df_firm["freq_ind"] = normind.tolist() 修正
时间: 2023-06-19 17:04:56 浏览: 40
修正建议:
如果您想将 `normind` 转换为列表并将其赋值给 `df_firm` 的 `freq_ind` 列,可以使用以下代码:
```python
df_firm["freq_ind"] = normind.values.tolist()
```
这将会将 `normind` 转换为一个包含所有元素的列表,并将其赋值给 `df_firm` 的 `freq_ind` 列。请注意,使用 `values` 属性是为了确保将 `normind` 转换为一个 Pandas Series 对象的值列表。
相关问题
case PM660_SUBTYPE: chip->chg.chg_param.smb_version = PM660_SUBTYPE; chip->chg.wa_flags |= BOOST_BACK_WA | OTG_WA | OV_IRQ_WA_BIT | TYPEC_PBS_WA_BIT; chg->param.freq_buck = pm660_params.freq_buck; chg->param.freq_boost = pm660_params.freq_boost; chg->chg_freq.freq_5V = 650; chg->chg_freq.freq_6V_8V = 850; chg->chg_freq.freq_9V = 1050; chg->chg_freq.freq_12V = 1200; chg->chg_freq.freq_removal = 1050; chg->chg_freq.freq_below_otg_threshold = 1600; chg->chg_freq.freq_above_otg_threshold = 800; break;代码分析
这段代码是在处理 PM660 芯片类型的充电参数。具体来说,它完成了以下操作:
1. 将 SMB 版本号设置为 PM660_SUBTYPE。
2. 开启一些工作模式和异常保护标志,包括 BOOST_BACK_WA、OTG_WA、OV_IRQ_WA_BIT 和 TYPEC_PBS_WA_BIT。
3. 设置一些频率参数,包括充电时的不同电压下的频率(chg_freq.freq_5V、chg_freq.freq_6V_8V、chg_freq.freq_9V、chg_freq.freq_12V),以及移除充电器时的频率(chg_freq.freq_removal)等。
4. 设置 chg_param.freq_buck 和 chg_param.freq_boost 参数,这些参数在 PM660 芯片类型中都是固定的。
这些参数的设置将影响 PM660 芯片的充电行为,从而保证充电的效率和安全性。
优化这段import numpy as np import matplotlib.pyplot as plt %config InlineBackend.figure_format='retina' def generate_signal(t_vec, A, phi, noise, freq): Omega = 2*np.pi*freq return A * np.sin(Omega*t_vec + phi) + noise * (2*np.random.random def lock_in_measurement(signal, t_vec, ref_freq): Omega = 2*np.pi*ref_freq ref_0 = 2*np.sin(Omega*t_vec) ref_1 = 2*np.cos(Omega*t_vec) # signal_0 = signal * ref_0 signal_1 = signal * ref_1 # X = np.mean(signal_0) Y = np.mean(signal_1) # A = np.sqrt(X**2+Y**2) phi = np.arctan2(Y,X) print("A=", A, "phi=", phi) # t_vec = np.linspace(0, 0.2, 1001) A = 1 phi = np.pi noise = 0.2 ref_freq = 17.77777 # signal = generate_signal(t_vec, A, phi, noise, ref_freq) # lock_in_measurement(signal, t_vec, ref_freq)
import numpy as np
import matplotlib.pyplot as plt
%config InlineBackend.figure_format='retina'
def generate_signal(t_vec, A, phi, noise, freq):
Omega = 2*np.pi*freq
return A * np.sin(Omega*t_vec + phi) + noise * (2*np.random.random)
def lock_in_measurement(signal, t_vec, ref_freq):
Omega = 2*np.pi*ref_freq
ref_0 = 2*np.sin(Omega*t_vec)
ref_1 = 2*np.cos(Omega*t_vec)
signal_0 = signal * ref_0
signal_1 = signal * ref_1
X = np.mean(signal_0)
Y = np.mean(signal_1)
A = np.sqrt(X**2+Y**2)
phi = np.arctan2(Y,X)
print("A=", A, "phi=", phi)
t_vec = np.linspace(0, 0.2, 1001)
A = 1
phi = np.pi
noise = 0.2
ref_freq = 17.77777
signal = generate_signal(t_vec, A, phi, noise, ref_freq)
lock_in_measurement(signal, t_vec, ref_freq)