cf.Field.argmin

Field.argmin(axis=None, unravel=False)

Return the indices of the minimum values along an axis.

If no axis is specified then the returned index locates the minimum of the whole data.

In case of multiple occurrences of the minimum values, the indices corresponding to the first occurrence are returned.

Performance

If the data index is returned as a tuple (see the unravel parameter) then all delayed operations are computed.

New in version 3.15.1.

See also

argmax, where, cf.Data.argmin

Parameters

axis: optional

Select the domain axis over which to locate the minimum values, defined by the domain axis that would be selected by passing the given axis to a call of the field construct’s domain_axis method. For example, for a value of 'X', the domain axis construct returned by f.domain_axis('X') is selected.

By default the minimum over the flattened data is located.

unravel: bool, optional

If True then when locating the minimum over the whole data, return the location as an integer index for each axis as a tuple. By default an index to the flattened array is returned in this case. Ignored if locating the minima over a subset of the axes.

Returns

Data or tuple of int

The location of the minimum, or minima.

Examples

>>> f = cf.example_field(2)
>>> print(f)
Field: air_potential_temperature (ncvar%air_potential_temperature)
------------------------------------------------------------------
Data            : air_potential_temperature(time(36), latitude(5), longitude(8)) K
Cell methods    : area: mean
Dimension coords: time(36) = [1959-12-16 12:00:00, ..., 1962-11-16 00:00:00]
                : latitude(5) = [-75.0, ..., 75.0] degrees_north
                : longitude(8) = [22.5, ..., 337.5] degrees_east
                : air_pressure(1) = [850.0] hPa

Find the T axis indices of the minimum at each X-Y location:

>>> i = f.argmin('T')
>>> print(i.array)
[[ 5 14  4 32 11 34  9 27]
 [10  7  4 21 11 10  3 33]
 [21 33  1 30 26  8 33  4]
 [15 10 12 19 23 20 30 25]
 [28 33 31 11 15 12  9  7]]

Find the coordinates of the global minimum value, showing that it occurs on 1960-03-16 12:00:00 at location 292.5 degrees east, -45.0 degrees north:

>>> g = f[f.argmin(unravel=True)]
>>> print(g)
Field: air_potential_temperature (ncvar%air_potential_temperature)
------------------------------------------------------------------
Data            : air_potential_temperature(time(1), latitude(1), longitude(1)) K
Cell methods    : area: mean
Dimension coords: time(1) = [1960-03-16 12:00:00]
                : latitude(1) = [-45.0] degrees_north
                : longitude(1) = [292.5] degrees_east
                : air_pressure(1) = [850.0] hPa

See cf.Data.argmin for further examples.