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1,200 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright (c) 2015, 2016 Sebastian Raschka
https
Step1: The use of watermark is optional. You can install this IPython extension via "pip install watermark". For more information, please se... | Python Code:
%load_ext watermark
%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,sklearn,nltk
Explanation: Copyright (c) 2015, 2016 Sebastian Raschka
https://github.com/rasbt/python-machine-learning-book
MIT License
Python Machine Learning - Code Examples
Chapter 8 - Applying Machine Learning To S... |
1,201 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression with scikit-learn and statmodels
This notebook demonstrates how to conduct a valid regression analysis using a combination of Sklearn and statmodels libraries. While sklearn is po... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
Explanation: Regression with scikit-learn and statmodels
This notebook demonstrates how to conduct a valid regression analysis using a combination of Sklearn and statmodels libraries. While sklearn is popular and p... |
1,202 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DATASCI W261
Step1: Data Visualiazation
Step2: MrJob class code
The solution of linear model $$ \textbf{Y} = \textbf{X}\theta $$ is
Step3: Driver
Step4: Gradient descent - doesn't work | Python Code:
%matplotlib inline
import numpy as np
import pylab
size = 1000
x = np.random.uniform(-40, 40, size)
y = x * 1.0 - 4 + np.random.normal(0,5,size)
data = zip(range(size),y,x)
#data = np.concatenate((y, x), axis=1)
np.savetxt('LinearRegression.csv',data,'%i,%f,%f')
data[:10]
Explanation: DATASCI W261: Machin... |
1,203 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Run from bootstrap paths
Now we will use the initial trajectories we obtained from bootstrapping to run an MSTIS simulation. This will show both how objects can be regenerated from storage a... | Python Code:
%matplotlib inline
import openpathsampling as paths
import numpy as np
import math
# the openpathsampling OpenMM engine
import openpathsampling.engines.openmm as eng
Explanation: Run from bootstrap paths
Now we will use the initial trajectories we obtained from bootstrapping to run an MSTIS simulation. Thi... |
1,204 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This notebook demonstrates how to perform diffusivity and ionic conductivity analyses starting from a series of VASP AIMD simulations using Python Materials Genomics (pymatgen) ... | Python Code:
from IPython.display import Image
%matplotlib inline
import matplotlib.pyplot as plt
import json
import collections
from pymatgen.core import Structure
from pymatgen.analysis.diffusion_analyzer import DiffusionAnalyzer, \
get_arrhenius_plot, get_extrapolated_conductivity
from pymatgen.analysis.diffusio... |
1,205 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Lasso
Modified from the github repo
Step1: Hitters dataset
Let's load the dataset from the previous lab.
Step2: Exercise Compare the previous methods to the Lasso on this dataset. Tun... | Python Code:
# %load ../standard_import.txt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import scale
from sklearn.model_selection import LeaveOneOut
from sklearn.linear_model import LinearRegression, lars_path, Lasso, LassoCV
%matplotlib inline
n=100
p=1000
X = np.... |
1,206 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Keras Backend
In this notebook we will be using the Keras backend module, which provides an abstraction over both Theano and Tensorflow.
Let's try to re-implement the Logistic Regression Mod... | Python Code:
import keras.backend as K
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from kaggle_data import load_data, preprocess_data, preprocess_labels
X_train, labels = load_data('../data/kaggle_ottogroup/train.csv', train=True)
X_train, scaler = preprocess_data(X_train)
Y_train, encoder = p... |
1,207 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Feedback or issues?
For any feedback or questions, please open an issue.
Vertex SDK for Python
Step1: Enter your project and GCS bucket
Enter your Project Id in the cell below. Then run the... | Python Code:
!pip3 uninstall -y google-cloud-aiplatform
!pip3 install --upgrade google-cloud-kms
!pip3 install google-cloud-aiplatform
import IPython
app = IPython.Application.instance()
app.kernel.do_shutdown(True)
Explanation: Feedback or issues?
For any feedback or questions, please open an issue.
Vertex SDK for Pyt... |
1,208 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
User guide and example for the Landlab SPACE component
This notebook provides a brief introduction and user's guide for the Stream Power And Alluvial Conservation Equation (SPACE) component ... | Python Code:
## Import Numpy and Matplotlib packages
import numpy as np
import matplotlib.pyplot as plt # For plotting results; optional
## Import Landlab components
# Pit filling; optional
from landlab.components import DepressionFinderAndRouter
# Flow routing
from landlab.components import FlowAccumulator
# SPACE mo... |
1,209 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Threaded Serial Port reader</h1>
<hr style="border
Step1: <span>
We first create the queue where we want the serial port thread will be pushing the readings.
</span>
Step2: <span>
It i... | Python Code:
import sys
#sys.path.insert(0, '/home/asanso/workspace/att-spyder/att/src/python/')
sys.path.insert(0, 'i:/dev/workspaces/python/att-workspace/att/src/python/')
Explanation: <h1>Threaded Serial Port reader</h1>
<hr style="border: 1px solid #000;">
<span>
<h2>Serial Port reader in an execution thread.<br>
P... |
1,210 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Naive-Bayes" data-toc-modified-id="Naive-Bayes-1"><span class="toc-item-num"... | Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', '..', 'notebook_format'))
from formats import load_style
load_style(plot_style = False)
os.chdir(path)
# 1. magic for inline plot
# 2. magic to... |
1,211 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Constraints
Setup
Let's first make sure we have the latest version of PHOEBE 2.3 installed (uncomment this line if running in an online notebook session such as colab).
Step1: What are Cons... | Python Code:
#!pip install -I "phoebe>=2.3,<2.4"
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.default_binary()
Explanation: Constraints
Setup
Let's first make sure we have the latest version of PHOEBE 2.3 installed (uncomment this line... |
1,212 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocean
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cnrm-cerfacs', 'cnrm-cm6-1-hr', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: CNRM-CERFACS
Source ID: CNRM-CM6-1-HR
Topic: Ocean
Sub-Topics: Ti... |
1,213 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dogs versus Cats Redux Competition on Kaggle
Setup
Step1: Prepare Data
Note
Step2: Create validation and test sets
Step3: Checkpoint - Extract Features
Step4: Checkpoint - Transfer Learn... | Python Code:
#reset python environment
%reset -f
from pathlib import Path
import numpy as np
import tensorflow as tf
import time
import os
current_dir = os.getcwd()
home_directory = Path(os.getcwd())
dataset_directory = home_directory / "datasets" / "dogs-vs-cats-redux-kernels-edition"
training_dataset_dir = dataset_di... |
1,214 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 7</font>
Download
Step1: Missão 2
Step2: Teste da Solução | Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
Explanation: <font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 7</font>
Download: http://github.com/dsacademybr
End of explanation
class... |
1,215 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load data from http
Step1: Load sales time-series data
Step2: Following Aarshay Jain over at Analytics Vidhya (see here) we implement a Rolling Mean, Standard Deviation + Dickey-Fuller tes... | Python Code:
# code written in py_3.0
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import seaborn as sns
Explanation: Load data from http://media.wiley.com/product_ancillary/6X/11186614/DOWNLOAD/ch08.zip, SwordForecasting.xlsx
End of explanation
# find path to... |
1,216 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div style='background-image
Step1: 1. Chebyshev derivative method
Exercise
Define a python function call "get_cheby_matrix(nx)" that initializes the Chebyshev derivative matrix $D_{ij}$, c... | Python Code:
# This is a configuration step for the exercise. Please run it before calculating the derivative!
import numpy as np
import matplotlib.pyplot as plt
from ricker import ricker
# Show the plots in the Notebook.
plt.switch_backend("nbagg")
Explanation: <div style='background-image: url("../../share/images/he... |
1,217 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fundamentals of text processing
Content in this section is adapted from Ramalho (2015) and Lutz (2013).
The most basic characters in a string are the ASCII characters. The string library in ... | Python Code:
string.ascii_letters
Explanation: Fundamentals of text processing
Content in this section is adapted from Ramalho (2015) and Lutz (2013).
The most basic characters in a string are the ASCII characters. The string library in Python, helpfully has these all listed out.
End of explanation
string.punctuation
s... |
1,218 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial
Step1: 1. Data
We should now have all the data loaded, named as it was before. As a reminder, these are the NGC numbers of the galaxies in the data set
Step2: 2. Independent fits ... | Python Code:
exec(open('tbc.py').read()) # define TBC and TBC_above
import dill
# may need to change the load path
TBC() # dill.load_session('../ignore/cepheids_one.db')
exec(open('tbc.py').read()) # (re-)define TBC and TBC_above
Explanation: Tutorial: The Cepheid Period-Luminosity Relation for Multiple Galaxies
So far... |
1,219 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CS446/546 - Class Session 19 - Correlation network
In this class session we are going to analyze gene expression data from a human bladder cancer cohort, using python. We will load a data ma... | Python Code:
import pandas
import scipy.stats
import matplotlib
import pylab
import numpy
import statsmodels.sandbox.stats.multicomp
import igraph
import math
Explanation: CS446/546 - Class Session 19 - Correlation network
In this class session we are going to analyze gene expression data from a human bladder cancer co... |
1,220 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Intro to TensorFlow
What is a Computation Graph?
Everything in TensorFlow comes down to building a computation graph. What is a computation graph? Its just a series of math operations that o... | Python Code:
a = tf.placeholder(tf.float32)
b = tf.placeholder(tf.float32)
c = tf.add(a, b)
d = tf.subtract(b, 1)
e = tf.multiply(c, d)
Explanation: Intro to TensorFlow
What is a Computation Graph?
Everything in TensorFlow comes down to building a computation graph. What is a computation graph? Its just a series of mat... |
1,221 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic 1D non-linear regression with Keras
TODO
Step1: Make the dataset
Step2: Make the regressor | Python Code:
import tensorflow as tf
tf.__version__
import keras
keras.__version__
import h5py
h5py.__version__
import pydot
pydot.__version__
Explanation: Basic 1D non-linear regression with Keras
TODO: see https://stackoverflow.com/questions/44998910/keras-model-to-fit-polynomial
Install Keras
https://keras.io/#insta... |
1,222 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Model Fitting
One of the most common things in scientific computing is model fitting. Numerical Recipes devotes a number of chapters to this.
scipy "curve_fit"
astropy.modeling
lmfit (emcee)... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import math
Explanation: Model Fitting
One of the most common things in scientific computing is model fitting. Numerical Recipes devotes a number of chapters to this.
scipy "curve_fit"
astropy.modeling
lmfit (emcee) - Levenberg-Marquardt... |
1,223 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Define simple printing functions
Step1: Constructing and allocating dictionaries
The syntax for dictionaries is that {} indicates an empty dictionary
Step2: There are multiple ways to cons... | Python Code:
from __future__ import print_function
import json
def print_dict(dd):
print(json.dumps(dd, indent=2))
Explanation: Define simple printing functions
End of explanation
d1 = dict()
d2 = {}
print_dict(d1)
print_dict(d2)
Explanation: Constructing and allocating dictionaries
The syntax for dictionaries i... |
1,224 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Convolutional GANs
In this notebook, you'll build a GAN using convolutional layers in the generator and discriminator. This is called a Deep Convolutional GAN, or DCGAN for short. The D... | Python Code:
%matplotlib inline
import pickle as pkl
import matplotlib.pyplot as plt
import numpy as np
from scipy.io import loadmat
import tensorflow as tf
!mkdir data
Explanation: Deep Convolutional GANs
In this notebook, you'll build a GAN using convolutional layers in the generator and discriminator. This is called... |
1,225 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Angular Correlations of Amorphous Materials
This notebook demonstrates caclulating the angular correlation of diffraction patterns recorded from an amorphous (or crystalline) material.
The d... | Python Code:
data_path = "data/09/PdNiP_test.hspy"
%matplotlib inline
import pyxem as pxm
import hyperspy.api as hs
pxm.__version__
data = hs.load("./data/09/PdNiP_test.hspy")
Explanation: Angular Correlations of Amorphous Materials
This notebook demonstrates caclulating the angular correlation of diffraction patterns ... |
1,226 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy
numpy je paket (modul) za (efikasno) numeričko računanje u Pythonu. Naglasak je na efikasnom računanju s nizovima, vektorima i matricama, uključivo višedimenzionalne stukture. Napisan ... | Python Code:
from numpy import *
Explanation: Numpy
numpy je paket (modul) za (efikasno) numeričko računanje u Pythonu. Naglasak je na efikasnom računanju s nizovima, vektorima i matricama, uključivo višedimenzionalne stukture. Napisan je u C-u i Fortanu te koristi BLAS biblioteku.
End of explanation
v = array([1,2,3,4... |
1,227 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Intuit craft demonstration
Kyle Willett (Fellow, Insight Data Science)
<font color='red'>Create a reasonable definition(s) of rule performance.</font>
The definition of rule performance I us... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
from sqlalchemy import create_engine
from sqlalchemy_utils import database_exists, create_database
import psycopg2
import pandas as pd # Requires v 0.18.0
import numpy as np
import seaborn as sns
sns.set_style("whitegrid")
dbname = 'risk'
username = '... |
1,228 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Simple Time Series Analysis Of The S&P 500 Index
This notebook presents some basic ideas from time series analysis applied to stock market data, specificially the daily closing value of th... | Python Code:
%matplotlib inline
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
import seaborn as sb
sb.set_style('darkgrid')
#path = os.getcwd() + '\data\stock_data.csv'
path = "/data/stock_data.csv"
stock_data = pd.read_csv(path)
stock_data['Date'] = stock... |
1,229 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Aula 04 - pandas
Objetivos
Análise séries temporais
Ler, manipular e plotar dados tabulares
Guia de group-by e outras operações tabulares avançadas
Ler um CSV e mostrar apenas o início da ta... | Python Code:
import pandas as pd
pd.read_csv('./data/dados_pirata.csv').head()
Explanation: Aula 04 - pandas
Objetivos
Análise séries temporais
Ler, manipular e plotar dados tabulares
Guia de group-by e outras operações tabulares avançadas
Ler um CSV e mostrar apenas o início da tabela.
End of explanation
df = pd.read_... |
1,230 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Display Exercise 1
Imports
Put any needed imports needed to display rich output the following cell
Step1: Basic rich display
Find a Physics related image on the internet and display it in t... | Python Code:
%matplotlib inline
import numpy as np
from matplotlib import pyplot as plt
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
from IPython.html import widgets
from IPython.display import Image
assert True # leave this to grade the import statements
Explanation... |
1,231 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Index - Back - Next
Widget Events
Special events
Step1: The Button is not used to represent a data type. Instead the button widget is used to handle mouse clicks. The on_click method of t... | Python Code:
from __future__ import print_function
Explanation: Index - Back - Next
Widget Events
Special events
End of explanation
from IPython.html import widgets
print(widgets.Button.on_click.__doc__)
Explanation: The Button is not used to represent a data type. Instead the button widget is used to handle mouse cli... |
1,232 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Info from the web
This notebook goes with a blog post at Agile*.
We're going to get some info from Wikipedia, and some financial prices from Yahoo Finance. We'll make good use of the request... | Python Code:
url = "http://en.wikipedia.org/wiki/Jurassic" # Line 1
Explanation: Info from the web
This notebook goes with a blog post at Agile*.
We're going to get some info from Wikipedia, and some financial prices from Yahoo Finance. We'll make good use of the requests library, a really nicely designed Python libra... |
1,233 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numerical Differentiation
Step1: Applications
Step5: Question
Image you're planning a mission to the South Pole Aitken Basin and want to explore some permanently shadowed craters. What fac... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as pl
Explanation: Numerical Differentiation
End of explanation
from IPython.display import Image
Image(url='http://wordlesstech.com/wp-content/uploads/2011/11/New-Map-of-the-Moon-2.jpg')
Explanation: Applications:
Derivative difficult to compu... |
1,234 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This notebook gives suggests how to solve the problem of non-linear compressible flow using the automatic differentiation library included in PorePy.
The Ad functionality in Po... | Python Code:
import numpy as np
import scipy.sparse as sps
import matplotlib.pyplot as plt
# Porepy modules
import porepy as pp
Explanation: Introduction
This notebook gives suggests how to solve the problem of non-linear compressible flow using the automatic differentiation library included in PorePy.
The Ad function... |
1,235 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dates in timeseries models
Step1: Getting started
Step2: Right now an annual date series must be datetimes at the end of the year.
Step3: Using Pandas
Make a pandas TimeSeries or DataFram... | Python Code:
from __future__ import print_function
import statsmodels.api as sm
import numpy as np
import pandas as pd
Explanation: Dates in timeseries models
End of explanation
data = sm.datasets.sunspots.load()
Explanation: Getting started
End of explanation
from datetime import datetime
dates = sm.tsa.datetools.date... |
1,236 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Hierarchical Linear Regression
Author
Step1: In the dataset, we were provided with a baseline chest CT scan and associated clinical information for a set of patients. A patient has... | Python Code:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
train = pd.read_csv('https://gist.githubusercontent.com/ucals/'
'2cf9d101992cb1b78c2cdd6e3bac6a4b/raw/'
'43034c39052dcf97d4b894d2ec1bc3f90f3623d9/'
'osic_... |
1,237 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Executed
Step1: Notebook arguments
sigma (float)
Step2: Fitting models
Models used to fit the data.
1. Simple Exponential
In this model, we define the model function as an exponential tran... | Python Code:
sigma = 0.016
time_window = 30
time_step = 5
time_start = -900
time_stop = 900
decimation = 20
t0_vary = True
true_params = dict(
tau = 60, # time constant
init_value = 0.3, # initial value (for t < t0)
final_value = 0.8, # final value (for t -> +inf)
t0 = 0) ... |
1,238 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Installating R on WinPython
This procedure applys for Winpython (Version of December 2015 and after)
1 - Downloading R binary
Step1: 2 - checking and Installing R binary in the right place... | Python Code:
import os
import sys
import io
# downloading R may takes a few minutes (80Mo)
try:
import urllib.request as urllib2 # Python 3
except:
import urllib2 # Python 2
# specify R binary and (md5, sha1) hash
# R-3.4.3:
r_url = "https://cran.r-project.org/bin/windows/base/R-3.4.3-win.exe"
hashes=("0ff087... |
1,239 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FloPy
SpatialReference demo
A short demonstration of functionality in the SpatialReference class for locating the model in a "real world" coordinate reference system
Step1: description
Spat... | Python Code:
import sys
sys.path.append('../..')
import os
import numpy as np
import matplotlib.pyplot as plt
import flopy
from flopy.utils.reference import SpatialReference
import flopy.utils.binaryfile as bf
% matplotlib inline
outpath = 'temp/'
Explanation: FloPy
SpatialReference demo
A short demonstration of functi... |
1,240 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Artificial Intelligence Nanodegree
Machine Translation Project
In this notebook, sections that end with '(IMPLEMENTATION)' in the header indicate that the following blocks of code will requi... | Python Code:
import helper
# Load English data
english_sentences = helper.load_data('data/small_vocab_en')
# Load French data
french_sentences = helper.load_data('data/small_vocab_fr')
print('Dataset Loaded')
Explanation: Artificial Intelligence Nanodegree
Machine Translation Project
In this notebook, sections that end... |
1,241 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Heat
In this example the laser-excitation of a sample Structure is shown.
It includes the actual absorption of the laser light as well as the transient temperature profile calculation.
Setup... | Python Code:
import udkm1Dsim as ud
u = ud.u # import the pint unit registry from udkm1Dsim
import scipy.constants as constants
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
u.setup_matplotlib() # use matplotlib with pint units
Explanation: Heat
In this example the laser-excitation of a sample... |
1,242 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
7. Maximum Likelihood fit
Step1: We use the pancake dataset, sampled at 300 random locations to produce a quite dense sample.
Step2: First of, the variogram is calculated. We use Scott's r... | Python Code:
import skgstat as skg
from skgstat.util.likelihood import get_likelihood
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import minimize
import warnings
from time import time
import matplotlib.pyplot as plt
warnings.filterwarnings('ignore')
Explanation: 7. Maximum Likelihood fit
End ... |
1,243 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
hypothesis
Test the hypothesis about alcohol consumption and life expectancy Specifically, is how quantity litters alcohol consumption per year in a country is related a life expectancy, or ... | Python Code:
''' Categoriacal explanatory variable with five levels '''
alcohol_map = {1: '>=0 <5', 2: '>=5 <10', 3: '>=10 <15', 4: '>=15 <20', 5: '>=20 <25'}
data2['alcohol'] = pd.cut(data1.alcohol,[0,5,10,15,20,25],
labels=[i for i in alcohol_map.values()])
data2["alcohol"] = data2["alcohol... |
1,244 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
```
Licensed under the Apache License, Version 2.0 (the "License");
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the Li... | Python Code:
![ -d nested-transformer ] || git clone --depth=1 https://github.com/google-research/nested-transformer
!cd nested-transformer && git pull
!pip install -qr nested-transformer/requirements.txt
Explanation: ```
Licensed under the Apache License, Version 2.0 (the "License");
Licensed under the Apache License,... |
1,245 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Store the data to HDF5 file for rapid analysis and calculation
This tutorial discuss the analyses that can be performed using the dnaMD Python module included in the do_x3dna package. The tu... | Python Code:
import os
import numpy as np
import matplotlib.pyplot as plt
import dnaMD
%matplotlib inline
try:
os.remove('cdna.h5')
except:
pass
Explanation: Store the data to HDF5 file for rapid analysis and calculation
This tutorial discuss the analyses that can be performed using the dnaMD Python module incl... |
1,246 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
레버리지와 아웃라이어
레버리지 (Leverage)
개별적인 데이터 표본이 회귀 분석 결과에 미치는 영향은 레버리지(leverage)분석을 통해 알 수 있다.
레버리지는 래의 target value $y$가 예측된(predicted) target $\hat{y}$에 미치는 영향을 나타낸 값이다. self-influence, self-sens... | Python Code:
from sklearn.datasets import make_regression
X0, y, coef = make_regression(n_samples=100, n_features=1, noise=20, coef=True, random_state=1)
# add high-leverage points
X0 = np.vstack([X0, np.array([[4],[3]])])
X = sm.add_constant(X0)
y = np.hstack([y, [300, 150]])
plt.scatter(X0, y)
plt.show()
model = sm.O... |
1,247 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Check ensemble of OpenMM temperature replica exchange simulations
Note
Step1: Ensemble validation is particularly useful for validating enhanced sampling methods such
as temperature replica... | Python Code:
# enable plotting in notebook
%matplotlib notebook
Explanation: Check ensemble of OpenMM temperature replica exchange simulations
Note: This notebook can be run locally by cloning the
Github repository.
The notebook is located in doc/examples/openmm_replica_exchange.ipynb. The input and output files of the... |
1,248 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Apply logistic regression to categorize whether a county had high mortality rate due to contamination
1. Import the necessary packages to read in the data, plot, and create a logistic regres... | Python Code:
import pandas as pd
%matplotlib inline
import numpy as np
from sklearn.linear_model import LogisticRegression
Explanation: Apply logistic regression to categorize whether a county had high mortality rate due to contamination
1. Import the necessary packages to read in the data, plot, and create a logistic ... |
1,249 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This example is a Jupyter notebook. You can download it or run it interactively on mybinder.org.
Linear regression
Data
The true parameters of the linear regression
Step1: Generate data
Ste... | Python Code:
import numpy as np
k = 2 # slope
c = 5 # bias
s = 2 # noise standard deviation
# This cell content is hidden from Sphinx-generated documentation
%matplotlib inline
np.random.seed(42)
Explanation: This example is a Jupyter notebook. You can download it or run it interactively on mybinder.org.
Linear regress... |
1,250 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MySQL-python
It is an interface to MySQL that
Step1: WARNING
Step2: It is recommend to interpolate sql using the DB API.
It knows how to deal with strings, integers, booleans, None...
Quer... | Python Code:
# let's create a testing database
# CREATE DATABASE IF NOT EXISTS mod_mysqldb DEFAULT CHARACTER SET 'UTF8' DEFAULT COLLATE 'UTF8_GENERAL_CI';
# GRANT ALL PRIVILEGES ON mod_mysqldb.* TO 'user'@'localhost' IDENTIFIED BY 'user';
# let's connect to our database
import MySQLdb as mysql
conn = mysql.connect('loc... |
1,251 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GPyTorch Regression With KeOps
Introduction
KeOps is a recently released software package for fast kernel operations that integrates wih PyTorch. We can use the ability of KeOps to perform e... | Python Code:
import math
import torch
import gpytorch
from matplotlib import pyplot as plt
%matplotlib inline
%load_ext autoreload
%autoreload 2
Explanation: GPyTorch Regression With KeOps
Introduction
KeOps is a recently released software package for fast kernel operations that integrates wih PyTorch. We can use the a... |
1,252 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step3: Computing for Mathematics - 2020/2021 individual coursework
Important Do not delete the cells containing
Step7: b. $1/2$
Available marks
Step11: c. $3/4$
Available marks
Step15: d.... | Python Code:
import random
def sample_experiment():
### BEGIN SOLUTION
Returns true if a random number is less than 0
return random.random() < 0
number_of_experiments = 1000
sum(
sample_experiment() for repetition in range(number_of_experiments)
) / number_of_experiments
### END SOLUTION
q1_a_... |
1,253 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convert data to NILMTK format and load into NILMTK
Step1: NILMTK uses an open file format based on the HDF5 binary file format to store both the power data and the metadata. The very first... | Python Code:
!! pip install -U Pillow==6.1.0
Explanation: Convert data to NILMTK format and load into NILMTK
End of explanation
from nilmtk.dataset_converters import convert_redd
convert_redd('../datasets/REDD/low_freq', '../datasets/REDD/low_freq.h5')
Explanation: NILMTK uses an open file format based on the HDF5 bina... |
1,254 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Space Time Scan
Using SatScan
Start SaTScan and make a new session
Under the "Input" tab
Step1: Save to SatScan format
Embarrasingly, we now seem to have surpassed SaTScan in terms of speed... | Python Code:
%matplotlib inline
from common import *
#datadir = os.path.join("//media", "disk", "Data")
datadir = os.path.join("..", "..", "..", "..", "..", "Data")
south_side, points = load_data(datadir)
grid = grid_for_south_side()
import open_cp.stscan as stscan
import open_cp.stscan2 as stscan2
trainer = stscan.STS... |
1,255 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="images/charizard.png" alt="Expert" width="200">
Expert level
Welcome to the expert level!
For this level, I'm assuming you are somewhat familiar with the Python programming languag... | Python Code:
%matplotlib notebook
# Import the MNE-Python module, which contains all the data analysis routines we need
import mne
print('MNE-Python imported.')
# Configure the graphics engine
from matplotlib import pyplot as plt
plt.rc('figure', max_open_warning=100)
%matplotlib notebook
from mayavi import mlab # May... |
1,256 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Large Scale Text Classification for Sentiment Analysis
Scalability Issues
The sklearn.feature_extraction.text.CountVectorizer and sklearn.feature_extraction.text.TfidfVectorizer classes suff... | Python Code:
from sklearn.feature_extraction.text import CountVectorizer
vectorizer = CountVectorizer(min_df=1)
vectorizer.fit([
"The cat sat on the mat.",
])
vectorizer.vocabulary_
Explanation: Large Scale Text Classification for Sentiment Analysis
Scalability Issues
The sklearn.feature_extraction.text.CountVector... |
1,257 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TruePeakDetector use example
This algorithm implements the “true-peak” level meter as descripted in the second annex of the ITU-R BS.1770-2[1] or the ITU-R BS.1770-4[2] (default).
Note
Step1... | Python Code:
import essentia.standard as es
import numpy as np
import matplotlib
matplotlib.use('nbagg')
import matplotlib.pyplot as plt
import ipywidgets as wg
from IPython.display import Audio
from essentia import array as esarr
plt.rcParams["figure.figsize"] =(9, 5)
Explanation: TruePeakDetector use example
This al... |
1,258 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Unit 2
Step1: 1. What is the output of the commands above?
Now each time we call a function that’s in a library, we use the syntax
Step2: 2. In the command above, why did we use pd.read_ta... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Unit 2: Programming Design
Lesson 14: Packages and Data Analysis
Notebook Authors
(fill in your two names here)
Facilitator: (fill in name)
Spokesperson: (fill in name)
Process Analyst: (fill in name)
Quality Control: (fill in name)
If ther... |
1,259 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyBroom Example - Multiple Datasets - Scipy Robust Fit
This notebook is part of pybroom.
This notebook demonstrate using pybroom when fitting a set of curves (curve fitting) using robust fit... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format='retina' # for hi-dpi displays
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.pylab import normpdf
import seaborn as sns
from lmfit import Model
import lmfit
print('lmfit: %s' % lmfit.__version__)
sns.set_style(... |
1,260 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
In this notebook, we will demonstrate how to copy and paste Page resources within the SAME agent from a Source Flow to a Target Flow.
These same methods/functions can be further... | Python Code:
#If you haven't already, make sure you install the `dfcx-scrapi` library
!pip install dfcx-scrapi
Explanation: Introduction
In this notebook, we will demonstrate how to copy and paste Page resources within the SAME agent from a Source Flow to a Target Flow.
These same methods/functions can be further modif... |
1,261 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow IO Authors.
Step1: TensorFlow を使用した Azure Blob Storage
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: Azurite の... | 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 writing, software
# dist... |
1,262 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
version 1.1
Введение (Introduction)
Данный блокнот является дополнительным материалом к статье по демонстрации примеров анализа данных и линейной регрессии представленной публикации на пор... | Python Code:
#import libraries
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import requests, bs4
import time
from sklearn import model_selection
from collections import OrderedDict
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import trai... |
1,263 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Aerobic metabolic model
Import the necessary libraries
Step1: Load the data
Step2: Compute the aerobic metabolic model
Step3: Plot the information related to the MAP determination using P... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from skcycling.data_management import Rider
from skcycling.metrics import aerobic_meta_model
from skcycling.utils.fit import log_linear_model
from skcycling.utils.fit import linear_model
from datetime import date
Explanation: Aerobic met... |
1,264 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: 2. Check the types of the variable that you take into account along the way.
Step2: 3. Draw the histogram of total day minutes and total intl calls and interpret the ... | Python Code:
#codes here
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_csv("https://raw.githubusercontent.com/Yorko/mlcourse.ai/master/data/telecom_churn.csv")
df.head()
Explanation: <a href="https://colab.research.google.com/github/gaargly/gaargly.github.io/b... |
1,265 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PageRank exercise
Question 1
Consider three Web pages with the following links
Step1: Suppose we compute PageRank with a β of 0.7, and we introduce the additional constraint that the sum of... | Python Code:
from IPython.display import Image
Image(filename='pagerank1.jpeg')
Explanation: PageRank exercise
Question 1
Consider three Web pages with the following links:
End of explanation
import numpy as np
# Adjacency matrix
# m1 = [ 0, 0, 0]
# [0.5, 0, 0]
# [0.5, 1, 1]
m1 = np.matrix([[0, 0, 0],[0.5, 0... |
1,266 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<img src="../../img/ods_stickers.jpg">
Открытый курс по машинному обучению. Сессия № 2
</center>
Автор материала
Step1: Проведем небольшой EDA
Step2: Для начала всегда неплохо бы ... | Python Code:
# подгружаем все нужные пакеты
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker
%matplotlib inline
# настройка внешнего вида графиков в seaborn
sns.set_context(
"notebook",
font_scale = 1.5,
rc = {
... |
1,267 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Autoregressive Moving Average (ARMA)
Step1: Sunpots Data
Step2: Does our model obey the theory?
Step3: This indicates a lack of fit.
In-sample dynamic prediction. How good does our model ... | Python Code:
%matplotlib inline
from __future__ import print_function
import numpy as np
from scipy import stats
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
from statsmodels.graphics.api import qqplot
Explanation: Autoregressive Moving Average (ARMA): Sunspots data
End of explanatio... |
1,268 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AI Explanations
Step1: Run the following cell to create your Cloud Storage bucket if it does not already exist.
Step2: Import libraries
Import the libraries for this tutorial.
Step3: Down... | Python Code:
from datetime import datetime
TIMESTAMP = datetime.now().strftime("%Y%m%d%H%M%S")
import os
PROJECT_ID = "" # TODO: your PROJECT_ID here.
os.environ["PROJECT_ID"] = PROJECT_ID
BUCKET_NAME = PROJECT_ID # TODO: replace your BUCKET_NAME, if needed
REGION = "us-central1"
os.environ["BUCKET_NAME"] = BUCKET_NA... |
1,269 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import Socorro crash data into the Data Platform
We want to be able to store Socorro crash data in Parquet form so that it can be made accessible from re
Step4: We create the pyspark dataty... | Python Code:
!conda install boto3 --yes
import logging
logging.basicConfig(level=logging.INFO)
log = logging.getLogger(__name__)
Explanation: Import Socorro crash data into the Data Platform
We want to be able to store Socorro crash data in Parquet form so that it can be made accessible from re:dash.
See Bug 1273657 fo... |
1,270 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analyzing Pronto CycleShare Data with Python and Pandas
This notebook originally appeared as a post on the blog Pythonic Perambulations. The content is BSD licensed.
<!-- PELICAN_BEGIN_SUMMA... | Python Code:
# !curl -O https://s3.amazonaws.com/pronto-data/open_data_year_one.zip
# !unzip open_data_year_one.zip
Explanation: Analyzing Pronto CycleShare Data with Python and Pandas
This notebook originally appeared as a post on the blog Pythonic Perambulations. The content is BSD licensed.
<!-- PELICAN_BEGIN_SUMMAR... |
1,271 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2017 Google LLC.
Step1: # 텐서 만들기 및 조작
학습 목표
Step2: ## 벡터 덧셈
텐서에서 여러 일반적인 수학 연산을 할 수 있습니다(TF API). 다음 코드는
각기 정확히 6개 요소를 가지는 두 벡터(1-D 텐서)를 만들고 조작합니다.
Step3: ### 텐서 형태
형태는 텐서의 크기와 ... | 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, software
# distribute... |
1,272 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spark + Python = PySpark
Esse notebook introduz os conceitos básicos do Spark através de sua interface com a linguagem Python. Como aplicação inicial faremos o clássico examplo de contador d... | Python Code:
ListaPalavras = ['gato', 'elefante', 'rato', 'rato', 'gato']
palavrasRDD = sc.parallelize(ListaPalavras, 4)
print type(palavrasRDD)
Explanation: Spark + Python = PySpark
Esse notebook introduz os conceitos básicos do Spark através de sua interface com a linguagem Python. Como aplicação inicial faremos o cl... |
1,273 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Categorical Embeddings
We will use the embeddings through the whole lab. They are simply represented by a matrix of tunable parameters (weights).
Let us assume that we are given a pre-traine... | Python Code:
import numpy as np
embedding_size = 4
vocab_size = 10
embedding_matrix = np.arange(embedding_size * vocab_size, dtype='float32')
embedding_matrix = embedding_matrix.reshape(vocab_size, embedding_size)
print(embedding_matrix)
Explanation: Categorical Embeddings
We will use the embeddings through the whole l... |
1,274 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interactive WebGL trajectory widget
Note
Step1: To enable these features, we first need to run enable_notebook to initialize
the required javascript.
Step2: The WebGL viewer engine is call... | Python Code:
from __future__ import print_function
import mdtraj as md
traj = md.load_pdb('http://www.rcsb.org/pdb/files/2M6K.pdb')
print(traj)
Explanation: Interactive WebGL trajectory widget
Note: this feature requires a 'running' notebook, connected to a live kernel. It will not work with a staticly rendered display... |
1,275 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implementing logistic regression from scratch
The goal of this notebook is to implement your own logistic regression classifier. You will
Step1: Load review dataset
For this assignment, we ... | Python Code:
import graphlab
Explanation: Implementing logistic regression from scratch
The goal of this notebook is to implement your own logistic regression classifier. You will:
Extract features from Amazon product reviews.
Convert an SFrame into a NumPy array.
Implement the link function for logistic regression.
Wr... |
1,276 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id="ndvi_std_top"></a>
NDVI STD
Deviations from an established average z-score.
<hr>
Notebook Summary
A baseline for each month is determined by measuring NDVI over a set time
The data c... | Python Code:
import sys
import os
sys.path.append(os.environ.get('NOTEBOOK_ROOT'))
import time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.ticker import FuncFormatter
import seaborn as sns
from utils.data_cube_utilities.dc_load import get_product_exten... |
1,277 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Gaussian Mixture Models and Expectation Maximisation in Shogun
By Heiko Strathmann - heiko.strathmann@gmail.com - http
Step2: Set up the model in Shogun
Step3: Sampling from mixture... | Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
# import all Shogun classes
from modshogun import *
from matplotlib.patches import Ellipse
# a tool for visualisation
def get_gaussian_ellipse_artist(mean, cov, nstd=1.96, color="red", linewidth=3):
... |
1,278 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Python
An introduction to Python for middle and high school students using Python 3 syntax.
Getting started
We're assuming that you already have Python 3.6 or higher installe... | Python Code:
print('Hello, World!')
Explanation: Introduction to Python
An introduction to Python for middle and high school students using Python 3 syntax.
Getting started
We're assuming that you already have Python 3.6 or higher installed. If not, go to Python.org to download the latest for your operating system. Ver... |
1,279 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
pandas
pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language
http
Step1: Working... | Python Code:
# Series
import numpy as np
import pandas as pd
myArray = np.array([2,3,4])
row_names = ['p','q','r']
mySeries = pd.Series(myArray,index=row_names)
print (mySeries)
print (mySeries[0])
print (mySeries['p'])
# Dataframes
myArray = np.array([[2,3,4],[5,6,7]])
row_names = ['p','q']
col_names = ['One','Two','T... |
1,280 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiment
Step1: Load and check data
Step2: ## Analysis
Experiment Details
Step3: Does improved weight pruning outperforms regular SET
Step4: No significant difference between the two a... | Python Code:
%load_ext autoreload
%autoreload 2
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import glob
import tabulate
import pprint
import click
import numpy as np
import pandas as pd
from ray.tune.commands import *
from nupic.research.framewo... |
1,281 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Discretize PV row sides and indexing
In this section, we will learn how to
Step1: Prepare PV array parameters
Step2: Create discretization scheme
Step3: Create a PV array
Import the Order... | Python Code:
# Import external libraries
import matplotlib.pyplot as plt
# Settings
%matplotlib inline
Explanation: Discretize PV row sides and indexing
In this section, we will learn how to:
create a PV array with discretized PV row sides
understand the indices of the timeseries surfaces of a PV array
plot a PV array ... |
1,282 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocean
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'bcc', 'bcc-esm1', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: BCC
Source ID: BCC-ESM1
Topic: Ocean
Sub-Topics: Timestepping Framework, Advect... |
1,283 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<H1>Bidirectional connections as a function of the distance </H1>
<P>
We will analyze the probability of finding bidirectionally connected inhibitory synapses are over-represented as a funct... | Python Code:
%pylab inline
import warnings
from inet import DataLoader, __version__
from inet.utils import II_slice
print('Inet version {}'.format(__version__))
Explanation: <H1>Bidirectional connections as a function of the distance </H1>
<P>
We will analyze the probability of finding bidirectionally connected inhibit... |
1,284 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about emb... | Python Code:
import time
import numpy as np
import tensorflow as tf
import utils
Explanation: Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about embedding words for use in natural lang... |
1,285 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Temp
Step1: Remove corrupted h5 files on the repo and remove all ZIP-files on the data repo
Step2: Recreate all the ZIP folders
Load the existing h5 files and use this to create the zip fi... | Python Code:
from file_transfer.creds import URL, LOGIN, PASSWORD
btos = dm.BaltradToS3(URL, LOGIN, PASSWORD, "lw-enram", profile_name="lw-enram")
btos.transfer(name_match="_vp_", overwrite=True,
limit=5, verbose=True)
btos.transferred
s3handle.create_zip_version(btos.transferred)
import shutil
shutil.rm... |
1,286 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Populations
Step1: Let's create a population. Agent creation is here dealt with automatically. Still, it is possible to manually add or remove agents (Hence the IDs of the agents), what wil... | Python Code:
import naminggamesal.ngpop as ngpop
Explanation: Populations
End of explanation
pop_cfg={
'voc_cfg':{
'voc_type':'matrix',
'M':5,
'W':10
},
'strat_cfg':{
'strat_type':'naive',
'vu_cfg':{'vu_type':'BLIS_epirob'}
},
'interact_cfg':{
... |
1,287 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data science pipeline
Step1: Primary object types
Step2: What are the features?
* TV
Step3: Linear regression
Pros
Step4: Splitting X and y into training and testing sets
Step5: Linear ... | Python Code:
# conventional way to import pandas
import pandas as pd
# read CSV file directly from a URL and save the results
data = pd.read_csv('http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv', index_col=0)
# display the first 5 rows
data.head()
Explanation: Data science pipeline: pandas, seaborn, scikit-learn¶
Ag... |
1,288 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Language Translation
In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset o... | 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)
Explanation: Language Translation
In this project, you’re going ... |
1,289 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify ... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'bcc', 'bcc-csm2-hr', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: BCC
Source ID: BCC-CSM2-HR
Topic: Seaice
Sub-Topics: Dynamics, Thermodynam... |
1,290 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Partie 5
Step1: <a name="PbGeneral">Problèmatique générale</a>
Objectif
L'objectif principal de l'automatique ou de la théorie du contrôle est d'imposer un comportement dynamique spécifique... | Python Code:
# -*- coding: utf-8 -*-
from IPython.display import HTML
HTML('''<script>
code_show=true;
function code_toggle() {
if (code_show){
$('div.input').hide();
} else {
$('div.input').show();
}
code_show = !code_show
}
$( document ).ready(code_toggle);
</script>
Pour afficher le code python, cliquer sur ... |
1,291 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
My sample df has four columns with NaN values. The goal is to concatenate all the rows while excluding the NaN values. | Problem:
import pandas as pd
import numpy as np
df = pd.DataFrame({'keywords_0':["a", np.nan, "c"],
'keywords_1':["d", "e", np.nan],
'keywords_2':[np.nan, np.nan, "b"],
'keywords_3':["f", np.nan, "g"]})
import numpy as np
def g(df):
df["keywords_all"] = df.apply(lamb... |
1,292 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Structures de données
Plus de détails sur les listes
Le type de données liste possède d’autres méthodes. Voici toutes les méthodes des objets listes
Step1: Utiliser les listes comme de... | Python Code:
ma_liste = [66.6, 333, 333, 1, 1234.5]
print (ma_liste.count(333), ma_liste.count(66.6), ma_liste.count('x'))
ma_liste2 = list(ma_liste)
ma_liste2.sort()
print (ma_liste2)
ma_liste.insert(2, -1)
ma_liste.append(333)
ma_liste
ma_liste.index(333)
ma_liste.remove(333)
print(ma_liste)
ma_liste.reverse()
ma_lis... |
1,293 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
I combined all the code lines I said should be at the begining of your code.
Step1: Importing mltools
First you want to make sure it sits in the same folder or wherever you put your PYTHON_... | Python Code:
from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
np.random.seed(0)
Explanation: I combined all the code lines I said should be at the begining of your code.
End of explanation
!ls
Explanation: Importing mltools
First you want to make sure it sits in the ... |
1,294 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples on the use of roppy's FluxSection class
The FluxSection class implements a staircase approximation to a section,
starting and ending in psi-points and following U- and V-edges.
No i... | Python Code:
# Imports
=======
The class depends on `numpy` and is part of `roppy`. To read the data `netCDF4` is needed.
The graphic package `matplotlib` is not required for `FluxSection` but is used for visualisation in this notebook.
# Imports
import numpy as np
import matplotlib.pyplot as plt
from netCDF4 import Da... |
1,295 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hierarchical Topic Models and the Nested Chinese Restaurant Process
Tun-Chieh Hsu, Xialingzi Jin, Yen-Hua Chen
I. Background
Recently, complex probabilistic models are increasingly prevalent... | Python Code:
import numpy as np
from scipy.special import gammaln
import random
from collections import Counter
import string
import graphviz
import pygraphviz
import pydot
Explanation: Hierarchical Topic Models and the Nested Chinese Restaurant Process
Tun-Chieh Hsu, Xialingzi Jin, Yen-Hua Chen
I. Background
Recently,... |
1,296 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify ... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mpi-m', 'mpi-esm-1-2-hr', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: MPI-M
Source ID: MPI-ESM-1-2-HR
Topic: Seaice
Sub-Topics: Dynamics, T... |
1,297 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Goal
Question
Step1: Init
Step2: Using nestly
Step3: Plotting results
Step4: Sandbox
Enrichment of TP for abundant incorporators?
What is the abundance distribution of TP and FP?
Are mor... | Python Code:
workDir = '/home/nick/notebook/SIPSim/dev/bac_genome1210/'
genomeDir = '/home/nick/notebook/SIPSim/dev/bac_genome1210/genomes/'
R_dir = '/home/nick/notebook/SIPSim/lib/R/'
Explanation: Goal
Question: how is incorporator identification accuracy affected by the percent isotope incorporation of taxa?
Using ge... |
1,298 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CS446/519 - Class Session 7 - Transitivity (Clustering Coefficients)
In this class session we are going to compute the local clustering coefficient of all vertices in the undirected human
pr... | Python Code:
from igraph import Graph
from igraph import summary
import pandas
import numpy
import timeit
from pympler import asizeof
import bintrees
Explanation: CS446/519 - Class Session 7 - Transitivity (Clustering Coefficients)
In this class session we are going to compute the local clustering coefficient of all ve... |
1,299 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AutoML Text entity extractionn model
Installation
Install the latest version of AutoML SDK.
Step1: Install the Google cloud-storage library as well.
Step2: Restart the Kernel
Once you've i... | Python Code:
! pip3 install google-cloud-automl
Explanation: AutoML Text entity extractionn model
Installation
Install the latest version of AutoML SDK.
End of explanation
! pip3 install google-cloud-storage
Explanation: Install the Google cloud-storage library as well.
End of explanation
import os
if not os.getenv("AU... |
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