Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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3,400 | <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: Environments
Step9: Python Environments
Step10: In addition to the step() method, environments also provide a reset() method that starts a new... |
3,401 | <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 Model Garden
Step2: Import TensorFlow, TensorFlow Datasets, and a few helper libraries.
Step3: The tensorflow_models... |
3,402 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import pastas as ps
import matplotlib.pyplot as plt
ps.set_log_level("ERROR")
ps.show_versions(numba=True, lmfit=True)
head = pd.read_csv("data_wagna/head_wagna.csv", index_col=0, parse_dates=True,
squeeze=True, skiprows=2).loc["... | <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. Read Data and plot autocorrelation
Step2: 2. Run models with AR(1) noise model
Step3: 3. Run models with ARMA(1,1) noise model
Step4: 4. P... |
3,403 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
x = 5
y = 10
z = x + y
print (z) # affiche z
x = 2
y = x + 1
print (y)
x += 5
print (x)
a = 0
for i in range (0, 10) :
a = a + i # répète dix fois cette ligne
print (a)
a = 10
if a > 0 :
print(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: Partie 1
Step2: On programme sert souvent à automatiser un calcul comme le calcul mensuel du taux de chômage, le taux d'inflation, le temps qu'... |
3,404 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import keras
import keras.backend as K
from keras.layers import Conv2D
from keras.models import Sequential
%matplotlib inline
inputs = np.random.randint(1, 9, size=(4, 4))
inputs
def show_matrix(m, color, cmap, title=None):
rows, co... | <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: Convolution Operation
Step2: The matrix is visualized as below. The higher the intensity the bright the cell color is.
Step3: We are using sm... |
3,405 | <ASSISTANT_TASK:>
Python Code:
def hello_world():
print('hello world')
# wrap hello world in a function that does logging
def wrap_hello():
print('Enter: hello_world')
hello_world()
print('Exit: hello_world')
wrap_hello()
# to wrap any function at all, write a generic wrapper that takes the 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: 2. Advanced Decorators
Step2: 3. Metaclasses
|
3,406 | <ASSISTANT_TASK:>
Python Code:
!rm -rf /tmp/ImageNetTrainTransfer
#Import
import pandas as pd
import numpy as np
import os
import tensorflow as tf
import random
from PIL import Image
#Inception preprocessing code from https://github.com/tensorflow/models/blob/master/slim/preprocessing/inception_preprocessing.py
#useful... | <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: Lettura file words di ImageNet
Step2: Aggiunta colonna di lunghezza del label (quante classi contiene ogni label).
Step3: Train DF
Step4: Pul... |
3,407 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
pylab.rcParams['figure.figsize'] = (6, 6)
import datajoint as dj
from pipeline.preprocess import *
(dj.ERD.from_sequence([Prepare, Sync, ExtractRaw, Spikes])-1).draw()
dj.ERD(Prepare).add_parts().draw()
dj.ERD(ExtractRaw).add_parts().draw()
Prepare.GalvoAverageFrame().h... | <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: The preprocess schema extracts, aligns, and synchronizes multiphoton trace data from both galvo and AOD systems.
Step2: Here are the main eleme... |
3,408 | <ASSISTANT_TASK:>
Python Code:
raw_dataset = pd.read_csv(source_path + "Speed_Dating_Data.csv")
raw_dataset.head(3)
raw_dataset_copy = raw_dataset
#merged_datasets = raw_dataset.merge(raw_dataset_copy, left_on="pid", right_on="iid")
#merged_datasets[["iid_x","gender_x","pid_y","gender_y"]].head(5)
#same_gender = merge... | <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: Data exploration
Step3: Data processing
Step4: Feature engineering
Step5: Modelling
Step6: Variables selection
Step7: Decision Tree
Step8: ... |
3,409 | <ASSISTANT_TASK:>
Python Code:
%load_ext sql
%sql mysql://studentuser:studentpw@mysqlserver/dognitiondb
%sql USE dognitiondb
%config SqlMagic.displaylimit=25
%%sql
SELECT ct.created_at, DAYOFWEEK(ct.created_at)
FROM complete_tests ct
LIMIT 49, 200
%%sql
SELECT ct.created_at, DAYOFWEEK(ct.created_at),
CASE DAYOFWE... | <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: <img src="https
Step2: Of course, the results of the query in Question 1 would be much easier to interpret if the output included the name of t... |
3,410 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
class Halley:
def __init__(self, a):
self.f = lambda x: a[0] + a[1] * x + a[2] * tf.pow(x, 2) + a[3] * tf.pow(x, 3) + a[4] * tf.pow(x, 4)
self.df = lambda x: tf.gradients(self.f(x), x)[0] # TensorFlow does automatic differentiation!
... | <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: Iterate 3 times
Step2: Iterate until condition
|
3,411 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import pyther as pt
def main_eos():
print("-" * 79)
components = ["METHANE"]
MODEL = "PR"
specification = "constants"
component_eos = pt.parameters_eos_constans(components, MOD... | <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: Luego de hacer la importación de las librerías que se van a utilizar, en la función main_eos() definida por un usuario se realiza la especificac... |
3,412 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.array([1, 2, 3])
print(a)
print('')
b = np.array([(1, 2, 3), (4, 5, 6)])
print(b)
a + b
a * b
b - a
a**2
10*np.sin(a) # seno trigonométrico
b<35
print('Axis 1: %s' % b[0])
print(np.average(b))
print(b.sum())
print(b.min())
print(b.max())
b.sum(axis=0) # sum of ea... | <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: Exercícios
|
3,413 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
file_name_string = 'C:/Users/Charles Kelly/Desktop/Exercise Files/02_07/Final/EmployeesWithGrades.xlsx'
employees_df = pd.read_excel(file_name_string, 'Sheet1', index_col=None, na_values=['NA'])
employees_df
employees_df["Grade"] = employees_df["Gra... | <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: Change data type
Step2: Rename the categories
Step3: Values in data frame have not changed
Step4: tabulate Department, Name, and YearsOfServi... |
3,414 | <ASSISTANT_TASK:>
Python Code:
from crpropa import *
## settings for MHD model (must be set according to model)
filename_bfield = "clues_primordial.dat" ## filename of the magnetic field
gridOrigin = Vector3d(0,0,0) ## origin of the 3D data, preferably at boxOrigin
gridSize = 1024 #... | <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: to make use of periodicity of the provided data grid, use
Step2: to not follow particles forever, use
Step3: Uniform injection
Step4: Injecti... |
3,415 | <ASSISTANT_TASK:>
Python Code:
import numpy as np # 数値計算を行うライブラリ
import scipy as sp # 科学計算ライブラリ
from scipy import stats # 統計計算ライブラリ
significance = 0.05
o = [17, 10, 6, 7, 15, 5] # 実測値
e = [10, 10, 10, 10, 10, 10] # 理論値
chi2, p = stats.chisquare(o, f_exp = e)
print('chi2 値は %(chi2)s' %locals())
print('確率は %(p)s' %local... | <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 STYLE="background
Step2: <h4 style="padding
Step3: <h2 STYLE="background
Step4: <h4 style="padding
Step5: <h4 style="border-bottom
Step6... |
3,416 | <ASSISTANT_TASK:>
Python Code:
# ! pip install -u gremlinpython graphistry
# ! pip install -u pandas
# see https://rapids.ai/ if trying GPU dataframes
! pip show gremlinpython graphistry | grep 'Name\|Version'
import graphistry
graphistry.__version__
# To specify Graphistry account & server, use:
# graphistry.registe... | <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: Imports
Step2: Configure
Step3: Connect
Step4: Query & plot
Step5: Customize your visuals & Embed
Step6: Generate URL for other systems
|
3,417 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
a = tf.constant([1,2,3])
b = tf.constant([4,5,6,7])
def g(a,b):
tile_a = tf.tile(tf.expand_dims(a, 1), [1, tf.shape(b)[0]])
tile_a = tf.expand_dims(tile_a, 2)
tile_b = tf.tile(tf.expand_dims(b, 0), [tf.shape(a)[0], 1])
tile_b = tf.expand_dims(tile_b... | <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:
|
3,418 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
# %matplotlib inline
%matplotlib tk
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
os.getcwd()
os.chdir('C:\\Users\\manolis\\Desktop\\PycharmProjects\\IRAS\\IRAS\\ref IR spectra')
os.listdir()
nist = pd.read_csv( 'guaiacol IR_solution... | <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: We determined that the NIST data for Guaiacol (2-methoxyphenol) had 18 values that were zero in the transmittance data and therefore infinity wh... |
3,419 | <ASSISTANT_TASK:>
Python Code:
import os.path as op
import mne
data_path = mne.datasets.sample.data_path()
fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis-ave.fif')
evokeds = mne.read_evokeds(fname, baseline=(None, 0), proj=True)
print(evokeds)
evoked = mne.read_evokeds(fname, condition='Left Auditory', ba... | <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: The
Step2: Notice that the reader function returned a list of evoked instances. This is
Step3: If you're gone through the tutorials of raw an... |
3,420 | <ASSISTANT_TASK:>
Python Code:
from random import choice
from time import sleep
from rv.api import Pattern, Project, m, NOTE, NOTECMD
from sunvox.api import init, Slot
init(None, 44100, 2, 0)
slot = Slot()
project = Project()
inst = project.output << project.new_module(
m.AnalogGenerator,
sustain=False,
r... | <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: Initialize SunVox
Step2: Create a project with an Analog Generator
Step3: Create a tiny 4×4 pattern
Step4: Randomize the notes in the pattern... |
3,421 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact
def char_probs(s):
Find the probabilities of the unique characters in the string s.
Parameters
----------
s : str
A string of characters.
... | <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:
Step2: Character counting and entropy
Step4: The entropy is a quantiative measure of the disorder of a probability distribution. It is used extensivel... |
3,422 | <ASSISTANT_TASK:>
Python Code:
from quantopian.pipeline import Pipeline
from quantopian.research import run_pipeline
from quantopian.pipeline.data.builtin import USEquityPricing
from quantopian.pipeline.factors import SimpleMovingAverage
mean_close_10 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length... | <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: For this example, we need two factors
Step2: Then, let's create a percent difference factor by combining our mean_close_30 factor with our mean... |
3,423 | <ASSISTANT_TASK:>
Python Code:
%%file example.py
from mpi4py.MPI import COMM_WORLD as communicator
import random
# Draw one random integer between 0 and 100
i = random.randint(0, 100)
print('Rank %d' %communicator.rank + ' drew a random integer: %d' %i )
# Gather the results
integer_list = communicator.gather( i, root=... | <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: What happened?
Step2: The code executes faster than the serial example, because each process has a smaller amount of work, and the two processe... |
3,424 | <ASSISTANT_TASK:>
Python Code:
import pandas
df = pandas.read_csv('C:\\Users\\user\\Desktop\\TRABALHO-4.csv', sep=';')
df
tempo_medio = 1.1558 / 30
print("O tempo médio entre as chegadas à fila é", tempo_medio*60, "minutos.")
taxa_de_chegada = 1 / tempo_medio
print(taxa_de_chegada)
pandas.DataFrame.mean(df['SAIDA-EN... | <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: Respostas
Step2: d) A taxa de chegada de usuários no sistema
Step3: $$\Lambda = 25.956\ clientes/hora$$
Step4: f) A taxa de atendimento dos u... |
3,425 | <ASSISTANT_TASK:>
Python Code:
# Authors: Jeff Hanna <jeff.hanna@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne import io
from mne.datasets import refmeg_noise
from mne.preprocessing import ICA
import numpy as np
print(__doc__)
data_path = refmeg_noise.data_path()
raw_fname = data_path + '/sample_reference... | <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: Read raw data, cropping to 5 minutes to save memory
Step2: Note that even though standard noise removal has already
Step3: The PSD of these da... |
3,426 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from selenium import webdriver
import os,time,json
import pandas as pd
from collections import defaultdict,Counter
import matplotlib.pyplot as plt
url = "http://www.imdb.com/list/ls061683439/"
with open('./filmfare.json',encoding="utf-8") as f:
datatbl = json.load(... | <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: Getting Data
Step2: Store Data in a Python Dictionary
Step3: Data before Clean Up
Step4: Clean Data
Step5: How does data in Dictionary look... |
3,427 | <ASSISTANT_TASK:>
Python Code:
#Compute x = 4 * 3 and print the result
x = 4 * 3
print(x)
#Compute y = 6 * 9 and print the result
y = 6 * 9
print(y)
# Import the Pandas library
import pandas as pd
kaggle_path = "http://s3.amazonaws.com/assets.datacamp.com/course/Kaggle/"
# Load the train and test datasets to create tw... | <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. Get the Data with Pandas
Step2: 3.Understanding your data
Step3: 4. Rose vs Jack, or Female vs Male
Step4: 5.Does age play a role?
Step5: ... |
3,428 | <ASSISTANT_TASK:>
Python Code:
x=1
print x
type(x)
x.conjugate()
type(1+2j)
z=1+2j
print z
(1,2)
t=(1,2,"text")
t
t
def foo():
return (1,2)
x,y=foo()
print x
print y
def swap(x,y):
return (y,x)
x=1;y=2
print "{0:d} {1:d}".format(x,y)
x,y=swap(x,y)
print "{:f} {:f}".format(x,y)
dir(1)
x=[]
x.append("text")
x
x.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: if/else, for, while, pass, break, continue
Step2: List
Step3: Dictionary
Step4: Function
Step5: Module
|
3,429 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import pandas as pd
pd.options.display.max_rows = 999
pd.set_option('display.width', 1000)
import glob
header = ["evaluation_type", "dataset", "kwargs", "evaluation", "value", "num_skipped"]
similarity_dfs = []
similarity_names = []
similarity_glob = ... | <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: Similarity task
Step2: Analogy task
Step3: We then present the results using the threecosadd analogy function.
Step4: Bigger Analogy Test Set... |
3,430 | <ASSISTANT_TASK:>
Python Code:
# import packages
import phylogenetics as phy
import phylogenetics.tools as tools
import phylopandas as ph
import pandas as pd
from phylovega import TreeChart
# intitialize project object and create project folder
project = phy.PhylogeneticsProject(project_dir='tutorial', overwrite=True)... | <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. Inititialize a phylogenetics project
Step2: 2. Read in your starting sequence(s)
Step3: 3. Use BLAST to search for orthologs similar to you... |
3,431 | <ASSISTANT_TASK:>
Python Code:
# remove display of install details
%%capture --no-display
!pip install ipyparallel
import subprocess
subprocess.Popen(['ipcluster', 'start', '-n', '4'])
# authorize Google to access Google drive files
!pip install -U -q PyDrive
from pydrive.auth import GoogleAuth
from pydrive.drive impor... | <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: End of Warning
Step2: Problem 1) Light Curve Data
Step3: As we have many light curve files (in principle as many as 37 billion...), we will de... |
3,432 | <ASSISTANT_TASK:>
Python Code:
# Authors: Remi Flamary <remi.flamary@unice.fr>
# Stanislas Chambon <stan.chambon@gmail.com>
#
# License: MIT License
import numpy as np
import matplotlib.pylab as pl
import ot
n_source_samples = 100
n_target_samples = 100
theta = 2 * np.pi / 20
noise_level = 0.1
Xs, ys = ot.dat... | <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: Generate data
Step2: Plot data
Step3: Instantiate the different transport algorithms and fit them
Step4: Plot transported samples
|
3,433 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
from load_utils import *
d = load_diffs(keep_diff = True)
df_events, df_blocked_user_text = ... | <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: Q
Step2: Model does not assign 0 scores, like the annotators.
Step3: Q
Step4: Q
Step5: Q
|
3,434 | <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
<END_TASK>
<USER_TASK:>
Description:
Step1: 시계열 예측
Step2: 날씨 데이터세트
Step3: 이 튜토리얼은 시간별 예측만 다루므로 10분 간격부터 1시간까지 데이터를 서브 샘플링하는 것으로 시작합니다.
Step4: 데이터를 살펴보겠습니다. 다음은 처음 몇 개의 행입니다.
Step5: 시간이... |
3,435 | <ASSISTANT_TASK:>
Python Code:
class Point():
Holds on a point (x,y) in the plane
def __init__(self, x=0, y=0):
assert isinstance(x, (int, float)) and isinstance(y, (int, float))
self.x = float(x)
self.y = float(y)
p = Point(1,2)
print("point", p.x, p.y)
origin = Point()
print("orig... | <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: Classes
Step2: Notice that when we send a Point to the console we get
Step4: Which is not useful, so we will define how Point is represented i... |
3,436 | <ASSISTANT_TASK:>
Python Code:
!sequana_coverage --download-reference FN433596
! art_illumina -sam -i FN433596.fa -p -l 100 -ss HS20 -f 20 -m 500 -s 40 -o paired_dat -f 100
# no need for the *aln and *sam, let us remove them to save space
!rm -f paired*.aln paired_dat.sam
!sequana_mapping --reference FN433596.fa --fi... | <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: Simulated FastQ data
Step2: Creating the BAM (mapping) and BED files
Step3: This uses bwa and samtools behind the scene. Then, we will convert... |
3,437 | <ASSISTANT_TASK:>
Python Code:
try:
n = int(input("Enter n: "))
if n > 0:
q = 1
elif n == 0:
q = 2
else:
q = 3
except:
q = 4
n = int(input("Enter n: "))
if n > 0:
q = 1
if n >10:
q = 2
if n > 20:
q = 3
else:
q = 4
a = 10
b = "15"
c = 10.5
w = a + c... | <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. 1
Step2: a. 1
Step3: a. 4
Step4: a. 4
Step5: Functions, continued
Step6: dir() and help() built-in functions
Step7: Watch Me Code 1
Ste... |
3,438 | <ASSISTANT_TASK:>
Python Code:
from IPython import display
display.Image('img/simple.jpg', width=400)
import random
import math
import numpy
from string import Template
from deap import base
from deap import creator
from deap import tools
from deap import algorithms
from lily_template import TEMPLATE
# Global Variabl... | <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: Will be rempresented as
Step2: The file lily_template has the template to create the lilypond file and to give it format I used the string.Temp... |
3,439 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import networkx as nx
K_5=nx.complete_graph(5)
nx.draw(K_5)
def complete_deg(n):
Return the integer valued degree matrix D for the complete graph K_n.
D = np.diag([n-1 for i 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: Complete graph Laplacian
Step3: The Laplacian Matrix is a matrix that is extremely important in graph theory and numerical analysis. It is defi... |
3,440 | <ASSISTANT_TASK:>
Python Code:
from coherence import load_coherence_dataset
coherence_ds = load_coherence_dataset()
X = coherence_ds.data
y = coherence_ds.target
from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.25, random_state=1)
from sklearn.... | <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: Train-Test Split
Step2: K-fold Cross Validation and HyperParameter Tuning
Step3: Setting HyperParameters to tune
Step4: Show HyperParameters ... |
3,441 | <ASSISTANT_TASK:>
Python Code:
# import the standard numerical and plotting packages
import matplotlib.pyplot as plt
import numpy as np
from skimage.io import imread
# load the images
a = imread("B005_1.tif")
b = imread("B005_2.tif")
fig, axs = plt.subplots(1, 2, figsize=(9, 4))
axs[0].imshow(a, cmap=plt.cm.gray)
axs[... | <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 have downloaded some sample images from PIV challenge,
Step2: The two images show the positions of the particles at two different times. We... |
3,442 | <ASSISTANT_TASK:>
Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
# Importando um módulo em Python
import math
# Verificando todos os métodos disponíveis no módulo
dir(math)
# Usando um dos métodos do módu... | <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: Módulos e Pacotes
|
3,443 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('..')
import socnet as sn
sn.graph_width = 320
sn.graph_height = 180
g = sn.load_graph('4-dijkstra.gml', has_pos=True)
for n, m in g.edges():
g.edge[n][m]['label'] = g.edge[n][m]['c']
sn.show_graph(g, elab=True)
class Heap(object):
def __init__(self, ... | <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 seguir, vamos configurar as propriedades visuais
Step2: Por fim, vamos carregar e visualizar um grafo
Step3: Algoritmo de Dijkstra
Step4: E... |
3,444 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
from pandas.tools.plotting import scatter_matrix
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
import matplotlib.colors as colors
filename = '../facies_vectors.csv'
training_data = pd.read_csv(filename)
training_data
... | <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 Preparation and Model Selection
Step2: The accuracy function and accuracy_adjacent function are defined in teh following to quatify the pr... |
3,445 | <ASSISTANT_TASK:>
Python Code:
#INPUT
#folder = 'sample' # create this folder and place the exported file
folder = 'all'
#export_filename = 'English_Vocabulary_Sample.csv'
export_filename = 'English_Vocabulary3.csv'
Generate a dictionary from Anki export file.
Note:
Only GRE words have proper Serial No. Rest words have... | <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: CSV export file manipulations
Step5: Copying media files to folders
Step7: Sort the columns
Step13: GRE words only
|
3,446 | <ASSISTANT_TASK:>
Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
# Execute this cell to enable verbose SSH commands
logging.getLogger('ssh').setLevel(logging.DEBUG)
# Other python modules required by this notebook
import json
import os
# Setup a target configuration
conf = {
# Ta... | <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: <br><br><br><br>
Step2: Commands execution on remote target
Step3: Example of frameworks configuration on remote target
Step4: Create a big/L... |
3,447 | <ASSISTANT_TASK:>
Python Code:
fifteen_factorial = 15*14*13*12*11*10*9*8*7*6*5*4*3*2*1
print(fifteen_factorial)
import math
print(math.factorial(15))
print("Result correct?", math.factorial(15) == fifteen_factorial)
print(math.factorial(5), math.sqrt(2*math.pi)*5**(5+0.5)*math.exp(-5))
print(math.factorial(10), math.... | <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: Exercise 2
Step2: Exercise 3
Step4: We see that the relative error decreases, whilst the absolute error grows (significantly).
Step6: In late... |
3,448 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize as opt
a_true = 0.5
b_true = 2.0
c_true = -4.0
def quad(x,a,b,c):
return a*x**2 + b*x + c
N = 30
xdata = np.linspace(-5,5,N)
dy = 2.0
np.random.seed(0)
ydata = quad(xdata,a_true,b_true,c_true... | <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: Fitting a quadratic curve
Step2: First, generate a dataset using this model using these parameters and the following characteristics
Step3: No... |
3,449 | <ASSISTANT_TASK:>
Python Code:
import glob
from IPython.display import Image
import numpy as np
import openmc
# 1.6 enriched fuel
fuel = openmc.Material(name='1.6% Fuel')
fuel.set_density('g/cm3', 10.31341)
fuel.add_nuclide('U235', 3.7503e-4)
fuel.add_nuclide('U238', 2.2625e-2)
fuel.add_nuclide('O16', 4.6007e-2)
# bor... | <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: Generate Input Files
Step2: With our three materials, we can now create a materials file object that can be exported to an actual XML file.
Ste... |
3,450 | <ASSISTANT_TASK:>
Python Code:
PROJECT = 'cloud-training-demos' # Replace with your PROJECT
BUCKET = 'cloud-training-bucket' # Replace with your BUCKET
REGION = 'us-central1' # Choose an available region for Cloud MLE
import os
os.environ['BUCKET'] = BUCKET
os.environ['PROJECT'] = PROJECT
os.environ['REGIO... | <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: Exploring the data
Step2: Define features
Step3: Train a model in BigQuery
Step4: With the demo dataset ready, it is possible to create a lin... |
3,451 | <ASSISTANT_TASK:>
Python Code:
%%bash
export PROJECT=$(gcloud config list project --format "value(core.project)")
echo "Your current GCP Project Name is: "$PROJECT
%%bash
pip install tensorflow==2.6.0 --user
import os
PROJECT = "qwiklabs-gcp-bdc77450c97b4bf6" # REPLACE WITH YOUR PROJECT NAME
REGION = "us-central1" # R... | <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 make sure we install the necessary version of tensorflow. After doing the pip install above, click Restart the kernel on the notebook so t... |
3,452 | <ASSISTANT_TASK:>
Python Code:
bigdf = pandas.read_csv('/media/notconfusing/9d9b45fc-55f7-428c-a228-1c4c4a1b728c/home/maximilianklein/snapshot_data/2016-01-03/gender-index-data-2016-01-03.csv')
gender_qid_df = bigdf[['qid','gender']]
def map_gender(x):
if isinstance(x,float):
return 'no gender'
else:
... | <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: Rel risk. P(gender|misaligned)/P(gender)
|
3,453 | <ASSISTANT_TASK:>
Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
# Exercício 1 - Imprima na tela os números de 1 a 10. Use uma lista para armazenar os números.
# Exercício 2 - Crie uma lista de 5 objetos ... | <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: Exercícios Cap02
|
3,454 | <ASSISTANT_TASK:>
Python Code:
import gensim, logging, os
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
class Corpus(object):
'''Clase Corpus que permite leer de manera secuencial un directorio de documentos de texto'''
def __init__(self, directorio):
... | <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: Entrenamiento de un modelo
Step2: CORPUSDIR contiene una colección de noticias en español (normalizada previamente a minúsculas y sin signos de... |
3,455 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.stats import norm
from clintrials.dosefinding.efftox import EffTox, LpNormCurve, efftox_dtp_detail
from clintrials.dosefinding.efficacytoxicity import dose_transition_pathways, print_dtps
real_doses = [7.5, 15, 30, 45]
trial_size = 30
cohort_size = 3
first_do... | <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 above parameters are explained in the manuscript.
Step2: The EffTox class is an object-oriented implementation of the trial design by Thall... |
3,456 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division
from terminaltables import AsciiTable
import inet
inet.__version__
from inet import DataLoader
mydataset = DataLoader('../../data/PV') # create an object with information of all connections
len(mydataset.experiment)
mydataset.nIN, mydataset.nPC # number o... | <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: <H2>Object creation</H2>
Step2: <H2>Object atttributes</H2>
Step3: Details of every experiments are given in a list
Step4: and details fo the... |
3,457 | <ASSISTANT_TASK:>
Python Code:
from owslib.iso import namespaces
# Append gmi namespace to namespaces dictionary.
namespaces.update({"gmi": "http://www.isotc211.org/2005/gmi"})
namespaces.update({"gml": "http://www.opengis.net/gml/3.2"})
# Select RA
RAs = {
"GLOS": "Great Lakes Observing System",
"SCCOOS": "So... | <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: Now we select a Regional Association
Step2: Next we generate a geoportal query and georss feed
Step3: Time to query the portal and parse out t... |
3,458 | <ASSISTANT_TASK:>
Python Code:
from keras.layers import Conv2D, MaxPooling2D, Input, Dense, Flatten, Activation, add, Lambda
from keras.layers.normalization import BatchNormalization
from keras.layers.pooling import GlobalAveragePooling2D
from keras.optimizers import RMSprop
from keras.backend import tf as ktf
from ker... | <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: Read the MNIST data. Notice that we assume that it's 'kaggle-DigitRecognizer/data/train.csv', and we use helper function to read into a dictiona... |
3,459 | <ASSISTANT_TASK:>
Python Code:
def net_force(mass, acceleration):
return mass * acceleration
# Function as above, but with DOCUMENTATION
def net_force(mass, acceleration):
Calculates f=ma, returns force.
We assume mass, acceleration are of type int/float.
return mass * acceleration
def add(... | <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: I argued that one of the main drawbacks of this code is that "[it] implicitly assumes the user knows to pass in numbers". In this lecture I aim ... |
3,460 | <ASSISTANT_TASK:>
Python Code:
import os
import pandas as pd
import requests
from windpowerlib import ModelChain, WindTurbine, create_power_curve
from windpowerlib import data as wt
import logging
logging.getLogger().setLevel(logging.DEBUG)
def get_weather_data(filename='weather.csv', **kwargs):
r
Imports wea... | <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: You can use the logging package to get logging messages from the windpowerlib. Change the logging level if you want more or less messages.
Step3... |
3,461 | <ASSISTANT_TASK:>
Python Code:
!pip install --upgrade --user pixiedust
!pip install --upgrade --user pixiedust-flightpredict
import pixiedust_flightpredict
pixiedust_flightpredict.configure()
from pyspark.mllib.regression import LabeledPoint
from pyspark.mllib.linalg import Vectors
from numpy import array
import nump... | <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: <h3>If PixieDust was just installed or upgraded, <span style="color
Step2: Train multiple classification models
Step3: Evaluate the models
Ste... |
3,462 | <ASSISTANT_TASK:>
Python Code:
record_f = open("Sample_Data/Swim_Records/record_list.txt")
record = record_f.read().decode('utf-8').split('\n')
record_f.close()
for line in record:
print(line)
from __future__ import print_function
record_f = open("Sample_Data/Swim_Records/record_list.txt", 'r')
record = record_f.r... | <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: 복습
Step2: 이제 위 코드를 수정하여 아래 결과를 얻고자 한다.
Step3: 현재 두 개의 리스트는 기존 테이블의 리스트의 순서와 동일한 순서대로 항목을 갖고 있다.
Step4: 이제 원하는 자료들의 쌍을 입력한다.
Step5: 이제 평택의 정... |
3,463 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
plt.ion()
from astropy import time
from poliastro.twobody.orbit import Orbit
from poliastro.bodies import Earth
from poliastro.plotting import OrbitPlotter
from poliastro.neos import neows
eros = neows.orbit_from_name('Eros')
frame = OrbitPlotter()
frame.p... | <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: NeoWS module
Step2: You can also search by IAU number or SPK-ID (there is a faster neows.orbit_from_spk_id() function in that case, although)
S... |
3,464 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'uhh', 'sandbox-2', 'toplevel')
# 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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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
3,465 | <ASSISTANT_TASK:>
Python Code:
import os
os.chdir('..')
os.getcwd()
!{'dpp'}
!{'dpp run --verbose ./committees/kns_committee'}
KNS_COMMITTEE_DATAPACKAGE_PATH = './data/committees/kns_committee/datapackage.json'
from datapackage import Package
kns_committee_package = Package(KNS_COMMITTEE_DATAPACKAGE_PATH)
kns_commi... | <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: List the available pipelines
Step2: Run a pipeline
Step3: Inspect the output datapackage descriptor
Step4: Each package may contain multiple ... |
3,466 | <ASSISTANT_TASK:>
Python Code:
qubits = []
for i in range(3):
q = qubit.Qubit('Transmon')
q.C_g = 3.87e-15
q.C_q = 75.1e-15
q.C_resToGnd = 79.1e-15
qubits.append(q)
q = qubit.Qubit('OCSQubit')
q.C_g = 2.94e-15
q.C_q = 48.5e-15
q.C_resToGnd = 51.5e-15
qubits.append(q)
cpw = cpwtools.CPW(material='al... | <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: CPW
Step2: $\lambda/4$ readout resonators
Step3: Qubit parameters
Step4: Feedline with and without crossovers
Step5: Inductive Coupling
Step... |
3,467 | <ASSISTANT_TASK:>
Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
# License: BSD-3-Clause
from functools import partial
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # noqa, analysis:ignore
import mne
from mne.stats import (ttest_1samp_... | <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: Hypothesis testing
Step2: The data averaged over all subjects looks like this
Step3: In this case, a null hypothesis we could test for each vo... |
3,468 | <ASSISTANT_TASK:>
Python Code:
import math
print("The square root of 3 is:", math.sqrt(3))
print("π is:", math.pi)
print("The sin of 90 degrees is:", math.sin(math.radians(90)))
math.
math.erf?
s = "Hello!"
s.join() # or press <shift>+<tab> inside the brackets
from IPython.display import Image
Image('imgs/leonardo.j... | <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: Exploring modules -- getting help
Step2: To get help with a particular function, type math.sin?
Step4: A notebook can display (nearly) anythin... |
3,469 | <ASSISTANT_TASK:>
Python Code:
a = {
"x" : 1,
"y" : 2,
"z" : 3
}
b = {
"w" : 10,
"x" : 11,
"y" : 2
}
# Find keys in common
a.keys() & b.keys()
# Find keys in a that are not in b
a.keys() - b.keys()
# Find (key,value) pairs in common
a.items() & b.items()
# Make a new dictionary with certain ke... | <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: 为了寻找两个字典的相同点，可以简单的在两字典的 keys() 或者 items() 方法返回结果上执行集合操作。比如：
Step2: 这些操作也可以用于修改或者过滤字典元素。 比如，假如你想以现有字典构造一个排除几个指定键的新字典。 下面利用字典推导来实现这样的需求：
|
3,470 | <ASSISTANT_TASK:>
Python Code:
index_of_users = mkUserIndex(df=apps, user_col='uid')
index_of_items = mkItemIndex(df=apps, item_col='job_title')
print('# users: %d' %len(user_ids))
print('# job titles: %d' %len(item_ids))
from scipy.io import *
user_apply_job = mmread(DATA_DIR + 'user_apply_job.mtx')
printInfo(user_app... | <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: Applicant-apply-(Job, Employer) matrix
|
3,471 | <ASSISTANT_TASK:>
Python Code:
indexfile = "./datafiles/index_latest.txt"
import numpy as np
dataindex = np.genfromtxt(indexfile, skip_header=6, unpack=True, delimiter=',', dtype=None, \
names=['catalog_id', 'file_name', 'geospatial_lat_min', 'geospatial_lat_max',
'geospatial_lon_min... | <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 read the index file (comma separated values), we will try with the genfromtxt function.
Step2: Map of observations
Step3: We import the mod... |
3,472 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
raw_inputs = [
[711, 632, 71],
[73, 8, 3215, 55, 927],
[83, 91, 1, 645, 1253, 927],
]
# By default, this will pad using 0s; it is configurable via the
# "value" paramet... | <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: Introduction
Step2: Masking
Step3: As you can see from the printed result, the mask is a 2D boolean tensor with shape
Step4: This is also the... |
3,473 | <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
<END_TASK>
<USER_TASK:>
Description:
Step1: Introduction to OpenFermion
Step2: Initializing the FermionOperator data structure
Step3: The preferred way to specify the coefficient in open... |
3,474 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import control as ct
import control.optimal as opt
ct.use_fbs_defaults()
def vehicle_update(t, x, u, params):
# Get the parameters for the model
a = params.get('refoffset', 1.5) # offset to vehicle reference point
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: Vehicle steering dynamics (Example 3.11)
Step2: Vehicle driving on a curvy road (Figure 8.6a)
Step3: Linearization of lateral steering dynamic... |
3,475 | <ASSISTANT_TASK:>
Python Code:
# Authors: Denis Engemann <denis.engemann@gmail.com>
# Luke Bloy <luke.bloy@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
from mne.filter import next_fast_len
import mne
print(__doc__)
data_path = mne.datasets.opm.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: Load data, resample. We will store the raw objects in dicts with entries
Step2: Do some minimal artifact rejection just for VectorView data
Ste... |
3,476 | <ASSISTANT_TASK:>
Python Code:
from IPython.parallel import Client, error
cluster = Client(profile='mpi')
view = cluster[:]
%%px
from mpi4py import MPI
mpi = MPI.COMM_WORLD
bcast = mpi.bcast
barrier = mpi.barrier
rank = mpi.rank
print "MPI rank: %i/%i" % (mpi.rank,mpi.size)
%%px
import sys
from proteus.iproteus impor... | <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: IPython Parallel "Magics"
Step2: Load Proteus
Step3: Define the tank geometry
Step4: Physics and Numerics
Step5: Numerical Solution Object
S... |
3,477 | <ASSISTANT_TASK:>
Python Code:
import re # Regular Expressions
import pandas as pd # DataFrames & Manipulation
import nltk.data # Sentence tokenizer
from nltk.corpus import stopwords # Import the stop word list
from bs4 import BeautifulSoup # HTML processi... | <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: Prepare text processing
Step4: Define functions for cleaning the text data.
Step5: Initialize and train the model
Step6: Save the model for l... |
3,478 | <ASSISTANT_TASK:>
Python Code:
### Load in necessary libraries for data input and normalization
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
%load_ext autoreload
%autoreload 2
from my_answers import *
%load_ext autoreload
%autoreload 2
from my_answers import *
### load in and normalize the data... | <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: Lets take a quick look at the (normalized) time series we'll be performing predictions on.
Step2: 1.2 Cutting our time series into sequences
S... |
3,479 | <ASSISTANT_TASK:>
Python Code:
import stripy as stripy
import numpy as np
xmin = 0.0
xmax = 10.0
ymin = 0.0
ymax = 10.0
extent = [xmin, xmax, ymin, ymax]
spacingX = 0.5
spacingY = 0.5
ellip0 = stripy.cartesian_meshes.elliptical_mesh(extent, spacingX, spacingY, refinement_levels=0)
ellip1 = stripy.cartesian_meshes.elli... | <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: Uniform meshes by refinement
Step2: Refinement strategies
Step3: Visualisation of refinement strategies
Step4: Targetted refinement
Step5: V... |
3,480 | <ASSISTANT_TASK:>
Python Code:
import warnings
warnings.filterwarnings('ignore')
import os
import pathlib
import matplotlib.pyplot as plt
import numpy as np
from landlab.components import FlowDirectorSteepest, NetworkSedimentTransporter
from landlab.data_record import DataRecord
from landlab.grid.network import Network... | <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. Load a shapefile that represents the river network
Step2: Alright, let's see what fields we read in with this shapefile
Step3: Great! Looks... |
3,481 | <ASSISTANT_TASK:>
Python Code:
#!/usr/bin/python
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from stats import parse_results, get_percentage, get_avg_per_seed, draw_pie, draw_bars, draw_bars_comparison, draw_avgs
pr, eigen, bet = parse_results('test_ws.txt')
draw_pie(get_percentage(pr))
dra... | <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: Parse results
Step2: PageRank Seeds Percentage
Step3: Avg adopters per seed comparison
Step4: Eigenvector Seeds Percentage
Step5: Avg adopte... |
3,482 | <ASSISTANT_TASK:>
Python Code:
import csv as csv
csv_file_object = csv.reader(open('titanic_train.csv', 'rb'))
header = csv_file_object.next()
print(header)
lines = [line for line in csv_file_object]
print(lines[0])
print(lines[1])
import pandas as pd
titanic_train = pd.read_csv("titanic_train.csv")
titanic_train
com... | <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 pandas!
Step2: Community health status from data.gov
Step3: -9999 Indicate N.A. value from the source data for the Unemployed column on th... |
3,483 | <ASSISTANT_TASK:>
Python Code::
# map an integer to a word
def word_for_id(integer, tokenizer):
for word, index in tokenizer.word_index.items():
if index == integer:
return word
return None
# generate a description for an image
def generate_desc(model, tokenizer, photo, max_length):
# seed the generation proces... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
|
3,484 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
rng = np.random.RandomState(42)
x = rng.rand(1000000)
y = rng.rand(1000000)
%timeit x + y
%timeit np.fromiter((xi + yi for xi, yi in zip(x, y)), dtype=x.dtype, count=len(x))
mask = (x > 0.5) & (y < 0.5)
tmp1 = (x > 0.5)
tmp2 = (y < 0.5)
mask = tmp1 & tmp2
import num... | <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 discussed in Computation on NumPy Arrays
Step2: But this abstraction can become less efficient when computing compound expressions.
Step3: ... |
3,485 | <ASSISTANT_TASK:>
Python Code:
df['Total day minutes'].hist();
sns.boxplot(df['Total day minutes']);
df.hist();
df['State'].value_counts().head()
df['Churn'].value_counts()
sns.countplot(df['Churn']);
sns.countplot(df['State']);
sns.countplot(df[df['State'].\
isin(df['State'].value_counts().head().ind... | <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. Категориальные
Step2: 2. Взаимодействия признаков
Step3: 2.2. Количественный с категориальным
Step4: 2.3. Категориальный с категориальн... |
3,486 | <ASSISTANT_TASK:>
Python Code:
import psyplot.project as psy
import xarray as xr
%matplotlib inline
%config InlineBackend.close_figures = False
import numpy as np
x = np.linspace(-1, 1.)
y = np.linspace(-1, 1.)
x2d, y2d = np.meshgrid(x, y)
z = - x2d**2 - y2d**2
ds = xr.Dataset(
{'z': xr.Variable(('x', 'y'), z)},
... | <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: First we create some sample data in the form of a 2D parabola
Step2: For a simple 2D plot of a scalar field, we can use the
Step3: The plot fo... |
3,487 | <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']
clooney = people[people['name'] == 'George Clooney']
clooney['text']
obama['word_count'] = graphlab.text_analytics.count_words(ob... | <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 some text data - from wikipedia, pages on people
Step2: Data contains
Step3: Explore the dataset and checkout the text it contains
Step4:... |
3,488 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
# This code translate from a binary number using the prefix "0b" to a base 10 number.
int('0b11', 2)
# This code translate from base 10 to base 2.
bin(9)
# Just looking a large binary number
bin(2**53)
import bitstrin... | <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: <div id='intro' />
Step2: <div id='nature' />
Step3: The next two functions are self-explanatory
Step4: So if we compute gap(1) we should get... |
3,489 | <ASSISTANT_TASK:>
Python Code:
%pdb on
%pdb
def pick_and_take():
picked = numpy.random.randint(0, 1000)
raise NotImplementedError()
pick_and_take()
import pdb;pdb.set_trace()
def func(x):
return x + 1
for i in range(100):
print(func(i))
if i == 10 or i == 20:
import pdb;pdb.set_trace()
raise Exception... | <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: Tracer
Step2: Interactive Python Console
Step3: Pixie Debugger
|
3,490 | <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
<END_TASK>
<USER_TASK:>
Description:
Step1: Changepoint Detection
Step2: Likelihood
Step4: Doing it the long way
Step5: Using emcee
Step6: Based on an example from Chapter 1 of Bayesia... |
3,491 | <ASSISTANT_TASK:>
Python Code:
from sympy import *
from sympy.vector import CoordSys3D
N = CoordSys3D('N')
x1, x2, x3 = symbols("x_1 x_2 x_3")
alpha1, alpha2, alpha3 = symbols("alpha_1 alpha_2 alpha_3")
L, ga, gv, c = symbols("L g_a g_v c")
init_printing()
x = alpha1
y = alpha2
a1=gv *2*pi/L
z = ga * cos(c * alpha1)
r... | <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: Coordinates
Step2: Mid-surface coordinates is defined with the following vector $\vec{r}=\vec{r}(\alpha_1, \alpha_2)$
Step3: Tangent to curve
... |
3,492 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import scipy.io as sio
import math
n=100 # number of iterations
#initial
B=0.15 # Model Noise
R=0.02 # Observation Noise
A = 0.5 # Model Matrix
# creation of numpy arrays for variables
z= np.zeros(n)
m= np... | <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: Lorenz equations
|
3,493 | <ASSISTANT_TASK:>
Python Code:
# Importa la librería financiera.
# Solo es necesario ejecutar la importación una sola vez.
import cashflows as cf
import cashflows as cf
##
## Se tienen cuatro fuentes de capital con diferentes costos
## sus datos se almacenarar en las siguientes listas:
##
monto = [0] * 4
interes = [... | <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: Problema del costo de capital
Step2: En la modelación de créditos con cashflow se consideran dos tipos de costos
|
3,494 | <ASSISTANT_TASK:>
Python Code:
from collections import OrderedDict
#JSON to store all the informacion.
jsonsOccupants = []
#Number of occupants
N = 3
#Definition of the states
states = OrderedDict([('Leaving','out'), ('Resting', 'sofa'), ('Working in my laboratory', 'wp')])
#Definition of the schedule
schedule = {'t1':... | <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.- We define the building plan or the distribution of the space.
Step2: 3.- We implement a Model inheriting a base class of SOBA.
Step3: 4.- ... |
3,495 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import HTML
input_form =
<div style="background-color:gainsboro; border:solid black; width:300px; padding:20px;">
Variable Name: <input type="text" id="var_name" value="foo"><br>
Variable Value: <input type="text" id="var_value" value="bar"><br>
<button onclick="set_... | <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: IPython Notebook
Step3: After pressing <button>Set Value</button> above
Step4: Examining the code, we see that
Step7: And then we'll manipula... |
3,496 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
sys.path.insert(0, "../..")
import importlib
import numpy as np
import pandas as pd
import yellowbrick
import yellowbrick as yb
from yellowbrick.features.importances import FeatureImportances
import matplotlib as mpl
import matplotlib.pyplot as plt
from sklearn import... | <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 Iris Datasets for Example Code
Step2: Logistic Regression with Mean of Feature Importances
Step3: Logistic Regression with Stacked Featur... |
3,497 | <ASSISTANT_TASK:>
Python Code:
class vector_math:
'''
This is the base class for vector math - which allows for initialization with two vectors.
'''
def __init__(self, vectors = [[1,2,2],[3,4,3]]):
self.vect1 = vectors[0]
self.vect2 = vectors[1]
def set_vects(self, vect... | <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: Other vector operations that could be done
Step2: List Comprehensions are Powerful tools in Python
|
3,498 | <ASSISTANT_TASK:>
Python Code:
user = #type CMEMS user name within colons
password = #type CMEMS password within colons
product_name = 'INSITU_BAL_NRT_OBSERVATIONS_013_032' #type aimed CMEMS in situ product
distribution_unit = 'cmems.smhi.se' #type aimed hosting institution
index_file = 'index_latest.txt' #type aimed... | <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: <h3>DOWNLOAD</h3>
Step2: <h3>QUICK VIEW</h3>
Step3: <h3>FILTERING CRITERIA</h3>
Step4: Regarding the above glimpse, it is posible to filter b... |
3,499 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
from sklearn.svm import SVR
from sklearn.linear_model import Lasso
from sklearn.metrics import mean_squared_error
from sklearn.preprocessing import StandardScaler
from sklearn.cross_validation import train_test_split
# input data reading
df = pd.rea... | <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: Regression sample
|
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