fix OverflowError: (34, "Result too large") problem
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@ -233,7 +233,7 @@ def get_durable_data(path, config_file, data, scenario_time, hr, w2t):
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if len(_d2d_trq['device_servo_trq_feedback_0']) / 1000 > scenario_time + 1:
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_df = pd.DataFrame(_d2d_trq)
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for i in range(6):
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_ = sqrt(_df[f'device_servo_trq_feedback_{i}'].apply(lambda x: (rcs[i]*x/1000)**2).sum()/len(_df[f'device_servo_trq_feedback_{i}']))
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_ = sqrt(100*_df[f'device_servo_trq_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'device_servo_trq_feedback_{i}']))
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del data[0][f"axis{i + 1}"][0]
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data[0][f"axis{i + 1}"].append(_)
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_df = pd.DataFrame(data[0])
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@ -248,7 +248,7 @@ def get_durable_data(path, config_file, data, scenario_time, hr, w2t):
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_df = pd.DataFrame(_d2d_vel)
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for i in range(6):
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_ = sqrt(_df[f'hw_joint_vel_feedback_{i}'].apply(lambda x: (rcs[i]*x/1000)**2).sum()/len(_df[f'hw_joint_vel_feedback_{i}']))
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_ = sqrt(100*_df[f'hw_joint_vel_feedback_{i}'].apply(lambda x: (rcs[i]*x/10000)**2).sum()/len(_df[f'hw_joint_vel_feedback_{i}']))
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del data[1][f"axis{i + 1}"][0]
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data[1][f"axis{i + 1}"].append(_)
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_df = pd.DataFrame(data[1])
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