semvec/pypi-packages huggingface dataset:
midas-dlpdata 2.1.0
A Midas module for commercial buildings datasets.
Requires Python: >=3.10

# Midas Default Load Profiles Data Simulator

The *dlpdata* module, provided by the *midas-dlpdata* package, provides a simulator for the default load profiles provided by the BDEW set.

Version: 2.1

## Installation

This package will usually installed automatically together with `midas-mosaik`, if you opt-in the `bh` extra. 
It is available on pypi, so you can install it manually with

```bash
    pip install midas-dlpdata
```

## Usage

The intended use-case for the time simulator is to be used inside of midas.
However, it can be used in any mosaik simulation scenario.

### Inside of midas

To use the dlp data inside of midas, add `dlpdata` to your modules

```yaml
    my_scenario:
      modules:
        - dlpdata
        # - ...
```

and provide a *scope* and a configuration:

```yaml
    my_scenario:
      # ...
      dlp_data_params:
        my_scenario:
          meta_scaling: 1.5
          interpolate: True
          randomize_data: True
          randomize_cos_phi: True
          active_mapping:
          15: [[G4, 262.8]]
          17: [[H0, 1038.06]]
```

The numbers 15 and 17 stand for the bus number which depends on the used grid.

### Any Mosaik Scenario

If you don't use midas, you can add the `dlpdata` manually to your `mosaik scenario`_ file. 
First, the entry in the `sim_config`:

.. _`mosaik scenario`: https://mosaik.readthedocs.io/en/latest/tutorials/demo1.html

```python
    sim_config = {
        "DLPSimulator": {
          "python": "midas_powerseries.simulator:PowerSeriesSimulator"},
        # ...
    }
```

Next, you need to start the simulator (assuming a `step_size` of 900). 
Since it uses a custom data model, you have to specify it here:

```python
    dlpdata_sim = world.start(
        "DLPSimulator",
        step_size=900,
        model_import_str="midas_dlp.model:DLPModel",
        use_custom_time_series=True,
        start_date="2020-01-01 00:00:00+0100",
        data_path="/path/to/folder/where/dataset/is/located/",
        filename="bdew_default_load_profiles.csv",  # this is default
    )
```

Then the models can be started:

```python
    houshold = dlpdata_sim.CalculatedQTimeSeries(name="H0", scaling=1038.06)
    trade = dlpdata_sim.CalculatedQTimeSeries(name="G4", scaling=262.8)
```

Finally, the models need to be connected to other entities:

```python
    world.connect(trade, other_entity, "p_mw", "q_mvar")
```

## License

The data is taken from [BDEW](https://www.bdew.de/energie/standardlastprofile-strom/).
midas-comdata 2.1.0
A Midas module for commercial buildings datasets.
Requires Python: >=3.10

# Midas Commercial Data Simulator

The *comdata* module, provided by the *midas-comdata* package, provides a simulator for a commercial building reference data set.

Version: 2.1

## Usage

The intended use-case for the time simulator is to be used inside of midas.
However, it can be used in any mosaik simulation scenario.

### Inside of midas

To use the store inside of midas, add `comdata` to your modules

```yaml
    my_scenario:
      modules:
        - comdata
        # - ...
```
and provide a *scope* and a configuration:

```yaml
    my_scenario:
      # ...
      comdata_params:
        my_grid_scope:
          interpolate: True
          randomize_data: True
          randomize_cos_phi: True
          mapping:
            22: [[Hospital, 0.002]] # industrial subgrid
            35: [[StripMall, 0.015]]
``` 

The number 22, 35 stands for the bus number, which depends on the grid.

### Any mosaik scenario

If you don't use midas, you can add the `comdata` manually to your [mosaik scenario](https://mosaik.readthedocs.io/en/latest/tutorials/demo1.html) file.
First, the entry in the `sim_config`:

```python
  sim_config = {
      "CommercialDataSimulator": {
        "python": "midas_powerseries.simulator:PowerSeriesSimulator"
      },
      # ...
  }
```

Next, you need to start the simulator (assuming a `step_size` of 900):

```python
    comdata_sim = world.start(
        "CommercialDataSimulator",
        step_size=900,
        data_step_size=3600,
        start_date="2020-01-01 00:00:00+0100",
        data_path="/path/to/folder/where/dataset/is/located/",
        filename="commercial_profiles.csv",  # this is default
    )
```

Then the models can be started:

```python
    hospital = comdata_sim.CalculatedQTimeSeries(name="Hospital", scaling=0.002)
    strip_mall = comdata_sim.CalculatedQTimeSeries(name="StripMall", scaling=0.015)
```

Finally, the modells need to be connected to other entities:

```python
    world.connect(hospital, other_entity, "p_mw", "q_mvar")
```

## License

The data set ist taken from the project [Oben Energy Data Initiative](https://data.openei.org/about).
protolint-bin 0.56.4
A pluggable linter and fixer to enforce Protocol Buffer style and conventions.

This package contains the pre-compiled binaries.
Home-page: https://github.com/yoheimuta/protolint/
Author: yohei yoshimuta
Maintainer: yohei yoshimuta
License: MIT
Project-URL: Official Website, https://github.com/yoheimuta/protolint/
Project-URL: Source Code, https://github.com/yoheimuta/protolint.git
Project-URL: Issue Tracker, https://github.com/yoheimuta/protolint/issues
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Go
Classifier: Topic :: Software Development :: Pre-processors
Classifier: Topic :: Utilities
Requires-Python: >= 3.0
Description-Content-Type: text/rst
License-File: LICENSE

protolint
=========

protolint is the pluggable linting/fixing utility for Protocol Buffer
files (proto2+proto3)

-  Runs fast because this works without compiler.
-  Easy to follow the official style guide. The rules and the style
   guide correspond to each other exactly.

   -  Fixer automatically fixes all the possible official style guide
      violations.

-  Allows to disable rules with a comment in a Protocol Buffer file.

   -  It is useful for projects which must keep API compatibility while
      enforce the style guide as much as possible.
   -  Some rules can be automatically disabled by inserting comments to
      the spotted violations.

-  Loads plugins to contain your custom lint rules.
-  Undergone testing for all rules.
-  Many integration supports.

   -  protoc plugin
   -  Editor integration
   -  GitHub Action
   -  CI Integration

   .. rubric:: Usage in python projects
      :name: usage-in-python-projects

You can use ``protolint`` as a linter within your python projects, the
wheel ``protolint-bin`` on `pypi <https://pypi.org>`__ contains the
pre-compiled binaries for various platforms. Just add the desired
version to your ``pyproject.toml`` or ``requirements.txt``.

The wheels downloaded will contain the compiled go binaries for
``protolint`` and ``protoc-gen-protolint``. Your platform must be
compatible with the supported binary platforms.

You can add the linter configuration to the ``tools.protolint`` package
in ``pyproject.toml``.

More information
----------------

You will find more information on the `projects
homepage <https://github.com/yoheimuta/protolint>`__.
Avril14 0.0.1
library for creating neural networks
Requires Python: >=3.6
Keywords: machine learning neural networks

# Avril 14 #
## What is this? ##
avril 14 - is a library for creating and training neural networks
## Functions ##
lin_layer() - create linear layer, which is recorded as

![equation](https://latex.codecogs.com/svg.image?&space;Wx&plus;b), where
![equation](https://latex.codecogs.com/svg.image?W) - weights of layer

![equation](https://latex.codecogs.com/svg.image?b) - biases of layer

relu() - activation function

backprop() - start process of neural network learning

## Guide 1: approximation of cos function ##