pyRobShrk

# name=Godin
# description=This jython script reads your DSSVue selection, and performs Godin tidal smoothing.
# description=The original 1972 Godin algorithm was to apply successive 25-hour averages to hourly data.
# description=This filter is slightly modified for 15-minute data, and specific to the periods of tidal constituents.
# description=The 51-period (12.5-hr) filters M4, MS4 and MN4, 97-period (24-hr) filters S2 and K2, and 101-period (25-hr) filters M2, N2, and L2.
# displayinmenu=false
# displaytouser=true
# displayinselector=false
from hec.hecmath import HecMath
from hec.heclib.dss import HecDss, DSSPathname

pyRobShrk

_search = LAMBDA(txt, searchtext, [case_sensitive],
    // Test the inputs for errors so that we can distinguish
    // the error that comes from FIND/SEARCH as meaning "not-found".
    IFS(
        ISERROR(txt),
        txt,
        ISERROR(searchtext),
        searchtext,
        ISERROR(case_sensitive),
        case_sensitive,

pyRobShrk

/*
Name: Show Moon Phase Emoji (MOONPHASE)
Description: Returns a lunar phase character closest matching to any Excel Date/Time value.
If you calculate for daily values at midnight, the lunar cycle will be the same for every 3 or 4 days (3.691 days).
🌑🌒🌓🌔🌕🌖🌗🌘
*/

MOONPHASE = LAMBDA(datetime,LET(
    phase,MOD(ROUND(MOD(datetime-1.5,29.53059)/3.69125,0),8)+1,
    UNICHAR(127760+phase)));

pyRobShrk

aalii
aargh
aarti
abaca
abaci
aback
abacs
abaft
abaka
abamp

pyRobShrk

Function Muskingum(timeSeries As Range, _
                   K As Double, X As Double, _
                   Optional Reaches As Integer = 1) As Variant
'Muskingum routing in Excel
'Returns a column array the same length as timeSeries (use array formula or spill)
'K (travel time) is in same units as the time step of the input timeSeries
'X must be between 0 and 0.5
'Reaches will be automatically adjusted to avoid negative coefficients if K is < 1 / (2*(1-X)) or K > 1/2X
Dim Coeffs(1 To 5) As Double

pyRobShrk

Function interp(X As Double, xRange As Range, yRange As Range) As Double

    ascending = xRange.Cells(1) < xRange.Cells(2)
    With WorksheetFunction
        If ascending Then i = .Match(X, xRange) Else i = .Match(X, xRange, -1)
        Set x1x2 = Range(xRange.Cells(i), xRange.Cells(i + 1))
        Set y1y2 = Range(yRange.Cells(i), yRange.Cells(i + 1))
        interp = X * .Slope(y1y2, x1x2) + .Intercept(y1y2, x1x2)
    End With
    

pyRobShrk

# Remove duplicate vertices from lines
# A point is considered duplicate if it has the same XY coordinates within a tolerance (precision)
# The precision is an integer number of decimal places
# for X,Y in lat, long, 5 decimals is 1.1 meters and 6 is 11 cm
def removeDupeVertices(feature, precision):
	fields = ['SHAPE@'] + [f.name for f in arcpy.ListFields(feature)]
	sr = arcpy.Describe(feature).SpatialReference
	upd = arcpy.da.UpdateCursor(feature,fields)
	orphanList = []
	for row in upd:

pyRobShrk

# Objective: A system capable of encoding geographic points, and polylines in ASCII characters
# 			 Obviously Google and geohash have similar algorithms, but with limited precision
#
# A 24-bit integer can store binary integer values up to 16,777,215
# Using PEM format, 24 bits can be represented as 4 base-64 characters with the alphabet:
# ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/
# A polyline can be represented by a string of characters,
# where each 8 characters is a longitude/latitude location
# For maximum flexibility, a polyline or point string is prefixed with three characters
# The first two characters specifies the origin - the lower left corner of a MGRS GZD

pyRobShrk

import pandas as pd
def GIStable2Clipboard(inTable, exportFields="all"):
	desc = arcpy.Describe(inTable)
	if exportFields =="all":
		exportFields = [f.name for f in arcpy.ListFields(inTable) if not f.name == desc.shapeFieldName]
		aliases = [f.aliasName for f in arcpy.ListFields(inTable) if not f.name == desc.shapeFieldName]
	pd.DataFrame.from_records(arcpy.da.TableToNumPyArray(inTable,exportFields),
							index=desc.OIDFieldName, columns=aliases).to_clipboard()

pyRobShrk

import numpy as np
from scipy.interpolate import RectBivariateSpline as Spline
import pygeodesy as geo
from pygeodesy.ellipsoidalVincenty import LatLon

class Geoid12B(): #NAD 83 Ellipsoid
    # https://www.ngs.noaa.gov/GEOID/GEOID12B/GEOID12B_CONUS.shtml
    # Download a Geoid Grid in little endian binary format ('g2012bu5.bin')
    def __init__(self, leBinFile):
        glamn, glomn, dla, dlo = np.fromfile(leBinFile,'<f8',4)