Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
13,600 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modeling dynamics of FS Peptide
This example shows a typical, basic usage of the MSMBuilder command line to model dynamics of a protein system.
Step1: Get example data
Step2: Featurization... | Python Code:
# Work in a temporary directory
import tempfile
import os
os.chdir(tempfile.mkdtemp())
# Since this is running from an IPython notebook,
# we prefix all our commands with "!"
# When running on the command line, omit the leading "!"
! msmb -h
Explanation: Modeling dynamics of FS Peptide
This example shows a... |
13,601 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classification with Neural Decision Forests
Author
Step1: Prepare the data
Step2: Remove the first record (because it is not a valid data example) and a trailing
'dot' in the class labels.... | Python Code:
import tensorflow as tf
import numpy as np
import pandas as pd
from tensorflow import keras
from tensorflow.keras import layers
import math
Explanation: Classification with Neural Decision Forests
Author: Khalid Salama<br>
Date created: 2021/01/15<br>
Last modified: 2021/01/15<br>
Description: How to train... |
13,602 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Линейная регрессия и стохастический градиентный спуск
Задание основано на материалах лекций по линейной регрессии и градиентному спуску. Вы будете прогнозировать выручку компании в зависимос... | Python Code:
def write_answer_to_file(answer, filename):
with open(filename, 'w') as f_out:
f_out.write(str(round(answer, 3)))
Explanation: Линейная регрессия и стохастический градиентный спуск
Задание основано на материалах лекций по линейной регрессии и градиентному спуску. Вы будете прогнозировать выручк... |
13,603 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Take the set of pings, make sure we have actual clientIds and remove duplicate pings. We collect each unique ping.
Step1: Transform and sanitize the pings into arrays.
Step2: Create a set ... | Python Code:
def dedupe_pings(rdd):
return rdd.filter(lambda p: p["meta/clientId"] is not None)\
.map(lambda p: (p["meta/documentId"], p))\
.reduceByKey(lambda x, y: x)\
.map(lambda x: x[1])
Explanation: Take the set of pings, make sure we have actual clientIds and remove d... |
13,604 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ApJdataFrames Kraus2017
Title
Step1: Get all tables right away.
There are 7 tables.
Step2: Convert the astropy tables to pandas dataframes. | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
pd.options.display.max_columns = 150
#%config InlineBackend.figure_format = 'retina'
import astropy
from astropy.table import Table
from astropy.io import ascii
from IPython.core.display import display, HTML
displa... |
13,605 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
logictools WaveDrom Tutorial
WaveDrom is a tool for rendering digital timing waveforms. The waveforms are defined in a simple textual format.
This notebook will show how to render digital w... | Python Code:
from pynq.lib.logictools.waveform import draw_wavedrom
Explanation: logictools WaveDrom Tutorial
WaveDrom is a tool for rendering digital timing waveforms. The waveforms are defined in a simple textual format.
This notebook will show how to render digital waveforms using the pynq library.
The logictools o... |
13,606 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load in Catalogue - Limit to ISC, GCMT/HRVD, EHB, NEIC, BJI
Step1: Define Rule Sets
The catalogue covers the years 2005/06. To illustrate how to apply time variable hierarchies we consider ... | Python Code:
parser = ISFReader("inputs/isc_test_catalogue_isf.txt",
selected_origin_agencies=["ISC", "GCMT", "HRVD", "NEIC", "EHB", "BJI"],
selected_magnitude_agencies=["ISC", "GCMT", "HRVD", "NEIC", "BJI"])
catalogue = parser.read_file("ISC_DB1", "ISC Global M >= 5")
print("Catal... |
13,607 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example 7
Step1: Setup an identical instance of NPTFit to Example 6
Firstly we initialize an instance of nptfit identical to that used in the previous example.
Step2: Evaluate the Likeliho... | Python Code:
# Import relevant modules
%matplotlib inline
%load_ext autoreload
%autoreload 2
import numpy as np
import healpy as hp
import matplotlib.pyplot as plt
from NPTFit import nptfit # module for performing scan
from NPTFit import create_mask as cm # module for creating the mask
from NPTFit import psf_correction... |
13,608 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PageRank
Ways to think about SVD
Data compression
SVD trades a large number of features for a smaller set of better features
All matrices are diagonal (if you use change of bases on the doma... | Python Code:
#@title Power iteration
import numpy as np
def power_iteration(A, num_simulations):
# Ideally choose a random vector
# To decrease the chance that our vector
# Is orthogonal to the eigenvector
b_k = np.random.rand(A.shape[0])
for _ in range(num_simulations):
# calculate the matr... |
13,609 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ProteinB
Step1: Auxiliary functions
Step2: Create a feature reader
We create a feature reader to obtain minimal distances between all residues which are not close neighbours. Feel free to ... | Python Code:
import sys
import math
sys.path.append("/Users/suarezalvareze2/Documents/workspace/NMpathAnalysis/nmpath")
%matplotlib inline
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pyemma
import mdtraj as md
from glob import glob
# My modules
from auxfunctions import *
from mfpt... |
13,610 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src='https
Step1: 如何使用和开发微信聊天机器人的系列教程
A workshop to develop & use an intelligent and interactive chat-bot in WeChat
WeChat is a popular social media app, which has more than 800 millio... | Python Code:
import IPython.display
IPython.display.YouTubeVideo('YSL--3j12VA')
Explanation: <img src='https://www.iss.nus.edu.sg/Sitefinity/WebsiteTemplates/ISS/App_Themes/ISS/Images/branding-iss.png' width=15% style="float: right;">
<img src='https://www.iss.nus.edu.sg/Sitefinity/WebsiteTemplates/ISS/App_Themes/ISS/I... |
13,611 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Frame
The client bank XYZ is running a direct marketing campaign. It wants to identify customers who would potentially be buying their new term deposit plan.
Acquire
Data is obtained from UC... | Python Code:
#Import the necessary libraries
import numpy as np
import pandas as pd
#Read the train and test data
train = pd.read_csv("../data/train.csv")
test = pd.read_csv("../data/test.csv")
Explanation: Frame
The client bank XYZ is running a direct marketing campaign. It wants to identify customers who would potent... |
13,612 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TV Script Generation
In this project, you'll generate your own Simpsons TV scripts using RNNs. You'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Network y... | Python Code:
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
Explanation: TV Script Generation
In this project, you'll generate your own Simpsons TV scripts using RNNs. You'll be using part... |
13,613 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preprocessing
Step1: Config
Automatically discover the paths to various data folders and compose the project structure.
Step2: Read data
Original question datasets.
Step3: Load tools
Step... | Python Code:
from pygoose import *
import nltk
Explanation: Preprocessing: Unique Question Corpus
Based on the training and test sets, extract a list of unique documents.
Imports
This utility package imports numpy, pandas, matplotlib and a helper kg module into the root namespace.
End of explanation
project = kg.Projec... |
13,614 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training Hybrid Recommendation Model with the MovieLens Dataset
Note
Step1: Import the dataset and trained model
In the previous notebook, you imported 20 million movie recommendations and ... | Python Code:
import os
import tensorflow as tf
PROJECT = "your-project-id-here" # REPLACE WITH YOUR PROJECT ID
# Do not change these
os.environ["PROJECT"] = PROJECT
os.environ["TFVERSION"] = '2.5'
Explanation: Training Hybrid Recommendation Model with the MovieLens Dataset
Note: It is recommended that you complete the ... |
13,615 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to pandas
by Maxwell Margenot
Part of the Quantopian Lecture Series
Step1: With pandas, it is easy to store, visualize, and perform calculations on your data. With only a few l... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Introduction to pandas
by Maxwell Margenot
Part of the Quantopian Lecture Series:
www.quantopian.com/lectures
github.com/quantopian/research_public
Notebook released under the Creative Commons Attribution 4.0 License.
panda... |
13,616 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The function $\texttt{toDot}(\texttt{Parent})$ takes a dictionary $\texttt{Parent}$.
For every node $x$, $\texttt{Parent}[x]$ is the parent of $x$. It draws this dictionary
as a family tr... | Python Code:
def toDot(Parent):
dot = gv.Digraph()
M = Parent.keys()
for x in M:
p = Parent[x]
if x == p:
dot.node(str(x), shape='doublecircle')
else:
dot.node(str(x), shape='circle')
dot.edge(str(x), str(p))
return dot
Explanation: T... |
13,617 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overview
Use linked DMA channels to perform "scan" across multiple ADC input channels.
See diagram below.
Channel configuration ##
DMA channel $i$ copies conesecutive SC1A configurations to ... | Python Code:
from arduino_rpc.protobuf import resolve_field_values
from teensy_minimal_rpc import SerialProxy
import teensy_minimal_rpc.DMA as DMA
import teensy_minimal_rpc.ADC as ADC
# Disconnect from existing proxy (if available)
try:
del proxy
except NameError:
pass
proxy = SerialProxy()
Explanation: Overvie... |
13,618 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook shows the how tallies can be combined (added, subtracted, multiplied, etc.) using the Python API in order to create derived tallies. Since no covariance information is obtained... | Python Code:
%load_ext autoreload
%autoreload 2
import glob
from IPython.display import Image
import numpy as np
import openmc
from openmc.statepoint import StatePoint
from openmc.summary import Summary
%matplotlib inline
Explanation: This notebook shows the how tallies can be combined (added, subtracted, multiplied, e... |
13,619 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FCN-8s Tutorial
Step1: This notebook walks you through how to work with this FCN-8s implementation. I will take the Cityscapes dataset as an example to train the model on in this notebook, ... | Python Code:
from fcn8s_tensorflow import FCN8s
from data_generator.batch_generator import BatchGenerator
from helpers.visualization_utils import print_segmentation_onto_image, create_video_from_images
from cityscapesscripts.helpers.labels import TRAINIDS_TO_COLORS_DICT, TRAINIDS_TO_RGBA_DICT
from math import ceil
impo... |
13,620 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> Reading NEXRAD Level II data from Google Cloud public datasets </h1>
This notebook demonstrates how to use PyART to visualize data from the Google Cloud public dataset.
Step1: <h3> Ins... | Python Code:
%bash
rm -rf data
mkdir data
cd data
RADAR=KIWA
YEAR=2013
MONTH=07
DAY=23
HOUR=23
gsutil cp gs://gcp-public-data-nexrad-l2/$YEAR/$MONTH/$DAY/$RADAR/*_$RADAR_${YEAR}${MONTH}${DAY}${HOUR}0000_${YEAR}${MONTH}${DAY}${HOUR}5959.tar temp.tar
tar xvf temp.tar
rm *.tar
ls
Explanation: <h1> Reading NEXRAD Level II ... |
13,621 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook is the reproduction of an exercise found at http
Step1: We'll read the data from ZoneA.dat.
Step2: We want the first, second and fourth columns of the data set, representing ... | Python Code:
import sys
sys.path.append('..')
sys.path.append('../geostatsmodels')
from geostatsmodels import utilities, variograms, model, kriging, geoplot
import matplotlib.pyplot as plt
import numpy as np
import pandas
Explanation: This notebook is the reproduction of an exercise found at http://people.ku.edu/~gbohl... |
13,622 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep learning for Natural Language Processing
Simple text representations, bag of words
Word embedding and... not just another word2vec this time
1-dimensional convolutions for text
Aggregat... | Python Code:
low_RAM_mode = True
very_low_RAM = False #If you have <3GB RAM, set BOTH to true
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Deep learning for Natural Language Processing
Simple text representations, bag of words
Word embedding and... not just ano... |
13,623 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Algebra Lineal con Python
Esta notebook fue creada originalmente como un blog post por Raúl E. López Briega en Mi blog sobre Python. El contenido esta bajo la licencia BSD.
<img alt="Algebra... | Python Code:
# Vector como lista de Python
v1 = [2, 4, 6]
v1
# Vectores con numpy
import numpy as np
v2 = np.ones(3) # vector de solo unos.
v2
v3 = np.array([1, 3, 5]) # pasando una lista a las arrays de numpy
v3
v4 = np.arange(1, 8) # utilizando la funcion arange de numpy
v4
Explanation: Algebra Lineal con Python
Esta... |
13,624 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DualMap plugin
This plugin is using the Leaflet plugin Sync by Jieter
Step1: The DualMap class accepts the same arguments as the normal Map class. Except for these
Step2: You can access th... | Python Code:
import folium
import folium.plugins
Explanation: DualMap plugin
This plugin is using the Leaflet plugin Sync by Jieter:
https://github.com/jieter/Leaflet.Sync
The goal is to have two maps side by side. When you pan or zoom on one map, the other will move as well.
End of explanation
m = folium.plugins.DualM... |
13,625 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import data from web scrawlers
Here we first build a web scrawler to scrap all the trafic information from the official twitter accounts of RATP, SNCF
Step1: First, have a look at the data
... | Python Code:
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
# ---- Summary of the twitter accounts -----#
# RER_A
# RERB
# RERC_SNCF --< Infotrafic
# RERD_SNCF --< Infotrafic
# RERE_SNCF --< Infotrafic
# Ligne12_RATP --< from 1 to 14 lines
line_list = ['RER_A', 'RER_B', 'RE... |
13,626 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Classification & How To "Frame Problems" for a Neural Network
by Andrew Trask
Twitter
Step1: Lesson
Step2: Project 1
Step3: Transforming Text into Numbers | Python Code:
def pretty_print_review_and_label(i):
print(labels[i] + "\t:\t" + reviews[i][:80] + "...")
g = open('reviews.txt','r') # What we know!
reviews = list(map(lambda x:x[:-1],g.readlines()))
g.close()
g = open('labels.txt','r') # What we WANT to know!
labels = list(map(lambda x:x[:-1].upper(),g.readlines())... |
13,627 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Note
Step1: First, we import the energy data from the sample CSV and transform it into records
Step2: The records we just created look like this
Step3: The energy trace data looks like th... | Python Code:
# library imports
from eemeter.structures import (
EnergyTrace,
EnergyTraceSet,
Intervention,
ZIPCodeSite,
Project
)
from eemeter.io.serializers import ArbitraryStartSerializer
from eemeter.ee.meter import EnergyEfficiencyMeter
import pandas as pd
import pytz
Explanation: Note:
Most use... |
13,628 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building an ML App
Now that we have a machine learning model to predict the defaults, let us try to build a web application to lend loans.
It'll have two parts
Step1: Let us run it as a se... | Python Code:
%%file sq.py
def square(n):
return n*n
Explanation: Building an ML App
Now that we have a machine learning model to predict the defaults, let us try to build a web application to lend loans.
It'll have two parts:
a form to submit the loans
admin panel to look at the submitted loans and their probabil... |
13,629 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
From NumPy to Leaflet
This notebook shows how to display some raster geographic data in IPyLeaflet. The data is a NumPy array, which means that you have all the power of the Python scientifi... | Python Code:
import requests
import os
from tqdm import tqdm
import zipfile
import rasterio
from affine import Affine
import numpy as np
import scipy.ndimage
from rasterio.warp import reproject, Resampling
import PIL
import matplotlib.pyplot as plt
from base64 import b64encode
try:
from StringIO import StringIO
... |
13,630 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Let's begin by querying our newly transformed vcf table, containing variants for the human chromosome 21.
For instructions on the BigQuery transformation see
Step2: ... | Python Code:
from google.colab import auth
auth.authenticate_user()
print('Authenticated')
Explanation: <a href="https://colab.research.google.com/github/isb-cgc/examples-Python/blob/master/ISB_CGC_Query_of_the_Month_November_2018.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.sv... |
13,631 | 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-brief-tutorial-for-the-WormBase-Enrichment-Suite,-Python-interface" data-toc-modified-id="A-brief-tutorial-for-the-WormBase-Enrich... | Python Code:
# this first cell imports the libraries we typically use for data science in Python
import pandas as pd
import numpy as np
# this is the WormBase Enrichment Suite module (previously just TEA)
import tissue_enrichment_analysis as ea
# plotting libraries
import matplotlib.pyplot as plt
import seaborn as sns
... |
13,632 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Remote WMI Wbemcomn DLL Hijack
Metadata
| | |
|
Step1: Download & Process Mordor Dataset
Step2: Analytic I
Look for non-system accounts SMB accessing a C
Step3: Analy... | Python Code:
from openhunt.mordorutils import *
spark = get_spark()
Explanation: Remote WMI Wbemcomn DLL Hijack
Metadata
| | |
|:------------------|:---|
| collaborators | ['@Cyb3rWard0g', '@Cyb3rPandaH'] |
| creation date | 2020/10/09 |
| modification date | 2020/10/09 |
| playbook related... |
13,633 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 4- Decision Trees
This assignment uses 2012 data obtained from the Federal Election Commission on contributions to candidates from committees. The data dictionary is available at http
St... | Python Code:
from __future__ import division, print_function
from collections import Counter, defaultdict
from itertools import combinations
import pandas as pd
import numpy as np
import itertools
import sklearn
from sklearn.tree import DecisionTreeClassifier
from sklearn.feature_extraction import DictVectorizer #to t... |
13,634 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
200-D Multivariate Normal
Let's go for broke here.
Setup
First, let's set up some environmental dependencies. These just make the numerics easier and adjust some of the plotting defaults to ... | Python Code:
# system functions that are always useful to have
import time, sys, os
import pickle
# basic numeric setup
import numpy as np
from numpy import linalg
from scipy import stats
# inline plotting
%matplotlib inline
# plotting
import matplotlib
from matplotlib import pyplot as plt
# seed the random number gene... |
13,635 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cmcc', 'cmcc-cm2-hr5', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: CMCC
Source ID: CMCC-CM2-HR5
Sub-Topics: Radiative Forcings.
Proper... |
13,636 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1.4 查找最大或最小的N个元素
怎样从一个集合中获得最大或者最小的N个元素列表？
Step1: 当查找的元素个数较小时(N < nSum)，函数nlargest and nsmalest 是很适合<br>若 仅仅想查找唯一的 最小或最大N=1的元素的话，使用max and min 更快<br>若N的大小的和集合大小接近时，通常先排序在切片更快 sorted(items... | Python Code:
import heapq
nums = [1,8,23,44,56,12,-2,45,23]
print(heapq.nlargest(3,nums))
print(heapq.nsmallest(3,nums))
portfolio = [
{'name':'IBM','shares':100,'price':91.1},
{'name':'AAPL','shares':50,'price':543.22},
{'name': 'FB', 'shares': 200, 'price': 21.09},
{'name': 'HPQ', 'shares': 35, 'price... |
13,637 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial Part 16
Step1: For this example, we will create a data distribution consisting of a set of ellipses in 2D, each with a random position, shape, and orientation. Each class correspo... | Python Code:
%tensorflow_version 1.x
!curl -Lo deepchem_installer.py https://raw.githubusercontent.com/deepchem/deepchem/master/scripts/colab_install.py
import deepchem_installer
%time deepchem_installer.install(version='2.3.0')
Explanation: Tutorial Part 16: Conditional Generative Adversarial Network
Note: This exampl... |
13,638 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lists
Some methods of list
Step1: <code>del</code> statement can be used to remove an item from a list given its index
Step2: <code>list()</code>
Step3: Sort a list
<code>sorted</code><co... | Python Code:
pets = ['dog', 'cat', 'pig']
print pets.index('cat')
pets.insert(0, 'rabbit')
print pets
pets.pop(1)
print pets
Explanation: Lists
Some methods of list:
<code>list.append(x)</code>: add <code>x</code> to the end
<code>list.insert(i, x)</code>: insert <code>x</code> at position <code>i</code>
<code>list.ind... |
13,639 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Account for AOI reflection losses (in full mode only)
In this section, we will learn
Step1: Let's define a few helper functions that will help clarify the notebook
Step2: Get timeseries in... | Python Code:
# Import external libraries
import os
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime
import pandas as pd
import warnings
# Settings
%matplotlib inline
np.set_printoptions(precision=3, linewidth=300)
warnings.filterwarnings('ignore')
plt.style.use('seaborn-whitegrid')
plt.r... |
13,640 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Estandarizacion de datos de los Anuarios Geoestadísticos de INEGI 2017
1. Introduccion
Parámetros que salen de esta fuente
Step1: 2. Descarga de datos
Cada entidad cuenta con una página que... | Python Code:
descripciones = {
'P0610': 'Ventas de electricidad',
'P0701': 'Longitud total de la red de carreteras del municipio (excluyendo las autopistas)'
}
# Librerias utilizadas
import pandas as pd
import sys
import urllib
import os
import csv
import zipfile
# Configuracion del sistema
print('Python {} on ... |
13,641 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Baseline prediction for homework type
The baseline prediction method we use for predicting which homework the notebook came from uses the popular plagiarism detector JPlag.
We feed each note... | Python Code:
# First step is to load a balanced dataset of homeworks
import sys
home_directory = '/dfs/scratch2/fcipollone'
sys.path.append(home_directory)
import numpy as np
from nbminer.notebook_miner import NotebookMiner
hw_filenames = np.load('../homework_names_jplag_combined_per_student.npy')
min_val = min([len(te... |
13,642 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Decision Analysis
The Price is Right problem
On November 1, 2007, contestants named Letia and Nathaniel appeared on
The Price is Right, an American game show. They competed
in a game called ... | Python Code:
from price import *
import matplotlib.pyplot as plt
player1, player2 = MakePlayers(path='../code')
MakePrice1(player1, player2)
plt.legend();
Explanation: Decision Analysis
The Price is Right problem
On November 1, 2007, contestants named Letia and Nathaniel appeared on
The Price is Right, an American game... |
13,643 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading files
The iterator notation is easiest.
Step1: (The comma at the end suppresses extra newline). Can also use the object-oriented interface.
Step2: Reading all of the lines at once
... | Python Code:
f = open('kaiju_movies.dat')
for movie in f:
print movie,
f.close()
Explanation: Reading files
The iterator notation is easiest.
End of explanation
f = file('kaiju_movies.dat')
for movie in f:
print movie,
f.close()
Explanation: (The comma at the end suppresses extra newline). Can also use the obje... |
13,644 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating STIX Content
Creating STIX Domain Objects
To create a STIX object, provide keyword arguments to the type's constructor
Step1: Certain required attributes of all objects will be set... | Python Code:
from stix2 import Indicator
indicator = Indicator(name="File hash for malware variant",
pattern="[file:hashes.md5 = 'd41d8cd98f00b204e9800998ecf8427e']",
pattern_type="stix")
print(indicator.serialize(pretty=True))
Explanation: Creating STIX Content
Creating STIX... |
13,645 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to use this Notebook
The development cycle intended here is to
Init an experiment
Reset the model and optimizer
Restart wandb
Run one epoch
Add any new logs for plots, as needed
Then re... | Python Code:
from functools import partial
import torch
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
Explanation: How to use this Notebook
The development cycle intended here is to
Init an experiment
Reset the model and optimizer
Restart wandb
Run one epoch
Add any new logs for plots, as ne... |
13,646 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Storage To Table
Move using bucket and path prefix.
License
Copyright 2020 Google LLC,
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in com... | Python Code:
!pip install git+https://github.com/google/starthinker
Explanation: Storage To Table
Move using bucket and path prefix.
License
Copyright 2020 Google LLC,
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 o... |
13,647 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with this work for additional information
regarding copyri... | Python Code:
import logging
import random
import time
import matplotlib.pyplot as plt
import mxnet as mx
from mxnet import gluon, np, npx, autograd
import numpy as onp
Explanation: Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
distributed with th... |
13,648 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'hadgem3-gc31-ll', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: MOHC
Source ID: HADGEM3-GC31-LL
Topic: Land
Sub-Topics: Soil, Snow, Veget... |
13,649 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
If we're making the fin frames with a router/2-axis mill, we need to know what angle of chamfer cutter to use.
This is just the trig to make sure that the angle of the leading edge is $\leq$... | Python Code:
import math as m
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
Explanation: If we're making the fin frames with a router/2-axis mill, we need to know what angle of chamfer cutter to use.
This is just the trig to make sure that the angle of the leading edge is $\leq$ the mach angle.
... |
13,650 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Programming Paradigms
In the initial days we had only one type of programming paradigms, the paradigm of the developer
Step1: Functional
Step2: Functional
Step3: the abov... | Python Code:
towns = ["Rio de Janeiro", "Bhopal", "Budd Lake", "New York", "São Paulo", "Curitib]a "]
count = 0
for city in towns:
print(city)
count = count + 1
print()
print("Total number of cities:", count)
Explanation: Introduction to Programming Paradigms
In the initial days we had only one type of programm... |
13,651 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Twitter + Watson Tone Analyzer Sample Notebook
In this sample notebook, we show how to load and analyze data from the Twitter + Watson Tone Analyzer Spark sample application (code can be fou... | Python Code:
# Import SQLContext and data types
from pyspark.sql import SQLContext
from pyspark.sql.types import *
Explanation: Twitter + Watson Tone Analyzer Sample Notebook
In this sample notebook, we show how to load and analyze data from the Twitter + Watson Tone Analyzer Spark sample application (code can be found... |
13,652 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Doppler shifts
Exploring doppler shift on precision and quality. Specifically in the Z-band.
This showed the largest change with application of dopplershifts (Fegueira 2016 Fig. C.3 and C.4)... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
from tqdm import tqdm
import PyAstronomy.pyasl as pyasl
from astropy import constants as const
import eniric
from eniric import config
# config.cache["location"] = None # Disable caching for these tests
config.cache["location"] = ".joblib" # Enable cachi... |
13,653 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about emb... | Python Code:
import time
import numpy as np
import tensorflow as tf
import utils
Explanation: Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about embedding words for use in natural lang... |
13,654 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Face Generation
In this project, you'll use generative adversarial networks to generate new images of faces.
Get the Data
You'll be using two datasets in this project
Step3: Explore ... | Python Code:
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
DON'T MODIFY ANYTHING IN THIS CELL
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
Explanation: Face Generation
In this project, you'll use generative adversa... |
13,655 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Crash Course In Linear Algebra For Data Scientists
Preamble
This notebook was made for the purposes of quickly introducing the theoretical groundwork of Linear Algebra for Data Scientists.
T... | Python Code:
import numpy as np
Explanation: Crash Course In Linear Algebra For Data Scientists
Preamble
This notebook was made for the purposes of quickly introducing the theoretical groundwork of Linear Algebra for Data Scientists.
To that end, we will be primarily making the computer do the hard work of doing the te... |
13,656 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook
Roadmap
Data Generating Process
Objects of Interest
Processing Specification
Setting up Simulation
Conducting Estimation
Inspection of Results
Over the next couple of lectures, we w... | Python Code:
%%capture
# Notebook metods
from IPython.core.display import HTML, Image
# Unix Pattern Extensions
import glob
# Operating System Interfaces
import os
# Lexical Analysis
import shlex
# Copy operations
import copy
# Encoders and Decoders
import codecs
# Statistical Modeling and Econometrics
import statsmo... |
13,657 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pick one of these to explore re
Step1: Run Decision Trees, Prune, and consider False Positives
Step2: As a check, consider Feature selection
Step3: Find the Principal Components
Step4: S... | Python Code:
# Look only at train IDs
features = df.columns.values
X = train_id_dummies
y = df['ord_del']
# Non Delay Specific
features = df.columns.values
target_cols = ['temp','precipiation',
'visability','windspeed','humidity','cloudcover',
'is_bullet','is_limited','t_northbound',
'd_monday','... |
13,658 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
H2O Tutorial
Author
Step1: Enable inline plotting in the Jupyter Notebook
Step2: Intro to H2O Data Munging
Read csv data into H2O. This loads the data into the H2O column compressed, in-me... | Python Code:
import pandas as pd
import numpy
from numpy.random import choice
from sklearn.datasets import load_boston
from h2o.estimators.random_forest import H2ORandomForestEstimator
import h2o
h2o.init()
# transfer the boston data from pandas to H2O
boston_data = load_boston()
X = pd.DataFrame(data=boston_data.data,... |
13,659 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 Google LLC
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 Licens... | Python Code:
# Import all necessary libs
from google.colab import auth
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from IPython.display import display, HTML
# Authenticate the user to query datasets in Google BigQuery
auth.authenticate_user()
%matplotlib inline
Explanation: Copyright 20... |
13,660 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Overview
Hour 1
Tuples
Dictionaries
Take Up Midterm
Hours 2 and 3
Work Time
Lists
A list is an object that contains multiple data items
Lists are mutable
Lists can be indexed and sliced
List... | Python Code:
number_list = [1, 2, 4, 8, 16, 32]
the_pythons = ["Graham", "Terry", "Michael", "Eric", "Terry", "John"]
mixed = [1, "Terry", 4]
print (mixed)
Explanation: Overview
Hour 1
Tuples
Dictionaries
Take Up Midterm
Hours 2 and 3
Work Time
Lists
A list is an object that contains multiple data items
Lists are muta... |
13,661 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Installation tips
Create Anaconda virtual environment with ipython notebook support
conda create -n tf ipython-notebook --yes
The set up as explained in the official site failed for me. Some... | Python Code:
import tensorflow as tf
#----------------------------------------------------------
# Basic graph structure and operations
# tf.add , tf.sub, tf.mul , tf.div , tf.mod , tf.poe
# tf.less , tf.greater , tf.less_equal , tf.greater_equal
# tf.logical_and , tf.logical_or , logical.xor
#----------------------... |
13,662 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Precision vs Accuracy Precision is the accuracy of basic arithmetic operations used in the computation Accuracy is the absolute or relative error of the approximate quantity* NOTE
Step1: Th... | Python Code:
# Definition 1: Round down to p-sig. digit numberx = 0.90x1 = 0.99 # 2 correct significant digit, actual difference 0.09x2 = 0.89 # 1 correct significant digit, actual difference 0.01
# Definition 2: Round to nearest p-sig. digit numbery = 0.9951 # --> 0.10y1 = 0.9499 # --> 0.90 , only 1 correct sig. dig... |
13,663 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Intelligence II - Team MensaNord
Sheet 08
Nikolai Zaki
Alexander Moore
Johannes Rieke
Georg Hoelger
Oliver Atanaszov
Step1: Exercise 1
Step2: Simulation with M=1
Step3: Simulation... | Python Code:
from __future__ import division, print_function
import matplotlib.pyplot as plt
%matplotlib inline
import scipy.stats
import numpy as np
Explanation: Machine Intelligence II - Team MensaNord
Sheet 08
Nikolai Zaki
Alexander Moore
Johannes Rieke
Georg Hoelger
Oliver Atanaszov
End of explanation
def E(W, s):
... |
13,664 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<H1>PrimerDesign</H1>
We need to define a sequence of 17 bases with the following requirements
Step1: The function product is what we need to obtain a sequence of x elements with the four n... | Python Code:
%pylab inline
from itertools import product, permutations
from math import pow
Explanation: <H1>PrimerDesign</H1>
We need to define a sequence of 17 bases with the following requirements:
<ul>
<li>Total GC content: 40-60%</li>
<li>GC Clamp: < 3 in the last 5 bases at the 3' end of the primer.</li>
... |
13,665 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 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 obt... | Python Code:
#@title Util functions
import csv
import os
from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns
import tensorflow.compat.v1 as tf
from tensorflow.compat.v1.io import gfile
def read_csv_as_dataframe(path):
with gfile.GFile(path, "r") as file:
reader = csv.reader(file, delimi... |
13,666 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Annotating Public Resources Using I-Python Notebook
<h2>A Linear Algebra Example</h2>
Step1: Yes, you may embed Youtubes in your I-Python Notebooks, meaning you may follow up on a presentat... | Python Code:
from IPython.display import YouTubeVideo
YouTubeVideo("3Md5KCCQX-0")
Explanation: Annotating Public Resources Using I-Python Notebook
<h2>A Linear Algebra Example</h2>
End of explanation
import numpy as np
from scipy import linalg
# https://en.wikipedia.org/wiki/Hermitian_matrix
A = np.matrix('2, 2+1j, 4;... |
13,667 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kubeflow pipelines
Learning Objectives
Step1: Restart the kernel
After you install the additional packages, you need to restart the notebook kernel so it can find the packages.
Import libra... | Python Code:
!pip3 install --user kfp --upgrade
Explanation: Kubeflow pipelines
Learning Objectives:
1. Learn how to deploy a Kubeflow cluster on GCP
1. Learn how to create a experiment in Kubeflow
1. Learn how to package you code into a Kubeflow pipeline
1. Learn how to run a Kubeflow pipeline in a repeatable ... |
13,668 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Simple Autoencoder
We'll start off by building a simple autoencoder to compress the MNIST dataset. With autoencoders, we pass input data through an encoder that makes a compressed represen... | Python Code:
%matplotlib inline
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', validation_size=0)
Explanation: A Simple Autoencoder
We'll start off by building a simple autoencoder to c... |
13,669 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ApJdataFrames Erickson2011
Title
Step1: Table 2- Optical Properties of Candidate Young Stellar Objects
Step2: Table 3 - Association Members with Optical Spectra
Step3: The code to merge t... | Python Code:
%pylab inline
import seaborn as sns
sns.set_context("notebook", font_scale=1.5)
#import warnings
#warnings.filterwarnings("ignore")
import pandas as pd
Explanation: ApJdataFrames Erickson2011
Title: THE INITIAL MASS FUNCTION AND DISK FREQUENCY OF THE Rho OPHIUCHI CLOUD: AN EXTINCTION-LIMITED SAMPLE
Author... |
13,670 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Abstractions for representing environments
Environmental models can be represented either through a GridMeshModel or a TriMeshModel, using a grid and a triangular based representation of ... | Python Code:
from pextant.mesh.abstractmesh import NpDataset
import numpy as np
xx,yy= np.mgrid[0:5,0:5]
basic_terrain = NpDataset(0.1*(xx**2+yy**2), resolution=1)
basic_terrain
Explanation: 1. Abstractions for representing environments
Environmental models can be represented either through a GridMeshModel or a TriMesh... |
13,671 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
9.试作下图所示电力系统的阻抗图，并将参数注载图上（不计线路和变压器的电阻和导纳）。
1.计算时取6KV电压为基本级。
2.计算时取10KV电压为基本级。
3.计算时取110KV电压为基本级。
<img src="./第9、10题图.png" />
1.解：
先计算各参数的实际值。
Step1: 计算各变压器变比：
Step2: 将实际值归算成6kv为基准的归算值：
Ste... | Python Code:
x1=0.4
L1=100
X_L1=x1*L1
x2=0.4
L2=80
X_L2=x2*L2
#T1 SF7-16000/110
Sn_T1=16 #MVA
Uk1=10.5 #%
Un_T1=121#KV
X_T1=Uk1*Un_T1**2/(100*Sn_T1)
#T2 S
Sn_T2=31.5 #MVA
Uk2=10.5 #%
Un_T2=121#KV
X_T2=Uk2*Un_T2**2/(100*Sn_T2)
X_T1
Explanation: 9.试作下图所示电力系统的阻抗图，并将参数注载图上（不计线路和变压器的电阻和导纳）。
1.计算时取6KV电压为基本级。
2.计算时取10KV电压为基本级... |
13,672 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
pandas 3
자료 안내
Step1: 분석을 위한 테스트 데이터를 만들어 보자.
Step2: 위의 함수를 이용하여 테스트 데이터를 만들고, 이를 다시 데이터프레임으로 만들어보자.
Step3: 위의 데이터프레임을 Excel 파일로 저장하자. 이 때 인덱스 값은 원래의 테스트 데이터셋의 일부가 아니기 때문에 저장하지 않는다.
Step4... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import numpy.random as np
# 쥬피터 노트북에서 그래프를 직접 나타내기 위해 사용하는 코드
# 파이썬 전문 에디터에서는 사용하지 않음
%matplotlib inline
Explanation: pandas 3
자료 안내:
pandas 라이브러리 튜토리얼에
있는 Lessons for new pandas users의 03-Lesson 내용을 담고 있다.
익명함수(lambda 함수), GroupBy, apply, transform에 대한... |
13,673 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Structure Data Example
Step1: Please Download
https
Step2: Dealing with NaN
There are many approaches possibles for NaN values in the data, here we just changing it to " " or 0 depending o... | Python Code:
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
# We're using pandas to read the CSV file. This is easy for small datasets, but for large and complex datasets,
# tensorflow parsing and processing functions are more powerful
import pandas as pd
im... |
13,674 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Su-Schrieffer–Heeger (SSH) model
Saumya Biswas (saumyab@uoregon.edu)
The celebrated SSH model is analyzed with QuTiP's lattice module below.
The above figure shows a SSH model with 6 sit... | Python Code:
from qutip import *
import matplotlib.pyplot as plt
import numpy as np
val_s = ['site0','site1']
(H_cell_form,T_inter_cell_form,H_cell,T_inter_cell) = cell_structures( val_s)
H_cell_form
T_inter_cell_form
Explanation: The Su-Schrieffer–Heeger (SSH) model
Saumya Biswas (saumyab@uoregon.edu)
The celebrated S... |
13,675 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sets implemented as AVL Trees
This notebook implements <em style="color
Step1: Given an ordered binary tree $t$, the expression $t.\texttt{isEmpty}()$ checks whether $t$ is the empty tree.
... | Python Code:
class Set:
def __init__(self):
self.mKey = None
self.mLeft = None
self.mRight = None
self.mHeight = 0
Explanation: Sets implemented as AVL Trees
This notebook implements <em style="color:blue;">sets</em> as <a href="https://en.wikipedia.org/wiki/AVL_tree">AVL trees... |
13,676 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import data
Step1: Set parameters
Step2: Preprocessing
Step6: 1. Distribution regression
Kernel mean embedding
Instead of fitting a model to the instances, the idea of distribution regres... | Python Code:
def load_data():
full_data = pd.read_csv("Data/X.csv")
train_y = pd.read_csv("Data/y_train.csv")
# Rename columns to something more interpretable
columns = (["reflectance_" + str(i) for i in range(7)]
+ ["solar_" + str(i) for i in range(5)] + ["id"])
full_data.columns = c... |
13,677 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
odm2api demo with Little Bear SQLite sample DB
Largely from https
Step1: Read the database
Step2: Run some basic sample queries
Step3: Read some metadata from the database
Step4: Samplin... | Python Code:
import os
from odm2api.ODMconnection import dbconnection
odm2db_fpth = os.path.join('data', 'ODM2.sqlite')
session_factory = dbconnection.createConnection('sqlite', odm2db_fpth, 2.0)
Explanation: odm2api demo with Little Bear SQLite sample DB
Largely from https://github.com/ODM2/ODM2PythonAPI/blob/master/E... |
13,678 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Convolutional GANs
In this notebook, you'll build a GAN using convolutional layers in the generator and discriminator. This is called a Deep Convolutional GAN, or DCGAN for short. The D... | Python Code:
%matplotlib inline
import pickle as pkl
import matplotlib.pyplot as plt
import numpy as np
from scipy.io import loadmat
import tensorflow as tf
!mkdir data
Explanation: Deep Convolutional GANs
In this notebook, you'll build a GAN using convolutional layers in the generator and discriminator. This is called... |
13,679 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Intermediate Linear Algebra - Eigenvalues & Eigenvectors
Key Equation
Step1: Solving Equation $Ax=\lambda x$
Special Case
Step2: 3 x 3 Matrix
Let us write it in the form
$$ Ax = \lambda ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('fivethirtyeight')
plt.rcParams['figure.figsize'] = (10, 6)
def vector_plot (vector):
X,Y,U,V = zip(*vector)
C = [1,1,2,2]
plt.figure()
ax = plt.gca()
ax.quiver(X,Y,U,V,C, angles='xy',scale_units='xy',sc... |
13,680 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis of Movie Reviews
In this tutorial, we will load a trained model and perform inference on a new movie review.
Setup
As before, we first create a computational backend to te... | Python Code:
from neon.backends import gen_backend
be = gen_backend(backend='gpu', batch_size=1)
print be
Explanation: Sentiment Analysis of Movie Reviews
In this tutorial, we will load a trained model and perform inference on a new movie review.
Setup
As before, we first create a computational backend to tell neon on ... |
13,681 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Calculate Coverage
You've defined an AOI, you've specified the image type you are interested and the search query. Great! But what is the coverage of your AOI given your search query? Wouldn... | Python Code:
# Notebook dependencies
from __future__ import print_function
import datetime
import copy
from functools import partial
import os
from IPython.display import display, Image
import matplotlib
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from planet import ... |
13,682 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Domestic Load Research Programme Load Profile Uncertainty Analysis
This notebook requires access to a directory with hourly load profile data. The data files must be saved in /data/profiles/... | Python Code:
#load support functions
import observations.obs_processing as obs
import features.feature_ts as ts
import features.feature_socios as socios
#initiate offline plotting for plotly
import plotly.offline as offline
import cufflinks as cf
offline.init_notebook_mode()
#cf.set_config_file(offline=True, world_read... |
13,683 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Insertion Sort
The function sort is specified via two equations
Step1: The auxiliary function insert is specified as follows | Python Code:
def sort(L):
if L == []:
return []
x, *R = L
return insert(x, sort(R))
Explanation: Insertion Sort
The function sort is specified via two equations:
$\mathtt{sort}([]) = []$
$\mathtt{sort}\bigl([x] + R\bigr) =
\mathtt{insert}\bigl(x, \mathtt{sort}(R)\bigr)$
This is most easily im... |
13,684 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Probabilistic Programming in Python using PyMC
Authors
Step1: Here is what the simulated data look like. We use the pylab module from the plotting library matplotlib.
Step2: Model Specific... | Python Code:
import numpy as np
# Intialize random number generator
np.random.seed(123)
# True parameter values
alpha, sigma = 1, 1
beta = [1, 2.5]
# Size of dataset
size = 100
# Predictor variable
X1 = np.linspace(0, 1, size)
X2 = np.linspace(0,.2, size)
# Simulate outcome variable
Y = alpha + beta[0]*X1 + beta[1]*X2 ... |
13,685 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You are currently looking at version 1.0 of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the Jupyter Notebook ... | Python Code:
import pandas as pd
pd.Series?
animals = ['Tiger', 'Bear', 'Moose']
pd.Series(animals)
numbers = [1, 2, 3]
pd.Series(numbers)
animals = ['Tiger', 'Bear', None]
df = pd.Series(animals)
df['number_column'] = -99999
df
numbers = [1, 2, None]
pd.Series(numbers)
import numpy as np
np.nan == None
np.nan == np.na... |
13,686 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Will explore aggregation framework for some analysis and then explore how we could use it for data cleaning
Example of Aggregation Framework
Let's find out who tweeted the most
... | Python Code:
import pprint
def get_client():
from pymongo import MongoClient
return MongoClient('mongodb://localhost:27017/')
def get_collection():
return get_client().examples.twitter
collection = get_collection()
def aggregate_and_show(collection, query, limit = True):
_query = query[:]
if limit:
... |
13,687 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Extracting Structure from Scientific Abstracts
using a LSTM neural network
Paul Willot
This project was made for the ICADL 2015 conference.
In this notebook we will go through all steps requ... | Python Code:
#%install_ext https://raw.githubusercontent.com/rasbt/watermark/master/watermark.py
%load_ext watermark
# for reproducibility
%watermark -a 'Paul Willot' -mvp numpy,scipy,spacy
Explanation: Extracting Structure from Scientific Abstracts
using a LSTM neural network
Paul Willot
This project was made for the ... |
13,688 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Image Classification using tf.keras
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: TODO
St... | 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... |
13,689 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="../../../images/qiskit-heading.gif" alt="Note
Step1: Next, we create a Python dictionary to specify the problem we want to solve. There are defaults for many additional values tha... | Python Code:
from qiskit_aqua_chemistry import AquaChemistry
Explanation: <img src="../../../images/qiskit-heading.gif" alt="Note: In order for images to show up in this jupyter notebook you need to select File => Trusted Notebook" width="500 px" align="left">
Qiskit Aqua: Chemistry basic how to
The latest version of t... |
13,690 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Further testing of the sklearn pull request
Step1: Test of the warnings
Testing
Area calculation tests
Testing in the context of modelling
Step2: Test of the warnings
Step3: Testing
The m... | Python Code:
__author__ = 'Nick Dingwall'
Explanation: Further testing of the sklearn pull request
End of explanation
import matplotlib.pyplot as plt
import matplotlib
%matplotlib inline
import numpy as np
from sklearn.metrics.base import _average_binary_score
from sklearn.metrics import precision_recall_curve
import w... |
13,691 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Converting automata to strings
Use to_str() to output a string representing the automaton in different formats.
Step1: Saving automata to files
Use save() to save the automaton into a file.... | Python Code:
a = spot.translate('a U b')
for fmt in ('hoa', 'spin', 'dot', 'lbtt'):
print(a.to_str(fmt))
Explanation: Converting automata to strings
Use to_str() to output a string representing the automaton in different formats.
End of explanation
a.save('example.aut').save('example.aut', format='lbtt', append=Tru... |
13,692 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pedestrian and Face Detection on Simple Azure
Pedestrian and Face Detection uses OpenCV to identify people standing in a picture or a video and NIST use case in this document is built with A... | Python Code:
from simpleazure import SimpleAzure
saz = SimpleAzure()
Explanation: Pedestrian and Face Detection on Simple Azure
Pedestrian and Face Detection uses OpenCV to identify people standing in a picture or a video and NIST use case in this document is built with Apache Spark and Mesos clusters on multiple compu... |
13,693 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Truly an 11x Developer solution to the ~~world's~~ universe's premier code interview question!
What is "pynads"
All joking aside, I've been hacking together a collection of Haskell-esque too... | Python Code:
from pynads import Container
class Person(Container):
__slots__ = ('name', 'age')
def __init__(self, name, age):
self.name = name
self.age = age
def _get_val(self):
return {'name': self.name, 'age': self.age}
def __repr__(self):
return "Person(name=... |
13,694 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<header class="w3-container w3-teal">
<img src="images/utfsm.png" alt="" align="left"/>
<img src="images/inf.png" alt="" align="right"/>
</header>
<br/><br/><br/><br/><br/>
IWI131
Programaci... | Python Code:
a, b = 2, 3
while b < 300:
print b,
a, b = b, a+b
Explanation: <header class="w3-container w3-teal">
<img src="images/utfsm.png" alt="" align="left"/>
<img src="images/inf.png" alt="" align="right"/>
</header>
<br/><br/><br/><br/><br/>
IWI131
Programación de Computadores
Sebastián Flores
¿Qué conte... |
13,695 | 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 0
Step1: From a sample of the RMS Titanic data, we can see the various features present for each passenger on the s... | Python Code:
import numpy as np
import pandas as pd
# RMS Titanic data visualization code
from titanic_visualizations import survival_stats
from IPython.display import display
%matplotlib inline
# Load the dataset
in_file = 'titanic_data.csv'
full_data = pd.read_csv(in_file)
# Print the first few entries of the RMS Ti... |
13,696 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyGSLIB
QQ and PP plots
Step1: Getting the data ready for work
If the data is in GSLIB format you can use the function pygslib.gslib.read_gslib_file(filename) to import the data into a Pand... | Python Code:
#general imports
import pygslib
Explanation: PyGSLIB
QQ and PP plots
End of explanation
#get the data in gslib format into a pandas Dataframe
cluster= pygslib.gslib.read_gslib_file('../data/cluster.dat')
true= pygslib.gslib.read_gslib_file('../data/true.dat')
true['Declustering Weight'] = 1
Explanati... |
13,697 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Detecting outliers in time series
Step1: TL;DR
Step2: STL Decomposition
Seasonal and Trend decomposition using Loess (STL) was introduced by Cleveland et al. (1990). This method performs ... | Python Code:
__author__ = "Ben Bernstein"
Explanation: Detecting outliers in time series
End of explanation
from roam_outliers import *
Explanation: TL;DR: We describe a method of finding outliers in time series data by combining two distinct techniques, STL decomposition and sequential Grubbs' tests. In the end, we ar... |
13,698 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Theano, Lasagne
and why they matter
got no lasagne?
Install the bleeding edge version from here
Step1: theano teaser
Doing the very same thing
Step2: How does it work?
if you're currently ... | Python Code:
import numpy as np
def sum_squares(N):
return <student.Implement_me()>
%%time
sum_squares(10**8)
Explanation: Theano, Lasagne
and why they matter
got no lasagne?
Install the bleeding edge version from here: http://lasagne.readthedocs.org/en/latest/user/installation.html
Warming up
Implement a function ... |
13,699 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 Google LLC
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 Licens... | Python Code:
!git clone https://github.com/google-research/google-research.git
import sys
import os
import tarfile
import urllib
import zipfile
sys.path.append('./google-research')
Explanation: Copyright 2019 Google LLC
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.