Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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14,100 | <ASSISTANT_TASK:>
Python Code:
from mosasaurus.Target import Target
# load a target from SIMBAD
t = Target(starname='GJ1132', name='GJ1132b')
t.summarize()
t.star.summarize()
# create a target from values (in case you want to work offline)
import astropy.units as u
t = Target(starname='GJ1132', name='GJ1132b',
... | <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: Determine the basic properties of this instrument.
Step2: Determine the basic properties of this night, including a nightly observing log.
Step... |
14,101 | <ASSISTANT_TASK:>
Python Code:
import rebound
import reboundx
import astropy.units as u
import astropy.constants as constants
import numpy as np
import matplotlib.pyplot as plt
sim = rebound.Simulation()
sim.units = ('yr', 'AU', 'Msun')
sim.add(m = 1)
a0=1
sim.add(m = 1.e-4, a=a0, e=0, inc = 0)
sim.move_to_com()
ps = s... | <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 add the type_I_migration effect, and set the appropriate disk parameters. Note that we chose code units of AU for all the distances above... |
14,102 | <ASSISTANT_TASK:>
Python Code:
# Authors: Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
from os import path as op
import mne
from mne.preprocessing import maxwell_filter
print(__doc__)
data_path = op.join(mne.datasets.misc.data_path(verbose=True), 'movement')
head_pos = mne.chpi.read_head_pos(op.join(... | <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: Visualize the "subject" head movements. By providing the measurement
Step2: This can also be visualized using a quiver.
Step3: Process our sim... |
14,103 | <ASSISTANT_TASK:>
Python Code:
# import some useful packages
import numpy as np
import matplotlib.pyplot as plt
import seaborn
import networkx as nx
import pandas as pd
import random
import json
# latex rendering of text in graphs
import matplotlib as mpl
mpl.rc('text', usetex = False)
mpl.rc('font', family = 'serif')
... | <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: Test drug_gene_heatprop module
Step2: More detailed description of methods below...
Step3: What is this drug-gene graph like?
Step4: But we p... |
14,104 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import sys
sys.path.insert(0,'../code/functions/')
import tiffIO as tIO
import connectLib as cLib
import plosLib as pLib
import time
import scipy.ndimage as ndimage
import numpy as np
import scipy.ndimage as ndimage
class ClusterComponen... | <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 Actual Code
Step2: I will be using the below cell for analyzing Cluster Component's Performance
Step3: Cluster Components Conditions
Step4... |
14,105 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
digits = load_digits()
X_train, X_test, y_train, y_test = train_test_split(
digits.data, digits.target, random_state=0)
X... | <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: Really Simple API
Step2: 1) Instantiate an object and set the parameters
Step3: 2) Fit the model
Step4: 3) Apply / evaluate
Step5: And again... |
14,106 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import logging
from scipy.stats import norm
import dora.active_sampling as sampling
import time
from dora.active_sampling import pltutils
import matplotlib.pyplot as pl
import matplotlib as mpl
%matplotlib inline
def ground_truth(X):
return np.sin(X-5) + np.sin(X/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: Problem Setup
Step2: Next we need to set the bounds for the problem. In this example, the space is one dimensional. So the upper and lower boun... |
14,107 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
view_sentence_range = (0, 10)
DON'T MODIFY AN... | <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: Language Translation
Step3: Explore the Data
Step6: Implement Preprocessing Function
Step8: Preprocess all the data and save it
Step10: Chec... |
14,108 | <ASSISTANT_TASK:>
Python Code:
#import statements
from keras.layers.core import Dense, Activation, Dropout
from keras.layers.recurrent import LSTM
from keras.models import Sequential
import lstm, time
import pandas as pd
import matplotlib as plt
from sklearn.preprocessing import StandardScaler
import numpy as np
#read ... | <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 is what our data looks like
Step3: now we can proceed with the analysis
Step4: TRAINING TIME!
|
14,109 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import IEtools
import pylab as pl
%pylab inline
filename1='C:/econdata/GDP.xls'
filename2='C:/econdata/PAYEMS.xls'
filename3='C:/econdata/CPIAUCSL.xls'
gdp = IEtools.FREDxlsRead(filename1)
lab = IEtools.FREDxlsRead(filename2)
cpi = IEtools.FREDxlsRead(filename3)
pl.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: Read in the files
Step2: Here's a plot of nominal GDP
Step3: And here is nominal GDP growth
Step4: Fit information equilibrium parameters
Ste... |
14,110 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import medfilt
import gitInformation
from neo.io import NeuralynxIO
% matplotlib inline
gitInformation.printInformation()
# Session folder with all needed neuralynx files
sessionfolder = 'C:\\Users\\Dominik\\Documents\\G... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Filter data with different window lenghts.
Step2: Calculate the threshold for each filtered data
Step3: Plot Each data and the threshold
Step4... |
14,111 | <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: <table class="tfo-notebook-buttons" align="left">
Step3: If you're putting a nontrivial chunk of forward pass code into the shim, you want to k... |
14,112 | <ASSISTANT_TASK:>
Python Code:
from os.path import join, expandvars
from joblib import Parallel, delayed
from tax_credit.framework_functions import (runtime_make_test_data,
runtime_make_commands,
clock_runtime,
... | <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 test datasets
Step2: Preparing the method/parameter combinations
Step3: Generate the list of commands and run them
Step4: Next, we w... |
14,113 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
Pleiades_NIR = np.genfromtxt('../Projects/pleiades_colors/data/Stauffer_Pleiades_nir.dat',
usecols=(2, 3, 5, 6, 8, 9)) # J, errJ, H, errH, K, errK
dist_mod = 5.62 # distance modulus for t... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Solar Abundances and NIR Broadband Photometric Colors
Step2: Now we'll need to load appropriate stellar evolution isochrones with bolometric co... |
14,114 | <ASSISTANT_TASK:>
Python Code:
try:
if __IPYTHON__:
# this is used for debugging purposes only. allows to reload classes when changed
get_ipython().magic(u'load_ext autoreload')
get_ipython().magic(u'autoreload 2')
except NameError:
print('Not IPYTHON')
pass
import sys
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: <h1> Using the workload manager SLURM </h1>
Step2: <b> We can see here that the number of processes are the number of core your computer posses... |
14,115 | <ASSISTANT_TASK:>
Python Code:
#Load blast hits
blastp_hits = pd.read_csv("2_blastp_hits.csv")
blastp_hits.head()
#Filter out Metahit 2010 hits, keep only Metahit 2014
blastp_hits = blastp_hits[blastp_hits.db != "metahit_pep"]
#Assumes the Fasta file comes with the header format of EMBOSS getorf
fh = open("1_orf/d9539... | <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. Process blastp results
Step2: 2.2 Annotate blast hits with orf stats
Step3: 2.3 Extract best hit for each ORF ( q_cov > 0.8 and pct_id > 40... |
14,116 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division, print_function
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
try: plt.style.use('ggplot')
except: pass
# We need distributions to model priors.
from qinfer import distributions
# The noisy coin model has already been implmented, s... | <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 get access to NumPy and matplotlib, IPython's %pylab magic command is quite useful. With the inline argument, all plots will be made a part o... |
14,117 | <ASSISTANT_TASK:>
Python Code:
# Authors: Jose C. Garcia Alanis <alanis.jcg@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from mne.datasets.limo import load_data
from mne.stats import linear_regression
from mne.viz import plot_events, plot_compare_evokeds
from mne import comb... | <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: About the data
Step2: Note that the result of the loading process is an
Step3: Visualize events
Step4: As it can be seen above, conditions ar... |
14,118 | <ASSISTANT_TASK:>
Python Code:
# Only needed in a Jupyter Notebook
%matplotlib inline
# Optional plot styling
import matplotlib
matplotlib.style.use('bmh')
import matplotlib.pyplot as plt
from pycalphad import equilibrium
from pycalphad import Database, Model
import pycalphad.variables as v
import numpy as np
db = Dat... | <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: Al-Fe (Heat Capacity and Degree of Ordering)
Step2: We also compute degree of ordering at fixed temperature as a function of composition.
Step3... |
14,119 | <ASSISTANT_TASK:>
Python Code:
import _initpath
import numpy
import zerosum.balance
data = numpy.array([
[1.0, 3.0, 0.5],
[1.0 / 3.0, 1.0, 0.5],
[2.0, 2.0, 1.0]])
names = ['Hammer', 'Spear', 'Curse']
data = 1.0 / data
balance = zerosum.balance.HazardSymmetricBalance(data)
result = balance.optimize()
for... | <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: Then we take the data as it appeared in Hazard's slides. The example given was symmetric, which means that the base matrix is log-skew-symmetric... |
14,120 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nasa-giss', 'sandbox-1', 'atmoschem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("nam... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
14,121 | <ASSISTANT_TASK:>
Python Code:
# Execute this cell to load the notebook's style sheet, then ignore it
from IPython.core.display import HTML
css_file = '../../style/custom.css'
HTML(open(css_file, "r").read())
# import SymPy libraries
from sympy import symbols, differentiate_finite, Function
# Define symbols
x, h = sym... | <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: Generalization of Taylor FD operators
|
14,122 | <ASSISTANT_TASK:>
Python Code:
import os
from time import time
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import fitsio
import seaborn as sns
from speclite import filters
from desitarget import desi_mask
from desisim.io import read_basis_templates
%pylab inline
sns.set(style='... | <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: Read the targets catalog
Step3: Read the templates and compute colors on a redshift grid.
Step5: Generate some plots
|
14,123 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
try:
import seaborn
except ImportError:
pass
data = {'country': ['Belgium', 'France', 'Germany', 'Netherlands', 'United Kingdom'],
'population': [11.3, 64.3, 81.3, 16.9, 64.9],
... | <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: Some notes on selecting data
Step2: or multiple columns
Step3: But, slicing accesses the rows
Step4: So as a summary, [] provides the followi... |
14,124 | <ASSISTANT_TASK:>
Python Code:
from crpropa import *
obs = Observer()
obs.add(ObserverPoint())
obs.add(ObserverInactiveVeto())
t = TextOutput("photon_electron_output.txt", Output.Event1D)
obs.onDetection(t)
sim = ModuleList()
sim.add(SimplePropagation())
sim.add(Redshift())
sim.add(EMPairProduction(CMB(),True))
sim.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:
Step1: (Optional) plotting of the results
Step2: Photon Propagation outside of CRPropa with EleCa and DINT
Step3: The file 'photon_output.txt' will ... |
14,125 | <ASSISTANT_TASK:>
Python Code:
x = 1
x = 1.0
x = True
x = "True"
(1.0 + 2.0)*3
(100>0) and (1./3<1./2)
a = 3
b = 4
c = (a**2 + b**2)**0.5
peri = a + b + c
a = 1
b = a
c = a + b
a = c
print a, b, c
nombre = raw_input("Ingrese su nombre: ")
edad = int(raw_input("Ingrese su edad [años]: "))
altura = float(raw_input("... | <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: 1.2 Expresión
Step2: Asignación
Step3: Cálculo de expresión y luego asignación
Step4: Asignación
Step5: 2- Input y Output
Step6: 2.2 Salida... |
14,126 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy
from numpy.random import choice
from sklearn.datasets import load_boston
from h2o.estimators.random_forest import H2ORandomForestEstimator
import h2o
h2o.init()
# transfer the boston data from pandas to H2O
boston_data = load_boston()
X = pd.DataFrame(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: Enable inline plotting in the Jupyter Notebook
Step2: Intro to H2O Data Munging
Step3: View the top of the H2O frame.
Step4: View the bottom ... |
14,127 | <ASSISTANT_TASK:>
Python Code:
# %load ./arguments.py
#!/usr/bin/python
import sys
# it's easy to print this list of course:
print sys.argv
# or it can be iterated via a for loop:
for i in range(len(sys.argv)):
if i == 0:
print "Function name: %s" % sys.argv[0]
else:
print "%d. argument: %s" % (... | <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: Writing a Module
Step2: This is a really simple equation, but by making this a function, we can make it more sophisticated or change the expone... |
14,128 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
import glob
from IPython.display import Image
import numpy as np
import openmc
from openmc.statepoint import StatePoint
from openmc.summary import Summary
from openmc.source import Source
from openmc.stats import Box
%matplotlib inline
# Instantiate som... | <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 the nuclides we defined, we will now create three materials for the fuel, water, and cladding of the fuel pin.... |
14,129 | <ASSISTANT_TASK:>
Python Code:
import json
import numpy as np
import tensorflow.compat.v1 as tf
import tqdm
# Suppress noisy log messages.
from tensorflow.python.util import deprecation
deprecation._PRINT_DEPRECATION_WARNINGS = False
AMINO_ACID_VOCABULARY = [
'A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step4: Library functions
Step5: Download model and vocabulary
Step6: Load the model into TensorFlow
Step7: Load tensors for class prediction
Step8: ... |
14,130 | <ASSISTANT_TASK:>
Python Code:
%load_ext sql
from django.conf import settings
connection_string = 'postgresql+psycopg2://{USER}:{PASSWORD}@{HOST}:{PORT}/{NAME}'.format(
**settings.DATABASES['default']
)
%sql $connection_string
%%sql
SELECT cvr."FILING_ID", COUNT(DISTINCT cvr."FORM_TYPE")
FROM "CVR_CAMPAIGN_DISCLOS... | <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: Cover Sheets
Step2: Do the FILER_ID values vary between amendments to the same any campaign filing?
Step3: Joining to FILER_FILINGS_CD
Step4: ... |
14,131 | <ASSISTANT_TASK:>
Python Code:
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pandas as pd
from model_tool import ToxModel
SPLITS = ['train', 'dev', 'test']
wiki = {}
debias = {}
random = {}
for split in SPLITS:
wiki[split] = '../data/wiki_%s.csv... | <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 Data
Step2: Train Models
Step3: Random model
Step4: Plain wikipedia model
Step5: Debiased model
|
14,132 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
# As an alternative, one may use: %pylab notebook
# For old Matplotlib and Ipython versions, use the non-interactive version:
# %matplotlib inline or %pylab inline
# To ignore warnings (http://stackoverflow.com/questions/9031783/hide-all-warnings-in-ipython)
import wa... | <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: Useful keyboard shortcuts
Step2: 3D plots
Step3: Animations
Step4: Interactive plots with Plotly
Step5: IPython built-in magic commands
Step... |
14,133 | <ASSISTANT_TASK:>
Python Code:
from time import time
start_nb = time()
# Initialize logging.
import logging
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s')
sentence_obama = 'Obama speaks to the media in Illinois'
sentence_president = 'The president greets the press in Chicago'
sentence_obama = s... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: These sentences have very similar content, and as such the WMD should be low. Before we compute the WMD, we want to remove stopwords ("the", "to... |
14,134 | <ASSISTANT_TASK:>
Python Code:
import torch
from torch import nn
import os
import sys
module_path = os.path.abspath(os.path.join('..'))
if module_path not in sys.path:
sys.path.append(module_path)
%matplotlib inline
import matplotlib.pyplot as plt
import torchsde
def plot(ts, samples, xlabel, ylabel, title=''):
... | <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: Just like how each ordinary differential equation (ODE) is governed by a vector field, a stochastic differential equation (SDE) is governed by t... |
14,135 | <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 math
import numpy as np
import pandas as pd
from thinkbayes2 import 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: The August birthday problem
Step2: I'll roll the data so September comes first.
Step3: Here are the diagnosis rates, which we can check agains... |
14,136 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
import numpy as np
from dh_py_access import package_api
import dh_py_access.lib.datahub as datahub
import xarray as xr
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from po_data_process import get_data_in_pandas_dataframe, make_plot,get_comp... | <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: <font color='red'>Please put your datahub API key into a file called APIKEY and place it to the notebook folder or assign your API key directly ... |
14,137 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd
import matplotlib as mp
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
qb_games = pd.read_csv('qb_games.csv')
qb_games.columns.values
qb_games['Fantasy Points'] = (qb_games['Pass Yds']/25) + (6 * qb_games['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: Calculate Fantasy Points
Step2: Get the average QB fantasy points by year
Step3: Observation
Step4: Observation
Step5: Observation
Step6: O... |
14,138 | <ASSISTANT_TASK:>
Python Code:
# Utils
import sys
import os
import shutil
import time
import pickle
import numpy as np
# Deep Learning Librairies
import tensorflow as tf
import keras.preprocessing.image as kpi
import keras.layers as kl
import keras.optimizers as ko
import keras.backend as k
import keras.models as km
im... | <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: La commande suivante permet de verifier qu'une carte GPU est bien disponible sur la machine utilisée. Si c'est le cas et si Keras a bien été ins... |
14,139 | <ASSISTANT_TASK:>
Python Code:
import sys
import math
import numpy as np
import pandas as pd
import scipy.optimize as so
import scipy.integrate as si
import matplotlib.pyplot as plt
import nest
%matplotlib inline
plt.rcParams['figure.figsize'] = (12, 3)
def Vpass(t, V0, gNaL, ENa, gKL, EK, taum, I=0):
tau_eff = ta... | <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: Neuron Model
Step2: Agreement is excellent.
Step3: Agreement is as good as possible
Step5: ISIs are as predicted
Step6: I_h channel
Step7: ... |
14,140 | <ASSISTANT_TASK:>
Python Code:
import sys
import os
sys.path.append(os.environ.get('NOTEBOOK_ROOT'))
import xarray as xr
import numpy as np
import datacube
from utils.data_cube_utilities.data_access_api import DataAccessApi
from datacube.utils.aws import configure_s3_access
configure_s3_access(requester_pays=True)
ap... | <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: <span id="plat_prod">Choose Platforms and Products ▴</span>
Step2: Choose product
Step3: <span id="extents">Get the Extents of the Cube ... |
14,141 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
lst = [10, 20, 30, 40]
arr = np.array([10, 20, 30, 40])
arr[0]
lst[0]
arr[-1]
arr[2:]
lst[-1] = 'a string inside a list'
lst
arr[-1] = 'a string inside an array'
arr.dtype
arr[-1] = 1.234
arr
np.zeros(5, dtype=float)
np.zeros(3, dtype=int)
np.zeros(3, dtype=comple... | <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 do this to save time with all future functions. Instead of needing to type (for example)
Step2: Elements of a one-dimensional array are acce... |
14,142 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
deaths_df = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv')
# Question 3
# Display first 5 rows
# of the loaded data
deaths_df.head(5... | <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: Question 3
Step2: ...and do a short summary about the data;
Step3: Question 5
Step4: Question 6
|
14,143 | <ASSISTANT_TASK:>
Python Code:
#|export
from __future__ import annotations
from fastai.torch_basics import *
from torch.utils.data.dataloader import _MultiProcessingDataLoaderIter,_SingleProcessDataLoaderIter,_DatasetKind
_loaders = (_MultiProcessingDataLoaderIter,_SingleProcessDataLoaderIter)
#|hide
from nbdev.showdoc... | <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: DataLoader helpers
Step2: DataLoader -
Step3: Arguments to DataLoader
Step4: If you don't set bs, then dataset is assumed to provide an itera... |
14,144 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import datetime
dt = datetime.datetime(year=2016, month=12, day=19, hour=13, minute=30)
dt
print(dt) # .day,...
print(dt.strftime("%d %B %Y"))
ts = pd.Timestamp('2016-12-19')
ts
ts.month
ts ... | <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: Dates and times in pandas
Step3: Like with datetime.datetime objects, there are several useful attributes available on the... |
14,145 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import nashpy as nash
import matplotlib.pyplot as plt
A = np.array([[4, 3], [2, 1]])
game = nash.Game(A)
timepoints = np.linspace(0, 10, 1000)
epsilon = 10 ** -1
xs = game.replicator_dynamics(
y0=[1 - epsilon, epsilon],
timepoints=timepoints,
)
plt.plot(xs);
... | <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 case of $a>c$
Step2: The case of $a=c$ and $b>d$
Step3: $a=c$ and $b < d$
Step4: $a < c$
Step5: We see in the above case that the popula... |
14,146 | <ASSISTANT_TASK:>
Python Code:
import pensieve as pens
import textacy
from collections import defaultdict
from random import random
def make_markov_chain(docs):
my_dict = defaultdict(list)
inverse_dict = defaultdict(list)
for doc in docs:
print("Reading ",doc)
d = pens.Doc(doc)
for ... | <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: Define our markiv hcain functions. First to create the dics. First attempt only takes triplets of words a b c and adds {'a b'
Step2: Load the b... |
14,147 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import pickle
import seaborn as sns
from pandas import DataFrame, Index
from sklearn import metrics
from sklearn.linear_model import SGDClassifier
from sklearn.svm import SVC
from sklearn.kernel_approximation import RBFSampler, Nystroem
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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<USER_TASK:>
Description:
Step1: Query by Committee
Step2: Stochastic Gradient Descent
Step3: Random selection of data points at each iteration.
Step4: SVM with Random Sampli... |
14,148 | <ASSISTANT_TASK:>
Python Code:
for i in [1,2,3]:
print(i)
for ch in 'test':
print(ch)
for k in {1:'test1',2:'test'}:
print(k)
",".join(["a","b","c"])
",".join(('this','is','a','test'))
",".join({'key1':'value','key2':'value2'})
x = iter([1,2,3])
print(x)
print(next(x))
print(next(x))
print(next(x))
prin... | <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 we use it with a string, it loops over its characters.
Step2: If use it with a dictionary, it loops over its keys
Step3: So there are many ... |
14,149 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import antipackage
import github.ellisonbg.misc.vizarray as va
def checkerboard(size):
Return a 2d checkboard of 0.0 and 1.0 as a NumPy array
# YOUR CODE HERE
raise NotI... | <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: Checkerboard
Step3: Use vizarray to visualize a checkerboard of size=20 with a block size of 10px.
Step4: Use vizarray to visualize a checkerb... |
14,150 | <ASSISTANT_TASK:>
Python Code:
from explauto.environment import environments
print 'Available environments: {}'.format(environments.keys())
env_cls, env_configs, _ = environments['simple_arm']
print 'Available configurations for the simple arm environment: {}'.format(env_configs.keys())
config = env_configs['default'... | <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: According to your installation, you will see different available environments
Step2: There are 4 different configurations for the simple arm (w... |
14,151 | <ASSISTANT_TASK:>
Python Code:
An example to store the output without "pickle"
testfile = 'nopickle.txt'
var1 = 1143
var2 = ["AECS", "LAYOUT", "KUNDALAHALLI"]
var3 = 58.30
var4 = ("Bangalore", 560037)
def ezhudhu():
with open(testfile, 'w+') as f:
f.write(str(var1))
f.write(str(var2))
f.writ... | <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: Howto with examples on 'pickle' module ==> 28/May/2016
Step4: This is the content of nopickle.txt
Step6: ** This is the content of pickle.tx... |
14,152 | <ASSISTANT_TASK:>
Python Code:
species = 'Mus_musculus'
taxid = '10090'
assembly = 'GRCm38.p6'
genbank = 'GCF_000001635.26'
sumurl = ('ftp://ftp.ncbi.nlm.nih.gov/genomes/all/{0}/{1}/{2}/{3}/{4}_{5}/'
'{4}_{5}_assembly_report.txt').format(genbank[:3], genbank[4:7], genbank[7:10],
... | <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: The variables defined above can be modified for any other species, resulting in new results for the following commands.
Step2: Sequences of eac... |
14,153 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from pymatbridge import Octave
octave = Octave()
octave.start()
%load_ext pymatbridge
%%matlab
load('Chap17_Data')
%%matlab
whos
%%matlab
fieldnames(spike)
%%matlab
size(spike(1).times)
%%matlab
size(spike(2).times) %nb de décharges pour l'essai 2
%%matlab
size(sp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Section 1
Step2: <ol start="2">
Step3: <font color="red">Quelles variables sont présentes? Quel est le type de la variable spike? Quelle est ... |
14,154 | <ASSISTANT_TASK:>
Python Code:
from collections import deque
dq = deque()
dq.append(1)
dq.append(2)
dq.appendleft(3)
dq
v = dq.pop()
v
dq.popleft()
dq
dq = deque(maxlen = 3)
for n in range(10):
dq.append(n)
dq
import heapq
nums = [1, 8, 2, 23, 7, -4, 18, 23, 42, 37, 2]
#heapq is created from a list
heap = list(nu... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Using maxlen to limit the num of items in a deque
Step2: 2. Heapq
Step3: nlargest / nsmallest wraps creation of a heap for one-time access
Ste... |
14,155 | <ASSISTANT_TASK:>
Python Code:
from calendar import TextCalendar, HTMLCalendar
tc = TextCalendar(firstweekday=6)
tc.prmonth(2016, 3)
object
timedelta
tzinfo
timezone
time
date
datetime
pass
import time as _time
from datetime import date, time, datetime
d1 = date(2016, 3, 29)
d2 = date.... | <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: datetime 模块解决了绝大部分时间与日期相关的操作问题，其中包含了：
Step3: Date
Step4: 获得 date 对象之后，可以分别获取年、月、日等属性（strftime也是通用的格式化方法，将在后面介绍）：
Step5: Time
Step6: datetime... |
14,156 | <ASSISTANT_TASK:>
Python Code:
from IPython.core.display import HTML
css_file = 'pynoddy.css'
HTML(open(css_file, "r").read())
import sys, os
import matplotlib.pyplot as plt
# adjust some settings for matplotlib
from matplotlib import rcParams
# print rcParams
rcParams['font.size'] = 15
# determine path of repository t... | <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 in Experiment object
Step2: Adjust properties of tilt event
Step3: Now, we can define a stochastic variable for the tilt rotation
Step4... |
14,157 | <ASSISTANT_TASK:>
Python Code:
import pickle
from geopy.distance import vincenty
station_data = pickle.load( open( "station_data.p", "rb" ) )
bike_location = pickle.load( open( "bike_location.p", "rb" ) )
print(station_data['RD']['Bethesda'])
print(bike_location['Silver Spring Metro/Colesville Rd & Wayne Ave'])
vinc... | <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 all data (data was previously cleaning in other notebooks)
Step2: Now I have one dict with metro stations and one with bike stations
Ste... |
14,158 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import json
import requests
import time
import pickle
from ipywidgets import FloatProgress
from IPython.display import display
#from API_client.python.datahub import datahub
#from API_c... | <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: Combine statistics and hard limits
Step2: Dump the file for later use
Step3: Helper methods to plot the problematic data
Step4: Merge all .pi... |
14,159 | <ASSISTANT_TASK:>
Python Code:
import os
import json
import numpy as np
import tfx
import tensorflow as tf
import tensorflow_transform as tft
import tensorflow_data_validation as tfdv
import tensorflow_model_analysis as tfma
from tensorflow_transform.tf_metadata import schema_utils
import logging
from src.common 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: Setup Google Cloud project
Step2: Set configurations
Step3: Create Interactive Context
Step4: 1. Hyperparameter generation
Step5: 2. Data ex... |
14,160 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cccr-iitm', 'sandbox-1', 'landice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
14,161 | <ASSISTANT_TASK:>
Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
texto = "Cientista de Dados é a profissão que mais tem crescido em todo mundo.\n"
texto = texto + "Esses profissionais precisam se especial... | <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: ** ATENÇÃO ****
Step2: Usando a expressão with
Step3: Manipulando Arquivos CSV (comma-separated values )
Step4: Manipulando Arquivos JSON (Ja... |
14,162 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
from numpy import *
from scipy.integrate import odeint
from matplotlib.pyplot import *
ion()
def consumer_resource1(y, t, r, K, b1, m1, b2, m2):
return array([ y[0] * (r*(1-y[0]/K) - b1*y[1] - b2*y[2]),
y[1] * (b1*y[0] - m1),
... | <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="2">2. Coexistência em equilíbrio
Step2: <div id="3">3. Não-linearidade relativa</div>
|
14,163 | <ASSISTANT_TASK:>
Python Code:
# downloading packages:
!pip install wget pycroscopy
# Ensure python 3 compatibility:
from __future__ import division, print_function, absolute_import, unicode_literals
# In case some of these packages are not installed, install them
#!pip install -U os wget numpy h5py matplotlib pycrosco... | <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: 0. Select the Raw Data File
Step2: 1. Exploring the Raw Data File
Step3: 2. Loading the data
Step4: 3. Read the parameters
Step5: 3.a Prepar... |
14,164 | <ASSISTANT_TASK:>
Python Code:
# Import packages
%run startup.py
bf = Session(host="localhost")
def show_first_trace(trace_answer_frame):
Prints the first trace in the answer frame.
In the presence of multipath routing, Batfish outputs all traces
from the source to destination. This function pick... | <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: Analyzing public cloud and hybrid networks
Step3: Initializing the Network and Snapshot
Step4: The network snapshot that we just initialized i... |
14,165 | <ASSISTANT_TASK:>
Python Code:
dest_A_rand_I = []
dest_B_rand_I = []
dest_A_rand_p = []
dest_B_rand_p = []
for i in range(1000):
phi = np.random.uniform(0,np.pi*2, 50).reshape((-1,1))
num = np.arange(0,50).reshape((-1,1))
OX = np.random.randint(0,500, 50).reshape((-1,1))
OY = np.random.randint(0,500, 50... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Generate 1000 random datasets of 50 vectors with constrained origins (to induce positive spatial autocorrrlation), then calculate the vector Mor... |
14,166 | <ASSISTANT_TASK:>
Python Code:
#Se prepara el entorno de trabajo
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
#matplotlib.style.use('ggplot') se puede correr este código para usar gráficos del tipo de ggplot2 en R
plt.rcParams['figure.... | <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: Con la muestra de datos que se define en Ingresos_2, la idea es procesarla y explorar los datos. Esto de manera sencilla implica conocer los tip... |
14,167 | <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: Implementing Custom Aggregations
Step2: Design summary
Step3: Instead of summing value, the example task is to sum value * 2.0 and then divide... |
14,168 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import os
assert os.path.isfile('yearssn.dat')
data = np.loadtxt('yearssn.dat')
#Creates two arrays, year is the first column of data and ssc is the second column of data
year = data[:,0]
ssc = data[:,1]
print (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: Line plot of sunspot data
Step2: Use np.loadtxt to read the data into a NumPy array called data. Then create two new 1d NumPy arrays named year... |
14,169 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2022 DeepMind Technologies Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICE... | <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: Imports
Step2: Load ImageNet dataset
Step3: Define a set of evaluation metrics
Step4: Load pre-trained Epinet
Step5: From the checkpoint, we... |
14,170 | <ASSISTANT_TASK:>
Python Code:
# gym オープンソースライブラリの読み込み
import gym
# 環境を作る
env = gym.make('CartPole-v0') # 'CartPole-v0' は環境ID
#env = gym.make('MountainCar-v0') # 'MountainCar-v0'という別の環境
#env = gym.make('MsPacman-v0') # 'MsPacman-v0'という別の環境
env.seed(42)
# 環境の初期化（最初の観測が得られる）
env.reset()
# 描画
env.render()
# 行動選択（... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step 1
Step1: Step 2
Step2: Step 3
Step3: 観測
Step4: 空間
Step5: Descrete
Step6: Box
Step7: スペースからサンプリングすることも、ある値がスペースに含まれているか調べることもできる。
Step8: 環境
... |
14,171 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
14,172 | <ASSISTANT_TASK:>
Python Code:
MovieTextFile = open("tmdb_5000_movies.csv")
# for line in MovieTextFile:
# print(line) # not quite right
# type(MovieTextFile)
import csv
with open("tmdb_5000_movies.csv",encoding="utf8") as f:
reader = csv.reader(f)
MovieList = list(reader)
MovieList[:5]
import pandas as pd... | <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: Import data as a list of lines
Step2: Import data as a data frame
Step3: Goal 2
Step4: Goal 3
|
14,173 | <ASSISTANT_TASK:>
Python Code:
# Setup your dependencies
import os
# The Google Cloud Notebook product has specific requirements
IS_GOOGLE_CLOUD_NOTEBOOK = os.path.exists("/opt/deeplearning/metadata/env_version")
# Google Cloud Notebook requires dependencies to be installed with '--user'
USER_FLAG = ""
if IS_GOOGLE_CLO... | <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: Import libraries and define constants
Step2: Tutorial
Step3: Create the study configuration
Step4: Create the study
Step7: Metric evaluation... |
14,174 | <ASSISTANT_TASK:>
Python Code:
!pip install -I "phoebe>=2.1,<2.2"
%matplotlib inline
import phoebe
from phoebe import u # units
import numpy as np
import matplotlib.pyplot as plt
logger = phoebe.logger()
b = phoebe.default_binary()
b.set_value('sma@binary', 20)
b.set_value('q', 0.8)
b.set_value('ecc', 0.8)
b.set_valu... | <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 always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
Step2: And let's make our system... |
14,175 | <ASSISTANT_TASK:>
Python Code:
#Import data from json file and create a list
data = []
with open('/home/borjaregueral/Digital_Music_5.json') as f:
for line in f:
data.append(json.loads(line))
#Create a dataframe with the columns that are interesting for this exercise
#Columns left out: 'helpful', 'reviewTim... | <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: Build Sentiment Scores and Categories
Step2: Bag of Words
Step3: Bernoulli
Step4: Logistic Model
Step5: TFIDF
Step6: Logistic Model
Step7: ... |
14,176 | <ASSISTANT_TASK:>
Python Code:
import graphlab
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
'''Check GraphLab Create version'''
from distutils.version import StrictVersion
assert (StrictVersion(graphlab.version) >= StrictVersion('1.8.5')), 'GraphLab Create must be version 1.8.5 or later.'
wiki... | <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: Load Wikipedia dataset
Step2: Extract word count vectors
Step3: Find nearest neighbors
Step4: Let's look at the top 10 nearest neighbors by p... |
14,177 | <ASSISTANT_TASK:>
Python Code:
# If you'd like to download it through the command line...
!curl -O http://www.cs.cornell.edu/home/llee/data/convote/convote_v1.1.tar.gz
# And then extract it through the command line...
!tar -zxf convote_v1.1.tar.gz
# glob finds files matching a certain filename pattern
import glob
# Gi... | <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: You can explore the files if you'd like, but we're going to get the ones from convote_v1.1/data_stage_one/development_set/. It's a bunch of text... |
14,178 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%pylab inline
from __future__ import print_function
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import theano
import numpy as np
from theano import tensor as T
from numpy.linalg import inv
x = 2
print(x)
y = x**2
print(y)
# Theano symbolic... | <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: Testing variable assignment and operations in python
Step2: Extra
Step3: Simple Linear Regression
Step5: From linear regression using the mod... |
14,179 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cmcc', 'cmcc-esm2-hr5', 'ocean')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
14,180 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
!pip install qq-training-wheels auquan_toolbox --upgrade
from qq_training_wheels.momentum_trading import MomentumTradingParams
from backtester.trading_system import TradingSystem
from backtester.features.feature import Feature
import numpy as np
class ... | <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 import everything we need to run our backtesting algorithm
Step2: The class below implements all the logic you need to run the momentum b... |
14,181 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
14,182 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from __future__ import division
from matplotlib import pyplot as plt
import numpy as np
import pymc3 as pm
import scipy as sp
import seaborn as sns
from statsmodels.datasets import get_rdataset
from theano import tensor as tt
blue, *_ = sns.color_palette()
SEED = 513229... | <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 draw and plot samples from the stick-breaking process.
Step2: As stated above, as $\alpha \to \infty$, samples from the Dirichlet process co... |
14,183 | <ASSISTANT_TASK:>
Python Code:
OSMFILE = 'dataset/jakarta.osm'
%%writefile 02-codes/audit.py
import xml.etree.cElementTree as ET
from collections import defaultdict
import re
import pprint
from optparse import OptionParser
# OSMFILE = "sample.osm"
# OSMFILE = "example_audit.osm"
#In Indonesia, type first, then name. 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:
Step5: To audit the osm file, first we need to know the overview of the data.
Step7: This will save the jakarta osm that has been audited into jakarta... |
14,184 | <ASSISTANT_TASK:>
Python Code:
#Import libraries
import matplotlib.pyplot as plt
import mdtraj as md
import glob
import numpy as np
from msmbuilder.dataset import dataset
%pylab inline
#Import longest trajectory.
t = md.load("run0-clone138.h5")
frame = np.arange(len(t))[:, np.newaxis]
# Using 0.25 so that units are in... | <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 timestep for these simulations is 2 fs (can be found in /data/choderalab/fah/initial-models/projects/ABL1_HUMAN_D0_V1/RUN0/integrator.xml [s... |
14,185 | <ASSISTANT_TASK:>
Python Code:
# As usual, a bit of setup
from __future__ import print_function
import time
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.fc_net import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_... | <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: Dropout
Step2: Dropout forward pass
Step3: Dropout backward pass
Step4: Fully-connected nets with Dropout
Step5: Regularization experiment
|
14,186 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
#import tensorflow.contrib.learn.python.learn as learn
import tflearn
import scipy as sp
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from random import shuffle, randint
from sklearn.utils import shuffle as mutualShuf... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step9: Import and process data
Step10: Neural Network
Step11: Test accuracy of model(s)
Step12: What if the model hasn't seen data from the patient?... |
14,187 | <ASSISTANT_TASK:>
Python Code:
import os
import numpy as np
import mne
sample_data_folder = mne.datasets.sample.data_path()
sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
'sample_audvis_filt-0-40_raw.fif')
raw = mne.io.read_raw_fif(sample_data_raw_file)
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: Loading data
Step2: By default,
Step3:
Step4: Preprocessing
Step5: Once we're confident about which component(s) we want to remove, we pas... |
14,188 | <ASSISTANT_TASK:>
Python Code:
import ray
import ray.rllib.agents.ppo as ppo
from ray import serve
def train_ppo_model():
trainer = ppo.PPOTrainer(
config={"framework": "torch", "num_workers": 0},
env="CartPole-v0",
)
# Train for one iteration
trainer.train()
trainer.save("/tmp/rllib... | <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: Hiding and removing cells
Step2:
|
14,189 | <ASSISTANT_TASK:>
Python Code:
df.head()
hm = HeatMap(df, x=bins('mpg'), y=bins('displ'))
show(hm)
hm = HeatMap(df, x=bins('mpg'), y=bins('displ'), values='cyl', stat='mean')
show(hm)
hm = HeatMap(df, x=bins('mpg'), y=bins('displ', bin_count=15),
values='cyl', stat='mean')
show(hm)
hm = HeatMap(df, x=... | <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: 2D Binning
Step2: Binning and Aggregating Values
Step3: Specifying the Number of Bins
Step4: Mixing binning and non-binned data
Step5: The S... |
14,190 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.stats import kurtosis, skew
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import cm
import seaborn as sb
import sqlite3
%matplotlib inline
plt.rcParams['figure.figsize'] = (8,6)
plt.rc('axes', titlesize=18)
plt.rc('axes', labelsize=15)
s... | <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: Reading the Metadata SQL table
Step2: Exploring the Metadata tables
Step3: There are no missing values but that does not mean there are not an... |
14,191 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from pandas import DataFrame,read_csv
#Emplacement des compteurs avec la correspondance pour les noms dans les fichiers de comptage.
#http://donnees.ville.montreal.qc.ca/dataset/f170fecc-18db-44bc-b4fe-5b0b6d2c7297/resource/c7d0546a-a218-479e-bc9f-c... | <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. Charger des données
Step2: 2.1 Charger des colonnes spécifiques
Step3: 2.2 Charger une colonne en index
Step4: Dans cet exemple, en charga... |
14,192 | <ASSISTANT_TASK:>
Python Code:
# Useful Functions
def find_cointegrated_pairs(data):
n = data.shape[1]
score_matrix = np.zeros((n, n))
pvalue_matrix = np.ones((n, n))
keys = data.keys()
pairs = []
for i in range(n):
for j in range(i+1, n):
S1 = data[keys[i]]
S2 = ... | <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: Exercise 1
Step2: b. Cointegration Test II
Step3: Exercise 2
Step4: b. Real Cointegration Test II
Step5: Exercise 3
Step6: b. Testing the C... |
14,193 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('fivethirtyeight')
plt.rcParams['figure.figsize'] = (10, 6)
x = np.arange(-10, 10, 1)
y1 = (15 - x)/3
y2 = (2 - 2*x)/-1
plt.plot(x, y1)
plt.text(x[-1], y1[-1], 'row1')
plt.plot(x, y2)
plt.text(x[-1], y2[-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: Column-wise / Vectors (2x2)
Step2: Now we know the answer to this is a linear combination of the two vectors. So we multiply the first vector ... |
14,194 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from math import sqrt
import pprint
import matplotlib.pyplot as plt
import seaborn as sns
from sklea... | <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 required datasets
Step2: Cleaning and preparing the datasets
Step3: Randomly splitting the dataset into training and testing set... |
14,195 | <ASSISTANT_TASK:>
Python Code:
from googlefinance import getQuotes
import time
import json
import os
import sys
from IPython.display import clear_output
def buscar_accion(nombre_accion):
clear_output()
os.system('cls' if os.name=='nt' else 'clear')
print(json.dumps(getQuotes(nombre_accion), indent=2)... | <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: Paso 2
Step2: Paso 3
|
14,196 | <ASSISTANT_TASK:>
Python Code:
from classy import *
data=load_excel('data/iris.xls',verbose=True)
print(data.vectors.shape)
print(data.targets)
print(data.target_names)
print(data.feature_names)
subset=extract_features(data,[0,2])
plot2D(subset,legend_location='upper left')
C=SVM()
data_train,data_test=split(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: Load the Data
Step2: Look at the data
Step3: since you can't plot 4 dimensions, try plotting some 2D subsets
Step4: I don't want to do the cl... |
14,197 | <ASSISTANT_TASK:>
Python Code:
import venusar
import motif
import thresholds
import motifs
import activity
import tf_expression
import gene_expression
# to get code changes
import imp
imp.reload(motif)
motif_f_base='../../data/HOCOMOCOv10.JASPAR_FORMAT.TF_IDS.txt'
pc = 0.1
th = 0
bp = [0.25, 0.25, 0.25, 0.25]
moti... | <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 Motif Definitions
Step2: Convert to DataFrame for Analysis of Duplication
Step3: Move On
|
14,198 | <ASSISTANT_TASK:>
Python Code:
print('Number of apps in the dataset : ' , len(df))
df.sample(7)
# - Installs : Remove + and ,
df['Installs'] = df['Installs'].apply(lambda x: x.replace('+', '') if '+' in str(x) else x)
df['Installs'] = df['Installs'].apply(lambda x: x.replace(',', '') if ',' in str(x) else x)
df['Insta... | <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 Cleaning
Step2: Basic EDA
Step3: This is the basic exploratory analysis to look for any evident patterns or relationships between the fea... |
14,199 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import requests
import re
plt.style.use('ggplot')
import matplotlib
%matplotlib inline
# Download the data file from `puu.sh` and save it locally under `file_name`:
url = "http://puu.sh/oBCfW/c006093339.xlsx" # Script... | <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: Loading Dataset
Step2: Cleaning Data
Step3: Calculating New Parameters
Step4: a = {}
Step5: Notice the lack of IPOs following the popping of... |
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