numpy array creating with a sequence
arrays, numpy, python, scipy, sequence
Solution
Well NumPy implements MATLAB's array-creation function, vector, using two functions instead of one--each implicitly specifies a particular axis along which concatenation ought to occur. These functions are:
r_ (row-wise concatenation) and
c_ (column-wise)
So for your example, the NumPy equivalent is:
>>> import numpy as NP
>>> v = NP.r_[.2, 1:10, 60.8]
>>> print(v)
[ 0.2 1. 2. 3. 4. 5. 6. 7. 8. 9. 60.8]
The column-wise counterpart is:
>>> NP.c_[.2, 1:10, 60.8]
slice notation works as expected [start:stop:step]:
>>> v = NP.r_[.2, 1:25:7, 60.8]
>>> v
array([ 0.2, 1. , 8. , 15. , 22. , 60.8])
Though if an imaginary number of used as the third argument, the slicing notation behaves like linspace:
>>> v = NP.r_[.2, 1:25:7j, 60.8]
>>> v
array([ 0.2, 1. , 5. , 9. , 13. , 17. , 21. , 25. , 60.8])
Otherwise, it behaves like arange:
>>> v = NP.r_[.2, 1:25:7, 60.8]
>>> v
array([ 0.2, 1. , 8. , 15. , 22. , 60.8])
Problem
I am on my transitional trip from MATLAB to scipy(+numpy)+matplotlib. I keep having issues when implementing some things. I want to create a simple vector array in three different parts. In MATLAB I would do something like: ``` vector=[0.2,1:60,60.8]; ``` This results in a one dimensional array of 62 positions. I'm trying to implement this using scipy. The closest I am right now is this: ``` a=[[0.2],linspace(1,60,60),[60.8]] ``` However this creates a list, not an array, and hence I cannot reshape it to a vector array. But then, when I do this, I get an error ``` a=array([[0.2],linspace(1,60,60),[60.8]]) ValueError: setting an array element with a sequence. ``` I believe my main obstacle is that I can't figure out how to translate this simple operation in MATLAB: ``` a=[1:2:20]; ``` to numpy. I know how to do it to access positions in an array, although not when creating a sequence. Any help will be appreciated, thanks!