tabular.fast

Fast functions for manipulating and comparing numpy ndarrays (and recarrays), e.g. efficient NumPy algorithms for solving list-membership problems:

arrayuniqify, recarrayuniqify, equalspairs, recarrayequalspairs, isin, recarrayisin, recarraydifference, arraymax, arraymin
tabular.fast.arrayuniqify(X, retainorder=False)

Very fast uniqify routine for numpy arrays.

Parameters

X : numpy array

Determine the unique elements of this numpy array.

retainorder : Boolean, optional

Whether or not to return indices corresponding to unique values of X that also sort the values. Default value is False, in which case [D,s] is returned. This can be used to produce a uniqified version of X by simply taking:

X[s][D]

or:

X[s[D.nonzero()[0]]]

Returns

D : numpy array

List of “first differences” in the sorted verion of X. Returned when retainorder is False (default).

s : numpy array

Permutation that will sort X. Returned when retainorder is False (default).

ind : numpy array

List of indices that correspond to unique values of X, without sorting those values. Returned when retainorder is True.

See Also:

tabular.fast.recarrayuniqify(X, retainorder=False)

Very fast uniqify routine for numpy record arrays (or ndarrays with structured dtype).

Record array version of func:tabular.fast.arrayuniqify.

Parameters

X : numpy recarray

Determine the unique elements of this numpy recarray.

retainorder : Boolean, optional

Whether or not to return indices corresponding to unique values of X that also sort the values. Default value is False, in which case [D,s] is returned. This can be used to produce a uniqified version of X by simply taking:

X[s][D]

or:

X[s[D.nonzero()[0]]]

Returns

D : numpy recarray

List of “first differences” in the sorted verion of X. Returned when retainorder is False (default).

s : numpy array

Permutation that will sort X. Returned when retainorder is False (default).

ind : numpy array

List of indices that correspond to unique values of X, without sorting those values. Returned when retainorder is True.

See Also:

tabular.fast.equalspairs(X, Y)

Indices of elements in a sorted numpy array equal to those in another.

Given numpy array X and sorted numpy array Y, determine the indices in Y equal to indices in X.

Returns [A,B] where A and B are numpy arrays of indices in X such that:

Y[A[i]:B[i]] = Y[Y == X[i]]`

A[i] = B[i] = 0 if X[i] is not in Y.

Parameters

X : numpy array

Numpy array to compare to the sorted numpy array Y.

Y : numpy array

Sorted numpy array. Determine the indices of elements of Y equal to those in numpy array X.

Returns

A : numpy array

List of indices in Y, len(A) = len(Y).

B : numpy array

List of indices in Y, len(B) = len(Y).

See Also:

tabular.fast.recarrayequalspairs(X, Y, weak=True)

Indices of elements in a sorted numpy recarray (or ndarray with structured dtype) equal to those in another.

Record array version of func:tabular.fast.equalspairs, but slightly different because the concept of being sorted is less well-defined for a record array.

Given numpy recarray X and sorted numpy recarray Y, determine the indices in Y equal to indices in X.

Returns [A,B,s] where s is a permutation of Y such that for:

Y = X[s]

we have:

Y[A[i]:B[i]] = Y[Y == X[i]]

A[i] = B[i] = 0 if X[i] is not in Y.

Parameters

X : numpy recarray

Numpy recarray to compare to the sorted numpy recarray Y.

Y : numpy recarray

Sorted numpy recarray. Determine the indices of elements of Y equal to those in numpy array X.

Returns

A : numpy array

List of indices in Y, len(A) = len(Y).

B : numpy array

List of indices in Y, len(B) = len(Y).

s : numpy array

Permutation of Y.

See Also:

tabular.fast.isin(X, Y)

Indices of elements in a numpy array that appear in another.

Fast routine for determining indices of elements in numpy array X that appear in numpy array Y, returning a boolean array Z such that:

Z[i] = X[i] in Y

Parameters

X : numpy array

Numpy array to comapare to numpy array Y. For each element of X, ask if it is in Y.

Y : numpy array

Numpy array to which numpy array X is compared. For each element of X, ask if it is in Y.

Returns

b : numpy array (bool)

Boolean numpy array, len(b) = len(X).

See Also:

tabular.fast.recarrayisin(), tabular.fast.arraydifference()
tabular.fast.recarrayisin(X, Y, weak=True)

Indices of elements in a numpy record array (or ndarray with structured dtype) that appear in another.

Fast routine for determining indices of elements in numpy record array X that appear in numpy record array Y, returning a boolean array Z such that:

Z[i] = X[i] in Y

Record array version of func:tabular.fast.isin.

Parameters

X : numpy recarray

Numpy recarray to comapare to numpy recarray Y. For each element of X, ask if it is in Y.

Y : numpy recarray

Numpy recarray to which numpy recarray X is compared. For each element of X, ask if it is in Y.

Returns

b : numpy array (bool)

Boolean numpy array, len(b) = len(X).

See Also:

tabular.fast.recarraydifference(X, Y)

Records of a numpy recarray (or ndarray with structured dtype) that do not appear in another.

Fast routine for determining which records in numpy array X do not appear in numpy recarray Y.

Record array version of func:tabular.fast.arraydifference.

Parameters

X : numpy recarray

Numpy recarray to comapare to numpy recarray Y. Return subset of X corresponding to elements not in Y.

Y : numpy recarray

Numpy recarray to which numpy recarray X is compared. Return subset of X corresponding to elements not in Y.

Returns

Z : numpy recarray

Subset of X corresponding to elements not in Y.

See Also:

tabular.fast.arraydifference(), tabular.fast.recarrayisin()
tabular.fast.arraymax(X, Y)

Fast “vectorized” max function for element-wise comparison of two numpy arrays.

For two numpy arrays X and Y of equal length, return numpy array Z such that:

Z[i] = max(X[i],Y[i])

Parameters

X : numpy array

Numpy array; len(X) = len(Y).

Y : numpy array

Numpy array; len(Y) = len(X).

Returns

Z : numpy array

Numpy array such that Z[i] = max(X[i],Y[i]).

See Also

tabular.fast.arraymin(X, Y)

Fast “vectorized” min function for element-wise comparison of two numpy arrays.

For two numpy arrays X and Y of equal length, return numpy array Z such that:

Z[i] = min(X[i],Y[i])

Parameters

X : numpy array

Numpy array; len(X) = len(Y).

Y : numpy array

Numpy array; len(Y) = len(X).

Returns

Z : numpy array

Numpy array such that Z[i] = max(X[i],Y[i]).

See Also

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