Fix nas estatísticas

utilsv2/stats.py

@@ -1,4 +1,5 @@
 import time
+from datetime import datetime
 
 import numpy as np
 from pymongo import MongoClient
@@ -10,35 +11,52 @@ def print_filters(filters):
         _res += f"{k}: {v}\n"
 
 
-def calculate_stats(data: list, filters):
-    _stats_txt = "Estatísticas\n"
-    _stats_txt += f"Número de eventos: {len(data)}\n"
-    _res = calc_mag(data)
-    _stats_txt += f"Magnitudes:\n\tMédia: {_res[0]} \u00b1 {_res[1]}\n\tMediana: {_res[2]}\n\tValor Mínimo: {_res[3]}\n\tValor Máximo: {_res[4]}\n"
-    _res = calc_depth(data)
-    _stats_txt += f"\nProfundidade:\n\tMédia: {_res[0]} \u00b1 {_res[1]}\n\tMediana: {_res[2]}\n\tValor Mínimo: {_res[3]}\n\tValor Máximo: {_res[4]}\n"
+def pprint(v):
+    return f"\tMédia: {v[0]} \u00b1 {v[1]}; Mediana: {v[2]}; Máximo: {v[4]}; Mínimo: {v[3]}"
+
+
+def stats(data):
+    _stats = f"===Estatística==\nNúmero total de eventos: {len(data)}\n"
+    aux = []
+    currMonth: datetime = data[0]["DateTime"]
+    idx = 0
+    while idx < len(data):
+        if data[idx]["DateTime"].month == currMonth.month:
+            aux.append(data[idx])
+            idx += 1
+        else:
+            m = calc_mag(aux)
+            d = calc_depth(aux)
+            aux = []
+            _stats += f"{currMonth.strftime('%Y-%m')}:\n\tMagnitude: {pprint(m)}\n\tProfundidade: {pprint(d)}\n"
+            currMonth = data[idx]["DateTime"]
+
+    m = calc_mag(aux)
+    d = calc_depth(aux)
+    _stats += f"{currMonth.strftime('%Y-%m')}:\nMagnitude: {pprint(m)}\nProfundidade: {pprint(d)}\n"
 
     fname = f"stats-{time.time_ns()}.txt"
     with open(fname, "wb") as fp:
-        fp.write(_stats_txt.encode("utf-8"))
+        fp.write(_stats.encode("utf-8"))
 
-    print(_stats_txt)
-
-
-def get_data(client: MongoClient):
-    pass
+    # print(_stats)
 
 
 def calc_depth(data):
     if len(data) == 0:
         return 0
     depths = np.array([v["Depth"] for v in data], dtype=float)
-    return (
-        np.average(depths),
-        np.std(depths),
-        np.median(depths),
-        np.min(depths),
-        np.max(depths),
+    return list(
+        map(
+            float,
+            (
+                round(np.average(depths), 3),
+                round(np.std(depths), 3),
+                round(np.median(depths), 3),
+                np.min(depths),
+                np.max(depths),
+            ),
+        )
     )
 
 
@@ -46,4 +64,15 @@ def calc_mag(data):
     if len(data) == 0:
         return 0
     mags = np.array([v["Magnitudes"]["L"]["Magnitude"] for v in data], dtype=float)
-    return (np.average(mags), np.std(mags), np.median(mags), np.min(mags), np.max(mags))
+    return list(
+        map(
+            float,
+            (
+                round(np.average(mags), 3),
+                round(np.std(mags), 3),
+                round(np.median(mags), 3),
+                np.min(mags),
+                np.max(mags),
+            ),
+        )
+    )