Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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11,100 | <ASSISTANT_TASK:>
Python Code:
%%bash
signac --help
% pwd
% rm -rf projects/tutorial/cli
% mkdir -p projects/tutorial/cli
% cp idg projects/tutorial/cli
% cd projects/tutorial/cli
%%bash
signac init TutorialCLIProject
%%bash
signac project
signac project --workspace
%%bash
signac job '{"kT": 1.0, "p": 1.0, "N": 10... | <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: To interact with a project on the command line, the current working directory needs to be within or below the project root directory.
Step2: Ne... |
11,101 | <ASSISTANT_TASK:>
Python Code:
#cargar librerias
import pandas as pd
import numpy as np
df = pd.read_csv('co_properties.csv.gz', compression='gzip', header=0, sep=',', quotechar='"')
df.head()
df.l3.value_counts()
df=df[df['l3']=='Bogotá D.C']
df.l3.value_counts()
df.groupby('currency').agg({'id':'count'})
df=df... | <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: Cargo los datos que vienen de <a href='https
Step2: Propiedades en Bogotá
Step3: Propiedades que el precio esta en COP
Step4: Propiedades en... |
11,102 | <ASSISTANT_TASK:>
Python Code:
PATH_NEWS_ARTICLES = ""
from nltk.corpus import stopwords
from nltk.tokenize import TweetTokenizer
from nltk.stem.snowball import SnowballStemmer
import re
import pickle
import pandas as pd
import gensim
from gensim import corpora, models
df=pd.read_csv(PATH_NEWS_ARTICLES)
df.head(5)
sto... | <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. TEXT PROCESSING
Step2: 2. TOPIC MODELING
Step4: Generate Topics for a new Article
Step5: Describing parameters
|
11,103 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alexandre Barachant <alexandre.barachant@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeline import make_pipeline
from sklearn.linear_model import LogisticRegression
... | <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
|
11,104 | <ASSISTANT_TASK:>
Python Code:
%%capture --no-stderr
KFP_PACKAGE = 'https://storage.googleapis.com/ml-pipeline/release/0.1.14/kfp.tar.gz'
!pip3 install $KFP_PACKAGE --upgrade
import kfp.components as comp
dataproc_submit_hadoop_job_op = comp.load_component_from_url(
'https://raw.githubusercontent.com/kubeflow/pipe... | <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 the component using KFP SDK
Step2: Sample
Step3: Insepct Input Data
Step4: Clean up the existing output files (optional)
Step5: Example... |
11,105 | <ASSISTANT_TASK:>
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 writin... | <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 with TensorFlow Lite Model Maker
Step2: Import the required packages.
Step3: Simple End-to-End Example
Step4: You could ... |
11,106 | <ASSISTANT_TASK:>
Python Code:
from larray import *
# load 'demography_eurostat' dataset
demography_eurostat = load_example_data('demography_eurostat')
# extract the 'population' array from the dataset
population = demography_eurostat.population
population
# Array summary: metadata + dimensions + description of axes
... | <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: Inspecting Array objects
Step2: Get axes
Step3: Get axis names
Step4: Get number of dimensions
Step5: Get length of each dimension
Step6: G... |
11,107 | <ASSISTANT_TASK:>
Python Code:
import reprlib
class Sentence:
def __init__(self, text):
self.text = text
self.words = text.split()
def __getitem__(self, index):
return self.words[index]
def __len__(self):
#completes sequence protocol, but not needed for iterab... | <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: To iterate over an object x, Python automatically calls iter(x) (i.e. x.__iter__).
Step2: What's actually going on here?
Step3: We can comple... |
11,108 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
from IPython.display import Image
import base64
Image(data=base64.decodestring("iVBORw0KGgoAAAANSUhEUgAAAMYAAABFCAYAAAARv5krAAAYl0lEQVR4Ae3dV4wc1bYG4D3YYJucc8455yCSSIYrBAi4EjriAZHECyAk3rAID1gCIXGRgIvASIQr8UTmgDA5imByPpicTcYGY+yrbx+tOUWpu2e6u7qnZ7qXVFP... | <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: We're going to be building a model that recognizes these digits as 5, 0, and 4.
Step3: Working with the images
Step4: The first 10 pixels are ... |
11,109 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import pints
import pints.toy
model = pints.toy.Hes1Model()
print('Outputs: ' + str(model.n_outputs()))
print('Parameters: ' + str(model.n_parameters()))
times = model.suggested_times()
smooth_times = np.linspace(times[0], times[-1], 100... | <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 can get some suggested parameters and plot some data! In experiments, typically it is not easy to have high sampling rate (time points), so o... |
11,110 | <ASSISTANT_TASK:>
Python Code:
def cria_matriz(num_linhas, num_colunas):
matriz = [] #lista vazia
for i in range(num_linhas):
linha = []
for j in range(num_colunas):
linha.append(0)
matriz.append(linha)
for i in range(num_colunas):
for j in range(num_linhas):
... | <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: Exercício 1
Step2: Exercício 2
Step3: Praticar tarefa de programação
Step4: Exercício 2
|
11,111 | <ASSISTANT_TASK:>
Python Code:
import os, glob
import fitsio
import numpy as np
import matplotlib.pyplot as plt
from astropy.table import vstack, Table, hstack
import seaborn as sns
sns.set(context='talk', style='ticks', font_scale=1.0)
%matplotlib inline
lslgaver = b'L6'
lslgafile = '/global/cfs/cdirs/desi/users/ioann... | <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: Geometry comparison of LSLGA galaxies
Step2: Compare the various sizes
|
11,112 | <ASSISTANT_TASK:>
Python Code:
# load and plot dataset
from pandas import read_csv
from pandas import datetime
from matplotlib import pyplot
# load dataset
def parser(x):
return datetime.strptime(x, '%Y-%m-%d')
series = read_csv('../data/yellowstone-visitors.csv', header=0, parse_dates=[0], index_col=0, squeeze=Tru... | <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 park's recreational visits are highly seasonable with the peak season in July. The park tracks monthly averages from the last four years on... |
11,113 | <ASSISTANT_TASK:>
Python Code:
from pytadbit.mapping.analyze import eig_correlate_matrices, correlate_matrices
from pytadbit import load_hic_data_from_reads
from cPickle import load
from matplotlib import pyplot as plt
reso = 1000000
base_path = 'results/{0}/03_filtering/valid_reads12_{0}.tsv'
bias_ice_path = 'results/... | <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: Write a little function to load HiCData obeject
Step2: Load data
Step3: DRY normalized
Step4: Plot correlations
Step5: DRY
Step6: Repeat at... |
11,114 | <ASSISTANT_TASK:>
Python Code:
(val_classes, train_classes,
val_labels, train_labels,
val_filenames, train_filenames,
test_filenames) = get_classes('data/fish/')
print(val_classes)
print(train_classes)
print(val_labels)
print(train_labels)
print(val_filenames)
print(train_filenames)
print(test_filenames)
# removing ... | <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: Precompute convolutional output
Step2: Fully convolutional net (FCN)
Step3: Bounding boxes and Multi-Output
|
11,115 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pylab as plt
from tsfresh.examples.har_dataset import download_har_dataset, load_har_dataset, load_har_classes
import seaborn as sns
from tsfresh import extract_features, extract_relevant_features, select_features
from tsfresh.utilities.dataframe_funct... | <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 and visualize data
Step2: Extract Features
Step3: Train and evaluate classifier
Step4: Compare against naive classification accuracy
|
11,116 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import time as tm
import matplotlib.pyplot as plt
# Discretization
c1=20 # Number of grid points per dominant wavelength
c2=0.5 # CFL-Number
nx=2000 # Number of grid points
T=10 # Total propagation time
# Source Signal
f0= 10 # Center fre... | <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: Input Parameter
Step2: Preparation
Step3: Create space and time vector
Step4: Source signal - Ricker-wavelet
Step5: Time stepping
Step6: Sa... |
11,117 | <ASSISTANT_TASK:>
Python Code:
%%file data.scons
Flow('trace',None,'spike n1=2001 d1=0.001 k1=1001 | ricker1 frequency=30')
Flow('gather','trace','spray axis=2 n=49 d=25 o=0 label=Offset unit=m | nmostretch inv=y half=n v0=2000')
Result('gather','window f1=888 n1=392 | grey title=Gather')
from m8r import view
view('gat... | <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: Display the same with Python (matplotlib)
Step2: Apply moveout with incorrect velocity
Step3: Slope estimation
Step4: Non-physical flattening... |
11,118 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv('ohw_anonymised.csv', index_col='datetime', parse_dates=True)
df_ohw20 = df[df.ohw20_repo]
df
weekly_commits = df.author.groupby(df.index.week).count()
df_hw = df[df.index.week==33]
hw_commits = df_h... | <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 read in the anaonymised data to a pands dataframe and make a second dataframe of only commits to OHW20 repos
Step2: Commits in time
Step3: ... |
11,119 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df = pd.read_csv('Class10_wine_data.csv')
df.head()
# Plot the first two feature columns
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('white')
#plt.figure(figsize=(8,6))
plt.scatter(df['Alcohol'], df['Malic acid'])
plt.xlabel('Alcohol (%/L)')
pl... | <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: There are a number of different features here. We'll focus on the first two
Step2: Standarization scaling
Step3: We've accomplished what we se... |
11,120 | <ASSISTANT_TASK:>
Python Code:
import sys
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
import statsmodels.sandbox.stats.multicomp as mc
import multiprocessing as mp
%matplotlib inline
import os
os.environ['OMP_NUM_THREADS'] = str(1)
import warnings
warnings.filterwarnings('ignore')
imp... | <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: 0.0 Basic parameters
Step4: Set up basic functions
Step6: Set up functions for RSA analysis (instead of SVM decoding)
Step7: Run statistics w... |
11,121 | <ASSISTANT_TASK:>
Python Code:
items = ['banana', 'apple', 'carrot']
stock = [2, 3, 4]
def get_stock(item_name, items, stock):
item_index = items.index(item_name)
how_many = stock[item_index]
return how_many
print(get_stock('apple', items, stock))
items = [('banana', 2), ('apple', 3), ('carrot', 4)]
def... | <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: <p style="text-align
Step2: <p style="text-align
Step3: <p style="text-align
Step4: <p style="text-align
Step5: <p style="text-align
Step6: ... |
11,122 | <ASSISTANT_TASK:>
Python Code:
name = input('请输入你的姓名')
print('你好',name)
print('请输入出生的月份与日期')
month = int(input('月份：'))
date = int(input('日期：'))
if month == 4:
if date < 20:
print(name, '你是白羊座')
else:
print(name,'你是非常有性格的金牛座')
if month == 5:
if date < 21:
print(name, '你是非常有性格... | <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: 练习 2：写程序，可由键盘读入两个整数m与n(n不等于0)，询问用户意图，如果要求和则计算从m到n的和输出，如果要乘积则计算从m到n的积并输出，如果要求余数则计算m除以n的余数的值并输出，否则则计算m整除n的值并输出。
Step2: 练习 3：写程序，能够根据北京雾霾PM2.5数值给出... |
11,123 | <ASSISTANT_TASK:>
Python Code:
import SimpleITK as sitk
from downloaddata import fetch_data, fetch_data_all
print(sitk.Version())
from __future__ import print_function
import importlib
from distutils.version import LooseVersion
required_packages = {'IPython' : '4.0.0',
'numpy' : '1.9.2',
... | <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 following cell checks that all expected packages and correct versions are installed. SimpleITK may possibly work with other versions of thes... |
11,124 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
lenses_data = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/lenses/lenses.data', sep='\s+', header=None
)
lenses_data.columns= ['index', 'age', 'spec_type', 'astigmatic', 'tear_prod_rate', 'lens_type... | <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: Attribute Information
Step2: Calculating Mututal Information Score Directly
Step3: Mutual Information is defined by
Step4: Next step is to ca... |
11,125 | <ASSISTANT_TASK:>
Python Code:
from scipy.special import legendre
q = 20
n_steps = 100000
t = np.linspace(0, 1, n_steps)
P = np.asarray([legendre(i)(2*t - 1) for i in range(q)]).T
total = np.zeros((q,q))
for Pt in P:
Ct = np.outer(Pt, Pt)
total += Ct / n_steps
plt.figure(figsize=(12,6))
plt.subplot(1, 2, 1... | <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: That seems to indicate this identity
Step2: Hmm... now that is a very interesting structure. I'm even more convinced that there's a nice comp... |
11,126 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from numpy.linalg import eigvalsh
from collections import namedtuple
import TB
TB.band(TB.Si)
TB.band(TB.GaAs)
TB.band(TB.Ge)
def SiGe_band(x=0.2):
Si_data = TB.bandpts(TB.Si)
Ge_data = TB.bandpts(TB.Ge)
da... | <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: Interpolated SiGe band structure
Step2: Plotting misc parts of Brillouin zones
|
11,127 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import flopy
reload(flopy)
from flopy.modflow import *
from flopy.mt3d import *
nlay, nrow, ncol = 3, 10, 10
ml = Modflow("test")
dis = ModflowDis(ml,nlay=nlay, nrow=nrow, ncol=ncol)
mt = Mt3dms(modflowmodel=ml)
btn = Mt3dBtn(mt, sconc=1.0,ncomp=2)
mt = Mt3dms(modflow... | <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: for btn, sconc is passed as a normal util_3d-compatible argument, no need for the list anymore
Step2: or we pass in the sconc2 kwarg explicitly... |
11,128 | <ASSISTANT_TASK:>
Python Code:
# Authors: Jona Sassenhagen <jona.sassenhagen@gmail.com>
#
# License: BSD-3-Clause
import mne
from mne.event import define_target_events
from mne.channels import make_1020_channel_selections
print(__doc__)
data_path = mne.datasets.testing.data_path()
fname = data_path / 'EEGLAB' / 'test_... | <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 EEGLAB example data (a small EEG dataset)
Step2: Create Epochs
Step3: Plot using
Step4: Plot using median
|
11,129 | <ASSISTANT_TASK:>
Python Code:
# General syntax to import specific functions in a library:
##from (library) import (specific library function)
from pandas import DataFrame, read_csv
# General syntax to import a library but no functions:
##import (library) as (give the library a nickname/alias)
import matplotlib.pyplo... | <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 Data
Step2: To merge these two lists together we will use the zip function.
Step3: We are basically done creating the data set. We now ... |
11,130 | <ASSISTANT_TASK:>
Python Code:
import LangByWord as lbw
import BuildTrainingDataFiles as btdf
# Set the input directory for preprocessing here:
base_input_dir = '/Users/frank/data/LanguageDetectionModel/txt'
# Set the output directory for the preprocessing here:
base_output_dir = '/Users/frank/data/LanguageDetectionMo... | <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: Preprocess the database
Step2: Begin preprocessing the language data
Step3: Train the language detection model and save as an object.
Step4: ... |
11,131 | <ASSISTANT_TASK:>
Python Code:
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install empiricaldist
# Get utils.py
from os.path import basename, exists
def download(url):
filename = basename(url)
... | <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: Whenever people compare Bayesian inference with conventional approaches, one of the questions that comes up most often is something like, "What ... |
11,132 | <ASSISTANT_TASK:>
Python Code:
import graph_tool.all as gt
import pandas as pd
import numpy as np
from IPython.display import display
%matplotlib inline
print("graph-tool version: {}".format(gt.__version__.split(' ')[0]))
with pd.option_context('display.max_colwidth', -1):
display(pd.DataFrame.from_records(gt.coll... | <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: Show datasets in collection
Step2: Another graph example
Step3: Social graph drawing 101
Step4: Create a graph using Python iterations
Step5:... |
11,133 | <ASSISTANT_TASK:>
Python Code:
import magpy as mp
single_particle = mp.Model(
radius = [12e-9],
anisotropy = [4e4],
anisotropy_axis = [[0., 0., 1.]],
magnetisation_direction = [[1., 0., 0.]],
location = [[0., 0., 0.]],
damping = 0.1,
temperature = 300.,
magnetisation = 400e3
)
results ... | <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: To create our model, we need to specify the geometry and material properties of the system. The units and purpose of each property is defined be... |
11,134 | <ASSISTANT_TASK:>
Python Code:
num = float(input())
if num >= 5.50:
print("Excellent!")
grade = float(input())
if grade >= 5.50:
print("Excellent!")
else:
print("Not excellent.")
num = int(input())
if num % 2 == 0:
print("even")
else:
print("odd")
num = int(input())
if num == 0:
print("zero")... | <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: <h2>02.Excellent or Not</h2>
Step2: <h1>03.Even or Odd</h1>
Step3: <h2>04.Greater Number</h2>
Step4: <h2>06.Bonus Score</h2>
Step5: <h2>07.S... |
11,135 | <ASSISTANT_TASK:>
Python Code:
import libsbml
import pandas as pd
import re
!curl -o BMID000000140222.xml http://www.ebi.ac.uk/biomodels-main/download?mid=BMID000000140222
document = libsbml.readSBML('BMID000000140222.xml')
model = document.getModel()
bigg = re.compile(r'BIGG:.*</p>')
brenda = re.compile(r'BRENDA:.*... | <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: Retrieving the whole-genome metabolic model from path2models
Step2: reading path2models SBML
Step3: construct regex patterns
Step4: create pa... |
11,136 | <ASSISTANT_TASK:>
Python Code:
dimensions = 10
input_scale = 1
n_neurons_per_dim = 50
intercept_low = -0.5
intercept_high = 1.0
tau_input = 0.01
tau_recurrent = 0.1
tau_reset = 0.2
max_rate_high = 200
max_rate_low = 150
sensory_delay = 0.05
reset_scale = 0.3
model = nengo.Network()
with model:
vocab = spa.Vocabular... | <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: Here is the plot of the average firing rate across all the neurons
Step2: But that's across all the neurons. In the empirical data we're compa... |
11,137 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pylab as plt
!cd ../devops/geoserver && vagrant status
from IPython.core.display import display, HTML
from geonotebook.config import Config
geoserver = Config().vis_server
display(HTML(geoserver.c.get("/about/status").text))
!curl -o /tmp/L57.G... | <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: Make sure you have the geoserver VM running
Step2: Display geoserver status
Step3: Get the data from S3
Step4: Adding an RGB layer to the map... |
11,138 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%pylab inline
#use a nicer plotting style
plt.style.use(u'seaborn-notebook')
print(plt.style.available)
data = pd.read_csv('./data/assembly.dat',delimiter='\t',skiprows=11,names=['s','usec','ax','ay','az','gx','gy','g... | <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: Motion Data
Step2: for more details on plotting options see also
Step3: try it with the gyroscope data ... what's the difference?
Step4: Feat... |
11,139 | <ASSISTANT_TASK:>
Python Code:
import seisobs
sfile_directory = 'TEST_'
cat = seisobs.seis2cat(sfile_directory)
cat
spec1 = seisobs.specs.specs['1']
print ('colspecs\n')
print (spec1.colspec)
print ('\n')
print ('colnames\n')
print (spec1.colname)
print('\n')
print ('colformat\n')
print (spec1.colformat)
example_lin... | <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 should have taken about 20 seconds to read in 50 files. A bit slow so hopefully you don't have to read thousands of s-files very often.
Ste... |
11,140 | <ASSISTANT_TASK:>
Python Code:
from sklearn.datasets import load_iris
from sklearn.neighbors import KNeighborsClassifier
iris = load_iris()
X, y = iris.data, iris.target
classifier = KNeighborsClassifier()
y
import numpy as np
rng = np.random.RandomState(0)
permutation = rng.permutation(len(X))
X, y = X[permutation],... | <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 labels in iris are sorted, which means that if we split the data as illustrated above, the first fold will only have the label 0 in it, whil... |
11,141 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import seaborn as sns
%matplotlib inline
posts_df = pd.DataFrame.from_csv("reddit_posts_the_donald_201604.csv")
posts_df[0:5]
posts_df['created'] = pd.to_datetime(posts_df.created_utc, unit='s')
posts_df['created_date'] = posts_df.created.dt.date
posts_df['downs'] = po... | <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: Visualizations
Step2: Daily average of number of upvotes per post
|
11,142 | <ASSISTANT_TASK:>
Python Code:
import pymongo
db = pymongo.MongoClient().tweets_db
coll = db.emotweets
coll
coll.count()
query = {'coordinates': {'$ne': None}}
coll.find(query).count()
query = {'hashtags': {'$in': ['happy']}}
coll.find(query).count()
coll.find_one()
%matplotlib inline
import pymongo # in case we... | <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: Next we establish a link with the database. We know that the database created by tweetharvester is called tweets_db and within it is a collectio... |
11,143 | <ASSISTANT_TASK:>
Python Code:
#Import modules
import sys, os
import pandas as pd
from openpyxl import load_workbook
#Set the location of the data directory
dataDir = '../../Data'
#Get the water balance input csv file
inDataFN = dataDir + os.sep + 'StateData' + os.sep + 'la_2010.csv'
#Get the template
inXlsxFN = dataD... | <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/Set the filenames required
Step2: Below we set the field to column mappings. The number on the right of the '=' refers to the column in the... |
11,144 | <ASSISTANT_TASK:>
Python Code:
import vector2d
u = vector2d.Vector(1,2)
u
INVENTORY_TEXT =
apple, 0.60
banana, 0.20
grapefruit, 0.75
grapes, 1.99
kiwi, 0.50
lemon, 0.20
lime, 0.25
mango, 1.50
papaya, 2.95
pineapple, 3.50
blueberries, 1.99
blackberries, 2.50
peach, 0.50
plum, 0.33
clementine, 0.25
cantaloupe, 3.25
pea... | <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: This module has a special section, starting with
Step4: Item
Step5: Here are some tests your code should pass
Step6: How do they behave in a ... |
11,145 | <ASSISTANT_TASK:>
Python Code:
import dicom # for reading dicom files
import os # for doing directory operations
import pandas as pd # for some simple data analysis (right now, just to load in the labels data and quickly reference it)
# Change this to wherever you are storing your data:
# IF YOU ARE FOLLOWING ON KAGGL... | <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: At this point, we've got the list of patients by their IDs, and their associated labels stored in a dataframe. Now, we can begin to iterate thro... |
11,146 | <ASSISTANT_TASK:>
Python Code:
import os
workDir = '/home/nick/notebook/SIPSim/dev/bac_genome1210/SSU_genes_per_ng_DNA/'
rnammerDir = os.path.join(workDir + 'rnammer')
genomeDir = '/home/nick/notebook/SIPSim/dev/bac_genome1210/genomes/'
import glob
import pyfasta
import numpy as np
import pandas as pd
from collections... | <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: Init
Step2: Size distribution of bacterial genomes
Step3: Distribution of 16S gene copies per genome
Step4: Fitting distribution
Step5: Dist... |
11,147 | <ASSISTANT_TASK:>
Python Code:
path = Config().data/'rossmann'
train_df = pd.read_pickle(path/'train_clean')
train_df.head().T
n = len(train_df); n
idx = np.random.permutation(range(n))[:2000]
idx.sort()
small_df = train_df.iloc[idx]
small_cont_vars = ['CompetitionDistance', 'Mean_Humidity']
small_cat_vars = ['Store'... | <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: Experimenting with a sample
Step2: Preparing full data set
Step3: Model
Step4: (10th place in the competition was 0.108)
Step5: (10th place ... |
11,148 | <ASSISTANT_TASK:>
Python Code:
a = spot.translate('(a U b) & GFc & GFd', 'BA', 'complete'); a
a.show("v")
a.show(".ast")
f = spot.formula('a U b'); f
spot.translate(f)
f.translate()
f.translate('mon')
f = spot.formula('Ga | Gb | Gc'); f
f.translate('ba', 'small').show('.v')
f.translate('ba', 'det').show('v.')
spo... | <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 call the spot.setup() in the first cells has installed a default style for the graphviz output. If you want to change this style temporaril... |
11,149 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from qiskit_aqua.operator import Operator
num_qubits = 2
temp = np.random.random((2 ** num_qubits, 2 ** num_qubits))
qubitOp = Operator(matrix=temp + temp.T)
temp = np.random.random((2 ** num_qubits, 2 ** num_qubits))
evoOp = Operator(matrix=temp + temp.T)
from qiskit_... | <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 EOH, we would like to evolve some initial state (e.g. the uniform superposition state) with evoOp and do a measurement using qubitOp. Below,... |
11,150 | <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
<END_TASK>
<USER_TASK:>
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... |
11,151 | <ASSISTANT_TASK:>
Python Code:
# Import libraries
import numpy as np
import pandas as pd
from time import time
from sklearn.metrics import f1_score
# Read student data
student_data = pd.read_csv("student-data.csv")
print "Student data read successfully!"
# TODO: Calculate number of students
n_students = len(student_da... | <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: Implementation
Step2: Preparing the Data
Step3: Preprocess Feature Columns
Step4: Implementation
Step5: Training and Evaluating Models
Step6... |
11,152 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import SimpleITK as sitk
# Download data to work on
%run update_path_to_download_script
from downloaddata import fetch_data as fdata
img1 = sitk.ReadImage(fdata("cthead1.png"))
sitk.Show(img1, title="cthead1")
img2 = sitk.ReadImage(fdata... | <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: SimpleITK has a built in Show method which saves the image to disk and launches a user configurable program ( defaults to ImageJ ), to display t... |
11,153 | <ASSISTANT_TASK:>
Python Code:
with open('paris.txt') as f:
lines = f.read().splitlines()
N, M, T, C, S = map(int, lines[0].split())
paris_coords = []
for i in range(1, N + 1):
paris_coords.append(list(map(float, lines[i].split()))) # Read coords
paris = {node: {} for node in range(N)}
... | <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: How many nodes?
Step2: Which means the node 0 leads to the node 1079 with cost 113 and so on.
Step3: Geolocation using geopy
Step5: We need a... |
11,154 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import glob
import os
import numpy as np
import matplotlib.pyplot as plt
import sklearn
import sklearn.ensemble
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import cross_val_score, train_test_split, cross_val_predict, learning_curve
... | <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: Importing the quite heavy DataFrame with the voting fields and the results. We drop a useless column and create a Name field, which will contain... |
11,155 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
np.linspace(0,10,11)
def myFib(a,b):
return a+b
fibLength = 10 #the length we want for our Fibonacci sequence
fibSeq = np.zeros(fibLength) #make a numpy array of 10 zeros
# Let's define the first 2 elements of the Fibonacci sequence
fibSeq[0] = 0
fibSeq[1] = 1
i ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: You can do a lot with the numpy module. Below is an example to jog your memory
Step2: Do you remember the Fibonacci sequence from yesterday's L... |
11,156 | <ASSISTANT_TASK:>
Python Code:
parm_runtime_env_GCP = True
# parm_runtime_env_GCP = False
# Copyright 2016 Google Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# import subprocess
# retcode = subprocess.call(['pip', 'install', '-U', 'google-api-python-client'])
# retcode = subprocess.call(['p... | <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: Using Google Cloud Platform's Machine Learning APIs
Step2: 导入需要用到的一些功能程序库：
Step3: GCP Machine Learning API Key
Step4: 多媒体二进制base64码转换 (Define... |
11,157 | <ASSISTANT_TASK:>
Python Code:
from datetime import datetime
TIMESTAMP = datetime.now().strftime("%Y%m%d%H%M%S")
import os
PROJECT_ID = "" # TODO: your PROJECT_ID here.
os.environ["PROJECT_ID"] = PROJECT_ID
BUCKET_NAME = PROJECT_ID # TODO: replace your BUCKET_NAME, if needed
REGION = "us-central1"
os.environ["BUCKET_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: Run the following cell to create your Cloud Storage bucket if it does not already exist.
Step2: Import libraries
Step3: Download and preproces... |
11,158 | <ASSISTANT_TASK:>
Python Code:
def z_score(x, m, s):
return (x - m) / s
print(z_score(95, 100, 15), z_score(130, 100, 15), z_score(7, 100, 15))
# We should see -0.3333333333333333 2.0 -6.2 or 1/3 deviation below average, 2 above and 6.2 below.
import scipy.stats as st
def p(x, m, s):
z = z_score(x, m, s)
... | <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: I created a function that takes the observation, mean and standard deviation and returns the z-score. Notice it's just a little bit of arithmet... |
11,159 | <ASSISTANT_TASK:>
Python Code:
import pandas
import numpy
import os
import ijson
path = os.chdir('/Users/superuser/Documents/projects/SDRegionalDataLib/age friendly community/acs2015_1yr_B01001/')
ageData = pandas.read_csv('acs2015_1yr_B01001.csv');
ageData.head()
colNames = list(ageData.columns.values)
#show the firs... | <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: <font color = 'blue'> get a list of the column names </font>
Step2: <font color='blue'> function
Step3: codingDF is intended to be used as a l... |
11,160 | <ASSISTANT_TASK:>
Python Code:
class Dataset(torch.utils.data.Dataset):
Class for getting individual Pixel Data element frame items of a DICOM VL Whole Slide Microscocpy Image data set stored on a remote server.
def __init__(self, url: str, study_id: str, series_id: str, instance_id: str):
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step4: Implement a custom pytoch Dataset to load image frames from a remote DICOM VL Whole Slide Microscopy Image instance
Step6: Implement a simple b... |
11,161 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
# Initialize random number generator
np.random.seed(123)
# True parameter values
alpha, sigma = 1, 1
beta = [1, 2.5]
# Size of dataset
size = 100
# Predictor variable
X1 = np.random.randn(size)
X2 = np.random.randn(size) * 0.2
# Simulate ... | <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: Here is what the simulated data look like. We use the pylab module from the plotting library matplotlib.
Step2: Model Specification
Step3: Now... |
11,162 | <ASSISTANT_TASK:>
Python Code:
from biofloat import ArgoData
from os.path import join, expanduser
ad = ArgoData(cache_file = join(expanduser('~'),
'biofloat_fixed_cache_age365_variablesDOXY_ADJUSTED-PSAL_ADJUSTED-TEMP_ADJUSTED.hdf'))
ocdf = ad.get_cache_file_oxy_count_df()
print ocdf.groupby('wmo').sum().sum()
pr... | <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: That's over 10 million measurements from over 42,000 profiles from 301 floats. The load_biofloat_cache.py script examined 559 floats for valid o... |
11,163 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
Image(filename='lda_plate.png')
vocabulary = []
for cdn1 in sim.codons:
for cdn2 in sim.codons:
if cdn1 == cdn2:
continue
vocabulary.append(cdn1+"-"+cdn2)
print 'vocabulary: ', len(vocabulary)
transitions = np.zeros((N,M-1... | <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: Recall that the Dirichlet Process (DP) (Ferguson, 1973) is essentially a distribution over distributions, where each draw from a DP is itself a ... |
11,164 | <ASSISTANT_TASK:>
Python Code:
from biothings_explorer.user_query_dispatcher import FindConnection
from biothings_explorer.hint import Hint
ht = Hint()
# find all potential representations of CML
cml_hint = ht.query("MONDO:0011996")
# select the correct representation of CML
cml = cml_hint['Disease'][0]
cml
# find all ... | <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 you can see above, by default, BTE will query all APIs integrated.
Step2: The Registry class stores all APIs used in BTE.
Step3: check the ... |
11,165 | <ASSISTANT_TASK:>
Python Code:
greeting = 'Hello'
guest = "John"
my_string = 'Hello "John"'
named_greeting = 'Hello, {name}'.format(name=guest)
named_greeting2 = '{}, {}'.format(greeting, guest)
print named_greeting
print named_greeting2
fruit_list = ['apple', 'orange', 'peach', 'mango', 'bananas', 'pineapple']
name_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: data containers
Step2: Indexing starts with zero.
Step3: tuples
Step4: sets
Step5: dictionaries
Step7: Functions
Step8: function is just a... |
11,166 | <ASSISTANT_TASK:>
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 writin... | <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: ビジュアルアテンションを用いた画像キャプショニング
Step2: MS-COCO データセットのダウンロードと準備
Step3: オプション
Step4: InceptionV3 を使った画像の前処理
Step5: InceptionV3 を初期化し Imagenet で学習済み... |
11,167 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import matplotlib.pyplot as plt
import torch
from torch import nn
from torch import optim
import torch.nn.functional as F
from torchvision import datasets, transforms, models
data_dir = 'Cat_Dog_data'
# TODO: Define transf... | <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: Most of the pretrained models require the input to be 224x224 images. Also, we'll need to match the normalization used when the models were trai... |
11,168 | <ASSISTANT_TASK:>
Python Code:
help(abs)
import numpy as np
help(np)
!echo this is output from the echo command from the Linux shell
!python --version
!python -c 'print("foo"); print("bar")'
!python -c 'print("foo"); print("bar")' | wc -l
!python -c 'import numpy as np; help(np)' | wc -l
!python -c 'import numpy a... | <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 have to import the numpy module in order to get help on any of its functions which we attempt below. But if we ask for help on all of np (num... |
11,169 | <ASSISTANT_TASK:>
Python Code:
import openpyxl
# Import OS module to navigate directories
import os
# Change the directory to the excel file location, using relative and absolute paths as previously discussed.
os.chdir('files')
os.listdir()
workbook = openpyxl.load_workbook('example.xlsx')
type(workbook)
sheet = wor... | <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 must first nagivate to the directory containing the spreadsheets, which for this notebook is the subdirectory 'files'.
Step2: We must now op... |
11,170 | <ASSISTANT_TASK:>
Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import functions from the modsim.py module
from modsim import *
m = UNITS... | <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: Bungee jumping
Step3: Now here's a version of make_system that takes a Params object as a parameter.
Step4: Let's make a System
Step6: spring... |
11,171 | <ASSISTANT_TASK:>
Python Code:
# matplotlib und numpy importieren
%pylab nbagg
# Arbeiten mit Daten
import pandas as pd
# Zum Fitten
import lmfit
# Fehlerrechnung
import uncertainties as uct
from uncertainties.umath import *
def residual(userfcn):
Gibt für eine Modellfunktion die entsprechende Residuenfunkt... | <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: Die Fitroutine minimiert das $\chi^2$, welches aus den Quadraten der Residuen (=Abweichung der Modellvorhersage von den Messwerten) berechnet wi... |
11,172 | <ASSISTANT_TASK:>
Python Code:
naturalness = 'naturalness'
naturalness_value_field = 'value'
n_types = 7
sample_points = 'sample_points_field'
radius = 500
use_viewshed = False
def getViewshedSuffix():
if use_viewshed:
viewshed_suffix = '_viewshed'
else:
viewshed_suffix = ''
return viewshed... | <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 viewshed suffix (for filenames)
Step2: Import statements
Step3: GRASS import statements
Step4: Function declarations
Step5: extract poin... |
11,173 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
# DataFrame cariñosamente df
df = pd.read_csv('cs_DGII_Nomina_2016.csv',sep=';', encoding="ISO-8859-1") # encoding???
df.head()
df.tail(10)
df.shape
df.info()
df.isnull().any()
df.columns
df.Mes.head()
df.columns = [x.strip().lower() for x in df.columns.values... | <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: Cargamos el archivo a un DataFrame en memoria
Step2: Demos un vistazo a los primeros 5 registros
Step3: y a los ultimos 10
Step4: Que tamaño ... |
11,174 | <ASSISTANT_TASK:>
Python Code:
with open('./apps/server_app.py', 'r') as f:
print(f.read())
# Exercise: Modify the app to display the pickup locations and add a tilesource, then run the app with bokeh serve
# Tip: Refer to the previous notebook
import holoviews as hv
import geoviews as gv
import dask.dataframe as... | <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: Of the three parts of this app, part 2 should be very familiar by now -- load some taxi dropoff locations, declare a Points object, datashade th... |
11,175 | <ASSISTANT_TASK:>
Python Code:
from nltk.tag import StanfordNERTagger
from nltk.tokenize import word_tokenize
# Adapt those lines to your installation
jar_location = '/Users/sech/stanford-ner-2018-10-16/stanford-ner.jar'
model_location_3classes = '/Users/sech/stanford-ner-2018-10-16/classifiers/english.all.3class.dists... | <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: Let's take a paragraph from the Wikipedia page of Ada Lovelace as an example. We need to put the text in triple quotes since the text itself con... |
11,176 | <ASSISTANT_TASK:>
Python Code:
# These are the libraries will be used for this lab.
import numpy as np
import matplotlib.pyplot as plt
import torch
import pandas as pd
# Convert 2D List to 2D Tensor
twoD_list = [[11, 12, 13], [21, 22, 23], [31, 32, 33]]
twoD_tensor = torch.tensor(twoD_list)
print("The New 2D Tensor: ... | <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: <!--Empty Space for separating topics-->
Step2: Bravo! The method <code>torch.tensor()</code> works perfectly.Now, let us try other functions w... |
11,177 | <ASSISTANT_TASK:>
Python Code:
# reload modules
# Reload all modules (except those excluded by %aimport) every time before executing the Python code typed.
%load_ext autoreload
%autoreload 2
# import libraries
import logging
import os
import sys
import gc
import pandas as pd
import numpy as np
import random
import sta... | <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: 1.1. Initialise General Settings
Step2: Common variables
Step3: <br/><br/>
Step4: <br/><br/>
Step5: 2.3. Load Features Names
Step6: 2.4. L... |
11,178 | <ASSISTANT_TASK:>
Python Code:
__author__ = "kyubyong. kbpark.linguist@gmail.com"
import numpy as np
np.__version__
x = np.arange(4).reshape((2, 2))
print("x=\n", x)
x = np.arange(4).reshape((2, 2))
print("x=\n", x)
x = np.arange(10).reshape((2, 5))
print("x=\n", x)
x = np.arange(1, 11).reshape((2, 5))
print("x=\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: Order statistics
Step2: Q2. Return the maximum value of x along the second axis. Reduce the second axis to the dimension with size one.
Step3: ... |
11,179 | <ASSISTANT_TASK:>
Python Code:
sset0 = storage.samplesets[0]
numeric_labels = { s.ensemble : s.replica for s in sset0}
string_labels = { s.ensemble : str(s.replica) for s in sset0 }
numeric_to_string = { numeric_labels[e] : string_labels[e] for e in numeric_labels.keys()}
%%time
trace_1 = paths.trace_ensembles_for_rep... | <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: Trace of ensemble visited by a replica
Step2: Replica flow
Step3: Trips
Step4: Transition matrix
Step5: If you would like to set a different... |
11,180 | <ASSISTANT_TASK:>
Python Code:
from __future__ import unicode_literals # If Python 2
import spacy.en
from spacy.tokens import Token
from spacy.parts_of_speech import ADV
nlp = spacy.en.English()
# Find log probability of Nth most frequent word
probs = [lex.prob for lex in nlp.vocab]
probs.sort()
words = [w for w in nlp... | <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: spaCy tokenizes words, then treats each token as a Token object. Each token has an integer and string representation. Each token also has things... |
11,181 | <ASSISTANT_TASK:>
Python Code:
!pip install --user statsmodels
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime
%config InlineBackend.figure_format = 'retina'
df = pd.read_csv('gs://cloud-training/ai4f/AAPL10Y.csv')
df['date'] = pd.to_datetime(df['date'])
df.sor... | <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: Import data from Google Clod Storage
Step2: Prepare data for ARIMA
Step3: Let's create a column for weekly returns. Take the log to of the ret... |
11,182 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
import graphlab
products = graphlab.SFrame('amazon_baby_subset.gl/')
import json
with open('important_words.json', 'r') as f:
important_words = json.load(f)
important_words = [str(s) for s in important_words]
# Remote punctuation
def remove_punctuati... | <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: Load and process review dataset
Step2: Just like we did previously, we will work with a hand-curated list of important words extracted from the... |
11,183 | <ASSISTANT_TASK:>
Python Code:
a = 10
b = 22
print("a =", a, ", b =", b)
print("~~~~~~~~~~~~~~~~~")
print("a + b:\t", a + b)
print("a - b:\t", a - b)
print("a * b:\t", a * b)
print("a / b:\t", a / b)
print("a//b:\t", a//b)
print("a % b:\t", a % b)
print("-a:\t", -a)
print("a < b:\t", a < b)
print("a > b:\t", a > b)
pri... | <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: Numeric Vs String
Step2: As shown above only "*" multiplication is possible between string & real numeric value
Step3: Complex Vs Numeric
Step... |
11,184 | <ASSISTANT_TASK:>
Python Code:
import diplib as dip
a = dip.Image((10,20), 1)
a.Fill(3)
b = a[0:4, 4:-1]
b.Fill(55)
a[:3, :10] = 100
a[5:7, 10:15] = 200
a.Show('normal')
m = a >= 100
m.Show()
a[m].Show('normal')
a[m] = 176
a.Show('normal')
import numpy as np
b = np.random.rand(a.Size(1), a.Size(0))
dip.Show(b)
... | <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 image object
Step2: Indexing into an Image object works as it does for other array types in
Step3: Images can be displayed using the Show ... |
11,185 | <ASSISTANT_TASK:>
Python Code:
!gsutil cp gs://ml-design-patterns/audio_train/00353774.wav cello.wav
!gsutil cp gs://ml-design-patterns/audio_train/001ca53d.wav sax.wav
import matplotlib.pyplot as plt
from scipy import signal
from scipy.io import wavfile
import numpy as np
fig, ax = plt.subplots(2, 2, figsize=(15, 10))... | <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: Vision ML on video
Step3: Text
|
11,186 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import display
from datetime import datetime
from matplotlib import pyplot as plt
from scipy import misc
import h5py
import json
import numpy as np
import os
import pandas as pd
import sys
# local
sys.path.insert(0, os.path.dirname(os.getcwd()))
from pywim.utils.dsp.... | <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: 1.2.1 Start up
Step2: 1.2.2 Creating the file
Step3: 1.2.3 Reading the file
|
11,187 | <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, sof... | <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: Support Vector Machines
Step2: You can see in the data description above that the range of values for each of the columns is quite a bit differ... |
11,188 | <ASSISTANT_TASK:>
Python Code:
def stupid_generator(end):
i = 0
while i < end:
yield i
i+=1
stupid_generator(3)
def stupid_list(end):
i = 0
result = []
while i < end:
result.append(i)
i+=1
return result
stupid_list(3)
it = stupid_generator(3)
it.next()
list(stup... | <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: Le but de la fonction stupid_generator est de lister les entiers inférieurs à end. Cependant, elle ne retourne pas directement la liste mais un ... |
11,189 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
%matplotlib inline
import openpathsampling as paths
import numpy as np
import matplotlib.pyplot as plt
from tqdm.auto import tqdm
import os
import openpathsampling.visualize as ops_vis
from IPython.display import SVG
%%time
flexible = paths.Storage("a... | <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: Note that the accepted trials with recrossing does not account for how long the trial remained active. It also doesn't tell us whether the trial... |
11,190 | <ASSISTANT_TASK:>
Python Code:
def change_base(x: int, base: int):
ret = ""
while x > 0:
ret = str(x % base) + ret
x //= base
return ret
<END_TASK> | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
11,191 | <ASSISTANT_TASK:>
Python Code:
from iuvs import io
%autocall 1
files = !ls ~/data/iuvs/level1b/*.gz
files
l1b = io.L1BReader(files[1])
l1b.darks_interpolated.shape
dark0 = l1b.detector_dark[0]
dark1 = l1b.detector_dark[1]
dark2 = l1b.detector_dark[2]
io.image_stats(dark0)
io.image_stats(dark1)
io.image_stats(dark2)
... | <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 darks_interpolated data-cube consists of the interpolated darks that have been subtracted from the raw image cube for this observation. They... |
11,192 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD-3-Clause
import matplotlib.pyplot as plt
import mne
from mne import io
from mne.stats import permutation_cluster_test
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
raw_fname = dat... | <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: Set parameters
Step2: Read epochs for the channel of interest
Step3: Compute statistic
Step4: Plot
|
11,193 | <ASSISTANT_TASK:>
Python Code:
filename = "../data/example_file.txt"
fp = open(filename, "w")
for string in ["Hello", "Hey", "moi"]:
fp.write(string + "\n")
fp.close()
fp = open(filename, "r")
for line in fp:
print(line.strip()) # the \n is contained in the line, calling strip removes whitespace at the end and ... | <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: Context handlers
Step2: File i/o packages in stdlib
Step3: The implementation technical details like the "rt" vs "r" mode vary a bit, check do... |
11,194 | <ASSISTANT_TASK:>
Python Code:
%load_ext rpy2.ipython
%%R
physeqDir = '/var/seq_data/fullCyc/MiSeq_16SrRNA/515f-806r/lib1-7/phyloseq/'
physeq_bulk_core = 'bulk-core'
physeq_SIP_core = 'SIP-core_unk'
%%R
library(dplyr)
library(tidyr)
library(ggplot2)
library(phyloseq)
%%R
F = file.path(physeqDir, physeq_SIP_core)
phys... | <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: Init
Step2: Mapping bulk and SIP data
Step3: Pre-fraction dataset
|
11,195 | <ASSISTANT_TASK:>
Python Code:
import gym
import tensorflow as tf
import numpy as np
# Create the Cart-Pole game environment
env = gym.make('CartPole-v0')
env.reset()
rewards = []
actions = [np.random.choice(2) for _ in range(100)]
for _ in range(1000):
env.render()
state, reward, done, info = env.step(env.ac... | <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: Note
Step2: We interact with the simulation through env. To show the simulation running, you can use env.render() to render one frame. Passing ... |
11,196 | <ASSISTANT_TASK:>
Python Code:
class Sarsa_Agent:
def __init__(self, environment, n0, mlambda):
self.n0 = float(n0)
self.env = environment
self.mlambda = mlambda
# N(s) is the number of times that state s has been visited
# N(s,a) is the number of times that action a... | <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: Plot the mean- squared error against λ.
Step2: For λ = 0 and λ = 1 only, plot the learning curve of mean-squared error against episode number.
... |
11,197 | <ASSISTANT_TASK:>
Python Code:
from numpy import random, array
#Create fake income/age clusters for N people in k clusters
def createClusteredData(N, k):
random.seed(10)
pointsPerCluster = float(N)/k
X = []
for i in range (k):
incomeCentroid = random.uniform(20000.0, 200000.0)
ageCentroi... | <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'll use k-means to rediscover these clusters in unsupervised learning
|
11,198 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import xgboost as xgb
from sklearn.metrics import roc_curve, auc
from sklearn.metrics import precision_recall_curve
df = pd.read_csv("iris.csv")
def rotMat3D(a,r):
Return the matrix that rota... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step3: Rotations
Step5: PCA
Step8: FastFourier Transformation
Step9: Save python object with pickle
Step10: Progress Bar
Step11: Check separations... |
11,199 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
from datetime import date
from matplotlib import pyplot as plt
# Load marineHeatWaves definition module
import marineHeatWaves as mhw
sst = np.loadtxt('data/sst_WA.csv', delimiter=',')
# Generate time vector using datetime format (January 1 of year 1... | <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. Load daily SST data
Step2: 3. Detect Marine Heatwave
Step3: 3.2 Check properties of MHWs
Step4: Maximum intensities (in $^∘$C) of the fir... |
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