LogViewer

class petropy.LogViewer(log, template_xml_path=None, template_defaults=None, top=None, height=None)[source]

Uses matplotlib to create a figure and axes to display log data. XML templates are required to diplay curve data, with a few defaults provided.

log

Log – The Log class with data updated from any edits performed within LogViewer

fig

Figure – The matplotlib Figure object

axes

ndarray – numpy ndarray of AxesSubplot objects where each axes is a curve track

Parameters:
  • log (Log) – A Log object with curve data to display in the LogViewer
  • template_xml_path (str (default None)) – Path to xml template.
  • template_defaults (str) – Name of default template options. Uses prebuilt template to display data
  • top (float (default None)) – Setting to set initial top of graph
  • height (float (default None)) – Setting to set amout of feet to display

Note

template_defaults string must be from these options

raw
multimin_oil
multimin_gas
multimin_oil_sum
multimin_gas_sum

Examples

>>> import petropy as ptr
# create LogViewer with default triple-combo template and display
#
# Load sample wolfcamp log
>>> log = ptr.log_data('WFMP')
# create LogViewer with 'raw' template
>>> viewer = ptr.LogViewer(log, template_defaults = 'raw')
>>> viewer.show() # diplay log data

>>> import petropy as ptr
# create LogViewer for 11 x 17 paper
# with default triple-combo template and save
#
# Load sample wolfcamp log
>>> log = ptr.log_data('WFMP')
# create LogViewer with 'raw' template (default)
>>> viewer = ptr.LogViewer(log)
# use fig attribute to change size to 17 x 11
>>> viewer.fig.set_size_inches(17, 11)
# file path for image file
>>> s = 'path/to/save/wfmp_log.png'
# saves matplotlib figure
>>> viewer.fig.savefig(s)

>>> import petropy as ptr
# create LogViewer with custom template and save
#
# Load sample wolfcamp log
>>> log = ptr.log_data('WFMP')
# specify path to template file
>>> t = 'path/to/my/custom/template.xml'
# create log view with template
>>> viewer = ptr.LogViewer(log, template_xml_path = t)
# define path to save the log picture
>>> s = 'path/to/save/figure.png'
# save figure using matplotlib savefig method
>>> viewer.fig.savefig(s)

>>> import petropy as ptr
# create LogViewer with default triple-combo template,
# make graphical edits, then save log changes
#
# Load sample wolfcamp log
>>> log = ptr.log_data('WFMP')
>>> viewer = ptr.LogViewer(log)
# diplay log data and graphically edit
>>> viewer.show(edit_mode = True)
# define path to save the updated log data
>>> file_path = 'path/to/save/wfmp_edits.las'
# write updated log to new las file.
# Executed after figures are closed.
>>> viewer.log.write(file_path)
Raises:
  • ValueError – If template_defaults parameter is not in key of dictionary items
  • ValueError – If template_xml_path are both specified
  • ValueError – tick spacing must be specified in depth track
  • ValueError – number spacing must be specified in depth track
  • ValueError – left and right values for each curve must be specified in xml template
  • ValueError – curve must be in log
  • ValueError – curve display_name must be specified in xml template
  • ValueError – curve curve_name must be specified in xml template
  • ValueError – curve fill_color must be specified for cumulative tracks
show(edit_mode=False, window_location=(10, 30))[source]

Calls matplotlib.pyplot.show() to display log viewer. If edit_mode == True, it includes options to graphically edit curve data, and stores these changes within the LogViewer object. After editing is finished, access the updated petropy.Log data with the .log property.

Parameters:
  • edit_mode (bool (default False)) – Setting to allow editing of curve data
  • window_location (float, float tuple (default 10, 30)) – Tuple of floats to specify top left location of LogViewer First value is pixels from the left of the screen. Second value is pixels from the top of the screen.

Example

>>> import petropy as ptr
>>> log = ptr.log_data('WFMP') # sample Wolfcamp log
>>> viewer = ptr.LogViewer(log) # default triple-combo template
>>> viewer.show() # display graphs

>>> import petropy as ptr
>>> log = ptr.log_data('WFMP') # sample Wolfcamp log
>>> viewer = ptr.LogViewer(log)
# display graphs with editing option
>>> viewer.show(edit_mode = True)
>>> file_path = 'path/to/new_file.las'
# writes changed data to new las file
>>> viewer.log.write(file_path)