semvec/pypi-packages huggingface dataset:
FPGAflow-esdg 0.3.5
FPGAFlow scripted tool-flow for FPGA firmware development

######
Readme
######

``FPGAFlow`` is a python script to handle a complete FPGA design flow where the design files, libraries and
supplementary tools are stored in a source code repository.

`Source Code Repository <https://bitbucket.org/mjroberts/fpgaflow/src/master/docs/>`_
`Documentation <https://fpgaflow.readthedocs.io/en/latest/index.html>`_

License
-------

`BSD`_ © 2018-2019 Science and Technology Facilities Council & contributors

.. _BSD: LICENSE
ialarmclient-phoenix 1.0.0
Meiantech, iAlarm, Antifurto365, AllarmiWireless and other alarm systems support

# Python client for iAlarm

Also compatible with Meiantech, Allarmi365, and others

## Usage example

```
#!/usr/bin/env python
import asyncio

from ialarmclient import IalarmClient


async def start():
    ialarm = IalarmClient(
        username="username", # <- Your alarm web interface username
        password="password", # <- Your alarm web interface password
        url="http://192.168.123.123" # <- Your alarm web interface URL (no trailing slash)
    )

    # Refresh alarm status, to be called every time you need to read updated information
    # May take up to 30-40 seconds the first time. Subsequent calls will be almost immediate.
    await ialarm.refresh() 

    # Retrieve information about your alarm zones (name, status, etc...)
    zones = await ialarm.get_zones()
    for zone in zones:
        if zone.type != ialarmclient.ZONE_TYPE_DISABLED:
            print("Zone {} is {}".format(zone.number, zone.name))
            # Other information can be read (see IalarmZone)

    # Retrieve alarm status (armed, disarmed, power failure, etc...)
    status = await ialarm.get_status()

    # Commands to arm/disarm your system
    await ialarm.arm_stay()
    await ialarm.arm_away()
    await ialarm.disarm()
    await ialarm.cancel_alarm()

    # List all zones in alarm
    status = await ialarm.get_status()
    for alarmed_zone in status.alarmed_zones:
        print("Zone {} is alarmed".format(alarmed_zone.name))

    # Status information for your system
    if status.power_source_failure:
        print("Power failure")

    if status.low_battery:
        print("Low battery")

    if status.panic_alarm:
        print("Panic alarm triggered")

    if status.arm_status == ialarmclient.STATUS_ARMED_AWAY:
        print("System armed")
    elif status.arm_status == ialarmclient.STATUS_ARMED_STAY:
        print("System armed (STAY)")
    elif status.arm_status == ialarmclient.STATUS_DISARMED:
        print("System disarmed")    

if __name__ == "__main__":
    loop = asyncio.get_event_loop()
    loop.run_until_complete(start())

```
sorted-months-weekdays 0.2
Get sorted Months and Weeks by chronological order

# sorted-months-weekdays
It sorts list of months or list of weekdays in a chronological order not in alphabetical order

The default python or pandas sort functions sort month names and weekdays in an alphabetical order. I checked a lot to find a function which sorts in chronological order but couldn't find one, so I created this simple package.

# How to install
    pip install sorted-months-weekdays
    
There are two main functions in this package
    Month_Sorted_Month
    Weekday_Sorted_Week
   
# How to import
    from sorted_months_weekdays import Month_Sorted_Month, Weekday_Sorted_Week
    
# Example1
```python
    samplemonthnames1 = ['Apr','Jan','Dec','Mar','Oct']
    samplemonthnames2 = ['December', 'January', 'June', 'March', 'September']
    
    Month_Sorted_Month(samplemonthnames1)
    Result: ['Jan', 'Mar', 'Apr', 'Oct', 'Dec']
    
    Month_Sorted_Month(samplemonthnames2)
    Result: ['January', 'March', 'June', 'September', 'December']
```
# Example2
``` python
    testweeknames1 = ['Tue','Thu','Mon','Sun']
    testweeknames2 = ['Saturday','Tuesday','Friday','Monday']
    
    Weekday_Sorted_Week(testweeknames1)
    Result: ['Mon', 'Tue', 'Thu', 'Sun']
    
    Weekday_Sorted_Week(testweeknames2)
    Result: ['Monday', 'Tuesday', 'Friday', 'Saturday']
```
This function also handles lower and upper case and mixed case months and weekdays lists.
deepoc 1.1.4
A machine learning tool to classify complex datasets based on ontologies


# DeepOC

DeepOC is the core of [BioModel Classifier](https://bitbucket.org/biomodels/model-classifier/src/master/) - the python application to classify biomodels automatically using Deep Neural Network. DeepOC provides some very low level functions for classifying model based on ontology, which allow us to adapt to any other projects.

## Installing

    pip install deepoc

## Usage
First, you need a ground truth dataset, which is a dict of model and list of it's corresponding ontologies

    {
	    "model_1": ["GO:00001", "GO:00003", "GO:00002"],
	    "model_2: ["GO:00004", "GO:00002"]
    }
To generate dataset and train DNN model:

    ground_truth = ...
    train_file = "path/to/your train csv file"
    test_file = "path/to/your test csv file"
    val_file = "path/to/your val csv file"
    features = deepoc.build_features(ground_truth)

    # Picking the first 300 features  
    selected_features = [feature['feature'] for idx, feature in enumerate(features) if idx < 300]

    train, test, val = deepoc.generate_dataset(ground_truth, features, classes)

    # Writing dataset to file  
    deepoc.write_dataset_to_file(train, train_file)  
    deepoc.write_dataset_to_file(test, test_file)  
    deepoc.write_dataset_to_file(val, val_file)

    # Configure DNN model to use Gradient Descent optimizer, 1 hidden layer with 150 nodes, learning rate of 0.001 and dropout rate of 0.5
    classifier = DeepOCClassifier(workspace, 'GD', [150], 0.001, train_file, test_file, classes, 0.5)
    # Train the model with 3000 epoch, validate every 10 epochs and batch size of 16
    classifier.train_dll_model(3000, 10, 16)

    # Validate the result:
    for record in val:
	    model = record['model']
	    predict_result = classifier.predict(record)  
	    logger.info('Model %s: %s', model, predict_result)

More examples can be found in *tests* folder.

### Classify model based on any ontology other than Gene Ontology
To make this library work with other kind of ontology, implement the [OntologyService](https://bitbucket.org/biomodels/deepoc/src/master/deepoc/ontology/ontology_service.py) according to your ontology and instantize your object at [https://bitbucket.org/biomodels/deepoc/src/master/deepoc/ontology/__init__.py](https://bitbucket.org/biomodels/deepoc/src/master/deepoc/ontology/__init__.py) 

## Developers

-   [Vu Tu](https://bitbucket.org/vmtu)

## Contact

## Licensing

Biological Model Classifier source code is distributed under the GNU Affero General Public License.  
Please read  [license.txt](LICENSE)  for information on the software availability and distribution.