pipeline complete 😎

Author: Exr0n

calculate.py

@@ -52,7 +52,7 @@ def SSE(indicies, prediction, logits, logits_error, function):
 def unwrap(datatable):
     return datatable.inches, datatable.normalized_count_rate.apply(lambda x:x.value), datatable.normalized_count_rate.apply(lambda x:x.delta)
 
-def sMinFit(datatable, function, param=1, lr=1e-4, epsilon=1e-8, epochs=100000):
+def sMinFit(datatable, function, param=1, lr=1e-4, epsilon=1e-8, epochs=int(1e4)):
     inches, logits, logits_err = unwrap(datatable)
     dydx = epsilon
 

drive.py

@@ -50,10 +50,18 @@ def plot(index):
 # =======
     # print(result.attrs["material"], result.predicted_halfthickness.apply(lambda row:row.value).mean())
 
-def process(indx):
-    t, smin = sMinFit(results[indx], RelativeIntersity, lr = 5e-4 if "tissue" == results[indx].attrs["material"] else 2e-8)
+def process(indx, ax=None):
+    t, smin = sMinFit(results[indx], RelativeIntersity, lr = 5e-4 if "tissue" == results[indx].attrs["material"] else 2e-7)
 
-    return [smin, t]
+    inches, logits, logits_err = unwrap(results[indx])
+    t_min, t_max = calculateSfitUncert(t, smin, smin+1, lambda T: SSE(inches, T, logits, logits_err, RelativeIntersity), ax=ax, low=0.1, high=30)
+
+    if ax is not None:
+        ax.set_xlabel(f"T ({results[7].attrs['material']})")
+        ax.set_ylabel("S(T)")
+        ax.legend()
+
+    return smin, t, t_min, t_max
 
 # if __name__ == '__main__':
     # with Pool(5) as p:
@@ -64,14 +72,6 @@ def process(indx):
 # >>>>>>> 68cb3cc3a83d6f09391e99a4e1cc04d712bebe16
 
 if __name__ == '__main__':
-    # plot(7)
     fig, ax = plt.subplots()
-    inches, logits, logits_err = unwrap(results[7])
-    param = 0.946
-    smin = 82
-    calculateSfitUncert(param, smin, smin+1, lambda T: SSE(inches, T, logits, logits_err, RelativeIntersity), ax=ax, low=0.1, high=30)
-
-    ax.set_xlabel(f"T ({results[7].attrs['material']})")
-    ax.set_ylabel("S(T)")
-    ax.legend()
+    print(process(7, ax))
     plt.show()