Sigh won't include M1 devices on the provisioning profile. (temp workaround: edit /sigh/runner.rb)

New Issue Checklist

[x] Updated fastlane to the latest version
[x] I read the Contribution Guidelines
[x] I read docs.fastlane.tools
[x] I searched for existing GitHub issues

Issue Description

When running sigh to generate the provisioning profiles for an iOS app, sigh filters out the Mac devices on the developer portal. This means that M1 (Apple Silicon) machines are not included on the provisioning profiles. I was able to work around this by editing sigh and removing the code that filters the list of devices fetched from the portal.
Command executed

match(git_url: "<repo_url>",
      type: "development",
      app_identifier: [
          "<id1>",
          "<id2>"
      ]
)

Complete output when running fastlane, including the stack trace and command used

The command executes successfully.
Environment

Stack

Key
Value

OS
11.0.1

Ruby
2.6.3

Bundler?
true

Git
git version 2.24.3 (Apple Git-128)

Installation Source
/Library/Ruby/Gems/2.6.0/bin/fastlane

Host
macOS 11.0.1 (20B29)

Ruby Lib Dir
/System/Library/Frameworks/Ruby.framework/Versions/2.6/usr/lib

OpenSSL Version
LibreSSL 2.8.3

Is contained
false

Is homebrew
false

Is installed via Fabric.app
false

Xcode Path
/Applications/Xcode.app/Contents/Developer/

Xcode Version
12.2

Hey @raphaelcruzeiro 👋
Could you provide the changes you made to sign/runner.rb to help future readers? 😊

Sure thing @rogerluan. I'm not much of a Ruby programmer so when changing the filter didn't work, so I just removed it (note the last else). This is what sigh/runner.tb looks like to me now:
    def devices_to_use
      # Only use devices if development or adhoc
      return [] if !Sigh.config[:development] && !Sigh.config[:adhoc]

      device_classes = case Sigh.config[:platform].to_s
                       when 'ios'
                         [
                           Spaceship::ConnectAPI::Device::DeviceClass::APPLE_WATCH,
                           Spaceship::ConnectAPI::Device::DeviceClass::IPAD,
                           Spaceship::ConnectAPI::Device::DeviceClass::IPHONE,
                           Spaceship::ConnectAPI::Device::DeviceClass::IPOD,
                           Spaceship::ConnectAPI::Device::DeviceClass::MAC
                         ]
                       when 'tvos'
                         [Spaceship::ConnectAPI::Device::DeviceClass::APPLE_TV]
                       when 'macos', 'catalyst'
                         [Spaceship::ConnectAPI::Device::DeviceClass::MAC]
                       end
      if api_token
        return Spaceship::ConnectAPI::Device.all.select do |device|
          device_classes.include?(device.device_class)
        end
      else
        return Spaceship::ConnectAPI::Device.all()
      end
    end

Interesting @raphaelcruzeiro , so even after adding Spaceship::ConnectAPI::Device::DeviceClass::MAC, to the list of device_classes under 'ios' didn't work? 🤔 I'd expect that deviceClass would have more cases than fastlane knows, but fastlane is up-to-date with App Store Connect API specification:
"deviceClass" : {
    "type" : "string",
    "enum" : [ "APPLE_WATCH", "IPAD", "IPHONE", "IPOD", "APPLE_TV", "MAC" ]
},

Not sure what else could be done to fix this issue

Interesting @raphaelcruzeiro , so even after adding Spaceship::ConnectAPI::Device::DeviceClass::MAC, to the list of device_classes under 'ios' didn't work? 🤔 I'd expect that deviceClass would have more cases than fastlane knows, but fastlane is up-to-date with App Store Connect API specification:
"deviceClass" : {
    "type" : "string",
    "enum" : [ "APPLE_WATCH", "IPAD", "IPHONE", "IPOD", "APPLE_TV", "MAC" ]
},

Not sure what else could be done to fix this issue

This is just a big guess, but maybe Catalyst is missing in the enum depicting the deviceClass

This is just a big guess, but maybe Catalyst is missing in the enum depicting the deviceClass

@rogerluan As you can see on my code above, it didn't. I am not really a Ruby developer so it's very much possible that I missed something obvious.

@rogerluan As you can see on my code above, it didn't. I am not really a Ruby developer so it's very much possible that I missed something obvious.

I think this is still an issue and is not yet ready to be closed!
@rogerluan yes, maybe Fastlane is up to date with the App Store Connect API specifications, however it does not comply with the current apple developer profile management! Let me explain:
When you want to build an iOS app on an Apple Silicon Mac (Xcode Target: "My Mac (Designed for iPad)") you have to add the Mac specific Provisioning-UDID to the device list in the related provisioning profile. The selected platform must be "macos", else the UDID would be recognized as an iPod ^^.
Then in your Apple developer account under Profiles>[chose the right iOS profile]   you have to enable "include Mac devices".

...after updating your local profiles the Xcode build succeeds!
BUT: Fastlane match or sigh don't comply with this behavior. If I run fastlane match with --force_for_new_devices or --force. The iOS provisioning profile gets reset to exclude Mac devices and there is no option to avoid it.
@raphaelcruzeiro your provided workaround is simple but awesome if someone is in need that it works. However, I would prefer an additional fastlane match parameter to comply with this option.
To make things clear:
While I was working on this issue, there were a number of misleading error messages and information:

Apple asks for the device UUID. But in case of (Xcode Target: "My Mac (Designed for iPad)") you have to provide the Provisioning-UDID of the device.
The platform of the device still is "macos" even though the provisioning profile is "iOS".
Catalyst has nothing to do with it. It is still an iOS App, only. However, Apple Silicon can run iOS apps ^^

Agreed, it would be awesome to have Fastlane support this out-of-the-box specially now since M1 devices are gonna get more and more common.


MQTT topic naming: request/response -> in/out

This works when used in the demo app via
cd streaming-demo-app
npm install ../
go ...


Cannot specify path to rust-analyzer on windows

This line always results in an error on windows, making it impossible to specify the path to rust-analyzer.
let exits = PLUGIN_RPC
            .execute_process(program.to_string(), vec![server_path.to_string()])
            .map(|r| r.success)
            .unwrap_or(false);

Looking at the sourceode, it executes the program "where" with the path you provide. This does not work. Here is an example of the output:
where C:\Users\bnhei\.cargo\bin\rust-analyzer.exe
ERROR: Invalid pattern is specified in "path:pattern".

As we can see, we cannot simply input the path to rust analyzer with the where command. It will always fail. The correct format for this command is: {path-to-folder}:{filename-pattern-matcher}.

Same issue on Linux. Using lapce nightly. Rust plugin installed via lapce UI.

bumped.


Add a regex_cache to the SpamWave model and end post_matches? early

The primary issue this PR is attempting to improve is to reduce the time it takes to validate a spam waves, particularly the support number spam wave. The Support Number spam wave takes a considerable amount of time to validate (many tens of minutes) with a reduced complexity regular expression, and will often fail to validate due to taking too long. This PR should also reduce the CPU load for testing each reported post against active spam waves.
For regular expressions, a considerable amount of the time to use one is the time it takes to compile it into the representation which the regular expression engine then uses to run the regex. Currently, the spam wave code compiles each of the three regular expressions in the spam wave every time a post is run through post_matches?(). For validation, that can be several thousands of post reports. That's quite a bit of extra time spent re-compiling the same regexes.
This PR adds two levels of caching to the regexes used in the the SpamWave class. The first level is regex_cache as a class variable. If there's no compiled Regexp in the regex_cache for the regular expression text, then Rails.cache is checked for a serialized version of the compiled Regexp. If it doesn't exist in Rails.cache, then the regex text is compiled and the Regexp is stored in both levels of cache. The size of regex_cache is limited to MAX_REGEX_CACHE_SIZE, which is, currently, set to 100. Entries in the Rails.cache expire after 6 hours.
In addition to immediately returning false upon failure to match the non-regex based criteria, false is returned at the first point one of the three regexes fails to match. The regexes are run against the post in the order of increasing maximum length of the text (i.e. username, title, body) in order to fail with the least amount of effort, if possible.
The overall expectation is a notable reduction in the amount of time it takes to validate a spam wave and reduce the amount of time it takes to determine if an incoming report matches each active spam wave.

While I'm interested in having this reviewed and generally prefer not to merge without giving at least 24 hours for review, I'm going to go ahead and merge this and deploy, then watch the logs to verify it's doing what it's supposed to do. Given the current activity with support number spam, it would be quite helpful to have the support number spam wave working, which this will hopefully allow. Around now is also the lowest activity day/time of the week, so hopefully the least impact, should there be problems.


Java: Handlebars templating support

Add the necessary hooks and dependencies in our API.
Ensure we keep YAML/template processing as generic as possible. We should  support the use of other templating engines being swapped out.

Completed during implementation of v1 for Java.


32 CI test-coverage

Closes: #32
Goal
Add Coveralls to CI to encourage test coverage.
Approach

Follow Coveralls' (flawed) instructions.
These results seem to indicate success, but I want to confirm the badge works once this branch is merged to master. If so, I'll open a subsequent PR to replace the committed token with an environment variable.

Hopefully the test failure above will be fixed by merging to master.

@ivanoblomov still failing after rebasing on top of current master.
FYI error is:
/home/runner/work/_temp/5d59eb67-62c2-440e-a951-91f9698ca047.sh: line 3: coveralls: command not found

@neilberkman removing coveralls report and the GitHub action, and using the webhook instead worked. Ready for re-review!


Not getting any response while running DNX command multiple times.

From @v-pavanp on May 3, 2016 4:29

VSCode Version: 1.1.0-alpha
OS Version: windows10

Steps to Reproduce:

Create Aspnet C# console app using yeoman.
Set proper dotnet environment and verify response using dnx restore and dnx run.
Launch VSCode and open project folder.
Configure launch.json, task.json.
Perform DNX restore and DNX run command and verify response.
6, Now update project.json and add "debugType": "portable" under compilationOptions.
Build project and verify if any error message or warning is showing up.
Now try to perform "DNX restore" and "DNX: run command" operation from command palette and verify app behavior.

Actual: DNX command is responding very first time only and for further dnx execution there is no response.
Expected: User should get proper response when executing DNX command from command palette.
Note: Each time user needs to reload window or restart app to get DNX response.

Copied from original issue: Microsoft/vscode#6055

Dnx commands are obsolete(I guess), try using dotnet restore.
To create a new project you can use "dotnet new" in command line

If you're using the .NET CLI, the DNX commands definitely won't work.

Actually, if you see in the provided gif with the bug then you will find that DNX command is working but only at every first time (when you launch an app) and each time we need to restart VSCode to make it working.

It's interesting that they work at all, but I can imagine them not working consistently. Could you run dotnet --info to show what version you have installed?

Find the below detail:
C:\src\MyTestAppExpressForTimer\MyTestAppExpressForTimer>dotnet --info
Unknown option: --info
.NET Command Line Tools (1.0.0-beta-001661)
Usage: dotnet [common-options] [command] [arguments]
Arguments:
[command]     The command to execute
[arguments]   Arguments to pass to the command
Common Options (passed before the command):
-v|--verbose  Enable verbose output
--version     Display .NET CLI Version Info
Common Commands:
new           Initialize a basic .NET project
restore       Restore dependencies specified in the .NET project
build         Builds a .NET project
publish       Publishes a .NET project for deployment (including the runtime)
run           Compiles and immediately executes a .NET project
repl          Launch an interactive session (read, eval, print, loop)
pack          Creates a NuGet package

Also to provide you more info, from command line I am getting DNX response all the time, it is just a matter with VSCode for same project.

It sounds like you are living in a bit of a half-DNX/.NET CLI world, which can be a bit broken. If you're working on a .NET Core app (as opposed to the older DNX-style app), I'd recommend grabbing the latest .NET CLI from https://github.com/dotnet/cli and the most recent C# Extension for VS Code from https://github.com/OmniSharp/omnisharp-vscode/releases.
Please check out @gregg-miskelly's response to you in #270. He provided all of the information you need to get fixed up.

I got it fixed and able to debug my code. Please close this issue as I didn't see option for closing.

Glad to hear it! Let us know if you have anymore trouble.


Creating Audiio Object with Local Wav Files

Hi, I want to create a new Audio object with a local wav file, but it's giving me a NoBackendError. I'm wondering if you could please tell me how to fix this. My local wav file is called baiyang.wav. It is located in my local clone of amen, inside the example_audio folder with the two example audio. I used the same command in example_audio_file(). Below is the directory of my file and the error I got. Thank you so much.

Hi there!
That's an error from librosa, a library that Amen uses for reading audio.  You can look around on the internet for various fixes, but this thread is probably a good place to start.
Good luck!


Web - LHN - Endless spinner after navigating to free policy from OldDot

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Action Performed:

Log in NewDot with an account that has a existing workspace
Navigate to OldDot and sign in to a different account that has a existing free workspace.
Go to Settings > Policies > Group and click on free Workspace policy

Expected Result:
You're redirected to NewDot, you're logged in with the same account as in OldDot, LHN should display corresponding chats
Actual Result:
Encounter an endless spinner upon redirect to NewDot
Workaround:
Unknown
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Windows / Chrome

Version Number: <IP_ADDRESS>
Reproducible in staging?: Yes
Reproducible in production?: Yes
If this was caught during regression testing, add the test name, ID and link from TestRail:
Email or phone of affected tester (no customers): NewDot - Logged in with applausetester+1014pronin@applause.expensifail.com)/ Price123@
OldDot - Logged in with<EMAIL_ADDRESS>[Price123@
Logs: https://stackoverflow.com/c/expensify/questions/4856
Notes/Photos/Videos: Any additional supporting documentation
https://user-images.githubusercontent.com/93399543/211566784-91fa1076-6451-4cf3-b527-fa6240a66703.mp4
Expensify/Expensify Issue URL:
Issue reported by: Applause - Internal Team
Slack conversation:
View all open jobs on GitHub
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~017e871f98bc45cb2c
Upwork Job ID:<PHONE_NUMBER>715187712
Last Price Increase: 2023-01-24

Will take a look at this one!

Sorry, I was out with Covid all of last week, catching up today

I don't see a Slack convo linked - is that common? It's a bit hard to reproduce but I'm looking into how to make it happen locally

Bug0 Triage Checklist
Note: see this SO for more information.

[ ] The "bug" is actually a bug
[ ] The bug is not a duplicate report of an existing GH.

If it is, close the GH and add any novel details to the original GH instead

[ ] The bug is reproducible, following the reproduction steps.

[ ] If the GH doesn’t have steps to reliably reproduce the bug and you figure it out, then please add them.
[ ] If you’re unable to reproduce the bug, add the Needs reproduction label.
[ ] Comment on the issue outlining the steps you took to try to reproduce the bug, your results and tag the issue reporter and the Applause QA member who created the issue. Ask them to clarify reproduction steps and/or to check the reproduction steps again. Close issue.

[ ] The GH template is filled out as fully as possible

The GH body and title are clear (ie. could an external contributor understand it and work on it?)

[ ] The GH was created by an Expensify employee or a QA tester
[ ] If the bug is an OldDot issue, you should decide whether it is widespread enough to justify fixing or it is better to wait for reunification. If it’s better to wait, close the GH & provide this justification
[ ] If there's a link to Slack, check the discussion to see if we decided not to fix it
[ ] Decide if the GH should be resolved by an External contributor or Internal engineer, add the appropriate label

@yuwenmemon should I mark this Internal then?

Just did

@kbecciv @thesahindia @greg-schroeder  Now, instead of seeing the Chats from the previous logged in session, I'm seeing and endless spinner. Are you folks seeing the same?

So at least for the issue above, it seems like we're not removing the FullScreenLoadingIndicator that's coming from the LogOutPreviousUserPage.
The other thing I notice is that the modal property in Onyx has isVisible set to false:

When we load the workspace already logged in, this shows up as true.
@neil-marcellini I see you worked on some of this. I'm not sure where exactly to go from here. Any ideas? 🤔

@yuwenmemon @greg-schroeder @thesahindia this issue is now 4 weeks old and preventing us from maintaining WAQ. This should now be your highest priority. Please post below what your plan is to get a PR in review ASAP. Thanks!

@yuwenmemon, @greg-schroeder, @thesahindia Huh... This is 4 days overdue. Who can take care of this?

Trying to repro again now to see if I get the old chats or the endless spinner

I updated the issue title/OP with the current bug behavior

@neil-marcellini I see you worked on some of this. I'm not sure where exactly to go from here. Any ideas? 🤔

I would check and make sure that we are signing out the previous user and then signing in the transitioning user. In the past the transitioning user has gotten signed out due to weirdness with Onyx.clear. Perhaps there was a regression?

@yuwenmemon, @greg-schroeder, @thesahindia Eep! 4 days overdue now. Issues have feelings too...

@yuwenmemon, @greg-schroeder, @thesahindia Huh... This is 4 days overdue. Who can take care of this?

No update just yet but looking back into this tomorrow.

Hmmm... @neil-marcellini I see that we properly call OpenReport with a successful response:

So I feel like we're properly signed in. Maybe somewhere we're not dismissing a spinner properly?

Oh hm but I do see that the FullScreenLoadingIndicator we're showing is coming from the LogOutPreviousUserPage

Okay, some git bisecting points to this commit as the one that at least introduced the spinner. Make sense as it has to do with Onyx.clear.
Need to step out but will resume looking again tomorrow.

Yes I think the transitioning user gets signed in and then somehow they are getting signed out again. Last time it was due to Onyx.clear setting the default key state for the session, which set the authToken to null after the user had been signed in. There could be a different cause this time.

Hmmm... I'm not sure it's related to having an authToken or not, since we do successfully load the report:
https://user-images.githubusercontent.com/4741899/219119095-d9a1dbbc-33d7-4b9f-82ed-d0b57e2d2a72.mp4

@marcaaron I'm curious... what's the difference between these two routes? Any idea why they would get called one after the other?
[info] Navigating to route - {"path":"/?initial=true&screen=Workspace_Initial&params=%5Bobject%20Object%5D&path=%2Fworkspace%2FC767ECB09FE25125"}
[info] Navigating to route - {"path":"/workspace/C767ECB09FE25125"}

I'm pretty confused. The second appears to be a normal route to a workspace page. The other looks like something gone wrong params=%5Bobject%20Object%5D in particular suggests something weird is happening since that is a string representation of a JS object (a.k.a. params=[object Object]).

Hmmm... After another few hours of looking, I'm pretty stumped. Although I don't think this has any dependence on the API, so gonna flip it External and see if we have any good ideas from our contributors. I have two newsletter projects I need to focus on 😅

Current assignee @greg-schroeder is eligible for the External assigner, not assigning anyone new.

Current assignee @thesahindia is eligible for the External assigner, not assigning anyone new.

Current assignee @yuwenmemon is eligible for the External assigner, not assigning anyone new.

@yuwenmemon, @greg-schroeder, @thesahindia Whoops! This issue is 2 days overdue. Let's get this updated quick!

Awaiting proposals

Looks like something related to react-navigation may have been mentioned in this issue discussion.
As a reminder, please make sure that all proposals are not workarounds and that any and all attempt to fix the issue holistically have been made before proceeding with a solution. Proposals to change our DeprecatedCustomActions.js files should not be accepted.
Feel free to drop a note in #expensify-open-source with any questions.

📣 @ntdiary! 📣
Hey, it seems we don’t have your contributor details yet! You'll only have to do this once, and this is how we'll hire you on Upwork.
Please follow these steps:

Get the email address used to login to your Expensify account. If you don't already have an Expensify account, create one here. If you have multiple accounts (e.g. one for testing), please use your main account email.
Get the link to your Upwork profile. It's necessary because we only pay via Upwork. You can access it by logging in, and then clicking on your name. It'll look like this. If you don't already have an account, sign up for one here.
Copy the format below and paste it in a comment on this issue. Replace the placeholder text with your actual details.

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Thanks @ntdiary - are you proposing we try these solutions you've listed in that order? Have you tried each type of implementation?

We need to ensure that dismissModal is executed after the navigationRef is ready.
For example:
create a new Promise object for isNavigationReady.
or may need to create a Promise for navigationRef.
or reset drawer promise object in BaseDrawerNavigator.componentWillUnmount

@thesahindia can you take a look at @ntdiary's proposal and let us know what you think?
@ntdiary Just for reference if we like your proposal and hire you, you'll be the one to make the PR and get paid 💰

Thanks! @ntdiary feed free to create a PR!

📣 @ntdiary You have been assigned to this job by @yuwenmemon!
Please apply to this job in Upwork and leave a comment on the Github issue letting us know when we can expect a PR to be ready for review 🧑💻
Keep in mind: Code of Conduct | Contributing 📖

Excellent, let us know if you have any questions @ntdiary!

Reviewing label has been removed, please complete the "BugZero Checklist".

The solution for this issue has been :rocket: deployed to production :rocket: in version 1.2.77-4 and is now subject to a 7-day regression period :calendar:. Here is the list of pull requests that resolve this issue:

https://github.com/Expensify/App/pull/15500

If no regressions arise, payment will be issued on 2023-03-09. :confetti_ball:
After the hold period is over and BZ checklist items are completed, please complete any of the applicable payments for this issue, and check them off once done.

[ ] External issue reporter
[ ] Contributor that fixed the issue
[ ] Contributor+ that helped on the issue and/or PR

As a reminder, here are the bonuses/penalties that should be applied for any External issue:

Merged PR within 3 business days of assignment - 50% bonus
Merged PR more than 9 business days after assignment - 50% penalty

BugZero Checklist: The PR fixing this issue has been merged! The following checklist (instructions) will need to be completed before the issue can be closed:

[ ] [@thesahindia / @yuwenmemon] The PR that introduced the bug has been identified. Link to the PR:
[ ] [@thesahindia / @yuwenmemon] The offending PR has been commented on, pointing out the bug it caused and why, so the author and reviewers can learn from the mistake. Link to comment:
[ ] [@thesahindia / @yuwenmemon] A discussion in #expensify-bugs has been started about whether any other steps should be taken (e.g. updating the PR review checklist) in order to catch this type of bug sooner. Link to discussion:
[ ] [@ntdiary] Propose regression test steps to ensure the same bug will not reach production again.
[ ] [@greg-schroeder] Link the GH issue for creating/updating the regression test once above steps have been agreed upon:

Extended offers to @ntdiary and @thesahindia, please accept and will take care of payment!

paid!

@yuwenmemon @thesahindia do you guys mind filling out the items listed here? Also, are you able to weigh in on the regression test posed above? <3

All paid, regression test GH created. Closing.


Update Go code to new interfaces

See:

https://github.com/senzing-garage/g2-sdk-go-base/issues/151

Pull requests:

https://github.com/senzing-garage/go-rest-api-service/pull/154


Option to select multiple Maven Server IDs at once

Thank you for this very useful plugin!
My team uses this plugin with our AWS Code Artifact repositories. The only problem is that we have 3 different repositories in CodeArtifact that our projects use, so we have to run the tool 3 times for 3 different servers in our settings.xml file. They could all use the same token though, since they are in the same AWS environment.
Could you add a multi-select option to the "Maven server id" selector, so that we could run the tool once and it would use 1 generated token in multiple different <server> sections in the settings.xml file? Or even add an option <all> to the drop down that would allow you to update all servers which use the aws username?
Thanks!

I was looking for other work-arounds for this issue. It turns out that AWS lets you create an Aggregate repository that uses all of your other repos as upstream repos. I'm going to create an aggregate repo so that we only need to use 1 repo in our settings.xml file.
This change might still be useful in some scenarios, but it is certainly not needed. Feel free to close if you don't want to implement this option.

Hi, Jesse, I was thinking about what would be the best UX for this solution,
I will try implementing it in the best possible way asap.
Best regards,
Lu.
On Thu, Aug 22, 2024 at 7:17 PM Jesse Webb @.***> wrote:

I was looking for other work-arounds for this issue. It turns out that AWS
lets you create an Aggregate repository that uses all of your other repos
as upstream repos. I'm going to create an aggregate repo so that we only
need to use 1 repo in our settings.xml file.
This change might still be useful in some scenarios, but it is certainly
not needed. Feel free to close if you don't want to implement this option.
—
Reply to this email directly, view it on GitHub
https://github.com/coderazzi/aws_codeartifact_maven/issues/16#issuecomment-2305264467,
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.
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Hi, Jesse,
it took some time, but I have deployed a new version with configuration for
multiple tokens.
You can verify it, it is a beta download:
https://plugins.jetbrains.com/plugin/16777-aws-codeartifact--maven/versions/beta
Best,
Lu
On Fri, Aug 23, 2024 at 9:50 AM coderazzi @.***> wrote:

Hi, Jesse, I was thinking about what would be the best UX for this
solution,
I will try implementing it in the best possible way asap.
Best regards,
Lu.
On Thu, Aug 22, 2024 at 7:17 PM Jesse Webb @.***>
wrote:

I was looking for other work-arounds for this issue. It turns out that
AWS lets you create an Aggregate repository that uses all of your other
repos as upstream repos. I'm going to create an aggregate repo so that we
only need to use 1 repo in our settings.xml file.
This change might still be useful in some scenarios, but it is certainly
not needed. Feel free to close if you don't want to implement this option.
—
Reply to this email directly, view it on GitHub
https://github.com/coderazzi/aws_codeartifact_maven/issues/16#issuecomment-2305264467,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AAH54IJ7SAUQ3VFOO35DR3DZSYMLFAVCNFSM6AAAAABM6QXKCKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGMBVGI3DINBWG4
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laravel 8.17.1 profile-photos in public storage file not getting propagated

Laravel Version: 8.17.1
PHP Version: 7.4.10
Database Driver & Version:

Description:
not able to see profile-photos  the photos shows up in the storage/public/profile-photos file and in the database but not in the public/storage/profile-photos file and therefore not in the dashboard header either.
Steps To Reproduce:
I just did the normal Laravel new project name --jer
registered and went to the profile page to choose a photo the initial photo showed up but after saving it I just got my name. and know photo. when I checked the database the profile_photo_path was there so I went to the storage\app\ and found a livewire-temp file with a image in it.  Next I went to the storage\app\public\profile-photos folder and it to had a image in it. But when I went to public\Storage\Profile-photos it was empty.  so I then ran the php artisan storage:link command but it said that the "link already exists".
now what? why is it not putting the image in the public folder?  what do I nave to do to get it to do so?  if I copy the image from the storage folder to the public folder it works just fine.  It seems to me that the automatic copy function is not working.

PS this did work in Laravel 8.12.3 just fine.


[BUG] bloxstrap.org is blacklisted

Acknowledgement of preliminary instructions

[X] I have read the preliminary instructions, and I am certain that my problem has not already been addressed.
[ ] My answer given in the checkbox above is a lie.

What problem did you encounter?
When I go to bloxstrap.org site in any web browser, my antivirus software and uBlock Origin extension block access. Please fix that issue.

bloxstrap.org is a fake domain the only one (as of right now) that is owned by PizzaBoxer is bloxstrap.pizzaboxer.xyz

Thanks. I need to quickly reinstall the bloxstrap because I used fake one.


Replace hash based node cache with ZK node versino based

@mpolden please review and merge. This is the same construct as in the controller.

Yes, that was when nodes didn't have a stable path. That change should allow this :)


enrico_sed issue: Error in "Preparing submission of fit into energy bins"

Hi, I am facing the following error while running enrico_sed.
After fitting the spectrum over the full energy range with GTLIKE, it shows the following error:
************************************************************
*** Preparing submission of fit into energy bins ***
************************************************************
('Emin = 100.0 MeV', 'Emax = 300000.0 MeV', 'Nbins = 5')
Debug: read energy bins: logE
Energy bins (before energy cuts): [1.00000000e+02 4.95934420e+02 2.45950949e+03 1.21975541e+04
6.04918691e+04 3.00000000e+05]
Energy bins (after energy cuts): [1.00000000e+02 4.95934420e+02 2.45950949e+03 1.21975541e+04
6.04918691e+04 3.00000000e+05]
[Message]: Submitting # 0 at energy 222
Traceback (most recent call last):
File "/home/hegro/enrico/bin/enrico_sed", line 48, in
liste = np.genfromtxt(sys.argv[1],dtype="str",unpack=True)
File "/home/hegro/anaconda3/envs/fermi/lib/python3.7/site-packages/numpy/lib/npyio.py", line 2068, in genfromtxt
raise ValueError(errmsg)
ValueError: Some errors were detected !
Line #9 (got 1 columns instead of 3)
Line #20 (got 1 columns instead of 3)
Line #29 (got 1 columns instead of 3)
Line #37 (got 1 columns instead of 3)
Line #43 (got 1 columns instead of 3)
Line #49 (got 1 columns instead of 3)
Line #54 (got 1 columns instead of 3)
Line #70 (got 1 columns instead of 3)
Line #79 (got 1 columns instead of 3)
Line #85 (got 1 columns instead of 3)
Line #101 (got 1 columns instead of 3)
Line #111 (got 1 columns instead of 3)
Line #123 (got 1 columns instead of 3)
Line #142 (got 1 columns instead of 3)
Line #158 (got 1 columns instead of 3)
Line #166 (got 1 columns instead of 3)
Line #181 (got 1 columns instead of 3)
Line #195 (got 1 columns instead of 3)
Line #206 (got 1 columns instead of 3)
Line #212 (got 1 columns instead of 3)
Line #222 (got 1 columns instead of 3)
Line #226 (got 1 columns instead of 3)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/hegro/enrico/bin/enrico_sed", line 55, in
sed(config,infile)
File "/home/hegro/enrico/bin/enrico_sed", line 13, in sed
run(infile)
File "/home/hegro/enrico/enrico/RunGTlike.py", line 262, in run
energybin.RunEbin(folder,Nbin,Fit,FitRunner,sedresult)
File "/home/hegro/enrico/enrico/energybin.py", line 209, in RunEbin
configfiles = PrepareEbin(Fit, FitRunner,sedresult)
File "/home/hegro/enrico/enrico/energybin.py", line 202, in PrepareEbin
config.write(open(config['out'] + '/' +filename, 'w')) #save the config file in a ascii file
File "/home/hegro/enrico/enrico/extern/configobj.py", line 2098, in write
outfile.write(output_bytes)
TypeError: write() argument must be str, not bytes
It seems that there are two different issues. One in "/home/hegro/enrico/bin/enrico_sed", line 48 and another in "/home/hegro/enrico/enrico/extern/configobj.py", line 2098. The program stops just before making the configuration file for the first energy bin.

Hi
strange error. So there is no .conf in the EBin folder ?
david

Hi @davidsanchez,
Thanks for your quick reply.
It creates a config file only for the 0th energy bin in the Ebin#/ folder. But that file is empty. It seems that enrico_sed is showing this error while writing the config file.

Do you have the output of the fit ?

Yes, I have the .results file and also fitted models and figures in the Spectrum folder.

I mean could you pass here the output (not the file but what is printed on the screen/log)

The following is the GTLIKE output:
************************************************************
***   8     gtlike --- Run likelihood analysis
************************************************************
Fit output with MINUIT: 49240.716557181666 [quality: 3]
Fit output with MINUIT: 49240.71546901978 [quality: 3]
************************************************************
***   9 Remove all the weak (TS<1.00) sources
************************************************************
[FitMaker]: deleting source 4FGL J1332.6-1256 with TS = -0.00712294147524517 from the model
[FitMaker]: deleting source 4FGL J1337.6-1257 with TS = -0.0054168528149602935 from the model
[FitMaker]: deleting source 4FGL J1339.9-0138 with TS = -0.00010943903180304915 from the model
[FitMaker]: deleting source 4FGL J1340.0-1501 with TS = -4.487123806029558e-05 from the model
[FitMaker]: deleting source 4FGL J1340.8-0409 with TS = -0.002124518563505262 from the model
[FitMaker]: deleting source 4FGL J1341.8-2053 with TS = 0.00562053217436187 from the model
[FitMaker]: deleting source 4FGL J1344.2-1723 with TS = 0.002037400350673124 from the model
[FitMaker]: deleting source 4FGL J1349.5-1131 with TS = -0.009064615194802172 from the model
[FitMaker]: deleting source 4FGL J1351.0+0029 with TS = -0.00397688354132697 from the model
[FitMaker]: deleting source 4FGL J1351.4-1529 with TS = 0.0005873925256310031 from the model
[FitMaker]: deleting source 4FGL J1354.3-0206 with TS = -0.008570907593821175 from the model
[FitMaker]: deleting source 4FGL J1354.8-1041 with TS = -0.023390544301946647 from the model
[FitMaker]: deleting source 4FGL J1356.2-1726 with TS = -0.00021614355500787497 from the model
[FitMaker]: deleting source 4FGL J1356.6+0234 with TS = -0.0003922647883882746 from the model
[FitMaker]: deleting source 4FGL J1357.5+0127 with TS = -0.004804356009117328 from the model
[FitMaker]: deleting source 4FGL J1359.1-1152 with TS = -0.0008298519387608394 from the model
[FitMaker]: deleting source 4FGL J1359.4+0202 with TS = -0.006153804948553443 from the model
[FitMaker]: deleting source 4FGL J1400.0-2415 with TS = -0.00019897155289072543 from the model
[FitMaker]: deleting source 4FGL J1400.6-1432 with TS = -0.01788416002818849 from the model
[FitMaker]: deleting source 4FGL J1401.2-0915 with TS = -0.018669255761778913 from the model
[FitMaker]: deleting source 4FGL J1402.5-1827 with TS = 0.0305073520867154 from the model
[FitMaker]: deleting source 4FGL J1404.8+0402 with TS = -0.004239161993609741 from the model
[FitMaker]: deleting source 4FGL J1405.3-0640 with TS = -0.0005581212608376518 from the model
[FitMaker]: deleting source 4FGL J1405.9-1853 with TS = 0.001975885999854654 from the model
[FitMaker]: deleting source 4FGL J1406.1-2508 with TS = 0.005351646672352217 from the model
[FitMaker]: deleting source 4FGL J1406.4-1654 with TS = -0.0003738041123142466 from the model
[FitMaker]: deleting source 4FGL J1407.4-0820 with TS = -0.1396521363494685 from the model
[FitMaker]: deleting source 4FGL J1408.9-0751 with TS = -0.6610691065288847 from the model
[FitMaker]: deleting source 4FGL J1410.1+0202 with TS = -0.011197760599316098 from the model
[FitMaker]: deleting source 4FGL J1411.5-0723 with TS = -0.0692166864319006 from the model
[FitMaker]: deleting source 4FGL J1415.9-1504 with TS = -0.11498336688964628 from the model
[FitMaker]: deleting source 4FGL J1416.1-2417 with TS = -0.002590631425846368 from the model
[FitMaker]: deleting source 4FGL J1419.3+0444 with TS = -0.010185415143496357 from the model
[FitMaker]: deleting source 4FGL J1419.4-0838 with TS = -8.049897782693733 from the model
[FitMaker]: deleting source 4FGL J1420.3+0612 with TS = -0.04499155444500502 from the model
[FitMaker]: deleting source 4FGL J1420.9-2431 with TS = -0.013904778665164486 from the model
[FitMaker]: deleting source 4FGL J1421.1-1120 with TS = -0.37450297402392607 from the model
[FitMaker]: deleting source 4FGL J1424.1-1750 with TS = 0.6752714891335927 from the model
[FitMaker]: deleting source 4FGL J1424.2+0433 with TS = -0.09707877573964652 from the model
[FitMaker]: deleting source 4FGL J1425.4-0119 with TS = -0.3083101874071872 from the model
[FitMaker]: deleting source 4FGL J1427.4-1823 with TS = 0.8454158349777572 from the model
[FitMaker]: deleting source 4FGL J1429.8-0739 with TS = -0.32103219722921494 from the model
[FitMaker]: deleting source 4FGL J1429.8-3058 with TS = -0.08873161011433695 from the model
[FitMaker]: deleting source 4FGL J1431.1-3120 with TS = -0.0877268161275424 from the model
[FitMaker]: deleting source 4FGL J1438.0-3128 with TS = -0.08501442096894607 from the model
[FitMaker]: deleting source 4FGL J1439.5-2525 with TS = -0.08072148643259425 from the model
[FitMaker]: deleting source 4FGL J1440.0-1530 with TS = -0.5827226449036971 from the model
[FitMaker]: deleting source 4FGL J1440.0-2343 with TS = -0.08050154559896328 from the model
[FitMaker]: deleting source 4FGL J1440.9+0609 with TS = -0.2526294031558791 from the model
[FitMaker]: deleting source 4FGL J1441.4-1934 with TS = -0.3516205923369853 from the model
[FitMaker]: deleting source 4FGL J1441.6-1522 with TS = -0.22813979879720137 from the model
[FitMaker]: deleting source 4FGL J1442.0+0732 with TS = -0.20392694701149594 from the model
[FitMaker]: deleting source 4FGL J1442.1-2800 with TS = -0.1801933503447799 from the model
[FitMaker]: deleting source 4FGL J1442.2+0622 with TS = -0.24505722265166696 from the model
[FitMaker]: deleting source 4FGL J1442.7+1200 with TS = -0.19393373461207375 from the model
[FitMaker]: deleting source 4FGL J1443.7-0954 with TS = 0.5919872793310788 from the model
[FitMaker]: deleting source 4FGL J1445.0-0326 with TS = 0.038157326518557966 from the model
[FitMaker]: deleting source 4FGL J1445.2-1954 with TS = -0.4091331794625148 from the model
[FitMaker]: deleting source 4FGL J1445.9-1626 with TS = -1.4692265302728629 from the model
[FitMaker]: deleting source 4FGL J1446.0-3039 with TS = -0.35505657641624566 from the model
[FitMaker]: deleting source 4FGL J1446.8-1830 with TS = -0.5631435969262384 from the model
[FitMaker]: deleting source 4FGL J1447.0-2657 with TS = -0.35449709350359626 from the model
[FitMaker]: deleting source 4FGL J1449.7-0910 with TS = -0.6322071081522154 from the model
[FitMaker]: deleting source 4FGL J1450.4+0910 with TS = -0.40708087899838574 from the model
[FitMaker]: deleting source 4FGL J1450.8-1424 with TS = -0.6991924689064035 from the model
[FitMaker]: deleting source 4FGL J1451.5+1415 with TS = -0.3978167547029443 from the model
[FitMaker]: deleting source 4FGL J1453.0-1318 with TS = -0.598968280130066 from the model
[FitMaker]: deleting source 4FGL J1458.8-2120 with TS = 0.8467100420966744 from the model
[FitMaker]: deleting source 4FGL J1459.5+1527 with TS = -0.44808528445719276 from the model
[FitMaker]: deleting source 4FGL J1504.4+1029 with TS = -1.1950261394522386 from the model
[FitMaker]: deleting source 4FGL J1506.4-0540 with TS = -0.6278970189887332 from the model
[FitMaker]: deleting source 4FGL J1506.6+0813 with TS = -0.5225255366094643 from the model
[FitMaker]: deleting source 4FGL J1507.1-1901 with TS = -0.3066996732231928 from the model
[FitMaker]: deleting source 4FGL J1509.8-2906 with TS = -0.5499284198158421 from the model
[FitMaker]: deleting source 4FGL J1511.8-0513 with TS = -0.8063493656372884 from the model
[FitMaker]: deleting source 4FGL J1512.1-2255 with TS = 0.07174629121436737 from the model
[FitMaker]: deleting source 4FGL J1513.0-3118 with TS = -0.7445610385329928 from the model
[FitMaker]: deleting source 4FGL J1513.4-2549 with TS = -0.7277904406364542 from the model
[FitMaker]: deleting source 4FGL J1513.4-3231 with TS = -0.7332403636828531 from the model
[FitMaker]: deleting source 4FGL J1513.7-1519 with TS = -1.2569260614545783 from the model
[FitMaker]: deleting source 4FGL J1514.6-2044 with TS = -0.9393997341103386 from the model
[FitMaker]: deleting source 4FGL J1514.8-0949 with TS = -0.4429111217323225 from the model
[FitMaker]: deleting source 4FGL J1516.5+0015 with TS = -0.7426417550450424 from the model
[FitMaker]: deleting source 4FGL J1518.0-2731 with TS = -1.37464570227894 from the model
[FitMaker]: deleting source 4FGL J1518.4+0750 with TS = -1.4463787041459 from the model
[FitMaker]: deleting source 4FGL J1518.6+0614 with TS = -1.4699186400102917 from the model
[FitMaker]: deleting source 4FGL J1518.8+0203 with TS = -1.4848621228593402 from the model
[FitMaker]: deleting source 4FGL J1520.0-0905 with TS = -1.8766564701509196 from the model
[FitMaker]: deleting source 4FGL J1520.8-0348 with TS = -2.012707375586615 from the model
[FitMaker]: deleting source 4FGL J1521.1+0421 with TS = -1.5306927689525764 from the model
[FitMaker]: deleting source 4FGL J1522.6-2730 with TS = -1.5203909049159847 from the model
[FitMaker]: deleting source 4FGL J1523.2+0533 with TS = -1.8323717760649743 from the model
[FitMaker]: deleting source 4FGL J1526.1-0831 with TS = -0.8386709330516169 from the model
[FitMaker]: deleting source 4FGL J1526.6-2743 with TS = -1.6678279140178347 from the model
[FitMaker]: deleting source 4FGL J1526.7-1529 with TS = -1.5006464588805102 from the model
[FitMaker]: deleting source 4FGL J1527.8+1013 with TS = -1.7209935879218392 from the model
[FitMaker]: deleting source 4FGL J1528.2-2905 with TS = -1.563290631675045 from the model
[FitMaker]: deleting source 4FGL J1528.5-2240 with TS = -1.3921759924851358 from the model
[FitMaker]: deleting source 4FGL J1530.0-1522 with TS = -2.2924059934011893 from the model
[FitMaker]: deleting source 4FGL J1530.5-3026 with TS = -1.6009327300853329 from the model
[FitMaker]: deleting source 4FGL J1531.6+0406 with TS = -1.5690247454040218 from the model
[FitMaker]: deleting source 4FGL J1532.7-1319 with TS = -1.794215024652658 from the model
[FitMaker]: deleting source 4FGL J1534.3-3312 with TS = -1.6439705352531746 from the model
[FitMaker]: deleting source 4FGL J1534.8+0131 with TS = -1.854856799429399 from the model
[FitMaker]: deleting source 4FGL J1535.3-3135 with TS = -2.040357100064284 from the model
[FitMaker]: deleting source 4FGL J1536.8-3155 with TS = -2.0372036802145885 from the model
[FitMaker]: deleting source 4FGL J1537.9-1344 with TS = -2.3804225515923463 from the model
[FitMaker]: deleting source 4FGL J1538.9+0425 with TS = -2.764180639118422 from the model
[FitMaker]: deleting source 4FGL J1539.1+1008 with TS = -2.0972365172492573 from the model
[FitMaker]: deleting source 4FGL J1539.7-1127 with TS = -0.0814510937925661 from the model
[FitMaker]: deleting source 4FGL J1540.7+1449 with TS = -2.2104425191500923 from the model
[FitMaker]: deleting source 4FGL J1541.7+1413 with TS = -2.2100856833567377 from the model
[FitMaker]: deleting source 4FGL J1541.9-2915 with TS = -2.204504262015689 from the model
[FitMaker]: deleting source 4FGL J1543.6+0452 with TS = -2.4586422513239086 from the model
[FitMaker]: deleting source 4FGL J1543.6-0244 with TS = -3.2729999945440795 from the model
[FitMaker]: deleting source 4FGL J1544.2-2554 with TS = -2.4789599007490324 from the model
[FitMaker]: deleting source 4FGL J1545.8-2336 with TS = -2.49981462174037 from the model
[FitMaker]: deleting source 4FGL J1546.0+0819 with TS = -2.501213362760609 from the model
[FitMaker]: deleting source 4FGL J1546.1-1003 with TS = -2.0015596741141053 from the model
[FitMaker]: deleting source 4FGL J1546.8-3244 with TS = -2.432929141970817 from the model
[FitMaker]: deleting source 4FGL J1547.3-1531 with TS = -2.6921811999636702 from the model
[FitMaker]: deleting source 4FGL J1547.3-2802 with TS = -2.4674340159690473 from the model
[FitMaker]: deleting source 4FGL J1548.8-2250 with TS = -2.716789146477822 from the model
[FitMaker]: deleting source 4FGL J1549.5+0236 with TS = -0.1269955691532232 from the model
[FitMaker]: deleting source 4FGL J1549.8-3044 with TS = -2.9124242155085085 from the model
[FitMaker]: deleting source 4FGL J1550.7+0528 with TS = -2.9749823057063622 from the model
[FitMaker]: deleting source 4FGL J1550.8-0822 with TS = -3.320431684871437 from the model
[FitMaker]: deleting source 4FGL J1550.8-1750 with TS = -3.7547942544333637 from the model
[FitMaker]: deleting source 4FGL J1552.0+0850 with TS = -3.116513828819734 from the model
[FitMaker]: deleting source 4FGL J1553.5-3118 with TS = -3.1233273915131576 from the model
[FitMaker]: deleting source 4FGL J1553.6+1257 with TS = -3.1199018865299877 from the model
[FitMaker]: deleting source 4FGL J1553.6-2422 with TS = -3.26602428710612 from the model
[FitMaker]: deleting source 4FGL J1554.4-1215 with TS = -3.979134609660832 from the model
[FitMaker]: deleting source 4FGL J1555.7+1111 with TS = -3.2220485062571242 from the model
[FitMaker]: deleting source 4FGL J1555.7-2908 with TS = -3.220626394817373 from the model
[FitMaker]: deleting source 4FGL J1557.9-0001 with TS = -3.3736008114210563 from the model
[FitMaker]: deleting source 4FGL J1557.9-1404 with TS = -3.3684789294784423 from the model
[FitMaker]: deleting source 4FGL J1559.8-2525 with TS = -3.529605369840283 from the model
[FitMaker]: deleting source 4FGL J1600.9-3054 with TS = -3.3784282783744857 from the model
[FitMaker]: deleting source 4FGL J1602.9-1928 with TS = -3.6147006698010955 from the model
[FitMaker]: deleting source 4FGL J1603.6-0451 with TS = -1.7658788010012358 from the model
[FitMaker]: deleting source 4FGL J1603.8+1104 with TS = -3.6699032923352206 from the model
[FitMaker]: deleting source 4FGL J1605.1-1140 with TS = -4.543095158049255 from the model
[FitMaker]: deleting source 4FGL J1608.0-2038 with TS = -3.957604248265852 from the model
[FitMaker]: deleting source 4FGL J1608.4+0055 with TS = -3.837419725372456 from the model
[FitMaker]: deleting source 4FGL J1608.7+1029 with TS = -3.7961084456328535 from the model
[FitMaker]: deleting source 4FGL J1612.4+0409 with TS = -3.968019324776833 from the model
[FitMaker]: deleting source 4FGL J1613.3-1907 with TS = -3.993967721282388 from the model
[FitMaker]: deleting source 4FGL J1614.5-2230 with TS = -3.9933687043812824 from the model
[FitMaker]: deleting source 4FGL J1615.3-1512 with TS = -3.997596652203356 from the model
[FitMaker]: deleting source 4FGL J1616.9-2257 with TS = -3.8500702803139575 from the model
[FitMaker]: deleting source 4FGL J1617.2-2535 with TS = -3.848815622564871 from the model
[FitMaker]: deleting source 4FGL J1617.3-1513 with TS = -4.021806043718243 from the model
[FitMaker]: deleting source 4FGL J1621.0-2625 with TS = -3.864028885640437 from the model
[FitMaker]: deleting source 4FGL J1621.7-1103 with TS = -4.040665007472853 from the model
[FitMaker]: deleting source 4FGL J1623.0-0315 with TS = -4.053999381794711 from the model
[FitMaker]: deleting source 4FGL J1623.7-2315c with TS = -3.9335171463462757 from the model
[FitMaker]: deleting source 4FGL J1625.1-0020 with TS = -3.9349588968907483 from the model
[FitMaker]: deleting source 4FGL J1625.3-2338 with TS = -3.937131130194757 from the model
[FitMaker]: deleting source 4FGL J1625.7-2527 with TS = -3.935349335835781 from the model
[FitMaker]: deleting source 4FGL J1626.9-2431e with TS = -3.9536801656649914 from the model
[FitMaker]: deleting source 4FGL J1627.7+0251 with TS = -3.9639646167197498 from the model
[FitMaker]: deleting source 4FGL J1630.1-1049 with TS = -4.129757436996442 from the model
[FitMaker]: deleting source 4FGL J1632.8-1048 with TS = -4.124212827649899 from the model
[FitMaker]: deleting source 4FGL J1634.7+0235 with TS = -3.989087947367807 from the model
[FitMaker]: deleting source 4FGL J1636.5-0454 with TS = -3.9881095696182456 from the model
[FitMaker]: deleting source 4FGL J1638.0+0042 with TS = -3.98934607092815 from the model
[FitMaker]: deleting source 4FGL J1641.9-0621 with TS = -3.972606141556753 from the model
[FitMaker]: deleting source 4FGL J1643.5-0646 with TS = -3.9964283176668687 from the model
[FitMaker]: deleting source 4FGL J1646.0-0942 with TS = -4.000405719489208 from the model
[FitMaker]: deleting source 4FGL J1646.7-1330 with TS = -4.002770798004349 from the model
[FitMaker]: deleting source 4FGL J1647.2-0154 with TS = -4.002640689301188 from the model
[FitMaker]: deleting source 4FGL J1648.1-1547 with TS = -4.002837581574568 from the model
[FitMaker]: keeping source 4FGL J1418.4-0233 with TS=6.26e+00
[FitMaker]: keeping source 4FGL J1433.0-1801 with TS=2.18e+00
[FitMaker]: keeping source 4FGL J1503.7-1540 with TS=2.78e+00
[FitMaker]: keeping source 4FGL J1505.0+0326 with TS=2.85e+00
[FitMaker]: keeping source 4FGL J1510.8-0542 with TS=1.45e+00
[FitMaker]: keeping source 4FGL J1512.2+0202 with TS=8.87e+00
[FitMaker]: keeping source 4FGL J1517.7-2422 with TS=2.31e+00
[FitMaker]: keeping source 4FGL J1544.5-1126 with TS=5.39e+00
[FitMaker]: keeping source 4FGL J1549.8-0659 with TS=6.73e+00
[FitMaker]: keeping source GalDiffModel with TS=5.39e+02
[FitMaker]: keeping source IsoDiffModel with TS=4.75e+01
[FitMaker]: keeping source PKS1510 with TS=7.78e+01
************************************************************
***  10 Re-optimize ---
************************************************************
Fit output with MINUIT: 49237.40090700385 [quality: 3]
[FitMaker]: Fit with gtlike performed

No value of the source parameters?

Yes, the source parameters are given below. Sorry for being late.
************************************************************
***  12    Results --- Print results of the fit
************************************************************
(4FGL J1418.4-0233
Spectrum: LogParabola
0           norm:  7.394e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
1          alpha:  1.646e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
2           beta:  7.432e-02  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
3             Eb:  1.836e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1433.0-1801
Spectrum: LogParabola
4           norm:  1.251e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
5          alpha:  2.491e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
6           beta:  2.664e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
7             Eb:  7.345e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1503.7-1540
Spectrum: PowerLaw
8      Prefactor:  6.605e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
9          Index: -1.806e+00  0.000e+00 -6.000e+00 -5.000e-01 ( 1.000e+00) fixed
10         Scale:  3.868e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1505.0+0326
Spectrum: LogParabola
11          norm:  1.771e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-11) fixed
12         alpha:  2.477e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
13          beta:  1.038e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
14            Eb:  4.009e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1510.8-0542
Spectrum: LogParabola
15          norm:  2.736e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
16         alpha:  2.385e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
17          beta:  1.082e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
18            Eb:  8.653e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1512.2+0202
Spectrum: LogParabola
19          norm:  2.310e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
20         alpha:  2.013e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
21          beta:  1.158e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
22            Eb:  9.521e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1517.7-2422
Spectrum: LogParabola
23          norm:  1.037e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-11) fixed
24         alpha:  2.078e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
25          beta:  2.835e-02  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
26            Eb:  8.241e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1544.5-1126
Spectrum: LogParabola
27          norm:  4.632e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-11) fixed
28         alpha:  2.290e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
29          beta:  1.942e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
30            Eb:  6.317e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1549.8-0659
Spectrum: PowerLaw
31     Prefactor:  1.192e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
32         Index: -1.946e+00  0.000e+00 -6.000e+00 -5.000e-01 ( 1.000e+00) fixed
33         Scale:  2.845e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
GalDiffModel
Spectrum: ConstantValue
34         Value:  8.948e-01  5.175e-02  1.000e-02  1.000e+01 ( 1.000e+00)
IsoDiffModel
Spectrum: FileFunction
35    Normalization:  1.159e+00  1.670e-01  1.000e-03  1.000e+03 ( 1.000e+00)
PKS1510
Spectrum: EblAtten::LogParabola
36          norm:  2.711e-01  6.199e-02  0.000e+00  1.000e+04 ( 1.000e-10)
37         alpha:  2.604e+00  1.851e-01  5.000e-01  5.000e+00 ( 1.000e+00)
38          beta:  2.638e-07  3.085e-04  0.000e+00  5.000e+00 ( 1.000e+00)
39            Eb:  7.428e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
40      tau_norm:  1.000e+00  0.000e+00  0.000e+00  2.500e+00 ( 1.000e+00) fixed
41      redshift:  3.610e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
42     ebl_model:  4.000e+00  0.000e+00  0.000e+00  2.000e+01 ( 1.000e+00) fixed
, '\n')
[FitMaker]: Results for the Fit
Source Name	Npred	TS
Values and (MINOS) errors for PKS1510
('TS : ', 81.4517104744591)
norm :  0.27 +/-  0.06 [ -0.06, + 0.06 ] 1e-10
alpha :  2.60 +/-  0.19 [ -0.17, + 0.18 ] 1e+00
beta :  0.00 +/-  0.00 [ 0.00, + 0.08 ] 1e+00
Eb :  742.81   1e+00
tau_norm :  1.00   1e+00
redshift :  0.36   1e+00
ebl_model :  4.00   1e+00
('The covariance matrix is :\n', array([[ 3.84235593e-03, -8.64026848e-03,  4.45721575e-07],
[-8.64026848e-03,  3.42631416e-02,  3.51962508e-06],
[ 4.45721575e-07,  3.51962508e-06,  9.51680064e-08]]))
Source Flux  [1.00e+02 MeV, 3.00e+05 MeV] :
4FGL J1418.4-0233   Integral Flux : 1.04e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1433.0-1801   Integral Flux : 7.08e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1503.7-1540   Integral Flux : 6.03e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1505.0+0326   Integral Flux : 3.40e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1510.8-0542   Integral Flux : 2.60e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1512.2+0202   Integral Flux : 1.61e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1517.7-2422   Integral Flux : 7.24e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1544.5-1126   Integral Flux : 1.79e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1549.8-0659   Integral Flux : 8.52e-09 +/-  0.00e+00 ph/cm2/s
GalDiffModel   Integral Flux : 4.66e-04 +/-  2.70e-05 ph/cm2/s
IsoDiffModel   Integral Flux : 1.42e-04 +/-  2.05e-05 ph/cm2/s
PKS1510   Integral Flux : 3.14e-07 +/-  5.39e-08 ph/cm2/s
[Message]: Save Ebin results in
After this last line, "Preparing submission of fit into energy bins" starts and gives the error I am facing.

Since beta = 0 I wonder is there is not a problem when computing the Ebin value for the preparation.
is the tool working with powerlaw and not logparabola?

I have not checked that. I will soon get back to you after trying with power-law.
Thanks a lot.

Hi @davidsanchez,
Even after using Powerlaw I am getting the same error.
************************************************************
***   8     gtlike --- Run likelihood analysis
************************************************************
Fit output with NEWMINUIT:<PHONE_NUMBER>750247 [quality: 3]
Fit output with NEWMINUIT:<PHONE_NUMBER>908735 [quality: 3]
************************************************************
***   9 Remove all the weak (TS<1.00) sources
************************************************************
[FitMaker]: deleting source 4FGL J1332.6-1256 with TS = -0.04718278115615249 from the model
[FitMaker]: deleting source 4FGL J1337.6-1257 with TS = -0.03308165748603642 from the model
[FitMaker]: deleting source 4FGL J1339.9-0138 with TS = -0.0017700272146612406 from the model
[FitMaker]: deleting source 4FGL J1340.0-1501 with TS = -0.0003813205985352397 from the model
[FitMaker]: deleting source 4FGL J1340.8-0409 with TS = -0.009637835435569286 from the model
[FitMaker]: deleting source 4FGL J1341.8-2053 with TS = 0.005774950608611107 from the model
[FitMaker]: deleting source 4FGL J1344.2-1723 with TS = 0.004564363858662546 from the model
[FitMaker]: deleting source 4FGL J1349.5-1131 with TS = -0.018318327609449625 from the model
[FitMaker]: deleting source 4FGL J1351.0+0029 with TS = -0.023295827908441424 from the model
[FitMaker]: deleting source 4FGL J1351.4-1529 with TS = 0.005106414319016039 from the model
[FitMaker]: deleting source 4FGL J1354.3-0206 with TS = -0.04544624825939536 from the model
[FitMaker]: deleting source 4FGL J1354.8-1041 with TS = -0.08907121839001775 from the model
[FitMaker]: deleting source 4FGL J1356.2-1726 with TS = -0.00015146378427743912 from the model
[FitMaker]: deleting source 4FGL J1356.6+0234 with TS = -0.0058215787867084146 from the model
[FitMaker]: deleting source 4FGL J1357.5+0127 with TS = -0.035968151642009616 from the model
[FitMaker]: deleting source 4FGL J1359.1-1152 with TS = -0.003657888271845877 from the model
[FitMaker]: deleting source 4FGL J1359.4+0202 with TS = -0.047188837081193924 from the model
[FitMaker]: deleting source 4FGL J1400.0-2415 with TS = -0.00047628278844058514 from the model
[FitMaker]: deleting source 4FGL J1400.6-1432 with TS = -0.07473151001613587 from the model
[FitMaker]: deleting source 4FGL J1401.2-0915 with TS = -0.05562049651052803 from the model
[FitMaker]: deleting source 4FGL J1402.5-1827 with TS = 0.2294903879519552 from the model
[FitMaker]: deleting source 4FGL J1404.8+0402 with TS = -0.05497795296832919 from the model
[FitMaker]: deleting source 4FGL J1405.3-0640 with TS = -0.04703488864470273 from the model
[FitMaker]: deleting source 4FGL J1405.9-1853 with TS = 0.017766353208571672 from the model
[FitMaker]: deleting source 4FGL J1406.1-2508 with TS = 0.013963139150291681 from the model
[FitMaker]: deleting source 4FGL J1406.4-1654 with TS = 0.05359412415418774 from the model
[FitMaker]: deleting source 4FGL J1407.4-0820 with TS = -0.21642160043120384 from the model
[FitMaker]: deleting source 4FGL J1408.9-0751 with TS = 0.4846203044289723 from the model
[FitMaker]: deleting source 4FGL J1410.1+0202 with TS = -0.11254791682586074 from the model
[FitMaker]: deleting source 4FGL J1411.5-0723 with TS = -0.07851669215597212 from the model
[FitMaker]: deleting source 4FGL J1415.9-1504 with TS = -0.5757134656887501 from the model
[FitMaker]: deleting source 4FGL J1416.1-2417 with TS = -0.062495491467416286 from the model
[FitMaker]: deleting source 4FGL J1419.3+0444 with TS = -0.10012476972769946 from the model
[FitMaker]: deleting source 4FGL J1419.4-0838 with TS = -30.14560132205952 from the model
[FitMaker]: deleting source 4FGL J1420.3+0612 with TS = -0.7107797234784812 from the model
[FitMaker]: deleting source 4FGL J1420.9-2431 with TS = -0.5302165753673762 from the model
[FitMaker]: deleting source 4FGL J1421.1-1120 with TS = -1.4810180228669196 from the model
[FitMaker]: deleting source 4FGL J1424.1-1750 with TS = 0.9125199260888621 from the model
[FitMaker]: deleting source 4FGL J1424.2+0433 with TS = -1.193835963262245 from the model
[FitMaker]: deleting source 4FGL J1425.4-0119 with TS = 0.6610181507421657 from the model
[FitMaker]: deleting source 4FGL J1429.8-0739 with TS = 0.9821309450780973 from the model
[FitMaker]: deleting source 4FGL J1429.8-3058 with TS = -1.1142299519851804 from the model
[FitMaker]: deleting source 4FGL J1431.1-3120 with TS = -1.1135205717291683 from the model
[FitMaker]: deleting source 4FGL J1438.0-3128 with TS = -1.1085676022339612 from the model
[FitMaker]: deleting source 4FGL J1439.5-2525 with TS = -1.025706824613735 from the model
[FitMaker]: deleting source 4FGL J1440.0-2343 with TS = -0.8145688596414402 from the model
[FitMaker]: deleting source 4FGL J1440.9+0609 with TS = -1.7193607148947194 from the model
[FitMaker]: deleting source 4FGL J1441.6-1522 with TS = -2.093805378768593 from the model
[FitMaker]: deleting source 4FGL J1442.0+0732 with TS = -1.629143452970311 from the model
[FitMaker]: deleting source 4FGL J1442.1-2800 with TS = -1.4940652754157782 from the model
[FitMaker]: deleting source 4FGL J1442.2+0622 with TS = -1.7662649381672964 from the model
[FitMaker]: deleting source 4FGL J1442.7+1200 with TS = -1.5927041773684323 from the model
[FitMaker]: deleting source 4FGL J1443.7-0954 with TS = -3.3974955189041793 from the model
[FitMaker]: deleting source 4FGL J1445.2-1954 with TS = -1.1914646159857512 from the model
[FitMaker]: deleting source 4FGL J1445.9-1626 with TS = -0.1921513294801116 from the model
[FitMaker]: deleting source 4FGL J1446.0-3039 with TS = -2.7552227897103876 from the model
[FitMaker]: deleting source 4FGL J1446.8-1830 with TS = -1.082256834837608 from the model
[FitMaker]: deleting source 4FGL J1447.0-2657 with TS = -2.705702427541837 from the model
[FitMaker]: deleting source 4FGL J1449.7-0910 with TS = -4.103773457580246 from the model
[FitMaker]: deleting source 4FGL J1450.4+0910 with TS = -3.220675316872075 from the model
[FitMaker]: deleting source 4FGL J1450.8-1424 with TS = -3.0599430225556716 from the model
[FitMaker]: deleting source 4FGL J1451.5+1415 with TS = -3.1591151595348492 from the model
[FitMaker]: deleting source 4FGL J1453.0-1318 with TS = -5.6541840301360935 from the model
[FitMaker]: deleting source 4FGL J1459.5+1527 with TS = -3.3692556312307715 from the model
[FitMaker]: deleting source 4FGL J1503.7-1540 with TS = 0.035875847563147545 from the model
[FitMaker]: deleting source 4FGL J1504.4+1029 with TS = -10.433423016802408 from the model
[FitMaker]: deleting source 4FGL J1505.0+0326 with TS = -2.5067064395407215 from the model
[FitMaker]: deleting source 4FGL J1506.4-0540 with TS = -7.503941100789234 from the model
[FitMaker]: deleting source 4FGL J1506.6+0813 with TS = -7.1273982061538845 from the model
[FitMaker]: deleting source 4FGL J1507.1-1901 with TS = -4.334615467814729 from the model
[FitMaker]: deleting source 4FGL J1509.8-2906 with TS = -7.9606776010477915 from the model
[FitMaker]: deleting source 4FGL J1511.8-0513 with TS = -6.676686772610992 from the model
[FitMaker]: deleting source 4FGL J1512.1-2255 with TS = -2.120941399480216 from the model
[FitMaker]: deleting source 4FGL J1513.0-3118 with TS = -9.934668803820387 from the model
[FitMaker]: deleting source 4FGL J1513.4-2549 with TS = -9.52027996594552 from the model
[FitMaker]: deleting source 4FGL J1513.4-3231 with TS = -9.929540937184356 from the model
[FitMaker]: deleting source 4FGL J1513.7-1519 with TS = -7.18776526406873 from the model
[FitMaker]: deleting source 4FGL J1514.6-2044 with TS = -9.773236632230692 from the model
[FitMaker]: deleting source 4FGL J1514.8-0949 with TS = -21.920337482122704 from the model
[FitMaker]: deleting source 4FGL J1516.5+0015 with TS = -17.95164467347786 from the model
[FitMaker]: deleting source 4FGL J1518.0-2731 with TS = -16.37476376700215 from the model
[FitMaker]: deleting source 4FGL J1518.4+0750 with TS = -17.088869789149612 from the model
[FitMaker]: deleting source 4FGL J1518.6+0614 with TS = -17.1449495179113 from the model
[FitMaker]: deleting source 4FGL J1518.8+0203 with TS = -17.812832938856445 from the model
[FitMaker]: deleting source 4FGL J1520.0-0905 with TS = -16.456986023578793 from the model
[FitMaker]: deleting source 4FGL J1521.1+0421 with TS = -18.408769365749322 from the model
[FitMaker]: deleting source 4FGL J1522.6-2730 with TS = -17.697319971513934 from the model
[FitMaker]: deleting source 4FGL J1523.2+0533 with TS = -19.27926300826948 from the model
[FitMaker]: deleting source 4FGL J1526.1-0831 with TS = -17.48181006743107 from the model
[FitMaker]: deleting source 4FGL J1526.6-2743 with TS = -18.83463413431309 from the model
[FitMaker]: deleting source 4FGL J1526.7-1529 with TS = -15.850976601592265 from the model
[FitMaker]: deleting source 4FGL J1527.8+1013 with TS = -19.45063897536602 from the model
[FitMaker]: deleting source 4FGL J1528.2-2905 with TS = -17.7270847709151 from the model
[FitMaker]: deleting source 4FGL J1528.5-2240 with TS = -18.443796607432887 from the model
[FitMaker]: deleting source 4FGL J1530.0-1522 with TS = -20.14630087907426 from the model
[FitMaker]: deleting source 4FGL J1530.5-3026 with TS = -18.13530919898767 from the model
[FitMaker]: deleting source 4FGL J1531.6+0406 with TS = -19.16272693348583 from the model
[FitMaker]: deleting source 4FGL J1534.3-3312 with TS = -18.50864328769967 from the model
[FitMaker]: deleting source 4FGL J1534.8+0131 with TS = -20.31474939547479 from the model
[FitMaker]: deleting source 4FGL J1535.3-3135 with TS = -22.604830294381827 from the model
[FitMaker]: deleting source 4FGL J1536.8-3155 with TS = -22.600193538120948 from the model
[FitMaker]: deleting source 4FGL J1537.9-1344 with TS = -23.99506931635551 from the model
[FitMaker]: deleting source 4FGL J1538.9+0425 with TS = -17.229344128863886 from the model
[FitMaker]: deleting source 4FGL J1539.1+1008 with TS = -23.510000391979702 from the model
[FitMaker]: deleting source 4FGL J1539.7-1127 with TS = -3.785195583710447 from the model
[FitMaker]: deleting source 4FGL J1540.7+1449 with TS = -24.520194033742882 from the model
[FitMaker]: deleting source 4FGL J1541.7+1413 with TS = -24.515706458943896 from the model
[FitMaker]: deleting source 4FGL J1541.9-2915 with TS = -24.359692086698487 from the model
[FitMaker]: deleting source 4FGL J1543.6+0452 with TS = -25.338525953469798 from the model
[FitMaker]: deleting source 4FGL J1543.6-0244 with TS = -22.788386102183722 from the model
[FitMaker]: deleting source 4FGL J1544.2-2554 with TS = -27.303646102547646 from the model
[FitMaker]: deleting source 4FGL J1544.5-1126 with TS = -5.573418781044893 from the model
[FitMaker]: deleting source 4FGL J1545.8-2336 with TS = -32.295088520273566 from the model
[FitMaker]: deleting source 4FGL J1546.0+0819 with TS = -32.41764909692574 from the model
[FitMaker]: deleting source 4FGL J1546.1-1003 with TS = -26.326419832766987 from the model
[FitMaker]: deleting source 4FGL J1546.8-3244 with TS = -31.729724588920362 from the model
[FitMaker]: deleting source 4FGL J1547.3-1531 with TS = -32.347653151955456 from the model
[FitMaker]: deleting source 4FGL J1547.3-2802 with TS = -32.14562020939775 from the model
[FitMaker]: deleting source 4FGL J1548.8-2250 with TS = -33.77411496115383 from the model
[FitMaker]: deleting source 4FGL J1549.8-0659 with TS = -12.8806197111262 from the model
[FitMaker]: deleting source 4FGL J1549.8-3044 with TS = -34.95192214904819 from the model
[FitMaker]: deleting source 4FGL J1550.7+0528 with TS = -35.47673192061484 from the model
[FitMaker]: deleting source 4FGL J1550.8-0822 with TS = -28.75547376088798 from the model
[FitMaker]: deleting source 4FGL J1550.8-1750 with TS = -40.22569047193974 from the model
[FitMaker]: deleting source 4FGL J1552.0+0850 with TS = -37.30626433016732 from the model
[FitMaker]: deleting source 4FGL J1553.5-3118 with TS = -37.23272131604608 from the model
[FitMaker]: deleting source 4FGL J1553.6+1257 with TS = -37.405601147795096 from the model
[FitMaker]: deleting source 4FGL J1553.6-2422 with TS = -38.447705400176346 from the model
[FitMaker]: deleting source 4FGL J1554.4-1215 with TS = -40.82508387067355 from the model
[FitMaker]: deleting source 4FGL J1555.7+1111 with TS = -38.581499801715836 from the model
[FitMaker]: deleting source 4FGL J1555.7-2908 with TS = -38.445685231592506 from the model
[FitMaker]: deleting source 4FGL J1557.9-0001 with TS = -37.26235058088787 from the model
[FitMaker]: deleting source 4FGL J1557.9-1404 with TS = -41.6021245616721 from the model
[FitMaker]: deleting source 4FGL J1559.8-2525 with TS = -41.38403822632972 from the model
[FitMaker]: deleting source 4FGL J1600.9-3054 with TS = -39.9204228798626 from the model
[FitMaker]: deleting source 4FGL J1602.9-1928 with TS = -41.672173132770695 from the model
[FitMaker]: deleting source 4FGL J1603.6-0451 with TS = -35.412631890154444 from the model
[FitMaker]: deleting source 4FGL J1603.8+1104 with TS = -42.668103146832436 from the model
[FitMaker]: deleting source 4FGL J1605.1-1140 with TS = -45.864348266855814 from the model
[FitMaker]: deleting source 4FGL J1608.0-2038 with TS = -45.13055558933411 from the model
[FitMaker]: deleting source 4FGL J1608.4+0055 with TS = -44.739526169491 from the model
[FitMaker]: deleting source 4FGL J1608.7+1029 with TS = -44.21675104775932 from the model
[FitMaker]: deleting source 4FGL J1612.4+0409 with TS = -45.72495644376613 from the model
[FitMaker]: deleting source 4FGL J1613.3-1907 with TS = -45.63142455462366 from the model
[FitMaker]: deleting source 4FGL J1614.5-2230 with TS = -45.692146487534046 from the model
[FitMaker]: deleting source 4FGL J1615.3-1512 with TS = -45.67846902215388 from the model
[FitMaker]: deleting source 4FGL J1616.9-2257 with TS = -44.356941077974625 from the model
[FitMaker]: deleting source 4FGL J1617.2-2535 with TS = -44.361602918594144 from the model
[FitMaker]: deleting source 4FGL J1617.3-1513 with TS = -45.90691906574648 from the model
[FitMaker]: deleting source 4FGL J1621.0-2625 with TS = -44.516300047631375 from the model
[FitMaker]: deleting source 4FGL J1621.7-1103 with TS = -45.64100295235403 from the model
[FitMaker]: deleting source 4FGL J1623.0-0315 with TS = -46.448418434127234 from the model
[FitMaker]: deleting source 4FGL J1623.7-2315c with TS = -45.164457448525354 from the model
[FitMaker]: deleting source 4FGL J1625.1-0020 with TS = -45.19735654105898 from the model
[FitMaker]: deleting source 4FGL J1625.3-2338 with TS = -45.212698179646395 from the model
[FitMaker]: deleting source 4FGL J1625.7-2527 with TS = -45.22826033877209 from the model
[FitMaker]: deleting source 4FGL J1626.9-2431e with TS = -45.35340453707613 from the model
[FitMaker]: deleting source 4FGL J1627.7+0251 with TS = -45.66326837451197 from the model
[FitMaker]: deleting source 4FGL J1630.1-1049 with TS = -46.99712919967715 from the model
[FitMaker]: deleting source 4FGL J1632.8-1048 with TS = -46.83025384659413 from the model
[FitMaker]: deleting source 4FGL J1634.7+0235 with TS = -45.867026975611225 from the model
[FitMaker]: deleting source 4FGL J1636.5-0454 with TS = -45.69732435862534 from the model
[FitMaker]: deleting source 4FGL J1638.0+0042 with TS = -45.87123578169849 from the model
[FitMaker]: deleting source 4FGL J1641.9-0621 with TS = -45.62718513002619 from the model
[FitMaker]: deleting source 4FGL J1643.5-0646 with TS = -45.78288045828231 from the model
[FitMaker]: deleting source 4FGL J1646.0-0942 with TS = -45.80861942563206 from the model
[FitMaker]: deleting source 4FGL J1646.7-1330 with TS = -45.826185922371224 from the model
[FitMaker]: deleting source 4FGL J1647.2-0154 with TS = -45.99587436916772 from the model
[FitMaker]: deleting source 4FGL J1648.1-1547 with TS = -45.83019928005524 from the model
[FitMaker]: keeping source 4FGL J1418.4-0233 with TS=4.69e+01
[FitMaker]: keeping source 4FGL J1427.4-1823 with TS=7.33e+00
[FitMaker]: keeping source 4FGL J1433.0-1801 with TS=1.44e+00
[FitMaker]: keeping source 4FGL J1440.0-1530 with TS=1.97e+00
[FitMaker]: keeping source 4FGL J1441.4-1934 with TS=1.12e+00
[FitMaker]: keeping source 4FGL J1445.0-0326 with TS=1.30e+01
[FitMaker]: keeping source 4FGL J1458.8-2120 with TS=2.00e+00
[FitMaker]: keeping source 4FGL J1510.8-0542 with TS=4.73e+01
[FitMaker]: keeping source 4FGL J1512.2+0202 with TS=4.27e+01
[FitMaker]: keeping source 4FGL J1517.7-2422 with TS=1.33e+01
[FitMaker]: keeping source 4FGL J1520.8-0348 with TS=9.86e+00
[FitMaker]: keeping source 4FGL J1532.7-1319 with TS=7.61e+01
[FitMaker]: keeping source 4FGL J1549.5+0236 with TS=1.52e+01
[FitMaker]: keeping source GalDiffModel with TS=6.83e+03
[FitMaker]: keeping source IsoDiffModel with TS=4.88e+02
[FitMaker]: keeping source PKS1510 with TS=1.83e+03
************************************************************
***  10 Re-optimize ---
************************************************************
Fit output with NEWMINUIT:<PHONE_NUMBER>5209485 [quality: 3]
[FitMaker]: Fit with gtlike performed
************************************************************
***  11    PlotSED --- Generate SED plot
************************************************************
[Result]: Decorrelation energy : 3.62e+02 MeV
[Result]: Diffential flux  at the Decorrelation energy : 2.68e-10 +/-  9.55e-12 ph/cm2/s/MeV
[Result]: SED value at the Decorrelation energy : 5.63e-11 +/-  2.00e-12 erg/cm2/s
************************************************************
***  12    Results --- Print results of the fit
************************************************************
(4FGL J1418.4-0233
Spectrum: LogParabola
0           norm:  7.394e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
1          alpha:  1.646e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
2           beta:  7.432e-02  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
3             Eb:  1.836e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1427.4-1823
Spectrum: PowerLaw
4      Prefactor:  3.593e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
5          Index: -1.959e+00  0.000e+00 -6.000e+00 -5.000e-01 ( 1.000e+00) fixed
6          Scale:  3.204e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1433.0-1801
Spectrum: LogParabola
7           norm:  1.251e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
8          alpha:  2.491e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
9           beta:  2.664e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
10            Eb:  7.345e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1440.0-1530
Spectrum: PowerLaw
11     Prefactor:  1.537e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
12         Index: -2.191e+00  0.000e+00 -6.000e+00 -5.000e-01 ( 1.000e+00) fixed
13         Scale:  2.233e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1441.4-1934
Spectrum: LogParabola
14          norm:  9.894e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-14) fixed
15         alpha:  1.315e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
16          beta:  5.084e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
17            Eb:  5.129e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1445.0-0326
Spectrum: PowerLaw
18     Prefactor:  4.228e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
19         Index: -1.818e+00  0.000e+00 -6.000e+00 -5.000e-01 ( 1.000e+00) fixed
20         Scale:  4.007e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1458.8-2120
Spectrum: LogParabola
21          norm:  2.538e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
22         alpha:  1.737e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
23          beta:  4.947e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
24            Eb:  1.487e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1510.8-0542
Spectrum: LogParabola
25          norm:  2.736e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
26         alpha:  2.385e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
27          beta:  1.082e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
28            Eb:  8.653e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1512.2+0202
Spectrum: LogParabola
29          norm:  2.310e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
30         alpha:  2.013e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
31          beta:  1.158e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
32            Eb:  9.521e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1517.7-2422
Spectrum: LogParabola
33          norm:  1.037e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-11) fixed
34         alpha:  2.078e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
35          beta:  2.835e-02  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
36            Eb:  8.241e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1520.8-0348
Spectrum: LogParabola
37          norm:  9.149e-01  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-13) fixed
38         alpha:  1.505e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
39          beta:  2.065e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
40            Eb:  3.291e+03  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1532.7-1319
Spectrum: LogParabola
41          norm:  7.414e-01  1.058e-01  0.000e+00  1.000e+04 ( 1.000e-11)
42         alpha:  2.030e+00  0.000e+00  5.000e-01  5.000e+00 ( 1.000e+00) fixed
43          beta:  1.043e-01  0.000e+00  0.000e+00  5.000e+00 ( 1.000e+00) fixed
44            Eb:  8.468e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
4FGL J1549.5+0236
Spectrum: PowerLaw
45     Prefactor:  2.659e+00  0.000e+00  0.000e+00  1.000e+04 ( 1.000e-12) fixed
46         Index: -2.420e+00  0.000e+00 -6.000e+00 -5.000e-01 ( 1.000e+00) fixed
47         Scale:  8.074e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
GalDiffModel
Spectrum: ConstantValue
48         Value:  9.405e-01  1.700e-02  1.000e-02  1.000e+01 ( 1.000e+00)
IsoDiffModel
Spectrum: FileFunction
49    Normalization:  1.157e+00  5.375e-02  1.000e-03  1.000e+03 ( 1.000e+00)
PKS1510
Spectrum: PowerLaw
50     Prefactor:  4.779e-01  2.102e-02  0.000e+00  1.000e+04 ( 1.000e-10)
51         Index: -2.399e+00  3.605e-02 -6.000e+00 -5.000e-01 ( 1.000e+00)
52         Scale:  7.428e+02  0.000e+00  3.000e+01  3.000e+05 ( 1.000e+00) fixed
, '\n')
[FitMaker]: Results for the Fit
Source Name	Npred	TS
Values and (MINOS) errors for PKS1510
('TS : ', 1873.8933641960612)
Prefactor :  0.48 +/-  0.02 [ -0.02, + 0.02 ] 1e-10
Index :  -2.40 +/-  0.04 [ -0.04, + 0.04 ] 1e+00
Scale :  742.81   1e+00
('The covariance matrix is :\n', array([[0.00044201, 0.00044577],
[0.00044577, 0.00129992]]))
Source Flux  [1.00e+02 MeV, 3.00e+05 MeV] :
4FGL J1418.4-0233   Integral Flux : 1.04e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1427.4-1823   Integral Flux : 3.34e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1433.0-1801   Integral Flux : 7.08e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1440.0-1530   Integral Flux : 1.17e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1441.4-1934   Integral Flux : 1.32e-10 +/-  0.00e+00 ph/cm2/s
4FGL J1445.0-0326   Integral Flux : 4.24e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1458.8-2120   Integral Flux : 1.22e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1510.8-0542   Integral Flux : 2.60e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1512.2+0202   Integral Flux : 1.61e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1517.7-2422   Integral Flux : 7.24e-08 +/-  0.00e+00 ph/cm2/s
4FGL J1520.8-0348   Integral Flux : 1.48e-09 +/-  0.00e+00 ph/cm2/s
4FGL J1532.7-1319   Integral Flux : 4.40e-08 +/-  6.28e-09 ph/cm2/s
4FGL J1549.5+0236   Integral Flux : 2.94e-08 +/-  0.00e+00 ph/cm2/s
GalDiffModel   Integral Flux : 4.90e-04 +/-  8.86e-06 ph/cm2/s
IsoDiffModel   Integral Flux : 1.42e-04 +/-  6.60e-06 ph/cm2/s
PKS1510   Integral Flux : 4.20e-07 +/-  1.72e-08 ph/cm2/s
[Message]: Save Ebin results in
************************************************************
*** Preparing submission of fit into energy bins ***
************************************************************
('Emin = 100.0 MeV', 'Emax = 300000.0 MeV', 'Nbins = 6')
Debug: read energy bins: logE
Energy bins (before energy cuts): [1.00000000e+02 3.79769610e+02 1.44224957e+03 5.47722558e+03
2.08008382e+04 7.89952623e+04 3.00000000e+05]
Energy bins (after energy cuts): [1.00000000e+02 3.79769610e+02 1.44224957e+03 5.47722558e+03
2.08008382e+04 7.89952623e+04 3.00000000e+05]
[Message]: Submitting # 0 at energy 194
Traceback (most recent call last):
File "/home/hegro/enrico/bin/enrico_sed", line 48, in
liste = np.genfromtxt(sys.argv[1],dtype="str",unpack=True)
File "/home/hegro/anaconda3/envs/fermi/lib/python3.7/site-packages/numpy/lib/npyio.py", line 2068, in genfromtxt
raise ValueError(errmsg)
ValueError: Some errors were detected !
Line #9 (got 1 columns instead of 3)
Line #20 (got 1 columns instead of 3)
Line #29 (got 1 columns instead of 3)
Line #37 (got 1 columns instead of 3)
Line #43 (got 1 columns instead of 3)
Line #49 (got 1 columns instead of 3)
Line #54 (got 1 columns instead of 3)
Line #70 (got 1 columns instead of 3)
Line #79 (got 1 columns instead of 3)
Line #85 (got 1 columns instead of 3)
Line #101 (got 1 columns instead of 3)
Line #111 (got 1 columns instead of 3)
Line #123 (got 1 columns instead of 3)
Line #142 (got 1 columns instead of 3)
Line #158 (got 1 columns instead of 3)
Line #166 (got 1 columns instead of 3)
Line #181 (got 1 columns instead of 3)
Line #195 (got 1 columns instead of 3)
Line #206 (got 1 columns instead of 3)
Line #212 (got 1 columns instead of 3)
Line #222 (got 1 columns instead of 3)
Line #226 (got 1 columns instead of 3)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/hegro/enrico/bin/enrico_sed", line 55, in
sed(config,infile)
File "/home/hegro/enrico/bin/enrico_sed", line 13, in sed
run(infile)
File "/home/hegro/enrico/enrico/RunGTlike.py", line 262, in run
energybin.RunEbin(folder,Nbin,Fit,FitRunner,sedresult)
File "/home/hegro/enrico/enrico/energybin.py", line 209, in RunEbin
configfiles = PrepareEbin(Fit, FitRunner,sedresult)
File "/home/hegro/enrico/enrico/energybin.py", line 202, in PrepareEbin
config.write(open(config['out'] + '/' +filename, 'w')) #save the config file in a ascii file
File "/home/hegro/enrico/enrico/extern/configobj.py", line 2098, in write
outfile.write(output_bytes)
TypeError: write() argument must be str, not bytes

I will try to reproduce the error

I am working on it. it tooks time since our cluster was down.
d

Hi I am not able to reproduce the problem you have; I am not using the last fermitools but I will update and retry`
d

Thanks, @davidsanchez for your kind effort.
I am also trying to solve it but still the same error persists.

Hi,
I have the same problem. Is there a solution to this problem?

Hi
I never been able to reproduce this bug. could you send me your config files?
david

Thank you for your prompt reply. Of course, I am running the sed for mrk 421 with NumEnergyBins = 7. In the Ebin # / folder is created the .confg file for the 0th energy but is empty.
The file mrk421.conf :
Default config and validation file for Enrico.

Besides providing default options it is also used
to check the user config file.
Options without default options here must be
specified in the user config file
Folder where the output will be stored
out = /home/marisol/Desktop/sed_mkr421-prueba/datos
verbosity
verbose = yes
#Overwrite existing output files. Use with caution
clobber = yes
#Submit the job to a cluster?
Submit = no
[target]
name = Mrk421
ra = 166.113808
dec = 38.20883287
redshift = 0.031
ebl_model = 4
spectrum = PowerLaw
# 0=Kneiske, 1=Primack05, 2=Kneiske_HighUV, 3=Stecker05, 4=Franceschini, 5=Finke, 6=Gilmore, 10=Dominguez11
# full list http://www-glast.stanford.edu/cgi-bin/viewcvs/celestialSources/eblAtten/eblAtten/EblAtten.h?view=markup
fit_tau = no
[space]
xref = 166.113808
yref = 38.20883287
rad = 10.0
binsz = 0.1
coordsys = CEL
proj = AIT
phibins = 0
[file]
spacecraft = sc.fits
event = fotones.dat
xml = /home/marisol/Desktop/sed_mkr421-prueba/datos/Mrk421_PowerLaw_model.xml
tag = LAT_Analysis
# keep track of the parent config during nested operations (e.g. energy/time bins)
parent_config = ""
[time]
tmin = 239557417.192
tmax = 271093418.192
file = ""
type = MET
[energy]
emin = 2000.0
emax = 300000.0
enumbins_per_decade = 10
decorrelation_energy = no
[event]
irfs = CALDB
evclass = 128
evtype = 3
[analysis]
zmax = 100
# General analysis options
likelihood = binned
# Correct energy dispersion?
EnergyDispersion = yes
ComputeDiffrsp = yes
roicut = no
# cuts applied during the first coarse bin selection:
evtroicuts = yes
evttimecuts = yes
filter = (DATA_QUAL>0)&&(LAT_CONFIG==1)
# should we keep the srcmaps for all sources in the srcMap file?
# this should speed up future fits, at the cost of disk space.
keep_all_srcmaps = no
[environ]
# Analysis environment configuration
# Can also be done via shell environment variables
FERMI_DATA_DIR = ""
FERMI_CATALOG_DIR = ""
FERMI_CATALOG = ""
FERMI_DIFFUSE_DIR = ""
FERMI_PREPROCESSED_DIR = ""
[fitting]
optimizer = MINUIT
ftol = 1e-06
# if source_ts < min_source_TS in the fit, the source is removed from the model
min_source_TS = 1.0
[model]
# The following options determine the xml model
diffuse_gal_dir = ""
diffuse_iso_dir = ""
diffuse_gal = ""
diffuse_iso = ""
# user points sources for diffuse catalog sources
# freeze spectral parameters for weak and far away sources:
min_significance_catalog = 4.0
min_significance_free = 25.0
max_radius = 5.0
# Add all source in a radius of analyse ROI + this radius
max_roi = 10.0
# Add gaussian noise to the spectral parameters of free sources (may help during the fit)
parameters_noise = 0.0
[Spectrum]
#Generates fits files or not?
FitsGeneration = yes
#Generates plots (SED, model map)
ResultPlots = yes
# Plot (update) the parent config related plots during energy bin production
ResultParentPlots = no
#Freeze the spectral index of the source. Has no implication if 0 (Left free to vary)
FrozenSpectralIndex = 0.0
[UpperLimit]
#Assumed Spectral index
SpectralIndex = 2.0
# UL method could be Profile or Integral (provided by the fermi collaboration).
#Poisson is base on the Feldman-Cousins method for low signal. Only 95 % yet available
Method = Profile
envelope = no
#Compute an UL if the TS of the sources is <TSlimit
TSlimit = 25.0
# Confidence level for the Ul computation
cl = 0.95
[LightCurve]
#Generates fits files or not?
FitsGeneration = yes
#Number of points for the LC
NLCbin = 20
#Index for the power law. Left free to vary if 0
SpectralIndex = 2.0
MakeConfFile = yes
#Bayesian blocks
BayesianBlocks = no
#Compute Variability index as in the 2FGL.
ComputeVarIndex = yes
#Compute an UL if the TS of the sources is <TSLightCurve
TSLightCurve = 9.0
#Generates control plots
DiagnosticPlots = yes
# Plot (update) the parent config related plots during time bin production
DiagnosticParentPlots = no
[BayesianBlocks]
#Generates fits files or not?
FitsGeneration = yes
#False alarm probability
p0 = 0.01
#Index for the power law. Left free to vary if 0
SpectralIndex = 2.0
MakeConfFile = yes
#Compute an UL if the TS of the sources is <TSLightCurve
TSLightCurve = 9.0
#Generates control plots
DiagnosticPlots = yes
# Plot (update) the parent config related plots during time bin production
DiagnosticParentPlots = no
[FoldedLC]
#Number of bins for the orbitally folded LC
NLCbin = 10
#Epoch of phase=0 in MJD, equal to tmin is 0
epoch = 0.0
#Orbital period in days
Period = 0.0
[AppLC]
#Generates fits files or not?
FitsGeneration = yes
#Spectral index for the exposure calculation
index = 2.0
#Apperture radius
rad = 1.0
#Number of bins
NLCbin = 10
#bin form data or frozen bin size
binsFromData = no
#minimum energy for the apperture lightcurve, if -1 use the one define in energy section
emin = -1.0
emax = -1.0
[Ebin]
#Generates fits files or not?
FitsGeneration = yes
NumEnergyBins = 7
#Compute an UL if the TS of the sources is <TSEnergyBins
TSEnergyBins = 9.0
# How to generate the Ebins
# - logE: log scaled bins
# - TS: similar TS per bin
# - mix: half-way between log and TS.
# - [ E1, E2, E3, E4, ..., EN ]: custom binning.
# - default is logE
DistEbins = logE
[TSMap]
#Re-fit before computing the TS map
Re-Fit = no
#Numbers of pixel in x and y
npix = 10
#Remove or not the target from the model
RemoveTarget = yes
#Generate the TS map pixel by pixel or by grouping the pixels by row.
#(reduce the numbers of jobs but each job is longer)
method = row
[findsrc]
#Generates fits files or not?
FitsGeneration = yes
#Reoptimize before
Refit = yes
[srcprob]
#Generates fits files or not?
FitsGeneration = yes
#radius for the computation
rad = 1.0
# list of sources
srclist = ""
# number of photons to print
numberPhoton = 10
[Contours]
parname1 = Prefactor
parname2 = Index
[ComponentAnalysis]
# EUnBinned to the energy (MeV) where
# binned and unbinned analysis should be split
# disabled if -1
EUnBinned = -1.0
# Divide the analysis in FrontBack classes
FrontBack = no
# Divide the analysis in PSF classes
PSF = no
# Divide the analysis in EDISP classes
EDISP = no
# Divide the analysis in EDISP classes
FGL4 = no

Hi,
I have the same error, did you manage to solve it ?
************************************************************
*** Preparing submission of fit into energy bins ***
************************************************************
('Emin = 442.894 MeV', 'Emax = 300000.0 MeV', 'Nbins = 3')
Debug: read energy bins: mix
Energy bins (before energy cuts): [   442.894        3101.56570034  22704.03766592 300000.        ]
Energy bins (after energy cuts): [   442.894        3101.56570034  22704.03766592 300000.        ]
[Message]: Submitting # 0 at energy 1172
Traceback (most recent call last):
File "/home/narek/enrico/bin/enrico_sed", line 48, in
liste = np.genfromtxt(sys.argv[1],dtype="str",unpack=True)
File "/home/narek/anaconda3/envs/fermi/lib/python3.7/site-packages/numpy/lib/npyio.py", line 2122, in genfromtxt
raise ValueError(errmsg)
ValueError: Some errors were detected !
Line #6 (got 1 columns instead of 3)
Line #15 (got 1 columns instead of 3)
Line #24 (got 1 columns instead of 3)
Line #31 (got 1 columns instead of 3)
Line #37 (got 1 columns instead of 3)
Line #43 (got 1 columns instead of 3)
Line #48 (got 1 columns instead of 3)
Line #59 (got 1 columns instead of 3)
Line #66 (got 1 columns instead of 3)
Line #71 (got 1 columns instead of 3)
Line #82 (got 1 columns instead of 3)
Line #88 (got 1 columns instead of 3)
Line #95 (got 1 columns instead of 3)
Line #106 (got 1 columns instead of 3)
Line #116 (got 1 columns instead of 3)
Line #121 (got 1 columns instead of 3)
Line #130 (got 1 columns instead of 3)
Line #136 (got 1 columns instead of 3)
Line #142 (got 1 columns instead of 3)
Line #146 (got 1 columns instead of 3)
Line #152 (got 1 columns instead of 3)
Line #156 (got 1 columns instead of 3)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/narek/enrico/bin/enrico_sed", line 55, in
sed(config,infile)
File "/home/narek/enrico/bin/enrico_sed", line 13, in sed
run(infile)
File "/home/narek/enrico/enrico/RunGTlike.py", line 261, in run
energybin.RunEbin(folder,Nbin,Fit,FitRunner,sedresult)
File "/home/narek/enrico/enrico/energybin.py", line 209, in RunEbin
configfiles = PrepareEbin(Fit, FitRunner,sedresult)
File "/home/narek/enrico/enrico/energybin.py", line 202, in PrepareEbin
config.write(open(config['out'] + '/' +filename, 'w')) #save the config file in a ascii file
File "/home/narek/enrico/enrico/extern/configobj.py", line 2098, in write
outfile.write(output_bytes)
TypeError: write() argument must be str, not bytes

Hi,
If you change config.write(open(config['out'] + '/' +filename, 'w')) with config.write(open(config['out'] + '/' +filename, 'wb')) it works without a problem.

Hi,
I confirm that it works without problem by correcting what you mention in the file /home/user/enrico/enrico/energybin.py, thank you so much! ('w' by 'wb')

Hi
thanks a lot. I'll made a fix then


support .well-known/oidc-configuration

some IdP's (i'm looking at you Keycloak) use a url for authentication that seems to be nonstandard "/auth" vs "/authentication". Keycloak does however provide a .well-knonw/oidc-configuration endpoint, which shows you where the jwks endpoint is, where the auth endpoint is etc.
Enable browzer runtime to find/read/use a well-known/oidc-configuration endpoint

For reference, that well known configuration document is defined in the OIDC Discovery spec here:  https://openid.net/specs/openid-connect-discovery-1_0.html

Now available in 0.51.0


Cannot find submodule parsers.naturallanguage.gigaword needed in convert2graph

I am trying to run the script convert2graph.py, but was unable to find the required submodule for summary parsing. Could you kindly upload (or point me to the resources) this submodule?
Again, it is parsers.naturallanguage.gigaword. Thanks!

Should be fixed by the latest PR

Oh? You meant it is already fixed (or is it going to be fixed)? I still don't see that submodule, though. Would you mind pointing me to the correct location? Thanks 😃

The file should now be self-contained, so that module is no longer needed

Thank you very much 😃
Yes, I was able to run the graph converter and now the model is being trained on a small subset of the cnndm data. Appreciate your work!