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1. 删除未使用部分 2. 删除本地sqlite保存功能 3. 新增do_current多采集两条曲线 4. 优化耐久采集，修改最短间隔未30s

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gitea
2025-04-10 11:33:42 +08:00
parent 6e547ca6a3
commit 387618efb9
10 changed files with 258 additions and 40 deletions
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23
codes/autotest/do_current.py
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@ -67,7 +67,7 @@ class DoCurrentTest(QThread):
def single_axis_proc(self, records, number):
text = "single" if number < 6 else "hold"
number = number if number < 6 else number - 6
d_vel, d_trq, d_sensor, d_trans = [], [], [], []
d_vel, d_trq, d_sensor, d_trans, d_predict_trq, d_real_trq = [], [], [], [], [], []
for record in records:
data = eval(record[0])["data"]
for item in data:
@ -80,17 +80,24 @@ class DoCurrentTest(QThread):
d_sensor.extend(d_item)
elif item.get("channel", None) == number and item.get("name", None) == "hw_estimate_trans_trq_res":
d_trans.extend(d_item)
elif item.get("channel", None) == number and item.get("name", None) == "hw_predict_trq_res":
d_predict_trq.extend(d_item)
elif item.get("channel", None) == number and item.get("name", None) == "hw_real_trq_res":
d_real_trq.extend(d_item)
df1 = pandas.DataFrame.from_dict({"hw_joint_vel_feedback": d_vel})
df2 = pandas.DataFrame.from_dict({"device_servo_trq_feedback": d_trq})
df3 = pandas.DataFrame.from_dict({"hw_sensor_trq_feedback": d_sensor})
df4 = pandas.DataFrame.from_dict({"hw_estimate_trans_trq_res": d_trans})
df = pandas.concat([df1, df2, df3, df4], axis=1)
df5 = pandas.DataFrame.from_dict({"hw_predict_trq_res": d_predict_trq})
df6 = pandas.DataFrame.from_dict({"hw_real_trq_res": d_real_trq})
df = pandas.concat([df1, df2, df3, df4, df5, df6], axis=1)
filename = f"{self.dir_path}/single/j{number + 1}_{text}_{time.time()}.data"
df.to_csv(filename, sep="\t", index=False)
def scenario_proc(self, records, number, scenario_time):
d_vel, d_trq, d_sensor, d_trans = [[], [], [], [], [], []], [[], [], [], [], [], []], [[], [], [], [], [], []], [[], [], [], [], [], []]
# d_vel, d_trq, d_sensor, d_trans, d_predict_trq, d_real_trq = [[], [], [], [], [], []], [[], [], [], [], [], []], [[], [], [], [], [], []], [[], [], [], [], [], []], [[], [], [], [], [], []], [[], [], [], [], [], []]
d_vel, d_trq, d_sensor, d_trans, d_predict_trq, d_real_trq = [[[], [], [], [], [], []] for _ in range(6)]
for record in records:
data = eval(record[0])["data"]
for item in data:
@ -104,13 +111,19 @@ class DoCurrentTest(QThread):
d_sensor[axis].extend(d_item)
elif item.get("channel", None) == axis and item.get("name", None) == "hw_estimate_trans_trq_res":
d_trans[axis].extend(d_item)
elif item.get("channel", None) == number and item.get("name", None) == "hw_predict_trq_res":
d_predict_trq[axis].extend(d_item)
elif item.get("channel", None) == number and item.get("name", None) == "hw_real_trq_res":
d_real_trq[axis].extend(d_item)
for axis in range(6):
df1 = pandas.DataFrame.from_dict({"hw_joint_vel_feedback": d_vel[axis]})
df2 = pandas.DataFrame.from_dict({"device_servo_trq_feedback": d_trq[axis]})
df3 = pandas.DataFrame.from_dict({"hw_sensor_trq_feedback": d_sensor[axis]})
df4 = pandas.DataFrame.from_dict({"hw_estimate_trans_trq_res": d_trans[axis]})
df = pandas.concat([df1, df2, df3, df4], axis=1)
df5 = pandas.DataFrame.from_dict({"hw_predict_trq_res": d_predict_trq[axis]})
df6 = pandas.DataFrame.from_dict({"hw_real_trq_res": d_real_trq[axis]})
df = pandas.concat([df1, df2, df3, df4, df5, df6], axis=1)
filename = f"{self.dir_path}/s_{number-11}/j{axis+1}_s_{number-11}_{scenario_time}_{time.time()}.data"
df.to_csv(filename, sep="\t", index=False)
@ -139,7 +152,7 @@ class DoCurrentTest(QThread):
@staticmethod
def change_curve_state(stat):
curves = ["hw_joint_vel_feedback", "device_servo_trq_feedback", "hw_sensor_trq_feedback", "hw_estimate_trans_trq_res"]
curves = ["hw_joint_vel_feedback", "device_servo_trq_feedback", "hw_sensor_trq_feedback", "hw_estimate_trans_trq_res", "hw_predict_trq_res", "hw_real_trq_res"]
display_pdo_params = [] if not stat else [{"name": curve, "channel": chl} for curve in curves for chl in range(6)]
clibs.c_hr.execution("diagnosis.open", open=stat, display_open=stat)
clibs.c_hr.execution("diagnosis.set_params", display_pdo_params=display_pdo_params)