treetopper 1.1.6
Python module for calculating Timber data from tree species of the west coast
License: MIT
Requires Python: >=3.6
Keywords: forestry,natural resources,natural,resources,forest,environmental,environmental science,science,timber,tree,trees,west,coast,west coast,logging,cruising,scaling,inventory,forests,board feet,cubic feet,DBH,diameter at breast height,DIB,diameter inside bark,RD,relative density,HDR,height to diameter ratio,species,VBAR,volume to basal area ratio,BA,basal area,TPA,trees per acre,scribner,timber marketing,forest marketing,timber management,forest management

# treetopper
Python module for calculating Stand data using tree species of the west coast.

DOCUMENTATION
https://zacharybeebe.github.io/treetopper/


pip install treetopper


If you would like to download a blank, formatted inventory sheet in .csv or .xlsx...

    In the terminal:

        python -m treetopper.blank_sheet

    And follow the prompts



To go through example workflows with treetopper, this can be done in with the stand module.

There are 6 different workflows that show examples of how treetopper works, these workflows
will show console reports, create csv/xlsx files of stand plot data, create pdf reports,
and/or create FVS-formatted databases

The workflow number 1 through 6 is the only argument when calling the stand module.

    In the terminal:

        python -m treetopper.stand [workflow_number]

    The summary of the workflow and the outputs will print at the bottom of the terminal




The species available for calculation are below and must have the correct species code...

        'DF': 'DOUGLAS-FIR'
        'WH': 'WESTERN HEMLOCK'
        'RC': 'WESTERN REDCEDAR'
        'SS': 'SITKA SPRUCE'
        'ES': 'ENGLEMANN SPRUCE'
        'SF': 'SILVER FIR'
        'GF': 'GRAND FIR'
        'NF': 'NOBLE FIR'
        'WL': 'WESTERN LARCH'
        'WP': 'WHITE PINE'
        'PP': 'PONDEROSA PINE'
        'LP': 'LODGEPOLE PINE'
        'JP': 'JEFFERY PINE'
        'SP': 'SUGAR PINE'
        'WF': 'WHITE FIR'
        'RF': 'RED FIR'
        'RW': 'COASTAL REDWOOD'
        'IC': 'INSENCE CEDAR'
        'RA': 'RED ALDER'
        'BM': 'BIGLEAF MAPLE'
        'CW': 'BLACK COTTONWOOD'
        'AS': 'QUAKING ASPEN'



An example of how to get started is...

    from treetopper import *

    """
    This workflow will create a quick cruise stand from manually entered plot/tree data
    and then will display a console report, create a pdf report and create a csv file
    of the stand's plot data in the current working directory.

    Using the ThinTPA class, we will run a thinning scenario on the stand to a target density
    of 80 Trees per Acre considering all species and diameter ranges. Then it will display a
    console report of the thinning and create a pdf report.

    Finally we will use the FVS class to create a SQLite database that is formatted for use
    in FVS. FVS is the US Forest Service's "Forest Vegetation Simulator" software.
    """

    ## Instantiating the Stand class
    stand = Stand('WF1', -20)
    # Stand(Stand Name, Plot Factor, [optional] Acres, Inventory Date)

    plot_factor = stand.plot_factor

    ## Entering Tree Data for a Quick Cruise, using the TimberQuick class
    tree_data = [[TimberQuick('DF', 29.5, 119, plot_factor), TimberQuick('WH', 18.9, 102, plot_factor),
                  TimberQuick('WH', 20.2, 101, plot_factor), TimberQuick('WH', 19.9, 100, plot_factor),
                  TimberQuick('DF', 20.6, 112, plot_factor)],
                 [TimberQuick('DF', 25.0, 117, plot_factor), TimberQuick('DF', 14.3, 105, plot_factor),
                  TimberQuick('DF', 20.4, 119, plot_factor), TimberQuick('DF', 16.0, 108, plot_factor),
                  TimberQuick('RC', 20.2, 124, plot_factor), TimberQuick('RC', 19.5, 116, plot_factor),
                  TimberQuick('RC', 23.4, 121, plot_factor), TimberQuick('DF', 17.8, 116, plot_factor),
                  TimberQuick('DF', 22.3, 125, plot_factor)]
                 ]
    #TimberQuick(Species Code, DBH, Total Height, Plot Factor, [optional] Preferred Log Length, Minimum Log Length)

    ## Adding Tree data to Plot class and adding the Plot class to the Stand class
    for trees in tree_data:
        plot = Plot()
        for tree in trees:
            plot.add_tree(tree)
        stand.add_plot(plot)

    ## Generating Stand class data reports
    print(stand.console_report())
    stand.pdf_report('example_stand_report')
    # stand.pdf_report(Filename, [optional] Directory)
    stand.table_to_csv('example_csv_export.csv')
    # stand.table_to_csv(Filename, [optional] Directory)


    ## Running a thinning scenario on the Stand class, using the ThinTPA class
    thin80tpa = ThinTPA(stand, 80)
    # ThinTPA(Stand Class, Target Density, [optional] Species to Cut (list), Minimum DBH to Cut, Maximum DBH to Cut)


    ## Generating Thin class report
    print(thin80tpa.console_report())
    thin80tpa.pdf_report('example_thin_report')
    # thin80tpa.pdf_report(Filename, [optional] Directory)


    ## Creating a FVS-formatted database from the Stand class data
    fvs = FVS()
    fvs.set_stand(stand, 'PN', 612, 6, 45, 'DF', 110)
    # fvs.set_stand(Stand Class, Variant, Forest Number, Region Number, Stand Age, Site Class Species, Site Index, **kwargs)
    fvs.sqlite_db('sqlite_db')
    # fvs.sqlite_db(Filename, [optional] Directory, Blank Database (bool))