From 6766184df8c2b1641da1b1b58ff7b89b5ef00475 Mon Sep 17 00:00:00 2001 From: David Rotermund <54365609+davrot@users.noreply.github.com> Date: Fri, 15 Dec 2023 00:19:20 +0100 Subject: [PATCH] Create README.md Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com> --- numpy/ndarray/README.md | 288 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 288 insertions(+) create mode 100644 numpy/ndarray/README.md diff --git a/numpy/ndarray/README.md b/numpy/ndarray/README.md new file mode 100644 index 0000000..d56358e --- /dev/null +++ b/numpy/ndarray/README.md @@ -0,0 +1,288 @@ +# [The N-dimensional array (ndarray)​](https://numpy.org/doc/stable/reference/arrays.ndarray.html) +{:.no_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](mailto:davrot@uni-bremen.de) + +## Chaining of (ndarray) methods​ + +```python +import numpy as np +a = np.ones((3, 3)) +b = a.mean(axis=1).max() +print(b) # -> 1.0 +``` + +## [numpy.ndarray.fill​](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.fill.html) + + + +## [Array methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-methods) + +### [Array conversion](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-conversion) + +||| +|---|---| +|[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.| +|[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.| +|[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)| +|[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.| +|[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.| +|[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).| +|[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.| +|[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.| +|[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.| +|[ndarray.byteswap([inplace])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.byteswap.html#numpy.ndarray.byteswap)|Swap the bytes of the array elements| +|[ndarray.copy([order])](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.copy.html#numpy.ndarray.copy)|Return a copy of the array.| +|[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.| +|[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.| +|[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.| +|[ndarray.fill(value)](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.fill.html#numpy.ndarray.fill)|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 indices. + +|[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 this array. + +|[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](https://numpy.org/doc/stable/reference/arrays.ndarray.html#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](https://numpy.org/doc/stable/reference/arrays.ndarray.html#arithmetic-matrix-multiplication-and-comparison-operations) + +|[ndarray.\_\_lt\_\_(value, /)]()| +Return selfvalue. + +|[ndarray.\_\_ge\_\_(value, /)]()| +Return self>=value. + +|[ndarray.\_\_eq\_\_(value, /)]()| +Return self==value. + +|[ndarray.\_\_ne\_\_(value, /)]()| +Return self!=value. + +|[ndarray.\_\_bool\_\_(/)]()| +True if self else False + +|[ndarray.\_\_neg\_\_(/)]()| +-self + +|[ndarray.\_\_pos\_\_(/)]()| ++self + +|[ndarray.\_\_abs\_\_(self)]()| + +|[ndarray.\_\_invert\_\_(/)]()| +~self + +|[ndarray.\_\_add\_\_(value, /)]()| +Return self+value. + +|[ndarray.\_\_sub\_\_(value, /)]()| +Return self-value. + +|[ndarray.\_\_mul\_\_(value, /)]()| +Return self*value. + +|[ndarray.\_\_truediv\_\_(value, /)]()| +Return self/value. + +|[ndarray.\_\_floordiv\_\_(value, /)]()| +Return self//value. + +|[ndarray.\_\_mod\_\_(value, /)]()| +Return self%value. + +|[ndarray.\_\_divmod\_\_(value, /)]()| +Return divmod(self, value). + +|[ndarray.\_\_pow\_\_(value[, mod])]()| +Return pow(self, value, mod). + +|[ndarray.\_\_lshift\_\_(value, /)]()| +Return self<>value. + +|[ndarray.\_\_and\_\_(value, /)]()| +Return self&value. + +|[ndarray.\_\_or\_\_(value, /)]()| +Return self|value. + +|[ndarray.\_\_xor\_\_(value, /)]()| +Return self^value. + +|[ndarray.\_\_iadd\_\_(value, /)]()| +Return self+=value. + +|[ndarray.\_\_isub\_\_(value, /)]()| +Return self-=value. + +|[ndarray.\_\_imul\_\_(value, /)]()| +Return self*=value. + +|[ndarray.\_\_itruediv\_\_(value, /)]()| +Return self/=value. + +|[ndarray.\_\_ifloordiv\_\_(value, /)]()| +Return self//=value. + +|[ndarray.\_\_imod\_\_(value, /)]()| +Return self%=value. + +|[ndarray.\_\_ipow\_\_(value, /)]()| +Return self**=value. + +|[ndarray.\_\_ilshift\_\_(value, /)]()| +Return self<<=value. + +|[ndarray.\_\_irshift\_\_(value, /)]()| +Return self>>=value. + +|[ndarray.\_\_iand\_\_(value, /)]()| +Return self&=value. + +|[ndarray.\_\_ior\_\_(value, /)]()| +Return self|=value. + +|[ndarray.\_\_ixor\_\_(value, /)]()| +Return self^=value. + +|[ndarray.\_\_matmul\_\_(value, /)]()| +Return self@value. + + +### [Special methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#special-methods) + +[special methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#special-methods) + + +