Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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10,000 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The ELS matching procedure
This practical is based on the concepts introduced for optimising electrical contacts in photovoltaic cells. The procedure was published in [J. Mater. Chem. C (201... | Python Code:
%%bash
cd Electronic/
python scan_energies.py -h
Explanation: The ELS matching procedure
This practical is based on the concepts introduced for optimising electrical contacts in photovoltaic cells. The procedure was published in [J. Mater. Chem. C (2016)]((http://pubs.rsc.org/en/content/articlehtml/2016/tc... |
10,001 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sklearn
sklearn.datasets
документация
Step1: Генерация выборок
Способы генерации данных
Step2: datasets.make_classification
Step3: "Игрушечные" наборы данных
Наборы данных
Step4: Визуали... | Python Code:
from sklearn import datasets
%pylab inline
Explanation: Sklearn
sklearn.datasets
документация: http://scikit-learn.org/stable/datasets/
End of explanation
circles = datasets.make_circles()
print "features: {}".format(circles[0][:10])
print "target: {}".format(circles[1][:10])
from matplotlib.colors import ... |
10,002 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div class="alert alert-block alert-info" style="margin-top
Step1: <a id="ref0"></a>
<h2 align=center>What is Convolution?</h2>
Convolution is a linear operation similar to a linear equatio... | Python Code:
import torch
import torch.nn as nn
import matplotlib.pyplot as plt
import numpy as np
from scipy import ndimage, misc
Explanation: <div class="alert alert-block alert-info" style="margin-top: 20px">
<a href="http://cocl.us/pytorch_link_top"><img src = "http://cocl.us/Pytorch_top" width = 950, align = "ce... |
10,003 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Learning to speak like Alice
A generative character based language model is created by training an RNN on the text of Alice in Wonderland.
Setup Imports
Step1: Read input
Step2: Build voca... | Python Code:
from __future__ import division, print_function
from keras.layers.recurrent import SimpleRNN
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.utils.visualize_util import plot
import numpy as np
%matplotlib inline
Explanation: Learning to speak like Alice
A generativ... |
10,004 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Extract Landmarks Data in Melbourne from Wikipedia Interactively
<a id=toc>
Extract landmarks data
Step1: URL for the landmarks in the Melbourne city centre.
Step3: Extract POI coordinates... | Python Code:
%matplotlib inline
import requests, re, os
from bs4 import BeautifulSoup
from bs4.element import Tag
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import lxml
from fastkml import kml, styles
from shapely.geometry import Point
Explanation: Extract Landmarks Data in Melbourne from Wi... |
10,005 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualization 1
Step1: Scatter plots
Learn how to use Matplotlib's plt.scatter function to make a 2d scatter plot.
Generate random data using np.random.randn.
Style the markers (color, size... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Explanation: Visualization 1: Matplotlib Basics Exercises
End of explanation
# This assignment wasn't graded for some reason, having a 0.0/0.0 score. Resubmitting the assignment for grading on this one
# as well as on the Theory and Prac... |
10,006 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Word embeddings
Import various modules that we need for this notebook (now using Keras 1.0.0)
Step1: Load the MNIST dataset, flatten the images, convert the class labels, and scale the data... | Python Code:
%pylab inline
import copy
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from keras.datasets import imdb, reuters
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.optimizers import SGD, RMSprop
from keras.utils import n... |
10,007 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load and Split Kaggle Data
Step1: Build baseline text classification model in Sklearn
Step2: This is about as good as the best Kagglers report they did.
Step3: Score Random Wikipedia Use... | Python Code:
data_filename = '../data/train.csv'
data_df = pd.read_csv(data_filename)
corpus = data_df['Comment']
labels = data_df['Insult']
train_corpus, test_corpus, train_labels, test_labels = \
sklearn.cross_validation.train_test_split(corpus, labels, test_size=0.33)
Explanation: Load and Split Kaggle Data
End of... |
10,008 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Pandas
pandas is a Python package providing fast, flexible, and expressive data structures designed to work with relational or labeled data both. It is a fundamental high-lev... | Python Code:
from IPython.core.display import HTML
HTML("<iframe src=http://pandas.pydata.org width=800 height=350></iframe>")
%matplotlib inline
import pandas as pd
import numpy as np
# Set some Pandas options
pd.set_option('html', False)
pd.set_option('max_columns', 30)
pd.set_option('max_rows', 20)
Explanation: Intr... |
10,009 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 高级自动微分
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 控制梯度记录
在自动微分指南中，您已了解构建梯度计算时如何控制条带监视变量和张量。... | 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... |
10,010 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Digit Recognizer
Import Libraries
Step1: Loading Data
Step2: Plotting images and their class values
Step3: Viewing shape and content of data
Step4: Flattening images
The neural-network t... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
from keras.utils import np_utils
from keras.datasets import mnist
# for Multi-layer Perceptron (MLP) model
from keras.models import Sequential
from keras.layers import Dense
# for Convolutional Neural Network (CNN) mo... |
10,011 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
基本的登陆
Step1: sending cookie
Step2: Re-direction
302 means the URL has been redirected to some other location. We could use allow_redirects=False to disable this feature.
Step3: time out
S... | Python Code:
url='http://httpbin.org'
req=requests.get(url+'/basic-auth/user/passwd',auth=('user','passwd'))
print(req.text)
print(req.url)
print(req.status_code)
import json
payload={'some':'data'}
headers={'Content-Type':'application/json','Authorization':'some token'}
req=requests.post(url+'/post',data=json.dumps(pa... |
10,012 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
tacotron2
Step1: Run tacotron2
Step2: speech contains the raw waveform and sampling rate, which can be played back.
Step3: You can also plot the waveform. | Python Code:
%tensorflow_version 1.x
!pip3 install --quiet ml4a
Explanation: tacotron2: Text-to-speech synthesis
Generates speech audio from a text string. See the original code and paper.
Set up ml4a and enable GPU
If you don't already have ml4a installed, or you are opening this in Colab, first enable GPU (Runtime > ... |
10,013 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Manual sanity checks for the formula and text within mmrd.tex
Check fitting formula by hand, and compare with raw data
Step1: Load data file that contains QNM amplitudes from fitting algori... | Python Code:
%matplotlib inline
from numpy import exp,sqrt,log,linspace,pi,sin
import kerr
from os import system
import matplotlib as mpl
from matplotlib.pyplot import *
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['font.family'] = 'serif'
mpl.rcParams['font.size'] = 12
mpl.rcParams['axes.labelsize'] = 20
mpl.rcPar... |
10,014 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Encontro 05
Step1: Configurando a biblioteca
Step2: O objetivo desta atividade é realizar $24$ simulações de centralidade diferentes, para avaliar o desempenho de medidas clássicas em rela... | Python Code:
import sys
sys.path.append('..')
import socnet as sn
Explanation: Encontro 05: Simulação de Centralidades
Importando a biblioteca:
End of explanation
sn.node_size = 10
sn.edge_width = 1
sn.edge_color = (192, 192, 192)
sn.node_label_position = 'top center'
Explanation: Configurando a biblioteca:
End of expl... |
10,015 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 3
We're going to switch gears a little and talk about the astrophysical part of Astrophysical Machine Learning. This exercise will have you examine two different forms of data. The ... | Python Code:
from astropy.io import fits as fits
fitsimage=fits.open('filename.fits')
image=np.flipud(fitsimage[0].data)
Explanation: Exercise 3
We're going to switch gears a little and talk about the astrophysical part of Astrophysical Machine Learning. This exercise will have you examine two different forms of data. ... |
10,016 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
6b Calculate binned gradient-network overlap
This file works out the average z-score inside a gradient percentile area
written by Jan Freyberg for the Brainhack 2017 Project_
This should rep... | Python Code:
% matplotlib inline
from __future__ import print_function
import nibabel as nib
from nilearn.image import resample_img
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import os
import os.path
# The following are a progress bar, these are not strictly necessary:
from ipywidgets impor... |
10,017 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Model Evaluation
Pipeline and Feature Unions
It is always a good decision to make your code as readable as possible. Not only so that others can pick it up and use it easily, but so that yo... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.utils import resample
from sklearn.preprocessing import PolynomialFeatures, StandardScaler, LabelEncoder, OneHotEncoder
from ... |
10,018 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This note book gives the trend of a single word in single mailing list.
Step1: You'll need to download some resources for NLTK (the natural language toolkit) in order to do the kind of proc... | Python Code:
%matplotlib inline
from bigbang.archive import Archive
import bigbang.parse as parse
import bigbang.graph as graph
import bigbang.mailman as mailman
import bigbang.process as process
import networkx as nx
import matplotlib.pyplot as plt
import pandas as pd
from pprint import pprint as pp
import pytz
import... |
10,019 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The goal of punk is to make available sime wrappers for a variety of machine learning pipelines.
The pipelines are termed primitves and each primitive is designed with a functional programmi... | Python Code:
import punk
help(punk)
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from sklearn import datasets
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from punk import feature_select... |
10,020 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cross Spectra
This tutorial shows how to make and manipulate a cross spectrum of two light curves using Stingray.
Step1: 1. Create two light curves
There are two ways to make Lightcurve obj... | Python Code:
import numpy as np
from stingray import Lightcurve, Crossspectrum, AveragedCrossspectrum
import matplotlib.pyplot as plt
import matplotlib.font_manager as font_manager
%matplotlib inline
font_prop = font_manager.FontProperties(size=16)
Explanation: Cross Spectra
This tutorial shows how to make and manipula... |
10,021 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import necessary libraries
Step1: K-means clustering
Example adapted from here.
Load dataset
Step2: Define and train model
Step3: Extract the labels and the cluster centers
Step4: Plot t... | Python Code:
import numpy as np
from scipy import ndimage
from time import time
from sklearn import datasets, manifold
from sklearn.cluster import KMeans, AgglomerativeClustering
from sklearn.mixture import GMM
from sklearn.cross_validation import StratifiedKFold
import matplotlib.pyplot as plt
import matplotlib as mpl... |
10,022 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Probability Authors.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: TensorFlow Distributions
Step2: Basic Univariate Distributions
Let... | 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... |
10,023 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ensemble Learning
<!-- new sections -->
<!-- Ensemble learning -->
<!-- - Machine Learning Flach, Ch.11 -->
<!-- - Machine Learning Mohri, pp.135- -->
<!-- - Data Mining Witten, Ch. 8 -->
St... | Python Code:
from IPython.display import Image
Image('../../../python_for_probability_statistics_and_machine_learning.jpg')
from pprint import pprint
import textwrap
import sys, re
def displ(x):
if x is None: return
print ("\n".join(textwrap.wrap(repr(x).replace(' ',''),width=80)))
sys.displayhook=displ
Explanat... |
10,024 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Construct the metadata just based on the headers
Step1: Add the frame types as we've always done
Step2: Find the unique configurations. The unique configurations are found by matching dat... | Python Code:
fitstbl = PypeItMetaData('keck_lris_red', file_list=file_list, background_index=True)
Explanation: Construct the metadata just based on the headers
End of explanation
_ = fitstbl.get_frame_types(flag_unknown=True)
Explanation: Add the frame types as we've always done
End of explanation
cfgs = fitstbl.uniqu... |
10,025 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import required packages
Step1: Download and Prep NASA's Turbofan Engine Degradation Simulation (PHM08 Challenge) Data Set
Step2: Read training data into a DataFrame.
Step3: Create traini... | Python Code:
import os
import matplotlib.pyplot as plt
import pandas as pd
import swat # SAS Viya Python interface
%matplotlib inline
Explanation: Import required packages
End of explanation
DATA_URL = 'https://ti.arc.nasa.gov/m/project/prognostic-repository/Challenge_Data.zip'
DATA_DIR = '.'
train_tsv = os.path.join... |
10,026 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LAB 5a
Step1: Import necessary libraries.
Step2: Set environment variables.
Set environment variables so that we can use them throughout the entire lab. We will be using our project name f... | Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
!pip3 install cloudml-hypertune
Explanation: LAB 5a: Training Keras model on Cloud AI Platform
Learning Objectives
Setup up the environment
Create trainer module's task.py to hold hyperparameter argparsing code
Create trainer module's mode... |
10,027 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using a random forest for demographic model selection
In Schrider and Kern (2017) we give a toy example of demographic model selection via supervised machine learning in Figure Box 1. Follow... | Python Code:
#untar and compile ms and sample_stats
!tar zxf ms.tar.gz; cd msdir; gcc -o ms ms.c streec.c rand1.c -lm; gcc -o sample_stats sample_stats.c tajd.c -lm
#I get three compiler warnings from ms, but everything should be fine
#now I'll just move the programs into the current working dir
!mv msdir/ms . ; mv msd... |
10,028 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
06 - Data Preparation and Advanced Model Evaluation
by Alejandro Correa Bahnsen
version 0.2, May 2016
Part of the class Machine Learning for Security Informatics
This notebook is licensed un... | Python Code:
import pandas as pd
import zipfile
with zipfile.ZipFile('../datasets/titanic.csv.zip', 'r') as z:
f = z.open('titanic.csv')
titanic = pd.read_csv(f, sep=',', index_col=0)
titanic.head()
# check for missing values
titanic.isnull().sum()
Explanation: 06 - Data Preparation and Advanced Model Evaluatio... |
10,029 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 12
Step1: If you want to create a tuple with a single value, add a comma (,) after the value, but don’t add parenthesis
You can also use the built in function tuple
Step2: Most lis... | Python Code:
a_tuple = ( 'a', 'b', 'c', 'd', 'e' )
a_tuple = 'a', 'b', 'c', 'd', 'e'
a_tuple = 'a',
type( a_tuple )
Explanation: Chapter 12: Tuples
Contents
- Tuples are immutable
- Tuple assignment
- Tuples as return values
- Variable-length argument tuples
- Lists and tuples
- Dictionaries and tuples
- Comparing tupl... |
10,030 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Name
Data preparation using SparkSQL on YARN with Cloud Dataproc
Label
Cloud Dataproc, GCP, Cloud Storage, YARN, SparkSQL, Kubeflow, pipelines, components
Summary
A Kubeflow Pipeline compo... | Python Code:
%%capture --no-stderr
KFP_PACKAGE = 'https://storage.googleapis.com/ml-pipeline/release/0.1.14/kfp.tar.gz'
!pip3 install $KFP_PACKAGE --upgrade
Explanation: Name
Data preparation using SparkSQL on YARN with Cloud Dataproc
Label
Cloud Dataproc, GCP, Cloud Storage, YARN, SparkSQL, Kubeflow, pipelines, compo... |
10,031 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Q 5.1
Step1: (a) The squared reconstruction error vs iteration number.
Step2: (b) Let us say that the number of assignments for a mean is the number of points assigned to that
mean. Plot t... | Python Code:
km_16 = KMeans(k=16, train_X=X_train, train_y=y_train,
pca_obj=pca_training,
max_iter = 500,
test_X=X_test, test_y=y_test,
verbose=False)
km_16.run()
Explanation: Q 5.1:
k = 16, MNIST data transformed by first 50 PCA components.
End of explanation
km_16_rec... |
10,032 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
We're going to improve the tweet_enricher.py script from Gnip-Analysis-Pipeline. We'll make a simplified version and create variations that improve it in various ways.
To enric... | Python Code:
DT_FORMAT_STR = "%Y-%m-%dT%H:%M:%S.%f"
def stream_of_tweets(n=10):
# generator function to generate sequential tweets
for i in range(n):
time.sleep(0.01)
tweet = {
'body':'I am tweet #' + str(i),
'postedTime':datetime.datetime.now().strftime(DT_FORMAT_STR) ... |
10,033 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lab 4 - Tensorflow ANN for regression
In this lab we will use Tensorflow to build an Artificial Neuron Network (ANN) for a regression task.
As opposed to the low-level implementation from th... | Python Code:
%matplotlib inline
import math
import random
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import load_boston
import numpy as np
import tensorflow as tf
sns.set(style="ticks", color_codes=True)
Explanation: Lab 4 - Tensorflow ANN for regression
In this lab ... |
10,034 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Management
In this guide you will learn how to load different data files into DataFrames and how to interact with the CARTO platform to upload DataFrames into tables and download tables... | Python Code:
from geopandas import read_file
gdf = read_file('https://libs.cartocdn.com/cartoframes/samples/starbucks_brooklyn_geocoded.geojson')
gdf.head()
Explanation: Data Management
In this guide you will learn how to load different data files into DataFrames and how to interact with the CARTO platform to upload Da... |
10,035 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compile and deploy the TFX pipeline to Kubeflow Pipelines
This notebook is the second of two notebooks that guide you through automating the Real-time Item-to-item Recommendation with BigQue... | Python Code:
%load_ext autoreload
%autoreload 2
!pip install -q -U kfp
Explanation: Compile and deploy the TFX pipeline to Kubeflow Pipelines
This notebook is the second of two notebooks that guide you through automating the Real-time Item-to-item Recommendation with BigQuery ML Matrix Factorization and ScaNN solution ... |
10,036 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading and writing files
Step1: It says that the file is opened, reminds the filename and indicates that it is in mode 'r', which means 'read'
You can call specific functions on an object ... | Python Code:
# We can create a file object and store it inside a variable.
# you can see objects as a different type of data
f=open("awanode-farmlab-2017-08-14.txt")
print(f)
Explanation: Reading and writing files
End of explanation
f=open("awanode-farmlab-2017-08-14.txt")
# The read() function reads the content of a f... |
10,037 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
XML example and exercise
study examples of accessing nodes in XML tree structure
work on exercise to be completed and submitted
reference
Step1: XML example
for details about tree travers... | Python Code:
from xml.etree import ElementTree as ET
import pandas as pd
Explanation: XML example and exercise
study examples of accessing nodes in XML tree structure
work on exercise to be completed and submitted
reference: https://docs.python.org/2.7/library/xml.etree.elementtree.html
data source: http://www.dbis.i... |
10,038 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create dataframe
Step2: Make plot | Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
Explanation: Title: Back To Back Bar Plot In MatPlotLib
Slug: matplotlib_back_to_back_bar_plot
Summary: Back To Back Bar Plot In MatPlotLib
Date: 2016-05-01 12:00
Category: Python
Tags: Data Visualization
Authors: Chr... |
10,039 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chem 30324, Spring 2020, Homework 7
Due March 27, 2020
Variations on the hydrogen atom
Step1: So the normalized 1s wavefunction is $\tilde{R}_{10}(r) = \frac{2}{\sqrt[4]{\pi}} 2^{\frac{3}{4... | Python Code:
import sympy as sy
import numpy as np
from sympy import *
r = Symbol('r')
I = integrate(exp(-2*r**2)*r**2,(r,0,+oo))
C = sqrt(1/I)
print(latex(simplify(C)))
Explanation: Chem 30324, Spring 2020, Homework 7
Due March 27, 2020
Variations on the hydrogen atom:
The variational principle guarantees that the exp... |
10,040 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Populate local MDCS instance with student data and metadata
Import MDCS API tool module
Step1: Host and user information
Step2: List of file prefixes for micrograph images and XML metadata... | Python Code:
import mdcs
Explanation: Populate local MDCS instance with student data and metadata
Import MDCS API tool module
End of explanation
user='admin'
pswd='admin'
host='http://127.0.0.1:8000'
template_name='DiffusionDemo'
Explanation: Host and user information
End of explanation
name_list=[
"GE-DiffusionCou... |
10,041 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Rational approximations of 𝝿
The fractions 22/7 and 355/113 are good approximations of pi. Let's find more.
Step1: Spoiler alert
Step2: We'll need to go to larger and larger denominators ... | Python Code:
from math import pi
pi
Explanation: Rational approximations of 𝝿
The fractions 22/7 and 355/113 are good approximations of pi. Let's find more.
End of explanation
pi.as_integer_ratio()
f"{884279719003555/281474976710656:0.48f}"
Explanation: Spoiler alert: Who knew that Python floats have this handy method... |
10,042 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Chapter 19 - More about Natural Language Processing Tools (spaCy)
Text data is unstructured. But if you want to extract information from text, then you often need to p... | Python Code:
%%capture
!wget https://github.com/cltl/python-for-text-analysis/raw/master/zips/Data.zip
!wget https://github.com/cltl/python-for-text-analysis/raw/master/zips/images.zip
!wget https://github.com/cltl/python-for-text-analysis/raw/master/zips/Extra_Material.zip
!unzip Data.zip -d ../
!unzip images.zip -d .... |
10,043 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Prepare data so the format is as compatible with the 2018 data as possible
Step1: Examine response rates per day
Step2: The high spike seen on 1/13/20 aligns with the time when the surve... | Python Code:
survey_data = prepare_2019.get_df(
"contribex-survey-2019.csv"
)
Explanation: Prepare data so the format is as compatible with the 2018 data as possible
End of explanation
(
p9.ggplot(survey_data, p9.aes(x="date_taken"))
+ p9.geom_bar()
+ p9.theme(axis_text_x=p9.element_text(angle=45, ha="r... |
10,044 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analysis of a run with constraints, and a run without
I have made a little analysis to test our ability to date a tree with node order constraints. I use the following tree
Step1: Then I wi... | Python Code:
import sys
from ete3 import Tree, TreeStyle, NodeStyle
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
import scipy
import re
t = Tree("(((a:0.1,b:0.1):0.2, (c:0.2,d:0.2):0.1):0.6, ((e:0.4,f:0.4):0.3, (g:0.5,h:0.5):0.2):0.2);")
ts = TreeStyle()
ts.min_leaf_separation= 0
t... |
10,045 | 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... |
10,046 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'hadgem3-gc31-mm', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: MOHC
Source ID: HADGEM3-GC31-MM
Topic: Aerosol
Sub-Topics: Transpor... |
10,047 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Jupyter Notebook backend demo
This example shows how vispy's low-level gloo interface can be used to display a WebGL canvas in a notebook. By default, vispy will detect that it is bei... | Python Code:
import numpy as np
import vispy
import vispy.gloo as gloo
from vispy import app
from vispy.util.transforms import perspective, translate, rotate
# load the vispy bindings manually for the notebook which enables webGL
# %load_ext vispy
n = 100
a_position = np.random.uniform(-1, 1, (n, 3)).astype(np.float32)... |
10,048 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Read data
Step1: Target variable
Step2: Target variable is Survived.
Quality metric
Your score is the percentage of passengers you correctly predict. That means - accuracy.
Model
One varia... | Python Code:
train_df = pd.read_csv('../input/train.csv')
test_df = pd.read_csv('../input/test.csv')
all_df = train_df.append(test_df)
all_df['is_test'] = all_df.Survived.isnull()
all_df.index = all_df.Survived
del all_df['Survived']
all_df.head()
Explanation: Read data
End of explanation
train_df.describe()
Explanatio... |
10,049 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Part 3
Step1: Applying the Rotation
Let's try out our function, using it to derive the heptagon edges from the P1-P0 edge, and drawing the result, using the original "render" function that ... | Python Code:
# load the definitions from the previous notebooks
%run DrawingTheHeptagon.py
r = sigma-rho
s = rho-1
t = one-rho # the __sub__ function requires a HeptagonNumber on the left, so "1-rho" won't work
u = rho-1
def rotate(v) :
x, y = v
return ( r*x + t*y, s*x + u*y )
def plusv( v1, v2 ) :
h1, h2 =... |
10,050 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex AI
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Once you've installed the additional packages, you need to restart the not... | Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
Explanation: Vertex AI: Vertex AI Migration: Custom Scikit-Learn model with pre-built training contain... |
10,051 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modeling and Simulation in Python
Case study.
Copyright 2017 Allen Downey
License
Step1: Unrolling
Let's simulate a kitten unrolling toilet paper. As reference material, see this video.
Th... | Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import functions from the modsim.py module
from modsim import *
Explanation: Modeling and Si... |
10,052 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Managing kubernetes objects using common resource operations with the python client
Some of these operations include;
create_xxxx
Step1: Load config from default location.
Step2: Create A... | Python Code:
from kubernetes import client, config
Explanation: Managing kubernetes objects using common resource operations with the python client
Some of these operations include;
create_xxxx : create a resource object. Ex create_namespaced_pod and create_namespaced_deployment, for creation of pods and deployments re... |
10,053 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GPyOpt
Step1: In this example we will optimize the 2D Six-Hump Camel function (available in GPyOpt). We will assume that exact evaluations of the function are observed. The explicit form of... | Python Code:
%pylab inline
import GPyOpt
import GPy
import numpy as np
Explanation: GPyOpt: Bayesian Optimization with fixed constraints
Written by Javier Gonzalez, University of Sheffield.
Reference Manual index
Last updated Friday, 11 March 2016.
In this notebook we will learn how to solve optimization problems with ... |
10,054 | 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... |
10,055 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LDA/QDA on height/weight data
We're asked to fit a Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) model to the height/weight data and compute the the misclassif... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
# benchmark sklearn implementations, these are much faster
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.discriminant_analysis import Qu... |
10,056 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Two Moons Normalizing Flow Using Distrax + Haiku
Neural Spline Flow based off of distrax documentation for a flow. Code to load 2 moons example dataset sourced from Chris Waites's jax-flows ... | Python Code:
!pip install -qq -U dm-haiku distrax optax
import matplotlib.pyplot as plt
from IPython.display import clear_output
from sklearn import datasets, preprocessing
try:
import distrax
except ModuleNotFoundError:
%pip install -qq distrax
import distrax
import jax
import jax.numpy as jnp
import numpy... |
10,057 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Idea
Using the vmstat command line utility to quickly determine the root cause of performance problems.
Step1: Data Input
In this version, we use a helper library that I've built to read in... | Python Code:
%less ../datasets/vmstat_loadtest.log
Explanation: Idea
Using the vmstat command line utility to quickly determine the root cause of performance problems.
End of explanation
from ozapfdis.linux import vmstat
stats = vmstat.read_logfile("../datasets/vmstat_loadtest.log")
stats.head()
Explanation: Data Input... |
10,058 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Olfaction Model Demo
This notebook illustrates how to run a Neurokernel-based model of part of the fruit fly's antennal lobe.
Background
The early olfactory system in Drosophila consists of ... | Python Code:
%cd -q ~/neurokernel/examples/olfaction/data
%run gen_olf_input.py
%run create_olf_gexf.py
Explanation: Olfaction Model Demo
This notebook illustrates how to run a Neurokernel-based model of part of the fruit fly's antennal lobe.
Background
The early olfactory system in Drosophila consists of two antennal ... |
10,059 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data reduction for paleomagnetic data aboard the JOIDES Resolution
This notebook is for people wanting to download and manipulate data from an IODP Expedition using data in the LIMS Online R... | Python Code:
# import a bunch of packages for use in the notebook
import pmagpy.pmag as pmag # a bunch of PmagPy modules
import pmagpy.pmagplotlib as pmagplotlib
import pmagpy.ipmag as ipmag
import pmagpy.contribution_builder as cb
from pmagpy import convert_2_magic as convert # conversion scripts for many lab formats
... |
10,060 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
확률론적 선형 회귀 모형
OLS(Ordinary Least Square) 방법을 사용하면 데이터에 대한 확률론적인 가정없이도 최적의 가중치를 계산할 수 있다. 그러나 이 경우에는 계산한 가중치가 어느 정도의 신뢰도 또는 안정성을 가지는지 확인할 수 있는 방법이 없다. 이를 확인하고자 하는 시도 중의 하나가 부트스트래핑(bootstrappi... | Python Code:
from sklearn.datasets import make_regression
X0, y, coef = make_regression(n_samples=100, n_features=1, noise=20, coef=True, random_state=0)
dfX0 = pd.DataFrame(X0, columns=["X1"])
dfX = sm.add_constant(dfX0)
dfy = pd.DataFrame(y, columns=["y"])
model = sm.OLS(dfy, dfX)
result = model.fit()
print(result.pa... |
10,061 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div style="text-align
Step1: <a id="ref3"></a>
Building a Graph
As we said before, TensorFlow works as a graph computational model. Let's create our first graph.
To create two source opera... | Python Code:
import tensorflow as tf
Explanation: <div style="text-align:center"><img src = "https://www.tensorflow.org/_static/images/tensorflow/logo.png"></div>
<a id="ref2"></a>
How does TensorFlow work?
TensorFlow defines computations as Graphs, and these are made with operations (also know as “ops”). So, when we w... |
10,062 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Week 1 Tutorial
GitHub Workflow and Goals for the Class
Getting Started
Ideally, you have already work through the Getting Started page on the course GitHub repository. You will need a compu... | Python Code:
class SolutionMissingError(Exception):
def __init__(self):
Exception.__init__(self,"You need to complete the solution for this code to work!")
def REPLACE_WITH_YOUR_SOLUTION():
raise SolutionMissingError
REMOVE_THIS_LINE = REPLACE_WITH_YOUR_SOLUTION
Explanation: Week 1 Tutorial
GitHub Workf... |
10,063 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Content and Objective
Show result of LS estimator for polynomials
Step1: Parameters
Step2: Do LS Estimation
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' : 30}
plt.rc('font', **font)
plt.rc('text', usetex=True)
matplotlib.rc('figure', figsize=(30, 15) )
Explanation: Content and Objective
Show resul... |
10,064 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
matplotlib 学习手册
整理和学习 matplotlib 的基本知识点和使用方法
参考
matplotlib org
Matplotlib 教程
IPython 以及 pylab 模式
IPython 是 Python 的一个增强版本。它在下列方面有所增强：命名输入输出、使用系统命令（shell commands）、排错（debug）能力。我们在命令行终端给 IPyth... | Python Code:
# 导入 matplotlib 的所有内容（nympy 可以用 np 这个名字来使用）
from pylab import *
# 创建一个 8 * 6 点（point）的图，并设置分辨率为 80
figure(figsize=(8,6), dpi=80)
# 创建一个新的 1 * 1 的子图，接下来的图样绘制在其中的第 1 块（也是唯一的一块）
subplot(1,1,1)
X = np.linspace(-np.pi, np.pi, 256,endpoint=True)
C,S = np.cos(X), np.sin(X)
# 绘制余弦曲线，使用蓝色的、连续的、宽度为 1 （像素）的线条
plot(X,... |
10,065 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preparation of the reference genome
Usually NGS reads are mapped against a reference genome containing only the assembled chromosomes, and not the remaining contigs. And this methodology is ... | Python Code:
species = 'Mus_musculus'
taxid = '10090'
assembly = 'GRCm38.p6'
genbank = 'GCF_000001635.26'
Explanation: Preparation of the reference genome
Usually NGS reads are mapped against a reference genome containing only the assembled chromosomes, and not the remaining contigs. And this methodology is perfec... |
10,066 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GP Regression with a Spectral Mixture Kernel
Introduction
This example shows how to use a SpectralMixtureKernel module on an ExactGP model. This module is designed for
When you want to use e... | Python Code:
import math
import torch
import gpytorch
from matplotlib import pyplot as plt
%matplotlib inline
%load_ext autoreload
%autoreload 2
Explanation: GP Regression with a Spectral Mixture Kernel
Introduction
This example shows how to use a SpectralMixtureKernel module on an ExactGP model. This module is designe... |
10,067 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Facetted subgrids
We can split the image (facetting), and we can split the grid (subgrids) and do a lot of operations separately. This works out relatively straightforwardly. However, can we... | Python Code:
%matplotlib inline
from matplotlib import pylab
import matplotlib.patches as patches
import matplotlib.path as path
from ipywidgets import interact
import numpy
import sys
import random
import itertools
import time
import scipy.special
import math
pylab.rcParams['figure.figsize'] = 16, 10
pylab.rcParams['i... |
10,068 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Test the Retrieval Latency of Approximate vs Exact Matching
Step1: Exact Matching
Step2: Approximate Matching (ScaNN) | Python Code:
import tensorflow as tf
import time
PROJECT_ID = 'ksalama-cloudml'
BUCKET = 'ksalama-cloudml'
INDEX_DIR = f'gs://{BUCKET}/bqml/scann_index'
BQML_MODEL_DIR = f'gs://{BUCKET}/bqml/item_matching_model'
LOOKUP_MODEL_DIR = f'gs://{BUCKET}/bqml/embedding_lookup_model'
songs = {
'2114406': 'Metallica: Nothing... |
10,069 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this post, we are going to construct a unit conversion table in python. The table will have columns for meters (m), centimeter (cm), and inches (in). We will start off with a list of valu... | Python Code:
meters = [0, 10, 20, 30, 40, 50]
meters
centimeters = meters*0.01
centimeters
Explanation: In this post, we are going to construct a unit conversion table in python. The table will have columns for meters (m), centimeter (cm), and inches (in). We will start off with a list of values that will be our meter ... |
10,070 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
From raw data to dSPM on SPM Faces dataset
Runs a full pipeline using MNE-Python
Step1: Load and filter data, set up epochs
Step2: Visualize fields on MEG helmet
Step3: Look at the whiten... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD-3-Clause
import matplotlib.pyplot as plt
import mne
from mne.datasets import spm_face
from mne.preprocessing import ICA, create_eog_epochs
from mne import io, combine_evoked
fro... |
10,071 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Paris Saclay Center for Data Science
Titanic RAMP
Step1: Exploratory data analysis
Loading the data
Step2: The original training data frame has 891 rows. In the starting kit, we give you a... | Python Code:
%matplotlib inline
import os
import glob
import numpy as np
from scipy import io
import matplotlib.pyplot as plt
import pandas as pd
from rampwf.utils.importing import import_module_from_source
Explanation: Paris Saclay Center for Data Science
Titanic RAMP: survival prediction of Titanic passengers
Benoit ... |
10,072 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bundle setup
Step1: We will set the pblum mode to dataset-scaled for estimators and optimizers, to avoid having to add pblum to the fitted parameters or adjusting it manually. We will also ... | Python Code:
lc = np.loadtxt('data/lc.V.data')
rv1 = np.loadtxt('data/rv1.data')
rv2 = np.loadtxt('data/rv2.data')
b = phoebe.default_binary()
b.add_dataset('lc', times = lc[:,0], fluxes=lc[:,1], sigmas=lc[:,2], passband='Johnson:V')
b.add_dataset('rv', passband='Johnson:V')
b['times@rv@primary'], b['rvs@rv@primary'], ... |
10,073 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Burgers' equation
Step1: In this chapter, we study a simple scalar nonlinear conservation law
Step2: Notice that at first $q$ remains single-valued for every $x$. However, after some time ... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'svg'
from ipywidgets import interact
from ipywidgets import widgets
from ipywidgets import FloatSlider, fixed
from exact_solvers import burgers
from exact_solvers import burgers_demos
from IPython.display import HTML
Explanation: Burgers' equation
E... |
10,074 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing 2 Stacks of Catalogues
Environment
Step1: Need more packages?
Step2: Main()
Run legacy-zeropoints-qa.py like this "python legacy-zeropoints-qa.py" to analyze everything.
See bel... | Python Code:
import sys
print sys.executable
# Hack!, this avoids messing with NERSC's config file for jupyter hub
sys.path.append('/global/homes/k/kaylanb/repos/astrometry.net')
sys.path.append('/global/homes/k/kaylanb/repos/tractor')
sys.path
print sys.path
Explanation: Comparing 2 Stacks of Catalogues
Environment: a... |
10,075 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convolutional Autoencoder
Sticking with the MNIST dataset, let's improve our autoencoder's performance using convolutional layers. Again, loading modules and the data.
Step1: Network Archit... | 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)
img = mnist.train.images[2]
plt.imshow(img.reshape((28, 28)), cmap='Greys_r')
Explanati... |
10,076 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Quick Intro to Keras Functional API
Preamble
Step1: Step 2 | Python Code:
# let's load MNIST data as we did in the exercise on MNIST with FC Nets
# %load ../solutions/sol_52.py
Explanation: Quick Intro to Keras Functional API
Preamble: All models (layers) are callables
```python
from keras.layers import Input, Dense
from keras.models import Model
this returns a tensor
inputs = I... |
10,077 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This script checks if all the ROI atlases in functional space have all the ROIs
Step1: As seen from histogram most of the corrupted ROIs are in cerebellum.
Therefore I have chosen to consid... | Python Code:
import numpy as np
import nibabel as nib
atlas_path = '/home1/varunk/results_again_again/ABIDE1_Preprocess_Datasink/atlas_paths/atlas_file_list.npy'
atlas_files = np.load(atlas_path)
atlas_files[41]
in_file = atlas_files[40]
atlas_values_list = nib.load(in_file).get_data().ravel()
universe = set(np.arange(... |
10,078 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Whoosh
Step1: Means the sound made by something that is moving quickly
Whoosh, so fast and easy that even a lawyer could manage it
What is Whoosh?
Whoosh is a library of classes and functio... | Python Code:
from IPython.display import Image
Image(filename='files/screenshot.png')
from IPython.display import Image
Image(filename='files/whoosh.jpg')
Explanation: Whoosh: a fast pure-Python search engine library
Pydata Madrid
2016.04.10
Who am I?
Claudia Guirao Fernández
@claudiaguirao
Background: Double degre... |
10,079 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 7 Regularization for Deep Learning
the best fitting model is a large model that has been regularized appropriately.
7.1 Parameter Norm Penalties
\begin{equation}
\tilde{J}(\theta... | Python Code:
show_image("fig7_2.png")
Explanation: Chapter 7 Regularization for Deep Learning
the best fitting model is a large model that has been regularized appropriately.
7.1 Parameter Norm Penalties
\begin{equation}
\tilde{J}(\theta; X, y) = J(\theta; X, y) + \alpha \Omega(\theta)
\end{equation}
where $\Omega(... |
10,080 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Les tables concernant l'âge et le sexe
Output
Step1: Les tables concernant le statut d'actif.ve
Output
Step2: Les tables concernant le statut d'actif.ve occupée
Taux de chômage trimestrie... | Python Code:
pd.read_csv("data/demographie/pop_age_sexe_2016.csv").head()
Explanation: Les tables concernant l'âge et le sexe
Output : pop_age_sexe_2016.csv
Input :
Table générée à partir de pop-1janvier-fe.xls (https://www.insee.fr/fr/statistiques/1892086)
Source : Insee, estimations de population (résultats provisoi... |
10,081 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!--BOOK_INFORMATION-->
<a href="https
Step1: Although the original images consisted of 92 x 112 pixel images, the version available
through scikit-learn contains images downscaled to 64 x ... | Python Code:
from sklearn.datasets import fetch_olivetti_faces
dataset = fetch_olivetti_faces()
X = dataset.data
y = dataset.target
Explanation: <!--BOOK_INFORMATION-->
<a href="https://www.packtpub.com/big-data-and-business-intelligence/machine-learning-opencv" target="_blank"><img align="left" src="data/cover.jpg" st... |
10,082 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Repeated measures ANOVA on source data with spatio-temporal clustering
This example illustrates how to make use of the clustering functions
for arbitrary, self-defined contrasts beyond stand... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Eric Larson <larson.eric.d@gmail.com>
# Denis Engemannn <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import numpy as np
from numpy.random import randn
import matplotlib.pyplot as plt
i... |
10,083 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Classification 2
Step2: Exercise 7.2
Show that a classifier $\hat y_i = \text{sign}(\beta^\top x_i)$ is defined by a separating hyperplane. Assume that $\beta \in \mathbb R^{p+1}$ a... | Python Code:
def lm_sim(N = 100):
simulate a binary response and two predictors
X1 = (np.random.randn(N*2)).reshape((N,2)) + np.array([2,3])
X0 = (np.random.randn(N*2)).reshape((N,2)) + np.array([.5,1.5])
y = - np.ones(N*2)
y[:N]=1
X = np.vstack((X1,X0))
return X, y, X0, X1
X_sim,y_sim,X0,X1... |
10,084 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting started - a single particle
In this tutorial, we'll simulate the stochastic dynamics of a single nanoparticle. We model clusters of nanoparticles using the magpy.Model class. In this... | Python Code:
import magpy as mp
Explanation: Getting started - a single particle
In this tutorial, we'll simulate the stochastic dynamics of a single nanoparticle. We model clusters of nanoparticles using the magpy.Model class. In this case we only have a single particle in our cluster. The first step is to import magp... |
10,085 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!--BOOK_INFORMATION-->
<img align="left" style="padding-right
Step1: The plt interface is what we will use most often, as we shall see throughout this chapter.
Setting Styles
We will use t... | Python Code:
import matplotlib as mpl
import matplotlib.pyplot as plt
Explanation: <!--BOOK_INFORMATION-->
<img align="left" style="padding-right:10px;" src="figures/PDSH-cover-small.png">
This notebook contains an excerpt from the Python Data Science Handbook by Jake VanderPlas; the content is available on GitHub.
The... |
10,086 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
人生苦短，我用python
python第四课
课程安排
1、numpy
2、pandas
3、matplotlib
numpy
数组跟列表，列表可以存储任意类型的数据，而数组只能存储一种类型数据
Step1: 从原有列表转换为数组
Step2: 生成数组
Step3: random
Step4: 范围取值
Step5: | Data type | Descr... | Python Code:
import array
a = array.array('i', range(10))
# 数据类型必须统一
a[1] = 's'
a
import numpy as np
Explanation: 人生苦短，我用python
python第四课
课程安排
1、numpy
2、pandas
3、matplotlib
numpy
数组跟列表，列表可以存储任意类型的数据，而数组只能存储一种类型数据
End of explanation
a_list = list(range(10))
b = np.array(a_list)
type(b)
Explanation: 从原有列表转换为数组
End of exp... |
10,087 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
We covered a lot of information today and I'd like you to practice developing classification trees on your own. For each exercise, work through the problem, determine the result, and provide... | Python Code:
import pandas as pd
%matplotlib inline
from sklearn import datasets
from pandas.tools.plotting import scatter_matrix
import matplotlib.pyplot as plt
from sklearn import tree
iris = datasets.load_iris()
x = iris.data[:,2:]
y = iris.target
plt.figure(2, figsize=(8, 6))
plt.scatter(x[:, 0], x[:, 1], c=y, c... |
10,088 | 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... |
10,089 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: 과대적합과 과소적합
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: IMDB 데이터셋 다운로드
이전 노트북에서처럼 임베딩을 사... | 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... |
10,090 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
W6 Lab Assignment
Deep dive into Histogram and boxplot.
Step1: Histogram
Let's revisit the table from the class
| Hours | Frequency |
|-------|-----------|
| 0-1 | 4,300 |
| 1-3 | 6... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import pandas as pd
sns.set_style('white')
%matplotlib inline
Explanation: W6 Lab Assignment
Deep dive into Histogram and boxplot.
End of explanation
bins = [0, 1, 3, 5, 10, 24]
data = {0.5: 4300, 2: 6900, 4: 4900, 7: 2000, 15: 2100}... |
10,091 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GeoNet FDSN webservice with Obspy demo - Event Service
This demo introduces some simple code that requests data using GeoNet's FDSN webservices and the obspy module in python. This notebook ... | Python Code:
from obspy import UTCDateTime
from obspy.clients.fdsn import Client as FDSN_Client
from obspy import read_inventory
Explanation: GeoNet FDSN webservice with Obspy demo - Event Service
This demo introduces some simple code that requests data using GeoNet's FDSN webservices and the obspy module in python. Th... |
10,092 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This notebook is an analysis of the Crowdflower labels of 10,000 revisions of Wikipedia talk pages by users who have been blocked for personal harassment. These revisions are ch... | Python Code:
%matplotlib inline
from __future__ import division
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import time
import datetime
from scipy import stats
import warnings
warnings.filterwarnings('ignore')
pd.set_option('display.max_colwidth', 1000)
# Download data from google drive (Resp... |
10,093 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Validation and Verification of the 25mm collimator simulation, GP3, PhSF
Here we provide code and output which verifies and validates the 25mm collimator simulation. We're using simul... | Python Code:
import math
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import BEAMphsf
import beam_loader
import H1Dn
import H1Du
import ListTable
%matplotlib inline
def cm2mm(value):
converts cm to mm
return value*10.0
Explanation: Validation and Verification of the 25mm collim... |
10,094 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Setup the environment
Step1: Do the work to do the plotting
Step2: Print yields and plot all the templates
$B_s \to D_s^- \mu^+ \nu_{\mu} $
Step3: Print yields and plot all the templates... | Python Code:
import sys
sys.path.append('../../FourVector')
sys.path.append('../project')
from FourVector import FourVector
from ThreeVector import ThreeVector
from FutureColliderTools import SmearVertex, GetCorrectedMass, GetMissingMass2, GetQ2
from FutureColliderDataLoader import LoadData_KMuNu, LoadData_DsMuNu
from ... |
10,095 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Here, we transform some strings to lowercase. This is because there are duplicate entries in the dataset which in both upper and lower.
This increases redundancy
Step1: There is still alot ... | Python Code:
cleandata1['SOC_NAME'].value_counts()
Explanation: Here, we transform some strings to lowercase. This is because there are duplicate entries in the dataset which in both upper and lower.
This increases redundancy
End of explanation
cleandata1['SOC_NAME'].value_counts().count()
Explanation: There is still a... |
10,096 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2/1/17
FEProblemBase
Step1: Jacobian calculations related to deviatoric stress tensor ($\hat{\tau}$) and rate of strain tensor ($\hat{\epsilon}$)
Note that the total stress tensor ($\hat{\s... | Python Code:
import sympy as sp
sxx, sxy, syx, syy, nx, ny = sp.var('sxx sxy syx syy nx ny')
s = sp.Matrix([[sxx, sxy],[syx, syy]])
n = sp.Matrix([nx, ny])
s*n
prod = n.transpose()*s*n
prod2 = n.transpose()*(s*n)
print(prod)
print(prod2)
print(prod==prod2)
prod.shape
sp.expand(prod) == sp.expand(prod2)
lhs = n.transpos... |
10,097 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
适配器模式(Adapter pattern)是一种结构型设计模式，帮助我们实现两个不兼容接口之间的兼容。
首先，解释一下不兼容接口的真正含义。如果我们希望把一个老组件用于一个新系统中，或者把一个新组件用于一个老系统中，不对代码进行任何修改两者就能够通信的情况很少见。但又并非总是能修改代码，或因为我们无法访问这些代码(例如，组件以外部库的方式提供)，或因为修改代码本身就不切实际。... | Python Code:
import os
class Dog(object):
def __init__(self):
self.name = "Dog"
def bark(self):
return "woof!"
class Cat(object):
def __init__(self):
self.name = "Cat"
def meow(self):
return "meow!"
class Human(object):
def __init__(self):
self.name = "Human"
... |
10,098 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hdf5 File format
Vaex uses hdf5 (Hierarchical Data Format) for storing data. You can think of hdf5 files as being a file system, where the 'files' contain N-dimensional arrays, or think of i... | Python Code:
import h5py
import numpy as np
h5file = h5py.File("/Users/users/breddels/src/vaex/data/helmi-dezeeuw-2000-10p.hdf5", "r")
FeH = h5file["/data/FeH"]
# FeH is your regular numpy array (with some extras)
print("mean FeH", np.mean(FeH), "length", len(FeH))
Explanation: Hdf5 File format
Vaex uses hdf5 (Hierarch... |
10,099 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Customer Churn
Credits
Step1: We'll be keeping the statistical model pretty simple for this example so the feature space is almost unchanged from what you see above. The following code simp... | Python Code:
from __future__ import division
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import json
from sklearn.cross_validation import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.cross_validation import train_test_split
from sklearn.svm import SVC
from sklearn.ensem... |
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