def integer_label_protein(sequence, max_length=1200): encoding = np.zeros(max_length) for idx, letter in enumerate(sequence[:max_length]): try: letter = letter.upper() encoding[idx] = CHARPROTSET[letter] except KeyError: logging.warning( f"character {letter} does not exists in sequence category encoding, skip and treat as " f"padding." ) return encoding什么意思
时间: 2023-05-11 10:01:48 浏览: 67
这是一个用于将蛋白质序列转换为整数标签的函数,其中输入参数为蛋白质序列和最大长度。函数会将蛋白质序列中的每个字母转换为对应的整数标签,并将其存储在一个长度为最大长度的数组中返回。如果蛋白质序列中的字母不在预定义的字符集中,则会被视为填充字符。
相关问题
class TimeWindowSequence(Sequence): def __init__(self, x, y, batch_size, window_size): self.x = x self.y = y self.batch_size = batch_size self.window_size = window_size self.window_count = int(np.ceil(x.shape[0] / window_size)) def __len__(self): return int(np.ceil(self.x.shape[0] / self.batch_size)) def __getitem__(self, idx): batch_x = np.zeros((self.batch_size, self.window_size, self.x.shape[1])) batch_y = np.zeros((self.batch_size, self.y.shape[1])) for i in range(self.batch_size): j = idx * self.batch_size + i if j >= self.window_count: break window_x = self.x[j*self.window_size:(j+1)*self.window_size, :] window_y = self.y[j*self.window_size:(j+1)*self.window_size, :] batch_x[i, :window_x.shape[0], :] = window_x batch_y[i, :] = window_y[-1, :] return batch_x, batch_y出现
这段代码中似乎缺少了一个缩进,导致 `return` 语句在 `for` 循环内部。可以尝试将 `return` 语句缩进到 `for` 循环外部,如下所示:
```
class TimeWindowSequence(Sequence):
def __init__(self, x, y, batch_size, window_size):
self.x = x
self.y = y
self.batch_size = batch_size
self.window_size = window_size
self.window_count = int(np.ceil(x.shape[0] / window_size))
def __len__(self):
return int(np.ceil(self.x.shape[0] / self.batch_size))
def __getitem__(self, idx):
batch_x = np.zeros((self.batch_size, self.window_size, self.x.shape[1]))
batch_y = np.zeros((self.batch_size, self.y.shape[1]))
for i in range(self.batch_size):
j = idx * self.batch_size + i
if j >= self.window_count:
break
window_x = self.x[j*self.window_size:(j+1)*self.window_size, :]
window_y = self.y[j*self.window_size:(j+1)*self.window_size, :]
batch_x[i, :window_x.shape[0], :] = window_x
batch_y[i, :] = window_y[-1, :]
return batch_x, batch_y
```
这样应该就可以解决这个问题了。
pad_packed_sequence(sequence = output_packed, batch_first = True, padding_value=self.config.pad_idx, total_length = seq_lens.max())
这段代码是什么意思?
这段代码是将经过PackedSequence打包的RNN的输出进行解包,返回一个元组(output, lengths),其中output是解包后的输出张量,lengths是一个包含每个序列的实际长度的张量。其中,sequence是经过PackedSequence打包后的张量,batch_first表示是否将batch_size放在第一维,padding_value表示填充的值,total_length表示序列的总长度,seq_lens.max()表示序列中最长的长度。
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