Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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11,900 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CLIXO Ontology Tree Generator
This is a notebook to generate tree data file from original table and annotations.
This is the final version of the script creating an Cytoscape.js file with g... | Python Code:
# Load data sets
import pandas as pd
treeSourceUrl = './data/preds_yeastnet_no_gi_0.04_0.5.txt.propagate.small_parent_tree'
geneCountFile = './data/preds_yeastnet_no_gi_0.04_0.5.txt.propagate.term_sizes'
alignmentFile = './data/alignments_FDR_0.1_t_0.1'
geneAssignment = './data/preds_yeastnet_no_gi_0.04_0.... |
11,901 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
贝叶斯分类器含义
贝叶斯分类器是一种基于贝叶斯概率的模型,属于生成式分类器算法,用来处理分类问题.最常见的是朴素贝叶斯分类器和高斯贝叶斯分类器,"朴素"是因为它假设各个预测变量之间相互独立,"高斯"是因为它假设每类数据的每个预测变量都服从参数独立的高斯分布,也就是正态分布.
贝叶斯公式
贝叶斯分类器来源于贝叶斯公式,也就是条件概率公式,以离散情况为例便是$P(Y|X)=\fra... | Python Code:
import requests
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder
from sklearn.naive_bayes import MultinomialNB
from sklearn.metrics import classification_report
Explanation: 贝叶斯分类器含义
贝叶斯分类器是一种基于贝叶斯概率的模型,属于生成式分类器算法,用来处理分类问题.最常见的是朴素贝叶斯分类器... |
11,902 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
(Run the last cell first in order to enable custom formatting)
Learning Pandas
AMCDawes
Dec 2015
Some parts of our CCDimage code would be much improved by the use of pandas. In particular, s... | Python Code:
# standard imports:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
# use inline plots:
%matplotlib inline
# use ggplot style:
matplotlib.style.use('ggplot')
Explanation: (Run the last cell first in order to enable custom formatting)
Learning Pandas
AMCDawes
Dec 201... |
11,903 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Battleship!
A variation on the classic game. A ship of random length will be placed on a board whose size is determined by you, the player. You may also select the number of turns you woul... | Python Code:
from random import randint
from ipythonblocks import BlockGrid
from IPython.display import clear_output
def place_ship(boardsize):
'''
Place a ship randomly on the board
of size boardsize x boardsize.
Randomly decide whether it is vertical
or horizontal, what length ship, the
pla... |
11,904 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Write a function
Step1: V- 1 - used numpy to sum soon realized numpy does not work on codality. I have usually required more time working on solutions when solving something espically with ... | Python Code:
Ax = [-1, 3, -4, 5, 1, -6, 2, 1]
Explanation: Write a function:
def solution(A)
that, given a zero-indexed array A consisting of N integers, returns any of its equilibrium indices. The function should return −1 if no equilibrium index exists.
For example, given array A shown above, the function may return ... |
11,905 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Online Learning
DavisSML
Step1: Loss
Step6: Exercise 8.2
Look at LROnline.py and determine what the decay argument is doing. Play with the arguments and see when you achieve convergence a... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
## open wine data
wine = pd.read_csv('../../data/winequality-red.csv',delimiter=';')
Y = wine.values[:,-1]
X = wine.values[:,:-1]
n,p = X.shape
X = n**0.5 * (X - X.mean(axis=0)) / X.std(axis=0)
## Look at LROnline.py
from LROnline impor... |
11,906 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning Engineer Nanodegree
Introduction and Foundations
Project
Step1: From a sample of the RMS Titanic data, we can see the various features present for each passenger on the shi... | Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
from IPython.display import display # Allows the use of display() for DataFrames
# Import supplementary visualizations code visuals.py
import visuals as vs
# Pretty display for notebooks
%matplotlib inline
# Load the datas... |
11,907 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 11
Step1: Load time series data
Step2: There are a few supported file formats. AT2 files can be loaded as follows
Step3: Create site profile
This is about the simplest profile th... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pysra
%matplotlib inline
# Increased figure sizes
plt.rcParams["figure.dpi"] = 120
Explanation: Example 11 : Time series SRA using FDM
Time series analysis to acceleration transfer functions and spectral ratios.
End of explanation
fname = "data/NIS0... |
11,908 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Raykar(RGZ)
Step1: It seems that higher values of $\alpha$ are correlated with lower values of $\beta$, and vice versa. This seems to make some intuitive sense.
Raykar-estimated $\vec \alph... | Python Code:
from pprint import pprint
import crowdastro.crowd.util
from crowdastro.crowd.raykar import RaykarClassifier
import crowdastro.experiment.experiment_rgz_raykar as rgzr
from crowdastro.experiment.results import Results
import crowdastro.plot
import h5py
import matplotlib.pyplot as plt
import numpy
import skl... |
11,909 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
11,910 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analýza volatilních pohybů v Pythonu a Pandas 1
V následujícím grafu jsou pro příklad zvýrazněny volatilní pohyby
Step1: Každý řádek představuje cenu pro daný den a to nejvyšší (High), nejn... | Python Code:
import pandas as pd
import pandas_datareader.data as web
import datetime
start = datetime.datetime(2015, 1, 1)
end = datetime.datetime(2018, 8, 31)
spy_data = web.DataReader('SPY', 'yahoo', start, end)
spy_data = spy_data.drop(['Volume', 'Adj Close'], axis=1) # sloupce 'Volume' a 'Adj Close' nebudu potřebo... |
11,911 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python Crash Course Exercises
This is an optional exercise to test your understanding of Python Basics. The questions tend to have a financial theme to them, but don't look to deeply into th... | Python Code:
price = 300
import math
math.sqrt( price )
import math
math.sqrt( price )
Explanation: Python Crash Course Exercises
This is an optional exercise to test your understanding of Python Basics. The questions tend to have a financial theme to them, but don't look to deeply into these tasks themselves, many of ... |
11,912 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Datasets
We introduce several datasets used as running examples in TSA.
Step2: Dataset 1
This dataset is derived from a time series of daily GBP/USD exchange rates, $(S_t){t=0,1,\l... | Python Code:
# Copyright (c) Thalesians Ltd, 2019. All rights reserved
# Copyright (c) Paul Alexander Bilokon, 2019. All rights reserved
# Author: Paul Alexander Bilokon <paul@thalesians.com>
# Version: 1.0 (2019.04.23)
# Email: education@thalesians.com
# Platform: Tested on Windows 10 with Python 3.6
Explanation:
End... |
11,913 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AI Platform
Step1: Step 1
Step2: Inspect what the data looks like by looking at the first couple of rows
Step8: Step 2
Step11: The second file, called model.py, defines the input functio... | Python Code:
import os
Explanation: AI Platform: Qwik Start
This lab gives you an introductory, end-to-end experience of training and prediction on AI Platform. The lab will use a census dataset to:
Create a TensorFlow 2.x training application and validate it locally.
Run your training job on a single worker instance i... |
11,914 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<H1>Covariance and correlation</H1>
Step1: <H2>Covariance</H2>
<P>Measures how two variables vary in tandem from their means. To measure the covariance we take a variable that consist of a ... | Python Code:
%pylab inline
Explanation: <H1>Covariance and correlation</H1>
End of explanation
# generate two random variables
x = np.random.normal(3.0, 1.0, 1000)
y = np.random.normal(50.0, 10.0, 1000)
# calculate variance vectors
x_var = [i - x.mean() for i in x]
y_var = [i - y.mean() for i in y]
# compute dot produc... |
11,915 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
jQAssistant Demos
Neo4j-Server starten
mvn jqassistant
Step1: Klasse mit den meisten Methoden auflisten
Step2: Statische, geschriebene Variablen
Step3: Aggregation von Messergebnissen übe... | Python Code:
%load_ext cypher
Explanation: jQAssistant Demos
Neo4j-Server starten
mvn jqassistant:server
Browser öffnen
http://localhost:7474/browser/
Drawer öffnen
Labels durchklicken
Commit
Class
:DECLARES
jQAssistant Dokumentation: http://buschmais.github.io/jqassistant/doc/1.3.0/#_java_plugin
Beispiel-Queries
Setup... |
11,916 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FD_1D_DX4_DT2_fast 1-D acoustic Finite-Difference modelling
GNU General Public License v3.0
Author
Step1: Input Parameter
Step2: Preparation
Step3: Create space and time vector
Step4: So... | Python Code:
%matplotlib inline
import numpy as np
import time as tm
import matplotlib.pyplot as plt
Explanation: FD_1D_DX4_DT2_fast 1-D acoustic Finite-Difference modelling
GNU General Public License v3.0
Author: Florian Wittkamp
Finite-Difference acoustic seismic wave simulation
Discretization of the first-order acou... |
11,917 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Big-graph generation
In this demo, we will verify that our big-graph generation code is functioning properly on a small portion of a real DWI dataset that we can manually verify very easily.... | Python Code:
import ndmg
import ndmg.utils as mgu
# run small demo for experiments
print(mgu.execute_cmd('ndmg_demo-dwi', verb=True)[0])
Explanation: Big-graph generation
In this demo, we will verify that our big-graph generation code is functioning properly on a small portion of a real DWI dataset that we can manually... |
11,918 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Case Study - Text classification for SMS spam detection
We first load the text data from the dataset directory that should be located in your notebooks directory, which we created by running... | Python Code:
import os
with open(os.path.join("datasets", "smsspam", "SMSSpamCollection")) as f:
lines = [line.strip().split("\t") for line in f.readlines()]
text = [x[1] for x in lines]
y = [int(x[0] == "spam") for x in lines]
text[:10]
y[:10]
print('Number of ham and spam messages:', np.bincount(y))
type(text)
ty... |
11,919 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating Models with TensorFlow and PyTorch
In the tutorials so far, we have used standard models provided by DeepChem. This is fine for many applications, but sooner or later you will want... | Python Code:
!pip install --pre deepchem
Explanation: Creating Models with TensorFlow and PyTorch
In the tutorials so far, we have used standard models provided by DeepChem. This is fine for many applications, but sooner or later you will want to create an entirely new model with an architecture you define yourself. ... |
11,920 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
IPython
IPython (Interactive Python) is an enhanced Python shell which provides a more robust and productive development environment for users. There are several key features that set it apa... | Python Code:
import numpy as np
np.sin(4)**2
_1
_i1
_1 / 4.
Explanation: IPython
IPython (Interactive Python) is an enhanced Python shell which provides a more robust and productive development environment for users. There are several key features that set it apart from the standard Python shell.
Interactive data analy... |
11,921 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NGC ... (UGC ...)
Step1: <h2 id="tocheading">Оглавление</h2>
<div id="toc"></div>
Статьи
Разное
Step2: Кинематические данные по звездам
Кривая вращения
Step3: Дисперсии
Для большой оси
St... | Python Code:
from IPython.display import HTML
from IPython.display import Image
import os
%pylab
%matplotlib inline
%run ../../utils/load_notebook.py
from photometry import *
from instabilities import *
name = '...'
gtype = '...'
incl = None
scale = None #kpc/arcsec
data_path = None
# sin_i, cos_i = np.sin(incl*np.pi/1... |
11,922 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced Numpy Techniques
<img src="assets/numpylogo.png" alt="http
Step1: Bandwidth-limited ops
Have to pull in more cache lines for the pointers
Poor locality causes pipeline stalls
Step2... | Python Code:
import numpy as np
import time
import gc
import sys
assert sys.maxsize > 2 ** 32, "get a new computer!"
# Allocation-sensitive timing needs to be done more carefully
# Compares runtimes of f1, f2
def compare_times(f1, f2, setup1=None, setup2=None, runs=5):
print(' format: mean seconds (standard erro... |
11,923 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'ipsl', 'sandbox-2', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: IPSL
Source ID: SANDBOX-2
Topic: Ocnbgchem
Sub-Topics: Tracers.
Prop... |
11,924 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
xkcd 1313
Step1: We can see that there are multiple names that are both winners and losers
Step2: Clinton? He won both his elections, didn't he? Yes, Bill Clinton did, but George Clinton (... | Python Code:
from __future__ import division, print_function
import re
import itertools
def words(text): return set(text.split())
winners = words('''washington adams jefferson jefferson madison madison monroe
monroe adams jackson jackson van-buren harrison polk taylor pierce buchanan
lincoln lincoln grant gra... |
11,925 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The following source code defines a convolutional neural network architecture called LeNet. LeNet is a popular network known to work well on digit classification tasks. We will use a slightl... | Python Code:
data = mx.sym.var('data')
# first conv layer
conv1 = mx.sym.Convolution(data=data, kernel=(5,5), num_filter=20)
tanh1 = mx.sym.Activation(data=conv1, act_type="tanh")
pool1 = mx.sym.Pooling(data=tanh1, pool_type="max", kernel=(2,2), stride=(2,2))
# second conv layer
conv2 = mx.sym.Convolution(data=pool1, k... |
11,926 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's do a quick inspection of the data by plotting the distribution of the different types of cuisines in the dataset.
Step1: Italian and mexican categories dominate the recipes dataset. W... | Python Code:
train = pd.read_json("train.json")
matplotlib.style.use('ggplot')
cuisine_group = train.groupby('cuisine')
cuisine_group.size().sort_values(ascending=True).plot.barh()
plt.show()
Explanation: Let's do a quick inspection of the data by plotting the distribution of the different types of cuisines in the data... |
11,927 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
To create a new database, we first import sqlite3 and then instantiate a new database object with the sqlite3.connect() method.
Step2: Next, we connect to the database with the sqlite3.conn... | Python Code:
import sqlite3
db = sqlite3.connect("name_database.db")
Explanation: To create a new database, we first import sqlite3 and then instantiate a new database object with the sqlite3.connect() method.
End of explanation
# create a database called name_database.db
# add one table to the database called names_ta... |
11,928 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Load and inspect the data
Step1: 2. Let the toolkit choose the model
Step2: 3. The simple thresholding model
Step3: 4. The moving Z-score model
Step4: 5. The Bayesian changepoint mode... | Python Code:
import graphlab as gl
okla_daily = gl.load_timeseries('working_data/ok_daily_stats.ts')
print "Number of rows:", len(okla_daily)
print "Start:", okla_daily.min_time
print "End:", okla_daily.max_time
okla_daily.print_rows(3)
import matplotlib.pyplot as plt
%matplotlib notebook
plt.style.use('ggplot')
fig, a... |
11,929 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
KinMS galaxy fitting tutorial
This tutorial aims at getting you up and running with galaxy kinematic modelling using KinMS! To start you will need to download the KinMSpy code and have it in... | Python Code:
from kinms import KinMS
import numpy as np
from astropy.io import fits
from kinms.utils.KinMS_figures import KinMS_plotter
Explanation: KinMS galaxy fitting tutorial
This tutorial aims at getting you up and running with galaxy kinematic modelling using KinMS! To start you will need to download the KinMSpy ... |
11,930 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This is the IOHMM model with the parameters learned in a supervised way. This is corresponding to the counting frequency process as in the supervised HMM. See notes in http
Step1: Load spee... | Python Code:
from __future__ import division
import json
import warnings
import numpy as np
import pandas as pd
from IOHMM import SupervisedIOHMM
from IOHMM import OLS, CrossEntropyMNL
warnings.simplefilter("ignore")
Explanation: This is the IOHMM model with the parameters learned in a supervised way. This is correspo... |
11,931 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sebastian Raschka, 2015
Python Machine Learning Essentials
Compressing Data via Dimensionality Reduction
Note that the optional watermark extension is a small IPython notebook plugin that I ... | Python Code:
%load_ext watermark
%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,scipy,matplotlib,scikit-learn
# to install watermark just uncomment the following line:
#%install_ext https://raw.githubusercontent.com/rasbt/watermark/master/watermark.py
Explanation: Sebastian Raschka, 2015
Python Machine Learning Es... |
11,932 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Energy Lancaster publication miner
This workbook parses all of the publications listed on Energy Lancaster's Lancaster University Research Portal page and extracts keywoprds an topical data ... | Python Code:
#python dom extension functions to get class and other attributes
def getAttr(dom,cl,attr='class',el='div'):
toreturn=[]
divs=dom.getElementsByTagName(el)
for div in divs:
clarray=div.getAttribute(attr).split(' ')
for cli in clarray:
if cli==cl: toreturn.append(div)
... |
11,933 | Given the following text description, write Python code to implement the functionality described.
Description:
Construct two N
Function to generate two arrays satisfying the given conditions ; Declare the two arrays A and B ; Iterate from range [ 1 , 2 * n ] ; Assign consecutive numbers to same indices of the two array... | Python Code:
def printArrays(n ) :
A , B =[] ,[] ;
for i in range(1 , 2 * n + 1 ) :
if(i % 2 == 0 ) :
A . append(i ) ;
else :
B . append(i ) ;
print("{ ▁ ", end = "") ;
for i in range(n ) :
print(A[i ] , end = "") ;
if(i != n - 1 ) :
print(", ▁ ", end = "") ;
print("} ") ;
prin... |
11,934 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
COSC Learning Lab
03_interface_startup.py
Related Scripts
Step1: Implementation
Step2: Execution
Step3: HTTP | Python Code:
help('learning_lab.03_interface_startup')
Explanation: COSC Learning Lab
03_interface_startup.py
Related Scripts:
* 03_interface_shutdown.py
* 03_interface_configuration.py
Table of Contents
Table of Contents
Documentation
Implementation
Execution
HTTP
Documentation
End of explanation
from importlib import... |
11,935 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GEM-PRO - SBML Model
This notebook gives an example of how to run the GEM-PRO pipeline with a SBML model, in this case iNJ661, the metabolic model of M. tuberculosis.
<div class="alert alert... | Python Code:
import sys
import logging
# Import the GEM-PRO class
from ssbio.pipeline.gempro import GEMPRO
# Printing multiple outputs per cell
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
Explanation: GEM-PRO - SBML Model
This notebook gives an example of h... |
11,936 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Beaming and Boosting
Due to concerns about accuracy, support for Beaming & Boosting has been disabled as of the 2.2 release of PHOEBE (although we hope to bring it back in a future release).... | Python Code:
#!pip install -I "phoebe>=2.3,<2.4"
Explanation: Beaming and Boosting
Due to concerns about accuracy, support for Beaming & Boosting has been disabled as of the 2.2 release of PHOEBE (although we hope to bring it back in a future release).
It may come as surprise that support for Doppler boosting has been ... |
11,937 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Upvote data
Step1: In the Yelp Question in HW1, please normalize the data so that it has the same L2 norm. We will grade it either way, but please state clearly what you did to treat the ye... | Python Code:
# Load a text file of integers:
y = np.loadtxt("yelp_data/upvote_labels.txt", dtype=np.int)
# Load a text file with strings identifying the 1000 features:
featureNames = open("yelp_data/upvote_features.txt").read().splitlines()
featureNames = np.array(featureNames)
# Load a csv of floats, which are the val... |
11,938 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
11,939 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="img/nao.jpg" align="right" width=200>
Sensor de so (micròfon)
El micròfon del robot detecta el soroll ambiental. No sap reconèixer paraules, però si pot reaccionar a una palmada, o... | Python Code:
from functions import connect, sound, forward, stop
connect()
Explanation: <img src="img/nao.jpg" align="right" width=200>
Sensor de so (micròfon)
El micròfon del robot detecta el soroll ambiental. No sap reconèixer paraules, però si pot reaccionar a una palmada, o un crit. Altres robots més sofisticats co... |
11,940 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Initial Overview
First we want to have a look at the data.
Step1: Ok, so we're getting a pretty simple input format
Step2: According to my knowledge with quora, this is indeed a full text ... | Python Code:
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
df = pd.read_csv('../data/raw/train.csv')
df.head()
Explanation: Initial Overview
First we want to have a look at the data.
End of explanation
questions = pd.concat([df['question1'], df['question... |
11,941 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using ctools from Python
In this notebook you will learn how to use the ctools and cscripts from Python instead of typing the commands in the console.
ctools provides two Python modules that... | Python Code:
import gammalib
import ctools
import cscripts
Explanation: Using ctools from Python
In this notebook you will learn how to use the ctools and cscripts from Python instead of typing the commands in the console.
ctools provides two Python modules that allow using all tools and scripts as Python classes. To u... |
11,942 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exemplo de CRUD no MongoDB
Exemplo de CRUD completo em MongoDB
Autor
Step1: Definindo um documento para ser inserido
Step2: Inserindo o documento na base
Step3: Recuperando documentos
Ste... | Python Code:
from pymongo import MongoClient
cli = MongoClient()
db = cli['treinamento']
col = db['cadastro']
Explanation: Exemplo de CRUD no MongoDB
Exemplo de CRUD completo em MongoDB
Autor: Christiano Anderson
Propus Data Science
Estabelecendo a conexão com o banco
End of explanation
cad = {
'nome': 'Christiano ... |
11,943 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing Stock Indices
by Magnus Erik Hvass Pedersen
/ GitHub / Videos on YouTube
Introduction
When comparing the historical returns on stock indices, it is a common mistake to only conside... | Python Code:
%matplotlib inline
# Imports from Python packages.
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
import pandas as pd
import numpy as np
import os
# Imports from FinanceOps.
from data_keys import *
from data import load_index_data, load_usa_cpi
from data import load_usa_gov_bon... |
11,944 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple Sounding
Use MetPy as straightforward as possible to make a Skew-T LogP plot.
Step1: We will pull the data out of the example dataset into individual variables and
assign units. | Python Code:
import matplotlib.pyplot as plt
import numpy as np
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
# Change default to be better for skew-T
plt.rcParams['figure.figsize'] = (9, 9)
# Upper air d... |
11,945 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Here we want to place n events of transition between an ancestral lifestyle and a convergent lifestyle in a phylogeny.
We want these n events to be independent, not nested.
We return them in... | Python Code:
from ete3 import Tree
import string
import scipy.stats as stats
import numpy as np
tl = Tree()
# We create a random tree topology
numTips = 20
candidateNames = list(string.ascii_lowercase)
tipNames = candidateNames[0:20]
tl.populate(numTips, names_library=tipNames)
print (tl)
#Alternatively we could read a... |
11,946 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data deduplication
Introduction
This example shows how to find records in datasets belonging to the same
entity. In our case,we try to deduplicate a dataset with records of
persons. We will ... | Python Code:
import recordlinkage
from recordlinkage.datasets import load_febrl1
Explanation: Data deduplication
Introduction
This example shows how to find records in datasets belonging to the same
entity. In our case,we try to deduplicate a dataset with records of
persons. We will try to link within the dataset based... |
11,947 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image classification with EANet (External Attention Transformer)
Author
Step1: Prepare the data
Step2: Configure the hyperparameters
Step3: Use data augmentation
Step4: Implement the pat... | Python Code:
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import tensorflow_addons as tfa
import matplotlib.pyplot as plt
Explanation: Image classification with EANet (External Attention Transformer)
Author: ZhiYong Chang<br>
Date created: 2021/10/19<br>
La... |
11,948 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
La función
Esta ecuación por Glass y Pasternack (1978) sirve para modelar redes neuronales y de interacción génica.
$$x_{t+1}=\frac{\alpha x_{t}}{1+\beta x_{t}}$$
Donde $\alpha$ y $\beta$ so... | Python Code:
def g(x, alpha, beta):
assert alpha >= 0 and beta >= 0
return (alpha*x)/(1 + (beta * x))
def plot_cobg(x, alpha, beta):
y = np.linspace(x[0],x[1],300)
g_y = g(y, alpha, beta)
cobweb(lambda x: g(x, alpha, beta), y, g_y)
# configura gráfica interactiva
interact(plot_cobg,
x=wid... |
11,949 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
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', 'cccma', 'sandbox-3', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: CCCMA
Source ID: SANDBOX-3
Topic: Landice
Sub-Topics: Glaciers, Ice.
Pr... |
11,950 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to run the /home/test/indras_net/models/flocking model.
First we import all necessary files.
Step1: We then initialize global variables.
Step2: Next we call the set_up function to set ... | Python Code:
from models.flocking import set_up
Explanation: How to run the /home/test/indras_net/models/flocking model.
First we import all necessary files.
End of explanation
from indra.agent import Agent, X, Y
from indra.composite import Composite
from indra.display_methods import BLUE, TREE
from indra.env import En... |
11,951 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The Cirq Developers
Step1: Rabi oscillation experiment
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: In this experiment,... | 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
# dis... |
11,952 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
sell-short-in-may-and-go-away
see
Step1: Some global data
Step2: Define Strategy Class
Step3: Run Strategy
Step4: Run Benchmark, Retrieve benchmark logs, and Generate benchmark stats
Ste... | Python Code:
import datetime
import matplotlib.pyplot as plt
import pandas as pd
import pinkfish as pf
# Format price data
pd.options.display.float_format = '{:0.2f}'.format
%matplotlib inline
# Set size of inline plots
'''note: rcParams can't be in same cell as import matplotlib
or %matplotlib inline
%matplo... |
11,953 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2. Acquire the Data
Finding Data Sources
There are three place to get onion price and quantity information by market.
Agmarket - This is the website run by the Directorate of Marketing & In... | Python Code:
# Import the library we need, which is Pandas
import pandas as pd
# Read all the tables from the html document
AllTables = pd.read_html('MonthWiseMarketArrivalsJan2016.html')
# Let us find out how many tables has it found?
len(AllTables)
Explanation: 2. Acquire the Data
Finding Data Sources
There are thre... |
11,954 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
분산 분석 기반의 카테고리 분석
회귀 분석 대상이 되는 독립 변수가 카테고리 값을 가지는 변수인 경우에는 카테고리 값에 의해 연속 변수인 y값이 달라진다. 이러한 경우, 분산 분석(ANOVA)을 사용하면 카테고리 값의 영향을 정량적으로 분석할 수 있다. 또한 이는 카테고리 값에 의해 회귀 모형이 달라지는 것으로도 볼 수 있기 때문에 모형 ... | Python Code:
from sklearn.preprocessing import OneHotEncoder
encoder = OneHotEncoder()
x0 = np.random.choice(3, 10)
x0
encoder.fit(x0[:, np.newaxis])
X = encoder.transform(x0[:, np.newaxis]).toarray()
X
dfX = pd.DataFrame(X, columns=encoder.active_features_)
dfX
Explanation: 분산 분석 기반의 카테고리 분석
회귀 분석 대상이 되는 독립 변수가 카테고리 값... |
11,955 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This IPython notebook illustrates how to perform matching using the rule-based matcher.
First, we need to import py_entitymatching package and other libraries as follows
Step1: ... | Python Code:
# Import py_entitymatching package
import py_entitymatching as em
import os
import pandas as pd
Explanation: Introduction
This IPython notebook illustrates how to perform matching using the rule-based matcher.
First, we need to import py_entitymatching package and other libraries as follows:
End of explana... |
11,956 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
https
Step1: Step 0 - hyperparams
Step2: Step 1 - collect data (and/or generate them)
Step3: Step 2 - Build model
Step4: Step 3 training the network
Step5: TODO Co integration
https | Python Code:
from __future__ import division
import tensorflow as tf
from os import path
import numpy as np
import pandas as pd
import csv
from sklearn.model_selection import StratifiedShuffleSplit
from time import time
from matplotlib import pyplot as plt
import seaborn as sns
from mylibs.jupyter_notebook_helper impor... |
11,957 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using the template below, make a widget view that displays text, possibly 'Hello World'.
Step1: Using the template below, make a color picker widget. This can be done in a few steps | Python Code:
%%javascript
delete requirejs.s.contexts._.defined.CustomViewModule;
define('CustomViewModule', ['jquery', 'widgets/js/widget'], function($, widget) {
var CustomView = widget.DOMWidgetView.extend({
});
return {CustomView: CustomView};
});
from IPython.html.widgets import DOMWidget
from IPython.... |
11,958 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
minimask mosaic example
Construct a mosaic of squares over the sky
Step1: Specify the location of the mask file to write
Step2: Construct a mask using a tile pattern with centers specified... | Python Code:
%matplotlib notebook
import os
import numpy as np
import tempfile
import matplotlib.pyplot as pyplot
import logging
logging.basicConfig(level=logging.INFO)
import minimask.mask as mask
import minimask.healpix_projection as hp
import minimask.io.mosaic as mosaic
Explanation: minimask mosaic example
Construc... |
11,959 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DAT210x - Programming with Python for DS
Module4- Lab1
Step1: Every 100 samples in the dataset, we save 1. If things run too slow, try increasing this number. If things run too fast, try de... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
from mpl_toolkits.mplot3d import Axes3D
from plyfile import PlyData, PlyElement
# Look pretty...
# matplotlib.style.use('ggplot')
plt.style.use('ggplot')
Explanation: DAT210x - Programming with Python for DS
Module4- Lab1
End of explanat... |
11,960 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> Feature Engineering </h1>
In this notebook, you will learn how to incorporate feature engineering into your pipeline.
<ul>
<li> Working with feature columns </li>
<li> Adding feature cr... | Python Code:
%%bash
source activate py2env
conda install -y pytz
pip uninstall -y google-cloud-dataflow
pip install --upgrade apache-beam[gcp]==2.9.0
Explanation: <h1> Feature Engineering </h1>
In this notebook, you will learn how to incorporate feature engineering into your pipeline.
<ul>
<li> Working with feature col... |
11,961 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1 toc-item"><a href="#A-short-study-of-Rényi-entropy" data-toc-modified-id="A-short-study-of-Rényi-entropy-1"><span class="toc-item-num">1 </sp... | Python Code:
!pip install watermark matplotlib numpy
%load_ext watermark
%watermark -v -m -a "Lilian Besson" -g -p matplotlib,numpy
import numpy as np
import matplotlib.pyplot as plt
Explanation: Table of Contents
<p><div class="lev1 toc-item"><a href="#A-short-study-of-Rényi-entropy" data-toc-modified-id="A-short-stud... |
11,962 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Combining and Merging Streams
Step1: Combining Streams with Binary Operators
For streams x, y, and a binary operator, op
Step2: Examples of zip_stream and zip_map
zip_stream is similar to ... | Python Code:
import sys
sys.path.append("../")
from IoTPy.core.stream import Stream, run
from IoTPy.agent_types.op import map_element
from IoTPy.helper_functions.recent_values import recent_values
Explanation: Combining and Merging Streams
End of explanation
w = Stream('w')
x = Stream('x')
y = Stream('y')
z = (x+y)*w
#... |
11,963 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python Exercises
This notebook is for programming exercises in python using
Step1: Python Statistics
Step2: Some simpler exercises based on common python function
Question
Step3: Questio... | Python Code:
import math
import numpy as np
import pandas as pd
import re
from operator import itemgetter, attrgetter
Explanation: Python Exercises
This notebook is for programming exercises in python using :
Statistics
Inbuilt Functions and Libraries
Pandas
Numpy
End of explanation
def median(dataPoints):
"comp... |
11,964 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image Processing
This ipython (sorry, Jupyter) notebook contains the examples that I'll be covering in the 1-dimensional part of my image processing session. There are no external data file... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
# A nice alternative to inline (which allows interaction with the plots, but can be confusing) is
# %matplotlib notebook
Explanation: Image Processing
This ipython (sorry, Jupyter) notebook contains the examples that I'll be covering in ... |
11,965 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep CNN Models
Constructing and training your own ConvNet from scratch can be Hard and a long task.
A common trick used in Deep Learning is to use a pre-trained model and finetune it to the... | Python Code:
from keras.applications import VGG16
from keras.applications.imagenet_utils import preprocess_input, decode_predictions
import os
# -- Jupyter/IPython way to see documentation
# please focus on parameters (e.g. include top)
VGG16??
vgg16 = VGG16(include_top=True, weights='imagenet')
Explanation: Deep CNN M... |
11,966 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
자료 안내
Step1: 주의
위 모듈을 임포트하면 아래 모듈 또한 자동으로 임포트 된다.
GongSu21_Statistics_Averages.py
주요 내용
상관분석
공분산
상관관계와 인과관계
주요 예제
21장에서 다룬 미국의 51개 주에서 거래되는 담배(식물)의 도매가격 데이터를 보다 상세히 분석한다.
특히, 캘리포니아 주에서 거래된... | Python Code:
from GongSu22_Statistics_Population_Variance import *
Explanation: 자료 안내: 여기서 다루는 내용은 아래 사이트의 내용을 참고하여 생성되었음.
https://github.com/rouseguy/intro2stats
상관분석
안내사항
지난 시간에 다룬 21장과 22장 내용을 활용하고자 한다.
따라서 아래와 같이 21장과 22장 내용을 모듈로 담고 있는 파이썬 파일을 임포트 해야 한다.
주의: 아래 두 개의 파일이 동일한 디렉토리에 위치해야 한다.
* GongSu21_Statistics_Aver... |
11,967 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notes from David Beazley's Python3 Metaprogramming tutorial (2013)
"ported" to Python 2.7, unless noted otherwise
A Debugging Decorator
Step1: Decorators with arguments
Calling convention
p... | Python Code:
from functools import wraps
def debug(func):
msg = func.__name__
# wraps is used to keep the metadata of the original function
@wraps(func)
def wrapper(*args, **kwargs):
print(msg)
return func(*args, **kwargs)
return wrapper
@debug
def add(x,y):
return x+y
add(2,3)
d... |
11,968 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Geospatial data models
Resources
Step1: In startup pannel set GIS Data Directory to path to datasets,
for example on MS Windows, C
Step2: The -p flag for g.region is used to print the regi... | Python Code:
# Obtain sample data and set new Grass mapset
import urllib
from zipfile import ZipFile
import os.path
zip_path = "/home/jovyan/work/tmp/nc_spm_08_grass7.zip"
mapset_path = "/home/jovyan/grassdata"
if not os.path.exists(zip_path):
urllib.urlretrieve("https://grass.osgeo.org/sampledata/north_carolina/nc... |
11,969 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Performing Linear Regression in TensorFlow
I gathered this data for current real estate listing prices in North Bergen from Zillow. Let's see if we can use it to develop a model for housing ... | Python Code:
%matplotlib inline
#Typical imports
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
import pandas as pd
# plots on fleek
matplotlib.style.use('ggplot')
# Read the housing data from the csv file into a pandas dataframe
# the names keyword allows us to name the co... |
11,970 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Linear Regression
Learning Objectives
Analyze a Pandas Dataframe
Create Seaborn plots for Exporatory Data Analysis
Train a Linear Regression Model using Scikit-Learn
Introdu... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns # Seaborn is a Python data visualization library based on matplotlib.
%matplotlib inline
Explanation: Introduction to Linear Regression
... |
11,971 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
pandasのデータフレーム
Step1: ２次元の array を DataFrame に変換する例です。
Step2: columns オプションで、各列の column 名を指定します。
Step3: Series オブジェクトから DataFrame を作成する例です。
Step4: 各列の column 名と対応する Series オブジェクトのディクショナリ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from pandas import Series, DataFrame
Explanation: pandasのデータフレーム
End of explanation
from numpy.random import randint
dices = randint(1,7,(5,2))
dices
Explanation: ２次元の array を DataFrame に変換する例です。
End of explanation
diceroll = DataFrame(... |
11,972 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: NumPy has many built-in functions and capabilities. We won't cover them all but instead we will focus on some of the most important aspects of NumPy
Step2: Built-in Me... | Python Code:
import numpy as np
Explanation: <a href='http://www.pieriandata.com'><img src='../Pierian_Data_Logo.png'/></a>
<center><em>Copyright Pierian Data</em></center>
<center><em>For more information, visit us at <a href='http://www.pieriandata.com'>www.pieriandata.com</a></em></center>
NumPy
NumPy is a powerful ... |
11,973 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generative Adversarial Network
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten d... | Python Code:
%matplotlib inline
import pickle as pkl
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data')
Explanation: Generative Adversarial Network
In this notebook, we'll be building a gen... |
11,974 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Input Data
Step1: Test Frame
Nodes
Table nodes (file nodes.csv) provides the $x$-$y$ coordinates of each node. Other columns, such
as the $z$- coordinate are optional, and ignored if give... | Python Code:
from salib import extend, NBImporter
from Tables import Table, DataSource
from Nodes import Node
from Members import Member
from LoadSets import LoadSet, LoadCombination
from NodeLoads import makeNodeLoad
from MemberLoads import makeMemberLoad
from collections import OrderedDict, defaultdict
import numpy a... |
11,975 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Keras
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: tf.keras ではKerasと互換性のあるコードを実行できますが、注意... | 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... |
11,976 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Two Envelope Paradox - Simulated
Introduction
Bayesian statistics can most naively be described as the art of thinking conditionally. Conditional probability leads often to unexpected ou... | Python Code:
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pymc as pm
from numpy.random import choice
%matplotlib inline
matplotlib.style.use('ggplot')
matplotlib.rc_params_from_file("../styles/matplotlibrc" ).update()
Explanation: The Two Envelope Paradox - Simulated
Introduction
Bayesian... |
11,977 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dimensionality Reduction with the Shogun Machine Learning Toolbox
By Sergey Lisitsyn (lisitsyn) and Fernando J. Iglesias Garcia (iglesias).
This notebook illustrates <a href="http
Step1: Th... | Python Code:
import numpy
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
def generate_data(curve_type, num_points=1000):
if curve_type=='swissroll':
tt = numpy.array((3*numpy.pi/2)*(1+2*numpy.random.rand(num_points)))
height = numpy.array((numpy.random.rand(num_points)-0.5))
X = numpy.ar... |
11,978 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generative Adversarial Network
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten d... | Python Code:
%matplotlib inline
import pickle as pkl
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data')
Explanation: Generative Adversarial Network
In this notebook, we'll be building a gen... |
11,979 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: MNIST on TPU (Tensor Processing Unit)<br>or GPU using tf.Keras and tf.data.Dataset
<table><tr><td><img valign="middle" src="https
Step2: (you can double-ckick on collapsed cells to v... | Python Code:
import os, re, time, json
import PIL.Image, PIL.ImageFont, PIL.ImageDraw
import numpy as np
import tensorflow as tf
from matplotlib import pyplot as plt
AUTOTUNE = tf.data.AUTOTUNE
print("Tensorflow version " + tf.__version__)
#@title visualization utilities [RUN ME]
This cell contains helper functions use... |
11,980 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load necessary packages
Step1: Define functions for filtering, moving averages, and normalizing data
Step2: Read bandwidth and rain/temperature data and normalize them
Step3: Smoothing da... | Python Code:
%matplotlib inline
from scipy import interpolate
from scipy import special
from scipy.signal import butter, lfilter, filtfilt
import matplotlib.pyplot as plt
import numpy as np
from numpy import genfromtxt
from nitime import algorithms as alg
from nitime import utils
from scipy.stats import t
import pandas... |
11,981 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Практическое задание к уроку 1 (2 неделя).
Линейная регрессия
Step1: Мы будем работать с датасетом "bikes_rent.csv", в котором по дням записаны календарная информация и погодные условия, ха... | Python Code:
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
Explanation: Практическое задание к уроку 1 (2 неделя).
Линейная регрессия: переобучение и регуляризация
В этом задании мы на примерах увидим, как переобучаются линейные модели, разберем, почему так происходит, и... |
11,982 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assembly of system with multiple domains, variables and numerics
This tutorial has the dual purpose of illustrating parameter assigment in PorePy, and also showing how to set up problems in... | Python Code:
import numpy as np
import scipy.sparse as sps
import porepy as pp
Explanation: Assembly of system with multiple domains, variables and numerics
This tutorial has the dual purpose of illustrating parameter assigment in PorePy, and also showing how to set up problems in (mixed-dimensional) geometries. It co... |
11,983 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classifying dogs vs cats with Alex Net
In this notebook, we try to implement a (somehow simplified) version of Alex Net to solve the Cats vs Dogs problem from Kaggle.
Following indications f... | Python Code:
from __future__ import division, print_function
from matplotlib import pyplot as plt
%matplotlib inline
import os, errno
import numpy as np
from tqdm import tqdm
from shutil import copy
import numpy as np
import pandas as pd
import cv2
import bcolz
IMAGE_WIDTH = 227
IMAGE_HEIGHT = 227
Explanation: Classify... |
11,984 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex client library
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Once you've installed the Vertex client library and Google clo... | Python Code:
import os
import sys
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install -U google-cloud-aiplatform $USER_FLAG
Explanation: Vertex client library: AutoML image segmentation model for online prediction
<table a... |
11,985 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Contents and Objectives
Implementation of the water-filling algorithm
Interactive illustration of the water-filling principle
Step1: Specify total power p_tot as well as the noise levels of... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from ipywidgets import interactive
import ipywidgets as widgets
%matplotlib inline
# plotting options
font = {'size' : 30}
plt.rc('font', **font)
plt.rc('text', usetex=matplotlib.checkdep_usetex(True))
matplotlib.rc('figure', figsize=(... |
11,986 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Near-duplicate image search
Author
Step1: Load the dataset and create a training set of 1,000 images
To keep the run time of the example short, we will be using a subset of 1,000 images fro... | Python Code:
import matplotlib.pyplot as plt
import tensorflow as tf
import numpy as np
import time
import tensorflow_datasets as tfds
tfds.disable_progress_bar()
Explanation: Near-duplicate image search
Author: Sayak Paul<br>
Date created: 2021/09/10<br>
Last modified: 2021/09/10<br>
Description: Building a near-dupli... |
11,987 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overlapping Mixtures of Gaussian Processses
Valentine Svensson 2015 <br> (with small edits by James Hensman November 2015)
This illustrates use of the OMGP model described in
Overlapping Mix... | Python Code:
%matplotlib inline
import GPy
from GPclust import OMGP
import matplotlib
matplotlib.rcParams['figure.figsize'] = (12,6)
from matplotlib import pyplot as plt
Explanation: Overlapping Mixtures of Gaussian Processses
Valentine Svensson 2015 <br> (with small edits by James Hensman November 2015)
This illustrat... |
11,988 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial
Step1: Modern X-ray CCDs are technologically similar to the CCDs used in optical astronomy
Step2: Both files are in FITS image format, which we can read in using astropy.io.fits (... | Python Code:
exec(open('tbc.py').read()) # define TBC and TBC_above
import astropy.io.fits as pyfits
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from astropy.visualization import LogStretch
logstretch = LogStretch()
import scipy.stats as st
Explanation: Tutorial: X-ray Image Data
This notebook... |
11,989 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Encontro 02, Parte 2
Step1: A seguir, vamos configurar as propriedades visuais
Step2: Por fim, vamos carregar e visualizar um grafo
Step3: Caminhos de comprimento mínimo
Seja $\langle n_0... | Python Code:
import sys
sys.path.append('..')
import socnet as sn
Explanation: Encontro 02, Parte 2: Revisão de Busca em Largura
Este guia foi escrito para ajudar você a atingir os seguintes objetivos:
implementar o algoritmo de busca em largura;
usar funcionalidades avançadas da biblioteca da disciplina.
Primeiramente... |
11,990 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Posterior Predictive Checks
PPCs are a great way to validate a model. The idea is to generate data sets from the model using parameter settings from draws from the posterior.
Elaborating sl... | Python Code:
%matplotlib inline
import numpy as np
import pymc3 as pm
import seaborn as sns
import matplotlib.pyplot as plt
from collections import defaultdict
Explanation: Posterior Predictive Checks
PPCs are a great way to validate a model. The idea is to generate data sets from the model using parameter settings fro... |
11,991 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simulation API
A merchant wants to offer products and maximize profits. Just like on a real online marketplace, he can look at all existing offers, add some own, restock or reprice. First, i... | Python Code:
import sys
sys.path.append('../')
Explanation: Simulation API
A merchant wants to offer products and maximize profits. Just like on a real online marketplace, he can look at all existing offers, add some own, restock or reprice. First, it has to order products from the producer, which comes with costs. All... |
11,992 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!-- Some HTML for ncie picture -->
<p>
<a href="https
Step1: A. The semantic connections
Step2: A. Web of Science - Recursion 1.
Search details
Date
Step3: Keyword analysis
Step4: J... | Python Code:
maketimeseries() # Load this function from bottom of notebook to print.
Explanation: <!-- Some HTML for ncie picture -->
<p>
<a href="https://commons.wikimedia.org/wiki/File:Open_Science_-_Prinzipien.png#/media/File:Open_Science_-_Prinzipien.png"><img src="https://upload.wikimedia.org/wikipedia/commons... |
11,993 | Given the following text description, write Python code to implement the functionality described.
Description:
Queries for rotation and Kth character of the given string in constant time
Python3 implementation of the approach ; Function to perform the required queries on the given string ; Pointer pointing to the curre... | Python Code:
size = 2
def performQueries(string , n , queries , q ) :
ptr = 0 ;
for i in range(q ) :
if(queries[i ][0 ] == 1 ) :
ptr =(ptr + queries[i ][1 ] ) % n ;
else :
k = queries[i ][1 ] ;
index =(ptr + k - 1 ) % n ;
print(string[index ] ) ;
if __name__== "__main __":
string = "a... |
11,994 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FAI1 Practical Deep Learning I | 11 May 2017 | Wayne Nixalo
In this notebook I'll be building a simple linear model in Keras using Sequential()
Tutorial on Linear Model for MNIST
Step1: Tha... | Python Code:
# Import relevant libraries
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import SGD, RMSprop
from keras.preprocessing import image
import numpy as np
import os
# Data functions ~ mostly from utils.py or vgg16.py
def get_batches(dirname, gen=image.ImageDataGenerat... |
11,995 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<font size="8">Energy Meter Examples</font>
<br>
<font size="5">BayLibre's ACME Cape and IIOCapture</font>
<br>
<hr>
Import Required Modules
Step1: Target Configuration
Step2: Workload Exe... | Python Code:
import logging
reload(logging)
logging.basicConfig(
format='%(asctime)-9s %(levelname)-8s: %(message)s',
datefmt='%I:%M:%S')
# Enable logging at INFO level
logging.getLogger().setLevel(logging.INFO)
# Generate plots inline
%matplotlib inline
import os
# Support to access the remote target
import de... |
11,996 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multi-bootstrap for evaluating pretrained LMs
This notebook shows an example of a paired multi-bootstrap analysis. This type of analysis is applicable for any kind of intervention that is ap... | Python Code:
#@title Import libraries and multibootstrap code
import re
import os
import numpy as np
import pandas as pd
import sklearn.metrics
import scipy.stats
from tqdm.notebook import tqdm # for progress indicator
import multibootstrap
scratch_dir = "/tmp/multiberts_mnli"
if not os.path.isdir(scratch_dir):
o... |
11,997 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 6.1.2 - Using word embeddings
Embedding layer with Keras
Step1: The layers transforms a 2D input tensor of integer of shape (number_of samples, sequence_length) into a 3D floating p... | Python Code:
import keras
keras.__version__
from keras.layers import Embedding
# Number of maximum tokens is equal of maximum word index + 1
max_number_of_tokens = 1000
embedding_dimentionality = 64
embedding_layer = Embedding(max_number_of_tokens, embedding_dimentionality)
Explanation: Chapter 6.1.2 - Using word embed... |
11,998 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Starting the Analysis Cluster
NEXUS utilizes Apache Spark running on Apache Mesos for its analytical functions. Now that the infrastructure has been started, we can start up the analysis clu... | Python Code:
# TODO Run this cell to see the status of the Mesos slaves. You should see 3 slaves connected.
import requests
import json
response = requests.get('http://mesos-master:5050/state.json')
print(json.dumps(response.json()['slaves'], indent=2))
Explanation: Starting the Analysis Cluster
NEXUS utilizes Apache S... |
11,999 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Model10
Step2: Feature functions(private)
Step3: Feature function(public)
Step4: Utility functions
Step5: GMM
Classifying questions
features
Step7: B. Modeling
Select model
Step8... | Python Code:
import gzip
import pickle
from os import path
from collections import defaultdict
from numpy import sign
Load buzz data as a dictionary.
You can give parameter for data so that you will get what you need only.
def load_buzz(root='../data', data=['train', 'test', 'questions'], format='pklz'):
buzz_data ... |
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