;; gorilla-repl.fileformat = 1

;; **
;;; # Compare hidden unit count
;;; on 3x3 bars, learning-rate 5e-8
;; **

;; @@
(ns compare-hidden-unit-count
  (:require [gorilla-plot.core :as plot]
            [gg4clj.core :as gg4clj]
            [clojure.math.combinatorics :refer [cartesian-product]]
            [cnc.analytics :as a]
            [cnc.execute :as exe]
            [clojure.pprint :refer [pprint]]
            [hasch.core :refer [uuid]]
            [boltzmann.matrix :refer [full-matrix]]
            [clojure.java.shell :refer [sh]]
            [cnc.core :refer [state]]
            [cnc.execute :refer [slurp-bytes]]
            [clojure.core.matrix :as mat]
            [clj-hdf5.core :as hdf5]
            [konserve.protocols :refer [-get-in -bget -exists?]]
            [geschichte.platform :refer [<!?]]
            [boltzmann.core :refer [train-cd sample-gibbs]]
            [boltzmann.theoretical :refer [create-theoretical-rbm]]
            [boltzmann.formulas :as f]
            [boltzmann.protocols :refer [-weights -biases]]
            [boltzmann.visualize :as v]
            [clojure.core.matrix :refer [dot matrix]]
            [datomic.api :as d]
            [clojure.core.async :refer [chan] :as async]
            [quil.core :as q]))
(def store (get-in @state [:repo :store]))
(def states (apply cartesian-product (repeat 9 [0 1])))
(def conn (a/conn "train current rbms4"))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/conn</span>","value":"#'compare-hidden-unit-count/conn"}
;; <=

;; @@
(def exps [{:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 5.0E-8, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_6b71e97c/", :output {:bias_theo_history.h5 #uuid "1e3bd015-161d-54f2-ac87-b4dcfde5f558", :weight_theo_history.h5 #uuid "1a760e37-d74d-5fbf-9690-86ea0c703cf9"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 1.0E-7, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_dc96dd1d/", :output {:bias_theo_history.h5 #uuid "3be62f43-6829-5e65-a664-4b662057eabd", :weight_theo_history.h5 #uuid "37ddc647-db22-51b2-a5c2-1db250faac44"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 5.0E-10, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_3016da4b/", :output {:bias_theo_history.h5 #uuid "1b2039c3-eb94-53a1-916b-043e6ce51aca", :weight_theo_history.h5 #uuid "1850ce11-b497-50e6-9ebd-7fc61d432dfb"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 1.0E-10, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_3d36f2de/", :output {:bias_theo_history.h5 #uuid "1c18b593-220a-57cb-9c23-efc772fcabad", :weight_theo_history.h5 #uuid "29c06dc6-e6be-56ac-92b4-525029ed210d"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 5.0E-9, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_cdb30dce/", :output {:bias_theo_history.h5 #uuid "2f5425c9-4c7b-5bc1-8ff3-20bb763824d9", :weight_theo_history.h5 #uuid "1c22cc55-c5c1-5f52-b749-25722fbccd13"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 5.0E-7, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_76031897/", :output {:bias_theo_history.h5 #uuid "36af20ab-2b35-5501-a418-73673ab221ab", :weight_theo_history.h5 #uuid "27b13978-fb54-5236-abd5-2e04911d2361"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 1.0E-8, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_2b6e5d60/", :output {:bias_theo_history.h5 #uuid "35c956c6-6c66-53b2-afec-c853c533e8f7", :weight_theo_history.h5 #uuid "210ca203-07d9-5143-aafb-03d103604b89"}} {:exp-params {:git-commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169", :training-params {:h_count 15, :dt 0.1, :epochs 30000, :burn_in_time 0.0, :learning_rate 1.0E-9, :phase_duration 100.0, :weight_recording_interval 100.0, :sim_setup_kwargs {:grng_seed 42, :rng_seeds_seed 42}, :stdp_burnin 10.0}, :calibration-id #uuid "22f685d0-ea7f-53b5-97d7-c6d6cadc67d3", :data-id #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94", :source-path "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py", :args ["srun-log" "python" "/wang/users/weilbach/cluster_home/model-nmsampling/code/ev_cd/train.py"]}, :base-directory "experiments/Fri Mar 13 11:53:36 CET 2015_9b5d9be4/", :output {:bias_theo_history.h5 #uuid "0b624147-d245-5cf8-9af9-1edf835a15dc", :weight_theo_history.h5 #uuid "3dda9ee5-f0a6-5fd6-82f2-5077d72acab1"}}])
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/exps</span>","value":"#'compare-hidden-unit-count/exps"}
;; <=

;; @@
(def bars (<!? (-bget store #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94"  
                      #(-> % :input-stream slurp read-string))))
bars
;; @@
;; =>
;;; {"type":"list-like","open":"<span class='clj-vector'>[</span>","close":"<span class='clj-vector'>]</span>","separator":" ","items":[{"type":"list-like","open":"<span class='clj-vector'>[</span>","close":"<span class='clj-vector'>]</span>","separator":" ","items":[{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"}],"value":"[1 0 0 1 0 0 1 0 0]"},{"type":"list-like","open":"<span class='clj-vector'>[</span>","close":"<span class='clj-vector'>]</span>","separator":" ","items":[{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"}],"value":"[0 0 1 0 0 1 0 0 1]"},{"type":"list-like","open":"<span class='clj-vector'>[</span>","close":"<span class='clj-vector'>]</span>","separator":" ","items":[{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>1</span>","value":"1"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"},{"type":"html","content":"<span class='clj-long'>0</span>","value":"0"}],"value":"[1 1 1 0 0 0 0 0 0]"}],"value":"[[1 0 0 1 0 0 1 0 0] [0 0 1 0 0 1 0 0 1] [1 1 1 0 0 0 0 0 0]]"}
;; <=

;; @@
(def weight-blobs (map #(get-in % [:output :weight_theo_history.h5]) exps))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/weight-blobs</span>","value":"#'compare-hidden-unit-count/weight-blobs"}
;; <=

;; @@
(def weights (map #(->> (a/get-hdf5-tensor store % "/weight") 
                       last
                       a/drop-half
                       (partition 9)
                       (mapv vec)
                       ) weight-blobs))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/weights</span>","value":"#'compare-hidden-unit-count/weights"}
;; <=

;; @@
(def bias-blobs (map #(get-in % [:output :bias_theo_history.h5]) exps))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/bias-blobs</span>","value":"#'compare-hidden-unit-count/bias-blobs"}
;; <=

;; @@
(def biases (map #(-> (a/get-hdf5-tensor store % "/weight") last vec) bias-blobs))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/biases</span>","value":"#'compare-hidden-unit-count/biases"}
;; <=

;; @@
(def learningrate-vs-probs
  (let [vc 9]
    (sort-by 
      first
      (doall (map (fn [e w b] 
             [(get-in e [:exp-params :training-params :learning_rate]) 
                    (map #(f/prob-visi (create-theoretical-rbm w (vec (take vc b)) (vec (drop vc b))) %) bars)])
         exps weights biases)))))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/learningrate-vs-probs</span>","value":"#'compare-hidden-unit-count/learningrate-vs-probs"}
;; <=

;; @@
learningrate-vs-probs
;; @@
;; =>
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;; <=

;; @@
(do (gg4clj/view 
  [[:<- :d (gg4clj/data-frame {:learning_rate (map (comp first) learningrate-vs-probs)    
                               :sum (vec (map #(apply + (second %)) learningrate-vs-probs))
                               :z (vec (concat (repeat (count learningrate-vs-probs) "ev-cd")))})]
  (gg4clj/r+ [:ggplot :d [:aes {:x (keyword "factor(learning_rate)") :y :sum :fill :z}]]
                        [:geom_point {:stat "identity"}])]
  {:width 10})
  )
;; @@
;; =>
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;; <=

;; @@
(def new-exps (map (fn [[lr w-hist b-hist]] 
                     [lr 
                      (->> (a/get-hdf5-tensor store w-hist "/weight") 
                       last
                       a/drop-half
                       (partition 9)
                       (mapv vec))
                                           
                      (->> (a/get-hdf5-tensor store b-hist "/weight") last vec)])
                
                
(d/q '[:find ?lr ?w-hist ?b-hist
       :where
       #_[?exp :git/commit-id "2d96fc2983f748f8b327c7f2fd3fdaa4f23cd169"]
       [?exp :ref/data #uuid "0b619370-6716-5ae8-89b6-9c38b4e11e94"]
       [?exp :ref/trans-params ?vid]
       [?exp :ref/training-params ?train-params-id]
       [(cnc.analytics/load-key ?train-params-id :learning_rate) ?lr]
       [(cnc.analytics/load-key ?vid) ?vls]
       [(:base-directory ?vls) ?base-dir]
       [(.contains ^String ?base-dir "experiments/Tue Mar 17 16:02")]
       [(:output ?vls) ?out]
       [(:weight_theo_history.h5 ?out) ?w-hist]
       [(:bias_theo_history.h5 ?out) ?b-hist]]
     (d/db conn))))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/new-exps</span>","value":"#'compare-hidden-unit-count/new-exps"}
;; <=

;; @@
(defn lr-vs-probs [exps]
  (let [vc 9]
    (sort-by 
      first
      (doall (map (fn [[lr w b]] 
             [lr 
                    (map #(f/prob-visi (create-theoretical-rbm w (vec (take vc b)) (vec (drop vc b))) %) bars)])
         exps)))))
;; @@
;; =>
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;; <=

;; @@
(def lr-vs-probs (lr-vs-probs new-exps))
;; @@
;; =>
;;; {"type":"html","content":"<span class='clj-var'>#&#x27;compare-hidden-unit-count/lr-vs-probs</span>","value":"#'compare-hidden-unit-count/lr-vs-probs"}
;; <=

;; @@
lr-vs-probs
;; @@
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;; <=

;; @@
(do (gg4clj/view 
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                               :sum (vec (map #(apply + (second %)) lr-vs-probs))
                               :z (vec (concat (repeat (count lr-vs-probs) "ev-cd")))})]
  (gg4clj/r+ [:ggplot :d [:aes {:x (keyword "factor(learning_rate)") :y :sum :fill :z}]]
                        [:geom_point {:stat "identity"}]
             #_[:scale_x_discrete {:limits (keyword "c(1E-8,5E-8,1E-7,5E-7,1E-6,5E-6,1E-5,5E-5)")}])]
  {:width 10})
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