288 lines
9.6 KiB
Markdown
288 lines
9.6 KiB
Markdown
# [The N-dimensional array (ndarray)](https://numpy.org/doc/stable/reference/arrays.ndarray.html)
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{:.no_toc}
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<nav markdown="1" class="toc-class">
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* TOC
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{:toc}
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</nav>
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## The goal
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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.
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Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
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## Chaining of (ndarray) methods
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```python
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import numpy as np
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a = np.ones((3, 3))
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b = a.mean(axis=1).max()
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print(b) # -> 1.0
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```
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## [numpy.ndarray.fill](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.fill.html)
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## [Array methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-methods)
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### [Array conversion](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-conversion)
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|[ndarray.item(*args)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html#numpy.ndarray.item)|Copy an element of an array to a standard Python scalar and return it.|
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|[ndarray.tolist()](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tolist.html#numpy.ndarray.tolist)|Return the array as an a.ndim-levels deep nested list of Python scalars.|
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|[ndarray.itemset(*args)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.itemset.html#numpy.ndarray.itemset)|Insert scalar into an array (scalar is cast to array's dtype, if possible)|
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|[ndarray.tostring([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tostring.html#numpy.ndarray.tostring)|A compatibility alias for tobytes, with exactly the same behavior.|
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|[ndarray.tobytes([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tobytes.html#numpy.ndarray.tobytes)|Construct Python bytes containing the raw data bytes in the array.|
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|[ndarray.tofile(fid[, sep, format])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tofile.html#numpy.ndarray.tofile)|Write array to a file as text or binary (default).|
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|[ndarray.dump(file)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dump.html#numpy.ndarray.dump)|Dump a pickle of the array to the specified file.|
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|[ndarray.dumps()](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dumps.html#numpy.ndarray.dumps)|Returns the pickle of the array as a string.|
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|[ndarray.astype(dtype[, order, casting, ...])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.astype.html#numpy.ndarray.astype)|Copy of the array, cast to a specified type.|
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|[ndarray.byteswap([inplace])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.byteswap.html#numpy.ndarray.byteswap)|Swap the bytes of the array elements|
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|[ndarray.copy([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.copy.html#numpy.ndarray.copy)|Return a copy of the array.|
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|[ndarray.view([dtype][, type])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.view.html#numpy.ndarray.view)|New view of array with the same data.|
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|[ndarray.getfield(dtype[, offset])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.getfield.html#numpy.ndarray.getfield)|Returns a field of the given array as a certain type.|
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|[ndarray.setflags([write, align, uic])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.setflags.html#numpy.ndarray.setflags)|Set array flags WRITEABLE, ALIGNED, WRITEBACKIFCOPY, respectively.|
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|[ndarray.fill(value)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.fill.html#numpy.ndarray.fill)|Fill the array with a scalar value.|
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### Shape manipulation
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|[ndarray.reshape(shape[, order])]()|
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Returns an array containing the same data with a new shape.
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|[ndarray.resize(new_shape[, refcheck])]()|
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Change shape and size of array in-place.
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|[ndarray.transpose(*axes)]()|
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Returns a view of the array with axes transposed.
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|[ndarray.swapaxes(axis1, axis2)]()|
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Return a view of the array with axis1 and axis2 interchanged.
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|[ndarray.flatten([order])]()|
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Return a copy of the array collapsed into one dimension.
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|[ndarray.ravel([order])]()|
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Return a flattened array.
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|[ndarray.squeeze([axis])]()|
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Remove axes of length one from a.
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### Item selection and manipulation
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|[ndarray.take(indices[, axis, out, mode])]()|
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Return an array formed from the elements of a at the given indices.
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|[ndarray.put(indices, values[, mode])]()|
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Set a.flat[n] = values[n] for all n in indices.
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|[ndarray.repeat(repeats[, axis])]()|
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Repeat elements of an array.
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|[ndarray.choose(choices[, out, mode])]()|
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Use an index array to construct a new array from a set of choices.
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|[ndarray.sort([axis, kind, order])]()|
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Sort an array in-place.
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|[ndarray.argsort([axis, kind, order])]()|
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Returns the indices that would sort this array.
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|[ndarray.partition(kth[, axis, kind, order])]()|
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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.
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|[ndarray.argpartition(kth[, axis, kind, order])]()|
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Returns the indices that would partition this array.
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|[ndarray.searchsorted(v[, side, sorter])]()|
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Find indices where elements of v should be inserted in a to maintain order.
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|[ndarray.nonzero()]()|
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Return the indices of the elements that are non-zero.
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|[ndarray.compress(condition[, axis, out])]()|
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Return selected slices of this array along given axis.
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|[ndarray.diagonal([offset, axis1, axis2])]()|
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Return specified diagonals.
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### [Calculation](https://numpy.org/doc/stable/reference/arrays.ndarray.html#calculation)
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|[ndarray.max([axis, out, keepdims, initial, ...])]()|
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Return the maximum along a given axis.
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|[ndarray.argmax([axis, out, keepdims])]()|
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Return indices of the maximum values along the given axis.
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|[ndarray.min([axis, out, keepdims, initial, ...])]()|
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Return the minimum along a given axis.
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|[ndarray.argmin([axis, out, keepdims])]()|
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Return indices of the minimum values along the given axis.
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|[ndarray.ptp([axis, out, keepdims])]()|
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Peak to peak (maximum - minimum) value along a given axis.
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|[ndarray.clip([min, max, out])]()|
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Return an array whose values are limited to [min, max].
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|[ndarray.conj()]()|
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Complex-conjugate all elements.
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|[ndarray.round([decimals, out])]()|
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Return a with each element rounded to the given number of decimals.
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|[ndarray.trace([offset, axis1, axis2, dtype, out])]()|
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Return the sum along diagonals of the array.
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|[ndarray.sum([axis, dtype, out, keepdims, ...])]()|
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Return the sum of the array elements over the given axis.
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|[ndarray.cumsum([axis, dtype, out])]()|
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Return the cumulative sum of the elements along the given axis.
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|[ndarray.mean([axis, dtype, out, keepdims, where])]()|
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Returns the average of the array elements along given axis.
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|[ndarray.var([axis, dtype, out, ddof, ...])]()|
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Returns the variance of the array elements, along given axis.
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|[ndarray.std([axis, dtype, out, ddof, ...])]()|
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Returns the standard deviation of the array elements along given axis.
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|[ndarray.prod([axis, dtype, out, keepdims, ...])]()|
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Return the product of the array elements over the given axis
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|[ndarray.cumprod([axis, dtype, out])]()|
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Return the cumulative product of the elements along the given axis.
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|[ndarray.all([axis, out, keepdims, where])]()|
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Returns True if all elements evaluate to True.
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|[ndarray.any([axis, out, keepdims, where])]()|
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Returns True if any of the elements of a evaluate to True.
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## [Arithmetic, matrix multiplication, and comparison operations](https://numpy.org/doc/stable/reference/arrays.ndarray.html#arithmetic-matrix-multiplication-and-comparison-operations)
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|[ndarray.\_\_lt\_\_(value, /)]()|
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Return self<value.
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|[ndarray.\_\_le\_\_(value, /)]()|
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Return self<=value.
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|[ndarray.\_\_gt\_\_(value, /)]()|
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Return self>value.
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|[ndarray.\_\_ge\_\_(value, /)]()|
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Return self>=value.
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|[ndarray.\_\_eq\_\_(value, /)]()|
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Return self==value.
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|[ndarray.\_\_ne\_\_(value, /)]()|
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Return self!=value.
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|[ndarray.\_\_bool\_\_(/)]()|
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True if self else False
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|[ndarray.\_\_neg\_\_(/)]()|
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-self
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|[ndarray.\_\_pos\_\_(/)]()|
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+self
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|[ndarray.\_\_abs\_\_(self)]()|
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|[ndarray.\_\_invert\_\_(/)]()|
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~self
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|[ndarray.\_\_add\_\_(value, /)]()|
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Return self+value.
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|[ndarray.\_\_sub\_\_(value, /)]()|
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Return self-value.
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|[ndarray.\_\_mul\_\_(value, /)]()|
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Return self*value.
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|[ndarray.\_\_truediv\_\_(value, /)]()|
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Return self/value.
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|[ndarray.\_\_floordiv\_\_(value, /)]()|
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Return self//value.
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|[ndarray.\_\_mod\_\_(value, /)]()|
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Return self%value.
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|[ndarray.\_\_divmod\_\_(value, /)]()|
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Return divmod(self, value).
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|[ndarray.\_\_pow\_\_(value[, mod])]()|
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Return pow(self, value, mod).
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|[ndarray.\_\_lshift\_\_(value, /)]()|
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Return self<<value.
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|[ndarray.\_\_rshift\_\_(value, /)]()|
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Return self>>value.
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|[ndarray.\_\_and\_\_(value, /)]()|
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Return self&value.
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|[ndarray.\_\_or\_\_(value, /)]()|
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Return self|value.
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|[ndarray.\_\_xor\_\_(value, /)]()|
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Return self^value.
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|[ndarray.\_\_iadd\_\_(value, /)]()|
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Return self+=value.
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|[ndarray.\_\_isub\_\_(value, /)]()|
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Return self-=value.
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|[ndarray.\_\_imul\_\_(value, /)]()|
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Return self*=value.
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|[ndarray.\_\_itruediv\_\_(value, /)]()|
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Return self/=value.
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|[ndarray.\_\_ifloordiv\_\_(value, /)]()|
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Return self//=value.
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|[ndarray.\_\_imod\_\_(value, /)]()|
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Return self%=value.
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|[ndarray.\_\_ipow\_\_(value, /)]()|
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Return self**=value.
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|[ndarray.\_\_ilshift\_\_(value, /)]()|
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Return self<<=value.
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|[ndarray.\_\_irshift\_\_(value, /)]()|
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Return self>>=value.
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|[ndarray.\_\_iand\_\_(value, /)]()|
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Return self&=value.
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|[ndarray.\_\_ior\_\_(value, /)]()|
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Return self|=value.
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|[ndarray.\_\_ixor\_\_(value, /)]()|
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Return self^=value.
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|[ndarray.\_\_matmul\_\_(value, /)]()|
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Return self@value.
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### [Special methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#special-methods)
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[special methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#special-methods)
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