Reduces long series to the number of columns a plot can show, keeping peaks.
Items are split into columns buckets of consecutive items, in order. Each
function decides what a bucket keeps:
peaks/3— one item per bucket, the one furthest from zeromin_max/3— the smallest and largest item per bucket, in their original orderm4/2— first, smallest, largest and last{x, y}point per bucket, in x order
Items come back unchanged, so tuples such as {value, weight} survive when a
value_fun extracts the number. Lists no longer than columns are returned as-is.
A nil item is a gap and is never passed to value_fun. A bucket holding only
gaps keeps a gap in place of its items; otherwise its gaps are ignored.
Summary
Functions
Reduces several series at the same indices, so stacked layers stay aligned.
M4 reduction of {x, y} points: first, minimum, maximum and last per bucket.
Keeps the smallest and the largest item per bucket, in their original order.
Keeps one item per bucket: the one whose value has the largest magnitude.
Types
Functions
@spec aligned_peaks([[term()]], pos_integer(), value_fun()) :: [[term()]]
Reduces several series at the same indices, so stacked layers stay aligned.
Each index is a column of one item per series; the column kept per bucket is the one whose summed magnitude is largest. Series are cut to the length of the shortest. Returns one list per input series.
Examples
iex> Drafter.Visualization.Reduce.aligned_peaks([[1, 5, 1, 1], [1, 1, 1, 9]], 2)
[[5, 1], [1, 9]]@spec m4([{number(), number()}], pos_integer()) :: [{number(), number()}]
M4 reduction of {x, y} points: first, minimum, maximum and last per bucket.
Points must be sorted by x. Returns at most 4 * columns points, in x order,
with duplicates within a bucket removed. A line drawn through the result covers
the same pixels as a line through every input point at columns pixels wide.
Examples
iex> Drafter.Visualization.Reduce.m4([{0, 1}, {1, 7}, {2, 0}, {3, 4}], 1)
[{0, 1}, {1, 7}, {2, 0}, {3, 4}]
iex> Drafter.Visualization.Reduce.m4([{0, 1}, {1, 7}, {2, 0}, {3, 4}, {4, 2}, {5, 3}], 1)
[{0, 1}, {1, 7}, {2, 0}, {5, 3}]@spec min_max([term()], pos_integer(), value_fun()) :: [term()]
Keeps the smallest and the largest item per bucket, in their original order.
Returns exactly 2 * columns items when the list is longer than columns, so
series reduced to the same columns line up index for index. A bucket whose
minimum and maximum are the same item contributes it twice.
Examples
iex> Drafter.Visualization.Reduce.min_max([5, 1, 9, 2, 8, 3], 2)
[1, 9, 2, 8]
iex> Drafter.Visualization.Reduce.min_max([4, 4, 4], 1)
[4, 4]@spec peaks([term()], pos_integer(), value_fun()) :: [term()]
Keeps one item per bucket: the one whose value has the largest magnitude.
Returns at most columns items.
Examples
iex> Drafter.Visualization.Reduce.peaks([1, 9, 2, 3, -7, 1], 3)
[9, 3, -7]
iex> Drafter.Visualization.Reduce.peaks([{1, 0.5}, {4, 1.0}], 1, &elem(&1, 0))
[{4, 1.0}]
iex> Drafter.Visualization.Reduce.peaks([nil, nil, 3, nil], 2)
[nil, 3]