move views into own folder and begin prising away dataset code

1 files changed, 0 insertions, 159 deletions

diff --git a/app/client/modules/samplernn/samplernn.loss.js b/app/client/modules/samplernn/samplernn.loss.js
deleted file mode 100644
index 6ca69ef..0000000
--- a/app/client/modules/samplernn/samplernn.loss.js
+++ /dev/null
@@ -1,159 +0,0 @@
-import { h, Component } from 'preact'
-import { bindActionCreators } from 'redux'
-import { connect } from 'react-redux'
-
-import { lerp, norm, randint, randrange } from '../../util'
-
-import * as samplernnActions from './samplernn.actions'
-
-import Group from '../../common/group.component'
-import Slider from '../../common/slider.component'
-import Select from '../../common/select.component'
-import Button from '../../common/button.component'
-import { FileList } from '../../common/fileList.component'
-import TextInput from '../../common/textInput.component'
-
-class SampleRNNLoss extends Component {
-  constructor(props){
-    super()
-    props.actions.load_loss()
-  }
-  render(){
-    this.refs = {}
-    return (
-      <div className='app lossGraph'>
-        <div className='heading'>
-          <h3>SampleRNN Loss</h3>
-          <canvas ref={(ref) => this.refs['canvas'] = ref} />
-        </div>
-      </div>
-    )
-  }
-  componentDidUpdate(){
-    const { lossReport } = this.props.samplernn
-    if (! lossReport) return
-    const canvas = this.refs.canvas
-    canvas.width = window.innerWidth
-    canvas.height = window.innerHeight
-    canvas.style.width = canvas.width + 'px'
-    canvas.style.height = canvas.height + 'px'
-
-    const ctx = canvas.getContext('2d')
-    const w = canvas.width = canvas.width * devicePixelRatio
-    const h = canvas.height = canvas.height * devicePixelRatio
-    ctx.clearRect(0,0,w,h)
-
-    const keys = Object.keys(lossReport).sort().filter(k => !!lossReport[k].length)
-    let scaleMax = 0
-    let scaleMin = Infinity
-    let epochsMax = 0
-    keys.forEach(key => {
-      const loss = lossReport[key]
-      epochsMax = Math.max(loss.length, epochsMax)
-      loss.forEach((a) => {
-        const v = parseFloat(a.training_loss)
-        if (! v) return
-        scaleMax = Math.max(v, scaleMax)
-        scaleMin = Math.min(v, scaleMin)
-      })
-    })
-    // scaleMax *= 10
-    console.log(scaleMax, scaleMin, epochsMax)
-
-    scaleMax = 3
-    scaleMin = 0
-    const margin = 0
-    const wmin = 0
-    const wmax = w
-    const hmin = 0
-    const hmax = h
-    const epochsScaleFactor = 1 // 3/2
-
-    let X, Y
-    for (var ii = 0; ii < epochsMax; ii++) {
-      X = lerp((ii)/(epochsMax/(epochsScaleFactor))*(epochsScaleFactor), wmin, wmax)
-      ctx.strokeStyle = 'rgba(0,0,0,0.3)'
-      ctx.beginPath(0, 0)
-      ctx.moveTo(X, 0)
-      ctx.lineTo(X, h)
-      ctx.lineWidth = 1
-      // ctx.stroke()
-      if ( (ii % 5) === 0 ) {
-        ctx.lineWidth = 2
-        ctx.stroke()
-        const fontSize = 12
-        ctx.font = 'italic ' + (fontSize * devicePixelRatio) + 'px "Georgia"'
-        ctx.fillStyle = 'rgba(0,12,28,0.6)'
-        ctx.fillText(ii/5*6, X + (8 * devicePixelRatio), h - ((fontSize + 4) * devicePixelRatio))
-      }
-    }
-    for (var ii = scaleMin; ii < scaleMax; ii += 1) {
-      Y = lerp(ii/scaleMax, hmin, hmax)
-      // ctx.strokeStyle = 'rgba(255,255,255,1.0)'
-      ctx.beginPath(0, 0)
-      ctx.moveTo(0, (h-Y))
-      ctx.lineTo(w, (h-Y))
-      ctx.lineWidth = 1
-      // ctx.stroke()        
-      // if ( (ii % 1) < 0.1) {
-        // ctx.strokeStyle = 'rgba(255,255,255,1.0)'
-        ctx.lineWidth = 2
-        ctx.setLineDash([4, 4])
-        ctx.stroke()        
-        ctx.stroke()
-        ctx.stroke()        
-        ctx.setLineDash([0,0])
-        const fontSize = 12
-        ctx.font = 'italic ' + (fontSize * devicePixelRatio) + 'px "Georgia"'
-        ctx.fillStyle = 'rgba(0,12,28,0.6)'
-        ctx.fillText(ii.toFixed(1), w-50, (h-Y) + fontSize + (10 * devicePixelRatio))
-      // }
-    }
-    ctx.lineWidth = 1
-
-    keys.forEach(key => {
-      const loss = lossReport[key]
-      const vf = parseFloat(loss[loss.length-1].training_loss) || 0
-      const vg = parseFloat(loss[0].training_loss) || 5
-      // console.log(vf)
-      const vv = 1 - norm(vf, scaleMin, scaleMax/2)
-      ctx.lineWidth = (1-norm(vf, scaleMin, scaleMax)) * 5
-      ctx.strokeStyle = 'rgba(' + [randrange(30,190), randrange(30,150), randrange(60,120)].join(',') + ',' + 0.8+ ')'
-      let begun = false
-      loss.forEach((a, i) => {
-        const v = parseFloat(a.training_loss)
-        if (! v) return
-        const x = lerp((i-2)/(epochsMax/(epochsScaleFactor))*(epochsScaleFactor), wmin, wmax)
-        const y = lerp(norm(v, scaleMin, scaleMax), hmax, hmin)
-        if (i === 0) {
-          return
-        }
-        if (! begun) {
-          begun = true
-          ctx.beginPath(x,y)
-        } else {
-          ctx.lineTo(x,y)          
-          // ctx.stroke()
-        }
-      })
-      ctx.stroke()
-      const i = loss.length-1
-      const v = parseFloat(loss[i].training_loss)
-      const x = lerp((i-2)/(epochsMax/(epochsScaleFactor))*(epochsScaleFactor), wmin, wmax)
-      const y = lerp(norm(v, scaleMin, scaleMax), hmax, hmin)
-      const fontSize = 9
-      ctx.font = 'italic ' + (fontSize * devicePixelRatio) + 'px "Georgia"'
-      ctx.fillText(key, x + fontSize, y + fontSize)
-    })
-  }
-}
-
-const mapStateToProps = state => ({
-  samplernn: state.module.samplernn,
-})
-
-const mapDispatchToProps = (dispatch, ownProps) => ({
-  actions: bindActionCreators(samplernnActions, dispatch),
-})
-
-export default connect(mapStateToProps, mapDispatchToProps)(SampleRNNLoss)