Examples

Initialising arrays and assigning values in the script

The first example demonstrates a simple dynamic script with the usage of index variables, assigning values and looping over over the array indices:

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from pcraster import *
from pcraster.framework import *
from pcraster.collection import *
import os
import random

class SimpleLoops():
  def __init__(self, cloneMap):
    setclone(cloneMap)

  def initial(self):

    # oldcalc: Plants  = [TG,SG];
    self.Plants = Index(["TG", "SG"])

    # initialising QMax[Plants]
    self.QMax = VariableCollection([self.Plants], value=None)
    # and assigning values manually
    self.QMax[self.Plants.TG] = 10000.0
    self.QMax[self.Plants.SG] = 15000.0

    # initialising Cvr[Plants]
    self.Cvr = VariableCollection([self.Plants], value=None)
    # and assigning values manually
    self.Cvr[self.Plants.TG] = readmap(os.path.join("maps", "CvrTG.imp"))
    self.Cvr[self.Plants.SG] = readmap(os.path.join("maps", "CvrSG.imp"))

    # oldcalc:
    #foreach p in Plants {
    #  dH[p]          = 0;
    #  dH_1[p]        = 0;
    #}
    self.dH = VariableCollection([self.Plants], value=0)
    self.dH_1 = VariableCollection([self.Plants], value=0)

    # initialising timeseries report
    self.CvrTss = VariableCollection([self.Plants], value=ValueTimeoutputTimeseries("Cvr", self, idMap="clone.cln", noHeader=False))

  def dynamic(self):
    # just some random calculations
    for plant in self.Plants:
      self.dH[plant] = random.random()
      self.dH_1[plant] += self.dH[plant]
      self.Cvr[plant] += self.dH_1[plant]

      # reporting timeseries
      self.CvrTss[plant].sample(self.Cvr[plant])

model = SimpleLoops("clone.cln")
dynModel = DynamicFramework(model, endTimeStep=5, firstTimestep=1)
dynModel.run()

In the initial section we create an index type, called Plants with two types of array-index, namely TG and SG. After that, two variables, QMax and Cvr are initialised and individual values are assigned. For two other variables, dH and dH_1, array-indeces are initialised with an default value of 0.

In the dynamic section we loop over the array-indices and execute some simple operations.

Using parameter files for variable initialisation

The second example simplifies the initialisation of variables by external files:

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from pcraster import *
from pcraster.framework import *
from pcraster.collection import *
import random

class ParameterFileModel(object):
  def __init__(self, cloneMap):
    setclone(cloneMap)

  def initial(self):

    # Plants  = [TG,SG];
    self.Plants = Index(["TG", "SG"])

    # initialising QMax[Plants]
    self.QMax = VariableCollection([self.Plants], value=ValueFromParameterTable("QMax", "plant.tbl", Scalar))

    # initialising Cvr[Plants]
    self.Cvr = VariableCollection([self.Plants], value=ValueFromParameterTable("Cvr", "plant.tbl", Scalar))

    #foreach p in Plants {
    #  dH[p]          = 0;
    #  dH_1[p]        = 0;
    #}
    self.dH = VariableCollection([self.Plants], value=0)
    self.dH_1 = VariableCollection([self.Plants], value=0)

    # initialising timeseries report
    self.CvrTss =VariableCollection([self.Plants], value=ValueTimeoutputTimeseries("Cvr", self, idMap="clone.cln", noHeader=False))

  def dynamic(self):
    # just some random calculations
    for plant in self.Plants:
      self.dH[plant] = random.random()
      self.dH_1[plant] += self.dH[plant]
      self.Cvr[plant] += self.dH_1[plant]

      # reporting timeseries
      self.CvrTss[plant].sample(self.Cvr[plant])


model = ParameterFileModel("clone.cln")
dynModel = DynamicFramework(model, endTimeStep=5, firstTimestep=1)
dynModel.run()

The functionality of the example above equals the one of the first example. Here, the variables QMax and Cvr are initialised from a parameter file ‘plant.tbl’.

Parameter files

The structure of the parameter files must be the same as used for oldcalc. Therefore, the second example uses a parameter file like:

# TG - TallGrass
# SG - ShortGass

# initial cover, can be a spatial
Cvr    TG     maps\CvrTG.imp
Cvr    SG     maps\CvrSG.imp

# quality of plant material [J g-1]
QMax   TG     10000.     
QMax   SG     15000.

# maximum vegetation density [g m-2]
kv     TG       1000.
kv     SG       500.

# maximum relative growth rate [g g-1 d-1]
rv     TG       0.05
rv     SG       0.1

# minimum and maximum value for the average distance between patches
AvDstPatchMin	TG	 2.
AvDstPatchMin	SG   50.
AvDstPatchMax	TG	 2.
AvDstPatchMax	SG   100.

# minimum and maximum value for the standard deviation for distance between patches.
StdevDstPatchMin	TG	0.
StdevDstPatchMin	SG  0.
StdevDstPatchMax	TG	0.
StdevDstPatchMax	SG  0.

# 'dimension' of the grass, 2D or 3D
Dim    TG       3.
Dim    SG       2.

# ratio stem to foliage at the end of the growing season, represents quality
fLeaf2Stalk	TG	0.50
fLeaf2Stalk	SG	0.95

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