Version: Python

emmin_tick

emmin_tick creates a tick-based (row-based) EMMIN (exponential moving minimum) for an update_by table operation. The formula for the tick-based EMMIN of a column $X$ is:

$a = e^{\frac{-1}{\tau}}$

$\min_0(X) = x_0$

$\min_i(X) = \min(a*\min_{i-1}(X), \; x_i)$

Where:

$\tau$ is decay_ticks, an input parameter to the method.
$\min_i(X)$ is the exponential moving minimum of $X$ at step $i$ .
$x_i$ is the current value.
$i$ denotes the time step, ranging from $i=1$ to $i = n-1$ , where $n$ is the number of elements in $X$ .

Syntax

emmin_tick(
    decay_ticks: int,
    cols: list[str],
    op_control: OperationControl = None,
) -> UpdateByOperation

Parameters

Parameter	Type	Description
decay_ticks	int	The decay rate in ticks.
cols	list[str]	The column(s) to be operated on. These can include expressions to rename the output (e.g., `NewCol = Col`). When left empty, the rolling count is calculated for all applicable columns.
op_control	OperationControl	Defines how special cases should behave. When `None`, the default `OperationControl` settings will be used.

Returns

An UpdateByOperation to be used in an update_by table operation.

Examples

One column, no groups

The following example calculates the tick-based (row-based) EMMIN of the X column, renaming the resulting column to EmMinX. The decay rate, decay_ticks is set to 2. No grouping columns are specified, so the EMMIN is calculated over all rows.

from deephaven.updateby import emmin_tick
from deephaven import empty_table

source = empty_table(10).update(
    ["Letter = (i % 2 == 0) ? `A` : `B`", "X = randomInt(0,25)"]
)

result = source.update_by(ops=emmin_tick(decay_ticks=2, cols=["EmMinX = X"]))

result
source

One EMMIN column, one grouping column

The following example builds on the previous by specifying Letter as the key column. Thus, the EMMIN is calculated on a per-letter basis.

from deephaven.updateby import emmin_tick
from deephaven import empty_table

source = empty_table(10).update(
    ["Letter = (i % 2 == 0) ? `A` : `B`", "X = randomInt(0,25)"]
)

result = source.update_by(
    ops=emmin_tick(decay_ticks=2, cols=["EmMaxX = X"]), by=["Letter"]
)

result
source

Multiple EMMIN columns, multiple grouping columns

The following example builds on the previous by calculating the EMMIN of multiple columns in the same UpdateByOperation. Also, the groups are defined by unique combinations of letter and boolean in the Letter and Truth columns, respectively.

from deephaven.updateby import emmin_tick
from deephaven import empty_table

source = empty_table(20).update(
    [
        "Letter = (i % 2 == 0) ? `A` : `B`",
        "Truth = randomBool()",
        "X = randomInt(0,25)",
        "Y = randomInt(0,25)",
    ]
)

result = source.update_by(
    ops=emmin_tick(decay_ticks=2, cols=["EmMinX = X", "EmMinY = Y"]),
    by=["Letter", "Truth"],
)

result
source

Multiple `UpdateByOperations`, multiple grouping columns

The following example builds on the previous by calculating the EMMIN of multiple columns, each with its own UpdateByOperation. This allows each EMMIN to have its own decay rate. The different decay rates are reflected in the renamed resultant column names.

from deephaven.updateby import emmin_tick
from deephaven import empty_table

source = empty_table(20).update(
    [
        "Letter = (i % 2 == 0) ? `A` : `B`",
        "Truth = randomBool()",
        "X = randomInt(0,25)",
        "Y = randomInt(0,25)",
    ]
)

emmin_x = emmin_tick(decay_ticks=2, cols=["EmMinX2rows = X"])
emmin_y = emmin_tick(decay_ticks=4, cols=["EmMinY5rows = Y"])

result = source.update_by(ops=[emmin_x, emmin_y], by=["Letter", "Truth"])

result
source

Syntax​

Parameters​

Returns​

Examples​

One column, no groups​

One EMMIN column, one grouping column​

Multiple EMMIN columns, multiple grouping columns​

Multiple UpdateByOperations, multiple grouping columns​

Related documentation​