figures Namespace Reference

Functions
	build_parent_map (root=xmlparameters)
	find_species (root, mnemonic)
	_get_from_default (root, name_lower)
	get_par (name, species_mnemonic, root=xmlparameters, parent_map=parent_map)
	get_par (_name, _type='mean')
	Helpers.
	weibull (_x, _p1, _p2, _p3=1.0)
	Response functions.
	get_par_range (_name)
	plot_response_row (_ax, _func, _x, _names, _xlabel, _ylabel, _xlim=None, _ylim=None, _legend=False)
	plot_response (_filename, _func, _x, _names, _xlabel, _ylabel, _xlim=None, _ylim=None, _legend=False, _adjust=None)
	plot_single (_filename, _func, _x, _xlabel, _ylabel, _xlim=None, _ylim=None)
	ph_logistic (_x, _ph_50, _width)
	ph_bell (_x, _half_width, _exponent, _ph_opt)
	ph_cutoff (_fact)
	get_par (_name, _xml)
	Helpers.

Variables
	fig = plt.figure( figsize=(7, 4))
	zs = np.array([temp(x, t1, t2) * weibull(y, w1, w2, w3) for x,y in zip(np.ravel(X), np.ravel(Y))]) zs = np.array([2.0 / (1.0/temp(x, t1, t2) + 1.0/weibull(y, w1, w2, w3)) for x,y in zip(np.ravel(X), np.ravel(Y))]) Z = zs.reshape(X.shape)
	_xlim
	Microbial processes.
	_ylim
	Nitrification.
	p_mix = get_par('METRX_F_PERTUBATION_MIX')
	Bioturbation (D_eff_dailyturbation_sl) response factors (constants are hard-coded in soilchemistry-metrx-physics-chemistry.cpp)

Detailed Description

Response functions of MeTrX plotted for the doxygen documentation.

Parameter values (mean, min, max) are read from resources/parameters-site.xml,
figures are written to ../figures/.

Function Documentation

_get_from_default()

figures._get_from_default ( root, name_lower )

protected

Fallback: get parameter from species mnemonic='none'.

def _get_from_default(root, name_lower):
    """Fallback: get parameter from species mnemonic='none'."""
    default_species = find_species(root, 'none')
    if default_species is None:
        return None  # or raise
 
    for elem in default_species.findall('par'):
        if elem.attrib.get('name', '').lower() == name_lower:
            return float(elem.attrib['value'])
    return None
 

References find_species().

Referenced by get_par().

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build_parent_map()

figures.build_parent_map

(

root = xmlparameters

)

Build a dict: child_element -> parent_element.

def build_parent_map(root=xmlparameters):
    """Build a dict: child_element -> parent_element."""
    return {child: parent for parent in root.iter() for child in parent}

References build_parent_map().

Referenced by build_parent_map(), and get_par().

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find_species()

figures.find_species	(		root,
			mnemonic )

Return the first <species> element with the given mnemonic.

def find_species(root, mnemonic):
    """Return the first <species> element with the given mnemonic."""
    for node in root.iter('species'):
        if node.attrib.get('mnemonic') == mnemonic:
            return node
    return None
 

Referenced by _get_from_default(), and get_par().

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get_par() [1/3]

figures.get_par	(	_name	,
		_type	= 'mean' )

Helpers.

Return value ('mean'), 'min' or 'max' of a site parameter.

def get_par( _name, _xml) :
    for elem in _xml :
        if elem.attrib.get( 'name').lower() == _name.lower() :
            return float(elem.attrib.get( 'value', ''))
    return None
    

get_par() [2/3]

figures.get_par	(		_name,
			_type = 'mean' )

Helpers.

Return value ('mean'), 'min' or 'max' of a site parameter.

def get_par( _name, _xml) :
    for elem in _xml :
        if elem.attrib.get( 'name').lower() == _name.lower() :
            return float(elem.attrib.get( 'value', ''))
    return None
    

References get_par(), and weibull().

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get_par() [3/3]

figures.get_par	(		name,
			species_mnemonic,
			root = xmlparameters,
			parent_map = parent_map )

name: parameter name (string), e.g. 'aejm'
species_mnemonic: e.g. ':corns:' or ':poaceae:'
root: root <speciesparameters> element
parent_map: optional precomputed parent map (for efficiency)

def get_par(name, species_mnemonic, root=xmlparameters, parent_map=parent_map):
    """
    name: parameter name (string), e.g. 'aejm'
    species_mnemonic: e.g. ':corns:' or ':poaceae:'
    root: root <speciesparameters> element
    parent_map: optional precomputed parent map (for efficiency)
    """
    if parent_map is None:
        parent_map = build_parent_map(root)
 
    name_lower = name.lower()
 
    # 1. Find requested species node
    species_node = find_species(root, species_mnemonic)
    if species_node is None:
        # if the species doesn't exist at all, skip to default
        return _get_from_default(root, name_lower)
 
    # 2. Walk up the hierarchy: species -> parent species -> ...
    current = species_node
    while current is not None and current.tag == 'species':
        for elem in current.findall('par'):
            if elem.attrib.get('name', '').lower() == name_lower:
                return float(elem.attrib['value'])
        current = parent_map.get(current)
 
    # 3. If not found, try the default species mnemonic="none"
    return _get_from_default(root, name_lower)
 
 

References _get_from_default(), build_parent_map(), find_species(), and get_par().

Referenced by get_par(), get_par(), and get_par_range().

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get_par_range()

figures.get_par_range

(

_name

)

Return dictionary with mean, min and max of a site parameter.

def get_par_range(_name):
    """Return dictionary with mean, min and max of a site parameter."""
    return {t: get_par(_name, t) for t in ('mean', 'min', 'max')}
 

References get_par().

Referenced by plot_response_row().

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ph_bell()

figures.ph_bell	(		_x,
			_half_width,
			_exponent,
			_ph_opt )

MeTrX_get_fact_ph_bell (arguments in order of site parameters _1, _2, _3).

def ph_bell(_x, _half_width, _exponent, _ph_opt):
    """MeTrX_get_fact_ph_bell (arguments in order of site parameters _1, _2, _3)."""
    return 1.0 / (1.0 + (abs(_x - _ph_opt) / _half_width)**_exponent)

ph_cutoff()

figures.ph_cutoff

(

_fact

)

Processes with pH response below FACT_PH_MIN are not calculated (SoilChemistryMeTrX::FACT_PH_MIN).

def ph_cutoff(_fact):
    """Processes with pH response below FACT_PH_MIN are not calculated (SoilChemistryMeTrX::FACT_PH_MIN)."""
    return _fact if _fact >= FACT_PH_MIN else 0.0

References plot_response().

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ph_logistic()

figures.ph_logistic	(		_x,
			_ph_50,
			_width )

MeTrX_get_fact_ph_logistic: increasing with pH for _width > 0, decreasing for _width < 0.

def ph_logistic(_x, _ph_50, _width):
    """MeTrX_get_fact_ph_logistic: increasing with pH for _width > 0, decreasing for _width < 0."""
    return 1.0 / (1.0 + math.exp(-(_x - _ph_50) / _width))

plot_response()

figures.plot_response	(		_filename,
			_func,
			_x,
			_names,
			_xlabel,
			_ylabel,
			_xlim = None,
			_ylim = None,
			_legend = False,
			_adjust = None )

Plot response with sensitivity to each parameter (see plot_response_row) and save figure.

                  _xlim=None, _ylim=None, _legend=False, _adjust=None):
    """Plot response with sensitivity to each parameter (see plot_response_row) and save figure."""
    n = len(_names) + 1
    fig, ax = plt.subplots(1, n, figsize=(5*n, 4))
    plot_response_row(ax, _func, _x, _names, _xlabel, _ylabel, _xlim, _ylim, _legend)
    if _adjust is not None:
        plt.subplots_adjust(**_adjust)
    save(_filename)
 

References plot_response_row().

Referenced by ph_cutoff().

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plot_response_row()

figures.plot_response_row	(		_ax,
			_func,
			_x,
			_names,
			_xlabel,
			_ylabel,
			_xlim = None,
			_ylim = None,
			_legend = False )

Plot _func(x, *parameters) on a row of axes.

The first panel shows the response with all parameters at their mean value.
Each further panel varies one parameter between min (blue), mean (black) and
max (red) while the other parameters are kept at their mean value.

def plot_response_row(_ax, _func, _x, _names, _xlabel, _ylabel, _xlim=None, _ylim=None, _legend=False):
    """Plot _func(x, *parameters) on a row of axes.
 
    The first panel shows the response with all parameters at their mean value.
    Each further panel varies one parameter between min (blue), mean (black) and
    max (red) while the other parameters are kept at their mean value.
    """
    pars = [get_par_range(name) for name in _names]
    means = [p['mean'] for p in pars]
 
    _ax[0].plot(_x, [_func(x, *means) for x in _x], colors['mean'])
    _ax[0].set_title('\n'.join(f"{n}: {p['mean']}" for n, p in zip(_names, pars)), fontsize=8)
 
    for k, par in enumerate(pars):
        ax = _ax[k+1]
        for t in ('mean', 'min', 'max'):
            values = list(means)
            values[k] = par[t]
            ax.plot(_x, [_func(x, *values) for x in _x], colors[t],
                    label=None if t == 'mean' else str(par[t]))
        ax.set_title('\n'.join(f"{n}: [{p['min']}, {p['max']}]" if i == k else f"{n}: {p['mean']}"
                               for i, (n, p) in enumerate(zip(_names, pars))), fontsize=8)
        if _legend:
            ax.legend()
 
    for ax in _ax:
        format_axes(ax, _xlabel, _ylabel, _xlim, _ylim)
 

References get_par_range().

Referenced by plot_response().

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plot_single()

figures.plot_single	(		_filename,
			_func,
			_x,
			_xlabel,
			_ylabel,
			_xlim = None,
			_ylim = None )

Plot response without parameter variation and save figure.

def plot_single(_filename, _func, _x, _xlabel, _ylabel, _xlim=None, _ylim=None):
    """Plot response without parameter variation and save figure."""
    fig, ax = plt.subplots(1, 1, figsize=(5, 4))
    ax.plot(_x, [_func(x) for x in _x])
    format_axes(ax, _xlabel, _ylabel, _xlim, _ylim)
    save(_filename)
 
 

Variable Documentation

_xlim

figures._xlim

protected

Microbial processes.

Methane production and oxidation.

Decomposition and humification.

Denitrification.

_ylim

figures._ylim

protected

Nitrification.

Anaerobic volume fraction and pore connectivity.

fig

figures.fig = plt.figure( figsize=(7, 4))

zs = np.array([temp(x, t1, t2) * weibull(y, w1, w2, w3) for x,y in zip(np.ravel(X), np.ravel(Y))]) zs = np.array([2.0 / (1.0/temp(x, t1, t2) + 1.0/weibull(y, w1, w2, w3)) for x,y in zip(np.ravel(X), np.ravel(Y))]) Z = zs.reshape(X.shape)

ax.plot_surface(X, Y, Z, cmap="winter", rstride=1, cstride=1) ax.set_title('Temperature-moisture factor') ax.set_xlabel('T [oC]') ax.set_ylabel('wfps [-]') ax.set_zlabel('response [-]') plt.savefig(script_dir+"/../figures/temp_moist.png")