fixed positioning is actually very easy to understand. An element that has fixed positioning will remain in whatever position it is in the website browser, no matter how you scroll.
Absolute positioning is the hardest to understand, because it's like a version of relative positioning in relative positioning. An element with absolute positioning will positioned as if the last object referred to was it's own window in a browser.


Random posts about ... stuff
by Q
SELECT
retrieves rows from zero or more tables.
WITH
All queries will be computed and serve as temporary tables that can be referenced in the FROM
list. A WITH
query can be referenced more than once while computed only once.
FROM
If more than one element is specified, they are cross-joined together.
WHERE
All rows do not satisfy the condition are eliminated from the output.
GROUP BY
/aggregate function calls/Having
The output will be combined into groups of rows then aggregated. If the Having
clause is present, it eliminates groups that do not satisfy the given condition.
 It is the default behaviorUNION
/INTERSECT
/EXCEPT
UNION
returns all rows that are in one or both of the result setsINTERSECT
returns all rows that are strictly in both result setsEXCEPT
returns the rows that are in the fist result but not in the secondIn all three cases, duplicate rows are eliminated unless ALL
is specified
ORDER BY
The returned rows are sorted in the specified order
LIMIT
The SELECT
statement only returns a subset of the result rows
FOR UPDATE
/FOR NO KEY UPDATE
/FOR SHARE
/FOR KEY SHARE
The SELECT
statement locks the selected rows against concurrent updatesTo join the table flights
with the table logs
:
To retrieve from the table flights
with some constraints:
To obtain the union of the tables flights
with logs
:
References:
Updated: 12 June 2020


Marmotta User Accounts
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--- title: dash_oop_components keywords: fastai sidebar: home_sidebar summary: "`dash_oop_components` is a small helper library with object-oriented dashboard building blocks for the plotly dash library" description: "`dash_oop_components` is a small helper library with object-oriented dashboard building blocks for the plotly dash library" nb_path: "index.ipynb" ---
pip install dash_oop_components
Documentation can be found at: https://oegedijk.github.io/dash_oop_components/
An example covid tracking dashboard has been deployed to dash-oop-demo.herokuapp.com (code at github.com/oegedijk/dash_oop_demo), showcasing:
Plotly's dash is an awesome library that allows you to build rich interactive data driven web apps with pure python code. However the default style of dash apps is quite declarative, which for large projects can lead to code that becomes unwieldy, hard to maintain, and hard to collaborate on:
This library provides a number object-oriented wrappers for organizing your dash code that allow you to write clean, modular, composable, re-usable and fully configurable dash code.
It includes:
DashFigureFactory
: a wrapper for your data/plotting functionality, keeping data/plotting logic
seperate from your dashboard interaction logic.DashComponent
: a self-contained, modular, configurable unit that combines a dash layout with dash callbacks.DashFigureFactory
for plots or other data outputDashComponents
are composable, meaning that you can nest them into new composite components.DashConnectors
to connect callbacks between componentsDashApp
: Build a dashboard out of a DashComponent
and run it.DashComponentTabs
you can also track state for current tab only All wrappers:
Cool extras:
.yaml
file,
including import details, and be fully reloaded from this config file.dashapp
CLI!A full example dashboard can be found at github.com/oegedijk/dash_oop_demo and has been deployed to https://dash-oop-demo.herokuapp.com/
Below is the code for similar but slightly simpler example. Full explanation for the dash_oop_demo
dashboard can be found in the example documentation.
The example is a rewrite of this Charming Data dash instruction video (go check out his other vids, they're awesome!).
First we define a basic DashFigureFactory
that loads a covid dataset, and provides a single plotting functionality, namely plot_time_series(countries, metric)
. Make sure to call super().__init__()
in order to store params to attributes (that's how the datafile parameters gets automatically assigned to self.datafile for example), and store them to a ._stored_params
dict so that they can later be exported to a config file.
class CovidPlots(DashFigureFactory):
def __init__(self, datafile="covid.csv"):
super().__init__()
self.df = pd.read_csv(self.datafile)
self.countries = self.df.countriesAndTerritories.unique().tolist()
self.metrics = ['cases', 'deaths']
def plot_time_series(self, countries, metric):
return px.line(
data_frame=self.df[self.df.countriesAndTerritories.isin(countries)],
x='dateRep',
y=metric,
color='countriesAndTerritories',
labels={'countriesAndTerritories':'Countries', 'dateRep':'date'},
)
figure_factory = CovidPlots("covid.csv")
print(figure_factory.to_yaml())
Then we define a DashComponent
that takes a plot_factory and build a layout with two dropdowns and a graph.
super().__init__()
all parameters are automatically stored to attributes (so that we can access
e.g. self.hide_country_dropdown
), and to a ._stored_params
dict (which can then be exported to .yaml
)make_hideable()
staticmethod, to conditionally
wrap certain layout elements in a hidden div.'value'
attribute by wrapping it in
self.querystring(params)(dcc.Dropdown)(..)
, and passing the urls's querystring params
down to the layout function upon pageload.component_id
's are unique by adding +self.name
. However if you use
self.id(component_id)
, then self.name
gets automatically tagged on, and you can use
self.Input()
, self.Output()
and self.State()
instead of the regular dash
Input()
,
Output()
and State()
functions.name
, gets a random uuid string automatically gets assigned.component_callbacks(self, app)
methodplot_factory
for the plotting logic.class CovidTimeSeries(DashComponent):
def __init__(self, plot_factory,
hide_country_dropdown=False, countries=None,
hide_metric_dropdown=False, metric='cases', name=None):
super().__init__()
if not self.countries:
self.countries = self.plot_factory.countries
def layout(self, params=None):
return dbc.Container([
dbc.Row([
dbc.Col([
html.H3("Covid Time Series"),
self.make_hideable(
self.querystring(params)(dcc.Dropdown)(
id=self.id('timeseries-metric-dropdown'),
options=[{'label': metric, 'value': metric} for metric in ['cases', 'deaths']],
value=self.metric,
), hide=self.hide_metric_dropdown),
self.make_hideable(
self.querystring(params)(dcc.Dropdown)(
id=self.id('timeseries-country-dropdown'),
options=[{'label': country, 'value': country} for country in self.plot_factory.countries],
value=self.countries,
multi=True,
), hide=self.hide_country_dropdown),
dcc.Graph(id=self.id('timeseries-figure'))
]),
])
])
def component_callbacks(self, app):
@app.callback(
self.Output('timeseries-figure', 'figure'),
self.Input('timeseries-country-dropdown', 'value'),
self.Input('timeseries-metric-dropdown', 'value')
)
def update_timeseries_plot(countries, metric):
if countries and metric is not None:
return self.plot_factory.plot_time_series(countries, metric)
raise PreventUpdate
A composite DashComponent
that combines two CovidTimeSeries
into a single layout.
Both subcomponents are passed the same plot_factory
but assigned different initial values.
self.plot_left.layout(params)
and self.plot_right.layout(params)
self.component_callbacks(app)
.register_callbacks(app)
first registers all callbacks of subcomponents,
and then calls component_callbacks(app)
.subcomponent.name
fields in the ids.name="left"
and name="right"
.class DuoPlots(DashComponent):
def __init__(self, plot_factory):
super().__init__()
self.plot_left = CovidTimeSeries(plot_factory,
countries=['China', 'Vietnam', 'Taiwan'],
metric='cases', name='left')
self.plot_right = CovidTimeSeries(plot_factory,
countries=['Italy', 'Germany', 'Sweden'],
metric='deaths', name='right')
def layout(self, params=None):
return dbc.Container([
html.H1("Covid Dashboard"),
dbc.Row([
dbc.Col([
self.plot_left.layout(params)
]),
dbc.Col([
self.plot_right.layout(params)
])
])
], fluid=True)
dashboard = DuoPlots(figure_factory)
print(dashboard.to_yaml())
DashApp
: Pass the dashboard
to the DashApp
to create a dash flask application.
mode='inline'
, 'external'
or 'jupyterlab'
when you are working in a notebook in order to keep
the notebook interactive while the app is runningquerystrings=True
you automatically keep track of the state of the dashboard int the url querystringbootstrap=True
the default bootstrap css gets automatically included. You can also choose particular themes, e.g. bootstrap=dbc.themes.FLATLY
**kwargs
app = DashApp(dashboard, querystrings=True, bootstrap=True)
print(app.to_yaml())
if run_app:
app.run(9051)
app.to_yaml("covid_dashboard.yaml")
app2 = DashApp.from_yaml("covid_dashboard.yaml")
We can check that the configuration of this new app2
is indeed the same as app
:
print(app2.to_yaml())
And if we run it it still works!
if run_app:
app2.run()


--- title: Israel shot 129 date: 2004-05-09T00:00:00.000Z filepathOriginal: photos/IMG0135.jpg filepathThumbnail: photos/IMG0135.thumbnail.jpg filepathPreview: photos/IMG0135.preview.jpg ---
At Rosh Hanikra: Semii, Lani, Ari, Nim, Tanz, Jase, Jordi, and Nat


//Unpack inputs
if "effective_aspect_ratio" in wing:
ar = wing.effective_aspect_ratio
elif "extended" in wing:
if "aspect_ratio" in wing.extended:
//Unpack inputs
if wing.has_key("effective_aspect_ratio"):
ar = wing.effective_aspect_ratio
elif wing.has_key("extended"):
if wing.extended.has_key("aspect_ratio"):


I am a 35-year-old woman who discovered that MDMA eliminated my gag reflex during oral sex.
I've had a couple of previous experiences with MDMA and quite a few more with oral sex, but had never combined the two. I am not on any other medications or supplements and did not take any other drug along with the MDMA. On the evening in question, about two hours into an Ecstasy trip, I was performing oral sex on my companion when I became aware that the gag reflex that normally would kick in at a certain point was simply gone.  No special effort was required to keep this up, and I comfortably continued on for about 10 minutes (and could have continued longer, given the opportunity, but other activities beckoned).
Within several hours, my voice became noticeably hoarse, which I suspect was due to the act. We also noticed that -- although he didn't have an orgasm during that particular act -- for the rest of the night after that, the usual MDMA-induced inhibition of orgasm was gone on his side, and I've speculated that my (our?) achievement was responsible for that.
I will note that while I consider myself not unskilled in this area, I've never been able to achieve this previously. I intend to conduct further study to attempt to replicate my results.
COLLABORATOR'S ACCOUNT:
I am the male companion referenced in the report above. I am also 35 years old, and had only taken MDMA a few times prior to this experience. Prior to the incident in question, we had had sex twice that night, once right after we ingested Ecstasy, and once perhaps an hour later after we both had begun to feel the effects of the drug. I did not achieve an orgasm during the second session of sex.  After a couple minutes I became aware of an unfamiliar sensation -- I looked down and my companion had swallowed the entirety of my phallus. She appeared to notice at the same time, and we agreed her gag reflex appeared to be suppressed by MDMA.
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.


|
e-puck
1.0
|
#include "e_poxxxx.h"
#include "e_po3030k.h"
#include "e_po6030k.h"
#include "e_po8030d.h"
#include "../../motor_led/e_epuck_ports.h"
#include "../../I2C/e_I2C_protocol.h"
#include "../../motor_led/e_init_port.h"
Macros | |
| #define | DEVICE_ID 0xDC |
Functions | |
| int | e_poxxxx_config_cam (unsigned int sensor_x1, unsigned int sensor_y1, unsigned int sensor_width, unsigned int sensor_height, unsigned int zoom_fact_width, unsigned int zoom_fact_height, int color_mode) |
| void | e_poxxxx_set_mirror (int vertical, int horizontal) |
| void | e_poxxxx_write_cam_registers (void) |
| int | e_poxxxx_init_cam (void) |
| static unsigned | readee (unsigned page, unsigned addr) |
| int | e_poxxxx_get_orientation (void) |
| void | e_poxxxx_set_awb_ae (int awb, int ae) |
| void | e_poxxxx_set_rgb_gain (unsigned char r, unsigned char g, unsigned char b) |
| void | e_poxxxx_set_exposure (unsigned long exp) |
| unsigned int | getCameraVersion () |
Variables | |
| static unsigned int | camera_version |
| #define DEVICE_ID 0xDC |
| int e_poxxxx_config_cam | ( | unsigned int | sensor_x1, |
| unsigned int | sensor_y1, | ||
| unsigned int | sensor_width, | ||
| unsigned int | sensor_height, | ||
| unsigned int | zoom_fact_width, | ||
| unsigned int | zoom_fact_height, | ||
| int | color_mode | ||
| ) |
| int e_poxxxx_get_orientation | ( | void | ) |
Return the camera orientation
| int e_poxxxx_init_cam | ( | void | ) |
Initalize the camera, return the version in hexa, 0x3030 or 0x6030
| void e_poxxxx_set_awb_ae | ( | int | awb, |
| int | ae | ||
| ) |
Enable/Disable AWB and AE
| awb | 1 means AWB enabled, 0 means disabled |
| ae | 1 means AE enabled, 0 means disabled |
| void e_poxxxx_set_exposure | ( | unsigned long | exp | ) |
Set exposure time
| t | Exposure time, LSB is in 1/64 line time |
| void e_poxxxx_set_mirror | ( | int | vertical, |
| int | horizontal | ||
| ) |
| void e_poxxxx_set_rgb_gain | ( | unsigned char | r, |
| unsigned char | g, | ||
| unsigned char | b | ||
| ) |
Set the gains of the camera
| red | The red pixels' gain (0..255) |
| green | The green pixels' gain (0..255) |
| blue | The blue pixels' gain (0..255) |
| void e_poxxxx_write_cam_registers | ( | void | ) |
| unsigned int getCameraVersion | ( | ) |
|
static |
|
static |


SURF & PADDLE CO.
An Ironyard Academy Project Est. Fall 2013
about
search
SURF & PADDLE CO. BLOG
A FANTASTIC ENGAGING HEADLINE GOES HERE
on Monday Oct. 7th 9:22pm


'''
Pymodbus Interfaces
---------------------
A collection of base classes that are used throughout
the pymodbus library.
'''
from pymodbus.exceptions import NotImplementedException
#---------------------------------------------------------------------------#
# Generic
#---------------------------------------------------------------------------#
[docs]class Singleton(object):
'''
Singleton base class
http://mail.python.org/pipermail/python-list/2007-July/450681.html
'''
[docs] def __new__(cls, *args, **kwargs):
''' Create a new instance
'''
if '_inst' not in vars(cls):
cls._inst = object.__new__(cls)
return cls._inst
#---------------------------------------------------------------------------#
# Project Specific
#---------------------------------------------------------------------------#
[docs]class IModbusDecoder(object):
''' Modbus Decoder Base Class
This interface must be implemented by a modbus message
decoder factory. These factories are responsible for
abstracting away converting a raw packet into a request / response
message object.
'''
[docs] def decode(self, message):
''' Wrapper to decode a given packet
:param message: The raw modbus request packet
:return: The decoded modbus message or None if error
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def lookupPduClass(self, function_code):
''' Use `function_code` to determine the class of the PDU.
:param function_code: The function code specified in a frame.
:returns: The class of the PDU that has a matching `function_code`.
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs]class IModbusFramer(object):
'''
A framer strategy interface. The idea is that we abstract away all the
detail about how to detect if a current message frame exists, decoding
it, sending it, etc so that we can plug in a new Framer object (tcp,
rtu, ascii).
'''
[docs] def checkFrame(self):
''' Check and decode the next frame
:returns: True if we successful, False otherwise
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def advanceFrame(self):
''' Skip over the current framed message
This allows us to skip over the current message after we have processed
it or determined that it contains an error. It also has to reset the
current frame header handle
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def addToFrame(self, message):
''' Add the next message to the frame buffer
This should be used before the decoding while loop to add the received
data to the buffer handle.
:param message: The most recent packet
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def isFrameReady(self):
''' Check if we should continue decode logic
This is meant to be used in a while loop in the decoding phase to let
the decoder know that there is still data in the buffer.
:returns: True if ready, False otherwise
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def getFrame(self):
''' Get the next frame from the buffer
:returns: The frame data or ''
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def populateResult(self, result):
''' Populates the modbus result with current frame header
We basically copy the data back over from the current header
to the result header. This may not be needed for serial messages.
:param result: The response packet
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def processIncomingPacket(self, data, callback):
''' The new packet processing pattern
This takes in a new request packet, adds it to the current
packet stream, and performs framing on it. That is, checks
for complete messages, and once found, will process all that
exist. This handles the case when we read N + 1 or 1 / N
messages at a time instead of 1.
The processed and decoded messages are pushed to the callback
function to process and send.
:param data: The new packet data
:param callback: The function to send results to
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs] def buildPacket(self, message):
''' Creates a ready to send modbus packet
The raw packet is built off of a fully populated modbus
request / response message.
:param message: The request/response to send
:returns: The built packet
'''
raise NotImplementedException(
"Method not implemented by derived class")
[docs]class IModbusSlaveContext(object):
'''
Interface for a modbus slave data context
Derived classes must implemented the following methods:
reset(self)
validate(self, fx, address, count=1)
getValues(self, fx, address, count=1)
setValues(self, fx, address, values)
'''
__fx_mapper = {2: 'd', 4: 'i'}
__fx_mapper.update([(i, 'h') for i in [3, 6, 16, 22, 23]])
__fx_mapper.update([(i, 'c') for i in [1, 5, 15]])
[docs] def decode(self, fx):
''' Converts the function code to the datastore to
:param fx: The function we are working with
:returns: one of [d(iscretes),i(inputs),h(oliding),c(oils)
'''
return self.__fx_mapper[fx]
[docs] def reset(self):
''' Resets all the datastores to their default values
'''
raise NotImplementedException("Context Reset")
[docs] def validate(self, fx, address, count=1):
''' Validates the request to make sure it is in range
:param fx: The function we are working with
:param address: The starting address
:param count: The number of values to test
:returns: True if the request in within range, False otherwise
'''
raise NotImplementedException("validate context values")
[docs] def getValues(self, fx, address, count=1):
''' Validates the request to make sure it is in range
:param fx: The function we are working with
:param address: The starting address
:param count: The number of values to retrieve
:returns: The requested values from a:a+c
'''
raise NotImplementedException("get context values")
[docs] def setValues(self, fx, address, values):
''' Sets the datastore with the supplied values
:param fx: The function we are working with
:param address: The starting address
:param values: The new values to be set
'''
raise NotImplementedException("set context values")
[docs]class IPayloadBuilder(object):
'''
This is an interface to a class that can build a payload
for a modbus register write command. It should abstract
the codec for encoding data to the required format
(bcd, binary, char, etc).
'''
[docs] def build(self):
''' Return the payload buffer as a list
This list is two bytes per element and can
thus be treated as a list of registers.
:returns: The payload buffer as a list
'''
raise NotImplementedException("set context values")
#---------------------------------------------------------------------------#
# Exported symbols
#---------------------------------------------------------------------------#
__all__ = [
'Singleton',
'IModbusDecoder', 'IModbusFramer', 'IModbusSlaveContext',
'IPayloadBuilder',
]


Monument for San Francisco
In collaboration with the Immersive Lab, created at the Zurich University of the Arts’ Institute for Computer Music and Sound Technology I created an interactive timeline using archival footage of San Francisco. The installation was touch interactive and features ambisonic sound. The software was written in C++ woth the Openframeworks Libaries.Venus of the Anthropocene
I work with the Artist Lynn Hershman and wrote the software for her recent work, Venus of the Anthropocene. The work is an edition of 3 and was exhibited in New York, London and San Francisco in 2017. The facial recognition software that is capable of sentiment analysis and was written in Openframeworks, NodeJS and uses the SkyBiometry APIUntitled Surveillance Vehicle
I was facinated by the possibilities of computer vision on the Raspberry Pi. I designed and 3d printed a robot thay can stream video and do facial detection of veiwersSensor Driven Augmented Reality
This was a project for the Intel/Amazon Internet of Things hackathon in 2016. We created a lasercut house with emebedded sensors and actuators. Data from the sensors were streamed to an augemented reality app via the Amazon cloud. The Project won grand Prize.


This benchmark helps to find a suitable value for the speed option of the JSidle packer. Open this page in the target browser to benchmark the javascript execution speed.


Derek Hardy Tel. +44 (0)1344 854455 Address: Met.Office, Room 709, London Road, Bracknell, Berkshire, RG12 2SZ. United Kingdom
Or register your enquiry or complaint here (Your browser must support forms)


Hello World!
This lesson is meant for absolute beginners in Python. We'll learn how to craft a function that says "Hello, World!".Lesson objectives:
-
Create a
.py
file in the correct directory. - Understand how to define a function in Python.
- Learn how to make a function return a value.
This lesson teaches you how to define a Python function. Try running the tests for this lesson before doing anything else!
Running Python Unit Tests
Here's a command that will allow you to run your tests from the top level directory of this project (the test_driven_python
folder):
python -m unittest -vf tests.test_lesson_0_hello_world
That can look a little overwhelming at first, so let's break it down.
python
indicates that we want to run something in Python-m
tells Python to run the module we want (test.test_lesson_x
) as a scriptunittest
tells Python that we're running unit tests-vf
is a combination of two separate options:-v
encourages Python to be as verbose as possible with its output-f
tells Python to stop running the tests once it hits a failure. This is entirely optional, but you should try doing this to fix one failure at a time while you get the hang of how Python works
-
Finally, we tell Python which file it should run. In this case, that's
tests.test_lesson_0_hello_world
What error did you get when you first ran that command?
Remember, errors are built to be helpful, not scary!
You should have seen an ImportError
. This is Python telling you that it's unable to import the module hello_world
because there is no hello_world.py
file in the lesson 0 directory.
hello_world.py
in lessons/lesson_0_hello_world
Run the tests again. What's your next failure?
Defining a function in Python
Functions in Python are defined by the def
keyword, followed by your function name. After your function name there are two parenthases followed by a colon, ():
. If you're defining a function that accepts arguments this is where they'll go. Don't worry about arguments for now, though. We'll cover those in the next lesson.
Python operates using significant whitespace. This means that each time you enter a new function or logical block, you need to indent your code by 4 spaces. Python knows when you're done with your block when you unindent by 4 spaces.
def does_something():
print "something"
Print vs Return
Two core concepts to think about when using Python are print
and return
.
print
takes something in your function and prints it out into your terminal for you to read. This is a great way to see what's going on inide your function while it's running. print
is incredibly useful for debugging, but does not provide your program with any useful information. print
is for human use only.
return
is the keyword that lets Python know that you're ready to exit the function with the value on that line. return
provides useful information to the computer so that computed values can be passed from one function to another. Whenever you want to set something as the result of your function, use return
. Remember that this will exit the function. You should never have any logic in your function that is unreachable after the return
statement.
Note: if you've used other programming lanugages before, you might have come across the idea of implicit returns, meaning that the last variable in the top level scope of the function will always be returned. This is not the case in Python. If you want your function to return something, you must always explicitly state it, otherwise your function will return None
.
Finishing the challenge
Now that you have your hello_world.py
file, edit it to include a function that returns the string "Hello World!"  You'll know you're done when the output on your terminal reads:
Ran 2 tests in 0.000s OK
You're ready to move on to Lesson 1: Greetings!


The results.jsp had a lot more functionality. Much of it is for paging the search results we'll not
cover this as it's commented well enough. It does not perform any optimizations such as caching results,
etc. as that would make this a more complex example. The first thing in this page is the actual imports
for the Lucene classes and Lucene demo classes. These classes are loaded from the jars included in the
WEB-INF/lib directory in the final war file.
You'll notice that this file includes the same header and footer as the "index.jsp". From there the jsp
constructs an IndexSearcher with the "indexLocation" that was specified in the "configuration.jsp". If there
is an error of any kind in opening the index, it is diplayed to the user and a boolean flag is set to tell
the rest of the sections of the jsp not to continue.
From there, this jsp attempts to get the search criteria, the start index (used for paging) and the maximum
number of results per page. If the maximum results per page is not set or not valid then it and the
start index are set to default values. If only the start index is invalid it is set to a default value. If
the criteria isn't provided then a servlet error is thrown (it is assumed that this is the result of url tampering
or some form of browser malfunction).
The jsp moves on to construct a StandardAnalyzer just as in the simple demo, to analyze the search critieria, it
is passed to the QueryParser along with the criteria to construct a Query object. You'll also notice the
string literal "contents" included. This is to specify the search should include the contents and not
the title, url or some other field in the indexed documents. If there is any error in constructing a Query
object an error is displayed to the user.
In the next section of the jsp the IndexSearcher is asked to search given the query object. The results are
returned in a collection called "hits". If the length property of the hits collection is 0 then an error
is displayed to the user and the error flag is set.
Finally the jsp iterates through the hits collection and displayed properties of the "Document" objects we talked
about in the first walkthrough. These objects contain "known" fields specific to their indexer (in this case
"IndexHTML" constructs a document with "url", "title" and "contents"). You'll notice that these results are paged
but the search is repeated every time. This is an area where optimization could improve performance for large
result sets.


Strange Factories
Written and directed by John Harrigan, Cinema Museum, London, 2013
Victor is a writer, possessed by a terrifying story, hunting for refugee performers of a theatre destroyed in a mysterious fire. Drawn to a remote settlement founded by the mysterious Stronheim, he finds his friends under the wing of an aristocratic noble and her childlike ward. A dangerous pact is made between Victor and Stronheim: The destroyed theatre will be reconstructed, and in return, Victor must complete his story — no matter the cost.
Experience the madness and terror of haunted cinema, as you witness the film unravel inside Stronheim's factory and its characters come to life around you. Strange Factories draws on ancient theatrical traditions and mystical exploration, to wrench at the heart of what it means to be human. Will you allow it to show you the wonder behind the moving pictures — the dreams of violent imagination?
Not everyone can survive the violence of Creation.
Strange Factories is the first feature film by FoolishPeople. It was released on October 26, 2013. Strange Factories is available for purchase at strangefactories.vhx.tv/buy.


Hidden builder content for webbuild/index.html. See that file for the entry point into the web build system. This file needs to live in the buildscripts directory because of some assumptions in buildUtil.js.


@remarks Use the File class for typical operations such as copying, moving, renaming, creating, opening, deleting, and appending to files. You can also use the File class to get and set file attributes or date and time information related to the creation, access, and writing of a file.
Many of the File methods return other I/O types when you create or open files. You can use these other types to further manipulate a file. For more information, see specific File members such as OpenText, CreateText, or Create.
Because all File methods are static, it might be more efficient to use a File method rather than a corresponding FileInfo instance method if you want to perform only one action. All File methods require the path to the file that you are manipulating.
By default, full read/write access to new files is granted to all users.
The following table describes the enumerations that are used to customize the behavior of various File methods.
| Enumeration | Description |
|---|---|
| FileAccess | Specifies read and write access to a file. |
| FileShare | Specifies the level of access permitted for a file that is already in use. |
| FileMode | Specifies whether the contents of an existing file are preserved or overwritten, and whether requests to create an existing file cause an exception. |
| Note |
|---|
| In members that accept a path as an input string, that path must be well-formed or an exception is raised. For example, if a path is fully qualified but begins with a space, the path is not trimmed in methods of the class. Therefore, the path is malformed and an exception is raised. Similarly, a path or a combination of paths cannot be fully qualified twice. For example, "c:\temp c:\windows" also raises an exception in most cases. Ensure that your paths are well-formed when using methods that accept a path string. |
In members that accept a path, the path can refer to a file or just a directory. The specified path can also refer to a relative path or a Universal Naming Convention (UNC) path for a server and share name. For example, all the following are acceptable paths:
Public Sub Main() Const Path As String = "c:\temp\MyTest.txt" If Not File.Exists(Path) Then ' Create a file to write to. Dim sw As StreamWriter Set sw = File.CreateText(Path) sw.WriteLine "Hello" sw.WriteLine "And" sw.WriteLine "Welcome" sw.Flush End If ' Open the file to read from. Dim sr As StreamReader Set sr = File.OpenText(Path) Do While sr.Peek >= 0 Debug.Print sr.ReadLine Loop End Sub


--- layout: page title: Black Hole ---
TUdo is temporarily closed for the public due to the pandemic 😷.

Contact us at<EMAIL_ADDRESS>see you soon :)


Colonisation.
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Changing experiences of the natural world
by University of LeedsDigital innovations have the potential to bring people closer to nature, to help ensure there is the necessary strong public support for conservation measures. Examples below.
Author Professor Les Firbank, from the University of Leeds' School of Biology and Global Food and Environment Institute, said: "Our growing digital connection to wildlife, aided by broadcasters such as David Attenborough, may be crucial to securing broad public support for the protection of wildlife, which we are currently driving to extinction at record rates.
"In future, expertise in public engagement and digital innovation are likely to be as important as expertise in conservation biology, to ensure the values and culture of a community are placed at the heart of the protection of nature.
"Urbanisation is changing our cultural relationships with wildlife, and this has to be taken into account by nature conservation organisations if conservation is to be successful into the future."
"The growing popularity of rewilding may well be a reflection of humanity's changing view of ourselves, seeing humans as separate to nature, rather than as part of it.
"We need to defend and rebuild our connections with nature to help shape a culture that recognises the need to conserve wildlife.
Examples of digital innovation taking place today include:
- Fitness apps that compare people to wild animals (such as snow leopards)
- Live feeds for nests, birds, mammals, from urban through to wild nature (including peregrine falcons at the University of Leeds)
- Gamification of simple experiments on habitat management in gardens (e.g. providing bird food)
- Virtual reality experiences of climate change and wild lands (e.g. virtual planet)
- Creating local wildlife hubs linked through social media, such as people tracking the number of birds killed by pet cats or sightings of foxes and other predators
Professor Firbank added: "Agriculture is the biggest driver of global biodiversity loss, and it has led us to the extinction crisis we face today.
"Increasing urbanization means that fewer people are experiencing nature through traditional, extensive farming, and instead they are experiencing a form of wild-nature through digital media."
The paper, published in the journal One Earth at 16.00 GMT on Friday 22nd November 2019, is titled 'The changing cultural dimensions of biodiversity conservation'.


Add a New THANG
List of THANGS To Do
| THANG Name | THANG Due Date | THANG Completed? |
|---|
* - DAMN THANGS is a better word for tasks. We all want to succeed in life. For some people, that means writing down tasks and completing them.
This app is designed to help you add and track the DAMN THANGS you got to do.
| THANG Name | THANG Due Date | THANG Completed? |
|---|


Left-aligned text is the standard because it gives the reader a vertical anchor to jump back to on every line. You should use it for most of your body text (unless you have a very good reason not to).
Center-aligned text doesn’t have that anchor, so it’s easier for the eye to get lost when it tries to jump to the next line. Reserve it for special kinds of content, like poems, lyrics, and headings.
Only use right-aligned text when it makes sense for the layout. For example, a caption for an image:
Of course, if you’re publishing content in a language that’s read right-to-left, that’s another story...
Justified text requires a good hyphenation engine. Without an intelligent way to split long words across lines, you get big spaces between words, which makes it harder to scan the text. Most browsers don’t have good built-in hyphenation engines.


One App for all your unit conversions.
Created By: Rushi
Just select the unit from drop down and enter the value, the app does the rest of conversion


Schaller, G., D. Schaerer, G. Meynet, and A. Maeder. "New Grids of Stellar Models from 0.8 to
120 Solar Masses at Z = 0.020 and Z = 0.001." Astronomy and Astrophysics Supplement
Series 96.2 (1992): 269-331. SAO/NASA Astrophysics Data System. Web. 4 Feb. 2016.
Tognelli, E., P. G. Prada Moroni, and S. Degl'Innocenti. "The Pisa Pre-main Sequence Tracks
and Isochrones. A Database Covering a Wide Range of Z, Y, Mass, and Age Values."
Astronomy & Astrophysics, Volume 533 (2011): 1-20. SAE/NASA Astrophysics Data
System. Harvard-Smithsonian Center for Astrophysics. Web. 20 Feb. 2016.
Go Back


TypeError: Data must be a string or a buffer when trying touse vue-bulma-tabs @jsmith replied 53 minutes ago Question 13
I'm trying to use hamburger menu on bulma css, but it doesn't work. What is wrong? @hamburgler replied 5 hours ago Question 2


Black Region Detection
Detect Anomalies
The detected anomalies are shown below.
{{anomalies | safe}}


Licensed Therapist
MA in Counseling, Doane College
BA in Psychology, UNL
<EMAIL_ADDRESS>Office Hours
Monday–Thursday 9am–5pm
Eric is a licensed independent mental health practitioner as well as a provisionally licensed alcohol and drug counselor, practicing for two years in Lincoln. He aims to address mental health and substance abuse concerns from a trauma-informed approach. Eric is also a registered service provider for the state of Nebraska and has worked closely with the office of probation to provide services to those on probation with legal concerns.
Outside the office, Eric enjoys sports, camping, cooking, and spending time with his family.
Please complete forms before your appointment


{% extends "base.html" %} {#Head container#} {% load staticfiles %} {% load bootstrap %} {% load i18n widget_tweaks %} {% block content %}
{%trans "This page will automatically refresh. Your Annotation request should be complete in 1-3 minutes per sample (more if you requested many SeqIDs)." %}
{%trans "You don't have to remain on this page - this Annotation request will be visible on " %} {%trans "Annotation Home" %}
{% if request.user.email in prokka_request.emails_array %}{%trans "Your email is already on the list to be notified."%}
{%trans "Would you like to add another email?"%} {% else %}{%trans "Would you like an email upon completion?"%}
{% endif %} {% elif prokka_request.status == 'Unprocessed' %}{%trans "Return to" %} {%trans "Annotation Home" %}
{% elif prokka_request.status == 'Complete' %}{%trans "These results will be available for 7 days." %}


Join the numbers and get to the 2048 tile!
How to play: Swipe ←, ↑, ↓, → to move the tiles. When two tiles with the same number touch, they merge into one!


Page not Found
The page you are looking for is not available or has been removed. Try going to Home Page by using the button below.
Go to Home PageThe page you are looking for is not available or has been removed. Try going to Home Page by using the button below.
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Locker.Fsm
A utility module that helps in creating :gen_fsm
processes that
are registered in locker
. Options are similar to the ones with
Locker.Server
.
Example
You can create a standard :gen_fsm
process that is registered
under locker
like this:
defmodule MyFsm do
use Locker.Fsm, lease_length: 10000
def init(_) do
{:ok, :initial_state, %{}}
end
end
Similar to Locker.Server
, this module also implements start/2
and start_link/2
functions and if the opts
contain a key name
the process will be registered by that name under Locker.Registry
.
When overriding terminate/3
you will need to add call to
super(reason, statename, state)
similarly to Locker.Server
so
that the process will be properly unregistered during termination.


A blockquote on multiple lines like this. But it has two paragraphs.
A blockquote on multiple lines like this.
But it has two paragraphs.


Working with component-based entities¶
sdl2.ext
supports a component oriented programming pattern to separate
object instances, carried data and processing logic within applications
or games. It uses an entity based approach, in which object instances are
unique identifiers, while their data is managed within components, which
are stored separately. For each individual component type a processing
system will take care of all necessary updates on running the application.
Component-based patterns¶
Component-based means that - instead of a traditional OOP approach - object information are split up into separate data bags for reusability and that those data bags are separated from any application logic.
Behavioural design¶
Imagine a car class in traditional OOP, which might look like
class Car:
def __init__(self):
self.color = "red"
self.position = 0, 0
self.velocity = 0, 0
self.sprite = get_some_car_image()
...
def drive(self, timedelta):
self.position[0] = self.velocity[0] * timedelta
self.position[1] = self.velocity[1] * timedelta
...
def stop(self):
self.velocity = 0, 0
...
def render(self, screen):
screen.display(self.sprite)
mycar = new Car()
mycar.color = "green"
mycar.velocity = 10, 0
The car features information stored in attributes (color
, position
,
...) and behaviour (application logic, drive()
, stop()
...).
A component-based approach aims to split and reduce the car to a set of information and external systems providing the application logic.
class Car:
def __init__(self):
self.color = "red"
self.position = 0, 0
self.velocity = 0, 0
self.sprite = get_some_car_image()
class CarMovement:
def drive(self, car, timedelta):
car.position[0] = car.velocity[0] * timedelta
car.position[1] = car.velocity[1] * timedelta
...
def stop(self):
car.velocity = 0, 0
class CarRenderer:
def render(self, car, screen):
screen.display(car.sprite)
At this point of time, there is no notable difference between both approaches, except that the latter one adds additional overhead.
The benefit comes in, when you
- use subclassing in your OOP design
- want to change behavioural patterns on a global scale or based on states
- want to refactor code logic in central locations
- want to cascade application behaviours
The initial Car
class from above defines, how it should be displayed
on the screen. If you now want to add a feature for rescaling the screen
size after the user activates the magnifier mode, you need to refactor
the Car
and all other classes that render things on the screen, have
to consider all subclasses that override the method and so on.
Refactoring the CarRenderer
code by adding a check for the magnifier
mode sounds quite simple in contrast to that, not?
The same applies to the movement logic - inverting the movement logic requires you to refactor all your classes instead of a single piece of application code.
Information design¶
Subclassing with traditional OOP for behavioural changes also might
bloat your classes with unnecessary information, causing the memory
footprint for your application to rise without any need. Let’s assume
you have a Truck
class that inherits from Car
. Let’s further
assume that all trucks in your application look the same. Why should any
of those carry a sprite
or color
attribute? You would need to
refactor your Car
class to get rid of those superfluous information,
adding another level of subclassing. If at a later point of time you
decide to give your trucks different colors, you need to refactor
everything again.
Wouldn’t it be easier to deal with colors, if they are available on the truck and leave them out, if they are not? We initially stated that the component-based approach aims to separate data (information) from code logic. That said, if the truck has a color, we can handle it easily, if it has not, we will do as usual.
Also, checking for the color of an object (regardless, if it is a truck, car, aeroplane or death star) allows us to apply the same or similar behaviour for every object. If the information is available, we will process it, if it is not, we will not do anything.
All in all¶
Once we split up the previously OOP-style classes into pure data containers and some separate processing code for the behaviour, we are talking about components and (processing) systems. A component is a data container, ideally grouping related information on a granular level, so that it is easy to (re)use. When you combine different components to build your in-application objects and instantiate those, we are talking about entities.
- Component
- provides information (data bag)
- Entity
- In-application instance that consists of component items
- System
- Application logic for working with Entity items and their component data
- World
- The environment that contains the different System instances and all Entity items with their component data
Within a strict COP design, the application logic (ideally) only knows about data to process. It does not know anything about entities or complex classes and only operates on the data.
To keep things simple, modular and easy to maintain and change, you usually
create small processing systems, which perform the necessary operations on the
data they shall handle. That said, a MovementSystem
for our car entity would
only operate on the position and velocity component of the car entity. It does
not know anything about the the car’s sprite or sounds that the car makes,
since this is nothing it has to deal with.
To display the car on the screen, a RenderingSystem
might pick up the
sprite component of the car, maybe along with the position information (so it
knows, where to place the sprite) and render it on the screen.
If you want the car to play sounds, you would add an audio playback system, that can perform the task. Afterwards you can add the necessary audio information via a sound component to the car and it will make noise.
Component-based design with sdl2.ext¶
Note
This section will deal with the specialities of COP patterns and provide the bare minimum of information. If you are just starting with such a design, it is recommended to read through the The Pong Game tutorial.
sdl2.ext
provides a World
class in which all other objects
will reside. The World
will maintain both, Entity
and
component items, and allows you to set up the processing logic via
the System
and Applicator
classes.
>>> appworld = World()
Components can be created from any class that inherits from the
object
type and represent the data bag of information for the
entity and application world. Ideally, they should avoid any
application logic (except from getter and setter properties).
class Position2D(object):
def __init__(self, x=0, y=0):
self.x = x
self.y = y
Entity
objects define the in-application objects and only consist of
component-based attributes. They also require a World
at
object instantiation time.
class CarEntity(Entity):
def __init__(self, world, x=0, y=0):
self.position2d = Position2D(x, y)
Note
The world argument in __init__()
is necessary. It will be
passed to the internal __new__()
constructor of the
Entity
and stores a reference to the World
and also
allows the Entity
to store its information in the
World
.
The Entity
also requries its attributes to be named exactly as
their component class name, but in lowercase letters. If you name a
component MyAbsolutelyAwesomeDataContainer
, an Entity
will
force you to write the following:
class SomeEntity(Entity):
def __init__(self, world):
self.myabsolutelyawesomedatacontainer = MyAbsolutelyAwesomeDataContainer()
Note
This is not entirely true. A reference of the object will be stored on a
per-class-in-mro basis. This means that if MyAbsolutelyAwesomeDataContainer
inherits from ShortName
, you can also do:
class SomeEntity(Entity):
def __init__(self, world):
self.shortname = MyAbsolutelyAwesomeDataContainer()
Components should be as atomic as possible and avoid complex
inheritance. Since each value of an Entity
is stored per class
in its mro list, components inheriting from the same class(es) will
overwrite each other on conflicting classes:
class Vector(Position2D):
def __init__(self, x=0, y=0, z=0):
super(Vector, self).__init__(x, y)
class SomeEntity(Entity):
def __init__(self, world):
# This will associate self.position2d with the new Position2D
# value, while the previous Vector association is overwritten
self.position2d = Position2D(4, 4)
# self.vector will also associate a self.position2d attribute
# with the Entity, since Vector inherits from Position2D. The
# original association will vanish, and each call to
# entity.position2d will effectively manipulate the vector!
self.vector = Vector(1,2,3)
API¶
-
class
sdl2.ext.
Entity
(world : World)¶ An entity is a specific object living in the application world. It does not carry any data or application logic, but merely acts as identifier label for data that is maintained in the application world itself.
As such, it is a composition of components, which would not exist without the entity identifier. The entity itself is non-existent to the application world as long as it does not carry any data that can be processed by a system within the application world.
-
id
¶ The id of the Entity. Every Entity has a unique id, that is represented by a
uuid.UUID
instance.
-
delete
() → None¶ Deletes the
Entity
from itsWorld
. This basically callsWorld.delete()
with theEntity
.
-
-
class
sdl2.ext.
Applicator
¶ A processing system for combined data sets. The
Applicator
is an enhancedSystem
that receives combined data sets based on its setSystem.componenttypes
-
is_applicator
¶ A boolean flag indicating that this class operates on combined data sets.
-
componenttypes
¶ A tuple of class identifiers that shall be processed by the
Applicator
.
-
process
(world : World, componentsets : iterable)¶ Processes tuples of component items. componentsets will contain object tuples, that match the
componenttypes
of theApplicator
. If, for example, theApplicator
is defined asclass MyApplicator(Applicator): def __init__(self): self.componenttypes = (Foo, Bar)
its process method will receive
(Foo, Bar)
tuplesdef process(self, world, componentsets): for foo_item, bar_item in componentsets: ...
Additionally, the
Applicator
will not process all possible combinations of valid components, but only those, which are associated with the sameEntity
. That said, anEntity
must contain aFoo
as well as aBar
component in order to have them both processed by theApplicator
(while aSystem
with the samecomponenttypes
would pick either of them, depending on their availability).
-
-
class
sdl2.ext.
System
¶ A processing system within an application world consumes the components of all entities, for which it was set up. At time of processing, the system does not know about any other component type that might be bound to any entity.
Also, the processing system does not know about any specific entity, but only is aware of the data carried by all entities.
-
process
(world : World, components : iterable)¶ Processes component items.
This method has to be implemented by inheriting classes.
-
-
class
sdl2.ext.
World
¶ An application world defines the combination of application data and processing logic and how the data will be processed. As such, it is a container object in which the application is defined.
The application world maintains a set of entities and their related components as well as a set of systems that process the data of the entities. Each processing system within the application world only operates on a certain set of components, but not all components of an entity at once.
The order in which data is processed depends on the order of the added systems.
-
systems
¶ The processing system objects bound to the world.
-
add_system
(system : object)¶ Adds a processing system to the world. The system will be added as last item in the processing order.
The passed system does not have to inherit from
System
, but must feature acomponenttypes
attribute and aprocess()
method, which match the signatures of theSystem
classclass MySystem(object): def __init__(self): # componenttypes can be any iterable as long as it # contains the classes the system should take care of self.componenttypes = [AClass, AnotherClass, ...] def process(self, world, components): ...
If the system shall operate on combined component sets as specified by the
Applicator
, the class instance must contain ais_applicator
property, that evaluates toTrue
class MyApplicator(object): def __init__(self): self.is_applicator = True self.componenttypes = [...] def process(self, world, components): pass
The behaviour can be changed at run-time. The
is_applicator
attribute is evaluated for every call toWorld.process()
.
-
delete_entities
(entities : iterable)¶ Removes a set of
Entity
instances from the World, including all their component data.
-
insert_system
(index : int, system : System)¶ Adds a processing
System
to the world. The system will be added at the specified position in the processing order.
-
get_entities
(component : object) → [Entity, ...]¶ Gets the entities using the passed component.
Note
This will not perform an identity check on the component but rely on its
__eq__
implementation instead.
-


Win Half a Grand
thanks to The Playlist
Cash is king and with Christmas just around the corner we thought we’d give away Half a Grand!
Our next music survey ready to go and this time you could win $500 to spend however you like, wherever you like!
Blow it all on pressies or drinks or the turkey, ham, prawns and all the trimmings for Chrissie Lunch.
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Click the button below to visit The Playlist…
PS. If you’re already a member of The Playlist, check your inbox for the invitation we sent you (it’ll save you time giving us your personal details again)!
Competition opens Wednesday 20 November and closes midnight Monday 25 November 2019.
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The Hot Tomato Broadcasting Company’s Standard Competition Terms and Conditions apply to all 102.9 Hot Tomato and myGC contests.


Blogging is not rocket science, it's about being yourself, and putting what you have into it.
I am sorry to inform, currently there are no blogs. Thanks for your interest I will surely write some in the near future. Do come back. Thanks.


| JointDefinitionRecord |
|
| JointDefinitionRecord.Builder |
RecordBuilder for JointDefinitionRecord instances.
|
| JointIdRecord |
|
| JointIdRecord.Builder |
RecordBuilder for JointIdRecord instances.
|
| JointPositionRecord |
|
| JointPositionRecord.Builder |
RecordBuilder for JointPositionRecord instances.
|
| JointPropDefinitionRecord |
|
| JointPropDefinitionRecord.Builder |
RecordBuilder for JointPropDefinitionRecord instances.
|
| MotionFrameEventRecord |
|
| MotionFrameEventRecord.Builder |
RecordBuilder for MotionFrameEventRecord instances.
|
| MotionFrameRecord |
|
| MotionFrameRecord.Builder |
RecordBuilder for MotionFrameRecord instances.
|
| MotionMessagingUtils |
|
| PortableJointDefinition |
|
| PortableMotionFrameEvent |
|
| PortableMotionFrameEvent.Factory |
|
| PortableMotionFrameEvent.MessageRecordAdapter |
|
| PortableMotionFrameEvent.RecordMessageAdapter |
|
| PortableRobotDefinitionResponse |
|
| PortableRobotDefinitionResponse.MessageRecordAdapter |
|
| PortableRobotDefinitionResponse.RecordMessageAdapter |
|
| PortableRobotPositionResponse |
|
| PortableRobotPositionResponse.MessageRecordAdapter |
|
| PortableRobotPositionResponse.RecordMessageAdapter |
|
| PortableRobotRequest |
|
| PortableRobotRequest.Factory |
|
| PortableRobotRequest.MessageRecordAdapter |
|
| PortableRobotRequest.RecordMessageAdapter |
|
| PortableRobotResponse |
|
| PortableRobotResponse.Factory |
|
| PortableRobotResponse.MessageRecordAdapter |
|
| PortableRobotResponse.RecordMessageAdapter |
|
| PortableRobotResponse.RobotResponseKeyAdapter |
|
| PortableRobotResponseHeader |
|
| PortableRobotStatusResponse |
|
| PortableRobotStatusResponse.MessageRecordAdapter |
|
| PortableRobotStatusResponse.RecordMessageAdapter |
|
| RobotDefinitionResponseRecord |
|
| RobotDefinitionResponseRecord.Builder |
RecordBuilder for RobotDefinitionResponseRecord instances.
|
| RobotPositionMapRecord |
|
| RobotPositionMapRecord.Builder |
RecordBuilder for RobotPositionMapRecord instances.
|
| RobotPositionResponseRecord |
|
| RobotPositionResponseRecord.Builder |
RecordBuilder for RobotPositionResponseRecord instances.
|
| RobotRequestRecord |
|
| RobotRequestRecord.Builder |
RecordBuilder for RobotRequestRecord instances.
|
| RobotResponseHeaderRecord |
|
| RobotResponseHeaderRecord.Builder |
RecordBuilder for RobotResponseHeaderRecord instances.
|
| RobotStatusResponseRecord |
|
| RobotStatusResponseRecord.Builder |
RecordBuilder for RobotStatusResponseRecord instances.
|
| SynchronizedJointConfigRecord |
|
| SynchronizedJointConfigRecord.Builder |
RecordBuilder for SynchronizedJointConfigRecord instances.
|
| SynchronizedRobotConfigRecord |
|
| SynchronizedRobotConfigRecord.Builder |
RecordBuilder for SynchronizedRobotConfigRecord instances.
|


Here is some plain old boring text.
Here is some normal text that is neither boring nor exciting.
Contributing to MDN is easy and fun.


Chapter 4 Introduction to Statistical Analysis of the microbiome data
library(phyloseq)
library(tidyverse)
library(gt)
This section provides a quick introduction to some common analytic methods used to analyze microbiome data. In previous sections we worked with microbiome generated data, but ran through some fairly standard protocols that would apply to any Illumina-seq generated data and FASTQ files.
Now we are at the visualisation and statistical analysis phase - and we should start to see the implementation of some very familiar R tools.
Briefly today we will use R to understand more about
Describing the microbial community composition of a set of samples
Estimating within- and between-sample diversity
Identifying differentially abundant taxa
4.1 Important files
We’re mostly going to be working with just 3 files now.
A count table: the number of reads for each unique sequence
A taxonomy table: the assigned taxonomy for each sequence according to the SILVA database
A sample file: this is the “metadata” it contains any information we have provided about the different samples
If you worked through the entirety of the previous session you will already have the necessary R objects in your workspace. If you didn’t we can load them using a .RData
file. You should see that your Environment is suddenly populated by a number of R objects.
The one thing missing that we also need to load is a sample info object (it tells us meta-data about the origins and conditions of each environmental sample.)
<- read.table("sample_info.tsv", header=T, row.names=1,
sample_info_tab check.names=F, sep="\t")
4.2 Phyloseq
Microbiome community analysis works really well with a package called phyloseq
it allows you to make special R objects that hold the distinct sets of information on ASV abundance, taxonomy and relation to the environmental samples in one R object.
<- phyloseq(otu_table(asv_tab_no_contam, taxa_are_rows=T),
ps sample_data(sample_info_tab),
tax_table(asv_tax_no_contam))
ps
## phyloseq-class experiment-level object
## otu_table() OTU Table: [ 2498 taxa and 16 samples ]
## sample_data() Sample Data: [ 16 samples by 4 sample variables ]
## tax_table() Taxonomy Table: [ 2498 taxa by 7 taxonomic ranks ]
Note
Since we’ve already used decontam to remove likely contaminants in the previous steps, we’re dropping the “blank” samples from our count table - so now there are 16 samples total.
Take a look at each of the three objects: asv_tab_no_contam, sample_data, tax_table. There are just simple lists - can you comfortably work out the information they contain?
asv_tab_no_contam
A count table: the number of reads for each unique sequenceasv_tax_no_contam
A taxonomy table: the assigned taxonomy for each sequence according to the SILVA databasesample_info_tab
A sample file: this is the “metadata” it contains any information we have provided about the different samples
4.3 Relative abundance of bacteria by taxonomic Class
We will use some functions provided by phyloseq
to agglomerate the reads to Class-level and plot the results
<- ps %>%
taxonomy tax_glom(taxrank="class") %>% ### Preserves taxonomy only to Taxonomic level class
transform_sample_counts(function(x){x/sum(x)})%>% ### this function turns Abundance from raw counts to a relative proportion
psmelt() %>% ###converts phyloseq object into a tibble
filter(Abundance >0.05) ### remove any ASVs at less than 5% abundance
Often an early step in many microbiome projects to visualize the relative abundance of organisms at specific taxonomic ranks.
%>%
taxonomy ggplot(aes(x=Sample, y=Abundance, fill=class))+
geom_bar(stat="identity")
The ability to discriminate between more than say a dozen colors in a single plot is a limitation of the stacked bar plot - so we have filtered out less abundant reads (<5%). We run the risk that we might miss something important here, so its important to visualise the data in different ways.
There are a total of 10 Bacterial classes (at greater than 5% abundance).
Let’s generate boxplots according to char
and facet these according to Bacterial class
. This will allow us to compare how different bacterial classes appear to change in relative abundance between samples.
Try and produce something similar to the plot below
Think about what you can infer from these plots?
4.4 Alpha diversity - community richness
This is a common ecological term, and one that applies just as well when we consider microbial ecosystems.
What is the mean species diversity in the different sample sites?
<- estimate_richness(ps)
ps_richness ps_richness
This command generates a number of different diversity indices.
Firstly we can take this information and use join
functions to attach it back onto our sample metadata
$Sample <- rownames(sample_info_tab)
sample_info_tab
$Sample <- rownames(ps_richness)
ps_richness
<- left_join(sample_info_tab, ps_richness, "Sample")
full_richness full_richness
| temp | type | char | color | Sample | Observed | Chao1 | se.chao1 | ACE | se.ACE | Shannon | Simpson | InvSimpson | Fisher |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2.0 | water | water | blue | BW1 | 61 | 62.5000 | 2.5911387 | 61.88289 | 3.569938 | 3.576981 | 0.9585698 | 24.13700 | 12.04096 |
| 2.0 | water | water | blue | BW2 | 204 | 205.9091 | 2.1571603 | 205.71458 | 7.069400 | 4.436499 | 0.9750331 | 40.05305 | 43.45043 |
| 13.7 | rock | glassy | black | R10 | 383 | 385.4375 | 2.1449492 | 386.66260 | 9.717693 | 5.079826 | 0.9872712 | 78.56183 | 81.57801 |
| 7.3 | biofilm | biofilm | darkgreen | R11BF | 144 | 145.1538 | 1.5236935 | 146.00669 | 5.980036 | 3.309788 | 0.9044015 | 10.46042 | 25.68876 |
| 7.3 | rock | glassy | black | R11 | 281 | 284.4737 | 2.9104269 | 284.57048 | 8.337302 | 4.812376 | 0.9851114 | 67.16529 | 59.63308 |
| NA | rock | altered | chocolate4 | R12 | 524 | 525.8947 | 1.9684441 | 525.94449 | 11.362166 | 5.789071 | 0.9956479 | 229.77212 | 115.57917 |
| 8.6 | rock | altered | chocolate4 | R1A | 497 | 501.2500 | 2.9984998 | 502.32876 | 11.107301 | 5.666947 | 0.9945360 | 183.01554 | 115.04680 |
| 8.6 | rock | altered | chocolate4 | R1B | 577 | 579.6000 | 2.2526890 | 580.24471 | 11.965009 | 5.812676 | 0.9953007 | 212.79743 | 129.04718 |
| 8.6 | rock | altered | chocolate4 | R2 | 608 | 609.4062 | 1.5321223 | 610.17688 | 12.296746 | 5.850938 | 0.9955702 | 225.74143 | 133.85232 |
| 12.7 | rock | altered | chocolate4 | R3 | 566 | 567.5517 | 1.6446664 | 568.36545 | 11.819663 | 5.788769 | 0.9953827 | 216.57487 | 122.16253 |
| 12.7 | rock | altered | chocolate4 | R4 | 643 | 644.2857 | 1.4737632 | 644.75628 | 12.645710 | 5.718854 | 0.9940234 | 167.31991 | 137.19651 |
| 12.7 | rock | altered | chocolate4 | R5 | 624 | 624.2069 | 0.5163104 | 624.78554 | 12.367463 | 5.966462 | 0.9962834 | 269.06381 | 137.21126 |
| 12.7 | rock | altered | chocolate4 | R6 | 523 | 527.2857 | 3.1338410 | 527.52112 | 11.340777 | 5.711816 | 0.9948403 | 193.80933 | 115.90757 |
| NA | rock | carbonate | darkkhaki | R7 | 435 | 436.7838 | 1.7397113 | 438.10995 | 10.011218 | 5.557851 | 0.9939838 | 166.21652 | 110.12229 |
| 13.5 | rock | glassy | black | R8 | 424 | 428.1379 | 3.0460370 | 428.53605 | 10.245312 | 5.295582 | 0.9910943 | 112.28782 | 91.16232 |
| 13.7 | rock | glassy | black | R9 | 296 | 300.5652 | 3.3753169 | 300.44067 | 8.397187 | 4.348445 | 0.9517400 | 20.72112 | 63.39469 |
4.4.1 Analyse and plot
We now have a tidy data frame with sample information and a variety of diversity indices.
Using the Shannon index as the measure of diversity - can you construct a figure to show the diversity differences between treatments?
Again using the Shannon index - can you construct a
general linear model
to work out which treatments/effects might be having a significant effect on diversity?
4.5 Beta diversity
4.5.1 Heatmaps
Heatmaps are basically false colour images where cells in the matrix with high relative values are coloured differently from those with low relative values. Heatmaps can range from very simple blocks of colour with lists along 2 sides, or they can include information about hierarchical clustering, and/or values of other covariates of interest.
We will make a simple heatmap here, but a common addition might be a dendrogram - a phylogenetic tree to indicate how closely related different
<- prune_taxa(names(sort(taxa_sums(ps),TRUE)[1:20]), ps) ## subset to include only the top 20 most abundant ASVs
ps_top20
plot_heatmap(ps_top20,"MDS",distance = "bray", ## here we are setting up the parameters for the heat map
sample.label="char", ## set the x axis to display by sample
low="purple", ## set the color for low abundance OTUs
high="darkorange") ## set the color for high abundance OTUs
4.5.2 Multidimensional analysis
Often in ecological research, we are interested not only in comparing univariate descriptors of communities, like diversity (above), but also in how the constituent species — or the composition — changes from one community to the next.
One common tool to do this is non-metric multidimensional scaling, or NMDS. The goal of NMDS is to collapse information from multiple dimensions (e.g, from multiple communities, sites, etc.) into just a few, so that they can be visualized and interpreted.
Consider a single axis representing the abundance of a single species. Along this axis, we can plot the communities in which this species appears, based on its abundance within each.
Now consider a second axis of abundance, representing another species. We can now plot each community along the two axes (Species 1 and Species 2).
Keep going and imagine how many axes we would have to produce!!!!
The goal of NMDS is to represent the original position of communities in multidimensional space as accurately as possible using a reduced number of dimensions that can be easily plotted and visualized (and to spare your thinker).
NMDS does not use the absolute abundances of species in communities, but rather their rank orders. The use of ranks omits some of the issues associated with using absolute distance (e.g., sensitivity to transformation), and as a result is a flexible technique
### Ordination using built in functions in phyoseq (calls vegan)
<- ordinate(ps, method="NMDS",k=2, distance="bray") ord.nmds.bray
## Square root transformation
## Wisconsin double standardization
## Run 0 stress 0.04869473
## Run 1 stress 0.0478881
## ... New best solution
## ... Procrustes: rmse 0.01639951 max resid 0.04610477
## Run 2 stress 0.04346713
## ... New best solution
## ... Procrustes: rmse 0.05294335 max resid 0.1316673
## Run 3 stress 0.05216743
## Run 4 stress 0.04346694
## ... New best solution
## ... Procrustes: rmse 0.0006780795 max resid 0.002148741
## ... Similar to previous best
## Run 5 stress 0.05216581
## Run 6 stress 0.04346719
## ... Procrustes: rmse 0.0007087707 max resid 0.002245379
## ... Similar to previous best
## Run 7 stress 0.04788334
## Run 8 stress 0.05218892
## Run 9 stress 0.04346725
## ... Procrustes: rmse 0.0002716828 max resid 0.0008608943
## ... Similar to previous best
## Run 10 stress 0.04346722
## ... Procrustes: rmse 0.0007270832 max resid 0.0023034
## ... Similar to previous best
## Run 11 stress 0.04788122
## Run 12 stress 0.04346737
## ... Procrustes: rmse 0.0008170541 max resid 0.002587991
## ... Similar to previous best
## Run 13 stress 0.04788857
## Run 14 stress 0.043467
## ... Procrustes: rmse 6.761702e-05 max resid 0.0002142312
## ... Similar to previous best
## Run 15 stress 0.05217513
## Run 16 stress 0.05218083
## Run 17 stress 0.04346707
## ... Procrustes: rmse 0.000608542 max resid 0.001927707
## ... Similar to previous best
## Run 18 stress 0.1096243
## Run 19 stress 0.05584216
## Run 20 stress 0.04950525
## *** Solution reached
You should see each iteration of the NMDS until a solution is reached (i.e., stress was minimized after some number of reconfigurations of the points in 2 dimensions). You can increase the number of default iterations using the argument trymax=. which may help alleviate issues of non-convergence. If high stress is your problem, increasing the number of dimensions to k=3 might also help.
Often in ecological research, we are interested not only in comparing univariate descriptors of communities, like diversity (above), but also in how the constituent species — or the composition — changes from one community to the next.
One common tool to do this is non-metric multidimensional scaling, or NMDS. The goal of NMDS is to collapse information from multiple dimensions (e.g, from multiple communities, sites, etc.) into just a few, so that they can be visualized and interpreted.
Consider a single axis representing the abundance of a single species. Along this axis, we can plot the communities in which this species appears, based on its abundance within each.
Now consider a second axis of abundance, representing another species. We can now plot each community along the two axes (Species 1 and Species 2).
Keep going and imagine how many axes we would have to produce!!!!
The goal of NMDS is to represent the original position of communities in multidimensional space as accurately as possible using a reduced number of dimensions that can be easily plotted and visualized (and to spare your thinker).
NMDS does not use the absolute abundances of species in communities, but rather their rank orders. The use of ranks omits some of the issues associated with using absolute distance (e.g., sensitivity to transformation), and as a result is a flexible technique
We can use the function plot.ordination to use our NMDS scaling to position our samples on a ggplot
<-plot_ordination(ps, ord.nmds.bray, color="char", title="Bray NMDS")
ord1 ord1
And we can add customisations to improve the plot
+ stat_ellipse(type="norm",
ord1 geom="polygon",
aes(fill=char),
alpha=0.3,
linetype="dashed") +
geom_point(pch=21, aes(fill=char), colour="white", stroke=0.5, size=3)+
theme_classic()
4.6 Question
We have now produced several different visualisations and analyses of the microbiome communities from these deep sea samples. What do you think are the most important or interesting findings here?
4.7 Summary
This is a very brief introduction to using big data. Hopefully you can see that many of the command line tools, data cleaning and analysis and visualisation you have been practising prepare you for Big Data Biology.
In this example, in order to have generated and processed this data, you would have needed to know
- Sampling techniques
- Molecular lab skills
- Data analysis and coding knowledge
- Ecological skills (community analysis)
Biology is increasingly interdisciplinary - and the skills you learn in one module should be transferable to other things you do.
And remember at the heart of everything is Data! It doesn’t matter what you are studying or why - good data skills are fundamental.
Thank you!


Refactoring Patterns for Python Code
Python is a batteries-included language with most utilities already present in its standard library. In this article, I will go over real world case studies on how to refactor python code.
1. Test for Existence
Consider a use-case where we need to print first element of a list. We check if list has elements and then print the first element.
a = [1, 2, 3]
if len(a) > 0:
print(a[0])
In Python, empty data structures are treated as False as illustrated below.
>>> bool([])
False
>>> bool([1, 2, 3])
True
So, we can exploit this feature to make the previous code succinct without checking the length.
a = [1, 2, 3]
if a:
print(a[0])
2. Check for range
You need to check if an age is between 18 and 65 years old.
if age >=18 and age <=65:
print("Do Something")
Python allows combining comparision operators to check if value falls in a range similar to a math equation. So, we can refactor the code as:
if 18 <= age <=65:
print("Do Something")
3. Multiple Equality Check
We need to check if a character is a vowel or consonant.
c = 'u'
if c == 'a' or c == 'e' or c == 'i' or c =='o' or c == 'u':
print('vowel')
else:
print('consonant')
We can use the in
operator to simplify the boolean expression.
c = 'u'
if c in ('a', 'e', 'i', 'o', 'u'):
print('vowel')
else:
print('consonant')
4. Setting default value
In a webapp, we are displaying 10 items to user by default. If we get count as attribute in request, we display that count of items.
count = get_count()
count = count if count else 10
Here, instead of if / else, we can use the or
operator to simplify the expression.
count = get_count() or 10
5: You don’t need lambda
We need to convert a list of numbers from string to integer. We use a lambda function to take each element and use the inbuilt int(…) function to convert that to integer.
a = ['1', '2', '3']
nums = list(map(lambda x: int(x), a))
We can use the inbuilt function directly without requiring lambda function. We know map
expects a function as the first argument that takes one parameter and since int
is a function that takes one parameter, it can be used.
a = ['1', '2', '3']
nums = list(map(int, a))
The same pattern can be used for functions such as sorted.
sorted(a, key=int)
6. Intermediate List
We need a sum of squares of numbers from 1 to 100.
a = sum([i*i for i in range(100)])
Instead of creating list using list comprehension, we can use a generator expression for optimization. Notice the removal of square brackets. The list is not created in memory.
a = sum(i*i for i in range(100))
7. Boolean Result
We need to check if a person is eligible for voting or not.
def is_voter(age):
if age >= 18:
return True
else:
return False
Here since we are returning the result of the boolean expression in if statement, we can directly return the result itself.
def is_voter(age):
return age >= 18
8: Loop Index
Suppose, you want to print an numbered list of colors present in a list.
i = 1
colors = ['Red', 'Blue', 'Green']
for color in colors:
print(i, color)
i = i + 1
Output:
1 Red
2 Blue
3 Green
We can refactor the code using builtin enumerate function. The variable used for counting is no longer needed.
colors = ['Red', 'Blue', 'Green']
for i, color in enumerate(colors, start=1):
print(i, color)
9: Easier to Ask for Forgiveness than Permission
Consider a function that divides two numbers. We need to handle the case when denominator is zero.
def divide(x, y):
if y == 0:
return None
else:
return x / y
In Python, exceptions are preferred to handle failure conditions. So, we can refactor the above code using a try-catch statements.
def divide(x, y):
try:
return x / y
except ZeroDivisionError:
return None
10. Loop over dictionary
Suppose we need to print the keys of a dictionary.
d = {'one':1, 'two': 2}
for key in d.keys():
print(key)
By default, a loop over a dictionary iterates over the keys. So we can refactor the above code as:
d = {'one':1, 'two': 2}
for key in d:
print(key)
11. Default value in dictionary
Consider a case where we need to count frequency of characters.
chars = ['A', 'B', 'A', 'C']
counts = {}
for char in chars:
if char not in counts:
counts[char] = 1
else:
counts[char] += 1
print(counts)
# {'A': 2, 'B': 1, 'C': 1}
We can use the defaultdict collection to set the default value as 0. So, we don’t need to check if key is already present or not now.
from collections import defaultdict
chars = ['A', 'B', 'A', 'C']
counts = defaultdict(int)
for char in chars:
counts[char] += 1
print(counts)


No change in Shiv Sena's stand on Maharashtra govt formation: Sanjay Raut
In an veiled attack on the BJP, Sanjay Raut said those responsible for political instability were causing harm the state
by PTISenior Shiv Sena leader Sanjay Raut, November 7, said there was no change in his party's stand on government formation in Maharashtra and reiterated the demand for sharing the chief minister's post.
He also asked that if the people's mandate was for the 'Maha-Yuti' (grand alliance), why the BJP was not staking claim to form government.
In an veiled attack on the BJP, he said those responsible for political instability were causing harm the state.
"There is no change in the Shiv Sena's stand on government formation; all our MLAs are supporting (party chief) Uddhav Thackeray," Raut said addressing a press conference here.
He asserted that the chief minister of the state will be from the "Sena only".
"If the mandate is for 'Maha-Yuti', why not stake claim to form the government? Why have you (BJP) returned empty- handed after meeting the governor?" the Rajya Sabha member sought to know.
"When you say the mandate is for 'Maha-Yuti', the mandate is also for what was agreed upon when the alliance was formalised (before the Lok Sabha polls)," Raut said.
The BJP and the Shiv Sena are engaged in a bitter tug-of-war over the latter's demand for equal distribution of portfolios and sharing the chief minister's post. The BJP has rejected the Sena's demand for sharing the chief minister's post for two-and-a-half years each.
The tenure of the present Assembly ends on November 9.Special Thursday Expiry on 10th 7th Nov
Early Closure to The Great Diwali Discount. Last Chance to get Moneycontrol PRO for a year @ Rs. 289/- only
Coupon code: DIWALI


|
ArUco Unity
0.1.0
OpenCV's ArUco Marker Detection module adapted for Unity 5.
|
Describes an ArUco grid board. More...
Inherits ArucoUnity.Utility.ArucoBoard.
Static Public Member Functions | |
| static int | GetArucoHashCode (int markersNumberX, int markersNumberY, float markerSideLength, float markerSeparation) |
Protected Member Functions | |
| override void | UpdateHashCode () |
| ArucoBoard.UpdateHashCode More... | |
| override void | UpdateBoard () |
| ArucoBoard.UpdateBoard More... | |
| Protected Member Functions inherited from ArucoUnity.Utility.ArucoBoard | |
| override void | Awake () |
| Initialize the properties and suscribe to ArucoObject.PropertyUpdated. More... | |
| override void | OnPropertyUpdated () |
| ArucoObject.OnPropertyUpdated. More... | |
| Protected Member Functions inherited from ArucoUnity.Utility.ArucoObject | |
| virtual void | OnPropertyUpdating () |
| Call the event PropertyUpdating. More... | |
Static Protected Member Functions | |
| static int | GetArucoHashCode (ArucoGridBoard arucoGridBoard) |
Properties | |
| int | MarkersNumberX [get, set] |
| Number of markers in the X direction. More... | |
| int | MarkersNumberY [get, set] |
| Number of markers in the Y direction. More... | |
| float | MarkerSeparation [get, set] |
| Separation between two consecutive markers in the grid. In pixels for Creators. In meters for Trackers and Calibrators. More... | |
| int | MarkersUsedForEstimation [get, set] |
| Properties inherited from ArucoUnity.Utility.ArucoBoard | |
| override int | HashCode [get] |
| ArucoObject.HashCode. More... | |
| int | MarginsSize [get, set] |
| The size of the margins in pixels (default: 0). Used by the Creators. More... | |
| Cv.Size | ImageSize [get, protected set] |
| The image size for drawing the board. More... | |
| Aruco.Board | Board [get, protected set] |
| The associated board from the ArucoUnity plugin library. More... | |
| float | AxisLength [get, protected set] |
| Cv.Vec3d | Rvec [get, set] |
| Cv.Vec3d | Tvec [get, set] |
| Properties inherited from ArucoUnity.Utility.ArucoObject | |
| abstract int | HashCode [get] |
| Aruco.Dictionary | Dictionary [get, set] |
| The dictionary to use. More... | |
| float | MarkerSideLength [get, set] |
| The size of each marker. In pixels for Creators. In meters for Trackers and Calibrators. More... | |
| int | MarkerBorderBits [get, set] |
| Number of bits in marker borders (default: 1). Used by Creators. More... | |
Additional Inherited Members | |
| Public Member Functions inherited from ArucoUnity.Utility.ArucoObject | |
| delegate void | ArucoObjectEventHandler (ArucoObject arucoObject) |
| Protected Attributes inherited from ArucoUnity.Utility.ArucoBoard | |
| int | hashCode |
| Events inherited from ArucoUnity.Utility.ArucoObject | |
| ArucoObjectEventHandler | PropertyUpdating = delegate { } |
| Executed before a property is going to be updated. More... | |
| ArucoObjectEventHandler | PropertyUpdated = delegate { } |
| Executed after a property has been updated. More... | |
Describes an ArUco grid board.
|
inlinestatic |
|
inlinestaticprotected |
|
inlineprotectedvirtual |
ArucoBoard.UpdateBoard
Implements ArucoUnity.Utility.ArucoBoard.
|
inlineprotectedvirtual |
ArucoBoard.UpdateHashCode
Implements ArucoUnity.Utility.ArucoBoard.
|
getset |
Separation between two consecutive markers in the grid. In pixels for Creators. In meters for Trackers and Calibrators.
|
getset |
Number of markers in the X direction.
|
getset |
Number of markers in the Y direction.
|
getset |


Steve Jobs is the authorized biography of Steve Jobs. The biography was written at the request of Jobs by acclaimed biographer Walter Isaacson, a former executive at CNN and Time who has written best-selling biographies about Benjamin Franklin and Albert Einstein.
Based on more than forty interviews with Jobs conducted over two years—in addition to interviews with more than one hundred family members, friends, adversaries, competitors, and colleagues—Isaacson was given "exclusive and unprecedented" access to Jobs's life. Jobs is said to have encouraged the people interviewed to speak honestly. Although Jobs cooperated with the book, he asked for no control over its content other than the book's cover, and waived the right to read it before it was published.


Tools for transferable species distribution modeling and pseudo-absence data generation allowing the straightforward design of relatively complex experiments with multiple factors affecting the uncertainty (variability) of SDM outputs (pseudo-absence sample, climate projection, modeling algorithm, etc.), and the quantification of the contribution of different factors to the final variability following the method described in Deque el al. (2010) <doi:10.1007/s00382-011-1053-x>. Multiple methods for pseudo-absence data generation can be applied, including the novel Three-step method as described in Iturbide et al. (2015) <doi:10.1016/j.ecolmodel.2015.05.018>. Additionally, a function for niche overlap calculation is provided, considering the metrics described in Warren et al. (2008) <10.1111/j.1558-5646.2008.00482.x> and in Pianka (1973) <10.1146/annurev.es.04.110173.000413>.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.4.0), raster, sp |
| Imports: | splancs, spam, spatstat, sampling, dismo, rpart, tree, e1071, earth, randomForest, PresenceAbsence, lattice, graphics, grDevices, gtools, ranger, abind |
| Suggests: | rJava (≥ 0.5-0), caret (≥ 6.0-76) |
| Published: | 2018-02-13 |
| Author: | Maialen Iturbide [aut, cre], Joaquin Bedia [ctb], SantanderMetGroup http://meteo.unican.es [ctb] |
| Maintainer: | Maialen Iturbide <miturbide at ifca.unican.es> |
| BugReports: | https://github.com/SantanderMetGroup/mopa/issues |
| License: | GPL-3 |
| URL: | https://github.com/SantanderMetGroup/mopa/wiki |
| NeedsCompilation: | no |
| Citation: | mopa citation info |
| CRAN checks: | mopa results |
| Reference manual: | mopa.pdf |
| Package source: | mopa_1.0.1.tar.gz |
| Windows binaries: | r-devel: mopa_1.0.1.zip, r-release: mopa_1.0.1.zip, r-oldrel: mopa_1.0.1.zip |
| OS X binaries: | r-release: mopa_1.0.1.tgz, r-oldrel: mopa_1.0.1.tgz |
| Old sources: | mopa archive |
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a couple weeks ago i went outto a tree farm near my house and picked three bags full of the yellow-orange flys. i took the caps off of them and placed them in my dehydrator for a couple hours. i have done this drug plenty of times before- (ex. 1.eating them raw 15 caps, 2.making soup w/10 caps, 3. raw caps mixed w/ pasta w/ 15caps) just to name a few but without smoking some weed with them they make me feel really nauseas. so 2 nights ago i made some more mushroom soup w/10 caps and waited 'til i got really nauseas then took 2 hits off of my pipe and was good to go, minutes later i got a sudden wave of thoughts my vision was going in and out and everything seemed to move in slow-mo and in waves. lasted a couple hours but i really didnt note anything about it except it really was cool.
none of my experiences compares to my journey last night.
i was really bored throughout the day and the night came pretty fast and with nothing else to do and no pot or beer to drink i decided i should go and eat a couple caps from my collection of amanitas. but i hesitated because i didnt want to get nauseas with no weed to smoke.... but i was bored so i said fuck it.
i took 8 medium sized caps and ate them by themselves with only some iced tea to wash them down, but i dont mind the taste of mushrooms so it went down easy.

Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Effects of TNFα on HepG2 cell and THLE-2 cell. Cells were treated with PBS (Control) or TNFα at 10 μg/mL for 24 h, and then were subject to (A) MTT assay for determining cell viability and (B) cell cycle distribution analysis for determining sub-G1 phase ratio. *, ** and ***, P <0.05, 0.01 and 0.005 as compared to control, respectively.


{% extends "teacher/dashboard.html" %} {% block title %}查看实验详情{% endblock %} {% block right %} {% include "experiment/_experiment_info.html"%} {% include "experiment/_student_list.html" %} {% endblock %}


h = neterr(w, net, x, t) [h, varargout] = neterr(w, net, x, t, varargin)
h = nethess(w, net, x, t)
takes a weight vector w
and a network
data structure net
, together with the matrix x
of input
vectors and the matrix t
of target vectors, and returns the
value of the Hessian evaluated at w
.
[e, varargout] = nethess(w, net, x, t, varargin)
also returns any additional
return values from the network Hessian function, and passes additional arguments
to that function.
In evidence
, this function is called once to compute the
data contribution to the Hessian
[h, dh] = nethess(w, net, x, t, dh);and again to update the Hessian for new values of the hyper-parameters
h = nethess(w, net, x, t, dh);
neterr
, netgrad
, netopt
Copyright (c) Ian T Nabney (1996-9)


Serving the community and
the freshest homemade food since 19XX
This is a placeholder parapgraph that can be used to explain the restaurant, the owners behind the restaurant, the food, etc. This text can be changed within the HTML, at the section that reads "p id = "aboutText." Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer nec odio. Praesent libero. Sed cursus ante dapibus diam. Sed nisi. Nulla quis sem at nibh elementum imperdiet. Duis sagittis ipsum. Praesent mauris. Fusce nec tellus sed augue semper porta. Mauris massa. Vestibulum lacinia arcu eget nulla. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Curabitur sodales ligula in libero.
with Cream Cheese: add $1.00 | with Home Fries or Grits: add $0.95 | with Bacon, Ham or Sausage, and Ham Fries or Grits: add $2.50
Served with 2 Eggs any style
Served with Home Fries
Served with Home Fries
Served with Applesauce or Sour Cream
with Blueberries, Strawberries, or Chocolate Chips: add $1.75
with Peanut Butter: add $0.50 | with Cream Cheese: add $0.50 | with Chive Cream Cheese: add $0.75 | with Vegetable Cream Cheese: add $0.75 | with Cinnamon Raisin Cream Cheese: add $0.75 | with Nova and Cream Cheese Spread: add $3.20 | with Sliced Nova and cream Cheese: add $5.00
2 Eggs, Bacon, Ham, or Sausage, with Pancakes, French Toast, or Potato Pancakes
American, Swiss, Cheddar, or Cream Cheese
Ham, Green Peppers, and Onions
Kosher
with Feta: add $1.20
Vegetable in a Spicy Spanish Sauce
Mushroom, Green Peppers, Onions, and Tomato
Corn Beef Hash and Swiss Cheese
Served with Sausage Gravy
with Onions: add $0.60
with Bacon, Ham, or Sausage: add $0.75 | and Cheese: $1.25
with Bacon, Ham, or Sausage: add $1.00
Hot or Cold
Hot or Cold
Kosher
Served with Fries & Slaw
Kaiser Roll: add $0.35 | Tomato: add $0.60 | Cheese: add $0.85 | Onion: add $0.60
Cup of Homemade Soup with your Choice of any Sandwich Marked with *
add $1.00
Two Juicy Burger Patties, Four Cheeses (American, Swiss, Cheddar and Provolone), Bacon, Thousand Island, Cole Slaw, Lettuce, Tomato, and Onion, Served with French Fries
Substitute French Fries: add $1.00
Monday through Friday – Includes Soup & Beverage
Orange, Apple, Grapefruit or Tomato
JP's Bagel Place is located at 2649 Hollywood Blvd Hollywood, FL 33020
Open daily from 7:00AM to 2:00PM - Saturday and Sunday until 1:00PM


The list-hits operation returns all of a Requester's HITs. The operation returns HITs of any status, except for HITs that have been deleted of with the delete-hit operation or that have been auto-deleted.
See also: AWS API Documentation
list-hits
[--next-token <value>]
[--max-results <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
Pagination token
--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values.
--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.
NextToken -> (string)
If the previous response was incomplete (because there is more data to retrieve), Amazon Mechanical Turk returns a pagination token in the response. You can use this pagination token to retrieve the next set of results.
NumResults -> (integer)
The number of HITs on this page in the filtered results list, equivalent to the number of HITs being returned by this call.
HITs -> (list)
The list of HIT elements returned by the query.
(structure)
The HIT data structure represents a single HIT, including all the information necessary for a Worker to accept and complete the HIT.
HITId -> (string)
A unique identifier for the HIT.HITTypeId -> (string)
The ID of the HIT type of this HITHITGroupId -> (string)
The ID of the HIT Group of this HIT.HITLayoutId -> (string)
The ID of the HIT Layout of this HIT.CreationTime -> (timestamp)
The date and time the HIT was created.Title -> (string)
The title of the HIT.Description -> (string)
A general description of the HIT.Question -> (string)
The data the Worker completing the HIT uses produce the results. This is either either a QuestionForm, HTMLQuestion or an ExternalQuestion data structure.Keywords -> (string)
One or more words or phrases that describe the HIT, separated by commas. Search terms similar to the keywords of a HIT are more likely to have the HIT in the search results.HITStatus -> (string)
The status of the HIT and its assignments. Valid Values are Assignable | Unassignable | Reviewable | Reviewing | Disposed.MaxAssignments -> (integer)
The number of times the HIT can be accepted and completed before the HIT becomes unavailable.Reward -> (string)
A string representing a numeric value.AutoApprovalDelayInSeconds -> (long)
The amount of time, in seconds, after the Worker submits an assignment for the HIT that the results are automatically approved by Amazon Mechanical Turk. This is the amount of time the Requester has to reject an assignment submitted by a Worker before the assignment is auto-approved and the Worker is paid.Expiration -> (timestamp)
The date and time the HIT expires.AssignmentDurationInSeconds -> (long)
The length of time, in seconds, that a Worker has to complete the HIT after accepting it.RequesterAnnotation -> (string)
An arbitrary data field the Requester who created the HIT can use. This field is visible only to the creator of the HIT.QualificationRequirements -> (list)
A condition that a Worker's Qualifications must meet in order to accept the HIT. A HIT can have between zero and ten Qualification requirements. All requirements must be met by a Worker's Qualifications for the Worker to accept the HIT.
(structure)
The QualificationRequirement data structure describes a Qualification that a Worker must have before the Worker is allowed to accept a HIT. A requirement may optionally state that a Worker must have the Qualification in order to preview the HIT.
QualificationTypeId -> (string)
The ID of the Qualification type for the requirement.Comparator -> (string)
The kind of comparison to make against a Qualification's value. You can compare a Qualification's value to an IntegerValue to see if it is LessThan, LessThanOrEqualTo, GreaterThan, GreaterThanOrEqualTo, EqualTo, or NotEqualTo the IntegerValue. You can compare it to a LocaleValue to see if it is EqualTo, or NotEqualTo the LocaleValue. You can check to see if the value is In or NotIn a set of IntegerValue or LocaleValue values. Lastly, a Qualification requirement can also test if a Qualification Exists or DoesNotExist in the user's profile, regardless of its value.IntegerValues -> (list)
The integer value to compare against the Qualification's value. IntegerValue must not be present if Comparator is Exists or DoesNotExist. IntegerValue can only be used if the Qualification type has an integer value; it cannot be used with the Worker_Locale QualificationType ID. When performing a set comparison by using the In or the NotIn comparator, you can use up to 15 IntegerValue elements in a QualificationRequirement data structure.
(integer)
LocaleValues -> (list)
The locale value to compare against the Qualification's value. The local value must be a valid ISO 3166 country code or supports ISO 3166-2 subdivisions. LocaleValue can only be used with a Worker_Locale QualificationType ID. LocaleValue can only be used with the EqualTo, NotEqualTo, In, and NotIn comparators. You must only use a single LocaleValue element when using the EqualTo or NotEqualTo comparators. When performing a set comparison by using the In or the NotIn comparator, you can use up to 30 LocaleValue elements in a QualificationRequirement data structure.
(structure)
The Locale data structure represents a geographical region or location.
Country -> (string)
The country of the locale. Must be a valid ISO 3166 country code. For example, the code US refers to the United States of America.Subdivision -> (string)
The state or subdivision of the locale. A valid ISO 3166-2 subdivision code. For example, the code WA refers to the state of Washington.RequiredToPreview -> (boolean)
If true, the question data for the HIT will not be shown when a Worker whose Qualifications do not meet this requirement tries to preview the HIT. That is, a Worker's Qualifications must meet all of the requirements for which RequiredToPreview is true in order to preview the HIT. If a Worker meets all of the requirements where RequiredToPreview is true (or if there are no such requirements), but does not meet all of the requirements for the HIT, the Worker will be allowed to preview the HIT's question data, but will not be allowed to accept and complete the HIT. The default is false.HITReviewStatus -> (string)
Indicates the review status of the HIT. Valid Values are NotReviewed | MarkedForReview | ReviewedAppropriate | ReviewedInappropriate.NumberOfAssignmentsPending -> (integer)
The number of assignments for this HIT that are being previewed or have been accepted by Workers, but have not yet been submitted, returned, or abandoned.NumberOfAssignmentsAvailable -> (integer)
The number of assignments for this HIT that are available for Workers to accept.NumberOfAssignmentsCompleted -> (integer)
The number of assignments for this HIT that have been approved or rejected.


How to Change from Gecode 5.1.0 to Gecode 6.0.0
As Gecode 6.0.0 is a major revision, you will have to change programs that are written for Gecode 5.1.0. The big change is that the Boolean argument "share" during cloning is not any longer needed. That means you have to remove the argument from both the definition of and the calls to the following functions, where this applies to pretty much all objects used by Gecode such as spaces, scripts (that means your models), propagators, branchers, variables, views, and so on:
- in constructors used during cloning, and
- in copy functions used during cloning, and
- in update functions used during cloning.


Basic Panel example
HIDE
Basic Panel example
SHOW
Basic Panel example
FADETOGGLE
TOGGLE
Hola
Basic Panel example
SLIDEUP