Unnamed: 0 int64 0 15.9k | cleaned_code stringlengths 67 124k ⌀ | cleaned_prompt stringlengths 168 30.3k ⌀ |
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6,200 | <ASSISTANT_TASK:>
Python Code:
MODEL_NAME = 'reg-model-01'
TRAIN_DATA_FILE = 'data/train-data.csv'
VALID_DATA_FILE = 'data/valid-data.csv'
TEST_DATA_FILE = 'data/test-data.csv'
RESUME_TRAINING = False
PROCESS_FEATURES = True
MULTI_THREADING = False
HEADER = ['key','x','y','alpha','beta','target']
HEADER_DEFAULTS = [[0... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 1. Define Dataset Metadata
Step2: 2. Define Data Input Function
Step3: 3. Define Feature Columns
Step4: 4. Create an Estimator
Step5: b. Set... |
6,201 | <ASSISTANT_TASK:>
Python Code:
import os.path as op
import numpy as np
from mayavi import mlab
import mne
from mne.datasets import sample
from mne.minimum_norm import read_inverse_operator, apply_inverse
from mne.simulation import simulate_stc, simulate_evoked
seed = 42
# parameters for inverse method
method = 'sLORET... | <SYSTEM_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 set some parameters.
Step2: Load the MEG data
Step3: Estimate the background noise covariance from the baseline period
Step4: Gener... |
6,202 | <ASSISTANT_TASK:>
Python Code:
# system functions that are always useful to have
import time, sys, os
# basic numeric setup
import numpy as np
import math
# inline plotting
%matplotlib inline
# plotting
import matplotlib
from matplotlib import pyplot as plt
# seed the random number generator
rstate = np.random.default_... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: 2-D Gaussian Shells
Step2: Default Run
Step3: Bounding Options
Step4: We can see the amount of overhead associated with 'balls' and 'cubes' i... |
6,203 | <ASSISTANT_TASK:>
Python Code:
import os
from google.cloud import bigquery
PROJECT = !gcloud config list --format 'value(core.project)'
PROJECT = PROJECT[0]
BUCKET = PROJECT
REGION = "us-central1"
os.environ["BUCKET"] = BUCKET
os.environ["REGION"] = REGION
%%bash
## Create a BigQuery dataset for babyweight if it does... | <SYSTEM_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 environment variables so that we can use them throughout the entire lab. We will be using our project ID for our bucket.
Step2: The source ... |
6,204 | <ASSISTANT_TASK:>
Python Code:
my_cat = 'cheshire'
catepillar_question = 'Who are you?'
_catepillar_question = 'Who are you?'
catepillar_Question1 = 'Who are you?'
1catepillar_question = 'Who are you?'
my_cat = 'cheshire'
my_cat = 'grinning'
my_cat = 'cheshire'
print(my_cat)
# see if you can display the value assig... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Here my_cat is the variable, and 'cheshire' is the value assigned to that variable. In general in Python, the thing on the left hand side of the... |
6,205 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'test-institute-2', 'sandbox-2', 'toplevel')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
6,206 | <ASSISTANT_TASK:>
Python Code:
ENDPOINT = "<YOUR_ENDPOINT>"
PROJECT_ID = !(gcloud config get-value core/project)
PROJECT_ID = PROJECT_ID[0]
%%writefile kfp-cli/Dockerfile
# TODO
IMAGE_NAME = "kfp-cli"
TAG = "latest"
IMAGE_URI = f"gcr.io/{PROJECT_ID}/{IMAGE_NAME}:{TAG}"
!gcloud builds # COMPLETE THE COMMAND
%%writef... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Creating the KFP CLI builder
Step2: Build the image and push it to your project's Container Registry.
Step3: Exercise
Step4: Understanding th... |
6,207 | <ASSISTANT_TASK:>
Python Code:
from cobra import Model, Reaction, Metabolite
# Best practise: SBML compliant IDs
cobra_model = Model('example_cobra_model')
reaction = Reaction('3OAS140')
reaction.name = '3 oxoacyl acyl carrier protein synthase n C140 '
reaction.subsystem = 'Cell Envelope Biosynthesis'
reaction.lower_bo... | <SYSTEM_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 need to create metabolites as well. If we were using an existing model, we could use get_by_id to get the apporpriate Metabolite objects inst... |
6,208 | <ASSISTANT_TASK:>
Python Code:
from notebook_preamble import J, V, define
define('BTree-iter == [not] [pop] roll< [dupdip rest rest] cons [step] genrec')
J('[] [23] BTree-iter') # It doesn't matter what F is as it won't be used.
J('["tommy" 23 [] []] [first] BTree-iter')
J('["tommy" 23 ["richard" 48 [] []] ["jenny" 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: Adding Nodes to the BTree
Step2: (As an implementation detail, the [[] []] literal used in the definition of BTree-new will be reused to supply... |
6,209 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
# Crear una seríe indicando la producción por mes
produccion = pd.Series( [120,130,110,150,170,180,170,160,190,175,160,141],
index=['ene','feb','mar','abr','may','jun','jul','ago','sep','oct','nov','dec'] )
print(produccion)
# Crear una serie ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Pandas es una librería orientada a objetos y los objetos más importantes que incluye son las Series y los DataFrames.
Step2: Atributos y Método... |
6,210 | <ASSISTANT_TASK:>
Python Code:
from biofloat import ArgoData
ad = ArgoData()
wmo_list = ad.get_oxy_floats_from_status()
sdf, _ = ad._get_df(ad._STATUS)
sdf.ix[:, 'WMO':'GREYLIST'].head()
%pylab inline
def dist_plot(df, title):
from datetime import date
ax = df.hist(bins=100)
ax.set_xlabel('AGE (days)')
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get the default list of floats that have oxygen data.
Step2: We can explore the distribution of AGEs of the Argo floats by getting the status d... |
6,211 | <ASSISTANT_TASK:>
Python Code:
#importing all required modules
#important otherwise pop-up window may not work
%matplotlib inline
import numpy as np
import scipy as sp
from scipy.integrate import odeint, ode, romb, cumtrapz
import matplotlib as mpl
import matplotlib.pyplot as plt
from math import *
import seaborn
from... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: RLC circuit is governed by the following formulas
Step2: RLC circuit fed with dc voltage
Step3: RLC Circuit with sinusoidal voltage
|
6,212 | <ASSISTANT_TASK:>
Python Code:
import os
os.listdir('partonopeus')
inputFiles = {}
for inputFile in os.listdir('partonopeus'):
siglum = inputFile[0]
contents = open('partonopeus/' + inputFile,'rb').read()
inputFiles[siglum] = contents
from lxml import etree
print(etree.tostring(etree.XML(inputFiles['A']))... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: We create a dictionary to hold our input files, using the single-letter filename before the '.xml' extension as the key and the file itself as t... |
6,213 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cas', 'sandbox-1', 'toplevel')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "em... | <SYSTEM_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... |
6,214 | <ASSISTANT_TASK:>
Python Code:
from landlab.components import SpeciesEvolver, Profiler
from landlab.components.species_evolution import ZoneController
from landlab.io import read_esri_ascii
from landlab.plot import imshow_grid
import matplotlib.pyplot as plt
import numpy as np
# Create a model grid and set a topograph... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Prepare the grid
Step2: Create a grid field of air temperature at the land surface
Step3: Setup SpeciesEvolver and zones
Step4: View record_d... |
6,215 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mpi-m', 'sandbox-2', 'seaice')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", "em... | <SYSTEM_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... |
6,216 | <ASSISTANT_TASK:>
Python Code:
import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import timeit
import warnings
from itertools import product
warnings.filterwarnings("ignore")
pd.options.mode.chained_assignment = None # default='warn'
from ipyleaflet import (
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Просуммируйте общее количество поездок такси из каждой географической зоны и посчитайте количество ячеек, из которых в мае не было совершено ни ... |
6,217 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from matplotlib import pyplot as plt
# Number of row and columns in the matrix
nrows = 200
# Number of maximum iterations
maxiters = 500
# Radius of neighbors that affect the value of the current cell (radius of 1 means that only the 8 cells immediately
# adjacent hav... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Model Parameters
Step2: The<code> makematrix()</code> function takes as argument the number of rows and columns of the matrix to model
Step3: ... |
6,218 | <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
# create a data frame containing variables of disparate scale
scratch_df = pd.DataFrame({'x1': pd.Series(np.random.choice(1000, 20)),
... | <SYSTEM_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 sample data set
Step2: Standardize
|
6,219 | <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... |
6,220 | <ASSISTANT_TASK:>
Python Code:
a = 3
print(type(a))
b = [1, 2.5, 'This is a string']
print(type(b))
c = 'Hello world!'
print(type(c))
a = [1, 2, 3, 4]
print('This is the zeroth value in the list: {}'.format(a[0]))
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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: If you come from a background of matlab, remember that indexing in python
|
6,221 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import numpy.linalg as la
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
%matplotlib inline
def plot_all(m, d, m_est, d_pred):
Helper function for plotting. You can ignore this.
fig = plt.figure(figsize=(10,6))
ax0 = fig.add_subpl... | <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: Linear inverse solutions in NumPy
Step3: Mauricio's 1D problem in 2D
Step4: Form the discrete kernel, G.
Step5: Compute the data; this is the... |
6,222 | <ASSISTANT_TASK:>
Python Code:
import logging # python logging module
# basic format for logging
logFormat = "%(asctime)s - [%(levelname)s] (%(funcName)s:%(lineno)d) %(message)s"
# logs will be stored in tweepy.log
logging.basicConfig(filename='tweepytrends.log', level=logging.INFO,
format=logFormat... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Authentication and Authorisation
Step3: Post this step, we will have full access to twitter api's
Step9: Streaming with tweepy
|
6,223 | <ASSISTANT_TASK:>
Python Code:
#@title
# Copyright 2020 Google LLC.
# 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... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Here is how you can set the fastmath backend to tensorflow-numpy and verify that it's been set.
Step2: 2. Convert Trax to Keras
Step3: 3. Expo... |
6,224 | <ASSISTANT_TASK:>
Python Code:
from statistics import mean
def occ(n):
"The expected occupancy for a row of n houses (under misanthrope rules)."
return (0 if n == 0 else
1 if n == 1 else
mean(occ(L) + 1 + occ(R)
for (L, R) in runs(n)))
def runs(n):
A list [(L, 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: The Puzzle of the Misanthropic Neighbors
Step2: Let's check that occ(4) is 2, as we computed it should be
Step3: And that runs(7) is what we d... |
6,225 | <ASSISTANT_TASK:>
Python Code:
%load_ext watermark
%watermark -u -v -d -p matplotlib,numpy
%matplotlib inline
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from matplotlib import pyplot as plt
# Generate some 3D sample data
mu_vec1 = np.array([0,0,0]) # mean vector
cov_mat1 = np.array([[1,0,0],[0,1,0],[0... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: <font size="1.5em">More info about the %watermark extension</font>
Step2: <br>
Step3: <br>
Step4: <br>
Step5: <br>
Step6: <br>
|
6,226 | <ASSISTANT_TASK:>
Python Code:
try:
import verta
except ImportError:
!pip install verta
HOST = "app.verta.ai"
PROJECT_NAME = "Spam Detection"
EXPERIMENT_NAME = "tf–idf"
# import os
# os.environ['VERTA_EMAIL'] =
# os.environ['VERTA_DEV_KEY'] =
from __future__ import print_function
import json
import os
impor... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: This example features
Step2: Imports
Step3: Run Workflow
Step4: Instantiate Client
Step5: Fit Model
Step6: Define Model Class
Step7: Earli... |
6,227 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
list1 = [1, 2, 3, 4, 5] # Define a list
array1 = np.array(list1) # Pass the list to np.array()
type(array1) # Check the object's type
print("array1 = ", array1) # Check the content of the array (printing in Python 3)
print ("a... | <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 can create an ndarray by passing a list to the np.array() function
Step2: To create an array with more than one dimension, we can pass a nes... |
6,228 | <ASSISTANT_TASK:>
Python Code:
dot = Digraph(comment='Design of Experiments')
dot.body.extend(['rankdir=LR', 'size="10,10"'])
dot.node_attr.update(shape='rectangle', style='filled', fontsize='20', fontname="helvetica")
dot.node('X', 'Controllable Factors', color='mediumseagreen', width='3')
dot.node('Z', 'Noise Factors... | <SYSTEM_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 For?
Step2: ((((
Step3: Factorial Design
Step5: Statistical Power
Step6: Calculating Power with dexpy
Step7: Fractional Factoria... |
6,229 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as pl
pl.style.use('ggplot')
import numpy as np
from scipy.stats import gamma
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels import WhiteKernel, RBF
from revrand import StandardLinearModel, Ge... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Dataset settings and creation
Step2: Algorithm Settings
Step3: Parameter learning
Step4: Model Querying
Step5: Score the models
Step6: Plot... |
6,230 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from ttim import *
import pandas as pd
H = 7 #aquifer thickness
zt = -18 #top boundary of aquifer
zb = zt - H #bottom boundary of aquifer
Q = 788 #constant discharge
#unkonwn parameters: kaq, Saq
ml = ModelMaq(kaq=60,... | <SYSTEM_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 basic parameters for the model
Step2: Create conceptual model
Step3: Load data of two observation wells
Step4: Calibrate using only the d... |
6,231 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'miroc', 'miroc-es2h', 'toplevel')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name", ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 2... |
6,232 | <ASSISTANT_TASK:>
Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Transfer learning and fine-tuning
Step2: Data preprocessing
Step3: Show the first nine images and labels from the training set
Step4: As the ... |
6,233 | <ASSISTANT_TASK:>
Python Code:
data_in_shape = (5, 5, 2)
conv = Conv2D(4, (3,3), strides=(1,1), padding='valid',
data_format='channels_last', dilation_rate=(1,1),
activation='linear', use_bias=True)
layer_0 = Input(shape=data_in_shape)
layer_1 = conv(layer_0)
model = Model(inputs=layer_0, ou... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: [convolutional.Conv2D.1] 4 3x3 filters on 5x5x2 input, strides=(1,1), padding='valid', data_format='channels_last', dilation_rate=(1,1), activat... |
6,234 | <ASSISTANT_TASK:>
Python Code:
import os
import inspect
import sys
import pandas as pd
import charts
from opengrid.library import houseprint
import matplotlib.pyplot as plt
%matplotlib inline
plt.rcParams['figure.figsize'] = 16,8
hp = houseprint.Houseprint()
# for testing:
# hp = houseprint.Houseprint(spreadsheet='uni... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Houseprint
Step2: A Houseprint object can be saved as a pickle. It loses its tmpo session however (connections cannot be pickled)
Step3: TMPO
... |
6,235 | <ASSISTANT_TASK:>
Python Code:
from resources.iot.device import IoT_sensor_consumer
from IPython.core.display import display
import ipywidgets as widgets
from resources.iot.device import IoT_mqtt_publisher, IoT_sensor
widgets.FloatProgress(value=30.0, min=0, max=100.0, bar_style='danger', orientation='vertical')
widge... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Barra
Step2: Label
Step3: Criando dois componentes visuais
Step4: Renderizando componentes visuais
Step5: Criando um componente que consome ... |
6,236 | <ASSISTANT_TASK:>
Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csiro-bom', 'sandbox-2', 'aerosol')
# Set as follows: DOC.set_author("name", "email")
# TODO - please enter value(s)
# Set as follows: DOC.set_contributor("name"... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Document Authors
Step2: Document Contributors
Step3: Document Publication
Step4: Document Table of Contents
Step5: 1.2. Model Name
Step6: 1... |
6,237 | <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'
class DLProgress(tqdm):
last_b... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
6,238 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
plt.rcParams = plt.rcParamsOrig
from tqdm.notebook import trange
class HMM:
def __init__(self, p_start, p_trans, p_emit, p_stop=None):
assert p_trans.shape[0] == p_emit.shape[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:
Step5: 1. Hidden Markov Model (10 poin)
Step6: Contoh kasus di bawah ini diadaptasi dari sini. Contoh ini adalah penggunaan HMM untuk mencari sequence... |
6,239 | <ASSISTANT_TASK:>
Python Code:
# Author: Denis A. Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import os
import os.path as op
import numpy as np
from scipy.misc import imread
import matplotlib.pyplot as plt
import mne
from mne import io
from mne.datasets import spm_face
from mne.minimum_norm import a... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get data
Step2: Estimate covariances
Step4: Show the resulting source estimates
|
6,240 | <ASSISTANT_TASK:>
Python Code:
import modin.pandas as pd
import pandas
import numpy as np
import time
frame_data = np.random.randint(0, 100, size=(2**18, 2**8))
df = pd.DataFrame(frame_data).add_prefix("col")
pandas_df = pandas.DataFrame(frame_data).add_prefix("col")
modin_start = time.time()
print(df.mask(df < 50))
mo... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Concept for exercise
Step2: Speed improvements
Step3: Congratulations! You have just implemented new DataFrame functionality!
|
6,241 | <ASSISTANT_TASK:>
Python Code:
! pip3 install -U google-cloud-automl --user
! pip3 install google-cloud-storage
import os
if not os.getenv("AUTORUN"):
# Automatically restart kernel after installs
import IPython
app = IPython.Application.instance()
app.kernel.do_shutdown(True)
PROJECT_ID = "[your-pro... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Install the Google cloud-storage library as well.
Step2: Restart the Kernel
Step3: Before you begin
Step4: Region
Step5: Timestamp
Step6: A... |
6,242 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import timeit
import aurora as au # import Aurora
import aurora.autodiff as ad # importing Aurora's automatic differentiation framework
import matplotlib.pyplot as plt
import seaborn as sbn
sbn.set()
BATCH_SIZE = 64
LR = 1e-4
USE_GPU = False
NUM_ITERS = 20
# utility 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: Let's Explore the Dataset
Step2: Building the Computational Graph
Step3: Training Our Model
Step4: Reporting Testing Accuracy and Plotting Tr... |
6,243 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from sklearn.datasets import fetch_olivetti_faces
random_state = 32
dataset = fetch_olivetti_faces(shuffle=True, random_state=random_state)
X, y = dataset['data'], dataset['target']
n_x, n_y = dataset['images'][0].shape
X_data = X.reshape(-1, n_x, n_y).transpose(1, 2, 0... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Get the connectivity (spatial structure)
Step2: Custering
Step3: Results visualization
|
6,244 | <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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<USER_TASK:>
Description:
Step1: Image Classification
Step2: Explore the Data
Step5: Implement Preprocess Functions
Step8: One-hot encode
Step10: Randomize Data
Step12: Che... |
6,245 | <ASSISTANT_TASK:>
Python Code:
import csv # module used for reading and converting .CSV files
import os # module that enables local operating system dependent commands
filepath = 'C:/Users/Radley/Downloads/' # store file location as a string
filename = 'lbl.csv' # store the file name as a ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Normally, you're file of interest is not located in the default working directory of Python. os.chdir() changes the working directory so we can ... |
6,246 | <ASSISTANT_TASK:>
Python Code:
from jyquickhelper import add_notebook_menu
add_notebook_menu()
import httplib2 # pip install httplib2
import json # déjà installée, sinon : pip install json
import apiclient.discovery # pip install google-api-python-client
import bs4 # déjà ja installée, sinon : pip install bs4
import... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Le traitement automatique des langues (ou Natural Language Processing) propose un ensemble de méthodes permettant (entre autres)
Step2: Récupé... |
6,247 | <ASSISTANT_TASK:>
Python Code:
2 * 4 - (7 - 1) / 3 + 1.0
1 / 0
1.0 / 0.0
3 / 2
3 // 2
2 ** 16
2 + 3j
1j
# Valor absoluto
abs(2 + 3j)
abs(_13)
int(18.6)
round(18.6)
float(1)
complex(2)
str(256568)
a = 2.
type(a)
isinstance(a, float)
print('hola mundo')
max(1,5,8,7)
min(-1,1,0)
a = 1 + 2j
b = 3.14159
b
x, y ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Las divisiones por cero lanzan un error
Step2: <div class="alert alert-info">Más adelante veremos cómo tratar estos errores. Por otro lado, cua... |
6,248 | <ASSISTANT_TASK:>
Python Code:
# execute this cell
np.random.seed(0)
x = np.concatenate([stats.cauchy(-5, 1.8).rvs(500),
stats.cauchy(-4, 0.8).rvs(2000),
stats.cauchy(-1, 0.3).rvs(500),
stats.cauchy(2, 0.8).rvs(1000),
stats.cauchy(4, 1.5).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: Hey, nice histogram!
Step2: Problem 1b
Step4: Problem 1d
Step5: Problem 2a
Step6: Problem 2b
Step7: Problem 3c
Step8: Problem 3d
Step9: ... |
6,249 | <ASSISTANT_TASK:>
Python Code:
import urllib
import json
import time
import pandas as pd
import datetime
from arctic import Arctic
import arctic
import subprocess
import platform
import os
import krakenex
if platform.system() == "Darwin":
os.chdir('/users/'+os.getlogin()+'/MEGA/App')
if platform.system() == "Darwin... | <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: The kraken API can be installed via pip
Step3: Let's now run the functions to see what happens
Step4: The function get_kraken_balance() return... |
6,250 | <ASSISTANT_TASK:>
Python Code:
import sys
sys.path.insert(1, '..')
import crowdastro.data
import io
import astropy.io.votable
import requests
import requests_cache
requests_cache.install_cache(cache_name='gator_cache', backend='sqlite', expire_after=None)
def fetch(subject):
if subject['metadata']['source'].starts... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: How many objects are in SWIRE $\cap$ RGZ–ATLAS?
Step2: So there are $56190$ galaxies in SWIRE $\cap$ RGZ–ATLAS. Let's also get that... |
6,251 | <ASSISTANT_TASK:>
Python Code:
from collections import defaultdict
import numpy as np
from mock import patch
from grove.simon.simon import Simon, create_valid_2to1_bitmap
mask = '110'
bm = create_valid_2to1_bitmap(mask, random_seed=42)
expected_map = {
'000': '001',
'001': '101',
'010': '000',
'011': '... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Simon's algorithm can be used to find the mask $m$ of a 2-to-1 periodic Boolean function defined by
Step2: To understand what a 2-to-1 function... |
6,252 | <ASSISTANT_TASK:>
Python Code:
all_scores = pd.read_excel("Grades/Book1.xlsx")
all_scores["Is A"] = all_scores["Final Score"] >= 90
# https://courses.cs.vt.edu/~cs1604/grading.html
letter_grade = []
for grade in all_scores["Final Score"]:
if grade >= 90:
letter_grade.append("A")
elif grade >= 80:
... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Importing Clusters "Clustered_Sessions.csv"
Step2: Clustered_Users
Step3: Graphs
Step4: Correlation and Regression - Scatter Plots
Step5:
S... |
6,253 | <ASSISTANT_TASK:>
Python Code:
# 这个项目设计来帮你熟悉 python list 和线性代数
# 你不能调用任何NumPy以及相关的科学计算库来完成作业
# 本项目要求矩阵统一使用二维列表表示，如下：
A = [[1,2,3],
[2,3,3],
[1,2,5]]
B = [[1,2,3,5],
[2,3,3,5],
[1,2,5,1]]
# 向量也用二维列表表示
C = [[1],
[2],
[3]]
#TODO 创建一个 4*4 单位矩阵
I = [[1,0,0,0],
[0,1,0,0],
[0,0,1,0]... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: 1.2 返回矩阵的行数和列数
Step2: 1.3 每个元素四舍五入到特定小数数位
Step3: 1.4 计算矩阵的转置
Step4: 1.5 计算矩阵乘法 AB
Step5: 2 Gaussign Jordan 消元法
Step6: 2.2 初等行变换
Step7: 2.3... |
6,254 | <ASSISTANT_TASK:>
Python Code:
from IPython.display import display
from dividedDifferences import get_coeff, get_polynomial
from sympy import init_printing
from sympy import symbols, simplify
from sympy import Eq, S, Function
init_printing()
# The values in the points we use for the extrapolation
f0, f1, f2, f3 = symbo... | <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: Intro
Step2: sorted after increasing value of the coordinate $x$. These points takes the following values
Step3: Our goal is to use these four... |
6,255 | <ASSISTANT_TASK:>
Python Code:
url = "https://lists.wikimedia.org/pipermail/analytics/"
arx = Archive(url,archive_dir="../archives")
#threads = arx.get_threads()
len(arx.get_threads())
y = [t.get_num_messages() for t in arx.get_threads()]
plt.hist(y, bins=30)
plt.xlabel('number of messages in a thread')
plt.show()
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: We can count the number of threads in the archive easily. The first time you run Archive.get_thread it may take some time to compute, but the re... |
6,256 | <ASSISTANT_TASK:>
Python Code:
import pints
import pints.toy as toy
import numpy as np
import matplotlib.pyplot as plt
# Load a forward model
model = toy.LogisticModel()
# Create some toy data
real_parameters = [0.015, 500] # growth rate, carrying capacity
times = np.linspace(0, 1000, 100)
org_values = model.simulate(... | <SYSTEM_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 1d histograms
Step2: Plotting 2d histograms and a matrix of parameter distribution plots
Step3: Matrix of parameter distribution plot... |
6,257 | <ASSISTANT_TASK:>
Python Code:
# Simple Function
def greet():
'''Simple Greet Function'''
print('Hello World')
greet()
# Function with arguments
def greet(name):
'''Simple Greet Function with arguments'''
print('Hello ', name)
greet('John')
# printing the doc string
print(greet.__doc__)
# Fu... | <SYSTEM_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 2
Step2: Example 3
Step3: Scope and Lifetime of Variables
Step4: Variables defined outside the function are visible from inside which... |
6,258 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import torch
MyNet = torch.nn.Sequential(torch.nn.Linear(4, 15),
torch.nn.Sigmoid(),
torch.nn.Linear(15, 3),
)
MyNet.load_state_dict(torch.load("my_model.pt"))
input ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
|
6,259 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from numpy import *
from bokeh import *
from bokeh.plotting import *
output_notebook()
from matmodlab2 import *
from pandas import read_excel
from scipy.optimize import leastsq
diff = lambda x: np.ediff1d(x, to_begin=0.)
trace = lambda x, s='SIG': x[s+'11'] + x[s+'22'] ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Summary
Step2: Hydrostatic Response
Step3: It appears that the unloading occurs at data point 101 and continues until the end of the data. Th... |
6,260 | <ASSISTANT_TASK:>
Python Code:
from wikidataintegrator import wdi_core, wdi_login, wdi_helpers
from wikidataintegrator.ref_handlers import update_retrieved_if_new_multiple_refs
import pandas as pd
from pandas import read_csv
import requests
from tqdm.notebook import trange, tqdm
import ipywidgets
import widgetsnbexten... | <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: Retrieve and map WDIDs
Step3: Query Wikidata for instances of drugs whose names match to product label names
Step4: Merge tables to convert dr... |
6,261 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data_path = 'Bike-Sharing-Dataset/hour.csv'
rides = pd.read_csv(data_path)
rides.head()
rides[:24*10].plot(x='dteday', y='cnt')
dummy_fields = ['seas... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Load and prepare the data
Step2: Checking out the data
Step3: Dummy variables
Step4: Scaling target variables
Step5: Splitting the data into... |
6,262 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
path = "data/dogscats/sample/"
#path = "data/dogscats"
from __future__ import division,print_function
import os, json
from glob import glob
import numpy as np
np.set_printoptions(precision=4, linewidth=100)
from matplotlib import pyplot as plt
from importlib import r... | <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: Define path to data
Step2: A few basic libraries that we'll need for the initial exercises
Step3: We have created a file most imaginatively ca... |
6,263 | <ASSISTANT_TASK:>
Python Code:
from games import *
from notebook import psource, pseudocode
%psource Game
%psource TicTacToe
moves = dict(A=dict(a1='B', a2='C', a3='D'),
B=dict(b1='B1', b2='B2', b3='B3'),
C=dict(c1='C1', c2='C2', c3='C3'),
D=dict(d1='D1', d2='D2', d... | <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: GAME REPRESENTATION
Step2: Now let's get into details of all the methods in our Game class. You have to implement these methods when you create... |
6,264 | <ASSISTANT_TASK:>
Python Code:
#Normal inputs
import pandas as pd
import numpy as np
import seaborn as sns
import pylab as plt
%matplotlib inline
from IPython.display import Image, display
#Make the notebook wider
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:90% !important; }<... | <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: Save CSV to disk (df.to_csv())
Step2: 2. Tidy data
Step3: 2.2 What is tidy data?
Step4: 2.3 Tidying messy datasets
Step5: Data to study
Step... |
6,265 | <ASSISTANT_TASK:>
Python Code:
df = pd.read_csv('../data/raw_running_data.csv')
print(type(df))
df.head(10)
?pd.read_csv()
df.dtypes
df.columns
df.index
df['Date'].head()
df = pd.read_csv('../data/raw_running_data.csv', parse_dates=['Date'])
df.Date.head()
df.set_index('Date', inplace=True)
df.plot()
?df.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: You'll also notice that there are a TON of extra parameters that can be passed into this function, we can skip rows, specify dtypes, if there's ... |
6,266 | <ASSISTANT_TASK:>
Python Code:
# Imports
import sys
import pandas as pd
import csv
%matplotlib inline
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (20.0, 10.0)
# %load util.py
#!/usr/bin/python
# Util file to import in all of the notebooks to allow for easy code re-use
# Calculate Percent of Attende... | <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: Reading the Data
Step2: Sanitizing the Data
Step3: Analysis and Visualization (V1)
Step4: Analysis and Visualization (V2)
Step5: this is sti... |
6,267 | <ASSISTANT_TASK:>
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='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: Network Architecture
Step2: Training
Step3: Denoising
Step4: Checking out the performance
|
6,268 | <ASSISTANT_TASK:>
Python Code:
from nltk.book import *
print(sent1)
print(sent3)
print(sent5)
print(text6)
print(text6.name)
print("This text has %d words" % len(text6.tokens))
print("The first hundred words are:", " ".join( text6.tokens[:100] ))
print(text5[0])
print(text3[0:11])
print(text4[0:51])
text6.concordan... | <SYSTEM_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 import statement reads the book samples, which include nine sentences and nine book-length texts. It has also helpfully put each of these t... |
6,269 | <ASSISTANT_TASK:>
Python Code:
def x_2z_over_dst(z):
w = 2*pi
# beta = 1, wn =w
wd = w*sqrt(1-z*z)
# Clough Penzien p. 43
A = z/sqrt(1-z*z)
def f(t):
return (cos(wd*t)+A*sin(wd*t))*exp(-z*w*t)-cos(w*t)
return pl.vectorize(f)
t = pl.linspace(0,20,1001)
print(t)
zetas = (.02, .05, .1... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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<USER_TASK:>
Description:
Step1: Above we compute some constants that depend on $\zeta$,
Step2: We want to see what happens for different values of $\zeta$, so we create
Step3:... |
6,270 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import log as ln
from itertools import cycle # used to create a loopable colormap
def get_Atom_prop(Atom,Prop):
'''
This is a helper to get certain values from the tables
You can't get the symbol... | <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: This defines the location of a file that holds all the atomic data we need. the files holds values fro the calculation of the sputter yield acco... |
6,271 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import pandas as pd
import statsmodels.api as sm
import matplotlib.pyplot as plt
macrodata = sm.datasets.macrodata.load_pandas().data
macrodata.index = pd.period_range('1959Q1', '2009Q3', freq='Q')
endog = macrodata['infl']
endog.plot(figsize=(15, 5)... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Basic example
Step2: Constructing and estimating the model
Step3: Forecasting
Step4: The get_forecast method is more general, and also allows... |
6,272 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
from pylab import *
%matplotlib inline
import os
import sys
#TODO: specify your caffe root folder here
caffe_root = "X:\caffe_siggraph/caffe-windows-master"
sys.path.insert(0, caffe_root+'/python')
import caffe
#TODO: change to your own network and deploying file
PRET... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: caffe
Step2: Now we can load up the network. You can change the path to your own network here. Make sure to use the matching deploy prototxt fi... |
6,273 | <ASSISTANT_TASK:>
Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
import phoebe
import numpy as np
b = phoebe.default_binary()
b.set_value('q', value=0.7)
b.set_value('incl', component='binary', value=87)
b.set_value('requiv', component='primary', value=0.8)
b.set_value('teff', component='secondary', value=6500)
b.s... | <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: As always, let's do imports and initialize a logger and a new bundle.
Step2: Now we'll try to exaggerate the effect by spinning up the secondar... |
6,274 | <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, software
... | <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: Reformer
Step2: Setting up data and model
Step4: As we see above, "Crime and Punishment" has just over half a million tokens with the BPE voca... |
6,275 | <ASSISTANT_TASK:>
Python Code:
import tensorflow as tf
import numpy as np
np.random.seed(10)
A = tf.constant(np.random.randint(low=0, high=5, size=(10, 20, 30)))
B = tf.constant(np.random.randint(low=0, high=5, size=(10, 20, 30)))
import numpy as np
def g(A,B):
return tf.constant(np.einsum( 'ikm, jkm-> ijk', 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:
|
6,276 | <ASSISTANT_TASK:>
Python Code:
import datetime
from functools import reduce
import json
import os
import numpy as np
import pandas as pd
from planet import api
import rasterio
from sklearn.cluster import MiniBatchKMeans
from sklearn.ensemble import RandomForestClassifier
from utils import Timer
import visual
# Import 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: Download Scenes
Step2: Download portions of OrthoTile strips that overlap AOI
Step3: Get mosaic image names
Step4: Classify Scenes
Step5: Vi... |
6,277 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import pandas
import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = (16.0, 8.0)
df = pandas.read_csv('./stroopdata.csv')
df.describe()
df.hist()
import math
df['differences'] = df['Incongruent']-df['Congruent']
N =df['differences'].count()
print "Sample siz... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
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Description:
Step1: Provide one or two visualizations that show the distribution of the sample data. Write one or two sentences noting what you observe about the pl... |
6,278 | <ASSISTANT_TASK:>
Python Code:
import medusa
from medusa.test import create_test_ensemble
ensemble = create_test_ensemble("Staphylococcus aureus")
import pandas as pd
biolog_base = pd.read_csv("../medusa/test/data/biolog_base_composition.csv", sep=",")
biolog_base
# convert the biolog base to a dictionary, which we can... | <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: Let's simulate growth on two different carbon sources, D-glucose (metabolite id
Step2: Now let's visualize the distributions of predicted flux ... |
6,279 | <ASSISTANT_TASK:>
Python Code:
#%qtconsole # For inspecting variables.
# Standard
import os
from glob import glob # Unix style pathname pattern expansion.
import csv
import pickle
import time
# Scientific Computing and Visualization
import numpy as np; np.random.seed(13) # Lucky seed.
import matplotlib.pyplot as plt... | <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: 0 Load Data
Step2: 1 Dataset Summary, Exploration, and Balancing
Step3: Exploratory Visualization
Step4... |
6,280 | <ASSISTANT_TASK:>
Python Code:
# imports
import numpy as np
import matplotlib.pyplot as plt
from landlab import RasterModelGrid, imshow_grid
from landlab.components import TidalFlowCalculator
# set up the grid
grid = RasterModelGrid(
(3, 101), xy_spacing=2.0
) # only 1 row of core nodes, between 2 boundary rows
gr... | <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: As we would expect, the numerical solution is slightly lower than the analytical solution, because our simplified analytical solution does not t... |
6,281 | <ASSISTANT_TASK:>
Python Code:
import logging
import os.path
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
from gensim import corpora, models, similarities
if (os.path.exists("/tmp/deerwester.dict")):
dictionary = corpora.Dictionary.load('/tmp/deerwester.dict')
cor... | <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: if you want to see logging events.
Step2: In this tutorial, I will show how to transform documents from one vector representation into another.... |
6,282 | <ASSISTANT_TASK:>
Python Code:
import numpy as np
import pandas as pd
column_names = ['user_id', 'item_id', 'rating', 'timestamp']
df = pd.read_csv('u.data', sep='\t', names=column_names)
df.head()
movie_titles = pd.read_csv("Movie_Id_Titles")
movie_titles.head()
df = pd.merge(df,movie_titles,on='item_id')
df.head(... | <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 then read in the u.data file, which contains the full dataset. You can read a brief description of the dataset here.
Step2: Let's take a... |
6,283 | <ASSISTANT_TASK:>
Python Code:
print "Hello World!"
x=42
print x+10
print x/4
x="42"
print x+10
print x+"10"
x=[1, 2, 3]
y=[4,5, 6]
print x
print x*2
print x+y
print range(10)
print range(20, 50, 3)
print []
x=range(10)
print x
print "First value", x[0]
print "Last value", x[-1]
print "Fourth to sixth values", x[3:... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: There are, however, a few lines that you will usually see in a Python script. The first line often starts with #! and is called the shebang. For... |
6,284 | <ASSISTANT_TASK:>
Python Code:
import skrf
import numpy as np
import matplotlib.pyplot as mplt
nw = skrf.network.Network('./190ghz_tx_measured.S2P')
vf = skrf.VectorFitting(nw)
vf.vector_fit(n_poles_real=4, n_poles_cmplx=4)
vf.plot_convergence()
vf.get_rms_error()
# plot frequency responses
fig, ax = mplt.subplots(... | <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: This example is a lot more tricky to fit, because the responses contain a few "bumps" and noise from the measurement. In such a case, finding a ... |
6,285 | <ASSISTANT_TASK:>
Python Code:
class Module(object):
def __init__ (self):
self.output = None
self.gradInput = None
self.training = True
Basically, you can think of a module as of a something (black box)
which can process `input` data and produce `ouput` data.
This is like a... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step12: Module is an abstract class which defines fundamental methods necessary for a training a neural network. You do not need to change anything her... |
6,286 | <ASSISTANT_TASK:>
Python Code:
data_path = '../../SFPD_Incidents_-_from_1_January_2003.csv'
data = pd.read_csv(data_path)
mask = (data.Category == 'PROSTITUTION') & (data.Y != 90)
filterByCat = data[mask]
reducted = filterByCat[['PdDistrict','X','Y']]
X = data.loc[mask][['X','Y']]
centers = {}
def knn(k):
md = c... | <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: Then we want to filter the data set.
Step2: To reduce the amount of data we need to load on the page, we only extract the columns that we need.... |
6,287 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
# Imports from Python packages.
import matplotlib.pyplot as plt
from matplotlib.ticker import FuncFormatter
from scipy.stats import ttest_rel, ttest_ind
import pandas as pd
import numpy as np
import os
# Imports from FinanceOps.
from data_keys import *
from data import ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Load Data
Step12: Mathematical Model
Step14: Print Statistics
Step16: Plotting Function
Step17: Case Study
Step18: The statistics above sho... |
6,288 | <ASSISTANT_TASK:>
Python Code:
%lsmagic
%pwd
%pwd?
%%javascript
IPython.toolbar.add_button_group([
{
'label':'renumber all code cells',
'icon':'icon-list-ol',
'callback':function() {
var cells = IPython.notbook.get_cells();
cells = cells.filter(function(c)
{
return c in... | <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: 現在のディレクトリを確認
Step2: コマンドの説明を確認するには?をつける
|
6,289 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
from bigbang.archive import Archive
from bigbang.archive import load as load_archive
from bigbang.thread import Thread
from bigbang.thread import Node
from bigbang.utils import remove_quoted
import matplotlib.pyplot as plt
import datetime
import csv
from collections imp... | <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: First, collect data from a public email archive.
Step2: Let's check the number of threads in this mailing list corpus
Step3: We can plot the ... |
6,290 | <ASSISTANT_TASK:>
Python Code:
from nilmtk import DataSet
iawe = DataSet('/data/iawe.h5')
elec = iawe.buildings[1].elec
elec
fridge = elec['fridge']
fridge.available_columns()
df = next(fridge.load())
df.head()
series = next(fridge.power_series())
series.head()
series = next(fridge.power_series(ac_type='reactive'))... | <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 us see what measurements we have for the fridge
Step2: Loading data
Step3: Load a single column of power data
Step4: or, to get reactive ... |
6,291 | <ASSISTANT_TASK:>
Python Code:
import requests
r = requests.get("http://en.wikipedia.org/wiki/Main_Page")
type(r.request), type(r.content), type(r.headers)
from pprint import pprint
pprint(r.content[0:1000])
r.request.headers
r.headers
r.content[:1000]
r.text[:1000]
from bs4 import BeautifulSoup
page = Beautiful... | <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: This response object contains various information about the request you sent to the server, the resources returned, and information about the re... |
6,292 | <ASSISTANT_TASK:>
Python Code:
import pandas as pd
from sklearn import linear_model
import matplotlib.pyplot as plt
# read data in pandas frame
dataframe = pd.read_csv('datasets/house_dataset1.csv')
# assign x and y
x_feature = dataframe[['Size']]
y_labels = dataframe[['Price']]
# check data by printing first few rows
... | <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: Plot data
Step2: Train model
Step3: Predict output using trained model
Step4: Plot results
Step5: Do it yourself
Step6: Predict labels usin... |
6,293 | <ASSISTANT_TASK:>
Python Code:
import matplotlib.pylab as plt
import numpy as np
import seaborn as sns; sns.set()
%matplotlib inline
import keras
from keras.models import Sequential, Model
from keras.layers import Dense
from keras.optimizers import Adam
import salty
from numpy import array
from numpy import argmax
from... | <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: only N+ contain positive charges in this dataset
Step2: We may want to remove cations with more than 25 heavy atoms
Step3: so some keras versi... |
6,294 | <ASSISTANT_TASK:>
Python Code:
import os
import sys
import pytz
import inspect
import numpy as np
import pandas as pd
import datetime as dt
import matplotlib.pyplot as plt
import tmpo
from opengrid import config
from opengrid.library import plotting
from opengrid.library import houseprint
c=config.Config()
%matplotlib ... | <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: This notebook shows step by step how water leaks of different severity can be detected
Step2: The purpose is to automatically detect leaks, und... |
6,295 | <ASSISTANT_TASK:>
Python Code:
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
import numpy as np
from matplotlib import pyplot as plt
device = 'cuda' if torch.cuda.is_available() else 'cpu'
print("We are using the following device for learning:",device)
batch_size_train = 60000 ... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Import and load MNIST dataset (Preprocessing)
Step2: Plot 8 random images
Step3: Specify Autoencoder
Step4: Helper function to get a random m... |
6,296 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
# use seaborn's default plotting styles for matplotlib
import seaborn; seaborn.set()
from gatspy.datasets import fetch_rrlyrae
rrlyrae = fetch_rrlyrae()
lcid = rrlyrae.ids[0]
t, y, dy, filts = rrlyrae.get_lightcurve(lci... | <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'll fit the multiband periodogram model to this data. For more information on the model, refer to the VanderPlas and Ivezic paper mentione... |
6,297 | <ASSISTANT_TASK:>
Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rc("image", aspect="equal")
import SimpleITK as sitk
# Download data to work on
%run update_path_to_download_script
from downloaddata import fetch_data as fdata
img = sitk.GaussianSource(size=[64] * 2)
plt.im... | <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 us begin by developing a convenient method for displaying images in our notebooks.
Step2: Multi-dimension slice indexing
Step3: Cropping
S... |
6,298 | <ASSISTANT_TASK:>
Python Code:
# First check the Python version
import sys
if sys.version_info < (3,4):
print('You are running an older version of Python!\n\n' \
'You should consider updating to Python 3.4.0 or ' \
'higher as the libraries built for this course ' \
'have only been test... | <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: Session 1 - Introduction to Tensorflow
Step2: Places your images in a folder such as dirname = '/Users/Someone/Desktop/ImagesFromTheInternet'. ... |
6,299 | <ASSISTANT_TASK:>
Python Code:
from google.cloud import bigquery
from datetime import datetime
import matplotlib.pyplot as plt, seaborn as sns
PROJECT_ID = 'yourProject' # Change to your project.
!gcloud config set project $PROJECT_ID
try:
from google.colab import auth
auth.authenticate_user()
print("Colab user... | <SYSTEM_TASK:>
Given the following text description, write Python code to implement the functionality described below step by step
<END_TASK>
<USER_TASK:>
Description:
Step1: Configure GCP environment settings
Step2: Authenticate your GCP account
Step3: Explore the sample data
Step4: Count the number of songs that ... |
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