Unnamed: 0 int64 0 16k | text_prompt stringlengths 110 62.1k | code_prompt stringlengths 37 152k |
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13,400 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Prepare a minimal data set.
Step1: Plotting separate data columns as separate sub-plots
Step2: Plot multiple groups (from same data columns) onto the same plot.
Step3: Jake Vanderplas | Python Code:
df = pd.DataFrame({'age':[1.,2,3,4,5,6,7,8,9],
'height':[4, 4.5, 5, 6, 7, 8, 9, 9.5, 10],
'gender':['M','F', 'F','M','M','F', 'F','M', 'F'],
#'hair color':['brown','black', 'brown', 'blonde', 'brown', 'red',
# 'brown'... |
13,401 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CSAL4243
Step1: Logistic Regression
Step2: <br>
Iris Flower Dataset
Using sepal length and width, predict the type of flower.
K - Nearest Neighbor (kNN) Classifier
Step3: <br>
Logistic Re... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
from sklearn import neighbors
df = pd.read_csv('datasets/exam_dataset1.csv', encoding='utf-8')
n_neighbors = 5
X = np.array(df[['exam1','exam2']])
y = np.array(df[['admission']]).ravel()
h = ... |
13,402 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic ploting
Generate coordinate vectors
Step1: Generate coordinate matrices
Step2: Compute function value
Step3: Plot contours
Step4: Plot Decision Boundary
First, generate the data an... | Python Code:
nx, ny = 100, 100
x = np.linspace(-5, 5, nx)
y = np.linspace(-5, 5, ny)
Explanation: Basic ploting
Generate coordinate vectors
End of explanation
xx, yy = np.meshgrid(x, y, sparse=True)
Explanation: Generate coordinate matrices
End of explanation
z = np.sin(xx**2 + yy**2) / (xx**2 + yy**2)
Explanation: Com... |
13,403 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Get the Data
Set index_col=0 to use the first column as the index.
Step2: Standardize the Variables
Because the KNN classifier predicts the class of a given test obser... | Python Code:
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
K Nearest Neighbors with Python
You've been given a classified data set from a company! They've hidde... |
13,404 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced
Step1: Default Systems
Although the default empty Bundle doesn't include a system, there are available
constructors that create default systems. To create a simple binary with com... | Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.Bundle()
Explanation: Advanced: Building a System
Setup
Let's first make sure we have the latest version of PHOEBE 2.4 installed (uncomment t... |
13,405 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Language Translation
Student
Step3: Explore the Data
Play around with view_sentence_range to view different parts of the data.
Step6: Implement Preprocessing Function
Text to Word I... | 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
Student: Angel Martinez-Tenor ... |
13,406 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
WNixalo
2018/2/11 17
Step1: 1.
Consider the polynomial $p(x) = (x-2)^9 = x^9 - 18x^8 + 144x^7 - 672x^6 + 2016x^5 - 4032x^4 + 5376x^3 - 4608x^2 + 2304x - 512$
a. Plot $p(x)$ for $x=1.920,\,1... | Python Code:
%matplotlib inline
import numpy as np
import torch as pt
import matplotlib.pyplot as plt
plt.style.use('seaborn')
Explanation: WNixalo
2018/2/11 17:51
Homework No.1
End of explanation
def p(x, mode=0):
if mode == 0:
return x**9 - 18*x**8 + 144*x**7 - 672*x**6 + 2016*x**5 - 4032*x**4 + 5376*x**3... |
13,407 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This notebook is the computational appendix of arXiv
Step1: Checking criticial visibility
The question whether a qubit or qutrit POVM is simulable by projective measurements bo... | Python Code:
from __future__ import print_function, division
from fractions import Fraction
import numpy as np
import numpy.linalg
import random
import time
from povm_tools import basis, check_ranks, complex_cross_product, dag, decomposePovmToProjective, \
enumerate_vertices, find_best_shrinking_factor, get_random_... |
13,408 | 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... |
13,409 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2A.eco - Mise en pratique des séances 1 et 2 - Utilisation de pandas et visualisation - correction
Correction de l'exercice 3 et disponibilités des velibs.
Step1: Exercice 3 - Disponibilité... | Python Code:
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
from pyensae.datasource import download_data
files = download_data("td2a_eco_exercices_de_manipulation_de_donnees.zip",
url="https://github.com/sdpython/ensae_teaching_cs/raw/master/_doc/notebooks/td2a_... |
13,410 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
MNIST
Step1: Dataset description
Datasource
Step2: Distribution of class frequencies
Step3: Chisquare test on class frequencies
Step4: Display a few sample images
Step5: View different ... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import *
import scipy
%matplotlib inline
Explanation: MNIST
End of explanation
training = pd.read_csv("/data/MNIST/mnist_train.csv", header = None)
testing = pd.read_csv("/data/MNIST/mnist_test.csv", header = None)
X_train,... |
13,411 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fire up graphlab create
Step1: Load some house value vs. crime rate data
Dataset is from Philadelphia, PA and includes average house sales price in a number of neighborhoods. The attribute... | Python Code:
%matplotlib inline
import graphlab
Explanation: Fire up graphlab create
End of explanation
sales = graphlab.SFrame.read_csv('Philadelphia_Crime_Rate_noNA.csv/')
sales
Explanation: Load some house value vs. crime rate data
Dataset is from Philadelphia, PA and includes average house sales price in a number o... |
13,412 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to the 'First steps with pandas'!
After this workshop you can (hopefully) call yourselves Data Scientists!
Gitter
Step1: What is pandas?
pandas is an open source, BSD-licensed libra... | Python Code:
import platform
print('Python: ' + platform.python_version())
import numpy as np
print('numpy: ' + np.__version__)
import pandas as pd
print('pandas: ' + pd.__version__)
import scipy
print('scipy: ' + scipy.__version__)
import sklearn
print('scikit-learn: ' + sklearn.__version__)
import matplotlib as plt
p... |
13,413 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Budyko Transport for Energy Balance Models
In this document an Energy Balance Model (EBM) is set up with the energy tranport parametrized through the the budyko type parametrization term (in... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import climlab
from climlab import constants as const
Explanation: Budyko Transport for Energy Balance Models
In this document an Energy Balance Model (EBM) is set up with the energy tranport parametrized through the the budyko type para... |
13,414 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Analyzing public cloud and hybrid networks
Public cloud and hybrid networks can be hard to debug and secure. Many of the standard tools (e.g., traceroute) do not work in the cloud set... | Python Code:
# Import packages
%run startup.py
bf = Session(host="localhost")
def show_first_trace(trace_answer_frame):
Prints the first trace in the answer frame.
In the presence of multipath routing, Batfish outputs all traces
from the source to destination. This function picks the first one.
... |
13,415 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
k-Nearest Neighbor (kNN) exercise
Complete and hand in this completed worksheet (including its outputs and any supporting code outside of the worksheet) with your assignment submission. For ... | Python Code:
# Run some setup code for this notebook.
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
from __future__ import print_function
# This is a bit of magic to make matplotlib figures appear inline in the notebook
# rather than in a new window.
%matplo... |
13,416 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
pupil_new explanation (in detail)
This is a notebook on explaining deeplabcut workflow (Detailed version)
Let's import pupil first (and datajoint)
Step1: OK, now let's see what is under pup... | Python Code:
import datajoint as dj
from pipeline import pupil
Explanation: pupil_new explanation (in detail)
This is a notebook on explaining deeplabcut workflow (Detailed version)
Let's import pupil first (and datajoint)
End of explanation
dj.ERD(pupil.schema)
Explanation: OK, now let's see what is under pupil module... |
13,417 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Convolutional Neural Networks
Welcome to the first week of the first deep learning certificate! We're going to use convolutional neural networks (CNNs) to allow our computer to see - s... | Python Code:
%matplotlib inline
#change image dim ordering?
# from keras import backend
# backend.set_image_dim_ordering('th')
Explanation: Using Convolutional Neural Networks
Welcome to the first week of the first deep learning certificate! We're going to use convolutional neural networks (CNNs) to allow our computer ... |
13,418 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First, import the processing tools that contain classes and methods to read, plot and process standard unit particle distribution files.
Step1: The module consists of a class 'ParticleDistr... | Python Code:
import processing_tools as pt
Explanation: First, import the processing tools that contain classes and methods to read, plot and process standard unit particle distribution files.
End of explanation
filepath = './example/example.h5'
data = pt.ParticleDistribution(filepath)
data.su2si
data.dict['x']
Explana... |
13,419 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basic Cheshire objects and methods
This file wants to document how one can use Cheshire to query the CLiC database.
It fills in the gaps of the official cheshire documentation and it
provi... | Python Code:
# coding: utf-8
import os
from cheshire3.baseObjects import Session
from cheshire3.document import StringDocument
from cheshire3.internal import cheshire3Root
from cheshire3.server import SimpleServer
session = Session()
session.database = 'db_dickens'
serv = SimpleServer(session, os.path.join(cheshire3... |
13,420 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Use of PYBIND11_MAKE_OPAQUE
pybind11 automatically converts std
Step1: Two identical classes
Both of then creates random vectors equivalent to std
Step2: Scenarii
Three possibilities | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
%matplotlib inline
Explanation: Use of PYBIND11_MAKE_OPAQUE
pybind11 automatically converts std::vector into python list. That's convenient but not necessarily efficient depending on how it is used after that. PYBIND11_MAKE_OPAQUE is used to c... |
13,421 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1"><a href="#Seriation-Classification
Step1: sklearn-mmadsen is a python package of useful machine learning tools that I'm accumulating for research and ... | Python Code:
import numpy as np
import networkx as nx
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
import cPickle as pickle
from copy import deepcopy
from sklearn.metrics import classification_report, accuracy_score, confusion_matrix
train_graphs = pickle.load(open("train... |
13,422 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Read HIV Data
Step1: Read in Clinical Data
Step2: Update clinical data with new data provided by Howard Fox
Step3: Clean up diabetes across annotation files
Step4: All of the patients ar... | Python Code:
import os
if os.getcwd().endswith('Setup'):
os.chdir('..')
import NotebookImport
from Setup.Imports import *
Explanation: Read HIV Data
End of explanation
c1 = pd.read_excel(ucsd_path + 'DESIGN_Fox_v2_Samples-ChipLAyout-Clinical UNMC-UCSD methylomestudy.xlsx',
'HIV- samples from Old... |
13,423 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Encontro 22
Step1: Início da Atividade 1
Definindo uma função que gera um grafo aleatório tal que a probabilidade de uma aresta existir é c sobre o número de nós
Step2: Gerando um grafo pa... | Python Code:
import sys
sys.path.append('..')
import socnet as sn
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Encontro 22: Mundos Pequenos
Importando as bibliotecas:
End of explanation
from random import random
def generate_random_graph(num_nodes, c):
g = sn.generate_empty_graph(num_nodes)
... |
13,424 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reinforcement Learning
Step1: Ok, on to the agent itself. I'll present the code in full here, then explain parts in more detail.
Step2: You'll see that this is quite similar to the previou... | Python Code:
import numpy as np
from blessings import Terminal
class Game():
def __init__(self, shape=(10,10)):
self.shape = shape
self.height, self.width = shape
self.last_row = self.height - 1
self.paddle_padding = 1
self.n_actions = 3 # left, stay, right
self.term ... |
13,425 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: グラフと tf.function の基礎
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: 一方、Function は、TensorFl... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
13,426 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Вопросы по прошлому занятию
Что найдет регулярка "^\d+.\d{1,2}.\d{1,2}\s[^A-Z]?$" ?
Что делает функция filter(lambda s
Step1: Упражнение
Написать класс RangeCounter, который принимает начал... | Python Code:
a = 1
b = 3
a + b
a.__add__(b)
type(a)
isinstance(a, int)
class Animal(object):
mammal = True # class variable
def __init__(self, name, voice, color="black"):
self.name = name
self.__voice = voice # "приватный" или "защищенный" атрибут
self._color = color # "тип... |
13,427 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Acme
Step1: Installation
Install Acme
Step2: Install the environment library
Step3: Install visualization packages
Step4: Import Modules
Step5: Load an environment
We can now load an en... | Python Code:
environment_library = 'gym' # @param ['dm_control', 'gym']
Explanation: Acme: Quickstart
Guide to installing Acme and training your first D4PG agent.
<a href="https://colab.research.google.com/github/deepmind/acme/blob/master/examples/quickstart.ipynb" target="_parent"><img src="https://colab.research.goo... |
13,428 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 6
Imports
Put the standard imports for Matplotlib, Numpy and the IPython widgets in the following cell.
Step1: Exploring the Fermi distribution
In quantum statistics, the ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.display import Image
from IPython.html.widgets import interact, interactive, fixed
Explanation: Interact Exercise 6
Imports
Put the standard imports for Matplotlib, Numpy and the IPython widgets in the following cell.
End of... |
13,429 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: Build a digit classifier app with TensorFlow Lite
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
S... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
13,430 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook used to develop code
output from classification is data frame with slave_logs (maybe rename that column?) indicating
Step1: Load and clean data
Load CLIWOC ship logs
Step2: Find d... | Python Code:
classifier_algorithm = "Decision Tree"
import collections
import exploringShipLogbooks
import numpy as np
import os.path as op
import pandas as pd
import exploringShipLogbooks.wordcount as wc
from fuzzywuzzy import fuzz
from sklearn import preprocessing
from sklearn.naive_bayes import MultinomialNB
from sk... |
13,431 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
For more info on Myria, access to the demo cluster, and setting up a cluster
Step1: MyriaL Basics
First you would scan in whatever tables you want to use in that cell.
These are the tables... | Python Code:
# myria-python functionality
from myria import *
# myriaL cell functionality
%load_ext myria
# connection for myria-python functionality
connection = MyriaConnection(rest_url='http://localhost:8753')
# same as: http://ec2-52-36-55-94.us-west-2.compute.amazonaws.com:8753
# connection for myriaL cell functio... |
13,432 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FloPy
Quick demo on how FloPy handles external files for arrays
Step1: make an hk and vka array. We'll save hk to files - pretent that you spent months making this important model property... | Python Code:
import os
import sys
import shutil
import numpy as np
import flopy
print(sys.version)
print('numpy version: {}'.format(np.__version__))
print('flopy version: {}'.format(flopy.__version__))
# make a model
nlay,nrow,ncol = 10,20,5
model_ws = os.path.join("data","external_demo")
if os.path.exists(model_ws):
... |
13,433 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Step1: Trying that with a real picture
Step2: A color image is a 3D array, where the last dimension has size 3 and represents the red, green, and blue channels
Step3: These a... | Python Code:
import numpy as np
r = np.random.rand(500, 500)
from matplotlib import pyplot as plt, cm
plt.imshow(r, cmap=cm.gray, interpolation='nearest')
Explanation: Introduction: images are numpy arrays
A grayscale image is just a 2D array:
End of explanation
from skimage import data
coins = data.coins()
print(type(... |
13,434 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex client library
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Once you've installed the Vertex client library and Google clo... | Python Code:
import os
import sys
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install -U google-cloud-aiplatform $USER_FLAG
Explanation: Vertex client library: Custom training image super resolution model for online predic... |
13,435 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Distribution
the way in which something is shared out among a group or spread over an area
Random Variable
a variable whose value is subject to variations due to chance (i.e. randomness, in ... | Python Code:
import pandas as pd
import seaborn as sns
sns.set(color_codes=True)
%matplotlib inline
#Import the data
cars = pd.read_csv("cars_v1.csv", encoding="ISO-8859-1")
#Replace missing values in Mileage with mean
cars.Mileage.fillna(cars.Mileage.mean(), inplace=True)
sns.distplot(cars.Mileage, kde=False)
Explanat... |
13,436 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Практическое задание к уроку 1 (2 неделя).
Линейная регрессия
Step1: Мы будем работать с датасетом "bikes_rent.csv", в котором по дням записаны календарная информация и погодные условия, ха... | Python Code:
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
Explanation: Практическое задание к уроку 1 (2 неделя).
Линейная регрессия: переобучение и регуляризация
В этом задании мы на примерах увидим, как переобучаются линейные модели, разберем, почему так происходит, и... |
13,437 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SciPy 시작하기
SciPy란
과학기술계산용 함수 및 알고리즘 제공
Home
http
Step1: scipy.constants 상수
특별 상수
scipy.pi
기타 상수
scipy.constants.XXXX
단위
yotta, zetta, exa, peta, tera, giga, mega, kilo, hecto, deka
deci,... | Python Code:
rv = sp.stats.norm(loc=10, scale=10)
rv.rvs(size=(3, 10), random_state=1)
sns.distplot(rv.rvs(size=10000, random_state=1))
xx = np.linspace(-40, 60, 1000)
pdf = rv.pdf(xx)
plt.plot(xx, pdf)
cdf = rv.cdf(xx)
plt.plot(xx, cdf)
Explanation: SciPy 시작하기
SciPy란
과학기술계산용 함수 및 알고리즘 제공
Home
http://www.scipy.org/
Doc... |
13,438 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Competition site
http
Step1: Constants
Step2: Data Loading
- Costs Data
Step3: - Elevation Data
Step4: - Sample Data
Parcels that have already been auctioned and exploited (see the gold_... | Python Code:
import pandas as pd
pd.set_option('display.float_format', '{:.2f}'.format)
import numpy as np
import matplotlib.pyplot as plt
%matplotlib notebook
Explanation: Competition site
http://www.kaybensoft.com/dublinr/10_competition_site.html
Imports
End of explanation
total_budget = 50000000
gold_price = 1500 # ... |
13,439 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 컨볼루셔널 변이형 오토인코더
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: MNIST 데이터세트 로드하기
각 MNIST 이미지는 원래... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
13,440 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tracking Parameters and Metrics for Vertex AI Custom Training Jobs
Learning objectives
In this notebook, you learn how to
Step1: Please ignore the incompatibility errors.
Restart the kernel... | Python Code:
import os
# The Google Cloud Notebook product has specific requirements
IS_GOOGLE_CLOUD_NOTEBOOK = os.path.exists("/opt/deeplearning/metadata/env_version")
# Google Cloud Notebook requires dependencies to be installed with '--user'
USER_FLAG = ""
if IS_GOOGLE_CLOUD_NOTEBOOK:
USER_FLAG = "--user"
# Inst... |
13,441 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1><span style="color
Step1: Simulate a gene tree with 14 tips and MRCA of 1M generations
Step2: Simulate sequences on single gene tree and write to NEXUS
When Ne is greater the gene tree... | Python Code:
# conda install ipyrad -c conda-forge -c bioconda
# conda install mrbayes -c conda-forge -c bioconda
# conda install ipcoal -c conda-forge
import toytree
import ipcoal
import ipyrad.analysis as ipa
Explanation: <h1><span style="color:gray">ipyrad-analysis toolkit:</span> mrbayes</h1>
In these analyses our ... |
13,442 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The EOH (Evolution of Hamiltonian) Algorithm
This notebook demonstrates how to use the Qiskit Aqua library to invoke the EOH algorithm and process the result.
Further information may be foun... | Python Code:
import numpy as np
from qiskit_aqua.operator import Operator
num_qubits = 2
temp = np.random.random((2 ** num_qubits, 2 ** num_qubits))
qubitOp = Operator(matrix=temp + temp.T)
temp = np.random.random((2 ** num_qubits, 2 ** num_qubits))
evoOp = Operator(matrix=temp + temp.T)
Explanation: The EOH (Evolution... |
13,443 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Sample programs
Before working on the following programming examples, it is necessary to upload some text files to Colab. For that, select the folder icon on the left ... | Python Code:
from IPython.display import Image
from IPython.core.display import HTML
Image(url= "https://github.com/OSGeoLabBp/tutorials/blob/master/english/data_processing/lessons/images/file_proc.png?raw=true")
Explanation: <a href="https://colab.research.google.com/github/OSGeoLabBp/tutorials/blob/master/english/da... |
13,444 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Lecture 3
Step2: <h1>Discrete Fourier Series</h1>
Consider a function $f$ periodic over a domain $0\leq x\leq 2\pi$, discretized by $N_x$ points. The longest wavelength wave that can... | Python Code:
%matplotlib inline
# plots graphs within the notebook
%config InlineBackend.figure_format='svg' # not sure what this does, may be default images to svg format
from IPython.display import Image
from IPython.core.display import HTML
def header(text):
raw_html = '<h4>' + str(text) + '</h4>'
return ra... |
13,445 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SVC Test
This is an example use case of a support vector classifier. We will infer a data classification function from a set of training data.
We will use the SVC implementation in the sciki... | Python Code:
from sklearn import svm
import pandas as pd
import pylab as pl
import seaborn as sns
%matplotlib inline
Explanation: SVC Test
This is an example use case of a support vector classifier. We will infer a data classification function from a set of training data.
We will use the SVC implementation in the sciki... |
13,446 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright (c) 2017-2020 Serpent-Tools developers team, GTRC
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF... | Python Code:
import os
mdxFile = os.path.join(
os.environ["SERPENT_TOOLS_DATA"],
"ref_mdx0.m",
)
Explanation: Copyright (c) 2017-2020 Serpent-Tools developers team, GTRC
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABI... |
13,447 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
python生成器
本文讲解一下python生成器的基本用法。
生成器的使用场景
当数据量很大的时候，比如从一个超大文本文件中读取内容，如果一下子把数据全部放在列表中，相当于一下子把大量数据放在了内存中，有可能造成内存溢出。那么如何解决呢？
解决方案：不存储所有的数据，而是存储列表元素的生成算法（相当于递推公式），只在使用的时候再根据生成算法生成相应的元素（惰性计算），这就是生... | Python Code:
a = (x for x in range(3))
print '【Output】'
print type(a)
print a.next()
print '-----'
for x in a:
print x
Explanation: python生成器
本文讲解一下python生成器的基本用法。
生成器的使用场景
当数据量很大的时候，比如从一个超大文本文件中读取内容，如果一下子把数据全部放在列表中，相当于一下子把大量数据放在了内存中，有可能造成内存溢出。那么如何解决呢？
解决方案：不存储所有的数据，而是存储列表元素的生成算法（相当于递推公式），只在使用的时候再根据生成算法生成相应的元素（惰性计算... |
13,448 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
svgpathtools
svgpathtools is a collection of tools for manipulating and analyzing SVG Path objects and Bézier curves.
Features
svgpathtools contains functions designed to easily read, write ... | Python Code:
from __future__ import division, print_function
# Coordinates are given as points in the complex plane
from svgpathtools import Path, Line, QuadraticBezier, CubicBezier, Arc
seg1 = CubicBezier(300+100j, 100+100j, 200+200j, 200+300j) # A cubic beginning at (300, 100) and ending at (200, 300)
seg2 = Line(20... |
13,449 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kubeflow E2E MNIST Case
Step1: Configure the Docker Registry for Kubeflow Fairing
In order to build docker images from your notebook we need a docker registry where the images will be store... | Python Code:
!pip show kubeflow-fairing
Explanation: Kubeflow E2E MNIST Case: Building, Distributed Training and Serving
This example guides you through:
1. Taking an example TensorFlow model and modifying it to support distributed training.
1. Using Kubeflow Fairing to build docker image and launch a TFJob to trai... |
13,450 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<h1> ILI285 - Computación Científica I / INF285 - Computación Científica </h1>
<h2> Generalized Minimal Residual Method </h2>
<h2> <a href="#acknowledgements"> [S]cient... | Python Code:
import numpy as np
import scipy as sp
from scipy import linalg as la
import matplotlib.pyplot as plt
import scipy.sparse.linalg
%matplotlib inline
#%load_ext memory_profiler
import matplotlib as mpl
mpl.rcParams['font.size'] = 14
mpl.rcParams['axes.labelsize'] = 20
mpl.rcParams['xtick.labelsize'] = 14
mpl.... |
13,451 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h2><span style="color
Step1: Short tutorial
Setup input files and params
Step2: calculate distances
Step3: save results
Step4: Draw the matrix
Step5: Draw matrix reordered to match gro... | Python Code:
# conda install ipyrad -c bioconda
# conda install toyplot -c eaton-lab (optional)
import ipyrad.analysis as ipa
import toyplot
Explanation: <h2><span style="color:gray">ipyrad-analysis toolkit:</span> distance</h2>
Key features:
Calculate pairwise genetic distances between samples.
Filter SNPs to reduce ... |
13,452 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Titanic data exercise
Step1: 1. Describe each attribute, both with basic statistics and plots. State clearly your assumptions and discuss your findings.
pclass
the class a person belongs to... | Python Code:
import pandas as pd
import numpy as np
import glob # to find all files in folder
from datetime import datetime
from datetime import date, time
from dateutil.parser import parse
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
sns.set_context('notebook')
pd.options.mode.chained_assig... |
13,453 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Passing Messages to Processes
As with threads, a common use pattern for multiple processes is to divide a job up among several workers to run in parallel. Effective use of multiple processes... | Python Code:
import multiprocessing
class MyFancyClass:
def __init__(self, name):
self.name = name
def do_something(self):
proc_name = multiprocessing.current_process().name
print('Doing something fancy in {} for {}!'.format(
proc_name, self.name))
def worker(q):
obj = q.... |
13,454 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NumPy - multidimensional data arrays
Ondrej Lexa 2016
Introduction
The numpy package (module) is used in almost all numerical computation using Python. It is a package that provide high-per... | Python Code:
from pylab import *
Explanation: NumPy - multidimensional data arrays
Ondrej Lexa 2016
Introduction
The numpy package (module) is used in almost all numerical computation using Python. It is a package that provide high-performance vector, matrix and higher-dimensional data structures for Python. It is imp... |
13,455 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Load Iris Flower Data
Step2: Standardize Features
Step3: Train Support Vector Classifier
Step4: Create Previously Unseen Observation
Step5: Predict Class Of Observation | Python Code:
# Load libraries
from sklearn.svm import LinearSVC
from sklearn import datasets
from sklearn.preprocessing import StandardScaler
import numpy as np
Explanation: Title: Support Vector Classifier
Slug: support_vector_classifier
Summary: How to train a support vector classifier in Scikit-Learn
Date: 2017-... |
13,456 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 4
Imports
Step2: Line with Gaussian noise
Write a function named random_line that creates x and y data for a line with y direction random noise that has a normal distribut... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Explanation: Interact Exercise 4
Imports
End of explanation
def random_line(m, b, sigma, size=10):
Create a line y = m*x + b + N(0,sigm... |
13,457 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple Linear Regression
In this module we will learn how to use data to learn a trend and use this trend to predict new observations. First we load the base libraries.
Step1: The easiest w... | Python Code:
import csv
import numpy as np
import scipy as sp
import pandas as pd
import sklearn as sk
import matplotlib.pyplot as plt
from IPython.display import Image
print('csv: {}'.format(csv.__version__))
print('numpy: {}'.format(np.__version__))
print('scipy: {}'.format(sp.__version__))
print('pandas: {}'.format(... |
13,458 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Flocs Data Demo
How to Export Data
Both static and collected data can be exported by command make export-data-to-csv.
This command creates CSV tables for all models registered in flocs/manag... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
Explanation: Flocs Data Demo
How to Export Data
Both static and collected data can be exported by command make export-data-to-csv.
This command creates CSV tables for all models registered in flocs/management/commands... |
13,459 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Projects
Wells are one of the fundamental objects in welly.
Well objects include collections of Curve objects. Multiple Well objects can be stored in a Project.
On this page, we take a close... | Python Code:
import welly
welly.__version__
Explanation: Projects
Wells are one of the fundamental objects in welly.
Well objects include collections of Curve objects. Multiple Well objects can be stored in a Project.
On this page, we take a closer look at the Project class. It lets us handle groups of wells. It is rea... |
13,460 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'ukesm1-0-ll', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: MOHC
Source ID: UKESM1-0-LL
Topic: Ocnbgchem
Sub-Topics: Tracers.
... |
13,461 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'hammoz-consortium', 'sandbox-1', 'atmoschem')
Explanation: ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era: CMIP6
Institute: HAMMOZ-CONSORTIUM
Source ID: SANDBOX-1
Topic: Atmoschem
... |
13,462 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Neuron Lang is a python based DSL for naming neurons. Neurons are modelled as collections of phenotypes with semantics backed by Web Ontology Language (OWL2) classes. Neuron Lang provides to... | Python Code:
from neurondm import *
# set predicates in the event that the default config options do not work
# if you cloned the NIF-Ontology into a nonstandard location change ontology_local_repo in devconfig.yaml
from pyontutils.namespaces import ilxtr as pred
from neurondm import phenotype_namespaces as phns
config... |
13,463 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Moon Phase Correlation Analysis
Step1: This Wikipedia article has a nice description of how to calculate the current phase of the moon. In code, that looks like this
Step2: Let's randomly ... | Python Code:
import ujson as json
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import plotly.plotly as py
from moztelemetry import get_pings, get_pings_properties, get_one_ping_per_client
from moztelemetry.histogram import Histogram
import datetime as dt
%pylab inline
Explanation: Moon Phase C... |
13,464 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 Google LLC.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: Using the Meta-Dataset Data Pipeline
This notebook shows how to use meta_dataset’s input pi... | Python Code:
# 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
# distribute... |
13,465 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A neural network from first principles
The code below was adpated from the code supplied in Andrew Ng's Coursera course on machine learning. The original code was written in Matlab/Octave an... | Python Code:
# Import libraries
import numpy as np
import matplotlib.pyplot as plt
import math
from sklearn.metrics import accuracy_score
import pickle
import sys
Explanation: A neural network from first principles
The code below was adpated from the code supplied in Andrew Ng's Coursera course on machine learning. The... |
13,466 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Building a better model
Following the baseline model and some feature engineering, we will now build a better predictive model. This will follow a few new patterns
Step1: Data
Step2: Clean... | Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import os
import sys
import sklearn
import sqlite3
import matplotlib
import numpy as np
import pandas as pd
import enchant as en
import seaborn as sns
import statsmodels.api as sm
import matplotlib.pyplot as plt
from sklearn.ensemble import RandomForest... |
13,467 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kaggle San Francisco Crime Classification
Berkeley MIDS W207 Final Project
Step1: DDL to construct table for SQL transformations
Step2: Local, individual load of updated data set (with wea... | Python Code:
# Import relevant libraries:
import time
import numpy as np
import pandas as pd
from sklearn.neighbors import KNeighborsClassifier
from sklearn import preprocessing
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import StandardScaler
from sklearn.naive_bayes import BernoulliNB
fr... |
13,468 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modeling and Simulation in Python
Chapter 13
Copyright 2017 Allen Downey
License
Step4: Code from previous chapters
make_system, plot_results, and calc_total_infected are unchanged.
Step6: ... | 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... |
13,469 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Key Requirements for the iRF scikit-learn implementation
The following is a documentation of the main requirements for the iRF implementation
Typical Setup
Import the required dependencies
I... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from sklearn.datasets import load_breast_cancer
import numpy as np
from functools import reduce
# Needed for the scikit-learn wrapper function
from sklearn.utils import resample
from sklearn.ensemble import RandomForestClassifier
from math import ceil
# Im... |
13,470 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Step1: Air Quality Dataset
Regression machine learning task
From UCI repository
Step2: Insurance Dataset
Classification machine learning problem.
Formatted data from Kaggle | Python Code:
from feature_selector import FeatureSelector
import pandas as pd
Explanation: Introduction: Testing Feature Selector
In this notebook we will test the feature selector using two additional datasets. We will try out many of the FeatureSelector methods on these standard machine learning sets to make sure tha... |
13,471 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Expectation Maximization with Mixtures
Implementation of a mixture model using the t distribution.
Source
D. Peel, G. J. McLachlan; Robust mixture modelling using the t distribution. Statist... | Python Code:
actual_mu01 = [0,0]
actual_cov01 = [[1,0], [0,1]]
actual_df01 = 15
actual_mu02 = [1,1]
actual_cov02 = [[.5, 0], [0, 1.5]]
actual_df02 = 15
size = 300
x01 = multivariate_t_rvs(m=actual_mu01, S=actual_cov01, df=actual_df01, n=size)
x02 = multivariate_t_rvs(m=actual_mu02, S=actual_cov02, df=actual_df02, n... |
13,472 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'miroc', 'sandbox-1', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: MIROC
Source ID: SANDBOX-1
Sub-Topics: Radiative Forcings.
Properties... |
13,473 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Programowanie w języku Python
http
Step1: Cechy Pythona
W Pythonie typ posiadają wartości, a nie zmienne, tak więc Python jest językiem z typami dynamicznymi.
Wszystkie wartości przekazy... | Python Code:
import this
Explanation: Programowanie w języku Python
http://mumin.pl/Skrypt_A_do_Z/
https://docs.python.org/3/tutorial/
http://books.icse.us.edu.pl/
Python
<img src="http://upload.wikimedia.org/wikipedia/commons/thumb/6/66/Guido_van_Rossum_OSCON_2006.jpg/320px-Guido_van_Rossum_OSCON_2006.jpg"
align='rig... |
13,474 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Iris univariate joint probability distribution
Again, it's the Iris dataset (I promise I will unleash some 'real' datasets at some point). I've done a lot of bivariate cluster plots, so I wa... | Python Code:
%matplotlib inline
import pandas as pd
import sys
sys.path.append("../../../bayesianpy")
import bayesianpy
from bayesianpy.network import Builder as builder
import logging
import os
import math
import numpy as np
import scipy.stats as ss
import matplotlib.pyplot as plt
import seaborn as sns
logger = loggin... |
13,475 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generative Adversarial Networks
Generative Adversarial Networks
In Adversarial training procedure two models are trained together. The generative model, G, that estimates the data distributi... | Python Code:
# Imports
%reload_ext autoreload
%autoreload 1
import os, sys
sys.path.append('../')
sys.path.append('../common')
from tools_general import tf, np
from IPython.display import Image
from tools_train import get_train_params, OneHot, vis_square
import imageio
# define parameters
networktype = 'DCGAN_MNIST'
wo... |
13,476 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Problem 1.
If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these multiples is 23. Find the sum of all the multiples of 3 or 5 belo... | Python Code:
x = range(1,10)
x
def sum_number_mode(a,b,maxbarrier):
x = 0
for i in range(1,maxbarrier-1):
if i%a == 0 or i%b == 0:
x += i
return x
sum_number_mode(3,5,1001)
Explanation: Problem 1.
If we list all the natural numbers below 10 that are multiples of 3 or 5, we ... |
13,477 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Pyro
Michael Zingale, Alice Harpole
Stony Brook University
Why pyro?
Python is a good introductory language—it helps make the way these algorithms work clearer
High lev... | Python Code:
import mesh.patch as patch
import mesh.boundary as bnd
import numpy as np
g = patch.Grid2d(16, 16, ng=2)
print(g)
bc = bnd.BC(xlb="periodic", xrb="periodic", ylb="reflect", yrb="outflow")
print(bc)
d = patch.CellCenterData2d(g)
d.register_var("a", bc)
d.create()
print(d)
Explanation: Introduction to Pyro
M... |
13,478 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Hub Authors.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: Classify Flowers with Transfer Learning
<table class="tfo-notebook-buttons"... | Python Code:
# Copyright 2018 The TensorFlow Hub Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... |
13,479 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Emissions
Step1: Loading a configuration from file
We will use the following file as an example
Step2: The following line loads the setup detailled in that file
Step3: Browsing the config... | Python Code:
from pygchem import emissions
Explanation: Emissions: HEMCO Python API
The module pygchem.emissions provides an API for Harvard-NASA Emissions Component (HEMCO). Currently, it allows to read / write HEMCO configuration files and to browse or edit an existing configuration (or create a new configuration fro... |
13,480 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time Series Prediction
Objectives
1. Build a linear, DNN and CNN model in keras to predict stock market behavior.
2. Build a simple RNN model and a multi-layer RNN model in keras.
3. Comb... | Python Code:
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import tensorflow as tf
from google.cloud import bigquery
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import (Dense, De... |
13,481 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
FDMS TME3
Kaggle How Much Did It Rain? II
Florian Toque & Paul Willot
Data Vize
Step1: 13.765.202 lines in train.csv
8.022.757 lines in test.csv
Load the dataset
Step2: Per wikipedia... | Python Code:
# from __future__ import exam_success
from __future__ import absolute_import
from __future__ import print_function
%matplotlib inline
import sklearn
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import random
import pandas as pd
import scipy.stats as stats
# Sk cheats
from sklear... |
13,482 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Please find torch implementation of this notebook here
Step1: Imports
Step2: Load Data
Step3: Let's view some images(Because the images are normalized so we need to first convert them to ... | Python Code:
# Install Augmax for Image Augmentation
try:
import augmax
except ModuleNotFoundError:
%pip install -qq git+https://github.com/khdlr/augmax.git -q
import augmax
# Install the jax-resnet
try:
import jax_resnet
except ModuleNotFoundError:
%pip install -qq git+https://github.com/n2cholas/... |
13,483 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The problem with my w(\theta) calculation appears to be fairly fundamental
Step1: Load up the tptY3 buzzard mocks.
Step2: Load up a snapshot at a redshift near the center of this bin.
Step... | Python Code:
from pearce.mocks import cat_dict
import numpy as np
from os import path
from astropy.io import fits
from astropy import constants as const, units as unit
import george
from george.kernels import ExpSquaredKernel
import matplotlib
#matplotlib.use('Agg')
from matplotlib import pyplot as plt
%matplotlib inli... |
13,484 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Previous
2.8 多行匹配模式
问题
你正在试着使用正则表达式去匹配一大块的文本，而你需要跨越多行去匹配。
解决方案
这个问题很典型的出现在当你用点 (.) 去匹配任意字符的时候，忘记了点 (.) 不能匹配换行符的事实。 比如，假设你想试着去匹配 C 语言分割的注释：
Step1: 为了修正这个问题，你可以修改模式字符串，增加对换行的支持。比如：
Step2: 在这... | Python Code:
import re
comment = re.compile(r"/\*(.*?)\*/")
text1 = '/* this is a comment */'
text2 = '''/* this is a
multiline comment */
'''
comment.findall(text1)
comment.findall(text2)
Explanation: Previous
2.8 多行匹配模式
问题
你正在试着使用正则表达式去匹配一大块的文本，而你需要跨越多行去匹配。
解决方案
这个问题很典型的出现在当你用点 (.) 去匹配任意字符的时候，忘记了点 (.) 不能匹配换行符的事实。 比如，... |
13,485 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Executing Squonk services
This notebook is an example of executing Squonk services using Python's requests module.
It assumes you are executing against the JobExector service running in an O... | Python Code:
import requests
import json
# requests_toolbelt module is used to handle the multipart responses.
# Need to `pip install requests-toolbelt` from a terminal to install. This might need doing each time the Notebook pod starts
from requests_toolbelt.multipart import decoder
# Define some URLs and params
base_... |
13,486 | 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: 네트워크
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 네트워크 정의하기
네트워크 API
TF-Agents에서는 Keras Networ... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
13,487 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Context
John Doe remarked in #AP1432 that there may be too much code in our application that isn't used at all. Before migrating the application to the new platform, we have to analyze which... | Python Code:
import pandas as pd
coverage = pd.read_csv("../input/spring-petclinic/jacoco.csv")
coverage = coverage[['PACKAGE', 'CLASS', 'LINE_COVERED' ,'LINE_MISSED']]
coverage['LINES'] = coverage.LINE_COVERED + coverage.LINE_MISSED
coverage.head(1)
Explanation: Context
John Doe remarked in #AP1432 that there may be t... |
13,488 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Row-reduce and variable transformations in non-linear equation systems, an applied example
Step1: Let's consider
Step2: Let's define the stoichiometry and composition
Step3: and now a fun... | Python Code:
from __future__ import (absolute_import, division, print_function)
from functools import reduce, partial
from operator import mul
import sympy as sp
import numpy as np
import matplotlib.pyplot as plt
from pyneqsys.symbolic import SymbolicSys, TransformedSys, linear_exprs
sp.init_printing()
Explanation: Row... |
13,489 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exploration of pairwise string similarity algorithms
Numerous string similarity measuring algirithms are studied below to understand how they work and which one would be the most stuitable. ... | Python Code:
import scipy
import numpy as np
import strsimpy
from Bio import pairwise2
from Bio.Seq import Seq
from Bio.pairwise2 import format_alignment
import matplotlib
import matplotlib.pyplot as plt
similar_strings = ["user_id", "userid", "UserId", "userID"]
Explanation: Exploration of pairwise string similar... |
13,490 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Feature Synthesis
Deep Feature Synthesis (DFS) is an automated method for performing feature engineering on relational and temporal data.
Input Data
Deep Feature Synthesis requires stru... | Python Code:
import featuretools as ft
es = ft.demo.load_mock_customer(return_entityset=True)
es
Explanation: Deep Feature Synthesis
Deep Feature Synthesis (DFS) is an automated method for performing feature engineering on relational and temporal data.
Input Data
Deep Feature Synthesis requires structured datasets in o... |
13,491 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Quality Check API Example
Step1: Create a session. Note the api endpoint, lab-services.ovation.io for Ovation Service Lab.
Step2: Create a Quality Check (QC) activity
A QC activity determi... | Python Code:
import urllib
import ovation.lab.workflows as workflows
import ovation.session as session
Explanation: Quality Check API Example
End of explanation
s = session.connect(input('Email: '), api='https://lab-services.ovation.io')
Explanation: Create a session. Note the api endpoint, lab-services.ovation.io for ... |
13,492 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy Exercise 4
Imports
Step1: Complete graph Laplacian
In discrete mathematics a Graph is a set of vertices or nodes that are connected to each other by edges or lines. If those edges don... | Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
Explanation: Numpy Exercise 4
Imports
End of explanation
import networkx as nx
K_5=nx.complete_graph(5)
nx.draw(K_5)
Explanation: Complete graph Laplacian
In discrete mathematics a Graph is a set of vertices or node... |
13,493 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to Python!
I know what you are all thinking...finally!
Okay let's check out the basics of Python.
I am typing this inside of Jupyter notebook which yields a markdown/programming envi... | Python Code:
3
type(3)
3.0
type(3.0)
type('c')
type('ca')
type("ca")
True
type(True)
type(T) #Not defined unlike R
type(true)
type(x=3) #An assignment does not return a value. This is different from C/C++/R.
x=2 #assignment
x
x==3 #Boolean
Explanation: Welcome to Python!
I know what you are all thinking...finally!
Okay... |
13,494 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
GEE nested covariance structure simulation study
This notebook is a simulation study that illustrates and evaluates the performance of the GEE nested covariance structure.
A nested covarianc... | Python Code:
import numpy as np
import pandas as pd
import statsmodels.api as sm
Explanation: GEE nested covariance structure simulation study
This notebook is a simulation study that illustrates and evaluates the performance of the GEE nested covariance structure.
A nested covariance structure is based on a nested seq... |
13,495 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sources
Bowers, Johnson, Pease, "Prospective hot-spotting
Step1: Visualise the risk intensity directly
Our random data includes events from the past week, and from one (whole) week ago. We... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import open_cp
import open_cp.prohotspot as phs
# Generate some random data
import datetime
times = [datetime.datetime(2017,3,10) + datetime.timedelta(days=np.random.randint(0,10)) for _ in range(20)]
times.sort()
xc = np.random.random(s... |
13,496 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
如何用Python从海量文本抽取主题？
你在工作、学习中是否曾因信息过载叫苦不迭？有一种方法能够替你读海量文章，并将不同的主题和对应的关键词抽取出来，让你谈笑间观其大略。本文使用Python对超过1000条文本做主题抽取，一步步带你体会非监督机器学习LDA方法的魅力。想不想试试呢？
每个现代人，几乎都体会过信息过载的痛苦。文章读不过来，音乐听不过来，视频看不过来。可是现实的压力... | Python Code:
import pandas as pd
df = pd.read_csv("datascience.csv", encoding='gb18030') #注意它的编码是中文GB18030，不是Pandas默认设置的编码，所以此处需要显式指定编码类型，以免出现乱码错误。
# 之后看看数据框的头几行，以确认读取是否正确。
df.head()
#我们看看数据框的长度，以确认数据是否读取完整。
df.shape
Explanation: 如何用Python从海量文本抽取主题？
你在工作、学习中是否曾因信息过载叫苦不迭？有一种方法能够替你读海量文章，并将不同的主题和对应的关键词抽取出来，让你谈笑间观其大略。本文使用P... |
13,497 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Working with the python dyNET package
The dyNET package is intended for neural-network processing on the CPU, and is particularly suited for NLP applications. It is a python-wrapper for the ... | Python Code:
# we assume that we have the dynet module in your path.
# OUTDATED: we also assume that LD_LIBRARY_PATH includes a pointer to where libcnn_shared.so is.
from dynet import *
# create a model and add the parameters.
m = Model()
pW = m.add_parameters((8,2))
pV = m.add_parameters((1,8))
pb = m.add_parameters((... |
13,498 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Automata
Editing Automata
Vcsn provides different means to enter automata. One, which also applies to plain Python, is using the automaton constructor
Step1: See the documentation of vcsn... | Python Code:
import vcsn
vcsn.automaton('''
context = "lal_char(ab), z
$ -> p <2>
p -> q <3>a,<4>b
q -> q a
q -> $
''')
Explanation: Automata
Editing Automata
Vcsn provides different means to enter automata. One, which also applies to plain Python, is using the automaton constructor:
End of explanation
%%automaton a
... |
13,499 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Review from the previous lecture
In yesterday's Lecture 2, you learned how to use the numpy module, how to make your own functions, and how to import and export data. Below is a quick review... | Python Code:
import numpy as np
Explanation: Review from the previous lecture
In yesterday's Lecture 2, you learned how to use the numpy module, how to make your own functions, and how to import and export data. Below is a quick review before we move on to Lecture 3.
Remember, to use the numpy module, first it must be ... |
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