Using lgtm.com and fixing found alerts (#1452)

* lgtm in readme, and mac nui fixes

* call super inits in radars

* unused imports, dup lines

* more radars, more unused imports

* pass CP into RadarInterfaceBase

* more fixups

* unused imports

* delete unused lines

* ugh, new unused import

Co-authored-by: George Hotz <geohot@gmail.com>

selfdrive/debug/internal/measure_steering_accuracy.py

@@ -2,8 +2,7 @@
 import os
 import argparse
 import signal
-from collections import deque, defaultdict
-from statistics import mean
+from collections import defaultdict
 
 import cereal.messaging as messaging
 

selfdrive/debug/internal/measure_torque_time_to_max.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python3
 import os
-import sys
 import argparse
 import struct
 from collections import deque
@@ -8,7 +7,6 @@ from statistics import mean
 
 from cereal import log
 import cereal.messaging as messaging
-from cereal.services import service_list
 
 if __name__ == "__main__":
 

selfdrive/debug/mpc/tune_longitudinal.py

@@ -3,7 +3,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 from selfdrive.controls.lib.longitudinal_mpc import libmpc_py
 from selfdrive.controls.lib.drive_helpers import MPC_COST_LONG
-import math
 
 # plot liongitudinal MPC trajectory by defining boundary conditions:
 # ego and lead vehicles state. Use this script to tune MPC costs
@@ -16,7 +15,7 @@ def RW(v_ego, v_l):
 
 def NORM_RW_ERROR(v_ego, v_l, p):
     return (RW(v_ego, v_l) + 4.0 - p)
-    return (RW(v_ego, v_l) + 4.0 - p) / (np.sqrt(v_ego + 0.5) + 0.1)
+    #return (RW(v_ego, v_l) + 4.0 - p) / (np.sqrt(v_ego + 0.5) + 0.1)
 
 
 v_ego = 20.0
@@ -36,7 +35,7 @@ a_lead_tau = 0.
 
 # a_lead_tau = 2.90729817665
 
-min_a_lead_tau = (a_lead**2 * math.pi) / (2 * (v_lead + 0.01)**2)
+#min_a_lead_tau = (a_lead**2 * math.pi) / (2 * (v_lead + 0.01)**2)
 min_a_lead_tau = 0.0
 
 print(a_lead_tau, min_a_lead_tau)

selfdrive/debug/tuner.py

@@ -1,67 +0,0 @@
-#!/usr/bin/env python3
-"""
-This tool can be used to quickly changes the values in a JSON file used for tuning
-Keys like in vim:
- - h: decrease by 0.05
- - l: increase by 0.05
- - k: move pointer up
- - j: move pointer down
-"""
-
-import tty
-import sys
-import json
-import termios
-from collections import OrderedDict
-
-FILENAME = '/data/tuning.json'
-
-def read_tuning():
-  while True:
-    try:
-      return json.loads(open(FILENAME).read())
-    except:
-      pass
-
-def main():
-  dat = json.loads(open(FILENAME, 'r').read())
-  dat = OrderedDict(sorted(dat.items(), key=lambda i: i[0]))
-
-  cur = 0
-  while True:
-    sys.stdout.write("\x1Bc")
-
-    for i, (k, v) in enumerate(dat.items()):
-      prefix = "> " if cur == i else "  "
-      print((prefix + k).ljust(20) + "%.2f" % v)
-
-    key = sys.stdin.read(1)[0]
-
-    write = False
-    if key == "k":
-      cur = max(0, cur - 1)
-    elif key == "j":
-      cur = min(len(dat.keys()) - 1, cur + 1)
-    elif key == "l":
-      dat[dat.keys()[cur]] += 0.05
-      write = True
-    elif key == "h":
-      dat[dat.keys()[cur]] -= 0.05
-      write = True
-    elif key == "q":
-      break
-
-    if write:
-      open(FILENAME, 'w').write(json.dumps(dat))
-
-
-if __name__ == "__main__":
-  orig_settings = termios.tcgetattr(sys.stdin)
-  tty.setcbreak(sys.stdin)
-
-  try:
-    main()
-    termios.tcsetattr(sys.stdin, termios.TCSADRAIN, orig_settings)
-  except:
-    termios.tcsetattr(sys.stdin, termios.TCSADRAIN, orig_settings)
-    raise