您可以使用numpy.append()
,但由于您还需要将新数据转换为记录数组:
import numpy as np
y = np.zeros(4,dtype=('a4,int32,float64'))
y = np.append(y, np.array([("0",7,24.5)], dtype=y.dtype))
由于 ndarray 不能动态改变它的大小,当你想追加一些新数据时,你需要复制所有数据。您可以创建一个减少调整大小频率的类:
import numpy as np
class DynamicRecArray(object):
def __init__(self, dtype):
self.dtype = np.dtype(dtype)
self.length = 0
self.size = 10
self._data = np.empty(self.size, dtype=self.dtype)
def __len__(self):
return self.length
def append(self, rec):
if self.length == self.size:
self.size = int(1.5*self.size)
self._data = np.resize(self._data, self.size)
self._data[self.length] = rec
self.length += 1
def extend(self, recs):
for rec in recs:
self.append(rec)
@property
def data(self):
return self._data[:self.length]
y = DynamicRecArray(('a4,int32,float64'))
y.extend([("xyz", 12, 3.2), ("abc", 100, 0.2)])
y.append(("123", 1000, 0))
print y.data
for i in xrange(100):
y.append((str(i), i, i+0.1))