Outreachy project advice May 2024

[pgleeson]

Hi!

Welcome to the Outreachy contribution period for May 2024. Thanks for your interest in ModECI and MDF!

There are some suggested tasks below for potential applicants to try during the contribution period.

Please note that the ModECI project this round will require some solid previous experience in Python and ML. There are few open issues which are "low hanging fruit", mainly due to a number of very successful previous Outreachy rounds! Therefore we’d like to see how well you can get a feel for what MDF is intended for, and demo some example models in the format.

Task 1: Read the MDF paper, install MDF locally and try some of the example models

The paper introducing MDF can be found at https://mdf.readthedocs.io/en/latest/api/MDFpaper.html. Have a read over it, don’t worry if you don’t understand it all (it’s mainly intended for neuroscientists) but it should give you a feel for the aims of the project. See https://mdf.readthedocs.io/en/latest/api/Installation.html for installation details for the MDF package. Run the example Python scripts in https://github.com/ModECI/MDF/tree/main/examples/MDF to get a feel for the language.

Task 2: Create an OSB account and edit a Jupyter notebook to create a novel MDF model

1. Create a new account on Open Source Brain v2: https://www.v2.opensourcebrain.org
2. Create a new workspace from the ModECI MDF OSBv2 repository (which points to the main MDF GitHub repository here: https://github.com/ModECI/MDF)
3. Open the workspace in the JupyterLab application.
4. Install the latest version of MDF which has been copied into the workspace (launch a Terminal, go to /opt/workspace/ModECI MDF/main, type pip install .)
5. Open the simple example Jupyter notebook (at /opt/workspace/ModECI MDF/main/examples/SimpleExample.ipynb) and go through this to understand the main concepts in MDF.
6. Create a new notebook in your workspace which creates an MDF model with a number of connected nodes, with a unique mathematical expression in each and at least one time derivative (example). It should represent a simple model of a dynamical system in biology or physics containing an ordinary differential equation, and demonstrate your understanding of MDF.
7. Email us a link to the workspace (see Outreachy for mentors' contact details).

To get a feel for what OSBv2 can be used for see the Guided tour of OSBv2

Task 3: Create a simple Streamlit application which uses MDF

A simple graphical application should be created using Streamlit which imports MDF and allows a model to be executed at the press of a button, with output displayed. Ideally it would use the example MDF you have created above, and potentially plots the output at multiple time points (as in this example). Email us a link to where the public app is hosted (e.g. a Space on HuggingFace).

[rasmodev]

@pgleeson Thank you for the update.

[Innocentefea]

Thanks for the update @pgleeson this is helpful.

[ai-naymul]

Hi!

Welcome to the Outreachy contribution period for May 2024. Thanks for your interest in ModECI and MDF!

There are some suggested tasks below for potential applicants to try during the contribution period.

Please note that the ModECI project this round will require some solid previous experience in Python and ML. There are few open issues which are "low hanging fruit", mainly due to a number of very successful previous Outreachy rounds! Therefore we’d like to see how well you can get a feel for what MDF is intended for, and demo some example models in the format.

Task 1: Read the MDF paper, install MDF locally and try some of the example models

The paper introducing MDF can be found at https://mdf.readthedocs.io/en/latest/api/MDFpaper.html. Have a read over it, don’t worry if you don’t understand it all (it’s mainly intended for neuroscientists) but it should give you a feel for the aims of the project. See https://mdf.readthedocs.io/en/latest/api/Installation.html for installation details for the MDF package. Run the example Python scripts in https://github.com/ModECI/MDF/tree/main/examples/MDF to get a feel for the language.

Task 2: Create an OSB account and edit a Jupyter notebook to create a novel MDF model

1. Create a new account on Open Source Brain v2: https://www.v2.opensourcebrain.org
2. Create a new workspace from the ModECI MDF OSBv2 repository (which points to the main MDF GitHub repository here: https://github.com/ModECI/MDF)
3. Open the workspace in the JupyterLab application.
4. Install the latest version of MDF which has been copied into the workspace (launch a Terminal, go to /opt/workspace/ModECI MDF/main, type pip install .)
5. Open the simple example Jupyter notebook (at /opt/workspace/ModECI MDF/main/examples/SimpleExample.ipynb) and go through this to understand the main concepts in MDF.
6. Create a new notebook in your workspace which creates an MDF model with a number of connected nodes, with a unique mathematical expression in each and at least one time derivative (example). It should represent a simple model of a dynamical system in biology or physics containing an ordinary differential equation, and demonstrate your understanding of MDF.
7. Email us a link to the workspace (see Outreachy for mentors' contact details).

To get a feel for what OSBv2 can be used for see the Guided tour of OSBv2

Task 3: Create a simple Streamlit application which uses MDF

A simple graphical application should be created using Streamlit which imports MDF and allows a model to be executed at the press of a button, with output displayed. Ideally it would use the example MDF you have created above, and potentially plots the output at multiple time points (as in this example). Email us a link to where the public app is hosted (e.g. a Space on HuggingFace).

Hi everyone,

I'm thrilled to join the Outreachy internship program and contribute to the Streamlit based interface for running/visualizing ML/AI models in MDF project.I'm eager to apply my skills to bridge the fields of AI, ML, and neuroscience through the MDF format.

I've started familiarizing myself with the MDF package and its examples, particularly the SimpleExample notebook. I'm intrigued by the potential of MDF to streamline computational model sharing across diverse domains.

I have a few questions regarding the project:

1. For initial contributions, would you recommend focusing on any specific aspect of the Streamlit web application?

2. Are there any common pitfalls or challenges new contributors should be aware of when working with MDF models?

I'm looking forward to weekly zoom chats and interacting through GitHub issues and pull requests, as mentioned by Padraig Gleeson(@pgleeson ). I'm also open to live debugging sessions and regular status meetings as suggested by Ankur Sinha(@sanjayankur31 ). My goal is to learn, contribute meaningfully, and adapt to the mentorship styles of both mentors.

Thank you for this opportunity. I'm excited to start this journey and contribute to the ModECI community.

Regards,
Naymul

[Mankavelda]

Thank you for the guide @pgleeson

[ai-naymul]

Hi!

Welcome to the Outreachy contribution period for May 2024. Thanks for your interest in ModECI and MDF!

There are some suggested tasks below for potential applicants to try during the contribution period.

Please note that the ModECI project this round will require some solid previous experience in Python and ML. There are few open issues which are "low hanging fruit", mainly due to a number of very successful previous Outreachy rounds! Therefore we’d like to see how well you can get a feel for what MDF is intended for, and demo some example models in the format.

Task 1: Read the MDF paper, install MDF locally and try some of the example models

The paper introducing MDF can be found at https://mdf.readthedocs.io/en/latest/api/MDFpaper.html. Have a read over it, don’t worry if you don’t understand it all (it’s mainly intended for neuroscientists) but it should give you a feel for the aims of the project. See https://mdf.readthedocs.io/en/latest/api/Installation.html for installation details for the MDF package. Run the example Python scripts in https://github.com/ModECI/MDF/tree/main/examples/MDF to get a feel for the language.

Task 2: Create an OSB account and edit a Jupyter notebook to create a novel MDF model

1. Create a new account on Open Source Brain v2: https://www.v2.opensourcebrain.org
2. Create a new workspace from the ModECI MDF OSBv2 repository (which points to the main MDF GitHub repository here: https://github.com/ModECI/MDF)
3. Open the workspace in the JupyterLab application.
4. Install the latest version of MDF which has been copied into the workspace (launch a Terminal, go to /opt/workspace/ModECI MDF/main, type pip install .)
5. Open the simple example Jupyter notebook (at /opt/workspace/ModECI MDF/main/examples/SimpleExample.ipynb) and go through this to understand the main concepts in MDF.
6. Create a new notebook in your workspace which creates an MDF model with a number of connected nodes, with a unique mathematical expression in each and at least one time derivative (example). It should represent a simple model of a dynamical system in biology or physics containing an ordinary differential equation, and demonstrate your understanding of MDF.
7. Email us a link to the workspace (see Outreachy for mentors' contact details).

To get a feel for what OSBv2 can be used for see the Guided tour of OSBv2

Task 3: Create a simple Streamlit application which uses MDF

A simple graphical application should be created using Streamlit which imports MDF and allows a model to be executed at the press of a button, with output displayed. Ideally it would use the example MDF you have created above, and potentially plots the output at multiple time points (as in this example). Email us a link to where the public app is hosted (e.g. a Space on HuggingFace).

Hey, I have a question regarding the tasks:

For creating a novel MDF model with connected nodes and unique mathematical expressions, could you suggest some simple yet illustrative examples of dynamical systems in biology or physics that would be suitable for a beginner?

[sanjayankur31]

For the moment, just the models in the MDF examples should be sufficient. The idea is for all of you to familiarise yourselves with how MDF works and its core concepts.

[Innocentefea]

Sure it is, and it's getting interesting to be acquitted with.

[Talikamuhib]

Hello world!

Thank you for info!

Happy contributing! :)

[rimjhimittal]

Hello everyone,

I'm thrilled to announce my participation in the Outreachy contribution phase with ModECI for the May to August 2024 round. . I'm eager to contribute to the Streamlit-based interface for running and visualizing ML/AI models in MDF.

As I delve into this project, I'm curious about your perspectives on the key features or functionalities of the Streamlit web application that you believe would benefit most from enhancements or additions in the context of our project goals?

Looking forward to your insights!

Warm regards,
Rimjhim

P.S. Mentors, I'm excited to engage with you both throughout this journey. Padraig Gleeson (@pgleeson) and Ankur Sinha (@sanjayankur31), I'm eager to learn from your mentorship styles and contribute meaningfully to the ModECI community.

[sanjayankur31]

Welcome all! It's great to have you here. The first period now is primarily for you to familiarise yourselves with the project---its core concepts, the code, the development environment. So please follow the tasks that Padraig has suggested in the top post here. They should give you plenty to explore.

[Olawumi-11]

Thanks you

[sanjayankur31]

I think it should work with 3.11 now. The issue was that some of the python libraries we need weren't ready for python 3.11.

Could you folks test it out and confirm, and if everything works with py3.11, a pull request to the documentation could be opened :)

[rasmodev]

@sanjayankur31 will check and advise

[rimjhimittal]

This project works well with python3.11.8 for me. Might be a very simple question, but what exactly do you expect when you ask to "test it out"? @sanjayankur31

[sanjayankur31]

The gold standard is that "all functionality" works, i.e., all the code works. In practice, we have lots of tests that and examples that are run. See the GitHub actions in this repository for more information on what tests/examples are run.

[Aeeshah1]

Hi!

Welcome to the Outreachy contribution period for May 2024. Thanks for your interest in ModECI and MDF!

There are some suggested tasks below for potential applicants to try during the contribution period.

Please note that the ModECI project this round will require some solid previous experience in Python and ML. There are few open issues which are "low hanging fruit", mainly due to a number of very successful previous Outreachy rounds! Therefore we’d like to see how well you can get a feel for what MDF is intended for, and demo some example models in the format.

Task 1: Read the MDF paper, install MDF locally and try some of the example models

The paper introducing MDF can be found at https://mdf.readthedocs.io/en/latest/api/MDFpaper.html. Have a read over it, don’t worry if you don’t understand it all (it’s mainly intended for neuroscientists) but it should give you a feel for the aims of the project. See https://mdf.readthedocs.io/en/latest/api/Installation.html for installation details for the MDF package. Run the example Python scripts in https://github.com/ModECI/MDF/tree/main/examples/MDF to get a feel for the language.

Task 2: Create an OSB account and edit a Jupyter notebook to create a novel MDF model

1. Create a new account on Open Source Brain v2: https://www.v2.opensourcebrain.org
2. Create a new workspace from the ModECI MDF OSBv2 repository (which points to the main MDF GitHub repository here: https://github.com/ModECI/MDF)
3. Open the workspace in the JupyterLab application.
4. Install the latest version of MDF which has been copied into the workspace (launch a Terminal, go to /opt/workspace/ModECI MDF/main, type pip install .)
5. Open the simple example Jupyter notebook (at /opt/workspace/ModECI MDF/main/examples/SimpleExample.ipynb) and go through this to understand the main concepts in MDF.
6. Create a new notebook in your workspace which creates an MDF model with a number of connected nodes, with a unique mathematical expression in each and at least one time derivative (example). It should represent a simple model of a dynamical system in biology or physics containing an ordinary differential equation, and demonstrate your understanding of MDF.
7. Email us a link to the workspace (see Outreachy for mentors' contact details).

To get a feel for what OSBv2 can be used for see the Guided tour of OSBv2

Task 3: Create a simple Streamlit application which uses MDF

A simple graphical application should be created using Streamlit which imports MDF and allows a model to be executed at the press of a button, with output displayed. Ideally it would use the example MDF you have created above, and potentially plots the output at multiple time points (as in this example). Email us a link to where the public app is hosted (e.g. a Space on HuggingFace).

Thank you for the update

[39148127]

Hello everyone, am glad to be part of this project and am looking forward to learn a
lot from it

[mqnifestkelvin]

Hi Lilian welcome, your sure to learn a whole lot here.

[akriti-dhurandher]

Hi everyone I am Akriti Dhurandher, I am very excited to be a contributor in this project and this guide is very helpful

[mqnifestkelvin]

Hey welcome Dhurandher so good to have you.

[Innocentefea]

Hello everyone I am thrilled to be here, I am Innocent Efe, I am looking forward to contributing to this project, and all the guidance given so far has been super helpful.

[mqnifestkelvin]

Welcome Innocent, Nice to have you.

[Innocentefea]

Pleasure is mine Kelvin, nice having you here too.

[39148127]

@pgleeson @sanjayankur31
Am trying to clone this MDF repository from gitub, i have tried a number of times but it keeps giving me this error, my internet is perfect
Cloning into 'MDF'...
remote: Enumerating objects: 13220, done.
remote: Counting objects: 100% (2249/2249), done.
remote: Compressing objects: 100% (819/819), done.
error: RPC failed; curl 92 HTTP/2 stream 5 was not closed cleanly: CANCEL (err 8)
error: 7330 bytes of body are still expected
fetch-pack: unexpected disconnect while reading sideband packet
fatal: early EOF
fatal: fetch-pack: invalid index-pack output

[39148127]

Hello Innocent, I have tried disconnecting and connecting. I have also tried to clone using github desktop but it terminates before cloning all the files
git clone https://github.com/ModECI/MDF.git

[Innocentefea]

Try to fork the repo and try cloning it again..

[39148127]

I have solved it, thank you

[codinghappiness-web]

@39148127 pls can you say how you solved the issue?

[39148127]

Hello @codinghappiness-web the problem was my internet connection. Cloning needs a fast internet. I was using shared WI-FI so I looked for a faster one and immediately the issue was resolved

[AshitaSri]

@sanjayankur31 @pgleeson
->I am trying to build a model where I am defining global parameters for the whole graph .

Set environment parameters at the graph level
heat_graph.metadata = {
"parameters": [
Parameter(id="ambient_temp", value=20.0),
Parameter(id="heat_transfer_coeff", value=0.1)
]
}

-> At each node I am trying to use these variables -for example -

a_node = Node(id="A")
temp_time_derivative_expression = "-(temp - ambient_temp) * heat_transfer_coeff"
a_node.parameters.append(Parameter(id="temp_time_derivative", value=temp_time_derivative_expression))

->during evaluation
ValueError: Error! Could not evaluate parameters using known vars. The following vars are missing:
temp_time_derivative: heat_transfer_coeff, ambient_temp

How to resolve this? 

[Innocentefea]

Hello @AshitaSri have you sorted this out or are you still having a problem fixing it?

[AshitaSri]

NO sir , I am still facing this problem . I mooved forward by adding these parameter inside the node . But still can't resolve this issue

[rimjhimittal]

Hey @AshitaSri , could you please mail your python notebook to [email protected]? I can try to help you with this issue.

[AshitaSri]

yeah sure! Thanks

[pgleeson]

@AshitaSri I believe it is currently only possible to access the parameters in the current node for expressions in that node. Is there some where you read that gave you the impression it should be possible to use them in a sub node?

The simplest option for passing these values if you do need to set them in a single place is to use an edge and pass the value out with an output port, and then get it in with an input port

[Ashita17]

Hello everyone, I am Ashita, an Outreachy applicant for the May 2024 cohort. Looking forward to learn from all of you and make valuable contributions!

[Innocentefea]

Hello Ashita, nice having you here.

[Ashita17]

thank you innocentefea !

[komalverma04]

Hello Everyone, I am Komal Verma, an outreachy applicant. I'm very excited to contribute in the project.

[Innocentefea]

Hello Komalverma, nice having you here.

[Devadeut]

Hello Everyone,
I am Devashri, a bit late to the party! Hope to contribute and enjoy our journey.
Thanks @pgleeson and @sanjayankur31 for onboarding to the contribution period.

[Innocentefea]

Hello Devashri, nice having you here.

[Munanom]

Hi, everyone. I'm Muna Said and I am excited to be part of the Outreachy internship program and to actively participate in enhancing the Streamlit-based interface for executing and visualizing ML/AI models within the MDF project. I am enthusiastic about utilizing my skills to connect the realms of ML and Python through the MDF format.

[damidfkm]

can anyone help me out, why i keep getting this when i run pip install . and pip install modeci-mdf

[sanjayankur31]

What version of Python are you on please? Onnx provides packages for Python 3.8--3.11 from the looks of it, so it should work if you're on one of these versions:

https://pypi.org/project/onnx/#files

[damidfkm]

ohh, I'm on 3.12, my bad

[sanjayankur31]

No worries. Try a different Python version that is supported and that should work.

[rimjhimittal]

How to use an ONNX function like atan here?
when i write tan it works, but does not with atan

phi_node.parameters.append(
       Parameter(
           id="phi",
           function="tan",
           args={"x": "(omega*L - 1/(omega*C))/R"},
       )
   )

[rimjhimittal]

Okay thanks, I'll give it a try. And I have removed the wrong commits from my PR for now.

[rimjhimittal]

For adding arctan function i added the following code to standard.py:

    add_mdf_function(
        "arctan",
        description="Inverse tangent function",
        arguments=[STANDARD_ARG_0, "scale"],
        expression_string="scale * arctan(%s)" % (STANDARD_ARG_0),
    )

and added arctan to create_python_expression() func as well
but when i try to evaluate the test graph, i get :

Error! Could not evaluate expression [scale * arcnumpy.tan(variable0)] 

it should have been numpy.arctan instead.

[pgleeson]

It's probably an issue here. tan( is being replaced with numpy.tan(, before arctan is found. Adding arctan to the start of that list should solve the issue. Please also add arccos and arcsin also if you're opening a PR.

MDF/src/modeci_mdf/functions/standard.py

Lines 72 to 77 in ca4843a

	for func in ["exp", "sin", "cos", "tan", "sinh", "cosh", "tanh"]:
	if "numpy." + func not in expression_string:
	expression_string = expression_string.replace(
	"%s(" % func, "numpy.%s(" % func
	)

[rimjhimittal]

Hi, I tried doing that but the code still confused arctan with tan. So now i have addressed this issue by using regex in create_python_expression() function.
I have added all three functions and an example file using them and have made the pull request here, after formatting the code in black format.

[rimjhimittal]

Let me know if I should work on updating the documentation and readme with the addition of arc_func.

[39148127]

Am having a problem with Generating a graph image from my model.
I have confirmed the image path its the same. This is the error it gives:
Error: no "view" mailcap rules found for type "image/png"
/usr/bin/xdg-open: 869: www-browser: not found
/usr/bin/xdg-open: 869: links2: not found
/usr/bin/xdg-open: 869: elinks: not found
/usr/bin/xdg-open: 869: links: not found
/usr/bin/xdg-open: 869: lynx: not found
/usr/bin/xdg-open: 869: w3m: not found
xdg-open: no method available for opening 'AB.png'
@pgleeson @sanjayankur31 Could you kindly help with this

[sanjayankur31]

What platform are you running your code on? Is this on your computer or on OSBv2, or somewhere else?

The error is here is that there needs to be a default viewer that the system can use to show png files , but it cannot find one.

[Zhu-VISH]

Hi @pgleeson I am very happy to connect with this amazing community and learn so many new things while setting up this project locally. Thanks a lot for all the examples and assistance.

I am able to execute all the examples and modify the jupyter notebook nicely. But, I am stuck on the execution of MDF -> examples -> PsyNeuLink -> generate_json_and_scripts.py .

Here's the error I am encountering every time from last two days, please help me solve this issue:

Thanks a lot :-)

[pgleeson]

Hi @Zhu-VISH. Good catch.
That file is explicitly excluded from the tests:

MDF/tests/test_examples.py

Lines 27 to 32 in 067ff41

	example_exclusion_strings = [
	".reconstructed.py",
	"generate_json_and_scripts.py",
	"pytorch_ddm.py",
	"keras_model.py",
	]

So just ignore it. Was probably a temporary file to help generate PsyNeuLink example scripts.

[Devadeut]

@pgleeson @sanjayankur31 In the MDF model, Can't we have a closed-loop model?
eg., a->b->c->a, continuous updation of a,b,c. We give an initial value to each.
I can send you my code file if that helps.

[pgleeson]

Hi @Devadeut. Currently that's not possible... There is an issue describing the problem, and the branch where the solution is being worked on here: #455.
For now, assume cyclic/closed loop graphs are not supported.

[Devadeut]

okay, it's an interesting problem to tackle. Thank you!

[Devadeut]

@pgleeson So how can we perform cyclic dependencies then?

[pgleeson]

This has been pretty much solved in the branch referred to above, but has not yet been discussed in detail with all of the other developers. For now don't use cyclic dependencies in your examples.

[Devadeut]

@pgleeson @sanjayankur31
Others if anyone came across similar error!
My Streamlit application worked fine locally. But when I am building it on huggingface streamlit space, it is showing an error regarding graphviz, as follows:

---

ExecutableNotFound: failed to execute PosixPath('dot'), make sure the Graphviz executables are on your systems' PATH
Traceback:
File "/usr/local/lib/python3.10/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 542, in _run_script
exec(code, module.dict)
File "/home/user/app/app.py", line 20, in
image_path=run_model(mode="graph")
File "/home/user/app/model.py", line 205, in main
model.to_graph_image(
File "/usr/local/lib/python3.10/site-packages/modeci_mdf/mdf.py", line 576, in to_graph_image
raise (e)
File "/usr/local/lib/python3.10/site-packages/modeci_mdf/mdf.py", line 555, in to_graph_image
mdf_to_graphviz(
File "/usr/local/lib/python3.10/site-packages/modeci_mdf/interfaces/graphviz/exporter.py", line 526, in mdf_to_graphviz
name = graph.render()
File "/usr/local/lib/python3.10/site-packages/graphviz/_tools.py", line 171, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/graphviz/rendering.py", line 122, in render
rendered = self._render(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/graphviz/_tools.py", line 171, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/graphviz/backend/rendering.py", line 326, in render
execute.run_check(cmd,
File "/usr/local/lib/python3.10/site-packages/graphviz/backend/execute.py", line 81, in run_check
raise ExecutableNotFound(cmd) from e

---

guide me through this. How can I resolve this error?

[pgleeson]

Try adding graphviz to a file packages.txt at the top level of your repo

[Devadeut]

i tried adding it, but it didn't work.
I solved it by manually changing path var:

---

import os
import sys
Add Graphviz bin directory to PATH
graphviz_bin_dir = os.path.join(sys.prefix, "bin")
os.environ["PATH"] += os.pathsep + graphviz_bin_dir

---

If anyone having this problem, you can additionally try this too.

[Iqra350]

I simply resolve this issue by instaling the graphviz by

[awanishyadav967]

Hi @pgleeson can I email the streamlit and workspace link for the early feedback?

[sanjayankur31]

Hello, please email us at p.gleeson AT ucl.ac.uk and ankur.sinha AT ucl.ac.uk

[pgleeson]

Please don't post information here on out of office replies etc. We are both aware of the deadlines for this process and are committed to providing feedback in a timely, but not immediate, manner. There are a large number of applicants for this proposal and you should assume feedback will take 1-2 days, and will be unlikely over the weekend, or just before the deadline.

[rimjhimittal]

@pgleeson @sanjayankur31
Do we have any example of passing outputs from two previous nodes to input of a third node. I tried doing that, but the third node takes input from only one of them. Basically we make the third node something like this then:

    node_3.input_ports.append(InputPort(id="Input_from_node_1"))
    node_3.input_ports.append(InputPort(id="Input_from_node_2"))

but we are not defining which previous node we are expecting to take that input from because id is the only parameter we pass in InputPort function and which makes "Input_from_node_2" NoneType.

I can see the same issue here : #509 (comment)

[rimjhimittal]

Alright! I was able to solve it by using mod_graph.edges.append(Edge(id="", sender="", etc)) instead of simple_connect().

[pgleeson]

Good that you solved it @rimjhimittal

[pgleeson]

Hi all, it's getting close to the deadline! Thanks for all the great contributions so far, but please make sure to get your applications in on time.
We get asked every year about the internship timeline in the application form. The timeline is for the applicant to define what tasks they will accomplish during the project, broken down into approx 2 week intervals. We won't specify exactly what should be put here, rather would be good to see what each applicant comes up with here themselves, based on their understanding of what needs to be done in the project. Doesn't have to be very detailed, it will just give us an impression of how you plan to manage your time. The end point will be producing robust, publicly accessible Streamlit based application(s) linked from the MDF website which demonstrate the usefulness of MDF for new users, and we're interested in hearing your thoughts on the steps required to get there.
Also, while you can still make contributions past the final application deadline, the assessment will be made fairly soon after and will be based on what's recorded in the application form, so don't assume that work after that point will influence it much.
Good luck!

[Iqra350]

Thank you so much for clarification.

[rimjhimittal]

Since most of the work we are submitting is not in the form of PR's so will the "Date contribution was accepted or merged:" matter?

[pgleeson]

Don't worry too much about when the PRs are precisely merged etc. The main point is that the contribution is useful and recorded in the application

[rimjhimittal]

@pgleeson
Could we consider optimizing the size of this image for future updates? It is 40MB rn, so it tends to load a bit slowly as compared to rest of the website, and optimizing its size could enhance the overall sleekness of the website.
https://github.com/ModECI/Website/blob/main/img/glow_bg.png

[pgleeson]

Good catch!
ModECI/Website#55

[pgleeson]

Hi all!
Thanks for all of the great contributions this round. It's always great to see so many new users trying out MDF, and coming up with new insights for how to use it. We had a lot of interest, but as I mentioned will probably only have one internship place, so thank you to all for your work on this, and hope you have gained something from this process. We will hopefully be able to participate again in future rounds of the Outreachy program.

[pgleeson]

Just a quick note for anyone who has created OSB workspaces as part of this. There may be an issue with the URLs for these after a recent update of our server, e.g.

https://v2.opensourcebrain.org/workspace/1207 - used to work, now fails
https://v2.opensourcebrain.org/workspaces/1207 - works now

If you are having a problem accessing your links to the workspaces you created, just replace workspace with workspaces (i.e. plural).

Hopefully this will be fixed soon and the original form will also work again: OpenSourceBrain/OSBv2#887