Python 用于分隔 numpy 数组的字典键和值
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Dictionary keys and values to separate numpy arrays
提问by VeilEclipse
I have a dictionary as
我有一本字典
Samples = {5.207403005022627: 0.69973543384229719, 6.8970222167794759: 0.080782939731898179, 7.8338517407140973: 0.10308033284258854, 8.5301143255505334: 0.018640838362318335, 10.418899728838058: 0.14427355015329846, 5.3983946820220501: 0.51319796560976771}
I want to separate the keysand valuesinto 2 numpyarrays.
I tried np.array(Samples.keys(),dtype=np.float)but i get an error TypeError: float() argument must be a string or a number
我想将keys和values分成2个numpy数组。我试过了，np.array(Samples.keys(),dtype=np.float)但出现错误TypeError: float() argument must be a string or a number
采纳答案by ankostis
You can use np.fromiterto directly create numpyarrays from the dictionary key and values views:
您可以使用从字典键和值视图np.fromiter直接创建numpy数组：
In python 3:
在python 3中：
keys = np.fromiter(Samples.keys(), dtype=float)
vals = np.fromiter(Samples.values(), dtype=float)
In python 2:
在蟒蛇 2 中：
keys = np.fromiter(Samples.iterkeys(), dtype=float)
vals = np.fromiter(Samples.itervalues(), dtype=float)
回答by 1478963
keys = np.array(dictionary.keys())
values = np.array(dictionary.values())
回答by A.J. Uppal
Just assign all of the values to a list, and then convert to a np.array().
只需将所有值分配给一个列表，然后转换为np.array().
import numpy as np
Samples = {5.207403005022627: 0.69973543384229719, 6.8970222167794759: 0.080782939731898179, 7.8338517407140973: 0.10308033284258854, 8.5301143255505334: 0.018640838362318335, 10.418899728838058: 0.14427355015329846, 5.3983946820220501: 0.51319796560976771}
keys = np.array(Samples.keys())
vals = np.array(Samples.values())
Or, if you want to iterate over it:
或者，如果你想迭代它：
import numpy as np
Samples = {5.207403005022627: 0.69973543384229719, 6.8970222167794759: 0.080782939731898179, 7.8338517407140973: 0.10308033284258854, 8.5301143255505334: 0.018640838362318335, 10.418899728838058: 0.14427355015329846, 5.3983946820220501: 0.51319796560976771}
keys = vals = []
for k, v in Samples.items():
keys.append(k)
vals.append(v)
keys = np.array(keys)
vals = np.array(vals)
回答by pratyaksh
On python 3.4, the following simply works:
在 python 3.4 上，以下简单有效：
Samples = {5.207403005022627: 0.69973543384229719, 6.8970222167794759: 0.080782939731898179, 7.8338517407140973: 0.10308033284258854, 8.5301143255505334: 0.018640838362318335, 10.418899728838058: 0.14427355015329846, 5.3983946820220501: 0.51319796560976771}
keys = np.array(list(Samples.keys()))
values = np.array(list(Samples.values()))
The reason np.array(Samples.values())doesn't give what you expect in Python 3 is that in Python 3, the values() method of a dict returns an iterable view, whereas in Python 2, it returns an actual list of the keys.
原因np.array(Samples.values())没有给出您在 Python 3 中所期望的内容，因为在 Python 3 中，dict 的 values() 方法返回一个可迭代视图，而在 Python 2 中，它返回一个实际的键列表。
keys = np.array(list(Samples.keys()))will actually work in Python 2.7 as well, and will make your code more version agnostic. But the extra call to list()will slow it down marginally.
keys = np.array(list(Samples.keys()))实际上也可以在 Python 2.7 中工作，并使您的代码与版本无关。但是额外的调用list()会稍微减慢它的速度。
回答by Hosana Gomes
In Python 3.7:
在 Python 3.7 中：
import numpy as np
Samples = {5.207403005022627: 0.69973543384229719, 6.8970222167794759: 0.080782939731898179, 7.8338517407140973: 0.10308033284258854, 8.5301143255505334: 0.018640838362318335, 10.418899728838058: 0.14427355015329846, 5.3983946820220501: 0.51319796560976771}
keys = np.array(list(Samples.keys()))
vals = np.array(list(Samples.values()))
Note: It's important to say that in this Python version dict.keys()and dict.values()return objects of type dict_keysand dict_values, respectively.
注：说在这个Python版本是很重要的dict.keys()，并dict.values()返回对象类型dict_keys和dict_values分别。
