Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
|---|---|---|
12,200 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
diabetes = pd.read_csv('Class01_diabetes_data.csv')
diabetes.head()
diabetes.dropna(inplace=True)
diabetes.head()
diabetes.plot(x='Age',y='Target',kind='scatter')
diabetes.plot(x='Sex',y='Target',kind='scatter')
diabetes.plot(x='BMI',y='Target',kind='scatter')
dia... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The next step will be to copy the data file that we will be using for this tutorial into the same folder as these notes. We will be looking at a... |
12,201 | <ASSISTANT_TASK:>
Python Code:
quotient = 7 / 3
print(format(quotient, '.2f'))
remainder = 7 % 3
print(remainder)
5 == 5
5 == 6
type(True), type(False)
x = 10
y = 9
if x < y:
print('x is less than y')
elif x > y:
print('x is greater than y')
else:
print('x and y are equal')
x = 18
y = 20
if x == y:
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The modulus operator turns out to be surprisingly useful. For example, you can check whether one number is divisible by another
Step2: The True... |
12,202 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
pd.__version__
np.__version__
# set some options to control output display
pd.set_option('display.notebook_repr_html',False)
pd.set_option('display.max_columns',10)
pd.set_option('display.max_rows',10)
# create one item series
s1 = pd.Series(1)
s1
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Creating Series
Step2: '0' is the index and '1' is the value. The data type (dtype) is also shown. We can also retrieve the value using the ass... |
12,203 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'ncar', 'sandbox-1', 'landice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "em... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
12,204 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.image as mpimg
import matplotlib.pyplot as plt
import sys,os
ia898path = os.path.abspath('/etc/jupyterhub/ia898_1s2017/')
if ia898path not in sys.path:
sys.path.append(ia898path)
import ia898.src as ia
from numpy.fft import fft2
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Numeric sample
Step2: See that f and h are periodic images and the period is (H,W) that is the shape of f.
Step3: gg and g need to be equal
St... |
12,205 | <ASSISTANT_TASK:>
Python Code:
import sys
import os
sys.path.append(os.environ.get('NOTEBOOK_ROOT'))
from utils.data_cube_utilities.clean_mask import landsat_clean_mask_full
# landsat_qa_clean_mask, landsat_clean_mask_invalid
from utils.data_cube_utilities.dc_mosaic import create_hdmedians_multiple_band_mosaic
from uti... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <span id="Composites_retrieve_data">Load Data from the Data Cube ▴</span>
Step2: <span id="Composites_most_common">Most Common Composites... |
12,206 | <ASSISTANT_TASK:>
Python Code:
import luigi as lg
import json
import pickle
import sys
basedir = '/Users/joewandy/git/lda/code/'
sys.path.append(basedir)
from multifile_feature import SparseFeatureExtractor
from lda import MultiFileVariationalLDA
class ExtractSpectra(lg.Task):
datadir = lg.Parameter()
prefix =... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: These are what we want from the new pipeline.
Step2: Example Step 2
Step3: Example Step 3
Step4: Run the pipeline
Step5: And run the pipelin... |
12,207 | <ASSISTANT_TASK:>
Python Code:
# Authors: Laura Gwilliams <laura.gwilliams@nyu.edu>
# Jean-Remi King <jeanremi.king@gmail.com>
# Alex Barachant <alexandre.barachant@gmail.com>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
import numpy as np
import ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set parameters and read data
Step2: Loop through frequencies, apply classifier and save scores
Step3: Plot frequency results
Step4: Loop thro... |
12,208 | <ASSISTANT_TASK:>
Python Code:
import time
import numpy as np
import h5py
import matplotlib.pyplot as plt
import scipy
from PIL import Image
from scipy import ndimage
from dnn_app_utils_v2 import *
%matplotlib inline
plt.rcParams['figure.figsize'] = (5.0, 4.0) # set default size of plots
plt.rcParams['image.interpolati... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2 - Dataset
Step2: The following code will show you an image in the dataset. Feel free to change the index and re-run the cell multiple times t... |
12,209 | <ASSISTANT_TASK:>
Python Code:
# Setup taken from notebook 17.
import itertools
import sys
import bson
import h5py
import keras.layers
import keras.models
import matplotlib.pyplot
import numpy
import pandas
import sklearn.cross_validation
import sklearn.dummy
import sklearn.linear_model
import sklearn.metrics
sys.path.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Baseline — logistic regression with CNN, astro, and distance features
Step2: Scaling inputs
Step3: Scaling inputs = good. This isn't ter... |
12,210 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alex Rockhill <aprockhill206@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
raw = mne.io.read_raw_fif(data_path + '/MEG/sample/sample_audvis_raw.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load sample subject data
Step2: Plot the raw data and CSD-transformed raw data
Step3: Also look at the power spectral densities
Step4: CSD ca... |
12,211 | <ASSISTANT_TASK:>
Python Code:
from collections import defaultdict
dict_of_colors = defaultdict(list)
with open('input.txt', 'r') as fd:
for line in fd:
if 'no other bags' not in line:
sentence = line.split(' ')
main_color = ' '.join(line.split(' ')[:2])
for i, word in... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Problem 2
|
12,212 | <ASSISTANT_TASK:>
Python Code:
!pip3 install bayesian-optimization
def black_box_function(x, y):
return -x ** 2 - (y - 1) ** 2 + 1
from bayes_opt import BayesianOptimization
# 파라미터 경계 정의
pbounds = {'x': (2, 4), 'y': (-3, 3)}
optimizer = BayesianOptimization(
f=black_box_function,
pbounds=pbounds,
verb... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1. 최적화할 함수 정의
Step2: 2. 최적화 시작
Step3: n_iter
Step4: 최상의 조합은 optimizer.max로 확인 가능
Step5: 2.1 범위 수정
Step6: 3. 최적화 가이드
Step7: 4. 저장, 로딩, 재시작... |
12,213 | <ASSISTANT_TASK:>
Python Code:
set1 = set('Moment of Truth')
set1
set2 = set()
set2.add('A')
set2
# set is similar to dictionary but containing only keys
setA = {'Apple','America','August'}
setA
set3 = set()
set3.add('Blue')
set3.add('Green')
print(set3)
set3.add('Blue')
print(set3)
# please note set is case-sensitive... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set can contain only unique entries. If you try to duplicate an entry in the set
Step2: Sets will not allow any mutable objects. As you can see... |
12,214 | <ASSISTANT_TASK:>
Python Code:
# возьмем лог, который "penalize higher values more than smaller values"
ts_log = np.log(rub["Adj Close"])
test_stationarity(ts_log)
# далее вычтем скользящее среднее
moving_avg = pd.rolling_mean(ts_log,50)
plt.plot(ts_log)
plt.plot(moving_avg, color='red')
ts_log_moving_avg_diff = ts_log... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Два способа убрать сезонность
|
12,215 | <ASSISTANT_TASK:>
Python Code:
import sys
print('{0[0]}.{0[1]}'.format(sys.version_info))
pi = 3.1416
radio = 5
area= pi * radio**2
print(area)
color_list_1 = set(["White", "Black", "Red"])
color_list_2 = set(["Red", "Green"])
color_list_1 - color_list_2
path = 'C:/Users/Margarita/Documents/Mis_documentos/Biologia_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2. Calcule el área de un circulo de radio 5
Step2: 3. Escriba código que imprima todos los colores de que están en color_list_1 y no estan pres... |
12,216 | <ASSISTANT_TASK:>
Python Code:
import seaborn as sns
%matplotlib inline
tips = sns.load_dataset('tips')
tips.head()
sns.distplot(tips['total_bill'])
# Safe to ignore warnings
sns.distplot(tips['total_bill'],kde=False,bins=30)
sns.jointplot(x='total_bill',y='tip',data=tips,kind='scatter')
sns.jointplot(x='total_bill... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Data
Step2: distplot
Step3: To remove the kde layer and just have the histogram use
Step4: jointplot
Step5: pairplot
Step6: rugplot
Step7: ... |
12,217 | <ASSISTANT_TASK:>
Python Code:
X = ["Some say the world will end in fire,",
"Some say in ice."]
len(X)
from sklearn.feature_extraction.text import CountVectorizer
vectorizer = CountVectorizer()
vectorizer.fit(X)
vectorizer.vocabulary_
X_bag_of_words = vectorizer.transform(X)
X_bag_of_words.shape
X_bag_of_words
X_b... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: tf-idf Encoding
Step2: tf-idfs are a way to represent documents as feature vectors. tf-idfs can be understood as a modification of the raw term... |
12,218 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csiro-bom', 'sandbox-2', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name",... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
12,219 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import math
def radius(x):
length of a vector
if len(x.shape) == 1:
return math.sqrt(np.inner(x,x))
# elif len(x.shape) == 2:
def potential(pos):
potential, defined as a negative number... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step6: The Plummer potential for mass $M_p$ and core radius $r_c$ is given by
Step11: Integrator
Step13: Helper functions
Step14: Initial conditions... |
12,220 | <ASSISTANT_TASK:>
Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
pip install --user apache-beam[gcp]==2.16.0
# Ensure the right version of Tensorflow is installed.
!pip freeze | grep tensorflow==2.1
import apache_beam as beam
print(beam.__version__)
# change these to try this notebook... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Run the command again if you are getting oauth2client error.
Step2: You may receive a UserWarning about the Apache Beam SDK for Python 3 as not... |
12,221 | <ASSISTANT_TASK:>
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
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Reformer
Step2: Load example data and model
Step3: Sample from the model
Step4: Sampling is an inherently serial process and will take up to ... |
12,222 | <ASSISTANT_TASK:>
Python Code:
#urllib is used to download the utils file from deeplearning.net
from urllib import request
response = request.urlopen('http://deeplearning.net/tutorial/code/utils.py')
content = response.read()
target = open('utils.py', 'wb')
target.write(content)
target.close()
#Import the math function... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Constructing the Layers of RBMs
Step2: The MNIST Dataset
Step3: Creating the Deep Belief Network
Step4: RBM Train
Step5: Now we can convert ... |
12,223 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import tensorflow as tf
# Implement forward path
# TensorFlow figures out backprop
w = tf.Variable(0, dtype=tf.float32)
cost = tf.add(tf.add(w ** 2, tf.multiply(-10.0, w)), 25)
learning_rate = 0.01
train = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Taken from Andrew Ng's Coursera Deep Learning series
Step2: An alternative way of identifying the cost is to use overloaded operations
Step3: ... |
12,224 | <ASSISTANT_TASK:>
Python Code:
#read data
df = pd.read_fwf('linear_regression_demo/brain_body.txt')
x_values = df[['Brain']]
y_values = df[['Body']]
#train model on data
body_reg = linear_model.LinearRegression()
body_reg.fit(x_values, y_values)
#visualize results
plt.scatter(x_values, y_values)
plt.plot(x_values, body... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Siraj's Week 1 challange
Step2: So now we have simple trained dataset. now to make a prediction.
Step3: Linear Regression Quiz
Step4: Program... |
12,225 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import HTML
def Complex(a, b): # constructor
return (a,b)
def real(c): # method
return c[0]
def imag(c):
return c[1]
def str_complex(c):
return "{0}+{1}i".format(c[0], c[1])
c1 = Complex(1,2) # constructor
print(real(c1), " ", str_complex(c1))
c1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Motiviation
Step2: But things aren't hidden so I can get through the interface
Step3: Because I used a tuple, and a tuple is immutable, I can'... |
12,226 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import itertools
from scipy import stats
from statsmodels.stats.descriptivestats import sign_test
from statsmodels.stats.weightstats import zconfint
%pylab inline
weight_data = pd.read_csv('weight.txt', sep = '\t', header = 0)
weight_data.head()
pyl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Загрузка данных
Step2: Двухвыборочные критерии для связных выборок
Step3: Критерий знаков
Step4: Критерий знаковых рангов Вилкоксона
Step5: ... |
12,227 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import numpy
from matplotlib import pyplot
%matplotlib notebook
dt = 1e-5
dx = 1e-2
x = numpy.arange(0,1+dx,dx)
y = numpy.zeros_like(x)
y = x * (1 - x)
def update_heat(y, dt, dx):
dydt = numpy.zeros_like(y)
dydt[1:-1] = dt/dx**2 * (y[2:] + y[:-2] - ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Note
Step2: The solution looks good - smooth, the initial profile is diffusing nicely. Try with something a bit more complex, such as $y(0, x) ... |
12,228 | <ASSISTANT_TASK:>
Python Code:
def pretty_print_review_and_label(i):
print(labels[i] + "\t:\t" + reviews[i][:80] + "...")
g = open('reviews.txt','r') # What we know!
reviews = list(map(lambda x:x[:-1],g.readlines()))
g.close()
g = open('labels.txt','r') # What we WANT to know!
labels = list(map(lambda x:x[:-1].uppe... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Note
Step2: Lesson
Step3: Project 1
Step4: We'll create three Counter objects, one for words from postive reviews, one for words from negativ... |
12,229 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'inpe', 'sandbox-3', 'atmoschem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
12,230 | <ASSISTANT_TASK:>
Python Code:
%tensorflow_version 1.x
import tensorflow as tf
print(tf.__version__)
# Silence deprecation warnings for now.
tf.logging.set_verbosity(tf.logging.ERROR)
device_name = tf.test.gpu_device_name()
if device_name != '/device:GPU:0':
print('GPU device not found')
gpu = False
else:
print('... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set up FFN code and sample data
Step2: Run inference
|
12,231 | <ASSISTANT_TASK:>
Python Code:
%%writefile requirements.txt
joblib~=1.0
numpy~=1.20
scikit-learn~=0.24
google-cloud-storage>=1.26.0,<2.0.0dev
# Required in Docker serving container
%pip install -U -r requirements.txt
# For local FastAPI development and running
%pip install -U "uvicorn[standard]>=0.12.0,<0.14.0" fastapi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Restart the kernel
Step2: Before you begin
Step3: Otherwise, set your project ID here.
Step4: Authenticate your Google Cloud account
Step5: ... |
12,232 | <ASSISTANT_TASK:>
Python Code:
%pip install 'firebase_admin>=4.1.0'
%pip install 'tensorflow>=2.1.0'
import ipywidgets
uploader = ipywidgets.FileUpload(
accept='.json',
multiple=False
)
service_acct_file = {}
def handle_upload(change):
service_acct_file['name'] = next(iter(change['owner'].value))
servi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 2. Set up a Firebase project
Step2: 4. Set your Google Application Credentials location
Step3: 5. Initialize Firebase Admin
Step4: 6. Train y... |
12,233 | <ASSISTANT_TASK:>
Python Code:
print('Hello, world!')
2 + 2
import numpy
a_integer = 5
a_float = 1.41421356237
a_integer + a_float
a_number = a_integer + a_float
print(a_number)
a_string = 'How you doing, world?'
print(a_string)
a_integer + a_string
print(a_integer, a_string)
str(a_integer) + a_string
a_float = 3.1417... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Define Variables
Step3: Comments are handy to temporarily turn some lines on or off and to document Python files. In Jupyter notebooks using ma... |
12,234 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
import numpy as np
import seaborn as sns
import pandas as pd
from Lec08 import *
plot_svc();
x = np.linspace(-1, 1, 100);
plt.plot(x, x**2)
plt.xlabel("$y-\hat{f}$", size=18);
x = np.linspace(-1, 1, 100);
plt.plot(x, np.abs(x));
plt.xlabel("$y-\hat{f}$", size=18);
plt.yla... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: EECS 445
Step2: Separating Hyperplanes
Step3: Absolute Loss
Step4: 0-1 Loss
Step5: Logistic Loss
Step6: Hinge Loss
Step7: Exponential Loss... |
12,235 | <ASSISTANT_TASK:>
Python Code:
from math import fabs
def bisection(x1, x2, f1, f2, fh, sizevec):
This function finds the root of a function using bisection.
Parameters
----------
x1 : float
lower bound
x2 : float
upper bound
f1 : float
function value at lower bo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Bracketing Methods (Bisection example)
Step2: We are interseted in optimization, so we don't want to find the root of our
|
12,236 | <ASSISTANT_TASK:>
Python Code:
import sys, os
import re
from os import listdir
from os.path import isfile, join
def fromFileToCSV (folderpath,csvfilename) :
files = [f for f in listdir(folderpath) if isfile(join(folderpath, f))]
random.shuffle(files)
for filepath in files:
if filepath.endswith(".pn... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Nous créeons ensuite notre fonction que nous appellerons fromFileToCSV. Cette fonction prend deux arguements
Step2: La variable files est une ... |
12,237 | <ASSISTANT_TASK:>
Python Code:
# Load library
import numpy as np
# Create two vectors
vector_a = np.array([1,2,3])
vector_b = np.array([4,5,6])
# Calculate dot product
np.dot(vector_a, vector_b)
# Calculate dot product
vector_a @ vector_b
<END_TASK> | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create Two Vectors
Step2: Calculate Dot Product (Method 1)
Step3: Calculate Dot Product (Method 2)
|
12,238 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
size = 50
x = np.array((np.random.randint(1,10,size), np.random.randint(1,10,size))).T
print x
mu = np.average(x, 0) # This performs the average over the two main dimensions
mu
x0_bar = 0
x1_bar = 0
for xi in x:
x0_bar += xi[0]
x1_bar += xi[1]
x0_bar /= float(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Unweighted Mean
Step2: To verify...
Step3: Standard Deviation
Step4: This time we will verify using vectorized code...
Step5: Variance
Step6... |
12,239 | <ASSISTANT_TASK:>
Python Code:
%%bash
# Install packages to test model locally.
apt-get update
apt-get install -y python-numpy python-dev cmake zlib1g-dev libjpeg-dev xvfb libav-tools xorg-dev python-opengl libboost-all-dev libsdl2-dev swig libffi-dev
pip install gym
pip install gym[atari]
pip install opencv-python
apt... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: First run locally to make sure everything is working.
Step2: Run on ML-Engine
Step3: TODO
Step4: Launch tensorboard
|
12,240 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm, datasets
from sklearn.cross_validation import train_test_split
from sklearn.metrics import confusion_matrix
import matplotlib
from matplotlib import pyplot as plt
%matplotlib inline
#load the d... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Classification problem with Unbalanced classes
Step2: Precision, Recall and F measures
|
12,241 | <ASSISTANT_TASK:>
Python Code:
from ipyparallel import Client
cluster = Client()
dview = cluster[:]
dview.use_dill()
lview = cluster.load_balanced_view()
len(dview)
# import os
# from scripts.hpc05 import HPC05Client
# os.environ['SSH_AUTH_SOCK'] = os.path.join(os.path.expanduser('~'), 'ssh-agent.socket')
# cluster = ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This next cell is for internal use with our cluster at the department, a local ipcluster will work
Step2: Make sure to add the correct path lik... |
12,242 | <ASSISTANT_TASK:>
Python Code:
print 'The default path: '+fp.fhd_base()
fp.set_fhd_base(os.getcwd().strip('scripts')+'katalogss/data')
print 'Our path: '+fp.fhd_base()
fhd_run = 'mock_run'
s = '%sfhd_%s'%(fp.fhd_base(),fhd_run)
!ls -R $s
obsids = fp.get_obslist(fhd_run)
obsids
comps = fp.fetch_comps(fhd_run, obsids... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We also need to define the version specifying the name of the run. This is equivalent to the case string in eor_firstpass_versions.pro, or the s... |
12,243 | <ASSISTANT_TASK:>
Python Code:
from larray import *
age_category = Axis(["0-9", "10-17", "18-66", "67+"], "age_category")
age_category
age_category = Axis("age_category=0-9,10-17,18-66,67+")
age_category
a = Axis('a=a0,a1,a2,a3')
a
a = Axis('a=a0..a3')
a
arr = zeros("a=a0..a2; b=b0,b1; c=c0..c5")
arr
immigration ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The LArray library offers two syntaxes to build axes and make selections and aggregations.
Step2: The second one consists of using strings that... |
12,244 | <ASSISTANT_TASK:>
Python Code:
from importlib import reload
import xml_parser
reload(xml_parser)
from xml_parser import Xml_parser
#Xml_parser = Xml_parser().collect_data("../pmi_data")
authorID_to_titles = utils.load_pickle("../pmi_data/authorID_to_publications.p")
authorID_to_count = {k:len(v['titles']) for k,v in t... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Observation of the data
Step2: We can observe that most of the authors have between 1 and 50 publications. A few author have around 50 and 200 ... |
12,245 | <ASSISTANT_TASK:>
Python Code:
import json
import os
import numpy as np
import pandas as pd
import pickle
import uuid
import time
import tempfile
from googleapiclient import discovery
from googleapiclient import errors
from google.cloud import bigquery
from jinja2 import Template
from kfp.components import func_to_cont... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Run the command in the cell below to install gcsfs package.
Step2: Prepare lab dataset
Step3: Next, create the BigQuery dataset and upload the... |
12,246 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
# Create a tensorflow constant
hello = tf.constant("Hello World!")
# Print this variable as is
print(hello)
# Create a new session
sess = tf.Session()
# Print the constant
print("Printing using Session.run()")
print(sess.run(hello))
# Also
print("Printing using ev... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Oops! That is not what we wanted! This is because the variable hello hasn't been evaluated yet. Tensorflow needs a session to run the graph in!
... |
12,247 | <ASSISTANT_TASK:>
Python Code:
from oemof.solph import EnergySystem
import pandas as pd
# initialize energy system
energysystem = EnergySystem(timeindex=pd.date_range('1/1/2016',
periods=168,
freq='H'))
# import e... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Import input data
Step2: Add entities to energy system
Step4: Optimize energy system and plot results
Step5: Adding the gas sector
Step6: Ad... |
12,248 | <ASSISTANT_TASK:>
Python Code:
from fretbursts import *
sns = init_notebook(apionly=True)
print('seaborn version: ', sns.__version__)
# Tweak here matplotlib style
import matplotlib as mpl
mpl.rcParams['font.sans-serif'].insert(0, 'Arial')
mpl.rcParams['font.size'] = 12
%config InlineBackend.figure_format = 'retina'
u... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get and process data
Step2: Filtering method
Step3: DCBS Method
Step4: The function bext.burst_search_and_gate()
Step5: Before plotting we s... |
12,249 | <ASSISTANT_TASK:>
Python Code:
<image>
<section data-background="img/cover.jpg" data-state="img-transparent no-title-footer">
<div class="intro-body">
<div class="intro_h1"><h1>Title</h1></div>
<h3>Subtitle of the Presentation</h3>
<p><strong><span class="a">Speaker 1</span></strong> <span class="b"></span> <span>Job T... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Cover Slide 2
Step3: Headline Subslide
|
12,250 | <ASSISTANT_TASK:>
Python Code:
import essentia.streaming as ess
import essentia
audio_file = '../../../test/audio/recorded/mozart_c_major_30sec.wav'
# Initialize algorithms we will use.
loader = ess.MonoLoader(filename=audio_file)
framecutter = ess.FrameCutter(frameSize=4096, hopSize=2048, silentFrames='noise')
windowi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Let's plot the resulting HPCP
Step2: Now we can run a naive estimation of chords with 2-second sliding window over the computed HPCPgram
|
12,251 | <ASSISTANT_TASK:>
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 imp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: DDL to construct table for SQL transformations
Step2: Note
Step3: Model Prototyping
|
12,252 | <ASSISTANT_TASK:>
Python Code:
xy = np.random.multivariate_normal([0,0], [[10,7],[7,10]],1000)
plt.plot(xy[:,0],xy[:,1],"o")
plt.show()
pca = PCA(n_components=2)
xy_pca = pca.fit(xy)
plt.plot(xy[:,0],xy[:,1],"o")
scalar = xy_pca.explained_variance_[0]
plt.plot([0,xy_pca.components_[0,0]*scalar/2],[0,xy_pca.component... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Create a Principle Component Analysis (PCA) object
Step2: num_components is the number of axes on which you spread the data out. You can only ... |
12,253 | <ASSISTANT_TASK:>
Python Code:
folder = os.path.join('..', 'data')
newsbreaker.init(os.path.join(folder, 'topic_model'), 'topic_model.pkl', 'vocab.txt')
entries = load_entries(folder)
entries_dict = defaultdict(list)
for entry in entries:
entries_dict[entry.feed].append(entry)
client = MongoClient()
db = client.new... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Algorithm
Step2: Save coefs (X) and Y, along with tests (to know what each row refers to) to work with it later
Step3: What without NEs
Step4:... |
12,254 | <ASSISTANT_TASK:>
Python Code:
import numpy as np, matplotlib.pyplot as plt, pandas as pd, pymc as mc
import dismod_mr
model = dismod_mr.data.load('pd_sim_data')
model.keep(areas=['europe_western'], sexes=['female', 'total'])
summary = model.input_data.groupby('data_type')['value'].describe()
np.round(summary,3).sort... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: DisMod-MR uses the integrative systems modeling (ISM) approach to produce simultaneous
Step2: Of the 348 rows of data, here is how the values b... |
12,255 | <ASSISTANT_TASK:>
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 impo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Batch Normalization
Step2: Batch normalization
Step3: Batch Normalization
Step4: Batch Normalization
Step5: Fully Connected Nets with Batch ... |
12,256 | <ASSISTANT_TASK:>
Python Code:
# Ensure the right version of Tensorflow is installed.
!pip freeze | grep tensorflow==2.1
%pip install apache-beam[gcp]==2.13.0
import apache_beam as beam
print(beam.__version__)
# change these to try this notebook out
BUCKET = 'cloud-training-demos-ml'
PROJECT = 'cloud-training-demos'
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: After installing Apache Beam, restart your kernel by selecting "Kernel" from the menu and clicking "Restart kernel..."
Step2: You may receive a... |
12,257 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
import skrf as rf
import numpy as np
from numpy import real, log10, sum, absolute, pi, sqrt
import matplotlib.pyplot as plt
from scipy.optimize import minimize, differential_evolution
rf.stylely()
# Load raw measurements
MSL100_raw = rf.Network('MSL100.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Measurement of two microstripline with different lengths
Step2: The measured data shows that the electrical length of MSL200 is approximately t... |
12,258 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.optimize import linprog
import quantecon.game_theory as gt
U = np.array(
[[0, -1, 1],
[1, 0, -1],
[-1, 1, 0]]
)
p0 = gt.Player(U)
p1 = gt.Player(-U.T)
g = gt.NormalFormGame((p0, p1))
print(g)
gt.lemke_howson(g)
gt.support_enumeration(g)
m, n... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: じゃんけん・ゲームを例に計算してみる．
Step2: quantecon.game_theory でナッシュ均衡を求める
Step3: プレイヤー1の行列は -U の転置 (.T) であることに注意．
Step4: scipy.optimize.linprog で線形計画問題を解く... |
12,259 | <ASSISTANT_TASK:>
Python Code:
class Directions:
NORTH = 'North'
SOUTH = 'South'
EAST = 'East'
WEST = 'West'
STOP = 'Stop'
def P_1(eps, E_N, E_S):
'''
Calculates: P(X=x|E_{N}=e_{N},E_{S}=e_{S})
Arguments: E_N, E_S \in {True,False}
0 <= eps <= 1 (epsilon)
Returns: dict... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: a. Bayes' net for instant perception and position.
Step2: ii. $P(E_{E}=e_{E}|E_{N}=e_{N},E_{S}=E_{S})$
Step3: iii. $P(S)$, where $S\subseteq{e... |
12,260 | <ASSISTANT_TASK:>
Python Code:
from explauto.environment import environments
environments.keys()
from explauto.environment import available_configurations
available_configurations('simple_arm').keys()
available_configurations('simple_arm')['mid_dimensional']
available_configurations('pendulum').keys()
from explauto... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: According to your installation, you will see at least two available environments
Step2: For example, the 'mid_dimensional' configuration corres... |
12,261 | <ASSISTANT_TASK:>
Python Code:
from pynq.overlays.base import BaseOverlay
base = BaseOverlay("base.bit")
from time import sleep
from pynq.lib import Pmod_Timer
pt = Pmod_Timer(base.PMODA,0)
pt.stop()
# Generate a 10 ns pulse every period*10 ns
period=100
pt.generate_pulse(period)
# Sleep for 4 seconds and stop the ti... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Instantiate Pmod_Timer class. The method stop() will stop both timer sub-modules.
Step2: 2. Generate pulses for a certain period of time
Step3:... |
12,262 | <ASSISTANT_TASK:>
Python Code:
%pylab notebook
%precision %.4g
V = 240 # [V]
Z1 = 10.0 * exp(1j* 30/180*pi)
Z2 = 10.0 * exp(1j* 45/180*pi)
Z3 = 10.0 * exp(1j*-90/180*pi)
I1 = V/Z1
I2 = V/Z2
I1_angle = arctan(I1.imag/I1.real)
I2_angle = arctan(I2.imag/I2.real)
print('''I1 = {:.1f} A ∠{:.1f}°
I2 = {:.1f} A ∠{:.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Description
Step2: Answer the following questions about this power system.
Step3: Therefore the total current from the source is $\vec{I} = \v... |
12,263 | <ASSISTANT_TASK:>
Python Code:
# change these to try this notebook out
BUCKET = 'cloud-training-demos-ml'
PROJECT = 'cloud-training-demos'
REGION = 'us-east1' #'us-central1'
import os
os.environ['BUCKET'] = BUCKET
os.environ['PROJECT'] = PROJECT
os.environ['REGION'] = REGION
%%bash
if ! gsutil ls | grep -q gs://${BUCKE... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Create Keras model
Step2: Next, define the feature columns. mother_age and gestation_weeks should be numeric.
Step3: We can visualize the DNN ... |
12,264 | <ASSISTANT_TASK:>
Python Code:
# Imports
import sys,math
sys.path.insert(0, '..') # path to ../common.py
import numpy as np
import matplotlib.pyplot as plt
from common import *
# READ PRESSURES AND FLOWS FROM FILE
qVals = np.loadtxt('Qgeneral')
pVals = np.loadtxt('Pgeneral')
print('Total Number of interfaces: %d' % (qV... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: As you can see, the model selected for this tutorial has 20 outlets.
Step2: PART II
Step3: We would like to use legendre polynomials for regre... |
12,265 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'sandbox-3', 'atmos')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "emai... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
12,266 | <ASSISTANT_TASK:>
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 ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
12,267 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import YouTubeVideo
YouTubeVideo(id="JjpbztqP9_0", width="100%")
from nams import load_data as cf
G = cf.load_sociopatterns_network()
from nams.solutions.paths import bfs_algorithm
# UNCOMMENT NEXT LINE TO GET THE ANSWER.
# bfs_algorithm()
# FILL IN THE BLANKS BELOW... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Graph traversal is akin to walking along the graph, node by node,
Step4: Exercise
Step5: Visualizing Paths
Step6: As you can see, it returns ... |
12,268 | <ASSISTANT_TASK:>
Python Code:
import facebook # for connecting to Facebook Graph API
import pprint
import datetime
import pandas as pd
import logging
logger = logging.Logger('catch_all')
# send request to Facebook Graph API, fetching last 50 posts of each page :
def collector(page, token, lim) :
graph = facebook.G... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set up variables
Step2: First, run this code to create new csv files of all pages
Step3: A csv file example
Step4: Then, run this code hour... |
12,269 | <ASSISTANT_TASK:>
Python Code:
import my_util as my_util; from my_util import *
HOME_DIR = 'd:/larc_projects/job_analytics/'
DATA_DIR = HOME_DIR + 'data/clean/'
title_df = pd.read_csv(DATA_DIR + 'new_titles_2posts_up.csv')
def distTitle(agg_df, for_domain=False, for_func=False):
fig = plt.figure()
plt.hist(agg... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Helpers
Step2: Distribution of job posts among job titles
Step3: Job posts distribution among standard job titles
Step4: Statistics for Domai... |
12,270 | <ASSISTANT_TASK:>
Python Code:
# You will need these things!
import numpy as np
import pandas as pd
# the structure of a function is like this:
def dir2cart(dec,inc,R): # first line starts with 'def', has the name and the input parameters (data)
# all subsequent lines are indented
# continue this function ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Let's write a little function to do the conversion.
Step2: Now let's read in a data file with some geomagnetic field vectors in it.
Step3: Pro... |
12,271 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import sympy as sp
from devito import Grid, TimeFunction
# Create our grid (computational domain)
Lx = 10
Ly = Lx
Nx = 11
Ny = Nx
dx = Lx/(Nx-1)
dy = dx
grid = Grid(shape=(Nx,Ny), extent=(Lx,Ly))
# Define u(x,y,t) on this grid
u = TimeFunction(name='u', grid=grid, time_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Now, lets look at the output of $\partial u/\partial x$
Step2: By default the 'standard' Taylor series expansion result, where h_x represents t... |
12,272 | <ASSISTANT_TASK:>
Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
! pip3 install -U google-cloud-storage $USER_FLAG
if os.getenv("IS_TESTING"):
!... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Step3: Before you begin
Step4: Region
Step5:... |
12,273 | <ASSISTANT_TASK:>
Python Code:
exec(open('tbc.py').read()) # define TBC and TBC_above
import astropy.io.fits as pyfits
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from io import StringIO # StringIO behaves like a file object
import scipy.stats as st
from pygtc import plotGTC
import incredibl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Once again, we will read in the X-ray image data, and extract a small image around an AGN that we wish to study.
Step2: Fitting for 2 parameter... |
12,274 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from __future__ import print_function
import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
PROJ_ROOT = os.path.join(os.pardir, os.pardir)
def load_pumps_data(values_path, labels_path):
# YOUR CODE HERE
pass
values = os.p... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Use debugging tools throughout!
Step4: Exercise 2
Step6: Exercise 3
|
12,275 | <ASSISTANT_TASK:>
Python Code:
import ipywidgets as widgets
out = widgets.Output(layout={'border': '1px solid black'})
out
with out:
for i in range(10):
print(i, 'Hello world!')
from IPython.display import YouTubeVideo
with out:
display(YouTubeVideo('eWzY2nGfkXk'))
with out:
display(widgets.IntS... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: The Output widget can capture and display stdout, stderr and rich output generated by IPython. You can also append output directly to an output ... |
12,276 | <ASSISTANT_TASK:>
Python Code:
class Node :
def __init__(self , key ) :
self . key = key
self . left = None
self . right = None
def printSingles(root ) :
if root is None :
return
if root . left is not None and root . right is not None :
printSingles(root . left )
printSingles(root . right... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
12,277 | <ASSISTANT_TASK:>
Python Code:
import cvxpy as cp
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from cvxpylayers.tensorflow.cvxpylayer import CvxpyLayer
from sklearn.datasets import make_blobs
from sklearn.model_selection import train_test_split
tf.random.set_seed(0)
np.random.seed(0)
n = ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: We are given training data $(x_i, y_i){i=1}^{N}$,
Step2: Assume that our training data is subject to a data poisoning attack,
Step3: Below, we... |
12,278 | <ASSISTANT_TASK:>
Python Code:
from nussl import datasets, separation, evaluation
import os
import multiprocessing
from concurrent.futures import ThreadPoolExecutor
import logging
import json
import tqdm
import glob
import numpy as np
import termtables
# set up logging
logger = logging.getLogger()
logger.setLevel(loggi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Setting up
Step2: Evaluation
|
12,279 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import xarray as xr
import cartopy.crs as ccrs
from matplotlib import pyplot as plt
print("numpy version : ", np.__version__)
print("pandas version : ", pd.__version__)
print("xarray version : ", xr.version.version)
! curl -L -... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: As an example, consider this dataset from the xarray-data repository.
Step2: In this example, the logical coordinates are x and y, while the ph... |
12,280 | <ASSISTANT_TASK:>
Python Code:
# To enable Tensorflow 2 instead of TensorFlow 1.15, uncomment the next 4 lines
#try:
# %tensorflow_version 2.x
#except Exception:
# pass
# library to store and manipulate neural-network input and output data
import numpy as np
# library to graphically display any data
import matplotl... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Get the data
Step2: Build the artificial neural-network
Step3: Train the artificial neural-network model
Step4: Evaluate the model
Step5: Pr... |
12,281 | <ASSISTANT_TASK:>
Python Code:
# the output of plotting commands is displayed inline within frontends,
# directly below the code cell that produced it
%matplotlib inline
from __future__ import print_function
# this python library provides generic shallow (copy) and deep copy (deepcopy) operations
from copy import dee... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Setting project directory
Step2: Genesis Field file dfl
Step3: Statistical properties postprocessing
|
12,282 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import math
x = np.linspace(.25,1,num=201)
obj = []
for i in range(len(x)):
obj.append(math.sqrt(1/x[i]**2-1))
plt.plot(x,obj)
import cvxpy as cp
x = cp.Variable(pos=True)
obj = cp.sqrt(cp.inv_pos(... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Minimizing this objective function subject to constraints representing payload requirements is a standard aerospace design problem. In this case... |
12,283 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation, rc
from IPython.display import HTML
# first set up the figure, the axes and the plot element we want to animate
fig, ax = plt.subplots()
ax.set_xlim( 0, 2)
ax.set_ylim(-1, 2)
line, = ax... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: To show the animation, anim uses its conversion of the video to html5 using its method to_html5_video(), and the result is shown through the HTM... |
12,284 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
def isccsym2(F):
if len(F.shape) == 1: F = F[np.newaxis,np.newaxis,:]
if len(F.shape) == 2: F = F[np.newaxis,:,:]
n,m,p = F.shape
x,y,z = np.indices((n,m,p))
Xnovo = np.mod(-1*x,n)
Ynovo = np.mod(-1*y,m)
Znovo = np.mod(-1*z,p)
aux = ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Examples
Step2: Numeric Example
Step3: Numeric Example
Step4: Numeric Example
Step5: Numeric Example
Step6: Image Example
Step7: Image Exa... |
12,285 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pyiast
import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
%config InlineBackend.rc = {'font.size': 13, 'lines.linewidth':3,\
'axes.facecolor':'w', 'legend.numpoints':1,\
'fig... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Generate synthetic pure-component isotherm data, fit Langmuir models to them.
Step2: Generate data according to Langmuir model, store in list o... |
12,286 | <ASSISTANT_TASK:>
Python Code:
# Case Study : Predicting Housing Price
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
# Importing Boston housing data
from sklearn.datasets import load_boston
boston = load_boston()
boston.keys()
boston.feature_names
X = bo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Validating the assumptions made in regression
Step2: How can you improve the accuracy of a regression model ?
Step3: Evaluation Metrics
|
12,287 | <ASSISTANT_TASK:>
Python Code:
import graphlab
people = graphlab.SFrame('people_wiki.gl/')
people.head()
len(people)
obama = people[people['name'] == 'Barack Obama']
obama
obama['text']
obama['word_count'] = graphlab.text_analytics.count_words(obama['text'])
print obama['word_count']
obama_word_count_table = obama... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Cargar el dataset
Step2: Los datos contienen articulos de wikipedia sobre diferentes personas.
Step3: Buscaremos al expresidente Barack Obama
... |
12,288 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
view_sentence_range = (8, 100)
DON'T MODIFY ANYTHING IN THIS CELL
import nu... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: TV Script Generation
Step3: Explore the Data
Step6: Implement Preprocessing Functions
Step9: Tokenize Punctuation
Step11: Preprocess all the... |
12,289 | <ASSISTANT_TASK:>
Python Code:
from goatools.base import get_godag
godag = get_godag("go-basic.obo", optional_attrs={'relationship'})
go_leafs = set(o.item_id for o in godag.values() if not o.children)
virion = 'GO:0019012'
from goatools.gosubdag.gosubdag import GoSubDag
gosubdag_r0 = GoSubDag(go_leafs, godag)
nt_vir... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: 2) Depth-01 term, GO
Step2: Notice that dcnt=0 for GO
Step3: 3) Depth-01 term, GO
Step4: 4) Depth-01 term, GO
Step5: 5) Descendants under GO... |
12,290 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
import calin.simulation.detector_efficiency
import calin.simulation.atmosphere
import calin.provenance.system_info
data_dir = calin.provenance.system_info.build_info().data_install_dir() + "/simulation/"
print("Simulation data directory:",data_dir)
det_eff = calin.simulati... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: 1 - Get location of calin simulation data files
Step2: 2 - Construct detector efficiency
Step3: 3 - Load lightcone efficiency
Step4: 4 - Resc... |
12,291 | <ASSISTANT_TASK:>
Python Code:
import random
import time
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from fct import normalize_min_max, plot_2d, plot_clusters
def build_d(datas, centers):
Return a 2D-numpy array of the distances between each
point in the dataset and the centers. The ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step6: Algorithm
Step7: Application
|
12,292 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
l = [('A', '1', 'a'), ('A', '1', 'b'), ('A', '2', 'a'), ('A', '2', 'b'), ('B', '1','a'), ('B', '1','b')]
np.random.seed(1)
df = pd.DataFrame(np.random.randn(5, 6), columns=l)
def g(df):
df.columns = pd.MultiIndex.from_tuples(df.columns, names=[... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
12,293 | <ASSISTANT_TASK:>
Python Code:
class BinaryTree():
def __init__(self, children = None):
A binary tree is either a leaf or a node with two subtrees.
INPUT:
- children, either None (for a leaf), or a list of size excatly 2
of either two bina... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step7: Arbres binaires
Step8: Il y a 5 arbres binaires de taille 3. L'un deux est celui que nous venons de construire.
Step19: Le but de ce TP est d... |
12,294 | <ASSISTANT_TASK:>
Python Code:
import copy
try:
import ujson as json
except ImportError:
import json
import math
import operator
import random
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from numpy.linalg import norm as np_norm
import matplotlib.pyplot as plt
import pandas as pd
from scipy.sp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Simple, visualizable spaces
Step2: We have a 2-dimensional feature space containing 1000 pieces of data. Each coordinate is orthogonal, and we ... |
12,295 | <ASSISTANT_TASK:>
Python Code:
from owslib.csw import CatalogueServiceWeb
from owslib import fes
import numpy as np
#endpoint = 'https://dev-catalog.ioos.us/csw'
#endpoint = 'http://gamone.whoi.edu/csw'
endpoint = 'https://data.ioos.us/csw'
#endpoint = 'https://ngdc.noaa.gov/geoportal/csw'
csw = CatalogueServiceWeb(en... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step2: Search first for records containing the two text strings
Step3: Now let's print out the references (service endpoints) to see what types of ser... |
12,296 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
plt.rcParams['figure.figsize'] = (20.0, 10.0)
plt.rcParams['font.family'] = "serif"
df = pd.read_csv('../../../datasets/movie_metadata.csv')
df.head()
# split each movie's genr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: For the bar plot, let's look at the number of movies in each category, allowing each movie to be counted more than once.
Step2: Basic plot
Step... |
12,297 | <ASSISTANT_TASK:>
Python Code:
def generator1():
yield 1
yield 2
yield 3
for value in generator1():
print(value)
def generator2():
yield "Hello"
yield "World"
my_gen = generator2()
print(next(my_gen))
print(next(my_gen))
def check_for_value(num):
try:
while True:
rec... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Coroutines
Step2: Coroutine Pipelines
Step3: Asynchronous Python
Step4: Async and Await (python 3.5+)
|
12,298 | <ASSISTANT_TASK:>
Python Code:
%%capture
!wget https://github.com/cltl/python-for-text-analysis/raw/master/zips/Data.zip
!wget https://github.com/cltl/python-for-text-analysis/raw/master/zips/images.zip
!wget https://github.com/cltl/python-for-text-analysis/raw/master/zips/Extra_Material.zip
!unzip Data.zip -d ../
!unz... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Chapter 6 - Lists
Step2: Square brackets surround lists, and commas separate the elements in the list
Step3: Please note that there are two wa... |
12,299 | <ASSISTANT_TASK:>
Python Code:
df['Age'].describe()
df.groupby('Gender')['Income'].describe()
df['Income'].describe()
df['SchoolMajor'].value_counts()
df['SchoolDegree'].value_counts()
df.sort_values(by='StudentDebtOwe', ascending=False).head()
df[(df['BootcampFullJobAfter']==1) & (df['BootcampLoanYesNo']==1)].he... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: 2. What are the maximum income for female programmers?
Step2: 3. how much does a programmer make on average per year?
Step3: 4. what is the mo... |
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