CLEAR AND PRESENT DANGER A film review by Chris Klecker Copyright 1994 Chris Klecker
Starring Harrison Ford and William Dafoe
"How dare you, sir!" Harrison Ford yells near the end of the film, that has us all screaming, "Yes! Yes! Yes!" After enduring about two hours of watching Jack Ryan getting pushed around like some shopping cart we get to witness Ford's irresistible anger as he lays it all down on the President. Amidst the amount of political garble and CIA research, CLEAR AND PRESENT DANGER delivers yet other tally for the Tom Clancy chalkboard.
CLEAR AND PRESENT DANGER is about a successful drug dealer who orders the death of two senators, one being the President's friend. So now in a fit of rage the President announces that there in a fact a clear and present danger in Columbia and against all drug dealers from Columbia. The book was in fact based in Mexico instead of South America, however it really makes no difference in this movie. After the President makes his speech, he takes $650 million that was issued to them to help stop the drug cartel in Columbia with strict orders not to use any military or troops to fight the war on drugs. Ryan answers back with, "No troops."
So now it gets interesting. With Ryan's word, the President break the promise and uses the money to finance a small army that is under strict cover from any outside sources. William Dafoe's character is an ex-marine and heads the mission personally from Columbia. Dafoe's army conquers a few planes and factories when suddenly a hit on a house become futile. Ryan hears the news and immediately becomes suspicious. Suddenly the army is cut off and now Ryan has to choose what's more important: The elimination of drugs or the truth.
CLEAR AND PRESENT DANGER is far better than PATRIOT GAMES, but not as cunning and resourceful as THE HUNT FOR RED OCTOBER. Nonetheless, Danger gives Ford another notch in his almost perfect movie record. Not only is CLEAR AND PRESENT DANGER interesting, but automatically assumes that the audience is in fact smart enough to know what's going on. Moreover, watching Ford down the President like it was his job was well worth the $6.50.
grade: B+
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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My Project
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#include <worker_posix.h>
Public Attributes | |
| struct nn_mutex | sync |
| struct nn_queue | tasks |
| struct nn_queue_item | stop |
| struct nn_efd | efd |
| struct nn_poller | poller |
| struct nn_poller_hndl | efd_hndl |
| struct nn_timerset | timerset |
| struct nn_thread | thread |
| HANDLE | cp |
| HANDLE nn_worker::cp |
| struct nn_efd nn_worker::efd |
| struct nn_poller_hndl nn_worker::efd_hndl |
| struct nn_poller nn_worker::poller |
| struct nn_queue_item nn_worker::stop |
| struct nn_mutex nn_worker::sync |
| struct nn_queue nn_worker::tasks |
| struct nn_thread nn_worker::thread |
| struct nn_timerset nn_worker::timerset |


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No ad hoc staff missing in Kogi —INEC
by Agency ReportThe Independent National Electoral Commission has said that none of its ad hoc staff is missing in Kogi, where governorship and senatorial elections had held on Saturday.
There had been claims that some ad hoc staff of the commission were abducted to enable politicians rig the election and falsify results; but INEC said the reports were untrue.
Taking to its verified Twitter handle @inecnigeria on Sunday afternoon, INEC had tweeted:


The language of data analysis is the R programming language. It powers the work of people like data scientists, statisticians, social and natural scientists all over the world by allowing them to perform and communicate their data analyses in a principled way.
Throughout this course you’ll learn how to program in R and use the R programming language to make graphics, produce reports and even create interactive web applications. Before you do, you’ll need to get yourself ready by installing:
There are many other guides available for installing R that are just a web search away. One particular favourite is this guide by Kieran Healy from his Data Visualisation book. It is also worth reading the appendix which provides a comprehensive tutorial on how to read R documentation.
You might be asking: so what’s the difference between R and RStudio? Julie Lowndes gives a great answer:
If R were an airplane, RStudio would be the airport, providing many, many supporting services that make it easier for you, the pilot, to take off and go to awesome places. Sure, you can fly an airplane without an airport, but having those runways and supporting infrastructure is a game-changer.
The following provides an overview of how to download, install and get up and running with R and RStudio.
You can download the R language from the Comprehensive R Archive Network or CRAN for short.
On the CRAN website, there are a list of links to download R for different operating systems, for example, Linux, (Mac) OS X and Windows. To download R to your computer, select the link that corresponds to your operating system. You can then install R.
Once you have installed R, you are ready to install RStudio. For this course, the free version of RStudio is suitable. Get RStudio from the RStudio downloads page. Select the ‘Download’ link and then select the installer that corresponds to your operating system.
If you are a Windows user, the CRAN website will redirect you to a page with a list of subdirectories. Select the link called base
.
Please note, the following image is an example only; the version listed on the website may differ.
You will be directed to a new page with a link to download R, for example, Download R 3.6.2 for Windows
. Select the link to download R for Windows.
Once R has finished downloading, open the .exe file and work through the setup prompts. Once the setup is complete, download the latest version of the RStudio executable. Then, open the ‘.exe’ file and work through the setup prompts.
If you are a Mac OS X user, the CRAN website will redirect you to a page with a list of releases. Select the link, for example, R-3.6.2.pkg
to download the latest release.
Please note, the following image is an example only; the version listed on the website may differ.
Once R has finished downloading, open the ‘.pkg’ and then work through the setup prompts. Once the setup is complete, download the latest version of RStudio. Then, open the ‘.dmg’ file and then follow the prompts.
Well done, you’ve installed R and RStudio on your computer. Open RStudio to check that everything has installed correctly and to explore the RStudio interface. The RStudio interface should be divided into four panes:
scripts pane - the place where you write and save your R code.
tab for the console - the place where your code gets run. You can write code directly in here, but you might forget the code you write, so it’s a good idea to write your code in the scripts pane.
tab for Files, Plots, Packages, Help, and a Viewer - files are listed here, just like a ‘Finder’ in Mac OS X or ‘My Computer’ in Windows.
tab for Environment, History and Connections - things you create in R that are a result of code being run, such as data, objects and models are listed in the Environment.
Continue to explore RStudio by making your way through this exercise - using R as a calculator. At the prompt of your console in RStudio, run the following code chunk:
1999 * 2 / 1000
(39 + 13 + 2) / 4
cos(pi)
Store the results of your computation as an object using the left arrow <-
(The shortcut in RStudio is Alt + -).
Again, at the prompt of your console in RStudio, run the following code chunk:
my_variable <- 7 * 8
This is read as my_variable
gets the value of 7*8
. In your RStudio the object called my_variable
should be listed in the Environment pane.
Print the value of my_variable
again by typing my_variable
at the console.
Names of objects are important. You want them to be descriptive, and if you have multiple words in a name you need a way of dealing with that.
The convention we will use in this course is snake_case, where we separate multiple words by an underscore, and use all lower case. The most important thing though is to be consistent with your names.
Names are case sensitive and their spelling matters, otherwise R will not be able to correctly interpret the result.
Try running the following code:
my_Variable
my_varíable
R gives an error for the first line of code because there was an upper case V
instead of a lower case v
. Similarly, the second is an error because there was an accented i
instead of an unaccented i
.
Most computations are performed by using functions. Functions take some input (arguments) and return an output. As an example, let’s use R’s built-in random number generator function runif()
to generate 10 random numbers between 0 and 1.
If you type the number 10 as the first argument you will get 10 random numbers between 0 and 1.
runif(10)
#> [1] 0.29614707 0.32769903 0.87429311 0.61414034 0.07141809 0.46152141
#> [7] 0.19531762 0.09259858 0.12866640 0.01490003
If you type runif()
in the RStudio console and then press TAB on your keyboard, a floating tooltip will appear that contains the names of the inputs to the function.
You can be more explicit by specifying each input:
runif(n = 10, min = 0, max = 1)
#> [1] 0.4047332 0.5594455 0.2644337 0.2554977 0.2643289 0.7931630 0.3091934
#> [8] 0.3777057 0.5361418 0.4788223
By changing the values of the arguments, we can finally generate our numbers between 0 and 10.
runif(10, min = 0, max = 10)
#> [1] 3.247854 6.602838 5.587097 6.730972 9.619522 2.864200 4.059660 9.238728
#> [9] 9.546601 3.739686
And you can save the result to an object using the <-
operator.
y <- runif(10, min = 0, max = 10)
y
#> [1] 3.7441952 9.0954289 6.1879159 2.6384848 7.8668463 0.3675443 7.5540640
#> [8] 3.2578185 5.9189878 6.2539780
So far, you’ve explored the basics of using R as a calculator and creating objects and calling functions.
Consider expanding your R vocabulary by using the following functions to compute the mean using the mean()
function, the variance using the var()
function, and the range using the range()
function of the object y
you just created. Again, you can do this from the Console.
Remember, if you are not sure how to use the function, type the name of it in the console and press TAB on your keyboard.
set.seed
by typing a question mark in front of it at the console: ?set.seed
. If you need help understanding this read over this document.When working on a new project, it is possible for your files to be spread out and stored in different locations across your computer.
This can create problems, particularly when you are programming because knowing exactly where your files are is really important. When they are spread out, this makes extra work for yourself.
Storing files in folders, and folders in a ‘filing cabinet’ helps centralise your work: it keeps it organised so it is easier to find.
Using RStudio projects is like providing a filing cabinet for your work! Using them centralises your work, making your life easier as you do not have to manage where files are. For each project, you need to create one RStudio project.
Make your way through the following steps to create an RStudio project on your computer for all the work that you’ll do in this course.
On your computer, open RStudio. Then, select ‘File’ > ‘New Project’.
A pop-up window labelled ‘New Project’ should be displayed in RStudio. From the pop-up window, select ‘New directory’.
You’re creating a new project, so select ‘New project’.
Enter the name of the directory you want to create. It would be a good idea to name it by the course you are taking, like “intro_datascience”.
Select ‘Create project’ once you’ve named your directory.
Your RStudio will have a projects tab on the upper right hand corner. Remember, every time you start to work on something for this course, be sure to open this project!
Whenever you are ready to write code for the course go to your project folder and then select the ‘.Rproj’ file. This will automatically open RStudio and take you to the right directory!
Packages are the way R users share useful code. You can think of each R package as a book. Once you’ve installed a package, you can load the code contained in it using library
- which is like checking out a book from the library!
There are more than 14,000 packages available on CRAN contributed by a range of R users, from experts to those relatively new to R. There are another thousand or so on the Bioconductor archive, which focuses primarily on bioinformatics applications. There are many more on people’s Github pages that may be in development. For example: Earo Wang’s mists
package
As an example, you can install the rmarkdown
package for making reproducible reports using the following code chunk:
install.packages("rmarkdown")
Continue to develop your skills in RStudio by making your way through this exercise. Follow the instructions specified in ‘Creating a new RStudio project’ to create another RStudio project that will contain all your materials as you work through this course.
Then, use the console to install the tidyverse
and visdat
packages. You’ll use these packages throughout the course to read, visualise and analyse data.
After you’ve installed the packages, run library(tidyverse)
at the console, then, run the following code chunk:
glimpse(diamonds)
filter(diamonds, carat <= 2.5)
library(tidyverse)
at the console?tidyverse
?


In this demo you will go through the steps required to build the web front end portion of GeekQuiz, focusing on the single page application interaction using Angular 2, and the CSS3 flip animation.
In this demo, you will see how to:
Follow these steps to setup your environment for the demo.
If you don't have one, create a user account for the application. To do that, press F5, click Register and provide the information required. After that, close the browser window.
Note: Remember the information you provided as you will be using it during the demo.
In Visual Studio, close all open files.
This demo is composed of the following segments:
Press CTRL + , and search for "_Layout.cshtml" (without the quotes).
Opening the layout file
Press Enter. The "_Layout.cshtml" file is opened in the editor.
Add the following code inside the <environment names="Development">
tag located inside the head
tag.

Add the following code inside the <environment names="Staging,Production">
tag located inside the head
tag.

Updating the layout file to include the new dependencies
Now, press CTRL + , again and search for "index.cshtml" (without the quotes).
Opening the index view
Press Enter. The Index.cshtml file is opened in the editor.
Add the following code at the bottom of the file. This code will be used as the root of the SPA application.

<geekquiz-app>Loading...</geekquiz-app>

Add the following code snippet at the bottom of the file. This code will include the app.js file that will be created during the next steps.
@section Scripts {

}
Right-click the js folder located under wwwroot and select New Item... under Add.
Creating a new item
Select TypeScript File under the DNX | Client-Side menu, change the name to app.ts and click Add.
Adding a new TypeScript file
Add the following code in the app.ts file you just created.
import {bootstrap, Component, View, NgFor, NgClass, AfterViewInit, Inject} from 'angular2/angular2';
import {Http, HTTP_BINDINGS, Headers} from 'angular2/http';
@Component({
selector: 'geekquiz-app',
viewBindings: [HTTP_BINDINGS]
})
class AppComponent implements AfterViewInit {
public answered = false;
public title = "loading question...";
public options = [];
public correctAnswer = false;
public working = false;
constructor( @Inject(Http) private http: Http) {
}
answer() {
return this.correctAnswer ? 'correct' : 'incorrect';
}
nextQuestion() {
this.working = true;
this.answered = false;
this.title = "loading question...";
this.options = [];
var headers = new Headers();
headers.append('If-Modified-Since', 'Mon, 27 Mar 1972 00:00:00 GMT');
this.http.get("/api/trivia", { headers: headers })
.map(res => res.json())
.subscribe(
question => {
this.options = question.options;
this.title = question.title;
this.answered = false;
this.working = false;
},
err => {
this.title = "Oops... something went wrong";
this.working = false;
});
}
sendAnswer(option) {
this.working = true;
var answer = { 'questionId': option.questionId, 'optionId': option.id };
var headers = new Headers();
headers.append('Content-Type', 'application/json');
this.http.post('/api/trivia', JSON.stringify(answer), { headers: headers })
.map(res => res.json())
.subscribe(
answerIsCorrect => {
this.answered = true;
this.correctAnswer = (answerIsCorrect === true);
this.working = false;
},
err => {
this.title = "Oops... something went wrong";
this.working = false;
});
}
afterViewInit() {
this.nextQuestion();
}
}
bootstrap(AppComponent);
Add the following View decorator to the AppComponent class below the Component decorator.
@View({
directives: [NgFor, NgClass],
template: `

{{title}}

<button class="btn btn-info btn-lg option" *ng-for="#option of options" [disabled]="working">{{option.title}}</button>

`
})
Save the changes and show that Visual Studio compiles the TypeScript files generating JavaScript code.
![Showing the generated code](images/showing-the-generated-code.png?raw=true "Showing the generated code")
_Showing the generated code_
Press F5.
Note: If the Log in page is displayed, provide the credentials you created during the setup steps.
As shown in the following figure, the buttons will be displayed. Click any of the buttons. Nothing will happen.
Showing the app running
Dock the Visual Studio window to the left, and the browser window to the right.
Docking the windows
In Visual Studio, press CTRL + , again and search for "flip.css" (without the quotes).
Opening the flip.css file
Press Enter. The flip.css file is opened in the editor.
Show the flip.css file.
Go back to the app.ts file, add the (click)="sendAnswer(option)"
to the <button>
element inside the each loop. The resulting <button>
element is the one from the following code snippet.
<button class="btn btn-info btn-lg option" *ng-for="#option of options" (click)="sendAnswer(option)" [disabled]="working">{{option.title}}</button>
Add the following code snippet as the first child of

and save the changes.

{{answer()}}

<button class="btn btn-info btn-lg next option" (click)="nextQuestion()" [disabled]="working">Next Question</button>

Click Refresh Browser Link.
Refreshing the Browser using Browser Link
In the web browser, click any of the buttons. The flip animation will take place and the result (correct/incorrect) will be displayed.
Showing the flip animation
By completing this demo you should have:


<EMAIL_ADDRESS>Online documentation generator
URL to a public GIT project:
Branch
Browse the docs
Notes
Early release (alpha)
Supported repositories:
GIT only
Supported protocols:
http and https
Doc generator:
doxygen
Generated formats:
html only
What's new
1.11.2018
Alpha version has been release
More...
Configration and customization
FAQ
Pricing and plans
Rules and policies
Contact and support


--- layout: default title: Home ---
Hey there! My name is Vishwaa Sofat and I am a recent graduate from Stuyvesant High School and an incoming
first year at the University of Califonia, Berkeley, where I intend on double majoring in Computer Science
and Political Science. I hope to combine my interests in both areas to address the issue of
healthcare inequities and grow the work of my non-profit,
Direct Health Access.
Throughout high school, I have been actively involved in student government—most recently in my capacity as
Student Union President. I have also been a leader for the Model United Nations and Varsity Cricket
teams. I also write poetry in my free time!
I hope to continue pursuing these passions in college.
I have previously worked on Capitol Hill and advised Congressional representatives, local officials, and the Chancellor
of the NYC Department of Education. I have also had the opportunity to engage in a mentorship program
at Google NYC and pursue personal projects to further my full-stack software development and product management experience.
I am currently looking for an internship for Summer 2020, particularly in web/software development and politics/public policy. If you
think I would be a good fit, please reach out.


GROBID-Dictionaries
About
Dictionary services
Bibliography services
Admin
Doc
|
This is an open source project available on GitHub under Apache 2 License. Contact: Mohamed Khemakhem. For documentation and link to the Javadoc, please visit the Grobid Wiki pages. |


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cf.Field.bin¶
-
Field.
bin
(method, digitized, weights=None, measure=False, scale=None, mtol=1, ddof=1, radius='earth', great_circle=False, return_indices=False, verbose=None)[source]¶ Collapse the data values that lie in N-dimensional bins.
The data values of the field construct are binned according to how they correspond to the N-dimensional histogram bins of another set of variables (see
cf.histogram
for details), and each bin of values is collapsed with one of the collapse methods allowed by the method parameter.The number of dimensions of the output binned data is equal to the number of field constructs provided by the digitized argument. Each such field construct defines a sequence of bins and provides indices to the bins that each value of another field construct belongs. There is no upper limit to the number of dimensions of the output binned data.
The output bins are defined by the exterior product of the one-dimensional bins of each digitized field construct. For example, if only one digitized field construct is provided then the output bins simply comprise its one-dimensional bins; if there are two digitized field constructs then the output bins comprise the two-dimensional matrix formed by all possible combinations of the two sets of one-dimensional bins; etc.
An output value for a bin is formed by collapsing (using the method given by the method parameter) the elements of the data for which the corresponding locations in the digitized field constructs, taken together, index that bin. Note that it may be the case that not all output bins are indexed by the digitized field constructs, and for these bins missing data is returned.
The returned field construct will have a domain axis construct for each dimension of the output bins, with a corresponding dimension coordinate construct that defines the bin boundaries.
New in version 3.0.2.
See also
- Parameters
- method:
str
The collapse method used to combine values that map to each cell of the output field construct. The following methods are available (see https://ncas-cms.github.io/cf-python/analysis.html#collapse-methods for precise definitions):
method
Description
Weighted
'maximum'
The maximum of the values.
Never
'minimum'
The minimum of the values.
Never
'maximum_absolute_value'
The maximum of the absolute values.
Never
'minimum_absolute_value'
The minimum of the absolute values.
Never
'mid_range'
The average of the maximum and the minimum of the values.
Never
'range'
The absolute difference between the maximum and the minimum of the values.
Never
'median'
The median of the values.
Never
'sum'
The sum of the values.
Never
'sum_of_squares'
The sum of the squares of values.
Never
'sample_size'
The sample size, i.e. the number of non-missing values.
Never
'sum_of_weights'
The sum of weights, as would be used for other calculations.
Never
'sum_of_weights2'
The sum of squares of weights, as would be used for other calculations.
Never
'mean'
The weighted or unweighted mean of the values.
May be
'mean_absolute_value'
The mean of the absolute values.
May be
'mean_of_upper_decile'
The mean of the upper group of data values defined by the upper tenth of their distribution.
May be
'variance'
The weighted or unweighted variance of the values, with a given number of degrees of freedom.
May be
'standard_deviation'
The square root of the weighted or unweighted variance.
May be
'root_mean_square'
The square root of the weighted or unweighted mean of the squares of the values.
May be
'integral'
The integral of values.
Always
Collapse methods that are “Never” weighted ignore the weights parameter, even if it is set.
Collapse methods that “May be” weighted will only be weighted if the weights parameter is set.
Collapse methods that are “Always” weighted require the weights parameter to be set.
- digitized: (sequence of)
Field
One or more field constructs that contain digitized data with corresponding metadata, as would be output by
cf.Field.digitize
. Each field construct contains indices to the one-dimensional bins to which each value of an original field construct belongs; and there must bebin_count
andbin_bounds
properties as defined by thedigitize
method (and any of the extra properties defined by that method are also recommended).The bins defined by the
bin_count
andbin_bounds
properties are used to create a dimension coordinate construct for the output field construct.Each digitized field construct must be transformable so that it is broadcastable to the input field construct’s data. This is done by using the metadata constructs of the to create a mapping of physically compatible dimensions between the fields, and then manipulating the dimensions of the digitized field construct’s data to ensure that broadcasting can occur.
- weights: optional
Specify the weights for the collapse calculations. The weights are those that would be returned by this call of the field construct’s
weights
method:f.weights(weights, measure=measure, scale=scale, radius=radius, great_circle=great_circle, components=True)
. See the measure, *scale, radius and great_circle parameters andcf.Field.weights
for details.Note
By default weights is
None
, resulting in unweighted calculations.Note
Setting weights to
True
is generally a good way to ensure that all collapses are appropriately weighted according to the field construct’s metadata. In this case, if it is not possible to create weights for any axis then an exception will be raised.However, care needs to be taken if weights is
True
when cell volume weights are desired. The volume weights will be taken from a “volume” cell measure construct if one exists, otherwise the cell volumes will be calculated as being proportional to the sizes of one-dimensional vertical coordinate cells. In the latter case if the vertical dimension coordinates do not define the actual height or depth thickness of every cell in the domain then the weights will be incorrect.If weights is the boolean
True
then weights are calculated for all of the domain axis constructs.- Parameter example:
To specify weights based on the field construct’s metadata for all axes use
weights=True
.- Parameter example:
To specify weights based on cell areas, leaving all other axes unweighted, use
weights='area'
.- Parameter example:
To specify weights based on cell areas and linearly in time, leaving all other axes unweighted, you could set
weights=('area', 'T')
.
- measure:
bool
, optional Create weights, as defined by the weights parameter, which are cell measures, i.e. which describe actual cell sizes (e.g. cell areas) with appropriate units (e.g. metres squared). By default the weights are scaled to lie between 0 and 1 and have arbitrary units (see the scale parameter).
Cell measures can be created for any combination of axes. For example, cell measures for a time axis are the time span for each cell with canonical units of seconds; cell measures for the combination of four axes representing time and three dimensional space could have canonical units of metres cubed seconds.
When collapsing with the
'integral'
method, measure must be True, and the units of the weights are incorporated into the units of the returned field construct.Note
Specifying cell volume weights via
weights=['X', 'Y', 'Z']
orweights=['area', 'Z']
(or other equivalents) will produce an incorrect result if the vertical dimension coordinates do not define the actual height or depth thickness of every cell in the domain. In this case,weights='volume'
should be used instead, which requires the field construct to have a “volume” cell measure construct.If
weights=True
then care also needs to be taken, as a “volume” cell measure construct will be used if present, otherwise the cell volumes will be calculated using the size of the vertical coordinate cells.- scale: number, optional
If set to a positive number then scale the weights, as defined by the weights parameter, so that they are less than or equal to that number. By default the weights are scaled to lie between 0 and 1 (i.e. scale is 1).
- Parameter example:
To scale all weights so that they lie between 0 and 0.5:
scale=0.5
.
- mtol: number, optional
Set the fraction of input data elements which is allowed to contain missing data when contributing to an individual output data element. Where this fraction exceeds mtol, missing data is returned. The default is 1, meaning that a missing datum in the output array occurs when its contributing input array elements are all missing data. A value of 0 means that a missing datum in the output array occurs whenever any of its contributing input array elements are missing data. Any intermediate value is permitted.
- Parameter example:
To ensure that an output array element is a missing datum if more than 25% of its input array elements are missing data:
mtol=0.25
.
- ddof: number, optional
The delta degrees of freedom in the calculation of a standard deviation or variance. The number of degrees of freedom used in the calculation is (N-ddof) where N represents the number of non-missing elements contributing to the calculation. By default ddof is 1, meaning the standard deviation and variance of the population is estimated according to the usual formula with (N-1) in the denominator to avoid the bias caused by the use of the sample mean (Bessel’s correction).
- radius: optional
Specify the radius used for calculating the areas of cells defined in spherical polar coordinates. The radius is that which would be returned by this call of the field construct’s
radius
method:f.radius(radius)
. See thecf.Field.radius
for details.By default radius is
'earth'
which means that if and only if the radius can not found from the datums of any coordinate reference constructs, then the default radius taken as 6371229 metres.- great_circle:
bool
, optional If True then allow, if required, the derivation of i) area weights from polygon geometry cells by assuming that each cell part is a spherical polygon composed of great circle segments; and ii) and the derivation of line-length weights from line geometry cells by assuming that each line part is composed of great circle segments.
New in version 3.2.0.
- verbose:
int
orstr
orNone
, optional If an integer from
-1
to3
, or an equivalent string equal ignoring case to one of:'DISABLE'
(0
)'WARNING'
(1
)'INFO'
(2
)'DETAIL'
(3
)'DEBUG'
(-1
)
set for the duration of the method call only as the minimum cut-off for the verboseness level of displayed output (log) messages, regardless of the globally-configured
cf.log_level
. Note that increasing numerical value corresponds to increasing verbosity, with the exception of-1
as a special case of maximal and extreme verbosity.Otherwise, if
None
(the default value), output messages will be shown according to the value of thecf.log_level
setting.Overall, the higher a non-negative integer or equivalent string that is set (up to a maximum of
3
/'DETAIL'
) for increasing verbosity, the more description that is printed to convey information about the operation.
- method:
- Returns
Field
The field construct containing the binned values.
Examples
Find the range of values that lie in each bin:
>>> print(q) Field: specific_humidity (ncvar%q) ---------------------------------- Data : specific_humidity(latitude(5), longitude(8)) 0.001 1 Cell methods : area: mean Dimension coords: latitude(5) = [-75.0, ..., 75.0] degrees_north : longitude(8) = [22.5, ..., 337.5] degrees_east : time(1) = [2019-01-01 00:00:00] >>> print(q.array) [[ 7. 34. 3. 14. 18. 37. 24. 29.] [ 23. 36. 45. 62. 46. 73. 6. 66.] [110. 131. 124. 146. 87. 103. 57. 11.] [ 29. 59. 39. 70. 58. 72. 9. 17.] [ 6. 36. 19. 35. 18. 37. 34. 13.]] >>> indices = q.digitize(10) >>> b = q.bin('range', digitized=indices) >>> print(b) Field: specific_humidity ------------------------ Data : specific_humidity(specific_humidity(10)) 0.001 1 Cell methods : latitude: longitude: range Dimension coords: specific_humidity(10) = [10.15, ...,<PHONE_NUMBER>0000002] 0.001 1 >>> print(b.array) [14. 11. 11. 13. 11. 0. 0. 0. 7. 0.]
Find various metrics describing how
tendency_of_sea_water_potential_temperature_expressed_as_heat_content
data varies withsea_water_potential_temperature
andsea_water_salinity
:>>> t Field: sea_water_potential_temperature (ncvar%sea_water_potential_temperature) ------------------------------------------------------------------------------ Data : sea_water_potential_temperature(time(1), depth(1), latitude(5), longitude(8)) K Cell methods : area: mean time(1): mean Dimension coords: time(1) = [2290-06-01 00:00:00] 360_day : depth(1) = [3961.89990234375] m : latitude(5) = [-1.875, ..., 3.125] degrees_north : longitude(8) = [75.0, ..., 83.75] degrees_east Auxiliary coords: model_level_number(depth(1)) = [18] >>> s Field: sea_water_salinity (ncvar%sea_water_salinity) ---------------------------------------------------- Data : sea_water_salinity(time(1), depth(1), latitude(5), longitude(8)) psu Cell methods : area: mean time(1): mean Dimension coords: time(1) = [2290-06-01 00:00:00] 360_day : depth(1) = [3961.89990234375] m : latitude(5) = [-1.875, ..., 3.125] degrees_north : longitude(8) = [75.0, ..., 83.75] degrees_east Auxiliary coords: model_level_number(depth(1)) = [18] >>> x Field: tendency_of_sea_water_potential_temperature_expressed_as_heat_content (ncvar%tend) ----------------------------------------------------------------------------------------- Data : tendency_of_sea_water_potential_temperature_expressed_as_heat_content(time(1), depth(1), latitude(5), longitude(8)) W m-2 Cell methods : area: mean time(1): mean Dimension coords: time(1) = [2290-06-01 00:00:00] 360_day : depth(1) = [3961.89990234375] m : latitude(5) = [-1.875, ..., 3.125] degrees_north : longitude(8) = [75.0, ..., 83.75] degrees_east Auxiliary coords: model_level_number(depth(1)) = [18] >>> print(x.array) [[[[-209.72 340.86 94.75 154.21 38.54 -262.75 158.22 154.58] [ 311.67 245.91 -168.16 47.61 -219.66 -270.33 226.1 52.0 ] [ -- -112.34 271.67 189.22 9.92 232.39 221.17 206.0 ] [ -- -- -92.31 -285.57 161.55 195.89 -258.29 8.35] [ -- -- -7.82 -299.79 342.32 -169.38 254.5 -75.4 ]]]]
>>> t_indices = t.digitize(6) >>> s_indices = s.digitize(4)
>>> n = x.bin('sample_size', [t_indices, s_indices]) >>> print(n) Field: number_of_observations ----------------------------- Data : number_of_observations(sea_water_salinity(4), sea_water_potential_temperature(6)) 1 Cell methods : latitude: longitude: point Dimension coords: sea_water_salinity(4) = [6.3054151982069016, ..., 39.09366758167744] psu : sea_water_potential_temperature(6) = [278.1569468180338, ...,<PHONE_NUMBER>5149743] K >>> print(n.array) [[ 1 2 2 2 -- 2] [ 2 1 3 3 3 2] [-- -- 3 -- 1 --] [ 1 -- 1 3 2 1]]
>>> m = x.bin('mean', [t_indices, s_indices], weights=['X', 'Y', 'Z', 'T']) >>> print(m) Field: tendency_of_sea_water_potential_temperature_expressed_as_heat_content ---------------------------------------------------------------------------- Data : tendency_of_sea_water_potential_temperature_expressed_as_heat_content(sea_water_salinity(4), sea_water_potential_temperature(6)) W m-2 Cell methods : latitude: longitude: mean Dimension coords: sea_water_salinity(4) = [6.3054151982069016, ..., 39.09366758167744] psu : sea_water_potential_temperature(6) = [278.1569468180338, ...,<PHONE_NUMBER>5149743] K >>> print(m.array) [[ 189.22 131.36 6.75 -41.61 -- 100.04] [-116.73 232.38 -4.82 180.47 134.25 -189.55] [ -- -- 180.69 -- 47.61 --] [158.22 -- -262.75 64.12 -51.83 -219.66]]
>>> i = x.bin( ... 'integral', [t_indices, s_indices], ... weights=['X', 'Y', 'Z', 'T'], measure=True ... ) >>> print(i) Field: long_name=integral of tendency_of_sea_water_potential_temperature_expressed_as_heat_content -------------------------------------------------------------------------------------------------- Data : long_name=integral of tendency_of_sea_water_potential_temperature_expressed_as_heat_content(sea_water_salinity(4), sea_water_potential_temperature(6)) 86400 m3.kg.s-2 Cell methods : latitude: longitude: sum Dimension coords: sea_water_salinity(4) = [6.3054151982069016, ..., 39.09366758167744] psu : sea_water_potential_temperature(6) = [278.1569468180338, ...,<PHONE_NUMBER>5149743] K >>> print(i.array) [[<PHONE_NUMBER>400.0<PHONE_NUMBER>776.0<PHONE_NUMBER>20.0 -1605439586304.0 --<PHONE_NUMBER>472.0] [-4509735059456.0<PHONE_NUMBER>232.0 -280126521344.0<PHONE_NUMBER>7648.0<PHONE_NUMBER>280.0 -7317268463616.0] [ -- --<PHONE_NUMBER>3312.0 --<PHONE_NUMBER>60.0 --] [<PHONE_NUMBER>952.0 -- -5073676009472.0<PHONE_NUMBER>152.0 -2000787079168.0 -4243632160768.0]]
>>> w = x.bin('sum_of_weights', [t_indices, s_indices], weights=['X', 'Y', 'Z', 'T'], measure=True) Field: long_name=sum_of_weights of tendency_of_sea_water_potential_temperature_expressed_as_heat_content -------------------------------------------------------------------------------------------------------- Data : long_name=sum_of_weights of tendency_of_sea_water_potential_temperature_expressed_as_heat_content(sea_water_salinity(4), sea_water_potential_temperature(6)) 86400 m3.s Cell methods : latitude: longitude: sum Dimension coords: sea_water_salinity(4) = [7.789749830961227, ..., 36.9842486679554] psu : sea_water_potential_temperature(6) = [274.50717671712243, ...,<PHONE_NUMBER>594401] K >>> print(w.array) [[19319093248.0<PHONE_NUMBER>8.0<PHONE_NUMBER>6.0<PHONE_NUMBER>4.0 --<PHONE_NUMBER>6.0] [38628990976.0<PHONE_NUMBER>8.0<PHONE_NUMBER>2.0<PHONE_NUMBER>8.0<PHONE_NUMBER>2.0<PHONE_NUMBER>8.0] [ -- --<PHONE_NUMBER>2.0 --<PHONE_NUMBER>8.0 --] [19309897728.0 --<PHONE_NUMBER>8.0<PHONE_NUMBER>2.0<PHONE_NUMBER>8.0<PHONE_NUMBER>8.0]]
Demonstrate that the integral divided by the sum of the cell measures is equal to the mean:
>>> print(i/w) Field: ------- Data : (sea_water_salinity(4), sea_water_potential_temperature(6)) kg.s-3 Cell methods : latitude: longitude: sum Dimension coords: sea_water_salinity(4) = [7.789749830961227, ..., 36.9842486679554] psu : sea_water_potential_temperature(6) = [274.50717671712243, ...,<PHONE_NUMBER>594401] K >>> (i/w == m).all() True


Sonic Cube(s)
The sonic cube is an IoT device developed with the intention of providing to users and performers a playful and engaging way to interact with sounds.
The object is a padded fabric cube with the particular property of sending MIDI notes what thrown or held. The surface of the device is made out of felt, and it’s embroidered with a pattern of conductive thread that works as a capacitive sensor that allows the device to sense when the user it’s holding it. Inside the device there’s an accelerometer that can detect the movements of the cube.
The cubes are also equipped with a set of 2 LEDs that provide a visual feedback foe the user. The core of the device is an esp32 micro controller that is able to process the input provided by the sensors and send it to a computer through a BLE connection
This project it’s been developed within the course “SENSOR LAB 2.0 – Laboratorio didattico di Iot E Coding” provided by Area Science Park
You can find some work in progress pictures here
A special thanks goes to Seeedstudio, that provided excellent quality PCB / PCBA service in the development and the production of this project


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ã
XT
v
The
New
York
copyright
reserved
Botanical
Garden
YO
t?
isiEW
botanical
gardeN
FLORA
NEOTROPICA
Sideroxylon
americanum
(Miller)
Penn
T.D.PENNINGTON
1986
PLANTS
OF
BAHAMA
ISLANDS
Bumelia
glomerata
Griseb.
Great
Abacos
in
coppice
about
2È5
miles
northwest
of
Hole-in-the-wall,
Shrub
2.5
m
tall,
very
thorny.
March
12,
1975
d.
s.Corren
&
F.G.Meyer
44576
Herbarium
FAIRCHILD
TROPICAL
GARDEN
NEW
YORK
BOTANICAL
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01443262
01443262
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


void mtrace(void);
The muntrace() function disables the hook functions installed by mtrace(), so that tracing information is no longer recorded for the memory-allocation functions. If no hook functions were successfully installed by mtrace(), muntrace() does nothing.
When mtrace() is called, it checks the value of the environment variable MALLOC_TRACE, which should contain the pathname of a file in which the tracing information is to be recorded. If the pathname is successfully opened, it is truncated to zero length.
If MALLOC_TRACE is not set, or the pathname it specifies is invalid or not writable, then no hook functions are installed, and mtrace() has no effect. In set-user-ID and set-group-ID programs, MALLOC_TRACE is ignored, and mtrace() has no effect.
The tracing output produced after a call to mtrace() is textual, but not designed to be human readable. The GNU C library provides a Perl script, mtrace(1), that interprets the trace log and produces human-readable output. For best results, the traced program should be compiled with debugging enabled, so that line-number information is recorded in the executable.
The tracing performed by mtrace() incurs a performance penalty (if MALLOC_TRACE points to a valid, writable pathname).
$ cat t_mtrace.c #include <mcheck.h> #include <stdlib.h> #include <stdio.h> int main(int argc, char *argv[]) { int j; mtrace(); for (j = 0; j < 2; j++) malloc(100); /* Never freed--a memory leak */ calloc(16, 16); /* Never freed--a memory leak */ exit(EXIT_SUCCESS); }When we run the program as follows, we see that mtrace() diagnosed memory leaks at two different locations in the program:
$ cc -g t_mtrace.c -o t_mtrace $ export MALLOC_TRACE=/tmp/t $ ./t_mtrace $ mtrace ./t_mtrace $MALLOC_TRACE Memory not freed: ----------------- Address Size Caller 0x084c9378 0x64 at /home/cecilia/t_mtrace.c:12 0x084c93e0 0x64 at /home/cecilia/t_mtrace.c:12 0x084c9448 0x100 at /home/cecilia/t_mtrace.c:16
The first two messages about unfreed memory correspond to the two malloc(3) calls inside the for loop. The final message corresponds to the call to calloc(3) (which in turn calls malloc(3)).


Mustang Mach E Specs Leaked Ahead of LA Auto Show Reveal
by Tim HealeyYour humble editor made a beeline for In N’ Out Burger upon landing at LAX, as Midwesterners are wont to do, and while I munched on my meal, I discovered via the Twitterverse that the details of the Ford Mustang Mach E, which I am about to see up close tomorrow, were leaked. Spoiled, like a Hollywood movie on Reddit.
Ford flew media out to the Los Angeles Auto Show early so that we could spend time with the Mach E, all for some enterprising forum user to leak the info before showtime.
To be fair, the specs could be inaccurate, or could change. But here’s what hit the Web earlier tonight, thanks to the Mach E Forum.
There are five trim levels: Select ($43,895), Premium ($50,600), California Route 1 ($52,400), First Edition (limited edition, $59,900), and GT ($60,500). Those prices don’t include destination or the federal EV tax credit of $7,500.
Buyers will be able to get rear- or all-wheel drive, and the GT is slated to run 0-60 in the mid-three-second range.
First Editions should have a range of 270 miles, while the GT and Select will be around 230, with the rest being around 300.
Other nuggets include the ability to add 47 miles of range in 10 minutes of charge time and two large interior digital displays, including a center-stack tablet that looks much like what Tesla offers.
Ford’s CoPilot360 2.0 and CoPilot360 Assist 2.0 driver-aid systems appear to be standard.
Check back with us throughout the weekend for more information on Ford’s newest Mustang.


Scrolling Text Demo
This little demo is designed to provide a quick overview of some of the capabilities of the scrolling text function.
As you will the content is not just limited to text but can in fact contain any HTML content including images hyper links etc.
Very Easy to Use
We have created a Visual Configurator Tool which makes it very easy for anyone to add scrolling functionality to any web page. No knowledge of HTML, JavaScript, CSS or any other programming code is required. Everything is done by selecting options and copy and paste operations.
It is entirely possible to add a scrolling box within minutes.


Alex Farris has been playing guitar since he was 7 years old.
Since then, he has found his passion for drums, bass, piano, singing,
and anything else he can get his hands on. Over the years,
Alex has played in many bands from originals to covers of 80’s and 90’s rock n’ roll.
He has composed music for independent rap artists around the Sacramento
area and for independent filmmakers.
Along the way, he has found his biggest passion to be in acting.
Performing in pieces ranging from commercials to feature films.
Grateful for the ability to follow his dreams and pursue his passions,
Alex works hard every day and strives to be the best he can be,
hoping his art will bring as much emotion to others as it has to him.
To get a hold of Alex feel free to email or call.
Thank you.
<EMAIL_ADDRESS>916-410-0424


Me and a friend nicknamed Duck decided to do Yopo on a night after some jamming. Duck usually snorts alot of speed and occasionally cocaine and I wanted to show him what responsible, consciousness expanding, visionary drugs are like.
Preparation:
-----------------
I took about a handful of Yopo seeds and roasted them in a frying pan until the shells were dry enough to peel off. I peeled off the shells and ground up the seed's flesh using mortar & pestle. Through this powdered seed material I added about half a teaspoon of powdered Lime (Calcium hydroxide) A.K.A. 'Chuna' in asian health-food stores. The Yopo/Lime ratio was about 9:1 eyeballed. I've insufflated Yopo twice before, but I did it right after mixing the Lime with the ground Yopo. Recently I read on Wikipedia that in order for Yopo to reach it's full potential it must be properly prepared. Apparently Native American Indians prepared Yopo in a specific way so this is exactly what I did.
I added the Lime to the Yopo, added a tiny bit of water to the mass, just enough to make it breaddough-like, and then kneaded into a ball for serveral minutes. This way all Lime and Yopo alkaloids come into contact and react by turning all present 5-OH-DMT(Bufotenine) into 5CaO-DMT(Bufotenate) which has a far greater ability to cross the blood-brain barrier, minimizing physical effects and optimizing psychological effects. Also any present NN,DMT and 5-MeO-DMT are converted into freebase form.
After kneading it for a while I put the Yopo ball in a small custard-bowl and pressed it into a very thin, flat Yopo-pancake on the bottom of the bowl. I placed this bowl on top of a cup of hot tea I made so the Yopo in the bowl would be gently heated from below and the water evaporated quickly. We let it sit there for about 20 minutes and it was completely dry. My friend Duck chopped it all up until there were no lumps left and it was fine as dust.
Dosage:
-----------------
I made a heck of alot of 'lime-treated' Yopo snuff so we just put it all on a mirror tile and split the heap in 2. Out of these 2 separated heaps we shaped them into 2 Yopo-lines that were for about 4 to 4,5 seeds worth per line. The remaining Yopo was put into an empty weed bag.
Set & Setting:
-----------------
My rather large bedroom with dimmed lights. We sat down on a chill-out mattress with lots of pillows and soft blankets on it, layed back, with 2 buckets within easy reach of us. The night before I had done LSD. Half of 1 Hoffman-blotter which are extra strong 'cause they're double dipped. I was still in the gentle afterglow of acid. Initially I was a little nervous, but I took some time to clear my mind of any emotions and thoughts and managed to calm myself down completely till I was ready. I knew it was going to be rough. We were ready to go and Duck gave me the snorting-tube and held the Mirror-tile under my nose.
The Experience:
-----------------
T= 00:00
I snort one of the two lines. Nearly got all of it down my nose, but left a tiny tiny bit. It must have been about 4 seeds altogether. Quite immediately Duck followed me and snorted his line. We both sat back and I felt the physical precursing Yopo feeling in my body immediately. A sort of tension in all of my flesh and muscles. As this physical rush steadily increased I fell into a sort of hypnotic stupor. The cramps increased and now suddenly strange waves of tingling energy flushed all through my body. Like the tingling you feel when you've slept on your arm, but then without the numbness and all over the body.
T= 00:04
The physical feeling had taken a hold of me and in this stuporlike state I sat staring at a wall of my room. Suddenly I noticed seeing lots of colorful, bright, transparent planes moving rapidly across the space between me and the wall. I tell my friend I'm seeing things now and he replies by saying he still feels nothing accept a nose on fire. I told him: 'Don't worry, you wait.' Soon I start feeling sick to the stomach very suddenly. I reach for my bucket and start puking. Right now visions of other worlds with the strangest, brightest colors are shooting into my eyes at supersonic speed. Flickering. Like a stroboscope but one that shoots visions of completely other worlds into my eyesight every other millisecond.
I puked about 5 times and my friend started puking too. I had to take a leak so I went downstairs to the bathroom taking my bucket with me. When I was sitting on the toilet I puked some more.  The Yopo had taken it's effect so I decided to snort all yopo out of my nose. I did that and had to gag 3 more times. All along visions were extreme, but they were still busy growing steadier and more coherent.
T= 00:15
I was now laying back, feeling that the nausea had subsided as suddenly as it came on, and I felt very euphoric and serene. The visions with my eyes opened were so intense and realistic. With my eyes closed I observed intricate colorswirls and patterns moving with the speed of ADHD, It was very busy and active 'in there'.
I would look to the left of the mattress and see a bent leg as if it was from a sitting man. His pants were chique white pants and he wore dark brown, leather 'business-class' shoes. The leg would stay there for a while and sometimes the foot would switch my way and back. Constantly I saw brightly colored figures walking around me. Not like in front of me, but in my peripheral vision. I felt totally in Yopo's tight grasp on me and accepted it's roughness.
T= 00:30
I am a little less stupified and a little more wakeful so I start observing my room. Man, reality sure wasn't what it used to be. It was pretty much as if I was in 2 worlds at the same time. The spirits had increased in number and my room was crowded. Now also a couple of children were around me. I continuously saw feet of people passing me by and hands of people moving close to my face. Especially when I turned my head.
It went further still, to a peak-experience that comes faintly close to what I've read about the DMT experience. I fell into a stuporlike trance again, but this time I was seeing my room 360 all around me and all spirits in it while my eyes where nearly closed. Don't ask me how that's possible. I don't know how, but it is apparently. In this highly visionary state I saw one of the spirits, an 8 year old girl with black long hair with no face, wearing the brightest, most elegant white dress and a chain of bright flowers around her head.
I could draw her in detail and I certainly will. She bent over forwards, towards my back, and reached out to touch my shoulder. I saw all this in a different way of seeing, She was behind me. It was like 'seeing' in a dream. When the girl's fingertips touched my shoulder I actually felt the finger pushing into me, between my neck and my shoulder.  I was amazed, not shocked. Rather intrigued that I could actually have been touched by a spirit and physically feel it. I looked around to be sure it wasn't my friend Duck's finger, but it wasn't, He was next to me lying flat on his back with his eyes closed.
T= 00:35
By now I was so far gone into the other realm that I couldn't tell if, during what happened next, my eyes were opened or closed. I was looking at the pivoted, aubergine-colored red wall in my room as I very gradually zoned out and went into a dream vision. This was the most amazing part of my trip. I somehow 'saw' myself sitting in lotus posture trying to make sense of it all and being unable to. Before me is this nightly sky-blue plane with darker blue patterns swimming across it. I perceived all these things and try to think about them and what it all means.
Suddenly I realize that this is the perfect opportunity to learn to be a Silent Observer. To Observe only and not to give it all any thought. I figured I would do the thinking later, so that now I wasn't distracted by thoughts and could observe and remember everything I perceived. I was struggling, but with an incredible faith I kept trying and succeeded. I felt very proud of myself.
This blue plane had started morphing into a scene of a forest. Actually a rather large open spot in a forest. I was basically Dreaming and I felt my eyes doing intense REMs. I still struggled not to get lost in thoughts and stay thoughtless and pay attention to what I was experiencing. It was hard, but somehow I was certain I wouldn't fail and I never did. The forest-scene continued to form and at the same time I had a Matrix-like 'blue-pill, red-pill'-moment. I thought:' Do I go full speed into this realm of madness?' 'Or do I go back safely to the physical world, to my room?' I doubted for a while, kind of fearing the madness of this all and worried about the possible consequences.
Then I turned towards the madness, rid myself of fear and care and charged headfirst into it. I don't know if I experienced this visually, but I did 'see' it in a way. I felt as if I had finally understood how to be fearless, careless and mindful. I conquered my fears, Hushed my cares and made the Mindful decision to enter the mental realm.
What I was seeing was the dream taking complete, immersive form. I was in a forest on an open place. There were lots of colorful people on that terrain and a couple of open tents. I came in there and I was greeted with a loud cheering. I was struggling trying to keep my concentration at what I was experiencing, but I did very well. The people observed me and I felt sort of encouraged by them to keep my mind clear and lucid and as they started dancing I suddenly got it. 'It' being what they wanted me to do and what I felt I wanted to do, I danced with them.
I was dancing in a dream with elf-like spirits and one of them, a mature older female, looked at me with a big grin and signed with her hands to encourage me and give me the confirmation that I had done right. She cheered, as did all others around me, I communicated with them and understood, overcame my astonishment and was now dancing amongst them in the dream scene. As I was dancing I noticed the sun started shining very, very brightly.
The main colors of the scene where yellow, light green, dark green, pink, and bright blue. I noticed the music playing very loud and joyfully was SKA, my Favourite music. I started skanking to the Ska and it felt like a total bliss. All the Spirit-people skanked along, cheered and were overjoyed by my dancing with them. It was as if they were actually waiting for me to arrive and played music to my likings in a scene they thought I would love. It felt like 'home' in a very strange manner. And these people felt like 'my people' in that they were heavenly and pretty much fit my personal ideal of spiritual communion. What 'family' should be, opposed to what it often is. I felt united with these people, welcome, appreciated and at perfect peace. I felt so incredibly happy.
T= 00:45
I had just come out of the dream like vision and I was strikingly clear minded yet still on a Psychedelic reveree. As if a great storm had just swept through my head and left it a vast, empty, calm plane.  Oh boy it was tasty and peaceful to smoke after the Yopo experience. We were still mistyfied of the aftereffects of Yopo and right after the Joint we smoked a Hashi. It was enough to bring back a last wave of mild visionary stupor to me.
We chatted a bit and I quickly sketched and wrote things from my visions so to remember them and share them with Duck. He was less conscious of the actual experience than I was, 'cause he remembers mainly colors and bright objects moving around and towards him, but he did mention walking past houses and looking into a window where he saw 2 people watching TV. He walked to the next window where he saw 2 people fighting. He saw that with his eyes closed. We smoked another cigarette and went to sleep early that night.
This experience tops my previous 2 yopo-experiences by far. I think the special preparation I made really made a significant difference. It made it MUCH more visionary. It is very rough, however I somehow can't see how you could possibly go bad on Yopo. I feel enlightened. Carefree, Fearfree and Mindfull.
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.


My name is Hunter Harding, and I'm a Computer Science student at University of Wisconsin - Green Bay. My passion for programming urges me to go above and beyond the content in my classes, meaning that every day I dive deeper into various technologies that most of my peers have yet to experience. I started programming at the age of 15 for a computer game using a modified version of LUA, and since then, I've progressed to powerful languages like Python and widespread languages like JavaScript. I am now teaching myself the MEVN (MongoDB, Express, Vue.js, Node.js) stack so that I can build robust systems and interactive user-experiences. Outside of programming, I love maintaining my 55-gallon aquarium, riding ski-lifts with my snowboard, and telling myself that I'm good at photography.