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Python Code:
from conf import LisaLogging
LisaLogging.setup()
%pylab inline
import json
import os
# Support to access the remote target
import devlib
from env import TestEnv
# Import support for Android devices
from android import Screen, Workload, System, ViewerWorkload
from target_script import Targ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Test environment setup
Step2: Workload definition
Step3: Workload execution
Step4: Traces visualisation
|
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Python Code:
import numpy as np
import matplotlib.pyplot as plt
from sklearn.pipeline import Pipeline
from sklearn.svm import SVR
from sklearn import cross_validation
np.random.seed(0)
n_samples = 200
kernels = ['linear', 'poly', 'rbf']
true_fun = lambda X: X ** 3
X = np.sort(5 * (np.random.rand(n_sam... | <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: Learning Curves
Step2: They all come from the same underlying process. But if you were asked to make a prediction, you would be more likely to ... |
7,802 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%reload_ext autoreload
%autoreload 2
from fastai.conv_learner import *
PATH = "data/cifar10/"
os.makedirs(PATH, exist_ok=True)
classes = ('plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck')
stats = (np.array([ 0.4914 , 0.48216, 0.44653]), n... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Viewing Data
Step2: Learner Initialization Tests
Step3:
Step4: Could num_classes be used for loss-choice logic?
Step5: Darknet53 Tests
Step... |
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Python Code:
import numpy as np
import matplotlib.pyplot as plt
from numpy.polynomial import Chebyshev as T
from numpy.polynomial.hermite import hermval
%matplotlib inline
def p_cheb(x, n):
RETURNS T_n(x)
value of not normalized Chebyshev polynomials
$\int \frac1{\sqrt{1-x^2}}T_m(x)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: Multivariate function approximation
Step5: Now, let's approximate the function with polynomials taking different maximal power $n$ and the corr... |
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Python Code:
# As usual, a bit of setup
import time, os, json
import numpy as np
import matplotlib.pyplot as plt
from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array
from cs231n.rnn_layers import *
from cs231n.captioning_solver import CaptioningSolver
from cs231n.cl... | <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 Captioning with LSTMs
Step2: Load MS-COCO data
Step3: LSTM
Step4: LSTM
Step5: LSTM
Step6: LSTM
Step7: LSTM captioning model
Step8: ... |
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Python Code:
from dolfin import *
from rbnics import *
@PullBackFormsToReferenceDomain()
@ShapeParametrization(
("x[0]", "x[1]"), # subdomain 1
("mu[0] * (x[0] - 1) + 1", "x[1]"), # subdomain 2
)
class EllipticOptimalControl(EllipticOptimalControlProblem):
# Default initialization of 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: 3. Affine Decomposition
Step2: 4. Main program
Step3: 4.2. Create Finite Element space (Lagrange P1)
Step4: 4.3. Allocate an object of the El... |
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Python Code:
import pandas as pd
import matplotlib
matplotlib.style.use('ggplot')
%matplotlib inline
training_data = {
'x': [0, 1, 2, 3],
'y': [4, 7, 7, 8]
}
train_df = pd.DataFrame.from_dict(training_data)
train_df
train_df.plot(kind='scatter', x='x', y='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:
Step1: Let's plot the data to see what it looks like
|
7,807 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
import sys
sys.path.append("../lib/")
import seaborn as sns
import pandas as pd
from operator import itemgetter
from dataContainer import DataContainer, dataClassMapper
container = DataContainer() # load the data
data = container.collapse() # rem... | <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 DataContainer class is a container that integrates the available datasets. It allows easy loading and combining (and hopefully more cool stu... |
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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: Train an LSTM weather forecasting model for the Coral Edge TPU
Step2: Prepare the climate dataset
Step3: Visualize the data
Step4: This heat ... |
7,809 | <ASSISTANT_TASK:>
Python Code:
# Show matplotlib plots inline (nicely formatted in the notebook)
%matplotlib inline
# Import libraries necessary for this project
import numpy as np
import pandas as pd
import renders as rs
import seaborn as sns
from matplotlib import pylab as plt
from IPython.display import display # ... | <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 Exploration
Step2: Implementation
Step3: Question 1
Step4: Answer
Step5: Question 2
Step6: Question 3
Step7: Answer
Step8: Observati... |
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Python Code:
from __future__ import print_function
import numpy as np
from PIL import Image # for bmp import
from glob import glob
from scipy.misc import imresize
import matplotlib.pyplot as plt
import math
import time
%matplotlib inline
def showImage(imageToPlot):
plt.figure(figsize=(2, 4))
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: Loading and studying the 342x719 image of fantom
Step2: Let's assume vertical line points are spaced by 1cm each. This corresponds to a depth o... |
7,811 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import os, sys
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import pandas as pd
import requests
import StringIO
# set matplotlib style
matplotlib.style.use('ggplot')
sitename = 'alligatorriver'
roiname = 'DB_0001'
infile = "{}_{}_roistats.csv".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: While the data can be read directly from a URL we'll start by doing the simple thing of reading the CSV file directly from our local disk.
Step2... |
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Python Code:
%load_ext autoreload
%autoreload 2
import numpy as np
policy = np.array([[0.3, 0.2, 0.5], [0.5, 0.4, 0.1], [0.8, 0.1, 0.1]])
print("This is represents the policy with 3 states and 3 actions p(row=a|col=s):\n", np.matrix(policy))
# 'raw_rewards' variable contains rewards obtained after tr... | <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: Policy Evaluation by Dynamic Programming
Step2: Policy Evaluation by Linear Programming
Step3: The result stays the same.
Step4: As can be s... |
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Python Code:
from pyspark.sql import SQLContext
# adding the PySpark module to SparkContext
sc.addPyFile("https://raw.githubusercontent.com/seahboonsiew/pyspark-csv/master/pyspark_csv.py")
import pyspark_csv as pycsv
# you may need to modify this line if the filename or path is different.
sqlContext =... | <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: Enter the following command in the next cell to look at the first record and click Run
Step2: Enter the following command in the next cell to g... |
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Python Code:
# Authors: Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Nicolas P. Rougier (graph code borrowed from his matplotlib gallery)
#
# License: BSD (3-clause)
import numpy as np
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: Load our data
Step2: Compute inverse solutions and their connectivity
Step3: Make a connectivity plot
Step4: Make two connectivity plots in t... |
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Python Code:
OUTFN = "AK_NCDC_FirstOrderStations.json"
SAVEDATA = False
stationdata = []
for station in all_stations:
path = os.path.join(endpoint_stations, "GHCND:{}".format(station))
fullbase = requests.compat.urljoin(baseurl, path)
r = requests.get(
fullbase,
headers=cu... | <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
|
7,816 | <ASSISTANT_TASK:>
Python Code:
import flopy
# load the model
model_ws = os.path.join("Freyberg","extra_crispy")
ml = flopy.modflow.Modflow.load("freyberg.nam",model_ws=model_ws)
# Because this model is old -- it predates flopy's modelgrid implementation.
# And because modelgrid has been implemented without backward co... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The plot shows the Freyberg (1988) model domain. The colorflood is the hydraulic conductivity ($\frac{m}{d}$). Red and green cells coorespond ... |
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Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
%matplotlib inline
import phoebe
from phoebe import u # units
import numpy as np
logger = phoebe.logger()
b = phoebe.default_binary()
b.add_dataset('lc', compute_phases=phoebe.linspace(0,1,101))
b.run_compute(irrad_method='none')
times = b.get_value('... | <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 first line is only necessary for ipython noteboooks - it allows the plots to be shown on this page instead of in interactive mode. Dependi... |
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Python Code:
#Initializations
from IPython.core.display import HTML
HTML(open("../styles/custom.css", "r").read())
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import math
pi = math.pi
from pint import UnitRegistry
ur = UnitRegistry()
# ideal gas parameters for air
gamma = 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: Coefficient of Discharge
Step2: Choked Flow
Step3: Critical Pressure Ratio
Step4: Procedure to Calculate the Airbag Vent Mass Flowrate
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7,819 | <ASSISTANT_TASK:>
Python Code:
import PIL
import PIL.Image
import scipy
import scipy.misc
ref = PIL.Image.open("sky.jpg")
ref = numpy.array(ref)
ref = scipy.misc.imresize(ref, 0.25, interp="bicubic")
target = PIL.Image.open("bird.jpg")
target = numpy.array(target)
target ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: compute strict interior and border regions
Step2: compute seamless clone (red)
|
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Python Code:
%matplotlib inline
from math import pi, sin, cos
import numpy as np
import openmc
fuel = openmc.Material(name='fuel')
fuel.add_element('U', 1.0)
fuel.add_element('O', 2.0)
fuel.set_density('g/cm3', 10.0)
clad = openmc.Material(name='zircaloy')
clad.add_element('Zr', 1.0)
clad.set_density... | <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 begin by creating the materials that will be used in our model.
Step2: With our materials created, we'll now define key dimensions in our... |
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Python Code:
import sympy
sympy.init_printing()
Theta = sympy.Matrix(sympy.symbols(
'theta_0:3_0:4')).reshape(3,4)
def Y(n):
return sympy.Matrix(sympy.symbols(
'G_x:z_0:{:d}'.format(n+1))).T.reshape(3, n+1)
def C(n):
return sympy.ones(n+1, 1)
def T(n):
return sympy.Matrix(sympy... | <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 let's us derive a recurisve form.
|
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Python Code:
import pandas as pd
%matplotlib inline
# load the raw data
df = pd.read_csv('../Data/shaneiphone_exp2.csv')
# plot gravity signal
df[['motionGravityX', 'motionGravityY', 'motionGravityZ']].plot()
# plot gyroscope signal [indices 7000 to 10000 include a series of sharp turns in the Censi... | <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 XYZ axes from SensorLog are in the frame of the iPhone. On the way to Censio, my phone was placed flat on the driver seat. On the return t... |
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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... |
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Python Code:
# import the required libraries
import numpy as np
import time
import random
import cPickle
import codecs
import collections
import os
import math
import json
import tensorflow as tf
from six.moves import xrange
# libraries required for visualisation:
from IPython.display import SVG, disp... | <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: define the path of the model you want to load, and also the path of the dataset
Step4: We define two convenience functions to encode a stroke i... |
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Python Code:
#%matplotlib inline
import matplotlib.pyplot as plt
plt.scatter((1,2,2.5), (2,1,2)); plt.xlim((0,3)); plt.ylim((0,3));
import numpy as np
A = np.array(((1,1),(2,1),(2.5,1))); b = np.array((2,1,2)) # Create A and b
x = np.dot(np.dot(np.linalg.inv(np.dot(A.T, A)), A.T), b) # Project b onto... | <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: Another way to express this problem is to say, I would like to find the equation of a line that satisfies all of the above points. Take the foll... |
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Python Code:
import numpy as np
import networkx as nx
from matplotlib import pyplot as plt
%matplotlib inline
from scipy.io import loadmat
import warnings
warnings.filterwarnings( 'ignore' )
def mcl_iter( A, p = 2, alpha = 2, theta = 1e-8, rel_eps = 1e-4, niter = 10000 ) :
## Convert A into a transit... | <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: Problems
Step2: The agorithm is desinged to transform the graph connectivity in such a way as to disconnect different communities and concentra... |
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Python Code:
import pandas as pd
import numpy as np
from fbprophet import Prophet
DATA_HOME_DIR = '/data/airline'
df = pd.read_csv(DATA_HOME_DIR+'/international-airline-passengers.csv',
sep=';',
names=['ds', 'y'],
header=0,
parse_dat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: The input to Prophet is always a dataframe with two columns
Step2: It looks like we have a exponential growth trend in the data, so in order to... |
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Python Code:
import moldesign as mdt
import moldesign.units as u
mdt.configure()
molecule = mdt.read('data/butane.xyz')
molecule
viewer = molecule.draw()
viewer # we tell Jupyter to draw the viewer by putting it on the last line of the cell
print(viewer.selected_atoms)
molecule.set_energy_model... | <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
Step2: 2. Read in a molecular structure
Step3: Jupyter notebooks will automatically print out the value of the last statement in any ... |
7,829 | <ASSISTANT_TASK:>
Python Code:
platform = 'lendingclub'
use_cuda = True
dtype = torch.cuda.FloatTensor
save_path = "model_dump/nn_1_0_0/"
store = pd.HDFStore(
dc.home_path+'/justin_tinkering/data_science/lendingclub/{0}_store.h5'.
format(platform),
append=True)
loan_info = store['train_filtered_columns']
co... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Until I figure out a good imputation method (e.g. bayes PCA), just drop columns with null still
Step2: instantiate network
Step3: get the weig... |
7,830 | <ASSISTANT_TASK:>
Python Code:
def resp_elas(m,c,k, cC,cS,w, F, x0,v0):
wn2 = k/m ; wn = sqrt(wn2) ; beta = w/wn
z = c/(2*m*wn)
wd = wn*sqrt(1-z*z)
# xi(t) = R sin(w t) + S cos(w t) + D
det = (1.-beta**2)**2+(2*beta*z)**2
R = ((1-beta**2)*cS + (2*beta*z)*cC)/det/k
S = ((1-beta**2)*cC - (2*be... | <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: Plastic response
Step2: An utility function
Step3: The system parameters
Step4: Derived quantities
Step5: Load definition
Step6: The actual... |
7,831 | <ASSISTANT_TASK:>
Python Code:
import frame_methods
import engine_methods as em
import itertools
import pandas as pd
import matplotlib.pyplot as plt
from scipy.stats import norm
import numpy as np
from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets
### Setup frame environm... | <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 must first setup a sample environment with a frame and components.
Step2: Scoring
Step3: Weight Distribution- Y
Step4: Collisions
Step5: ... |
7,832 | <ASSISTANT_TASK:>
Python Code:
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from astropy.time import Time
import astropy.units as u
from astropy.coordinates import EarthLocation
import pytz
import datetime
from astroplan import Observer
# Set up an observe... | <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: Convert that astropy.time.Time back to a localized datetime, arriving back at the original datetime (only this one is localized)
Step2: Let's s... |
7,833 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
%matplotlib inline
from sklearn.model_selection import KFold
from sklearn.ensemble import RandomForestClassifier as RFC
from sklearn.ensemble import AdaBoostClassifier as AdaBoost
from sklearn.multicl... | <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 begin by loading and examining our raw dataset, containing data obtained through the TMDB API and saved previously as a CSV file.
Step2: ... |
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Python Code:
%matplotlib inline
import sys, os
sys.path.insert(0, os.path.expanduser('~/work/git/github/taku-y/pymc3'))
import theano
theano.config.floatX = 'float64'
import matplotlib.pyplot as plt
import numpy as np
import pymc3 as pm
import pandas as pd
data = pd.read_csv('../data/radon.csv')
coun... | <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: Plotting the hierarchical model trace -its found values- from 500 iterations onwards (right side plot) and its accumulated marginal values (left... |
7,835 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'noaa-gfdl', 'gfdl-esm4', '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... |
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Python Code:
boys = int(input('How many boys are in the class: '))
girls = int(input('How many girls are in the class:'))
pupils = boys + girls
print('There are', pupils,'in the class altogether')
bigger_number = 12
smaller_number = 10
difference = bigger_number - smaller_number
print('The difference... | <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: Subtraction
Step2: Multiplication
Step3: Division
Step4: Extra Useful Bit
Step5: Working with Strings - aka Text
Step6: Change line 3 of th... |
7,837 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'messy-consortium', 'sandbox-1', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor(... | <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... |
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Python Code:
import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import urllib2
from __future__ import division
plt.style.use('ggplot')
np.random.seed(1)
url = ('https://raw.githubusercontent.com/Upward-Spiral-Science'
'/data/master/syn-density/output.csv')
data = urllib2.urlo... | <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: Using image data
Step2: Grabbing images from website
Step3: Now just need to figure out z-axis. The z values in the image data go from 2917-41... |
7,839 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.append('..')
import pandexo.engine.justdoit as jdi
exo_dict = jdi.load_exo_dict()
#WASP-43
exo_dict['star']['jmag'] = 9.995 # J magnitude of the system
exo_dict['star']['hmag'] = 9.397 # H magnitude of the system
#WASP-43b
exo_... | <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: Edit Inputs
Step2: Edit stellar and planet inputs
Step3: Step 2) Load in instrument dictionary
Step4: Edit HST/WFC3 detector and observation ... |
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Python Code:
def bcdToHexaDecimal(s ) :
len1 = len(s )
check = 0
num = 0
sum = 0
mul = 1
ans =[]
i = len1 - 1
while(i >= 0 ) :
sum +=(ord(s[i ] ) - ord('0' ) ) * mul
mul *= 2
check += 1
if(check == 4 or i == 0 ) :
if(sum <= 9 ) :
ans . append(chr(sum + ord('0' ) ) )
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
7,841 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mohc', 'sandbox-2', 'atmos')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "emai... | <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... |
7,842 | <ASSISTANT_TASK:>
Python Code:
from keras.layers import Bidirectional, Concatenate, Permute, Dot, Input, LSTM, Multiply
from keras.layers import RepeatVector, Dense, Activation, Lambda
from keras.optimizers import Adam
from keras.utils import to_categorical
from keras.models import load_model, Model
import keras.backen... | <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 - Translating human readable dates into machine readable dates
Step2: You've loaded
Step3: You now have
Step4: 2 - Neural machine translati... |
7,843 | <ASSISTANT_TASK:>
Python Code:
# standard import if you're using "formula notation"
import statsmodels.formula.api as smf
lm = smf.ols(formula='Sales ~ TV', data=data).fit()
lm.params
# lets make a prediction if TV advertising would spend $50,000
# Statsmodels formula interface expects a datarames
X_new = pd.DataFrame... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Plotting the Least Squares Line
Step2: null hypothesis
Step3: The most common way to evaluate the overall fit of a linear model is by the R-sq... |
7,844 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
dat_file = '../examples/1-rosenbrock/dakota.dat'
data = numpy.loadtxt(dat_file, skiprows=1, unpack=True, usecols=[0,2,3,4])
data
plot(data[1,], data[2,], 'ro')
xlim((-2, 2))
ylim((-2, 2))
xlabel('$x_1$')
ylabel('$x_2$')
title('Planview of parameter study locations')
plot(... | <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 the Dakota tabular data file.
Step2: Plot the path taken in the vector parameter study.
Step3: Plot the values of the Rosenbrock function... |
7,845 | <ASSISTANT_TASK:>
Python Code:
# Copyright 2020 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless 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:
Step3: Installation
Step4: Supported tasks and wrappers
Step5: These are the wrappers that can be applied to the tasks
Step6: Discrete Relative Acti... |
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Python Code:
import pandas as pd
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import cross_val_score
df = pd.read_csv("../input/fe-course-data/concrete.csv")
df.head()
X = df.copy()
y = X.pop("CompressiveStrength")
# Train and score baseline model
baseline = RandomF... | <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 can see here the various ingredients going into each variety of concrete. We'll see in a moment how adding some additional synthetic feature... |
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Python Code:
# create some noise
a = np.random.randn(50, 600, 100)
a.shape
# create some noise with higher variance and add bias.
b = 2. * np.random.randn(*a.shape) + 1.
b.shape
# manufacture some loss function
# there are n_epochs * n_batchs * batch_size
# recorded values of the loss
loss = 10 / np.... | <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: MultiIndex Dataframe
Step2: Visualization
Step3: CSV Read/Write
Step4: HDF5 Read/Write
Step5: Furthermore, the file sizes are significantly ... |
7,848 | <ASSISTANT_TASK:>
Python Code:
## Q2 Solution.
def hash(x):
return math.fmod(3 * x + 2, 11)
for i in xrange(1,12):
print hash(i)
## Q3 Solution.
prob = 1.0 / 10
a = (1 - prob)**4
print a
b = (1 - ( 1 - (1 - prob)**2) )**2
print b
c = (1 - (1.0 /10 * 1.0 / 9))
print c
## Q5 Solution.
vec1 = np.array([2, 1, 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: Q3.
Step2: Q4.
Step3: Q6.
Step4: Q7.
Step5: Q8.
Step6: Q10.
Step7: Q11.
Step8: Q13.
|
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Python Code:
c1 = lambda x: x + 1
c2 = lambda x: -x + 2
x1 = np.linspace(0.01, 2, 10)
x2 = np.linspace(-2, -0.01, 10)
plt.plot(x1, c1(x1), label=r"$y = x + 1$")
plt.plot(x2, c2(x2), label=r"$y = -x + 2$")
plt.plot(0, 2, 'wo', markersize=7)
plt.plot(0, 1, 'wo', markersize=7)
ax = plt.axes()
ax.set_ylim... | <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: Even though the value of $y$ for when $x = 0$ is undefined we can say something about the limits of this function.
Step2: Note that dividing b... |
7,850 | <ASSISTANT_TASK:>
Python Code:
__author__ = 'Shahariar Rabby'
import email
import imaplib
import ctypes
import getpass
import threading
from playsound import playsound
def user():
# ORG_EMAIL = "@gmail.com"
# FROM_EMAIL = "your mail" + ORG_EMAIL
# FROM_PWD = "your pass"
FROM_EMAIL = raw_input("insert E... | <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: User Details Function
Step2: Login function
Step3: Mail Server
Step4: This function call Check_Unseen in every 15 sec.
|
7,851 | <ASSISTANT_TASK:>
Python Code:
# Model Configuration
UNITS = 2 ** 11 # 2048
ACTIVATION = 'relu'
DROPOUT = 0.1
# Training Configuration
BATCH_SIZE_PER_REPLICA = 2 ** 11 # powers of 128 are best
# TensorFlow
import tensorflow as tf
print("Tensorflow version " + tf.__version__)
# TF 2.3 version
# Detect and init the TPU
... | <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 next few sections set up the TPU computation, data pipeline, and neural network model. If you'd just like to see the results, feel free to s... |
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Python Code:
cosmo = LambdaCDM(H0=70, Om0=0.3, Ode0=0.7, Tcmb0=2.725)
# check to make sure we have defined the bpz filter path
if not os.getenv('EZGAL_FILTERS'):
os.environ['EZGAL_FILTERS'] = (f'{os.environ["HOME"]}/Projects/planckClusters/MOSAICpipe/bpz-1.99.3/FILTER/')
model = ezgal.model('bc03... | <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: Create Stellar Population
Step2: Calculate a few things to get going.
Step5: Define the functions that we'll need
Step6: Start Calculating th... |
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Python Code:
# Imports and utility functions
import time
import numpy as np
import matplotlib.pyplot as plt
from qutip.sesolve import sesolve
from qutip.solver import Options, solver_safe
from qutip import sigmax, sigmay, sigmaz, identity, tensor, basis, Bloch
def timing_val(func):
def wrapper(*ar... | <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: Time dependent control functions
Step2: Hamiltonians, initial state and measurements
Step3: Solving the dynamics
Step4: Function type
Step5: ... |
7,854 | <ASSISTANT_TASK:>
Python Code:
results_file = '../data/lda_data_8.pickle'
n_iters = 10
for n in range(n_iters):
print "iteration %d" % n
print results_file
X, Y, Yaudio = classification.load_data_from_pickle(results_file)
# get only 80% of the dataset.. to vary the choice of outliers
X, _, Y, _ = tr... | <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: Estimate precision at K
|
7,855 | <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
from IPython.html import widgets
def print_sum(a, b):
Print the sum of the arguments a and b.
print(a + b)
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step2: Interact basics
Step3: Use the interact function to interact with the print_sum function.
Step5: Write a function named print_string that prin... |
7,856 | <ASSISTANT_TASK:>
Python Code:
from scipy import misc as scm
import os.path as op
import matplotlib.pyplot as plt
% matplotlib inline
datadir = '/tmp/113_1/'
im = scm.imread(op.join(datadir,'0090.png'))
plt.imshow(im, cmap='gray')
plt.show()
import os
import numpy as np
files = os.listdir(datadir) # get a list of all... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step 1
Step1: Step 2
Step2: It's also important to summarize what we've done, so that the user can Summarizing these results and those that require mo... |
7,857 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from sklearn.cluster import KMeans
def kmeans_missing(X, n_clusters, max_iter=10):
Perform K-Means clustering on data with missing values.
Args:
X: An [n_samples, n_features] array of data to cluster.
n_clusters: Number of clusters to form.
max... | <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: Filling up missing data with cluster algorithm
Step2: Example with fake data
Step3: 可以看出，采用全局平均值填充缺失值后，数据分布差别较大；相反采用聚类算法填充缺失值的效果较好。
Step4: 可以... |
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Python Code:
%load_ext autoreload
%autoreload 2
from __future__ import print_function
import numpy as np
import SDSS
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import copy
# We want to select galaxies, and then are only interested in their positions on the sky.
data = pd.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: The Correlation Function
Step2: Random Catalogs
Step3: Now let's plot both catalogs, and compare.
Step4: Estimating $\xi(\theta)$
|
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Python Code:
%matplotlib inline
import pandas as pd
import sklearn
import matplotlib.pyplot as plt
import seaborn as sns
# Setup Seaborn
sns.set_style("whitegrid")
sns.set_context("poster")
df_offers = pd.read_excel("./WineKMC.xlsx", sheetname=0)
df_offers.columns = ["offer_id", "campaign", "varietal... | <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
Step2: We see that the first dataset contains information about each offer such as the month it is in effect and several attributes about ... |
7,860 | <ASSISTANT_TASK:>
Python Code:
F=graphviz.Graph()#(engine='neato')
F.graph_attr['rankdir'] = 'LR'
F.edge('A_1','B_1')
F.edge('A_1','B_2')
F.edge('A_2','B_1')
F.edge('A_3','B_1')
F.edge('A_4','B_2')
F.edge('A_5','B_2')
F.edge('A_5','B_3')
F
F=graphviz.Graph()
F.graph_attr['rankdir'] = 'LR'
F.edge('A_1, A_2, A_3','B_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: The structure which we just described here happens to match a well-studied family of graphs known as Bipartite Graphs. There are tons of algorit... |
7,861 | <ASSISTANT_TASK:>
Python Code:
# Configure Jupyter so figures appear in the notebook
%matplotlib inline
# Configure Jupyter to display the assigned value after an assignment
%config InteractiveShell.ast_node_interactivity='last_expr_or_assign'
# import functions from the modsim.py module
from modsim import *
data = pd... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Code from the previous chapter
Step2: Interpolate the insulin data.
Step3: The glucose minimal model
Step5: Here's a version of make_system t... |
7,862 | <ASSISTANT_TASK:>
Python Code:
df = pd.read_csv('../data/date_fixed_running_data.csv')
df.head()
df['Unnamed: 0'].head()
df = pd.read_csv('../data/date_fixed_running_data.csv', parse_dates=['Date'])
df = pd.read_csv('../data/date_fixed_running_data.csv', parse_dates=[0])
df.head()
cols = ['Date', 'Miles', 'Time']
df... | <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 because when you save a data frame to a csv it doesn’t label the index column. So now our column is actually the ‘zero’ column. When you... |
7,863 | <ASSISTANT_TASK:>
Python Code:
import toytree
newick = "((a,b),(c, d));"
tre = toytree.tree(newick)
tre.draw();
URL = "https://treebase.org/treebase-web/search/downloadATree.html?id=11298&treeid=31264"
tre = toytree.tree(URL)
tre.draw(tip_labels_align=True, height=800, width=600);
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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:
Step1: Newick tree files
Step2: An example using a URL from treebase
|
7,864 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import matplotlib
import matplotlib.pyplot as mplt
from scipy import linalg
from scipy import io
### Ordinary Least Squares
### SOLVES 2-CLASS LEAST SQUARES PROBLEM
### LOAD DATA ###
### IF LoadClasses IS True, THEN LOAD DATA FROM FILES ###
### OTHERSIE, RANDOMLY GENERA... | <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 read in the example data. Note that you will need to update the filepaths below to work on your machine.
Step2: Now we can plot the da... |
7,865 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
import numpy as np
data_path = "C:/Users/Rishu/Desktop/dATA/boston/"
boston_data=pd.read_csv(data_path+'train.csv')
boston_data.info()
boston_data.head()
boston_data_test=pd.read_csv(data_path+'test.csv')
boston_data_test.head()
boston_data.describe()
import matplot... | <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: Loading the boston dataset - Train and Test
Step2: Understanding the distribution and relationship of the data
Step3: Plotting the target pric... |
7,866 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pynucastro as pyrl
files = ["c12-pg-n13-ls09",
"c13-pg-n14-nacr",
"n13--c13-wc12",
"n13-pg-o14-lg06",
"n14-pg-o15-im05",
"n15-pa-c12-nacr",
"o14--n14-wc12",
"o15--n15-wc12",
"o14-ap-f17-Ha9... | <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 collection of rates has the main CNO rates plus a breakout rate into the hot CNO cycle
Step2: To evaluate the rates, we need a composition... |
7,867 | <ASSISTANT_TASK:>
Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
# Generate plots inline
%matplotlib inline
import os
# Support to access the remote target
import devlib
from env import TestEnv
# RTApp configurator for generation of PERIODIC tasks
from wlgen import RTA, Ramp
# Setup targ... | <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 required modules
Step2: Target Configuration
Step3: Workload Execution and Power Consumptions Samping
Step4: Power Measurements Data
|
7,868 | <ASSISTANT_TASK:>
Python Code:
# 基础库导入
from __future__ import print_function
from __future__ import division
import warnings
warnings.filterwarnings('ignore')
warnings.simplefilter('ignore')
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import ipywidgets
%matplotlib inline
import os
import sys
... | <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: 下面读取上一节存储的训练集和测试集回测数据，如下所示：
Step2: 1. A股训练集主裁训练
Step3: 2. 验证A股主裁是否称职
Step4: order_has_result的交易单中记录了所买入时刻的交易特征，如下所示：
Step5: 可以通过一个一个迭代交易单，将交... |
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Python Code:
######################################
###THIS IS PSEUDOCODE; WILL NOT RUN###
######################################
###STEP 1: COMPUTATION OF FOREGROUND PROBABILITY###
cdfMapVolume = []
for image in volume:
#Get a distribution of intensities of the slice
dist = generateDistr... | <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: Write Code
Step2: 2.Generate Functionality Results
Step3: 3. Analyze Functionality Results
Step4: 2.Generate Results
Step5: 3. Analyze Resul... |
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Python Code:
# TensorFlow and tf.keras
import matplotlib.pyplot as plt
# Helper libraries
import numpy as np
import tensorflow as tf
from tensorflow import keras
print(tf.__version__)
fashion_mnist = keras.datasets.fashion_mnist
(train_images, train_labels), (
test_images,
test_labels,
) = fa... | <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 Fashion MNIST dataset
Step2: Loading the dataset returns four NumPy arrays
Step3: Explore the data
Step4: Likewise, there are 60,0... |
7,871 | <ASSISTANT_TASK:>
Python Code:
import random
import numpy as np
import matplotlib.pyplot as plt
import quantities as pq
import neo
import elephant.unitary_event_analysis as ue
# Fix random seed to guarantee fixed output
random.seed(1224)
# Download data
!wget -Nq https://github.com/INM-6/elephant-tutorial-data/raw/mas... | <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 download a data file containing spike train data from multiple trials of two neurons.
Step3: Write a plotting function
Step4: Load da... |
7,872 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from astropy.table import Table, join
from astropy import units as u
from astropy.coordinates import SkyCoord, search_around_sky
import pickle
from tqdm import tnrange, tqdm_notebook
from IPython.display import clear_output
from mltier1 import parallel_process, SingleML... | <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: Coordinates
Step3: Import the ML parameeters
Step4: Define the main functions
Step6: The following function could be us... |
7,873 | <ASSISTANT_TASK:>
Python Code:
from __future__ import division, print_function, unicode_literals
import pandas as pd
s = pd.Series([2,-1,3,5])
s
import numpy as np
np.exp(s)
s + [1000,2000,3000,4000]
s + 1000
s < 0
s2 = pd.Series([68, 83, 112, 68], index=["alice", "bob", "charles", "darwin"])
s2
s2["bob"]
s2[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: Now let's import pandas. People usually import it as pd
Step2: Series objects
Step3: Similar to a 1D ndarray
Step4: Arithmetic operations on ... |
7,874 | <ASSISTANT_TASK:>
Python Code:
import math
print("pi = %1.15f" %math.pi)
print("pi = %1.15e" %math.pi)
import numpy as np
import scipy as scp
print(" numpy pi = %1.15f" %np.pi)
print(" scipy pi = %1.15f" %scp.pi)
print("1+2 = ", 1+2)
print("1.0+2 = ", 1.0+2)
print("1.0+2.0 = ", 1.0+2.0)
print("4/2 = ", 4/2)
print("4//... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <h2>1.2 Basic operators <FONT FACE="courier" style="color
Step2: <h3>1.3 Mathematical functions</h3>
Step3: <h3>1.4 Booleans</h3>
Step4: Let'... |
7,875 | <ASSISTANT_TASK:>
Python Code:
# just some basic setup for the purpose of this demo:
%matplotlib inline
from IPython.display import display
import matplotlib.pyplot as plt
import numpy as np
from sklearn.manifold import TSNE
#alternative you can use bh_sne:
#from tsne import bh_sne
# generate a set of 4900 random 3D ... | <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 default method tries to warp the cloud towards a square shape. It does that by calculating the outer hull of the cloud and remapping it to a... |
7,876 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import os
import six.moves.urllib as urllib
import sys
import tarfile
import tensorflow as tf
import zipfile
from collections import defaultdict
from io import StringIO
from matplotlib import pyplot as plt
from PIL import Image
import cv2
# This is needed to display th... | <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: Env setup
Step2: Object detection imports
Step3: Model preparation
Step4: Download Model
Step5: Load a (frozen) Tensorflow model into memory... |
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Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Romain Trachel <trachelr@gmail.com>
# Jean-Remi King <jeanremi.king@gmail.com>
#
# License: BSD (3-clause)
import mne
from mne import io, EvokedArray
from mne.datasets import sample
from mne.decoding import Ve... | <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
Step2: Decoding in sensor space using a LogisticRegression classifier
Step3: Let's do the same on EEG data using a scikit-learn... |
7,878 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import random
import sys
from sklearn import model_selection
import tensorflow as tf
!pip install git+https://github.com/google-research/tensorflow_constrained_optimization
import tensorflow_constrained_optimization as... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Pairwise Regression Fairness
Step2: Evaluation Metrics
Step3: We will also need functions to evaluate the pairwise error rates for a linear mo... |
7,879 | <ASSISTANT_TASK:>
Python Code:
#!/usr/bin/env python
# -*- Python -*-
import sys
import time
import subprocess
#
# set up user environment
# RtmToolsDir, MyRtcDir, etc.
#
# from set_env import * : you may provide a setup file like this
#
RtmToolsDir="../.."
MyRtcDir=".."
NS0="localhost:9876"
#
# import user tools
... | <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 user environmet
Step2: import user tools
Step3: RtmEnv
Step4: NameSpace
Step5: RtcHandle
Step6: activate and deactivate rtcs
Step7: ... |
7,880 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
log = pd.read_csv("../dataset/linux_blame_log.csv.gz")
log.head()
log.info()
log['timestamp'] = pd.to_datetime(log['timestamp'])
log.head()
log['age'] = pd.Timestamp('today') - log['timestamp']
log.head()
log['component'] = log['path'].str.split("/").str[:2].str.jo... | <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: Was haben wir hier eigentlich?
Step2: <b>1</b> DataFrame (~ programmierbares Excel-Arbeitsblatt), <b>4</b> Series (= Spalten), <b>5665947</b> R... |
7,881 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from pandas import DataFrame
from sklearn.metrics import accuracy_score
from sklearn.datasets import load_iris
seed = 2017
np.random.seed(seed)
data = load_iris()
idx = np.random.permutation(150)
X = data.data[idx]
y = data.target[idx]
from mlens.ensemble import SuperL... | <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: Ensemble guide
Step2: To check the performance of estimator in the layers, call the data
Step3: To round off, let's see how the ensemble as a ... |
7,882 | <ASSISTANT_TASK:>
Python Code:
from pymongo import MongoClient
import time
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.pyplot import *
import datetime as dt
import random as rnd
import warnings
import datetime as dt
import csv
%matplotlib inline
warnings.... | <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: Extraction of Data from MongoDB and Creating DataFrame
Step2: First five rows from the dataframe
Step3: Data filterxation
Step4: Data Explora... |
7,883 | <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: Build the C++ "lstpu" example for Coral
Step2: Download example from GitHub
Step3: Build lstpu example for Dev Board
Step4: The following lin... |
7,884 | <ASSISTANT_TASK:>
Python Code:
from learning import *
from probabilistic_learning import *
from notebook import *
%psource DataSet
iris = DataSet(name="iris")
print(iris.examples[0])
print(iris.inputs)
iris2 = DataSet(name="iris",exclude=[1])
print(iris2.inputs)
print(iris.examples[:3])
print("attrs:", iris.attrs... | <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: Class Attributes
Step3: To check that we imported the correct dataset, we can do the following
Step4: Which correctly prints ... |
7,885 | <ASSISTANT_TASK:>
Python Code:
set1={"pop", "rock", "soul", "hard rock", "rock", "R&B", "rock", "disco"}
set1
album_list =[ "Michael Jackson", "Thriller", 1982, "00:42:19", \
"Pop, Rock, R&B", 46.0, 65, "30-Nov-82", None, 10.0]
album_set = set(album_list)
album_set
music_genres = set(["pop"... | <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 process of mapping is illustrated in the figure
Step2: Now let us create a set of genres
Step3: Convert the following list to a set ['rap... |
7,886 | <ASSISTANT_TASK:>
Python Code:
import sys
print(sys.version)
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_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: 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... |
7,887 | <ASSISTANT_TASK:>
Python Code:
# Problem 3.4, page 107 Anderson, Woessner and Hunt (2015)
# import Python libraries/functionality for use in this notebook
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import scipy.special
import sys, os
from mpl_toolkits.axes_grid1 import make_axes_locatable
# 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: We want to explore drawdown as a function of time
Step2: We will want to normalize our plots
Step3: Clobber the PNG output files
Step4: Loop ... |
7,888 | <ASSISTANT_TASK:>
Python Code:
###########################################################################
#
# Copyright 2021 Google Inc.
#
# 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
#... | <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) Dependencies
Step2: 1) Import dataset
Step3: 1.1) Define KPI column and feature set
Step4: 2) Build RBA Model
Step5: 2.1) Print the model... |
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Python Code:
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
%matplotlib inline
matplotlib.style.use('seaborn')
import pandas as pd
from animerec.data import get_data
users, anime = get_data()
from sklearn.model_selection import train_test_split
train, test = train_test_split(user... | <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 plot the objective and see how it decreases.
Step2: We can see quite clearly that this model does not overfit, just like the linear model... |
7,890 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'awi', 'sandbox-2', 'landice')
# 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... |
7,891 | <ASSISTANT_TASK:>
Python Code:
%pylab inline
import sys
import os
sys.path.insert(0,'..')
import graphmap
from graphmap.graphmap_main import GraphMap
from graphmap.memory_persistence import MemoryPersistence
G = GraphMap(MemoryPersistence())
from graphmap.graph_helpers import NodeLink
seattle_skyline_image_url = 'htt... | <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 let us import the module and create a GraphMap that persists in memory.
Step2: Let us create two nodes with images of Seattle skyline and... |
7,892 | <ASSISTANT_TASK:>
Python Code:
!pip install -q -U pip
!pip install -q tensorflow==2.2.0
!pip install -q -U google-auth google-api-python-client google-api-core
import os
import tensorflow as tf
import numpy as np
print(f'Tensorflow version: {tf.__version__}')
PROJECT_ID = 'yourProject' # Change to your project.
BUCKE... | <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 libraries
Step2: Configure GCP environment settings
Step3: Authenticate your GCP account
Step4: Create the embedding lookup model
Step... |
7,893 | <ASSISTANT_TASK:>
Python Code:
import time
from collections import namedtuple
import numpy as np
import tensorflow as tf
with open('anna.txt', 'r') as f:
text=f.read()
vocab = set(text)
vocab_to_int = {c: i for i, c in enumerate(vocab)}
int_to_vocab = dict(enumerate(vocab))
chars = np.array([vocab_to_int[c] for c ... | <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'll load the text file and convert it into integers for our network to use.
Step3: Now I need to split up the data into batches, and in... |
7,894 | <ASSISTANT_TASK:>
Python Code:
try:
import pint
except ImportError:
!pip install pint
import pint
try:
from modsim import *
except ImportError:
!pip install modsimpy
from modsim import *
!python --version
!jupyter-notebook --version
# Configure Jupyter so figures appear in the notebook
%matplo... | <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 first time you run this on a new installation of Python, it might produce a warning message in pink. That's probably ok, but if you get a m... |
7,895 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
outcome_0 = np.array([1.0, 0.0])
outcome_1 = np.array([0.0, 1.0])
a = 0.75
b = 0.25
prob_bit = a*outcome_0 + b*outcome_1
X,Y = prob_bit
plt.figure()
ax = plt.gca()
ax.quiver(X,Y,angles='xy',scale_units='xy',scale=1)
ax.... | <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: Given some state vector, like the one plotted above, we can find the probabilities associated to each outcome by projecting the vector onto the ... |
7,896 | <ASSISTANT_TASK:>
Python Code:
# As usual, a bit of setup
import time, os, json
import numpy as np
from scipy.misc import imread, imresize
import matplotlib.pyplot as plt
from cs231n.classifiers.pretrained_cnn import PretrainedCNN
from cs231n.data_utils import load_tiny_imagenet
from cs231n.image_utils import blur_imag... | <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: TinyImageNet and pretrained model
Step3: # Class visualization
Step4: You can use the code above to generate some cool images! An example is s... |
7,897 | <ASSISTANT_TASK:>
Python Code:
def f(x):
return x**3 + 4*x**2 -3
x = np.linspace(-3.1, 0, 100)
plt.plot(x, x**3 + 4*x**2 -3)
a = -3.0
b = -0.5
c = 0.5*(a+b)
plt.text(a,-1,"a")
plt.text(b,-1,"b")
plt.text(c,-1,"c")
plt.scatter([a,b,c], [f(a), f(b),f(c)], s=50, facecolors='none')
plt.scatter([a,b,c], [0,0,0], s=50, c... | <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 terminate the process whenever the function evaluated at the new midpoint is 'close enough' to zero. This method is an example of what ar... |
7,898 | <ASSISTANT_TASK:>
Python Code:
%matplotlib notebook
Example:
- Minimize Rosenbrock's Function with Nelder-Mead.
- Plot of parameter convergence to function minimum.
Demonstrates:
- standard models
- minimal solver interface
- parameter trajectories using retall
# Nelder-Mead solver
from mystic.solv... | <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: mystic
Step4: Diagnostic tools
Step6: NOTE IPython does not handle shell prompt interactive programs well, so the above should be run from a c... |
7,899 | <ASSISTANT_TASK:>
Python Code:
# In the tf.keras.layers package, layers are objects. To construct a layer,
# simply construct the object. Most layers take as a first argument the number
# of output dimensions / channels.
layer = tf.keras.layers.Dense(100)
# The number of input dimensions is often unnecessary, as it can... | <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 full list of pre-existing layers can be seen in the documentation. It includes Dense (a fully-connected layer),
Step2: Implementing custom ... |
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