Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
|---|---|---|
2,200 | <ASSISTANT_TASK:>
Python Code:
import sys
def maxSubArraySum(a , n , k , i ) :
max_so_far = - sys . maxsize ;
max_ending_here = 0 ;
while(i < n ) :
max_ending_here = max_ending_here + a[i ] ;
if(max_so_far < max_ending_here ) :
max_so_far = max_ending_here ;
if(max_ending_here < 0 ) :
max_ending... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
2,201 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import scipy.spatial
import matplotlib.pyplot as plt
%matplotlib inline
d = 2 # Dimensionality.
n = 100 # Number of samples.
c = 1 # Number of communities.
# Data matrix, structured in communities.
X = np.random.uniform(0, 1, (n, d))
X += np.linspace(0, 2, c).re... | <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 Graph
Step2: Step 2
Step3: Step 3
Step4: Step 4
Step5: Step 5
Step6: Step 6
Step7: 2 Fourier Basis
Step8: Visualize the eigenvectors $u... |
2,202 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', '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
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
2,203 | <ASSISTANT_TASK:>
Python Code:
# For using the same code in either Python 2 or 3
from __future__ import print_function
## Note: Python 2 users, use raw_input() to get player input. Python 3 users, use input()
from IPython.display import clear_output
def display_board(board):
pass
def player_input():
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Step 1
Step2: Step 2
Step3: Step 3
Step4: Step 4
Step5: Step 5
Step6: Step 6
Step7: Step 7
Step8: Step 8
Step9: Step 9
Step10: Step 10
|
2,204 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
import seaborn; seaborn.set()
from clusterlensing import ClusterEnsemble
import emcee
import corner
% matplotlib inline
import matplotlib
matplotlib.rcParams["axes.labelsize"] = 20
matplotlib.rcParams["legend.fontsize"] = 12
logm_true = ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Generate a noisy measurement to fit
Step2: Write down likelihood, prior, and posterior probilities
Step3: Sample the posterior using emcee
Ste... |
2,205 | <ASSISTANT_TASK:>
Python Code:
import requests as rq
import pandas as pd
import matplotlib.pyplot as mpl
import bs4
import os
from tqdm import tqdm_notebook
from datetime import time
%matplotlib inline
base_url = "https://pydata.org"
r = rq.get(base_url + "/berlin2018/schedule/")
bs = bs4.BeautifulSoup(r.text, "html.p... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Query Data
Step2: Let's query every talk description
Step3: Okay, make a dataframe and add some helpful columns
Step4: visualize some stuff
|
2,206 | <ASSISTANT_TASK:>
Python Code:
bounding_box_file = ""
result_shapefile_filepath = ""
p1 = pyproj.Proj("+init=epsg:31254")
p2 = pyproj.Proj("+init=epsg:4326")
p3 = pyproj.Proj("+init=epsg:3857")
p4 = pyproj.Proj("+init=epsg:25832")
import overpy
import fiona
import numpy
import geopandas
from shapely.ops import polygon... | <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: Import statements
Step2: Utility functions
Step3: Query OpenStreetMap using OverpassAPI via overpy python package
Step4: define bounding box ... |
2,207 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
import pandas as pd
from sklearn.cluster import KMeans
from sklearn.preprocessing import minmax_scale
def load_data(file_path, cols=None):
COL_NAMES = ["duration", "protocol_type", "service", "flag", "src_bytes",
"dst_bytes", "land", "wrong_fragme... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Data Loading
Step2: K-Means Evaluation
Step3: Loading the training data
Step4: Training
Step5: Test Set
Step6: Now to cluster the test data... |
2,208 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
#Load libraries for data processing
import pandas as pd #data processing, CSV file I/O (e.g. pd.read_csv)
import numpy as np
from scipy.stats import norm
# visualization
import seaborn as sns
plt.style.use('fivethirtyeight')
sns.set_styl... | <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: Label encoding
Step2: After encoding the class labels(diagnosis) in an array y, the malignant tumors are now represented as class 1(i.e prescen... |
2,209 | <ASSISTANT_TASK:>
Python Code:
import os.path as op
import numpy as np
import mne
data_path = mne.datasets.opm.data_path()
subject = 'OPM_sample'
subjects_dir = op.join(data_path, 'subjects')
raw_fname = op.join(data_path, 'MEG', 'OPM', 'OPM_SEF_raw.fif')
bem_fname = op.join(subjects_dir, subject, 'bem',
... | <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: Prepare data for localization
Step2: Examine our coordinate alignment for source localization and compute a
Step3: Perform dipole fitting
Step... |
2,210 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
import torch
from torch.utils.data import Dataset, DataLoader
import torch.nn as nn
class plot_error_surfaces(object):
def __init__(self,w_range, b_range,X,Y,n_samples=50,go=True):
W = np.lin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Helper functions
Step2: <a id="ref0"></a>
Step3: <a id="ref1"></a>
Step4: Create a logistic regression object or model
Step5: Replace the r... |
2,211 | <ASSISTANT_TASK:>
Python Code:
import json
import os
import nltk
import string
import re
import pandas as pd
from IPython.display import display
import numpy as np
import math
directory = 'sitespider/sites'
files = [x[2] for x in os.walk(directory)][0]
pages = []
for file in files:
with open("%s/%s" % (directory,... | <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) Implement a crawler
Step2: Importierung der analysierten Seiten
Step3: Konstanten
Step4: Funktionen
Step5: Hilfe-Funktionen
Step6: Die F... |
2,212 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import os
print os.getenv("HOME")
wd = os.path.join( os.getenv("HOME"),"mpi_tmpdir")
if not os.path.isdir(wd):
os.mkdir(wd)
os.chdir(wd)
print "WD is now:",os.getcwd()
%%writefile mpi002.py
from mpi4py import MPI
i... | <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: non-contigous slice
Step2: N - slices
|
2,213 | <ASSISTANT_TASK:>
Python Code:
from napalm import get_network_driver
import napalm_yang
import json
def use_mock_devices():
junos_configuration = {
'hostname': '127.0.0.1',
'username': 'vagrant',
'password': '',
'optional_args': {'path': "./junos_mock/", 'profile': ['junos'],
... | <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: Creating a Binding
Step2: At this point, you can use the "util" model_to_dict() to visualize the binding and the attached models
Step3: Popula... |
2,214 | <ASSISTANT_TASK:>
Python Code:
import os.path as op
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample, fetch_hcp_mmp_parcellation
from mne.minimum_norm import apply_inverse, read_inverse_operator
from mne import read_evokeds
data_path = sample.data_path()
sample_dir = op.join... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Then, we read the stc from file.
Step2: This is a
Step3: The SourceEstimate object is in fact a surface source estimate. MNE also
Step4: You... |
2,215 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install -U google-cloud-aiplatform $USER_FLAG
! pip3 install -U google-cloud-storage $USER_FLAG
if not 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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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:... |
2,216 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'thu', 'ciesm', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "email") ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
2,217 | <ASSISTANT_TASK:>
Python Code:
# useful additional packages
import matplotlib.pyplot as plt
import matplotlib.axes as axes
%matplotlib inline
import numpy as np
import networkx as nx
from qiskit.tools.visualization import plot_histogram
from qiskit_aqua import Operator, run_algorithm, get_algorithm_instance
from qiski... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: [Optional] Setup token to run the experiment on a real device
Step2: MaxCut problem
Step3: Brute force approach
Step4: Mapping to the Ising p... |
2,218 | <ASSISTANT_TASK:>
Python Code:
%run '00_database_connectivity_setup.ipynb'
IPython.display.clear_output()
%%execsql
drop table if exists gp_ds_sample_table;
create temp table gp_ds_sample_table
as
(
select
random() as x,
random() as y
from
generate_series(1, 10) x
) distributed rand... | <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: Your connection object is conn
Step4: SELECT query
|
2,219 | <ASSISTANT_TASK:>
Python Code:
3 * 4
x = [1, 2, 3]
print(x)
x.append(4)
print(x)
measurements = {'height': [1.70, 1.80, 1.50], 'weight': [60, 120, 50]}
measurements
measurements['height']
x = [1, 2, 3, 4]
[i**2 for i in x]
def calc_bmi(weight, height):
return weight / height**2
[calc_bmi(w, h) for w, h in zip(me... | <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: Lists
Step2: Dictionaries
Step3: Comprehensions
Step4: Level 1
Step5: Mixed types
Step6: Grouping
Step7: Seaborn
Step8: 2D distributions
... |
2,220 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
tmp = np.array([1., 2., 3.])
tmp_cubed = tmp**3
print(tmp)
print(tmp_cubed)
ex_dataframe = pd.DataFrame()
ex_dataframe['power_1'] = tmp
print(ex_dataframe)
def polynomial_sframe(feature, degree):
# assume that degree >= 1
# initialize 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: Next we're going to write a polynomial function that takes an SArray and a maximal degree and returns an SFrame with columns containing the SArr... |
2,221 | <ASSISTANT_TASK:>
Python Code:
rdt_dict = {
50: [184, 184, 184, 184, 279, 184, 198, 279, 192, 326],
100: [345, 501, 350, 350, 492, 350, 350, 496, 495, 350],
150: [501, 648, 648, 648, 501, 648, 648, 648, 501, 567],
200: [800, 800, 800, 800, 690, 800, 800, 800, 660, 800],
250: [960, 960, 960, 960, 96... | <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: Raspberry Pi using USB2Dynamixel
Step2: Plots
Step3: Baud rate
|
2,222 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plot
from ipywidgets import interactive
import ipywidgets as widgets
import math
from pulp import *
%matplotlib inline
# returns rho polynomial (highest exponents first) corresponding to average check node degree c_avg
def c_avg_to_rho(c_a... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We specify the check node degree distribution polynomial $\rho(Z)$ by fixing the average check node degree $d_{\mathtt{c},\text{avg}}$ and assum... |
2,223 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from keras.models import Sequential
from keras.layers.core import Dense, Activation
from keras.optimizers import SGD, Adadelta
from keras.callbacks import RemoteMonitor
import sys
sys.path.append('../python')
from data import Corpus
with Corpus('../data/mfcc_train_smal... | <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 let's load our data. In the VoxforgeDataPrep notebook, we created to arrays - inputs and outputs. The input nas the dimensions (num_sample... |
2,224 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cccma', 'sandbox-3', '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... |
2,225 | <ASSISTANT_TASK:>
Python Code:
#!/usr/bin/python
#-*- encoding: utf-8 -*-
Sample Codes for ThinkStats2 - Chapter3
Copyright 2015 @myuuuuun
URL: https://github.com/myuuuuun/ThinkStats2-Notebook
License: GNU GPLv3 http://www.gnu.org/licenses/gpl.html
%matplotlib inline
from __future__ import division, print_function
impo... | <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: ThinkStat2 Chapter2 Exerciseのサンプルコード 実行例
Step2: Exercise1
Step3: Exercise2
Step4: thinkstats2モジュールに入っているメソッド値が一致しているか調べる
Step5: Exercise3
... |
2,226 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
# Regresa 101 numeros igualmmente espaciados en el intervalo[-1,1]
x_train = np.linspace(-1, 1, 101)
# Genera numeros pseudo-aleatorios multiplicando la matriz x_train * 2 y
# sumando a cada elemento un ruido (una matriz del mismo tamani... | <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: Algoritmo de Regresion Lineal en TensorFlow
Step2: Regresion Lineal en Polinomios de grado N
Step3: Regularizacion
|
2,227 | <ASSISTANT_TASK:>
Python Code:
max_steps = 3000
batch_size = 128
data_dir = 'data/cifar10/cifar-10-batches-bin/'
model_dir = 'model/_cifar10_v2/'
X_train, y_train = cifar10_input.distorted_inputs(data_dir, batch_size)
X_test, y_test = cifar10_input.inputs(eval_data=True, data_dir=data_dir, batch_size=batch_size)
image... | <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: 初始化权重
Step2: 第一个卷积层
Step3: 第二个卷积层
Step4: 第一个全连接层
Step5: 第二个全连接层
Step6: 输出层
Step7: 使用in_top_k来输出top k的准确率，默认使用top 1。常用的可以是top 5。
Step8: 启动... |
2,228 | <ASSISTANT_TASK:>
Python Code:
import re, json, os, nltk, string, gensim, bz2
from gensim import corpora, models, similarities, utils
from nltk.corpus import stopwords
from os import listdir
from datetime import datetime as dt
import numpy as np
import codecs
import sys
stdin, stdout, stderr = sys.stdin, sys.stdout, sy... | <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: Build LSI Model
Step2: LsiModel的參數
Step3: Build Word2Vec Model
Step4: Build Doc2Vec Model
Step5: Build Doc2Vec Model from 2013 USPTO Patents... |
2,229 | <ASSISTANT_TASK:>
Python Code:
%%capture --no-stderr
!pip3 install kfp --upgrade
import kfp.components as comp
dataproc_submit_pig_job_op = comp.load_component_from_url(
'https://raw.githubusercontent.com/kubeflow/pipelines/1.7.0-rc.3/components/gcp/dataproc/submit_pig_job/component.yaml')
help(dataproc_submit_pig... | <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 component using KFP SDK
Step2: Sample
Step3: Example pipeline that uses the component
Step4: Compile the pipeline
Step5: Submit the... |
2,230 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 기본 분류
Step2: 패션 MNIST 데이터셋 임포트하기
Step3: load_data() 함수를 호출하면 네 개의 넘파이(NumPy) 배열이 반환됩니다
Step4: 데이터 탐색
Step5: 비슷하게 훈련 세트에는 60,000개의 레이블이 있습니다
... |
2,231 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import os
import sys
sys.path.append(os.path.join('..', '..'))
from data_models.parameters import arl_path
results_dir = arl_path('test_results')
from matplotlib import pylab
import numpy
from astropy.coordinates import SkyCoord
from astropy import units as u
from astro... | <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: Construct LOW core configuration
Step2: We create the visibility. This just makes the uvw, time, antenna1, antenna2, weight columns in a table
... |
2,232 | <ASSISTANT_TASK:>
Python Code:
import rebound
import reboundx
import numpy as np
sim = rebound.Simulation()
rebound.G = 6.674e-11 # SI units
sim.integrator = "whfast"
sim.dt = 1.e8 # At ~100 AU, orbital periods ~1000 yrs, so use a timestep of 1% of that, in sec.
sim.N_active = 1 # Make it so dust particles don't intera... | <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 set up REBOUNDx and add radiation_forces. We also have to set the speed of light in the units we want to use.
Step2: By default, the... |
2,233 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import display
from IPython.display import (
HTML, Image, Latex, Math, Markdown, SVG
)
text = Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nullam urna
libero, dictum a egestas non, placerat vel neque. In imperdiet iaculis fermentum.
Vestibulum ante i... | <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: Text
Step3: Text as output
Step4: Standard error
Step5: HTML
Step7: Markdown
Step9: LaTeX
Step11: SVG
|
2,234 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis A. Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne import io
from mne.datasets import sample
from mne.cov import compute_covariance
print(__doc__)
data_path = samp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Set parameters
Step2: Compute covariance using automated regularization
Step3: Show the evoked data
Step4: We can then show whitening for our... |
2,235 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from numpy.testing import assert_almost_equal
# Specify diffusion coefficient
nu = 0.1
def analytical_soln(xmax=1.0, tmax=0.2, nx=1000, nt=1000):
Compute analytical solution.
x = np.linspace(0, xmax, num=nx)
t = np.linspace(0, tmax, num=nt)
u = np.zeros(... | <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: Automatically 'discovering' the heat equation with reverse finite differencing
Step3: Okay, so now that we have our data to work on, we need to... |
2,236 | <ASSISTANT_TASK:>
Python Code:
from cartoframes.auth import set_default_credentials
set_default_credentials('cartoframes')
from cartoframes.viz import Map, Layer, Layout, basic_style
Layout([
Map(Layer('select * from drought_wk_1 where dm = 3', basic_style(color='#e15383'))),
Map(Layer('select * from drought_w... | <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: Same viewport
Step2: Different viewports
|
2,237 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
from scipy.stats import ttest_ind
import numpy as np
import mne
from mne.channels import find_layout, find_ch_connectivity
from mne.stats import spatio_temporal_cluster_test
np.random.seed(0)
# Load the data
path = mne.datasets.kiloword.data_path() + '/kwor... | <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: If we have a specific point in space and time we wish to test, it can be
Step2: Absent specific hypotheses, we can also conduct an exploratory
... |
2,238 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alexandre Barachant <alexandre.barachant@gmail.com>
#
# License: BSD (3-clause)
from mne import (io, compute_raw_covariance, read_events, pick_types, Epochs)
from mne.datasets import sample
from mne.preprocessing import Xdawn
from mne.viz import plot_epochs_image
print(__doc__)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set parameters and read data
|
2,239 | <ASSISTANT_TASK:>
Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Joan Massich <mailsik@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
import os.path as op
import numpy as np
import mne
from mne.datasets import eegbci
from mne.datasets import fe... | <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 data
Step2: Setup source space and compute forward
Step3: From here on, standard inverse imaging methods can be used!
Step4: Get an ... |
2,240 | <ASSISTANT_TASK:>
Python Code:
from skmultilearn.dataset import load_dataset
X_train, y_train, feature_names, label_names = load_dataset('emotions', 'train')
X_test, y_test, _, _ = load_dataset('emotions', 'test')
feature_names[:10]
label_names
from skmultilearn.problem_transform import BinaryRelevance
from sklearn.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Let's load up some data. In this tutorial we will be working with the emotions data set introduced in emotions.
Step2: The feature_names variab... |
2,241 | <ASSISTANT_TASK:>
Python Code:
from pathlib import Path
import pathlib
save_dir = "./test_dir"
Path(save_dir).mkdir(parents=True, exist_ok=True)
### get current directory
print(Path.cwd())
print(Path.home())
print(pathlib.Path.home().joinpath('python', 'scripts', 'test.py'))
# Reading and Writing Files
path = pathlib.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: useful functions
Step2: .name
Step3: Find the Last Modified File
Step4: Create a Unique File Name
Step5: dir exist and then glob with multip... |
2,242 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
from scipy import stats
np.random.seed(0)
mu = 0
sigma = 1
N = 3
np.random.lognormal(mean=mu, sigma=sigma, size=N)
np.random.seed(0)
stats.lognorm(sigma, loc=0, scale=np.exp(mu)).rvs(size=N)
import paramnormal
np.random.seed(0)
paramnormal.lognorma... | <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: Consider the lognormal distribution.
Step2: In scipy, you need an additional shape parameter (s), plus the usual loc and scale. Aside from the... |
2,243 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from math import pi
import control as ct
def vehicle_update(t, x, u, params={}):
Vehicle dynamics for cruise control system.
Parameters
----------
x : array
System state: car velocity in m/s
u : array
... | <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: Process Model
Step3: Engine model
Step4: Torque curves for a typical car engine. The graph on the left shows the torque generated by the engin... |
2,244 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
view_sentence_range = (0, 10)
DON'T MODIFY ANYTHING IN THIS CELL
import num... | <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: TV Script Generation
Step3: Explore the Data
Step6: Implement Preprocessing Functions
Step9: Tokenize Punctuation
Step11: Preprocess all the... |
2,245 | <ASSISTANT_TASK:>
Python Code:
from typing import Callable, Iterator, Tuple
import chex
import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import numpy as np
import optax
def generator() -> Iterator[Tuple[chex.Array, chex.Array]]:
rng = jax.random.PRNGKey(0)
while True:
rng, k1, k2 = jax.random.... | <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 demonstrate sampling from this as follows,
Step2: We now define our parametrized function $f(\theta, x)$, and choose a random initial value ... |
2,246 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import os
import glob
import SimpleITK as sitk
from PIL import Image
from scipy.misc import imread
%matplotlib inline
from IPython.display import clear_output
pd.options.mode.chained_assignment =... | <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 us import annotations
Step2: Candidates have two classes, one with nodules, one without
Step3: Classes are heaviliy unbalanced, hardly 0.2... |
2,247 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import pandas.io.data as web
import datetime
# date ranges
end = datetime.date(2015, 1, 26)
start = end + datetime.timedelta(weeks=-21)
start
# Get daily price data for Caltex
ctx = web.DataReader('ctx.ax', 'yahoo', start, end)
ctx
# resample to weekly ohlc data star... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get Daily price data for Caltex.
Step2: Transform to Weekly
Step3: All Ords Moving Average
|
2,248 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from IPython.display import SVG
from keras.utils.vis_utils import model_to_dot
import keras
from keras.datasets import mnist # load up the training data!
from keras.models import Sequential # our model
from keras.layers import Dense, Dropout, Flatten # layers we've see... | <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're going to use some examples from https
Step2: Typically it's good practice to specify your parameters together
Step3: In this case we alr... |
2,249 | <ASSISTANT_TASK:>
Python Code:
import os
import matplotlib.pyplot as plt
import pyzdde.zdde as pyz
%matplotlib inline
l = pyz.createLink() # create a DDE link object for communication
zfile = os.path.join(l.zGetPath()[1], 'Sequential', 'Objectives', 'Cooke 40 degree field.zmx')
l.zLoadFile(zfile)
l.zQuickFocus()
l.i... | <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 a lens file
Step2: Perform a quick-focus
Step3: Example of a Layout plot
Step4: Why do we need to set gamma?
Step5: Now that we have t... |
2,250 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
cancer = pd.read_csv('../data/cancer.csv')
cancer
ytotal, ntotal = cancer.sum().astype(float)
p_hat = ytotal/ntotal
p_hat
p_hat*(1.-p_hat)*ntotal
cancer.y.var()
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
fig, axes = plt.subplots(1, 2, figs... | <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: If we use a simple binomial model, which assumes independent samples from a binomial distribution with probability of mortality $p$, we can use ... |
2,251 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy, matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
customers = pd.read_csv('Ecommerce Customers')
customers.head()
customers.describe()
customers.info()
sns.jointplot(customers['Time on Website'], customers['Yearly Amount Spent'])
sns.j... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get the Data
Step2: Check the head of customers, and check out its info() and describe() methods.
Step3: Exploratory Data Analysis
Step4: Do ... |
2,252 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'inpe', 'sandbox-2', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "ema... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
2,253 | <ASSISTANT_TASK:>
Python Code:
# install Pint if necessary
try:
import pint
except ImportError:
!pip install pint
# download modsim.py if necessary
from os.path import exists
filename = 'modsim.py'
if not exists(filename):
from urllib.request import urlretrieve
url = 'https://raw.githubusercontent.com/A... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: In this case study we'll develop a model of Spider-Man swinging from a springy cable of webbing attached to the top of the Empire State Building... |
2,254 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
file = "knapsack1.txt"
fp = open(file, 'r+')
data = fp.readlines()
W, n = data[0].split(" ")
W, n = int(W), int(n)
v = []
w = []
for r in data[1:]:
v_i, w_i = r.split(" ")
v.append(int(v_i))
w.append(int(w_i))
A = np.zeros([n, W+1])
for i in range(n):
fo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Problem 2
Step2: A recursive Implementation of the knapsack algorithm with caching
|
2,255 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.mlab import griddata
m, n = 10, 4
xl, xr = (0.0, 1.0)
yb, yt = (0.0, 1.0)
h = (xr - xl) / (m - 1.0)
k = (yt - yb) / (n - 1.0)
xx = [xl + (i - 1)*h for i in range(1, m+1)]
yy = [yb + (i - 1)*k for i in ra... | <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: Para simplificar el sistema a resolver, cambiaremos los índices dobles por indices lineales mediante la conversión
Step2: Luego debemos constru... |
2,256 | <ASSISTANT_TASK:>
Python Code:
!pip install git+https://github.com/openai/baselines >/dev/null
!pip install gym >/dev/null
import numpy as np
import random
import gym
from gym.utils import seeding
from gym import spaces
def state_name_to_int(state):
state_name_map = {
'S': 0,
'A': 1,
'B': 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:
Step2: Environment
Step3: Try out Environment
Step4: Baseline
Step5: Train model
Step7: Step 1
Step8: Step 2
Step9: Visualizing Results
Step10: ... |
2,257 | <ASSISTANT_TASK:>
Python Code:
!pip show systemml
import pandas as pd
from systemml import MLContext, dml
ml = MLContext(sc)
print(ml.info())
sc.version
FsPath = "/tmp/data/"
inp = FsPath + "Input/"
outp = FsPath + "Output/"
import numpy as np
X_pd = pd.DataFrame(np.arange(1,2001, dtype=np.float)).values.reshape(100... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: SystemML Read/Write data from local file system
Step3: Generate Data and write out to file.
Step4: Alternatively to passing in/out file names,... |
2,258 | <ASSISTANT_TASK:>
Python Code:
from itertools import islice
def fibonacci():
a, b = 0, 1
while True:
yield a
a, b = b, a + b
n = 45
known_good_output = tuple(islice(fibonacci(), n))
# known_good_output
%timeit sum(islice(fibonacci(), n))
def fibonacci():
a, b = 0, 1
while True:
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: First we start with straightforward fibonacci generator function.
Step2: Next, we unroll the loop. Note that there are no assignments that just... |
2,259 | <ASSISTANT_TASK:>
Python Code:
# Can't find good material for this...
# Can't find good material for this.
# Let us see what this would look like in numpy.
# First make choose m and n such that m != n
m = 5
n = 10
# Make the matrix A
A = np.random.rand(m, n)
print(A)
# Now compute its eigenvalues.
try:
vals, vecs... | <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: PCA
Step2: PCA Algorithm Basics
Step3: Looks like we'll have to cheat a bit.
Step4: This.... actually makes sense. Lets compare the other mu... |
2,260 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
from ipywidgets import interact, FloatSlider
import SimpleITK as sitk
# Download data to work on
%run update_path_to_download_script
from downloaddata import fetch_data as fdata
from myshow import myshow, myshow3d
img_T1 = sitk.ReadImage(... | <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: Thresholding
Step2: ITK has a number of histogram based automatic thresholding filters including Huang, MaximumEntropy, Triangle, and the popul... |
2,261 | <ASSISTANT_TASK:>
Python Code:
# Execute this cell to load the notebook's style sheet, then ignore it
from IPython.core.display import HTML
css_file = '../style/custom.css'
HTML(open(css_file, "r").read())
# Import Libraries
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# Here, I introduce a ne... | <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: Triangular mesh generation
Step2: This quad mesh is already able to accurately describe the free-surface topography.
Step3: Next, we compute ... |
2,262 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import bigbang.mailman as mailman
import bigbang.graph as graph
import bigbang.process as process
from bigbang.parse import get_date
from bigbang.archive import Archive
reload(process)
import pandas as pd
import datetime
import matplotlib.pyplot as plt
import numpy as ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Import the BigBang modules as needed. These should be in your Python environment if you've installed BigBang correctly.
Step2: Now let's load t... |
2,263 | <ASSISTANT_TASK:>
Python Code:
import time
time.sleep(1000)
lista = ['perro' ,'gato']
print(lista)
lista[1]
import numpy as np
array_1 = np.array([3,4,5])
array_2 = np.array([4,8,7])
array_1 + array_2
array_1 = np.zeros(5)
print(array_1)
array_1[0]
arreglo = np.random.randint(1,10,500000)
np.mean(arreglo)
arre... | <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: Resetear
Step2: podemos agregar elementos
Step3: o podemos usar el modulo Numpy para arreglos numericos (Protip
Step4: y que tal arreglos vac... |
2,264 | <ASSISTANT_TASK:>
Python Code:
import os
import logging
import json
from nis_util import do_large_image_scan, set_optical_configuration, get_position
logging.basicConfig(format='%(asctime)s - %(levelname)s in %(funcName)s: %(message)s', level=logging.DEBUG)
logger = logging.getLogger(__name__)
path_to_nis = 'C:\\Progr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: set paths
Step2: do a dummy overview scan
Step3: corresponding points
Step4: save the calibration
Step5: test the transformation
|
2,265 | <ASSISTANT_TASK:>
Python Code:
from burnman import Composition
olivine_composition = Composition({'MgO': 1.8,
'FeO': 0.2,
'SiO2': 1.}, 'weight')
olivine_composition.print('molar', significant_figures=4,
normalization_compon... | <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: After initialization, the "print" method can be used to directly print molar, weight or atomic amounts. Optional variables control the print pre... |
2,266 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('../')
import numpy as np
from anemoi import MiniZephyr, SimpleSource, AnalyticalHelmholtz
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib
%matplotlib inline
from IPython.display import set_matplotlib_formats
set_matplotlib_formats('... | <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: Error plots for MiniZephyr vs. the AnalyticalHelmholtz response
Step2: Relative error of the MiniZephyr solution (in %)
|
2,267 | <ASSISTANT_TASK:>
Python Code:
Image("img/init.png")
Image("img/target_result.png")
# FOR WEB SCRAPING
from lxml import html
import requests
# FOR FUNCTIONAL PROGRAMMING
import cytoolz # pipe
# FOR DATA WRANGLING
import pandas as pd # use of R like dataframes
import re #re for regular expressions
# TO INSERT IMAGES
... | <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: Expected results
Step2: Techniques used
Step3: Data wrangling in action
Step4: The extracted tree still contains much noise
Step5: Use of la... |
2,268 | <ASSISTANT_TASK:>
Python Code:
!pip install tweepy
import tweepy
consumer_key=''
consumer_secret = ''
access_token = ''
access_token_secret = ''
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth)
public_tweets = api.home_timeline(... | <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: Assuming the installation worked, you can now import the tweepy module.
Step2: The next step is to get a costomer_key, consumer_secret, access_... |
2,269 | <ASSISTANT_TASK:>
Python Code:
from numpy.random import standard_normal # Gaussian variables
N = 1000; P = 5
X = standard_normal((N, P))
W = X - X.mean(axis=0,keepdims=True)
print(dot(W[:,0], W[:,1]))
from sklearn.decomposition import PCA
S=PCA(whiten=True).fit_transform(X)
print(dot(S[:,0], S[:,1]))
from numpy.rand... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: I'll skip ahead and use a pre-canned PCA routine from scikit-learn (but I'll dig into it a bit later!) Let's see what happens to the transformed... |
2,270 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.asarray([1,2,3,4])
pos = 2
element = 66
a = np.insert(a, pos, element)
<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:
|
2,271 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import seaborn as sns
import numpy as np
def find_peaks(a):
Find the indices of the local maxima in a sequence.
leest = []
if a[0] > a[1]:
leest.append(0)
for x in range(1,len(a)-1):
if (a[x-1]<a[x]) ... | <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: Peak finding
Step3: Here is a string with the first 10000 digits of $\pi$ (after the decimal). Write code to perform the following
|
2,272 | <ASSISTANT_TASK:>
Python Code:
import pyalps
lattice_range = [2, 3, 4, 5]
parms = [{
'LATTICE' : "open square lattice", # Set up the lattice
'MODEL' : "spinless fermions", # Select the model
'L' : L, # Lattice dimension
't' : -1 , ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: For now, we are only interested in relatively small systems, we will try lattice sizes between $2\times 2$ and $5\times 5$. With this, we set th... |
2,273 | <ASSISTANT_TASK:>
Python Code:
aapl = data.DataReader('AAPL', 'yahoo', '2000-01-01')
print(aapl.head())
plt.plot(aapl.Close)
print(aapl['Adj Close'].head())
%matplotlib inline
plt.plot(aapl['Adj Close'])
plt.ylabel('price')
plt.xlabel('year')
plt.title('Price history of Apple stock')
plt.show()
ibm = data.DataReader(... | <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: $\Rightarrow$ We get various different prices
Step2: $\Longrightarrow$ There was a stock split 7
Step3: For the apple chart one can see, that ... |
2,274 | <ASSISTANT_TASK:>
Python Code:
# importamos la librería numpy, y le damos como nombre np dentro del programa
import numpy as np
lista=[25,12,15,66,12.5]
vector=np.array(lista)
print(vector)
print("- vector original")
print(vector)
print("- sumarle 1 a cada elemento del vector:")
print(vector+1)
print("- multiplicar p... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Ahora que tenemos la librería, empecemos creando un vector de 5 elementos.
Step2: ¿Cuál es la diferencia entre vector y lista? Que vector, al ... |
2,275 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
print(type(a))
a
L = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
print(type(L))
L
a = np.arange(1000) #arange : 그냥 array range임 array로 바꿈
%time a2 = a**2
a1 = np.arange(10)
print(a1)
print(2 * a1)
L = range(1000)
%time L2 = [i**2 for i... | <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: 만들어진 ndarray 객체의 표현식(representation)을 보면 바깥쪽에 array()란 것이 붙어 있을 뿐 리스트와 동일한 구조처럼 보인다. 실제로 0, 1, 2, 3 이라는 원소가 있는 리스트는 다음과 같이 만든다.
Step2: 그러나 ndar... |
2,276 | <ASSISTANT_TASK:>
Python Code:
# Import useful libraries
import numpy as np
import pandas as pd
# Import required libraries for data visualisation
import matplotlib.pyplot as plt
import seaborn as sns
# Import the package
import kinact
# Magic
%matplotlib inline
# import data
data_fc, data_p_value = kinact.get_example... | <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 Start
Step2: 1. Loading the data
Step3: 2. Import prior-knowledge kinase-substrate relationships from PhosphoSitePlus
Step4: 3. KSEA
St... |
2,277 | <ASSISTANT_TASK:>
Python Code:
%load_ext watermark
%watermark -u -d -v -p numpy,matplotlib,scipy,pandas,sklearn,mlxtend
%matplotlib inline
from __future__ import division, print_function
from collections import defaultdict
import os
import numpy as np
from scipy import optimize
from scipy.stats import chisquare
import... | <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: Cosmic-ray composition effective area analysis
Step2: Load simulation DataFrame and apply quality cuts
Step3: Define energy binning for this a... |
2,278 | <ASSISTANT_TASK:>
Python Code:
import os
from tqdm import tqdm
from rmgpy import settings
from rmgpy.data.rmg import RMGDatabase
from rmgpy.kinetics import KineticsData
from rmgpy.rmg.model import getFamilyLibraryObject
from rmgpy.data.kinetics.family import TemplateReaction
from rmgpy.data.kinetics.depository import 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:
Steps
Step1: 0. helper methods
Step2: 1. load text-format fragment mech
Step3: 2. get thermo and kinetics
Step4: 2.1 correct entropy for certain fra... |
2,279 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
matplotlib.rcParams['figure.figsize'] = (10.0, 16.0)
import matplotlib.pyplot as plt
import numpy as np
import scipy as sp
from scipy import fftpack
from numpy import fft
import json
from functools import partial
class Foo: pass
from chest import Chest... | <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 a frame from a real simulation.
Step2: Load the governing properties from the frame.
Step3: Load the last midplane slice of the scalar fi... |
2,280 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy.stats import norm
from thunder import SourceExtraction
from thunder.extraction import OverlapBlockMerger
import matplotlib.pyplot as plt
%matplotlib inline
from thunder import Colorize
image = Colorize.image
path = 's3://neuro.datasets/challenges/neurofinde... | <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: Setup plotting
Step2: Load data
Step3: load and cache the raw data (we only load first 100 time points because we're on a single node)
Step4: ... |
2,281 | <ASSISTANT_TASK:>
Python Code:
# First, we'll "import" the software packages needed.
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib as mpl
import matplotlib.pyplot as plt
inline_rc = dict(mpl.rcParams)
# Starting a line with a hashtag tells the program not to read the line.
# That way we ca... | <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: Raw data
Step2: Plotting the data
Step3: Calculate and plot velocity
|
2,282 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from bigbang.archive import Archive
from bigbang.archive import load as load_archive
import bigbang.parse as parse
import bigbang.graph as graph
import bigbang.mailman as mailman
import bigbang.process as process
import networkx as nx
import matplotlib.pyplot as plt
imp... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Set a valid date frame for building the network.
Step2: Filter data according to date frame and export to .gexf file
|
2,283 | <ASSISTANT_TASK:>
Python Code:
def lstrip(iterable, obj):
stop = False
for item in iterable:
if stop:
yield item
elif item != obj:
yield item
stop = True
x = lstrip([0, 1, 2, 3, 0], 0)
x
list(x)
def lstrip(iterable, obj):
lstrip_stop = 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: Bonus2
Step3: Unit Tests
|
2,284 | <ASSISTANT_TASK:>
Python Code:
import os
fileCount = len(os.walk('./texts').next()[2])
print(fileCount)
print(os.walk('./texts').next()[2])
import glob
import re
files = {}
for fpath in glob.glob("./texts/*.txt"):
with open(fpath) as f:
fixed_text = re.sub("[^a-zA-Z'-]"," ",f.read())
files[fpath] = (... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: For the record, here are our texts
Step2: Let's get some basic information about these texts
|
2,285 | <ASSISTANT_TASK:>
Python Code:
[n for n in table.colnames if n.startswith('ks')]
p = table['ttest:out_of_transit&before_midtransit-vs-out_of_transit&after_midtransit']
poorly_normalized_oot_threshold = -1
mask_poorly_normalized_oot = np.log(p) > poorly_normalized_oot_threshold
plt.hist(np.log(p[~np.isnan(p)]))
plt.axv... | <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: If the distribution of fluxs before transit is significantly different from the distribution of fluxs after transit, mask those results.
Step2: ... |
2,286 | <ASSISTANT_TASK:>
Python Code:
import SimpleITK as sitk
# If the environment variable SIMPLE_ITK_MEMORY_CONSTRAINED_ENVIRONMENT is set, this will override the ReadImage
# function so that it also resamples the image to a smaller size (testing environment is memory constrained).
%run setup_for_testing
# Utility method t... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step3: Utility functions
Step4: Loading Data
Step5: Initial Alignment
Step6: Look at the transformation, what type is it?
Step7: Final registration... |
2,287 | <ASSISTANT_TASK:>
Python Code:
import pynmea2
msg = pynmea2.parse("$GPGGA,184353.07,1929.045,S,02410.506,E,1,04,2.6,100.00,M,-33.9,M,,0000*6D", check=True)
msg
msg.lat, msg.latitude, msg.latitude_minutes, msg.latitude_seconds
msg.lon, msg.longitude, msg.longitude_minutes, msg.longitude_seconds
pynmea2.parse("$GPVTG,... | <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: GGA - GPS Fix Data
Step2: The lat and lon attributes are in DDDMM.SSSSS format while latitude and longitude are their float values.
Step3: VT... |
2,288 | <ASSISTANT_TASK:>
Python Code:
using React, Interact
s = slider(0:0.01:1, label="Slider X:")
signal(s)
display(typeof(s));
isa(s, Widget)
display(typeof(signal(s)));
isa(signal(s), Signal{Float64})
s
xsquared = lift(x -> x*x, signal(s))
using Color
lift(x -> RGB(x, 0.5, 0.5), signal(s))
r = slider(0:0.01:1, label... | <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: Interact.jl provides interactive widgets for IJulia. Interaction relies on React.jl reactive programming package. React provides the type Signal... |
2,289 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# we will use numpy and matplotlib for all the following examples
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
def mexican_hat(x, mu, sigma):
return 2 / (np.sqrt(3 * sigma) * np.pi**0.25) * (1 - x**2 / sigma**2) * np.exp(-x**2 / (2 * sigma**2... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The mexican hat function/wavelet is the rescaled negative second derivative of the gaussian function (the probability distribution function of t... |
2,290 | <ASSISTANT_TASK:>
Python Code:
exp = butler.get("calexp", {"visit":903334, "detector":22, "instrument":"HSC"})
print(exp.getWcs())
wcs = butler.get("calexp.wcs", {"visit":903334, "detector":22, "instrument":"HSC"})
print(wcs)
vinfo = butler.get("calexp.visitInfo", {"visit":903334, "detector":22, "instrument":"HSC"})
pr... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We can get all data IDs/Dimensions.
Step2: In Gen3, we can also get the WCS and the file URI without dumping the images as Python objects, for... |
2,291 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
from matplotlib.pyplot import show, plot
import matplotlib.pyplot as plt
# 初始化一个全0的数组来存放剩余资本
# 以参数10000调用binomial函数，进行10000轮硬币赌博游戏
cash = np.zeros(10000)
cash[0] = 1000
outcome = np.random.binomial(9, 0.5, size=len(cash))
# 模拟每一轮抛硬币的结果，更新cash数组
# 打印出... | <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: 1. 随机数
Step2: 2. 超几何分布
Step3: 3. 连续分布
Step4: 3.2 对数正态分布
|
2,292 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt
import statsmodels.formula.api as smf
df_Obama = pd.read_csv("data/Fox_polls - Obama Job.csv")
df_Iran_Deal = pd.read_csv("data/Fox_polls - Iran Deal.csv")
df_Iran_Nego = pd.read_csv("data/Fox_polls - Iran Nego.csv")
... | <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 for the Obama Love and Iran Deal Approval
Step2: Now for Obama Love and Confidence in Negotiations with Iran
|
2,293 | <ASSISTANT_TASK:>
Python Code:
!ipython nbconvert 'Working With Markdown Cells.ipynb'
!ipython nbconvert --to=html 'Working With Markdown Cells.ipynb'
!ipython nbconvert --to=latex 'Working With Markdown Cells.ipynb'
!ipython nbconvert --to=latex 'Working With Markdown Cells.ipynb' --post=pdf
pyfile = !ipython ... | <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: Html is the default value (that can be configured) , so the verbose form would be
Step2: You can also convert to latex, which will take care of... |
2,294 | <ASSISTANT_TASK:>
Python Code:
# Import modules
import random
import numpy as np
# Import PySwarms
from pyswarms.single import GlobalBestPSO
# Algorithm paramters
random.seed(0)
# The weight capacity of the knapsack
capacity = 50
number_of_items = 10
item_range = range(number_of_items)
value = [random.randint(1,numbe... | <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: Knapsack problem
Step3: Early stopping using ftol
Step4: Extending property using ftol_iter
|
2,295 | <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
<END_TASK>
<USER_TASK:>
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... |
2,296 | <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: REINFORCE agent
Step2: Hyperparameters
Step3: Environment
Step4: We can render this environment to see how it looks. A free-swinging pole is ... |
2,297 | <ASSISTANT_TASK:>
Python Code:
# system functions that are always useful to have
import time, sys, os
# basic numeric setup
import numpy as np
# inline plotting
%matplotlib inline
# plotting
import matplotlib
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
# seed the random number generator... | <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: One of the key assumptions of (Static) Nested Sampling is that we "shrink" according to
Step2: We will now sample from this distribution using ... |
2,298 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pylab as plt
%matplotlib notebook
import h5hep
import pps_tools as pps
filename = 'dimuons_1000_collisions.hdf5'
pps.download_drive_file(filename)
### Other examples: ###
#pps.download_file_from_google_drive('dimuons_1000_collisions.hdf5','data/file... | <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 need the particle physics specific libraries. If you installed the libraries from the command shell properly as shown in the local setup ... |
2,299 | <ASSISTANT_TASK:>
Python Code:
import os
import requests
from datetime import datetime
from clint.textui import progress
import pandas
pandas.set_option('display.float_format', lambda x: '%.2f' % x)
pandas.set_option('display.max_columns', None)
def download_csv(name):
Accepts the name of a calaccess.download... | <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: Download raw data
Step3: Itemized receipts reported by campaigns
Step5: Hack down RCPT_CD table outside of Python
Step6: Concatenate them tog... |
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