This is my package for plotting approximations

Installation:

pip install plot_yar

Description:

plot_yar.plot_approx(X_data, Y_data, input_function, plot_name='plot_name', plot_title='plot_title', 
x_label='x_label', y_label='y_label', Y_absolute_sigma = 0, scientific_view = True, print_cross = True, 
save_as_csv = False, to_latex = False, save_fig=True): 

Parameters:

• X_data: array_like.
  X-axis data

• Y_data: array_like.
  Y-axis data

• input_function: string.
  Approximation function.
  You could use template functions from dict or your own funcitons:

input_function = 'linear' 
fun_examples = {'linear':'a0*x+a1', 'poly_2':'a0*x**2+a1*x+a2', 'poly_3':'a0*x**3+a1*x**2+a2*x+a3',
'exp':'e^(a0*x+a1)+a2', 'ln':'ln(a0*x+a1)+a2'}

• plot_name: string.
  Name of your plot (picture)

• plot_title: string.
  Your plot title

• y_label: string.
  Y-axis label

• x_label: string.
  X-axis label

• Y_absolute_sigma: float or array_like.
  Absolute Y-axis data error

• scientific_view: bool. (default True)
  If True numbers will be written as $6.7 E + 01$ instead $670$

• print_cross: bool. (default True)
  Print crosses error or not?

• to_latex: bool. (default False)
  If True save table of estimated coeffs to latex table, you could use this package:

 \usepackage{booktabs}

• save_as_csv: bool. (default False)
  If True save table of estimated coeffs to csv table

• save_fig: bool. (default True)
  If True create a folder "pictures" and save plot to .png

Example:

• in:

from plot_yar import plot_approx
plot_approx([[1.1,2.5,3.2],[2,3,4]],[[2,3,5],[5,6,8]], 'linear')

• out:

Coeffs table 0: 

  coeffs  coeffs_values  standard error  relative se, %
0    a_0      1.327E+00       2.811E-01       2.119E+01
1    a_1      3.265E-01       1.659E+00       5.080E+02

Standart_error_Y_0 = 4.629E-01
Coeffs table 1: 

  coeffs  coeffs_values  standard error  relative se, %
0    a_0      1.500E+00       8.333E-02       5.556E+00
1    a_1      1.833E+00       8.056E-01       4.394E+01

Standart_error_Y_1 = 2.357E-01