Week 4 glossary

Week 4 glossary#

Online resources#

The official numpy documentations can be found at https://numpy.org/doc/stable/reference/index.html#reference. You may find the page of array creation routines (https://numpy.org/doc/stable/reference/routines.array-creation.html) and mathematical functions (https://numpy.org/doc/stable/reference/routines.math.html) especially useful.

Numpy syntax#

arithmetic#

  • +, -, *, /, //, %, **: vectorized arithmetic operators between 2 numpy arrays or between a numpy array and a scalar.

logical comparison#

  • ==, !=, <, >, <=, >=: vectorized comparison operators between 2 numpy arrays or between a numpy array and a scalar.

  • ~: vectorized negation on a numpy boolean array

  • &, |: vectorized “and” and “or” between two numpy boolean arrays

Array indexing#

  • []: indexing operator on numpy arrays

  • :: create basic slicing of the form start:stop:step

Numpy constants#

  • np.e: the natural / Euler / exponential number

  • np.pi: the number \(\pi\)

  • np.nan: the “not a number” value

Numpy array attributes#

  • <ndarray>.size: the size (number of entries) of a numpy array

  • <ndarray>.shape: the shape of a numpy array

  • <ndarray>.ndim: number of dimensions of the numpy array

Numpy functions#

Array creation#

  • np.array(): create an array from a python list

  • np.linspace(): create a linearly-spaced array of \(n\) elements from \(a\) to \(b\) (\(b\) inclusive)

  • np.arange(): create an evenly-spaced array from \(a\) to \(b\) (\(b\) exclusive) at steps of \(d\)

  • np.zeros(): create an array of zeros

  • np.ones(): create an array of ones

  • np.full(): create a constant array

  • np.concatenate(): concatenate two numpy arrays into one

Mapping functions#

  • np.sqrt(): square root

  • np.exp(): exponentiation

  • np.log(): natural logarithm

  • np.log10(): base-10 logarithm

  • np.log2(): base-2 logrithm

  • np.sin(), np.cos(), np.tan(): trigonometric functions

  • np.arcsin(), np.arccos(), np.arctan(): inverse trigonometric functions

  • np.arctan2(): arctangent function accepting both x and y as arguments

  • deg2rad(), rad2deg(): conversion between radians and degrees

  • np.round(): round values to fixed decimal point

  • np.floor(): round down to the nearest integer

  • np.ceil(): round up to the nearest integer

  • np.fabs(): absolute value

Reduction functions#

  • np.mean(): calculating average

  • np.var(): calculating variance

  • np.std(): calculating standard deviation

  • np.median(): calculating median

  • np.quantile(): calculating quantiles

  • np.prod(): product over elements

  • np.sum(): sum over elements

  • np.max(), np.min(): finding extremum value of an array

  • np.argmax(), np.argmin(): finding the index at which the extremum is attained

  • np.nanmean(), np.nanmedian(), np.nanvar(), np.nanstd(), np.nanmin(), np.nanmax(), np.nansum(): “nan-omitted” variation of the respective functions without the nan in their names

Other functions#

  • np.sort(): sort an array

  • np.argsort(): sort the index of an array by the corresponding values

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