failed multithread attempt + other fixes

Author: Exr0n

calculate.py

@@ -176,3 +176,4 @@ def bisect(low, high, target, function):
         ax.axvline(x=param_max, label=f"T_max = {param_max:.6f}", color='blue')
 
     return param_min, param_max
+

drive.py

@@ -60,7 +60,8 @@ def process(indx, ax=None):
     inches, logits, logits_err = unwrap(results[indx])
     cost_func = lambda T: SSE(inches, T, logits, logits_err, RelativeIntersity)
 
-    t, smin = sMinFit(cost_func, lr = 5e-4 if "tissue" == attrs['material'] else 2e-7)
+    # t, smin = sMinFit(cost_func, lr = 5e-4 if "tissue" == attrs['material'] else 2e-7)
+    t, smin = sMinFit(cost_func)
 
     # neighborhood = np.arange(0, 0.05, 1/1000)   # 200 evenly spaced points
     # ax.scatter(neighborhood, list(map(lambda T: SSE(inches, T, logits, logits_err, RelativeIntersity), neighborhood)), color='black', label='S(T)')
@@ -74,7 +75,7 @@ def process(indx, ax=None):
         ax.scatter(neighborhood, list(map(cost_func, neighborhood)), color='black', label='S(T)')
 
         ax.set_title(f"{attrs['material']} {attrs['source']}")
-        ax.set_xlabel(f"T ({results[7].attrs['material']})")
+        ax.set_xlabel(f"T ({attrs['material']})")
         ax.set_ylabel("S(T)")
         ax.legend()
 
@@ -88,8 +89,14 @@ def process(indx, ax=None):
 
 # >>>>>>> 68cb3cc3a83d6f09391e99a4e1cc04d712bebe16
 
+from concurrent.futures import ThreadPoolExecutor
+
 if __name__ == '__main__':
-    for i in range(0, 9):
-        fig, ax = plt.subplots()
-        print(process(i, ax))
-        plt.savefig(f"out/{i}_{results[i].attrs['material']}_{results[i].attrs['source']}.png")
+    with open('out/params.tsv', 'w+') as wf, ThreadPoolExecutor(max_workers=10) as exer:
+        # for i in range(0, 9):
+        #     fig, ax = plt.subplots()
+        #     wf.write('	'.join((results[i].attrs['material'], results[i].attrs['source'], *list(map(lambda x: str(x), process(i, ax))))) + '\n')
+        #     plt.savefig(f"out/{i}_{results[i].attrs['material']}_{results[i].attrs['source']}.png")
+        res = exer.map(process, range(0, 9))
+        print(res)
+