array-to-latex: Turn a Numpy Array into Latex
Latex is used to write mathematical expressions. You can turn a Numpy array into latex using array-to-latex.
NumPy
unyt: Manipulate and Convert Units in NumPy Arrays
Working with NumPy arrays that have units can be difficult, as it is not immediately clear what the units are, which can lead to errors.
The unyt package solves this by providing a subclass of NumPy’s ndarray class that knows units.
unyt arrays support standard NumPy array operations and functions while preserving the units associated with the data.
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NumPy.take: Take Elements From an Array
If you want to take elements from a NumPy array at specific indices, use numpy.take.
Turn a pandas Series into a NumPy Array
If you want to turn a pandas Series into a NumPy array, use Series.values.
Check if Two NumPy Arrays Are Equal
If you try to check whether two arrays are equal, using an assert statement will give you an error. Use assert_array_equal instead.
assert_array_equal also shows you which elements are different between two arrays.
np.squeeze: Remove Axes of Length One From an Array
If one or more of your axes are of length one, you can remove those axes using numpy.squeeze.
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NumPy.testing.assert_almost_equal: Check If Two Arrays Are Equal up to a Certain Precision
Sometimes, you might only want to check if two arrays are equal up to a certain precision. If so, use np.testing.assert_almost_equal.
The code above shows an example of this method.
Link to the source code.
NumPy.linspace: Get Evenly Spaced Numbers Over a Specific Interval
If you want to get evenly spaced numbers over a specific interval, use np.linspace(start, stop, num).
The code above shows a use case of the np.linspace method.
Link to the source code.
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Numpy Comparison Operators
If you want to get elements of a Numpy array that are greater, smaller, or equal to a value or an array, simply use comparison operators such as <, <=, >, >=, ==.
The image above shows an example of using comparison operators.
Link to the source code.
np.all: Test Whether All Elements along a Given Axis of a NumPy Array Evaluate to True
If you want to test whether all elements along a given axis of a NumPy array evaluate to True, use np.all.
In the code above, I check if all elements are less than 3 in each column or row.
Link to the source code.
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