Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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Python Code:
%matplotlib inline
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', validation_size=0)
img = mnist.train.images[2]
plt.imshow(img.reshape((28, 28)), cmap='... | <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: Below I'm plotting an example image from the MNIST dataset. These are 28x28 grayscale images of handwritten digits.
Step2: We'll train an autoe... |
9,601 | <ASSISTANT_TASK:>
Python Code:
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../../data')
# training data
train_income=['Low','Medium','Low','High','Low','High','Medium','Medium','High','Low','Medium',
'Medium','High','Low','Medium']
train_age = ['Old','Young','Old','Young','Old','Young','Young','Old','... | <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 want to create a decision tree from the above training dataset. The first step for that is to encode the data into numeric values and bind th... |
9,602 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
a = np.array( [2,3,4,-1,-2] )
print('Dimensões: a.shape=', a.shape )
print('Tipo dos elementos: a.dtype=', a.dtype )
print('Imprimindo o array completo:\n a=',a )
b = np.array( [ [1.5, 2.3, 5.2],
[4.2, 5.6, 4.4] ] )
print('Um array bidimensional, dimens... | <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: Veja a seguir uma matriz bidimensional de dados ponto flutuante de 2 linhas e 3 colunas. Observe que a tupla do shape aumenta para a esquerda,
S... |
9,603 | <ASSISTANT_TASK:>
Python Code:
N = 0.001
R = 100
ml = ModelMaq(kaq=5, z=[10, 0], Saq=2e-4, tmin=1e-3, tmax=1e4)
ca = CircAreaSink(ml, 0, 0, 100, tsandN=[(0, 0.001)])
ml.solve()
ml.xsection(-200, 200, 0, 0, t=[0.1, 1, 10], figsize=(12, 4), sstart=-200)
x = np.linspace(-200, 200, 200)
qx = np.zeros_like(x)
for t in [0.1,... | <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: Circular area-sink and well
Step2: Two layers
|
9,604 | <ASSISTANT_TASK:>
Python Code:
# generic scientific/ipython header
from __future__ import print_function
from __future__ import division
import os, sys
import copy
import numpy as np
# Parent dictionary of in-common Movetypes-with-Odds to be used as the basis for each parameter's moves
parentMovesWithOdds = {}
parentM... | <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: Biasing Moves
Step2: Make 'moves with weights' dictionaries specialized for each parameter type
Step3: Make master dict-of-dicts so that param... |
9,605 | <ASSISTANT_TASK:>
Python Code:
import deepchem as dc
import numpy as np
class PongEnv(dc.rl.GymEnvironment):
def __init__(self):
super(PongEnv, self).__init__('Pong-v0')
self._state_shape = (80, 80)
@property
def state(self):
# Crop everything outside the play area, reduce the image size,
# and... | <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 create a network to implement the policy. We begin with two convolutional layers to process
Step2: We will optimize the policy using t... |
9,606 | <ASSISTANT_TASK:>
Python Code:
#example task: print each character in a word
#one way to do is use a series of print statements
word = 'lead'
print(word[0])
print(word[1])
print(word[2])
print(word[3])
word = 'tin'
print(word[0])
print(word[1])
print(word[2])
print(word[3])
#better approach
word = 'lead'
for char in 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: This is a bad appoach b/c
Step2: uses a for loop to repeat operations
Step3: Let's trace the execution
Step4: finding the length of a strin... |
9,607 | <ASSISTANT_TASK:>
Python Code:
# Import NumPy and seed random number generator to make generated matrices deterministic
import numpy as np
np.random.seed(2)
# Create a matrix with random entries
A = np.random.rand(4, 4)
print(A)
# Compute eigenvectors of A
evalues, evectors = np.linalg.eig(A)
print("Eigenvalues: {}".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: We can compute the eigenvectors and eigenvalues using the NumPy function linalg.eig
Step2: The matrix A is non-symmetric, hence it is no surpri... |
9,608 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas as pd #used for reading/writing data
import numpy as np #numeric library library
from matplotlib import pyplot as plt #used for plotting
import sklearn #machine learning library
wineData = pd.read_csv('data/winequality/winequality-red.csv', sep=';')
wine... | <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 inspect the contents of the data
Step2: All columns except the last one are the input parameters of the system, obtained from real vines... |
9,609 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from wmf import wmf
from fwm import utils
import numpy as np
import pylab as pl
DEM=wmf.read_map_raster('raster/dem2.tif',True)
DIR=wmf.read_map_raster('raster/dir.tif',True)
wmf.cu.nodata=-9999.0; wmf.cu.dxp=30.0
DIR[DIR<=0]=wmf.cu.nodata.astype(int)
DIR=wmf.cu.dir_r... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Lectura de mapas de direcciones y de elevación
Step2: Trazado de la cuenca y preparación de la misma
Step3: Parámetros físicos.
Step4: Prepar... |
9,610 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 3, figsize=(13,4))
x = np.linspace(0, 2*np.pi, 30*np.pi).astype(np.float32)
ax[0].plot(x, np.sin(x), label='sin')
ax[1].plot(x, np.cos(x), label='cos')
ax[2].plot(x, np.tan(x), label='tan')
ax[0].plot(x, np.arcs... | <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: Contents
Step2: <a id='More_trigonometric_functions'></a>
|
9,611 | <ASSISTANT_TASK:>
Python Code:
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install empiricaldist
# Get utils.py
from os.path import basename, exists
def download(url):
filename = basename(url)
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: In <<_TheEuroProblem>> I presented a problem from David MacKay's book, Information Theory, Inference, and Learning Algorithms
Step2: And we use... |
9,612 | <ASSISTANT_TASK:>
Python Code:
from sklearn import datasets
iris = # complete
fig, ax = plt.subplots()
ax.scatter( # complete
# complete
# complete
# complete
from sklearn.cluster import # complete
Kcluster = # complete
Kcluster.fit( # complete
fig, ax = plt.subplots()
ax.scatter( # complete
# complete
# complete
# ... | <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 1b
Step2: Problem 2) $k$-means clustering
Step3: Problem 2b
Step4: Problem 2c
Step5: Problem 2d
Step6: That doesn't look right at... |
9,613 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
from data_helper_functions import *
from IPython.display import display
pd.options.display.max_columns = 999
%matplotlib inline
with np.load('data/X.npz') as data: #old X, don't use, start at "Now with all channels..."
X = data['X']
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Random Forest seems to be giving the best results, so we'll stick with that for now
Step2: Maybe I should only use the AOD values since the sen... |
9,614 | <ASSISTANT_TASK:>
Python Code:
!git clone https://github.com/google-research/google-research.git
import sys
import os
import tarfile
import urllib
import zipfile
sys.path.append('./google-research')
# TF streaming
from kws_streaming.models import models
from kws_streaming.models import utils
from kws_streaming.models ... | <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: Examples of streaming and non streaming inference with TF/TFlite
Step4: Load wav file
Step5: Prepare batched model
Step6: Run inference with ... |
9,615 | <ASSISTANT_TASK:>
Python Code:
import random
from bisect import bisect_left
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
%matplotlib inline
class PropSelection(object):
def __init__(self, n):
self._n = n
self._frequencies = [0] * n
def copy_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: A Proportional Selection Base Class
Step2: Linear Walk
Step3: Bisecting Search
Step4: Stochastic Acceptance
Step5: First Demonstration
Step6... |
9,616 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import tensorflow as tf
with open('../sentiment-network/reviews.txt', 'r') as f:
reviews = f.read()
with open('../sentiment-network/labels.txt', 'r') as f:
labels = f.read()
reviews[:2000]
from string import punctuation
all_text = ''.join([c for c in reviews if... | <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 preprocessing
Step2: Encoding the words
Step3: Encoding the labels
Step4: If you built labels correctly, you should see the next output.... |
9,617 | <ASSISTANT_TASK:>
Python Code:
# 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 writing, sof... | <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: Intermediate Python - Objects
Step2: You can create your own object using the class keyword.
Step3: Why did we use the keyword class and not o... |
9,618 | <ASSISTANT_TASK:>
Python Code:
from plotSlope import slope
data = pd.read_csv(os.path.join('data','EU_GDP_2007_2013.csv'),index_col=0,na_values='-')
(data/1000).head()
f = slope(data/1000,kind='interval',height= 12,width=20,font_size=12,dpi=150,savename='EU_interval.png',title = u'title')
color = {"France":'b','Germ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Load data from file into a data frame
Step2: Plot it
Step3: Other example
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Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
view_sentence_range = (0, 10)
DON'T MODIFY AN... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Language Translation
Step3: Explore the Data
Step6: Implement Preprocessing Function
Step8: Preprocess all the data and save it
Step10: Chec... |
9,620 | <ASSISTANT_TASK:>
Python Code:
# Author: Roman Goj <roman.goj@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne.event import make_fixed_length_events
from mne.datasets import sample
from mne.time_frequency import csd_epochs
from mne.beamformer import tf_dics
from mne.viz import plot_source_spectrogram
print(__... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Read raw data
Step2: Time-frequency beamforming based on DICS
|
9,621 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
# RMS Titanic data visualization code
from titanic_visualizations import survival_stats
from IPython.display import display
%matplotlib inline
# Load the dataset
in_file = 'titanic_data.csv'
full_data = pd.read_csv(in_file)
# Print the first few ent... | <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: From a sample of the RMS Titanic data, we can see the various features present for each passenger on the ship
Step3: The very same sample of th... |
9,622 | <ASSISTANT_TASK:>
Python Code:
import os
os.environ['PYPMJ_CONFIG_FILE'] = '/path/to/your/config.cfg'
import sys
sys.path.append('..')
import pypmj as jpy
import numpy as np
jpy.load_extension('materials')
jpy.MaterialData?
jpy.MaterialData.materials.keys()
GaAs = jpy.MaterialData(material = 'gallium_arsenide')
G... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Now we can import pypmj and numpy. Since the parent directory, which contains the pypmj module, is not automatically in our path, we need to app... |
9,623 | <ASSISTANT_TASK:>
Python Code:
from astropy.io import ascii
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
%matplotlib inline
tbl = ascii.read('n121_match.cat')
def transform(v,i):
c1f555 = [-0.09,-0.124]
c2f555 = [0.034,0.018]
c1f814 = [0.06,0.001]
c2f814 = [-0.099,0.013]
for j in range(8):
... | <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: <hr>
Step2: Se obtuvo la isócrona de la imagen (línea verde). Al menos pasa cerca de los puntos obtenidos por fotometría.
Step3: <hr>
|
9,624 | <ASSISTANT_TASK:>
Python Code:
import sys
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
import statsmodels.sandbox.stats.multicomp as mc
import multiprocessing as mp
%matplotlib inline
import os
os.environ['OMP_NUM_THREADS'] = str(1)
import warnings
warnings.filterwarnings('ignore')
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: 0.0 Basic parameters
Step2: 1.0 Run information transfer mapping procedure
Step4: 1.2 Perform network-to-network information transfer mapping ... |
9,625 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nuist', 'sandbox-2', 'atmos')
# 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: 1... |
9,626 | <ASSISTANT_TASK:>
Python Code:
# boilerplate code
from __future__ import print_function
import os
from io import BytesIO
import numpy as np
from functools import partial
import PIL.Image
from IPython.display import clear_output, Image, display, HTML
import tensorflow as tf
#!wget https://storage.googleapis.com/downloa... | <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 id='loading'></a>
Step6: To take a glimpse into the kinds of patterns that the network learned to recognize, we will try to generate images ... |
9,627 | <ASSISTANT_TASK:>
Python Code:
!pip3 install meetup-api pandas pytest matplotlib clarifai
import meetup.api
import pandas as pd
API_KEY = ''
event_id=''
def get_members(event_id):
client = meetup.api.Client(API_KEY)
rsvps=client.GetRsvps(event_id=event_id, urlname='_ChiPy_')
member_id = ','.join([str(i['me... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This part of the exercise is straight from the previous team project. We use the meetup.com api to load get the ChiPy members who RSVP-ed for on... |
9,628 | <ASSISTANT_TASK:>
Python Code:
M = np.array(((2.0, 0.0), ( 0.0, 1.0)))
K = np.array(((3.0,-2.0), (-2.0, 2.0)))
p = np.array(( 0.0, 1.0)); w = 2.0
print_mat(M, pre='\\boldsymbol{M}=m\\,', fmt='%d')
print_mat(K, pre='\\boldsymbol{K}=k\\,', fmt='%d')
print_mat(p[:,None], pre=r'\boldsymbol{p}(t) = p_0\,', fmt='%d',
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Computing the eigenvalues and the eigenvectors
Step2: The @ operator stands, in this context, for matrix multiplication.
Step3: Modal Response... |
9,629 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import matplotlib.pyplot as plt
df3 = pd.read_csv('../data/df3')
%matplotlib inline
df3.plot.scatter(x='a',y='b',c='red',s=50
df3.info()
df3.head()
df3.plot.scatter(x='a',y='b',c='red',s=50,figsize=(12,3))
df3['a'].plot.hist()
plt.style.use('ggplot')
df3['a'].plot.h... | <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: Recrea la siguiente grafica de puntos de b contra a.
Step2: Crea un histograma de la columna 'a'.
Step3: Las graficas se ven muy bien, pero de... |
9,630 | <ASSISTANT_TASK:>
Python Code:
# remove after testing
%load_ext autoreload
%autoreload 2
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from urllib.request import urlopen
from sklearn.decomposition import PCA
from mclearn.viz import (plot_class_distribution,
... | <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: Distribution of Classes
Step2: Maps of Classes
Step3: Here are the distribution map of galaxies, stars, and quasars, respectively.
Step4: Pho... |
9,631 | <ASSISTANT_TASK:>
Python Code:
from scipy import stats
import numpy as np
np.random.seed(42)
x = np.random.normal(0, 1, 1000)
y = np.random.normal(0, 1, 1000)
statistic, p_value = stats.ks_2samp(x, 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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Description:
|
9,632 | <ASSISTANT_TASK:>
Python Code:
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
iris= sns.load_dataset('iris')
iris.head()
grd = sns.PairGrid(data=iris)
#then you can assign what you want plotted for diagonal, above diagonal, below diagonal.
# when mapping, pass just function pointers, dont cal... | <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: Pairgrids
Step2: lmplot() for scatter and regression per category
Step3: FacetGrid
Step4: Suppose we want to visualize total_bill by time of ... |
9,633 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn.datasets import make_blobs
from sklearn.svm import LinearSVC
x = np.linspace(-2.0, 2.0, num=100)
def huberizedHingeLoss(x, h):
if x > 1+h:
ret... | <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: Explain how the huberized hinge loss relates to the regular hinge loss and to the misclassification error loss.
Step2: 2.1.3 Numerical checks
... |
9,634 | <ASSISTANT_TASK:>
Python Code:
import cv2
from PIL import Image
import math
import copy
#the usual data science stuff
import os,sys
import glob
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
%matplotlib inline
ladyboy_big_input = '../data/ladyboy_big/'
ladyboy_big_output = '../data/processed/lad... | <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: Ladyboy
Step2: Ladyboy Big
Step3: Girl
|
9,635 | <ASSISTANT_TASK:>
Python Code:
# Package imports
import os
import pandas as pd
import numpy as np
import statistics
from ipywidgets import interact
import ipywidgets as widgets
# Bokeh Plots
from bokeh.io import output_notebook, push_notebook, show
from bokeh.plotting import figure
output_notebook()
# Hide warnings
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: Choose a file to check
Step2: Load and prepare data
Step3: Time Series
Step4: Measured vs Calibrated
Step5: Differences
|
9,636 | <ASSISTANT_TASK:>
Python Code:
import os
import matplotlib.pyplot as plt
from eniric import config, precision
# Load a spectrum
from astropy.io import fits
test_data = config.paths["phoenix_raw"]
print(test_data)
wav = fits.getdata(os.path.join(test_data, "WAVE_PHOENIX-ACES-AGSS-COND-2011.fits"))
flux = fits.getdata(
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: This precision has not been scaled to a specific flux/SNR level.
Step2: Scaling Effects
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Python Code:
import warnings
warnings.filterwarnings("ignore", category=FutureWarning)
import os, sys
sys.path = [os.path.abspath("../../")] + sys.path
from deep_learning4e import *
from notebook4e import *
psource(SimpleRNNLearner)
from keras.datasets import imdb
data = imdb.load_data(num_words=5000... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: train_data and val_data are needed when creating a simple rnn learner. Both attributes take lists of examples and the targets in a tuple. Please... |
9,638 | <ASSISTANT_TASK:>
Python Code:
# Import the library we need, which is Pandas
import pandas as pd
# Read the csv file of Monthwise Quantity and Price csv file we have.
df = pd.read_csv('MonthWiseMarketArrivals_clean.csv')
df.shape
df.head()
# Get the typeof each column
df.dtypes
# Changing the date column to a Time ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: You will find the variable df used quite often to store a dataframe
Step2: Understand Data Structure and Types
Step3: Data Structure
Step4: S... |
9,639 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
from IPython.display import display
from ipywidgets import *
from mpl_toolkits.mplot3d import Axes3D
import plotBL
HTML('../style/code_to... | <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 section specific modules
Step2: 4.5.2 $uv$ coverage
Step3: From the list above, you can select different configurations corresponding ... |
9,640 | <ASSISTANT_TASK:>
Python Code:
!pip install -q tf-nightly-gpu-2.0-preview
import tensorflow as tf
print(tf.__version__)
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
x_train.shape
import numpy as np
# add empty color dimension
x_train = np.expand_dims(x_train, -1)
x_test = np.expand... | <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: Alternative
Step2: Checking our results (inference)
|
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Python Code:
fbvary_results = []
for file in glob.glob('runs/evolved_mu_f_b_vary?replicate?datetime.datetime(2019, 5, *).hdf5'):
try:
fbvary_results.append(popev.PopulationReader(file))
except OSError:
pass
favary_results = []
for file in glob.glob('runs/evolved_mu_f_a_vary?rep... | <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: Graphs of population distribution and trajectories for base parameter set
Step2: Given a delta_f of .03 and a K of 1 million, we expect it woul... |
9,642 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
diff_raw = pd.read_csv(
"../../buschmais-spring-petclinic_fork/git_diff.log",
sep="\n",
names=["raw"])
diff_raw.head(16)
index_row = diff_raw.raw.str.startswith("index ")
ignored_diff_rows = (index_row.shift(1) | index_row.shift(2))
diff_raw = diff_raw[~(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: The output is the commit data that I've describe above where each in line the text file represents one row in the DataFrame (without blank lines... |
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Python Code:
import coral as cor # alternative you can import each module by itself e.g. from coral import design
dir(cor) # dir lists everything in a module/object. Ignore the double underscore items.
dna = cor.DNA("ATGC")
print "DNA: {}".format(dna)
# You can also run methods on the object - in t... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Top-level
Step2: As you can see above, to make DNA, RNA, or Peptide objects you just invoke the correct sequence. command and give it a valid s... |
9,644 | <ASSISTANT_TASK:>
Python Code:
import datetime
import os
import shutil
import numpy as np
import pandas as pd
import tensorflow as tf
from google.cloud import aiplatform
from matplotlib import pyplot as plt
from tensorflow import keras
from tensorflow.keras.callbacks import TensorBoard
from tensorflow.keras.layers impo... | <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 raw data
Step2: Use tf.data to read the CSV files
Step3: Build a simple keras DNN model
Step4: Next, we create the DNN model. The Sequen... |
9,645 | <ASSISTANT_TASK:>
Python Code:
import tellurium as te; te.setDefaultPlottingEngine('matplotlib')
%matplotlib inline
antimony_model = '''J0: -> y; -x;J1: -> x; y;x = 1.0;y = 0.2;'''
r = te.loada(antimony_model)
r.simulate(0,100,1000)
r.plot()
import tellurium as te
model = ''''''
model_backup = '''
model 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: Everything in a single tool - tellurium
Step2: Antimony is a language that is analog to SBML Systems Biology Markup Language but human-readable... |
9,646 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import Image
from IPython.display import HTML
from IPython.display import IFrame
assert True # leave this to grade the import statements
Image(url = 'http://newsroom.unl.edu/releases/downloadables/photo/20090923solenoid.jpg', width = 600, height = 600)
assert 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: Basic rich display
Step2: Use the HTML object to display HTML in the notebook that reproduces the table of Quarks on this page. This will requi... |
9,647 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from simmit import smartplus as sim
import os
v = np.random.rand(6)
trace = sim.tr(v)
print v
print trace
v = np.random.rand(6)
v_dev = sim.dev(v)
print v
print v_dev
v = np.random.rand(6)
Mises_sig = sim.Mises_stres... | <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: tr(vec)
Step2: dev(vec)
Step3: Mises_stress(vec)
Step4: Mises_strain(vec)
Step5: eta_stress(vec)
Step6: eta_strain(vec)
Step7: v2t_stress(... |
9,648 | <ASSISTANT_TASK:>
Python Code:
def findquadrant(point,size):
y,x = point
halfsize = size/2
if x < -halfsize:
if y > halfsize: return [0,0]
if y < -halfsize: return [2,0]
return [1,0]
if x > halfsize:
if y > halfsize: return [0,2]
if y < -halfsize: return [2,2]
... | <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: randomwalk each point for 1 day equivalent
Step2: make a grid from a scatter of many points
Step3: Find maximum time step without leaking mosq... |
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Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import StandardScaler
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_samples, silhouette_score
# We resort to a third party library to plot silhouette diagrams
! pi... | <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: Goal
Step2: The anomalies are the minority.
Step3: In unsupervised approaches, the label is not used
Step4: All the methods we will use, exce... |
9,650 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from __future__ import print_function
import os
import os.path as osp
import numpy as np
import pysptools.ml as ml
import pysptools.skl as skl
from sklearn.model_selection import train_test_split
home_path = os.environ['HOME']
source_path = osp.join(home_path, 'dev-data... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: X_train and y_train sets are built
Step2: We set an hypothesis and call the Gradient Boosting cross validation
Step3: Same but this time we ca... |
9,651 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
f=lambda x: np.sqrt(x[:,0]**2 + x[:,1]**2) #definición de norma2
density=1e-5
density_p=int(2.5*10**3)
x=np.arange(-1,1,density)
y1=np.sqrt(1-x**2)
y2=-np.sqrt(1-x**2)
x_p=np.random.uniform(-1,1,(density_p,2))
ind=f(x_p)<1
x_p_subset=x_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: Norma $2$
Step2: Norma $1$
Step3: Norma $\infty$
Step4: ```{admonition} Observación
Step5: en este caso $D=\left[\begin{array}{cc} \frac{1}{... |
9,652 | <ASSISTANT_TASK:>
Python Code:
from bs4 import BeautifulSoup
from urllib.request import urlopen
html_str = urlopen("http://static.decontextualize.com/widgets2016.html").read()
document = BeautifulSoup(html_str, "html.parser")
h3_tag = document.find_all('h3')
print(type(h3_tag))
[tag.string for tag in h3_tag]
print(len... | <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, in the cell below, use Beautiful Soup to write an expression that evaluates to the number of <h3> tags contained in widgets2016.html.... |
9,653 | <ASSISTANT_TASK:>
Python Code:
import gensim
import os
import collections
import smart_open
import random
# Set file names for train and test data
test_data_dir = '{}'.format(os.sep).join([gensim.__path__[0], 'test', 'test_data'])
lee_train_file = test_data_dir + os.sep + 'lee_background.cor'
lee_test_file = test_data... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: What is it?
Step2: Define a Function to Read and Preprocess Text
Step3: Let's take a look at the training corpus
Step4: And the testing corpu... |
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Python Code:
%matplotlib inline
import os
from pprint import pprint
import shutil
import subprocess
import urllib.request
import h5py
import numpy as np
import matplotlib.pyplot as plt
import openmc.data
# Download ENDF file
url = 'https://t2.lanl.gov/nis/data/data/ENDFB-VII.1-neutron/Gd/157'
filenam... | <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: ENDF
Step2: We can access the parameters contained within File 32 in a similar manner to the File 2 parameters from before.
Step3: The newly c... |
9,655 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from quantities import ms, s, Hz
from elephant.spike_train_generation import homogeneous_poisson_process, homogeneous_gamma_process
help(homogeneous_poisson_process)
t_start = 275.5 * ms
print(t_start)
t_start2 = 3. *... | <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 function requires four parameters
Step2: The nice thing about Quantities is that once the unit is specified you don't need to worry about r... |
9,656 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd # pandas for handling mixed data sets
import numpy as np # numpy for basic math and matrix operations
import matplotlib.pyplot as plt # pyplot for plotting
# scikit-learn for machine learning and data preprocessing
from sklearn.decompositio... | <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: Perform basic feature extraction
Step2: Compress x1 and x2 into a single principal component
Step3: Principal components analysis finds vector... |
9,657 | <ASSISTANT_TASK:>
Python Code:
# Run some setup code for this notebook.
import random
import numpy as np
from cs231n.data_utils import load_CIFAR10
import matplotlib.pyplot as plt
# This is a bit of magic to make matplotlib figures appear inline in the notebook
# rather than in a new window.
%matplotlib inline
plt.rcPa... | <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 would now like to classify the test data with the kNN classifier. Recall that we can break down this process into two steps
Step2: Inline Qu... |
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Python Code:
%pylab nbagg
import sygma as s
reload(s)
s.__file__
from scipy.integrate import quad
from scipy.interpolate import UnivariateSpline
import numpy as np
s1=s.sygma(iolevel=0,mgal=1e11,dt=1e7,tend=1.3e10,sn1a_rate='power_law',beta_pow=-1,
imf_type='salpeter',imf_bdys=[1,30],hards... | <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: Power law & Maoz
Step2: Maoz and power law with -1 is the same as visible below.
Step3: Gaussian
Step4: gauss_dtd=[4e9,3.2e9] (as mentioned i... |
9,659 | <ASSISTANT_TASK:>
Python Code:
!git clone https://github.com/google-research/google-research.git
import sys
import os
import tarfile
import urllib
import zipfile
sys.path.append('./google-research')
# TF streaming
from kws_streaming.models import models
from kws_streaming.models import utils
from kws_streaming.layers.... | <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: Example of model training
Step4: Set path to data
Step5: Set path to a model with config
Step6: Model training
Step7: Run model evaluation
|
9,660 | <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:... |
9,661 | <ASSISTANT_TASK:>
Python Code::
mean_absolute_error(y_test, predictions)
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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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Description:
|
9,662 | <ASSISTANT_TASK:>
Python Code:
import math
import torch
import gpytorch
from matplotlib import pyplot as plt
%matplotlib inline
%load_ext autoreload
%autoreload 2
train_x1 = torch.rand(50)
train_x2 = torch.rand(50)
train_y1 = torch.sin(train_x1 * (2 * math.pi)) + torch.randn(train_x1.size()) * 0.2
train_y2 = torch.cos... | <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 up training data
Step2: Set up a Hadamard multitask model
Step3: Training the model
Step4: Make predictions with the model
|
9,663 | <ASSISTANT_TASK:>
Python Code:
# Load library
import pandas as pd
# Create dates
dates = pd.Series(pd.date_range('2/2/2002', periods=3, freq='M'))
# View data
dates
# Show days of the week
dates.dt.weekday_name
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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:
Step1: Create Date And Time Data
Step2: Show Days Of The Week
|
9,664 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn
seaborn.set_style('whitegrid')
def r2(actual, predicted):
if isinstance(actual, list):
actual = np.array(actual)
if isinstance(predicted, list):
predicted = np.... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: We'll get a perfect R2=1 if actual and predicted values are the same
Step2: Now if we're a bit off on our predictions R2 will be still pretty h... |
9,665 | <ASSISTANT_TASK:>
Python Code:
%install_ext https://raw.githubusercontent.com/meduz/ipython_magics/master/tikzmagic.py
%load_ext tikzmagic
%%tikz
\filldraw [fill=white] (0,0) circle [radius=1cm];
\foreach \angle in {60,30,...,-270} {
\draw[line width=1pt] (\angle:0.9cm) -- (\angle:1cm);
}
\draw (0,0) -- (90:0.8cm);
... | <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: 만약 이 확률 변수의 확률 분포가 0 이상 360 미만의 구간내에서 균일 분포(uniform distribution) 모형을 가진다고 가정하면 답은 0(zero)이다.
Step2: 누적 밀도 함수 즉 cdf는 다음과 같은 특징을 가진다.
Step3: 이... |
9,666 | <ASSISTANT_TASK:>
Python Code:
document = ET.parse( './data/mondial_database.xml' )
import pandas as pd
root = document.getroot()
#get infant mortality of each country, add to heap if under capacity
#otherwise check if new value is greater than smallest.
inf_mort = dict()
for element in document.iterfind('country'):
... | <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: Not all the entries have an infant mortality rate element. So we need to make sure loop loops for the element named 'infant_mortality'.
Step2: ... |
9,667 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import scipy.optimize as opt
def modl(t,A,o,l,d):
return A*np.exp(-1*t)*np.cos(o*t)+d
thetabest,thetacov=opt.curve_fit(modl,tdata,ydata,np.array((6,1,1,0)),dy,absolute_sigma=True)
assert True # leave this to grade ... | <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: Fitting a decaying oscillation
Step2: Now, using curve_fit to fit this model and determine the estimates and uncertainties for the parameters
|
9,668 | <ASSISTANT_TASK:>
Python Code:
# import sqlite3 here
#open connection to database
# 1st challenge: Write a sql query to search for the name: zoidberg
# Note: It will return 0
# Add the zoidberg data to the database below. remeber to commit()
# Search for zoidberg again. This time, you should get the results below:
# ... | <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: It returned empty because there is no zoidberg in our list.
Step2: Next
Step3: Next
Step4: There is a problem with the above
|
9,669 | <ASSISTANT_TASK:>
Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
# Use Floyd's cifar-10 dataset if ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
9,670 | <ASSISTANT_TASK:>
Python Code:
import medusa
from medusa.test import create_test_ensemble
ensemble = create_test_ensemble("Staphylococcus aureus")
ensemble.base_model.objective.expression
ensemble.base_model.objective = 'EX_cpd00011_e'
print(ensemble.base_model.objective.expression)
ensemble.base_model.objective = 'bi... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: The current objective function is the biomass reaction (bio1)--to change this, just set the objective to another reaction. Let's change the obje... |
9,671 | <ASSISTANT_TASK:>
Python Code:
# Import helpful libraries and setup our project, bucket, and region
import os
PROJECT = "cloud-training-demos" # REPLACE WITH YOUR PROJECT ID
BUCKET = "cloud-training-demos-ml" # REPLACE WITH YOUR BUCKET NAME
REGION = "us-central1" # REPLACE WITH YOUR BUCKET REGION e.g. us-central1
# Do ... | <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: <h2> Create ML dataset using Dataflow </h2>
Step3: Let's pull a sample of our data into a dataframe to see what it looks like.
Step4: Let's ch... |
9,672 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import interp2d
from qutip import *
# shared parameters
gamma = 1 # decay rate
tlist = np.linspace(0, 13, 300)
taulist = tlis... | <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: Introduction
Step2: Setup the operators, Hamiltonian, and initial state
Step3: Calculate the emission flux
Step4: Visualize the emission flux... |
9,673 | <ASSISTANT_TASK:>
Python Code:
TMPrimaryHeader = BitStruct('transfer_frame_version_number' / BitsInteger(2),
'spacecraft_id' / BitsInteger(10),
'virtual_channel_id' / BitsInteger(3),
'ocf_flag' / Flag,
'maste... | <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 frames from CSV file. proxy_time is set by the client when sending the frame (using groundstation PC clock). server_time is set by the serv... |
9,674 | <ASSISTANT_TASK:>
Python Code:
class Stack():
def __init__(self):
self.items = []
def push(self, item):
self.items.append(item)
def pop(self):
return self.items.pop()
def peek(self):
return self.items[len(self.items) - 1]
def isEmpty(self):
... | <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: Stack examples
|
9,675 | <ASSISTANT_TASK:>
Python Code:
!sudo chown -R jupyter:jupyter /home/jupyter/training-data-analyst
# Ensure the right version of Tensorflow is installed.
!pip freeze | grep tensorflow==2.6
import tensorflow as tf
import pandas as pd
import numpy as np
import shutil
print(tf.__version__)
# In CSV, label is the first col... | <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: Read data created in the previous chapter.
Step2: <h2> Train and eval input functions to read from Pandas Dataframe </h2>
Step3: Our input fun... |
9,676 | <ASSISTANT_TASK:>
Python Code:
df_ranking=pd.read_csv('article_uni.csv', index_col=0)
print(df_ranking.shape)
df_ranking.head()
df.article_uni.replace('The London School of Economics and Political Science (United-Kingdom)',
'London School of Economics and Political Science', inplace=True)
from sklearn.preprocessing... | <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: a=pd.pivot_table(df,index=["article_uni"],values=["article_rating"],aggfunc=[len,np.mean], columns='year')
Step2: b=df[df.article_pub_date>=dat... |
9,677 | <ASSISTANT_TASK:>
Python Code:
import re
def tokenize(s):
'''Transform the string s into a list of tokens. The string s
is supposed to represent an arithmetic expression.
'''
lexSpec = r'''([ \t]+) | # blanks and tabs
([1-9][0-9]*|0) | # number
([()]) ... | <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 function tokenize receives a string s as argument and returns a list of tokens.
Step2: Implementing the Recursive Descend Parser
Step3: Th... |
9,678 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
## This is a list of everything in the module
np.__all__
an_array = np.array([0,1,2,3,4,5,6])
print an_array
print
print type(an_array)
print
help(an_array)
A = np.zeros((4,4))
print A
print
print A.shape
print
print A.diagonal()
print
A[0,0] = 2.0
print A
np.fill_diago... | <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: Speed
Step2: Views of the data (are free)
Step3: Exercise
Step4: Broadcasting is a way of looping on arrays which have "compatible" but unequ... |
9,679 | <ASSISTANT_TASK:>
Python Code:
# Standard Python libraries
from __future__ import absolute_import, division, print_function, unicode_literals
import os
import time
import numpy as np
import glob
import matplotlib.pyplot as plt
import PIL
import imageio
from IPython import display
import sklearn
import seaborn as sns
sn... | <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: Linear regression in 1d <a class="anchor" id="linreg-1d"></a>
Step2: Linear regression for boston housing <a class="anchor" id="linreg-boston">... |
9,680 | <ASSISTANT_TASK:>
Python Code:
class SimpleClass():
def __init__(self, str_input):
print("SIMPLE" + str_input)
class ExtendedClass(SimpleClass):
def __init__(self):
print('EXTENDED')
s = ExtendedClass()
class ExtendedClass(SimpleClass):
def __init__(self):
super().__init__(" My Str... | <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 child class will use its own initialization method, if not specified otherwise.
Step2: If we want to use initialization from the parent cla... |
9,681 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display, SVG
from IPython.display import Javascript
s =
<svg width="100" height="100">
<circle cx="50" cy="50" r="20" fi... | <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: Interact with SVG display
Step5: Write a function named draw_circle that draws a circle using SVG. Your function should take the parameters of ... |
9,682 | <ASSISTANT_TASK:>
Python Code:
# Import spaCy and load the language library. Remember to use a larger model!
import spacy
nlp = spacy.load('en_core_web_md')
# Choose the words you wish to compare, and obtain their vectors
word1 = nlp.vocab['wolf'].vector
word2 = nlp.vocab['dog'].vector
word3 = nlp.vocab['cat'].vector
#... | <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: CHALLENGE
Step2: Task #2
Step3: CHALLENGE
|
9,683 | <ASSISTANT_TASK:>
Python Code:
# Load a text file of integers:
y = np.loadtxt("yelp_data/upvote_labels.txt", dtype=np.int)
# Load a text file with strings identifying the 1000 features:
featureNames = open("yelp_data/upvote_features.txt").read().splitlines()
featureNames = np.array(featureNames)
# Load a csv of floats,... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: In the Yelp Question in HW1, please normalize the data so that it has the same L2 norm. We will grade it either way, but please state clearly wh... |
9,684 | <ASSISTANT_TASK:>
Python Code:
from erddapy import ERDDAP
e = ERDDAP(
server="https://gliders.ioos.us/erddap",
protocol="tabledap",
response="csv",
)
e.dataset_id = "whoi_406-20160902T1700"
e.variables = [
"depth",
"latitude",
"longitude",
"salinity",
"temperature",
"time",
]
e.cons... | <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 populate the object a dataset id, variables of interest, and
Step2: Longer introduction
Step3: All the get_<methods> will return a... |
9,685 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import sys
import os
import shutil
import numpy as np
from subprocess import check_output
# Import flopy
import flopy
# Set the name of the path to the model working directory
dirname = "P4-3_Hubbertville"
datapath = os.getcwd()
modelpath = os.path.join(datapath, dirna... | <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 a New Directory and Change Paths
Step2: Define the Model Extent, Grid Resolution, and Characteristics
Step3: Create the MODFLOW Model Ob... |
9,686 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'ec-earth-consortium', 'ec-earth3-lr', 'ocean')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contrib... | <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... |
9,687 | <ASSISTANT_TASK:>
Python Code:
a = {"x" : 1, "z" : 3}
b = {"y" : 2, "z" : 4}
from collections import ChainMap
c = ChainMap(a, b)
print(c["x"])
print(c["y"])
print(c["z"])
len(c)
list(c.keys())
list(c.values())
c["z"] = 10
c["w"] = 40
del c["x"]
a
del c["y"]
values = ChainMap()
values["x"] = 1
# Add a new mapping
va... | <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: 现在假设你必须在两个字典中执行查找操作(比如先从 a 中找，如果找不到再在 b 中找)。 一个非常简单的解决方案就是使用 collections 模块中的 ChainMap 类。比如：
Step2: 讨论
Step3: 如果出现重复键，那么第一次出现的映射值会被返回。 因此，例子程序... |
9,688 | <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
<END_TASK>
<USER_TASK:>
Description:
Step1: Set parameters and read data
Step2: Now, we estimate a set of xDAWN filters for the epochs (which contain only
Step3: Epochs are denoised by c... |
9,689 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from scipy import constants
import scipy.integrate
import scipy.special as func
from MeshedFields import *
import pygmsh
Ra = 0.020
Ri = 0.002
lca = 0.003
lci = 0.0003
geom = pygmsh.built_in.Geometry()
# we create the initial geometry as a streched ellipse to create
# ... | <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: Create a meshed screen with a central hole
Step2: The screen is placed at the origin. A beam is assumed to propagate in z direction<br>
Step3: ... |
9,690 | <ASSISTANT_TASK:>
Python Code:
# improve on the "stopword" filters here
#
# :-) (ask me about a smilie lexicon)
# not-so-simple words? (ask me about a regex for compound words)
# python variables names with underscores? (regex)
f = os.path.join(DATA_PATH, 'text.csv.gz')
df.to_csv(f, encoding='utf8', compression='gzip',... | <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: Make sure you can read it back in!
|
9,691 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
from formulae import design_matrices
rng = np.random.default_rng(7355608)
SIZE = 10
data = pd.DataFrame(
{
"y1": rng.normal(size=SIZE),
"y2": rng.choice(["A", "B", "C"], size=SIZE),
"x": rng.normal(size=SIZE),
"z"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Let's simulate some data to use throughout examples here. The number of observations isn't too important. We keep it low to understand what is g... |
9,692 | <ASSISTANT_TASK:>
Python Code:
mnist = mx.test_utils.get_mnist()
image = np.reshape(mnist['train_data'],(60000,28*28))
label = image
image_test = np.reshape(mnist['test_data'],(10000,28*28))
label_test = image_test
[N,features] = np.shape(image) #number of examples and features
f, (ax1, ax2, ax3, ax4) = plt.su... | <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 can optionally save the parameters in the directory variable 'model_prefix'. We first create data iterators for MXNet, with each batch of dat... |
9,693 | <ASSISTANT_TASK:>
Python Code:
%load_ext google.cloud.bigquery
%%bigquery daily_flakiness
select
job,
start_date,
round(sum(if(flaked=1,passed,runs))/sum(runs),3) build_consistency,
round(1-sum(flaked)/count(distinct commit),3) commit_consistency,
round (sum(flaked)/count(distinct commit),3) flake... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Compute daily flakiness of kubeflow presubmit tests
Step2: Daily flake rate of all presubmit tests over time
Step3: Daily build and commit co... |
9,694 | <ASSISTANT_TASK:>
Python Code:
y, sr = librosa.load('audio/simple_piano.wav')
ipd.Audio(y, rate=sr)
est_onsets = librosa.onset.onset_detect(y=y, sr=sr, units='time')
est_onsets
ref_onsets = numpy.array([0, 0.270, 0.510, 1.02,
1.50, 2.02, 2.53, 3.01])
librosa.display.waveplot(y, sr=sr, alpha... | <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: Detect Onsets
Step2: Load a fictional reference annotation.
Step3: Plot the estimated and reference onsets together.
Step4: Evaluate
Step5: ... |
9,695 | <ASSISTANT_TASK:>
Python Code:
# only necessary if you're running Python 2.7 or lower
from __future__ import print_function, division
from six.moves import range
# import matplotlib and define our alias
from matplotlib import pyplot as plt
# plot figures within the notebook rather than externally
%matplotlib inline
# 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: Overview
Step2: Problem
Step3: Now that our data is in an accessible format, let's try and get it into something we can do math with. Copy ov... |
9,696 | <ASSISTANT_TASK:>
Python Code:
import os
CWD = os.getcwd()
import girder_client
from pandas import read_csv
from imageio import imread
from histomicstk.annotations_and_masks.masks_to_annotations_handler import (
get_contours_from_mask,
get_single_annotation_document_from_contours,
get_annotation_documents_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: 1. Connect girder client and set parameters
Step2: Let's inspect the ground truth codes file
Step3: Read and visualize mask
Step4: 2. Get con... |
9,697 | <ASSISTANT_TASK:>
Python Code:
# Load image
import cv2
import numpy as np
from matplotlib import pyplot as plt
# Load image as grayscale
image_bgr = cv2.imread('images/plane_256x256.jpg')
image_gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)
image_gray = np.float32(image_gray)
# Set corner detector parameters
bloc... | <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 image
Step2: Define Corner Parameters
Step3: Detect Corners
Step4: Mark Corners
Step5: View Image
|
9,698 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
import theano
import theano.tensor as T
from carl.distributions import Normal
p = Normal(mu=0.0, sigma=1.0)
reals = np.linspace(-5, 5, num=1000)
pdf = p.pdf(X=reals.reshape(-1, 1)) # X is a 2D array of shape n_sam... | <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: Base API
Step2: Advanced API
Step3: Note
Step4: By construction, p.mu is a Theano symbolic expression which depends on several inputs, in thi... |
9,699 | <ASSISTANT_TASK:>
Python Code:
from sklearn.ensemble import RandomForestClassifier
from IPython.display import YouTubeVideo, HTML
YouTubeVideo("XOEN9W05_4A")
#The Donald Bren School of Information and Computer Sciences - University of California, Irvine
info_file = 'http://archive.ics.uci.edu/ml/machine-learning-datab... | <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: Watch the video of the type of activity that was recorded
Step2: The data is extracted from the .zip file on the UCI website
Step3: The datase... |
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