Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
|---|---|---|
1,000 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fixed $Y_i$ & Fixed $\alpha_{MLT}$
Analysis for the case that the proto-stellar (i.e., initial) helium mass fraction is fixed to a value that is linearly proportional to the heavy element ma... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
FeH_weak = np.genfromtxt('data/run09_mle_props.txt') # weak metallicity prior
FeH_strong = np.genfromtxt('data/run10_mle_props.txt') # strong metallicity prior
no_Teff = np.genfromtxt('data/run11_mle_props.txt') # no Teff observa... |
1,001 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Source
Step1: Source | Python Code:
flowData = pd.read_csv('../TableD_01110030-eng.csv')
flowData.head()
# Convert place names to unicode
flowData['GEO'] = flowData['GEO'].map(u)
flowData['GEODEST'] = flowData['GEODEST'].map(u)
flowData.head()
# Remove unneeded columns
dropCols = ['Geographical classification',
'Geographical class... |
1,002 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Temporal-Comorbidity Adjusted Risk of Emergency Readmission (TCARER)
<font style="font-weight
Step1: 1.1. Initialise General Settings
Step2: Common variables
Step3: <br/><br/>
2.1. Initi... | Python Code:
# reload modules
# Reload all modules (except those excluded by %aimport) every time before executing the Python code typed.
%load_ext autoreload
%autoreload 2
# import libraries
import logging
import os
import sys
import gc
import pandas as pd
import numpy as np
import random
import statistics
from datet... |
1,003 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Image features exercise
Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For more detai... | Python Code:
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] = 'gray'
# for auto-reloading ex... |
1,004 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LEARNING
This notebook serves as supporting material for topics covered in Chapter 18 - Learning from Examples , Chapter 19 - Knowledge in Learning, Chapter 20 - Learning Probabilistic Model... | Python Code:
from learning import *
from notebook import *
Explanation: LEARNING
This notebook serves as supporting material for topics covered in Chapter 18 - Learning from Examples , Chapter 19 - Knowledge in Learning, Chapter 20 - Learning Probabilistic Models from the book Artificial Intelligence: A Modern Approach... |
1,005 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exporting Burst Data
This notebook is part of a tutorial series for the FRETBursts burst analysis software.
In this notebook, show a few example of how to export FRETBursts
burst data to a ... | Python Code:
from fretbursts import *
sns = init_notebook()
Explanation: Exporting Burst Data
This notebook is part of a tutorial series for the FRETBursts burst analysis software.
In this notebook, show a few example of how to export FRETBursts
burst data to a file.
<div class="alert alert-info">
Please <b>cite</b> F... |
1,006 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ATM 623
Step1: Contents
First section title
<a id='section1'></a>
1. First section title
Some text.
<div class="alert alert-success">
[Back to ATM 623 notebook home](../index.ipynb)
</div>
... | Python Code:
# Ensure compatibility with Python 2 and 3
from __future__ import print_function, division
Explanation: ATM 623: Climate Modeling
Brian E. J. Rose, University at Albany
Lecture N: No title
About these notes:
This document uses the interactive Jupyter notebook format. The notes can be accessed in several d... |
1,007 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: In this notebook, we will use a multi-layer perceptron to develop time series forecasting models.
The dataset used for the examples of this notebook is on air pollution measured by co... | Python Code:
from __future__ import print_function
import os
import sys
import pandas as pd
import numpy as np
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
import datetime
#set current working directory
os.chdir('D:/Practical Time Series')
#Read the dataset into a pandas.DataFrame
df = ... |
1,008 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Evaluating Machine Learning Algorithms - Extended Examples
Preparations
Download Anaconda with Python 3.6 to install a nearly complete Python enviroment for data science projects
Install Ker... | Python Code:
# The %... is an iPython thing, and is not part of the Python language.
# In this case we're just telling the plotting library to draw things on
# the notebook, instead of on a separate window.
%matplotlib inline
# the import statements load differnt Python packages that we need for the tutorial
# See all ... |
1,009 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
11 Dimensionality Reduction
11.1 Eigenvalues and Eigenvectors of Symmetric Matrices
11.1.1 Definitions
$M e = \lambda e$, where $\lambda$ is an eigenvalue and $e$ is the corresponding eigenv... | Python Code:
plt.imshow(plt.imread('./res/fig11_2.png'))
Explanation: 11 Dimensionality Reduction
11.1 Eigenvalues and Eigenvectors of Symmetric Matrices
11.1.1 Definitions
$M e = \lambda e$, where $\lambda$ is an eigenvalue and $e$ is the corresponding eigenvector.
to make the eigenvector unique, we require that:
ever... |
1,010 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How many movies are listed in the titles dataframe?
Step1: 212811
What are the earliest two films listed in the titles dataframe?
Step2: Reproduction of the Corbett and Fitzimmons Fight, M... | Python Code:
titles.count()
Explanation: How many movies are listed in the titles dataframe?
End of explanation
titles.sort('year').head()
Explanation: 212811
What are the earliest two films listed in the titles dataframe?
End of explanation
t = titles
t[t.title == 'Hamlet'].count()
Explanation: Reproduction of the Cor... |
1,011 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
We will use matplotlib.pyplot for plotting and scipy's netcdf package for reading the model output. The %pylab inline causes figures to appear in the page and conveniently alias pyplot to pl... | Python Code:
%pylab inline
import scipy.io.netcdf
Explanation: We will use matplotlib.pyplot for plotting and scipy's netcdf package for reading the model output. The %pylab inline causes figures to appear in the page and conveniently alias pyplot to plt (which is becoming a widely used alias).
This analysis assumes yo... |
1,012 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Relationship between common similarity metrics
Reference
Step1: Inner product
Step2: Covariance
Average centered inner product
Step3: Cosine Similarity
Normalized (L2) inner product
Step4... | Python Code:
# Import some stuff
import numpy as np
import pandas as pd
import scipy.spatial.distance as spd
from pymer4.simulate import easy_multivariate_normal
from pymer4.models import Lm
import matplotlib.pyplot as plt
% matplotlib inline
# Prep some data
X = easy_multivariate_normal(50,2,corrs=.2)
a, b = X[:,0], ... |
1,013 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Easy unsupervised learning
With python, scikit-learn, and handwritten digits
Loading the digits dataset
It's a dataset that contains around 1700 images (8x8 pixels) of handwritten digits. Re... | Python Code:
from sklearn.datasets import load_digits
digits_dataset = load_digits()
print(digits_dataset.DESCR)
digits = digits_dataset['images']
n_digits = digits.shape[0] # how many images are there?
Explanation: Easy unsupervised learning
With python, scikit-learn, and handwritten digits
Loading the digits dataset... |
1,014 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
which artist has the most songs listed?
how many billboard hits did the rolling stones have?
vs the beatles?
how many songs total? how many years?
how many song lyrics have the word 'love'?
... | Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
#Which artist has the most songs listed?
print(df['Artist'].value_counts()[:1])
#How many hits did the Stones have?
len(df[df['Artist'] == 'the rolling stones'])
#How many did The Beatles have?
len(df[df['Artist'] == 'the beatles'])
#How many songs are the... |
1,015 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Foodnet - Spanish cuisine analysis
Author
Step1: Graph building
Step2: Graph analytics
Step3: Visualitzations | Python Code:
#imports
import networkx as nx
import pandas as pd
from itertools import combinations
import matplotlib.pyplot as plt
from matplotlib import pylab
import sys
from itertools import combinations
import operator
from operator import itemgetter
from scipy import integrate
# Exploring data
recipes_df = pd.rea... |
1,016 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The goal is to see how we can read the data contained in a netCDF file. Several possibilities will be examined.
Reading a local file
Let's assume we have downlowded a file from CMEMS. We def... | Python Code:
datafile = "~/CMEMS_INSTAC/INSITU_MED_NRT_OBSERVATIONS_013_035/history/mooring/IR_TS_MO_61198.nc"
import os
datafile = os.path.expanduser(datafile)
Explanation: The goal is to see how we can read the data contained in a netCDF file. Several possibilities will be examined.
Reading a local file
Let's assume ... |
1,017 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data from http
Step1: We can list the columns in the dataset
Step2: Let's look at a sorted list of the 10 most frequent types of incidents
Step3: Let's group the incidents by year
Step4: ... | Python Code:
import pandas as pd
%matplotlib inline
pd.set_option('display.max_rows', 1000)
pd.set_option('display.max_columns', 1000)
df = pd.read_csv('fire-incidents.csv')
df.head(3)
df.shape
Explanation: Data from http://catalog.data.gov/dataset/baton-rouge-fire-incidents
End of explanation
df.columns
df['DISPATCH D... |
1,018 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Version control for fun and profit
Step1: A repository
Step2: And this is pretty much the essence of Git!
First
Step3: Other settings
Change how you will edit text files (it will often as... | Python Code:
!ls
Explanation: Version control for fun and profit:
Git: the tool you didn't know you needed
Sources of this material:
This tutorial is adapted from
"Version Control for Fun and Profit" by Fernando Perez
For an excellent list of Git resources for scientists, see Fernando's Page.
Fernando's original noteb... |
1,019 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Discerning Haggis 2016-ml-contest submission
Author
Step1: Convenience functions
Step2: Load, treat and color data
Step3: Condition dataset
Step4: Test, train and cross-validate
Up to he... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from mpl_toolkits.axes_grid1 import make_axes_locatable
import seaborn as sns
sns.set(style='whitegrid',
rc={'lines.linewidth': 2.5,
'fig... |
1,020 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recursive Images and Fractals
Recursive images
One of the cool thing about graphs is they can link to themselves. The reason why this is a graph and not a quad tree (as most maps are) is to ... | Python Code:
%pylab inline
import sys
import os
sys.path.insert(0,'..')
import graphmap
from graphmap.graphmap_main import GraphMap
from graphmap.memory_persistence import MemoryPersistence
from graphmap.graph_helpers import NodeLink
G = GraphMap(MemoryPersistence())
seattle_skyline_image_url = 'https://upload.wikimedi... |
1,021 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
BayesianMarkovStateModel
This example demonstrates the class BayesianMarkovStateModel, which uses Metropolis Markov chain Monte Carlo (MCMC) to sample
over the posterior distribution of tran... | Python Code:
%matplotlib inline
import numpy as np
from matplotlib import pyplot as plt
from mdtraj.utils import timing
from msmbuilder.example_datasets import load_doublewell
from msmbuilder.cluster import NDGrid
from msmbuilder.msm import BayesianMarkovStateModel, MarkovStateModel
Explanation: BayesianMarkovStateMode... |
1,022 | 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-... |
1,023 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic CNN part-of-speech tagger with Thinc
This notebook shows how to implement a basic CNN for part-of-speech tagging model in Thinc (without external dependencies) and train the model on t... | Python Code:
!pip install "thinc>=8.0.0a0" "ml_datasets>=0.2.0a0" "tqdm>=4.41"
Explanation: Basic CNN part-of-speech tagger with Thinc
This notebook shows how to implement a basic CNN for part-of-speech tagging model in Thinc (without external dependencies) and train the model on the Universal Dependencies AnCora corpu... |
1,024 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!-- dom
Step1: With $\boldsymbol{\beta}\in {\mathbb{R}}^{p\times 1}$, it means that we will hereafter write our equations for the approximation as
$$
\boldsymbol{\tilde{y}}= \boldsymbol{X}... | Python Code:
%matplotlib inline
# Common imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from IPython.display import display
import os
# Where to save the figures and data files
PROJECT_ROOT_DIR = "Results"
FIGURE_ID = "Results/FigureFiles"
DATA_ID = "DataFiles/"
if not os.path.exists(PRO... |
1,025 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Loading the Book Ratings Dataset
Step1: Loading the Books Dataset
Step2: Some Books don't have unique ISBN, creating a 1
Step3: Data Preparation/ Cleaning <br>
Removing ratings equal to z... | Python Code:
ratings = pd.read_csv('../raw-data/BX-Book-Ratings.csv', encoding='iso-8859-1', sep = ';')
ratings.columns = ['user_id', 'isbn', 'book_rating']
print(ratings.dtypes)
print()
print(ratings.head())
print()
print("Data Points :", ratings.shape[0])
Explanation: Loading the Book Ratings Dataset
End of explanati... |
1,026 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ギブスサンプリングについて
$p(\bf{x}|\theta) = \frac{1}{Z(\theta)} \exp(-\Phi(\bf{x}, \theta))$
$\bf{x} = \left{ x_1, x_2, x_3, \dots, x_N \right}$
についての同時確率分布
$\bf{x} = \left{ x_1, x_2, x_3, \dots, x_N... | Python Code:
import numpy
from matplotlib import pyplot
%matplotlib inline
pyplot.style.use('ggplot')
a = 0.8
num_iter = 30000
cov_inv = [[ 1, -a],[-a, 1]]
mu_x = numpy.array([0, 0])
cov = numpy.linalg.pinv(cov_inv)
%%time
# normal sampling
x_1 = []
x_2 = []
for _ in range(num_iter):
data = numpy.random.multivari... |
1,027 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 2
Taylor Patti
2/15/2015
Excercises Completed
Exercise 5.18 (fit_pendulum_data.py)
Exercise 5.22 (midpoint_vec.py)
Exercise 5.23 (Lagrange_poly1.py)
Exercise 5.24 (Lagrange_poly2.py... | Python Code:
p1.pendulum_plotter()
p1.poly_plotter()
Explanation: Homework 2
Taylor Patti
2/15/2015
Excercises Completed
Exercise 5.18 (fit_pendulum_data.py)
Exercise 5.22 (midpoint_vec.py)
Exercise 5.23 (Lagrange_poly1.py)
Exercise 5.24 (Lagrange_poly2.py)
Exercise 5.25 (Lagrange_poly2b.py)
fit_pendulum_data
Provides ... |
1,028 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Jupyter notebooks
The first thing we'll do, discussed later, is import all the modules we'll need. You should in general do this at the very beginning of each notebook, and ... | Python Code:
# Import numerical packages
import numpy as np
import scipy.integrate
# Import pyplot for plotting
import matplotlib.pyplot as plt
# Seaborn, useful for graphics
import seaborn as sns
# Magic function to make matplotlib inline; other style specs must come AFTER
%matplotlib inline
# This enables SVG graphic... |
1,029 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'uhh', 'sandbox-1', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: UHH
Source ID: SANDBOX-1
Topic: Land
Sub-Topics: Soil, Snow, Vegetation, Energy ... |
1,030 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Пример использования библиотеки BigARTM для тематического моделирования
Для Bigartm v0.8.0
Редактировал Максим Чурилин
Импортируем BigARTM
Step1: Первое считывание данных (преобразуем удобн... | Python Code:
from matplotlib import pyplot as plt
%matplotlib inline
import artm
Explanation: Пример использования библиотеки BigARTM для тематического моделирования
Для Bigartm v0.8.0
Редактировал Максим Чурилин
Импортируем BigARTM:
End of explanation
batch_vectorizer = artm.BatchVectorizer(data_path="school.txt", dat... |
1,031 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assignment 7
Lorenzo Biasi, Julius Vernie
Step1: We load the variables and initilize the parameters we need
Step2: We run the filter
Step3: We can see a slight offset, we would expect th... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import loadmat
from numpy.linalg import inv
%matplotlib inline
Explanation: Assignment 7
Lorenzo Biasi, Julius Vernie
End of explanation
data = loadmat('data_files/Tut7_file1.mat')
locals().update(data)
data.keys()
p, T = z.shape
mu = np.zer... |
1,032 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook explains how to add batch normalization to VGG. The code shown here is implemented in vgg_bn.py, and there is a version of vgg_ft (our fine tuning function) with batch norm ca... | Python Code:
from __future__ import division, print_function
%matplotlib inline
from importlib import reload
import utils; reload(utils)
from utils import *
Explanation: This notebook explains how to add batch normalization to VGG. The code shown here is implemented in vgg_bn.py, and there is a version of vgg_ft (our ... |
1,033 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This is exactly the same as the OpenMM-based alanine dipeptide example, but this one uses Gromacs!
Imports
Step1: Setting up the engine
Now we set things up for the Gromacs simulation. Note... | Python Code:
from __future__ import print_function
%matplotlib inline
import matplotlib.pyplot as plt
import openpathsampling as paths
from openpathsampling.engines import gromacs as ops_gmx
import mdtraj as md
import numpy as np
Explanation: This is exactly the same as the OpenMM-based alanine dipeptide example, but t... |
1,034 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CAPITOLO 1.1
Step1: Iterazione nelle liste e cicli for su indice
Step2: DIZIONARI
Step3: Iterazione nei dizionari
ATTENZIONE
Step4: DYI
Step5: WARNING / DANGER / EXPLOSION / ATTENZIONE!... | Python Code:
# creazione
l = [1,2,3,10,"a", -12.333, 1024, 768, "pippo"]
# concatenazione
l += ["la", "concatenazione", "della", "lista"]
# aggiunta elementi in fondo
l.append(32)
l.append(3)
print(u"la lista è {}".format(l))
l.remove(3) # rimuove la prima occorrenza
print(u"la lista è {}".format(l))
i = l.index(10) ... |
1,035 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
OpenStreetMap is an open project, which means it's free and everyone can use it and edit as they like. OpenStreetMap is direct competitor of Google Maps. How OpenStreetMap can compete with t... | Python Code:
OSM_FILE = 'data/map.osm'
Explanation: OpenStreetMap is an open project, which means it's free and everyone can use it and edit as they like. OpenStreetMap is direct competitor of Google Maps. How OpenStreetMap can compete with the giant you ask? It's depend completely on crowd sourcing. There's lot of peo... |
1,036 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Machine Learning with scikit-learn
Lab 5
Step1: As always, we need to start with some data.
Let's first generate a set of outputs $y$ and predicted outputs $\hat{y}$ to illu... | Python Code:
%matplotlib inline
import warnings
warnings.filterwarnings("ignore", category=DeprecationWarning)
Explanation: Introduction to Machine Learning with scikit-learn
Lab 5: Model evaluation and selection
In this lab, we will apply a few model evaluation metrics we've seen in the lecture.
End of explanation
fr... |
1,037 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyMotW - IceCream
<h1 align="center">
<img src="https
Step1: If you have several print calls it can quickly become unclear what is being printed where. So many of us may have ended up doi... | Python Code:
def foo(i):
return i + 333
print(foo(123))
Explanation: PyMotW - IceCream
<h1 align="center">
<img src="https://github.com/gruns/icecream/raw/master/logo.svg" width="220px" height="370px" alt="icecream">
</h1>
https://github.com/gruns/icecream
available via conda-forge and pypi
Never use print() to d... |
1,038 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
O$_2$scl library linking example for O$_2$sclpy
See the O$_2$sclpy documentation at
https
Step1: This code dynamically links the O$_2$scl library. Environment
variables can be used to speci... | Python Code:
import sys
print(sys.path)
import o2sclpy
import sys
plots=True
if 'pytest' in sys.modules:
plots=False
Explanation: O$_2$scl library linking example for O$_2$sclpy
See the O$_2$sclpy documentation at
https://neutronstars.utk.edu/code/o2sclpy for more information.
End of explanation
link=o2sclpy.linker... |
1,039 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gaussian Process regression tutorial 2
Step1: Problem 0
Step2: Problem 1a
Step3: Now you will need to tell the GP object what inputs the covariance matrix is to be evaluated at. This is d... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import george, emcee, corner
from scipy.optimize import minimize
Explanation: Gaussian Process regression tutorial 2: Solutions
In this tutorial, we are to explore some slightly more realistic appl... |
1,040 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Get the data
2MASS => J, H K, angular resolution ~4"
WISE => 3.4, 4.6, 12, and 22 μm (W1, W2, W3, W4) with an angular resolution of 6.1", 6.4", 6.5", & 12.0"
GALEX imaging => Five imaging s... | Python Code:
from astroquery.gaia import Gaia
tables = Gaia.load_tables(only_names=True)
for table in (tables):
print (table.get_qualified_name())
#obj = ["3C 454.3", 343.49062, 16.14821, 1.0]
obj = ["PKS J0006-0623", 1.55789, -6.39315, 1]
#obj = ["M87", 187.705930, 12.391123, 1.0]
#### name, ra, dec, radius of con... |
1,041 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Photo-z Determination for SpIES High-z Candidates
Notebook that actually applies the algorithms from SpIESHighzQuasarPhotoz.ipynb to the quasar candidates.
Step1: Since we are running on se... | Python Code:
## Read in the Training Data and Instantiating the Photo-z Algorithm
%matplotlib inline
from astropy.table import Table
import numpy as np
import matplotlib.pyplot as plt
#data = Table.read('GTR-ADM-QSO-ir-testhighz_findbw_lup_2016_starclean.fits')
#JT PATH ON TRITON to training set after classification
#d... |
1,042 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning Engineer Nanodegree
Model Evaluation & Validation
Project
Step1: Data Exploration
In this first section of this project, you will make a cursory investigation about the Bos... | Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
from sklearn.cross_validation import ShuffleSplit
# Import supplementary visualizations code visuals.py
import visuals as vs
# Pretty display for notebooks
import matplotlib.pyplot as plt
%matplotlib inline
# Load the Bost... |
1,043 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Clustering analysis
In this first notebook, we conduct a k-means clustering analysis on using an included MFC mask.
Fortunately, Neurosynth includes a set of functions to make this rather ea... | Python Code:
import seaborn as sns
from nilearn import plotting as niplt
from matplotlib.colors import ListedColormap
import numpy as np
Explanation: Clustering analysis
In this first notebook, we conduct a k-means clustering analysis on using an included MFC mask.
Fortunately, Neurosynth includes a set of functions to... |
1,044 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ATLeS - Descriptive Statistics
This script is designed to provide a general purpose tool for producing descriptive statistics and visualizations for ATLES data. The intent is that this noteb... | Python Code:
from pathlib import Path
import configparser
import numpy as np
import pandas as pd
import seaborn
import matplotlib.pyplot as plt
import pingouinparametrics as pp
# add src/ directory to path to import ATLeS code
import os
import sys
module_path = os.path.abspath(os.path.join('..', 'src'))
if module_path ... |
1,045 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
HgTe edge in proximity to an s-wave superconductor
Step1: Let us define a simple real, and hence time reversal invariant lattice model that can serve as a good description to a 1D chiral ed... | Python Code:
#here we define sympy symbols to be used in the analytic calculations
g,mu,b,D,k=sympy.symbols('gamma mu B Delta k',real=True)
Explanation: HgTe edge in proximity to an s-wave superconductor
End of explanation
# onsite and hopping terms
U=sympy.Matrix([[-mu+b,g,0,D],
[g,-mu-b,-D,0],
... |
1,046 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 DeepMind Technologies Limited.
Step1: Environments
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: The code below defines ... | 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... |
1,047 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Issue #42
I am a new user of toytree tool, could you tell me please how can I change the position of inner nodes added custom labels. For examble I want to plot some new_added features above... | Python Code:
import toytree
toytree.__version__
Explanation: Issue #42
I am a new user of toytree tool, could you tell me please how can I change the position of inner nodes added custom labels. For examble I want to plot some new_added features above or below or right the branches . Could you help me with this please?... |
1,048 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
LogGabor user guide
Table of content
What is the LogGabor package?
Installing
Importing the library
Properties of log-Gabor filters
Testing filter generation
Testing on a sample image
Bu... | Python Code:
%load_ext autoreload
%autoreload 2
from LogGabor import LogGabor
parameterfile = 'https://raw.githubusercontent.com/bicv/LogGabor/master/default_param.py'
lg = LogGabor(parameterfile)
lg.set_size((32, 32))
Explanation: LogGabor user guide
Table of content
What is the LogGabor package?
Installing
Importin... |
1,049 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Crash Course in Supervised Learning with scikit-learn
Machine learning, like all fields of study, have a broad array of naming conventions and terminology. Most of these conventions you natu... | Python Code:
from __future__ import print_function
%matplotlib inline
from sklearn.datasets import load_digits
from matplotlib import pyplot as plt
import numpy as np
np.random.seed(42) # for reproducibility
digits = load_digits()
X = digits.data
y = digits.target
Explanation: Crash Course in Supervised Learning with ... |
1,050 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Double 7's (Short Term Trading Strategies that Work)
1. The Security is above its 200-day moving average or X-day ma
2. The Security closes at a 7-day low, buy.
3. If the Security closes at ... | Python Code:
import datetime
import matplotlib.pyplot as plt
import pandas as pd
import pinkfish as pf
# Format price data.
pd.options.display.float_format = '{:0.2f}'.format
%matplotlib inline
# Set size of inline plots.
'''note: rcParams can't be in same cell as import matplotlib
or %matplotlib inline
%matp... |
1,051 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute envelope correlations in volume source space
Compute envelope correlations of orthogonalized activity
Step1: Here we do some things in the name of speed, such as crop (which will
hu... | Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
# Sheraz Khan <sheraz@khansheraz.com>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
import mne
from mne.beamformer import make_lcmv, apply_lcmv_epochs
from mne.connectivity import envelope_corr... |
1,052 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Limpieza de dataset de la Encuesta Intercensal 2015 - Modulo Movilidad Cotidiana
1 . Introduccion
Para la construcción de indicadores de la Plataforma de Conocimiento de Ciudades Sustentable... | Python Code:
# Librerias utilizadas
import pandas as pd
import sys
import urllib
import os
import numpy as np
# Configuracion del sistema
print('Python {} on {}'.format(sys.version, sys.platform))
print('Pandas version: {}'.format(pd.__version__))
import platform; print('Running on {} {}'.format(platform.system(), plat... |
1,053 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: We show some very basic plots with matplotlib.
Step2: Simplest line chart.
Step3: Scatter plot.
Step4: In the process of learning data visualization we will try to ... | Python Code:
import matplotlib.pyplot as plt
Explanation: <a href="https://colab.research.google.com/github/subarnop/AMachineLearningWalkThrough/blob/master/learning_to_plot.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
Data visualization is a very... |
1,054 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
QC Configuration
Objective
Step1: load_cfg(), just for demonstration
Here we will import the load_cfg() function to illustrate different procedures. This is typically not necessary since Pr... | Python Code:
# A different version of CoTeDe might give slightly different outputs.
# Please let me know if you see something that I should update.
import cotede
print("CoTeDe version: {}".format(cotede.__version__))
Explanation: QC Configuration
Objective:
Show different ways to configure a quality control (QC) proced... |
1,055 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
vn.past.demo - Welcome!
1. Preface
past 是一个从属于vn.trader的市场历史数据解决方案模块。主要功能为：
从datayes（通联数据）等web数据源高效地爬取、更新历史数据。
基于MongoDB的数据库管理、快速查询，各种输出格式的转换。
基于Matplotlib快速绘制K线图等可视化对象。
主要依赖：pymongo，pandas，... | Python Code:
# init.py
from base import *
if __name__ == '__main__':
ds = DataGenerator()
ds.download()
Explanation: vn.past.demo - Welcome!
1. Preface
past 是一个从属于vn.trader的市场历史数据解决方案模块。主要功能为：
从datayes（通联数据）等web数据源高效地爬取、更新历史数据。
基于MongoDB的数据库管理、快速查询，各种输出格式的转换。
基于Matplotlib快速绘制K线图等可视化对象。
主要依赖：pymongo，pandas，reque... |
1,056 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing Python and Julia
This is a bruteforce attempt at solving Project Euler problem 14 with Python. The implementation is such that it is one-to-one with corresponding Julia code.
Step1... | Python Code:
# Collatz
def collatz_chain(n):
'Compute the Collatz chain for number n.'
k = 1
while n > 1:
n = 3*n+1 if (n % 2) else n >> 1
k += 1
# print n
return k
def solve_euler(stop):
'Which of the number [1, stop) has the longest Collatz chain.'
n, N, N_max = 1, 0, 0... |
1,057 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Working with data 2017. Class 2
Contact
Javier Garcia-Bernardo
garcia@uva.nl
0. Structure
Data types, structures and code II
Merging and concatenating dataframes
My second plots
Summary
Step... | Python Code:
##Some code to run at the beginning of the file, to be able to show images in the notebook
##Don't worry about this cell
#Print the plots in this screen
%matplotlib inline
#Be able to plot images saved in the hard drive
from IPython.display import Image
#Make the notebook wider
from IPython.core.display ... |
1,058 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Select, Add, Delete, Columns
Step1: dictionary like operations
dictionary selection with string index | Python Code:
import pandas as pd
import numpy as np
Explanation: Select, Add, Delete, Columns
End of explanation
cookbook_df = pd.DataFrame({'AAA' : [4,5,6,7], 'BBB' : [10,20,30,40],'CCC' : [100,50,-30,-50]})
cookbook_df['BBB']
Explanation: dictionary like operations
dictionary selection with string index
End of explan... |
1,059 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2/ Linearity
Step1: Simplest linear function
Step3: What about vector inputs?
Step5: Linear transformations
A linear transformation is function that takes vectors as inputs, and produces ... | Python Code:
# setup SymPy
from sympy import *
init_printing()
x, y, z, t = symbols('x y z t')
alpha, beta = symbols('alpha beta')
Explanation: 2/ Linearity
End of explanation
b, m = symbols('b m')
def f(x):
return m*x
f(1)
f(2)
f(1+2)
f(1) + f(2)
expand(f(x+y)) == f(x) + f(y)
Explanation: Simplest linear function... |
1,060 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Import and Preprocessing
We import Yelp business data from our trimmed cleaned.csv file.
For further processing, we only analyze American cities for now. Since this particular dataset has da... | Python Code:
from collections import Counter
from ast import literal_eval
import pandas as pd
import numpy as np
# import and cleaning
rests = pd.read_csv('cleaned.csv')
rests['categories'] = rests['categories'].apply(literal_eval)
# American cities only
rests = rests[rests['state'].isin(['PA', 'NC', 'IL', 'AZ', 'NV', ... |
1,061 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Linear Regression
By Evgenia "Jenny" Nitishinskaya and Delaney Granizo-Mackenzie with example algorithms by David Edwards
Part of the Quantopian Lecture Series
Step1: First we'll define a f... | Python Code:
# Import libraries
import numpy as np
from statsmodels import regression
import statsmodels.api as sm
import matplotlib.pyplot as plt
import math
Explanation: Linear Regression
By Evgenia "Jenny" Nitishinskaya and Delaney Granizo-Mackenzie with example algorithms by David Edwards
Part of the Quantopian Lec... |
1,062 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SparkSQL Lab
Step1: HiveContext, a superset of SQLContext, was recommended for most use cases. Please make sure you are using HiveContext now!
Part 2
Step2: Show time
Step3: (2b) Read fro... | Python Code:
from pyspark.sql import SQLContext, Row
sqlContext = SQLContext(sc)
sqlContext
from pyspark.sql import HiveContext, Row
sqlContext= HiveContext(sc)
sqlContext
Explanation: SparkSQL Lab:
From this lab, you would write code to execute SQL query in Spark. Makes your analytic life simpler and faster.
During ... |
1,063 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
E2E ML on GCP
Step1: Restart the kernel
Once you've installed the additional packages, you need to restart the notebook kernel so it can find the packages.
Step2: Before you begin
Set up y... | Python Code:
import os
# The Vertex AI Workbench Notebook product has specific requirements
IS_WORKBENCH_NOTEBOOK = os.getenv("DL_ANACONDA_HOME")
IS_USER_MANAGED_WORKBENCH_NOTEBOOK = os.path.exists(
"/opt/deeplearning/metadata/env_version"
)
# Vertex AI Notebook requires dependencies to be installed with '--user'
U... |
1,064 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting
Every region has two plotting functions, which draw the outlines of all regions
Step1: We use the srex regions to illustrate the plotting
Step2: Plot all regions
Calling plot() on... | Python Code:
import regionmask
regionmask.__version__
Explanation: Plotting
Every region has two plotting functions, which draw the outlines of all regions:
plot: draws the region polygons on a cartopy GeoAxes (map)
plot_regions: draws the the region polygons only
Import regionmask and check the version:
End of explana... |
1,065 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chopsticks!
A few researchers set out to determine the optimal length of chopsticks for children and adults. They came up with a measure of how effective a pair of chopsticks performed, call... | Python Code:
import pandas as pd
# pandas is a software library for data manipulation and analysis
# We commonly use shorter nicknames for certain packages. Pandas is often abbreviated to pd.
# hit shift + enter to run this cell or block of code
path = r'~/Downloads/chopstick-effectiveness.csv'
# Change the path to the... |
1,066 | 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... |
1,067 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Temporal sampling
Sampling nothing
Let's evolve 40 populations to mutation-drift equilibrium
Step1: Take samples from population
Step2: The output from this particular sampler type is a ge... | Python Code:
import fwdpy as fp
import numpy as np
import pandas as pd
nregions=[fp.Region(0,1,1)]
sregions=[fp.GammaS(0,1,0.1,0.1,0.1,1.0),
fp.GammaS(0,1,0.9,-0.2,9.0,0.0)
]
recregions=nregions
N=1000
nlist=np.array([N]*(10*N),dtype=np.uint32)
mutrate_neutral=50.0/float(4*N)
recrate=mutrate_neutral
... |
1,068 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Extra 3.1 - Historical Provenance - Application 2
Step1: Labelling data
Based on its trust value, we categorise the data entity into two sets
Step2: Having used the trust valuue to label a... | Python Code:
import pandas as pd
df = pd.read_csv("collabmap/ancestor-graphs.csv", index_col='id')
df.head()
df.describe()
Explanation: Extra 3.1 - Historical Provenance - Application 2: CollabMap Data Quality
Assessing the quality of crowdsourced data in CollabMap from their provenance.
In this notebook, we explore th... |
1,069 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 The TF-Agents Authors.
Step1: DQN C51/Rainbow
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Hyperparameters
Step3: Envi... | 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... |
1,070 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Indexing
Okay guys today's lecture is indexing.
What is indexing?
At heart, indexing is the ability to inspect a value inside a object. So basically if we have a list, X, of 100 items and ... | Python Code:
# flipping signs of numbers...
a = 5
b = -5
print(-a, -b)
# len function
x1 = []
x2 = "12"
x3 = [1,2,3]
print(len(x1), len(x2), len(x3))
x = [1,2,3]
print(x[100]) # <--- IndexError! 100 is waayyy out of bounds
Explanation: Indexing
Okay guys today's lecture is indexing.
What is indexing?
At heart, indexi... |
1,071 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notes on Numpy Arrays and Panda's Series and DataFrames
We need to import the numpy and pandas libraries before using them in this notebook
Step1: Intro to Numpy Arrays
Here create a 1-dime... | Python Code:
import numpy as np
import pandas as pd
Explanation: Notes on Numpy Arrays and Panda's Series and DataFrames
We need to import the numpy and pandas libraries before using them in this notebook
End of explanation
array = np.array([1,2,3,4],float)
array
Explanation: Intro to Numpy Arrays
Here create a 1-dimen... |
1,072 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Read in the Kobe Bryant shooting data [https
Step1: For now, use just the numerical datatypes. They are below as num_columns
Step2: The shot_made_flag is the result (0 or 1) of the shot th... | Python Code:
kobe = pd.read_csv('../data/kobe.csv')
Explanation: Read in the Kobe Bryant shooting data [https://www.kaggle.com/c/kobe-bryant-shot-selection]
End of explanation
[(col, dtype) for col, dtype in zip(kobe.columns, kobe.dtypes) if dtype != 'object']
num_columns = [col for col, dtype in zip(kobe.columns, kobe... |
1,073 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Re-referencing the EEG signal
This example shows how to load raw data and apply some EEG referencing schemes.
Step1: We will now apply different EEG referencing schemes and plot the resulti... | Python Code:
# Authors: Marijn van Vliet <w.m.vanvliet@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@inria.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_path()
raw_fna... |
1,074 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Digital Comics Data Analysis (Python) - Marvel or DC?
Introduction
After having done the analysis of the website (post here and the web scraping of the data from the Comixology website (post... | Python Code:
import warnings
warnings.filterwarnings('ignore')
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
comixology_df = pd.read_csv("comixology_comics_dataset_19.04.2016.csv",
encoding = "ISO-8859-1")
Explanation: Digital Comics Data Analy... |
1,075 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Simple Autoencoder
We'll start off by building a simple autoencoder to compress the MNIST dataset. With autoencoders, we pass input data through an encoder that makes a compressed represen... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', validation_size=0)
Explanation: A Simple Autoencoder
We'll ... |
1,076 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fitting Models Exercise 1
Imports
Step1: Fitting a quadratic curve
For this problem we are going to work with the following model
Step2: First, generate a dataset using this model using th... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize as opt
Explanation: Fitting Models Exercise 1
Imports
End of explanation
a_true = 0.5
b_true = 2.0
c_true = -4.0
dy = 2.0
x = np.linspace(-5,5,30)
Explanation: Fitting a quadratic curve
For this problem we are going... |
1,077 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Stroop Task
Background Information
In a Stroop task, participants are presented with a list of words, with each word displayed in a color of ink. The participant’s task is to say out ... | Python Code:
import math
import pandas as pd
import scipy.stats as st
from IPython.display import Latex
from IPython.display import Math
from IPython.display import display
%matplotlib inline
path = r'./stroopdata.csv'
df_stroop = pd.read_csv(path)
df_stroop
mu_congruent = round(df_stroop['Congruent'].mean(),4)
mu_inco... |
1,078 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have a dataframe with column names, and I want to find the one that contains a certain string, but does not exactly match it. I'm searching for 'spike' in column names like 'spike... | Problem:
import pandas as pd
data = {'spike-2': [1,2,3], 'hey spke': [4,5,6], 'spiked-in': [7,8,9], 'no': [10,11,12]}
df = pd.DataFrame(data)
s = 'spike'
def g(df, s):
spike_cols = [col for col in df.columns if s in col and col != s]
return df[spike_cols]
result = g(df.copy(),s) |
1,079 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Working with data 2017. Class 8
Contact
Javier Garcia-Bernardo
garcia@uva.nl
1. Clustering
2. Data imputation
3. Dimensionality reduction
Step1: 3. Dimensionality reduction
Many times we wa... | Python Code:
##Some code to run at the beginning of the file, to be able to show images in the notebook
##Don't worry about this cell
#Print the plots in this screen
%matplotlib inline
#Be able to plot images saved in the hard drive
from IPython.display import Image
#Make the notebook wider
from IPython.core.display ... |
1,080 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
graded = 9/9
Homework assignment #3
These problem sets focus on using the Beautiful Soup library to scrape web pages.
Problem Set #1
Step1: Now, in the cell below, use Beautiful Soup to wri... | Python Code:
from bs4 import BeautifulSoup
from urllib.request import urlopen
html_str = urlopen("http://static.decontextualize.com/widgets2016.html").read()
document = BeautifulSoup(html_str, "html.parser")
Explanation: graded = 9/9
Homework assignment #3
These problem sets focus on using the Beautiful Soup library to... |
1,081 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic MR
Class
Step1: Spin Velocity
When an atomic species with net spin is placed in a steady magnetic field, it precesses at a frequency that is characteristic of that species and that v... | Python Code:
%pylab inline
import matplotlib as mpl
mpl.rcParams["figure.figsize"] = (8, 6)
mpl.rcParams["axes.grid"] = True
from IPython.display import display
from ipywidgets import interact,FloatSlider
Explanation: Basic MR
Class: Psych 204a
Tutorial: Basic MR
Duration: 90 minutes
Authors: Originally writte... |
1,082 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Send email Clint
Importing all dependency
Step1: User Details Function
Step2: Login function
In this function we call user details function and get the user name and password, Than we use ... | Python Code:
# ! /usr/bin/python
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.header import Header
from email.utils import formataddr
import getpass
Explanation: Send email Clint
Importing all dependency
End of explanation
def user():
# ORG_EMAIL = "@... |
1,083 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Optimizing ORM Queries
Introduction
This notebook provides some background on the various extractor queries. These queries are on the Submission model which has foreign key relationships on... | Python Code:
import sys
import sqlalchemy as sa
import sqlalchemy.orm as sa_orm
import testing.postgresql
from app import models
from app.util import sqldebug
# open a test session
postgresql = testing.postgresql.Postgresql(base_dir='.test_db')
db_engine = sa.create_engine(postgresql.url())
models.init_database(db_engi... |
1,084 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Finding similar documents with Word2Vec and WMD
Word Mover's Distance is a promising new tool in machine learning that allows us to submit a query and return the most relevant documents. For... | Python Code:
from time import time
start_nb = time()
# Initialize logging.
import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s')
sentence_obama = 'Obama speaks to the media in Illinois'
sentence_president = 'The president greets the press in Chicago'
sentence_obama = sentence_obama.lowe... |
1,085 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Keras with MNIST
Import various modules that we need for this notebook.
Step1: Load the MNIST dataset, flatten the images, convert the class labels, and scale the data.
Step... | Python Code:
%pylab inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD, RMSprop
from keras.utils import np_utils
from keras.regularize... |
1,086 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training Visualization
In this part we’ll see how to create a simple but wrong model with Keras, and, gradually, how it can be improved with step-by-step debugging and understanding with Ten... | Python Code:
from keras.models import Model
from keras.layers import Convolution2D, BatchNormalization, MaxPooling2D, Flatten, Dense
from keras.layers import Input, Dropout
from keras.layers.advanced_activations import ELU
from keras.regularizers import l2
from keras.optimizers import SGD
import tensorflow as tf
from s... |
1,087 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Language Translation
In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset o... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
Explanation: Language Translation
In this project, you’re going ... |
1,088 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
So, this is all about the innocent little ✱ (star or asterisk) as a versatile syntax element in Python. Depending on the context, it fulfills quite a few different roles. Here is a pi... | Python Code:
# Yes. The code makes no sense. Thanks for pointing it out.
from os import *
def append(*, end=linesep):
def _append(function):
def star_reporter(*args, **kwargs):
print(*args, **kwargs, end=end)
return function(*args, **kwargs)
return star_reporter
return _a... |
1,089 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Initialisation
Ecrire un jeu d'instructions permettant
d'initialiser la vitesse de chacun des moteurs à 30°/s.
de mettre les moteurs poppy.m1 à poppy.m6 dans les positions données par la li... | Python Code:
i = 0
pos_init = [0, -90, 30, 0, 60, 0]
for m in poppy.motors:
m.moving_speed = 60
m.compliant = False
m.goal_position = pos_init[i]
i = i + 1
Explanation: Initialisation
Ecrire un jeu d'instructions permettant
d'initialiser la vitesse de chacun des moteurs à 30°/s.
de mettre les moteurs ... |
1,090 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2-3 Trees
Step1: Ths notebook presents <a href="https
Step2: The function make_string is a helper function used to shorten the implementation of __str__.
- obj is the object that is to b... | Python Code:
import graphviz as gv
Explanation: 2-3 Trees
End of explanation
class TwoThreeTree:
sNodeCount = 0
def __init__(self):
TwoThreeTree.sNodeCount += 1
self.mID = TwoThreeTree.sNodeCount
def getID(self):
return self.mID
def isNil(self):
ret... |
1,091 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multi-state complexes
<div class="admonition note">
**Topics**
Step1: As usual, we first need to import required modules and define a Model object. The creation of subunit states and subuni... | Python Code:
import steps.interface
from steps.model import *
mdl = Model()
with mdl:
A0, A1, A2 = SubUnitState.Create()
ASU = SubUnit.Create([A0, A1, A2])
CA = Complex.Create([ASU, ASU, ASU, ASU], statesAsSpecies=True)
Explanation: Multi-state complexes
<div class="admonition note">
**Topics**: C... |
1,092 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<img src="http
Step1: <div id='intro' />
Introduction
Back to TOC
In this jupyter notebook we will study the behaviour of a ABSRF (A Bad and Slow Root Finder).
Notice that we h... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import sympy as sym
sym.init_printing()
import bitstring as bs
import pandas as pd
pd.set_option("display.colheader_justify","center")
pd.options.display.float_format = '{:.10f}'.format
# This function shows the bits used for the sign, exponent and mantiss... |
1,093 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
가우시안 정규 분포
가우시안 정규 분포(Gaussian normal distribution), 혹은 그냥 간단히 정규 분포라고 부르는 분포는 자연 현상에서 나타나는 숫자를 확률 모형으로 모형화할 때 가장 많이 사용되는 확률 모형이다.
정규 분포는 평균 $\mu$와 분산 $\sigma^2$ 이라는 두 개의 모수만으로 정의되며 확률 밀도 함수... | Python Code:
mu = 0
std = 1
rv = sp.stats.norm(mu, std)
rv
Explanation: 가우시안 정규 분포
가우시안 정규 분포(Gaussian normal distribution), 혹은 그냥 간단히 정규 분포라고 부르는 분포는 자연 현상에서 나타나는 숫자를 확률 모형으로 모형화할 때 가장 많이 사용되는 확률 모형이다.
정규 분포는 평균 $\mu$와 분산 $\sigma^2$ 이라는 두 개의 모수만으로 정의되며 확률 밀도 함수(pdf: probability density function)는 다음과 같은 수식을 가진다.
$$ \m... |
1,094 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dynamic factors and coincident indices
Factor models generally try to find a small number of unobserved "factors" that influence a subtantial portion of the variation in a larger number of o... | Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
np.set_printoptions(precision=4, suppress=True, linewidth=120)
from pandas.io.data import DataReader
# Get the datasets from FRED
start = '1979-01-01'
end = '2014-12-01'
indprod = DataRead... |
1,095 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
错误可视化
对于任何科学的度量，准确地计算错误几乎和准确报告数字本身一样重要，甚至更为重要。例如，假设我正在使用一些天体观测来估计哈勃常数，这是对宇宙膨胀率的局部测量。我知道，目前的文献表明该值约为71（km / s）/ Mpc，我用我的方法测得的值为74（km / s）/ Mpc。值是否一致？给定此信息，唯一正确的答案是：没有办法知道。
假设我用报告的不确定性来补充此信息：当... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('seaborn-whitegrid')
import numpy as np
x = np.linspace(0, 10, 50)
dy = 0.8
y = np.sin(x) + dy * np.random.randn(50)
# yerr表示y的误差
plt.errorbar(x, y, yerr=dy, fmt='.k');
Explanation: 错误可视化
对于任何科学的度量，准确地计算错误几乎和准确报告数字本身一样重要，甚至更为重要。例如，假设我正在使用一些天体... |
1,096 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bar plot demo
This example shows you how to make a bar plot using the psyplot.project.ProjectPlotter.barplot method.
Step1: The default is that all bars have the same width. You can however... | Python Code:
import psyplot.project as psy
%matplotlib inline
%config InlineBackend.close_figures = False
axes = iter(psy.multiple_subplots(2, 2, n=3))
for var in ['t2m', 'u', 'v']:
psy.plot.barplot(
'demo.nc', # netCDF file storing the data
name=var, # one plot for each variable
y=[0, 1], ... |
1,097 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PDF Analysis Tutorial
Introduction
This tutorial demonstrates how to acquire a multidimensional pair distribution function (PDF) from both a flat field electron diffraction pattern and a sca... | Python Code:
%matplotlib inline
import hyperspy.api as hs
import pyxem as pxm
import numpy as np
Explanation: PDF Analysis Tutorial
Introduction
This tutorial demonstrates how to acquire a multidimensional pair distribution function (PDF) from both a flat field electron diffraction pattern and a scanning electron diffr... |
1,098 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ClickDetector use example
This algorithm detects the locations of impulsive noises (clicks and pops) on
the input audio frame. It relies on LPC coefficients to inverse-filter the
audio in or... | Python Code:
import essentia.standard as es
import numpy as np
import matplotlib.pyplot as plt
from IPython.display import Audio
from essentia import array as esarr
plt.rcParams["figure.figsize"] =(12,9)
def compute(x, frame_size=1024, hop_size=512, **kwargs):
clickDetector = es.ClickDetector(frameSize=frame_size,... |
1,099 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
automaton.compose
The (accessible part of the) composition of two transducers ($A_1$ and $A_2$).
Preconditions
Step1: The result of the composition has a useless state. Note that only the a... | Python Code:
import vcsn
ctx1 = vcsn.context("lat<lal<char(ab)>, lal<char(jk)>>, b")
ctx2 = vcsn.context("lat<lal<char(jk)>, lal<char(xy)>>, b")
a1 = ctx1.expression("(a|k)(a|j) + (b|k)*").automaton()
a1
a2 = ctx2.expression("(k|y)(k|x)*").automaton()
a2
Explanation: automaton.compose
The (accessible part of the) compo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.