是否可以在一个numpy记录数组中别名多个名称?
假设我像这样构造一个numpy记录数组是否可以在一个numpy记录数组中别名多个名称?,numpy,Numpy,假设我像这样构造一个numpy记录数组 num_rows = <whatever> data = np.zeros( (num_rows,), dtype={ 'names':['apple', 'banana'], 'formats': ['f8', 'f8'] } 及 等等。 有办法给不同的名字取别名吗? 例如,我是否可以设置其他名称manzana data['manzana'] 是同一件事吗 data['apple']
num_rows = <whatever>
data = np.zeros(
(num_rows,),
dtype={
'names':['apple', 'banana'],
'formats': ['f8', 'f8']
}
及
等等。
有办法给不同的名字取别名吗?
例如,我是否可以设置其他名称manzana
data['manzana']
是同一件事吗
data['apple']
?[“偏移量”和“标题”是给字段赋予不同名称的两种机制] 有一个
offset
参数可以这样工作。通常,它用于将另一个字段拆分为多个部分(例如,将int拆分为字节)。但它也适用于相同的字段。实际上,它定义了几个具有重叠数据的字段
In [743]: dt=np.dtype({'names':['apple','manzana','banana','guineo'],
'formats':['f8','f8','f8','f8'],
'offsets':[0,0,8,8]})
In [745]: np.zeros((3,),dtype=dt)
Out[745]:
array([(0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 0.0, 0.0)],
dtype={'names':['apple','manzana','banana','guineo'],
'formats':['<f8','<f8','<f8','<f8'],
'offsets':[0,0,8,8], 'itemsize':16})
In [746]: A=np.zeros((3,),dtype=dt)
In [747]: A['banana']=[1,2,3]
In [748]: A
Out[748]:
array([(0.0, 0.0, 1.0, 1.0),
(0.0, 0.0, 2.0, 2.0),
(0.0, 0.0, 3.0, 3.0)],
dtype={'names':['apple','manzana','banana','guineo'], 'formats':['<f8','<f8','<f8','<f8'], 'offsets':[0,0,8,8], 'itemsize':16})
In [749]: A['guineo']
Out[749]: array([ 1., 2., 3.])
In [750]: A['manzana']=[.1,.2,.3]
In [751]: A['apple']
Out[751]: array([ 0.1, 0.2, 0.3])
In [752]: A
Out[752]:
array([(0.1, 0.1, 1.0, 1.0),
(0.2, 0.2, 2.0, 2.0),
(0.3, 0.3, 3.0, 3.0)],
dtype={'names':['apple','manzana','banana','guineo'], 'formats':['<f8','<f8','<f8','<f8'], 'offsets':[0,0,8,8], 'itemsize':16})
我已经将@hpaulj的答案放入了一个简单的方法中,并在这里分享,以防有人想使用它
def add_alias(arr, original, alias):
"""
Adds an alias to the field with the name original to the array arr.
Only one alias per field is allowed.
"""
if arr.dtype.names is None:
raise TypeError("arr must be a structured array. Use add_name instead.")
descr = arr.dtype.descr
try:
index = arr.dtype.names.index(original)
except ValueError:
raise ValueError("arr does not have a field named '" + str(original)
+ "'")
if type(descr[index][0]) is tuple:
raise ValueError("The field " + str(original) +
" already has an alias.")
descr[index] = ((alias, descr[index][0]), descr[index][1])
arr.dtype = np.dtype(descr)
return arr
def add_name(arr, name):
"""
Adds a name to the data of an unstructured array.
"""
if arr.dtype.names is not None:
raise TypeError("arr must not be a structured array. "
+ "Use add_alias instead.")
arr.dtype = np.dtype([(name, arr.dtype.name)])
return arr
我知道,但我不明白这里的细节。看起来
banana
和guineo
的偏移量为8。这是如何让苹果和manzana共享数据的?我可能遗漏了一些明显的东西。在相同的偏移量下,apple
和manzana
是共享数据的不同字段。但是我发现标题
更接近你对别名的理解。
In [743]: dt=np.dtype({'names':['apple','manzana','banana','guineo'],
'formats':['f8','f8','f8','f8'],
'offsets':[0,0,8,8]})
In [745]: np.zeros((3,),dtype=dt)
Out[745]:
array([(0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 0.0, 0.0), (0.0, 0.0, 0.0, 0.0)],
dtype={'names':['apple','manzana','banana','guineo'],
'formats':['<f8','<f8','<f8','<f8'],
'offsets':[0,0,8,8], 'itemsize':16})
In [746]: A=np.zeros((3,),dtype=dt)
In [747]: A['banana']=[1,2,3]
In [748]: A
Out[748]:
array([(0.0, 0.0, 1.0, 1.0),
(0.0, 0.0, 2.0, 2.0),
(0.0, 0.0, 3.0, 3.0)],
dtype={'names':['apple','manzana','banana','guineo'], 'formats':['<f8','<f8','<f8','<f8'], 'offsets':[0,0,8,8], 'itemsize':16})
In [749]: A['guineo']
Out[749]: array([ 1., 2., 3.])
In [750]: A['manzana']=[.1,.2,.3]
In [751]: A['apple']
Out[751]: array([ 0.1, 0.2, 0.3])
In [752]: A
Out[752]:
array([(0.1, 0.1, 1.0, 1.0),
(0.2, 0.2, 2.0, 2.0),
(0.3, 0.3, 3.0, 3.0)],
dtype={'names':['apple','manzana','banana','guineo'], 'formats':['<f8','<f8','<f8','<f8'], 'offsets':[0,0,8,8], 'itemsize':16})
In [792]: dt1=np.dtype({'names':['apple','banana'],'formats':['f8','f8'], 'titles':['manzana', 'guineo'], 'offsets':[0,8]})
In [793]: A1=np.zeros((3,),dtype=dt1)
In [794]: A1
Out[794]:
array([(0.0, 0.0), (0.0, 0.0), (0.0, 0.0)],
dtype=[(('manzana', 'apple'), '<f8'), (('guineo', 'banana'), '<f8')])
In [795]: A1['apple']=[1,2,3]
In [796]: A1['guineo']=[.1,.2,.3]
In [797]: A1
Out[797]:
array([(1.0, 0.1), (2.0, 0.2), (3.0, 0.3)],
dtype=[(('manzana', 'apple'), '<f8'), (('guineo', 'banana'), '<f8')])
In [798]: A1['banana']
Out[798]: array([ 0.1, 0.2, 0.3])
def add_alias(arr, original, alias):
"""
Adds an alias to the field with the name original to the array arr.
Only one alias per field is allowed.
"""
if arr.dtype.names is None:
raise TypeError("arr must be a structured array. Use add_name instead.")
descr = arr.dtype.descr
try:
index = arr.dtype.names.index(original)
except ValueError:
raise ValueError("arr does not have a field named '" + str(original)
+ "'")
if type(descr[index][0]) is tuple:
raise ValueError("The field " + str(original) +
" already has an alias.")
descr[index] = ((alias, descr[index][0]), descr[index][1])
arr.dtype = np.dtype(descr)
return arr
def add_name(arr, name):
"""
Adds a name to the data of an unstructured array.
"""
if arr.dtype.names is not None:
raise TypeError("arr must not be a structured array. "
+ "Use add_alias instead.")
arr.dtype = np.dtype([(name, arr.dtype.name)])
return arr