Luke Campagnola campagnola

## gist:8966909
import pyqtgraph as pg
from pyqtgraph.Qt import QtGui, QtCore
pg.mkQApp()

## Create window with two ImageView widgets
win = QtGui.QMainWindow()
win.resize(800,800)
win.setWindowTitle('pyqtgraph example: DataSlicing')
cw = QtGui.QWidget()
win.setCentralWidget(cw)

## style_pass_examples
"""
pep8 violations:

E121,E123,E126,E201,E202,E203,E221,E222,E226,E227,E228,E231,E241,E251,
E302,E303,E401,E701,W291,W293,W391


Proposed style guidelines:
1. Is this code sufficiently readable?
2. Does the formatting cause extra effort for other people?

## triangulation
# -*- coding: utf8 -*-
"""
Constrained delaunay implementation based on

Domiter, V. and Žalik, B.
Sweep‐line algorithm for constrained Delaunay triangulation

(this implementation is not complete)
"""

## make_png.py
import numpy as np
import zlib
import struct

def make_png(data):
    """
    Convert numpy array to PNG byte array.

    *data* must be (H, W, 4) with dtype=ubyte
    """

## hdf5.py
"""
Demonstrates basic interaction with HDF5 library using python / ctypes
"""
import ctypes


# load library (this would be platform-dependent)
hdf5 = ctypes.cdll.LoadLibrary('libhdf5.so')

# Define constants

## 60Hz_removal.ipynb

      
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                campagnola
                / 60Hz_removal.ipynb
            
            
              Created
              June 21, 2019 21:40
            
              
                Very simple, artifact-free 60Hz hum removal (using scipy minimize)
              
          
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## composable_data_modeling.py
"""
Goals:
 - Extensible data modeling in python
 - Does _not_ use inheritance as a mechanism for model extension
 - Lightweight / simple infrastructure
 - Data objects have reasonably nice user API
"""

class Model:
    """Base class providing infrastructure for composable data modeling

## python-data-acquisition-camera.py
# extended from https://gist.github.com/HazenBabcock/8d1042f564dcaee60c3a3972f2d56999


class ImageData(object):
    """Contains information about one or more acquired frames.
    """
    def __init__(self, data, meta):
        self._data = data
        self._meta = meta

## flu_vs_covid19.py
"""
A week-by-week comparison of deaths caused by influenza and COVID-19 un the United States.

CDC influenza / pneumonia data:
https://www.cdc.gov/flu/weekly/#S2

COVID19 data:
http://www.healthdata.org/covid/data-downloads
"""
	import pyqtgraph as pg
	from pyqtgraph.Qt import QtGui, QtCore
	pg.mkQApp()

	## Create window with two ImageView widgets
	win = QtGui.QMainWindow()
	win.resize(800,800)
	win.setWindowTitle('pyqtgraph example: DataSlicing')
	cw = QtGui.QWidget()
	win.setCentralWidget(cw)
	"""
	pep8 violations:

	E121,E123,E126,E201,E202,E203,E221,E222,E226,E227,E228,E231,E241,E251,
	E302,E303,E401,E701,W291,W293,W391


	Proposed style guidelines:
	1. Is this code sufficiently readable?
	2. Does the formatting cause extra effort for other people?
	# -- coding: utf8 --
	"""
	Constrained delaunay implementation based on

	Domiter, V. and Žalik, B.
	Sweep‐line algorithm for constrained Delaunay triangulation

	(this implementation is not complete)
	"""
	import numpy as np
	import zlib
	import struct

	def make_png(data):
	"""
	Convert numpy array to PNG byte array.

	data must be (H, W, 4) with dtype=ubyte
	"""
	"""
	Demonstrates basic interaction with HDF5 library using python / ctypes
	"""
	import ctypes


	# load library (this would be platform-dependent)
	hdf5 = ctypes.cdll.LoadLibrary('libhdf5.so')

	# Define constants
	"""
	Goals:
	- Extensible data modeling in python
	- Does _not_ use inheritance as a mechanism for model extension
	- Lightweight / simple infrastructure
	- Data objects have reasonably nice user API
	"""

	class Model:
	"""Base class providing infrastructure for composable data modeling
	# extended from https://gist.github.com/HazenBabcock/8d1042f564dcaee60c3a3972f2d56999


	class ImageData(object):
	"""Contains information about one or more acquired frames.
	"""
	def __init__(self, data, meta):
	self._data = data
	self._meta = meta
	"""
	A week-by-week comparison of deaths caused by influenza and COVID-19 un the United States.

	CDC influenza / pneumonia data:
	https://www.cdc.gov/flu/weekly/#S2

	COVID19 data:
	http://www.healthdata.org/covid/data-downloads
	"""