# NumPy - logspace() function

The NumPy logspace() function returns numbers spaced evenly on a log scale. The values are generated in the range [base ** start, base ** stop] with specified number of samples. The endpoint of the interval can optionally be excluded.

### Syntax

```numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None)
```

### Parameters

 `start` `Required. `Specify the starting value of the sequence. The starting value is base ** start. `stop` `Required. `Specify the end value of the sequence (end value is base ** end), unless endpoint is False. In that case, num + 1 values are spaced over the interval in log-space, of which all but the last (a sequence of length num) are returned. `num` `Optional. `Specify the number of samples to generate. Default is 50. Must be non-negative. `endpoint` `Optional. `Specify boolean value. If True, stop is the last sample. Otherwise, it is not included. Default is True. `base` `Optional. `Specify base of the log space. The step size between the elements in ln(samples) / ln(base) (or log_base(samples)) is uniform. Default is 10.0. `dtype` `Optional. `Specify type of the output array. If dtype is not given, infer the data type from the other input arguments.

### Return Value

Returns an array with elements within the specified range.

### Example: creating array using logspace() function

In the example below, logspace() function is used with different parameters to create arrays.

```import numpy as np

#creating 5 samples points in the given range
Arr1 = np.logspace(1,2,num=5)
print("Arr1 is:", Arr1)

#when endpoint=False, (num+1) samples are
#generated and returns samples without last
Arr2 = np.logspace(1,2,num=5,endpoint=False)
print("Arr2 is:", Arr2)

#using base=2.0
Arr3 = np.logspace(1,2,num=5,base=2.0)
print("Arr3 is:", Arr3)
```

The output of the above code will be:

```Arr1 is: [10.     17.7827941   31.6227766   56.23413252  100.       ]
Arr2 is: [10.     15.84893192  25.11886432  39.81071706  63.09573445]
Arr3 is: [2.      2.37841423   2.82842712   3.36358566   4.         ]
```

### Example: Visualize the sample

In the example below, arrays are created by taking endpoint parameter as True and False, and plotted using matplolib library to visualize the result.

```import numpy as np
import matplotlib.pyplot as plt

#creating 10 samples points using endpoint=True
Arr1 = np.logspace(1,2,num=10,endpoint=True)

#creating 10 samples using endpoint=True
Arr2 = np.logspace(1,2,num=10,endpoint=False)

y = np.zeros(10)

#plotting Arr1 and Arr2
plt.plot(Arr1, y+0.3, 'o')
plt.plot(Arr2, y+0.6, 'o')
plt.ylim([0,1])
plt.legend(labels = ('Arr1', 'Arr2'))
plt.show()
```

The output of the above code will be: ❮ NumPy - Functions

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