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Description:
Step1: Now let's try applying a weighting in the frequency domain that doesn't change the TD variance.
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Python Code:
invasd = sqrt(2./srate)/sqrt(shaped_psd1)
invasd[0] = 0.
whitener = sig.hann(seglen*srate)*roll(irfft(invasd), seglen*srate/2)
wtest = TimeSeries(sig.convolve(shaped_noise2, whitener, mode='same')[8*srate:-8*srate],
sample_rate=srate)
p1 = wtest.psd(seglen).plot()
m... |
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Description:
Step1: Pandas
Step2: <hr>
Step3: <hr>
Step4: Keyboard Shortcuts
Step5: В IPython встроенны несколько полезных magic commands, одна из них %time поз... | <ASSISTANT_TASK:>
Python Code:
from IPython.display import IFrame
IFrame('http://jupyter.org/', width='100%', height=350)
from IPython.display import IFrame
IFrame('http://i.giphy.com/12Y8uwQsnpizCw.gif', width='100%', height=350)
from IPython.display import IFrame
IFrame('http://pandas.pydata.org/', width='100%', hei... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We will start by node label prediction. Download this network. It contains protein communications in Baker’s yeast. Each node (protein) has a sp... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import scipy as sp
import networkx as nx
%matplotlib inline
g = nx.read_gml('./data/ppi.CC.gml.txt')
cc = list(nx.connected_components(g))
g = nx.subgraph(g,cc[0])
g = nx.relabel.convert_node_labels_to_integers(g)
labels = np.array(nx.ge... |
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Description:
Step1: As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
Step2: Dataset Parameters
Step3:... | <ASSISTANT_TASK:>
Python Code:
!pip install -I "phoebe>=2.1,<2.2"
%matplotlib inline
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.default_binary()
b.add_dataset('lp', times=[0,1,2], wavelengths=np.linspace(549, 551, 101))
print b.fil... |
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Description:
Step1: PT3S
Step2: Install PT3S to site-packages
Step3: Logging
Step5: about from PT3S ... import ... and pip install -e .
Step6: ggf. Tests
Step7:... | <ASSISTANT_TASK:>
Python Code:
import doctest
>>> from platform import python_version
>>> print(python_version())
3.8.8
doctest.testmod()
### ggf. Rechte erforderlich:
### entweder in PowerShell: Start-Process powershell -Verb runAs
### oder RechteMausTaste WindowsSymbol: Windows PowerShell (Administrator)
### dann ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The dataset we just generated looks like this
Step2: Next up, let's split the dataset into a training and test set. The training set will be us... | <ASSISTANT_TASK:>
Python Code:
# Creating the dataset
# e.g. make_moons generates crescent-shaped data
# Check out make_classification, which generates ~linearly-separable data
from sklearn.datasets import make_moons
X, y = make_moons(
n_samples=500, # the number of observations
random_state=1,
noise=0.3 #... |
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Description:
Step1: And some more specialized dependencies
Step2: Configuration for this figure.
Step3: Open a chest located on a remote globus endpoint and load ... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
matplotlib.rcParams['figure.figsize'] = (10.0, 8.0)
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp1d, InterpolatedUnivariateSpline
from scipy.optimize import bisect
import json
from functools import partial
clas... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: If you want to use the CoNLL-03 corpus, you need to download it and unpack it in your Flair data and model folder. This folder should be in your... | <ASSISTANT_TASK:>
Python Code:
from flair.data import Corpus
from flair.datasets import WNUT_17
from flair.embeddings import TokenEmbeddings, WordEmbeddings, StackedEmbeddings
from typing import List
corpus: Corpus = WNUT_17().downsample(0.1)
print(corpus)
tag_type = 'ner'
tag_dictionary = corpus.make_tag_dictionary... |
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Description:
Step1: 5. Check conda installs
Step2: 6. Check pip installs
Step3: 7. Download data
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Python Code:
!python -V
# Should be 3.5
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import ricker
import pandas as pd
import requests
import numba
import ipyparallel as ipp
import obspy
import geopandas as gpd # Not a catastrophe if missing.
import folium # Not a catastro... |
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Description:
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Python Code:
import pandas as pd
df = pd.DataFrame({'datetime': ['2015-12-01 00:00:00-06:00', '2015-12-02 00:01:00-06:00', '2015-12-03 00:00:00-06:00']})
df['datetime'] = pd.to_datetime(df['datetime'])
df['datetime'] = df['datetime'].dt.tz_localize(None)
df.sort_values(by='datetime', inplace=True)
df[... |
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Description:
Step1: Lorenz system
Step3: Write a function solve_lorenz that solves the Lorenz system above for a particular initial condition $[x(0),y(0),z(0)]$. Y... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
def lorentz_derivs(yvec, t, sigma, rho, beta):
x = yvec[0]
y = yvec[1]
z = yvec[2]
dx = sigma*(y-x)
dy = x*(rho-z)... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Basic marker
Step2: Circle Marker
Step3: Icon Marker
Step4: RGB(A) to HEX colors
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Python Code:
import folium
carte = folium.Map(location=[45.5236, -122.6750], zoom_start=12)
marker = folium.Marker([45.5, -122.7], popup='Un marker')
marker.add_to(carte)
carte
carte = folium.Map(location=[45.5236, -122.6750], zoom_start=12)
circle = folium.CircleMarker(
[45.5, -122.7],
radi... |
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Description:
Step1: Next we choose a model and hyperparameters. Here we'll use a k-neighbors classifier with n_neighbors=1.
Step2: Then we train the model, and use... | <ASSISTANT_TASK:>
Python Code:
from sklearn.datasets import load_iris
iris = load_iris()
X = iris.data
y = iris.target
from sklearn.neighbors import KNeighborsClassifier
model = KNeighborsClassifier(n_neighbors=1)
model.fit(X, y)
y_model = model.predict(X)
from sklearn.metrics import accuracy_score
accuracy_score(y,... |
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Description:
Step1: Contents
Step2: 2. Different ways of learning from data
Step3: In the plot we can easily see that the blue points are concentrated on the top-... | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
%run ../scripts/1/discretize.py
data
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
# Adding a little bit of noise so that it's easier to visualize
data_with_noise = data.iloc[:, :2] + np.random.normal(loc=0, scale=0.1, size=(150,... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <center><img src="https
Step2: A grouping pattern, avoiding quadratic time
Step3: the bad way, quadratic time
Step4: there is a better approa... | <ASSISTANT_TASK:>
Python Code:
__AUTHORS__ = {'am': ("Andrea Marino",
"andrea.marino@unifi.it",),
'mn': ("Massimo Nocentini",
"massimo.nocentini@unifi.it",
"https://github.com/massimo-nocentini/",)}
__KEYWORDS__ = ['Python', 'Jupyter', ... |
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Description:
Step1: 1. Register a model
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Python Code:
# restart your notebook if prompted on Colab
try:
import verta
except ImportError:
!pip install verta
import os
# Ensure credentials are set up, if not, use below
# os.environ['VERTA_EMAIL'] =
# os.environ['VERTA_DEV_KEY'] =
# os.environ['VERTA_HOST'] =
from verta import Client... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Keras 예제에서 잘라내기
Step2: 잘라내기 없이 MNIST에 대한 모델 훈련하기
Step3: 기준 테스트 정확성을 평가하고 나중에 사용할 수 있도록 모델을 저장합니다.
Step4: 잘라내기로 사전 훈련된 모델 미세 조정하기
Step5: 기준선과... | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: First we need to define materials that will be used in the problem
Step2: With our three materials, we can now create a Materials object that c... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import math
import matplotlib.pyplot as plt
import numpy as np
import openmc
import openmc.mgxs
# 1.6 enriched fuel
fuel = openmc.Material(name='1.6% Fuel')
fuel.set_density('g/cm3', 10.31341)
fuel.add_nuclide('U235', 3.7503e-4)
fuel.add_nuclide('U238', 2.2625e-2)
fuel... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The following function runs a random model with a random independent variable y and four random covariates, using both the statsmodels and sciki... | <ASSISTANT_TASK:>
Python Code:
from data_cleaning_utils import import_data
dat = import_data('../Data/Test/pool82014-10-02cleaned_Subset.csv')
from regression import compare_OLS
compare_OLS(dat)
%matplotlib inline
from regression import user_model
user_model(data=dat)
%matplotlib inline
import pandas as pd
from regre... |
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Description:
Step1: Then, read the (sample) input tables for blocking purposes.
Step2: Combining Multiple Blockers
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Python Code:
# Import py_entitymatching package
import py_entitymatching as em
import os
import pandas as pd
# Get the datasets directory
datasets_dir = em.get_install_path() + os.sep + 'datasets'
# Get the paths of the input tables
path_A = datasets_dir + os.sep + 'person_table_A.csv'
path_B = datas... |
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Description:
Step1: Now we set up all necessary simulation parameters
Step2: Next we set up the system. As in part I, the orientation of the dipole moments is set ... | <ASSISTANT_TASK:>
Python Code:
import espressomd
import espressomd.magnetostatics
espressomd.assert_features('DIPOLES', 'LENNARD_JONES')
import numpy as np
lj_sigma = 1
lj_epsilon = 1
lj_cut = 2**(1. / 6.) * lj_sigma
# magnetic field constant
mu_0 = 1.
# Particles
N = 1000
# Volume fraction
# phi = rho * 4. / 3. * np.... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Split data into training and validation sets
Step2: Redefining the problem
Step3: Scaling
Step4: Parameters
Step5: Basic RNN
Step6: Executi... | <ASSISTANT_TASK:>
Python Code:
# Import libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
# Import data, format dates, sort data ascending by date
data = pd.read_csv(
'data/AirPassengers.csv',
sep=',',
header=0,
names=['date','no_passengers'],
u... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: What versions are we running?
Step2: Local Functions
Step3: Generate Data
Step4: View means of the various combinations (poisson mean values)... | <ASSISTANT_TASK:>
Python Code:
## Interactive magics
%matplotlib inline
%qtconsole --colors=linux
import sys
import warnings
warnings.filterwarnings('ignore')
import regex as re
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import patsy as pt
from scipy import optimize
# p... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Carte en moyenne temporelle sur la totalité de l'expérience
Step2: Carte en moyenne temporelle de $\chi$
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Python Code:
filename = 'resultat.nc'
import numpy as np
import matplotlib.pyplot as plt
from pylab import *
import cartopy.crs as ccrs
from netCDF4 import Dataset
from scipy.special import logit, expit
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
data = Dataset(filename)
longi... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We first define a function to prepare the datas in the format of keras (theano). The function also reduces the size of the imagesfrom 100X100 to... | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import tools as im
from matplotlib import pyplot as plt
from skimage.transform import resize
%matplotlib inline
path=os.getcwd()+'/' # finds the path of the folder in which the notebook is
path_train=path+'images/train/'
path_test=path+'images/test/'
path_real... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: MIDAS ADL
Step2: Figure 1
Step3: Mixing Frequencies
Step4: The arguments here are as follows
Step5: You can also call forecast directly. Th... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import datetime
import numpy as np
import pandas as pd
from midas.mix import mix_freq
from midas.adl import estimate, forecast, midas_adl, rmse
gdp = pd.read_csv('../tests/data/gdp.csv', parse_dates=['DATE'], index_col='DATE')
pay = pd.read_csv('../tests/data/pay.csv',... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The modified SVHN dataset can be found at
Step2: Below is a skeleton of the SVHN data iterator for you to fill out, with notes to help along th... | <ASSISTANT_TASK:>
Python Code:
from neon.backends import gen_backend
be = gen_backend(batch_size=128, backend='gpu')
# set the debug level to 10 (the minimum)
# to see all the output
import logging
main_logger = logging.getLogger('neon')
main_logger.setLevel(10)
import cPickle
fileName = 'data/svhn_64.p'
print("Loadin... |
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Description:
Step1: Problème
Step2: Idée de la solution
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Python Code:
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
from IPython.display import Image
Image("http://www.xavierdupre.fr/app/code_beatrix/helpsphinx/_images/biodiversite_tri2.png")
from pyquickhelper.helpgen import NbImage
NbImage("data/hexa.png")
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: There are a few frequency bands that are already part of the possum class
Step2: Polarization Spectra
Step3: Faraday Rotation
Step4: Generati... | <ASSISTANT_TASK:>
Python Code:
from possum import *
spec = possum()
spec._createASKAP12()
print('Min Frequency (Hz): {:e}'.format(spec.nu_.min()))
print('Max Frequency (Hz): {:e}'.format(spec.nu_.max()))
spec = possum()
spec._createFrequency(600, 800, 100, store=True)
# ===============================================... |
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Description:
Step2: Computing the trajectories and plotting the result
Step3: Let's call the function once to view the solutions. For this set of parameters, we se... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from ipywidgets import interact, interactive
from IPython.display import clear_output, display, HTML
import numpy as np
from scipy import integrate
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import cnames
from mat... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now we can plot the results. The Probe records the vector coming out of the answer variable, so in order to interpret that we can do the dot-pr... | <ASSISTANT_TASK:>
Python Code:
import nengo_spa as spa
import nengo
model = spa.Network()
with model:
# configure Nengo to just directly conpute things, rather than trying to implement the
# network with neurons
model.config[nengo.Ensemble].neuron_type = nengo.Direct()
model.config[nengo.Connection].sy... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Basics
Step2: You can assign several variables at once
Step3: There is no "begin-end"! You use indentation to specify blocks. Here is simple I... | <ASSISTANT_TASK:>
Python Code:
# you can mix text and code in one place and
# run code from a Web browser
a = 10
a
a, b = 1, 2
a, b
b, a = a, b
a, b
if a > b:
print("A is greater than B")
else:
print("B is greater than A")
# Integer
a = 1
print(a)
# Float
b = 1.0
print(b)
# String
c = "Hello world"
print(c)... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Exercise
Step2: Recursively computing values of a polynomial using difference equations
Step3: Second order polynomial
| <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scipy.signal as signal
import matplotlib.pyplot as plt
%matplotlib inline
# Define the continuous-time linear time invariant system F
a = 2
b = 1
num = [1, b]
den = [1, a]
F = signal.lti(num, den)
# Plot a step response
(t, y) = signal.step(F)
plt.figure(figsize=... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The Theory (section 6.3.3 - 6.3.5 of the syllabus)
Step2: Convenience function for setting up graphs
Step3: Draw the Theis type curve
Step4: ... | <ASSISTANT_TASK:>
Python Code:
from scipy.special import exp1 as W
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import exp1 as W
def newfig(title='forgot title?', xlabel='forgot the x-label?', ylabel='forgot the y-label?',
xlim=None, ylim=None, xscale='linear', yscale='linear', siz... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Install the required libraries
Step2: Wait for the message Configure docker credentials before moving on to the next cell.
Step3: Configure a ... | <ASSISTANT_TASK:>
Python Code:
import logging
import os
import uuid
from importlib import reload
from oauth2client.client import GoogleCredentials
credentials = GoogleCredentials.get_application_default()
import notebook_setup
reload(notebook_setup)
notebook_setup.notebook_setup()
import k8s_util
# Force a reload of ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: When feature_weight = None, the output should match Random Forest.
Step2: When feature_weight is uniform, it should give the same feature impor... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from sklearn.datasets import load_breast_cancer
import numpy as np
from functools import reduce
# Import our custom utilities
from imp import reload
from utils import irf_jupyter_utils
from utils import irf_utils
reload(irf_jupyter_utils)... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The first two lines deal with the ability to show your graphs (generated via matplotlib) within this notebook, the remaining two lines import ma... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# plots graphs within the notebook
%config InlineBackend.figure_format='svg' # not sure what this does, may be default images to svg format
import matplotlib.pyplot as plt #calls the plotting library hereafter referred as to plt
import numpy as np
L = 8*np.pi
N = 200
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Plots
Step2: Looking at Node size conditional probabilities
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Python Code:
# Necessary imports
import os
import time
from nbminer.notebook_miner import NotebookMiner
from nbminer.cells.cells import Cell
from nbminer.features.ast_features import ASTFeatures
from nbminer.stats.summary import Summary
from nbminer.stats.multiple_summary import MultipleSummary
#Load... |
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Description:
Step1: Najprej sem spletne strani FIS pobrala podatke o smučarjih in njihovih id številkah na spletišču FIS. Id-je sem potrebovala za sestavljanje url ... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as py
#import scipy
# Make the graphs a bit prettier, and bigger
#pd.set_option('display.mpl_style', 'default')
#plt.rcParams['figure.figsize'] = (15, 5)
# This is necessary to show lots of columns in pand... |
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Description:
Step1: Generate the data
Step2: Calculate the covariance matrix and get the eigen values/vectors
Step3: Plot the eigen vectors on the data
Step4: No... | <ASSISTANT_TASK:>
Python Code:
# to display interactive plots within the notebook
%matplotlib notebook
# to define the size of the plotted images
from pylab import rcParams
rcParams['figure.figsize'] = (10, 8)
import matplotlib.pyplot as plt
import numpy as np
from fct import generate_multivariate, normalize, plot_3d, ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This code sets up Ipython Notebook environments (lines beginning with %), and loads several libraries and functions. The core scientific stack ... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import math
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sbn
##from scipy import *
x = .5
print x
x_vector = np.array([1,2,3])
print x_vector
c_list = [1,2]
print "The list:",c_list
print "Has length:", len(c_list)
c_vector = np.array(c_list)
... |
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Description:
Step1: 2. Calculate the translational partition function of a CO molecule in the bottle at 298 K. What is the unit of the partition function?
Step2: 3... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
hbar = 1.05457e-34 # J*s
h = 6.62607e-34 # J*s
kB = 1.38065e-23 # J/K
m = 28.01*1.6605e-27 # kg/molecule
V = 0.02 # m^3
c = 2.99792e10 # cm/s
B = 1.931 # cm^-1
v = 2156.6 # cm^-1
T_trans = np.pi**2*hbar**2/2/m/V**(2/3)/kB
T_rot = h*c*B/kB... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Grab the min and max submission dates for filtering main_summary.
Step2: Load in main_summary, filtered to the min date of the experiment, and ... | <ASSISTANT_TASK:>
Python Code:
S3_PATH = "s3://net-mozaws-prod-us-west-2-pipeline-analysis/taarv2/cleaned_data/"
# Select essential columns.
clean_data = sqlContext.read.parquet(S3_PATH).select('client_id', 'locale', 'branch', 'submission_date_s3')
# Display number of rows per branch.
clean_data.groupBy('branch').count... |
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Description:
Step1: obtido no site <a href="http
Step2: O módulo ElementTree (ET)
Step3: Para vermos o elemento raiz da árvore, usamos
Step4: O objeto root, que ... | <ASSISTANT_TASK:>
Python Code:
arquivo = "IDEB por Município Rede Federal Séries Finais (5ª a 8ª).xml"
import xml.etree.ElementTree as ET
tree = ET.parse(arquivo)
root = tree.getroot()
root.tag
root.attrib
for child in root:
print(child.tag, child.attrib)
valoresIDEB = root.find('valores')
valoresIDEB
valore... |
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Description:
Step1: KL and non overlapping distributions
Step2: Approximation of the ratio using the f-gan approach
Step3: Gradients
Step4: Wasserstein distance ... | <ASSISTANT_TASK:>
Python Code:
import jax
import random
import numpy as np
import jax.numpy as jnp
import seaborn as sns
import matplotlib.pyplot as plt
import scipy
!pip install -qq dm-haiku
!pip install -qq optax
try:
import haiku as hk
except ModuleNotFoundError:
%pip install -qq haiku
import haiku as hk... |
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Description:
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Python Code:
import numpy as np
a = [np.array([1,2,3]),np.array([1,2,3]),np.array([1,2,3])]
def all_equal(iterator):
try:
iterator = iter(iterator)
first = next(iterator)
return all(np.array_equal(first, rest) for rest in iterator)
except StopIteration:
return T... |
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Description:
Step1: If you already have an H2O cluster running that you'd like to connect to (for example, in a multi-node Hadoop environment), then you can specify... | <ASSISTANT_TASK:>
Python Code:
import h2o
# Start an H2O Cluster on your local machine
h2o.init()
# This will not actually do anything since it's a fake IP address
# h2o.init(ip="123.45.67.89", port=54321)
#csv_url = "http://www.stat.berkeley.edu/~ledell/data/eeg_eyestate_splits.csv"
csv_url = "https://h2o-public-tes... |
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Description:
Step1: Bubble sort
Step2: We can see the essential features of Python used
Step4: Note
Step6: This gets rid of the need for a temporary variable.
St... | <ASSISTANT_TASK:>
Python Code:
def bubblesort(unsorted):
Sorts an array using bubble sort algorithm
Paramters
---------
unsorted : list
The unsorted list
Returns
sorted : list
The sorted list (in place)
last = len(unsorted)
# All Python ... |
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Description:
Step1: Survival analysis
Step3: The survival function is just the complementary CDF.
Step4: Here's the CDF and SF.
Step5: And here's the hazard func... | <ASSISTANT_TASK:>
Python Code:
from os.path import basename, exists
def download(url):
filename = basename(url)
if not exists(filename):
from urllib.request import urlretrieve
local, _ = urlretrieve(url, filename)
print("Downloaded " + local)
download("https://github.com/AllenDowney/Thin... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Why NumPy?
Step2: Introduction
Step3: In the numpy package the terminology used for vectors, matrices and higher-dimensional data sets is arra... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import traceback
import matplotlib.pyplot as plt
import numpy as np
%%time
total = 0
for i in range(100000):
total += i
%%time
total = np.arange(100000).sum()
%%time
l = list(range(0, 1000000))
ltimes5 = [x * 5 for x in l]
%%time
l = np.arange(1000000)
ltimes5 = ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Low frequency drifts and line noise
Step2: we see high amplitude undulations in low frequencies, spanning across tens of
Step3: On MEG sensors... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import mne
from mne.datasets import sample
from mne.preprocessing import create_ecg_epochs, create_eog_epochs
# getting some data ready
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif'
raw = mne.io.read_raw_fif(raw_fname, preloa... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step 1 - Creating a Checkpoint
Step1: Pre-Questions
Step2: This table shows the top 10 water consuming counties, the population, the amount of the pop... | <ASSISTANT_TASK:>
Python Code:
# Import modules that contain functions we need
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
# Our data is a table and is defined as the word 'data'.
# 'data' is set equal to the .csv file that is read by the pandas function.
# The .csv file mu... |
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Description:
Step1: 1. Initialization of setup
Step2: 2. Elemental Mass and Stiffness matrices
Step3: 3. Flux Matrices
Step4: 4. Discontinuous Galerkin Solution
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Python Code:
# Import all necessary libraries, this is a configuration step for the exercise.
# Please run it before the simulation code!
import numpy as np
import matplotlib.pyplot as plt
from gll import gll
from lagrange1st import lagrange1st
from flux_homo import flux
# Show the plots in the Notebo... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Define helper functions
Step2: Project specific parameters
Step3: Iterate through subjects and runs
Step4: Compute 2-way correlations
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Python Code:
import pandas as pd
import json
from scipy import stats, signal, linalg
from sklearn.decomposition import PCA
import nibabel as nib
import nipype
from nipype import Node, SelectFiles, DataSink, IdentityInterface
import matplotlib as mpl
import matplotlib.pyplot as plt
mpl.use("Agg")
from ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Interaction Between Neurons - Feature Visualization
Step2: Combining Objectives
Step3: Random Directions
Step4: Aligned Interpolation
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Python Code:
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, sof... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Continuous data is stored in objects of type
Step2: <div class="alert alert-info"><h4>Note</h4><p>Accessing the `._data` attribute is done her... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import mne
import os.path as op
from matplotlib import pyplot as plt
# Load an example dataset, the preload flag loads the data into memory now
data_path = op.join(mne.datasets.sample.data_path(), 'MEG',
'sample', 'sample_audvis_r... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Describes the tests needed to validate the PutFile functionality.
Step2: Check this by running
Step3: The response should be
Step4: Verify th... | <ASSISTANT_TASK:>
Python Code:
%env CLIENT bitrepository-client-1.9-RC1
!wget -Nq "https://sbforge.org/download/attachments/25395346/${CLIENT}.zip"
!unzip -quo ${CLIENT}.zip
%alias bitmag ${CLIENT}/bin/bitmag.sh %l
#Some imports we will need later
import random
import string
TESTFILE1='README.md'
%bitmag get-file-ids... |
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Description:
Step1: <a id='sec1.3'></a>
Step2: Extract POI category and visiting frequency.
Step3: <a id='sec1.4'></a>
Step5: <a id='sec1.5'></a>
Step7: <a id='... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import os
import math
import random
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
random.seed(123456789)
data_dir = 'data/data-ijcai15'
#fvisit = os.path.join(data_dir, 'userVisits-Osak.csv')
#fcoord = os.path.join(... |
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Description:
Step1: Set parameters
Step2: Compute statistic
Step3: View time-frequency plots
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Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.time_frequency import tfr_morlet
from mne.stats import permutation_cluster_1samp_test
from mne.datasets import sample
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step4: Objects
Step5: The above construct is a class, which is to say a model for creating objects.
Step6: Now we have an object called "jyry", which... | <ASSISTANT_TASK:>
Python Code:
class Student(object):
The above states that the code-block (indented area) below will define a
class Student, that derives from a class called 'object'. Inheriting from 'object' is S
def __init__(self, name, birthyear, interest=None):
__init__ is ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Once generate data
Step2: Step 1 - collect data
Step3: Step 2 - Build model
Step4: Step 3 training the network
Step5: One epoch takes approx... | <ASSISTANT_TASK:>
Python Code:
num_units = 400 #state size
input_len = 60
target_len = 30
batch_size = 64
with_EOS = False
total_size = 57994
train_size = 46400
test_size = 11584
data_folder = '../../../../Dropbox/data'
ph_data_path = '../data/price_history'
npz_full = ph_data_path + '/price_history_dp_60to30_57994.np... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 在这个例子中，对已排序的 _sorted 元素逐个与 i 进行比较，若 i 比已排序的所有元素都大，则只能排在已排序列表的最后。这时我们就需要一个额外的状态变量 inserted 来标记完成遍历循环还是中途被 break，在这种情况下，我们可以用 else 来取代这一状态变量：
Step... | <ASSISTANT_TASK:>
Python Code:
from random import randrange
def insertion_sort(seq):
if len(seq) <= 1:
return seq
_sorted = seq[:1]
for i in seq[1:]:
inserted = False
for j in range(len(_sorted)):
if i < _sorted[j]:
_sorted = [*_sorted[:j], i, *_sorted[j:]... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2. The data
Step2: The resulting DataFrame contains a row for each user and each column represents an artist. The values indicate whether the u... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import sklearn.metrics.pairwise
data = pd.read_csv('data/lastfm-matrix-germany.csv').set_index('user')
data.head()
data.shape
### BEGIN SOLUTION
similarity_matrix = sklearn.metrics.pairwise.cosine_similarity(np.transpose(data))
### END SOLUTION
# s... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Comparing distributions
Step2: Based on the data, the distribution for Rhode is slightly farther right than the distribution for Wei, but there... | <ASSISTANT_TASK:>
Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import classes from thinkbayes2
from thinkbayes2 import Hist, Pmf, Suite, ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Let's show the symbols data, to see how good the recommender has to be.
Step2: Let's run the trained agent, with the test set
Step3: And now a... | <ASSISTANT_TASK:>
Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
from multiprocessing import Pool
import pickle
%... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: What do we mean when we say local scope?
Step2: What would change if you added the line global name into the function update_name?
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Python Code:
initial_var = 358645317684531432678
name = "Oi, you there"
def update_name():
name = "what?"
print(name)
update_name()
print(name)
num_one = None
num_two = None
def power(one, two):
pass
from nose.tools import assert_equal, assert_not_equal
assert_equal(square(12,2), 144)
a... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Here's the Rosenbrock function in code. Since we're pretending it's the log-posterior, I've introduced a minus sign that doesn't normally appear... | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
Image(filename="DifficultDensities_banana_eg.png", width=350)
def Rosenbrock_lnP(x, y, a=1.0, b=100.0):
return -( (a-x)**2 + b*(y-x**2)**2 )
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (8.0,... |
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Description:
Step1: As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
Step2: Dataset Parameters
Step3:... | <ASSISTANT_TASK:>
Python Code:
!pip install -I "phoebe>=2.0,<2.1"
%matplotlib inline
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.default_binary()
ps, constraints = phoebe.dataset.orb()
print ps
print ps['times']
ps_compute = phoeb... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
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Python Code:
mod = 1000000007
def waysToColor(arr , n , k ) :
global mod
powOf2 =[0 for i in range(500 ) ]
c =[[ 0 for i in range(500 ) ] for j in range(500 ) ]
for i in range(n + 1 ) :
c[i ][0 ] = 1 ;
for j in range(1 , i + 1 ) :
c[i ][j ] =(c[i - 1 ][j ] + c[i - 1 ][j - 1 ] ) % mo... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Basic matrix arithmetics like
Step2: In mathematics, the dot product is an algebraic operation that takes two coordinate vectors of equal size ... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
x = np.array([1,5,2])
y = np.array([7,4,1])
x + y
x * y
x - y
x / y
x % y
x = np.array([1,2,3])
y = np.array([-7,8,9])
dot = np.dot(x,y)
np.dot(x,y)
x = np.array( ((2,3), (3, 5)) )
y = np.array( ((1,2), (5, -1)) )
x * y
x = np.matrix( ((2,3), (3, 5)) )
y = np.matrix(... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Setup the axon code
Step3: Single example axon, how does a0 (intial volage) drift with the number of nodes?
Step4: Now let's run axon for a fe... | <ASSISTANT_TASK:>
Python Code:
import pylab as plt
import numpy as np
%matplotlib inline
from __future__ import division
from scipy.integrate import odeint,ode
from numpy import zeros,ones,eye,tanh,dot,outer,sqrt,linspace,cos,pi,hstack,zeros_like,abs,repeat
from numpy.random import uniform,normal,choice
%config InlineB... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Install and import TFX
Step2: Please ignore the incompatibility error and warnings. Make sure to re-run the cell.
Step3: Import the MLMD libra... | <ASSISTANT_TASK:>
Python Code:
!pip install --upgrade pip
!pip install -q -U tfx
import os
import tempfile
import urllib
import pandas as pd
import tensorflow_model_analysis as tfma
from tfx.orchestration.experimental.interactive.interactive_context import InteractiveContext
from tfx import v1 as tfx
print('TFX vers... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Upper air data can be obtained using the siphon package, but for this example we will use
Step2: We will pull the data out of the example datas... | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import pandas as pd
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import add_metpy_logo, SkewT
from metpy.units import units
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.re... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Make performance scorers
Step2: Sequential Feature Selection with mlextend
Step3: The next cell will take many hours to run, skip it
Step4: R... | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn.metrics import f1_score, accuracy_score, make_scorer
filename = 'engineered_features.csv'
training_data = pd.read_csv(filename)... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load Boston Housing Dataset
Step2: Create Decision Tree
Step3: Train Model
Step4: Create Observation To Predict
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Python Code:
# Load libraries
from sklearn.tree import DecisionTreeRegressor
from sklearn import datasets
# Load data with only two features
boston = datasets.load_boston()
X = boston.data[:,0:2]
y = boston.target
# Create decision tree classifer object
regr = DecisionTreeRegressor(random_state=0)
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Restart the kernel
Step2: Before you begin
Step3: Region
Step4: Timestamp
Step5: Authenticate your Google Cloud account
Step6: Create a Clo... | <ASSISTANT_TASK:>
Python Code:
import os
# The Vertex AI Workbench Notebook product has specific requirements
IS_WORKBENCH_NOTEBOOK = os.getenv("DL_ANACONDA_HOME")
IS_USER_MANAGED_WORKBENCH_NOTEBOOK = os.path.exists(
"/opt/deeplearning/metadata/env_version"
)
# Vertex AI Notebook requires dependencies to be install... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: IPython Console
Step2: IPython Qt Console
Step3: IPython.parallel
| <ASSISTANT_TASK:>
Python Code:
from IPython.display import display, Image, HTML
from talktools import website, nbviewer
Image('images/ipython_console.png')
Image('images/ipython_qtconsole.png')
Image("images/ParallelKernels.png", width="80%")
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 10 Palavras Mais Frequentes
Step2: n-Grams
Step3: TF-IDF com CountVectorizer
| <ASSISTANT_TASK:>
Python Code:
# Bibliotecas
from pyspark.ml import Pipeline
from pyspark.ml.feature import Tokenizer, StopWordsRemover, CountVectorizer, NGram
livro = sc.textFile("Machado-de-Assis-Memorias-Postumas.txt")
text = ""
for line in livro.collect():
text += " " + line
data = spark.createDataFrame([(0, te... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Run as a Python module
Step2: Training should finish in just a few seconds because it ran outside of the Jupyter's runtime, as an independent p... | <ASSISTANT_TASK:>
Python Code:
import os
PROJECT = 'my-project-id' # REPLACE WITH YOUR PROJECT ID
BUCKET = 'my-bucket-name' # REPLACE WITH YOUR BUCKET NAME
REGION = 'us-central1' # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
MODEL_TYPE='dnn' # 'dnn' or 'cnn'
# do not change these
os.environ['PROJECT'] = PROJECT
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: In SciPy, the definition of the negative binomial distribution differs a little from the one in our introduction. They define $Y$ = Number of fa... | <ASSISTANT_TASK:>
Python Code:
import arviz as az
import bambi as bmb
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.stats import nbinom
az.style.use("arviz-darkgrid")
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
y = np.arange(0, 30)
k = 3
p1 = 0.5
p... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1) Data Source and Data Usage
Step2: From this data we calculated two key metrics which will be useful in determining which of these three arti... | <ASSISTANT_TASK:>
Python Code:
import sys # system module
import pandas as pd # data package
import matplotlib as mpl # graphics package
import matplotlib.pyplot as plt # pyplot module
import datetime as dt # date and time module
impo... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Even before you call your first TensorFlow function, a lot is going on behind the scenes. For example, an empty default graph object is created.... | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
g = tf.get_default_graph()
g
g.get_operations()
tf.constant(3.14)
g.get_operations()
const_operation = g.get_operations()[0]
len(const_operation.inputs), len(const_operation.outputs)
const_tensor = const_operation.outputs[0]
const_tensor
another_const_tensor ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: El bloque anterior se ejecuta en python y mantiene una conexión a una instancia de interprete interactivo de python, de manera que podemos usar ... | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function, division # Compatibilidad entre python 2 y 3
def imprime_division(a, b):
print(a/b)
imprime_division(4, 5)
%%latex
$\left(\frac{1}{\Gamma}\right)^{2}$
!ls -al
%%bash
touch archivoprueba.txt
ls *.txt
echo "Ya se verifico creación, ahora se elim... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: If we need only the keys 'a' and 'd', we can do this
Step2: We can also specify 'subkeys' by using a dotted-syntax
Step3: The dotted-syntax ca... | <ASSISTANT_TASK:>
Python Code:
d = {
'a': 'A',
'b': 'B',
'c': 'C',
'd': {
'x': 'D_X',
'y': 'D_Y',
'z': {
'I': 'D_Z_I',
'II': {
'1': 'D_Z_II_1',
'2': 'D_Z_II_2'
},
'III': 'D_Z_III'
}
}
}
f... |
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Description:
Step1: Step 4
Step2: Step 5
Step3: There should be 9 containers running
Step4: Step 7
Step5: There should be an additional 5 containers running
Ste... | <ASSISTANT_TASK:>
Python Code:
cd ~/nexus/esip-workshop/docker/infrastructure
docker-compose up -d cassandra1
docker logs -f cassandra1
docker-compose up -d
docker ps
cd ~/nexus/esip-workshop/docker/analysis
docker-compose up -d
docker ps
cd ~/nexus/esip-workshop/docker/ingest
docker-compose up -d
docker ps
dock... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Here we define the parameters that we use to extract all the informations from the vtk file
Step2: Now we initialize the file_handler that deal... | <ASSISTANT_TASK:>
Python Code:
import ezyrb as ez
output_name = 'Pressure'
weights_name = 'Weights'
namefile_prefix = '../tests/test_datasets/matlab_0'
file_format = '.vtk'
file_handler = ez.pod.Pod(output_name, weights_name, namefile_prefix, file_format)
file_handler.start()
while True:
add = input('Add a new s... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Notarás por el número a la izquierda (el número 1) que esa celda es diferente. Ese número significa que es el primero output o salida del progra... | <ASSISTANT_TASK:>
Python Code:
import numpy as np # Alias es np
import matplotlib.pyplot as plt # Alias es plt
T_init = 0.0 # Tiempo inicial
Tmax = 10.0 # Tiempo Total
dt= 2.0 # Salto
tiempos = np.arange(T_init, Tmax, dt)
print tiempos
T_init = 2.0 # Tiempo inicial
Tmax = 8.0 # Tiempo Total
dt= 1.0 # Salto... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'uhh', 'sandbox-1', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "emai... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Remise à zero(angle) Affichage et changement de l'id d'un moteur.
| <ASSISTANT_TASK:>
Python Code:
ports = pypot.dynamixel.get_available_ports()
if not ports:
raise IOError('no port found!')
print "Ports founds %s" % ports
for port in ports:
print('Connecting on port:', port)
dxl_io = pypot.dynamixel.DxlIO(port)
motors = dxl_io.scan()
print(" %s motors founds :... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Part 1
Step2: To cluster the images, we'll need to convert the images into a format we can pass into our KMeans model, which expects 1D feature... | <ASSISTANT_TASK:>
Python Code:
!pip install datacommons --upgrade --quiet
!pip install datacommons_pandas --upgrade --quiet
import datacommons
import datacommons_pandas
import numpy as np
import pandas as pd
# for visualization
import matplotlib.pyplot as plt
import seaborn as sns
# for clustering
from sklearn.cluster ... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The open() function opens a given filename as an object in 'read mode'.
Step2: To open a file in write mode, pass the w parameter to the open()... | <ASSISTANT_TASK:>
Python Code:
import os
os.listdir(os.path.abspath('files'))
dictionaryFile = open(os.path.abspath('files/dictionary.txt')) # Open the file
print(dictionaryFile.read()) # Read the file
print(dictionaryFile.readline()) # Read a line in the file until newline or EOF
content = dictionaryFile.read() # Sto... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Introduction
Step14: Training
Step15: Start training. Training takes about 20 ~ 30 minutes on a n1-standard-1 GCP VM.
Step16: In epoch 1, the... | <ASSISTANT_TASK:>
Python Code:
# Download and unzip data.
!mkdir -p /content/datalab/punctuation/tmp
!mkdir -p /content/datalab/punctuation/data
!mkdir -p /content/datalab/punctuation/datapreped
!wget -q -P /content/datalab/punctuation/tmp/ https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/corpora/euro... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Validate lab package version installation
Step2: Note
Step3: Note
Step4: The config.py module configures the default values for the environme... | <ASSISTANT_TASK:>
Python Code:
import yaml
# Set `PATH` to include the directory containing TFX CLI and skaffold.
PATH=%env PATH
%env PATH=/home/jupyter/.local/bin:{PATH}
!python -c "import tfx; print('TFX version: {}'.format(tfx.__version__))"
!python -c "import kfp; print('KFP version: {}'.format(kfp.__version__))"
... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Are there certain populations we're not getting reports from?
Step2: From the data, it seems that there's not much underrepresentation by gende... | <ASSISTANT_TASK:>
Python Code:
import pickle
import operator
import numpy as np
import pandas as pd
import gensim.models
data = pickle.load(open('/home/datauser/cpsc/data/processed/cleaned_api_data', 'rb'))
data.head()
pd.crosstab(data['GenderDescription'], data['age_range'])
#removing minor harm incidents
no_injuri... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <center>Find Simulations and Load data
Step2: <center>Recompose the Waveforms
Step3: <center>Plot the amplitudes to verify correct scaling bet... | <ASSISTANT_TASK:>
Python Code:
# Setup ipython environment
%load_ext autoreload
%autoreload 2
%matplotlib inline
# Setup plotting backend
import matplotlib as mpl
mpl.rcParams['lines.linewidth'] = 0.8
mpl.rcParams['font.family'] = 'serif'
mpl.rcParams['font.size'] = 12
mpl.rcParams['axes.labelsize'] = 20
from matplotli... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Language Translation
Step3: Explore the Data
Step6: Implement Preprocessing Function
Step8: Preprocess all the data and save it
Step10: Chec... | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
view_sentence_range = (0, 10)
DON'T MODIFY AN... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 3. When to use Python?
Step2: 5. Python as a calculator
Step3: 6. Variables & Types
Step4: 7. Variable Assignment
Step5: 8. Calculations wit... | <ASSISTANT_TASK:>
Python Code:
# Example, do not modify!
print(5 / 8)
# Put code below here
print(7 + 10)
# Just testing division
print(5 / 8)
# Addition works too
print(7 + 10)
# Addition and subtraction
print(5 + 5)
print(5 - 5)
# Multiplication and division
print(3 * 5)
print(10 / 2)
# Exponentiation
print(4 ** 2)... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Numpy has a really handy built-in function for padding images called pad. The required inputs are the array to be padded, the size of the pad re... | <ASSISTANT_TASK:>
Python Code:
# The standard fare:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline
# Recall our use of this module to work with FITS files in Lab 4:
from astropy.io import fits
#A dummy image - just a Gaussian PSF with a standard deviation of 5 pixels
import a... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Target distribution
Step2: Heat bath
Step3: SA algorithm
Step4: Run experiments
| <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib
matplotlib.use("nbagg")
import matplotlib.pyplot as plt
from IPython import display
from mpl_toolkits.mplot3d import Axes3D
!mkdir figures
!mkdir scripts
%cd /content/scripts
!wget -q https://raw.githubusercontent.com/probml/pyprobml/master/scripts/pyp... |
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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Import section specific modules
Step3: 1.9 A brief introduction to interferometry and its history
Step4: This function draws a double-slit set... | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
from IPython.display import display
from ipywidgets import interact
HTML('../style/code_toggle.html')
def double_slit (p0=[0],a0=[1],bas... |
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