Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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2,800 | <ASSISTANT_TASK:>
Python Code:
# test image stack
arr = []
for i in range(50):
b = np.random.rand(500,500)
b= (b*(2**16-1)).astype('uint16')
arr.append(b)
# snap (MPL)
button = widgets.Button(description='Snap')
display.display(button)
def on_button_clicked(b):
img=arr.pop()
plt.imshow(img, cma... | <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: Video
Step2: GUI and BUTTONS
Step3: Arrows
|
2,801 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
import urllib.request
import numpy as np
import simplejson as json
import pandas as pd
from netCDF4 import Dataset, date2num, num2date
import ipywidgets as widgets
from IPython.display import display, clear_output
import dateutil.parser
import matplotlib.pyplot as plt... | <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 ... |
2,802 | <ASSISTANT_TASK:>
Python Code:
# Installs the latest version of TFC compatible with the installed TF version.
!pip install tensorflow-compression~=$(pip show tensorflow | perl -p -0777 -e 's/.*Version: (\d\.\d).*/\1.0/sg')
# Downloads the 'models' directory from Github.
![[ -e /tfc ]] || git clone https://github.com/te... | <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: Enabling GPU
Step2: Imports and Definitions
Step3: Load files
Step4: Compress images
Step5: Show output
Step6: Download all compressed imag... |
2,803 | <ASSISTANT_TASK:>
Python Code:
# Importing standard libraries
import numpy as np
import pandas as pd
from ionchannelABC import IonChannelModel
icat = IonChannelModel('icat',
'models/Generic_iCaT.mmt',
vvar='membrane.V',
logvars=['environment.time',
... | <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: Setting up an ion channel model and experiments
Step2: Now that we have loaded a cell model, we need to specify how we will test it to compare ... |
2,804 | <ASSISTANT_TASK:>
Python Code:
# Author: Olaf Hauk <olaf.hauk@mrc-cbu.cam.ac.uk>
#
# License: BSD (3-clause)
import mne
from mne.datasets import sample
from mne.minimum_norm.resolution_matrix import make_inverse_resolution_matrix
from mne.minimum_norm.spatial_resolution import resolution_metrics
print(__doc__)
data_pat... | <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: EEGMEG
Step2: MEG
Step3: Visualization
Step4: For MEG only
Step5: Subtract the two distributions and plot this difference
Step6: These plot... |
2,805 | <ASSISTANT_TASK:>
Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', '..', 'notebook_format'))
from formats import load_style
load_style(plot_style=False)
os.chdir(path)
# 1. magic for inline 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: Evaluating Imbalanced Datasets
Step2: A brief description of the dataset based on the data overview section from the download source.
Step3: C... |
2,806 | <ASSISTANT_TASK:>
Python Code:
import argparse
import os
import matplotlib.pyplot as plt
from matplotlib.pyplot import imshow
import scipy.io
import scipy.misc
import numpy as np
import pandas as pd
import PIL
import tensorflow as tf
from keras import backend as K
from keras.layers import Input, Lambda, Conv2D
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:
Step2: Important Note
Step4: Expected Output
Step6: Expected Output
Step8: Expected Output
Step9: Expected Output
Step10: 3.1 - Defining classes, ... |
2,807 | <ASSISTANT_TASK:>
Python Code:
print('Hello)
1 / 0
open('doesnotexistfile.txt')
print(locals()['__builtins__'])
import sys
def divide(a,b):
try:
return a / b
except:
print(sys.exc_info()[0])
divide (1,2)
divide (2,0) # This will be captured by the 'except' clause
# print custom erro... | <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: Exceptions
Step2: Built-in Exceptions
Step3: Following are some of the built-in exceptions.
Step4: Catching Specific Exceptions
Step5: The l... |
2,808 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from neus import pyramid
from neus import partition
# instantiate a window object
center = [1.0]
width = [0.5]
win = pyramid.Pyramid(center, width)
# plot the support of the pyramid object
x = np.linspace(0.0, 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: Window objects
Step2: Partition objects
Step3: Partition objects act like callable lists so some of the expected list operations also work wit... |
2,809 | <ASSISTANT_TASK:>
Python Code:
import ibis
import os
hdfs_port = os.environ.get('IBIS_WEBHDFS_PORT', 50070)
hdfs = ibis.hdfs_connect(host='quickstart.cloudera', port=hdfs_port)
con = ibis.impala.connect(host='quickstart.cloudera', database='ibis_testing',
hdfs_client=hdfs)
print('Hello!')
tab... | <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: Projections
Step2: First, the basics
Step3: You can make a list of columns you want, too, and pass that
Step4: You can also use the explicit ... |
2,810 | <ASSISTANT_TASK:>
Python Code:
# import
from sklearn.cluster import KMeans, MiniBatchKMeans
from sklearn.linear_model import LogisticRegression
from sklearn import metrics
from sklearn.utils import shuffle
import mahotas as mh
from mahotas.features import surf
import glob
import numpy as np
import matplotlib.pyplot as ... | <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: Evaluating clusters
Step2: Image Quantization
Step3: Clustering to learn features
|
2,811 | <ASSISTANT_TASK:>
Python Code:
precipitation_df.head()
precipitation_df.tail()
precipitation_df['Country or Area'].values
precipitation_df = precipitation_df.set_index(precipitation_df["Country or Area"])
precipitation_df.drop(['Country or Area'], axis=1, inplace=True)
precipitation_df.head()
%matplotlib inline
ge... | <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: Each row in the table lists
Step2: Having the names of the countries or areas as a column comes in handy, but it would be more useful to have t... |
2,812 | <ASSISTANT_TASK:>
Python Code:
a = array([5,8,12,13,100,18,74])
print a
print "max:", a.max()
print "min: ", a.min()
print u"součet:", a.sum()
print u'dékla:', a.size
linspace(2,5,9)
linspace(0,5,4)
linspace(0,1,20)
arange(5)
arange(3,10)
arange(10,20,0.2)
zeros(5)
ones(20)
t=linspace(0,10,11)
print t
print t[1:5]
... | <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: linspace
Step2: arange
Step3: zeros, ones
Step4: Nejen výřezy
Step5: Ve výřezech lze prvky i přeskakovat
Step6: Výřez je možné použít i k p... |
2,813 | <ASSISTANT_TASK:>
Python Code:
lambda0 = 6301.5
JUp = 1.0
JLow = 1.0
gUp = 2.5
gLow = 0.0
lambdaStart = 6300.8
lambdaStep = 0.01
nLambda = 150
wavelength = lambdaStart + np.arange(nLambda) * lambdaStep
lineInfo = np.asarray([lambda0, JUp, JLow, gUp, gLow, lambdaStart, lambdaStep])
s = pymilne.milne(nLambda, lineInfo)
B... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Strong-field approximation Stokes V
Step2: Longitudinal magnetograph
Step3: Center-of-gravity
Step4: Influence of filling factor on inclinati... |
2,814 | <ASSISTANT_TASK:>
Python Code:
from mysolr import Solr
PDBE_SOLR_URL = "http://wwwdev.ebi.ac.uk/pdbe/search/pdb"
solr = Solr(PDBE_SOLR_URL, version=4)
UNLIMITED_ROWS = 10000000 # necessary because default in mysolr is mere 10
import logging, sys
#reload(logging) # reload is just a hack to make logging work in the noteb... | <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: Find your protein
Step2: Let us assume we are interested in carbonic anhydrases. We write the protein name as a regular expression allowing for... |
2,815 | <ASSISTANT_TASK:>
Python Code:
from fig_utils import *
import matplotlib.pyplot as plt
import time
%matplotlib inline
# Parameters
country_names = ['nigeria', 'tanzania', 'uganda', 'malawi', 'pooled']
country_paths = ['../data/output/LSMS/nigeria/',
'../data/output/LSMS/tanzania/',
'../... | <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: Out-of-country performance
Step2: Panel B
|
2,816 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
np
mylist = [3, 6, 1, 0, 10, 3]
mylist
print("The first element of 'mylist' is: " + str(mylist[0]))
print("The second element of 'mylist' is: " + str(mylist[1]))
myarray = np.array(mylist) # equivalent to np.array([3, 6, 1, 0, 10, 3])
myarray
# look at what type 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:
Step1: Now, we have access to all NumPy functions via the variable np (this is the convention in the Scientific Python community for referring to NumPy... |
2,817 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from simmit import smartplus as sim
from simmit import identify as iden
import os
dir = os.path.dirname(os.path.realpath('__file__'))
x = np.arange(0,182,2)
path_data = dir + '/data/'
peak_file = '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: In this Python Notebook we will show how to properly run a simulation of a composite material, providing the ODF (orientation density function) ... |
2,818 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mpi-m', 'mpi-esm-1-2-hr', 'toplevel')
# 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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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
2,819 | <ASSISTANT_TASK:>
Python Code:
np.random.seed(0)
data = np.random.randn(10, 10)
from ipywidgets import *
fig = plt.figure(padding_y=0.0)
grid_map = plt.gridheatmap(data)
fig
grid_map.display_format = ".2f"
grid_map.font_style = {"font-size": "16px", "fill": "blue", "font-weight": "bold"}
axes_options = {
"column"... | <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: Basic Heat map
Step2: Hide tick_labels and color axis using 'axes_options'
Step3: Non Uniform Heat map
Step4: Alignment of the data with resp... |
2,820 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scipy.sparse as sps
from porepy.numerics.ad.forward_mode import Ad_array
import porepy.numerics.ad.functions as af
x = Ad_array(2, 1)
y = x**2 + 3
print('y value is: ', y.val)
print('dy/dx is: ', y.jac)
h = af.exp(y)
print('h value is: ', h.val)
print('dh/dx ... | <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: Scalar AD-variables
Step2: We can now define a function $y=x^2 + 3$
Step3: To obtain the function value and the derivative we can call .val an... |
2,821 | <ASSISTANT_TASK:>
Python Code:
from lammps import IPyLammps
L = IPyLammps()
# 3d Lennard-Jones melt
L.units("lj")
L.atom_style("atomic")
L.atom_modify("map array")
L.lattice("fcc", 0.8442)
L.region("box block", 0, 4, 0, 4, 0, 4)
L.create_box(1, "box")
L.create_atoms(1, "box")
L.mass(1, 1.0)
L.velocity("all create", 1.4... | <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 initial state
Step2: Queries about LAMMPS simulation
Step3: Working with LAMMPS Variables
Step4: Accessing Atom data
Step5: Ac... |
2,822 | <ASSISTANT_TASK:>
Python Code:
from mpl_toolkits.mplot3d import Axes3D, axes3d
fig, ax = plt.subplots(1, 1, subplot_kw={'projection': '3d'})
X, Y, Z = axes3d.get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
plt.show()
from mpl_toolkits.axes_grid1 import AxesGrid
fig = plt.figure()
grid = AxesGrid... | <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: axes_grid1
Step2: This next feature is commonly requested on the mailing lists. The problem is that most people who request it don't quite kno... |
2,823 | <ASSISTANT_TASK:>
Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfil... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step3: The notMNIST dataset is too large for many computers to handle. It contains 500,000 images for just training. You'll be using a subset of this... |
2,824 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nasa-giss', 'sandbox-2', '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
<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... |
2,825 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2018 The TensorFlow Hub Authors. 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/LICENSE... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step3: 使用膨胀 3D CNN 进行动作识别
Step4: 使用 UCF101 数据集
Step5: 运行 ID3 模型并打印前 5 个动作预测。
Step6: 现在，尝试一个新的视频，地址为：https
|
2,826 | <ASSISTANT_TASK:>
Python Code:
import fb_scraper.prodcons
APP_ID = ''
APP_ID_SECRET = ''
ACCESS_TOKEN = ''
mgr = fb_scraper.prodcons.Manager(
access_token=ACCESS_TOKEN,
api_key=APP_ID,
api_secret=APP_ID_SECRET
)
mgr.graph.extend_token()
mgr.start()
mgr.scrape_post('XXXXXXXXXXXXXX') # Where 'XXXXXXX... | <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: Producer/Consummer Manager
Step2: Extending ACCESS_TOKEN
Step3: Start scraping threads
Step4: Add scraping jobs
|
2,827 | <ASSISTANT_TASK:>
Python Code:
# Q1. Create a graph
g = ...
with g.as_default():
# Define inputs
with tf.name_scope("inputs"):
a = tf.constant(2, tf.int32, name="a")
b = tf.constant(3, tf.int32, name="b")
# Ops
with tf.name_scope("ops"):
c = tf.multiply(a, b, name="c")
d ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Q4-8. You are to implement the graph below. Complete the code.
|
2,828 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
#%config InlineBackend.figure_format = 'svg'
#%config InlineBackend.figure_format = 'pdf'
import freqopttest.tst as tst
import kgof
import kgof.data as data
import kgof.density as density
import kgof.goftest as gof
import kgof.intertst... | <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: Test with random test locations
Step2: Test with optimized test locations
|
2,829 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
from scipy.interpolate import InterpolatedUnivariateSpline as spline
from pathlib import Path
%load_ext autoreload
%autoreload 2
hmcode_dir = Path("/home/steven/Documents/Projects/halos/HALOMOD/other-codes/HMcode")
def... | <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: Run HMcode
Step2: Make halomod model
Step3: The big picture (1h+2h)
Step4: Intermediate Products
Step5: Mass to Radius
Step6: sigma
Step7: ... |
2,830 | <ASSISTANT_TASK:>
Python Code:
ri = (40, 50, 60, 70, 80, 90, 100, 108)
ro = (40.7, 52.9, 69, 90.5, 123, 182, 305, 500)
Cq = (46.3, 47.0, 46.9, 47.0, 47.0, 47.0, 46.9, 46.9)
#Cq = (46.3, 49.5, 46.9, 49.5, 47.0, 51.7, 46.9, 54)
Cg = (1.5, 1.44, 1.47, 1.45, 1.46, 1.49, 1.42, 1.48)
Cgnd = (39.0... | <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... |
2,831 | <ASSISTANT_TASK:>
Python Code:
from oedes.fvm import mesh1d
from oedes import progressbar, testing, init_notebook, models, context
init_notebook()
%matplotlib inline
import matplotlib.pylab as plt
import numpy as np
params = {'T': 2500.,
'electron.mu': 1e-6,
'electron.energy': 0.,
'electr... | <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: Model and parameters
Step2: Results
Step3: Distribution of the electric field
Step4: Distribution of electrons and holes
Step5: Distribution... |
2,832 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import xarray as xr
import climlab
from climlab import constants as const
import cartopy.crs as ccrs # use cartopy to make some maps
ncep_url = "http://psl.noaa.gov/thredds/dodsC/Datasets/ncep.reanalysis.derived/"
ncep... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Make two maps
Step2: Make a contour plot of the zonal mean temperature as a function of time of year
Step3: Exploring the amplitude of the sea... |
2,833 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('..')
from synset2vec import Synset2Vec
from im2vec import Image2Vec
from tagger import ZeroshotTagger
i2v = Image2Vec()
s2v = Synset2Vec()
tagger = ZeroshotTagger()
labels = map(str.strip, open('../data/synsets_ilsvrc12_test1k.txt').readlines())
from PIL impo... | <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 the label set $Y_0$
Step2: 2. Load a pretrained CNN model
Step3: 3. Define a preprocess function for input images
Step4: 4. Perform zero... |
2,834 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import quandl
mydata = quandl.get("EIA/PET_RWTC_D")
mydata.head()
mydata.plot(figsize = (12, 6))
mydata = quandl.get("EIA/PET_RWTC_D",
returns = "numpy")
mydata = quandl.get("... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Make a Basic Data Call
Step2: Note that you need to know the "Quandl code" of each dataset you download. In the above example, it is "EIA/PET_R... |
2,835 | <ASSISTANT_TASK:>
Python Code:
# RUN THIS BLOCK FIRST TO SET UP VARIABLES!
a = True
b = False
x = 2
y = -2
cat = "Mittens"
print a
print (not a)
print (a == b)
print (a != b)
print (x == y)
print (x > y)
print (x = 2)
print (a and b)
print (a and not b)
print (a or b)
print (not b or a)
print not (b or a)
print (not ... | <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 might find it helpful to copy these variables somewhere you can easily see them when doing the problems. e.g. a piece of paper or a text... |
2,836 | <ASSISTANT_TASK:>
Python Code:
import math as m
def CountPairs(n ) :
cnt = 0
i = 1
while i * i <= n :
if(n % i == 0 ) :
div1 = i
div2 = n // i
sum = div1 + div2 ;
if(m . gcd(sum , n ) == 1 ) :
cnt += 1
i += 1
return cnt
n = 24
print(CountPairs(n ) )
<END_TASK>
| <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
|
2,837 | <ASSISTANT_TASK:>
Python Code:
row = 'NO PARKING (SANITATION BROOM SYMBOL) 7AM-7:30AM EXCEPT SUNDAY'
assert from_time(row) == '07:00AM'
assert to_time(row) == '07:30AM'
special_case1 = 'NO PARKING (SANITATION BROOM SYMBOL) 11:30AM TO 1PM THURS'
assert from_time(special_case1) == '11:30AM'
assert to_time(special_case1) ... | <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: Find out if any rows has NaN
Step2: Confirm that every row has from_time and to_time
Step3: Day of the week
Step4: Save to CSV
|
2,838 | <ASSISTANT_TASK:>
Python Code:
!python -V
#!pip3 install torch torchvision
import torch
print("PyTorch version: ")
torch.__version__
print("Device Name: ")
torch.cuda.get_device_name(0)
print("CUDA Version: ")
print(torch.version.cuda)
print("cuDNN version is: ")
print(torch.backends.cudnn.version())
# NVIDIA profiling... | <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 is a tensor?
Step2: Tensor Types
Step3: Every torch.Tensor has these attributes
Step4: Tensor datatypes are given in the table below. No... |
2,839 | <ASSISTANT_TASK:>
Python Code:
from shapely.geometry import Point, Polygon
# Create Point objects
p1 = Point(24.952242, 60.1696017)
p2 = Point(24.976567, 60.1612500)
# Create a Polygon
coords = [(24.950899, 60.169158), (24.953492, 60.169158), (24.953510, 60.170104), (24.950958, 60.169990)]
poly = Polygon(coords)
# Let'... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Let's check if those points are within the polygon
Step2: Okey, so we can see that the first point seems to be inside that polygon and the othe... |
2,840 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'Bike-Sharing-Dataset/hour.csv'
rides = pd.read_csv(data_path)
rides.head()
rides[:24*10].plot(x='dteday', y='cnt')
dummy_fields = ['seas... | <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 and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... |
2,841 | <ASSISTANT_TASK:>
Python Code:
!pip install Theano
!pip install lasagne
import numpy as np
def sum_squares(N):
return сумма квадратов чисел от 0 до N
%%time
sum_squares(10**8)
import theano
import theano.tensor as T
#будущий параметр функции
N = T.scalar("a dimension",dtype='int32')
#рецепт получения суммы квадрат... | <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: theano teaser
Step2: Как оно работает?
Step3: Компиляция
Step4: хинт для отладки
Step5: Для отладки желательно уменьшить масштаб задачи. Есл... |
2,842 | <ASSISTANT_TASK:>
Python Code:
import os
import csv
import cv2
import matplotlib.pyplot as plt
import random
import pprint
import numpy as np
from numpy import expand_dims
%tensorflow_version 1.x
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR)
from keras import backend as K
from keras.models import M... | <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: Confirm TensorFlow can see the GPU
Step2: Load the Dataset
Step3: Parse the CSV File
Step4: Clean and Pre-process the Dataset
Step5: Detect ... |
2,843 | <ASSISTANT_TASK:>
Python Code:
!pip3 install tensorflow_hub
%%bash
pip install --upgrade tensorflow
# Import helpful libraries and setup our project, bucket, and region
import os
import tensorflow as tf
import tensorflow_hub as hub
# PROJECT = "cloud-training-demos" # REPLACE WITH YOUR PROJECT ID
# BUCKET = "cloud-tra... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Now reset the notebook's session kernel! Since we're no longer using Cloud Dataflow, we'll be using the python3 kernel from here on out so don't... |
2,844 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
%matplotlib inline
pd.set_option('display.max_columns', 500)
df = sns.load_dataset('titanic')
# Write the code to look at the head of the dataframe
# Create a histogram to examine age distributi... | <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: Like scikit-learn, Seaborn has "toy" datasets available to import for exploration. This includes the Titanic data we have previously looked at. ... |
2,845 | <ASSISTANT_TASK:>
Python Code:
import WizardTree as wt
story = wt.CrawlComment(comment_id = "cy8z5uv")
wt.Export(story, "Output/WizardTree.json")
import WizardTree as wt
story = wt.Import("Output/WizardTree.json")
print "Title: " + story['title']
print "Author: " + story['author']
print "Url: " + story['url']
print "... | <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 story from JSON file
Step2: For the following examples, the variable story is assumed to contain the story
Step3: Visualize story structu... |
2,846 | <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: Estimators を使用するブースティング木
Step2: データセットはトレーニングセットと評価セットで構成されています。
Step3: トレーニングセットと評価セットには、それぞれ 627 個と 264 個の例があります。
Step4: 乗船者の大半は 20 代から 30 ... |
2,847 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import random
from collections import defaultdict
import mdtraj as md
import numpy as np
import scipy.cluster.hierarchy
stride = 5
subsampled = md.load('ala2.h5', stride=stride)
print(subsampled)
distances = np.empty((subsampled.n_frames, subsampled.... | <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: Compute the pairwise RMSD between all of the frames. This requires
Step2: Now that we have the distances, we can use out favorite clustering
St... |
2,848 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
pd.plotting.register_matplotlib_converters()
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
# Set up code checking
import os
if not os.path.exists("../input/fifa.csv"):
os.symlink("../input/data-for-datavis/fifa.csv", "../input/fifa.csv") ... | <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 code you just ran sets up the system to give you feedback on your work. You'll learn more about the feedback system in the next step.
Step ... |
2,849 | <ASSISTANT_TASK:>
Python Code:
from civis.ml import ModelPipeline
from civis import APIClient
client = APIClient()
# dynamically get database name
creds = client.credentials.list()
dbs = [db for db in find(creds, type='Database')
if 'redshift' in db.name.lower()]
db_name = dbs[0].name
model = ModelPipeline('ran... | <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: In the first example, we'll use a random forest model from scikit-learn. In addition, we'll grid search over hyperparameters for the maximum dep... |
2,850 | <ASSISTANT_TASK:>
Python Code:
import os
PROJECT = "cloud-training-demos" # REPLACE WITH YOUR PROJECT ID
BUCKET = "cloud-training-demos-ml" # REPLACE WITH YOUR BUCKET NAME
REGION = "us-central1" # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
# Do not change these
os.environ["PROJECT"] = PROJECT
os.environ["BUCKET"]... | <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: Create raw dataset
Step3: Create dataset for WALS
Step4: Creating rows and columns datasets
Step5: To summarize, you created the following da... |
2,851 | <ASSISTANT_TASK:>
Python Code:
import sys
import os
sys.path.append(os.getcwd()+'/../')
# our lib
from lib.resnet50 import ResNet50
from lib.imagenet_utils import preprocess_input, decode_predictions
#keras
from keras.preprocessing import image
from keras.models import Model
# sklearn
import sklearn
from sklearn.line... | <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: Extract NN Features
Step2: Predicting Own Labels from Selected Images
Step3: Horizontal Striped Data
Step4: neither the svm or the logistic r... |
2,852 | <ASSISTANT_TASK:>
Python Code:
%%javascript
IPython.OutputArea.prototype._should_scroll = function(lines) {
return false;
}
import datetime
import matplotlib.pyplot as plt
import pandas as pd
import talib
from talib.abstract import *
from talib import MA_Type
import pinkfish as pf
# Format price data
pd.options.dis... | <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: Some global data
Step2: Fetch symbol data from cache, if available.
Step3: Select timeseries between start and end.
Step4: Get info about TA-... |
2,853 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
dtype_dict = {'bathrooms':float, 'waterfront':int, 'sqft_above':int, 'sqft_living15':float,
'grade':int, 'yr_renovated':int, 'price':float, 'bedrooms':float, 'zipcode':str,
'long':float, 'sqft_lot15':float, 'sqft_living'... | <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: Useful pandas summary functions
Step2: As we see we get the same answer both ways
Step3: Aside
Step4: We can test that our function works by ... |
2,854 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from parcels import Field, FieldSet, ParticleSet, JITParticle, plotTrajectoriesFile, AdvectionRK4
import numpy as np
xdim, ydim = (10, 20)
Uflow = Field('U', np.ones((ydim, xdim), dtype=np.float32),
lon=np.linspace(0., 1e3, xdim, dtype=np.float32),
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Now, let's first define a zonal and meridional velocity field on a 1kmx1km grid with a flat mesh. The zonal velocity is uniform and 1 m/s, and t... |
2,855 | <ASSISTANT_TASK:>
Python Code:
import torch
import numpy as np
x = np.array([0, 1, 2, 3, 4]).astype('float32').reshape(-1,1)
y = x * 2 + 1
class Model(torch.nn.Module):
def __init__(self):
super(Model,self).__init__()
self.layer = torch.nn.Linear(1,1)
def forward(self, x):
return self.l... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Detail version with monitoring variables
Step2: Compatible version
Step3: GPU Version
Step4: GPU인지 CPU인지 검사
|
2,856 | <ASSISTANT_TASK:>
Python Code:
!pip install git+https://github.com/google/starthinker
from starthinker.util.configuration import Configuration
CONFIG = Configuration(
project="",
client={},
service={},
user="/content/user.json",
verbose=True
)
FIELDS = {
'auth_read':'user', # Credentials used for writing... | <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. Set Configuration
Step2: 3. Enter DV360 User Audit Recipe Parameters
Step3: 4. Execute DV360 User Audit
|
2,857 | <ASSISTANT_TASK:>
Python Code:
# Author: Hicham Janati <hicham.janati@inria.fr>
#
# License: MIT License
import numpy as np
import matplotlib.pylab as pl
import ot
# necessary for 3d plot even if not used
from mpl_toolkits.mplot3d import Axes3D # noqa
from matplotlib.collections import PolyCollection
# parameters
n =... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Generate data
Step2: Plot data
Step3: Barycenter computation
Step4: Barycentric interpolation
|
2,858 | <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
<END_TASK>
<USER_TASK:>
Description:
Step1: Language Translation
Step3: Explore the Data
Step6: Implement Preprocessing Function
Step8: Preprocess all the data and save it
Step10: Chec... |
2,859 | <ASSISTANT_TASK:>
Python Code:
# Imports
from sklearn import metrics
from sklearn.tree import DecisionTreeClassifier
import pandas as pd
# Training Data
training_raw = pd.read_table("../data/training_data.dat")
df_training = pd.DataFrame(training_raw)
# test Data
test_raw = pd.read_table("../data/test_data.dat")
df_tes... | <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: and again.
Step2: one more time
Step3: We see that the results are not the same. This is because the Decision Tree Classifier chooses a featu... |
2,860 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.read_excel("H-2B_Disclosure_Data_FY15_Q4.xlsx")
df.head()
#df.info()
df['CASE_NUMBER'].count()
df['NBR_WORKERS_REQUESTED'].sum()
df.groupby('FULL_TIME_POSITION')['NBR_WORKERS_REQUESTED'].sum()
df['NBR_WORKER... | <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. How many requests did the Office of Foreign Labor Certification (OFLC) receive in 2015?
Step2: 2. How many jobs did that regard in total? An... |
2,861 | <ASSISTANT_TASK:>
Python Code:
import tarfile
# 檔案名稱格式
filename_format="M06A_{year:04d}{month:02d}{day:02d}.tar.gz".format
xz_filename_format="xz/M06A_{year:04d}{month:02d}{day:02d}.tar.xz".format
csv_format = "M06A/{year:04d}{month:02d}{day:02d}/{hour:02d}/TDCS_M06A_{year:04d}{month:02d}{day:02d}_{hour:02d}0000.csv".f... | <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: 利用 pandas 來處理資料
Step2: csv 欄位依照手冊設定
Step3: 查看一下內容
|
2,862 | <ASSISTANT_TASK:>
Python Code:
from sklearn.feature_extraction.text import CountVectorizer
# Create a list of text documents:
text = ["The quick brown fox jumped over the lazy dog."]
# Create the transform:
vectorizer = CountVectorizer()
# Tokenize and build vocabulary:
vectorizer.fit(text)
# Summarize:
print("vectoriz... | <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: Above, you can see that we access the vocabulary to see what exactly was tokenized by calling
Step2: We can see that all words were made lowerc... |
2,863 | <ASSISTANT_TASK:>
Python Code:
# NOTE: we use non-random initializations for the cluster centers
# to make autograding feasible; normally cluster centers would be
# randomly initialized.
data = np.load('data/X.npz')
X = data['X']
centers = data['centers']
print ('X: \n' + str(X))
print ('\ncenters: \n' + str(center... | <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: Also, take a look at the imported functions k_means
Step4: This is the function you will run in Part C once you have completed the helper funct... |
2,864 | <ASSISTANT_TASK:>
Python Code:
import csv
data = {}
with open("songdata.csv") as file:
for author,_,_,lyric in csv.reader(file):
data[author] = data.get(author,{})
for word in set(lyric.lower().split()):
data[author][word] = data[author].get(word,0) + 1
data["ABBA"]
import re
# ht... | <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: Algo que no hicimos durante la clase, pero que si hay que hacer, es sacar las palabras que no nos dan informacion. Otra cosa que habria que hace... |
2,865 | <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: TensorFlowアドオンのコールバック：TimeStopping
Step2: データのインポートと正規化
Step3: シンプルなMNIST CNNモデルの構築
Step4: シンプルなTimeStoppingの使用法
|
2,866 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# Common imports
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn.linear_model as skl
from sklearn.metrics import mean_squared_error
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import Mi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Simple preprocessing examples, breast cancer data and classification, Support Vector Machines
Step2: More on Cancer Data, now with Logistic Reg... |
2,867 | <ASSISTANT_TASK:>
Python Code:
target = pd.read_csv('../data/train_target.csv')
target.describe()
target = target / 1000
logtarget = np.log1p(target)
def read():
Read training and test data and return a dataframe with ['Dataset','Id'] multi-index
raw_train = pd.read_csv('../data/train_prepared_light.csv'... | <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 sale price is in hte hundreds of thousands, so let's divide the price by 1000 to get more manageable numbers.
Step3: Merge the training and... |
2,868 | <ASSISTANT_TASK:>
Python Code:
# This is an inline comment: Python3
print('hello world')
# Python2
print 'hello world'
1 * 1.0
a = 3
type(a)
b = 3 > 5
print(b), type(b)
L = ['red', 'blue', 'green', 'black', 'white']
print(L)
L[1], L[3:], L[3:15]
L[1] = 'yellow'
print(L)
T = ('red', 'black')
T[1] = 'yellow'
print(L... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Basic Types
Step2: Let us now turn to containers
Step3: Lists are mutable objects, i.e. they can be changed.
Step4: What is an example of an ... |
2,869 | <ASSISTANT_TASK:>
Python Code:
from poppy.creatures import Poppy4dofArmMini
mini_dof = Poppy4dofArmMini()
for m in mini_dof.motors:
m.compliant = False
m.goto_position(0,1)
for m in mini_dof.motors:
m.pid=(4,1,0.1)
mini_dof.m3.goto_behavior= 'minjerk'
mini_dof.m3.goto_behavior
from pypot.primitive 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: With the goto_position method, you can set an angle and a time. But you can not be absolutely sure that the position will be effectively reach. ... |
2,870 | <ASSISTANT_TASK:>
Python Code:
gPlayers = [ 'X', 'O' ]
gStart = tuple( tuple(' ' for col in range(3)) for row in range(3) )
gStart
def to_list(State):
return [list(row) for row in State]
def to_tuple(State):
return tuple(tuple(row) for row in State)
def empty(Board):
return [ (row, col) for row in ran... | <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: In the following naive implementation, states are represented as tuples of tuples of strings. The game starts with an empty board. An empty fi... |
2,871 | <ASSISTANT_TASK:>
Python Code:
import toytree
# get a random tree with 10 tips
tree1 = toytree.rtree.unittree(ntips=10, seed=123)
# draw tree with admixture from node 2 to 3
tree1.draw(ts='s', admixture_edges=(2, 3));
# draw tree with admixture from tip r2 to ancestor of r4,r5
tree1.draw(ts='s', admixture_edges=('r2',... | <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: Quick example
Step2: Styling admixture edges
Step3: Admixture timing
Step4: Admixture edge style
Step5: Label
Step6: Parsing SNAQ newick fo... |
2,872 | <ASSISTANT_TASK:>
Python Code:
import torch
x = torch.Tensor(5, 3)
print(x)
import torch
from torch.autograd import Variable
# N is batch size; D_in is input dimension;
# H is hidden dimension; D_out is output dimension.
N, D_in, H, D_out = 64, 1000, 100, 10
# Create random Tensors to hold inputs and outputs, and wra... | <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: Tutorial
Step2: nn module
Step3: https
Step4: Quickstart
|
2,873 | <ASSISTANT_TASK:>
Python Code:
# Import numpy
import numpy as np
# Define T and g
T = 40
y0 =50
g = 0.01
# Compute yT using the direct approach and print
yT = (1+g)**T*y0
print('Direct approach: ',yT)
# Initialize a 1-dimensional array called y that has T+1 zeros
y = np.zeros(T+1)
# Set the initial value of y to eq... | <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: matplotlib
Step2: Next, we want to make sure that the plots that we create are displayed in this notebook. To achieve this we have to issue a c... |
2,874 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import sys
# local api/python3 path - adjust path for your system
japipath = 'C:\\j64\\j64-807\\addons\\api\\python3'
if japipath not in sys.path:
sys.path.append(japipath)
sys.path
import jbase as j
print(j.__doc__)
# start J - only one instance currently allowed... | <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: Configure the J Python3 addon
Step2: Character data is passed as bytes.
Step3: j.j() enters a simple REPL
Step4: J accepts a subset of NumPy ... |
2,875 | <ASSISTANT_TASK:>
Python Code:
from py2cytoscape.data.cynetwork import CyNetwork
from py2cytoscape.data.cyrest_client import CyRestClient
from py2cytoscape.data.style import StyleUtil
import py2cytoscape.util.cytoscapejs as cyjs
import py2cytoscape.cytoscapejs as renderer
import networkx as nx
import pandas as pd
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: Long Description
Step2: With py2cytoscape
Step3: Status
Step4: Creating empty networks
Step5: Load networks from files, URLs or web services... |
2,876 | <ASSISTANT_TASK:>
Python Code:
# Load libraries
from sklearn import linear_model, datasets
# Load data
iris = datasets.load_iris()
X = iris.data
y = iris.target
# Create cross-validated logistic regression
clf = linear_model.LogisticRegressionCV(Cs=100)
# Train model
clf.fit(X, y)
<END_TASK> | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Load Iris Dataset
Step2: Use Cross-Validation To Find The Best Value Of C
|
2,877 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
print np.linspace(0,9,10), np.exp(-np.linspace(0,9,10))
# This line configures matplotlib to show figures embedded in the notebook,
# instead of opening a new window for each figure. More about that later.
# If you are using an old version of IPython, try using '%pyl... | <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: Balance bewteen 'speed' (Beta-coefficient) and 'momentum' of the learning
Step2: Minimize An Expression
Step3: Here is a summary
Step4: Cauti... |
2,878 | <ASSISTANT_TASK:>
Python Code:
!conda install boto3 --yes
import logging
logging.basicConfig(level=logging.INFO)
log = logging.getLogger(__name__)
from pyspark.sql.types import *
def create_struct(schema):
Take a JSON schema and return a pyspark StructType of equivalent structure.
replace_definitions(sc... | <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:
Step4: We create the pyspark datatype for representing the crash data in spark. This is a slightly modified version of peterbe/crash-report-struct-code... |
2,879 | <ASSISTANT_TASK:>
Python Code:
import graphlab
sales = graphlab.SFrame('../Data/kc_house_data.gl/')
from math import log, sqrt
sales['sqft_living_sqrt'] = sales['sqft_living'].apply(sqrt)
sales['sqft_lot_sqrt'] = sales['sqft_lot'].apply(sqrt)
sales['bedrooms_square'] = sales['bedrooms']*sales['bedrooms']
# In the 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: Load in house sales data
Step2: Create new features
Step3: Squaring bedrooms will increase the separation between not many bedrooms (e.g. 1) a... |
2,880 | <ASSISTANT_TASK:>
Python Code:
import os
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install --upgrade google-cloud-aiplatform $USER_FLAG
! pip3 install -U google-cloud-storage $USER_FLAG
if os.getenv("IS_TESTING"):
!... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Step3: Before you begin
Step4: Region
Step5:... |
2,881 | <ASSISTANT_TASK:>
Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
%matplotlib inline
%pylab inline
pylab.rcParams[... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Let's generate the datasets
Step2: Let's generate the test dataset, also
Step3: Let's train a predictor with the same hyperparameters as for t... |
2,882 | <ASSISTANT_TASK:>
Python Code:
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
DON'T MODIFY ANYTHING IN THIS CELL
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
DON'T MODIFY ANYTHING IN THIS CELL
%m... | <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: Face Generation
Step3: Explore the Data
Step5: CelebA
Step7: Preprocess the Data
Step10: Input
Step13: Discriminator
Step16: Generator
Ste... |
2,883 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.array([1, 2, 3]) # Create a rank 1 array
print(type(a)) # Prints "<type 'numpy.ndarray'>"
print(a.shape) # Prints "(3,)"
print(a[0], a[1], a[2]) # Prints "1 2 3"
a[0] = 5 # Change an element of the array
print(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: As you can see, we can easily access all this information. One-dimensional arrays in NumPy can be used to represent vectors, while two-dimension... |
2,884 | <ASSISTANT_TASK:>
Python Code:
def secondary_polygon(Angle ) :
edges_primary = 360 // Angle
if edges_primary >= 6 :
edges_max_secondary = edges_primary // 2
return edges_max_secondary + 3
else :
return "Not ▁ Possible "
if __name__== ' __main __' :
Angle = 45
print(secondary_polygon(Angle ) )... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
2,885 | <ASSISTANT_TASK:>
Python Code:
one_to_ten = [1,2,3,4,5,6,7,8,9,10]
print one_to_ten
one_to_ten = []
one_to_ten.append(1)
print one_to_ten
one_to_ten.append(2)
print one_to_ten
one_to_ten.append(3)
print one_to_ten
one_to_ten.append(4)
print one_to_ten
one_to_ten.append(5)
print one_to_ten
one_to_ten.append(6)
print on... | <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: This is great, because now we can remember values that our sensors returned at specific instances of time. There are many operations we can use ... |
2,886 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
from math import sqrt
import sys
from bokeh.plotting import figure, show, ColumnDataSource, save
from bokeh.models import Range1d, HoverTool
from bokeh.io import output_notebook, output_file
import quandl
from gurobipy import *
# output_notebook() #T... | <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: First of all, we need some data to proceed. For that purpose we use Quandl. First, you're going to need the quandl package. This isn't totally n... |
2,887 | <ASSISTANT_TASK:>
Python Code:
import sys, os
# verbose = os.environ.get('RADICAL_PILOT_VERBOSE', 'REPORT')
os.environ['RADICAL_PILOT_VERBOSE'] = 'ERROR'
from adaptivemd import Project
project = Project('test')
from adaptivemd import LocalCluster AllegroCluster
resource_id = 'local.jhp'
if resource_id == 'local.jhp... | <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 want to stop RP from reporting all sorts of stuff for this example so we set a specific environment variable to tell RP to do so. If you want... |
2,888 | <ASSISTANT_TASK:>
Python Code:
import sys
import pandas as pd
import numpy as np
ALL = -1
# DEBUG = True
DEBUG = False
##============================================================
# Data file format:
# * tab-delimited input file
# * 1st line: dimension names and the last dimension is assumed to be the measure
# * re... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Now we can implement the buc_rec() algorithm and test it.
Step2: With the following pivot table, we can easily see the output is correct (i.e.,... |
2,889 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csir-csiro', 'sandbox-1', 'atmos')
# 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... |
2,890 | <ASSISTANT_TASK:>
Python Code:
# Pipeline class
from quantopian.pipeline import Pipeline
def make_pipeline():
# Create and return an empty Pipeline
return Pipeline()
# Import Pipeline class and USEquityPricing dataset
from quantopian.pipeline import Pipeline
from quantopian.pipeline.data import EquityPricing
f... | <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 add an output to our pipeline we need to include a reference to a dataset, and specify the computations we want to carry out on that data. Fo... |
2,891 | <ASSISTANT_TASK:>
Python Code:
import os
from nipype import Workflow, Node, Function
def sum(a, b):
return a + b
wf = Workflow('hello')
adder = Node(Function(input_names=['a', 'b'],
output_names=['sum'],
function=sum),
name='a_plus_b')
adder.inputs.a = 1
ad... | <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: Creating Workflow with one Node that adds two numbers
Step2: Creating a second node and connecting to the hello Workflow
Step3: And we can che... |
2,892 | <ASSISTANT_TASK:>
Python Code:
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["2006":]
evap = pd.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: 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... |
2,893 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from shapely.geometry import Point
from geopandas import datasets, GeoDataFrame, read_file
# NYC Boros
zippath = datasets.get_path('nybb')
polydf = read_file(zippath)
# Generate some points
b = [int(x) for x in polydf.total_bounds]
N = 8
pointdf = GeoDataFrame([
{'g... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Joins
Step2: We're not limited to using the intersection binary predicate. Any of the Shapely geometry methods that return a Boolean can be use... |
2,894 | <ASSISTANT_TASK:>
Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
import os
# TODO 1
PROJECT_ID = "cloud-training-demos" # Replace with your PROJECT
BUCKET = PROJECT_ID
REGION = 'us-central1'
os.environ["PROJECT_ID"] = PROJECT_ID
os.environ["BUCKET"] = BUCKET
!mkdir train
!touch trai... | <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: Next we will configure our environment. Be sure to change the PROJECT_ID variable in the below cell to your Project ID. This will be the project... |
2,895 | <ASSISTANT_TASK:>
Python Code:
import rebound
import numpy as np
def test_case():
sim = rebound.Simulation()
sim.integrator = 'whfast'
sim.add(m=1.) # add the Sun
sim.add(m=3.e-6, a=1.) # add Earth
sim.move_to_com()
sim.dt = 0.2
return sim
sim = test_case()
sim.integrator_whfast_safe_mode =... | <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: By default WHFast synchronizes and recalculates the Jacobi coordinates from the inertial ones every timestep. This guarantees that the user alw... |
2,896 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nerc', 'sandbox-2', 'atmoschem')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
2,897 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
from IPython.display import HTML
from ipywidgets import interact
HTML('../style/code_toggle.html')
def loop_DFT(x):
Implementin... | <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 section specific modules
Step3: 2.8. The Discrete Fourier Transform (DFT) and the Fast Fourier Transform (FFT)<a id='math
Step5: Althou... |
2,898 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import matplotlib as mpl
import matplotlib.pyplot as plt
plt.style.use('ggplot')
import numpy as np
from sympy import *
init_printing()
def linear_rgb(x):
return ((x+0.055)/1.055)**2.4
x = Symbol('x', real=True)
serie... | <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 following is the conversion from RGB to linear RGB (aka. gamma-correction), where I'm dropping the conditional part for very small values of... |
2,899 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pycomlink as pycml
import xarray as xr
from tqdm import tqdm
import urllib.request
import io
import pycomlink.processing.blackout_gap_detection as blackout_detection
# Do show xarray.Dataset representation as text because gitlab/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: CMLs with more than 35 minutes of blackout within the 10-day example data
Step2: Investiagte blackouts for two CMLs over three years
Step3: Th... |
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