Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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5,700 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cahn-Hilliard Example
This example demonstrates how to use PyMKS to solve the Cahn-Hilliard equation. The first section provides some background information about the Cahn-Hilliard equation ... | Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import numpy as np
import matplotlib.pyplot as plt
Explanation: Cahn-Hilliard Example
This example demonstrates how to use PyMKS to solve the Cahn-Hilliard equation. The first section provides some background information about the Cahn-Hilliard equation... |
5,701 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute IonPopSolver Results
Here, we'll run the IonPopSolver code using some of the EBTEL results in order to account for non-equilibrium ionization in our results. We'll use the multiproce... | Python Code:
import os
import pickle
import multiprocessing
import subprocess
import xml.etree.ElementTree as ET
import numpy as np
Explanation: Compute IonPopSolver Results
Here, we'll run the IonPopSolver code using some of the EBTEL results in order to account for non-equilibrium ionization in our results. We'll use... |
5,702 | 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', 'noaa-gfdl', 'sandbox-3', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: NOAA-GFDL
Source ID: SANDBOX-3
Topic: Seaice
Sub-Topics: Dynamics, The... |
5,703 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's scrape a practice table
The latest Mountain Goats album is called Goths. (It's good!) I made a simple HTML table with the track listing -- let's scrape it into a CSV.
Import the module... | Python Code:
from bs4 import BeautifulSoup
import csv
Explanation: Let's scrape a practice table
The latest Mountain Goats album is called Goths. (It's good!) I made a simple HTML table with the track listing -- let's scrape it into a CSV.
Import the modules we'll need
End of explanation
# in a with block, open the HTM... |
5,704 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NLP training example
In this example, we'll train an NLP model for sentiment analysis of tweets using spaCy.
First we download spaCy language libraries.
Step1: And import the boilerplate co... | Python Code:
!python -m spacy download en_core_web_sm
Explanation: NLP training example
In this example, we'll train an NLP model for sentiment analysis of tweets using spaCy.
First we download spaCy language libraries.
End of explanation
from __future__ import unicode_literals, print_function
import boto3
import json
... |
5,705 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Probabilistic Bayesian Neural Networks
Author
Step1: Create training and evaluation datasets
Here, we load the wine_quality dataset using tfds.load(), and we convert
the target feature to f... | Python Code:
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import tensorflow_datasets as tfds
import tensorflow_probability as tfp
Explanation: Probabilistic Bayesian Neural Networks
Author: Khalid Salama<br>
Date created: 2021/01/15<br>
Last modified: 2021/... |
5,706 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Integration Exercise 1
Imports
Step2: Trapezoidal rule
The trapezoidal rule generates a numerical approximation to the 1d integral
Step3: Now use scipy.integrate.quad to integrate the f an... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy import integrate
Explanation: Integration Exercise 1
Imports
End of explanation
def trapz(f, a, b, N):
Integrate the function f(x) over the range [a,b] with N points.
#I worked with James A
# YOUR CODE HERE
#ra... |
5,707 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook describes how to use the provided tools to interface with the data. It goes over the process of installing the tools, retrieving the data, and opening the data within a noteboo... | Python Code:
import numpy as np
import matplotlib.pylab as plt
%matplotlib notebook
Explanation: This notebook describes how to use the provided tools to interface with the data. It goes over the process of installing the tools, retrieving the data, and opening the data within a notebook.
<br>
<br>
Importing the tools ... |
5,708 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">Basic CFNCluster Setup</h1>
<h3 align="center">Author
Step1: 1. Install CFNCluster
Notice
Step2: 2. Upgrade CFNCluster
Step3: 3. Configure CFNCluster
To configure CFNCl... | Python Code:
import os
import sys
sys.path.append(os.getcwd().replace("notebooks/awsCluster", "src/awsCluster"))
## Input the AWS account access keys
aws_access_key_id = "/**aws_access_key_id**/"
aws_secret_access_key = "/**aws_secret_access_key**/"
## CFNCluster name
your_cluster_name = "cluster_name"
## The private ... |
5,709 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to use implemented algorithms
Overview
The project has the following structure
Step1: We will check if the library is imported correctly by computing a few parameters of empty graph.
St... | Python Code:
import sys, os
# sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath('../src/'))))
sys.path.append('../src/')
import graph
reload(graph)
Explanation: How to use implemented algorithms
Overview
The project has the following structure:
doc contains documentation of the project
src contains all t... |
5,710 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
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', 'mohc', 'ukesm1-0-ll', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: MOHC
Source ID: UKESM1-0-LL
Topic: Aerosol
Sub-Topics: Transport, Emiss... |
5,711 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Weight clustering in Keras example
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Train a ... | 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... |
5,712 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regridding input data to higher resolution
The initial resolution of the input file is used as the higher resolution that Badlands model can used. If one started with a given resolution and ... | Python Code:
import sys
print(sys.version)
print(sys.executable)
%matplotlib inline
# Import badlands grid generation toolbox
import pybadlands_companion.resizeInput as resize
Explanation: Regridding input data to higher resolution
The initial resolution of the input file is used as the higher resolution that Badlands ... |
5,713 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
xrange vs range looping
For long for loops with no need to track iteration use
Step1: This will loop through 10 times, but the iteration variable won't be unused as it was never assigned. ... | Python Code:
for _ in xrange(10):
print "Do something"
Explanation: xrange vs range looping
For long for loops with no need to track iteration use:
End of explanation
for i in range(1,10):
vars()['x'+str(i)] = i
Explanation: This will loop through 10 times, but the iteration variable won't be unused as it was n... |
5,714 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chopsticks!
A few researchers set out to determine the optimal length of chopsticks for children and adults. They came up with a measure of how effective a pair of chopsticks performed, call... | Python Code:
import pandas as pd
# pandas is a software library for data manipulation and analysis
# We commonly use shorter nicknames for certain packages. Pandas is often abbreviated to pd.
# hit shift + enter to run this cell or block of code
path = r'/Users/scott/googledrive/udacity/data_science/project_0/chopstick... |
5,715 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python for Webscraping
SOC 590
Step1: open US News Rankings for Sociology webpage
view page source to see html
Step3: create a function to extract page data from US News
Step4: make empty... | Python Code:
import os
import urllib
import webbrowser
import pandas as pd
from bs4 import BeautifulSoup
Explanation: Python for Webscraping
SOC 590: Big Data and Population Processes
17th October 2016
Tutorial 2: Webscraping with a function
Outline
Import modules
Examine html structure of a webpage
Use Beautiful Soup ... |
5,716 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Primeiramente, é necessária a leitura dos 3 arquivos, inserindo as informações em um vetor
Step1: Depois, devemos retirar cada quebra de linha no final de cada linha, ou seja, os '\n'.
Step... | Python Code:
import codecs
with codecs.open("imdb_labelled.txt", "r", "utf-8") as arquivo:
vetor = []
for linha in arquivo:
vetor.append(linha)
with codecs.open("amazon_cells_labelled.txt", "r", "utf-8") as arquivo:
for linha in arquivo:
vetor.append(linha)
with codecs.open("yelp_labelled.... |
5,717 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
How to batch convert sentence lengths to masks in PyTorch? | Problem:
import numpy as np
import pandas as pd
import torch
lens = load_data()
max_len = max(lens)
mask = torch.arange(max_len).expand(len(lens), max_len) > (max_len - lens.unsqueeze(1) - 1)
mask = mask.type(torch.LongTensor) |
5,718 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ETL with PySpark SQL
Step1: Importing and creating SparkSession
Step2: Setting filesystem and files
Load all CSV's files from HiggsTwitter dataset (http
Step3: Convert CSV's dataframes to... | Python Code:
import os
import sys
os.environ["SPARK_HOME"] = "/Users/projects/.pyenv/versions/3.7.10/envs/tatapower/lib/python3.7/site-packages/pyspark"
# os.environ["HADOOP_HOME"] = ""
# os.environ["PYSPARK_PYTHON"] = "/opt/cloudera/parcels/Anaconda/bin/python"
# os.environ["JAVA_HOME"] = "/usr/java/jdk1.8.0_161/jre"
... |
5,719 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Setup command line client
The following is code to get the client and set it up.
Step1: Describes the tests needed to validate the PutFile functionality.
The commands presented are just exa... | Python Code:
%env CLIENT bitrepository-client-1.9-RC1
!wget -Nq "https://sbforge.org/download/attachments/25395346/${CLIENT}.zip"
!unzip -quo ${CLIENT}.zip
%alias bitmag ${CLIENT}/bin/bitmag.sh %l
#Some imports we will need later
import random
import string
Explanation: Setup command line client
The following is code t... |
5,720 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Accompanying code examples of the book "Introduction to Artificial Neural Networks and Deep Learning
Step1: Scientific Computing in NumPy
This appendix offers a quick tour of the NumPy libr... | Python Code:
%load_ext watermark
%watermark -a 'Sebastian Raschka' -p numpy
Explanation: Accompanying code examples of the book "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python" by Sebastian Raschka. All code examples are released under the MIT license. If you... |
5,721 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Principal Component Analysis in Shogun
By Abhijeet Kislay (GitHub ID
Step1: Some Formal Background (Skip if you just want code examples)
PCA is a useful statistical technique that has found... | Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
# import all shogun classes
from shogun import *
import shogun as sg
Explanation: Principal Component Analysis in Shogun
By Abhijeet Kislay (GitHub ID: <a href='https://github.com/kislayabhi'>kislayabhi... |
5,722 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Subprocess WindowsError 5
场景是这样的,有一个app目录,里面有一个主程序main.py, 主程序会调用app目录外的updater.py对app目录进行升级
Step1: updater.py代码
启动后会对app目录重命名为app_old
Step2: build.py 代码
将main.py打包成exe并复制到main.py相同的目录
将u... | Python Code:
# encoding: utf-8
import logging
import os
import subprocess
import sys
CUR_DIR = os.path.dirname(os.path.abspath(sys.argv[0]))
logging.basicConfig(filename=os.path.join(CUR_DIR, "app.log"),
filemode="w",level=logging.INFO,
format='%(asctime)s [%(levelname)s]- %(mes... |
5,723 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Markov Chains
author
Step1: Markov chains have log probability, fit, summarize, and from summaries methods implemented. They do not have classification capabilities by themselves, but when ... | Python Code:
%matplotlib inline
import time
import pandas
import random
import numpy
import matplotlib.pyplot as plt
import seaborn; seaborn.set_style('whitegrid')
import itertools
from pomegranate import *
random.seed(0)
numpy.random.seed(0)
numpy.set_printoptions(suppress=True)
%load_ext watermark
%watermark -m -n -p... |
5,724 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TODO
Step1: Create a master bias frame
Step2: Create the master flat frame
Step3: Process object frames
Bias, flat corrections
Step4: Now that those intermediate frames are written, we n... | Python Code:
# Standard library
from os.path import join
import sys
if '/Users/adrian/projects/longslit/' not in sys.path:
sys.path.append('/Users/adrian/projects/longslit/')
# Third-party
from astropy.constants import c
import numpy as np
import matplotlib.pyplot as plt
import astropy.units as u
from astropy.io im... |
5,725 | 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', 'uhh', 'sandbox-3', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: UHH
Source ID: SANDBOX-3
Topic: Seaice
Sub-Topics: Dynamics, Thermodynamics,... |
5,726 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parallelization
Another nice thing about Python is, how easily you can parallelize your code. Here comes one example for multiprocessing.
map
An often used function in Python is map. It mapp... | Python Code:
def f(x):
return x**2
l = range(8)
s = map(f, l)
print 'input: ', l
print 'output:', s
Explanation: Parallelization
Another nice thing about Python is, how easily you can parallelize your code. Here comes one example for multiprocessing.
map
An often used function in Python is map. It mapps a given fun... |
5,727 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
Iterative vs fragment-based mapping
Advantages of iterative mapping
Advantages of fragment-based mapping
Mapping
Iterative mapping
Fragment-based mapping
Iterative vs fragm... | Python Code:
from pytadbit.mapping.full_mapper import full_mapping
Explanation: Table of Contents
Iterative vs fragment-based mapping
Advantages of iterative mapping
Advantages of fragment-based mapping
Mapping
Iterative mapping
Fragment-based mapping
Iterative vs fragment-based mapping
Iterative mapping first proposed... |
5,728 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a name="top"></a>
<div style="width
Step1: <a href="#top">Top</a>
<hr style="height
Step2: We can also find the list of datasets within a time range
Step3: Exercise
Starting from http
St... | Python Code:
from datetime import datetime, timedelta
from siphon.catalog import TDSCatalog
date = datetime.utcnow() - timedelta(days=1)
cat = TDSCatalog('http://thredds.ucar.edu/thredds/catalog/nexrad/level3/'
f'N0Q/LRX/{date:%Y%m%d}/catalog.xml')
Explanation: <a name="top"></a>
<div style="width:1000... |
5,729 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Monte Carlo integration
Monte Carlo is the simplest of all collocation methods.
It consist of the following steps
Step1: Then we generate samples from the three schemes
Step2: From the thr... | Python Code:
from problem_formulation import joint
joint
Explanation: Monte Carlo integration
Monte Carlo is the simplest of all collocation methods.
It consist of the following steps:
Generate (pseudo-)random samples $Q_1, ..., Q_N$.
Evaluate model solver $U_1=u(Q_1), ..., U_N=u(Q_N)$ for each sample.
Use empirical me... |
5,730 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What questions would you have about this data?
Step1: How would you encode categorical data such a carrier, day of week and origin airport as numerical features?
Step2: Features
Step3: Un... | Python Code:
df.shape
len(set(df.Origin))
df.FlightDate.min()
df.FlightDate.max()
df.DepTime.count()
df.DepTime.dropna().describe()
needed_columns = ['Year',
'Quarter',
'Month',
'DayofMonth',
'DayOfWeek',
'FlightDate',
'UniqueCarrier',
'Origin',
'OriginCityName',
'Dest',
'DestCityName',
'CRSDepTime',
'DepTi... |
5,731 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Demonstrate linear inverse model for the heat budget
Horizontal heat transports are non-linear terms if one assume that both temperatures and velocities have to be optimized. In order to kee... | Python Code:
import numpy as np
Explanation: Demonstrate linear inverse model for the heat budget
Horizontal heat transports are non-linear terms if one assume that both temperatures and velocities have to be optimized. In order to keep the model as simple as possible, we hypothesized that only velocities require optim... |
5,732 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploring QVEC
I want to spend some time now looking closer at QVEC's output, namely the correlations and the alignment matrix. The second main point of the original paper is that the alignm... | Python Code:
%matplotlib inline
import os
import csv
from itertools import product
import pandas as pd
import numpy as np
from scipy import stats
import statsmodels.api as sm
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
data_path = '../../data'
tmp_path = '../../tmp'
Explanation: Exploring QVEC
I wan... |
5,733 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regressão Linear
Este notebook mostra uma implementação básica de Regressão Linear e o uso da biblioteca MLlib do PySpark para a tarefa de regressão na base de dados Million Song Dataset do ... | Python Code:
sc = SparkContext.getOrCreate()
# carregar base de dados
from test_helper import Test
import os.path
baseDir = os.path.join('Data')
inputPath = os.path.join('millionsong.txt')
fileName = os.path.join(baseDir, inputPath)
numPartitions = 2
rawData = sc.textFile(fileName, numPartitions)
# EXERCICIO
numPoints ... |
5,734 | 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 | 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... |
5,735 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generate Training sets
Based on "Reproducible Experiments" notebook
Step1: Initiate experiment with this input file
Step2: Before we start to draw random realisations of the model, we shou... | Python Code:
%matplotlib inline
# here the usual imports. If any of the imports fails,
# make sure that pynoddy is installed
# properly, ideally with 'python setup.py develop'
# or 'python setup.py install'
import sys, os
import matplotlib.pyplot as plt
import numpy as np
# adjust some settings for matplotlib
from ma... |
5,736 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
9. Morphology — Lab exercises
XFST / foma
XFST provides two formalisms for creating FSA / FST for morphology and related fields
Step1: 2. subprocess
The subprocess module provides full acce... | Python Code:
import os
# Note that the actual output of `ls` is not printed!
print('Exit code:', os.system('ls -a'))
files = os.listdir('.')
print('Should have printed:\n\n{}'.format('\n'.join(files if len(files) <= 3 else files[:3] + ['...'])))
Explanation: 9. Morphology — Lab exercises
XFST / foma
XFST provides two f... |
5,737 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Handwritten Number Recognition with TFLearn and MNIST
In this notebook, we'll be building a neural network that recognizes handwritten numbers 0-9.
This kind of neural network is used in a ... | Python Code:
# Import Numpy, TensorFlow, TFLearn, and MNIST data
import numpy as np
import tensorflow as tf
import tflearn
import tflearn.datasets.mnist as mnist
Explanation: Handwritten Number Recognition with TFLearn and MNIST
In this notebook, we'll be building a neural network that recognizes handwritten numbers 0-... |
5,738 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Project 22
Step1: Importing of the dataset
Method definition for reading one of the available datasets
Step2: Checking for missing data
In the following lines, we check for missing values ... | Python Code:
# General Imports for more than one file
import pandas as pd
import numpy as np
# For reading the CSV
from pandas import read_csv
# Imports for the classification
from sklearn.metrics import confusion_matrix
from sklearn.metrics import f1_score
from sklearn.model_selection import cross_validate
from sklea... |
5,739 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Milestone 2 - this version has all the input completed, individually and each tested.
2-Dimensional Frame Analysis - Version 04
This program performs an elastic analysis of 2-dimensional str... | Python Code:
from __future__ import print_function
import salib as sl
sl.import_notebooks()
from Tables import Table
from Nodes import Node
from Members import Member
from LoadSets import LoadSet, LoadCombination
from NodeLoads import makeNodeLoad
from MemberLoads import makeMemberLoad
from collections import OrderedDi... |
5,740 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Video Codec Unit (VCU) Demo Example
Step1: Run the Demo
Step2: Video
Step3: Audio
Step4: Advanced options | Python Code:
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>
<form action="javascript:code_toggle()"><input type="submit" value... |
5,741 | 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... |
5,742 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Let's see what the column names that end in 'ID' are. Those are probably primary keys and foreign keys.
Step1: First, let's set the index to what I think is the primary key | Python Code:
for col in probe_spec.columns:
if col.endswith('ID'):
print col
Explanation: Let's see what the column names that end in 'ID' are. Those are probably primary keys and foreign keys.
End of explanation
probe_spec.set_index('DesignID',inplace=True)
probe_spec.head()
design_type = pd.read_csv('NiPO... |
5,743 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Short intro to the SCT library of AutoGraph
Work in progress, use with care and expect changes.
The pyct module packages the source code transformation APIs used by AutoGraph.
This tutorial ... | Python Code:
!pip install tf-nightly
Explanation: Short intro to the SCT library of AutoGraph
Work in progress, use with care and expect changes.
The pyct module packages the source code transformation APIs used by AutoGraph.
This tutorial is just a preview - there is no PIP package yet, and the API has not been finali... |
5,744 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numerical differential equations
In the simplest methods for solving differential equations numerically, one goes back to the definition of the differential operator
Step1: Now let us see i... | Python Code:
dx = 0.3
x = np.arange(0, 10, dx) # returns [0, dx, 2dx, 3dx, 4dx, 5dx, ...]
print(x)
f1 = np.sin(x)
f2 = x**2/100
f3 = np.log(1+x)-1
fs = [f1, f2, f3]
for i in range(3): plt.plot(x, fs[i])
df1 = np.cos(x)
df2 = x/50
df3 = 1/(1+x)
dfs = [df1, df2, df3]
Explanation: Numerical differential equations
In the s... |
5,745 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dynamic Pricing Game
Notebook for testing your algorithms
You can use this notebook to run your buyer/seller algorithms and compare them to the naive ones provided.
In the below code, make a... | Python Code:
import sys
import os
import matplotlib.pyplot as plt
import numpy.random as rn
import numpy as np
%matplotlib inline
# TODO: write the path to the root directory of the simulation game code below.
# It should have a README.md file under it and 'simulation_game', 'simulation_algos', 'test directories' unde... |
5,746 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Built-in linear stability analysis
Step1: To perform linear stability analysis, we simply call pyqg's built-in method stability_analysis
Step2: The eigenvalues are stored in omg, and th... | Python Code:
import numpy as np
from numpy import pi
import matplotlib.pyplot as plt
%matplotlib inline
import pyqg
m = pyqg.LayeredModel(nx=256, nz = 2, U = [.01, -.01], V = [0., 0.], H = [1., 1.],
L=2*pi,beta=1.5, rd=1./20., rek=0.05, f=1.,delta=1.)
Explanation: Built-in linear stability... |
5,747 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Hipster Effect
Step2: This gives us a nice way to move from our preference $x_i$ to a probability of switching styles. Here $\beta$ is inversely related to noise. For large $\beta$, the... | Python Code:
import numpy as np
import holoviews as hv
hv.notebook_extension(bokeh=True, width=90)
%%output backend='matplotlib'
%%opts NdOverlay [aspect=1.5 figure_size=200 legend_position='top_left']
x = np.linspace(-1, 1, 1000)
curves = hv.NdOverlay(key_dimensions=['$\\beta$'])
for beta in [0.1, 0.5, 1, 5]:
curv... |
5,748 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
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', 'inm', 'inm-cm5-0', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: INM
Source ID: INM-CM5-0
Topic: Aerosol
Sub-Topics: Transport, Emissions, ... |
5,749 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An Introduction to Bayesian Statistical Analysis
Though many of you will have taken a statistics course or two during your undergraduate (or graduate education, most of those who have will l... | Python Code:
from scipy.stats import binom
# Binomial probability mass function
yvals = range(10+1)
plt.plot(yvals, binom.pmf(yvals, 10, 0.5), 'ro')
# Binomial likelhood function
pvals = np.linspace(0, 1)
y = 4
plt.plot(pvals, binom.pmf(y, 10, pvals));
Explanation: An Introduction to Bayesian Statistical Analysis
Thoug... |
5,750 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2016 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtai... | Python Code:
%%javascript
// From https://github.com/kmahelona/ipython_notebook_goodies
$.getScript('https://kmahelona.github.io/ipython_notebook_goodies/ipython_notebook_toc.js')
Explanation: Copyright 2016 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use... |
5,751 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Receptive Field Estimation and Prediction
This example reproduces figures from Lalor et al's mTRF toolbox in
matlab [1]_. We will show how the
Step1: Load the data from the publication
Fir... | Python Code:
# Authors: Chris Holdgraf <choldgraf@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
# Nicolas Barascud <nicolas.barascud@ens.fr>
#
# License: BSD (3-clause)
# sphinx_gallery_thumbnail_number = 3
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
from os.pa... |
5,752 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 2
Due 11
Step1: The code below produces the data frames used in the examples
Step2: Pandas and Wrangling
For the examples that follow, we will be using a toy data set containing inform... | Python Code:
import pandas as pd
import numpy as np
# These lines load the tests.
!pip install -U okpy
from client.api.notebook import Notebook
ok = Notebook('lab02.ok')
Explanation: Lab 2
Due 11:59pm 01/27/2017 (Completion-based)
In this lab you will see some examples of some commonly used data wrangling tools in Pyth... |
5,753 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Survival Analysis with Plotly
Step1: Introduction
Survival analysis is a set of statistical methods for analyzing the occurrence of event data over time. It is also used to determine the r... | Python Code:
# You can also install packages from within IPython!
# Install Python Packages
!pip install lifelines
!pip install rpy2
!pip install plotly
!pip install pandas
# Install R libraries
%load_ext rpy2.ipython
%R install.packages("devtools")
%R install_github("ropensci/plotly")
%R install.packages("IOsurv")
%R ... |
5,754 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Trabajando de forma conjunta con Python y con R.
Hoy vamos a ver como podemos juntar lo bueno de R, algunas de sus librerías, con Python usando rpy2.
Pero, lo primero de todo, ¿qué es rpy2?... | Python Code:
# Importamos pandas y numpy para manejar los datos que pasaremos a R
import pandas as pd
import numpy as np
# Usamos rpy2 para interactuar con R
import rpy2.robjects as ro
# Activamos la conversión automática de tipos de rpy2
import rpy2.robjects.numpy2ri
rpy2.robjects.numpy2ri.activate()
import matplotlib... |
5,755 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 4
The greatest theorem never told
This chapter focuses on an idea that is always bouncing around our minds, but is rarely made explicit outside books devoted to statistics. In fact, ... | Python Code:
%matplotlib inline
import numpy as np
from IPython.core.pylabtools import figsize
import matplotlib.pyplot as plt
figsize(12.5, 5)
import pymc as pm
sample_size = 100000
expected_value = lambda_ = 4.5
poi = pm.rpoisson
N_samples = range(1, sample_size, 100)
for k in range(3):
samples = poi(lambda_, siz... |
5,756 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Read in the data..
Step1: The columns are the instances and rows the features so we need to transpose the dataset.
Step2: Read in the labels...
Step3: We are using the OAC labeling...
Ste... | Python Code:
data = pd.read_csv('/Users/Frankie/Documents/Dissertation/Data/pancreatic/24hProbeExpressionValues.csv')
data[:5]
Explanation: Read in the data..
End of explanation
data = data.T
Explanation: The columns are the instances and rows the features so we need to transpose the dataset.
End of explanation
label =... |
5,757 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to NumPy
Topics
Basic Synatx
creating vectors matrices
special
Step1: This code sets up Ipython Notebook environments (lines beginning with %), and loads several libraries and ... | Python Code:
%matplotlib inline
import math
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sbn
##from scipy import *
Explanation: Introduction to NumPy
Topics
Basic Synatx
creating vectors matrices
special: ones, zeros, identity eye
add, product, inverse
Mechanics: indexing, slicing, concatenating... |
5,758 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multiclass Classification
Last modification
Step1: In this example, the wine dataset contains 178 samples, 13 features, and 3 clases. Details of the dataset can be find here.
Step2: This s... | Python Code:
# Load the iris dataset and randomly permute it
import numpy as np
#import logging
#logger = logging.getLogger()
#logger.setLevel(logging.DEBUG)
#logging.debug("test")
from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
from sklearn.svm import SVC
from sklearn.model_s... |
5,759 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Alternative
Step2: Checking our results (inference) | Python Code:
!pip install -q tf-nightly-gpu-2.0-preview
import tensorflow as tf
print(tf.__version__)
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
x_train.shape
import numpy as np
# add empty color dimension
x_train = np.expand_dims(x_train, -1)
x_test = np.expand_dims(x_test, -1)
... |
5,760 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Integration Exercise 2
Imports
Step1: Indefinite integrals
Here is a table of definite integrals. Many of these integrals has a number of parameters $a$, $b$, etc.
Find five of these integr... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy import integrate
Explanation: Integration Exercise 2
Imports
End of explanation
def integrand(x, a):
return 1.0/(x**2 + a**2)
def integral_approx(a):
# Use the args keyword argument to feed extra ... |
5,761 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lesson 8
v1.1, 2020.4 2020.5 edit by David Yi
本课内容要点
函数介绍和用法
思考一下：剪刀石头布
函数用法
函数是组织好的、可重复使用的、用来实现单一或相关联功能的代码段。函数能提高应用的模块性，和代码的重复利用率。
python 提供了许多内建函数，比如 print(), max()；
python 提供的大量内建函数，可以满足绝... | Python Code:
# 计算圆的面积
# 不用函数的话，每次需要写一些重复的代码
r1 = 4
r2 = 6
r3 = 5.61
s1 = 3.14 * r1 * r1
s2 = 3.14 * r2 * r2
s3 = 3.14 * r3 * r3
print(s1)
print(s2)
print(s3)
# 定义一个函数，用来计算圆面积
# 输入 半径，返回 圆面积
def func1(r):
s = 3.14 * r * r
return s
print(func1(4))
print(func1(6))
print(func1(5.61))
# 先来看看 python 内置的获取最大值的函数
print... |
5,762 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: A notebook to process experimental results of ex2_prob_params.py. p(reject) as problem parameters are varied.
Step2: $$p(x)=\mathcal{N}(0, I) \
q(x)=\mathcal{N}(0, I)$$
Step3: $$p(x... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
#%config InlineBackend.figure_format = 'svg'
#%config InlineBackend.figure_format = 'pdf'
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import kgof.data as data
import kgof.glo as glo
import kgof.goftest as gof
import kgof.kernel ... |
5,763 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing Keras and Scikit models deployed on Cloud AI Platform with the What-if Tool
In this notebook we'll use the UCI wine quality dataset to train both tf.keras and Scikit learn regressi... | Python Code:
import sys
python_version = sys.version_info[0]
# If you're running on Colab, you'll need to install the What-if Tool package and authenticate
def pip_install(module):
if python_version == '2':
!pip install {module} --quiet
else:
!pip3 install {module} --quiet
try:
import google... |
5,764 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Image Classification
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. You'll preprocess the images... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if present
floyd_cifa... |
5,765 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Logistic Regression
Step2: <hr />
Data setup for the 10 digit classes
The data is the same that was used in the last post but this time I will use all of the 0-9 images. There are 42... | Python Code:
import pandas as pd # data handeling
import numpy as np # numerical computing
from scipy.optimize import minimize # optimization code
import matplotlib.pyplot as plt # plotting
import seaborn as sns
%matplotlib inline
sns.set()
import itertools # combinatorics functions for multinomial code
#
# Mai... |
5,766 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
3/10/17
Trying to get a critical infinite serpent simulation, e.g. $k_{\infty}$ = 1
U235 = .418%
U238 = .8625%
k = 1.07238
msr2g_enrU
2/10/17
Serpent run yielded k_eff of 1.03
msr2g_part_U_s... | Python Code:
k_nom = 1.0545
k_f_1144 = 1.04149
fuel_reactivity = (k_f_1144 - k_nom) / k_nom / 400
print(fuel_reactivity)
Explanation: 3/10/17
Trying to get a critical infinite serpent simulation, e.g. $k_{\infty}$ = 1
U235 = .418%
U238 = .8625%
k = 1.07238
msr2g_enrU
2/10/17
Serpent run yielded k_eff of 1.03
msr2g_part... |
5,767 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
My note
Step1: Test OpenCV
Step2: Test TensorFlow
Step3: Test Moviepy
Step4: Troubleshooting ffmpeg
NOTE
Step6: Create a new video with moviepy by processing each frame to YUV color spa... | Python Code:
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
%matplotlib inline
img = mpimg.imread('test.jpg')
plt.imshow(img)
Explanation: My note:
1. Install Anaconda
2. Setup the carnd-term1 environment as instructions in Starter Kit.
3. Run the test.ipynb in the carnd-term1 ker... |
5,768 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Create Dummy Variables with Pandas
| Python Code::
import pandas as pd
X = pd.get_dummies(X, columns=['neighbourhood_group','room_type'], drop_first=True)
|
5,769 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="images/logo.jpg" style="display
Step1: <p style="text-align
Step2: <p style="text-align
Step3: <p style="text-align
Step4: <p style="text-align
Step5: <p style="text-align
Ste... | Python Code:
def silly_generator():
a = 1
yield a
b = a + 1
yield b
c = [1, 2, 3]
yield c
Explanation: <img src="images/logo.jpg" style="display: block; margin-left: auto; margin-right: auto;" alt="לוגו של מיזם לימוד הפייתון. נחש מצויר בצבעי צהוב וכחול, הנע בין האותיות של שם הקורס: לומדים פייתון... |
5,770 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2/22/17
Step1: So it looks like there's excellent agreement between the theoretical calculation of the material buckling and the value output by serpent, so it seems reasonable to guess tha... | Python Code:
bm2 = .00202183
height = 198.12
radius = var('radius')
solns = solve(bm2 == (pi/height)^2 + (2.405/radius)^2, radius, solution_dict=True)
[s[radius].n() for s in solns]
radius = solns[1][radius].n()
print(radius)
nu = 2.43654
sigma_f = 1.3769e-3
sigma_a = 2.21110e-3
diff = 5.31788e-1
bm2_calc = (nu * sigma... |
5,771 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook was prepared by Donne Martin. Source and license info is on GitHub.
Kaggle Machine Learning Competition
Step1: Explore the Data
Read the data
Step2: View the data types of ea... | Python Code:
import pandas as pd
import numpy as np
import pylab as plt
# Set the global default size of matplotlib figures
plt.rc('figure', figsize=(10, 5))
# Size of matplotlib figures that contain subplots
fizsize_with_subplots = (10, 10)
# Size of matplotlib histogram bins
bin_size = 10
Explanation: This notebook w... |
5,772 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PySAL Change Log Statistics
Step1: with open('../packages.yml') as package_file
Step2: Our last main release was 2019-01-30
Step3: get dates of tags
with open('subtags', 'r') as tag_name
... | Python Code:
from __future__ import print_function
import os
import json
import re
import sys
import pandas
import subprocess
from subprocess import check_output
#import yaml
from datetime import datetime, timedelta
from dateutil.parser import parse
import pytz
utc=pytz.UTC
from datetime import datetime, timedelta
from... |
5,773 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
WHFast tutorial
This tutorial is an introduction to the python interface of WHFast, a fast and unbiased symplectic Wisdom-Holman integrator. This integrator is well suited for integrations o... | Python Code:
import rebound
Explanation: WHFast tutorial
This tutorial is an introduction to the python interface of WHFast, a fast and unbiased symplectic Wisdom-Holman integrator. This integrator is well suited for integrations of planetary systems in which the planets stay roughly on their orbits. If close encounter... |
5,774 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Partial function application
2. Pattern matching
Ciastocna aplikacia - Partially applied functions
http
Step1: Iny priklad
Step2: Balicek functools ma na to funkciu, ktora definiciu tak... | Python Code:
def add(a, b):
return a + b
def make_adder(a) :
def adder(b) :
return add(a, b)
return adder
add_two = make_adder(20)
add_two(4)
Explanation: 1. Partial function application
2. Pattern matching
Ciastocna aplikacia - Partially applied functions
http://blog.dhananjaynene.com/tags/function... |
5,775 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Big 3 statistics
uslisted.txt
Step1: Show types of companies
Step2: Step 1. Include only publicly listed companies from the US
Keep only larger shareholder percentage between direct and to... | Python Code:
#Install libraries needed
!pip install --upgrade pip
!pip install pandas
!pip install numpy
#Import libraries needed
import pandas as pd
import numpy as np
from collections import Counter
Explanation: Big 3 statistics
uslisted.txt: Downloaded from Orbis, file containing the following fields:
'Company name'... |
5,776 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Enron Scandal
Step1: 1. Data Processing and Exploratory Data Analysis
Load the Data
Step2: Explore the Data
Step3: Imbalanced target
Step4: Transform the data
Step5: Missing features
St... | Python Code:
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import helper
import keras
helper.info_gpu()
#sns.set_palette("Reds")
helper.reproducible(seed=0) # setup reproducible results from run to run using Keras
%matplotlib inline
%load_ext autoreload
%autorel... |
5,777 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 DeepMind Technologies Limited
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... | Python Code:
import numpy as np
import scipy.stats
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
sns.set_context('paper', font_scale=2.0, rc={'lines.linewidth': 2.0})
sns.set_style('whitegrid')
# We use INTEGRATION_LIMIT instead of infinity in integration limits
INTEGRATION_LIMIT = 10.
# Thres... |
5,778 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Anomaly Detection on MNIST
This notebook shows how a Deep Learning Auto-Encoder model can be used to find outliers in a dataset.
Consider the following three-layer neural network with one h... | Python Code:
import numpy as np
import theano
import lasagne
import matplotlib.pyplot as plt
%matplotlib inline
import gzip
import pickle
# Seed for reproducibility
np.random.seed(42)
# Download the MNIST digits dataset (actually, these are already downloaded locally)
# !wget -N --directory-prefix=./data/MNIST/ http://... |
5,779 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load airports of each country
Step1: record schedules for 2 weeks, then augment count with weekly flight numbers.
seasonal and seasonal charter will count as once per week for 3 months, so ... | Python Code:
L=json.loads(file('../json/L.json','r').read())
M=json.loads(file('../json/M.json','r').read())
N=json.loads(file('../json/N.json','r').read())
import requests
AP={}
for c in M:
if c not in AP:AP[c]={}
for i in range(len(L[c])):
AP[c][N[c][i]]=L[c][i]
sch={}
Explanation: Load airports of ea... |
5,780 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Win/Loss Betting Model
Step2: Pymc Model
Determining Binary Win Loss
Step3: Plot the last period rating for some teams
Step4: Plot some over time ratings | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
data = pd.read_csv('data.csv', index_col=0).reset_index(drop=True)
teams = np.sort(np.unique(np.concatenate([data['Team 1 ID'], data['Team 2 ID']])))
periods = data.Date.unique()
tmap = {v:k for ... |
5,781 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implementing Maps as Arrays
If the keys are natural numbers less than a given natural number n that is not
too big, a map can be implemented via an array.
The class ArrayMap shows how this ... | Python Code:
class ArrayMap:
def __init__(self, n):
self.mArray = [None] * n
def find(self, k):
return self.mArray[k]
def insert(self, k, v):
self.mArray[k] = v
def delete(self, k):
self.mArray[k] = None
def __repr__(self):
result = ... |
5,782 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assignment 4 Solution
Step1: 4. The Database object you just created has a phases attribute that is a dictionary. Print this dictionary. The keys are the phase names and the values are Phas... | Python Code:
from pycalphad import Database
solder_dbf = Database('Ag-Bi-Cu-Pb-Sb-Sn-nist-solders.tdb')
Explanation: Assignment 4 Solution: Introduction to pycalphad
User questions and feedback can be directed to the pycalphad Google Group. Bugs can be reported to the GitHub repo.
1. Ensure pycalphad is installed. For ... |
5,783 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GeoViews is a Python library that makes it easy to explore and visualize geographical, meteorological, and oceanographic datasets, such as those used in weather, climate, and remote sensing ... | Python Code:
import geoviews as gv
import geoviews.feature as gf
import xarray as xr
from cartopy import crs
gv.extension('bokeh', 'matplotlib')
(gf.ocean + gf.land + gf.ocean * gf.land * gf.coastline * gf.borders).opts(
'Feature', projection=crs.Geostationary(), global_extent=True, height=325).cols(3)
Explanation:... |
5,784 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Fully-Connected Neural Nets
In the previous homework you implemented a fully-connected two-layer neural network on CIFAR-10. The implementation was simple but not very modular since t... | Python Code:
# As usual, a bit of setup
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.fc_net import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array
from cs231n.solver import Solver
%matplot... |
5,785 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introducing Pandas
From the docs
Step1: Introducing DataFrame
From the docs
Step2: The Jupyter Notebook automatically renders DataFrame as HTML!
Note the first column; this is an Index, an... | Python Code:
import pandas as pd
pd.options.display.max_rows = 20
%matplotlib inline
Explanation: Introducing Pandas
From the docs:
A Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive.
We also use matplotlib:
A Py... |
5,786 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Learning
Assignment 4
Previously in 2_fullyconnected.ipynb and 3_regularization.ipynb, we trained fully connected networks to classify notMNIST characters.
The goal of this assignment i... | Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
from __future__ import print_function
import numpy as np
import tensorflow as tf
from six.moves import cPickle as pickle
from six.moves import range
pickle_file = '../notMNIST.pickle'
with open(pick... |
5,787 | 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 classification model for online prediction
<table... |
5,788 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deploying NVIDIA Triton Inference Server in AI Platform Prediction Custom Container (REST API)
In this notebook, we will walk through the process of deploying NVIDIA's Triton Inference Serve... | Python Code:
PROJECT_ID='[Enter project name - REQUIRED]'
REPOSITORY='caipcustom'
REGION='us-central1'
TRITON_VERSION='20.06'
import os
import random
import requests
import json
MODEL_BUCKET='gs://{}-{}'.format(PROJECT_ID,random.randint(10000,99999))
ENDPOINT='https://{}-ml.googleapis.com/v1'.format(REGION)
TRITON_IMAG... |
5,789 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of using two distance + thresholds in one ABC sampling run
Step1: Distance measure compares mean + variance | Python Code:
samples_size = 1000
mean = 2
sigma = 1
data = np.random.normal(mean, sigma, samples_size)
f,ax = plt.subplots()
sns.distplot(data)
def create_new_sample(theta):
mu,sigma = theta
if sigma<=0:
sigma=10
return np.random.normal(mu, sigma, samples_size)
Explanation: Example of using two dist... |
5,790 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 5.18
Plots L vs T from a source file and fits polynomials of varying degrees to it
Step1: Below are the polynomials being fit to the data
Step2: Exercise 5.22
Computes the midpoin... | Python Code:
p1.part_a()
Explanation: Exercise 5.18
Plots L vs T from a source file and fits polynomials of varying degrees to it
End of explanation
p1.part_b()
Explanation: Below are the polynomials being fit to the data
End of explanation
p2.midpointint(p2.function, 1, 3, 50)[0]
p2.sum_vectorized(p2.function, 1, 3, 5... |
5,791 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Hub Authors.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: Object Detection
<table class="tfo-notebook-buttons" align="left">
<td>
... | Python Code:
# Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... |
5,792 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: <a href="http
Step3: Doc tests
The following docstring section 'Examples' should help the user understand what is the component's purpose and how it works. It is an example (or examp... | Python Code:
import numpy as np
from landlab import Component, FieldError
class KinwaveOverlandFlowModel(Component):
Calculate water flow over topography.
Landlab component that implements a two-dimensional
kinematic wave model.
You can put other information here... Anything you
thi... |
5,793 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BBH class
$ecc==0$
Step1: 5 realization results
(93328, 13)
(17287278, 13)
(17380606, 14)
Step2: Mergers
Event Rate
Step3: $\frac{1}{4\pi/3(30Mpc)^313.5Gyr}=\frac{1}{4\pi/32700013.5 {Gpc}... | Python Code:
# ## load example data for testing
# BBHex=pd.read_csv('../data/RES/1024/BBHex.dat',delim_whitespace=True,header=None,
# names=['Galaxy','RA','Dec','Dist','VMag','Model','Age','T_eject','M1','M2','Seperation','Ecc','Period'])
# BBHex.sample(2)
# ## label example data for analysis
# merge_li... |
5,794 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step2: Parameters
Step3: Colab-only auth for this notebook and the TPU
Step4: TPU detection
Step5: tf.data.Dataset
Step6: Let's have a look at the data
Step7: Estimator ... | Python Code:
import os, re, math, json, shutil, pprint, datetime
import PIL.Image, PIL.ImageFont, PIL.ImageDraw # "pip3 install Pillow" or "pip install Pillow" if needed
import numpy as np
import tensorflow as tf
from matplotlib import pyplot as plt
from tensorflow.python.platform import tf_logging
print("Tensorflow v... |
5,795 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 09a
Step1: Next, let's load the data. The iris data set is included in scikit-learn's datasets submodule, so we can just load it directly like this
Step2: Exploratory data analysis
Let... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from sklearn import cluster
from sklearn import datasets
Explanation: Lab 09a: K-means clustering
Introduction
This lab focuses on $K$-means clustering using the Iris flower data set. At the end of the lab, you s... |
5,796 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
$\hat R$ locker
This notebook serves as a sandbox to understand the potential of the nested-$\hat R$ diagnostic. The underlying idea is to gather short chains into a long "super chains" and ... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License"); { display-mode: "form" }
# 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... |
5,797 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Identifying safe loans with decision trees
The LendingClub is a peer-to-peer leading company that directly connects borrowers and potential lenders/investors. In this notebook, you will buil... | Python Code:
import graphlab
graphlab.canvas.set_target('ipynb')
Explanation: Identifying safe loans with decision trees
The LendingClub is a peer-to-peer leading company that directly connects borrowers and potential lenders/investors. In this notebook, you will build a classification model to predict whether or not a... |
5,798 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Markov switching autoregression models
This notebook provides an example of the use of Markov switching models in Statsmodels to replicate a number of results presented in Kim and Nelson (19... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
import requests
from io import BytesIO
# NBER recessions
from pandas_datareader.data import DataReader
from datetime import datetime
usrec = DataReader('USREC', 'fred', start=datetime(1947... |
5,799 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Problem Set 01
1. COUNTING VOWELS
Assume s is a string of lower case characters.
Write a program that counts up the number of vowels contained in the string s. Valid vowels are
Step1: 2. CO... | Python Code:
s= 'wordsmith'
vowels = {'a','e','i','o','u'}
count = 0
for char in s:
if char in vowels:
count+=1
print "Number of vowels: " + str(count)
Explanation: Problem Set 01
1. COUNTING VOWELS
Assume s is a string of lower case characters.
Write a program that counts up the number of vowels contained ... |
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