| Tags | dealing with conflict, stress management |
I had a conflict involving a team project when I was still in college. There were five of us in a group and our deadline was quickly approaching, but nobody seemed to really take the project seriously because they felt that we could finish off everything at the very last minute. I didn't want to work overnight on the last minute for the project because there could be a high chance of messing up and not being able to account for things that we normally could have accounted for if we spent more time thinking about it. The source of the conflict mainly came from two members of the group who didn't really care about the project or the grades they would receive on it and they were perfectly content with ruining the grades of the remainder of the team. My emotions upon anaylzing the conflict were primarily confused and anger. I couldn't understand how people could be this selfish and uncaring of other people. I felt that these people had no sense of empathy at all.
In the end, the three of us in the group that cared about the projecte ended up reporting the two students in our group that never showed up to our preliminary meetings and didn't contribute or communicate at all in email or online group meetings. We ended up just working on the project with the three of us and did well. However, we had much more work to do than other groups people because of our lack of members. If I could go back in time, I feel that one of the things I would have done would be to reason with the two members who didn't show up more than I did back in the day. I feel that maybe The three of us remaining group members could've got them to actively participate more. Maybe something serious was happening in their lives that we didn't know about, but we didn't bother to ask exactly why they never interacted with us. We just saw them as lazy and uncaring towards our common goal. I think I could've spent more time thinking in their shoes.
I learned from this experience that it's very important to be communicative and open with team members for any team project or else nobody will know what is going on inside your head. It's important to be proactive and talk to teammates that may be lagging behind or distracted and figure out the root of the problem so that everyone will feel better during a negative/awkward situation.


Lecture 01: Getting started¶
In this lecture, we will learn how to get started and work with the Designsafe interface.
About Designsafe¶
Designsafe-ci is a new cyberinfrastructure for the natural hazards community. Designsafe provides cloud-based tools that support support the analysis, visualization, and integration of diverse data types. They support an end-to-end research workflows, enhance, amplify, and link the capabilities of other NHERI components. The designsafe network is as shown below:
About OpenFOAM¶
OpenFOAM (Open Source Field Operation And Manipulation) is a free, open-source software that uses Finite Volume Method to numerically solve differential equations. It is often used for calculation of problems related to fluid mechanics. Today, it is not only used at universities but also widely in the industrial sector.
In a simplistic sense, it is a collection of C++ programs representing the solvers and the utilities used for data manipulation. Along with solvers and utilities, OpenFOAM also has pre-processing and post-processing capabilities that allow setting up of cases, boundary conditions and also visualize the results. The general structure of OpenFOAM is described in the figure below.
There are four main steps involved while using a CFD software:
Pre-processing: This involves preparing the geometry and the computational model. As a part of this, CAD / BIM models are prepared followed by a clean-up process. The CAD / BIM models are prepared by designers to enable the digital-twinning process and includes all the details of the geometry. However, for the CFD simulations, we do not require all the details. For example, if we have a flow around a building, then the fluid will not interact with the objects inside the building and these can be stripped off. During the clean-up process, the CAD/BIM models are prepared for the necessary simulation. In other words, the wet-volume is extracted as a part of the clean-up process.
Meshing: Here, the geometry is discretized by dividing it into cells. This process of mesh generation and assignment of element types helps us to convert our differential equations (i.e. Navier-Stokes equation) into a matrix equation. In OpenFOAM, this is achieved by two tools, namely
blockMesh
andsnappyHexMesh
. We will discuss about these utilities in Lecture 04 and 05 of the beginner series.Solving: Once the geometry has been discretized and problem has been defined (i.e. assignment of boundary conditions), the resulting matrix equations are now solved using linear and nonlinear matrix solvers like conjugate gradient etc. We will briefly mention the solvers in Lecture 02 but discuss more about these in the advanced series of this CFD Notebooks.
Post-processing: Once the simulation has completed running, it is necessary to visualize the results and the quantities of interest. In this regard, we will use Paraview as a post-processing tool.
In order to run the siimulations, OpenFOAM uses set of files (called as dictionaries). These dictionaries are arranged in three main folders. We will be discussing all about this in the Lecture 02 of the beginner series.
In this lecture, we will only on learning the process to submit an OpenFOAM job through our Jupyter notebook and opening the result files using Paraview. In the upcoming lectures, we will see various aspects of OpenFOAM and how to modify them.
Jupyter Notebooks¶
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible: configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular: write plugins that add new components and integrate with existing ones. A Jupyter notebook is an interface that connects to the kernel. The kernel executes the code sent by the user and communicate back its results. This kernel is connected and remains active even if the web browser is closed. Once the notebook is opened again, the web application automatically re-connects to the kernel.
The Jupyter notebooks are made of cells of different types:
Markdown cells: These are cells used to write headings, descriptions and comments. These cells do not include python codes that need to be executed. Instead, here a Markdown language is used to define headings, lists, pure HTML and even equations using LaTeX.
Code cells: These are cells that include codes that need to be run. The method to execute these codes is by using Shift-Enter. This will execute the code on the kernel and show the output.
Common shortcuts¶
Some of the common shortcuts include:
Execute a run:
Shift-Enter
. Here the current cell is executed, show outputs (if any) and then moves to the next cell.Execute (in place):
Ctrl-Enter
. Here, the current cell is executed, show outputs (if any) and continues to be in the same cell. Once the execution is complete, the entire block of code is selected and one can start typing over it to execute the next command. This is a terminal style execution.Execute (and add new cell):
Alt-Enter
. Here, the current cell is executed, show outputs (if any) and creates a new cell below.
Computing allocations¶
Designsafe allocates 8000 service units (SU) for computing and 50GB of storage space. 8000 SU’s is crudely 8000 hours of cloud-computing time. To be more precise, 1 SU is equivalent to one hour of wall clock time on a single processor core of time used. The computing times are calculated for all computations run through the Workspace, through Jupyter notebooks or even direct CLI.
Additional allocations¶
An additional Allocation on DesignSafe is headed by a project PI, who can be
NSF Graduate Student Researcher Fellows
Research staff employed by federal agencies or non-NSF FFRDCs
State educational offices or organizations and local school districts, a teacher or educator at an accredited public or private K-12 school in the USA
Independent museums, observatories, libraries, research laboratories, professional societies and similar organizations in the United States that are directly associated with educational or research activities in the USA
U.S. commerial organizations, especially small businesses with strong capabilities in scientific or engineering research or education may apply for an allocation
One can request for additional computing allocations by raising a help ticket through the designsafe portal. Please include:
Information about the eligibility of the requestor
A description of the research to be performed
Sources of support
Justification for the number of SUs requested.


About Me
My name is Dan Merkl. I am excited to learn an overwhelming amount of knowledge in software development over these next three months. I graduated with a degree in Social Science but somehow found myself working in the mortgage industry for two years and then transitioned into auditing for a year. I've spent a lot of time navigating different system/programs and thought it would be more exciting to be the person developing those programs. That's what bring me here today!
For fun, I like being active, going camping, and relaxing at home. Lately I’ve been getting into kettlebell workouts and learning the different movements. It’s changed the way I work out and I feel like I’m in some of the best shape of my life now. When I’m not swinging kettlebells around I’m usually watching Netflix or reading something. My favorite show to watch on Netflix has been The Office. It’s a show I can turn on as background noise and tune in briefly for a good laugh or sit and binge it for hours.


{{ include('snippets/meta.html', {"title": "Plenty Admin Sign In", "description": "This is the sign in page of the admin UI", "author": "Jamie McDonnell"}) }}


--- layout: slate ---
Well, not wrong, but there is an easier way to view these files:
{% comment %}I hate hard-coding things like this, but I see no way to pass a site variable to an `includes` (sadface) Also, blindly assume it's hosted on GitHub.com. If they want to change it, they can do so manually.{% endcomment %}


David Boreanz, Seth Rogen set for special editions of 'Price is Right'
by Karen ButlerNov. 23 (UPI) -- CBS has announced plans to air this winter two celebrity editions of the game show The Price is Right.
Drew Carey will host The Price is Right at Night: A Holiday Extravaganza with the Cast of Seal Team on Dec. 22 and The Price is Right at Night: A Holiday Extravaganza with Seth Rogen on Dec. 23.
"Series star David Boreanaz and additional cast members from CBS' Seal Team kick off the two-night event when they welcome an audience full of active duty military and veterans to the special prime-time show. Boreanaz and cast will play for the charity Headstrong Project, which provides mental health treatment for post-9/11 veterans and their families," a network press release said.
The next night actor and comedian Seth Rogen will play for Hilarity for Charity, "the national Alzheimer's nonprofit organization founded by him and his wife, Lauren Miller Rogen, and dedicated to raising awareness, inspiring change and accelerating progress in Alzheimer's care, research and support."


I'am raneem abu jamous , from jordan , born in 1998 actually in 1998/12/21 so i considred my self born in 1999 I'm afraid of getting old and my youth is gone hhhhh
I am stadying electrical engineering in albalqa'a i relly don't like my University but i like my branch it is like me shine every thing around it
I don't have a favorite hobby, but I love sports a lot. I feel detached from everything around me. It's my self-love time And love to travel a lot. One of my wishes is to travel around the world, but I didn't get the chance yet
actually i love food soooooooo much , i can't count how many food is my favorite but let me cheat you if you will invite me someday shawerma,makhse,kabsa,lazamia,and every thing i made it


--- layout: default title: Home bg: '#0fbfcf' ---
Established in 2006, Blossom Academy is a dynamic educational daycare for children between the ages of 18 months to 5 years old.
The daycare is located in the vibrant Notre-Dame-de-Grace neighbourhood of Montreal, QC in Canada (see our Contact Us page to reach us).
Registration and enrollment is based on availability which varies each academic year.
Daycare education marks the beginning of learning to interact in a group, and for all children it is the beginning of daycare.
Daycare education gives children a liking for school, promotes children’s development by motivating them to exploit their full potential.
The social and cognitive basis developed in our daycare will prepare children for their future schooling and allow them to continue to learn throughout their lives.


This is the partial for view 2.
Showing of 'interpolate' filter: {{ 'Current version is v%VERSION%.' | interpolate }}
Learn more


[
Viewing Hints
] [
Exercise Solutions
] [
Volume 2
] [
Free Newsletter
]
[
Seminars
] [
Seminars on CD ROM
] [
Consulting
]
Thinking in C++, 2nd ed. Volume 1
©2000 by Bruce Eckel


This example demonstrates responsive design. There is two overlays: one which is sized and positioned with absolute length units, and one which uses relative length units and therefor behaves responsive.
Play with the developer tools to resize the web page or change your browsers window size to see the effect. If you set the size of the web page to 1920 x 1080 pixels (or you enter fullscreen mode with that screen resolution) you will see the two overlays converge.


Function includeDir
Catapult's built in Autoload function when using composer this is not needed,
Located at
Autoload.php
Parameters summary
|
$path |
Catapult's built in Autoload function when using composer this is not needed,
|
$path |


Train Toute Showing ::Dhaka to Rajshahi::Class- S_CHAIR:: 3-3-19
| |
Serial |
Train No |
Train Name |
Departure Time |
Action |
| |
1 |
769 |
DHUMKATU_EXPRESS |
06:00 |
|
| |
2 |
759 |
PADMA EXPRESS |
23:10 |
|
| |
3 |
753 |
SILKCITY |
14:40 |
|
| Serial |
Station Name |
Departure Time |
| 1 |
Dhaka |
06:00 |
| 2 |
BIMAN_BANDAR |
06:32 |
| 3 |
JAYDEBPUR |
06:57 |


$1540
| 120$ | Orders |
| 15$ | Investments |
| 55$ | Others |
tue
wed
thu
fri
sat
sun
mon
300
250
200
150
100
50
26
15%
12
11%
104
5%
29
84%
Recent orders
Status |
Clients |
Orders# |
Date |
|---|---|---|---|
| Paid Active | John Doe | 3435362 | Today 8:30 |
| Paid Active | Thomas Bayer | 3435362 | Today 16:30 |
| Paid Inactive | Nicolas Karabat | 3435362 | Yesterday |
| Unpaid Inactive | Alexandre Pome | 3435362 | 23th May |
| Paid Active | John Doe | 3435362 | Today 8:30 |
| Paid Active | Thomas Bayer | 3435362 | Today 16:30 |
| Paid Inactive | Nicolas Karabat | 3435362 | Yesterday |
| Unpaid Inactive | Alexandre Pome | 3435362 | 23th May |
Comments
That’s a great idea! I’m sure we could start this project as soon as possible.
Let’s meet tomorow!
Recent tickets
Status |
Subject |
Department |
Date |
|---|---|---|---|
| Open | Website down for one week | Support | Today 8:30 |
| Open | Restoring default settings | Support | Today 16:30 |
| Progress | Loosing control on server | Support | Yesterday |
| Closed | Authorizations keys | Support | 23th May |
That’s a great idea! I’m sure we could start this project as soon as possible.
Let’s meet tomorow!


About Me
My name is Aunri Stampley. I was born and raised in New Orleans, LA.
I am 30 years old. I enjoy working out, playing video games, browsing
the web, taking naps and spending time with loved ones. I was previously married and I have no kids. I recently finished a six year tour in the Navy and am in the middle of a career change.
Education/Experience
- Code Fellows graduate
- Executive Assistant in the Navy from 2011-2017
- Southeastern Louisiana University (Business Management 2005-2007)
Goals
- Get hired as an entry level developer
- Invest into the stock market
- Get down from 217 lbs to 205 lbs
Top Ten Hip Hop Artists
- Biggie
- Lil Wayne
- Jay-Z
- Nas
- ATCQ
- Outkast
- Kendrick Lamar
- Drake
- Kanye West
- Redman


Saghir Bashir (www.ilustat.com)
Life scientists, economists, ecologists, computer scientists, social scientists, linguists, mathematicians, physcists and many others have or are choosing data science as a career. The treasure trove of backgrounds presents knowledge sharing opportunities and challenges alike. However for newcomers this career transition and continuous development can be overwhelming and leave some of them with feelings of not belonging or lacking competence, characteristics of impostor’s syndrome. Educators, mentors, trainers and managers have a crucial role to play in developing newcomers to become competent and confident data scientists.
Data science is essentially composed of:
- Subject matter expertise
- Statistics
- Statistical programming
An individual could be proficient in all three but that is not usually the case. There could be different individuals representing the three components which in a sense is still “data science”. In reality, newcomers want to master 2 and 3 often placing a greater emphasis on 3. That leaves a gap in 1 and 2, the subject matter expertise and statistics. These are the foundations on which good data science is built and which need to be emphasised more in the learning and development process.
Data science starts with a collaboration with or request from a subject matter expert (e.g. ecologist, biologist, economist). The starting point could be some existing data or the need to collect new data to answer some questions of interest (e.g. identifying factors that influence some outcome). The data will have some history and definitions that need to be understood by the data scientist before embarking on any programming or statistical analysis. From the beginning it is usually an iterative process between the data scientist and the subject matter expert until the work is finalised. Building this into the learning and development of newcomers to data science is essential but no easy feat. This challenge is programming language independent.
There are many learning resources for most statistical programming languages (including for R) and data science. Newcomers are taught to perform different tasks, for example, plot data on a graph, read in data, create new variables, etc. The next step tends to be for them to explore real datasets often with limited to no statistical and subject area knowledge support leaving them vulnerable to making basic mistakes and adopting bad practices. Addressing these issues early could save a lot of heartache later.
The first point to accept is that there is no one size fits all approach. Tailoring a plan for each individual is in most situations unrealistic and unfeasible. However there are some common features that should be considered whichever approach is taken.
Finding Example Data
I stress and procrastinate the most about finding “the right” dataset(s) to stimulate discussion and interest. Many of the real life dataset that I would like to use are subject to confidentiality clauses or contain sensitive data that cannot be shared. Fortunately there are many R packages with datasets that can be used1. Knowing which one is “right” means understanding your target audience. A dataset that works well in one environment may not work in another although some can have global appeal (e.g. the gapminder
data). Choose carefully.
Having the “right” dataset means having real life questions (which can be exploratory) that are of interest to the target audience. The answers to these questions should feed into decision making processes or actions that can be taken. A subject matter expert could be consulted for support. This answers the “why” of the data.
The “what”, “why”, “when” and “how” of data must be explained before the audience start to process and analyse the data. Understanding the appropriateness, quality, validity and how the data were pre-processed empowers data scientists to find the best path for analysis, again in collaboration with the subject matter expert. It seems intuitive until you use learning resources where datasets are not (adequately) introduced or are changed without explanation.
Statistical Analysis
Newcomers are often taught to make their work reproducible and this practice is to be strongly encouraged for good reasons. The bigger aim should be to present “trustworthy data science”2 which incorporates reproducibility. It encourages full openness and transparency about all the strengths and weaknesses. This approach can be used to nudge newcomers into understanding the methods (models) they use and not to treat them as black boxes. A better understanding of the methods used increases the quality and value of interactions with subject matter experts.
Many newcomers can find the statistical part of data science daunting and complex. Their fears can be eased by making a connection to data as described above hence smoothing their route into, what may seem like, an “abstract” world of statistics. The key concepts and structure of most models can be developed through the questions and data (i.e., design and variables) which can then initially be expressed as some “mathematical” representation. Assumptions can be discussed and challenged in the context of interpreting the results with the subject matter expert. The cycle can be closed by addressing what will be communicated (and how) to answer the questions of interest.
Good reporting practices3 4 are important in building a culture of full accessibility through openness and transparency. These on top of reproducibility strengthen data science work by answering the “what” and “why” along with the “how” which in turn will allow the “future newcomer” to return to past work more easily. This approach also makes the process of handing projects over to others or receiving ongoing projects from others much smoother.
Global Audience
If you practice your data science on a computer that is less than five years old with constant access to electricity and internet then spare a thought for the Majority World countries (commonly referred to as “Third World”) and austerity affected European countries. Having taught in and collaborated with people in both classes of countries I learnt more about their day to day challenges.
Computers are often desktops connected to CRT monitors, that are more than 10 years old. In austerity affected European countries the public sector faced budget cuts forcing IT needs to very low down on the list of priorities. For most people, their priority was keeping their job even with significant reductions in pay and benefits.
It surprises me that so many computers continue to work in Majority World countries where electricity is not constant and is lost without notice (think of those hard disks). Clearly without electricity there is no internet access which even with electricity is not constant either. Users can have usage limits which are a function of time and/or download limits. Free access to websites and on-line communities, in many cases, is a luxury. On-line video training materials can be made accessible by providing documents, files and access to audio format or lower quality video. For instance a simple measure of accessibility can be to reference in a video exactly what you are talking about (e.g. “on slide 7…”, “in the top right hand side of the graph…”) to aid users who have ripped the audio or lower quality video.
If you want a true global reach with your educational materials then think of what you can do to reduce the size of what has to be downloaded and how your code can run on “less” powerful computers with limited internet access. Along with making code readable (à la R tidyverse
) you have the additional challenge of making it accessible which is a great way to learn new R tricks. When faced with these challenges, I use an older low specification laptop for testing purposes when developing or adapting courses.
Summary
In this post I have shared some of my thoughts on how data science education can be strengthened. I discussed integrating real life data science practices into learning and development activities especially by engaging subject matter experts and better integration of statistical methods. If you want real global reach then integrate access to Majority World and austerity affected countries into your offerings. By doing so you will also develop.
For a list of some of datasets available in R see: http://ilustat.com/shared/what_data_r/ (source code at https://github.com/saghirb/WhatData)↩
Some slides of a talk I gave about Trustworthy Data Science: https://speakerdeck.com/saghirb/when-to-trust-and-when-not-to-trust-data-science↩
Various guidelines for reporting of health research: https://www.equator-network.org/↩
A Guidance document on Statistical Reporting: https://www.efsa.europa.eu/en/efsajournal/pub/3908↩


eXplain$.io is a platform to run multi-agent simulations to help with your trade.
eXplain$.io uses different modelling to give near-future projections in an amnesic economy that is constantly distracted by black swan events.
How Does eXplain$.io work?
Step 1. lay out your fundamentals in the form of parameters
e.g. existing speculator vs investor ratio among holders of the asset, distribution of hedge funds, retails, etc holding the asset
Step 2. Use the default eXplain$ setting.
Or choose for each asset an “evolution co-efficient” of the speculator vs investor ratio (as a function of time), etc
Step 3. Pay & run your eXplain$ simulations. This will give you confidence scores on difference price projections in the next 2~4 hours.
Step 4. ???
Step 5. Profit $$$


Hello, World! I am located at ${location}
I provide access to ${len(containers)} Child Resources
${container}


BENADRYL READYMIST ITCH STOPPING- diphenhydramine hydrochloride and zinc acetate spray
Johnson & Johnson Consumer Products Company, Division of Johnson & Johnson Consumer Companies, Inc.
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
| Active ingredients |
Purpose |
| Diphenhydramine hydrochloride 2% |
Topical analgesic |
| Zinc acetate 0.1% |
Skin protectant |
Uses
- temporarily relieves pain and itching associated with:
- insect bites
- minor burns
- sunburn
- minor skin irritations
- minor cuts
- scrapes
- rashes due to poison ivy, poison oak, and poison sumac
- dries the oozing and weeping of poison ivy, poison oak, and poison sumac
Warnings
For external use only.
Flammable. Keep away from fire or flame.
Do not use
- on large areas of the body
- with any other product containing diphenhydramine, even one taken by mouth
Ask a doctor before use
- on chicken pox
- on measles
When using this product avoid contact with eyes
Stop use and ask a doctor if
- condition worsens or does not improve within 7 days
- symptoms persist for more than 7 days or clear up and occur again within a few days
Keep out of reach of children. If swallowed, get medical help or contact a Poison Control Center right away.
Directions
- do not use more than directed
- adults and children 2 years of age and older: spray on affected area not more than 3 to 4 times daily
- children under 2 years of age: ask a doctor
Other Information
- store at 20° to 25° C (68° to 77° F)
Inactive ingredients
alcohol, glycerin, povidone, purified water, tromethamine
Questions?
call 1-800-524-2624 (English/Spanish)
Distributed by:
Johnson & Johnson
Consumer Products Company
Division of Johnson & Johnson
Consumer Companies, Inc.
Skillman, NJ 08558
PRINCIPAL DISPLAY PANEL - 7 mL Can Blister Pack
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ITCH STOPPING SPRAY
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FOR
EXTERNAL
USE ONLY
Insect
Bites
Poison Ivy,
Oak, Sumac
Mosquito
Bites
Sunburn
Minor Cuts
& Scrapes
0.2 FL OZ (7mL)
Johnson & Johnson Consumer Products Company, Division of Johnson & Johnson Consumer Companies, Inc.


Liana is a Freelance, Full-Stack Developer & MBA focused on attention to detail, working collaboratively with team members and contributing to the overall success of the team. Technical skills include HTML, CSS, Bootstrap, JavaScript/jQuery, Node, Express, MongoDB, React.js & MySQL. Tools used are GitHub, Slack methodology, in addition to being an accomplished Project & Business Manager, Senior Sales Associate with over 12 years experience.
Modern, clean, unique and mobile-ready websites that will help you create an online presence and grow your business
Logo, collateral and graphic designs that promote your brand & business
Creating interesting and effective brands that give your business an edge in your target market
Helping you find additional talents needed to build your business, such as photographers, videographers and copywriters
Coordinate events and daily activities of the Studio Mentoring and training of new teachers Maintainted and updated Squarespace website
First Choice Coffee Services offers premium office coffee and beverages solutions, the latest, upscale and environmentally friendly options for businesses employees and their clients Left to persue Full-Stack Engineering
Mercury Matrix was a 3rd party outsourced sales and marketing firm under contract with CenturyLink to help promote and expand the FiberOptic footprint in Minnesota. Contract with CenturyLink ended in 2017 and the company disbanded.
Certificate in Full-Stack Web Development, focused on the MERN Stack
Applied Masters of Business Administration in Small Business & Entreprenurship
1000+ Hour Certification
Bachelor of Arts in Dietetics
Thanks, your message has been sent. I'll be in touch shortly.


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$1.50 would be needed to be able to unlock this feature. This is because as of recently, the bot
has become more used and over time has used a trendous amount of both storage space and processing
to be able to utilise all these custom backgrounds. All previously set custom backgrounds will not
be removed however to change it you will require to do the one time payment. This is simply put to
show support for the development of the bot as recently the bot now requires over 100 Gigabytes of
storage for storing both these custom backgrounds and 1 week cached images, its a little gesture
that you support the bot. Despite making custom backgrounds paid for again, there are still a
large amount of free backgrounds and once you have paid for custom backgrounds you are able to
apply this to any server


Basic Data Viewer
Advanced Data Viewer
Basic Result Viewer
Advanced Result Viewer
FSP Advanced Result Viewer
Compute
Members
Tasks Assigned
Hours Assigned


Edit Profile
Find a Venue
Profile
Log Out
Contact the Band
Full Name
Email address
Phone Number
Subject
Message


This opens the export pilot point panel. In the panel, basic pilot point attributes such as pilot point name, spectrum name, fatigue mission (in case it is overridden by the pilot point) and etc. can be edited. You can also supply a descriptive image for the pilot point when available. This will export the pilot point with the information into a zip archive. The archive can then be sent to the database administrator for uploading into ESCSAS database.


pymilvus¶
Example¶
You can find a example script in example.py.
Module Contents¶
Version¶
Get version of pymilvus by Milvus.__version__
.
Client¶
-
class
milvus.
Milvus
(host=None, port=None, handler='GRPC', **kwargs)[source]¶ Bases:
object
-
add_vectors
(collection_name, records, ids=None, partition_tag=None, params=None, **kwargs)¶ Insert vectors to a collection.
- Parameters
ids (list[int]) -- list of id
collection_name (str) -- Name of the collection to insert vectors to.
records -- List of vectors to insert.
partition_tag (str or None. If partition_tag is None, vectors will be inserted to the collection rather than partitions.) -- Tag of a partition.
timeout (int) -- Time to wait for server response before timeout.
- Returns
Status: Whether vectors are inserted successfully. ids: IDs of the inserted vectors.
- Return type
(Status, list(int))
-
client_version
()[source]¶ Returns the version of the client.
- Returns
Version of the client.
- Return type
(str)
-
compact
(collection_name, timeout=None, **kwargs)[source]¶ Compacts segments in a collection. This function is recommended after deleting vectors.
- Parameters
collection_name (str) -- Name of the collections to compact.
-
count_collection
(collection_name, timeout=10)[source]¶ Returns the number of vectors in a collection.
- Parameters
collection_name (str) -- target table name.
- Returns
Status: indicate if operation is successful
res: int, table row count
-
create_collection
(param, timeout=10)[source]¶ Creates a collection.
- Parameters
param (dict) --
Information needed to create a collection.
- `param={'collection_name': 'name',
'dimension': 16, 'index_file_size': 1024 (default)， 'metric_type': Metric_type.L2 (default) }`
timeout (double) -- Timeout in seconds.
- Returns
Whether the operation is successful.
- Return type
-
create_index
(collection_name, index_type=None, params=None, timeout=None, **kwargs)[source]¶ Creates index for a collection.
- Parameters
collection_name (str) -- Collection used to create index.
index -- index params
timeout (int) --
grpc request timeout.
if timeout = -1, method invoke a synchronous call, waiting util grpc response else method invoke a asynchronous call, timeout work here
- Returns
Whether the operation is successful.
-
create_partition
(collection_name, partition_tag, timeout=10)[source]¶ create a partition for a collection.
- Parameters
collection_name (str) -- Name of the collection.
partition_name (str) -- Name of the partition.
partition_tag (str) -- Name of the partition tag.
timeout (int) -- time waiting for response.
- Returns
Status: Whether the operation is successful.
-
delete_by_id
(collection_name, id_array, timeout=None)[source]¶ Deletes vectors in a collection by vector ID.
-
describe_collection
(collection_name, timeout=10)[source]¶ Returns information of a collection.
- Parameters
collection_name (str) -- Name of the collection to describe.
- Returns
(Status, table_schema) Status: indicate if query is successful table_schema: return when operation is successful
- Return type
(Status, TableSchema)
-
describe_index
(collection_name, timeout=10)[source]¶ Show index information of a collection.
- Parameters
collection_name (str) -- table name been queried
- Returns
Status: Whether the operation is successful. IndexSchema:
-
drop_collection
(collection_name, timeout=10)[source]¶ Deletes a collection by name.
- Parameters
collection_name (str) -- Name of the table being deleted
- Returns
Status, indicate if operation is successful
- Return type
-
drop_index
(collection_name, timeout=10)[source]¶ Removes an index.
- Parameters
collection_name (str) -- target collection name.
- Returns
Status: Whether the operation is successful.
：:rtype: Status
-
drop_partition
(collection_name, partition_tag, timeout=10)[source]¶ Deletes a partition in a collection.
- Parameters
collection_name (str) -- Collection name.
partition_tag (str) -- Partition name.
timeout (int) -- time waiting for response.
- Returns
Status: Whether the operation is successful.
-
flush
(collection_name_array=None, **kwargs)[source]¶ Flushes vector data in one collection or multiple collections to disk.
- Parameters
collection_name -- Name of one or multiple collections to flush.
-
property
handler
¶
-
has_collection
(collection_name, timeout=10)[source]¶ Checks whether a collection exists.
- Parameters
collection_name (str) -- Name of the collection to check.
timeout (int) -- Timeout in seconds.
- Returns
Status: indicate whether the operation is successful. bool if given collection_name exists
-
insert
(collection_name, records, ids=None, partition_tag=None, params=None, **kwargs)[source]¶ Insert vectors to a collection.
- Parameters
ids (list[int]) -- list of id
collection_name (str) -- Name of the collection to insert vectors to.
records -- List of vectors to insert.
partition_tag (str or None. If partition_tag is None, vectors will be inserted to the collection rather than partitions.) -- Tag of a partition.
timeout (int) -- Time to wait for server response before timeout.
- Returns
Status: Whether vectors are inserted successfully. ids: IDs of the inserted vectors.
- Return type
(Status, list(int))
-
property
name
¶
-
preload_collection
(collection_name, timeout=None)[source]¶ Loads a collection for caching.
- Parameters
collection_name (str) -- table to preload
- Returns
Status: indicate if invoke is successful
-
search
(collection_name, top_k, query_records, partition_tags=None, params=None, **kwargs)[source]¶ Search vectors in a collection.
- Parameters
collection_name (str) -- Name of the collection.
top_k (int) -- number of vertors which is most similar with query vectors
nprobe (int) -- cell number of probe
query_records (list[list[float32]]) -- vectors to query
partition_tags (list) -- tags to search
- :return
Status: Whether the operation is successful. result: query result
- Return type
-
search_in_files
(collection_name, file_ids, query_records, top_k, params=None, **kwargs)[source]¶ Searches for vectors in specific files of a collection.
The Milvus server stores vector data into multiple files. Searching for vectors in specific files is a method used in Mishards. Obtain more detail about Mishards, see
- Parameters
collection_name (str) -- table name been queried
file_ids (list[str] or list[int]) -- Specified files id array
query_records (list[list[float]]) -- all vectors going to be queried
query_ranges --
Optional ranges for conditional search.
If not specified, search in the whole table
top_k (int) -- how many similar vectors will be searched
- Returns
Status: indicate if query is successful results: query result
- Return type
-
search_vectors
(collection_name, top_k, query_records, partition_tags=None, params=None, **kwargs)¶ Search vectors in a collection.
- Parameters
collection_name (str) -- Name of the collection.
top_k (int) -- number of vertors which is most similar with query vectors
nprobe (int) -- cell number of probe
query_records (list[list[float32]]) -- vectors to query
partition_tags (list) -- tags to search
- :return
Status: Whether the operation is successful. result: query result
- Return type
-
search_vectors_in_files
(collection_name, file_ids, query_records, top_k, params=None, **kwargs)¶ Searches for vectors in specific files of a collection.
The Milvus server stores vector data into multiple files. Searching for vectors in specific files is a method used in Mishards. Obtain more detail about Mishards, see
- Parameters
collection_name (str) -- table name been queried
file_ids (list[str] or list[int]) -- Specified files id array
query_records (list[list[float]]) -- all vectors going to be queried
query_ranges --
Optional ranges for conditional search.
If not specified, search in the whole table
top_k (int) -- how many similar vectors will be searched
- Returns
Status: indicate if query is successful results: query result
- Return type
-
server_status
(timeout=10)[source]¶ Returns the status of the Milvus server.
- Returns
Status: Whether the operation is successful.
str : Status of the Milvus server.
- Return type
(Status, str)
-
server_version
(timeout=10)[source]¶ Returns the version of the Milvus server.
- Returns
Status: Whether the operation is successful.
str : Version of the Milvus server.
- Return type
(Status, str)
-
show_collections
(timeout=10)[source]¶ Returns information of all collections.
- Returns
Status: indicate if this operation is successful
- collections: list of table names, return when operation
is successful
- Return type
(Status, list[str])
-


%file newheader%>
<%file newnavbar%> <%profileheader base%>| <%wg%> | <%fmm%> | <%sstatus%> | <%profile-context%> |
The canonical URL for this profile is:
<%profileurl%>
<%profiledesc%>
<%profile.intro.include%>This profile was published on <%date%> <%status%> by <%author%>. <%profile.review%>
<%profile.intro%> <%profile.datadictionary%>Description of Profiles, Differentials, Snapshots, and how the XML and JSON presentations work.
This structure is derived from <%base-link%>.
<%summary%>This indicates the differences between this profile and the base <%base-link%> structure.
<%profile-structure-table-diff%>This provides the consolidated view (aka snapshot) of the profile after applying the changes in this profile to the base <%base-link%> structure.
<%profile-structure-table%>This structure is derived from <%base-link%>.
Differential View
This indicates the differences between this profile and the base <%base-link%> structure.
Snapshot View
This provides the consolidated view (aka snapshot) of the profile after applying the changes in this profile to the base <%base-link%> structure.
<%profile-structure-table%>XML Template
JSON Template
Alternate definitions: Master Definition (XML, JSON), <%schematron%>
<%profile.tx%> <%profile.inv%> <%profile.notes%>. <%profile.notes.include%>. <%file newfooter%>


--- layout: default title: "COSC 201: Algorithms and Data Structures" shorttitle: "COSC 201" --- Syllabus Schedule Slack group


=== Test case: lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 (click for source code)
=== Config value:
[{watchdog,<0.1586.0>},
<EMAIL_ADDRESS>{tc_group_properties,[]},
{tc_group_path,[]},
{data_dir,"/Users/anne-francevanswieten/lasp/_build/test/lib/lasp/test/lasp_client_server_advertisement_counter_SUITE_data/"},
<EMAIL_ADDRESS>=== Current directory is<EMAIL_ADDRESS>=== Started at 2017-04-18 15:45:10
*** User 2017-04-18 15:45:10.590 ***
Beginning test case client_server_state_based_test
*** User 2017-04-18 15:45:10.601 ***
Running client_server_ad_counter_state_based_test with nodes [server,client_1,
client_2,
client_3]
*** User 2017-04-18 15:45:10.601 ***
Launching Erlang distribution...
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.673 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
application: sasl
started_at: runner@MBPdeAnneFrance
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.694 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
application: syntax_tools
started_at: runner@MBPdeAnneFrance
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.710 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
application: compiler
started_at: runner@MBPdeAnneFrance
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.723 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
supervisor: {local,gr_sup}
started: [{pid,<0.1613.0>},
{id,gr_counter_sup},
{mfargs,{gr_counter_sup,start_link,[]}},
{restart_type,permanent},
{shutdown,5000},
{child_type,supervisor}]
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.727 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
supervisor: {local,gr_sup}
started: [{pid,<0.1615.0>},
{id,gr_param_sup},
{mfargs,{gr_param_sup,start_link,[]}},
{restart_type,permanent},
{shutdown,5000},
{child_type,supervisor}]
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.731 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
supervisor: {local,gr_sup}
started: [{pid,<0.1617.0>},
{id,gr_manager_sup},
{mfargs,{gr_manager_sup,start_link,[]}},
{restart_type,permanent},
{shutdown,5000},
{child_type,supervisor}]
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.731 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
application: goldrush
started_at: runner@MBPdeAnneFrance
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.739 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
supervisor: {local,lager_sup}
started: [{pid,<0.1624.0>},
{id,lager},
{mfargs,{gen_event,start_link,[{local,lager_event}]}},
{restart_type,permanent},
{shutdown,5000},
{child_type,worker}]
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.741 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
supervisor: {local,lager_sup}
started: [{pid,<0.1626.0>},
{id,lager_handler_watcher_sup},
{mfargs,{lager_handler_watcher_sup,start_link,[]}},
{restart_type,permanent},
{shutdown,5000},
{child_type,supervisor}]
*** System report during lasp_client_server_advertisement_counter_SUITE:client_server_state_based_test/1 2017-04-18 15:45:10.743 ***
=PROGRESS REPORT==== 18-Apr-2017::15:45:10 ===
supervisor: {local,lager_sup}
started: [{pid,<0.1628.0>},
{id,lager_crash_log},
{mfargs,
{lager_crash_log,start_link,
["log/crash.log",65536,10485760,[{hour,0}],5]}},
{restart_type,permanent},
{shutdown,5000},
{child_type,worker}]
*** User 2017-04-18 15:45:10.806 ***
Starting node: server
*** User 2017-04-18 15:45:10.809 ***
15:45:10.806 [info] Application lager started on node runner@MBPdeAnneFrance
*** User 2017-04-18 15:45:11.926 ***
Starting node: client_1
*** User 2017-04-18 15:45:13.507 ***
Starting node: client_2
*** User 2017-04-18 15:45:14.735 ***
Starting node: client_3
*** User 2017-04-18 15:45:15.842 ***
Loading lasp on node: server@MBPdeAnneFrance
*** User 2017-04-18 15:45:15.879 ***
Loading lasp on node: client_1@MBPdeAnneFrance
*** User 2017-04-18 15:45:15.916 ***
Loading lasp on node: client_2@MBPdeAnneFrance
*** User 2017-04-18 15:45:15.955 ***
Loading lasp on node: client_3@MBPdeAnneFrance
*** User 2017-04-18 15:45:16.845 ***
Starting lasp.
*** User 2017-04-18 15:45:18.047 ***
Custering nodes...
*** User 2017-04-18 15:45:18.047 ***
Joining node: server@MBPdeAnneFrance to client_1@MBPdeAnneFrance at port 53959
*** User 2017-04-18 15:45:18.050 ***
Joining node: server@MBPdeAnneFrance to client_2@MBPdeAnneFrance at port 53961
*** User 2017-04-18 15:45:18.051 ***
Joining node: server@MBPdeAnneFrance to client_3@MBPdeAnneFrance at port 53963
*** User 2017-04-18 15:45:18.052 ***
Joining node: client_1@MBPdeAnneFrance to server@MBPdeAnneFrance at port 53957
*** User 2017-04-18 15:45:18.055 ***
Joining node: client_1@MBPdeAnneFrance to client_2@MBPdeAnneFrance at port 53961
*** User 2017-04-18 15:45:18.057 ***
Joining node: client_1@MBPdeAnneFrance to client_3@MBPdeAnneFrance at port 53963
*** User 2017-04-18 15:45:18.058 ***
Joining node: client_2@MBPdeAnneFrance to server@MBPdeAnneFrance at port 53957
*** User 2017-04-18 15:45:18.061 ***
Joining node: client_2@MBPdeAnneFrance to client_1@MBPdeAnneFrance at port 53959
*** User 2017-04-18 15:45:18.062 ***
Joining node: client_2@MBPdeAnneFrance to client_3@MBPdeAnneFrance at port 53963
*** User 2017-04-18 15:45:18.063 ***
Joining node: client_3@MBPdeAnneFrance to server@MBPdeAnneFrance at port 53957
*** User 2017-04-18 15:45:18.066 ***
Joining node: client_3@MBPdeAnneFrance to client_1@MBPdeAnneFrance at port 53959
*** User 2017-04-18 15:45:18.067 ***
Joining node: client_3@MBPdeAnneFrance to client_2@MBPdeAnneFrance at port 53961
*** User 2017-04-18 15:45:18.068 ***
Lasp fully initialized.
*** User 2017-04-18 15:45:18.068 ***
Waiting for simulation to end
*** User 2017-04-18 15:47:28.085 ***
Simulation ended with success
*** User 2017-04-18 15:47:36.157 ***
Ending test case client_server_state_based_test
=== Ended at 2017-04-18 15:47:36
=== successfully completed test case
=== Returned value: ok
Test run history
| Top level test index


Despite being a very important part of any operating system, file systems tend to get little attention. Linux has three editions for Linux Device Drivers, another three for Understanding the Linux Kernel and two for Linux Kernel Development. For the 2.4 networking stack there is Linux Networking Architecture by Klaus Wehrle et al. and for the memory subsystem there is Understanding the Linux Virtual Memory Manager by Mel Gorman. The aptly named UNIX Filesystems: Evolution, Design, and Implementation is only giving a general overview of how things work. Practical File System Design with the Be File System by Dominic Giampaolo is an an enjoyable read but, as the name indicates, it only deals with BeFS. The same is also true for HFS+ in the very thick but also very interested Mac OS X Internals: A Systems Approach by Amit Singh. I really hope that someday somebody will spend some time and put together a nice book or website in which file systems, new and old, are presented and analyzed in detail.
As the disclaimer from the front page says, I don't know as much as I want about file systems. I'm making progress in learning about them in the traditional way of playing and understanding the existing code. What I'm attempting in this project is to complement this by a visual approach in which the main purpose is to try to graphically depict some the ways the things go. The main observable thing I'm using is the external symbols used by kernel modules. There are two main reasons for doing this. First, many operating systems build their file systems as kernel modules. This is useful because it separates the part we are interested in from the rest of kernel. And second, because the modules need to be loaded dynamically, the functions they call and data they access from the kernel show up as external (unresolved) symbols in their binaries. These can be easily extracted using nm. One drawback of this approach is represented by the chains of calls like the ones in the figure from below. Luckily, in the Linux kernel many functions are explicitly marked as inline so this case might not occur so frequently. I haven't check explicitly for this yet to but it is something I would like to do.
That being said, here is a quick overview of the next sections. The following two are the big ones. The first is a detail analysis of one particular Linux Kernel tree and the second is a shorter one done over a large number of file systems from Linux Kernel 2.6.0 to 2.6.29. After that there is a small section that shows some aspects of the BSD family. After conclusions there is an appendix consisting of three things: the first one explains how the file systems for Linux were compiled, the second one shows timelines for the releases of Linux Kernel, FreeBSD, NetBSD and OpenBSD; the last is a detailed map of the external symbols of the kernel modules analyzed in the second section.
On more thing. The figures are accompanied by captions which describe the plot and note some of the interesting things that are going on there. If you find any mistake please let me know and I'll try to fix it.
Happy reading/viewing!


-
Larry Ellison Bought an Island in Hawaii. Now What?
www.nytimes.com
How the tech billionaire came to own 87,000 acres, three hotels, a wastewater-treatment plant, a cemetery and 380 cats.
-
Computing Pioneer Ray Ozzie and Security Veteran Nico Sell Join ...
recode.net
The creator of Lotus Notes and former Microsoft chief software architect is now focused on mobile collaboration with Talko, the startup that came out ...
-
Apple's Beats Music Brand May Go Away. Apple's Beats Music Service Is ...
recode.net
That makes more sense.
-
Making Sense of Mobile When Everything Is Mobile (Video)
recode.net
How the staff of Re/code prepares the lineup for Code/Mobile, Oct. 27-28.
-
So you want to speak at Code/Mobile?
www.youtube.com
Rethinking, reinventing and recoding the mobile industry. Join us at Code/Mobile, the definitive tech industry event on October 27-28 in Half Moon ...
-
Code/Mobile
recode.net
Join a gathering of executives whose companies are leading the mobile revolution, as well as those whose businesses are being transformed— those ...
-
Inside Alibaba's Lavish IPO After-Party -- Video! Audio! Photos! Shrimp!
recode.net
Bonus: Audio of Jack Ma's welcome speech. Also: Oysters!
-
New Keyboards Bring Faster, Easier Typing to the iPhone 6
recode.net
At last, Apple will allow third-party keyboards on the iPhone and iPad. But which one is the best?
-
iPhone 6 Plus Review: How Big Is Too Big?
recode.net
Apple has finally joined the phablet party. How does it stack up?
-
The Cubli: a cube that can jump up, balance, and 'walk'
www.youtube.com
The Cubli is a 15 × 15 × 15 cm cube that can jump up and balance on its corner. Reaction wheels mounted on three faces of the cube rotate at high ...
-
The Man Who Would Teach Machines to Think
www.theatlantic.com
Douglas Hofstadter, the Pulitzer Prize–winning author of Gödel, Escher, Bach, thinks we've lost sight of what artificial intelligence really means. ...


| Home | Trees | Indices | Help |
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List to store ndarray-likes in. It will look for 'is' instead of calling __eq__ on each element.
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y in x
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L.index(value, [start, [stop]]) -> integer -- return first index of value. Raises ValueError if the value is not present.
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|---|
| Generated by Epydoc 3.0.1 on Tue Jul 4 11:59:34 2017 | http://epydoc.sourceforge.net |


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