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15,100 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Image Classification
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. You'll preprocess the images... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
class DLProgress(tqdm):
last_block = 0
def h... |
15,101 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting
In order to do inline plotting within a notebook, ipython needs a magic command, commands that start with the %
Step1: Importing some modules (libraries) and giving them short name... | Python Code:
%matplotlib inline
Explanation: Plotting
In order to do inline plotting within a notebook, ipython needs a magic command, commands that start with the %
End of explanation
import numpy as np
import matplotlib.pyplot as plt
Explanation: Importing some modules (libraries) and giving them short names such as ... |
15,102 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to import the data
1. Define search filters. This is needed if some data has to be filtered out.
2. Import data from ase databases.
3. Store references and calculate formation energies.
... | Python Code:
# Import and instantiate energy_landscape object.
from catmap.api.ase_data import EnergyLandscape
energy_landscape = EnergyLandscape()
# Import all gas phase species from db.
search_filter_gas = []
energy_landscape.get_molecules('molecules.db', selection=search_filter_gas)
# Import all adsorbates and slabs... |
15,103 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
디리클레 분포
2차원 히스토그램이라고 보면 된다. 진하기로 표시하면 된다. 6각형으로 해야 원에 가깝기 때문에 이렇게 만들었다.
모드값만 외우면 된다. 분산에서는 밑에가 3차수. 그래서 분산값이 작아진다.
모수를 찾아가는 과정이다. 베이지안에서. 샘플의 수가 부족하기 때문에. 샘플이 무한대로 있으면 분산을 0으로 보낼 수가 있다.
α 가... | Python Code:
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
fig = plt.figure()
ax = Axes3D(fig)
x = [1, 0, 0]
y = [0, 1, 0]
z = [0, 0, 1]
verts = [zip(x, y, z)]
ax.add_collection3d(Poly3DCollection(verts, edgecolor="k", lw=5, alpha=0.4))
ax.text(1, 0, 0, "(1,0,0)", posit... |
15,104 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Enable GPU
This notebook and pretty much every other notebook in this repository will run faster if you are using a GPU.
On Colab
Step1: Image and patch generation functions
Step2: Train ... | Python Code:
import tensorflow as tf
print(tf.version.VERSION)
device_name = tf.test.gpu_device_name()
if device_name != '/device:GPU:0':
raise SystemError('GPU device not found')
print('Found GPU at: {}'.format(device_name))
Explanation: Enable GPU
This notebook and pretty much every other notebook in this repositor... |
15,105 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Messy Sensor Data
Step1: The file seems to be tab seperated. There are dates, and some empty items.
Can we read it more clearly?
pandas.read_csv() is very versatile with keyword arguments.... | Python Code:
import pandas as pd
# Open a comma-separated values (CSV) file as a DataFrame
weather_observations = pd.read_csv('observations/Canberra_observations.csv')
# Print the first 5 entries
weather_observations.head()
Explanation: Messy Sensor Data:
A Programmer's Cleaning Guide
@Xavier_Ho, #pyconau
<small>Feel f... |
15,106 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Read CIFAR10 dataset
Step1: Normalize data
This maps all values in trn. and tst. data to range <-0.5,0.5>.
Some kind of value normalization is preferable to
provide consistent behavior acc... | Python Code:
from tools import readCIFAR, mapLabelsOneHot
# First run ../data/downloadCIFAR.sh
# This reads the dataset
trnData, tstData, trnLabels, tstLabels = readCIFAR('../data/cifar-10-batches-py')
plt.subplot(1, 2, 1)
img = collage(trnData[:16])
print(img.shape)
plt.imshow(img)
plt.subplot(1, 2, 2)
img = collage(... |
15,107 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Similarity Queries using Annoy Tutorial
This tutorial is about using the Annoy(Approximate Nearest Neighbors Oh Yeah) library for similarity queries in gensim
Why use Annoy?
The current impl... | Python Code:
#Set up the model and vector that we are using in the comparison
from gensim.similarities.index import AnnoyIndexer
from gensim.models.word2vec import Word2Vec
model = Word2Vec.load("/tmp/leemodel")
model.init_sims()
vector = model.syn0norm[0]
annoy_index = AnnoyIndexer(model, 500)
%%time
#Traditional impl... |
15,108 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Load the data
Step4: Computing the Cost Function
Fill in the compute_cost function below
Step6: Grid Search
Fill in the function grid_search() below
Step7: Let us play with the grid searc... | Python Code:
import datetime
from helpers import *
height, weight, gender = load_data(sub_sample=False, add_outlier=False)
x, mean_x, std_x = standardize(height)
y, tx = build_model_data(x, weight)
y.shape, tx.shape
Explanation: Load the data
End of explanation
def calculate_mse(e):
Calculate the mse for vector e.
... |
15,109 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div style="width
Step1: Creating the file and dimensions
The first step is to create a new file and set up the shared dimensions we'll be using in the file. We'll be using the netCDF4-pyth... | Python Code:
# Import some useful Python tools
from datetime import datetime, timedelta
import numpy as np
# Twelve hours of hourly output starting at 22Z today
start = datetime.utcnow().replace(hour=22, minute=0, second=0, microsecond=0)
times = np.array([start + timedelta(hours=h) for h in range(13)])
# 3km spacing i... |
15,110 | Given the following text description, write Python code to implement the functionality described.
Description:
This function takes two positive numbers x and y and returns the
biggest even integer number that is in the range [x, y] inclusive. If
there's no such number, then the function should return -1.
F... | Python Code:
def choose_num(x, y):
if x > y:
return -1
if y % 2 == 0:
return y
if x == y:
return -1
return y - 1 |
15,111 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: TensorBoard 性能分析
Step2: 确认 TensorFlow 可以看到 GPU。
Step7: 使用 TensorBoard callback 运行一个简单的模型
你将使用 Keras 来构建一个使用 ResNet56 (参考
Step8: 从 TensorFlow... | 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... |
15,112 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data from H2Cooling with Gravity
Step1: $$
\rho_{BE} (r) = \frac{C_s^2}{4 \pi G r^2} =\frac{L_0^2 \rho _0 t_0}{t_0^2 L_0^2}
$$
Step2: Simulate Profile
Step3: $$
4\pi \rho_0 \int _0 ^R \... | Python Code:
#HCG=np.load('../Data/H2CoolingG512.npz')
HCG=np.load('../Data/TabulatedG.npz')
f.quadruple(HCG,np.log10(HCG['RHO']),rows=2,nn=0,tlim=26,Save_Figure='H2CoolGRquad')
f.pprofile(HCG,'RHO',steps=4,itlim=26,tdk='Myrs',Save_Figure='H2CoolGRHOprofile',sc2='log',xlim=[0,20],yprop=256)
f.pprofile(HCG,'Temp',steps=... |
15,113 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<p><font size="4"> MOOC
Step1: 2) Letting $K$ range from 1 to 11, plot the loss probability for $\lambda = 4$ and for $\lambda = 10$ (and $\mu=5$). Remarks ? Compare it to the theoretical ... | Python Code:
%matplotlib inline
from pylab import *
def MM1K(K=3,lambda_ = 4.,mu = 5.,N0 = 2,Tmax=100):
N0 = min(N0,K)# enforcing buffer length constraint
p = lambda_/(mu+lambda_) # probability that the next event is an arrival when N(t) > 0
T = [0] # list of ins... |
15,114 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sympy (sympy.org) is a Python package used for solving equations with symbolic math.
Using Python and SymPy we can write and solve equations that come up in Engineering.
The example problem... | Python Code:
from sympy import symbols, nonlinsolve
Explanation: Sympy (sympy.org) is a Python package used for solving equations with symbolic math.
Using Python and SymPy we can write and solve equations that come up in Engineering.
The example problem below contains two equations with two unknown variables. You cou... |
15,115 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Testing TRICERATOPS EB modeling vs. isochrones
We want to test how the luminosity-scaling method compares to physical modeling based on colors & parallax.
This is the layout of the test
Step... | Python Code:
from isochrones import get_ichrone
mist = get_ichrone('mist', bands=['TESS', 'V', 'K'])
mass, age, feh = (0.8, 9.7, 0.0)
distance = 10 # pc
AV = 0.0
simulated_props = mist.generate(mass, age, feh, distance=distance, AV=AV)
simulated_props[['mass', 'radius', 'TESS_mag', 'V_mag', 'K_mag']]
Explanation: Test... |
15,116 | Given the following text description, write Python code to implement the functionality described.
Description:
Find sub
Python implementation of the approach ; Function to return the sum of the sub - matrix ; Function that returns true if it is possible to find the sub - matrix with required sum ; 2 - D array to store ... | Python Code:
N = 4
def getSum(r1 , r2 , c1 , c2 , dp ) :
return dp[r2 ][c2 ] - dp[r2 ][c1 ] - dp[r1 ][c2 ] + dp[r1 ][c1 ]
def sumFound(K , S , grid ) :
dp =[[ 0 for i in range(N + 1 ) ] for j in range(N + 1 ) ]
for i in range(N ) :
for j in range(N ) :
dp[i + 1 ][j + 1 ] = dp[i + 1 ][j ] + dp[i ][j ... |
15,117 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Decision Tree Classifier - random_state
In the previous notebook we got an accuracy score of just over 40%.
Lets just do that again.
Step1: and again.
Step2: one more time
Step3: We see ... | Python Code:
# Imports
from sklearn import metrics
from sklearn.tree import DecisionTreeClassifier
import pandas as pd
# Training Data
training_raw = pd.read_table("../data/training_data.dat")
df_training = pd.DataFrame(training_raw)
# test Data
test_raw = pd.read_table("../data/test_data.dat")
df_test = pd.DataFrame(t... |
15,118 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<small><i>This notebook was put together by Jake Vanderplas. Source and license info is on GitHub.</i></small>
Introduction to Scikit-Learn
Step1: This may seem like a trivial task, but it ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('seaborn')
# Import the example plot from the figures directory
from fig_code import plot_sgd_separator
plot_sgd_separator()
Explanation: <small><i>This notebook was put together by Jake Vanderplas. Source and license info is on GitHub.</i></... |
15,119 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Orbital Elements
We can add particles to a simulation by specifying cartesian components
Step1: Any components not passed automatically default to 0. REBOUND can also accept orbital elemen... | Python Code:
import rebound
sim = rebound.Simulation()
sim.add(m=1., x=1., vz = 2.)
Explanation: Orbital Elements
We can add particles to a simulation by specifying cartesian components:
End of explanation
sim.add(m=1., a=1.)
sim.status()
Explanation: Any components not passed automatically default to 0. REBOUND can a... |
15,120 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
DataFrame
A DataFrame is a Dataset organized into named columns. It is conceptually equivalent to a table in a relational database or a data frame in R/Python, but with richer optimizations ... | Python Code:
from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)
from pyspark.sql import Row
csv_data = raw.map(lambda l: l.split(","))
row_data = csv_data.map(lambda p: Row(
duration=int(p[0]),
protocol_type=p[1],
service=p[2],
flag=p[3],
src_bytes=int(p[4]),
dst_bytes=int(p[5])
... |
15,121 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Iterative Deepening
The function search takes three arguments to solve a search problem
Step1: The function depth_limited_search tries to find a solution to the search problem
$$ \langle Q,... | Python Code:
def search(start, goal, next_states):
limit = 36
while True:
Path = depth_limited_search(start, goal, next_states, [start], { start }, limit)
if Path is not None:
return Path
limit += 1
print(f'limit = {limit}')
Explanation: Iterative Deepening
The functi... |
15,122 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sensors
Hi ha quatre sensors diferents montats i connectats al robot
Step1: Sensor de tacte
És un polsador, que segons estiga polsat o no, donarà un valor vertader (True) o fals (False). Pe... | Python Code:
from functions import connect, touch, light, sound, ultrasonic, disconnect, next_notebook
connect()
Explanation: Sensors
Hi ha quatre sensors diferents montats i connectats al robot:
<img src="img/sensors.jpg" width=400>
Els de la figura corresponen al model NXT, però els de l'EV3 són equivalents.
Anem a c... |
15,123 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 Google LLC.
Step1: Case Study
Step2: Understanding the Data Format
Each row represents one labeled example. Column 0 represents the label that a human rater has assigned for... | 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... |
15,124 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have dfs as follows: | Problem:
import pandas as pd
df1 = pd.DataFrame({'id': [1, 2, 3, 4, 5],
'city': ['bj', 'bj', 'sh', 'sh', 'sh'],
'district': ['ft', 'ft', 'hp', 'hp', 'hp'],
'date': ['2019/1/1', '2019/1/1', '2019/1/1', '2019/1/1', '2019/1/1'],
'value': [1, 5, 9,... |
15,125 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A strawberry flavour gene vector for Saccharomyces cerevisiae
This Jupyter notebook describes the simulated cloning of the strawberry Fragaria × ananassa alcohol acyltransferase SAAT gene a... | Python Code:
# Import the pydna package functions
from pydna.all import *
# Give your email address to Genbank, so they can contact you.
# This is a requirement for using their services
gb=Genbank("bjornjobb@gmail.com")
# download the SAAT CDS from Genbank
# We know from inspecting the
saat = gb.nucleotide("AF193791 R... |
15,126 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 13
Step1: The try instruction allows exception handling in Python. If an exception occurs in a block marked by try, it is possible to handle the exception through the instruction ex... | Python Code:
print (10/0)
Explanation: Chapter 13: Exceptions
When a failure occurs in the program (such as division by zero, for example) at runtime, an exception is generated. If the exception is not handled, it will be propagated through function calls to the main program module, interrupting execution.
End of expla... |
15,127 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Display objects
A striplog depends on a hierarchy of objects. This notebook shows the objects related to display
Step1: A Decor attaches a display style to a Rock. From the docs
Step2: Lik... | Python Code:
from striplog import Decor
Explanation: Display objects
A striplog depends on a hierarchy of objects. This notebook shows the objects related to display:
Decor: One element from a legend — describes how to display a Rock.
Legend: A set of Decors — describes how to display a set of Rocks or a Striplog.
<hr ... |
15,128 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Solvers
A constraints-based reconstruction and analysis model for biological systems is actually just an application of a class of discrete optimization problems typically solved with linear... | Python Code:
import cobra.test
model = cobra.test.create_test_model('textbook')
model.solver = 'glpk'
# or if you have cplex installed
model.solver = 'cplex'
Explanation: Solvers
A constraints-based reconstruction and analysis model for biological systems is actually just an application of a class of discrete optimizat... |
15,129 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Assessing classifiers using GO in Shalek2013
For the GO analysis, we'll need a few other packages
Step2: Utility functions for gene ontology
Step3: Read in the Shalek2013 data and classify... | Python Code:
# Alphabetical order is standard
# We're doing "import superlongname as abbrev" for our laziness - this way we don't have to type out the whole thing each time.
import collections
# Python plotting library
import matplotlib.pyplot as plt
# Numerical python library (pronounced "num-pie")
import numpy as np
... |
15,130 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reprise pour proof of concept du pdf PythonEdu Amiens
Passer par un logiciel Windows alors que jupyter et jupyterhub existent me semble une grossière erreur d'aiguillage.
Je vais tenter de d... | Python Code:
#solution de l'équation ax = b pour a = 2 et b = 6
a=2
b=6
print("la solution solution de ",a,"* x = ",b,"est :")
print("x =",b/a)
#résoudre l'équation ax=b pour a≠0
a = int(input("entrez une valeur pour a ≠ 0 : "))
#on s'assure que a est bien différent de 0
if a==0:
#on redemande la saisie de a
... |
15,131 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise
Step1: Part 2
Use indexing (not a for loop) to find the 9 values representing $y_{i}+y_{i-1}$ for $i$ between 1 and 10.
Hint
Step2: Part 3
Write a function trapz(x, y), that appli... | Python Code:
import numpy as np
x = np.linspace(0, 3, 10)
y = x ** 2
print(x)
print(y)
Explanation: Exercise: trapezoidal integration
In this exercise, you are tasked with implementing the simple trapezoid rule
formula for numerical integration. If we want to compute the definite integral
$$
\int_{a}^{b}f(x)dx
$$
... |
15,132 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing Encoder-Decoders Analysis
Model Architecture
Step1: Perplexity on Each Dataset
Step2: Loss vs. Epoch
Step3: Perplexity vs. Epoch
Step4: Generations
Step5: BLEU Analysis
Step6:... | Python Code:
report_files = ["/Users/bking/IdeaProjects/LanguageModelRNN/experiment_results/encdec_noing6_200_512_04drb/encdec_noing6_200_512_04drb.json", "/Users/bking/IdeaProjects/LanguageModelRNN/experiment_results/encdec_noing10_200_512_04drb/encdec_noing10_200_512_04drb.json", "/Users/bking/IdeaProjects/LanguageMo... |
15,133 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.algo - Arbre et Trie (correction)
Correction.
Step1: Exercice 1
Step2: Exercice 2
Step3: Avec %timeit
Step4: Exercice 3
Step5: Exercice 4
Step6: Soit $N$ le nombre de mots dans la... | Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.algo - Arbre et Trie (correction)
Correction.
End of explanation
import random
def mot_alea (l) :
l = [ chr(97+random.randint(0,25)) for i in range(l) ]
return "".join(l)
taille = 20
N = 10000
mots = [ mot_ale... |
15,134 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Abstract
In this work we will to take a look at a data visualization using Python and the Titanic dataset. It's not intended to be the most accurate Titanic dataset analysis about Titanic, i... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
Explanation: Abstract
In this work we will to take a look at a data visualization using Python and the Titanic dataset. It's not intended to be the most accurate Titanic dataset analysis about Titanic, it's a project resultant of the co... |
15,135 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial 07
Step1: 1. Running a Default Simulation
In order to create a scenario object in Flow with network features depicted from OpenStreetMap, we will use the base Scenario class. This ... | Python Code:
# the TestEnv environment is used to simply simulate the network
from flow.envs import TestEnv
# the Experiment class is used for running simulations
from flow.core.experiment import Experiment
# all other imports are standard
from flow.core.params import VehicleParams
from flow.core.params import NetParam... |
15,136 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Loops
During the course of solving client requirements, comes across situations where group of some data needs to be processed against a defined set of instructions.
Loops help in resolving... | Python Code:
for x in "Manish Gupta":
print(x, end="^~", flush=True)
Explanation: Loops
During the course of solving client requirements, comes across situations where group of some data needs to be processed against a defined set of instructions.
Loops help in resolving situations where a piece of code needs to b... |
15,137 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CNN HandsOn with Keras
Problem Definition
Recognize handwritten digits
Data
The MNIST database (link) has a database of handwritten digits.
The training set has $60,000$ samples.
The test ... | Python Code:
import numpy as np
import keras
from keras.datasets import mnist
import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" # see issue #152
os.environ["CUDA_VISIBLE_DEVICES"] = ""
# Load the datasets
(X_train, y_train), (X_test, y_test) = mnist.load_data()
Explanation: CNN HandsOn with Keras
Problem Defin... |
15,138 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Atmospheres & Passbands
Setup
Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't wan... | Python Code:
!pip install -I "phoebe>=2.2,<2.3"
Explanation: Atmospheres & Passbands
Setup
Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't want to update to the latest release).
End of explanation
%matplotlib in... |
15,139 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matplotlib Exercise 3
Imports
Step2: Contour plots of 2d wavefunctions
The wavefunction of a 2d quantum well is
Step3: The contour, contourf, pcolor and pcolormesh functions of Matplotlib ... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Explanation: Matplotlib Exercise 3
Imports
End of explanation
def well2d(x, y, nx, ny, L=1.0):
Compute the 2d quantum well wave function.
# YOUR CODE HERE
raise NotImplementedError()
psi = well2d(np.linspace(0,1,10), np.linsp... |
15,140 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="https
Step1: MCMC (emcee)
MCMC is a convenient tool for drawing a sample from a given probability distribution.
Therefore, is mostly used to estimate parameters in Bayesian way.
e... | Python Code:
%pylab inline
np.random.seed(0)
p = [3.2, 5.6, 9.2]
x = np.arange(-8., 5., 0.1)
y = np.polyval(p, x) + np.random.randn(x.shape[0])*1.
plt.plot(x, y);
# STEP 1 - define your model
def my_model(p, x):
return np.polyval(p, x)
# STEP 2 - define your cost function
def my_costfun(p, x, y):
return np.sum(... |
15,141 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Image Classification
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. You'll preprocess the images... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if present
floyd_cifa... |
15,142 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Fully-Connected Neural Nets
In the previous homework you implemented a fully-connected two-layer neural network on CIFAR-10. The implementation was simple but not very modular since t... | Python Code:
# As usual, a bit of setup
from __future__ import print_function
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.fc_net import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array
fro... |
15,143 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyMC Geomod 1
Step1: Simplest case
Step2: Tha axis here represent the number of cells not the real values of geomodeller
Step3: Setting Bayes Model
Step4: Plotting Posteriors
Step5: Ext... | Python Code:
%matplotlib inline
from IPython.core.display import Image
import numpy as np
import matplotlib.pyplot as plt
import sys, os
import shutil
#import geobayes_simple as gs
import pymc as pm # PyMC 2
from pymc.Matplot import plot
from pymc import graph as gr
import numpy as np
#import daft
from IPython.core.pyl... |
15,144 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step function
DGP papers have often demonstrated a step function, as this cannot be well captured by GP with a stationary kernel. We'll do that here also
Step1: We'll now use a 2 layer DGP
... | Python Code:
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
%matplotlib inline
from gpflow.likelihoods import Gaussian
from gpflow.kernels import RBF, White
from gpflow.models.gpr import GPR
from gpflow.training import AdamOptimizer, ScipyOptimizer
from doubly_stochastic_dgp.dgp import DGP
n... |
15,145 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table align="left">
<td>
<a href="https
Step1: Set up your GCP project
The following steps are required, regardless of your notebook environment.
Select or create a GCP project.. Whe... | Python Code:
!pip install google-cloud-bigquery
# Automatically restart kernel after installs
import IPython
app = IPython.Application.instance()
app.kernel.do_shutdown(True)
Explanation: <table align="left">
<td>
<a href="https://colab.research.google.com/github/GoogleCloudPlatform/analytics-componentized-patter... |
15,146 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Neural Network using Numpy on Bike Sharing Time Series dataset
In this project, we'll build a neural network and use it to predict daily bike rental ridership.
Step1: Load and prepare the... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: A Neural Network using Numpy on Bike Sharing Time Series dataset
In this project, we'll build a neural network and use it to predict daily bike rental riders... |
15,147 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Document retrieval from wikipedia data
Fire up GraphLab Create
Step1: Load some text data - from wikipedia, pages on people
Step2: Data contains
Step3: Explore the dataset and checkout th... | Python Code:
import graphlab
Explanation: Document retrieval from wikipedia data
Fire up GraphLab Create
End of explanation
people = graphlab.SFrame('people_wiki.gl/')
Explanation: Load some text data - from wikipedia, pages on people
End of explanation
people.head()
len(people)
Explanation: Data contains: link to wik... |
15,148 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
We will train a model to predict drug resistance values from sequence.
This is the other general variant of supervised learning - where instead of predicting a "label" for a class (classific... | Python Code:
# Load the sequence data as a Pandas dataframe.
seqids = [s.id for s in SeqIO.parse('data/hiv-protease-sequences-expanded.fasta', 'fasta')]
sequences = [s for s in SeqIO.parse('data/hiv-protease-sequences-expanded.fasta', 'fasta')]
sequences = MultipleSeqAlignment(sequences)
sequences = pd.DataFrame(np.arr... |
15,149 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using tf.keras
This Colab is about how to use Keras to define and train simple models on the data generated in the last Colab 1_data.ipynb
Step2: Attention
Step3: Linear model
Step4: Conv... | Python Code:
# In Jupyter, you would need to install TF 2.0 via !pip.
%tensorflow_version 2.x
import tensorflow as tf
import json, os
# Tested with TensorFlow 2.1.0
print('version={}, CUDA={}, GPU={}, TPU={}'.format(
tf.__version__, tf.test.is_built_with_cuda(),
# GPU attached?
len(tf.config.list_physical_d... |
15,150 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Display Exercise 1
Imports
Put any needed imports needed to display rich output the following cell
Step1: Basic rich display
Find a Physics related image on the internet and display it in t... | Python Code:
from IPython.display import display
from IPython.display import Image
from IPython.display import HTML
assert True # leave this to grade the import statements
Explanation: Display Exercise 1
Imports
Put any needed imports needed to display rich output the following cell:
End of explanation
Image(url='https... |
15,151 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook is intended to demonstrate the basic features of the Python API for constructing input files and running OpenMC. In it, we will show how to create a basic reflective pin-cell m... | Python Code:
%matplotlib inline
import openmc
Explanation: This notebook is intended to demonstrate the basic features of the Python API for constructing input files and running OpenMC. In it, we will show how to create a basic reflective pin-cell model that is equivalent to modeling an infinite array of fuel pins. If ... |
15,152 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Computing a covariance matrix
Many methods in MNE, including source estimation and some classification
algorithms, require covariance estimations from the recordings.
In this tutorial we cov... | Python Code:
import os.path as op
import mne
from mne.datasets import sample
Explanation: Computing a covariance matrix
Many methods in MNE, including source estimation and some classification
algorithms, require covariance estimations from the recordings.
In this tutorial we cover the basics of sensor covariance compu... |
15,153 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dealing with Lookahead Conflicts
This notebook discusses conflicts that have their origin in insufficient looakahead.
We will discuss the following grammar
Step1: Specification of the Parse... | Python Code:
import ply.lex as lex
tokens = [ 'USELESS' ]
literals = ['U', 'V', 'W', 'X']
def t_USELESS(t):
r'This will never be used.'
__file__ = 'main'
lexer = lex.lex()
Explanation: Dealing with Lookahead Conflicts
This notebook discusses conflicts that have their origin in insufficient looakahead.
We will dis... |
15,154 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Ingestion & Exploratory Analysis of the UFO Database
Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States r... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import statsmodels.api as sm
import pandas as pd
import numpy as np
import geocoder
import re
import math
Explanation: Data Ingestion & Exploratory Analysis of the UFO Database
Unidentified Flying Objects (UFOs) have been an interesti... |
15,155 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating Labeled Data from a Planet Mosaic with Label Maker
In this notebook, we create labeled data for training a machine learning algorithm. As inputs, we use OpenStreetMap as the ground ... | Python Code:
import json
import os
import ipyleaflet as ipyl
import ipywidgets as ipyw
from IPython.display import Image
import numpy as np
Explanation: Creating Labeled Data from a Planet Mosaic with Label Maker
In this notebook, we create labeled data for training a machine learning algorithm. As inputs, we use OpenS... |
15,156 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mri', 'sandbox-1', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: MRI
Source ID: SANDBOX-1
Topic: Landice
Sub-Topics: Glaciers, Ice.
Proper... |
15,157 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Major League Baseball's Billion Dollar Problem
A study of MLB pitching injuries at the NYU Stern School of Business
Written by Isaac Gammal (isaac.gammal@stern.nyu.edu)
Background
Since the ... | Python Code:
'''Data were imported from referenced sources and stored locally'''
import sys # system module
import pandas as pd # data package
import matplotlib.pyplot as plt # graphics module
import datetime as dt # date and time module
import n... |
15,158 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Apache Spark
Spark applications run as independent sets of processes on a cluster, coordinated by the SparkContext object in your main program (called the driver program).
SparkContext... | Python Code:
import pyspark
sc = pyspark.SparkContext(appName="my_spark_app")
sc
Explanation: Using Apache Spark
Spark applications run as independent sets of processes on a cluster, coordinated by the SparkContext object in your main program (called the driver program).
SparkContext allocate resources across applicati... |
15,159 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Тест. Доверительные интервалы для среднего
Step1: Для 61 большого города в Англии и Уэльсе известны средняя годовая смертность на 100000 населения (по данным 1958–1964) и концентрация кальц... | Python Code:
import pandas as pd
import numpy as np
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
Explanation: Тест. Доверительные интервалы для среднего
End of explanation
water_data = pd.read_table('water.txt')
water_data.info()
water_data.describe()
water_... |
15,160 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First, load the UKDALE dataset into NILMTK. Here we are loading the HDF5 version of UKDALE which you can download by following the instructions on the UKDALE website.
Step1: Next, to speed... | Python Code:
dataset = nilmtk.DataSet('/data/mine/vadeec/merged/ukdale.h5')
Explanation: First, load the UKDALE dataset into NILMTK. Here we are loading the HDF5 version of UKDALE which you can download by following the instructions on the UKDALE website.
End of explanation
dataset.set_window("2014-06-01", "2014-07-01... |
15,161 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: working with numpy arrays
This notebook demonstrates how to use differences and sums to calculate derivatives and integrals and make some simple plots using the matplotlib module. If... | Python Code:
import numpy as np
from matplotlib import pyplot as plt
def cubeit(x,a,b):
construct cubic polynomial of the form
y = ax^3 + b
Parameters
----------
x: vector or float
x values
a: float
coefficient to multiply
b: float
coefficie... |
15,162 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Batch Normalization
One way to make deep networks easier to train is to use more sophisticated optimization procedures such as SGD+momentum, RMSProp, or Adam. Another strategy is to c... | Python Code:
# As usual, a bit of setup
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.fc_net import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array
from cs231n.solver import Solver
%matplot... |
15,163 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook-8
Step1: At the danger of repeating ourselves (but to make the point!)
Step2: This doesn't work because you can't use a list (["key1",1]) as a key, though as you saw above you can... | Python Code:
myDict = {
"key1": "Value 1",
3: "3rd Value",
"key2": "2nd Value",
"Fourth Key": [4.0, 'Jon']
}
print(myDict)
Explanation: Notebook-8: Dictionaries
Lesson Content
In this lesson, we'll continue our exploration of more advanced data structures. Last time we took a peek at a way to represent ... |
15,164 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Possible Solution
Step1: Explaining my code
Okay guys, my code is a bit complicated to understand at first glance, but I'm going to talk you through it.
board_temp = ["B"] * bomb_count + [n... | Python Code:
import random
def build_board(num_rows, num_cols, bomb_count=0, non_bomb_character="-"):
board_temp = ["B"] * bomb_count + [non_bomb_character] * (num_rows * num_cols - bomb_count)
if bomb_count:
random.shuffle(board_temp)
board = []
for i in range(0, num_rows*num_cols, num_cols):
... |
15,165 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create Population Data From Non-Normal Distribution
Step2: View the True Mean Of Population
Step3: Take A Sample Mean, Repeat 1000 Times
Step4: Plot The Sample Means Of All ... | Python Code:
# Import packages
import pandas as pd
import numpy as np
# Set matplotlib as inline
%matplotlib inline
Explanation: Title: Demonstrate The Central Limit Theorem
Slug: demonstrate_the_central_limit_theorem
Summary: Python introduction to the central limit theorem
Date: 2016-05-01 12:00
Category: Statistic... |
15,166 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Graph format
The EDeN library allows the vectorization of graphs, i.e. the transformation of graphs into sparse vectors.
The graphs that can be processed by the EDeN library have the followi... | Python Code:
%matplotlib inline
import pylab as plt
import networkx as nx
G=nx.Graph()
G.add_node(0, label='A')
G.add_node(1, label='B')
G.add_node(2, label='C')
G.add_edge(0,1, label='x')
G.add_edge(1,2, label='y')
G.add_edge(2,0, label='z')
from eden.util import display
print display.serialize_graph(G)
from eden.util... |
15,167 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Topic 2
Step1: Creating a Reddit Application
Go to https
Step2: Capturing Reddit Posts
Now for a given subreddit, we can get the newest posts to that sub.
Post titles are generally short,... | Python Code:
# For our first piece of code, we need to import the package
# that connects to Reddit. Praw is a thin wrapper around reddit's
# web APIs and works well
import praw
Explanation: Topic 2: Collecting Social Media Data
This notebook contains examples for using web-based APIs (Application Programmer Interfac... |
15,168 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Word2Vec Tutorial
In case you missed the buzz, word2vec is a widely featured as a member of the “new wave” of machine learning algorithms based on neural networks, commonly referred to as "d... | Python Code:
# import modules & set up logging
import gensim, logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
sentences = [['first', 'sentence'], ['second', 'sentence']]
# train word2vec on the two sentences
model = gensim.models.Word2Vec(sentences, min_count=1)
Expla... |
15,169 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Landice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'bcc', 'sandbox-2', 'landice')
Explanation: ES-DOC CMIP6 Model Properties - Landice
MIP Era: CMIP6
Institute: BCC
Source ID: SANDBOX-2
Topic: Landice
Sub-Topics: Glaciers, Ice.
Proper... |
15,170 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. I want to make sure my Plate ID is a string. Can't lose the leading zeroes!
2. I don't think anyone's car was built in 0AD. Discard the '0's as NaN.
3. I want the dates to be dates! Read ... | Python Code:
import pandas as pd
#import pandas as pd
import datetime
import datetime as dt
# import datetime
# import datetime as dt
dt.datetime.strptime('08/04/2013', '%m/%d/%Y')
datetime.datetime(2013, 8, 4, 0, 0)
parser = lambda date: pd.datetime.strptime(date, '%m/%d/%Y')
!head -n 10000 violations.csv > small-viol... |
15,171 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute distance to roads
This notebook computes the distance to each of the nearest road types in a 'roads' vector map from a vector map of 'points' (sample locations).
This notebook uses G... | Python Code:
points = 'sample_points_field'
roads = 'highway'
road_type_field = 'Type'
distance_table_filename = ""
Explanation: Compute distance to roads
This notebook computes the distance to each of the nearest road types in a 'roads' vector map from a vector map of 'points' (sample locations).
This notebook uses GR... |
15,172 | 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... |
15,173 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Compute MxNE with time-frequency sparse prior
The TF-MxNE solver is a distributed inverse method (like dSPM or sLORETA)
that promotes focal (sparse) sources (such as dipole fitting technique... | Python Code:
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import mne
from mne.datasets import sample
from mne.minimum_norm import make_inverse_operator, apply_inverse
from mne.inverse_sparse import tf_mixed_norm
from mne.viz import plot_sparse_source_estimates
print... |
15,174 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: <h1>Audio Applications</h1>
<BR>
Now that we have established the theory behind the geometry of 1D time series sliding window embeddings, we will look at our first real applications
S... | Python Code:
##Do all of the imports and setup inline plotting
%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from scipy.interpolate import InterpolatedUnivariateSpline
from ripser import ripser
from persim import plot_diagrams
import scipy.io.wavfile
from ... |
15,175 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Setup
Step1: Sometimes it's useful to have a zero value in the dataset, e.g. for padding
Step2: 3 char model
Step3: RNN
Step4: The first character of each sequence goes through dense_in(... | Python Code:
path = get_file('nietzsche.txt', origin="https://s3.amazonaws.com/text-datasets/nietzsche.txt")
text = open(path).read()
print('corpus length:', len(text))
text
chars = sorted(list(set(text)))
vocab_size = len(chars)+1
print('total chars:', vocab_size)
chars
Explanation: Setup
End of explanation
chars.inse... |
15,176 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Dropout
Dropout [1] is a technique for regularizing neural networks by randomly setting some features to zero during the forward pass. In this exercise you will implement a dropout la... | Python Code:
# As usual, a bit of setup
import sys
import os
sys.path.insert(0, os.path.abspath('..'))
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.fc_net import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient, eval_num... |
15,177 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn about emb... | Python Code:
import time
import numpy as np
import tensorflow as tf
import utils
from collections import Counter
import random
Explanation: Skip-gram word2vec
In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture. By implementing this, you'll learn... |
15,178 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example of Pythran Usage Within a Full Project
This notebook covers the creation of a simple, distutils-powered, project that ships a pythran kernel.
But first some cleanup
Step2: Project l... | Python Code:
!rm -rf hello setup.py && mkdir hello
Explanation: Example of Pythran Usage Within a Full Project
This notebook covers the creation of a simple, distutils-powered, project that ships a pythran kernel.
But first some cleanup
End of explanation
%%file hello/hello.py
#pythran export hello()
def hello():
... |
15,179 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Quick overview
Here are some quick examples of what you can do with xarray.DataArray objects. Everything is explained in much more detail in the rest of the documentation.
To begin, import n... | Python Code:
import numpy as np
import pandas as pd
import xarray as xr
Explanation: Quick overview
Here are some quick examples of what you can do with xarray.DataArray objects. Everything is explained in much more detail in the rest of the documentation.
To begin, import numpy, pandas and xarray using their customary... |
15,180 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 17
Analyze how travelers expressed their feelings on Twitter
A sentiment analysis job about the problems of each major U.S. airline.
Twitter data was scraped from February of 2015 ... | Python Code:
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
# read the data and set the datetime as the index
tweets = pd.read_csv('https://github.com/albahnsen/PracticalMachineLearningClass/raw/master/datasets/Tweets.zip', index_col=0)
tweets.head()
tweets.shape
Explanation: ... |
15,181 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: 過学習と学習不足について知る
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: Higgs データセット
このチュートリアルの目的は素粒... | 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... |
15,182 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1><center>[Notebooks](../) - [Numerical Cartography](../numerical cartography)</center></h1>
Geodetic datum transformations
Is common practice in Geospatial data science to work with datas... | Python Code:
#import the pyproj and numpy library
import pyproj
import numpy as np
# set a reference point P with coordinates:
P = (-70.93931369842528, 43.13567095719326)
# define projection UTM 19 N:
# UTM zone 19, WGS84 ellipse, WGS84 datum, defined by epsg code 32619
p1 = pyproj.Proj(init='epsg:32619')
#Find UT... |
15,183 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 10 – Introduction to Artificial Neural Networks
This notebook contains all the sample code and solutions to the exercises in chapter 10.
Setup
First, let's make sure this notebook wo... | Python Code:
# To support both python 2 and python 3
from __future__ import division, print_function, unicode_literals
# Common imports
import numpy as np
import os
# to make this notebook's output stable across runs
def reset_graph(seed=42):
tf.reset_default_graph()
tf.set_random_seed(seed)
np.random.seed(... |
15,184 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Generation Flow of Fragment Mechanism
Steps
Step1: 0. helper methods
Step2: 1. load text-format fragment mech
Step3: 2. get thermo and kinetics
Step4: 2.1 correct entropy for certain fra... | Python Code:
import os
from tqdm import tqdm
from rmgpy import settings
from rmgpy.data.rmg import RMGDatabase
from rmgpy.kinetics import KineticsData
from rmgpy.rmg.model import getFamilyLibraryObject
from rmgpy.data.kinetics.family import TemplateReaction
from rmgpy.data.kinetics.depository import DepositoryReaction
... |
15,185 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
intakeOutput
Intake and output recorded for patients. Entered from the nursing flowsheet (either manually or interfaced into the hospital system).
Step2: Examine a single patient
Step3: Ab... | Python Code:
# Import libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import psycopg2
import getpass
import pdvega
# for configuring connection
from configobj import ConfigObj
import os
%matplotlib inline
# Create a database connection using settings from config file
config='../db/conf... |
15,186 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Smooth Overlap of Atomic Positions
SOAP is a local descriptor, that maps the local environment around a point very accurately. It eliminates rotational, and permutation redundancies by integ... | Python Code:
# --- INITIAL DEFINITIONS ---
import numpy, math, random
from visualise import view
from ase import Atoms
import sys
sys.path.insert(0, './data/descriptor_codes/')
sys.path.insert(0, './data/descriptor_codes/src')
from dscribe.descriptors import SOAP
Explanation: Smooth Overlap of Atomic Positions
SOAP is ... |
15,187 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h2 align="center">点击下列图标在线运行HanLP</h2>
<div align="center">
<a href="https
Step1: 加载模型
HanLP的工作流程是先加载模型，模型的标示符存储在hanlp.pretrained这个包中，按照NLP任务归类。
Step2: 调用hanlp.load进行加载，模型会自动下载到本地缓存。自... | Python Code:
!pip install hanlp -U
Explanation: <h2 align="center">点击下列图标在线运行HanLP</h2>
<div align="center">
<a href="https://colab.research.google.com/github/hankcs/HanLP/blob/doc-zh/plugins/hanlp_demo/hanlp_demo/zh/dep_mtl.ipynb" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" ... |
15,188 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Scikit-Learn singalong
Step1: Download EEG Data
The following code downloads a copy of the EEG Eye State dataset. All data is from one continuous EEG measurement with the Emotiv EEG Neuroh... | Python Code:
import pandas as pd
import numpy as np
from collections import Counter
Explanation: Scikit-Learn singalong: EEG Eye State Classification
Author: Kevin Yang
Contact: kyang@h2o.ai
This tutorial replicates Erin LeDell's oncology demo using Scikit Learn and Pandas, and is intended to provide a comparison of th... |
15,189 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Word2Vec Example
(C) 2018 by Damir Cavar
Version
Step1: Using One-Hot Vectors
We can create a one-hot vector that selects the 3rd row
Step2: Let us create a matrix $A$ of four rows
Step3: ... | Python Code:
import numpy as np
Explanation: Word2Vec Example
(C) 2018 by Damir Cavar
Version: 1.1, November 2018
License: Creative Commons Attribution-ShareAlike 4.0 International License (CA BY-SA 4.0)
This is a tutorial related to the L665 course on Machine Learning for NLP focusing on Deep Learning, Spring and Fall... |
15,190 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Writing an algorithm (using Spark/Thunder)
In this notebook, we show how to write an algorithm and put it in a function that can be submitted to the NeuroFinder challenge. In these examples,... | Python Code:
%matplotlib inline
from thunder import Colorize
image = Colorize.image
tile = Colorize.tile
Explanation: Writing an algorithm (using Spark/Thunder)
In this notebook, we show how to write an algorithm and put it in a function that can be submitted to the NeuroFinder challenge. In these examples, the algorit... |
15,191 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Unit Tests
Overview and Principles
Testing is the process by which you exercise your code to determine if it performs as expected. The code you are testing is referred to as the code under t... | Python Code:
import numpy as np
# Code Under Test
def entropy(ps):
if not np.isclose(np.sum(ps), 1.0):
raise ValueError("Probability is not 1.")
items = ps * np.log(ps)
return -np.sum(items)
# Smoke test
probs = [
[0.1, 0.8, 0.1],
[0.1, 0.9],
[0.5, 0.5],
[1.0]
]
for prob in probs:
... |
15,192 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1. Define a function maximum that takes two numbers as arguments and returns the largest of them. Use the if-then-else construct available in Python. (It is true that Python has the max() fu... | Python Code:
assert maximum(3, 3) == 3
assert maximum(1, 2) == 2
assert maximum(3, 2) == 3
Explanation: 1. Define a function maximum that takes two numbers as arguments and returns the largest of them. Use the if-then-else construct available in Python. (It is true that Python has the max() function built in, but writi... |
15,193 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: 텐서플로로 분산 훈련하기
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: 전략의 종류
tf.distribute.Strategy... | 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... |
15,194 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Prediction using normal score for wall street columns using the same data clusters.
Here we will test how the prediction between using mixed receptive fields in time compares with non-time m... | Python Code:
import numpy as np
from sklearn import svm, cross_validation
import h5py
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
import sys
sys.path.append("../")
Explanation: Prediction using normal score for wall street columns using the same data clusters.
Here we will test how the pred... |
15,195 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Algebra and Functions
Step1: Contents
1.Laws of Indices
- Multiplication
- Division
- Raising to power
- Taking a root
- Fraction Indices
- Zero indices
- Negative indices
2.Surds
- Additio... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import math
Explanation: Algebra and Functions
End of explanation
# sample x values
x = np.linspace(-10, 10, 2001).astype(np.float32)
# known variables
a = 2.0
b = 5.0
c = -12.0
# quadratic equation
def eq(x,a,b,c):
return a*x**2 + b*x + c
y = eq(x,a,b... |
15,196 | 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: What are the earliest two films listed in the titles dataframe?
Step2: How many movies have the title "Hamlet"?
Step3: How many ... | Python Code:
titles.shape[0]
Explanation: How many movies are listed in the titles dataframe?
End of explanation
titles.sort(columns='year')[0:2]
Explanation: What are the earliest two films listed in the titles dataframe?
End of explanation
titles[titles['title']=='Hamlet'].shape[0]
Explanation: How many movies have t... |
15,197 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step4: 1T_Pandas로 배우는 SQL 시작하기 (1) - WHERE, ORDER BY
갯수 세기 (COUNT)
칼럼명 변경하기 (AS)
정렬 (ORDER BY)
특정 조건에 대한 필터링(WHERE)
Pandas에서는
JOIN ( merge ) ( * )
GROUP BY ( * )
잠시 주석에 대해서
Step7: SQL(Struc... | Python Code:
def hello():
주석입니다, docstring => 파이썬 코드를 문서화
pass
# 샵 이것도 주석
a =
#Multiline String입니다.
a = "여러줄
텍스트"
a = "여러줄\
텍스트"
a
a =
안녕하세요.
저는 김기표입니다.
a
a.strip()
a.replace("\n", " ")
a.replace("\n", " ").strip()
import pymysql
db = pymysql.connect(
"db.fastcamp.us",
"root",
... |
15,198 | 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 2
Step1: In the following cell, we are just defining what is needed to train the classifier and display it
Step2: Binary Support Vect... | Python Code:
%matplotlib inline
import numpy as np
# class '0'
features_0 = [-1.5, 0] + np.random.randn(100, 2)
labels_0 = np.zeros(100)
# class '1'
features_1 = [+1.5, 0] + np.random.randn(100, 2)
labels_1 = np.ones(100)
# show the training set with matplotlib
import matplotlib.pyplot as plt
plt.figure()
plt.plot(feat... |
15,199 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis on Movie Reviews
Using Logistic Regression, SGD, Naive Bayes, OneVsOne Models
0 - negative
1 - somewhat negative
2 - neutral
3 - somewhat positive
4 - positive
Load Librar... | Python Code:
import nltk
import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer
from sklearn.pipeline import Pipeline
from sklearn.linear_model import LogisticRegression, SGDClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.naive_ba... |
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