Dapid

import random
import tqdm
import numpy as np
import pylab as plt
def trial():
  coins = []
  for _ in range(10000):
    coin = random.randint(0, 1)
    # Monday
    coins.append(coin)

Dapid

import numpy as np
from scipy import stats

import pylab as plt


def compare(x, y, keys, name):
    keys_ = set(keys).intersection(x).intersection(y)
    print(set(keys) - keys_)
    keys = set(keys).intersection(x).intersection(y)

Dapid

dimension,indicator_id,indicator_name,iso3,country_name,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,9999
Composite indices,146206,HDI rank,AFG,Afghanistan,,,,,,,,,,,,,,,,,,,,,,,,,,,168,168,
Composite indices,146206,HDI rank,ALB,Albania,,,,,,,,,,,,,,,,,,,,,,,,,,,69,68,
Composite indices,146206,HDI rank,DZA,Algeria,,,,,,,,,,,,,,,,,,,,,,,,,,,83,85,
Composite indices,146206,HDI rank,AND,Andorra,,,,,,,,,,,,,,,,,,,,,,,,,,,35,35,
Composite indices,146206,HDI rank,AGO,Angola,,,,,,,,,,,,,,,,,,,,,,,,,,,145,147,
Composite indices,146206,HDI rank,ATG,Antigua and Barbuda,,,,,,,,,,,,,,,,,,,,,,,,,,,70,70,
Composite indices,146206,HDI rank,ARG,Argentina,,,,,,,,,,,,,,,,,,,,,,,,,,,47,47,
Composite indices,146206,HDI rank,ARM,Armenia,,,,,,,,,,,,,,,,,,,,,,,,,,,84,83,
Composite indices,146206,HDI rank,AUS,Australia,,,,,,,,,,,,,,,,,,,,,,,,,,,3,3,

Dapid

$ pip install pygaussdca
Collecting pygaussdca
  Using cached https://files.pythonhosted.org/packages/f9/e5/5df8d0224318f5811c64e026ae4cd5af37288238a0b259186983e55be19c/pyGaussDCA-0.1.2.tar.gz
Requirement already satisfied: numpy in /home/david/.virtualenv/py36/lib/python3.6/site-packages (from pygaussdca) (1.16.0)
Requirement already satisfied: scipy in /home/david/.virtualenv/py36/lib/python3.6/site-packages (from pygaussdca) (1.2.0)
Requirement already satisfied: pythran>=0.8.6 in /home/david/.virtualenv/py36/lib/python3.6/site-packages (from pygaussdca) (0.9.1)
Requirement already satisfied: ply>=3.4 in /home/david/.virtualenv/py36/lib/python3.6/site-packages (from pythran>=0.8.6->pygaussdca) (3.11)
Requirement already satisfied: networkx>=2 in /home/david/.virtualenv/py36/lib/python3.6/site-packages (from pythran>=0.8.6->pygaussdca) (2.2)                                                
Requirement already satisfied: gast in /home/david/.virtualenv/py36/lib/python3.6/site-packages (from pythran>=0.8.6->py

Dapid

import keras.backend as K
from keras.models import Model, load_model
from keras.layers import Input, BatchNormalization
from keras.layers import Conv1D


def add_1D_conv(model, filters, kernel_size):
    model = Conv1D(filters, kernel_size)(model)
    model = BatchNormalization()(model)
    return model

Dapid

from __future__ import division

import keras
import keras.backend as K
from keras.models import Model, load_model
from keras.layers import Input, Dropout, BatchNormalization
from keras.layers import Conv2D, Conv1D
from keras.layers.core import Lambda
from keras.regularizers import l2
from keras.layers.advanced_activations import ELU

Dapid

$ kernprof -lv scratch_4.py 


Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
    13                                           @profile
    14                                           def run():
    15         1           47     47.0      0.1      midpoints = k[:-1] + np.diff(k)/2
    16         1           43     43.0      0.1      idx_aux = np.searchsorted(sortedA, midpoints)
    17         1            1      1.0      0.0      idx = []

Dapid

import tables

class H5Generator(object):
    def __init__(self, h5file):
        self.h5 = tables.open_file(h5file)
        self.n_rows = int(self.h5.root.target.shape[0])
        self.ix = 0

        self.feature_keys = ('atom_contacts', 'residue_contacts', 'rsa', 'surface_area_bins', 'dssp_ss', 'pssm')
        self.target_key = 's_score'

Dapid

from __future__ import division
import collections

from keras import backend as K
from keras import activations, initializations, regularizers, constraints
from keras.engine import InputSpec
from keras.engine.topology import Layer


class Tensordot(Layer):

Dapid

(py27)[david@SQUIDS gpy_memtest]$ python memtest.py gpy
 /home/david/.virtualenvs/py27/lib/python2.7/site-packages/numpy/core/numeric.py:294: FutureWarning:in the future, full((3, 3), 666) will return an array of dtype('int64')
 /home/david/.virtualenvs/py27/lib/python2.7/site-packages/numpy/core/numeric.py:294: FutureWarning:in the future, full((3, 1), 42) will return an array of dtype('int64')
0
[]
191
[<GPy.models.gp_regression.GPRegression object at 0x7f97ce48f0d0>, {'_added_names_': set(['Gaussian_noise', 'rbf']), 'sampling_runs': [], 'mean_function': None, 'Y_normalized': ObsAr([[ 42.],
       [ 42.],
       [ 42.]]), '_fixes_': None, '_optimizer_copy_transformed': False, 'size': 3, 'parameters': [<GPy.core.parameterization.ties_and_remappings.Tie object at 0x7f97ce48fd90>, <GPy.kern._src.rbf.RBF object at 0x7f97ce48f1d0>, <GPy.likelihoods.gaussian.Gaussian object at 0x7f97ce48f850>], 'priors': <GPy.core.parameterization.index_operations.ParameterIndexOperations object at 0x7f97ce48fb50>, 'output_dim':