Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
6,800 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 1 - Introduction to Machine Learning
This chapter introduces some common concepts about learning (such as supervised and unsupervised learning) and some simples applications.
Supervi... | Python Code:
%run ../src/LinearRegression.py
%run ../src/PolynomialFeatures.py
# LINEAR REGRESSION
# Generate random data
X = np.linspace(0,20,10)[:,np.newaxis]
y = 0.1*(X**2) + np.random.normal(0,2,10)[:,np.newaxis] + 20
# Fit model to data
lr = LinearRegression()
lr.fit(X,y)
# Predict new data
x_test = np.array([0,20... |
6,801 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mock Spectra
Attempting to make synthetic spectra look real.
Step2: We will try to use urllib to pull synthetic spectra from the Phoenix model atmosphere server. This way, we can avoid stor... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import urllib
Explanation: Mock Spectra
Attempting to make synthetic spectra look real.
End of explanation
def phoenixFileURL(Teff, logg, FeH=0.0, aFe=0.0, brand='BT-Settl', solar_abund='CIFIST2011_2015'):
Create file name for a Pho... |
6,802 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Query for pile-up allignments at region "x"
We can query the database to obtain a pile-up of the reads from a given readgroup.
Initialize the client
As seen in the "1kg.ipynb" example, we ta... | Python Code:
import ga4gh.client as client
c = client.HttpClient("http://1kgenomes.ga4gh.org")
Explanation: Query for pile-up allignments at region "x"
We can query the database to obtain a pile-up of the reads from a given readgroup.
Initialize the client
As seen in the "1kg.ipynb" example, we take the following steps... |
6,803 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Representation of data submission workflow components based on W3C-PROV
Step1: generate empty Prov document and load submission workflow representation
Step2: The Provenance Model used is ... | Python Code:
%load_ext autoreload
%autoreload 2
%load_ext autoreload
%autoreload 2
import sys
sys.path.append('/home/stephan/Repos/ENES-EUDAT/submission_forms')
from dkrz_forms import form_handler
from dkrz_forms import checks
from dkrz_forms.config import test_config
from dkrz_forms.config import workflow_steps
#print... |
6,804 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Loading sample data
We begin by loading the data that we would like to summarize into a Pandas DataFrame.
- Variables are in columns
- Encounters/observations are in ... | Python Code:
# Import numerical libraries
import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
%matplotlib inline
# Import tableone
try:
from tableone import TableOne, load_dataset
except (ModuleNotFoundError, ImportError):
# install on Colab
!pip install tableone
... |
6,805 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This example builds HMM and MSMs on the alanine_dipeptide dataset using varing lag times
and numbers of states, and compares the relaxation timescales
Step1: First
Step2: Now sequences is ... | Python Code:
from __future__ import print_function
import os
%matplotlib inline
from matplotlib.pyplot import *
from msmbuilder.featurizer import SuperposeFeaturizer
from msmbuilder.example_datasets import AlanineDipeptide
from msmbuilder.hmm import GaussianHMM
from msmbuilder.cluster import KCenters
from msmbuilder.ms... |
6,806 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interactive 3-D Visualization
Step1: Loading an example geomodel
Step2: Basic plotting API
Data plot
Step3: Geomodel plot
Step4: Interactive plot
Passing the notebook=False keyword argum... | Python Code:
# Importing GemPy
import gempy as gp
# Embedding matplotlib figures in the notebooks
%matplotlib inline
# Importing auxiliary libraries
import numpy as np
import matplotlib.pyplot as plt
Explanation: Interactive 3-D Visualization
End of explanation
data_path = 'https://raw.githubusercontent.com/cgre-aachen... |
6,807 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Collaborative filtering on Google Analytics data
This notebook demonstrates how to implement a WALS matrix refactorization approach to do collaborative filtering.
Step2: Create raw dataset
... | Python Code:
import os
PROJECT = "cloud-training-demos" # REPLACE WITH YOUR PROJECT ID
BUCKET = "cloud-training-demos-ml" # REPLACE WITH YOUR BUCKET NAME
REGION = "us-central1" # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
# Do not change these
os.environ["PROJECT"] = PROJECT
os.environ["BUCKET"] = BUCKET
os.envir... |
6,808 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
机器学习纳米学位
监督学习
项目2
Step1: 练习：数据探索
首先我们对数据集进行一个粗略的探索，我们将看看每一个类别里会有多少被调查者？并且告诉我们这些里面多大比例是年收入大于50,000美元的。在下面的代码单元中，你将需要计算以下量：
总的记录数量，'n_records'
年收入大于50,000美元的人数，'n_greater_50k'.
年收入最多为50,000美元... | Python Code:
# 为这个项目导入需要的库
import numpy as np
import pandas as pd
from time import time
from IPython.display import display # 允许为DataFrame使用display()
# 导入附加的可视化代码visuals.py
import visuals as vs
# 为notebook提供更加漂亮的可视化
%matplotlib inline
# 导入人口普查数据
data = pd.read_csv("census.csv")
# 成功 - 显示第一条记录
display(data.head())
Expla... |
6,809 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
nb2py tutorial
All the examples are generated from this notebook and located in the folder tutorial_files.
Step1: Exporting marked cells
The dump function automatically exports cells starti... | Python Code:
import nb2py
Explanation: nb2py tutorial
All the examples are generated from this notebook and located in the folder tutorial_files.
End of explanation
#~
#This is a cell example with the standard marker
a=2
b=3
print(a+b)
nb2py.dump('tutorial.ipynb','tutorial_files/standard.py')
#please export this cell
... |
6,810 | 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-... |
6,811 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recovers true coefficients on artificial censored regression data
Step1: Note that the truncation values do not have to be the same for e.g. all left-censored observations, or all right-cen... | Python Code:
rs = np.random.RandomState(seed=10)
ns = 100
nf = 10
x, y_orig, coef = make_regression(n_samples=ns, n_features=nf, coef=True, noise=0.0, random_state=rs)
x = pd.DataFrame(x)
y = pd.Series(y_orig)
n_quantiles = 3 # two-thirds of the data is truncated
quantile = 100/float(n_quantiles)
lower = np.percentile(... |
6,812 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Whitening versus standardizing
Step1: First, just read in data, and take a peek. The data can be found on GitHub.
Step2: We're told that for gender, 1 is male, and 2 is female. Part (a) sa... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
Explanation: Whitening versus standardizing
End of explanation
raw_data = pd.read_csv("heightWeightData.txt", header=None, names=["gender", "height", "weight"])
raw_data.info()
raw_data.head()
... |
6,813 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
6,814 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mock community dataset generation
Run in a qiime 2.0.6 conda environment.
This notebook describes how mock community datasets were retrieved and files were generated for tax-credit compariso... | Python Code:
from tax_credit.process_mocks import (extract_mockrobiota_dataset_metadata,
extract_mockrobiota_data,
batch_demux,
denoise_to_phylogeny,
transport_to_repo
... |
6,815 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LSESU Applicable Maths Python Lesson 3
1/11/16
Today we will be learning about
* Strings and string indexing
* Reading files
* Lists
* List comprehensions
Recap from week 2
Functions
This i... | Python Code:
# Everyone should know how to create (or "declare") a string by now
var = 'This is a string'
alphabet = 'abcdefghijklmnopqrstuvwxyz'
Explanation: LSESU Applicable Maths Python Lesson 3
1/11/16
Today we will be learning about
* Strings and string indexing
* Reading files
* Lists
* List comprehensions
Recap... |
6,816 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Naive Bayes - Trabalho
Questão 1
Implemente um classifacor Naive Bayes para o problema de predizer a qualidade de um carro. Para este fim, utilizaremos um conjunto de dados referente a quali... | Python Code:
#Bibliotecas
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, classification_report
#Lendo o arquivo com os dados
df = pd.read_csv('carData.csv', header=None)
df.columns = ['buying', 'maint','doors','persons','lug_boot'... |
6,817 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Markov Madness
Ok let's get down to business! So the overall goal is to build a mathematical model that predicts with good accuracy who is likely to make it to the sweet 16 in the NCAA tourn... | Python Code:
import pandas as pd
import numexpr
import bottleneck
import numpy as np
import numpy.linalg as linalg
import matplotlib.pyplot as plt
%matplotlib inline
import scipy.stats as ss
reg_14_15 = pd.read_csv('2014_2015 Regular Season Stats.csv')
#Testing out our system
reg_14_15
Explanation: Markov Madness
Ok le... |
6,818 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An RNN model for temperature data
This time we will be working with real data
Step1: Download Data
Step2: <a name="hyperparameters"></a>
<a name="assignment1"></a>
Hyperparameters
<div cla... | Python Code:
import math
import sys
import time
import numpy as np
sys.path.insert(0, '../temperatures/utils/') #so python can find the utils_ modules
import utils_batching
import utils_args
import tensorflow as tf
from tensorflow.python.lib.io import file_io as gfile
print("Tensorflow version: " + tf.__version__)
from... |
6,819 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Test CacheOutput() class-based function decorator
Step1: Make an expensive function and time it
Step2: Cache the function results
If the exact same inputs are used again before the time li... | Python Code:
import datetime as dt
import time
import fridge
Explanation: Test CacheOutput() class-based function decorator
End of explanation
# This decorator just displays how long a function takes to run
def showtime(func):
def wrapper(*args,**kwargs):
start = dt.datetime.now()
result = func(... |
6,820 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Google BigQuery
Motivated by the structure in the OKCupid usernames, I looked at the reddit data on Google BigQuery.
Try to answer the questions
Step1: Had to impose a limit so that I did n... | Python Code:
%matplotlib inline
import os
import glob
import pylab
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 5)
import seaborn as sns
sns.set_style('whitegrid')
from matplotlib.dates import date2num
from datetime import datetime
from pysurvey.plot import setup_sns as setup
from pysurvey.p... |
6,821 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Evaluating-Imbalanced-Datasets" data-toc-modified-id="Evaluating-Imbalanced-... | Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', '..', 'notebook_format'))
from formats import load_style
load_style(plot_style=False)
os.chdir(path)
# 1. magic for inline plot
# 2. magic to p... |
6,822 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The situation
Type C thermocouples are not NIST calibrated to below 273.15 K. For my research specific scenario, I need to cool my sample (Molybdenum) to cryogenic temperatures and also anne... | Python Code:
# import a few packages
%matplotlib notebook
from thermocouples_reference import thermocouples
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sympy as sp
from scipy import optimize, interpolate, signal
typeC=thermocouples['C']
# make sure you are in the same dir as the file
#... |
6,823 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Classification 1
Step3: Evaluating a classifier
Most classifiers are "soft" because they can output a score, higher means more likely to be $Y=1$
- Logistic regression
Step4: Confus... | Python Code:
import pandas as pd
import numpy as np
import matplotlib as mpl
import plotnine as p9
import matplotlib.pyplot as plt
import itertools
import warnings
warnings.simplefilter("ignore")
from sklearn import neighbors, preprocessing, impute, metrics, model_selection, linear_model, svm, feature_selection
from ma... |
6,824 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'ncar', 'sandbox-2', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: NCAR
Source ID: SANDBOX-2
Topic: Landice
Sub-Topics: Glaciers, Ice.
Prop... |
6,825 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating Keras DNN model
Learning Objectives
Create input layers for raw features
Create feature columns for inputs
Create DNN dense hidden layers and output layer
Build DNN model tying all ... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
!pip install --user google-cloud-bigquery==1.25.0
Explanation: Creating Keras DNN model
Learning Objectives
Create input layers for raw features
Create feature columns for inputs
Create DNN dense hidden layers and output layer
Build DNN mod... |
6,826 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1T_크롤링 수업(중고나라 모바일)
Step1: 이미지 가져오기
Step2: https | Python Code:
#네이버 중고나라(모바일)
import requests
from bs4 import BeautifulSoup
# "맥북" 키워드로 검색
url = "http://m.cafe.naver.com/ArticleSearchList.nhn?search.query=맥북&search.menuid=&search.searchBy=0&search.sortBy=sim&search.clubid=10050146"
response = requests.get(url)
response.status_code, response
dom = BeautifulSoup(respons... |
6,827 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="http
Step1: Start by defining the parent catalog URL from NCI's THREDDS Data Server
Note
Step2: <a id='part1'></a>
Using Siphon
Siphon is a collection of Python utilities for do... | Python Code:
from netCDF4 import Dataset
import matplotlib.pyplot as plt
from siphon import catalog, ncss
import datetime
%matplotlib inline
Explanation: <img src="http://nci.org.au/wp-content/themes/nci/img/img-logo-large.png", width=400>
Programmatically accessing data through THREDDS and the VDI
...using Python 3
I... |
6,828 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Equalização de Histograma
A transformação de contraste que procura distribuir a ocorrência dos níveis de cinza igualmente
na faixa de tons de cinza é denominada equalização de histograma.
O ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import sys,os
ia898path = os.path.abspath('/etc/jupyterhub/ia898_1s2017/')
if ia898path not in sys.path:
sys.path.append(ia898path)
import ia898.src as ia
nb = ia.nbshow(2)
f = mpimg.imread('../data/c... |
6,829 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
数据结构
这一节介绍pandas中的数据结构。首先，导入numpy和pandas
Step1: 我们先对数据结构进行简短的介绍, 然后再详细说明各个数据结构内置的方法。
Series
Series是一个一维带label的数组，元素可以是任何数据类型(整数、字符串、浮点数,Python对象等等)。和Python列表一样，Series元素的数据类型可以不同。Series是值可变的... | Python Code:
import numpy as np
import pandas as pd
Explanation: 数据结构
这一节介绍pandas中的数据结构。首先，导入numpy和pandas:
End of explanation
s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
s
s.index
pd.Series(np.random.randn(5))
Explanation: 我们先对数据结构进行简短的介绍, 然后再详细说明各个数据结构内置的方法。
Series
Series是一个一维带label的数组，元素可以是任何数据... |
6,830 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Custom generators
Step1: Custom generator without __init__ method
Step2: Explicitly setting the name of generated items
Let's repeat the previous example, but explicitly set the name of ge... | Python Code:
import tohu
from tohu.v4.primitive_generators import *
from tohu.v4.derived_generators import *
from tohu.v4.dispatch_generators import *
from tohu.v4.custom_generator import *
from tohu.v4.utils import print_generated_sequence, make_dummy_tuples
print(f'Tohu version: {tohu.__version__}')
Explanation: Cust... |
6,831 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 2016-10-07
Step2: 1. L1-Regularized Logistic Regression
Let us start with default parameters.
Step3: Question Compute the cross-validated predictions of the l1-regularized logistic ... | Python Code:
import numpy as np
%pylab inline
# Load the data as usual (here the code for Python 2.7)
X = np.loadtxt('data/small_Endometrium_Uterus.csv', delimiter=',', skiprows=1, usecols=range(1, 3001))
y = np.loadtxt('data/small_Endometrium_Uterus.csv', delimiter=',', skiprows=1, usecols=[3001],
con... |
6,832 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Carnegie Mellon Data Science Club
Step1: Introduction
Step2: Let us take a look at the dimension of this data frame. This is held in the shape attribute of the dataframe.
Step3: We see t... | Python Code:
import warnings
warnings.filterwarnings("ignore")
Explanation: Carnegie Mellon Data Science Club : Practical Natural Language Processing
By Michael Rosenberg.
Description: This notebook contains an introduction to document analysis with OkCupid data. It is designed to be used at a workshop for introducing ... |
6,833 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualizzazione Facebook
Step1: 1. Confronto Salvini, Renzi e M5S
Step2: 2. Dettaglio Salvini
Step3: 2.1. Distribuzione Totale dei Likes ai Post di Salvini
Step4: 2. Focus su Anni 2014, ... | Python Code:
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%pylab inline
matplotlib.style.use('ggplot')
# Directory di Staging
dir_df = os.path.join(os.path.abspath(''),'stg')
dir_out = os.path.join(os.path.abspath(''),'out')
# Dataset Salvini
df_filename = r'df_posts_likes_salvini.pk... |
6,834 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An RNN model for temperature data
This time we will be working with real data
Step1: <a name="hyperparameters"></a>
<a name="assignment1"></a>
Hyperparameters
<div class="alert alert-block ... | Python Code:
import math
import sys
import time
import numpy as np
import utils_batching
import utils_args
import tensorflow as tf
from tensorflow.python.lib.io import file_io as gfile
print("Tensorflow version: " + tf.__version__)
from matplotlib import pyplot as plt
import utils_prettystyle
import utils_display
Expla... |
6,835 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-3', 'sandbox-2', 'atmoschem')
Explanation: ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era: CMIP6
Institute: TEST-INSTITUTE-3
Source ID: SANDBOX-2
Topic: Atmoschem
Su... |
6,836 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plot MST Measures
Here we plot different MST measures from the computed connectivity matrices.
Step1: MST Dataset Structure
The order of frequency bands is as follows
Step2: Plotting of MS... | Python Code:
from pprint import pprint
import scipy
import pandas as pd
from pandas.tools.plotting import parallel_coordinates
from pandas import concat
import matplotlib
# Set backend to pgf
matplotlib.use('pgf')
import matplotlib.pyplot as plt
import numpy as np
# Some nice default configuration for plots
plt.rcParam... |
6,837 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Re-referencing the EEG signal
Load raw data and apply some EEG referencing schemes.
Step1: Apply different EEG referencing schemes and plot the resulting evokeds. | Python Code:
# Authors: Marijn van Vliet <w.m.vanvliet@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import mne
from mne.datasets import sample
from matplotlib import pyplot as plt
print(__doc__)
# Setup for reading the raw data
data_path = sample.data_pa... |
6,838 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Connecting to the database
Step1: Create a list of dictionaries that have the following structure
Step2: Create a dataframe from list of dicts
Step3: FIVE NUMBER SUMMARY for the length of... | Python Code:
conn = pg8000.connect(user = 'dot_student', database='training', port=5432, host='training.c1erymiua9dx.us-east-1.rds.amazonaws.com', password='qgis')
conn.rollback()
cursor = conn.cursor()
cursor.execute("SELECT column_name FROM information_schema.columns WHERE table_name='dot_311'")
# run the commented o... |
6,839 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simulation Code
The code below will generate a test folume and populate it with a set of clusters.
Step1: Cluster Extraction Validation
First, be sure that our cluster extraction algorithm ... | Python Code:
def generatePointSet():
center = (rand(0, 9), rand(0, 999), rand(0, 999))
toPopulate = []
for z in range(-3, 2):
for y in range(-3, 2):
for x in range(-3, 2):
curPoint = (center[0]+z, center[1]+y, center[2]+x)
#only populate valid points
... |
6,840 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Day 23 Pre-class assignment
Goals for today's pre-class assignment
In this pre-class assignment, you will
Step1: Task 2
Step2: Task 3
Step3: Task 4
Step4: Task 5
Step6: Assignment wrapu... | Python Code:
# Put your code here!
Explanation: Day 23 Pre-class assignment
Goals for today's pre-class assignment
In this pre-class assignment, you will:
Create and slice multi-dimensional numpy arrays
Plot 2D numpy arrays
Make an animation of 2D numpy arrays
Assignment instructions
First, work through the Numpy 2D ar... |
6,841 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Query Coordianted Canyon Experiment database for BED information
Connect to a remote database, select specific data using Django queries
Executing this Notebook requires a personal STOQS ser... | Python Code:
acts = (Activity.objects.using('stoqs_cce2015')
.filter(name__contains='trajectory')
.order_by('name'))
Explanation: Query Coordianted Canyon Experiment database for BED information
Connect to a remote database, select specific data using Django queries
Executing this Notebook requires a pe... |
6,842 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Content and Objectives
Show effect and validity of Wiener-Khinchin
Method
Step1: Parameters
Step2: Signals and their spectra
Step3: Plotting | Python Code:
# importing
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
# showing figures inline
%matplotlib inline
# plotting options
font = {'size' : 20}
plt.rc('font', **font)
plt.rc('text', usetex=True)
matplotlib.rc('figure', figsize=(18, 10) )
Explanation: Content and Objectives
Show effe... |
6,843 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Real-time Patient Montioring with Streams and BioPy
This notebook shows how to use Python to analyze medical data in real time using Streams and existing Python modules like BioSPPY and SciP... | Python Code:
from icpd_core import icpd_util
from streamsx.topology.context import JobConfig
from streamsx.topology import context
streams_instance_name = ## Change this to Streams instance
try:
cfg=icpd_util.get_service_instance_details(name=streams_instance_name, instance_type="streams")
except TypeError:
cf... |
6,844 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<a href="http
Step1: La commande suivante permet de verifier qu'une carte GPU est bien disponible sur la machine utilisée. Si c'est le cas et si Keras a bien été installé dans la c... | Python Code:
# Utils
import sys
import os
import shutil
import time
import pickle
import numpy as np
# Deep Learning Librairies
import tensorflow as tf
import keras.preprocessing.image as kpi
import keras.layers as kl
import keras.optimizers as ko
import keras.backend as k
import keras.models as km
import keras.applica... |
6,845 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Random Variables
Frequently, when an experiment is performed, we are interested mainly in some function of the outcome as opposed to the actual outcome itself.
For instance,<br>
1) In recent... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
from itertools import product
# from IPython.core.display import HTML
# css = open('media/style-table.css').read() + open('media/style-notebook.css').read()
# HTML('<style>{}</style>'.format(css))
one_toss = np.array(['H', 'T'])
two_tosses = list(pr... |
6,846 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Segmentation
Step1: Load the volume, it contains two spheres. You can either identify the regions of interest (ROIs) yourself or use the predefined rectangular regions of interest specified... | Python Code:
import SimpleITK as sitk
%run update_path_to_download_script
from downloaddata import fetch_data as fdata
%matplotlib notebook
import gui
import matplotlib.pyplot as plt
import numpy as np
from scipy import linalg
from ipywidgets import interact, fixed
Explanation: Segmentation: Thresholding and Edge Detec... |
6,847 | 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... |
6,848 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using sci-analysis with pandas
Pandas is a python package that simplifies working with tabular or relational data. Because columns and rows of data in a pandas DataFrame are naturally array-... | Python Code:
import warnings
warnings.filterwarnings("ignore")
%matplotlib inline
import numpy as np
import scipy.stats as st
from sci_analysis import analyze
import pandas as pd
np.random.seed(987654321)
df = pd.DataFrame(
{
'ID' : np.random.randint(10000, 50000, size=60).astype(str),
'One' ... |
6,849 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data input for BIDS datasets
DataGrabber and SelectFiles are great if you are dealing with generic datasets with arbitrary organization. However if you have decided to use Brain Imaging Data... | Python Code:
from bids.grabbids import BIDSLayout
layout = BIDSLayout("/data/ds102/")
!tree /data/ds102/
Explanation: Data input for BIDS datasets
DataGrabber and SelectFiles are great if you are dealing with generic datasets with arbitrary organization. However if you have decided to use Brain Imaging Data Structure (... |
6,850 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: k - means
Randomly select starting locations for k points
Assign data points to closest k point
If no data changed its cluster membership stop
If there was a change, compute new means... | Python Code:
class KMeans:
k-means algo
def __init__(self, k):
self.k = k # number of clusters
self.means = None # means of clusters
def classify(self, input):
return the index of the cluster to closest to input
return min(range(self.k),
key = ... |
6,851 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This script is dedicated to querying all needed statistics for the project.
Step1: Helpers
Step2: Distribution of job posts among job titles
Step3: Job posts distribution among standard j... | Python Code:
import my_util as my_util; from my_util import *
HOME_DIR = 'd:/larc_projects/job_analytics/'
DATA_DIR = HOME_DIR + 'data/clean/'
title_df = pd.read_csv(DATA_DIR + 'new_titles_2posts_up.csv')
Explanation: This script is dedicated to querying all needed statistics for the project.
End of explanation
def dis... |
6,852 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
making predictions for a regression problem
| Python Code::
from keras.models import Sequential
from keras.layers import Dense
from sklearn.datasets import make_regression
from sklearn.preprocessing import MinMaxScaler
from numpy import array
X, y = make_regression(n_samples=100, n_features=2, noise=0.1, random_state=1)
scalarX, scalarY = MinMaxScaler(), MinMaxSca... |
6,853 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Unit Models
Exploration of model for basic constituent units of a neural network.
Perceptron
Starting with the perceptron, an early version model based on binary inputs and step function.
St... | Python Code:
# weights
W = np.array([-2,-2])
# bias
b = 3
# threshold. Can be discarded using the bias instead (bias=-threshold)
#threshold = 3
# perceptron firing rule
perceptron = lambda x : 1 if np.dot(X, W) + b >0 else 0
# input array
X = np.array([1,1])
# compute perceptron output
perceptron(X)
Explanation: Unit M... |
6,854 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mini-Assignment 2
Step1: Let's have a look at what the data looks like for our example paper
Step5: Some Utility Functions
We'll define some utility functions that allow us to tokenize a s... | Python Code:
Summaries_file = 'data/malaria__Summaries.pkl.bz2'
Abstracts_file = 'data/malaria__Abstracts.pkl.bz2'
import pickle, bz2
from collections import namedtuple
Summaries = pickle.load( bz2.BZ2File( Summaries_file, 'rb' ) )
paper = namedtuple( 'paper', ['title', 'authors', 'year', 'doi'] )
for (id, paper_info) ... |
6,855 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Minimizing a <span style="font-variant
Step1: The function cart_prod(A, B) computes the Cartesian product $A \times B$ of the sets $A$ and $B$ where $A \times B$ is defined as follows
Step2... | Python Code:
def arb(M):
for x in M:
return x
assert False, 'Error: arb called with empty set!'
Explanation: Minimizing a <span style="font-variant:small-caps;">Fsm</span>
The function arb(M) takes a non-empty set M as its argument and returns an arbitrary element from this set.
The set M is not changed... |
6,856 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
API calls
Step1: Now, we can all the rows together to print the tweets with one run. Try/except is also added to except possible errors.
Step2: User tweets
The library also provides the op... | Python Code:
from TwitterSearch import *
with open('token.txt','r') as f:
token = f.read().split()
# pass your credentials to the TwitterSearch class to create and object called "ts"
ts = TwitterSearch(
consumer_key = token[0],
consumer_secret = token[1],
access_token = token[2],
access_token_secret = token[3]
)
ts... |
6,857 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SAM
This notebook explores parsing and understanding the SAM (Sequence Alignment/Map) and related BAM format. SAM is an extremely common format for representing read alignments. Most widel... | Python Code:
# Here's a string representing a three-line SAM file. I'm temporarily
# ignoring the fact that SAM files usually have several header lines at
# the beginning.
samStr = '''\
r1 0 gi|9626243|ref|NC_001416.1| 18401 42 122M * 0 0 TGAATGCGAACTCCGGGACGCTCAGTAATGTGACGATAGCTGAAAACTGTACGATAAACNGTACGCTGAGGGCAGAAAAA... |
6,858 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NumPy
문제1.
NumPy 명령을 사용하여 다음 행렬을 생성하는 코드를 1줄로 작성하세요.
Step1: 문제2.
X 행렬이 다음과 같을 때 NumPy 슬라이싱 인덱싱을 사용하여 행렬의 짝수 부분만을 선택하여 행렬로 만드는 NumPy코드를 작성하세요.(행렬 인덱싱을 사용하지 말 것!)
Step2: 문제3.
X행렬이 다음과 같을 때 행... | Python Code:
X = np.array([[11, 12], [21, 22], [31, 32]])
X
Explanation: NumPy
문제1.
NumPy 명령을 사용하여 다음 행렬을 생성하는 코드를 1줄로 작성하세요.
End of explanation
X = np.array([[1,1,1,1], [1,2,4,8], [1,3,5,7], [1,4,16,32], [1,5,9,13]])
X
X[1::2, 1:]
Explanation: 문제2.
X 행렬이 다음과 같을 때 NumPy 슬라이싱 인덱싱을 사용하여 행렬의 짝수 부분만을 선택하여 행렬로 만드는 NumPy코드를 ... |
6,859 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Part 1 - Setup
We will be using
* PIL (Python Image Library) for getting the picture
* pytesseract for the OCR (Object Character Recognition)
* googlemaps and gmaps for mapping
Step1: Pa... | Python Code:
from PIL import Image
import pytesseract
import googlemaps
import gmaps as jupmap
import sys
from datetime import datetime
# get my private keys for google maps and gmaps
f = open('private.key', 'r')
for line in f:
temp = line.rstrip('').replace(',','').replace('\n','').split(" ")
exec(temp[0])... |
6,860 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Übung 2
Problem 2.1 - Lineare Regression mit Least Squares
Step1: Numpy Dokumentation
Step2: Versuch zur Bestimmung einer linearen Gleichungsfunktion.
Hier wird die händische Berechnung du... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
plt.style.use('ggplot')
Explanation: Übung 2
Problem 2.1 - Lineare Regression mit Least Squares
End of explanation
def print_sample(genfromtxt):
# column names
print(genfromtxt.dtype.names)
# data
for row in genfromtxt[:min((len(g... |
6,861 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning - Hands on Lab - Session #1
Lecturer
Step1: 2. Re-Import the Check NaN Function from Part 2
Step2: 3. Loading in the Data from Session #2
Step3: 3. Transforming Categoric... | Python Code:
import os
from datetime import datetime
import numpy as np
import pandas as pd
import sklearn as sk
Explanation: Machine Learning - Hands on Lab - Session #1
Lecturer: Jonathan DEKHTIAR
Date: 2017-03-13
<br/><br/>
Contact: contact@jonathandekhtiar.eu
Twitter: @born2data
LinkedIn: JonathanDEKHTIAR
Personal ... |
6,862 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python
Python présente plusieurs avantage à l'origine de son choix pour ce cours
Step1: Nombres
Step2: Chaînes de caractères
Step3: Listes et dictionnaires
Step4: Structures de contrôle ... | Python Code:
print 'Hello World !'
a = 5.
b = 7.
a + b
Explanation: Python
Python présente plusieurs avantage à l'origine de son choix pour ce cours:
C'est un langage généraliste présent dans de nombreuses domaines: calcul scientifique, web, bases de données, jeu vidéo, graphisme, etc. C'est un outil polyvalent qu'un i... |
6,863 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian Statistics
Step1: Is that counter-intuitive? Not really... The false positive rate is actually fairly high, and with the numbers as given, the chance is about ten times higher that... | Python Code:
P_positive_if_ill = .99
P_positive_if_notill = .01
P_ill = 1.e-3
P_notill = 1 - P_ill
print("P_ill_if_positive = ",
P_positive_if_ill * P_ill / (P_positive_if_ill * P_ill + P_positive_if_notill * P_notill ))
Explanation: Bayesian Statistics: the what, the why, and the how
This notebook contains illu... |
6,864 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Auto-Batched Joint Distributions
Step1: <table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: 전제 조건
Step3: 데시데라타(Desiderata)
확률적 추론에서는 종종 두 가지... | 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... |
6,865 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiment logger
The logger stores experimental data in a single SQLite database. It is intended to be fast and lightweight, but record all necessary meta data and timestamps for experiment... | Python Code:
# import sqlexperiment as sqle
# from sqlexperiment import experimentlog
from explogger import ExperimentLog
# log some JSON data
e = ExperimentLog(":memory:", ntp_sync=False)
e.log("mouse", data={"x":0, "y":0})
e.log("mouse", data={"x":0, "y":1})
e.log("mouse", data={"x":0, "y":2})
e.close()
# from experi... |
6,866 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Кафедра дискретной математики МФТИ
Курс математической статистики
Никита Волков
На основе http
Step1: Можно преобразовать список в массив.
Step2: print печатает массивы в удобной форме.
St... | Python Code:
import numpy as np
Explanation: Кафедра дискретной математики МФТИ
Курс математической статистики
Никита Волков
На основе http://www.inp.nsk.su/~grozin/python/
Библиотека numpy
Пакет numpy предоставляет $n$-мерные однородные массивы (все элементы одного типа); в них нельзя вставить или удалить элемент в пр... |
6,867 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Batch Normalization – Practice
Batch normalization is most useful when building deep neural networks. To demonstrate this, we'll create a convolutional neural network with 20 convolutional l... | Python Code:
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True, reshape=False)
Explanation: Batch Normalization – Practice
Batch normalization is most useful when building deep neural networks. To demonstrate this, we'll crea... |
6,868 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
==============================================
Read and visualize projections (SSP and other)
==============================================
This example shows how to read and visualize Sign... | Python Code:
# Author: Joan Massich <mailsik@gmail.com>
#
# License: BSD (3-clause)
import matplotlib.pyplot as plt
import mne
from mne import read_proj
from mne.io import read_raw_fif
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
subjects_dir = data_path + '/subjects'
fname = data_path ... |
6,869 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Built-in plotting methods for Raw objects
This tutorial shows how to plot continuous data as a time series, how to plot
the spectral density of continuous data, and how to plot the sensor lo... | Python Code:
import os
import mne
sample_data_folder = mne.datasets.sample.data_path()
sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
'sample_audvis_raw.fif')
raw = mne.io.read_raw_fif(sample_data_raw_file)
raw.crop(tmax=60).load_data()
Explanation: Built-in... |
6,870 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Installation
Ideally, before installation, create a clean python3 virtual environment to deploy the package, using virtualenvwrapper for example (see http
Step1: Installation with pip from ... | Python Code:
#### REMOVE in README.md ####
import JGV as package
from IPython.core.display import display, Markdown
if "__install_requires__" in package.__dict__:
display(Markdown("## Python packages dependencies:\n"))
for dep in package.__install_requires__:
display(Markdown("* {}\n".format(dep)))
####... |
6,871 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Relationships in the GO
Alex Warwick Vesztrocy, March 2016
For some analyses, it is possible to only use the <code>is_a</code> definitions given in the Gene Ontology.
However, it is importa... | Python Code:
import os
from goatools.obo_parser import GODag
if not os.path.exists('go-basic.obo'):
!wget http://geneontology.org/ontology/go-basic.obo
go = GODag('go-basic.obo', optional_attrs=['relationship'])
Explanation: Relationships in the GO
Alex Warwick Vesztrocy, March 2016
For some analyses, it is possibl... |
6,872 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="../static/images/iterables.png" width="240">
Iterables
Some steps in a neuroimaging analysis are repetitive. Running the same preprocessing on multiple subjects or doing statistic... | Python Code:
from nipype import Node, Workflow
from nipype.interfaces.fsl import BET, IsotropicSmooth
# Initiate a skull stripping Node with BET
skullstrip = Node(BET(mask=True,
in_file='/data/ds000114/sub-01/ses-test/anat/sub-01_ses-test_T1w.nii.gz'),
name="skullstrip")
Explanat... |
6,873 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 The TensorFlow Hub Authors.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: Transfer Learning for the Audio Domain with Model Maker
In this notebook, y... | Python Code:
# Copyright 2021 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... |
6,874 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sorting Objects in Instance Catalogs
Bryce Kalmbach
This notebook provides a series of commands that take a Twinkles Phosim Instance Catalog and creates different pandas dataframes for diffe... | Python Code:
import pandas as pd
import numpy as np
Explanation: Sorting Objects in Instance Catalogs
Bryce Kalmbach
This notebook provides a series of commands that take a Twinkles Phosim Instance Catalog and creates different pandas dataframes for different types of objects in the catalog. It first separates the full... |
6,875 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression (predicting unmasked value given (x, y, z, synapses))
Step 1
Step1: Now graphing this data
Step2: Step 4/5/6 part b
Step3: Now graphing it
Step4: Step 7 | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import urllib2
%matplotlib inline
sample_size = 10000
k_fold = 10
np.random.seed(1)
url = ('https://raw.githubusercontent.com/Upward-Spiral-Science'
'/data/master/syn-density/output.csv')
data = urllib2.urlopen(url)
csv = np.genfromtxt(data, delimit... |
6,876 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transfer Learning
Most of the time you won't want to train a whole convolutional network yourself. Modern ConvNets training on huge datasets like ImageNet take weeks on multiple GPUs. Instea... | Python Code:
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
vgg_dir = 'tensorflow_vgg/'
# Make sure vgg exists
if not isdir(vgg_dir):
raise Exception("VGG directory doesn't exist!")
class DLProgress(tqdm):
last_block = 0
def hook(self, block_num=1, block_size=... |
6,877 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Table de matières<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Un-exercice-d'algorithmique---mise-en-page-de-paragraphe,-résolutions-gourma... | Python Code:
%%bash
cat << EOF
AA AA AA AA AA AA B ;
AA AA AA AA AA AA B ;
EOF > /tmp/test_nongreedy_optimal.txt
cat /tmp/test_nongreedy_optimal.txt
%%bash
cat << EOF
AA AA AA AA AA AA B AA AA AA AA AA AA ;
B ;
EOF > test_greedy_suboptimal.txt
ca... |
6,878 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You are currently looking at version 1.2 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
df = pd.read_csv('olympics.csv', index_col=0, skiprows=1)
for col in df.columns:
if col[:2]=='01':
df.rename(columns={col:'Gold'+col[4:]}, inplace=True)
if col[:2]=='02':
df.rename(columns={col:'Silver'+col[4:]}, inplace=True)
if col[:2]=='03':
df.ren... |
6,879 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Solving the Cournot Oligopoly Model by Collocation
DEMAPP09 Cournot Oligopolist Problem
<br>
This example is taken from section 6.8.1, page(s) 159-162 of
Step1: and set the $\alpha$ and $\e... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from compecon import BasisChebyshev, NLP, nodeunif
from compecon.demos import demo
Explanation: Solving the Cournot Oligopoly Model by Collocation
DEMAPP09 Cournot Oligopolist Problem
<br>
This example is taken from section 6.8.1, page(s... |
6,880 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dolsek and Fajfar (2004)
This methodology makes use of work by Dolsek and Fajfar (2004) to estimate the inelastic displacement of a SDOF system based on its elastic displacement and the prop... | Python Code:
from rmtk.vulnerability.derivation_fragility.R_mu_T_no_dispersion.dolsek_fajfar import DF2004
from rmtk.vulnerability.common import utils
%matplotlib inline
Explanation: Dolsek and Fajfar (2004)
This methodology makes use of work by Dolsek and Fajfar (2004) to estimate the inelastic displacement of a SDOF... |
6,881 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Отчет по Лабоработной работе №3
Результаты определения параметров кэш-памяти
Описание процессора моего ноутбука с сайта cpu-world.com
Step1: Графики по данным, полученным из main_tooled.cpp... | Python Code:
%matplotlib inline
from matplotlib import pyplot
def prepare_stats(path='compact_report_stats.txt'):
graph = dict()
curStats = list()
for line in open(path):
k,v = map(str.strip, line.strip().split('='))
if k == 'n':
curStats = dict()
graph.setdefault(int... |
6,882 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright © 2020 The TensorFlow Authors.
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 ... | Python Code:
try:
import colab
!pip install --upgrade pip
except:
pass
!pip install -Uq tfx==0.25.0
!pip install -Uq tensorflow-text # The tf-text version needs to match the tf version
print("Restart your runtime enable after installing the packages")
Explanation: Copyright © 2020 The TensorFlow Autho... |
6,883 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Install Dependencies
First install the libraries needed to execute recipes, this only needs to be done once, then click play.
Step1: 2. Get Cloud Project ID
To run this recipe requires a... | Python Code:
!pip install git+https://github.com/google/starthinker
Explanation: 1. Install Dependencies
First install the libraries needed to execute recipes, this only needs to be done once, then click play.
End of explanation
CLOUD_PROJECT = 'PASTE PROJECT ID HERE'
print("Cloud Project Set To: %s" % CLOUD_PROJECT)
E... |
6,884 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook implements an array-based version of Heapsort.
Heapsort
The function call swap(A, i, j) takes an array A and two indexes i and j and exchanges the elements at these indexes.
S... | Python Code:
def swap(A, i, j):
A[i], A[j] = A[j], A[i]
Explanation: This notebook implements an array-based version of Heapsort.
Heapsort
The function call swap(A, i, j) takes an array A and two indexes i and j and exchanges the elements at these indexes.
End of explanation
def sink(A, k, n):
while 2 * k + 1 ... |
6,885 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Average driving speed against GDP
In this post I will attempt to combine two datasets I have worked on. Firstly the Average driving speeds by country as estimated by Google's location API, a... | Python Code:
df_GDP = pd.read_csv("../data_sets/GDP_by_Country_WorldBank/ny.gdp.mktp.cd_Indicator_en_csv_v2.csv",
quotechar='"', skiprows=2)
colnames_to_drop = df_GDP.columns[np.array([2, 3, -2, -1])]
for c in colnames_to_drop:
df_GDP.drop(c, 1, inplace=True)
df_GDP = df_GDP[~df_GDP['Country ... |
6,886 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. _ builtin _ 模块
1.1 apply
Step1: 效果等同于：
Step2: 那为什么要使用apply呢？
Step3: 何谓“关键字参数”？
apply使用字典传递关键字参数，实际上就是字典的键是函数的参数名，字典的值是函数的实际参数值。（相对于形参和实参）
根据上面的例子看，如果部分传递，只能传递后面的关键字参数，不能传递前面的。？？？？
a... | Python Code:
def function(a,b):
print a, b
apply(function, ("wheather", "Canada?"))
apply(function, (1, 3+5))
Explanation: 1. _ builtin _ 模块
1.1 apply:使用元组或字典中的参数调用函数
Python 允许你实时地创建函数参数列表. 只要把所有的参数放入一个元组中，然后通过内建的 apply 函数调用函数.
End of explanation
function("wheather", "Canada?")
function(1, 3+5)
Explanation: 效果等同于：... |
6,887 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
author
Step1: Let's try plotting the results. We first need to import the required libraries and methods
Step2: Next, we create numpy arrays to store the (x,y) values
Step3: We have to re... | Python Code:
T0 = 10. # initial temperature
Ts = 83. # temp. of the environment
r = 0.1 # cooling rate
dt = 0.05 # time step
tmax = 60. # maximum time
nsteps = int(tmax/dt) # number of steps
T = T0
for i in range(1,nsteps+1):
new_T = T - r*(T-Ts)*dt
T = new_T
print i,i*dt, T
# we can also do t ... |
6,888 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lecture 8
Step1: Indexing would still work as you would expect, but looping through a matrix--say, to do matrix multiplication--would be laborious and highly inefficient.
We'll demonstrate ... | Python Code:
matrix = [[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9] ]
print(matrix)
Explanation: Lecture 8: Advanced Data Structures
CBIO (CSCI) 4835/6835: Introduction to Computational Biology
Overview and Objectives
Before we get to some of the more advanced sequence analysis techniques, we need to cover s... |
6,889 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
304 - Medical Entity Extraction with a BiLSTM
In this tutorial we use a Bidirectional LSTM entity extractor from the MMLSPark
model downloader to extract entities from PubMed medical abstrac... | Python Code:
from mmlspark import CNTKModel, ModelDownloader
from pyspark.sql.functions import udf, col
from pyspark.sql.types import IntegerType, ArrayType, FloatType, StringType
from pyspark.sql import Row
from os.path import abspath, join
import numpy as np
import pickle
from nltk.tokenize import sent_tokenize, word... |
6,890 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="http
Step1: 1. Create the river network model grid
First, we need to create a Landlab NetworkModelGrid to represent the river network. Each link on the grid represents a reach of r... | Python Code:
import warnings
warnings.filterwarnings("ignore")
import matplotlib.pyplot as plt
import numpy as np
from landlab.components import FlowDirectorSteepest, NetworkSedimentTransporter
from landlab.data_record import DataRecord
from landlab.grid.network import NetworkModelGrid
from landlab.plot import graph
fr... |
6,891 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Representing Data and Engineering Features
Categorical Variables
One-Hot-Encoding (Dummy variables)
Step1: Checking string-encoded categorical data
Step2: Numbers can encode categoricals
S... | Python Code:
import pandas as pd
# The file has no headers naming the columns, so we pass header=None and provide the column names explicitly in "names"
data = pd.read_csv("data/adult.data", header=None, index_col=False,
names=['age', 'workclass', 'fnlwgt', 'education', 'education-num',
... |
6,892 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Self-Driving Car Engineer Nanodegree
Project
Step1: Read in an Image
Step9: Ideas for Lane Detection Pipeline
Some OpenCV functions (beyond those introduced in the lesson) that might be us... | Python Code:
#importing some useful packages
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import cv2
%matplotlib inline
Explanation: Self-Driving Car Engineer Nanodegree
Project: Finding Lane Lines on the Road
In this project, you will use the tools you learned about in the lesson... |
6,893 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Data setup</h1>
<h2>Use our function to read the data file</h2>
Step1: <h1>Plotting data on google maps</h1>
<h2>gmplot library</h2>
https
Step2: <h3>Our data dataframe contains latitu... | Python Code:
def read_311_data(datafile):
import pandas as pd
import numpy as np
#Add the fix_zip function
def fix_zip(input_zip):
try:
input_zip = int(float(input_zip))
except:
try:
input_zip = int(input_zip.split('-')[0])
except:... |
6,894 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced
Step1: Let's get started with some basic imports.
Step2: Overriding Computation Times
If compute_times is not empty (by either providing compute_times or compute_phases), the prov... | Python Code:
#!pip install -I "phoebe>=2.3,<2.4"
Explanation: Advanced: compute_times & compute_phases
Setup
Let's first make sure we have the latest version of PHOEBE 2.3 installed (uncomment this line if running in an online notebook session such as colab).
End of explanation
import phoebe
from phoebe import u # unit... |
6,895 | 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 = '/Users/Slimn/Desktop/Work/Project/Udacity/NanoDegree/P0/chopstick-... |
6,896 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What is the True Normal Human Body Temperature?
Background
The mean normal body temperature was held to be 37$^{\circ}$C or 98.6$^{\circ}$F for more than 120 years since it was first concept... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
df = pd.read_csv('data/human_body_temperature.csv')
df.head()
Explanation: What is the True Normal Human Body Temperature?
Background
The mean normal body temperature was held to be 37$^{\circ}$C or 98.6$^{\circ}... |
6,897 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
说明
目的： 为探讨在同一个样本点集下，cma-es算法对$f(x)$拟合效果与分段数的关系，实验记录每个分段方案下cma-es过程的迭代时间，关系矩阵变化过程，计算结果，cpu计算时间等进行对比。
函数：
<center>$ f(x)=10sin0.6x+uniform(-1.5,1.5)gauss(0,5),x \in[-7,7)$ </center>
分段： ... | Python Code:
import makeData as md
%pylab inline
plt.rc('figure', figsize=(16, 9))
X=md.loadData('result.tl')
import numpy as np
import pandas as pd
b=[]
for i in range(5,35,5):
temp=[]
for j in range(3):
temp.append(X[i][j]['iter'])
b.append(temp)
bs=np.array(b).T
ind=range(5,35,5)
d={'M1':pd.Serie... |
6,898 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent neural network that performs sentiment analysis. Using an RNN rather than a feedfoward network is more accurate ... | Python Code:
import numpy as np
import tensorflow as tf
with open('../sentiment_network/reviews.txt', 'r') as f:
reviews = f.read()
with open('../sentiment_network/labels.txt', 'r') as f:
labels = f.read()
reviews[:2000]
Explanation: Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent ... |
6,899 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Executed
Step1: The data has been generated by running the template notebook
usALEX-5samples-PR-raw-dir_ex_aa-fit-AexAem
for each sample.
To recompute the PR data used by this notebook run ... | Python Code:
data_file = 'results/usALEX-5samples-PR-raw-dir_ex_aa-fit-AexAem.csv'
Explanation: Executed: Mon Mar 27 11:38:35 2017
Duration: 3 seconds.
Direct ecitation coefficient fit
This notebook estracts the direct excitation coefficient from the set of 5 us-ALEX smFRET measurements.
What it does?
This notebook per... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.