[Solved] You have a large 2D numpy array data that is a transpose of a contiguous array.... What is the best way to get a contiguous array without changing the data values? | NumPy

NumPy - Fundamentals

You have a large 2D numpy array data that is a transpose of a contiguous array. You want to speed up computations that require contiguous memory. What is the best way to get a contiguous array without changing the data values?

AUse <code>np.ascontiguousarray(data)</code> to get a contiguous array

BUse <code>data.copy(order='K')</code> to get a contiguous copy

CUse <code>data.T</code> again to reverse transpose

DUse <code>data.flatten()</code> to get a 1D contiguous array

Step-by-Step Solution

Solution:

Step 1: Understand transpose effect on contiguity
Transposing an array usually breaks contiguity because rows and columns swap.
Step 2: Choose method to get contiguous array without changing data
np.ascontiguousarray returns a contiguous array copy without changing data values.
Step 3: Evaluate other options
data.copy(order='K') preserves the original layout (F-contiguous), so flags['C_CONTIGUOUS'] remains False; data.T reverses transpose but changes shape; flatten() changes shape to 1D, which may not be desired.
Final Answer:
Use np.ascontiguousarray(data) to get a contiguous array -> Option A
Quick Check:
ascontiguousarray fixes contiguity efficiently [OK]

Quick Trick: Use np.ascontiguousarray to ensure contiguous copy [OK]

Common Mistakes:

Using data.copy(order='K') which preserves F-contiguity
Thinking transpose reverses contiguity
Using flatten() changes array shape unexpectedly

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What is the best way to get a contiguous array without changing the data values?

Step 1: Understand transpose effect on contiguity

Step 2: Choose method to get contiguous array without changing data

Step 3: Evaluate other options

Final Answer:

Quick Check:

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