Vector: 1D array operations
- Create
- Test
- Update
- Get
- Aggregate
- Map
- Reorder
- Shrink
- Grow
- Convert
Create
| What | How | Details |
| Undefined, length n | np.empty(n) | Warning: don’t use the initial values |
| Zeros (FP, length n) | np.zeros(n) | |
| Zeros (int, length n) | np.zeros(n, dtype=np.int64) | |
| Ones (length n) | np.ones(n) | |
| True values (bool, length n) | np.full(n, fill_value=True) | |
| False values (bool, length n) | np.full(n, fill_value=False) | |
| Fill with value v (bool, length n) | np.full(n, fill_value=v) | |
| Increasing numbers [0, b-1] | np.arrange(b) | |
| Increasing numbers [a, b] | np.arrange(a, b) | |
| Numbers from a to b with step size s | np.arrange(a, b, s) | |
| Linear range from a to b of length n | np.linspace(a, b, num=n) | |
| From tuple | np.array(tuple) | |
| From list | np.array(list) | |
| From iter | np.fromiter(iter) | |
| From iter (max length n) | np.fromiter(iter, count=n) | |
| From two vectors | np.append(v1, v2) | |
| From vectors (concat) | np.concatenate((v1, v2)) | |
Test
| What | How | Details |
| Vector | v.ndim == 1 | |
| Logical type | v.dtype == np.bool_ | |
| Float type | v.dtype == np.float_ | |
| Integer type | v.dtype == np.int_ | |
Contains nan | np.isnan(v).any() | |
Contains inf | np.isinf(v).any() | |
| Contains value | value in v | |
| Does not contain value | value not in v | |
| All finite | np.isfinite(v).all() | |
| All elements are equal to value | (v == value).all() | |
| All elements are equal to valu | np.all(v == value) | |
| All numerical elements are close to value | np.all(np.isclose(v, value)) | |
| All numerical elements are equal | np.ptp(v) == 0 | |
| Vectors are equal | np.array_equal(v, v2) | |
Update
Operations are in-place.
| What | How | Details |
| Set first element | v[0] = value | |
| Set last element | v[-1] = value | |
| Set value for element i | v[i] = value | |
| Fill | v[:] = value | |
| Fill first n values | v[:n] = value | |
| Sort elements ascending | v.sort() | NaNs are put last |
| Sort elements descending | v[::-1].sort() | Note that this puts NaNs first! |
Get
| What | How | Details |
| Unique values | numpy.unique(v) | |
| Unique values | set(v) | |
| Number of unique values | len(numpy.unique(v)) | |
| Count non-zero values | np.count_nonzero(v) | |
| Count per unique value | np.unique(v, return_counts=True) | |
Count per positive integer from [0, max(v)] | np.bincount(v) | Elements must be nonnegative ints |
Aggregate
All operations produce a scalar value.
| What | How | Details |
| Min | np.min(v) | Use nanmin() if NaNs are present |
| Max | np.max(v) | |
| Max - min | np.ptp(v) | |
| Index of first max element | np.argmax(v) | Returns index of NaN if present! |
| Index of first min element | np.argmin(v) | Returns index of NaN if present! |
| Sum | np.sum(v) | |
| Mean | np.mean(v) | |
| Standard deviation | np.std(v) | |
| Variance | np.var(v) | |
| Median | np.median(v) | |
| Quantile q | np.quantile(v, q) | |
Map
| What | How | Details |
| Clip (truncate) between [a, b ] | np.clip(v, a_min=a, a_max=b) | |
| Bin index | np.digitize(v, bins) | |
Piecewise-linear interpolation of coordinate mapping xp -> yp | np.interp(v, xp, yp) | No option for extrapolation! |
| Piecewise-linear interpolation with extrapolation | f = scipy.interpolate.interp1d(xp, yp, fill_value = 'extrapolate')
f(v) | Deprecated and without replacement lol |
Reorder
| What | How | Details |
| Reverse elements | v[::-1] | |
| Reverse elements | np.flip(v) | |
| Shift elements forwards (roll) | np.roll(v, 1) | |
| Shift elements backwards (roll) | np.roll(v, -1) | |
| Ascending order indices | np.argsort(v) | |
| Descending order indices | np.argsort(-v) | |
| Sort ascending | np.sort(v) | NaNs are last |
| Sort descending | v[np.argsort(-v)] | NaNs are last |
Shrink
| What | How | Details |
| Difference | np.diff(v) | |
| Difference with lag | np.diff(v, n=lag) | |
Grow
| What | How | Details |
| Pad with value | np.pad(v, pad_width=1, constant_values=v) | |
| Pad with edge elements | np.pad(v, pad_width=1, mode='edge') | |
| Replicate n times | np.repeat(v, n) | |
| Append vector | np.append(v1, v2) | |
| Concatenate vectors | np.concatenate((v1, v2, v3)) | |
Convert
| What | How | Details |
| Bytes | v.tobytes() | |
| Tuple | tuple(v) | |
| List | v.tolist() | |
| Set | set(v) | |