[r] Use artifacts if no args or system libs found

Note: This requires https://github.com/single-cell-data/TileDB-SOMA/pull/1397
Issue and/or context:
The R package build has, besides the usual R package dependencies, a dual dependency on TileDB Core and the TileDB-SOMA C++ library.   This PR generalizes the build to access

either user-supplied local location of TileDB Core and/or TileDB-SOMA library installation (mixing is permitting)
optionally also automatic use of system-libraries if pkg-config is present and knows about the libraries
as a fallback (that can also be opted into) use of binary artifacts downloaded from GitHub

Changes:
This PR generalizes the build a to allow for the optional use, the use of partial optional use along with pkg-config, full use of pkg-config for both as before as well as an extended use of now two binary artifacts.  The artifact case has been tested on Docker when no libraries were present.
Notes for Reviewer:
This PR depends on #1397 to produce the artifacts first.  It also still requires a manual updating of which artifacts are downloaded, the pinning is currently hard.

Codecov Report
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  Lines        8215     5721     -2494
===========================================
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This PR is making good progress.  We now have

use a GHA yaml file library-artifacts.yaml to produce library artifacts from libtiledbsoma

this can be used at release time and it will upload artifacts to the release
the same yaml file is also used as workflow in the normal r-ci workflow

refactor the normal GHA yaml file r-ci.yml to invoke library-artifacts.yaml

the library artifacts are also uploaded as artifacts by library-artifacts.yaml
so that r-ci.yml can use them and we have consistent provision and use of the library
in non-CI use we continue to either

use libtiledbsoma as system library
or as a user-provided library via flags to configure ("export mode')
or as artifacts downloaded from the release

What is still missing is a consistent propagation of version numbers from the top level to the different packages.


feat: Active Model Serializers instrumentation

Active Model Serializers is the standard Rails JSON serialization library used with Rails API mode.
Ported from Datadog. I've dropped support for AMS 0.9.0 and am only supporting AMS 0.10.0+
There doesn't seem to be any semantic standards for serializers (which I guess is a subset of view/template rendering, which also doesn't exist)

Thanks @johnnyshields!


JBPM-5394: Removing wrong dependencies to drools-wb assets.

Hi @csadilek @manstis @Rikkola ,
Here is the fix for the showcase modules. In fact the dependency to the drools-wb was not necessry, it was my mistake, sorry guys. I have done a complete review for the dependencies, fixed some and hope no more issues due to this will appear... sorry for the inconveniences again.
See https://issues.jboss.org/browse/JBPM-5394
Thanks!

@romartin Not a problem. We used to have this kind of issues all the time and they would only get picked up when we started releasing. Now it looks like the automated builds protect us.

+1


TypeScript: Implement Default Loose Type Configs

Lightning's type system has the concept of Loose Template Specs (documented here) which allow properties and Refs that aren't actually declared in the Template Spec to be specified as if they were any. By default all Components that do not specify Template Spec (i.e. use the default Template Spec) use a Loose Template Spec.
Along side the Template Spec we offer another way to make Components more type strong called the Type Config. Unfortunately support for a Loose Type Config was not previously considered and it was brought to my attention by the Lightning UI team that this is making it difficult to use signals and events in their Component code because due to the way their classes are structured they are unable to easily pass through a Type Config.
Here I implement a Loose Type Config in much the same way that Loose Template Specs are implemented. By default Components that do not have a specified Type Config have Loose Type Configs and you are free to use any signals and events on these components. As a bonus, one can even explicitly extend the base TypeConfigLoose interface if they want the best of both worlds. Any event/signal is allowed and treated (essentially) as an any. But explicitly defined events/signals will still be type checked.
To-do

[x] Implementation
[x] Basic Unit tests
[x] Another pass on Unit Tests
[x] Test with TMDB project
[x] Share build with LUI team and collect feedback
[x] Add documentation
[ ] Wait for #445 to be merged to dev and then rebase this PR onto dev.

Currently the base of this PR is the ts-fix-getbyref branch from this PR!!

Accidentally closed the PR

Hey @frank-weindel, PR #445 has been merged into dev so you can do the changes regarding this PR.


Allow validation of one input against another

Changes: feat, docs
Scope: valdrFormItem-directive, valdr-service
Subject: Implementing cross model validation
Description
Implements the possibility of creating custom validation using other models in the form as parameters.
The user will define the required models in a requireModels contraint in the custom validator, which receives a list of field names. It will allow him to receive a third parameter in the validate function of its custom validator with the model values required in the requreModels constraint.
eg.:
yourApp.factory('customValidator', function () {
  return {
    name: 'customValidator', // this is the validator name that can be referenced from the constraints JSON
    validate: function (value, arguments, requiredModels) {
      // value: the value to validate
      // arguments: the validator arguments
      // requireModels: an object which has the required models values
      return value === requiredModels.password;
    }
  };
});

yourApp.config(function (valdrProvider) {
  valdrProvider.addConstraints({
    'Person': {
      'password': {
        'minLength': 8,
        'message': 'Password must have at least 8 characters.'
      },
      'password_confirm': {
        'customValidator': {
          'requireModels': ['password'],
          'message': 'Password onfirmation must be equals to Password'
        }
      },
    }
  });
});

It uses the parent form to find the model values and force revalidation of dependent fields after a dependency model changes, and passes the dependency model value as parameters in the custom validator.
Changes per component:

Require the FormController in valdrFormItem directive and passed the fields to the valdr service;
In the valdr service it checks the dependent models of each model to revalidate them after the dependency model changed and had its validation called;

I tested it with examples, but didn't create automated tests yet. I would appreciate if anybody could help me with that, I'm not used to frontend testing.

+1

+1

Coverage decreased (-4.4%) to 95.622% when pulling 0f7a0ae2a2aef40ccc558eb6223392348fbf2c1a on badoque:master into ec235ce5c36306ec0d3f82436808a12ca52c69df on netceteragroup:master.

As I said, I only tested manually, but not atomatically because I was not familiar with jasmine. I'm implementing the feat #57 in my fork, then I'll try to make the tests for both features now.

+1, would love if this could be merged 😄

Hey, is there any update for this?
Is the holdup the missing jasmine tests?


deploy server with docker

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Add a new device registration route

This PR adds a new route to the UI that is focused only on registering a new device. It should be a route that would only be accessible when enrolling a new device. Below is a NGINX example of how to handle headscale's register endpoint and redirect it to this new endpoint:
    location /register/nodekey {
        rewrite ^/register/(.*)$ /web/register.html?nodekey=$1 redirect;
    }

Now, instead of seeing headscale's default endpoint, it would be greeted with our familiar CreateDevice component with the device key prepopulated. The form only requires a user assignment and a submission. After successful submission, it redirects to the devices.html route.
It would be even better if we could specify this pattern in headscale itself, but I think we could accomplish the same thing at the reverse proxy layer.

I don't really get the purpose of this pull request. It's relying on information that requires an API key so from a security perspective there doesn't appear to be any benefit. It's also not adding any functionality that doesn't already exist on the devices page. I'm not a fan of adding complexity to the UI without a measurable benefit.

This PR accomplishes a way to pre-populate the device registration form with the nodekey from a URL.
One pain point I experienced when enrolling AppleTVs was it displayed a QR code with a URL to the basic white screen with text containing the cli command to finish node registration. It was quite cumbersome on mobile to do this otherwise.
I would've preferred it just take to me the UI where I can approve the device.
It would be better if there was a way for headscale to be configured to send users to a different url/path, such as one provided by one of the UI projects like this. That would avoid the redirect complexity this adds.
If it makes more sense to get that feature integrated in headscale first, we can close this for now and revisit this later.

I think adding the query string parameter to devices.html is much simpler. I'll make that change and see what you think.

This has been simplified. What do you think?

Looks good to me
create a /documentation/route_queries.md that explains what a uri query is, a heading for devices.html and explains the parameter and I'll merge it.

@routerino I complete the two requests. Let me know what you think of the documentation.

Looks good to me.


Azure Training issue

Hi Guys, good job, you made a very clear guideline about object detection and machine learning. I went thorugh the steps you described, but I am stuck at the model training with a resource issue in Azure.  I get a very general error 'Resource {dataName} is in conflicting state.' at the azure execution. To work around the issue, I´ve done some resources recreation and several different tests. still getting the same error. Maybe you have encountered the same error before?

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 63a4f3b7-a2a6-760a-534b-22788ba77b5c
Version Independent ID: 1bee7901-164f-d9a7-9e7b-fd0ba55ad42e
Content: Tutorial: Detect objects in images with Model Builder - ML.NET
Content Source: docs/machine-learning/tutorials/object-detection-model-builder.md
Product: dotnet-ml
GitHub Login: @briacht
Microsoft Alias: brachtma

Hi @Gholtmann, thanks for filing this issue!
I've transferred the issue to the Model Builder repo so the team can investigate.

Thank you @briacht - should you need further info to reproduce the issue, please dont hesitate to let me know.
El miércoles, 5 de mayo de 2021 13:08:30 ART, Bri Achtman @.***> escribió:
Hi @GHoltmann, thanks for filing this issue!
I've transferred the issue to the Model Builder repo so the team can investigate.
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@GHoltmann Sorry you're experiencing this problem, and thanks for reporting.
It sounds like the error is happening after you start training? Can you click on the "Monitor current run in Azure portal" link? If you don't see a link you can navigate there manually by going to https://ml.azure.com/ and navigating to the ML Workspace you are using, and then the Experiments tab.
There should be a more detailed error in the training run. If you don't see if in the status area, you may need to go into the child runs and see if the error is reported there.

Can you let me know the error details you see there? Let me know if you have questions. Thanks!

@GHoltmann Sorry for the delay. I've looked around and have no idea what is causing this. Would you mind taking a look at the resources this run is trying to use?
You can find the summary on the Environment page.

Specifically, is there only one Compute with your chosen name? Does the compute seem to be created correctly? We might need to pull the Azure team in on this one.

@beccamc thank you Becca, please see below the screen capture. It draws my attention that resource id has two hyphens instead of having a name.

@GHoltmann - Sorry for the delay again. Feel free to ping me if I don't respond in a few days.
Can you double check the data has uploaded properly?
Check your expected Label file location in Experiments -> ExperimentName -> FailedRun -> See All Properties -> Raw Json

Then go to Datastores-> workspaceBlobStore -> Browse (Preview)

Can you see if the json file is there, and the images are there?

Any update on this issue? Was the data uploaded to the expected spot?

Hi Becca, sorry for the delay. I tested many times but got stucked always at the same step. Was unable to solve the Azure issue by myself. Its probably simple for the Azure team to solve.
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El viernes, julio 9, 2021, 1:53 p. m., Becca McHenry @.***> escribió:
Any update on this issue? Was the data uploaded to the expected spot?
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Sorry to ask the same question, but was the data uploaded to the right spot, as described here?

Hi Becca,
I was unable to check specifically on your question once again since my azure trial account has expired. Any suggestions?
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El jueves, julio 15, 2021, 12:10 p. m., Becca McHenry @.***> escribió:
Sorry to ask the same question, but was the data uploaded to the right spot, as described here?
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Unfortunately I'm not sure what to do if that Azure trail has expired. Are you using a new Azure account?

Hi Becca! thank you for your help. Yes its a new Azure account and I guess there is something wrong with the accounts permissions. At my company we do have corporate Azure services, but for testing new solutions and concepts like this its easier to test with trial accounts rather than going through all the corporate approvals required internally to use a coporate Azure user.So considering the above, can you confirm is a newly created account goes smoothly with this ML setup?
El lunes, 30 de agosto de 2021 16:12:04 ART, Becca McHenry @.***> escribió:
Unfortunately I'm not sure what to do if that Azure trail has expired. Are you using a new Azure account?
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I haven't seen this problem with a newly created account. We are releasing a new Model Builder version this week (or early next).  I would recommend we try with that.

Oh thats great news. Could you lt me know when ot os released? I will try with the new version.
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El jueves, septiembre 2, 2021, 7:31 p. m., Becca McHenry @.***> escribió:
I haven't seen this problem with a newly created account. We are releasing a new Model Builder version this week (or early next). I would recommend we try with that.
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We just uploaded the new bits for VS 2019! You can download and try from the marketplace https://marketplace.visualstudio.com/items?itemName=MLNET.07
I think for your scenario you only need the VS 2019 Model Builder extension. In case you need other scenarios covered... the Model Builder GPU extension and VS 2022 aren't out yet. GPU should be available later today. VS 2022 will be available sometime between September 6th and September 15th.

Any luck with the new version?

Hi Becca, we will be testing your new version in November, as our team is currently working on other projects. I will keep you updated!
El viernes, 3 de septiembre de 2021 13:33:24 ART, Becca McHenry @.***> escribió:
We just uploaded the new bits for VS 2019! You can download and try from the marketplace https://marketplace.visualstudio.com/items?itemName=MLNET.07
I think for your scenario you only need the VS 2019 Model Builder extension. In case you need other scenarios covered... the Model Builder GPU extension and VS 2022 aren't out yet. GPU should be available later today. VS 2022 will be available sometime between September 6th and September 15th.
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Sounds good. I'll keep this open for tracking until you're able to test.

Hi! Were you able to test in November?

Hi Becca!, we were not able to test any of it. I would like to run the tests from sctratch with the new released version. For the simplicity of the tests, I used a personal azure test account. Do you recommend using our corporate account for the testings?
El martes, 15 de febrero de 2022 16:14:13 ART, Becca McHenry @.***> escribió:
Hi! Were you able to test in November?
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Using a personal azure account should be fine

Any update here?

Hi! Thanks for reporting this problem and testing out our Azure solution. I'm closing this issue. If you still have this problem (or any new problems) feel free to open another issue! Thanks again!

Hi Becca, I really was unable to test further but our company is very interested in testing and implementing machine learning for video recognition. Thank a lot for your help!
El miércoles, 8 de junio de 2022 18:33:50 ART, Becca McHenry @.***> escribió:
Hi! Thanks for reporting this problem and testing out our Azure solution. I'm closing this issue. If you still have this problem (or any new problems) feel free to open another issue! Thanks again!
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Make a copy of a model

Is there a way to make a deep copy of model? I want to replicate the DQN paper in which you freeze the target model and only after several step of iterations, you copy the temporal model to the target model. Thanks!

Early January, I can tell you it was possible to deep copy a keras model with theano backend. However, it was not possible to deep copy one with tensorflow backend. #1466
Is this the problem you are having?

Why not just transfer the weights to an identical model?
On 22 February 2016 at 06:26, João N. Laia<EMAIL_ADDRESS>wrote:

Early January, I can tell you it was possible to deep copy a keras model
with theano backend. However, it was not possible to deep copy one with
tensorflow backend. #1466 https://github.com/fchollet/keras/issues/1466
Is this the problem you are having?
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https://github.com/fchollet/keras/issues/1765#issuecomment-187202679.

@jnlaia Yeah deep_copy a model give me an error message. @fchollet Thanks. This is the solution I end up with. I created a new instance and copy over the weights.

Model's copy would be such a nice feature.
Could save a lot of time on initialization in case of similar models.

@fchollet @snakeztc in the case of creating a new instance from the json file - does this mean model.compile() is run each time, and then you get to a model.load_weights?

@viksit No need to compile if you're loading from the JSON file. These save and load functions might help: https://github.com/sharathrao13/deep-learning/blob/master/utils.py#L25 and https://github.com/sharathrao13/deep-learning/blob/master/utils.py#L56

@angadgill ah no, I mean that internally, the model.load_weights() function invokes model.compile() [1]. If your model is a complex one, this compile time can be pretty high. Being able to deep copy would make this compile() process only happen on initial load and you can replicate, as @VladMironov mentioned.
@VladMironov have you found any ways to quickly initialize the same model over multiple weight files?
[1] https://github.com/fchollet/keras/blob/master/keras/models.py#L211

@viksit I've tried python out-of-box copy.deepcopy with no luck (stopped with an exception).
Thought copy.copy could work, I haven't checked that properly.
Right now I'm simply initializing models (it takes ~7 minutes but I need it only once in a session) and then, if I need to, — I reset weights with model.load_weights

In Keras 2.0.7 there's a new function keras.models.clone_model(model, input_tensors) for that purpose.

@bzamecnik how can I get the appropriate format for the input_tensors?
e.g.
model2 = keras.models.clone_model(model, model.get_weights())
does not work.
i.e. I want model2 to be an exact copy of model. Thanks.

@SimonEnsemble input_tensors are tensors for external inputs, not weights (internal model parameters).

@bzamecnik I am using clone_model() to create 3 identical branches of a network. The problem is when I concatenate their output layers and build the final model using a terminal dense layer, I get an error saying all the layer names should be unique.
The last layer of 3 clones I made, has the same name. Is there a way to get unique layer names while making model clones?
PS: I am new here and hope that I am not making a mistake by continuing this thread. If I am, please let me know and I will open a new thread for the question.

@SimonEnsemble
model_copy = keras.models.clone_model(model)
model_copy.set_weights(model.get_weights())

@stavBodik I'm guessing this doesn't clone optimizer state?

@TristanJM
I don't remmber but copying the model means copying the structure ( layers ) of the model, and the last layer should include the optimizer and its state, so please just test it.
I don't remmber that I had problems with remmbering the optimizer state after copying and setting the weights.

@stavBodik @TristanJM
I used the following code:
model_copy = keras.models.clone_model(model)
model_copy.set_weights(model.get_weights())
mode_copy.save('model_copy.h5')
keras.models.load_model('model_copy.h5')
I get the following when I load the model -
UserWarning: No training configuration found in save file: the model was not compiled. Compile it manually.
warnings.warn('No training configuration found in save file:
So I don't think the clone_model clones the optimizer, the loss or the optimizer state. Still trying to figure out how to do that.

@sachag678 If you save and load the model, you have to recompile. Because compilation resets the models' weights, save them along with the model and load them after compilation:
# save
model_copy.save('model_copy.h5')
model_copy.save_weights('model_copy-weights.h5')

# load
model = keras.models.load_model('model_copy.h5')
model.compile(
   optimizer='rmsprop',
   loss='sparse_categorical_crossentropy',
   metrics=['accuracy']
)
model.load_weights('model_copy-weights.h5')

I'm not a hundred percent sure, but I think if you don't save and load the model, re-compilation is not necessary.

I agree with you. My issue is I want to save the status of the optimizer, the current loss. i.e if I'm using Adam then the alpha would have been changing over time. I don't want to start from the default value if I load the model and continue training it. I want it to start from the value of alpha when I saved it. My current thought is if I can access those values of the optimizer then I can save them separately and load them with the model and set them myself after recompiling.

@sachag678
https://stackoverflow.com/questions/49503748/save-and-load-model-optimizer-state
This might solve your problem.

@sachag678
clone_model()  doesn't work for me. I think you might try this like me.
first, write a function to return your Model structure, like model_build()
then, in main(), you could get the basic model by model_build()
when you need a copy model, just create a copy_one  by model_build()
and recover weights by copy_one.set_weights(model.get_weights())
hope works for you ~~

@mariushegele
Compilation does not reset layer weights.

@sachag678  thanks for pointing to set_weights.
I had to do this:
model_m1 = keras.models.clone_model(model)
#modify model here if needed
model_m1.build()
model_m1.set_weights(model.get_weights())

@stavBodik I'm guessing this doesn't clone optimizer state, how would one achieve that?

@TristanJM
I don't remmber but copying the model means copying the structure ( layers ) of the model, and the last layer should include the optimizer and its state, so please just test it.
I don't remmber that I had problems with remmbering the optimizer state after copying and setting the weights.

@stavBodik @TristanJM
I used the following code:
model_copy = keras.models.clone_model(model)
model_copy.set_weights(model.get_weights())
mode_copy.save('model_copy.h5')
keras.models.load_model('model_copy.h5')
I get the following when I load the model -
UserWarning: No training configuration found in save file: the model was not compiled. Compile it manually.
warnings.warn('No training configuration found in save file:
So I don't think the clone_model clones the optimizer, the loss or the optimizer state. Still trying to figure out how to do that.

@mariushegele
I agree with you. My issue is I want to save the status of the optimizer, the current loss. i.e if I'm using Adam then the alpha would have been changing over time. I don't want to start from the default value if I load the model and continue training it. I want it to start from the value of alpha when I saved it. My current thought is if I can access those values of the optimizer then I can save them separately and load them with the model and set them myself after recompiling.

In order to have the same optimizer state (e.g. learning rate) in your cloned model, you can access it from your original model.
`
cloned_model = tf.keras.models.clone_model(original_model)
cloned_model.compile(
optimizer=tf.keras.optimizers.Adam(learning_rate=original_model.optimizer.learning_rate),
loss='binary_crossentropy',
metrics=['accuracy']
)
`


What is the proper way to download everything from a bucket?

We have a CMS in GCP which has images uploaded to a bucket and we have a website that is being generated and deployed by Netlify. When Netlify generates the static website we want it to copy the contents of the bucket into the generated website.
From the documentation it seems that the only way to do this is:

Get a listing of the contents of the bucket.
Download each file individually.

Is there a better way? perhaps a way to download the entire thing as a .zip file?

Thank you for your reply @ddelgrosso1; in that case I will proceed with the above since the CMS does not have such a feature.
Are you able to suggest a reasonable maximum number of async/parallel downloads at a time?

I would generally recommend starting with a smaller number of concurrent downloads, i.e. 5 - 10 and scale up from there. In some informal testing I have found this to be a good starting point. How far you scale will of course depend on the size of the instances and network configuration you are utilizing on GCP.

Perfect, thank you!


devices not showing up in HA's energy's dashboard

Hello,
I configured powercalc in order to guestimate my lights and AC's consumption:
powercalc:
  scan_interval: 00:01:00 #Each minute
  power_sensor_friendly_naming: "{} Power Consumption"
  energy_sensor_friendly_naming: "{} Energy Consumption"
  create_domain_groups:
    - light
    - climate
  create_utility_meters: true
  utility_meter_types:
    - daily
    - weekly
    - monthly
    - yearly

Assigned a sensor to each light and climate entity:
sensor:
  - platform: powercalc
    entity_id: light.coffee_table
    name: Coffee Table Light
  - platform: powercalc
    entity_id: light.corner
    name: Corner Light
  - platform: powercalc
    entity_id: light.display_center
    name: Display Case Center Light
  - platform: powercalc
    entity_id: light.display_left
    name: Display Case Left Light
  - platform: powercalc
    entity_id: light.display_right
    name: Display Case Right Light
  - platform: powercalc
    entity_id: light.piano_table
    name: Display Piano Light
  - platform: powercalc
    entity_id: light.sonoff_mini_anteroom
    name: Anteroom Light
  - platform: powercalc
    entity_id: light.sonoff_mini_bathroom
    name: Bathroom Light
  - platform: powercalc
    entity_id: light.sonoff_mini_bedroom_parentheses
    name: Bedroom Light
  - platform: powercalc
    entity_id: light.sonoff_mini_entrance
    name: Entrance Light
  - platform: powercalc
    entity_id: light.sonoff_mini_kitchen_center
    name: Kitchen Center Light
  - platform: powercalc
    entity_id: light.sonoff_mini_kitchen_columns
    name: Kitchen Columns Light
  - platform: powercalc
    entity_id: light.sonoff_mini_livingroom_led_row_1
    name: Livingroom LED Row 1 Light
  - platform: powercalc
    entity_id: light.sonoff_mini_livingroom_led_row_2
    name: Livingroom LED Row 2 Light
  - platform: powercalc
    entity_id: climate.livingroom
    name: Livingroom HVAC
    fixed:
      states_power:
        cool: 4.0
        heat: 5.20
  - platform: powercalc
    entity_id: climate.bedroom
    name: Bedroom HVAC
    fixed:
      states_power:
        cool: 4.0
        heat: 5.20

And HA generated all a bunch of new sensors:
sensor.all_climate_energy
sensor.all_climate_energy_daily
sensor.all_climate_energy_monthly
sensor.all_climate_energy_weekly
sensor.all_climate_energy_yearly
sensor.all_climate_power
sensor.all_light_energy
sensor.all_light_energy_daily
sensor.all_light_energy_monthly
sensor.all_light_energy_weekly
sensor.all_light_energy_yearly
sensor.all_light_power
sensor.bedroom_hvac_energy
sensor.bedroom_hvac_energy_daily
sensor.bedroom_hvac_energy_monthly
sensor.bedroom_hvac_energy_weekly
sensor.bedroom_hvac_energy_yearly
sensor.bedroom_hvac_power
sensor.bugs_buster_energy
sensor.bugs_buster_power
sensor.coffee_table_light_energy
sensor.coffee_table_light_energy_daily
sensor.coffee_table_light_energy_monthly
sensor.coffee_table_light_energy_weekly
sensor.coffee_table_light_energy_yearly
sensor.coffee_table_light_power
sensor.corner_light_energy
sensor.corner_light_energy_daily
sensor.corner_light_energy_monthly
sensor.corner_light_energy_weekly
sensor.corner_light_energy_yearly
sensor.corner_light_power
sensor.fritz_box_7430_link_download_power_attenuation
sensor.fritz_box_7430_link_upload_power_attenuation
sensor.heater_energy
sensor.heater_power
sensor.ikea_of_sweden_tradfri_remote_control_7e6295fe_power
sensor.livingroom_hvac_energy
sensor.livingroom_hvac_energy_daily
sensor.livingroom_hvac_energy_monthly
sensor.livingroom_hvac_energy_weekly
sensor.livingroom_hvac_energy_yearly
sensor.livingroom_hvac_power
sensor.washing_machine_energy
sensor.washing_machine_power

which seems all great, except for the fact that none of them actually shows up in the energy dashboard:

What givers?
Am I doing something wrong in the configs?
Or perhaps they're actually not expected to show up in the energy dashboard?
I checked the generated sensors against those already showing up and they don't seems to be any different, thus I'd expect them to show up and contribute to the consumes canculation?

It takes some time for them to appear selectable in the energy dashboard. https://github.com/bramstroker/homeassistant-powercalc/wiki/FAQ#i-dont-see-energy-appearing-in-the-energy-dashboard-why-is-that.
Also you'll need to add the energy sensors you want under "Settings -> Dashboards -> Energy" and then add them under individual devices. Hope this helps.

Btw I think you can omit all the configuration except the two AC sensors, as they should be auto discovered by powercalc

I installed and configured powercalc on Friday and waited some days before opening the issue as I was expecting HA to possibly take some time to auto-magically discover everything but yes: adding them manually under settings def helped them to show up:

Even tho adding them one by one is a bit nuts :P and I'm still wondering what gives that in about 72h nothing was yet discovered.

These individual sensors and sources are never automatically appearing in the energy dashboard. You always have to add them one by one. A bit cumbersome but that's the way it works in HA.
Btw, is see you added them at sources. Would be better to add them to "Individual devices" as sources are meant for the power sources (i.e. Grid, Solar panels and multiple phases)

🤔 I have no idea 😁
I added them there because the smart socket with power meters I had where already showing up there:

Monkey sees, monkey does 😀
Im checking all this thing out because in next months I'll probably be installing solar panels, batteries, etc, to figure it out.
Thanks for the help and tips 👍


Donut title does not render if data is loaded via async

Hello! Thank you very much for the terrific product.
I have a donut chart being generated via data from a service. I have the chart itself working by setting the data in $scope.datapoints and $scope.datacolumns. However, the donut chart title does not appear.
I've created a workaround in the meantime by appending the title to the c3-chart-arcs-title, but I'd love to know if this could be resolved or if there's a better way to achieve the same.
Thanks!

I had a good look at this issue, problem is that I did not find a nice way of having static titles in combination with dynamic title. Need to think more about a solution, I do not want to create separate properties for all static and dynamic properties. Open for suggestions though.


Added new endpoints

Hi! until a few days Instagram added new endpoints to his graph-api (for example https://developers.facebook.com/docs/instagram-api/hashtag-search) is possible in the future, add this new endpoints?
Thanks a lot!

Yes,  sure.

@rakeshpatra - Has the new endpoint for hashtag-search been added?

@rakeshpatra - Has the new endpoint for hashtag-search been added?

Not yet, hashtag-search needs app approval, so couldn't integrate.

@rakeshpatra
Hi! Nice to meet you.
Has the new endpoint for Graph API's hashtag-search been added?
I understand that Facebook's app needs access approval to use that, but this gem can be used assuming that app got approval, can't it ?
If can, I want to contribute for the new endpoint function of this gem.
I am very sorry for my poor English.

Hey,
I would be more glad if someone can help me adding the new endpoints to the
gem, what I would need is a token with that permission so that we can test
and implement the feature.
You can always reach me, I will me happy to help as much as I can.
Thanks,
Rakesh
On Sat, 17 Oct, 2020, 9:28 AM Yuya Sumie<EMAIL_ADDRESS>wrote:

@rakeshpatra https://github.com/rakeshpatra
Hi! Nice to meet you.
Has the new endpoint for Graph API's hashtag-search been added?
I understand that Facebook's app needs access approval to use that, but
this gem can be used assuming that app got approval, can't it ?
If can, I want to contribute for the new endpoint function of this gem.
I am very sorry for my poor English.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/rakeshpatra/instagram_graph_api/issues/3#issuecomment-710742294,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ACEQR6RSEBZYDSAZQKFLSPLSLEI5HANCNFSM4GMMSFGA
.

Thank you for your reply.
I'll take access token and try.
To contribute, I need to fork and create PR, doesn't it ?

Yes, also if you can share the token with me I can add those endpoint to
the gem.
On Sat, 17 Oct, 2020, 9:55 AM Yuya Sumie<EMAIL_ADDRESS>wrote:

Thank you for your reply.
I'll take access token and try.
To contribute, I need to fork and create PR, doesn't it ?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/rakeshpatra/instagram_graph_api/issues/3#issuecomment-710745695,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ACEQR6SONCWJV3LE5NH72F3SLEMDBANCNFSM4GMMSFGA
.

@rakeshpatra
I have taken instagram_business_account's id & access_token, so how can I share them with you.

You can send me over email, else you can add me as a tester Or developer to
the Facebook app of your project.
My email id<EMAIL_ADDRESS>On Wed, 21 Oct, 2020, 10:33 PM Yuya Sumie<EMAIL_ADDRESS>wrote:

@rakeshpatra https://github.com/rakeshpatra
I have taken instagram_business_account's id & access_token, so how can I
share them with you.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
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or unsubscribe
https://github.com/notifications/unsubscribe-auth/ACEQR6QYJZKBL4YS3ONFBZLSL4H6FANCNFSM4GMMSFGA
.

Closing this #11 adds the endpoint to the gem.


make method accessible

Fixes accessibility issue mentioned by @helbertrios in #153.

I found In 5.5.1, this comes again! can some fix it ?


Simplify clock sync

While going through the _clock_sync function, I found an opportunity to simplify the code a bit. Furthermore, it seems like winsor_threshold was not really used as intended - instead if winsorizing, it merely divided the clock values by its value. Therefore, I've removed the parameter.

I'm guessing there's a reason Christian wanted the winsorizing in the python xdf importer. Let's get his input. @chkothe

Hey Clemens and Chad -- that parameter is indeed relevant for the robust estimation on the next line (it's the delta parameter of the Huber loss function above which deviations from the mean are treated as potential outliers and thus robustly).

@cbrnr It isn't used only for the clock values, but also for X 2 lines above.
As best as I can tell, values below rho will have their residuals penalized by L2, whereas values above rho will have their values penalized by L1. Instead of passing this value to the robust regression function as the rho value, you divide both x and y by the value and use the default rho=1. Is this equivalent? Am I interpreting the intention properly? If so, do you think we could simply pass the value to the robust regression function argument? Are there any numerical precision considerations I'm missing?
While we're on this topic, is that still considered 'winsorizing'? There doesn't seem to be any clipping. Maybe we should rename the parameter?

I don't see where winsor_threshold is used except for dividing X and y - that just scales the values of the clock and offsets by an equal amount. _robust_fit is then called with X and y with the default rho=1. If indeed rho should be rho / winsor_threshold (or some other scaled value), then I think it would be better to integrate that into the parameter itself.
But this is more or less an API decision, currently I find it really difficult to see how this algorithm works if part of a parameter needs to be worked into the data before applying the function. I'll revert this change and only leave the simplified reshaping of X.

@cbrnr yes the intention of those divisions should have been documented better, my fault. @cboulay the purpose of rho parameter is actually unrelated (it's a coupling parameter in the alternating-directions method), although it's possible that it does ultimately simplify in the way you describe (without having checked it myself) -- but normally the Huber threshold would be a third parameter that would have to be worked into the optimizer (I think some of the 1's in the code would have to be replaced by that). Now, while that would make things more explicit, and perhaps allow the robust fit method to be used in other contexts, for now it'd be a purely internal reshuffling, and we'd need to implement some strong tests to ensure that the behavior is identical (since it's easy for breakages to go unnoticed in that sort of code, especially if the test data don't exhibit the kinds of pathologies that the method is designed to protect against).

@cboulay re the naming, indeed it's a bit of a misnomer, although there's a subtle correspondence between the two methods (one trimming the input data and the other trimming an iterate). I think one could document that it's technically a misnomer and/or have a transition period with deprecation warning. In fact if you guys want to rename it, maybe one shouldn't even rename it to huber_threshold then (since we might swap that method some day, which would incur yet another API breakage) but more like robust_threshold. For now I'd personally err on the side of not breaking things for users without a strong reason (in line with the Linux mantra of never breaking user space) -- as in, there has to be enough on the upside to make up for things erroring our for scores of data analysts, and the cascade of issues coming with that.

I agree that we don't have to break/change anything for this function because it's not part of the public API. However, adding some explanations would help a great deal.

I've reverted all changes related to winsor_threshold and left only the array creation simplification.

I thinks it's the other way round, /= is in-place division, whereas X / winsor_threshold allocates a new array. But like you said, it's no big deal here anyway.

I know I've encountered situations where X /= a didn't work because of a shape mismatch in an intermediate variable that numpy creates but X = X / a worked fine. I guess this doesn't mean that the latter doesn't make a copy. Maybe it's because of the copy that it works better in some cases? Anyway, this is way off-topic. I think the change is fine as is.


plugin-stripe: deleteFromStripe hook crashes application

When I delete a product from Stripe, the following error crashes my application:
[17:31:22] INFO (payload): - Deleting Payload document with ID: '64fdfd696f7457b9e210f2ce'...
[17:31:22] INFO (payload): - ✅ Successfully deleted Payload document with ID: '64fdfd696f7457b9e210f2ce'.
POST /stripe/webhooks 200 17 - 5.742 ms
[17:31:22] INFO (payload): Document with ID: '64fdfd696f7457b9e210f2ce' in collection: 'products' has been deleted, deleting from Stripe...
[17:31:22] INFO (payload): - Deleting Stripe document with ID: 'prod_id'..
/Users/folder/api/node_modules/@payloadcms/plugin-stripe/dist/hooks/deleteFromStripe.js:33
            op = body.call(thisArg, _);
                      ^
APIError: Failed to delete Stripe document with ID: 'prod_id': No such product: 'prod_id'
    at /Users/folder/api/node_modules/@payloadcms/plugin-stripe/src/hooks/deleteFromStripe.ts:53:15
    at step (/Users/folder/api/node_modules/@payloadcms/plugin-stripe/dist/hooks/deleteFromStripe.js:33:23)
    at Object.throw (/Users/folder/api/node_modules/@payloadcms/plugin-stripe/dist/hooks/deleteFromStripe.js:14:53)
    at rejected (/Users/folder/api/node_modules/@payloadcms/plugin-stripe/dist/hooks/deleteFromStripe.js:6:65)
    at processTicksAndRejections (node:internal/process/task_queues:95:5) {
  status: 500,
  data: null,
  isPublic: false,
  isOperational: true
}

After some investigation it appears that the afterDelete deleteFromStripe collection hook errors out here after a 404 response from Stripe https://github.com/payloadcms/plugin-stripe/blob/main/src/hooks/deleteFromStripe.ts#L37
Looking at the webhook events after I delete a product in Stripe -> product.deleted  (deletes product in payload) -> deleteFromStripe collection hook attempts to delete product already deleted in Stripe
stripe.retrieve throws an error caused by 404 rather than returning null. expected behavior is for the else block to be called and the afterDelete hook to terminate without error.
Stripe 10.2.0
@payloadcms/plugin-stripe 0.0.14
payload 1.6.32

Circling back on this, this should now be possible through the context property on hooks: https://payloadcms.com/docs/hooks/context. Should be able to simply thread some key through context which indicates to subsequent hooks that the event was initiated by Stripe, in order to ultimately skip the follow-up deletion that is made.


Added an RCBD design example with two main independent variables.

@msimmond I've moved this RCBD example to this pull request. I'll make a pull request for each example so we can discuss the code for each example.
Stuff:

[x] Add in the transformation of the dependent variable.
[x] Why is the "block" variable ignored in LSD?
[x] Is this the desired interaction plot?
[x] Levene's test: I getting this error "Model must be completely crossed formula only."
[x] Add Tukey's 1-df test
[x] Add box plot
[x] Remove Tukey 1-df test?
[x] Add in final bar plot from LSD.test() results.
[x] Remove confint() call?
[x] Switch to non-ggplot bar chart.
[x] Confirm that the log10 transformation is correct.
[x] Why are two interaction plots needed for two variables? Doesn't one show it?

> source('rcbd_two_var.R', print.eval = TRUE)
Loading required package: lattice
Loading required package: grid
Loading required package: latticeExtra
Loading required package: RColorBrewer
Loading required package: multcomp
Loading required package: mvtnorm
Loading required package: survival
Loading required package: splines
Loading required package: TH.data
Loading required package: gridExtra

Attaching package: ‘HH’

The following objects are masked from ‘package:car’:

    logit, vif

Use suppressPackageStartupMessages to eliminate package startup messages.

Attaching package: ‘ggplot2’

The following object is masked from ‘package:latticeExtra’:

    layer

Loading required package: plyr
Shapiro-Wilk Normality Test
===============================================================================

	Shapiro-Wilk normality test

data:  residuals(model)
W = 0.9474, p-value = 0.08646

===============================================================================
Levene's Test
===============================================================================
Levene's Test for Homogeneity of Variance (center = median)
      Df F value  Pr(>F)
group  2  5.2195 0.01073 *
      33
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Levene's Test for Homogeneity of Variance (center = median)
      Df F value Pr(>F)
group  2  1.0005 0.3786
      33
===============================================================================
Tukey 1-df Test for Non-additivity
===============================================================================
Analysis of Variance Table

Response: log10.yield
               Df  Sum Sq  Mean Sq  F value    Pr(>F)
clone           2 0.60563 0.302815 165.9591 2.155e-14 ***
nitrogen        2 0.05674 0.028371  15.5491 5.349e-05 ***
block           3 0.03799 0.012662   6.9395  0.001713 **
squared.preds   1 0.01893 0.018925  10.3722  0.003787 **
clone:nitrogen  4 0.00993 0.002482   1.3605  0.278312
Residuals      23 0.04197 0.001825
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
===============================================================================
ANOVA Table
===============================================================================
Analysis of Variance Table

Response: log10.yield
               Df  Sum Sq  Mean Sq  F value    Pr(>F)
block           3 0.03799 0.012662   6.3335  0.002562 **
clone           2 0.60563 0.302815 151.4680 2.449e-14 ***
nitrogen        2 0.05674 0.028371  14.1914 8.556e-05 ***
clone:nitrogen  4 0.02284 0.005710   2.8563  0.045536 *
Residuals      24 0.04798 0.001999
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
===============================================================================
Least Significant Difference
===============================================================================

Study: model ~ c("clone", "nitrogen")

LSD t Test for log10.yield

Mean Square Error:  0.001999199

clone:nitrogen,  means and individual ( 95 %) CI

      log10.yield        std r       LCL       UCL       Min       Max
c1:n1   0.8701454 0.07582428 4 0.8240045 0.9162864 0.7781513 0.9542425
c1:n2   0.9256076 0.06669088 4 0.8794667 0.9717486 0.8450980 1.0000000
c1:n3   0.9528938 0.03959399 4 0.9067528 0.9990347 0.9030900 1.0000000
c2:n1   1.1288360 0.04171115 4 1.0826950 1.1749769 1.0791812 1.1760913
c2:n2   1.2234903 0.02455571 4 1.1773494 1.2696313 1.2041200 1.2552725
c2:n3   1.3052361 0.03735114 4 1.2590952 1.3513771 1.2552725 1.3424227
c3:n1   0.9746813 0.05953852 4 0.9285404 1.0208222 0.9030900 1.0413927
c3:n2   0.9726891 0.07497815 4 0.9265481 1.0188300 0.9030900 1.0791812
c3:n3   1.0072647 0.06313851 4 0.9611238 1.0534057 0.9542425 1.0791812

alpha: 0.05 ; Df Error: 24
Critical Value of t: 2.063899

Least Significant Difference 0.06525313
Means with the same letter are not significantly different.

Groups, Treatments and means
a 	 c2:n3 	 1.305
b 	 c2:n2 	 1.223
c 	 c2:n1 	 1.129
d 	 c3:n3 	 1.007
de 	 c3:n1 	 0.9747
de 	 c3:n2 	 0.9727
de 	 c1:n3 	 0.9529
ef 	 c1:n2 	 0.9256
f 	 c1:n1 	 0.8701
===============================================================================

Ok, maybe the only thing left on this one is to add in the correct transformation.

@msimmond I'm reading the transformation code here. What transformations do you want to support? Just base 10 log and raising to a power? Should we be doing the calculation to get the best exponent be done for the user should we simply let the user type in the desired value of the exponent?

For now I think 3 transformations should be available: base 10 log, square root, and raising to a power using the algorithm to find best fit.

Ok, that sounds fine.

@msimmond I've updated this example to strictly use the log10 transform and added a bar plot for the LSD.test. Is this correct? See the results at the top of this PR.

Should the confint() call be removed from all examples like we did in the CRD one?

I think the two interaction plots are redundant, is that the case?

@msimmond One question for this one:
You had a triple transformation, something like sqrt(log10(Y))^power and I changed it to simply a log10(Y) tranformation because that is what you had in the comments. Is this correct?

With the log10 transform I'm still seeing a sig p value in the Levene Test for clone.

I'm not seeing the sig p value in levene's for clone with the log 10 transform in the app. I think the code posted here is incorrectly using the original units - see comment in code.

Ok, I'll look at this soon. In the meantime does this do what you want?:
https://github.com/ucd-ipo/aip-analysis/pull/51/files#diff-07838b7a58641aa441c07b70abcfaa1fR843
I wrote this code to merge the summarySE and lsd.results$groups tables.

Yes, but not for the case where you have a transformed variable. If it's for an analysis of a transformed variable, columns 5, 6, 7, 8, and 9 would be replaced with the output from the original variable. Column 10 'M' would stay the same.


Some requests failing in dockerized Traefik but working when Traefik is run directly on the host machine

Do you want to request a feature or report a bug?
Bug
What did you do?

I am using Traefik as a reverse proxy to my web application and to automatically general SSL certs with lets encrypt.
My application is a dockerized flask app served with Gunicorn.
I started Traefik in two ways:

As a dockerized service running alongside my other docker-compose services. Here is the relevant snippet from my docker-compose file:

    traefik:
        container_name: traefik
        image: traefik:1.7.7
        volumes:
            - /var/run/docker.sock:/var/run/docker.sock:ro
            - ./traefik:/etc/traefik
        ports:
            - "80:80"
            - "443:443"
            - "${TRAEFIK_ADMIN_PORT:-8080}:8080"

Directly on the host machine using the binary downloaded from GitHub releases:

sudo ./traefik_linux-386 --configFile=traefik/traefik.toml
Note how I am using the same toml file in both instances.
What did you expect to see?
I expected to see no appreciable difference between running Traefik in the docker container and running it directly on the host.
What did you see instead?
Instead I saw many of the requests fail when running Traefik inside a docker container. When loading my web app some of the resources fail to load, while others load successfully. It is not always the same resources, but almost every page load some of the resources fail to load. Here is a screen grab of the safari network pane:

In comparison when I run the binary downloaded on GH releases directly on the host machine (still running my app with docker) then I never see any failed resources.
Output of traefik version: (What version of Traefik are you using?)

Dockerized:
docker run traefik version
Version:      v1.7.7
Codename:     maroilles
Go version:   go1.11.4
Built:        2019-01-08_10:21:03AM
OS/Arch:      linux/amd64

On Host Machine:
./traefik_linux-386 version
Version:      v1.7.7
Codename:     maroilles
Go version:   go1.11.4
Built:        2019-01-08_10:21:03AM
OS/Arch:      linux/386

What is your environment & configuration (arguments, toml, provider, platform, ...)?
debug = false
logLevel = "INFO"
defaultEntryPoints = ["http", "https"]

[accessLog]

[web]
# Port for the status page
address = ":8080"
  [web.auth.basic]
  users = ["admin:pass"]

# Entrypoints, http and https
[entryPoints]
  # http should be redirected to https
  [entryPoints.http]
  address = ":80"
    [entryPoints.http.redirect]
    entryPoint = "https"
  # https is the default
  [entryPoints.https]
  address = ":443"
    [entryPoints.https.tls]

# Enable ACME (Let's Encrypt): automatic SSL
[acme]
# Email address used for registration
email = "me"
storageFile = "/etc/traefik/acme.json"
entryPoint = "https"
onDemand = false
OnHostRule = true
  [acme.httpChallenge]
  entryPoint = "http"

[retry]

# Enable Docker configuration backend
[docker]
endpoint = "unix:///var/run/docker.sock"
watch = true
exposedbydefault = false

If applicable, please paste the log output in DEBUG level (--logLevel=DEBUG switch)
(paste your output here)

Please let me know if any more information is needed.
https://stackoverflow.com/questions/54119727/traefik-request-has-been-aborted-and-tls-handshake-error-error-showing-up-in

I think I’m actually seeing this exact same issue. Sporadic failures when requesting the web app through Traefik — reported as status code 000 by curl. When I curl the backend individually, all 200s. I’ll gather up some debug logs monentarily.

@paulcalabro For what its worth I tried the next few releases after reporting this issue and the issue still persisted. I reached out to containous via email and they said the issue was most likely something not related to Traefik and had to do with my environment. This could very well be the case but I think I am running a fairly simple and standard environment: AWS ubuntu image, official postgres docker container, official python 3.6 docker container
Luckily my workaround of running Traefik outside of the docker container on my actual host system has continued to work for me. I have not seen a single error since switching away from the official Traefik docker container. Have you tried not using the official Traefik docker container and instead running on your host system?

Hi! I'm Træfiker :robot: the bot in charge of tidying up the issues.
I have to close this one because of its lack of activity :disappointed:
Feel free to re-open it or join our Slack workspace for more community #support.


Problem with toHaveBeenFetchedTimes()method when compare similar URL's

🐛 Bug report

Problem with toHaveBeenFetchedTimes() when compare similar URL's
👣 Steps to reproduce

  it('should compare the strict string', async () => {
    const path = '/some/path/'
    const similarPath = '/some/path/with/id'

    await fetch(new Request(path))
    await fetch(new Request(similarPath))

    expect('/some/path/').toHaveBeenFetchedTimes(1)
    expect('/some/path/with/id').toHaveBeenFetchedTimes(1)
  })

🤔 Expected behavior

I expect that the test pass
🌯 Wrapito version

latest

Issue resolved https://github.com/mercadona/wrapito/pull/123 ✅


Create a sample for Message Sequence pattern

Create a sample for Message Sequence pattern.

Let's use range upload feature of a cloud storage (such as S3) to demo this.


getHeaderWidgetsColumns() not applied to Stats widgets

Package
filament/filament
Package Version
v3.2.92
Laravel Version
11.11.1
Livewire Version
v3.5.1
PHP Version
8.2.14
Problem description
When using getHeaderWidgetsColumns() with stats widgets the number of columns remains 3.
The problem is, that for stats widgets the number of columns is hardcoded into the view file:
//vendor/filament/widgets/resources/views/stats-overview-widget.blade.php

<x-filament-widgets::widget class="fi-wi-stats-overview">
    <div
        @if ($pollingInterval = $this->getPollingInterval())
            wire:poll.{{ $pollingInterval }}
        @endif
        @class([
            'fi-wi-stats-overview-stats-ctn grid gap-6',
            'md:grid-cols-1' => $columns === 1,
            'md:grid-cols-2' => $columns === 2,
            'md:grid-cols-3' => $columns === 3,
            'md:grid-cols-2 xl:grid-cols-4' => $columns === 4,
        ])
    >
        @foreach ($this->getCachedStats() as $stat)
            {{ $stat }}
        @endforeach
    </div>
</x-filament-widgets::widget>

Expected behavior
using getHeaderWidgetsColumns() should change the number of columns (widgets per row)
Steps to reproduce
Create a stat widgets and show them on the List page of a resource
Reproduction repository (issue will be closed if this is not valid)
https://github.com/milenmk/filament-issue
Relevant log output
No response

Donate 💰 to fund this issue

You can donate funding to this issue. We receive the money once the issue is completed & confirmed by you.
100% of the funding will be distributed between the Filament core team to run all aspects of the project.
Thank you in advance for helping us make maintenance sustainable!

When I put getColumns() { return 5;} or another number, each widget stretches to fill the entire row and I end up with 5 widgets each one above the other i.e. 5 rows. I have followed some examples so:

In my resource class

public static function getWidgets(): array
    {
        return [
            UsersStats::class,
        ];
    }

In class ListUsers extends ListRecords

use ExposesTableToWidgets;

protected function getHeaderWidgets(): array
    {
        return UsersResource::getWidgets();
    }

In class UsersStats extends BaseWidget

use InteractsWithPageTable;

    protected static ?string $pollingInterval = null;

    protected function getTablePage(): string
    {
        return ListUsers::class;
    }

    protected function getStats(): array
    {
        return [
            Stat::make('total_users', User::count())->label(__('Total Users')),
            Stat::make(
                'super_admin',
                $this->getPageTableQuery()->with('roles')->get()->filter(
                    fn (User $user) => $user->roles->where('name', 'SuperAdmin')->toArray()
                )->count()
            )
                ->label(__('Super Administrator')),
            Stat::make(
                'administrator',
                $this->getPageTableQuery()->with('roles')->get()->filter(
                    fn (User $user) => $user->roles->where('name', 'Administrator')->toArray()
                )->count()
            )
                ->label(__('Administrator')),
            Stat::make(
                'moderator',
                $this->getPageTableQuery()->with('roles')->get()->filter(
                    fn (User $user) => $user->roles->where('name', 'Moderator')->toArray()
                )->count()
            )
                ->label(__('Moderator')),
            Stat::make(
                'project_owner',
                $this->getPageTableQuery()->with('roles')->get()->filter(
                    fn (User $user) => $user->roles->where('name', 'ProjectOwner')->toArray()
                )->count()
            )
                ->label(__('Project Owner')),
        ];
    }

As I've said, there are 5 widgets and I'd like to have them in 1 row thus I presume I have to use getHeaderWidgetColumns but it doesn't work no matter where I put it: inside ListUsers or inside UsersStats.
As stated in my previous post, the reason is that the columns are hardcoded in /vendor/filament/widgets/resources/views/stats-overview-widget.blade.php

Please carefully read my previous comment.
The stats overview widget is just a single widget, so you will have to configure the number of columns on the stats overview widget.

I'm getting the same error mentioned by @milenmk .
When using:
protected function getColumns(): int
    {
        return 5; // Sets 5 columns for the stats
    }

    protected function getStats(): array
    {
        return [
            Stat::make('# of Vendors', User::where('status', Config('constant.status.active'))->whereRelation('roles', 'name', 'VENDOR')->count()),
            Stat::make('# of Products', Product::active()->count()),
            Stat::make('Today\'s Orders', Order::whereDate('created_at', Carbon::today())->count()),
            Stat::make('Total Sales', Order::sum('order_total')),
            Stat::make('Orders Till Date', Order::count())
        ];
    }

Each of the stats take the full line

It seems stats-overview-widget.blade.php doesn't support anything over 4 columns:
@class([
            'fi-wi-stats-overview-stats-ctn grid gap-6',
            'md:grid-cols-1' => $columns === 1,
            'md:grid-cols-2' => $columns === 2,
            'md:grid-cols-3' => $columns === 3,
            'md:grid-cols-2 xl:grid-cols-4' => $columns === 4,
        ])

Can someone change this on the core?

Thanks for clarifying, @mariomeyer.
Sorry if I missed your point earlier, @milenmk.
Would you be open to create a PR for this improvement, @mariomeyer?
Have a look at the existing grid component to see how that's approached using CSS variables.

@zepfietje I created #14668 but @danharrin said 3.x is closed for new features.

This is possible in v4


use nodeinfo for platform detection

https://github.com/jhass/nodeinfo

https://github.com/shadone/DiasporaNodeInfo


Windows 7 doesn’t resolve hostname <IP_ADDRESS>

hi there, all i get is the webpage is not available when i fire up static preview.... tried changing the default port and ip, but not working either.  i'm sure it's something to do on my end. but i  haven't been able to figure out.  the machine is running on win7 64bit.

Hi there!
My Static Preview doesn't even start for some reason as it used to. Need help!!!!
Thanks a lot!

Hi @htmlstrap,
are there any errors relating to this extension in the developer tools?

well, I re-installed the editor and all the extensions. so, now it work well.... thanks!


Check license in parent directories

When checking the report of a subpackage, the license check fails while the project is licensed in at the directory's root.
I think it would be interesting to check the parent directories for the License file.

I've got exactly the same issue!

@creack @kare could one of you provide an example just for reference? Just so I have something to base tests on

Here's one:

https://github.com/kare/vanity/
https://github.com/kare/vanity/tree/master/cmd/vanity

Looks like kare's repository contains a LICENSE in the root now. Sorry, I think it's easiest for us to just check the root dir for now. We'd certainly look at a PR if one were to be made though.


Use dependency labels consistent with PodToBUILD.

Asana: https://app.asana.com/0/1203960884932166/1204190072048671/f

Ran into this with node_modules dependencies that are trying to rely on react-native core libraries and need deps like @ReactCore//:ReactCore.

Hrm wait is this just another version of #2? This might be stale, gonna retest locally to verify.


Empty Sender header in send mails

Follow up of #314 : Our emails contain an empty Sender: header. See https://github.com/serlo/serlo.org/issues/314#issuecomment-613029910 for an example email.

It seems that the mail is created at https://github.com/serlo/serlo.org/blob/master/packages/public/server/src/module/Mailman/src/Mailman/Adapter/ZendMailAdapter.php#L70-L88 However, when I run this code I get the following message which does not contain a Sender header:
Date: Sat, 11 Apr 2020 14:09:38 +0200
From<EMAIL_ADDRESS>To<EMAIL_ADDRESS>Subject: subject
MIME-Version: 1.0
Content-Type: multipart/alternative;
 boundary="=_cbc7806d90858060cfc180074592d6ed"

This is a message in Mime Format.  If you see this, your mail reader does not support this format.

--=_cbc7806d90858060cfc180074592d6ed
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: 8bit

html
--=_cbc7806d90858060cfc180074592d6ed
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

plain
--=_cbc7806d90858060cfc180074592d6ed--

It seems that the mail is created at https://github.com/serlo/serlo.org/blob/master/packages/public/server/src/module/Mailman/src/Mailman/Adapter/ZendMailAdapter.php#L70-L88 However, when I run this code I get the following message which does not contain a Sender header:
Date: Sat, 11 Apr 2020 14:09:38 +0200
From<EMAIL_ADDRESS>To<EMAIL_ADDRESS>Subject: subject
MIME-Version: 1.0
Content-Type: multipart/alternative;
 boundary="=_cbc7806d90858060cfc180074592d6ed"

This is a message in Mime Format.  If you see this, your mail reader does not support this format.

--=_cbc7806d90858060cfc180074592d6ed
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: 8bit

html
--=_cbc7806d90858060cfc180074592d6ed
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

plain
--=_cbc7806d90858060cfc180074592d6ed--

I tested it with an account creation for an web.de account: The mail for activating the account is successfully delivered and the Sender header is set in the mail to the same value as the From header.


How to run a filter with "LIKE" parameter?

In QGIS I'm able to style my data by filtering them into several categories. On the screenshot, I'm showing that I want to filter in Maputnik all of the layers that start with "A %". How I can repeat the same in Maputnik?

@orangemug - could you please take a look on this?

I'm not 100% sure about this, but I don't think mapbox-gl-js supports this. Take a read of the spec at https://www.mapbox.com/mapbox-gl-js/style-spec, I think your best bet would be to add a extra field to your data, something like type, and match on that instead.

@orangemug, thanks!

No worries, also welcome to Maputnik!
If you have time please fill out the survey in the app, and/or tell us what you're using Maputnik for over in issue #164


Disable TableTest#testCloseConnectionPool

Purpose
$Subject. Tracked by #9048
#9048 was observed again in Jenkins released build but not locally. Only one connection seems to be kept open unnecessarily.

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@a0c7f75). Click here to learn what that means.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master   #12952   +/-   ##
=========================================
  Coverage          ?   59.42%
  Complexity        ?      659
=========================================
  Files             ?     2109
  Lines             ?   103245
  Branches          ?    13172
=========================================
  Hits              ?    61358
  Misses            ?    36694
  Partials          ?     5193

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update a0c7f75...cdacc00. Read the comment docs.


Fixing #895. Just adding a null check before accessing ProjectHelper.ParsedProject

Quick PR so as to avoid this bug interfering with everyone else's work. Will add tests at a later PR.

Thanks for the quick fix!


W3C trace context spec only implemented half-way?

We have the traceparent attribute defined in the common message properties spec.
W3C Spec says:

At a minimum they MUST propagate the traceparent and tracestate headers and guarantee traces are not broken. This behavior is also referred to as forwarding a trace.

So shouldn't we also add an optional tracestate field?

@jefftindall, what say you?

Since this is not currently being used, I'll close this issue till someone decides it is needed and we need to add it back.


Implement partial in-reply-to according to rfc5322.

According to the RFC In-Reply-To header could contain
multiple addresses with flexible format. K-9 creently
supports only a single In-Reply-To, so I assumed a
single In-Reply-To for mailto: links, to keep it simple.
Fixes https://github.com/k9mail/k-9/issues/5193
Initial disucssion at: https://forum.k9mail.app/t/in-reply-to-header-not-set/766

Please also add at least two test cases to MailToTest. One with a valid in-reply-to parameter and one with an invalid one.

Please also add at least two test cases to MailToTest. One with a valid in-reply-to parameter and one with an invalid one.

I added a few tests.

Almost there +1

Thanks for the thorough review! All applied.


cue: 0.4.3 -> 0.5.0

Description of changes

Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
23.05 Release Notes (or backporting 22.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[ ] Fits CONTRIBUTING.md.

I tested this on aarch64-darwin. It builds and runs fine; tested thusly:
$ nix run github:aaronjheng/nixpkgs/cue#cue -- version
cue version 0.5.0

go version go1.20.3
      -buildmode exe
       -compiler gc
       -trimpath true
     CGO_ENABLED 1
          GOARCH arm64
            GOOS darwin

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/2075

@ofborg test bootspec.basic


Bump Roslyn to 2.6.1, enable C# 7.2

Yeah, this should have been 2.6.1. Fixed. VSM upgraded it to the dotnet feed I guess, even though I selected in the UI from nuget.org feed.


In the use of these interfaces to add the code, the application will be smaller

//_ "github.com/siddontang/ledisdb/store/boltdb"
_ "github.com/siddontang/ledisdb/store/goleveldb"
_ "github.com/siddontang/ledisdb/store/leveldb"
//_ "github.com/siddontang/ledisdb/store/mdb"
//_ "github.com/siddontang/ledisdb/store/rocksdb"

In the use of these interfaces to add the code, the application will be smaller

@Leither ledis will use goleveldb and boltdb for default, and use go build tags for other storages, if you don't build with passing rocksdb, leveldb or lmdb tags, ledis will not build them.
Later I will check whether build with not passing these flags will reduce the application size.

@Leither , in my mac osx, I do like yours above, but the application size reduces little.


Failed to load the native TensorFlow runtime.

Issue type
Build/Install
Have you reproduced the bug with TensorFlow Nightly?
Yes
Source
source
TensorFlow version
tensorflow-intel==2.17.0
Custom code
Yes
OS platform and distribution
Windows 10
Mobile device
No response
Python version
3.12.4
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
I expected the code to run as inteneded and generate a file within a certain folder within my project structure
Standalone code to reproduce the issue
import pandas as pd
import os
import json
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error  # For evaluation after predictions
import tensorflow as tf
import numpy as np
import pickle

# Load configuration
CONFIG_PATH = os.path.join(os.path.dirname(__file__), 'C:/Users/path')

with open(CONFIG_PATH, 'r') as f:
    config = json.load(f)

def load_data(symbol):
    """
    Load processed data for a given stock symbol.
    """
    folder = os.path.join(os.path.dirname(__file__), 'C:/Users/path')
    file_path = os.path.join(folder, f'{symbol}.csv')

    if not os.path.exists(file_path):
        raise FileNotFoundError(f"Processed data for {symbol} not found.")

    df = pd.read_csv(file_path)
    return df

def preprocess_data(df):
    """
    Preprocess the data for LSTM. Scale it and reshape it for sequential training.
    """
    # Select features and target
    features = ['SMA_20', 'EMA_20', 'SMA_50', 'EMA_50', 'RSI', 'Volatility', 'ROC', 'MACD', 'Signal_Line']
    target = 'close'

    # Scaling the data
    scaler = MinMaxScaler(feature_range=(0, 1))
    scaled_data = scaler.fit_transform(df[features])

    # Creating sequences
    sequence_length = 60  # Use past 60 days to predict the next day
    X, y = [], []

    for i in range(sequence_length, len(scaled_data)):
        X.append(scaled_data[i-sequence_length:i])
        y.append(df[target].values[i])

    X, y = np.array(X), np.array(y)

    # Reshape X to be (samples, time steps, features)
    X = np.reshape(X, (X.shape[0], X.shape[1], len(features)))

    return X, y, scaler

def build_lstm_model(input_shape):
    """
    Build an LSTM model for stock price prediction.
    """
    model = tf.keras.Sequential()

    # LSTM layers
    model.add(tf.keras.layers.LSTM(units=100, return_sequences=True, input_shape=input_shape))
    model.add(tf.keras.layers.Dropout(0.2))  # Add dropout to prevent overfitting
    model.add(tf.keras.layers.LSTM(units=100, return_sequences=False))
    model.add(tf.keras.layers.Dropout(0.2))

    # Dense layers
    model.add(tf.keras.layers.Dense(units=50))
    model.add(tf.keras.layers.Dense(units=1))  # Output layer predicting closing price

    model.compile(optimizer='adam', loss=tf.keras.losses.MeanSquaredError(), metrics=[tf.keras.metrics.MeanSquaredError()])

    return model

def train_model(X, y):
    """
    Train the LSTM model.
    """
    # Build the model
    model = build_lstm_model((X.shape[1], X.shape[2]))

    # Train the model
    model.fit(X, y, epochs=20, batch_size=32, validation_split=0.2, verbose=1)

    return model

def save_model(model, symbol, scaler):
    """
    Save the trained LSTM model and the scaler for later use.
    """
    folder = os.path.join(os.path.dirname(__file__), 'C:/Users/path')
    os.makedirs(folder, exist_ok=True)

    model_file_path = os.path.join(folder, f'{symbol}_lstm_model.h5')
    scaler_file_path = os.path.join(folder, f'{symbol}_scaler.pkl')

    # Save the model
    model.save(model_file_path)
    print(f"Model saved as {symbol}_lstm_model.h5")

    # Save the scaler
    with open(scaler_file_path, 'wb') as f:
        pickle.dump(scaler, f)
    print(f"Scaler saved as {symbol}_scaler.pkl")

def train_and_save_models():
    """
    Load data for each stock, preprocess it, train the LSTM model, and save the trained model.
    """
    stock_symbols = config['stocks']

    for symbol in stock_symbols:
        print(f"Training LSTM model for {symbol}...")

        # Load and preprocess the data
        df = load_data(symbol)
        X, y, scaler = preprocess_data(df)

        # Train the model
        model = train_model(X, y)

        # Save the model and scaler
        save_model(model, symbol, scaler)

if __name__ == "__main__":
    train_and_save_models()

Relevant log output
Traceback (most recent call last):
  File "C:\Program Files\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 70, in <module>
    from tensorflow.python._pywrap_tensorflow_internal import *
ImportError: DLL load failed while importing _pywrap_tensorflow_internal: A dynamic link library (DLL) initialization routine failed.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\Users\path", line 6, in <module>
    import tensorflow as tf
  File "C:\Program Files\Lib\site-packages\tensorflow\__init__.py", line 40, in <module>
    from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow  # pylint: disable=unused-import
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Program Files\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 85, in <module>
    raise ImportError(
ImportError: Traceback (most recent call last):
  File "C:\Program Files\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 70, in <module>
    from tensorflow.python._pywrap_tensorflow_internal import *
ImportError: DLL load failed while importing _pywrap_tensorflow_internal: A dynamic link library (DLL) initialization routine failed.

Failed to load the native TensorFlow runtime.

Hi @nashole ,
Apologies for the delay, Could you please provide the tensorflow and the compatible version which you are trying to install. Also there are at least 3 possible scenarios:
You need to install the MSVC 2019 redistributable
Your CPU does not support AVX2 instructions
Your CPU/Python is on 32 bits
There is a library that is in a different location/not installed on your system that cannot be loaded.
https://github.com/tensorflow/tensorflow/issues/61887
Thank you!

Closing as duplicate of #61887 (and similar other issues).


*STORE set functions and their respective non-storing ones

Somehow [xx]STORE is extra faster than [xx] when compared to redis (check it on the edis benchmarks) for all such set commands. We need to fix that.

Same problem seems to affect SMEMBERS. It sounds like returning multiple elements from a set is really slow in edis

Nevermind... those where based on problems with the test machine :$


You can edit a kata that you don't have enough rank to forfeit and haven't solved

Describe the bug
On a kata that you don't have enough rank to forfeit, you can still edit the kata (=> forfeit through the edit button, or even actually edit it).
e.g. I'm 3 kyu, so if I wanted to see the solution to a 1kyu then the edit button will give me the solution :trollface:
To Reproduce
Steps to reproduce the behavior:

Go to a kata you don't have enough rank to forfeit (and you haven't solved it)
Click on Edit Kata
Muhahaha, there's the solution.

Expected Behavior
You can't edit a kata you haven't solved and don't have enough rank to forfeit.
Screenshots

Fixed


feat: ui update

Codecov Report

Merging #85 (c5ca11c) into master (abd86a2) will increase coverage by 0.98%.
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raftstore: add peer msg process duration metrics

What problem does this PR solve?
Add peer msg process duration to help investigate latency spike.
What is changed and how it works?

Add some peer msg process duration metrics
Make append log duration only count the time of handle_raft_ready

Related changes

No

Check List

No code

Release note

Add peer msg process duration metrics

/release

@BusyJay PTAL again

/bench

/bench

/run-build

/run-build

/run-build

Part metrics are added in https://github.com/tikv/tikv/pull/13677


Passing component to DominoDOM#render overwrites root node

Prevents future renders - actual bug!

This occurs when the top-level component being rendered returns another component as the result of its render. Fixed by 3bccdb151c5b6748accdb9a7a50ad7012f955b62.


integration 'luchtmeetnet' does not have a version key in the manifest file and was blocked from loading

The plugin worked for a while. For sometime I get this error message when HA starts:
2021-11-01 22:14:29 ERROR (SyncWorker_1) [homeassistant.loader] The custom integration 'luchtmeetnet' does not have a version key in the manifest file and was blocked from loading. See https://developers.home-assistant.io/blog/2021/01/29/custom-integration-changes#versions for more details

@johan-de-jong Can you please test the code that I have put in the Pull Request?

Hi, Yes will do

@johan-de-jong Can you please test the code that I have put in the Pull Request?

@bouwew The plugin works again for me. Thanks!


WIP: Setting up fVDB GHA tests

This PR seems to still be triggering lots of CI runs it shouldn't. I think the .github directory is ignored by default, so my best guess is that it's perhaps because the changes to exclude fvdb/** are not part of the master branch (ie the trigger is based on the result of merging this branch to master). Perhaps it makes sense to create a new PR just to add those changes and then we merge that? Also, if you merge origin/master to this branch, that will at least remove a bunch of the more expensive Windows builds.

This PR seems to still be triggering lots of CI runs it shouldn't. I think the .github directory is ignored by default, so my best guess is that it's perhaps because the changes to exclude fvdb/** are not part of the master branch (ie the trigger is based on the result of merging this branch to master). Perhaps it makes sense to create a new PR just to add those changes and then we merge that? Also, if you merge origin/master to this branch, that will at least remove a bunch of the more expensive Windows builds.

Yes perhaps I'll do that for the moment.  I've been manually cancelling all the tests I don't need thinking I've solved these runner issues and the fix is 'just around the corner' but the corner keeps getting farther away.


Added Readable Version of Thai Language

What does the program do ?

In what programming language it is written?

Thank you for participating  in hacktoberfest ❣ if you liked working on this repo you can share it with friends and star this project for helping others


Initial implementation of FIRRTL primitive wrapper generator

Treats all inputs/outputs as UInts. It uses the as{UInt,SInt} ops to "cast" them before/after the primitive.
These don't take into account the widths (i.e. the output of an add op is a different width than the coreir add). We can either try to insert that logic into the wrappers, or we can emit "select" operators around primitive ops to make sure the output widths match coreir semantics.

I think that these wrappers cannot handle the bit manipulation required to match the widths to the coreir primitives because they do not know the widths of the inputs (i.e. we would need some notion of a width parameter n to know how many bits to select). The firrtl backend will need to properly emit the bit selection operations to have the outputs of these operations match the coreir primitives.

I'm a little bit confused. Are you referring to bit slicing and concatenation? If so then yeah that might need to be a special case in the backend.
Also for your ops do we need the product of Sint and Uint for the input types? I thought we were going to just create one firrtl module for each coreIR op where the all inputs/outputs to the firrtl module are always a UInt. I have no notion of signed and unsigned types, but I know you were trying to put those types into magma so it would probably be useful for you.

@rdaly525 Oh that makes sense, I interpreted the wording of your issue as wanting to wrap the firrtl primitive ops in modules but now I see you actually want the coreir ops implemented as a module.

I'll open another PR with an updated script