Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
|---|---|---|
3,900 | <ASSISTANT_TASK:>
Python Code:
np.random.seed(0)
data = np.random.randn(10, 10)
col_sc = ColorScale()
grid_map = GridHeatMap(color=data, scales={'color': col_sc})
Figure(marks=[grid_map], padding_y=0.0)
x_sc, y_sc, col_sc = OrdinalScale(), OrdinalScale(reverse=True), ColorScale()
grid_map = GridHeatMap(color=data, 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:
Step1: Basic Heat map
Step2: Heat map with axes
Step3: Non Uniform Heat map
Step4: Alignment of the data with respect to the grid
Step5: By default... |
3,901 | <ASSISTANT_TASK:>
Python Code:
#for ronum in ranumlis:
# print ronum
randict = dict()
othgues = []
othlow = 0
othhigh = 9
for ranez in range(10):
randxz = random.randint(othlow, othhigh)
othgues.append(randxz)
othlow = (othlow + 10)
othhigh = (othhigh + 10)
#print othgues
tenlis = ['zero', '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: Makes dict with keys pointing to the 10s numbers.
|
3,902 | <ASSISTANT_TASK:>
Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
# Para visualização de gráficos
from pylab import *
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels as st
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: Statsmodels
Step2: Time-Series Analysis
|
3,903 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
lengths = [4, 3, 5, 2]
def g(lengths):
lengths_transposed = tf.expand_dims(lengths, 1)
range = tf.range(0, 8, 1)
range_row = tf.expand_dims(range, 0)
mask = tf.less(range_row, lengths_transposed)
result = tf.where(mask, tf.ones([4, 8]), tf.zeros... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
|
3,904 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2019 Google Inc. 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-2.0
#
# Unless ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step4: Define training and evaluation functions
Step5: Train and evaluate the model locally
Step6: Export the model using the joblib library
Step7: ... |
3,905 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")
import pandas as pd
names = ['Position','I','J','H','K_s','[3.6]','[4.5]','[5.8]','[8.0]','A_v','Luminosity']
link = 'http://iopscience.iop.org/0004-637X/720/2/1374/suppdata/apj363663t2_ascii.txt'
harve... | <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: Table 2 - Photometry of Selected Candidates
Step2: Data cleaning.
Step3: Split [value +or- error] into separate columns
Step4: Split the posi... |
3,906 | <ASSISTANT_TASK:>
Python Code:
skieval2d_periodic = pd.read_excel(SUBDIR+"ski-eval_2d_periodic_abridged.xlsx")
skieval2d_periodic
ax1 = skieval2d_periodic.ix[skieval2d_periodic['inch']==1].plot.area(x="m/s",y="drag",color="Red",label="1 in")
ax2 = skieval2d_periodic.ix[skieval2d_periodic['inch']==2].plot.area(x="m/s",... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Then I can immediately make some quick plots. For instance, for each width in inch, I can plot drag or lift vs. velocity (m/s)
|
3,907 | <ASSISTANT_TASK:>
Python Code:
def f(x):
Function to compute the value of 5x+2
return 5*x+2
f(3)
lambda x: 5*x+2
g = lambda x: 5*x+2
g(3)
# Calculating Harmonic Mean using lambda function
harmonic_mean = lambda x,y,z : 3/(1/x + 1/y + 1/z)**0.5
harmonic_mean(1,2,3)
# Sorting a List by thr last name using lam... | <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: Elements of Functional Programming in Python
Step2: Now we would compute the same expression using Lambda functions. To create a lambda express... |
3,908 | <ASSISTANT_TASK:>
Python Code:
# Import all necessary libraries, this is a configuration step for the exercise.
# Please run it before the simulation code!
import numpy as np
import matplotlib.pyplot as plt
from gll import gll
from lagrange1st import lagrange1st
from flux_hetero import flux
# Show the plots in the Note... | <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. Initialization of setup
Step2: 2. Elemental Mass and Stiffness matrices
Step3: 3. Flux Matrices
Step4: 4. Discontinuous Galerkin Solution
|
3,909 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csir-csiro', 'vresm-1-0', '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
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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... |
3,910 | <ASSISTANT_TASK:>
Python Code:
%run ~/Dropbox/pythonCode/LCSanalyzeblue.py
t = s.galfitflag & s.lirflag & s.sizeflag & ~s.agnflag & s.sbflag
galfitnogim = t & ~s.gim2dflag
sum(galfitnogim)
s.s.ISDSS[galfitnogim]
print sum(s.s.ISDSS[galfitnogim] == -1)
galfitsdssnogim = galfitnogim & (s.s.ISDSS != -1)
sum(galfitsdssno... | <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: Galaxies not in SDSS phot catalog
Step2: Galaxies in SDSS but no B/T fit
Step3: Download SDSS Images
Step4: NSAID 69538 (244.060699, 34.2584... |
3,911 | <ASSISTANT_TASK:>
Python Code:
# Numpy, JAX, Matplotlib and h5py should all be correctly installed and on the python path.
from __future__ import print_function, division, absolute_import
import datetime
import h5py
import jax.numpy as np
from jax import random
from jax.experimental import optimizers
from jax.config 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: Preliminaries - notes on using JAX
Step2: Load the data
Step3: Plot examples and statistics about the integrator RNN data.
Step4: The goal of... |
3,912 | <ASSISTANT_TASK:>
Python Code:
print(__doc__)
import numpy as np
np.random.seed(123)
import matplotlib.pyplot as plt
from skopt.benchmarks import branin as _branin
def branin(x, noise_level=0.):
return _branin(x) + noise_level * np.random.randn()
from matplotlib.colors import LogNorm
def plot_branin():
fig, ax... | <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: Toy model
Step2: This shows the value of the two-dimensional branin function and
Step3: Note that this can take a few minutes.
|
3,913 | <ASSISTANT_TASK:>
Python Code:
from dcgpy import expression_gdual_vdouble as expression
from dcgpy import kernel_set_gdual_vdouble as kernel_set
from pyaudi import gdual_vdouble as gdual
from matplotlib import pyplot as plt
import numpy as np
from numpy import sin, cos
from random import randint, random
np.seterr(all='... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: We consider a set of differential equations in the form
Step2: We define 50 random control of points where we check that the prime integral hol... |
3,914 | <ASSISTANT_TASK:>
Python Code:
bigfile = open('/Users/chengjun/百度云同步盘/Writing/OWS/ows-raw.txt', 'rb')
chunkSize = 1000000
chunk = bigfile.readlines(chunkSize)
print len(chunk)
with open("/Users/chengjun/GitHub/cjc/data/ows_tweets_sample.txt", 'w') as f:
for i in chunk:
f.write(i)
with open("/Users/chengj... | <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. 清洗错行的情况
Step2: 问题： 第一行是变量名
Step3: 如何来处理错误换行情况？
Step4: 3. 读取数据、正确分列
Step5: 4. 统计数量
Step6: 5. 清洗tweets文本
Step7: 安装twitter_text
Step8: 获得... |
3,915 | <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: カスタムレイヤー
Step2: レイヤー：有用な演算の共通セット
Step3: 既存のレイヤーのすべての一覧は、ドキュメントを参照してください。Dense（全結合レイヤー）、Conv2D、LSTM、BatchNormalization、Dropoutなどのたくさんのレイヤーが含まれて... |
3,916 | <ASSISTANT_TASK:>
Python Code:
import string
def norm_words(words):
words = words.lower().translate(None, string.punctuation)
return words
jeopardy["clean_question"] = jeopardy["Question"].apply(norm_words)
jeopardy["clean_answer"] = jeopardy["Answer"].apply(norm_words)
jeopardy.head()
def norm_value(value):
... | <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: Normalizing columns
Step2: Answers in questions
Step3: Only 0.6% of the answers appear in the questions itself. Out of this 0.6%, a sample of ... |
3,917 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License"); { display-mode: "form" }
# 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 l... | <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: 階乗混合
Step2: TFP を使ってガウス分布の階乗混合を構築する
Step3: tfd.Independent を使用しているところに注意してください。この「meta-distribution」は reduce_sum を、右端の reinterpreted_batch_ndi... |
3,918 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
df = pd.DataFrame({'Date':['2019-01-01','2019-02-08','2019-02-08', '2019-03-08']})
df['Date'] = pd.to_datetime(df['Date'])
df['Date'] = df['Date'].dt.strftime('%d-%b-%Y')
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Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
|
3,919 | <ASSISTANT_TASK:>
Python Code:
import os
from dotenv import load_dotenv, find_dotenv
# find .env automagically by walking up directories until it's found
dotenv_path = find_dotenv()
# load up the entries as environment variables
load_dotenv(dotenv_path)
PROJECT_DIR = os.path.dirname(dotenv_path)
RAW_DATA_DIR = PROJECT... | <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 some environment variables
Step2: Importing pandas and matplotlib.pyplot
Step3: Reading a file in Pandas
|
3,920 | <ASSISTANT_TASK:>
Python Code:
import folium
m = folium.Map([45, 0], zoom_start=4)
folium.Marker([45, -30], popup="inline implicit popup").add_to(m)
folium.CircleMarker(
location=[45, -10],
radius=25,
fill=True,
popup=folium.Popup("inline explicit Popup"),
).add_to(m)
ls = folium.PolyLine(
locations... | <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: Vega Popup
Step3: Fancy HTML popup
Step5: You can also put any HTML code inside of a Popup, thaks to the IFrame object.
Step6: Note that you ... |
3,921 | <ASSISTANT_TASK:>
Python Code:
from ipynb.fs.full.article_quality.db_monthly_stats import DBMonthlyStats, dump_aggregation
import configparser
config = configparser.ConfigParser()
config.read('../settings.cfg')
import os
def write_once(path, write_to):
if not os.path.exists(path):
print("Writing out " + p... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Read the configuration
Step2: Utility to make sure we only generate files once
Step3: Dump the monthly aggregations
|
3,922 | <ASSISTANT_TASK:>
Python Code:
import random
def rnd(n):
return [random.uniform(-1, 1) for _ in range(n)]
SHOTS = 5000
x = rnd(SHOTS)
y = rnd(SHOTS)
def pairs(seq1, seq2):
yes1, yes2, no1, no2 = [], [], [], []
for a, b in zip(seq1, seq2):
if (a*a + b*b)**.5 <= 1:
yes1.append(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: Now we can select coordinate pairs inside the circle
Step2: We now plot the shots inside the circle in blue, outside in red
Step3: We can now ... |
3,923 | <ASSISTANT_TASK:>
Python Code:
# Test here the my_auth implementation.
def my_auth(username, password,required_scopes=None):
An dummy authentication function.
:params: username, the username
:params: password, the password
:params: scopes, the scope
:returns: `{"sub": username, "scope": ... | <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: Authorization & securitySchemes
Step3: Add user support in get_echo
Step4: Test the my_auth implementation
Step6: Bearer token & JWT Security... |
3,924 | <ASSISTANT_TASK:>
Python Code:
# import packages
import pandas as pd # data management
import matplotlib.pyplot as plt # graphics
import datetime as dt # check today's date
import sys # check Python version
# IPython command, puts plots in notebook ... | <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: Question 0
Step3: Question 2
Step4: Question 3
Step5: Changed cell to Markdown with menu at top
Step6: Question 5
Step7: Question 6
Step8:... |
3,925 | <ASSISTANT_TASK:>
Python Code:
from __future__ import print_function
import sys
sys.path.append('../')
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import seaborn as sns
from hopfield import Hopfield
%matplotlib inline
sns.set(font_scale=2.0)
prng = np.random.RandomState(see... | <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: Dependency in how many states are added
Step2: We generate two random patterns and test whether the field (h) is dependent on the initial state... |
3,926 | <ASSISTANT_TASK:>
Python Code:
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import time
from tensorflow.python.client import timeline
%matplotlib inline
FLAGS = tf.app.flags.FLAGS
... | <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: mnist_loader
Step3: Test mnist data
Step4: We are generating synthetic data in this project, so all the 55000 samples can be used for training... |
3,927 | <ASSISTANT_TASK:>
Python Code:
from babi_loader import BabiDataset, pad_collate
from torch.utils.data import DataLoader
# There are 20 tasks, we should control which task we would like to load
task_id = 1
dataset = BabiDataset( task_id )
dataloader = DataLoader(dataset, batch_size=4, shuffle=False, collate_fn=pad_colla... | <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: 好了，现在我们导入了dataloader之后，可以尝试将每一个batch的数据打印出来看看是什么样子的
Step2: 可以看到，打印出来的都是数字索引，不是真实的文本，所以我们在输出之前，肯定需要对这些索引进行重新映射，找回原来的文本信息，我们先看一下查找表
Step3: 好了，根据... |
3,928 | <ASSISTANT_TASK:>
Python Code:
!python --version
!cat ~/.keras/keras.json
import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
import sklearn
import keras
import numpy
print('numpy:', numpy.__version__)
import scipy
print('scipy:', scipy.__version__)
import matplotlib
print('matp... | <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: Configure Keras with tensorflow
Step2: Test if everything is up&running
Step3: 2. Check installeded Versions
|
3,929 | <ASSISTANT_TASK:>
Python Code:
%%bash
rm $(pwd)/crash-*
from nipype import SelectFiles, Node, Workflow
from os.path import abspath as opap
from nipype.interfaces.fsl import MCFLIRT, IsotropicSmooth
# Create SelectFiles node
templates={'func': '{subject_id}/ses-test/func/{subject_id}_ses-test_task-fingerfootlips_bold.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: Example Crash 1
Step2: Investigating the crash
Step3: nipypecli allows you to rerun the crashed node using an additional option -r.
Step4: Wh... |
3,930 | <ASSISTANT_TASK:>
Python Code:
notes_file = 'synthnotes/data/note-events.parquet'
pq_root_path = 'synthnotes/data/xml_extracted'
pf = ParquetFile(notes_file)
df = pf.to_pandas()
xml_dir = 'synthnotes/data/xml_files'
xml_files = os.listdir(xml_dir)
ids = [int(f.split('.txt.xmi')[0]) for f in xml_files]
notes = df[df.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: Get the list of ids from the processed xml files so we can select a subset of the mimic notes
Step2: Select the subset of notes that we have xm... |
3,931 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import sys
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_fiel... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Load and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... |
3,932 | <ASSISTANT_TASK:>
Python Code:
import random
list10 = []
for x in range(10):
list10.append(random.randrange(100))
list100 = []
for x in range(100):
list100.append(random.randrange(100))
list1000 = []
for x in range(1000):
list1000.append(random.randrange(100))
def sort_list(old_list):
def find_new_index... | <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: binary sorting
Step2: sort_list(list10) was 29 µs, so this one is slower
Step3: sort_list() was total
|
3,933 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
import nengo
import numpy as np
import scipy.ndimage
from scipy.ndimage.interpolation import rotate
import matplotlib.animation as animation
from matplotlib import pylab
from PIL import Image
import nengo.spa as spa
import cPickle
import ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Load the MNIST training and testing images
Step2: Create array of images and rotated pairs and list of structural similarities
Step3: The Netw... |
3,934 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
%matplotlib inline
import seawater as sw
from pyspec import spectrum as spec
fni = "data/synthetic_uv.npz"
uv_synthetic = np.load(fni)
up = uv_synthetic['up']
# We may also want to calculate the wave... | <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 random data with $\kappa^{-3}$ spectrum
Step2: Compute and plot the 2D spectrum using $dx = dy = 1$
Step3: Calculating the isotropic spec... |
3,935 | <ASSISTANT_TASK:>
Python Code:
%%bash
find . -name "*.c" | xargs sed -i bck "/#include<malloc\.h>/d"
%%bash
cat ./isis/abs/allocate.cbck
from astropy import units as u, constants as const
class SnickersBar(object):
def __init__(self, w, h, l, weight, energy_density=2460 * u.kJ/ (100 * u.g)):
self.w = u.Qu... | <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: Quick introduction to chocolate bars and classes
Step2: Using cython
|
3,936 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
import numpy
import itk
from itk import TubeTK as ttk
from itkwidgets import view
PixelType = itk.F
Dimension = 3
ImageType = itk.Image[PixelType, Dimension]
# Read tre file
TubeFileReaderType = itk.SpatialObjectReader[Dimension]
tubeFileReader = TubeFileRe... | <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 tubes and a reference image which provides the size, spacing, origin, and orientation for the desired output image.
Step2: Visualize t... |
3,937 | <ASSISTANT_TASK:>
Python Code:
%load_ext autoreload
%autoreload 2
from __future__ import print_function
import hickle
import numpy as np
from pathos.multiprocessing import ProcessingPool as Pool
import random
import cProfile
import pstats
import StringIO
import timeit
import psutil
import sys
import os
import time... | <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: Set-up, Ingest
Step2: Both datasets are fit with BPZ.
Step3: The data files don't appear to come with information about the native format or m... |
3,938 | <ASSISTANT_TASK:>
Python Code:
from numpy import array
arr = array([1, 2, 3])
print(arr)
ten = array(range(10))
matrix = array([[1,2], [3, 4]])
nested_matrix = array([matrix, matrix])
strange_array = array([[1], 2])
print('Range demo:', ten)
print('Matrix demo:', matrix)
print('Array of NumPy arrays:', nested_matrix)
... | <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 just have to provide array constructor of numpy module with iterable type.
Step2: Types
Step3: Note that typecast was made automatically
S... |
3,939 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import os
assert os.environ["COLAB_TPU_ADDR"], "Make sure to select TPU from Edit > Notebook settings > Hardware accelerator"
#!pip install -q cloud-tpu-client==0.10 https://storage.googleapis.com/tpu-pytorch/wheels/torch_xla-1.8-cp37-cp3... | <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 lightning
Step2: Iris
Step3: CIFAR
|
3,940 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import numpy as np
import matplotlib.pyplot as plt
from pymks.datasets import make_checkerboard_microstructure
= make_checkerboard_microstructure(square_size=, n_squares=)
from pymks.tools import draw_microstructures
draw_microstruc... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 2-Point Statistics for Checkerboard Microstructure
Step2: Now let's take a look at how the microstructure looks.
Step3: Compute Periodic 2-Poi... |
3,941 | <ASSISTANT_TASK:>
Python Code:
# make plots show up in notebook
%matplotlib inline
import pandas as pd # data package
import matplotlib.pyplot as plt # pyplot module
from pandas_datareader import data
import datetime as dt # package to handle dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Comment. When you run the code cell above, its output appears below it.
Step2: World Bank.
Step3: Comment. In the previous cell, we used t... |
3,942 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
data = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
weights = np.array([1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5])
quantile = 0.25
ind_sorted = np.argsort(data)
sorted_data = data[ind_sorted]
sorted_weights = weights[ind_sorted]
Sn = np.cumsum(sorted_weight... | <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: Calculating percentiles / quantiles
Step3: I also found this post about equal frequency binning in Python useful.
|
3,943 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import log, sqrt
from sklearn import linear_model
dtype_dict = {'bathrooms':float, 'waterfront':int, 'sqft_above':int, 'sqft_living15':float, 'grade':int, 'yr_renovated':int, 'price':float, 'bedrooms':float,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Load the data
Step2: Feature engineering
Step3: LASSO
Step4: Calculate the RSS for best L1 on test data
Step5: 2 Phase LASSO for finding a d... |
3,944 | <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 $USER_FLAG
if os.environ["IS_TESTING"]:
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Step3: Before you begin
Step4: Region
Step5:... |
3,945 | <ASSISTANT_TASK:>
Python Code:
# Magics first (server issues)
%matplotlib inline
# Do below if you want interactive matplotlib plot ()
# %matplotlib notebook
# https://ipython.org/ipython-doc/dev/config/extensions/autoreload.html
%load_ext autoreload
%autoreload 2
# %install_ext http://raw.github.com/jrjohansson/vers... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Importing cleaned data
Step2: [Dead end] Does year predict production?
Step3: Does Hours worked correlate with output?
|
3,946 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pylab as pl
from IEtools import *
%pylab inline
filename='C:/econdata/GDP_PAYEMS.csv'
output = FREDcsvRead(filename)
plotData = output['data']
plotType = pl.plot
plotType = pl.semilogy
plotScale = 10**6
plotLabel = output['name']+' [$ p.c.]'
pl.figure(figsize=(1... | <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: Example
Step2: Dynamic equilibrium models
Step3: This uses the global fit approach.
Step4: Example
Step5: Dynamic equilibrium models
Step6: ... |
3,947 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
%matplotlib inline
import statsmodels.formula.api as smf
df = pd.read_csv('heights_weights_genders.csv')
df.head(3)
female_df = df[df['Gender'] == 'Female']
male_df = df[df['Gender'] == 'Male']
female_df... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: For Female
Step2: For Male
Step3: Function
|
3,948 | <ASSISTANT_TASK:>
Python Code:
Now, to confirm, let us do a little bit of simple tests.
import pandas as pd
from matplotlib import pyplot as plt
from matplotlib import cm as cm
import numpy as np
%matplotlib inline
train=pd.read_csv('../train.csv')
train.describe()
# first take a look at the whole picture of time data:... | <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: Nice little peaks on top of the picture show a periodic component of ~10000, very close to the number of minutes in a week
Step2: This has no 2... |
3,949 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'svg'
import matplotlib as mpl
mpl.rcParams['font.size'] = 8
figsize =(8,4)
mpl.rcParams['figure.figsize'] = figsize
import matplotlib.pyplot as plt
import numpy as np
from ipywidgets import interact
from ipywidgets import widgets, ... | <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: Admissible regions
Step2: Shocks and rarefactions
Step3: The stationary wave
Step4: From the rules determined above, we know that we can conn... |
3,950 | <ASSISTANT_TASK:>
Python Code:
#Advanced: Using other libs...
# To support both python 2 and python 3
from __future__ import division, print_function, unicode_literals
# Common imports
import numpy as np
import numpy.random as rnd
import os
# to make this notebook's output stable across runs
rnd.seed(42)
# To plot pret... | <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: Training and visualizing
Step2: Predicting classes and class probabilities
Step3: Sensitivity to training set details
Step4: Regression trees... |
3,951 | <ASSISTANT_TASK:>
Python Code:
from pyspark.sql import SQLContext
from pyspark.sql.types import *
from datetime import datetime as _datetime, timedelta, date
import boto3
import botocore
import csv
import os.path
bucket = "telemetry-parquet"
prefix = "main_summary/v4"
%time dataset = sqlContext.read.load("s3://{}/{}".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: How many cores are we running on?
Step2: And what do the underlying records look like?
Step5: We want to incrementally update the data, re-com... |
3,952 | <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: Interpolation
Step2: Now that Tensorflow Graphics is installed, let's import everything needed to run the demo contained in this notebook.
Step... |
3,953 | <ASSISTANT_TASK:>
Python Code:
# Authors: Olaf Hauk <olaf.hauk@mrc-cbu.cam.ac.uk>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Nicolas P. Rougier (graph code borrowed from his matplotlib gallery)
#
# License: BSD (3-clause)
import numpy as... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Load forward solution and inverse operator
Step2: Read and organise labels for cortical parcellation
Step3: Compute point-spread function summ... |
3,954 | <ASSISTANT_TASK:>
Python Code:
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_CLOUD_NOTEBOOK:
USER_FLAG... | <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: Restart the kernel
Step2: Before you begin
Step3: Otherwise, set your project ID here.
Step4: Authenticate your Google Cloud account
Step5: ... |
3,955 | <ASSISTANT_TASK:>
Python Code:
def sum_if_3(k, m):
if (m % 3 == 0) or (str(m).endswith('3')):
return k + m
else:
return k
sum_if_3(5, 18)
sum_if_3(4, 7)
if 'bc' in 'abcde':
print("'bc'가 'abcde'의 부분문자열이다.")
def sum_if_3s(k, m):
if (m % 3 == 0) or ('3' in str(m)):
return k + 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: 주의
Step2: 예제
Step3: 견본답안
Step4: 중첩 조건문과 일반화된 조건문
Step5: 다중 조건문(다중 if문) 활용 예제
Step6: 주의
Step7: 'while' 루프를 작성할 때 조건문이 언젠가는 만족되지 않아서 더 이상 루프... |
3,956 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from qutip import *
compl_circ = np.array([[(x + 1j*y) if x**2 + y**2 <= 1 else 0j
for x in np.arange(-1,1,0.005)]
for y in np.arange(-1,1,0.005)])
fig = plt.figure(figsiz... | <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: Colors
Step2: Schmidt plot
Step3: As we see, for separable state the plot is a product of x and y coordinates, while for the singlet state - i... |
3,957 | <ASSISTANT_TASK:>
Python Code:
# for fast array manipulation
import numpy as np
# for plotting
import matplotlib.pyplot as plt
# for numerical ODE integration
from scipy.integrate import odeint
# for nonlinear equations
from scipy.optimize import fsolve
# to display plots in-line
%matplotlib inline
def sigmoid(x, a, 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: Parameter definitions
Step2: For a stable limit cycle and a stable fixed point
Step3: More preparation
Step4: Solving and plotting
Step5: Nu... |
3,958 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import datetime
from qutip import Qobj, identity, sigmax, sigmaz, tensor
import random
import qutip.logging_utils as logging
logger = logging.get_logger()
#Set this to None or logging.WARN for 'quiet' execution
log_leve... | <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: Defining the physics
Step2: Defining the time evolution parameters
Step3: Set the conditions which will cause the pulse optimisation to termin... |
3,959 | <ASSISTANT_TASK:>
Python Code:
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install empiricaldist
# Get utils.py
import os
if not os.path.exists('utils.py'):
!wget https://github.com/AllenDowney... | <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: On September 5, 2020, prosecutors in Mississippi dropped charges against Curtis Flowers, freeing him after 23 years of incarceration.
Step2: To... |
3,960 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
# Modify the path
sys.path.append("..")
import pandas as pd
import yellowbrick as yb
import matplotlib.pyplot as plt
data = pd.read_csv("data/No-show-Issue-Comma-300k.csv")
data.head()
data.columns = ['Age','Gender','Appointment Registration','Appointment 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:
Step1: Load Medical Appointment Data
Step2: Feature Analysis
Step3: Rank2D
Step4: Diagnostic Interpretation from Rank2D(Covariance)
Step5: Diagnost... |
3,961 | <ASSISTANT_TASK:>
Python Code:
import os
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)
print(raw.info)
info ... | <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 seen in the introductory tutorial <tut-overview>, when a
Step2: However, it is not strictly necessary to load the
Step3: As you can ... |
3,962 | <ASSISTANT_TASK:>
Python Code:
rs = np.random.RandomState(seed=10)
ns = 100
nf = 10
x, y_orig, coef = make_regression(n_samples=ns, n_features=nf, coef=True, noise=0.0, random_state=rs)
x = pd.DataFrame(x)
y = pd.Series(y_orig)
n_quantiles = 3 # two-thirds of the data is truncated
quantile = 100/float(n_quantiles)
lowe... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Note that the truncation values do not have to be the same for e.g. all left-censored observations, or all right-censored observations, as in th... |
3,963 | <ASSISTANT_TASK:>
Python Code:
from collatex import *
from lxml import etree
import json,re
class WitnessSet:
def __init__(self,witnessList):
self.witnessList = witnessList
def generate_json_input(self):
json_input = {}
witnesses = []
json_input['witnesses'] = witnesses
... | <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 WitnessSet class represents all of the witnesses being collated. The generate_json_input() method returns a JSON object that is suitable for... |
3,964 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import tensorflow as tf
from gpflow.likelihoods import MultiClass
from gpflow.kernels import RBF, White
from gpflow.models.svgp import SVGP
from gpflow.training import AdamOptimizer
from scipy.stats import mode
from sci... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: We'll use 100 inducing points
Step2: We'll compare three models
Step3: For the SGP model we'll calcuate accuracy by simply taking the max mean... |
3,965 | <ASSISTANT_TASK:>
Python Code:
from polyglotdb import CorpusContext
import polyglotdb.io as pgio
corpus_root = '/mnt/e/Data/pg_tutorial'
parser = pgio.inspect_mfa(corpus_root)
parser.call_back = print # To show progress output
with CorpusContext('pg_tutorial') as c:
c.load(parser, corpus_root)
with CorpusContext(... | <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 import statements get the necessary classes and functions for importing, namely the CorpusContext class and
Step2: Important
Step3: Warnin... |
3,966 | <ASSISTANT_TASK:>
Python Code:
import os, re
# Provide the directory where files are located
directory = '/home/roli/FORESTs_BHAVYA/Combined_Libraries/ITS/'
#directory = '/home/roli/FORESTs_BHAVYA/Combined_Libraries/16S/'
# Provide a list of all the FeatureTables you will merge
# Produced by QIIME2 in STEP 7 (i.e. DAD... | <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: Step 2
Step2: Step 3
Step3: Step 4
Step4: Step 5
Step5: Step 6
Step6: Step 7
Step7: Step 8
|
3,967 | <ASSISTANT_TASK:>
Python Code:
from poppy.creatures import PoppyErgo
ergo = PoppyErgo()
from poppy.creatures import PoppyErgoJr
ergo = PoppyErgoJr()
ergo
ergo.m2
ergo.m2.present_position
ergo.m2.present_temperature
for m in ergo.motors:
print 'Motor "{}" current position = {}'.format(m.name, m.present_position)
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: For a PoppyErgoJr
Step2: Get robot current status
Step3: Turn on/off the compliancy of a motor
Step4: Go to the zero position
Step5: Make a ... |
3,968 | <ASSISTANT_TASK:>
Python Code:
## House keeping tasks
%reset -f
# standard imports
import urllib2
import os
import json
import StringIO
import pickle
# dataframe and numerical
import pandas as pd
import numpy as np
# plotting
import matplotlib.pyplot as plt
%matplotlib inline
#scipy
from scipy import stats
from scipy.... | <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 required dependencies
Step2: Load data from pickle
Step3: RFU, zscore and p-value
Step4: extract only the high binders
Step5: Wha... |
3,969 | <ASSISTANT_TASK:>
Python Code:
from jupyterthemes import get_themes
from jupyterthemes.stylefx import set_nb_theme
themes = get_themes()
set_nb_theme(themes[3])
# 1. magic for inline plot
# 2. magic to print version
# 3. magic so that the notebook will reload external python modules
# 4. magic to enable retina (high 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: Rossman GBT Modeling
Step2: We've pulled most of our configurable parameters outside into a json configuration file. In the ideal scenario, we ... |
3,970 | <ASSISTANT_TASK:>
Python Code:
document = 'Lorem Ipsum dolor sit amet'
# shingle and discard the last 5 as these are just the last n<5 characters from the document
shingles = [document[i:i+5] for i in range(len(document))][:-5]
shingles
other_document = 'Lorem Ipsum dolor sit amet is how dummy text starts'
# shingle 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: As we can see these two documents are not very similar, at least in terms of their 3-gram shingle Jaccard similarity. That aside the problem wit... |
3,971 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from __future__ import print_function
import numpy as np
import statsmodels.api as sm
import pandas as pd
from statsmodels.tsa.arima_process import arma_generate_sample
np.random.seed(12345)
arparams = np.array([.75, -.25])
maparams = np.array([.65, .35])
arparams = 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 some data from an ARMA process
Step2: The conventions of the arma_generate function require that we specify a 1 for the zero-lag of th... |
3,972 | <ASSISTANT_TASK:>
Python Code:
from rmgpy.chemkin import *
from rmgpy.tools.canteraModel import *
from IPython.display import display, Image
speciesList, reactionList = loadChemkinFile('data/minimal_model/chem_annotated.inp',
'data/minimal_model/species_dictionary.txt',
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load the species and reaction from the RMG-generated chemkin file chem_annotated.inp and species_dictionary.txt file found in your chemkin folde... |
3,973 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import numpy.random as rand
import matplotlib.pyplot as plt
matplotlib inline
mu1, mu2, mu3 = [15,20], [24,25], [38,40]
cov = [[10, 0], [0, 10]]
n_samples = 5000
data1 = rand.multivariate_normal(mu1, cov, n_samples)
data2 = rand.multivariate_normal(mu2, cov, n_samples... | <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: Compute mean values
Step2: Compute the between-class scatter matrix $S_b$
Step4: Compute the within-class scatter matrix $S_w$
Step5: Solve t... |
3,974 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import graphviz
from sklearn.linear_model import LinearRegression, LogisticRegression
import lingam
from lingam.utils import make_dot, remove_effect, predict_adaptive_lasso
from IPython.display import display_svg, SVG
print([np.__version__, pd.__vers... | <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: Indicate which variable belong to which group
Step2: Load data
Step3: Compute the residual when each variable of the second group on all the v... |
3,975 | <ASSISTANT_TASK:>
Python Code:
# directory where you want the spacer blasting to be done
## CHANGE THIS!
workDir = "/home/nyoungb2/t/CLdb_Ecoli/DR_consensus/"
import os
from IPython.display import FileLinks
%load_ext rpy2.ipython
if not os.path.isdir(workDir):
os.makedirs(workDir)
# checking that CLdb is in $PATH ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Init
Step2: Creating DR consensus seqs & loading into CLdb
Step3: That's it! Now, the CLdb.sqlite file contains the DR consensus sequences for... |
3,976 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
np.random.seed(69572)
%matplotlib inline
%load_ext writeandexecute
# plt.figure(figsize=(120,10))
small = (4,3)
mid = (10, 8)
large = (12, 8)
from __future__ import abso... | <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: Custom Functions
Step2: DataFrame Value Counts
Step4: Confusion Matrix
Step5: Import & Explore Data
Step6: Pre Processing
Step7: Text Data ... |
3,977 | <ASSISTANT_TASK:>
Python Code:
from sympy import *
init_printing(use_unicode=True)
a0 = Symbol('a_0')
e0 = Symbol('e_0')
e = Symbol('e')
a = Symbol('a')
integrando = Rational(12,19)*((1+Rational(73,24)*e**2+Rational(37,96)*e**4)
/(e*(1-e**2)*(1+Rational(121,304)*e**2)))
integrando
Integ... | <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: y ahora exponenciamos
Step2: Si definimos
Step3: La constante $C_1$ es determinada por la condición inicial $a(e_0)=a_0$ que, luego de ser ree... |
3,978 | <ASSISTANT_TASK:>
Python Code:
foo = dict() # Create an empty dict
foo['bar'] = 1 # Store an integer under the key 'bar'
print(foo['bar']) # Retrieve the integer stored in 'bar'
import scipy as sp
import numpy as np
import openpnm as op
%config InlineBackend.figure_formats = ['svg']
np.random.seed(10)
# Ins... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: A detailed tutorial on dictionaries can be found here. The dict does not offer much functionality aside from basic storage of arbitrary objects... |
3,979 | <ASSISTANT_TASK:>
Python Code:
from frozen_lake import FrozenLakeEnv
env = FrozenLakeEnv()
print(env.__doc__)
# Some basic imports and setup
import numpy as np, numpy.random as nr, gym
np.set_printoptions(precision=3)
def begin_grading(): print("\x1b[43m")
def end_grading(): print("\x1b[0m")
# Seed RNGs so you get the... | <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 look at what a random episode looks like.
Step2: In the episode above, the agent falls into a hole after two timesteps. Also note the sto... |
3,980 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import os
os.chdir('..')
import sys
sys.path.insert(0, './python')
import caffe
import os
import h5py
import shutil
import tempfile
import sklearn
import sklearn.datasets
import sklearn.linear_model
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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Description:
Step1: Synthesize a dataset of 10,000 4-vectors for binary classification with 2 informative features and 2 noise features.
Step2: Learn and evaluate ... |
3,981 | <ASSISTANT_TASK:>
Python Code:
import ROOT
from ROOT import TMVA
import os
ROOT.TMVA.Tools.Instance()
TMVA.PyMethodBase.PyInitialize()
## For PYMVA methods
TMVA.PyMethodBase.PyInitialize();
outputFile = ROOT.TFile.Open("CNN_ClassificationOutput.root", "RECREATE")
factory = ROOT.TMVA.Factory("TMVA_CNN_Classification", ... | <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: Declare DataLoader(s)
Step2: Setup Dataset(s)
Step3: Booking Methods
Step4: Book Convolutional Neural Network in TMVA
Step5: Book Convolutio... |
3,982 | <ASSISTANT_TASK:>
Python Code:
markers = ['Synap','Synap','VGlut1','VGlut1','VGlut2','Vglut3',
'psd','glur2','nmdar1','nr2b','gad','VGAT',
'PV','Gephyr','GABAR1','GABABR','CR1','5HT1A',
'NOS','TH','VACht','Synapo','tubuli','DAPI']
synapType = ['synap','synap','ex.pre','ex.pre',... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We then proceeded to try to separate the resulting filtered synapses into two groups through a naive kMean method, after tranforming the synapse... |
3,983 | <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
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<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... |
3,984 | <ASSISTANT_TASK:>
Python Code:
from pyspark.sql import Row
Person = Row("name", "age")
print Person
ali = Person("Alice", 11)
print ali
help(Row)
import re
import datetime
from pyspark.sql import Row
month_map = {'Jan': 1, 'Feb': 2, 'Mar':3, 'Apr':4, 'May':5, 'Jun':6, 'Jul':7,
'Aug':8, 'Sep': 9, 'Oct':10, 'Nov': 1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: version 1.0.0
Step4: (1b) Configuration and Initial RDD Creation
Step5: (1c) Data Cleaning
Step6: Part 2
Step7: (2b) Example
Step9: (2c) Ex... |
3,985 | <ASSISTANT_TASK:>
Python Code:
import pkg_resources
raw_data = pd.read_csv(pkg_resources.resource_stream('deepforest', 'data/train.csv'))
clean_data = raw_data.drop(["Cabin", "Name", "PassengerId", "Ticket"], axis=1)
clean_data = pd.get_dummies(clean_data).fillna(-1)
train, test = train_test_split(clean_data)
def split... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Baseline model
Step2: Deep Forest
Step3: This is not very handy, not at all. We already see a lot of code duplication, and one may feel there ... |
3,986 | <ASSISTANT_TASK:>
Python Code:
#####Test Machine Learning Algorithms
ip = 'Insert IP here'
conn = MongoClient(ip, 27017)
conn.database_names()
db = conn.get_database('cleaned_data')
reviews = db.get_collection('restaurant_reviews')
useridlist =[]
for user in users_dict.keys():
useridlist.append(user)
print(useridl... | <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.Create a user dataframe with the following columns
Step2: 2.Create a list of unique business IDs for that user
Step3: 3.Connect to the Mongo... |
3,987 | <ASSISTANT_TASK:>
Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
from __future__ import print_function
import imageio
import matplotlib.pyplot as plt
import numpy as np
import os
import sys
import tarfile
from IPython.display import display, Ima... | <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: First, we'll download the dataset to our local machine. The data consists of characters rendered in a variety of fonts on a 28x28 image. The lab... |
3,988 | <ASSISTANT_TASK:>
Python Code:
# Import modules that contain functions we need
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt
# Read in data that will be used for the calculations.
# Using pandas read_csv method, we can create a data frame
data = pd.read_csv("https://github.co... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: PART 1
Step2: Run the Code below to create a chart containing all of the Stars with Exoplantes within 100 light years!
Step3: <span style="col... |
3,989 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from collections import Counter
seqs = ['TCGGGGGTTTTT',
'CCGGTGACTTAC',
'ACGGGGATTTTC',
'TTGGGGACTTTT',
'AAGGGGACTTCC',
'TTGGGGACTTCC',
'TCGGGGATTCAT',
'TCGGGGATTCCT',
'TAGGGGACCTAC',
'TCGGG... | <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 have a DataFrame where we can get all the bases in each position to find the base(s) occurring most frequently. We'll create a second Da... |
3,990 | <ASSISTANT_TASK:>
Python Code:
utc = 0
sma = 1
ecc = 2
inc = 3
raan = 4
aop = 5
ma = 6
ta = 7
#fig1 = plt.figure(figsize = [15,8], facecolor='w')
fig_peri = plt.figure(figsize = [15,8], facecolor='w')
fig_peri_deorbit = plt.figure(figsize = [15,8], facecolor='w')
fig_apo = plt.figure(figsize = [15,8], facecolor='w')
f... | <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: Plot the orbital parameters which are vary significantly between different tracking files.
|
3,991 | <ASSISTANT_TASK:>
Python Code:
# Always run this first
# NOTE: Do not define new basic variables in this notebook;
# define them in Variables_Q.ipynb. Use this notebook
# to define new expressions built from those variables.
from __future__ import division # This needs to be here, even though it's in Varia... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
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Description:
Step1: Here, we set the PN order, if it is not already set. This will be used in numerous places below. This is the exponent of the largest power of ... |
3,992 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import Image
from scipy import ndimage
from lr_utils import load_dataset
%matplotlib inline
# Loading the data (cat/non-cat)
train_set_x_orig, train_set_y, test_set_x_orig, test_set_y, classes = load_dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: 2 - Overview of the Problem set
Step2: We added "_orig" at the end of image datasets (train and test) because we are going to preprocess them. ... |
3,993 | <ASSISTANT_TASK:>
Python Code:
import os
import matplotlib.pyplot as plt
import cv2
%matplotlib inline
def readRGBImage(imagepath):
image = cv2.imread(imagepath) # Height, Width, Channel
(major, minor, _) = cv2.__version__.split(".")
if major == '3':
# version 3 is used, need to convert
ima... | <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: Loading and save image
Step2: Change color format
Step4: Resize
Step5: Crop
Step6: Image processing with channels
|
3,994 | <ASSISTANT_TASK:>
Python Code:
# Imports
import numpy as np
import pandas as pd
import xarray as xr
from functools import lru_cache # For function result caching
# Special functions
# from scipy.special import sph_harm
import spherical_functions as sf
import quaternion
# Performance & benchmarking libraries
from jobli... | <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: Exploring Wigner 3js
Step2: This ends up as a relatively sparse array, since many combinations are invalid (do not follow angular momentum sele... |
3,995 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
N = 100 # points per class
D = 2 # dimensionality at 2 so we can eyeball it
K = 3 # number of classes
X = np.zeros((N*K, D)) # generate an empty matrix to hold X features
y = np.zeros(N*K, dtype='int32') # switching this to int32
# for 3... | <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
Step2: Notice the following
Step3: Predicting on a new value
Step4: Digging into the DNNClassifier
Step5: Exercises
|
3,996 | <ASSISTANT_TASK:>
Python Code:
import riip
ri = riip.RiiDataFrame()
ri.catalog.head(3)
ri.raw_data.loc[3].head(5) # first 5 rows for the material whose id is 3
ri.catalog.tail(3)
ri.raw_data.loc[2911].head(5) # first 5 rows for the material whose id is 2912
grid_data = ri.load_grid_data(3)
grid_data
import matpl... | <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: RiiDataFrame has an attribute named catalog that is a Pandas DataFrame provinding the catalog of experimental data as shown below.
Step2: The e... |
3,997 | <ASSISTANT_TASK:>
Python Code:
from ctypes import cdll
basics = cdll.LoadLibrary('./lib_basics.so')
basics.mul(2, 5)
from ctypes import c_int
first = (c_int * 3)(1, 2, 3)
vector3D = c_int * 3
second = vector3D(4, 5, 6)
c_result = basics.dot(first, second, 3)
python_result = sum(a * b for a, b in zip([1, 2, 3], [4... | <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 Linux
Step2: In Windows
Step3: See? It's easy
Step4: Say, we need to multiply 3-dimensional vectors
Step5: We can create an alias for thi... |
3,998 | <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: <table class="tfo-notebook-buttons" align="left">
Step2: NOTE
Step4: In order to feed the dataset into our model, we flatten the data, and con... |
3,999 | <ASSISTANT_TASK:>
Python Code:
!swirlcons --user:example=2 --user:rp-solver=4
#!mpirun -n 4 swirlcons
%run make_plots.py
%pylab inline
import glob
from matplotlib import image
from clawpack.visclaw.JSAnimation import IPython_display
from matplotlib import animation
figno = 0
fname = '_plots/*fig' + str(figno) + '.pn... | <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: Or, run code in parallel mode (command may need to be customized, depending your on MPI installation.)
Step2: Create PNG files for web-browser ... |
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