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Background +++++++++++
The Hill equation <https://www.physiologyweb.com/calculators/hill_equation_interactive_graph.html>_ is defined as follows:
y = bottom + ((top - bottom) * x\ :sup:nH\ ) / (EC50\ :sup:nH\ + x\ :sup:nH)
where bottom is the minimum activity; top is maximum activity; EC50 is the half-maximum effective dose; and nH is the Hill coefficient. The variables x & y are the stimuli dose and the cellular or tissue response. The hillfit module applies this biological equation, and is available with the MIT License <https://opensource.org/licenses/MIT>_.
Usage ++++++
+++++++++++++ installation +++++++++++++
The following command are executed in a command prompt/terminal environment::
pip install hillfit
+++++++++++ init +++++++++++
The data environment, in a Python IDE <https://www.simplilearn.com/tutorials/python-tutorial/python-ide>_, is defined:
.. code-block:: python
import hillfit hf = hillfit.HillFit(x_data, y_data, bottom_param=True)
list or ndarray: specifies the x-values & y-values, respectively, of the raw data that will be fitted with the Hill equation.bool: specifies whether the accessory bottom parameter of the Hill equation will be employed in the regression.++++++++++++++++ fitting() ++++++++++++++++
The parameterized data is fitted to the Hill equation, with the following arguments and their default values:
.. code-block:: python
hf.fitting(x_label='x', y_label='y', title='Fitted Hill equation', sigfigs=6, log_x=False, print_r_sqr=True, generate_figure=True, view_figure=True, export_directory=None, export_name=None, figure=True, curve_fit_kws:Optional[dict]=None)
str: specifies the x-axis & y-axis labels, respectively, that will be applied to the regression plot for the raw data points and the fitted Hill equation.str: specifies the title of the regression plot for the raw data points and the fitted Hill equation.int: specifies the number of significant figures <https://en.wikipedia.org/wiki/Significant_figures>_ that will be used in printed instances of the fitted Hill equation.bool: specifies whether the x-axis of the regression plot will be converted into a logarithmic scale.bool: specifies whether the regression plot will be generated and printed in the Python environment, respectively.bool: specifies whether the coefficient of determination (R\ :sup:2) regression plot will be printed in the Python environment.str: optionally specifies the folder and the directory to where the contents folder will be exported, where None design a unique folder name for the information in the current working directory.bool: specifies whether a figure will be exported with the fitted content.Optional[dict]: Keyword arguments to pass to scipy.optimize.curve_fit <https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html>_.Many data sets and exported components of the fitted information are accessible through the hillfit model object.
float: The fitted parameters of the Hill equation are accessible via hf.top, hf.bottom, hf.ec50, & hf.nH, respectively.2\ float: The coefficient of determination of the regression figure is available via hf.r_2.list: The x- and y-values of the fitted Hill equation are accessible via hf.x_fit & hf.y_fit, respectively.str: The fitted Hill equation, in an amenable string format for the eval() built-in function <https://pythongeeks.org/python-eval-function/>_ of Python that allows the user to directly execute the string as a function for an "x" variable, is accessible via hf.equation.matplotlib.figure: The fig and ax objects of the regression figure are available via hf.figure & hf.ax, respectively. This allows users to edit the figures after the simulation is conducted.ndarray: The arrays of original data are available via hf.x_data & hf.y_data, respectively.++++++++++ export() ++++++++++
The fitted Hill equation, with its data points and parameters, and the regression information are exported to a designated folder through the following syntax and arguments:
.. code-block:: python
hf.export(export_directory=None, export_name=None, figure=True)
str: optionally specifies the folder and the directory to where the contents folder will be exported, where None design a unique folder name for the information in the current working directory.bool: specifies whether a figure will be exported with the fitted content.Execution +++++++++++
Hillfit is executed through the following example sequence of the aforementioned functions, which is exemplified in the example Notebook of our GitHub repository <./examples>_:
.. code-block:: python
import hillfit hf = hillfit.HillFit(x_data, y_data) hf.fitting(x_label='test_x', y_label='test_y', title='Fitted Hill equation', generate_figure=False, export_name="example_contents")