If else statements in numpy arange-CodePudding

Basicaly I want to compare a variable between two np.arange()

x = 22.03
first = np.arange(18.5, 24.99, 0.01)
second = np.arange(25.0, 29.99, 0.01)

if x in first:
    print("x is in first")
elif x in second:
    print("x is in second")

I expect to see "x isin first" but rather I get nothing printed on the terminal. If I add another else: statement it will execute whatever is in that.

I am using numpy because I want to have a range of floats. The native range() function doesn't support floats

There happens no comparison between the two, why is that?

CodePudding user response：

Your array:

In [254]: first = np.arange(18.5, 24.99, 0.01)
In [255]: first.shape
Out[255]: (649,)
In [256]: first[:10]
Out[256]: 
array([18.5 , 18.51, 18.52, 18.53, 18.54, 18.55, 18.56, 18.57, 18.58,
       18.59])
In [257]: x=22.03

x isn't "found"

In [258]: x in first
Out[258]: False

Let's look for a close match:

In [259]: np.nonzero(np.isclose(x,first))
Out[259]: (array([353]),)
In [260]: first[353]
Out[260]: 22.030000000000552

The closest match is still a bit off - due to floating point calculations. 'in/equal' tests on floating point values are not reliable.

arange recommends linspace when using float steps. The resulting values are a closer match to our expectations:

In [264]: first1 = np.linspace(18.5,24.98,len(first))
In [265]: np.nonzero(np.isclose(x,first1))
Out[265]: (array([353]),)
In [266]: first1[353]
Out[266]: 22.03
In [267]: x in first1
Out[267]: True

There still is a potential for a float mismatch.

To better see the full precision of the floats, lets display the arrays as lists

In [268]: first[:10].tolist()
Out[268]: 
[18.5,
 18.51,
 18.520000000000003,
 18.530000000000005,
 18.540000000000006,
 18.550000000000008,
 18.56000000000001,
 18.57000000000001,
 18.580000000000013,
 18.590000000000014]
In [269]: first1[:10].tolist()
Out[269]: [18.5, 18.51, 18.52, 18.53, 18.54, 18.55, 18.56, 18.57, 18.58, 18.59]

CodePudding user response：

x = 22.03
first = np.arange(18.5, 24.99, 0.01)
second = np.arange(25.0, 29.99, 0.01)

type(first)
Out[13]: numpy.ndarray

# cast to list and proper value rounding for boolean comparison
first = [round(n, 2) for n in first]

x in first
Out[16]: True