richpsharp

import numpy
import matplotlib.pyplot

slope_in_radians_list = numpy.linspace(0.089, 0.785, 100)
beta_list = []
m_list = []
for slope_in_radians in slope_in_radians_list:
    beta = ((numpy.sin(slope_in_radians) / 0.0896) /
            (3 * numpy.sin(slope_in_radians)**0.8 + 0.56))
    m_list.append(beta/(1+beta))

richpsharp

"""InVEST Sediment Delivery Ratio (SDR) module.

The SDR method in this model is based on:
    Winchell, M. F., et al. "Extension and validation of a geographic
    information system-based method for calculating the Revised Universal
    Soil Loss Equation length-slope factor for erosion risk assessments in
    large watersheds." Journal of Soil and Water Conservation 63.3 (2008):
    105-111.
"""
import os

richpsharp

clear all
close all

addpath(genpath(pwd))

% channel init threshold [km2]
Ad_ini=1;

% length threshold [m]

richpsharp

"""SQLAlchemy models for STAC view."""
from ..db import db


class Job(db.Model):
    """Stores info about a non-trivial running job invoked from the API."""

    __tablename__ = "job_table"

    job_id = db.Column(db.String, primary_key=True)

richpsharp

"""Run pollination model on a variety of scenarios

All data should be in a "data" subdirectory in the same directory as this
script.

Run it with docker as the following:

docker container run -it --rm --name pollination_kelley -v `pwd`:/usr/local/workspace therealspring/inspring:latest pollination_simulations.py

"""

richpsharp

"""Tracer for NDR watershed processing."""
import argparse
import glob
import logging
import multiprocessing
import os
import shutil
import subprocess
import threading
import urllib

richpsharp

"""Tracer for floodplain extraction function with custom parameters."""
import logging
import os
import sys

import pygeoprocessing
import pygeoprocessing.routing
import numpy

logging.basicConfig(

richpsharp

"""Tracer for floodplain extraction function with custom parameters."""
import logging
import os
import sys

from inspring.floodplain_extraction.floodplain_extraction import floodplain_extraction_custom_power_params


logging.basicConfig(
    level=logging.DEBUG,

richpsharp

"""Tracer for floodplain extraction function"""

"""
def floodplain_extraction(
        t_return_parameter,
        min_flow_accum_threshold,
        dem_path,
        stream_gauge_vector_path,
        gauge_table_path,
        gauge_id_field,

richpsharp

import time

import numpy

def mask_op(array_a, array_b, nodata):
    result = numpy.full(array_a.shape, nodata, dtype=numpy.float)
    valid_mask = numpy.ones(array_a.shape, dtype=numpy.bool)
    valid_mask &= (array_a != nodata) & (array_b != nodata)
    result[valid_mask] = array_a[valid_mask]+array_b[valid_mask]
    return result