markus/lib-paveit-demo
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remove print

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Markus Clauß
2023-06-28 09:03:13 +02:00
parent 04f5845ef1
commit 423ad74d23
1 changed files with 22 additions and 20 deletions
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src/paveit/postprocessing/citt.py
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@@ -54,17 +54,12 @@ def citt(task_id: str):
line_mod = lm.models.LinearModel() line_mod = lm.models.LinearModel()
out = line_mod.fit(data.stiffness, x=data.phase) out = line_mod.fit(data.stiffness, x=data.phase)
print(out.best_values)
Emax = line_mod.eval(out.params, x=0.0) Emax = line_mod.eval(out.params, x=0.0)
Emin = 0 Emin = 0
assert Emin < Emax assert Emin < Emax
print(data.head())
# Fit data # Fit data
mod = lm.models.Model(stiffness_tp26, independent_vars=['f','T']) mod = lm.models.Model(stiffness_tp26, independent_vars=['f','T'])
@@ -104,25 +99,32 @@ def citt(task_id: str):
## run fit ## run fit
results = [] results = []
r2 = [] r2 = []
try:
methods = ['leastsq', 'powell']
methods = ['leastsq', 'powell'] for method in methods:
result = mod.fit(data.stiffness, T=data.T_set, f=data.f_set, method=method, verbose=False)
r2temp = 1.0 - result.redchi / np.var(data.stiffness.values, ddof=2)
r2.append(r2temp)
for method in methods: results.append(result)
result = mod.fit(data.stiffness, T=data.T_set, f=data.f_set, method=method, verbose=False)
best = np.nanargmax(r2)
r2temp = 1.0 - result.redchi / np.var(data.stiffness.values, ddof=2) res = results[best].best_values
r2.append(r2temp) res['stat_r2'] = r2[best]
results.append(result) except:
print('error regression, send default values')
best = np.nanargmax(r2)
res = mod.valuesdict()
res = results[best].best_values
#add metadata
res['nsamples'] = len(data) res['nsamples'] = len(data)
res['task_id'] = task_id res['task_id'] = task_id
res['stat_r2'] = r2[best]
res['date'] = datetime.datetime.now() res['date'] = datetime.datetime.now()
print(res) print(res)