## Disciplina
Disciplina is a mathematics module:
| Function Name | Args | Returns |
| --- | --- | --- |
| `isMathematicalFunction(mapping)` | `mapping`: A dictionary of sets representing the function | `True` if the mapping represents a function, `False` otherwise |
| `solveGraphically(f1, f2, x_range=(-10, 10), num_points=1000)` | `f1`: The first function to solve.<br> `f2`: The second function to solve.<br> `x_range`: The range of x values to plot.<br> `num_points`: The number of points to use in the plot. | A list of intersection points. |
| `solveOneVarEquation(equation)` | `equation`: The equation to solve. | The solution to the equation. |
| `sqrt(__x)` | `__x`: The number to calculate the square root of. | The square root of the number. |
| `rootOf(__x, num)` | `__x`: The number to calculate the nth root of.<br> `num`: The value of n. | The nth root of the number. |
| `isDivisible(x, num)` | `x`: The number to check.<br> `num`: The number to divide by. | `True` if x is divisible by num, `False` otherwise. |
| `normalize(value)` | `value`: The number to normalize. | The normalized number. |
## Acoustica
Acoustica is an acoustics module:
| Function | Arguments | Returns |
| -------- | --------- | ------- |
| `generateTone `| frequency: float, duration: float, vibrato_depth: float = 0.4, vibrato_rate: float = 5 | numpy.ndarray |
| `play` | notes: a list of tuples that contain the hertz and duration respectively | Plays the note |
| `getCarnaticHertz` | note: an str that represents the note | float or None |
| `getClassicalHertz` | note: an str the represents the note | float or None |
Raw data
{
"_id": null,
"home_page": "https://github.com/PyndyalaCoder/PyAlchemista",
"name": "PyAlchemista",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "",
"author": "Siddhu Pendyala",
"author_email": "elcientifico.pendyala@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/97/9e/2732cdb7f7224876dd06f67618f98bee396782425902065ef9a28377bef6/PyAlchemista-0.0.6.tar.gz",
"platform": null,
"description": "## Disciplina\nDisciplina is a mathematics module:\n| Function Name | Args | Returns |\n| --- | --- | --- |\n| `isMathematicalFunction(mapping)` | `mapping`: A dictionary of sets representing the function | `True` if the mapping represents a function, `False` otherwise |\n| `solveGraphically(f1, f2, x_range=(-10, 10), num_points=1000)` | `f1`: The first function to solve.<br> `f2`: The second function to solve.<br> `x_range`: The range of x values to plot.<br> `num_points`: The number of points to use in the plot. | A list of intersection points. |\n| `solveOneVarEquation(equation)` | `equation`: The equation to solve. | The solution to the equation. |\n| `sqrt(__x)` | `__x`: The number to calculate the square root of. | The square root of the number. |\n| `rootOf(__x, num)` | `__x`: The number to calculate the nth root of.<br> `num`: The value of n. | The nth root of the number. |\n| `isDivisible(x, num)` | `x`: The number to check.<br> `num`: The number to divide by. | `True` if x is divisible by num, `False` otherwise. |\n| `normalize(value)` | `value`: The number to normalize. | The normalized number. |\n\n\n## Acoustica\nAcoustica is an acoustics module:\n| Function | Arguments | Returns |\n| -------- | --------- | ------- |\n| `generateTone `| frequency: float, duration: float, vibrato_depth: float = 0.4, vibrato_rate: float = 5 | numpy.ndarray |\n| `play` | notes: a list of tuples that contain the hertz and duration respectively | Plays the note |\n| `getCarnaticHertz` | note: an str that represents the note | float or None |\n| `getClassicalHertz` | note: an str the represents the note | float or None |\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "A Python library that deals with different fields of science.",
"version": "0.0.6",
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "750acbe3019a59bf2364c331316f5bb96ea8f18ef2fbe773418d595b923e53a0",
"md5": "45bb5da685530a53a4fbc939cd22c14a",
"sha256": "02761b3217bb54babed47f523a9699b91907506148540cab194a97d5d4eaef94"
},
"downloads": -1,
"filename": "PyAlchemista-0.0.6-py3-none-any.whl",
"has_sig": false,
"md5_digest": "45bb5da685530a53a4fbc939cd22c14a",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 17138,
"upload_time": "2023-03-26T19:32:37",
"upload_time_iso_8601": "2023-03-26T19:32:37.946244Z",
"url": "https://files.pythonhosted.org/packages/75/0a/cbe3019a59bf2364c331316f5bb96ea8f18ef2fbe773418d595b923e53a0/PyAlchemista-0.0.6-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "979e2732cdb7f7224876dd06f67618f98bee396782425902065ef9a28377bef6",
"md5": "d0174d57ce12e5e759a003824c238e43",
"sha256": "55ca3dfea26baaf3566720a92a3952ff02159530887542bc47f75e894ca11989"
},
"downloads": -1,
"filename": "PyAlchemista-0.0.6.tar.gz",
"has_sig": false,
"md5_digest": "d0174d57ce12e5e759a003824c238e43",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 15266,
"upload_time": "2023-03-26T19:32:39",
"upload_time_iso_8601": "2023-03-26T19:32:39.534940Z",
"url": "https://files.pythonhosted.org/packages/97/9e/2732cdb7f7224876dd06f67618f98bee396782425902065ef9a28377bef6/PyAlchemista-0.0.6.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-03-26 19:32:39",
"github": true,
"gitlab": false,
"bitbucket": false,
"github_user": "PyndyalaCoder",
"github_project": "PyAlchemista",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "pyalchemista"
}