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The N-dimensional array (ndarray)
{:.no_toc}
* TOC {:toc}The goal
Class has a very important job as a core container type in Python. It is really hard to find a good overview how to use them in a good practice manner.
Questions to David Rotermund
Chaining of (ndarray) methods
import numpy as np
a = np.ones((3, 3))
b = a.mean(axis=1).max()
print(b) # -> 1.0
numpy.ndarray.fill
ndarray.fill(value)
Fill the array with a scalar value.
import numpy as np
A = np.ones((3, 3))
A.fill(7)
print(A)
Output:
[[7. 7. 7.]
[7. 7. 7.]
[7. 7. 7.]]
numpy.ndarray.ndim
ndarray.ndim
Number of array dimensions.
import numpy as np
A = np.ones((3, 3))
print(A.ndim) # -> 2
numpy.ndarray.shape
ndarray.shape
Tuple of array dimensions.
import numpy as np
A = np.ones((3, 3))
print(A.shape) # -> (3, 3)
numpy.ndarray.size
ndarray.size
Number of elements in the array.
import numpy as np
A = np.ones((3, 3))
print(A.size) # -> 9
Array methods
Array conversion
| ndarray.item(*args) | Copy an element of an array to a standard Python scalar and return it. |
| ndarray.tolist() | Return the array as an a.ndim-levels deep nested list of Python scalars. |
| ndarray.itemset(*args) | Insert scalar into an array (scalar is cast to array's dtype, if possible) |
| ndarray.tostring([order]) | A compatibility alias for tobytes, with exactly the same behavior. |
| ndarray.tobytes([order]) | Construct Python bytes containing the raw data bytes in the array. |
| ndarray.tofile(fid[, sep, format]) | Write array to a file as text or binary (default). |
| ndarray.dump(file) | Dump a pickle of the array to the specified file. |
| ndarray.dumps() | Returns the pickle of the array as a string. |
| ndarray.astype(dtype[, order, casting, ...]) | Copy of the array, cast to a specified type. |
| ndarray.byteswap([inplace]) | Swap the bytes of the array elements |
| ndarray.copy([order]) | Return a copy of the array. |
| ndarray.view([dtype][, type]) | New view of array with the same data. |
| ndarray.getfield(dtype[, offset]) | Returns a field of the given array as a certain type. |
| ndarray.setflags([write, align, uic]) | Set array flags WRITEABLE, ALIGNED, WRITEBACKIFCOPY, respectively. |
| ndarray.fill(value) | Fill the array with a scalar value. |
Shape manipulation
| ndarray.reshape(shape[, order]) | Returns an array containing the same data with a new shape. |
| ndarray.resize(new_shape[, refcheck]) | Change shape and size of array in-place. |
| ndarray.transpose(*axes) | Returns a view of the array with axes transposed. |
| ndarray.swapaxes(axis1, axis2) | Return a view of the array with axis1 and axis2 interchanged. |
| ndarray.flatten([order]) | Return a copy of the array collapsed into one dimension. |
| ndarray.ravel([order]) | Return a flattened array. |
| ndarray.squeeze([axis]) | Remove axes of length one from a. |
Item selection and manipulation
| ndarray.take(indices[, axis, out, mode]) | Return an array formed from the elements of a at the given |
| ndarray.put(indices, values[, mode]) | Set a.flat[n] = values[n] for all n in indices. |
| ndarray.repeat(repeats[, axis]) | Repeat elements of an array. |
| ndarray.choose(choices[, out, mode]) | Use an index array to construct a new array from a set of choices. |
| ndarray.sort([axis, kind, order]) | Sort an array in-place. |
| ndarray.argsort([axis, kind, order]) | Returns the indices that would sort this array. |
| ndarray.partition(kth[, axis, kind, order]) | Rearranges the elements in the array in such a way that the value of the element in kth position is in the position it would be in a sorted array. |
| ndarray.argpartition(kth[, axis, kind, order]) | Returns the indices that would partition |
| ndarray.searchsorted(v[, side, sorter]) | Find indices where elements of v should be inserted in a to maintain order. |
| ndarray.nonzero() | Return the indices of the elements that are non-zero. |
| ndarray.compress(condition[, axis, out]) | Return selected slices of this array along given axis. |
| ndarray.diagonal([offset, axis1, axis2]) | Return specified diagonals. |
Calculation
| ndarray.max([axis, out, keepdims, initial, ...]) | Return the maximum along a given axis. |
| ndarray.argmax([axis, out, keepdims]) | Return indices of the maximum values along the given axis. |
| ndarray.min([axis, out, keepdims, initial, ...]) | Return the minimum along a given axis. |
| ndarray.argmin([axis, out, keepdims]) | Return indices of the minimum values along the given axis. |
| ndarray.ptp([axis, out, keepdims]) | Peak to peak (maximum - minimum) value along a given axis. |
| ndarray.clip([min, max, out]) | Return an array whose values are limited to [min, max]. |
| ndarray.conj() | Complex-conjugate all elements. |
| ndarray.round([decimals, out]) | Return a with each element rounded to the given number of decimals. |
| ndarray.trace([offset, axis1, axis2, dtype, out]) | Return the sum along diagonals of the array. |
| ndarray.sum([axis, dtype, out, keepdims, ...]) | Return the sum of the array elements over the given axis. |
| ndarray.cumsum([axis, dtype, out]) | Return the cumulative sum of the elements along the given axis. |
| ndarray.mean([axis, dtype, out, keepdims, where]) | Returns the average of the array elements along given axis. |
| ndarray.var([axis, dtype, out, ddof, ...]) | Returns the variance of the array elements, along given axis. |
| ndarray.std([axis, dtype, out, ddof, ...]) | Returns the standard deviation of the array elements along given axis. |
| ndarray.prod([axis, dtype, out, keepdims, ...]) | Return the product of the array elements over the given axis |
| ndarray.cumprod([axis, dtype, out]) | Return the cumulative product of the elements along the given axis. |
| ndarray.all([axis, out, keepdims, where]) | Returns True if all elements evaluate to True. |
| ndarray.any([axis, out, keepdims, where]) | Returns True if any of the elements of a evaluate to True. |
Arithmetic, matrix multiplication, and comparison operations
Each of the arithmetic operations (+, -, *, /, //, %, divmod(), ** or pow(), <<, >>, &, ^, |, ~) and the comparisons (==, <, >, <=, >=, !=) is equivalent to the corresponding universal function (or ufunc for short) in NumPy.
for in-place operations see here