Skip to main content

Seismic viewer for numpy

Project description

EasyQC

Seismic Viewer for numpy arrays using pyqtgraph.

Usage Instructions

The goal is to provide an interactive seismic viewer at the python prompt. NB: if you use ipython use the %gui qt magic command before !

Keyboard Shortcuts

  • ctrl + A: increase display gain by +3dB
  • ctrl + Z: deacrease display gain by +3dB
  • ctrl + P: take screenshot to clipboard
  • ctrl + P: propagates display accross all windows (same window size, same axis, same gain)
  • up/down/right/left arrows: pan using keyboard

Minimum working example to display a numpy array.

import numpy as np
import scipy.signal

from easyqc.gui import viewseis

ntr, ns, sr, dx, v1 = (500, 2000, 0.002, 5, 2000)
data = np.zeros((ntr, ns), np.float32)
data[:, 500:600] = scipy.signal.ricker(100, 4)

# create a record with 400 traces and 2500 samples
noise = np.random.randn(ntr, ns) / 10
# create an arbitrary layout of 2 receiver lines of 200 sensors
a, b = np.meshgrid(np.arange(ntr / 2) * 8 + 2000, np.arange(2) * 50 + 5000)
# the header is a dictionary of numpy arrays, each entry being the same length as the number of traces
header = {'receiver_line': b.flatten(), 'receiver_number': a.flatten()}

# show the array with the header
fig0 = viewseis(data, si=.002, h=header, title='clean')
fig1 = viewseis(data + noise, si=.002, h=header, title='noisy')

Install Instructions

1) From pypi using pip:

pip install easyqc

2) From sources using pip:

I suggest to use a virtual environment and install in development mode (in-place)

git clone https://github.com/oliche/easyqc.git
cd easyqc
pip install -e .

3) From sources using anaconda

I suggest to install a conda environment and run from sources in development mode.

Installation

git clone https://github.com/oliche/easyqc.git
conda env create -f conda_easyqc.yaml
conda activate iblenv
conda develop ./easyqc

Update

conda env update --file conda_easyqc.yaml --prune

Or for a complete clean-up:

conda env list
conda env remove -n easyqc

And follow the install instructions above.

Contribution

Pypi Release checklist:

flake8
rm -fR dist
rm -fR build
python setup.py sdist bdist_wheel
twine upload dist/*
#twine upload --repository-url https://test.pypi.org/legacy/ dist/*

Test wheel:

virtualenv easyqc --python=3.8
source ./easyqc/bin/activate
pip install easyqc
#pip install -i https://test.pypi.org/simple/ easyqc  # doesnt' seem to install deps

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

easyqc-0.6.1.tar.gz (15.5 kB view details)

Uploaded Source

Built Distribution

easyqc-0.6.1-py3-none-any.whl (15.1 kB view details)

Uploaded Python 3

File details

Details for the file easyqc-0.6.1.tar.gz.

File metadata

  • Download URL: easyqc-0.6.1.tar.gz
  • Upload date:
  • Size: 15.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10

File hashes

Hashes for easyqc-0.6.1.tar.gz
Algorithm Hash digest
SHA256 7824cd34ceaf313e1c041eb7a36e67ef030a4b567473bbf502ca13b8b27d89ec
MD5 32cd239c7bfff95e4ce0a6786a592084
BLAKE2b-256 a76c7d4077c0ee0f608d60b5daf0175fe147268d8d6ee38d3a4e6aad99a19c73

See more details on using hashes here.

File details

Details for the file easyqc-0.6.1-py3-none-any.whl.

File metadata

  • Download URL: easyqc-0.6.1-py3-none-any.whl
  • Upload date:
  • Size: 15.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10

File hashes

Hashes for easyqc-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 529950a6897efe96fd674a1d4382fa6b72e51a2f53f8ac5ff9a037b5404198f1
MD5 fc6deca14fb0c48d83fc0052419ed2c9
BLAKE2b-256 0ba15c20fd51b0ab8230b664611aefeb622a2521a51cf0d008a9d8d569785230

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page