Reading and Plotting data with DC.IO class

The DC.IO class is a convenient way to handle DC data and carry inversions within a same class. It also has several plotting utils such as pseudosections. We show here an example of plotting DC data based on a demonstration dataset.

import numpy as np
import pandas as pd
import shutil
import os
import matplotlib.pyplot as plt
from SimPEG.electromagnetics.static import resistivity as DC
from SimPEG import Report
from SimPEG.utils.io_utils import download

Download an example DC data csv file

# file origina and name
url = "https://storage.googleapis.com/simpeg/examples/dc_data.csv"
fname = download(url, folder="./test_url", overwrite=True)

# read csv using pandas
df = pd.read_csv(fname)
# header for ABMN locations
header_loc = ["Spa." + str(i + 1) for i in range(4)]
# Apparent resistivity
header_apprho = df.keys()[6]

Out:

Downloading https://storage.googleapis.com/simpeg/examples/dc_data.csv
   saved to: /Users/josephcapriotti/codes/simpeg/examples/04-dcip/test_url/dc_data.csv
Download completed!

Convert file to DC.IO object

# Number of the data
ndata = df[header_loc[0]].values.size
# ABMN locations
a = np.c_[df[header_loc[0]].values, np.zeros(ndata)]
b = np.c_[df[header_loc[1]].values, np.zeros(ndata)]
m = np.c_[df[header_loc[2]].values, np.zeros(ndata)]
n = np.c_[df[header_loc[3]].values, np.zeros(ndata)]
# Apparent resistivity
apprho = df[header_apprho].values

# Create DC.IO survey Object object
IO = DC.IO()
# Generate DC survey using IO object
dc_survey = IO.from_ambn_locations_to_survey(
    a,
    b,
    m,
    n,
    survey_type="dipole-dipole",
    data_dc=apprho,
    data_dc_type="apparent_resistivity",
)

Out:

/Users/josephcapriotti/opt/anaconda3/envs/py36/lib/python3.6/site-packages/SimPEG/electromagnetics/static/resistivity/IODC.py:190: UserWarning: code under construction - API might change in the future
  warnings.warn("code under construction - API might change in the future")

Plot

fig, ax = plt.subplots(1, 1, figsize=(10, 3))
IO.plotPseudoSection(
    data_type="apparent_resistivity", scale="linear", clim=(0, 1000), ncontour=3, ax=ax
)
plt.show()

# clean up
shutil.rmtree(os.path.expanduser("./test_url"))

Out:

/Users/josephcapriotti/codes/simpeg/examples/04-dcip/plot_read_DC_data_with_IO_class.py:74: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
  plt.show()

Print the version of SimPEG and dependencies

Report()

Tue May 26 18:57:14 2020 MDT
OS	Darwin	CPU(s)	8	Machine	x86_64
Architecture	64bit	Environment	Python
Python 3.6.10 |Anaconda, Inc.| (default, May 7 2020, 23:06:31) [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
SimPEG	0.14.0b2	discretize	0.4.11	pymatsolver	0.1.2
vectormath	0.2.2	properties	0.6.1	numpy	1.18.1
scipy	1.4.1	cython	0.29.17	IPython	7.13.0
matplotlib	3.1.3	ipywidgets	7.5.1
Intel(R) Math Kernel Library Version 2019.0.4 Product Build 20190411 for Intel(R) 64 architecture applications

Moving Forward

If you have suggestions for improving this example, please create a pull request on the example in SimPEG

You might try:

• changing the contour levels

• try with you own dataset

• create a mask for negative apparent resistivities

• …