calippo

import pandas as pd
import matplotlib.pyplot as plt
import seaborn
from sklearn.cluster import KMeans
import numpy as np
from scipy.spatial.distance import cdist, pdist

def elbow(df, n):
    kMeansVar = [KMeans(n_clusters=k).fit(df.values) for k in range(1, n)]
    centroids = [X.cluster_centers_ for X in kMeansVar]

calippo

import pandas as pd

def fillWithMean(df):
  return df.fillna(df.mean()).dropna(axis=1, how='all')

calippo

def varianceSelection(X, THRESHOLD = .95):
    sel = VarianceThreshold(threshold=(THRESHOLD * (1 - THRESHOLD)))
    sel.fit_transform(X)
    return X[[c for (s, c) in zip(sel.get_support(), X.columns.values) if s]]

calippo

object Mappable {
  implicit class ToMapOps[A](val a: A) extends AnyVal {
    import shapeless._
    import ops.record._

    def toMap[L <: HList](implicit
      gen: LabelledGeneric.Aux[A, L],
      tmr: ToMap[L]
    ): Map[String, Any] = {
      val m: Map[tmr.Key, tmr.Value] = tmr(gen.to(a))

calippo

containers:
  env:
    image: davidshen84/scikit-learn
    run:
      publish:
        - 8888:8888
      interactive: true
      tty: true
      volume: ["./data:/data", "./notebook:/notebook"]

calippo

import shapeless._

sealed trait A
case object A1 extends A 
case object A2 extends A
case object A3 extends A
case class B(
  A1: String,
  A2: String,
  A3: String

calippo

alias sbt='f() { sbt "$@" |tee -a ~/.sbtlogs; };f'

calippo

import midi #pip install python-midi (https://github.com/vishnubob/python-midi)

pattern = midi.Pattern()
track = midi.Track()
pattern.append(track)
on = midi.NoteOnEvent(tick=0, velocity=100, pitch=60)
track.append(on)
off = midi.NoteOffEvent(tick=100, pitch=60)
track.append(off)
eot = midi.EndOfTrackEvent(tick=1)

calippo

echo “very spoofy” | mail -s “much boring” recipient@domain.tld

calippo

package intervals

import scala.language.implicitConversions
import cats.Monoid
import cats.syntax.foldable._
import cats.instances.list._
import scala.math.Ordering

object Main extends App {
  import Interval._