Photo : A distorted panoramic view of Miami beach and Miami
Publications
Links to my Google Scholar profile, ORCID registry, and Mendeley profile.
Some recent gray literature:
-
Elipot, S., K. Drushka, A. Subramanian, and M. Patterson (2022), Overcoming the challenges of ocean data uncertainty, Eos, 103, doi:10.1029/2022EO220021. Published on 12 January 2022.
-
Elipot, S. and Wenegrat, J., Vertical structure of near-surface currents – Importance, state of knowledge, and measurement challenges, in Drushka, K., & Bourassa, M. (Eds.). (2021), New frontiers for ocean surface currents. Variations, 19, 44 pp, doi:10.5065/ybca-0s03.
-
Nielsen-Gammon, J., K. A. Reed, S. Elipot, and M. Patterson (2021), Research Challenge on Climate at the Coasts: US CLIVAR Report, 2021-2, 20pp, doi:10.5065/0g4s-5w68.
-
Elipot, S., Centurioni, L., Haines, B. J., Lumpkin, R., Willis, J. K. (2021) Measuring Global-Mean Sea-Level Rise With Surface Drifting Buoys, Marine Technology Society Journal, Volume 55, Number 3, May/June 2021, pp. 66-67(2), doi:10.4031/MTSJ.55.3.12.
Submitted:
32. Kathryn L. Gunn, K. McMonigal, Lisa M. Beal, Shane Elipot, and Elaine McDonagh (2022), Indian Ocean remains net evapourative, in press for the AMS Journal of Physical Oceanography.
31. Brian K. Arbic, Shane Elipot, Jonathan M. Brasch, Dimitris Menemenlis, Aurelien L. Ponte, Jay F. Shriver, Xiaolong Yu, Edward D. Zaron, Matthew H. Alford, Maarten C. Buijsman, Ryan Abernathey, Paige E. Martin, Arin D. Nelson, (2022), Frequency dependence of near-surface oceanic kinetic energy from drifter observations and global high-resolution models revised for JGR: Oceans. Preprint available from arXiv as arxiv:2202.08877.
- In this paper we compare the estimates of oceanic kinetic energy in different frequency bands from the velocity data of the Global Drifter Program and from the outputs of two numerical model integrations (HYCOM and MITgcm LLC4320). Both model integrations include atmospheric forcing and tidal forcing.
30. Elipot, Shane, Adam Sykulski, Rick Lumpkin, Luca Centurioni, and Mayra Pazos (2022), A Dataset of Hourly Sea Surface Temperature From Drifting Buoys, in revision for Scientific Data. Preprint available from arXiv as arxiv:2201.08289v1.
- This paper is a Data Descriptor publication which means that it provides detailed descriptions of research datasets, including the methods used to collect the data and technical analyses supporting the quality of the measurements. We are very excited to finally share this new dataset of SST estimates from surface drifter data.
Published:
30. Miron, Philippe, Elipot, Shane, Lumpkin, Rick, & Dano, Bertrand. (2022). Accelerating Lagrangian analyses of oceanic data: benchmarking typical workflows (ec2022v4). Zenodo. https://doi.org/10.5281/zenodo.6781037
29. McMonigal, K., Kathy Gunn, Lisa Beal, Shane Elipot, and Josh K. Willis (2021), Reduction in meridional heat export contributes to recent Indian Ocean warming, Journal of Physical Oceanography, 50(12), doi:10.1175/JPO-D-21-0085.1
28. Jonathan M. Lilly and Elipot, S. (2021), A Unifying Perspective on Transfer Function Solutions to the Unsteady Ekman Problem, Fluids, 6(2), 85, dpoi:10.3390/fluids6020085
- This paper is a revisit of some theoretical aspects of my PhD work, expanding and unifying previous studies including some of the material presented in Elipot and Gille (2009a).
27. Erik van Sebille, Erik Zettler, Nicolas Wienders, Linda Amaral-Zettler, Shane Elipot, and Rick Lumpkin (2021), Dispersion of surface drifters in the Tropical Atlantic, Frontiers in Marine Science, 7, doi:10.3389/fmars.2020.607426.
26. Edward Zaron and Elipot, S. (2021), An Assessment of Global Ocean Barotropic Tide Models Using Geodetic Mission Altimetry and Surface Drifters, Journal of Physical Oceanography, 51(1), doi:10.1175/JPO-D-20-0089.1.
25. Elipot, S. (2020), Measuring global mean sea level changes with surface drifting buoys, Geophysical Research Letters, 47, e2020GL091078, doi:10.1029/2020GL091078.
- This paper was the focus of a Research Spotlight in AGU’s Eos : Thompson, E. (2020), A floating buoy fleet could help scientists track rising seas, Eos, 101, https://doi.org/10.1029/2020EO151862.
24. Kathryn L. Gunn, Lisa M. Beal, Shane Elipot, K. McMonigal, and Adam Houk (2020), Mixing of Subtropical, Central and Intermediate Waters Driven by Shifting and Pulsing of the Agulhas Current, Journal of Physical Oceanography, 50(12), doi:10.1175/JPO-D-20-0093.1.
23. K. McMonigal, Lisa M. Beal, Shane Elipot, Kathryn L. Gunn, Juliet Hermes, Tamaryn Morris, and Adam Houk (2020), The Impact of Meanders, Deepening and Broadening, and Seasonality on Agulhas Current Temperature Variability, Journal of Physical Oceanography, 50(12), doi:10.1175/JPO-D-20-0018.1
22. Xiaolong Yu, Aurélien L. Ponte, Shane Elipot, Dimitris Menemenlis, Edward D. Zaron, Ryan Abernathey (2019), Surface kinetic energy distributions in the global oceans from a high-resolution numerical model and surface drifter observations, Geophys. Res. Lett., 46(16), doi:10.1029/2019GL083074
21. Frajka-Williams, E. […], Elipot, S., […] (2019), Atlantic Meridional Overturning Circulation: Observed Transport and Variability, Front. Mar. Sci., 6:260. doi:10.3389/fmars.2019.00260
- This is an open-access OceanObs19 community white paper. What is the Atlantic MOC and how is it observed? In this paper led by Eleanor Frajka-Williams, we outline the different approaches used to observe the AMOC and summarize the key results to date. We also discuss alternate approaches for capturing AMOC variability including direct estimates (e.g., using sea level, bottom pressure, and hydrography from autonomous profiling floats), indirect estimates applying budgetary approaches, state estimates or ocean reanalyses, and proxies. Based on the existing observations and their results, and the potential of new observational and formal synthesis approaches, we make suggestions as to how to evaluate a comprehensive, future-proof observational network of the AMOC to deepen our understanding of the AMOC.
20. Howe, B. M., […], Elipot, S., […] (2019), SMART Cables for Observing the Global Ocean: Science and Implementation, Front. Mar. Sci., 6:424, doi:10.3389/fmars.2019.00424
- This is an open-access OceanObs19 community white paper. Did you know that the majority of internet traffic takes place on a multitude of undersea communication cables that crisscross the ocean seafloor? In this paper led by Bruce M. Howe we describe the mission of the SMART subsea cables initiative (Science Monitoring And Reliable Telecommunications). SMART sensors would “piggyback” on the power and communications infrastructure of a million kilometers of undersea fiber optic cable and thousands of repeaters, creating the potential for seafloor-based global ocean observing at a modest incremental cost.
19. Vermeulen, E., B. Backeberg, J. Hermes, and S. Elipot (2019), Investigating the relationship between volume transport and sea surface height in a numerical ocean model, Ocean Sci., 15, 513-526, doi:10.5194/os-15-513-2019
18. L’Hégaret, P., L. M. Beal, S. Elipot, and L. C. Laurindo (2018), Shallow cross-equatorial gyres of the Indian Ocean driven by seasonally reversing monsoon winds, J. Geophys. Res.-Oceans, 123, doi:10.1029/2018JC014553
17. Elipot, S., and L. M. Beal (2018), Observed Agulhas Current sensitivity to interannual and long-term trend atmospheric forcings, J. Clim., 31, 3077-3098, doi: 10.1175/JCLI-D-17-0597.1.
This paper has been selected as a research highlight for Nature Climate Change: G. Simpkins (2018), Nature Climate Change 8, 188, doi:10.1038/s41558-018-0111-3.
- This paper studies the atmosphere-driven interannual variability of the Agulhas jet transport based on the altimeter proxy derived in Beal and Elipot (2016). We find that 29% of the interannual variance of the Agulhas Current transport can be linearly related to six modes of Southern Hemisphere atmospheric variability, including ENSO and a SAM-related mode. The Agulhas transport proxy time series can be downloaded via the ACT website here.
16. Elipot, S., E. Frajka-Williams, C. W. Hughes, S. Olhede, and M. Lankhorst (2017), Observed basin-scale response of the North Atlantic Meridional Overturning Circulation to wind stress forcing, J. Clim., 30, 2029-2054, doi:10.1175/JCLI-D-16-0664.1. (Open access; if you download the PDF file, figures of this paper are best rendered in Adobe Acrobat or Adobe Reader).
- This paper explores the spatiotemporal covariance and forcing mechanisms of observed variability in the Atlantic meridional overturning circulation. We developed a novel statistical method (analytic SVD) to investigate the relation between overturning transports from four arrays in the North Atlantic (RAPID WAVE, LINE W, RAPID MOC/MOCHA and MOVE) and patterns of wind stress and its curl over the basin. We identify two significant modes of variability in the overturning circulation driven by surface winds. The first mode manifests on seasonal time scales and is interpreted in terms of Ekman transports and barotropic return flows. The second mode is evident on nonseasonal time scales and is interpreted in terms of horizontal gyre circulation anomalies, which couple to the variable bottom topography to yield overturning circulation changes.
15. Beal, L. M., and S. Elipot (2016), Broadening not strengthening of the Agulhas Current since the early 1990s, Nature, 540, 570573, doi:10.1038/nature19853.
- In this paper we show that, despite expectations, the Agulhas Current has not intensified since the early 1990s. Instead, we find that it has broadened as a result of more eddy activity.
14. Leber, G. M., L. M. Beal, and S. Elipot (2016), Wind and current forcing combine to drive strong upwelling in the Agulhas Current, J. Phys. Oceanogr., 47, 123-134, doi:10.1175/JPO-D-16-0079.1.
- In this paper, we investigate upwelling events inshore of the Agulhas Current at 34S. These events exchange shelf and slope waters, potentially enhancing primary productivity along the shelf and advecting larvae offshore. Hydrographic observations of a wind-driven upwelling event nd a current-driven upwelling event show that they can advect central waters more than 130 m upward onto the continental shelf, resulting in a 9C cooling. We use satellite data to assess the frequency, strength and forcing mechanisms of cold events from January 2003 11 through December 2011.
13. Elipot S., R. Lumpkin, R. C. Perez, J. M. Lilly, J. J. Early, and A. M. Sykulski (2016), A global surface drifter dataset at hourly resolution, J. Geophys. Res.-Oceans, 121, doi:10.1002/2016JC011716.
- This paper describes how we created a new hourly surface drifter dataset, now available publicly through the Data Assembly Center of the Global Drifter Program hosted at the Atlantic Oceanographic & Meteorological Laboratory
12. Elipot, S., and L.M. Beal (2015), Characteristics, Energetics, and Origins of Agulhas Current Meanders and their Limited Influence on Ring Shedding, J. Phys. Oceanogr., 45, 2294-2314, doi:10.1175/JPO-D-14-0254.1
- In this study we investigate in detail the variance of the Agulhas Current velocity field from the ACT array, especially focussing on what is happening during meanders, the so-called Natal Pulses. For this we lay out the details of a method of analysis of rotary variance, dubbed Rotary EOF (REOF). We also combined in-situ data from the ACT array with altimetry data to research the origins, and fate, of meanders.
11. Beal, L. M., S. Elipot, A. Houk, and G. Leber (2015), Capturing the Transport Variability of a Western Boundary Jet: Results from the Agulhas Current Time-series experiment (ACT), J. Phys. Oceanogr., 45, 1302-1324, doi:10.1175/JPO-D-14-0119.1 (Open Access)
- This paper presents the first results from the velocity moorings deployed as part of the Agulhas Current Time-Series Experiment, or ACT, that took place between 2010 and 2013 in the Indian Ocean. We provide the longest in-situ record to date of the Agulhas Current Jet transport.
10. Elipot, S., E. Frajka-Williams, C. Hughes, and J. Willis (2014), The Observed North Atlantic Meridional Overturning Circulation, its Meridional Coherence and Ocean Bottom Pressure, J. Phys. Oceanogr., 44, 517-537, doi:10.1175/JPO-D-13-026.1 (Open Access)
9. Polton, J., Y.-D. Lenn, S. Elipot, T. K. Chereskin, and J. Sprintall (2013), Can Drake Passage observations match Ekman’s classic theory? J. Phys. Oceanogr., 43, 1733-1740, doi:10.1175/JPO-D-13-034.1 (Open Access)
- Ekman’s theory of the wind-driven ocean surface boundary layer assumes a constant eddy viscosity and predicts that the current rotates with depth at the same rate as it decays in amplitude. This study presents a method for estimating ageostrophic currents from shipboard acoustic Doppler current profiler data in Drake Passage and finds that observations are consistent with Ekman’s theory.
8. Elipot, S., C. Hughes, S. Olhede, and J. Toole (2013), Coherence of western boundary pressure at the RAPID WAVE array: boundary wave adjustements or deep western boundary current advection?, J. Phys. Oceanogr., 43, 744-765, doi:10.1175/JPO-D-12-067.1 (Open Access)
- This study investigates the coherence between ocean bottom pressure signals at the Rapid Climate Change programme (RAPID) West Atlantic Variability Experiment (WAVE) array on the western North Atlantic continental slope, including the Woods Hole Oceanographic Institution Line W. We find several types of coherent signals: barotropic kelvin-like waves that propagates at speeds in excess of \( 128\, m s^{-1} \), and pressure-difference signals propagating at about \( 1\, m s^{-1} \), roughly consistent iwth coastally-trapped waves. These last signals are expected to be associated with depth-dependent basinwide meridional transport variations or an overturning circulation.
7. Hughes, C., S. Elipot, M.A. Morales Maqueda, and J. Loder (2013) Test of a Method for Monitoring the Geostrophic Meridional Overturning Circulation Using Only Boundary Measurements, J. Atmosph. Ocean. Techn., 30,789–809, doi:10.1175/JTECH-D-12-00149.1 (Open Access)
6. Lumpkin, R. and S. Elipot (2010), Surface Drifter Pair Spreading in the North Atlantic, J. Geophys. Res.-Oceans, 115, C12017, doi:10.1029/2010JC006338.
5. Elipot, S., R. Lumpkin, and G. A. Prieto (2010), Modification of inertial oscillations by the mesoscale eddy field, J. Geophys. Res.-Oceans, 115, C09010, doi:10.1029/2009JC005679.
4. Elipot, S., and S. T. Gille (2009), Estimates of wind energy input to the Ekman layer in the Southern Ocean from surface drifter data, J. Geophys. Res., 114, C06003, doi:10.1029/2008JC-005170.
3. Elipot, S., and S. T. Gille (2009), Ekman layers in the Southern Ocean: spectral models and observations, vertical viscosity and boundary layer depth, Ocean Sci., 5, 115-139, doi:10.5194/os-5-115-2009.
2. Elipot, S., and R. Lumpkin (2008), Spectral description of oceanic near-surface variability, Geophys. Res. Lett., 35, L05606, doi:10.1029/2007GL032589.
1. Beal, L. M. , T. K. Chereskin, Y.-D. Lenn , and S. Elipot (2006), The sources and mixing characteristics of the Agulhas Current, J. Phys. Oceanogr., 36, 2060-2074, doi:10.1175/JPO2964.1.
Others:
b. MacKinnon, J.A., Alford, M., Bouruet-Aubertot, P., Bindoff, N., Elipot, S., Gille, S., Girton, J., Gregg, M.C., Hallberg, R., Kunze, E., Naveira Garabato, A., Phillips, H., Pinkel, R., Polzin, K., Sanford, T., Simmons, H., and Speer, K., (2010), Using global arrays to investigate internal-waves and mixing, in Proceedings of the OceanObs09: Sustained Ocean Observations and Information for Society Conference (Vol. 1), Venice, Italy, 21-25 September 2009, Hall, J., Harrison D.E. and Stammer, D., Eds., ESA Publication WPP-306.
a. Elipot, S. (2006), Spectral characterization of Ekman velocities in the Southern Ocean based on surface drifter trajectories, Ph.D. dissertation, University of California, San Diego.


The DFT of a sequence of real data results in a special form of complex sequence known as a Hermitian sequence.
If the original sequence is purely real valued, i.e. z_j=x_j, then the definition of the real DFT used here is given by:
ztilde_j = a_j + i b_j = 1/sqrt(n) sum(for k=0,n-1) x_k exp(-i*2*pi*j*k/n) for j=0,1,...,n-1
where x_k are the real data to be transformed, ztilde_j are the transformed complex data.
In full complex representation, the Hermitian sequence would be a sequence of n complex values \tildez_j for j=0,1,...,n-1, where \tildez_n-j is the complex conjugate of \tildez_j for j=1,2,...,(n-1)/2; \tildez_0 is real valued; and, if n is even, \tildez_n/2 is also real valued. The symmetries defining Hermitian sequence mean that it can be stored using reduced amount of memory.
In ACML, there are two storage formats for the representation of
Hermitian sequences. The first format, called Hermitian-packed format, is
used on output from DZFFT
routines and on
input to ZDFFT
routines and is defined as follows:
let X be an array of length n and with first index 0,
An alternative way to store the Hermitian sequence, called complex-Hermitian
format, is to keep the complex
representation, store only the first n/2+1 complex numbers and drop the
remaining elements that contain redundant information. This approach can be
conveniently extended to multiple dimensions. For example, a 3D real data set
of size l*m*n can be transformed into Fourier space as a
complex data set of size (l/2+1)*m*n. It is still possible to
use l*m*n real numbers to store all Fourier coefficients
but intepreting such information would be extremely difficult. The 16
new subroutines (such as
DZFFT1D/1M/2D/3D
) introduced in version 5.0 of ACML all use the
complex-Hermitian format.
The following table shows the storage of a one-dimensional Hermitian sequence with 8 elements.
|
Given a Hermitian sequence, the inverse discrete transform can be defined as:
x_j = 1/sqrt(n) sum(for k=0,n-1) ztilde_k exp(i*2*pi*j*k/n) for j=0,1,...,n-1
or if written using the real and complex components:
x_j = 1/sqrt(n) * (a_0 + 2 sum(for k=1,n/2-1) (a_k cos(2*pi*j*k/n) - b_k sin(2*pi*j*k/n)) + a_n / 2)
where a_(n/2)=0 if n is odd, and tildez_k=a_k + i b_k is the Hermitian sequence to be transformed.
Note that, in the second definition above, the inverse transform has a negative sign in the exponent. So if a Hermitian sequence is stored in a Hermitian-packed format (for DZFFT, DZFFTM, SCFFT and SCFFTM), performing a forward and a backward transform consecutively does not recover the original data. To recover original real data, or otherwise to perform an inverse transform on a set of Hermitian data, the Hermitian data must be conjugated prior to performing the transform (i.e. changing the sign of the stored imaginary parts). This however does not apply to the remaining subroutines using the complex-Hermitian data storage.


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Young man caught allegedly taking photos of naked males in a bathroom on Legon campus
by Nana YawInformation reaching us has it that a young man whose identity is yet to be known is in grips of the University of Ghana Security after he was caught allegedly taking pictures and videos of some students.
The man according to the report, was caught taking a video of other male students in one of the male washrooms at Annex A of the Legon Hall, University of Ghana.
According to what was gathered, when the said young man was approached by some students who grew suspicious of his actions to unlock his phone so they can verify their claim, he refused to do so drawing more suspicions and attention from other students.
To avoid him being assaulted by the angry mob whose numbers were increasing by the minute, he was then dragged to the porters’ lodge by some students.
It is unclear, at the moment, if he is a student of the university or an outsider but per our information, the young man is being interrogated by the University of Ghana Security and will update readers on subsequent happenings. Stay with Ghbase.com.


You release successively red, orange, yellow, green, blue and purple keys! Colors are back in the internet world! Wizard Darshado is far far away now, until is revenge...
Lot of thanks to Azureflux for his awesome songs /Wizard House/ and /Reckless/ used in this game!
Sounds made on jfxr.
Seudides has been made in a Selfish Game Challenge mod, so it took approximatively 48 hours to made. Participate!
The selfish game is here for share, so here is the github source of Seudides
To mail me?:ertel.simon@gmail.com


My Learning
It include the following but not limited to
- Linux basic
- Linux advanced
- vim
- Markdown
- //TODO
- Shell scripting
- C/C++
- CUDA
- Git/GitHub
- Web hosting
Linux Basic
A few shortcuts
ctrl + alt + T
- Open terminalctrl + alt + <up/right/left>
- Switch workspacectrl + alt + shift + <right/left>
- Move current window to right/left workspacectrl + alt + <F1/F2/F3/F4/F5/F6>
- Open TTY login (does not use GUI)ctrl + alt + <F7>
- Leave TTY screen and switch to GUI<up/down>
- Move back/forth the previously typed terminal commands
Basic commands
$ pwd # path of working directory
$ ls # list the contents of current directory
$ cd Music # changes the current directory to `Music` directory
$ cd .. # change the directory to one level up except at '/'
$ cd - # jumps to previous `pwd` before a `cd`
$ ls -l # long listing the file
$ ls -lrt # list file based on the modified date. recent at the last.
$ man ls # list manual pages for `ls`
$ ls --version # shows the version of `ls`. Sometimes it is `<cmd> -v`
pwd
- path of working directoryls
- list the contents of current working directory i.epwd
cd folder
- changes the current directory tofolder
cd ..
- change the directory to one level up except at '/'cd -
- jumps to previouspwd
before acd
ls -l
- long listing of file/folderls -lrt
- list file based on the modified date. recent at the lastman <cmd>
- list manual pages for any valid linuxcmd
<cmd> --version
- shows the version of validcmd
Linux Administration
The easiest of all Linux distribution is Ubuntu. I have been using Linux along side from 2009, and from 2016 Linux is my main stream operating system. I have used Debian, Ubuntu, Fedora, OpenSUSE, and a few others. Thanks to my under-graduate projects and {TCE's FStival 2008](). But, now Linux Mint Cinnamon is my favourite (from 2017). I begin to dislike Unity-Gnome in Ubuntu, so moved to Mint. Am I ranting or self-trumpeting? Both. Okay, it is 2020. But still some commands are still in my muscle memory. I am just logging it here.
Admin commands
echo $HOME
- Displays the home of user who run itls -a
- Also list the hidden folders/files (it beging with a.
) e.g.bashrc
in $HOMEdf -h
- List all mounted partition along with used/available/% sizetop
- List all running process based on % of CPU usage. pressq
to closedu -h .
- List the file/folder size of current directorylscpu
- List the processor detailslsusb
- List of devices attached to the USB portcat /proc/meminfo
- List the RAM/memory detailsdmesg | grep tty
- Find thetty/devName
just attached via USBless /var/log/auth.log
- All login/out/suspend session are recored/var/log/*
- has all the logs file e.g. apt-get log is in `/var/log/apt/history.log
ps -ef | grep firefox
- List processes/id with the namefirefox
kill <pid>
- Kill the process withsending sigterminate kill -9 <pid>
- Kill the process withsending sigkill /home/<user>/.bashrc
- User specific bashrc filesource .bashrc
- Run and set bachrc file in current session/home/<user>/.bash_history
- List of cmd typed by theuser
echo $PATH
- Displays the environment variablePATH
PATH=$PATH:/usr/local/cuda-10.0/bin
- Set path in shellexport PATH
- will pass this env variable for subsequent commands ericssh username@ip-address
# e.gssh<EMAIL_ADDRESS>scp localfile user@ip-address:/some/location/on/server
Installation
- Most of new machine. You may have to disable fastboot/safeboot in BIOS
- Download you favourite linux as
iso
file - Burn iso to formatted USB/DVD using rufus, UNetbootin , usb-creator or Startup Disk creator
- Reboot and press the key F12/F10 (differ based on manufacturer) to bootfrom USB/DVD
- Mostly positive answer for moast. At select drive location, use MANUALLY
- Give appropriate drives "/", /home, and swap (/boot, /tmp optinal)
- You may leave it with / alone also.
- Upon installation and reboot. Grub will appear.
Markdown Syntax
Heading
# Heading 1
## Heading 2 ##
and so on till H6.
A short form for H1 and H2 is
Heading 1
=========
Heading 2
----------
Quoting text
| Syntax | Output |
|---|---|
Source code
This is inline `code` and
e.g. Use `git log` to see the commits.
- This is inline
code
and - e.g Use
git log
to see the commits.
This is called code block or fenced code. You may specify the language.
#include <iostream>
int main(int argc, char* argv[]){
std::cout << "Hello There!"<< std::endl;
return EXIT_SUCCESS;
}
You may mention language from this list to enable syntax hightlighting at line 1
.
Hyperlinks/Attachments
This is [Google](www.google.com) as a link.
This is Google as a link.
![Alt text rajzdocs logo](images/logo-6e5006f2.png)
![Some logo](http://example.com/logo.png)
Text formatting
*This text will be italic* and _This will also be italic_
**This text will be bold** and __This will also be bold__
_We **can** combine both_
~~This text will be stricked-out~~
This text will be italic and This will also be italic
This text will be bold and This will also be bold
We can combine both
This text will be stricked-out
List
* one // Unordered
* two
* three
1. One // Ordered
2. Two
3. Three
- This is also
- Unordered
- An another way
Multi-level or nesting
- Can be nested
* One.One
* One.Two
- Can also be nested this way
1. Two.One
1. Two.Two. What?
1. You see this? auto-increment.
- Three
- Thread.One
- one // Unordered
- two
- three
- One // Ordered
- Two
- Three
- This is also
- Unordered
- An another way
Multi-level or nesting
- Can be nested
- One.One
- One.Two
- Can also be nested this way
- Two.One
- Two.Two. What?
- You see this? auto-increment.
- Three
- Thread.One
Horizontal rule
If you need horizontal rule then, use three
asterisks,
***
hyphens or underscores like the below.
---
Also, have a blank line before and after!
___
If you need horizontal rule then, use three asterisks,
hyphens or underscores like the below.
Also, have a blank line before and after!
Table
Header 1 | Header 2
-------- | -----------
cell 1x1 | cell 1x2
cell 2x1 | cell 2x2
| Header 1 | Header 2 |
|---|---|
| cell 1x1 | cell 1x2 |
| cell 2x1 | cell 2x2 |
you may use handy table generator website to generate large tables.
References
- From the author of Markdown
- Github Markdown Guide
- Markdownguide Cheat-sheet
- Markdownguide DOs and DONTs
Not part of markdown
This search engine [1] is lot better than [2] and [3]
[1] - www.google.com
[2] - www.yahoo.com
[3] - www.bing.com
This search engine [1] is lot better than [2] and [3] Here's a sentence with a footnote. [^4].
[1] - www.google.com [2] - www.yahoo.com [3] - www.bing.com [^4]: This is the footnote.


{{template config_path="design/email/header_template"}}
|
Hi {{trans "%customer_name," customer_name=$customer.getName()}} {{trans "The life time for your %credits_name at %website_name is %life_time days." credits_name=$credits_name website_name=$website_name life_time=$life_time}} {{trans "After expiration date you won't be able to use them."}} {{trans "Your credits will expire:"}} {{block class='Magento\\Framework\\View\\Element\\Template' area='frontend' template='Swarming_StoreCredit::email/expiration_items.phtml' expiration_items=$expiration_items}}{{trans "Your current balance is %credits_balance." credits_name=$credits_name credits_balance=$credits_balance |raw}} {{trans 'If you have questions about your %credits_name balance, you can email us at %store_email' credits_name=$credits_name store_email=$store_email |raw}} |


GOODBYE LOVER (Warner Bros.) Starring: Patricia Arquette, Dermot Mulroney, Ellen DeGeneres, Mary-Louise Parker, Don Johnson, Ray McKinnon. Screenplay: Ron Peer and Joel Cohen & Alec Sokolow. Producers: Alexandra Milchan, Patrick McDarrah, Joel Roodman and Chris Daniel. Director: Roland Joffe.  Reviewed by Scott Renshaw.
 Aptly labeled a "film-gris" in the production notes, it's a convoluted comic thriller centered around Sandra Dunmore (Patricia Arquette), a real estate agent with dreams of the good life and a car full of motivational tapes reminding her that she can have it. Standing in her way, unfortunately, is her alcoholic husband Jake (Dermot Mulroney), which leads her to an affair with Jake's more successful brother Ben (Don Johnson), while Ben also romances a co-worker named Peggy (Mary-Louise Parker) on the side. When the tangled interactions of this quartet leads to murder, Det. Rita Pompano (Ellen DeGeneres) comes on the scene to investigate and discovers that very little is what it appears to be.
The reason nothing is what it appears to be is that GOODBYE LOVER is a film about twisty-turny plotting...and, essentially, that's _all_ it's about. Allegiances shift, backs are stabbed (figuratively and literally), and greed is the order of the day. It's the kind of stuff that usually makes a film interesting to watch thanks to its unpredictability, but GOODBYE LOVER becomes strangely predictable in its unpredictability. It's so instantly obvious that it's a film about hidden agendas that it becomes a matter of waiting until the next character's obviously hidden agenda is revealed. There's not much fun in the zigs and zags the story takes because every 20 minutes or so you know it's going to be time for the next zig or zag, and the next permutation in a series of unholy alliances.
There's still something over-the-top goofy about GOODBYE LOVER which makes it possible to slip into its sociopathic world. Patricia Arquette is an ideal cast as Sandra, a driven Barbie doll who sees herself as the cutthroat reincarnation of Julie Andrews' Maria from THE SOUND OF MUSIC. The performance is only so-so, but the character is such a wild blend of madonna and whore that she's enjoyable to watch.  The real key to appreciating GOODBYE LOVER, however, is slipping into the slickness of a production which takes the image of Los Angeles as duplicity capital of the world and blows it up to billboard size. From the encounters with spin-doctoring publicists to the ubiquitous use of mirrors, GOODBYE LOVER has a blast with tarted-up sleaze and the way motivated misanthropes can create an image that allows them get away with murder (literally and figuratively).
In fact, GOODBYE LOVER is so gleeful in its complete absence of humanity that it may take you a while after it's over before you feel the need to shower its decadence right off of yourself. It's too self-aware of its lack of real characters to inspire too much head-wagging, but it's still one of those films that finds it cool to set up the only person with an ounce of optimism as an object of ridicule. GOODBYE LOVER is full of ugly-on-the-inside types who feel justified doing whatever it takes to grab the golden ring because, after all, everyone else is doing it. There's just enough residual cheesiness to keep the film in the realm of the surreal, with just enough bleak attitude to blunt its surreal appeal. It's not a thriller so much as it is an ultra-black comedy, where part of the joke is on you for leaving your moral outrage at the door.
On the Renshaw scale of 0 to 10 jilted lovers: 6.
Visit Scott Renshaw's Screening Room http://www.inconnect.com/~renshaw/ *** Subscribe to receive new reviews directly by email! See the Screening Room for details, or reply to this message with subject "Subscribe".
The review above was posted to the
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---
start: 2019-07-25 18:00
edition: 69
participate: "https://www.meetup.com/Chennai-Geek-Night/events/263231984"
talk: "https://docs.google.com/forms/d/1llJxKCuEnPXOPHnXUQHnc8Unlt_Y4kPvWJqndjl_6Gg/viewform"
subnote: "This event will be live streamed on "
agenda:
-
time: "6:00"
title: "The State of React Native in 2019"
subtitle: "React Native - the open source framework for building cross platform mobile apps have been through a lot of major updates recently with the community running some interesting projects like Lean Core, Hermes Engine etc. This session is a deep dive into the current state of React Native, the new features, advantages and the architectural challenges you will face as you move along with the application development process."
speakers:
-
name: "Dani Akash"
profile: "https://twitter.com/DaniAkashS"
video_link: "https://www.youtube.com/watch?v=O_vVceZxtkc"
description: "Dani Akash is a React Developer from Pickyourtrail, a travel-tech startup. He is currently working on the React Native mobile app which provides on-trip support to customers travelling with Pickyourtrail. He has worked with many javascript technologies and is an active speaker in the chennai javascript communities. He has also published a book Javascript By Example which covers efficient ways to use javascript in modern applications."
image: "dani-akash.jpeg"
-
time: "7:00"
title: "Using Glitch to eliminate platform adoption barriers - How we reduced the time to 'Hello World' from 10 mins to 10 seconds"
subtitle: "The most rejoicing aspect of DevRel (Developer Relations) is to enable the developers to meet their end goals. However, that’s not an excuse to care less about the new developers or hobbyists who are getting on-boarded onto the platform. In fact, I believe that the fresh developers of today are the potential future platform evangelists. As a litmus test, a platform can be judged by it's first ‘Hello-World’ journey that it offers to a fresh developer. In a quest to analyze the adoption barriers and to make the hello-world more welcoming, I stumbled upon a really useful tool called “Glitch” which helped me to create insanely prepared boilerplates for developers to work on. Everything is already configured for the developers to start-off thus letting them validate or experience the richness of the platform upfront. I humbly present to you the story of how we reduced the setup time for our developers from several minutes to just a few seconds with Glitch!"
speakers:
-
name: "Hemchander S"
profile: "https://www.linkedin.com/in/hems23"
video_link: "https://www.youtube.com/watch?v=5GMxumC-sOw"
description: "Hemchander is from the Developer Relations team at Freshworks and is actively involved in building a vibrant developer ecosystem."
image: "hemchander.jpeg"
-
time: "7:45"
title: "Memory Safety in Rust"
subtitle: "In this talk we will be focusing on the language features, that helps Rust to ensure memory safety without needing for a garbage collector."
speakers:
-
name: "Jawahar"
profile: "https://www.jawahar.tech"
video_link: "https://www.youtube.com/watch?v=qwJWF7XeRxs"
description: "Jawahar is a Software Programmer who is passionate about learning new languages and frameworks. He has years of experience in building enterprise grade applications using various technologies. He is specifically interested in practicing functional programming with modern language features. "
image: "jawahar-babu.jpg"
-
time: "8:30"
title: "Networking & Dinner"
---


If you feel like I can somehow help you feel free to reach out to me.
I'm open for hiring by the way.
Sometimes I code.
The IM I'm most active one right now.
GPG encrypted mails are more than welcome!
Someday I'll start twittering about my awesome life.
In case you're interested in when I'm awake.


|
Portable Radio
|
Signaltrenght Bars. More...
#include <GUI.hpp>
Public Member Functions | |
| signalBars (const hwlib::xy &position, const unsigned int spacing=5, const unsigned int heightIncrement=5) | |
| Constructor. More... | |
| void | print (hwlib::window &window, const unsigned int amountOfLines) |
| Print Bars. More... | |
Signaltrenght Bars.
This is a class which makes it possible to represent a signalstrength through bars. They try to look like signalbars known from mobile phones. They are completely customizable; the position, width, height amount of bars and spacing between bars.
| signalBars::signalBars | ( | const hwlib::xy & | position, |
| const unsigned int | spacing = 5 , |
||
| const unsigned int | heightIncrement = 5 |
||
| ) |
Constructor.
This constructor has no mandatory parameters. The location defaults to hwlib::xy(0, 0), height to 5 and width to 15. However, these can be given to make use of the object.
| void signalBars::print | ( | hwlib::window & | window, |
| const unsigned int | amountOfLines | ||
| ) |
Print Bars.
This constructor function prints the given amount of lines; from 0 to 5.


|
Facial Recognition - Common Code
|
#include <stdio.h>
#include <stdlib.h>
#include <assert.h>
#include <stdint.h>
#include <string.h>
#include <ctype.h>
#include <math.h>
Go to the source code of this file.
Data Structures | |
| struct | matrix_t |
Macros | |
| #define | precision double |
| #define | UNDEFINED 0 |
| #define | ZEROS 1 |
| #define | ONES 2 |
| #define | FILL 3 |
| #define | IDENTITY 4 |
| #define | NOT_TRANSPOSED 0 |
| #define | TRANSPOSED 1 |
| #define | HORZ 0 |
| #define | VERT 1 |
| #define | COLOR 0 |
| #define | GRAYSCALE 1 |
| #define | PARENT 0 |
| #define | SUBMATRIX 1 |
| #define | IS_COLOR GRAYSCALE |
| #define | elem(M, i, j) (M)->data[(j) * (M)->numRows + (i)] |
| #define COLOR 0 |
Definition at line 23 of file matrixOperations.h.
| #define elem | ( | M, | |
| i, | |||
| j | |||
| ) | (M)->data[(j) * (M)->numRows + (i)] |
Definition at line 38 of file matrixOperations.h.
| #define FILL 3 |
Definition at line 17 of file matrixOperations.h.
| #define GRAYSCALE 1 |
Definition at line 24 of file matrixOperations.h.
| #define HORZ 0 |
Definition at line 21 of file matrixOperations.h.
| #define IDENTITY 4 |
Definition at line 18 of file matrixOperations.h.
| #define IS_COLOR GRAYSCALE |
Definition at line 27 of file matrixOperations.h.
| #define NOT_TRANSPOSED 0 |
Definition at line 19 of file matrixOperations.h.
| #define ONES 2 |
Definition at line 16 of file matrixOperations.h.
| #define PARENT 0 |
Definition at line 25 of file matrixOperations.h.
| #define precision double |
Definition at line 13 of file matrixOperations.h.
| #define SUBMATRIX 1 |
Definition at line 26 of file matrixOperations.h.
| #define TRANSPOSED 1 |
Definition at line 20 of file matrixOperations.h.
| #define UNDEFINED 0 |
Definition at line 14 of file matrixOperations.h.
| #define VERT 1 |
Definition at line 22 of file matrixOperations.h.
| #define ZEROS 1 |
Definition at line 15 of file matrixOperations.h.
| void loadPPMtoMatrixCol | ( | char * | path, |
| matrix_t * | M, | ||
| int | specCol, | ||
| unsigned char * | pixels | ||
| ) |
Definition at line 122 of file matrixOperations6.c.
Definition at line 116 of file matrixOperations3.c.
m_copy
Copies matrix M into a new matrix
ICA: data_t* copy(data_t* orig,int rows,int cols);
Definition at line 171 of file matrixOperations1.c.
Definition at line 153 of file matrixOperations3.c.
Definition at line 75 of file matrixOperations3.c.
Definition at line 30 of file matrixOperations4.c.
Definition at line 48 of file matrixOperations4.c.
Definition at line 12 of file matrixOperations4.c.
| void m_eigenvalues_eigenvectors | ( | matrix_t * | M, |
| matrix_t ** | p_eigenvalues, | ||
| matrix_t ** | p_eigenvectors | ||
| ) |
Definition at line 9 of file matrixOperations6.c.
| void m_elem_acos | ( | matrix_t * | M | ) |
m_acosAll
applies acos to all matrix elements
ICA: void matrix_acos(data_t *outmatrix, data_t *matrix, int rows, int cols);
Definition at line 108 of file matrixOperations2.c.
void sum_scalar_matrix(data_t *outmatrix, data_t *matrix, int rows, int cols, data_t scalar);
adds element-wise matrix to contant
Definition at line 228 of file matrixOperations2.c.
void divide_by_constant(data_t *outmatrix, data_t *matrix, int rows, int cols, data_t scalar);
divides matrix by contant
Definition at line 198 of file matrixOperations2.c.
void divide_scaler_by_matrix(data_t *outmatrix, data_t *matrix, int rows, int cols, data_t scalar) ;
divides constant by matrix element-wise
Definition at line 213 of file matrixOperations2.c.
| void m_elem_exp | ( | matrix_t * | M | ) |
void matrix_exp(data_t *outmatrix, data_t *matrix, int rows, int cols);
raises e to all matrix elements
Definition at line 153 of file matrixOperations2.c.
void scale_matrix(data_t *outmatrix, data_t *matrix, int rows, int cols, int scalar);
scales matrix by contant
Definition at line 184 of file matrixOperations2.c.
| void m_elem_negate | ( | matrix_t * | M | ) |
void matrix_negate(data_t *outmatrix, data_t *matrix, int rows, int cols);
negates all matrix elements
Definition at line 138 of file matrixOperations2.c.
void raise_matrix_to_power(data_t *outmatrix, data_t *matrix, int rows, int cols, int scalar);
raises all matrix elements to a power
Definition at line 169 of file matrixOperations2.c.
| void m_elem_sqrt | ( | matrix_t * | M | ) |
void matrix_sqrt(data_t *outmatrix, data_t *matrix, int rows, int cols);
applies sqrt to all matrix elements
Definition at line 123 of file matrixOperations2.c.
| void m_elem_truncate | ( | matrix_t * | M | ) |
void inv(dataem_t *outmatrix, data_t *matrix, int rows);
inverse of the matrix m_truncateAll
Truncates the entries in matrix M
ICA: void fix(data_t *outmatrix, data_t *matrix, int rows, int cols);
Definition at line 89 of file matrixOperations2.c.
void find(data_t *outvect, data_t **matrix, int rows, int cols); NOTE: this also assumes that outvect is a column vector) places the row indeces of non-zero elements in a vector This vector has additional, non-used space, not sure what to do about this -miller
Definition at line 320 of file matrixOperations2.c.
| void m_flipCols | ( | matrix_t * | M | ) |
m_flipCols
Swaps columns in M from left to right
ICA: void fliplr(data_t *outmatrix, data_t *matrix, int rows, int cols)
Definition at line 15 of file matrixOperations2.c.
| void m_fprint | ( | FILE * | stream, |
| matrix_t * | M | ||
| ) |
m_fprint
Prints matrix M to the stream specified Prints numRows, numCols, then each whole row of the matrix (aka [0][0], [0][1]..)
ICA: void print_matrix(data_t *matrix, int rows, int cols);
Definition at line 90 of file matrixOperations1.c.
| matrix_t* m_fread | ( | FILE * | stream | ) |
m_fread
reads matrix written by printMatrix in stream specified
Definition at line 153 of file matrixOperations1.c.
| void m_free | ( | matrix_t * | M | ) |
m_free
Frees memory for matrix M ICA: void free_matrix(data_t **matrix); void free_vector(data_t **vector);
Definition at line 73 of file matrixOperations1.c.
| matrix_t* m_fscan | ( | FILE * | stream | ) |
m_fscan
Scans matrix written by printMatrix in stream specified
Definition at line 131 of file matrixOperations1.c.
| void m_fwrite | ( | FILE * | stream, |
| matrix_t * | M | ||
| ) |
m_fwrite
Writes matrix M to the stream specified Writes numRows, numCols, then the data NOTE: will not work with submatrixes right now
Definition at line 112 of file matrixOperations1.c.
Definition at line 68 of file matrixOperations6.c.
| matrix_t* m_initialize | ( | int | mode, |
| int | numRows, | ||
| int | numCols | ||
| ) |
m_initialize
Returns a matrix pointer to a matrix of size M x N
Depending on the input variable "mode", data is either a 2D matrix of
ICA: void allocate_matrix(data_t **vector, int rows, int cols); void allocate_vector(data_t **vector, int length); void ones(data_t *onesMat, int rows, int cols); void eye(data_t *identity, int dimension); void fill_matrix(data_t *matrix, int rows, int cols);
Definition at line 26 of file matrixOperations1.c.
| void m_inverseMatrix | ( | matrix_t * | M | ) |
Definition at line 5 of file matrixOperations3.c.
Definition at line 37 of file matrixOperations5.c.
Definition at line 11 of file matrixOperations5.c.
void mean_of_matrix(data_t *outmatrix, data_t *matrix, int rows, int cols);
takes the mean value of each column
Definition at line 266 of file matrixOperations2.c.
void mean_of_matrix_by_rows(data_t *outmatrix,data_t *matrix,int rows,int cols);
takes the mean of the rows of a matrix, returns a col vect
Definition at line 303 of file matrixOperations2.c.
Definition at line 29 of file matrixOperations3.c.
| void m_normalize | ( | matrix_t * | M | ) |
void normalize(data_t *outmatrix, data_t *matrix, int rows, int cols);
normalizes the matrix
Definition at line 33 of file matrixOperations2.c.
Definition at line 57 of file matrixOperations5.c.
void reshape(data_t **outmatrix, int outRows, int outCols, data_t **matrix, int rows, int cols)
reshapes matrix by changing dimensions, keeping data
Definition at line 363 of file matrixOperations2.c.
Definition at line 51 of file matrixOperations3.c.
void sum_columns(data_t *outmatrix, data_t *matrix, int rows, int cols);
sums the columns of a matrix, returns a row vector
Definition at line 245 of file matrixOperations2.c.
void sum_rows(data_t *outmatrix, data_t *matrix, int rows, int cols);
sums the rows of a matrix, returns a col vect
Definition at line 282 of file matrixOperations2.c.
transpose matrix
This function transposes a matrix
ICA: void transpose(data_t *outmatrix, data_t *matrix, int rows, int cols);
Definition at line 346 of file matrixOperations2.c.
| void writePPMgrayscale | ( | char * | filename, |
| matrix_t * | M, | ||
| int | specCOl, | ||
| int | height, | ||
| int | width | ||
| ) |
Definition at line 168 of file matrixOperations6.c.


In this section, you can find out more about how to take advantage of our protein related features.
Other topics:


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Principal Component Analysis
The motivation behind using Principal Component Analysis is to solve the problem referred to as the curse of dimensionality. This is essentially the problem where there are thousands or even millions of features for each training instance which makes training extremely slow.
Dimensionality Reduction
In most real-word problems, the training instances are not spread out uniformly across all dimensions but instead highly correlated. Thus, we can often project a high dimension subspace to a lower-dimensional subspace.
Through Principal Component Analysis, we could project the data from a 2-Dimensional Subspace to a 1- Dimensional subspace along the "PCA 1st Dimension."
PCA Algorithm
- Standardize the data
- Compute the eigenvectors and the eigenvalues
- Compute the Covariance Matrix of the dataset
- Sort the eigenvectors and eigenvalues by decreasing value
- Pick the first k number of eigenvectors
- Use these eigenvectors to transform the samples onto the new subspace
Theory Behind PCA
- The Covariance matrix tells us the relationship between the variables.
- Eigenvectors give us the direction of the data while the Eigenvalues represent the magnitude or importance. Bigger values indicate the more important directions.
- The higher the eigenvalue, the higher the variance which indicates higher importance that we want to detect.
When to use PCA
- Reduce the number of variables taken into consideration
- To make variables independent of each other
Conclusion
I hope that you found this blog useful and that you gained some intuition behind the PCA algorithm. Now it is your turn to implement it!


DJ Greg James gets 'told off' by Will and Kate after he mocked Princess Charlotte on her first day of school
Royals asked for a quiet word…
by Nancy BrownRadio 1 DJ Greg James has revealed he got a telling off from the Duke and Duchess of Cambridge after he mocked their daughter Princess Charlotte on her first day of school.
The young royal started at St Thomas's Battersea back in September and, upon her arrival, the polite tot shook hands with her new teacher.
Accompanied by her mum, dad and elder brother Prince George, "excited" Charlotte made her way into class with the world watching.
Commenting on his breakfast show, Greg joked about the handshake and said: "Who the hell shakes hands with their teacher on the first day?"
Read more: Meghan Markle is named 2019's "most powerful dresser"
Fast-forward a couple of weeks and Greg bumps into the royal parents at Radio 1's Teen Hero Awards.
Greg said Prince William and Kate revealed they had been listening to the show on the morning that Charlotte started school and wanted a quiet word with him.
Greg revealed: "They said: 'We were listening on the morning of little Charlotte’s first day, and we want to talk to you about the handshaking thing....'"
He added: "I went: 'Oh God, no!'"
Read more: I'm A Celebrity viewers complain the show features too many adverts
Greg continued: "They’d heard me saying this school was so posh they had to shake hands with their teacher every day."
Trying to dig himself out of the hole, he added: "They were not like that in my day – you were pleased if you got a smile."
However, Greg seems to think all is forgiven with the royals.
He added: "I’m sure it’s all absolutely fine."
Earlier this week, the couple revealed that George and Charlotte had begged to attend the Royal Variety Performance with their parents, only to be told by Kate: "Not on a school night!"
Head to our Facebook page @EntertainmentDailyFix and let us know what you think of our story.


{{game.player2Email}} wins
{{game.player1Email}} Wins
Welcome {{game.playerEmail}}
Score: {{game.player2Death}}
Score: {{game.player1Death}}
{{message.userEmail}}: {{message.userMessage}}


Akan names are derived from Ghanian culture. Frequently in Ghana, children are given their first name as a 'day name' which corresponds to the day in the week they were born.
| DAY | MALE | FEMALE |
|---|---|---|
| Sunday | Kwasi | Akosua |
| Monday | Kwadwo | Adwoa |
| Tuesday | Kwabena | Abenaa |
| Wednesday | Kwaku | Akua |
| Thursday | Yaw | Yaa |
| Friday | Kofi | Afua |
| Saturday | Kwame | Ama |
This App takes your birthday and calculates the day of the week you were born and returns your Akan name instead.


Preview stock behavior given that:
Initial stock : INITSTOCK
Inflow rate : INFLOWRATE
Outflow rate : plus( OUTFLOWRATE_COEF + "Stock", OUTFLOWRATE_CONST )
Accuracy : ACCURACY
plural( "second", ACCURACY )
Period of observation : PERIOD
plural( "second", PERIOD )
RESULTS:
Final stock : FINALSTOCK
Stock behavior : stockBehaviorOverTime( STOCKBEHAVIOR )
SOLUTION


Neuro·D3
“A person can never walk on the same street twice. People recreate their city every time they experience it”-Nick Tyler, Neuroscience for cities
Through the last few years, we have collected big data from every imaginable digital field. Data-driven design can be defined as a decision-making approach to the design process that heavily relies on collecting data about people’s behavior and attitude.
In order to measure how people experience urban space and as a consequence how they behave inside of it, we need to understand the way they think, and how their brain functions. This is where neuroscience can help with the making of cities: understanding how people from a wide variety of perspectives can create their individual-yet-collective life in cities. With neuroscience we can discover how to help people respond to their sensorial perceptions so that this ecosystem can really work for them.
One important aspect of our life in the cities is User Experience. User Experience is how a user interacts with and experiences a space. It includes a person’s perceptions of utility, ease of use, and efficiency. User experience is subjective but the attributes that make it up are objective. We can learn more about user experience by exploring the way we perceive our environments.
Humans create cities based on their activities, while the city facilitates and limits our activities and behaviors. According to researchers from different scientific fields, buildings and cities have an impact upon the people – from physical to mental health, cognitive development and wellbeing to their levels of productivity.
Neuroscience and neurotechnology can offer us new ways to explore this impact, by helping urban professionals to create places that promote urban health and wellbeing, while mitigating the negative impacts of the city environment as far as possible.
In addition to this, new emerging digital technologies are offering us tools to work on bigger datasets. And for the first time in history many professionals from distinguishable disciplines are collaborating with the same objectives, working on new tools and new methodologies.
“With Neuroscience we can have a data-driven and data centered approach in design because what you are measuring is human data. However, we may have to come up with a new term (ss. Rather than Human-Centered) to describe a process where we capture data and people and the system makes decisions. We need to have a new, human-system-oriented, data-driven and common decision framework; a new archipelago”
You can explore the booklet of the project here: Neuro·D3


A demonstration of the ROAD method
The Regularized Optimal Affine Discriminant (ROAD) is a high-dimensional classification method, which was proposed by Fan et al. (2012)(pdf link). Currently, the code handles binary classifications, but extensions to multi-class will be available later. The following example illustrates how to apply ROAD.
Contents
Setting up the parameters
p = 1000; % number of variables n = 300; % number of observations s0 = 10; % number of nonzero mean differences rho = 0.5; % pairwise correlation coefficient randSeed = 1; % setup the random seed to let the program repeatable
Generate data
First, we generate the means and the common covariance matrix for the two classes. Then, we generate the training and testing data from the true multivariate guassian distributions.
mu1 = zeros(p,1); mu2 = zeros(p,1); mu2(1:s0) = 1; Sigma = eqcor(p,rho); rand('state', randSeed); randn('state',randSeed); nTrain = n; nTest = n; Y1Train = mvnrnd(repmat(mu1',nTrain,1),Sigma); Y2Train = mvnrnd(repmat(mu2',nTrain,1),Sigma); Y1Test = mvnrnd(repmat(mu1',nTest,1),Sigma); Y2Test = mvnrnd(repmat(mu2',nTest,1),Sigma); x = [Y1Train;Y2Train]; y = [zeros(n,1);ones(n,1)]; xtest = [Y1Test;Y2Test]; ytest = [zeros(n,1);ones(n,1)];
Test the ROAD method
Here we test the ROAD and screening-based versions S-ROAD1 and S-ROAD2. In the roadBatch function, the second to last parameter represents whether we use a diagonal-based version (0=no, 1=yes), and the last parameter represents whether we use a screening-based version (0=no, 1=1st version, 2=2nd version).
[ROADfit] = roadBatch(x, y, xtest, ytest, 0, 0) % ROAD [sROAD1fit] = roadBatch(x, y, xtest, ytest, 0, 1) % Screening-based ROAD version 1 (S-ROAD1) [sROAD2fit] = roadBatch(x, y, xtest, ytest, 0, 2) % Screening-based ROAD version 2 (S-ROAD2)


Scraping MIDI and tab files¶
DECIBEL uses a data set of audio, MIDI files and tabs. This data set is based on a subset of the Isophonics Reference Annotations [mauch2009omras2]. The Isophonics data set contains chord annotations for 180 Beatles songs, 20 songs by Queen, 7 songs by Carole King and 18 songs by Zweieck. In my experiments, I only used the songs by the Beatles and Queen, as there were no MIDI or tabs for Zweieck available and there were some inconsistencies in the Carole King annotations.
The decibel.file_scraper.midi_scraper
and decibel.file_scraper.tab_scraper
modules contains some handy
functions to automatically scrape a predefined list of MIDI and tab files from the internet. Using these functions, you
can either reproduce my experiments on the Isophonics dataset or create your own data set of MIDI and tab files.
Scraping MIDI files¶
This module contains all the methods you need for scraping either a single MIDI file or a predefined set of MIDI files from the Internet.
-
decibel.file_scraper.midi_scraper.
download_data_set_from_csv
(csv_path: str, midi_directory: str)[source]¶ Download a data set of MIDI files, as specified by the csv file in csv_path, and put them into midi_directory. If a MIDI file cannot be downloaded successfully, for example because the file already existed or because the Internet connection broke down, then the function continues with downloading the other MIDI files. After trying to download all prescribed MIDI files, this function returns a message indicating the number of MIDI files that were downloaded successfully and the number of MIDI files for which the download failed.
- Parameters
csv_path – Path to the csv file with lines in format [midi_name];[midi_url] (for example IndexMIDI.csv)
midi_directory – Local location for the downloaded files
-
decibel.file_scraper.midi_scraper.
download_midi
(midi_url: str, midi_directory: str, midi_name: str) -> (<class 'bool'>, <class 'str'>)[source]¶ Download a MIDI file from the Internet, using the midi_url and place it in the midi_directory, called midi_name. Return a message indicating success or failure.
- Parameters
midi_url – Location of the MIDI file on the Internet
midi_directory – Local directory where the MIDI file should be placed on your machine
midi_name – File name of your MIDI file
- Returns
Boolean and str message, indicating success or failure
Scraping Tab files¶
This module contains all the methods you need for scraping either a single tab file or a predefined set of tab files from the Internet.
-
decibel.file_scraper.tab_scraper.
download_data_set_from_csv
(csv_path: str, tab_directory: str)[source]¶ Download a data set of tab files, as specified by the csv file in csv_path, and put them into tab_directory. If a tab file cannot be downloaded successfully, for example because the file already existed or because the Internet connection broke down, then the function continues with downloading the other tab files. After trying to download all prescribed tab files, this function returns a message indicating the number of tab files that were downloaded successfully and the number of tab files for which the download failed.
- Parameters
csv_path – Path to the csv file with lines in format [url];[name];[key];[filename] (for example IndexTabs.csv)
tab_directory – Local location for the downloaded files
-
decibel.file_scraper.tab_scraper.
download_tab
(tab_url: str, tab_directory: str, tab_name: str) -> (<class 'bool'>, <class 'str'>)[source]¶ Download a tab file from the Internet, using the tab_url and place it in the tab_directory, called tab_name. Return a message indicating success or failure.
- Parameters
tab_url – Location of the tab file on the Internet
tab_directory – Local directory where the tab file should be placed on your machine
tab_name – File name of your tab file
- Returns
Boolean and str message, indicating success or failure
- mauch2009omras2
Mauch, Matthias, et al. “OMRAS2 metadata project 2009.” Proc. of 10th International Conference on Music Information Retrieval. 2009.


Module nakama.engine.defold
Nakama defold integration.
Functions
| uuid () | Returns a UUID from the device's mac address. |
| http (config, url_path, query_params, method, post_data, callback) | Make a HTTP request. |
| socket_create (config, on_message) | Create a new socket with message handler. |
| socket_connect (socket, callback) | Connect a created socket using web sockets. |
| socket_send (socket, message, callback) | Send a socket message. |
Functions
- uuid ()
-
Returns a UUID from the device's mac address.
Returns:
-
The UUID string.
- http (config, url_path, query_params, method, post_data, callback)
-
Make a HTTP request.
Parameters:
- config The http config table, see Defold docs.
- url_path The request URL.
- query_params Query params string.
- method The HTTP method string.
- post_data String of post data.
- callback The callback function.
Returns:
-
The mac address string.
- socket_create (config, on_message)
-
Create a new socket with message handler.
Parameters:
- config The socket config table, see Defold docs.
- on_message Your function to process socket messages.
Returns:
-
A socket table.
- socket_connect (socket, callback)
-
Connect a created socket using web sockets.
Parameters:
- socket The socket table, see socket_create.
- callback The callback function.
- socket_send (socket, message, callback)
-
Send a socket message.
Parameters:
- socket The socket table, see socket_create.
- message The message string to send.
- callback The callback function.


Make returning "make: Nothing to be done for `all'."
-
Bradley
I'm following the screencast tutorial steps and make doesn't produce the desired results:
$ ruby extconf.rb checking for ruby.h... yes creating Makefile $ make make: Nothing to be done for `all'.
Setup:
- OS X 10.6.4
- VIM 7.2.108
- ruby 1.8.7 (2009-06-12 patchlevel 174) [universal-darwin10.0]
-
Greg Hurrell
Did you install using the Vimball? Maybe not all of the files were correctly extracted. You could try re-extracting if that is the case.
If it did extract correctly then you should have the following in your
~/.vim/ruby/command-t
directory:Makefile controller.rb depend ext.c ext.h extconf.rb finder.rb match.c match.h match_window.rb matcher.c matcher.h prompt.rb ruby_compat.h scanner.rb settings.rb stub.rb vim/screen.rb vim/window.rb vim.rb
-
anonymous
I'm having the same problem:
- OSX 10.6.7
- ruby 1.8.7 (2009-06-12 patchlevel 174) [universal-darwin10.0]
- MacVim 7.3 (2010 Aug 15, compiled Aug 15 2010 22:03:01)
- gcc:
Using built-in specs. Target: i686-apple-darwin10 Configured with: /var/tmp/gcc/gcc-5664~89/src/configure --disable-checking --enable-werror --prefix=/usr --mandir=/share/man --enable-languages=c,objc,c++,obj-c++ --program-transform-name=/^[cg][^.-]*$/s/$/-4.2/ --with-slibdir=/usr/lib --build=i686-apple-darwin10 --program-prefix=i686-apple-darwin10- --host=x86_64-apple-darwin10 --target=i686-apple-darwin10 --with-gxx-include-dir=/include/c++/4.2.1 Thread model: posix gcc version 4.2.1 (Apple Inc. build 5664)
Here's the list of files extracted from the vimball:
. ├── Makefile ├── controller.rb ├── extconf.rb ├── finder │ ├── buffer_finder.rb │ └── file_finder.rb ├── finder.rb ├── match_window.rb ├── prompt.rb ├── scanner │ ├── buffer_scanner.rb │ └── file_scanner.rb ├── scanner.rb ├── settings.rb └── stub.rb
Looks like I'm missing a bunch of stuff from your example. I tried downloading from both your site and Vimscripts. This is version command-t-1.1b2.vba. I also tried the previous two versions with the same result. Weird.
-
Greg Hurrell
Yes, I've seen this a few times. I think this may be a bug in the Vimball implementation itself (that it can silently fail to extract some files, despite appearing to have succeeded). Just re-extract it and the missing files should appear.
-
anonymous
I found that using an older version of Vim (7.2) and making sure to extract from same directory as the vimball did the trick. So...
$> cd ~/Downloads $> /usr/bin/vim72 command-t-1.1b2.vba
Then extract as normal using
:so %
.Happily finding files now. Thanks for the great plugin.
-
anonymous
Hi. the first few times I tried to extract the vimball. I quit out of the list of files extracted with out looking at all of them. It seems kind of silly , but when I pushed the space bar and scrolled through all the files it worked fine. Then I could make an Command-T was happy. And me too.
Thank you much for this cool program.
Reply
This topic is now closed.


{% for pick in picks %}
{% include 'components/movie-info-row.html' with movie=pick %}
{% endfor %}
{% else %}
{% with image='images/login-error.svg' title='Log in required' description='In order to see the list and add movies to it, you have to be logged in.' %}
{% url 'login' as primary_action %}
{% url 'register' as secondary_action %}
{% include 'components/full-screen-message.html' with primary_button="Log in" secondary_button="Register" %}
{% endwith %}
{% endif %}
{% endblock %}
{% block bottom %}
{% include 'components/movie-info-overlay.html' %}
{% include 'messages/movie-card.html' with movie='' %}
{% include 'components/movie-info-row.html' with movie='' %}
{% endblock %}


--- layout: post title: "Functor variance compared to C#'s notion of variance" description: "A note on C# co- and contravariance, and how it relates to functors." date: 2021-10-25 5:53 UTC tags: [Software Design, F#] image: "/content/binary/contravariant-functor-diagram-for-action.png" image_alt: "Contravariant functor diagram." --- {% include JB/setup %}
{{ page.description }}
This article is an instalment in an article series about contravariant functors. It assumes that you've read the introduction, and a few of the examples.
If you know your way around C# you may know that the language has its own notion of co- and contravariance. Perhaps you're wondering how it fits with contravariant functors.
Quite well, fortunately.
For the C# perspective on co- and contravariance, the official documentation is already quite good. It starts with this example of assignment compatibility:
// Assignment compatibility. string str = "test"; // An object of a more derived type is assigned to an object of a less derived type. object obj = str;
This kind of assignment is always possible, because a string
is also already an object
. An upcast within the inheritance hierarchy is always possible, so C# automatically allows it.
F#, on the other hand, doesn't. If you try to do something similar in F#, it doesn't compile:
let str = "test" let obj : obj = str // Doesn't compile
The compiler error is:
This expression was expected to have type 'obj' but here has type 'string'
You have to explicitly use the upcast operator:
let str = "test" let obj = str :> obj
When you do that, the explicit type declaration of the value is redundant, so I removed it.
In this example, you can think of :>
as a function from string
to obj
: string -> obj
. In C#, the equivalent function would be Func<string, object>
.
These functions always exist for types that are properly related to each other, upcast-wise. You can think of it as a generic function 'a -> 'b
(or Func<A, B>
), with the proviso that A
must be 'upcastable' to B
:
In my head, I'd usually think about this as A being a subtype of B, but unless I explain what I mean by subtyping, it usually confuses people. I consider anything that can 'act as' something else a subtype. So string
is a subtype of object
, but I also consider TimeSpan
a subtype of IComparable
, because that cast is also always possible:
TimeSpan twoMinutes = TimeSpan.FromMinutes(2); IComparable comp = twoMinutes;
Once again, F# is only happy if you explicitly use the :>
operator:
let twoMinutes = TimeSpan.FromMinutes 2. let comp = twoMinutes :> IComparable
All this is surely old hat to any .NET developer with a few months of programming under his or her belt. All the same, I want to drive home one last point (that you already know): Automatic upcast conversions are transitive. Consider a class like HttpStyleUriParser, which is part of a small inheritance hierarchy: object -> UriParser -> HttpStyleUriParser
(sic, that's how the documentation denotes the inheritance hierarchy; be careful about the arrow direction!). You can upcast an HttpStyleUriParser
to both UriParser
and object
:
HttpStyleUriParser httParser = new HttpStyleUriParser(); UriParser parser = httParser; object op = httParser;
Again, the same is true in F#, but you have to explicitly use the :>
operator.
To recapitulate: C# has a built-in automatic conversion that upcasts. It's also built into F#, but here as an operator that you explicitly have to use. It's like an automatic function from subtype to supertype.
The C# documentation continues with an example of covariance:
// Covariance. IEnumerable<string> strings = new List<string>(); // An object that is instantiated with a more derived type argument // is assigned to an object instantiated with a less derived type argument. // Assignment compatibility is preserved. IEnumerable<object> objects = strings;
Since IEnumerable<T>
forms a (covariant) functor you can lift a function Func<A, B>
to a function from IEnumerable<A>
to IEnumerable<B>
. Consider the above example that goes from IEnumerable<string>
to IEnumerable<object>
. Let's modify the diagram from the functor article:
Since the C# compiler already knows that an automatic function (:>
) exists that converts string
to object
, it can automatically convert IEnumerable<string>
to IEnumerable<object>
. You don't have to call Select
to do this. The compiler does it for you.
How does it do that?
It looks for a little annotation on the generic type argument. For covariant types, the relevant keyword is out
. And, as expected, the T
in IEnumerable<T> is annotated with out
:
public interface IEnumerable<out T>
The same is true for Func<T, TResult>, which is both covariant and contravariant:
public delegate TResult Func<in T, out TResult>(T arg);
The in
keyword denotes contravariance, but we'll get to that shortly.
The reason that covariance is annotated with the out
keyword is that covariant type arguments usually sit in the return-type position. The rule is actually a little more nuanced than that, but I'll again refer you to Sandy Maguire's excellent book Thinking with Types if you're interested in the details.
So far, so good. What about contravariance? The C# documentation continues its example:
// Contravariance. // Assume that the following method is in the class: // static void SetObject(object o) { } Action<object> actObject = SetObject; // An object that is instantiated with a less derived type argument // is assigned to an object instantiated with a more derived type argument. // Assignment compatibility is reversed. Action<string> actString = actObject;
The Action<T> delegate gives rise to a contravariant functor. The T
is also annotated with the in
keyword, since the type argument sits in the input position:
public delegate void Action<in T>(T obj)
Again, let's modify the diagram from the article about contravariant functors:
Again, since the C# compiler already knows that an automatic function exists that converts string
to object
, it can automatically convert Action<object>
to Action<string>
. You don't have to call Contramap
to do this. The compiler does it for you.
It knows that Action<T>
is contravariant because it's annotated with the in
keyword. Thus, it allows contravariant assignment.
It all checks out.
The C# compiler understands co- and contravariance, but while it automatically supports it, it only deals with automatic conversion from subtype to supertype. Thus, for those kinds of conversions, you don't need a Select
or ContraMap
method.
The functor notion of co- and contravariance is a generalisation of how the C# compiler works.


A year in review;
We arose to begin our journey in the fall, and soared to new heights in the winter. Now, as we approach the end of this flight, we gather to reflect on three quarters of growth. Our five spring teams have been working hard to create beautiful, original sets for your viewing pleasure.
Come to our thirteenth exhibition, Voyage, to see the culmination of three quarters of growing, training, and challenging.
Sunday, June 2nd 2019 at 7PM
(Doors open at 6PM)
Ackerman Grand Ballroom
Admission is free, but seating is limited! Our past exhibitions have been fully packed, so make sure that you get a wristband as soon as you can!
if you are driving to this event, please find info on available parking lots below! Be sure to PAY BY SPACE.
Use this link to locate each parking lot. Simply type in the lot number in the search bar:
- By distance (closest to farthest): Lot 9, Lot 4, Lot 8
The '18-’19 year is coming to an end, and we can’t think of a better way to end spring quarter than with a little party.
Introducing FC's Spring 2019 Gala! The theme is Midsummer in the Mediterranean - dress your semi-formal best, grab a date and head down to Pauley Pavillion Club M10B on Wednesday, June 5th from 7:30-10:30 PM for a night to remember! Doors open at 7:00 PM.
The sun is shining, the birds are chirping, the flowers are in full bloom. Spring is here, and so is FC’s quarterly workshop series! Bounce down to Lot 4 P1 and learn some cool choreography from a variety of talented choreographers.
Stay tuned to this page and our social media for more information!
Not too big on commitment? There’s no better way to casually expand your dancing skill set than to check out a workshop happening this Friday with Trey Noh of the powerhouse better known as V MO! Make your way to Lot 4 P1 from 6-8PM on Friday, April 26th and pick up some spicy moves while you’re at it!


{% extends "layout.html" %} {% block pageTitle %} GOV.UK Prototype Kit {% endblock %} {% block content %}
This kit lets you rapidly create HTML prototypes of Census services.
It contains all you need to prototype anything from simple static pages to complex, data-driven transactions.
We recommend you add links to your prototype to this page, rather than delete it. You'll find this page in the kit at '/app/views/index.html'.
You can change the service name by editing the file '/app/config.js'.


Grandad with dementia missing from home with no wallet, money or form of ID
Mr Chandler is feared to be walking the streets in extremely cold temperatures
by Jenny KirkhamMerseyside Police confirmed at 11.30pm on Tuesday, November 19, that Gerard Chandler was located safe and well and returned home to his family.
An elderly man with dementia is missing from home with no wallet, money or form of ID.
Gerard Chandler was last seen in Old Swan at around 11am on Tuesday morning but has not been seen since.
Mr Chandler's family and police are becoming increasingly concerned for his wellbeing due to his dementia.
He has been described as 5"10, with a heavy build. When last seen, Gerard was wearing a navy anorak, grey trousers and black shoes.
On Facebook , his family have appealed for help in locating him and have advised people that he does not have any money or ID on him.
A post said: "Can everyone keep an eye out for our dad/grandad please.
"He has dementia and he’s been missing since 11 o’clock this morning in the Old Swan area with no wallet, money or form of ID.
"His name is Gerard Chandler, 5’10”, heavy set build. Wearing a navy jacket and grey pants."
"Would really appreciate it if everyone could have a look for him."
A spokesperson for Merseyside Police said: "Can you help? We are urgently appealing to find #missing man Gerard Chandler.
"Gerard suffers with Dementia & was last seen this morning in the #Stonycroft #Liverpool area wearing a navy blue anorak, dark grey trousers & black shoes.
"Any info or sightings call 101 or @MerPolCC ."


Region associated with a DataSet may indeed be rendered more often than you would have expected. This happens because certain events may change both the data contained inside the DataSet and its state. Sometimes instead only the data is changed, like after filtering or sorting, without affecting the state at all.
Since regions are designed to reflect both the data and the DataSet's state, they may react to changes that happens in quick succession.
There is no need to worry about this, even on very large amount of data the user experience is not affected.
Luga Data is designed to be as agnostic as possible regarding the REST endpoints it can consume. Unfortunately REST API can be really inconsistent, there is no way to design such functionality without enforcing severe constrains on the REST endpoint implementation it would consume. If you would like to such functionality you can extend the JavaScript classes and implement a .save() method that covers your specific needs.


Ronin Novelty Note 2 - Change the phone ringtone and notification sound
Document Id: KBDOC-00103
Created: 2011-10-02
Updated: 2011-10-10
Steps to change the phone ringtone for calls on your Ronin Novelty Note 2
- From the Settings screen, tap Personalization.
- Tap Sounds.
- Tap Ringtone.
- Tap your preferred ringtone.
- You've now changed the ringtone.
Steps to change the notification ringtone for texts on Ronin Novelty Note 2
- From the Settings screen, tap Personalization.
- Tap Sounds.
- Tap Text Tone.
- Tap your preferred ringtone.
- You've now changed the ringtone.
Steps to change the notification ringtone for emails on Ronin Novelty Note 2
- From the Settings screen, tap Personalization.
- Tap Sounds.
- Scroll to and tap New Mail.
- Tap your preferred ringtone.
- You've now changed the ringtone.
Tags: phone, changed, contacting, top, through, themselves


Select a date range to view:
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species:
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events:
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will be reviewed
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>
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Docs: surface
module¶
Contents:
-
euchar.surface.
bifiltration
(simplices, parametrization1, parametrization2, bins1, bins2)¶ Compute Euler characteristic surface of bifiltration.
- simplices
np.ndarray of shape (N, 3) or (N, 4). Each row is a simplex. For example [2 4 -1] is the edge (2,4) and [2 4 9] the triangle (2,4,9).
- parametrization1, parametrization2
np.ndarray of floats
- bins1, bins2
np.ndarrays of sorted floats, used to bin the parametrization values of simplices
- euler_char_surface
np.ndarray of integers
-
euchar.surface.
image_2D_and_function
(image, func, max_intensity=255, iterations=1, kwargs=None)¶ Compute the Euler characteristic surface of a give image with the bi-filtration given by sublevel sets of pixel values and iterative application of a given function on these sublevel sets.
- image
np.ndarray of integers
- iterations
number of times the function is applied to the image.
- func
function taking a sublevel set of image and returning a binary image of the same size.
- max_intensity
maximum value of elements in image
- kwargs
possible arguments of function func passed as a parameter.
- euler_char_surface
np.ndarray of integers
-
euchar.surface.
images_2D
(image1, image2, vector_of_euler_changes_2D=None, max_intensity1=255, max_intensity2=255)¶ Euler characteristic curve of a pair of 2D images.
This uses the vector of all possible Euler characteristic changes produced by a pixel insertion in 2D images. This is recomputed every time this function is called if it is not passes as a parameter.
- image1, image2
np.ndarray of integers
- vector_of_euler_changes_2D
list of integers, precomputed Euler characteristic changes produced by a single pixel insertion
- max_intensity1, max_intensity2
maximum value of any input of the form of image1 and image2
- euler_char_surface
np.ndarray of integers
-
euchar.surface.
images_3D
(image1, image2, vector_of_euler_changes_3D=None, max_intensity1=255, max_intensity2=255)¶ Euler characteristic surface of 3D images.
This uses the vector of all possible Euler characteristic changes produced by a voxel insertion in 3D images. This is must be passed as a parameter.
- image1, image2
np.ndarray of integers
- vector_of_euler_changes_3D
list of integers, precomputed Euler characteristic changes produced by a single voxel insertion
- max_intensity1, max_intensity2
maximum values of elements in image1 and image2
- euler_char_surface
np.ndarray of integers


--- title: R pkg development alongside packrat author: Ildi Czeller date: '2017-08-02' slug: r-pkg-development-alongside-packrat categories: ["R"] tags: ["packrat", "covr", "pkgdown"] ---
I use packrat for all my projects at Emarsys so for our internal packages as well as it eases collaboration. During package development there are numerous packages which come handy during development but not needed for usage. These are usually listed under the Suggests
or Enhances
field in the DESCRIPTION
file. But should these be tracked with packrat as well?
In my opinion, it depends. If it is testthat
or roxygen2
probably everyone contributing to the package will use it so it makes sense to track with packrat. However, if it is something only useful for a part of the package or you are experimenting with it like myself with covr
, pkgdown
or goodpractice
it makes sense not to make the project unnecessarily big and slow. In the following I will describe my experiences so far.
What makes all of this possible: the
packrat::with_extlib(packages = c(), expr = {})
command which basically allows you to use a library from outside your project library temporarily. Though I do not yet understand the subtleties of it, it already proved to be pretty useful.
It seems that with_extlib
does not load dependencies of used package so you need to manually add them (at least those for which you get an error otherwise).
packrat::with_extlib(
c("pkgdown", "pkgload", "pkgbuild",
"highlight", 'debugme', "processx"),
build_site()
)
I also tried calling build_site()
from the parent directory with pkgdown::build_site("folder_name_of_package")
but it failed after initializing, in the building home phase with the following error message:
pandoc: emsvisualizer/README.md: openFile: does not exist (No such file or directory)
Error: pandoc document conversion failed with error 1
You can use it from the parent directory without any problem if covr
is installed there:
covr::package_coverage("folder_name_of_package")
or to be more fancy
covr::shine(
covr::package_coverage(
"folder_name_of_package"
)
)
You can also use it from within the package directory.
packrat::with_extlib(
'covr',
{
library(covr)
covr::package_coverage()
}
)
However, if I run
packrat::with_extlib('covr', covr::package_coverage())
which was my first guess I get the following mysterious error message:
Warning: namespace ‘covr’ is not available and has been replaced
by .GlobalEnv when processing object ‘FUN.VALUE’
Error in tally_coverage(x, by = by) :
could not find function "tally_coverage"


host_name
host_name()
Return the machine's host name as a string.
Also see:
host_info
os_name
Core Module Index
|
Contents


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Photo Credits
We would like to warmly thank the many people who have
generously allowed us to use their wonderful photos of spiders and
insects. Copyright is retained by the respective photographers.
Photographers, in no particular order...
- Nick Monaghan www.lifeunseen.com
- Nicholas Fisher
- Alex Wild
- Greg Anderson
- Tom Murray
- Nicky Bay: Please refer to https://www.nickybay.com for online usage.
- Msc. José Miguel Díaz Miranda
- Jay Barnes: BugGuide user page
- Lisa Bentley
- Robert Whyte
- Iain Macaulay
- Mark Helle
- Flickr user Sankax
- Pavel Kirillov
- Nicholas Fisher
- Nick Monaghan
- Jim McLean


Kaite Donahue, Micaela McCall, Libby Aliberti, Mia Sievers
12-11-2018
So we analyzed data about dogs
# Make Histogram average height
import matplotlib.pyplot as plt
Ave_Height_Hist= plt.hist(Ave_Heights_Weights[:,0],color='skyblue', bins=20)
# Axis Labels
plt.xlabel('Average Height (Inches)')
plt.ylabel('# Dogs')
plt.title('Average Height of All Breeds')
# Save Image
plt.savefig('Ave_Height_Hist.png')
# Make Histagram of Average Weight
import matplotlib.pyplot as plt
Ave_Weight_Hist=plt.hist(Ave_Heights_Weights[:,1], color="skyblue", bins=20, )
#Axis Labels
plt.xlabel('Average Weight (lbs)')
plt.ylabel('# Dogs')
plt.title('Average Weight of All Breeds')
# Save Image
plt.savefig('Ave_Weight_Hist.png')
#Make Scatter Plot
import matplotlib.pyplot as plt
import matplotlib.pylab as plb
Ave_scatter= plt.scatter(Ave_Heights_Weights[:,0], Ave_Heights_Weights[:,1], s=[70], marker='*',color='skyblue')
#label axis
plt.xlabel('Average Height (Inches)')
plt.ylabel('Average Weight (lbs)')
plt.title('Average Height and Weight of All Breeds')
# Set axis limits
plt.xlim(1, 60)
plt.ylim(1, 190)
# Add trendline
z = np.polyfit(Ave_Heights_Weights[:,0], Ave_Heights_Weights[:,1],1)
p = np.poly1d(z)
plb.plot(Ave_Heights_Weights, p(Ave_Heights_Weights), 'm--')
#save figure
plt.savefig('Ave_scatter.png')
So first, we used KMeans clustering, which is an unsupervised learning technique, to cluster breeds based on their characteristics.
from sklearn.cluster import KMeans
from sklearn.preprocessing import StandardScaler
#scale
scaler=StandardScaler()
scaled_features=scaler.fit_transform(feature_array)
#create instance of KMeans clusters
kmeans=KMeans(n_clusters=5)
#fit to data
kmeans.fit(scaled_features)
#predict clusters
clusters=kmeans.predict(scaled_features)
We used t-SNE to plot the data in 2-dimensional space. The graph is colored by the KMeans clusters.
from sklearn.manifold import TSNE
#create instance of t-SNE
tsne=TSNE(learning_rate=100)
#fit t-SNE featres
tsne_features=tsne.fit_transform(scaled_features)breedlist=list(breeds.values.T.flatten())
##make plot
unique_clusters=list(set(clusters)) #cluster labels
cmap=cm.get_cmap("viridis",5) #color map
plt.scatter(x,y, alpha=0.5, c=clusters, label=unique_clusters, cmap=cmap, vmin=-0.5, vmax=4.4) #make graph
for x,y,breed in zip(x,y,breedlist):
plt.annotate(breed, (x,y), fontsize=4, alpha=0.5) #add labels
plt.scatter(x=cluster0['tsne0'],y=cluster0['tsne1'], alpha=0.5, c='red')
plt.title('KMeans Cluster 0')
zip0=zip(list(cluster0.tsne0), list(cluster0.tsne1), list(cluster0.breeds))
for x,y,breed in zip0:
plt.annotate(breed, (x,y), fontsize=6, alpha=0.5)
plt.savefig('src/visualization/cluster0.png')
#Here are the dogs that were clustered together by the KMearns clustering
#Conclusions - Our data formed 5 clusters based on height & weight - The average height was 19.5 inches and the average weight was 50.35 pounds, which is the average size of a Chesapeake Bay Retriever!
#Happy Holidays from Gitcha-Head-in-the-Game


Faster, easier, and reliable way of getting developer information in one portal for the decision making purposes for your organization.


This page shows a more complex usage of TinyMCE. On this page the mode is set to convert specific elements in this case a DIV element and a TEXTAREA into editor instances. The example below uses a custom CSS, thats why the text is red and it allso uses the "advanced" theme that includes more options than the default one. The code allso includes examples of custom call back functions and much more. Notice the submit button at the end of the page, this button triggers a save action. Read more about the features and possible settings of TinyMCE in the manual.
Some element, this is to be editor 2. This editor instance is a DIV element instead of a textarea.


--- layout: post title: 'moin-moin-after-taking-part-at-the-php' date: '2009-09-28T15:44:29+02:00' tags: [php, unconference] category: 'Programming' tumblr_url: http://andywenk.tumblr.com/post/199168434/moin-moin-after-taking-part-at-the-php ---
Moin Moin,
after taking part at the PHP Unconference this year in Hamburg and having a great time there, Judith Andresen had the idea to initialize a International PHP Unconference. I think this idea is just great. Not only german speaking PHP enthusiasts (and also people from other IT related areas), but also english speaking people will have the opportunity to attend to a real cool conference. The benefits are clear in my opinion:
- affordable costs
- due to the self structured and…


Provides tools for performing mathematical morphology operations, such as erosion and dilation, on data of arbitrary dimensionality. Can also be used for finding connected components, resampling, filtering, smoothing and other image processing-style operations.
| Version: | 1.5.3 |
| Imports: | methods, Rcpp |
| LinkingTo: | Rcpp |
| Suggests: | loder, testthat (≥ 0.9) |
| Published: | 2017-09-14 |
| Author: | Jon Clayden |
| Maintainer: | Jon Clayden <code at clayden.org> |
| BugReports: | https://github.com/jonclayden/mmand/issues |
| License: | GPL-2 |
| Copyright: | see file COPYRIGHTS |
| URL: | https://github.com/jonclayden/mmand |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| In views: | MedicalImaging |
| CRAN checks: | mmand results |
| Reference manual: | mmand.pdf |
| Package source: | mmand_1.5.3.tar.gz |
| Windows binaries: | r-devel: mmand_1.5.3.zip, r-release: mmand_1.5.3.zip, r-oldrel: mmand_1.5.3.zip |
| OS X binaries: | r-release: mmand_1.5.3.tgz, r-oldrel: mmand_1.5.3.tgz |
| Old sources: | mmand archive |
| Reverse imports: | corr2D, oasis |
| Reverse suggests: | RNiftyReg, spant, tractor.base |
Please use the canonical form https://CRAN.R-project.org/package=mmand to link to this page.


jack's hat
other 1/2 of TeenBrigade
Registered: Nov 2002
Location: Elven name: Merenwen Loss?lin So I live in the woods
Posts: 104 |
'Piece and Wore'-TF
Hey guys the next Teen Brigade installment is here soz about any spelling mistakes for those picky few. Well here it is the one I started. ENJOY!!!
‘Piece’ and ‘Wore’
“Those two are sooo boring.” Jack was trying to make small talk.
“Who are...oh.” Sam saw Jack’s face and guessed. Charlie and Jo had grown up a bit to fast for their liking. At the moment all they seemed to say to Sam and Jack were things like “Mum! I can't wear that, I wore that yesterday!” and “Dad, if I eat another piece of cake it will ruin my complexion!”
Little did they know that the best jokers around were taking them on a long ride.
“You just got bombarded by the teen brigade again,” sighed Sam. They both laughed very awkwardly.
Meanwhile, upstairs in their room, Charlie and Jo were in fits of laughter.
Finally Jo managed to stammer a sentence.
“Did you see his face?!?”
“Yeah, I know. He is, like, the king of the my-I-am-so-confused look!”
Neither of them could say any more for laughing.
“DAD!” Jack ran up the stairs to answer Charlie’s panicked shout.
“What?”
“How am I s’posed to wear this to the disco when it has been ironed?” Jack sighed. He should have known it would be this trivial. He left their room as Jo came up the stairs.
“You look nice,” he said. She stopped, turned to the door and ran in, desperate to get changed. Jack sighed again. Kids…
The SGC disco was a fairly grand affair, what with the mess hall being transformed into a dance hall. Jack accompanied Sam to the other side where seats and tables had been laid out, with a buffet on long tables set along the walls.
“Hey, guys.” It was Jonas.
“Hey, Jonas.”
“Hey, Daniel.”
“Where’re the teen brigade?”
“Dunno.” Jack sat down next to Jonas as Sam went for food. “Ya know, it’s hard being a dad. Harder than I thought. All they talk about is calories.”
“Well, that’s teenagers for you.”
“True.” Sam sat down with three plates of food. Jo sat next to Jonas.
“Hi, Jonas-Quinnus.” Jonas frowned. Charlie giggled, but offered an explanation.
“Blame him,” she said, pointing at Jack’s seat, which was now empty.
A few days later, Charlie was immersing herself in the latest shareware she’d downloaded from the Internet. EV Nova. Jack also played it, and Charlie thought that she might be able to register it because of that. She’d played it 42 times in 9 days. She was good.
“Hey hey!” Jo bounded into the room, but Charlie did nothing.
“I SAID hey hey!” No response. Jo looked over her shoulder at her adopted sister. “Oooh, what a surprise, you’re on that EZ Coca thingamabob.”
“It’s EV Nova, Jo. You should try it.”
“Mm, maybe. Didja hear those two?”
“Probably not. Why?”
“They’re talking about sitting us down and having a ‘talk’ about us growing up too fast.” Charlie looked up, a huge grin on her face.
“Hey! Does this mean that we can ask about going on missions?”
“Yup, totally!”
“Hey hey!”
“That’s my line.” They stared crossly at each other, but dissolved into a fit of giggles.
“Now listen. We know that you’re fifteen, but we feel that you’re considering things like cholesterol and stuff a little too early. You’re growing up, but you’re acting like you’re twenty. You get me?” asked Sam. Jack’s face was deadly serious. Jo and Charlie sighed.
“Loud and clear, but the thing is, we feel we’re responsible enough to be allowed on missions along with SG-1,” said Charlie. Sam and Jack glanced at each other.
“Well,” started Sam. “I’m not sure. I’ll talk to Jack and the general about it, but I can’t promise anything, ‘kay?”
“Yep.” Jo left the room. Charlie got up.
“We get it.” She left. Sam and Jack sighed. Kids…
“YES!” Jo and Charlie leapt up into a victory dance. Jack’s eyebrows leapt with them.
“You have GOT to be kidding me!”
“No, Jack, I’m not.” General Hammond had given them the authorisation they needed to go on missions. Sam sat there, quietly smiling to herself.
“They’ll learn.”
“What?”
“I said they’ll learn.”
“Oh.” Jack thought. “Learn what?”
“Do I look good or do I look good!” Jo jumped around in her new SG uniform. Charlie picked up a zat.
“Stylish.”
“Zat’s stylish!”
“Bad joke.” Sam walked in.
“Ready?” Charlie and Jo stood up.
“Yessir!” they replied. Sam led them to the gate room. Jack, Jonas and Teal’c were waiting.
“Love the hat, Jo.”
“Thanks, Dad.”
“Love the bandanna, Charlie.”
“Thanks.”
“SG-1, you have a go. Good luck,” said the general over the comm link. The new team strutted through the gate…
[GATE SEQUENCE!]
…into a forest. Jo surveyed the area.
“Cool.”
Movement in the bushes. Sam grabbed her zat, but she was unconscious a split second later. Jack and Teal’c followed suit.
Jonas, Charlie and Jo, meanwhile, were surveying the area around the gate. Movement again, but it was too slow for Jonas, who zatted it once. A flump. Charlie, the closest, took it upon herself to check it out.
“Ick.” It was a beast, very much like a tiger, but with a purple coat. It seemed to bee bleeding from an injury, caused by a staff weapon.
“Jaffa?” asked Jo. “Or Teal’c?” Jonas shrugged. Charlie looked up into the end of a staff weapon.
“Jaffa,” she confirmed.
“Our first mission.” Jo paced the cell. “The first.” Charlie sighed.
“Yes, so?”
“So! Nobody should get captured by evil snake-controlled people on their FIRST mission!”
“Most SG teams do,” pointed out Jonas.
“That’s not the point!”
“Yes it is,” murmured Charlie, but their bickering came to an abrupt end when they heard a huge explosion. Jonas jumped up.
“C4!” Charlie leapt up too, but the ceiling fell around them and she had to hop to avoid a large piece. Jack came through the hole and grabbed Jo.
“C’mon!” he yelled, but another piece fell on Charlie and rendered her unconscious. Jonas stooped to pick her up as Jack and Jo ran.
Teal’c dialled up the gate as Sam typed in the GDO code. Jack and Jo ran through, followed closely by Sam and Teal’c.
[GATE SEQUENCE]
They fell through and then all they could do was wait for Jonas and Charlie.
“C’mon, Jonas,” muttered Sam. But to no avail. The gate shut down.
***
“Damn!”
Jonas propped Charlie up by the DHD and redialled. The explosions were bigger. And closer. The seventh chevron engaged and Jonas fumbled for Charlie’s GDO. But she woke up.
“GDO!”
“Right.” She produced it from her pocket and entered the code. Jonas couldn’t wait. He picked her up and ran through.
***
The gate reopened. Sam twisseled round to see Jonas and Charlie dash through before Jonas collapsed. He did. Sam hugged him and Charlie. Charlie sighed. Jack grinned.
“Rethinking the mission thing?” Jo and Charlie exchanged glances.
“NO WAY!”
The End!
__________________
The Teen Brigade rulz
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