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(ns cc.ziptrial
  (:use [clojure.zip :as zip]
        [clojure.test]
       ))

(def v1 (zip/vector-zip [1 [2 3] [4 5]]))

(defn leafnodes [loc]
  "returns all the leaf nodes in loc"
  (filter (complement zip/branch?) ;filter only non-branch nodes

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(ns cc.ziptrial
  (:use [clojure.zip :as zip]
        [clojure.test]
       ))

(def v1 (zip/vector-zip [1 [2 3] [4 5]]))

(defn leafnodes [loc]
  "returns all the leaf nodes in loc"
  (filter (complement zip/branch?) ;filter only non-branch nodes

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;a sample zipper
(def v2 (zip/vector-zip [[2 3] [4]]))

(defn editfn [x]
  "returns a vector with 2 numbers"
  (let [a (* x 10)]
    [(inc a) (dec a)]))

(defn inext [node-edit loc ]
  "Adds children if loc is a leaf, else returns the next node"

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;the root of the tree.
;each node has a :self key, the value of which is its own value, and a vector
;that contains children.
(def mroot {:self 20 :cren [ 
                            {:self 10 :cren [{:self 11} {:self 12}]} 
                            {:self 30 :cren [{:self 31} {:self 32}]}
                            ]})

;create a zipper from the mroot tree.
(defn mzipper [root]

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;this returns the value of :self nodes from the root to the leaf
(defn gpath [n]
  "returns that path from the parent till the leaf"
  (conj (vec (map :self (zip/path n))) (-> n zip/node :self)))

;path from root to leaf.
(is (= '([20 10 11] [20 10 12] [20 30 31] [20 30 32])
       (map (comp gpath) (leafnodes (mzipper mroot)))))

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;adds 2 children to a leaf node
(defn add-children [{x :self :as m}]
  (assoc m :cren [ {:self (inc x)} {:self (dec x)}]))

(def xroot {:self 20 :cren [ 
                            {:self 10 } 
                            {:self 30 }
                            ]})

;the nodes 10 and 30 now have 2 children: 11,9 and 31,29

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print(__doc__)

# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#         Jan Hendrik Metzen <jhm@informatik.uni-bremen.de>
# License: BSD Style.

%matplotlib inline
import matplotlib.pyplot as plt

from sklearn import datasets

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(ns ;...
 (:require [tfevent-sink.event-io :as eio]))
 
(let [file-path "/tmp/run/tfevents.log"
      ;;create a scalar event with a name and value
      ev (eio/make-event "loss/mean-squared-error" (double 0.09))] 
   ;;create and initialize the event stream
  (eio/create-event-stream file-path)
  ;;append event to stream
  (eio/append-events file-path [ev])

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(:require 
  [confuse.binary-class-metrics :refer :all]
  [confuse.multi-class-metrics :refer :all])
;;list of predicted labels: they could be numbers or keywords
(def pred [1 0 1 1 0])
;;list of actual labels/ground truth
(def ac [1 1 1 1 0])

;;assume the positive class is 1
(true-positives ac pred 1)

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(def pi-job-spec
  {:apiVersion "batch/v1"
   :kind "Job"
   :metadata {:name "pi"}
   :spec {:ttlSecondsAfterFinished 200
          :template
          {:spec
           {:containers
            [{:name "pi"
              :imagePullPolicy "Always"