Feb-09-2018, 02:01 AM

i have been writing a python script for work that calculates some figures for me

it's basically two parts, one part is for when the data calls for a polynomial function, the other part is for when the data calls for an exponential function

for the polynomial functions, i've been using numpy polyfit to calcluate f(x) and f'(x), example code below

it's basically two parts, one part is for when the data calls for a polynomial function, the other part is for when the data calls for an exponential function

for the polynomial functions, i've been using numpy polyfit to calcluate f(x) and f'(x), example code below

x = np.array(expg[xtype]) # x-values y = np.array(expg[ytype]) # y-values py = np.polyfit(x,y, 2) # equation from x and y values py0 = np.polyder(np.poly1d(py)) # 1st derivative of function py print('Value at zero for first derivative of eq1',py0(0))is there something similar to polyfit for exponential functions? right now i'm using curve_fit, my code looks like this

x = np.array(expg[xtype]) # x-values y = np.array(expg[ytype]) #y-values def f(x, a, b, c): return a * np.exp(-b * x) + c paramsy, extrasy = curve_fit(f, x, y) # gives me the exponential function equation i'm looking for, i use this to make graphs later print('1st deriv value at 0', paramsy[0]*paramsy[1]) # basically i just do the chain rule here since i only need the value for f'(0)Is there a better way to find the first derivative of exponential functions? Ideally, something similar to polyfit