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analysis.py v 1.2.2.000

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Signed-off-by: Arthur Lu <learthurgo@gmail.com>
This commit is contained in:
Arthur Lu 2020-05-14 23:36:28 -05:00
parent 4c9e8eddaf
commit d83d56772d
1 changed files with 19 additions and 9 deletions
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26
analysis-master/analysis/analysis.py
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@ -7,10 +7,12 @@
# current benchmark of optimization: 1.33 times faster
# setup:
__version__ = "1.2.1.002"
__version__ = "1.2.2.000"
# changelog should be viewed using print(analysis.__changelog__)
__changelog__ = """changelog:
1.2.2.000:
- changed output of regressions to function strings instead of list of coefficients
1.2.1.002:
- renamed ArrayTest class to Array
1.2.1.001:
@ -412,7 +414,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
popt, pcov = scipy.optimize.curve_fit(lin, X, y)
regressions.append((popt.flatten().tolist(), None))
coeffs = popt.flatten().tolist()
regressions.append(str(coeffs[0]) + "*x+" + str(coeffs[1]))
except Exception as e:
@ -428,7 +431,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
popt, pcov = scipy.optimize.curve_fit(log, X, y)
regressions.append((popt.flatten().tolist(), None))
coeffs = popt.flatten().tolist()
regressions.append(str(coeffs[0]) + "*log(" + str(coeffs[1]) + "*(x+" + str(coeffs[2]) + "))+" + str(coeffs[3]))
except Exception as e:
@ -444,7 +448,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
popt, pcov = scipy.optimize.curve_fit(exp, X, y)
regressions.append((popt.flatten().tolist(), None))
coeffs = popt.flatten().tolist()
regressions.append(str(coeffs[0]) + "*e^(" + str(coeffs[1]) + "*(x+" + str(coeffs[2]) + "))+" + str(coeffs[3]))
except Exception as e:
@ -466,10 +471,14 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
params = model.steps[1][1].intercept_.tolist()
params = np.append(params, model.steps[1][1].coef_[0].tolist()[1::])
params.flatten()
params = params.tolist()
params = params.flatten().tolist()
plys.append(params)
temp = ""
counter = 0
for param in params:
temp += "(" + str(param) + "*x^" + str(counter) + ")"
counter += 1
plys.append(temp)
regressions.append(plys)
@ -483,7 +492,8 @@ def regression(inputs, outputs, args): # inputs, outputs expects N-D array
popt, pcov = scipy.optimize.curve_fit(sig, X, y)
regressions.append((popt.flatten().tolist(), None))
coeffs = popt.flatten().tolist()
regressions.append(str(coeffs[0]) + "*tanh(" + str(coeffs[1]) + "*(x+" + str(coeffs[2]) + "))+" + str(coeffs[3]))
except Exception as e: