Package: hillfit
BackgroundTheHill equationis defined as follows:y = bottom + ((top - bottom) * xnH) / (EC50nH+ xnH)wherebottomis the minimum activity;topis maximum activity;EC50is the half-maximum effective dose; andnHis the Hill coefficient. The variablesx&yare the stimuli dose and the cellular or tissue response. Thehillfitmodule applies this biological equation, and is available with theMIT License.UsageinstallationThe following command are executed in a command prompt/terminal environment:pip install hillfit__init__The data environment, in aPython IDE, is defined:importhillfithf=hillfit.HillFit(x_data,y_data,bottom_param=True)x_data&y_datalistorndarray: specifies the x-values & y-values, respectively, of the raw data that will be fitted with the Hill equation.bottom_parambool: specifies whether the accessorybottomparameter 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: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)x_label&y_labelstr: 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.titlestr: specifies the title of the regression plot for the raw data points and the fitted Hill equation.sigfigsint: specifies the number ofsignificant figuresthat will be used in printed instances of the fitted Hill equation.log_xbool: specifies whether the x-axis of the regression plot will be converted into a logarithmic scale.generate_figure&view_figurebool: specifies whether the regression plot will be generated and printed in the Python environment, respectively.print_r_sqrbool: specifies whether the coefficient of determination (R2) regression plot will be printed in the Python environment.export_name&export_directorystr: optionally specifies the folder and the directory to where the contents folder will be exported, whereNonedesign a unique folder name for the information in the current working directory.figurebool: specifies whether a figure will be exported with the fitted content.curve_fit_kwsOptional[dict]: Keyword arguments to pass toscipy.optimize.curve_fit.Accessible contentMany data sets and exported components of the fitted information are accessible through thehillfitmodel object.top,bottom,ec50, &nHfloat: The fitted parameters of the Hill equation are accessible viahf.top,hf.bottom,hf.ec50, &hf.nH, respectively.R2float: The coefficient of determination of the regression figure is available viahf.r_2.fitted_xs&fitted_yslist: The x- and y-values of the fitted Hill equation are accessible viahf.x_fit&hf.y_fit, respectively.fitted_equationstr: The fitted Hill equation, in an amenable string format for theeval() built-in functionof Python that allows the user to directly execute the string as a function for an “x” variable, is accessible viahf.equation.figure&axmatplotlib.figure: Thefigandaxobjects of the regression figure are available viahf.figure&hf.ax, respectively. This allows users to edit the figures after the simulation is conducted.x_data&y_datandarray: The arrays of original data are available viahf.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:hf.export(export_directory=None,export_name=None,figure=True)export_name&export_directorystr: optionally specifies the folder and the directory to where the contents folder will be exported, whereNonedesign a unique folder name for the information in the current working directory.figurebool: specifies whether a figure will be exported with the fitted content.ExecutionHillfit is executed through the following example sequence of the aforementioned functions, which is exemplified in theexample Notebook of our GitHub repository:importhillfithf=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")