minesh1291

logprob, seq = model.decode(np.array([[1,2,0]]).transpose())
print(math.exp(logprob))
print(seq)

logprob, seq = model.decode(np.array([[2,2,2]]).transpose())
print(math.exp(logprob))
print(seq)

minesh1291

import os
import urllib

import numpy as np
from numpy.lib.stride_tricks import as_strided
import matplotlib.pyplot as plt
import scipy
from scipy.io import wavfile
from sklearn.model_selection import StratifiedShuffleSplit
from hmmlearn import hmm

minesh1291

#######################
# feature engineering #
#######################   

def stft(x, fftsize=64, overlap_pct=.5):   
    #Modified from http://stackoverflow.com/questions/2459295/stft-and-istft-in-python
    hop = int(fftsize * (1 - overlap_pct))
    w = scipy.hanning(fftsize + 1)[:-1]    
    raw = np.array([np.fft.rfft(w * x[i:i + fftsize]) for i in range(0, len(x) - fftsize, hop)])
    return raw[:, :(fftsize // 2)]

minesh1291

#######################
# split training data #
#######################

sss = StratifiedShuffleSplit(n_splits=2, test_size=0.1, random_state=0)
sss.get_n_splits(all_obs, all_labels)

for n,i in enumerate(all_obs):
    all_obs[n] /= all_obs[n].sum(axis=0)

minesh1291

import numpy as np
from scipy.spatial.distance import cdist
from .dtw import dtw
from .lb import envelope, lb_keogh_cdist, lb_keogh_from_bounds
from .window import window_ts

def dtw_nearest_neighbours(query, db, bound_reach, step_size, subseq=False):
    assert query.ndim == 1
    assert db.ndim == 2
    assert query.flags.contiguous

minesh1291

Toc

Keyboard shortcuts

The IPython Notebook has two different keyboard input modes. Edit mode allows you to type code/text into a cell and is indicated by a green cell border. Command mode binds the keyboard to notebook level actions and is indicated by a grey cell border.

MacOS modifier keys:

• ⌘ : Command

minesh1291

Since Gmail discontinued the "Fixed-width fonts" lab, here's a CSS hack to use a
monospace font for incoming mail:

1. Install the dotjs extension:

https://addons.mozilla.org/en-US/firefox/addon/dotjs/

2. Put this in ~/.css/mail.google.com.css:

/* Read messages in fixed-width font */

minesh1291

# pred_batch shape is (N, CLASS_COUNT), where N is the batch size
# it is returned by Keras as a probabilities/logits
# this converts the probabilities to a 1 hot vector
pred_batch = model.predict_on_batch(image_batch)
pred_batch = (pred_batch == pred_batch.max(axis=1)).astype(int)

minesh1291

import functools
import dask
import dask.dataframe as dd
import pandas as pd

pdf = pd.DataFrame({
    'x': range(0, 100),
    'y': range(0, 100),
    'z': range(0, 100)
})

minesh1291

import functools

def prepost(func=None, *, prefix=''):
    def prepost_(func):
        @functools.wraps(func)
        def wrapper(*args, **kwargs):
            print(f'{prefix} start')
            result = func(*args, **kwargs)
            print(f'{prefix} end')
            return result