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version: 2.1 | ||
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orbs: | ||
# The python orb contains a set of prepackaged circleci configuration you can use repeatedly in your configurations files | ||
# Orb commands and jobs help you with common scripting around a language/tool | ||
# so you dont have to copy and paste it everywhere. | ||
# See the orb documentation here: https://circleci.com/developer/orbs/orb/circleci/python | ||
python: circleci/[email protected] | ||
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workflows: | ||
sample: # This is the name of the workflow, feel free to change it to better match your workflow. | ||
# Inside the workflow, you define the jobs you want to run. | ||
# For more details on extending your workflow, see the configuration docs: https://circleci.com/docs/2.0/configuration-reference/#workflows | ||
jobs: | ||
- build-and-test | ||
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jobs: | ||
build-and-test: # This is the name of the job, feel free to change it to better match what you're trying to do! | ||
# These next lines defines a docker executors: https://circleci.com/docs/2.0/executor-types/ | ||
# You can specify an image from dockerhub or use one of the convenience images from CircleCI's Developer Hub | ||
# A list of available CircleCI docker convenience images are available here: https://circleci.com/developer/images/image/cimg/python | ||
# The executor is the environment in which the steps below will be executed - below will use a python 3.9 container | ||
# Change the version below to your required version of python | ||
docker: | ||
- image: cimg/python:3.8 | ||
# Checkout the code as the first step. This is a dedicated CircleCI step. | ||
# The python orb's install-packages step will install the dependencies from a Pipfile via Pipenv by default. | ||
# Here we're making sure we use just use the system-wide pip. By default it uses the project root's requirements.txt. | ||
# Then run your tests! | ||
# CircleCI will report the results back to your VCS provider. | ||
environment: | ||
PYTHONPATH: /home/circleci/project | ||
steps: | ||
- checkout | ||
- python/install-packages: | ||
pkg-manager: pip | ||
# app-dir: ~/project/package-directory/ # If you're requirements.txt isn't in the root directory. | ||
pip-dependency-file: requirements.txt | ||
- run: | ||
name: Run tests | ||
# This assumes pytest is installed via the install-package step above | ||
command: pytest --cov --cov-report=html | ||
- store_artifacts: # store html coverage report as an artifact | ||
path: htmlcov | ||
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[report] | ||
exclude_lines = | ||
pragma: no cover | ||
if __name__ == .__main__.: | ||
pass | ||
\.\.\. | ||
raise NotImplementedError |
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rt-blocakge-manager | ||
[](https://circleci.com/gh/signetlabdei/rt-blocakge-manager) | ||
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Examples might need to import modules from other packages, e.g., `src/`. | ||
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One possibility to run examples is to append the root folder of the repository to the `PYTHONPATH` environment variable. | ||
For example: | ||
1. `cd` your terminal to the root folder of the repository | ||
1. Run the desired example as follows | ||
```bash | ||
PYTHONPATH=$PYTHONPATH:. python examples/your-example.py | ||
``` | ||
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A similar result can be obtained by exporting the updated `PYTHONPATH` to each newly opened terminal: | ||
1. `cd` your terminal to the root folder of the repository | ||
1. Add the current folder to the `PYTHONPATH` | ||
```bash | ||
export PYTHONPATH=$PYTHONPATH:. | ||
``` | ||
1. Run the desired example as follows | ||
```bash | ||
python examples/your-example.py | ||
``` | ||
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A further possibility is to setup your IDE to automatically export the root folder to the `PYTHONPATH`. | ||
For example, in VS Code it suffices to add `"env": {"PYTHONPATH": "${PYTHONPATH}:${workspaceFolder}"}` in the configuration contained in `.vscode/launch.json`. | ||
In some VS Code releases, it is also necessary to set `"terminal.integrated.env.<platform>": {"PYTHONPATH": "${workspaceFolder}"}` (where `<platform>` might be `windows`,`linux` or `osx`) in the settings file contained in `.vscode/settings.json`. |
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import functools | ||
import math | ||
from os import path | ||
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import src.utils as utils | ||
from src.diffraction_models import empirical_itu | ||
from src.environment import Environment, ObstacleInteraction | ||
from src.geometry import Point, Vector | ||
from src.mobility_model import ConstantVelocityMobilityModel as cvmm | ||
from src.obstacle import OrthoScreenObstacle | ||
from src.scenario import QdRealizationScenario | ||
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def main(): | ||
## Scenario params | ||
scenario_folder = "scenarios/HumanPresence" | ||
scenario_out = path.join(scenario_folder, "BlockageOut") | ||
obstacle_interactions = ObstacleInteraction.DIFFRACTION | ||
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scenario = QdRealizationScenario(scenario_folder) | ||
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## Obstacle params | ||
start_pos = Point(5, 0, 0) | ||
speed = 1.2 # [m/s] | ||
vel = Vector(0, speed, 0) | ||
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width = 0.4 # shoulder span [m] | ||
height = 1.7 # average human height [m] | ||
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distance_threshold = math.inf # [m] | ||
wavelength = utils.get_wavelength(scenario.get_frequency()) | ||
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# Setting up a diffraction loss model. The wavelength parameter is statically set to provide a function with the right signature to the obstacle | ||
diffraction_loss_model = functools.partial( | ||
empirical_itu, wavelength=wavelength) | ||
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mm = cvmm(start_pos=start_pos, vel=vel) | ||
obs = OrthoScreenObstacle(mm=mm, | ||
width=width, | ||
height=height, | ||
diffraction_loss_model=diffraction_loss_model, | ||
distance_threshold=distance_threshold) | ||
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## Setup and process | ||
env = Environment(scenario=scenario, | ||
obstacles=[obs], | ||
obstacle_interactions=obstacle_interactions) | ||
env.process() | ||
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out_scenario = env._scenario | ||
out_scenario.export(scenario_out, do_copy_unnecessary_files=True) | ||
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print(f"Processed scenario exported to '{path.abspath(scenario_out)}'") | ||
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if __name__ == "__main__": | ||
main() |
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# Tested with Python 3.8, 3.9 | ||
numpy~=1.21.4 | ||
pytest~=6.2.1 | ||
pytest-cov~=2.11.1 | ||
scipy~=1.5.3 |
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