Remove numpy data type

maro/cli/data_pipeline/citi_bike.py

@@ -8,7 +8,6 @@
 from enum import Enum
 
 import geopy.distance
-import numpy as np
 import pandas as pd
 from yaml import safe_load
 
@@ -320,7 +319,7 @@ def _process_distance(self, station_info: pd.DataFrame):
             0,
             index=station_info["station_index"],
             columns=station_info["station_index"],
-            dtype=np.float,
+            dtype=float,
         )
         look_up_df = station_info[["latitude", "longitude"]]
         return distance_adj.apply(
@@ -617,7 +616,7 @@ def _gen_distance(self, station_init: pd.DataFrame):
             0,
             index=station_init["station_index"],
             columns=station_init["station_index"],
-            dtype=np.float,
+            dtype=float,
         )
         look_up_df = station_init[["latitude", "longitude"]]
         distance_df = distance_adj.apply(

maro/rl/training/replay_memory.py

@@ -204,7 +204,7 @@ def __init__(
         self._states = np.zeros((self._capacity, self._state_dim), dtype=np.float32)
         self._actions = np.zeros((self._capacity, self._action_dim), dtype=np.float32)
         self._rewards = np.zeros(self._capacity, dtype=np.float32)
-        self._terminals = np.zeros(self._capacity, dtype=np.bool)
+        self._terminals = np.zeros(self._capacity, dtype=bool)
         self._next_states = np.zeros((self._capacity, self._state_dim), dtype=np.float32)
         self._returns = np.zeros(self._capacity, dtype=np.float32)
         self._advantages = np.zeros(self._capacity, dtype=np.float32)
@@ -373,7 +373,7 @@ def __init__(
         self._actions = [np.zeros((self._capacity, action_dim), dtype=np.float32) for action_dim in self._action_dims]
         self._rewards = [np.zeros(self._capacity, dtype=np.float32) for _ in range(self.agent_num)]
         self._next_states = np.zeros((self._capacity, self._state_dim), dtype=np.float32)
-        self._terminals = np.zeros(self._capacity, dtype=np.bool)
+        self._terminals = np.zeros(self._capacity, dtype=bool)
 
         assert len(agent_states_dims) == self.agent_num
         self._agent_states_dims = agent_states_dims

maro/streamit/client/metric.py

@@ -61,7 +61,7 @@ def is_float_type(v_type: type):
     Returns:
         bool: True if an float type.
     """
-    return v_type is float or v_type is np.float or v_type is np.float32 or v_type is np.float64
+    return v_type is float or v_type is np.float16 or v_type is np.float32 or v_type is np.float64
 
 
 def parse_value(value: object):

tests/requirements.test.txt

@@ -6,7 +6,7 @@ deepdiff>=5.7.0
 geopy>=2.0.0
 holidays>=0.10.3
 kubernetes>=21.7.0
-numpy>=1.19.5,<1.24.0
+numpy>=1.19.5
 pandas>=0.25.3
 paramiko>=2.9.2
 pytest>=7.1.2

tests/test_frame.py

@@ -311,7 +311,7 @@ def test_append_nodes(self):
         self.assertListEqual([0.0, 0.0, 0.0, 0.0, 9.0], list(states)[0:5])
 
         # 2 padding (NAN) in the end
-        self.assertTrue((states[-2:].astype(np.int) == 0).all())
+        self.assertTrue((states[-2:].astype(int) == 0).all())
 
         states = static_snapshot[1::"a3"]