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On Wed, Oct 18, 2017 at 7:30 PM, Nissim Derdiger wrote:
> 3. difference between values are:
> [ 2.25699615e+02 5.51561475e-01 3.81394744e+00 1.03807904e-01]
> Instead of:
> [225.699615478515
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Today's Topics:
1. different values for ndarray when printed with or
Hi all,
I have a ndarray, that shows different values when called like that: print(arr)
or like that print(arr[0::]).
When changing it back to a python string (with list = arr.tolist()) - both
prints return same value, but when converting that list back to np array
(arr=np.array(list)) - the pri
[Numpy-discussion] converting list of int16 values to
bitmask and back to bitmask and back to list of int32\float values
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On 08/10/17 09:12, Nissim Derdiger wrote:
> Hi again,
>
Hi again,
I realize that my question was not clear enough, so I've refined it into one
runnable function (attached below)
My question is basically - is there a way to perform the same operation, but
faster using NumPy (or even just by using Python better..)
Thanks again and sorry for the unclearn
Hi all!
I'm writing a Modbus TCP client using pymodbus3 library.
When asking for some parameters, the response is always a list of int16.
In order to make the values usable, I need to transfer them into 32bit bites,
than put them in the correct order (big\little endian wise), and then to cast
the
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Today's Topics:
1. Compare NumPy arrays with threshold and return the
differences (Nissim D
Hi,
In my script, I need to compare big NumPy arrays (2D or 3D), and return a list
of all cells with difference bigger than a defined threshold.
The compare itself can be done easily done with "allclose" function, like that:
Threshold = 0.1
if (np.allclose(Arr1, Arr2, Threshold, equal_nan=True)):
