## Record Arrays numpyrec

NumPy provides a powerful data-type object that allows any ndarray to hold (arbitrarily nested) record-like items with named-field access to the sub-types. This is possible without any special record-array sub-class. Consider the example where each item in the array is a simple record of name, age, and weight. You could specify a data-type for an array of such records using the following data-type object > > > desc dtype( 'names' 'name', 'age', 'weight' , 'fo > > > a array(...

## Trigonometric functions

All trigonometric functions use radians when an angle is called for. The ratio of degrees to radians is 180 n. sin x , y cos x , y tan x , y The standard trignometric functions. y sin x , y cos x , and y tan x . arcsin x , y arccos x , y arctan x , y The inverse trigonometric functions y sin-1 x , y cos-1 x , y tan-1 x . These return the value of y in radians such that sin y x with y G f cos y x with y 0,7r and tan y x with y f, f , respectively. Returns tan-1 f but takes into account the sign...

## Array conversion tolist

The contents of self as a nested list. gt gt gt a array 1,2,3 , 4,5,6 print a.tolist 1, 2, 3 , 4, 5, 6 If no arguments are passed in, then this method only works for arrays with one element a.size 1 . In this case, it returns a standard Python scalar object if possible copied from the first element of self. When the data type of self is longdouble or clongdouble, this returns a scalar array object because there is no available Python scalar that would not lose information. Void arrays return a...

## Shape functions

Force a sequence of arrays including array scalars to each be at least 1-d. Force a sequence of arrays including array scalars to each be at least 2-d. Dimensions of length 1 are pre-pended to reach a two-dimensional array. Force a sequence of arrays including array .scalars to each be at least 3-d. Dimensions of length 1 are pre-pended to reach a two-dimensional array. Return a new array with the contents of arr shifted rolled by the amount given in the integer argument shift along the axis...

## Basic indexing slicing

Indexing is a powerful tool in Python and NumPy takes full advantage of this power. In fact, some of capabilities of Python's indexing were first established by the needs of Numeric users.2 Indexing is also sometimes called slicing in Python, and slicing for an ndarray works very similarly as it does for other Python sequences. There are three big differences 1 slicing can be done over multiple dimensions, 2 exactly one ellipsis object can be used to indicate several dimensions at once, 3...

## Array construction using index tricks

The functions and classes in this category make it simpler to construct arrays. This indexing cross function is useful for forming indexing arrays necessary to select out the cross-product of N 1-dimensional arrays. Note that the default indexing does not do a cross-product which might be unexpected for someone coming from other programming environments . The default indexing is more general purpose. Using the ix_ constructor can produce the indexing arrays necessary to select a cross-product....

## Continuous Distributions

Continuous random numbers can take on an uncountable number of values. Therefore, the value returned by a continuous distribution is denoted x. Because there is an uncountable number of possibilities for the random number1, a continuous distribution is modeled by a probability density function, f x . To obtain the probability that the random number generated by X is in a certain interval, we integrate this density function I f x dx Probability X lt b . To obtain a probability, we have to...