Im using the following code to scale values from one interval to another. "outputs_max", "outputs_min" are numpy arrays, so are (as a result) "slope" and "intercept".
For higher clarity when displaying the result "scaled_outputs", I used pandas to create a DataFrame of the file "out.npy" which I called "output_array". The resulting array "scaled_outputs" hence is displayed in a DataFrame too and later on stored as a numpy file.
import pandas as pd
import numpy as np
output_file = np.load("U:\\out.npy")
output_array = pd.DataFrame(output_file)
desired_upper_bound = 1
desired_lower_bound = 0
slope = (desired_upper_bound - desired_lower_bound) / (outputs_max - outputs_min)
intercept = desired_upper_bound - (slope * rounded_outputs_max)
scaled_outputs = slope * output_array + intercept
np.save("U:\\scaled_outputs.npy", scaled_outputs)
Am I losing accuracy of the values by creating a DataFrame and passing it into the equation? Would it be better to pass the numpy array "output_file" and creating a DataFrame of "scaled_outputs"?
The result in the console is displayed with 5 decimals at max, which is why I'm asking.
