Histogram computation utilities with multiple binning methods.
Supports:
All functions require typed arrays (DoubleArray, LongArray).
Histogram computation utilities with multiple binning methods. Supports: - :freedman-diaconis (default) - Uses IQR-based bin width calculation - :knuth - Bayesian optimal bin count selection All functions require typed arrays (DoubleArray, LongArray).
(histogram data)(histogram data opts-or-iqr)Compute histogram from data.
Supports multiple binning methods via the :method option:
Requires a typed array (DoubleArray or LongArray).
Options: :method - Binning method (:freedman-diaconis or :knuth) :iqr - Pre-computed IQR (only for :freedman-diaconis) :max-bins - Maximum bins to search (only for :knuth, default 50)
Returns map containing: :type - :criterium/histogram-fixed-width or :criterium/histogram-knuth :counts - vector of bin counts :centers - vector of bin centers :width - bin width :density - vector of probability density values :n - total number of samples :num-bins - number of bins :min - minimum value :max - maximum value
Additional keys for :knuth method: :optimal-bins - optimal bin count M :log-posterior - log-posterior value at optimal M
For backward compatibility, second argument can be a number (pre-computed IQR).
Throws: ex-info {:error :histogram/no-values} for empty input ex-info {:error :histogram/same-values} when all values are the same
Compute histogram from data.
Supports multiple binning methods via the :method option:
- :freedman-diaconis (default) - Uses IQR-based bin width calculation
- :knuth - Bayesian optimal bin count selection
Requires a typed array (DoubleArray or LongArray).
Options:
:method - Binning method (:freedman-diaconis or :knuth)
:iqr - Pre-computed IQR (only for :freedman-diaconis)
:max-bins - Maximum bins to search (only for :knuth, default 50)
Returns map containing:
:type - :criterium/histogram-fixed-width or :criterium/histogram-knuth
:counts - vector of bin counts
:centers - vector of bin centers
:width - bin width
:density - vector of probability density values
:n - total number of samples
:num-bins - number of bins
:min - minimum value
:max - maximum value
Additional keys for :knuth method:
:optimal-bins - optimal bin count M
:log-posterior - log-posterior value at optimal M
For backward compatibility, second argument can be a number (pre-computed IQR).
Throws:
ex-info {:error :histogram/no-values} for empty input
ex-info {:error :histogram/same-values} when all values are the samecljdoc builds & hosts documentation for Clojure/Script libraries
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