(ns
  ^{:doc "Experimental"}
  org.apache.clojure-mxnet.ndarray-random-api
  (:refer-clojure :exclude [* - + > >= < <= / cast concat flatten identity load max
                            min repeat reverse set sort take to-array empty shuffle
                            ref])
  (:require [org.apache.clojure-mxnet.shape :as mx-shape]
            [org.apache.clojure-mxnet.util :as util])
  (:import (org.apache.mxnet NDArrayAPI)))

;; Do not edit - this is auto-generated

;; Licensed to the Apache Software Foundation (ASF) under one or more
;; contributor license agreements.  See the NOTICE file distributed with
;; this work for additional information regarding copyright ownership.
;; The ASF licenses this file to You under the Apache License, Version 2.0
;; (the "License"); you may not use this file except in compliance with
;; the License.  You may obtain a copy of the License at
;;
;;    http://www.apache.org/licenses/LICENSE-2.0
;;
;; Unless required by applicable law or agreed to in writing, software
;; distributed under the License is distributed on an "AS IS" BASIS,
;; WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
;; See the License for the specific language governing permissions and
;; limitations under the License.
;;


(defn
 exponential
 "Draw random samples from an exponential distribution.
  
  Samples are distributed according to an exponential distribution parametrized by *lambda* (rate).
  
  Example::
  
     exponential(lam=4, shape=(2,2)) = [[ 0.0097189 ,  0.08999364],
                                        [ 0.04146638,  0.31715935]]
  
  
  Defined in src/operator/random/sample_op.cc:L137
  
  `lam`: Lambda parameter (rate) of the exponential distribution. (optional)
  `shape`: Shape of the output. (optional)
  `ctx`: Context of output, in format [cpu|gpu|cpu_pinned](n). Only used for imperative calls. (optional)
  `dtype`: DType of the output in case this can't be inferred. Defaults to float32 if not defined (dtype=None). (optional)
  `out`: Output array. (optional)"
 ([] (exponential {}))
 ([{:keys [lam shape ctx dtype out],
    :or {lam nil, shape nil, ctx nil, dtype nil, out nil},
    :as opts}]
  (util/coerce-return
   (NDArrayAPI/random_exponential
    (util/->option lam)
    (util/->option (clojure.core/when shape (mx-shape/->shape shape)))
    (util/->option ctx)
    (util/->option dtype)
    (util/->option out)))))

(defn
 gamma
 "Draw random samples from a gamma distribution.
  
  Samples are distributed according to a gamma distribution parametrized by *alpha* (shape) and *beta* (scale).
  
  Example::
  
     gamma(alpha=9, beta=0.5, shape=(2,2)) = [[ 7.10486984,  3.37695289],
                                              [ 3.91697288,  3.65933681]]
  
  
  Defined in src/operator/random/sample_op.cc:L125
  
  `alpha`: Alpha parameter (shape) of the gamma distribution. (optional)
  `beta`: Beta parameter (scale) of the gamma distribution. (optional)
  `shape`: Shape of the output. (optional)
  `ctx`: Context of output, in format [cpu|gpu|cpu_pinned](n). Only used for imperative calls. (optional)
  `dtype`: DType of the output in case this can't be inferred. Defaults to float32 if not defined (dtype=None). (optional)
  `out`: Output array. (optional)"
 ([] (gamma {}))
 ([{:keys [alpha beta shape ctx dtype out],
    :or {alpha nil, beta nil, shape nil, ctx nil, dtype nil, out nil},
    :as opts}]
  (util/coerce-return
   (NDArrayAPI/random_gamma
    (util/->option alpha)
    (util/->option beta)
    (util/->option (clojure.core/when shape (mx-shape/->shape shape)))
    (util/->option ctx)
    (util/->option dtype)
    (util/->option out)))))