From ae181e0cb81b2261eb9dfb65f110f6749eb39c33 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Fri, 19 Mar 2021 18:52:05 +0100 Subject: [PATCH 1/9] some docs on avoiding cycles --- doc/create_model.rst | 10 ++++++++++ doc/framework.rst | 4 +++- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/doc/create_model.rst b/doc/create_model.rst index bec05b0b..51a9814b 100644 --- a/doc/create_model.rst +++ b/doc/create_model.rst @@ -241,6 +241,16 @@ In terms of computation and inputs, ``advect_model`` is equivalent to the ``advect_model_raw`` instance created above ; it is just organized differently. +Avoiding cycles in the model +---------------------------- +Often, a process involves updating a variable, that is used by other processes in the model. +This may result in a cycle being detected, and the model not able to run. The +process order is created based on variables with ``intent='out'``. Therefore, any variable +that is created with ``intent='inout'`` will be set last in the calculation order. +Any process that uses this variable as an input, will use the veriable from the previous timestep. +For example, the ``u`` variable in ``ProfileU`` has ``intent='inout'``, and is therefore last in the calculation order. + + Update existing models ---------------------- diff --git a/doc/framework.rst b/doc/framework.rst index 2c1a880b..9508059f 100644 --- a/doc/framework.rst +++ b/doc/framework.rst @@ -273,7 +273,9 @@ in their computation. In a model, the processes and their dependencies together form the nodes and the edges of a Directed Acyclic Graph (DAG). The graph topology is fully determined by the ``intent`` set for each variable -or foreign variable declared in each process. An ordering that is +or foreign variable declared in each process. That is, a process depends on +another process if and only if the 'parent' process has an ``intent='out'`` +variable, that is used by the 'child' process. An ordering that is computationally consistent can then be obtained using topological sorting. This is done at Model object creation. The same ordering is used at every stage of a model run. From 7cbf487172ee703a641e6bc40ed5bcfb6ceb7908 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Sat, 20 Mar 2021 13:37:57 +0100 Subject: [PATCH 2/9] show_inout_arrows and example notebook --- notebooks/cyclic.ipynb | 227 +++++++++++++++++++++++++++++++++++++++++ xsimlab/dot.py | 38 +++++++ 2 files changed, 265 insertions(+) create mode 100644 notebooks/cyclic.ipynb diff --git a/notebooks/cyclic.ipynb b/notebooks/cyclic.ipynb new file mode 100644 index 00000000..e266c978 --- /dev/null +++ b/notebooks/cyclic.ipynb @@ -0,0 +1,227 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "chronic-survivor", + "metadata": {}, + "outputs": [], + "source": [ + "import xsimlab as xs\n", + "import math" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "cloudy-viking", + "metadata": {}, + "outputs": [], + "source": [ + "@xs.process\n", + "class Biomass:\n", + " B_vars = xs.group('biomass')\n", + " dB = xs.variable(intent='inout',default=0)\n", + " B = xs.variable(intent='inout',default=1)\n", + " \n", + " #we can actually safely use run_step because of the cycle ordering?\n", + " def run_step(self):\n", + " self.dB = sum(self.B_vars)\n", + " self.B += self.dB\n", + "\n", + "#jsut some processes to have a longer cycle\n", + "@xs.process\n", + "class FracInterceptedLight:\n", + " leaf_area = xs.variable(global_name='leaf_area',intent='in')\n", + " intercepted_light = xs.variable(intent='out')\n", + " ext_coeff = xs.variable(default=0.8)\n", + " \n", + " def run_step(self):\n", + " self.intercepted_light = 1-math.exp(-self.ext_coeff*self.leaf_area)\n", + "\n", + "@xs.process\n", + "class LeafAreaAnnual:\n", + " leaf_area = xs.global_ref('leaf_area',intent='out')\n", + " prev_dB = xs.foreign(Biomass, 'dB')\n", + "\n", + " pl = xs.variable(default = 0.002)\n", + " init_leaf_area = xs.variable(default = 0.01)\n", + " \n", + " def initialize(self):\n", + " self.leaf_area = self.init_leaf_area\n", + " \n", + " @xs.runtime(args='step_delta')\n", + " def run_step(self,dt):\n", + " self.leaf_area += self.pl*self.prev_dB*dt\n", + "\n", + "#this process actually adds some to 'biomass' group\n", + "@xs.process\n", + "class LightLimitedPlantGrowth:\n", + " frac_light = xs.foreign(FracInterceptedLight,\"intercepted_light\")\n", + " \n", + " light_efficiency = xs.variable(default=3)\n", + " biomass_growth = xs.variable(intent='out',groups='biomass')\n", + " \n", + " @xs.runtime(args='step_delta')\n", + " def run_step(self,dt):\n", + " #wrongfully assuming \n", + " self.biomass_growth = self.light_efficiency*self.frac_light\n", + " \n", + "@xs.process\n", + "class InitialBiomass:\n", + " initial = xs.variable(default=1)\n", + " biomass = xs.foreign(Biomass,'B',intent='out')\n", + " \n", + " def initialize(self):\n", + " self.biomass = self.initial\n", + " \n", + "@xs.process\n", + "class BiomassDeath:\n", + " biomass = xs.foreign(Biomass,\"B\")\n", + " death_rate = xs.variable(default=0.0005)\n", + " biomass_death = xs.variable(intent='out',groups='biomass')\n", + " \n", + " @xs.runtime(args='step_delta')\n", + " def run_step(self,dt):\n", + " self.biomass_death = -self.biomass*self.death_rate*dt" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "positive-physiology", + "metadata": {}, + "outputs": [], + "source": [ + "model = xs.Model(\n", + " {\n", + " \n", + " 'f_light':FracInterceptedLight,\n", + " 'initial':InitialBiomass,\n", + " 'leaf_area':LeafAreaAnnual,\n", + " 'growth':LightLimitedPlantGrowth,\n", + " 'death':BiomassDeath,\n", + " 'biomass':Biomass,\n", + " }\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "fresh-helmet", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[('biomass', 'dB')] [('biomass', 'dB')] dB prev_dB\n", + "[('biomass', 'B')] [('biomass', 'B')] B biomass\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.visualize()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "large-correction", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.visualize(show_variables=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "acoustic-circulation", + "metadata": {}, + "outputs": [], + "source": [ + "ds_in = xs.create_setup(model=model,clocks={'clock':range(100)},output_vars={'biomass__B':'clock'})" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "controlling-breakfast", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#plot to verify that it works\n", + "ds_in.xsimlab.run(model).biomass__B.plot()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.1" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/xsimlab/dot.py b/xsimlab/dot.py index 409494b0..c71ca04a 100644 --- a/xsimlab/dot.py +++ b/xsimlab/dot.py @@ -43,6 +43,7 @@ INPUT_EDGE_ATTRS = {"arrowhead": "none", "color": "#b49434"} VAR_NODE_ATTRS = {"shape": "box", "color": "#555555", "fontcolor": "#555555"} VAR_EDGE_ATTRS = {"arrowhead": "none", "color": "#555555"} +INOUT_EDGE_ATTRS = {"color": "#000000", "style": "dashed"} def _hash_variable(var): @@ -98,12 +99,41 @@ def _add_var(self, var, p_name): if var_intent == VarIntent.OUT: edge_attrs.update({"arrowhead": "empty"}) edge_ends = p_name, var_key + elif var_intent == VarIntent.INOUT: + edge_attrs.update({"arrowhead": "empty"}) + edge_ends = p_name, var_key else: edge_ends = var_key, p_name self.g.node(var_key, label=var.name, **node_attrs) self.g.edge(*edge_ends, weight="200", **edge_attrs) + def add_inout_arrows(self): + for p_name, p_obj in self.model._processes.items(): + p_cls = type(p_obj) + + for var_name, var in variables_dict(p_cls).items(): + # test if the variable is inout + if var.metadata["intent"] == VarIntent.INOUT: + target_keys = _get_target_keys(p_obj, var_name) + + # now again cycle through all processes to see if there is a variable with the same reference + for p2_name, p2_obj in self.model._processes.items(): + p2_cls = type(p2_obj) + + for var2_name, var2 in variables_dict(p2_cls).items(): + # if the variable is + target2_keys = _get_target_keys(p2_obj, var2_name) + if ( + len(set(target_keys) & set(target2_keys)) + and var2.metadata["intent"] == VarIntent.IN + ): + edge_ends = p_name, p2_name + print(target_keys, target2_keys, var_name, var2_name) + self.g.edge( + *edge_ends, weight="200", **INOUT_EDGE_ATTRS + ) + def add_inputs(self): for p_name, var_name in self.model._input_vars: p_cls = type(self.model[p_name]) @@ -146,6 +176,7 @@ def to_graphviz( show_only_variable=None, show_inputs=False, show_variables=False, + show_inout_arrows=True, graph_attr={}, **kwargs, ): @@ -167,6 +198,9 @@ def to_graphviz( elif show_inputs: builder.add_inputs() + elif show_inout_arrows: + builder.add_inout_arrows() + return builder.get_graph() @@ -211,6 +245,7 @@ def dot_graph( show_only_variable=None, show_inputs=False, show_variables=False, + show_inout_arrows=True, **kwargs, ): """ @@ -236,6 +271,8 @@ def dot_graph( show_variables : bool, optional If True, show also the other variables (default: False). Ignored if `show_only_variable` is not None. + show_inout_arrows : bool, optional + if True, show references to inout variables as dotted lines. (default: True) **kwargs Additional keyword arguments to forward to `to_graphviz`. @@ -262,6 +299,7 @@ def dot_graph( show_only_variable=show_only_variable, show_inputs=show_inputs, show_variables=show_variables, + show_inout_arrows=show_inout_arrows, **kwargs, ) From 6389f2f97bc5ecff7cd3680341ac6472a589b338 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Sat, 20 Mar 2021 21:42:02 +0100 Subject: [PATCH 3/9] working! moved as_variable_key to utils --- notebooks/cyclic.ipynb | 165 +++++++++++++++++++++++++++++------------ xsimlab/dot.py | 6 +- xsimlab/model.py | 38 ++++++++-- xsimlab/utils.py | 27 +++++++ xsimlab/variable.py | 2 - xsimlab/xr_accessor.py | 29 +------- 6 files changed, 181 insertions(+), 86 deletions(-) diff --git a/notebooks/cyclic.ipynb b/notebooks/cyclic.ipynb index e266c978..bbb5a4cb 100644 --- a/notebooks/cyclic.ipynb +++ b/notebooks/cyclic.ipynb @@ -8,12 +8,34 @@ "outputs": [], "source": [ "import xsimlab as xs\n", - "import math" + "import math\n" ] }, { "cell_type": "code", "execution_count": 2, + "id": "thermal-measure", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "10" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "a,b = (10,20)\n", + "a" + ] + }, + { + "cell_type": "code", + "execution_count": 3, "id": "cloudy-viking", "metadata": {}, "outputs": [], @@ -23,11 +45,16 @@ " B_vars = xs.group('biomass')\n", " dB = xs.variable(intent='inout',default=0)\n", " B = xs.variable(intent='inout',default=1)\n", + " out_B = xs.variable(intent='out')\n", " \n", " #we can actually safely use run_step because of the cycle ordering?\n", - " def run_step(self):\n", + " @xs.runtime(args='step')\n", + " def run_step(self, n):\n", + "# print(\"Biomass calculating: \")\n", " self.dB = sum(self.B_vars)\n", " self.B += self.dB\n", + " self.out_B = self.B\n", + " print(\"Step: \", n,\" out_B: \", self.out_B)\n", "\n", "#jsut some processes to have a longer cycle\n", "@xs.process\n", @@ -37,6 +64,7 @@ " ext_coeff = xs.variable(default=0.8)\n", " \n", " def run_step(self):\n", + "# print(\"Frac light calculating: \")\n", " self.intercepted_light = 1-math.exp(-self.ext_coeff*self.leaf_area)\n", "\n", "@xs.process\n", @@ -52,20 +80,32 @@ " \n", " @xs.runtime(args='step_delta')\n", " def run_step(self,dt):\n", + "# print(\"leaf area calculating\")\n", " self.leaf_area += self.pl*self.prev_dB*dt\n", "\n", + "#the process maxrad also adds to growth\n", + "@xs.process\n", + "class MaxExtraTerrestrialRadiation:\n", + " maxrad = xs.variable(intent='out')\n", + " \n", + " @xs.runtime(args='step')\n", + " def run_step(self,n):\n", + " self.maxrad = 1+sin(n/math.pi)\n", + " \n", + " \n", "#this process actually adds some to 'biomass' group\n", "@xs.process\n", "class LightLimitedPlantGrowth:\n", " frac_light = xs.foreign(FracInterceptedLight,\"intercepted_light\")\n", + " maxrad = xs.foreign(MaxExtraTerrestrialRadiation,'maxrad')\n", " \n", " light_efficiency = xs.variable(default=3)\n", " biomass_growth = xs.variable(intent='out',groups='biomass')\n", " \n", " @xs.runtime(args='step_delta')\n", " def run_step(self,dt):\n", - " #wrongfully assuming \n", - " self.biomass_growth = self.light_efficiency*self.frac_light\n", + "# print(\"growth calcuating\")\n", + " self.biomass_growth = self.light_efficiency*self.frac_light*self.maxrad\n", " \n", "@xs.process\n", "class InitialBiomass:\n", @@ -74,7 +114,14 @@ " \n", " def initialize(self):\n", " self.biomass = self.initial\n", + "\n", + "@xs.process\n", + "class HalveFLight:\n", + " f_light = xs.foreign(FracInterceptedLight,'intercepted_light',intent='inout')\n", " \n", + " def run_step(self):\n", + " self.f_light = self.f_light/2\n", + " \n", "@xs.process\n", "class BiomassDeath:\n", " biomass = xs.foreign(Biomass,\"B\")\n", @@ -83,123 +130,145 @@ " \n", " @xs.runtime(args='step_delta')\n", " def run_step(self,dt):\n", - " self.biomass_death = -self.biomass*self.death_rate*dt" + "# print(\"death calcualting\")\n", + " self.biomass_death = -self.biomass*self.death_rate*dt\n", + " \n", + "@xs.process\n", + "class OtherClass:\n", + " biomass = xs.foreign(Biomass,\"out_B\", intent='in')\n", + " somevar = xs.variable(intent='out')\n", + " \n", + " def initialize(self):\n", + " self.somevar = 1\n", + " \n", + " def run_step(self):\n", + " print('otherclass: ', self.biomass)\n", + " self.somevar += self.biomass" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "positive-physiology", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "_dep_processes: {'halve_f_light': {'f_light'}, 'f_light': {'leaf_area'}, 'maxrad': set(), 'leaf_area': set(), 'growth': {'maxrad', 'halve_f_light'}, 'death': set(), 'biomass': {'growth', 'death'}, 'otherclass': {'biomass'}}\n", + "_dep_processes dict: {'halve_f_light': ['f_light'], 'f_light': ['leaf_area'], 'maxrad': [], 'leaf_area': [], 'growth': ['maxrad', 'halve_f_light'], 'death': [], 'biomass': ['growth', 'death'], 'otherclass': ['biomass']}\n" + ] + } + ], "source": [ "model = xs.Model(\n", " {\n", - " \n", + " 'halve_f_light':HalveFLight,\n", " 'f_light':FracInterceptedLight,\n", - " 'initial':InitialBiomass,\n", + "# 'initial':InitialBiomass,\n", + " 'maxrad':MaxExtraTerrestrialRadiation,\n", " 'leaf_area':LeafAreaAnnual,\n", " 'growth':LightLimitedPlantGrowth,\n", " 'death':BiomassDeath,\n", " 'biomass':Biomass,\n", - " }\n", + " 'otherclass':OtherClass\n", + " },custom_dependencies = {'growth__frac_light':'halve_f_light'}\n", ")" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "fresh-helmet", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[('biomass', 'dB')] [('biomass', 'dB')] dB prev_dB\n", - "[('biomass', 'B')] [('biomass', 'B')] B biomass\n" - ] - }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.visualize()" + "model.visualize()\n", + "# model.growth.variables()" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "large-correction", "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAA9UAAAJMCAIAAAB7NhJ3AAAABmJLR0QA/wD/AP+gvaeTAAAgAElEQVR4nOzdd3hUVfoH8DO9JTPpbdJ7T4AkJHQFFLEviK4goAhBlCJiRYq6sSGiK9gQxMZi4ScgRaQGEiAFAum9t0mbkkwv9/fHYJaFJEBIMinfz8Pjwz33zrlvwjjzzplz3kOjKIoAAAAAAMCAoFs6AAAAAACAEQT5NwAAAADAwEH+DQAAAAAwcJiWDgAAhrD09HSj0UgI8fPzc3JyuvGCsrKypqamG9uH+vWEkLi4OAaD0eUpAACAHiD/BoDe27Ztm1qtJoQkJiZOnTr1xguOHTt28uTJG9uH+vWEkF27dvH5/C5PAQAA9ICG+icA0GsLFiyYP39+l5nrMHblypWkpCTk3wAA0DuY/w0AAAAAMHCQfwMAAAAADBzk3wAAAAAAAwf5NwD0XlxcnLOzs6WjGGg2Njbx8fEofgIAAL2D9ZcAAAAAAAMH498AAAAAAAMH+TcAAAAAwMBB/g0AAAAAMHCQfwMAAAAADBzk3wAAAAAAAwf5NwAAAADAwEH+DQC9l56e3tTUZOkoBppcLj9//rzRaLR0IAAAMCQh/waA3tu2bVtOTo6loxholZWVW7Zs0Wq1lg4EAACGJOTfANDv1Gq1pUMAAAAYLJB/A0A/Onr06Pr169euXdvl2YyMjOeee66urm6AowIAALAg5N8A0I+mTZumUqkoiuryLIfDEQqFLBZrgKMCAACwIKalAwCA4YzBYNjZ2TU3N3d5NjIyMjIycoBDAgAAsCyMfwMAAAAADByMfwPAQCgrK9uzZ09paam/v/+zzz7r7OysVCrT0tJSU1NnzJgRGxtrviwtLS03N5fNZtfU1Pj6+s6aNYvFYtXU1KSkpFy4cGHdunUnTpxITk7mcrmLFi0KDAzcvXt3ZmamwWBITEyMjo42dyKXy/fs2ePg4NDS0qJQKJYuXWptbU0IqaysPHz4sFgsLioq0mq169at664RAACg/2D8GwB6Ly4uztnZ+aaXKRSKM2fO3H///bNmzcrLy1u/fr1Wq5XJZDU1NTk5OSaTyXzZoUOHDh48uHDhwqeeemr58uXnz59PSkqiKEokErW2tjY0NPz2229xcXGbN2+2srL68ssvv//++2nTpm3atMnFxWXHjh2dt/vkk0/UavWsWbMSExObmpp27drV2T516tSHH3549erVbDa7h8ae2djYxMfHMxiM2/pdAQAAmCH/BoDee/7558PDw296GZPJfPrpp6Ojox944IE5c+ZIpdKTJ0+KxeLOYW/y96D19OnTzXmttbX1o48+mp+fn5KSIhQKAwICCCEzZ8708fHh8Xhjx46VSCRTp04Vi8VcLjcmJkYikSgUis7evLy8zH/x9PSsrq4mhBiNxoaGhvLycnM8M2bM6K7xpry8vFavXs3hcG759wQAAPBfyL8BoN/x+fzOv0+ePJkQYk55rx1CLikp0Wq1Dg4OnS1jxowhhOTm5hJC6HQ6IYRGo5lPcbncax9uPmxvbzcfbtiw4dFHH9VqtceOHSstLTVvlMNgMCIjI3ft2vXVV191dHRERUV11wgAANCvkH8DwICytbVls9k6ne66dnONlI6Ojs4Wa2trDocjlUpv7KQzEb/2sHMei8lk+v3333fs2BEUFOTv79952apVq6Kiok6cOLFy5cq8vLweGgEAAPoP8m8AGGg0Gs3Dw+O6RicnJ0KIRCK5rl0sFt9W5xRFvffee7W1tcuWLfP09Lz2FIfDeeONN5YvX85gMJKSksz7/nTZCAAA0H+QfwPAgGpubjYYDAkJCde1BwYG8ni8jIyMzpbW1latVhsTE3Nb/ZeWll65ciUsLMx8aDQazbv/6PX648ePE0ImTpxoXtaZm5vbZeOd/HQAAAA3hfwbAPoXnU5XqVRGo5EQQlHUb7/99thjj5lHtc2zUPR6PSHE2tp63rx5RUVFOTk55gceOXJk8uTJ5kza/PDOGSbmQ/MDOw8NBkPnTZOTk6urq0+dOlVTUyOXy6uqquRy+alTp8w92NnZ8fl8X19fQkiXjQAAAP2HsXHjRkvHAADDmaenZ2tr66lTpwoKCnJzcyMjI6dPn04IKSkp2bdvX2Njo0KhcHNzc3Bw8PPz8/HxOXz4cFlZWXFxsbW19dy5c2k0WklJyYEDB9ra2jQajbe3d2Nj44EDB1pbW1UqlaenZ3Nz8/79+82D5d7e3p6enjKZLDs7u6SkJC4uLjw8/OLFiy0tLWPHjk1JSUlPT5dKpWfPnp0yZUpMTIzJZDp9+vR1jZb+hQEAwDBHM38zCwDQC+np6d7e3uap2yOHXC7Pz8+Pi4tDCXAAAOgFzD8BgN7btm1b53SRkaOysnLLli3msoYAAAC3C/k3AAAAAMDAQf4NAAAAADBwkH8DAPTGjVsIAQAA3AqmpQMAABiSnn/++YCAgLCwsLCwsICAABaLZemIAABgaED+DQDQGwsXLiwuLj59+vSvv/7KYrECAwPDwsLGjRvn5uZm6dAAAGBQQ/4NANAb48ePNxcyl0qlhYWFOTk5p06dcnNzQ/4NAAA9Q/4NAL0XFxfn7Oxs6SgGmo2NTXx8fGfxb1tb24SEhISEBEJIdzsqNDQ0ODk5oV44AAAQ7L8DANDfKIpasmSJRqMJDAwMDg4ODg4OCQlhMjH8AQAwQiH/BgDod/X19Xl5efn5+Xl5eTKZjMvlhoSEhIaGPvTQQzQazdLRAQDAgEL+DQAwoOrq6vLy8vLy8hQKxYYNGywdDgAADDTk3wAAg4tcLm9tbfX29qbTsUUDAMAwhAmIAACDS3p6+vbt2wUCQXBwcHh4eGhoqLe3N6apAAAMGxj/BgAYXCiKqq6uzs/Pz83NLSgo6OjoEAgEoaGhM2fODAsLs3R0AABwp5B/AwAMXhRFVVVVmeeLT5s2bfTo0ZaOCAAA7hTybwDovfT0dG9vbycnJ0sHMqDkcnl+fn5cXNwgqeedlZXl4ODg7u6OOSoAAEMC5n8DQO9t27Zt/vz5U6dOtXQgA6qysnLLli27du3i8/mWjoUQQnbu3CmRSEQiUWhoaGhoaFhYmLu7u6WDsqSmVk1Ds1qq0Da3aaUKrVJtUGuMFEV1qAyEED6PyaDTOGyGFZ9pI2Q72HLsbTjO9jwXBx4+v/STY8eO5eTkWDoKIISQe+65Jzw83NJRAPJvALgz5eXl16ah3Y0Kp6enG43GG9uH4vWVlZU3XmBBn376aUVFhXmOyu7du9VqtUgkCg8PX758+UiooKLTmwrL5Tkl0sIyeWWdsqpeqdYazKesBSxrKw6Py2AxGYQQHodJCKlv1pooYtCbNFqDQqlrV+rMXwOz2QxPV4G3WBDkI4oMtAnxs+FxBsX3G8NAaWlpQUFBSEiIpQMZ6TIyMqKiopB/DwbIvwHgjhw7duzYsWOdh9999x2Px7vxsm3btqnV6hvbh/r1gwGdTvfz8/Pz83vooYeMRmN5eXl+fn5zc/MwTr5NFFVUrkjNajqX1VxUIdfpTUIrloeb0M1VNCrM1cmB72DLsxKwGfSbD2hTFNXeoW+TayQtHZJWtaRFmZlTsa1dy2DQAryE8VGO40c7Rgba0m+hK+iBt7f36tWrLR3FSLdgwQJLhwBXYf43AMAI0tTUlJOTExYW5uLiYulYbhtFkZxi6aHk2lNpjVKFzk7EDfKzC/C08XIXOtr15VwgqUJTUSOvqJEXlLU1taqs+axJsc73TxaPCbenY5LK7fviiy/a2trWrl1r6UBGugULFozAGYODE8a/AQBGkIqKil27dmm1Wjs7u7C/OTs7Wzqum5C36/7vWPWBk7W1EqXY2WpCrEeov73Y2aqfbmcr5NqGcUeHORNCmtpUecWtl/Mlh5Jrnex4D0wRz57h5WjL7adbA8BIgPwbAGAEGTt27JgxY0pLS83zxXfu3KnT6ezt7Z988smJEydaOrou1EpUP/1R/sepWiaDHhvp8uTDYe4u/ZV2d8nJju8Uz78r3kPSoszIluw9Vv3DgfJ7J7jNfdDX39N6ICMBgGED+TcAwMjCZDKDg4ODg4NnzZql1+tLS0tzc3MHYRFJebvuhwPluw9ViKw49070Hh/jbtkFkc4Oggfu9p0x2ftSnuTk+ZpDyWemxrsunxfs5jQoyuAAwBCC/BsAYORisVghISE9FKY4cuSIQCAICwuzt7cfsKiMRmr3oYpvfi1hsxizZwTGR7sOntLmTAY9LtI1NsL1ckHToZPls1cmz3vI99nZAWzWsF3tCgB9Dvk3AAB0Kzs7+8qVKwaDwdnZuXO+uJ2dXf/dsbymfeO27NIqxfQJXncleHJYg7EIII1GRoU6RQQ5pF6s23Oo4uSFxg3PR0YE2lo6LgAYGpB/AwBAt1599VWtVltcXGyeL56cnGw0GsVi8aZNm5jMvn8H2ftX1eZd+e4uVi8viXVxEPR5/32LyaBPjvOIDHL8+VDhs+vOL34sYNGsgEEzUg8AgxfybwAA6AmHw4mIiIiIiCCEaLXaoqKiurq6Pk++9QbTph15+05Uz5jkM2OS9+CZcHJTtiJu4j+jz2bWfvNrSXGlYuMLUXwu3lsBoCd4jQAAgFvF4XAiIyMjIyO7PFtTU3P06NGwsLDQ0FCRSHTr3Wp1xpc+uHilSPrsnMiIIIc+Cnbg0GhkUqy7m5Pg299yl25M27YuzlrAsnRQADB4If8GAIC+0dHRUV5efvz4cZPJ5O7ubp4sHhoaKhQKe3iUVmd88f3M/DL58vmjPFyHcEU/fy/bF5+J2fp91rK307atHytECg4A3UD+DQAAfSMkJOTdd99Vq9UFBQV5eXn5+fnHjh2jKOrJJ598+OGHu3wIRZG1n1wuKJO/MG+UeGALe/cHB1ve8vmjPvsha/V7mV9sHMtioigKAHQB+TcAAPQlHo83evTo0aNHE0JUKlVBQUEP+2vu2FuSclHywlPDIfk2s7flLZsb/fGOzI+/zX91cbilwwGAwQgfzQEAoL/w+fwxY8a4u7t3eXbTx19+80vBrBmBfl42AxxYv3Ky5//zwZC9x6qOn2uwdCwAMBgh/wYAAAswGKnMQl1wgNOEGPGd96ZRq++8kz7sKirEMWGU6+Zv81Vqw533NnKo++7fcRDSaDSDsCuwCOTfAABgAb8draxpD5h1b+Ad9vPX0b/WrVv33LJldx7S6dOn16/fsGRp4p13RQh58G5/jc64Y29pn/Q27B09enT9+vVr167t8mxGRsZzzz1XV1c3wFH1lRMnTrzzzjsvvvjinXd19uzZpKSklStX3nlXYEHIvwEAYKCZTNRPf1SMHyN2sOXdYVfTpk/T63RGo7HXPUjbpOa/TJo0yWDQmwy97+paAj5r6nivvX9VqTQYAr+5adOmqVQqiqK6PMvhcIRCIYs1VEvK3HXXXXq9/o6epdKrz9Lx48cbDAaDAU+qoQ35NwAADLSzF5uaWjUTY/tg5gmdTrez733J8I6Ojo82b+7syt6hL6uPJ0S76Y3U4eShOmrbM7lcfvr0aZVK1Se9MRgMOzu77s5GRkZ+8MEHTk5OfXKvgUen0+3t7Xv9cKVS+dlnn3V21cMvCoYK5N8AADDQTlxo8Pe2cbTjWzYMvcHw0aZNksbGfuqfz2NGBTsePz88V2F2dHR8/vnnixcv3rx5c1paml6vt3REw5PBYPj0008lEomlA4G+hPqDAAAw0DJyWhNGud1JD2lpaekZ6dZW1lqtVipt62ynKOrPP/+sqKgoKy0TWAmWLl3q5uZGCJHJZD/8+IOjg2NLc7NcoVi+fIVQaJ2aklJdXd2uVG797DOxWPzoP/5h7kQqlW7bti0vL8/JyWnNmjUeHh69jjPQx/aXw0VanZHDZtzJzztoPfjggyUlJVu2bOFwOHFxcRMmTIiIiKDTez+6V1ZWtmfPntLSUn9//2effdbZ2VmpVKalpaWmps6YMSM2NtZ8WVpaWm5uLpvNrqmp8fX1nTVrFovFqqmpSUlJuXDhwrp1606cOJGcnMzlchctWhQYGLh79+7MzEyDwZCYmBgdHW3uRC6X79mzx8HBoaWlRaFQLF261NramhBSWVl5+PBhsVhcVFSk1WrXrVvXXWPPMjIyLl26ZGVlpdVqOyeQEEIoijp+/HhlZWVFRQWfz1+0aJGrq2t38Zw/f76mpkapVH711Vdubm4PPviguROZTLZ9+/b8/HwnJ6cVK1aIxX3wbRIMGIx/AwDAgGpsUbdINX6etr3uITk5+ddffl26JHHhwoVP/POf1dXVnaf27t3L5rCXLVu26aNNKpXqtdde02q1hJAPP/xQo1I/8cQTLyxf3iiRbP9mOyFkypQp3r4+ImvhC8uXdybfWp1u7297n3564XvvvS+RSL7d9e2d/LAB3rZ6vam4UnEnnQxmCQkJ69at2759+1NPPdXY2Pjuu+8+++yzW7duzcnJ6W4ydw8UCsWZM2fuv//+WbNm5eXlrV+/XqvVymSympqanJwck8lkvuzQoUMHDx5cuHDhU089tXz58vPnzyclJVEUJRKJWltbGxoafvvtt7i4uM2bN1tZWX355Zfff//9tGnTNm3a5OLismPHjs7bffLJJ2q1etasWYmJiU1NTbt27epsnzp16sMPP7x69Wo2m91DYw9SUlL27dv3zDPPzJ0797HHHqutre08tX//fjabvXjx4n/9619qtXrDhg3mZ2mX8UycONHb29va2joxMbEz+dbpdPv37587d+5bb73V1NT0448/3u6vGiwL+TcAAAyo5jYtIcTOhtu7h2u12h07dzz08IMsNpsQIhIKw8PDzKfa2tr2799/15S7CSF0On3C+PFSqTQtPZ0QQmg0bx8f82XeXl5VFRXd9c+g059+5mmx2N3b2ysqKqq09I4KmNgKOXQazfwjD2PW1tbTpk175513tm3bNnv27JqamnfeeWfZsmXffvttYWHhrffDZDKffvrp6OjoBx54YM6cOVKp9OTJk2KxuHPYm/w9SDx9+nQGg2G+9aOPPpqfn5+SkiIUCgMCAgghM2fO9PHx4fF4Y8eOlUgkU6dOFYvFXC43JiZGIpEoFP/9OOTl5WX+i6enp/mDnNFobGhoKC8vN8czY8aM7hp7oNVqf/jhh5kzZ5rXjFpbW4eEhJhPSaXSQ4cOTZo0iRBCp9Pj4+NlMtnFixe7i6dLDAZj3rx5bm5unp6e4eHh5sBgCMH8EwAAGFAyhZYQYsXvZS2LvPx8aZvUy8uns4XBuNpVQUGB0Wj4fNvWzlP33nMPh80mhLyblEQI0Wg0p0+fLikuMZFuh2aZTKY5sSOEWFlZdXQoexenGY1G4/OZh/fvvHL+Tiu9DDZd1up2cHCYOXPmzJkzq6qqUlJSUlNTjxw5IhAIhEJhU1PTTRdQ8vn/XRIwefLk3bt3mzPLzn8RQkhJSYlWq3W4ZqXsmDFjCCG5ubkTJ040T32h0WjmU1wu99qHmw/b29uFQiEhZMOGDYQQrVZ75syZ0tJS84A9g8GIjIzctWtXdXX13Llzo6KiumvsQWFhoVQq9fT07GxhMq9mXEVFRUaj8euvv+48NXXqVPOAepfxdInBYHT+UAKBoKOjo+d4YLBB/g0AN6dVtbXVX7J0FEOAyCmUL7yjac0jAo1GCDHd/uQEs9qaGkIIk9XFdOqamhouh/vC8uU3njKZTL/t/a2hruHhRx4JCMovKiq6pUh7F+L/6u0POtLZ2tqy2WydTndde3NzMyHk2ozT2tqaw+FcO8G6U2cifu1h5zwWk8m0f//+hoaGBx54oLCwsKSkxNy+atWqTz/99MSJE+np6atXrw4LC+uusTvmUuWdOfd1pzgcTmJiF2Xmu4unZ9f9jDAkIP8GgJtTtBRdOvq6paMYAiLvWssPfcTSUQx2tkI2IUSp0rNFvVmSyGSxCCFNkiax2/ULzrgcTktra0tLy7WDo3KFwtrKeuPGt0Q2opdWr76DwHvDZKLUasP9jzxz11iXAb51f6urq7t8+fJ1jS0tLenp6cnJyRUVFfb29nFxcQkJCadOnWpra+tF9UAajXbj4ldzPzfWA7ndBYgURb333ntCoXD5DR/YOBzOG2+8cfbs2R9++CEpKWnTpk1isbjLxu46N2fezc3N5oWV12Kz2W1tba2trddWJGxvb7eysuouHhh+kH8DwK2acP+rDGYv5+yOBKmH3rd0CEODgy2HENKm0NiKevN08vbyJoSkpKSMGjXq7zaTeWcTL28viqJ27dq1Zs0a8wm5XH7ixImwsLCsrEudaY3JYOj8Zp9OoxuM/biViVShMVGU+Ucextrb29PS0pKTk4uLiwUCwejRo+fNmxceHm4emj116lQv+mxubjYYDAkJCde1BwYG8ni8jIyMzsWIra2tWq02JibmtvovLS29cuXK0qVLzYdGo9H8rNDr9SdOnJgxY8bEiRODg4NXrFiRm5vr5OR0Y2MP+bd5Gve5c+ciIyPNLSaTyTzu7unpSVHUTz/9tGLFCvMpuVyenJwcEhLSZTyEEBqNdid798AghPwbAAAGlIsDz9GOW1Yl8/Ow6cXDQ0NDIiIjjx8/7ufvP/Xuu6urqvPy8hUKxZkzyXFxYwMCA5KTk/V6XfzY+IbGxoKCgjUvv9zY2EAIOXHyZGBgUElJcVV1lUwmq6istLWxsbOzk0qlFeUVHcqOwMBAg16vvaaOtVanMxoMFEX1+iv+0ioZi0UP8hH17uGD3/nz57///vu8vDxz/cHZs2f3uv4gnU5XqVRGo5HBYFAU9dtvvz322GPmHNc8C8VcYtza2nrevHnffPNNTk5OREQEIeTIkSOTJ082Twgx56mdM0zMh521yc2H124emZyc7O/vX1ZWVlNTI5fLq6qqBALBqVOn7rnnHvNON3w+39fXlxDSZWN3goKCwsLCTp8+7evrO3ny5Nra2sLCQoVCkZqaGhMT4+fnl5KSotfrY2NjGxsbi4qKVq1a1djY2GU8NjY2tra2MpmssrJSqVT6+/sbDIZrq63rdDpzso6JKEMIY+PGjZaOAQAGO5W8tq74iGfgBDodH9q7VVOS4ug1TuQYbOlABi+jQaOUVsokOUZ5RnaVfWxUL+fKJyQkyGSyo0ePHjlyhMvl2tnb+Xj7BgcHu7mJx4+f0Nramp2dc+nSJZFItHTpUlsbGwd7B5lMdjnrclFR4bhx4yKjojLT05ubmydMmODi6pqRnn7hwoXg4GCJRPLHH38olUo6ne7n55uZmbl//36NRkMICQ4JYfQqpzx5vsbZjv3w1N5XEB+02tvbjx49Wlpa6unp+fjjjycmJsbHx7u4uNyYBWZmZqrVanPFjx54enq2traeOnWqoKAgNzc3MjJy+vTphJCSkpJ9+/Y1NjYqFAo3NzcHBwc/Pz8fH5/Dhw+XlZUVFxdbW1vPnTuXRqOVlJQcOHCgra1No9F4e3s3NjYeOHCgtbVVpVJ5eno2Nzfv37/fPFju7e3t6ekpk8mys7NLSkri4uLCw8MvXrzY0tIyduzYlJSU9PR0qVR69uzZKVOmxMTEmEym06dPX9fY848zduxYmUx24sSJY8eOcblcW1tbLy+vgIAAV1fX+Pj4tra2vLy8K1euCIXCRYsWiUQie3v7LuMZN26cs7PzxYsXMzIyAgMDm5ubjxw5Yn6W+vj4ZGVlHT582PwsDQoK6vmTz759+6Kionr+5AADg9aL8pwAMNI0V59P/2MF5p/0LPXQ+6ET13hg/jchhBCdRqaS16rktUpFrUpep5LXKuW1WlWL+Sydbf/RmYUrn51u8S0w+5VSpd/w6bkXF4bMvsfL0rH0PblcnpWVFRcXd23Rki598cUXbW1ta9euHZjAoDsLFiyYP3/+1KlTLR0IYP4JAADcGb1WoVLUqeR17W3lHdIKlbxOKa8x6DoIITQ6k2flzBeJrex8nLwn8IVivkgssPGiM3hfZJ0+k1E7695AS4ffj85n1bNZ9JmThufGhCKRaMqUKZaOwpIWLVrU3ally5aZqyICdAn5NwAA3BKTUa9RNqnkdSrF33/kdR3SCqNBQwihM9hcgSNfJBY5BYuDZlrb+fJFYp6VC43edZGTuQ/6fPp9waRY9+E6BN6h1p84X/3YPZ58Lt5qh6drt9IEuC14UQAAgOt1Dmlfm2qr2xsoykQIYXGE5pFsB484z7BHzX/nC91uq1727Hu8fj9WvffP4qVPRvfbz2FJB0+U8jiMp//hb+lAAGDQQf4NADCiXZdqt7eVd7SV67XthBAancGzcuGLxHyh2ME97ursEZEnky248/syGLRXF4cv3XDhTEbtpFj3O+9wULlS0Hw+q+G91aP5PLzPAsD18LoAADAidD17RFZp1KvJNbNHrO18nb0n8oViKztfKxuv7maP9IlRIXaJTwR+9Uuxm5PA38u2/240wCQtyt0HCh6713tq/PV7rwAAEOTfAADDzwDMHukrTz/qX1Am3/Fr7rK50R6u1gMfQJ9rblN9/tPlIF/hiwtDLR0LAAxSyL8BAIawLlNtlaLOfJbDd7C29+2P2SN9hUYj/1oZ/dIHFz//6fJzc6M9h3gK3tym2vpDlosD7+NXY5gMbIYCAF1D/g0AMARQJoO6Q3Jdnq2UVRn0KnLN7JFrU20rW18Gcwhse85hMz5+LealDzK3fpc19+GQqBBHS0fUSyUV0m/35nq6Craui7MWsCwdDgAMXsi/AQAGF5NRp1E2m9dB3uLsEZ61K43Wm90ZBwk2i77l9djNO/N2/pZz70SfGZO8W2Tq6vp2jcYwIWYIFM+mKHImo+b3v0oZdNrEGCcupx8nzQPAMID8GwDAYrqZPVJPCEWuSbXFQVHmctoCkQeTbWXpqPtFq0wTF+lQ36Q6erbyr5RKk4nic5mrn73JFt+DQZtMs+dQYXGF1MNFUFXf8dXPxUfO1L24MHTCaCdLhwYAgxTybwDoR2q1lsfrmykQfdjVwLvZ7BEWV+B0w+wRHwaTa+nA+5FUocsvlYt4m9MAACAASURBVOWXyfPLZPml8ja5tvMURRFCSHigg8h6UP+LG4ymlMy6w6crXBy4299JyMhp/e73UrXWWN2gfPG9jEkxzqsWhHi4DKLZ9gAwSCD/BoB+ceDQyROn06qq6/f9/NkddnX0eOqff50pK6898Nu2PomtX5lnj5hT7fa28g5puUpep+5opExGMkxnj9yiDpWhoFxeUCbLL5Xnl8kamtU9XHzXWJe0Ky1FFW33TfaNj3al0wfXWkaKIln5koOnyhXtunkP+iyaHcBm0SMDbR+6233rj4VHztZRFDmTKTmX1TT7Xq+lTwQJUAUcAK6BVwQA6BcPzJhy+OhZo9HY6x5a2qQOdraEkOl3Jfxx+JTeaOi76Hq63Z0oSvsy+1QSIYRGo3OtnPhCd77I3cE9li9054vEfKE7izO063v0TlOr5vl30qrrlSbzyPbNzL7X69VnwxUd+u/3l+0+VHwspXL8GPH4MWLeINjI3WA0XcqTnDxX09isvDveZfm8YDcnfudZR1vuW8ujH7/P+6Nv83OKpQYjtedw5Z9n6xfN9p8zw3uwfYoAAEux/GsZAAxLdAbdydG+rl7Su4e3tyvfSvr8s81r/+7Krqyipk8D7PZ2d8LZe5Kz72S+UMwXutEZ7D6JbRhwsueG+Ikq6zp6uIb6u/x4XKTDmqfDCCFCK9YLc4P/Md1z98GK/Scqj5+rjo10jotw9XCzzGeYxmZlRnZj2pUGtdZw30Tx3AdG+3p0HUmov803/0o4eKp22+6iNrlW1q7b/G3+kbP1a54Oiwi0GeCwAWAQQv4NAIOO3mDYkLS117m7BW9n4xzq5DX+zvsZflY+FXImQ6JUd/slhjn59nQVvLd6NOOaytluTvw1z4QtmRP4f8er/zhZk5xW6+okGB3mHBbgIHa2ovX/gHJjizK/uDUrX1JV3+5sz5szw2v2vV72NjeZmE6n0R6622P6eLcf9pd9t69Mpzfll8oWvZn6yFTPlfNDMB0FYITDSwAA9KWzqRdTL2RZWwu0Gm1rm7SznaKofX+cKC2vLiyusBbw1qx8xt3dhRDSJpV/vfNXZye7RkmrXN7++stLREKrk6fTKiprFe0d73203dPTbe6c+82dtLbJPtyy43J2oauL48a1z3t79lSZrrVN9tfJc4ePnNmy6dV/vfdFdW3Dt1+9ZzQab+V23UULvWZvw1kyJ3DLd/k9XCPgMTe9PEbYVeVsoRVr4SN+Cx/xyy2RHT5Te/JC3aFT5TZCTqifna+Xjbe7yMmOf+Ojeq1NrqmslZdVywrL2prb1CIr9uQ459eXhI0KtaPfTsrP4zCWzAm8b5L4891Fx883UBT5/Xj12YuSNc+EYWt6gJEM+TcA9Jm/Tpz75f/+3LblTQ6bLZe3//Pplxn0q8sKf/zPH/b2Ni+vesZkNCWu3Pjcqrd//fETLpe9/p3P7GxETz/1D0LIgsWvf7rt+/WvL7t32vjjp86Vlde8vmZxZ+dare7HPX88v+RJvUH/3Mq3t321e1PSyz0EU1JadeDgyZq6xv1/nJx297jf/zih1+s3Jm27ldt1F21//eJGhsfv8/75z8p6iarLs3Q6LWnVqO5mdHQKD7AJD7B5+Znwogp5albzuaymXw4V6fQmKz7L083a2UHgZC9wsuc52vGtBCwm4+arWo0mqkOla23TSFqVTS0qSYuyprFd3q5jMmgB3qIHp4gnjHEK87e5k6nbHi6C91aPvi9T8sE3uU2tmhap9rXNl+6Od3n5mXAH20Fd4AUA+gnybwDoGxqNbusXPy1fNo/DZhNCRCLr6IjgnLxiQkhLq/TnvUcO/Po5IYTOoN81eezWL35KuXBx2pQEGo3m7+9p7sHXx720rLq7/hkMxguJTzIYDEJIzOjw3NySnuOJj4s6dSatqrr+3mkT3MXOD9w3hRByK7frIdrb/qXA35qlmq0/FnaXfBNCXno6dPwtF8ym0UiwryjYV7Rolr/eYCosV+SWSAvL5RV17WmXG1Saq7NcBHyW0IrNZTM4HCYhhMdhEkI0WiNFKJ3OqNEZO5RaRYfefDGXzfASW3mLBXfHO4UH2IT4ivp2G51JMc6xEQ47fiv54UC5yUSdvNCYnt2S+HjgnPu8b2tMfYiqrKz8+OOPLR3FSKfT6SwdAlyF/BsA+saVnMKWNqmfj3tnC5N59RUmJ7fYYDB+8PE3nacenHkXl80mhJiXPGo02j+PpeQXlpu3eOwSk8kwJ9+EEGsrfnuH8qYhMZlMBoPhLnbubLmV2/UQLfSC0Uj953DF9l9KOtPiG826x2vODO/e9c9i0iMCba5d19gs1TQ2q9vkuhappk2uU2kMSpWBIqRDqSeECHgcOp3G5zJ5XIadiONox7EVcpwduC4OvN4FcOt4HMYLc4OnJbgmfZVTWC7vUBk2f5t//HzD2sRIH/fhua2Smb+/v1rdU7lJGBixsbHOzs43vw76H/JvAOgbVdX1hBAWq4tXlcrqOh6Pc+1kkk4mo+nHPQeqaxv/OWdmdq5fbv5NRrX/1svxwlu5XQ/Rwu0qKJO/tz2noExuPgzwEj73z6D1/87qUP03Fx8VYvfS06F9eFNHW66j7eDduijYV/Ttu+N/+qP861+KdXrTlULpk2vOzH3Qd8mcQDZreJaBnz59+vTp0y0dBcAgMjz/VweAgcdiMQghDZLWG09xuJym5ram5v85JZe3m0zUS69/UFld/+arS/18PPs7wlu8XXfR9nd4w4xCqd/8bd7C11PNyTeXw1j8WMB374+fOMZp8WOBnZd5uAg+eiWGxRxZb0ZMBm3BI367P5o0OtSeEGIwUt/tK5v3ytm8UpmlQwOAgTCyXvIAoP/4+XoRQk6cOtfZQhGT0WQihPj5eFIU9fnX/+k8JZUqDv2ZXFBYlpaZMyrq6tinQW/s3J6FRqMbjd3ORemdW7xdd9H2bTDDGEWRQ8m1s1ec3nO40rzhzoQxTr9smbxkTqA5z378Pm8/T2tCiLWA9fFrMUKrLgqejAReboIvN8ZvfCFKZM0mhFTUdix689zWnwr1hj5+5gPAYIP5JwDQNyLDA8eMCjt09ExwoM9990wur6q9kl0kkymOnTw/cdzo0CDfv06c0+kME8fH1NU35uSVvP3mC+aS24ePngkN8S0oLC+vqm2TykrLq+1sRY4OtufSsopLKzs6VKHB/jq94dqVQzqdTm80UBRF63HhmsFgNJlMRqPRPHHcfO1NbxcVHthltP376xsuSqoUH3yTe6XwaulJsTP/5WfCrltYyWDQXlscnrjhwtsror3Fw3ne803RaOT+ye7xUY6bduSduNBgNFLf7StLz255a3n08J4RDjDCMTZu3GjpGABgsFPJa+uKj3gGTqDTe/rQPnlibFub/MChU/sOHudxuQ72tv6+nuGh/u5i17umjG1uabt0JT8tM9tGZP3SyoV2tiJHR7s2qTz9YnZeQemUibFjRoennL8kaWqdNiVe7Oacev7SmZSLEaEBDZLmX38/2tGhotNpQQE+59Kyft77p1qtIYREhAd2lji8ztHjqf+375hKrVaq1M5O9rY2wlu8XYC/15TJcTdGe9PfUk1JiqPXOJFjcO9+yUOdRmvc+X+lG7deqW9SE0KYDNqc+7w/WDOmy5KCLg68+CjH2HD7AQ9zMOJzmdPGufp6WGfmtmp1xhapdv/JGiaDHhlk2/MnTAAYomhU5/evAADdaK4+n/7Hign3v8pgDt5lbRaXeuj90IlrPEIfsXQgFnA2U7JpZ15D89UaF6ND7V9bHI4R3NvVKtP+68vslItN5sOYcPu3V0QP5rWkANA7mH8CAEPYfY8mdnfqzZcTx48bPZDBjEz1TaoPd+SlXrqaMtrbcFYtCJ0xwc2yUQ1R9jacj1+N3Xei+pPvClQaQ2Zu69w1Zzc8H3XrldEBYEhA/g0AQ9iR37+ydAgjl9FI/Xq08ov/FJsLe9NptBkT3VYvDDWvJoTeodHIo9M8R4far/3kUlGFQqrQvfh+xlMP+T33zyAmA3NRAIYJ5N8AAHDbSioV//oqJ//venlBPsLXFkeEB9j0/Ci4RV5ugp1J4z/7seDnI5UURb7fX3Ypv/XdF0e7Ovb7JkEAMABQfxAAAG6DVmf8+pfi+a+lmJNvLofxwtzg79+fgOS7b7FZ9JeeDtv8Soz5+4TcEtk/XzqTnCGxdFwA0AeQfwMAwK26mNf65Jqz238tMRgpQsj40U6/bJm84BE/Oh1TI/rFxBjn3Zsmjgq1I4Qo1YZXNl3csbcUdRMAhjrMPwEAgJtTKPVbfyzcd6LanPzZiTgrngq+f7K7peMa/pzsuV9uiP/8P0Xf7y8zUdSXe4pyi6VvrYgWCkbovkUAwwDGvwEA4CaOn2+YveL078erKYrQaGTmJPEvWyYh+R4wdDrthbnB7744ms9lEkJSLjUtfD21orbD0nEBQC9h/BsAALpVJ1G9vz33wpVm86G7M//1JRFxkQ6WjWpkmpbgGuAlfHlTZkVtR02DcuEbqUmrRk1AaUKAIQjj3wAA0AWjkdpzuOLJNWfNyTeDQVvwiN/PWyYj+bYgLzfBt++OnxzrTAhRqQ1rPszc+1eVpYMCgNuG8W8AALhecaXiX19mF5TJzYfBvqK1iRHBviLLRgWEEAGPuenlmO2/Fm//tcRopN7fnltZ1/HiglAsgQUYQpB/AwDAf2m0xi/2FO05XGkyUYQQAY+57Mmg2fd60WlI7wYLGo0smRPoZM/7YHuOwUjtOVxZ36ROWjWKy2FYOjQAuCWYfwIAAFdl5bc9uebs7oMV5uR7UozzL1smz5nhjeR7EHpkqse/18ZZC1iEkDOZkmVvpyk69JYOCgBuCfJvAAAgaq3xo515SzdeqGlUEkIcbDnvvzR686sxTvZcS4cG3YqNcNiRNM7NiU8IySmWLl5/vrlNY+mgAODmkH8DAIx0lwvb5r189ucjlSaKIoRMS3Dds3nS1HhXS8cFN+cjttqZNC7QW0gIKa9pX/Tmuap6paWDAoCbQP4NADByabTGrT8VJq6/UN2gJITY23A2vTzmvdWjzXuew5Bgb8P5cmP8qBA7QkhDs/qZtak5xTJLBwUAPUH+DQAwQmUVtD358tnv9pV1Dnv//PGkKXEulo4Lbpu1gLV13di7xroQQhQd+hfeSess2Q4AgxDybwCAEcc87L10w4Wav4e9P3olBsPeQxqbRX9/9eiH7/YghKg0htXvZx4/12DpoACga6g/CAC3qrm+kMFAftYtijJZOoRbkpXf9s4X2eZ1loSQaQmury+JEFqxLBsV3Dk6nbZ2aaQVn/XTwXK9wbT20yylxmDOyAFgUEH+DQC3qihrv6VDgDuiVBs+/b5g34lqiiKEEAdbzutLIibFOFs6LugzNBpZtSDExZH78a58k4lK+jJbrTE+MdPb0nEBwP+gUeaXYQAAGNYuXGlO+jKnsUVtPpyW4Pp6YoRQgGHv4Wnf8er3vs41URSNRlbND33yAR9LRwQA/4X8GwBgmLtu2NvRlvv6kvCJGPYe7v5KrV//2WWjkSKEJD4e+OzsAEtHBABXIf8GABjOzl9uTvoyR9KqJoTQaOSRqZ6r5ofweZh8OCIcP9ew7t9ZBiNFCFnwiN8Lc4MtHREAEIL8GwBguOpQGf79w3+HvV0deW8ujYyLdLB0XDCgzl5sem3zRZ3eRAh56iHfFU+FWDoiAED+DQAwHJ3Lak76KrupVUMw7D3inctqfnlTpjkFn32P1yvPhtNolo4JYGRD/g0AMKy0K/Wf/Vj4+/Fq86GrI2/dc5GxERj2HtHSslvWfJip0RoJIbPv9XplEVJwAEtC/g0AMHykXmp69+uc/xn2XhDC52LYG0hWQduq9zJUagMh5PH7vNc8E2bpiABGLuTfAADDQbtSv2ln3pEzdeZDd2f+umWRo0PtLRsVDCqXC9tWJmWoNAZCyLwHfVfOx1xwAMtA/g0AMOSlZbe883n2/xQ5wbA3dOVKoXRFUro5BZ/7gO+qBUjBASwA+TcAwBCm1hr//UPB3r+qzK/l7s789c9HjQqxs3RcMHhlFbStTEpXa42EkGdnByQ+HmjpiABGHOTfAABDVU6xbOPWy9UNSvPhzEniVxeHY9gbbiotu2X1+xnmiihLnwhaNMvf0hEBjCzIvwEAhh6Dkdq5t2TH3lKTiSKE2Ntw1iZGYEtLuHXnLzev+fBqUcJl/wx6+h9IwQEGDvJvAIAhpqy6fcPWy0UVCvPhtATX1xaHi6zZlo0KhpzkDMlrmy+ad8d8cUHokw/4WDoigJEC+TcAwJBhoqhfjlR+9mOhedjSWsB6+Zmw+yaJLR0XDFWn0hpf33LJaKRoNPL6kohHp3laOiKAEQH5NwDA0FDfpNq47UpWfpv5MCHacd1zkY52XMtGBUPd0ZT69Z9dNpkoOp2WtGrUtARXS0cEMPwh/wYAGOwoiuw7Uf3JdwXmsnF8HnPV/JBHpnpiC0PoEwdP1779+RWKIkwG7aNXYsaPdrJ0RADDHPJvAIBBrVWm/deX2SkXm8yHkUG2G1+I8nARWDYqGGb2HK7Y/G0+IYTDZnz2ZhxKWAL0K+TfAACD1/HzDe99naPo0BNC2Cz6kjmBTz3kS6dj3Bv63rbdRbt+LyWEWPGZX2yID/YVWToigGEL+TcAwGCkUOo37cj78+zV/eQDvIRvvRAV4C20bFQwvH28K/8/hyoIIbZC9tdvJ3iLrSwdEcDwhPwbAGDQOX+5+Z3Ps5ulGkIIg0Gb96Bv4uOBLCbd0nHBMEdR5O3Prxw8XUsIcbLnfvPOOFdHnqWDAhiGkH8DAAwiSrXh0+8Lfj9ebT70EVu9tTw6xA8zAWCAGIzUy5syzesNfMRW299JQGl5gD6H/BsAYLC4UijduPVyrURFCKHRyCNTPVcvDOVyGJaOC0YWrc648t2Mi3mthJAwf5svNsbz8CQE6FPIvwEALE+nN339S/EP+8tNFEUIcXXkrV8WFRNub+m4hjCjkVJqDD1cwGTQ+FzmgMUztCjVhsXrz5dUKgghk2KcN708Bqt+AfoQ8m8AAAvLL5Vt2Hqlsq7DfPjw3R4vLgwV8JAaXiVV6GTtOplCJzf/t0OvVBuUKoNSbVCqDUqVvkNlaFfqKULaO/SEEI3OaN4f9FbQ6TQrHpMQYm3FIoRY8ZnWApYVn2X+i7WAZS1gWvFZImu2oy3HwZZrJ2KPkEy0Rap9Zm1qQ7OaEPLINM+1iRGWjghg+ED+DQBgMSYT9cOB8q9+LtYbTIQQOxH7jcTIybHOlo5rQJlMVKtMK2nVtEg1klZNc5umuU0jadVIFTqZQidr15lMg+h9ik6j2dmw7W04jrZcOxuOqyPP3ZkvduaLnfl2Io6lo+tjNY3KZ9881ybXEUKWzAlc/FiApSMCGCaQfwMAWEadRLX+s8vZRVLz4dR419eWhNsM37VuFEVapJq6JlV9k7pOoqpvUtU1qeol6mapptcZNoNBE/DMI9ZMOo1mHsPmcRgsJp3JoPF6nF5iMFJqjcFoopRqA0WRDqWeENKu1LerDO1KfS9C4nOZ5kTc3Znv7W4V4Gnt42E91GdO55XKntt4Qa01EkJeWRT+2AwvS0cEMBwg/wYAsIBDybUf7shTqQ2EEAGPuXJ+yKPTPC0dVF9SdOir6pVV9R1VdR1VDcqqemVto/LWp4VYC1j2Nhwba7aNkG0nYtsK2TZCto2QY2PNElmzBTym+U//LU5VaQwdSkO7Ut+u0rcrDfJ2naRVI5Vrm9o0rTJtc5umVaa96Y9Dp9HcnHj+XkJfd6sAL6Gfl7WXm4BOG2LTV1IuNa35MNNopOh02gcvjZ4S52LpiACGPOTfAAADql2p/+Cb3KMp9ebDiEDbt1dEuzvzLRvVHZK360qq2itqO0qrFRW1HRW1HbJ23U0fJRSw3Jz5Lg48Z3uugx3XyY7rZMd1tOM623OHRNUXRYe+vklVK1HVmf80qeokqsYWtdHY7RurFZ8Z6m8T7m8THmATFmAzVKas7DtenfRVDiGEy2F8vj4+ItDG0hEBDG3IvwEABk5adstb2640t13dWOeZf/g/OztgyK3n0xtM5TUdRRXykqr28tr20qr2Nrm2h+vpdJqrI8/TVSB25oud+GJnvpsT382JZy1gDVjMA8ZopOqbVaVV7WU17WXV7aXV7TWNyu4ycldHXniAbVSwbVyEg4/7oN5scvuvJV//UkwIEVmzv00a5+EqsHREAEMY8m8AgIFwXYVBH7HV2yuig32HxsY6aq2xpFJRVKEoqpAXVSrKqtvNC0a7ZC1gebkJvMVWXm4CT1crLzeBh6uAzRq5m3fq9KaK2o6ymvaCMnleqayoQt7lxBUHW05shENsuH1shIOLw2DcdTLpq5x9x6sJIV5ugp1J44VWw/DjE8DAQP4NANDvSqvb1//7ckmVgvy9sc6LC0MH88o8iiJV9R25JbLsImluiayspr279YgcNsPX3crP09rXw9rf09rXw8rZfjDmjoOHwUgVV8hzS2V5JbLcEllNo/LG92EPF0FshP2EMc5jIx0Gz0cXk4l66cOrW2OOCrHbum7s4IkNYGhB/g0A0I9MFPXLkcp//1D4d4VBzpvPRU4c42TpuLqgVBtyS2Q5xVLzfxUd+i4vsxOxg3xEQT6iIB9hkI9Q7MwfcgsKBxVZu+5iXmtmTmt6Tkt1g/K6szwOIz7acVKM88QxToNhH3iV2vDs3/vyTB/nlrRqFP7xAXoB+TcAQH9paFZv2Ho5K7/NfHjXWJc3EiMGT4VBiiKVdR05xdKcYmlOiayipsPU1TuCnYgdHmAb4icK8hEF+wgd7bgDH+oI0dSqSc9pychpychtNS8S6ESn06KD7SbFOt091tXV0ZLfMDRLNQtfT21q1RBCFj8WsGROoAWDARiikH8DAPSL4+cb3vsqR6HUE0L4POaqwVFh0GSiCsvlmXmtF/Nac4pl7couBrkZDFqglzAi0DYi0CY80Hao12YZokoqFcmZkjMZksIK+bVv1DQaiQ62mzlJPDXB1VILWAvL5YkbLqg0BhqNrF8W9cAUd4uEATB0If8GAOhj7Ur9h9/k/vnfCoM2by2P9nCxZL2IOokqPaclPbslPaely4kl9jacED9RiK8oOtguMsh2SJT/GyHa5Lrzl5uOn29Iu9Jy7bJXNoseF+lw/2T3ybHOLOZAz8NOvdS0+oNMk4liMmj/XhsXG+EwwAEADGnIvwEA+lJ6dsvGwVFhsKKu42Jua2Zu68W81hurcTMYtGAfUUSgTXiAbWSQrWWnNMCt6FAZzmZKjpytS8tuuXY5rNCKde8Et1nTvfw8rQcynj2HKzd/m0cIEQpYO5LGeYsHdf1EgEEF+TcAQN+4rsKgt9jq7eXRIX4DWmGwTqLKyG29mNuSmdfaIr2+JjedRgvyEY4Jt48Jsx8VYsfn9bQ9OwxarTLtX6n1R87UFZTLr20fE2b/2AyvKbEuDMYAfd77aGfez0cqCSFuTvzv3h8/eNY2AAxyyL8BAPpAWXX7ur8rDBJCZk4Sv7YkYmAqDOr0pkv5reeymlMvNd1YQINGI34e1jHh9mPC7EeH2QuH45Y3I1ZFbceRs3VHztQ1tqg7G53subPu8XpkqscAbK5pMlEvfZCZcqmJEBIbbv/vN8cyByr1BxjSkH8DANwRiiI/H6n47MdC86YqdiL2m0sjJ8Y49/d9G5rV57KaUrOaM3Na1FrjdWe93AQx4Q4xYfajw+ztRBiVHM5MFJV6semXP6vSsps739JZTPq0ca7zH/bz7+dJKSq1YdGb50qr2wkhD9/t8eZzkf16O4DhAfk3AEDvNbao13/23wqDU+Jc3kiMsBX2V75rMFKXC9rMaXd5Tft1Z22F7IRox/gox5gIe0dbVAkccaoblL/+WXXwdE2HymBuodHI5FiXZ2b5h/TnTqsNzeqFr6e0yXWEkFcWhT82w6v/7gUwPCD/BgDopZMXGpO+yjaXE+GwGS/MDXpipk9/3KhFqk3Nakq91JSe3aJUG649RafRgv1E40c5jh/tFOInwlY4oNIYjpyp++XPqms/oY0f7bRoln9EoG0/3fRyYdvzb6fp9CY6nbbltdhxoxz76UYAwwPybwCA26ZSGzbtzDt4utZ8GBFo8/aKUX1eJ7tWojqd1ngqvTG3WHbdzjhCK1Z8lOO4UY4J0U6YXgI3oihyJlOy8/9K80tlnY2xEQ7PzvYfHWrfH3c8eLr2rW1XCCFCAevb98Z7ulqy4CbAIIf8GwDg9uSXyt789+WaBiUhhE6jzbnPa+X80D5cdlZe0372YtPZi5LsIul1r9A+7laTYpzjIhxGh9ljoRvcisuFbV//XJyR29rZEhfpsPKpkEBvYZ/fa8t3+bsPVhBCvNwEO98dj8W+AN1B/g0AcKtMFPXLkcp//1Bo3gbFxYH39vLoUaF2fdJzdpE0OV1yKr2xTqK69hSbRY+NcJgS6zx+jBNmdUPvZOa27txb0pmF0+m0B6a4L3080NGuL59RJhO1+oPM1EtNhJD4KMdP34i1SOV7gMEP+TcAwC25bqnl1HjXN5ZG3OEIn8FIZeS0nEprTM6QtMn/p1w3n8ccN8rx7rEu40Y5CVCoG/rC5cK2z34szC6Smg+5HMaT9/vMf8SvD59gKrXhmTfPlVW3E0LmPeS78qmQvuoZYDhB/g0AcHMnLjS8+1WOeakln8dcNT/k0Wmeve7NZKIu5rf9lVp/8kLDdbvB2wrZk2Kcp4x1iYtwYLMGelNxGPYoipxKa9y6u7Dm71LxdiL24scC/zHds6/GqmslqgWvpZif2O+sHDVjglufdAswnCD/BgDoiUpt+OT7gt+PV5sPw/xt3lkZ7eHSy7Vl5TXth8/UHUquvW5zShcHXkK048QxTgmjnDCxG/qbwUj9carmyz3Fnd+6BHgLX3s2PDKobwqkpGe3LE9KN5koqWd0sQAAIABJREFUNov+zTvjBngXWIDBD/k3AEC38ktlb356uaZRSQih02lPPeS79ImgXuTHxZWKv1Lr/0qtb2hWX9vu5sS/Z7zb1HiX4P4szwzQJaXa8N2+sv8cqtBojYQQOo320FSP5XODhVZ9sG7y+/1ln/1YSAhxceB99/4EVOkBuBbyb+gbZ3+Zq2gutnQU/cJv9ILghBcsHcWIo1Dqq+uVNQ3K6gZlq0zbJte2yXVShU6tMeh0JhNFmctg87hMJp3GYtF5XKatkG0rYtsJ2Y52XDcnnpeblaebwMa6l+/65qWWn35fYDBSpLdLLRua1X+l1h88XVtZ13Ftu6Mtd2qCy9QE16ggu5FWsHvBggVqtZoQkpiYOHXq1Bsv+PLLL0+ePHlj+1C/nhCya9cuPr+Pi1TeueY2zdafCg+fqTMfCgWsxXMC5tznfee15N/8NOtoSj0hJDrY7vMNY1lMzKcCuAr5N/SNsz8/yWLSnd2H287DFQXH3YIeQv49AOTtutwSWX6ZPLdEVlAmkyp0hBAmg+5ox7O2YgsFbAGfbWXF4rKZLCad0Gg8DoMQotEaKIoYjZRGq+9Q6duV+g6VTtGha25VmUuUWPNZIX6i8ACbsACbMH8bexvOrQRz3VLLaQmuryfexlJLebvuaGr9oeS6a0svE0JsrNl3x7vcM95tVKjdiN0oZ8GCBRMmTAgPD/fz83NycrrxgrKysqamphvbh/T1lZWVv//+++DMv83OZko++ja/vulq7Z2oYNvXFkfc4d71Wp1x8brzBeVyQsgTM71fejqsDwIFGBaQf0PfOPvzkyJbZ9/QLkaDhrSLydudfacj/+4nBiOVXdR24UrL+cvNxRUKE0U52fE8xEJPV6GLo8DJjmdnw6X1Kk81UZRMrm1uUzW2qGrq26sbFJIWJUURPw/rhGjHsVEOo0Ptu1vdeOJCw7tf5iiUekKIgMdcectLLU0mKjO39ffj1ckZEnP2b8blMCaMdpo5SRwf7YghwAULFsyfP7/LkeNh7MqVK0lJSYM5/yaEaHXG7/aVfbevTKc3EUIYDNq8B30THw+8kydtQ7N6wWsp5o/Tbz4X+fDdHn0WLsBQhppWADDQTBR1pUB6NLX+2LkGRYfOyZ4f5G07IcbT18vGitc3G3bQaTQ7G66dDTfI9+qMEbXWWFEjLyxrPZEm+fGPcj6XaR6KHhvp0Fn24bqlluEBNm+vuKWllgVl8kPJtUdT6mXtus5GFpM+YYzTzEnicaOcUMkEBj8Om7FkTuA9490+/CY3I7fVaKS+21d24UrzhuejArx6uVmPqyMvadWo5UnpRiP14Te5gV5CrMUEIMi/AWAgydp1+07U7D1a1diidnexnjLWIzrUycGWNwC35nEYof52of52hBCZQnulsOlSruTg6VpbIecf0z1m3evV1KpZd5tLLZvbNEfO1h1Kriuvab+2Pczf5v7J7vdOcOuTdWwAA8lbbPX5hvg/TtVs+a6gXakvqlAseC31mVn+Cx/1711lntgIhxXzQrZ8l6/Tm1756OIPH07o9aoMgGED+TcADISaBuWufWVHztaxmIz4aNdnHnN1cexlCb87ZyPkTI7zmBzn0SpVp11p/PVo9Xf7ygK8Rebk29WR99by6FEh3S61NBqpsxcl+0/UnLvcbDL9dwqfkz135kTxzCnuPmKrgfgxAPrNg3d5xEc5Jn2Vk3qpSW8wffVzcXKGZP2yyN4NhD/5gE9RhfzwmbrGFvXGrVc+fi1mxK5/ADDD/G/oG5j/Dd2RtKq/+a30j1M1jnb8yXEeMZHOHBbD0kH9D4PRdDmv6XR6TU19u5M978NXxoR2Uw2wVqLaf6Lm4Omaa6t3czmMu8a63D/ZPTbCHlkFdIeiqN4tZrCszoFwQgiLSV/6ROC8h3x78TxXa40LXkupqO0ghCz7Z9DT//Dv+1gBhg7k39A3kH/DjXR60/f7y3b+X6lQwJ4x2Scu0mUw5x8URbLym46eqWhqUz1+n3fi44F87tVvCHV6U3JG4+/HazJzW659yYwOtnvobvep8a587A8Pw1dTqybpq+xzWc3mw7hIh7deiHawvaVSQteqblDOfzVFqTbQabRP18bGRzn2daQAQwbyb+gbyL/hOlkFbe9+mdPQor5vks+kse5MxtBYgEhR1PnLjX+cKLXiMV9dHO7uwt9/vOZQcu21CyttrNn3T3Z/eJoH5pnAyLH/ZM3H3+arNAZCiK2QvW5Z1MQxXZRf7Nmxc/VvbMkihNiJ2D9+ONHRjtv3gQIMBci/oW8g/4ZOJoraubd0+68lIf52j90XZCcaem+x7Ur970eLM3Mlnq6C6galuZFGI5FBtvdPdp85ScxhD64pNAADoL5J9eanWTnFV6vaz5wkfn1JBJdze/8vbNqR98uflYSQiECbr95KQEVOGJkYGzdutHQMMBxU5+3l8qxsHX0tHUgfa6i6ZGXr5+ARZ+lAhgyFUv/KposHT9c9ck/ArHsDedz/Z+/OA6KqugCA39mZgRmYYWfYF9k3QQQMQcAyM7Uy06zQFk1NK7Ws3DPKPS0tTTNNU0vNpTQ3dhAEUVbZ932bDWZf3vfH+BEJKvvAcH5/MXfue3MGHnDmvfPOHZWFGRQywdvVxMSQlprVqFJhLH3yvBfsNi33fuNFe1d7/dFyLh+AwUXXJU0PtZTKVLklXIRQSVV78r3m8e6GTEYf+plM9Da+m9fa1CppbpOIpcogH6hCAWMR/BcBAAwaDl+6ZFNaYYVg5cLxoQGWmg5noPw8TNe868/U19EhE2eFW7FNR+7KKQAMDxIR/+Fbrvu+CGDpUxBCJZWCqLXJN1Lqe78HIgEX/ZGvOmU/9XfFrdSGoYoVgBEM8m8AwOBobpO8uz5V0KH4MMrPlt3P1TpGGnNj3U8WTyCRCO+uT62o69B0OACMCEE+xmf2TH5mvAlCSCxVrtt7/+tDuV3XfH0yU0Nq9Ee+6nWvtv6QA79ZYAyC/BsAMAhEEsWH32QoVLiVUeNZBqOv4PsJ9Kik5W/6MuiUlV+lc/iyp28AwBjAZJD3fDZh9SI3AgGHELpwq/qd9bcbWsS93HyCp9G7c5wQQiKJ4vM99yRS5RDGCsDIA/k3AGCgVBi2YV9Wc5t4yXwvhp4WrmynQyG+95qXSoVbs+OuTN7bk3ygR1FRUTExMZqOYrhlZ2fPnTtXLO5tejoq4HBo3nS7HzZONDSgIIQKyvhvrU1Oz2nt5ebvzHEM9jVGCJVVt0cfzBnCQAEYeSD/BgAM1NlrVSn3mt+e4zUaW530ki6N9N48z9Kq9sNnSzQdCxittLLh2Hg3w+PbJnk4GSCEeO2ylV+nn7xc3psN8Tjc1pW+FiY0hNC15PoLt6qHNlAARhLIvwEAA9LYKj5wqihyko29dc9rRmoNUyPdFyMcTlwuK6oQaDoW7adlp4q1m6kh9cjW4KjZDgghpRLbd6Lgi2/vS2VPLylh6JG+/tiXTMIjhHYdzS8o4w95rACMDJB/A41JTLk7+7UVldV1A5zZm/0olcr8B6U/Hz9/525uP8MFj3Hgt0KGHvm5ENv+bZ6WlrZo0aKampoBzuzNfpRKZVFR0enTp+/fv9e/aIP9LGwsGHuPP+jf5qA3rl+/vnHjxnXr1vX4bEZGxtKlS+vqnv53AwwnAgH3wQKXLSt81K3xb96uX7olrZUrfeqG7o4GH73lhhCSyVWf7srkt8MtFmBMgPwbaIyOjg6TSaeQn14u3H1mK4fbp/0UFJZf/Dvm5+Pnm5vbBhIzeERzm+RWasNzIbbE/i6iQaFQ9PX1Sb04DLrP5HY5DHqzn5KSkmvXrp86daqlpbclqo/A43DTw+zu5rfll/L6twfwVJGRkSKR6HGlGhQKhcFgkEikYY4K9Mb0yeyj0cFmRlSEUG4x7621yQ968Zvy6jSb556xQAg1too3H8jWxiIdAB4F+TfQmAA/j18Ofm1u9vTFFx6Z2d4u3BL9Q5/24+Hu9OpLzw0wYNDd2WuVerpkX3fTfu/B19d37969ZqZP38MjMzs6Onbt3t2n/bi4uLz44ox+h6o2zo5lZa73xz+VA9yPltm9e/elS5daW/v5waYrAoHAYrEe96yXl9f27dtNTPq88jkYHuNsGb98Pcnd0QAh1MKVvLcx9VrS0y9WrHvfy96KjhBKzmz+7e9elY8DMKpB/g1GGblCsSl6f119U183JJFG5UKMI1xiZvN4d1MCHjfMrytXKHbt3NnU2NjXDYnEQTgM/D3Nk++1qOA0XRfV1dWnTp1avnz5xo0br1+/3t7erumIgMYYMSmHtgSqT2nL5KqN32cdPlvy5F8XKoWwbfV4KoWAEPrhVBEUggOtBxkJ0Iz2dmF8UsatuNRXZk+dPMm/uLTy5q2U2MT0Y4e+3vfDiZTUe2xzky83rrQwN3lkZmz8nYrKWkF7xze7DltbW8x8PqzrswghDpf/09GzpiasxqY2Pr/9808W6zP0NP12tROHL62obX9uskO/99DR0XH79u2kpKQXXnghMDCworwiLiE+NSXl2717jxw+knE33dTMbO0nn5qamT0yMyU5ubq6ul0o3P/992w2e+qzz3Z9FiHE4/FOnDxhbGTc2tLCFwhWrFjJYNAH642Ps2NeuFFSXCFwsdfyW077ZO7cuePGjUtISDh16tQvv/zi5OQUGho6adIkKpXavx2WlZWdOXOmtLTU0dHx3XffNTU1FQqFd+7cSUlJmTZt2oQJE9TT7ty5k5eXRyaTa2pq7O3tX3nlFRKJVFNTk5ycnJaWtmHDhpiYmISEBB0dnXfeeWfcuHGnTp26e/euQqFYsmSJj4+Peid8Pv/MmTNGRkatra0CgeD999+n0+kIocrKyqtXr7LZ7KKiIqlUumHDhscNgq4oZMLWlb5ONowfThWpMOynP4prG4Xrl3qRHl+oZsfWW/O2+9Yfc+QK1Rff3ju5M0SXCikK0Fpw/htoRhuXV1FVk5GZq1KqEEKGLIPisuqGxpYfj5xZMO/FLzesqKppOHjkj+4zn4uc5Ohgrc+gf77mvQVzX3jkWYTQxq3fi4TiRW++/Pma9xoaW/Yd+FWDb1O7FZYLMAzZWvY/B+VyuTXV1VlZWSqVCiFkwDSoKC9vbGo6fvz4y6+8/Mknn9bV1h3/9UT3mWFhYbb2dvp0xgcrVrz08suPPIsQ2rFjh0Qknjdv3gcrVjQ2NR0+cngw3vFDFiZ6OhRiIXRB+S8cDufp6fnBBx8cOXLkk08+YbFYR48efffdd7dv356QkCCVPrwV7/jx4xEREU/dm0AgSExMfOGFF1555ZX8/PyNGzdKpVIej1dTU5Obm9v5g75y5crff/+9cOHCN998c8WKFampqdHR0RiG6evrt7W1NTQ0nDt3LiAgYPfu3Xp6egcPHvz1118jIyN37txpZmb2888/d77c3r17xWLxK6+8smTJkubm5mPHjnWOR0REzJo1a9WqVeT/313Q4+CTeXt7//777zQardffzlEPh0NRsx22r3l4VvtqYt1H32QIxYonbDIz3GraMxYIodom0VfQERxoNci/gWbYWrNDgv07HxqyDFyd7RFCS955zc6GPcHP09vLpbCkvPvMJ+8HIYTD4RwdrdVf29tZlpZBT9mhwuFLyWSC+p9r/1hZWU0MDOx8yGQynZycEEJvvvmWtbW1j4+Pm7tbWVlp95lP3g9CCOFwtnZ26i9tbWyqKir6HWR3OBxi0Mkc/tN7O4xNJBLJz8/v448/Pnz48OLFixFCBw8eXLJkyf79+zMzM5XKXq10SCQSFy1a5OPjM2PGjLlz53K53NjYWDab3XnaG/3/pPXUqVMJBAJCiE6nv/TSSw8ePEhOTmYwGOpjafr06XZ2dlQqdeLEiU1NTREREWw2W0dHx9/fv6mpSSD490OUjY2N+gtra+vq6mqEkFKpbGhoKC8vV8czbdq0xw32Bg433GVaI0FYgNmhLUEsfQpCKD2n9Z31t5vantRZ8vMlnlbmugihW7cbriTUDlOUAAw7uLgDNEb9L7MTHo9HCBEJDz8T0qhUsUjS48wn7+f73esQQhKJ9NrN5AeF5Rg20NUKq/LOld07PsCdaCUV0UKPunKAO8HjezgMCMSHg1QdWmcf6EdmPnk/X0dHI4QkEkl8fHxJcYkKDXKtth6NdOv8l9fOSLo/9csvv+jq6nYfX7RokVAoHDvzEUK6urqhoaGhoaEcDufy5cv//PNPYmIik8mcMWPGjBkznpyPdj1VHBoaeurUKXXK2/X3vaSkRCqVGhkZdY74+fkhhPLy8kJCQtTHUuer6OjodN1c/bC9vZ3BYCCENm3ahBCSSqWJiYmlpaXq7isEAsHLy+vYsWPV1dULFizw9vZ+3CB4AlcH/V++Dv7w64zKuo6y6vZFn9/e+8WEcbaMHifTdIhfrfR5d0OqXKHafjjP3dHAlg0FhEALQf4NtI1KqTp55nJ1beP8udNz8hzyHgx0tUJj60Bzh8hBiU3LpOcLe7PEhkaoVKpz58811DXMmj3byflBUVHR4O5fKlX6+78SEdhDFw51YtfdsmXLFIoeLr5r63y19vb21NTUlJSUwsJCPT29iRMnPvPMM66urn06GcxkMslkskz2aGfolpYWhFBHR0fnCJ1Op1AoXC4XdfPIK6ofdtaxqFSqS5cuNTQ0zJgxo7CwsKTk4d+Njz76aN++fTExMenp6atWrXJ3d3/cIHgCCxPaka1Bq3fczS7ktnAlSzal7vjEf4KHYY+T3RwNFr827sBvhWKpcsN3WT9/FaxeoAcAbQL5N9AqKhW2+vPtTKb+xs+XDdY+aQxLc0fIv3ugz2kUSTIVSlXnVYsRQqXCNm/eom+gv3rVqiF6CUGH1MXNJyjIpvebdC2c0Pr5MpksMzMzMTExKyuLQCB4enp+9NFHEyZM6Hf/GRwOZ2Vl9cigugthU9Oj3ZDYbHafdo5h2DfffMNgMFasWPHIUxQK5YsvvkhKSjpx4kR0dPTOnTvZbHaPg318Q2OOPp38w8bALQeyb6TUd4gUH0anf7nSJzLIvMfJb82yv5vbeientbCcf+BU4cdRbsMcLQBDbWT91wSgN3A4vFLZc1VJQWHZnbu5vt4P/1gr5EroETd0rMx0MQw1NPdQkzAM8Di8QtnzvVwlJcX379/z9PBQP1QpFI9bzKV/BB2yDpGcbTqG7qXrJblcnpmZuX///nfffXffvn0ymez9998/fPjw2rVrg4KC+p18t7S0KBSKoKCgR8bHjRtHpVIzMjI6R9ra2qRSqb//Y+8Y6VFpaWl2dnbnaWylUqk+YORy+a1btxBCISEh6ts68/Lyehzs3/saa8gk/NYPfV6fYYcQkitU6/bevxTb84K1eBzuy5W+hgYUhNDpKxWJd/vccBaAEQ7yb6Ax6n4IMvnDFEqhVCKEFP9PrKUyqUQi7XGmsRGzjcsrLq28l/VAIpF1fVZ9hfnq9cSyiuq//4kvr6rlcHml5dUcLl8oFCOEennvF+gNeys6S59SXNnDtf7ek8mkCCG5XK5+qD4MlApl57OdfTMemclisbhcbkV5RW5urlQq/c+zOIQQiomNraysunnzZlV1FY/Hq6is5PF4IpEIdak66J/icg6RgPd2YQ5kJ9onKSlp8eLFO3bsaGtri4qKOnLkyIYNG0JDQ/vRfxCPx4tEIvVvK4Zh586de/XVV9XnmNVVKOofNJ1Of+ONN4qKinJzc9Ub/vPPP6GhoepMWr15589a/bDz+FE/7FpRk5CQUF1dHRcXV1NTw+fzq6qq+Hx+XFyceg8sFotGo9nb2yOEehwEvYHH4T6Oclu9yA2HQyoVFn0w59dLZT3OZOmTNy33xuEQhqGvfsxp4fZwrwUAoxdh8+bNmo4BaIPq/PM6VD2mcW//D+U/KD155q+aukYev93a0rymtuG33/8StAvFYombi0NcYsafl28JRWKEEJFIPPX7350zTU0MTU0MU1LvJSZnero5yWTyrvvxcHficPnpmTn5BaVhIRP8xnskp95ram6ztjQ/9ceVqur6DqHYwty4N4tuqjVU3dNjOhhZBfTz+6LVcDhUXCkoKOMF+lj0bw9FRUXnzp9vqK/n8wVsNru+vv7PP//saG+XSMTOzs63U1L+uXpVnTETCMTzf/7ZOdPY2NjI2DgjPT0tLc3FxUUmk3Xdj4uLC4/Hy7qfVVRUGBwc7OXtfTc9vaWlxcKCfeHChdraWqFIZGZqatqLRTd7dD2p0tSQ8vJU6/5trpWuXbtGpVKnTZv2/vvvP//88/b29r1szNcja2vrtra2uLi4goKCvLw8Ly+vqVOnIoRKSkouXrzY2NgoEAgsLCyMjIwcHBzs7OyuXr1aVlZWXFxMp9MXLFiAw+FKSkouX77M4XAkEomtrW1jY+Ply5fb2tpEIpG1tXVLS8ulS5fUJ8ttbW2tra15PF5OTk5JSUlAQICHh0dmZmZra+vEiROTk5PT09O5XG5SUlJYWJi/v79KpYqPj39kcPC+kWOChxPTwoSWlNmsUqH0nFaZXDXB06j7HQFWZrpCkTK3mCuRKgvKBC+EssdmDxmglXCDe1kWjFlJv7+uzzS1d3t6W9/RJTPhsKn9VJegDzQdyAh1/wFn8abUVW/721r23M1A+3D4ki/3p3610mdqcD8/dWglLpfLZPbqgkBUVNRbb73Vmxbg2iQ7Ozs6Ovr48eP9Xo1I+yRkNH3x7T2ZXIUQmhFmuf59LwLh0fRaocTe23A7r4SHEFr+uvPClxw1ECgAQwDqTwAA/efrxnJ1MIi5XaXpQIbPrZQqE6ZO+MSe7xsbs3qZfI9xcMKrq9AJprvX+qsXEPg7vnbT/iyl8tHvD5GA2/qhr3ohzIO/F+cUDajaDYCRA/JvAMCALJs/LruwJa+4VdOBDIfKOsHtzPr3543rfqIOANBXgd7GBzcHGtDJCKHryfVrdt5Vnw7vytKUtu59T4SQUol98e19QYdcA4ECMNgg/wYADEigt/ELoZZn/ykSPXFlaS0gVyh//7vQz8Nw+mRLTccCgJZwczT4YdNElj4ZIZSc2fz5nnvdU/CpwRbTJ7MRQk1t4uhDsC490AaQfwMABurjKFcyEf/LuVylSmsvr2MYOnW5UNAhXbfEE+4BA2AQOdkwDm0JMmbqIIQS7zat2XG3+8Jeny32tLHQRQjFpjX+Fddz10IARhHIvwEAA6VPJ3/7mX91ffsfV4q0tcD1alx5dkHz9jV+0PYbgEFny9Y7uCXQxFAHIZSa1bIyOkMk+c/1NCqFsPVDXxIRjxDa/cuD+maRZgIFYJDA+pcAgEHgZMuI/th37a5MDEPzX3TWsjZhf8WUxdyuXr/U83ErZgMABsjaXPfQlqClm9MaW8X3HrR9/M3dvV9MUN+dqeZqr//eq04/nC4SihUbv8/6aUsQHq9Vf2cAQuj6T6EKuXZ+uPKass7KbXbnQ8i/AQCDI8TPZNen/p/sypTI5G/MciOTCE/fZsRTqrDz14pT79dv/sD7+cmwxjgAQ8jSlHZ4a9DSzWm1TaJ7D9pWfpX+3fqAril41EsOadmt9x60ZRdyf71cvnC2gwajBUMDM7f1Yxpp25pWRfcvPjIC/b/B4ID+30Dt/gPOmp2Zerrkt+d4mBiO7lINfrv02Pm8usaOrz7yDZ3Qz8V6AFDDMEzLrgsNkaY28ZJNaXVNIoTQRC+jPZ9NIJP+rZWtbxa9viZJKFYQCbij0ZNcHfQ1FykYfNd/muzgHmlmM17TgQyylCvb3ELWdD3/DfXfAIDB5OvGOrnjGQM94q4jd9Pu14/eD/g5hS07fkpXKpS/bn8Gkm8wcJB895KpIfXQlkD1jRZ3clpXb/9PU0ILE9rHC90QQgoltml/Vvc7NQEYFSD/BgAMMnNj6uGtQa9MtT5zpejAifvNnFFWzMcTSI/8kfPz2dywALPj2yfZWeppOiIAxhZTQ+rBzYHmxlSEUFp2y5od/0nBZ4VbRQSaI4Qqajt+OF2ksSgBGADIvwEAg49Mwn8U5Xrs60kIKbcfTD9/vbhdKNN0UE8nliiuxJV//cMdDld8YGPgxmVeNB24SQYADTAzov6wKdCY9bAjyrq997uujvnZYg9DAwpC6PSVitSsFo1FCUB/Qf4NABgqrg76v257ZtUit/yi1i+/T/0rpkzQPkKzcKFIfj258svvU2/fq3v3Vccze0Kg1QkAmmVpSju0OVDdFzw+vXHzgWzV/wvaDOjkTcu9cTiEYWjrjzmwKCYYdSD/BgAMIQIBN+dZm4sHwt5/bdzd3IZN+1KOX8ivrOVrOq5/1TV1nLlSuGnf7YS0mvkv2F7+ITxqtgOFrA3NWwAY7azMdQ/8f3XMa0l1+34t6HwqyMd4doQ1QqiFI9n5c57GQgSgX+DSKgBgyFHIhDdm2r823TYho+nU3xV7jmYaGuj4upsG+phrqkcKTyDNLmzOKmguq+JbmumueMN5ZrgVVJsAMNLYsfX2b5i4ZFNau1B+6u8KfTr57Zcd1U99vNAtM7+tukF4Lbk+xN/02UkWmg0VgN6DfzYAgGFCIuIjg8wjg8zzS3nXkupupDTcSqmyNKe72LFcHFn2lvpE4tBekVOpsMpaQWE5p7CsrapeoEcjRQSZf/q2q6+rIbSmAGDEcrJh7PzEb2V0ukyu+vF0EU2HOG+6LUKISiF89aHv2+tSFEps2+E8L2emmRFV08EC0CuQfwMAhpu7o4G7o8HHUW6Z+W0JGU2pWS23bldRyAQbNsPagmFjwbC2oDP1dQbltfgd0ur69uo6QU2DoLJWIJIozIyowb7GH77lPNHLiDTEGT/oLioq6q233oqI0La1Ap4sOzs7Ojr6+PHjVCokiP3h5264bdX4T3ZlKpXYt8ceGBqQpwZbIIRcHfQXvuR45FxJu1C+9cec/esnwmdpMCpA/g0A0Aw8HjfB02iCpxFCqKFwkxLjAAAgAElEQVRFfCe7JaeYl1/KiU2tVqkwHTLRxEjHiKlrzKIy9CgMPbKeHolOI1MoBBKRgMPh1KviSaUKJYYUcpVUrugQytuFMkGHrF0oa2kTtXBFLW1ikUSBwyErM113J4MXQs0nehnbWOhq+q2DMQoWvBuIEH/TTcu8N+3PUmHYxu+ydKmkYF9jhNC7c5xSs1ryS3npOa2//1Mxb7qdpiMF4Okg/waDBVdTklxTkqzpMAYfrLwyDMyNqbMjrWdHWiOERBJFUYWgql5YXd9R0ygqKm/l8GWCjt42TtGjkVgGFCsz2jO+xlbmNBsLPRd7fT0a/K0bQQ4dOnTo0KHOh487KxwVFSUWi7uPj/b5oN+en8wWCOW7juYrlNja3Zn710/0dmESCLjNH3i/uTZZIlXu/60o0NvYlg09+8FIB/+TwOBwDV4pl7ZrOoohoce01XQIYwtNh+jryvJ1ZXUdVCgxrkDKE8jEEqVEqlSqMKFYgRDSpRIJeByFTKDqEJgMsgGDDCUlI9zy5cuVyv+sWUgmk3s5c7TPp1AoPc4Evffa87atHMmxi2USqfLjbRmHNgc62TJs2Xor3nDZ+XO+VKb88ofsI1uD8XgoQwEjGg4uhwEAAABgtMAw9PVPuRdvVSOEjJk6P0cHmxtTMQytjE5Py25BCK180/XNmfaaDhP0x/WfJju4R5rZjNd0IIMs5co2t5A1Vm6zO0fgRBEAAAAARg0cDn3+nkdkkDlCqIUrWf7lnTaeFIdDXyzxpFGJCKGDZ4rKa7TzeizQGpB/AwAAAGA0weNxW1b4qBeprWkUfrwtQyxVmhtTV77hghCSyVVbf8xRqeDyPuiBWCzVdAgIQf03AAAAAEYdMgm/57MJy7feySniFpTxv9hzb/da/5en2qhbmuaV8E5cLo+a7aDpMMEIcvlKbEz8narq+ou/f3/nbu6NW8n/3EhCCPl6u5KIhA6RBMOwyPCgWdPDabTBaYD7BHD+GwAAAACjjw6FsHutv5WZLkIo+V7zdycKcTj0+eKHVSg//VFcVg1VKOBfM6aFSaUy9V3RE/091699X5dGRQh9v3v93p1fHDnw5fy50w8cOrX68x1yhWKog4H8GwAAAACjkgGdvPszf4YuCSH029/lZ69VmRtTP3zTFSEkk6s2H8hWKKEKBTyEJ+BNjA07H+JwOBqNihDq7JYTGRYUPjkwO7cwJ7doyIMZ6hcAAAAAABgidmy9nZ/6qRuP7volP+lu00uR1kE+xgihwnL+yb/KNR0gGLlw3ZZLZVuYIIQaGluG+qUh/wYAAADAKDbezfDzxR4IIZUKW/9dVmmVYMNSL7ouCSF0uFsVilyhKoW6lLEkKSVz2+4jB346vee7Y20c7pMn5+YX4/E4d1fHoY4K8m8AAAAAjG4vTrFaONsBISQSKz78OgPDUGcvlE37s8pq2g/8VogQKqoQLPoi5cfTQ15dAEaIGzG3j5+69PGKt5Yvnv9O1CsVVXXd55SUVRWXVqalZ2/cur+4tPKTj962s7Uc6sCg/wkAAAAARr1lr7s0toqvJde3cCWrd9w9tCUo9k5jalZLUYUg6rNkFYYEQsXFmGqVCmtoEaswDN+t9gBoGYlEtv/H31Yse4NCJiOE9PXpPp4uufnFj0z74/w1qVReV9dYXFYVETbRedxwLN4E578BAAAAMOrhcGjDMm/PcUyEUGE5f923975Y7EkhERBCUplKLlf9ebNK3RRc0CEvr+nQcLhg6GXnFrZyuA52/57MJhJ7OO+87tMlX2744OeDXx37KTrvQel7yzem3L431LFB/g0AAAAAbUAm4fd89m9HwqVfpknlyh5nZhVwhjc0oAFV1fUIIRKpt7UeDnbWyxfPVyqV+w6eHMq4EIL8GwAAAABaw4BO3r3WX5dGRAjVNooeN+0+5N9jAIlEQAg1NLX1fpNxTrYIobq6JoVyaFuAQ/4NAAAAAO1R3yxS9XzW+1+Qf48FDvY2CKGYuNudIxhSKVWqfx9ij7aHr6ppQAhZss2IhKG9QxLybwAAAABoAwxDxy+Wrdp2Vyx9ysnLFo6ktumxZ8eBdvDyGOfn637leuKFyzclEtmDovLsnCIeT3AzNlUikWEYJhKJEUISiVQ9v7Gpde+BXxFCixe9OtSxQf8TAAAAAIx6IrFi0/7s+PTGXs7PKuBYmtKGNCSgcdu2rtp34MTPx/88cfryC9PCJgWNVygUTAN6bn7Rrbg0oUiMEHpn6XpTUyO+oEMg6LC1sVj/6RIvD+ehDgzybwAAAACMetlF3D7dVXm/gDMjbMjbPAOZhMdtyKHoGunoGlNohjjcsFZe6NKoX3yyuMenJvh5fr7mveEMpivIvwEAAAAw6gX5GJ/dF7rv14IrCbXdynp7ACXgwwNPIGde+xRTKRFCODyBQmXp6Jnp6Brq6Jnq6Brr6Brr6JlQaEZUuhmBqKPpYIcP5N8AAAAA0AYGdPKm5d4zw62++Sm3ovYpHb5rGoQtXIkxcwzlfBpBJNEYRuN09a1sPOZIhM0SYauko0kibOG3FDZVJEpFrSql/OFMsp5CIamrSNc3tKHqGWo27KEG+TcAAAAAtIevK+vUrsm//VX+0x/FMrnqCTOzC7iRwebDFtiYxTL3aau/x7Lw7fFZqYgj4tfkJWwXtJXgcHhjC3etT74R9D8BAAAAgJYhEnBRsx1O7Zrs5/6kTA5KUIYH09y7vbVEIev5ikQHrzI79ktxR6PbM6sJRAqZojvM4WkE5N8AAAAA0EI2FroHNwd+s2o8k0HuccL9Qsi/h5ZSIWmry+Q1P8AwFbcx95Fn5VJBbvzXaRfe1zWwnjzvjJ33PI0EqRFQfwIA6L+oqCixWNx9/Pjx41QqdezM9/b2XrduXfdx0Cf19fVbtmzhcrmaDmTQLFmyJCIiQtNRjHWRQeb+HoY93pdZVtWeW8LrEMqb2iRNrWJ+h0zQIee3ywUdcr5QLpepxBIFQkipwkQSBUIIj8PpUokIIYRDdF0SiYTX1yPRdUkGdDJdl2TAIJsZ6ZgZUU2NqCYsHTJpjJ7ilEl43IZsTn0WpyGb31KAqRRUuhmJwuA25BhbB3VOayi9lZe4A4cj+E3bZuYQrsGANQLybwBA/y1fvlyp7GGhOTK557NNWjn/xo0bPU4GfaJOvo2MjBYuXKjpWAaKy+WePXtWJBIpFEO7hDXoJfV9mZN8Tb799UFzmwQhhHAIYUiFYYu+SMEhpEMhsgx0aFQijUKkUslmxlQ7GyKRgKdSiOq5OjpEhBCGYRLpw78AIolcLleJxAqRRF7VIBZJ2oVCOYcvkSseVpwbMXXsLPXsLfXsreh2bD0HGzpDl6SZ9z/0JMIWbkM2pyGb25AtaC3CMBWNwWaae1u5vmhkFUBjsHNiv+Q0ZKkni9sbcuO/aalOs3af7Rr8IZE8JgpOHgH5NwCg/wICAmB+VlYWhwNXsQekoaFhy5YtTCbziy++0NUd3f+MGxoajh07Zmpq2tDQQCTCP1lNEkkUD0r5eaW8vBJeXjG3jSdFCFHIBJlciWFIn07ht0uDfCxeetaRqjNoPylBh4wvkHIFklaOuKlNlJ7LuRxbK5YqcDhkaarrOc7A3cnAw9HA2U6fQMAN1osOPwxTdXAruQ3ZnIYsTv19cXsDDk9gGI5jmns7jH/L0HICWUe/63ymmXd9yQ2VUlZbeKUgZS9F1zBw9g+GbH9Nxa9x8KcBAACAJjU0NGzevJnJZG7YsEELku/O97Js2TJNhzMWqTCsqFyQlt2SmtWaW8xRKDEDBsXagjHJ39LGnGFhqqdLI7VwRGevFlPIRGNDamkVbxCTb4QQQ4/M0CNbWdC7DnIFkrpGYVUdv7xWEJ/eJJIoaDrECV5GgV5GE72NrMxGx2GPqRSCthJOfTa3Mbu1Nl0uERBJNAMzD0uXGSxzH6a5N4FIedy2LAtfpUKacPo1SUezo99Ch/EL8QStvRrQG5B/AwD6oKysTCaTubq6ajoQoCW0Nfke7e9l1FEqsbv5bbdu18fdaeJ3yAwYZGd7w9dnujraMA0YjyaFxiza0gU+9x80+bia5BW3YhiGww3tqWgmQ4fJ0PEYZ4gQwjDU1CYsqeAVlrftO1EoOaKwNNWNDDKLDLZwtmMMaRj9oJCLeI15nIYsbmM2pz5LpZRRaEb6Ji4Ovm8ZWQUwjJx7uZ6lroEVmcqi0AwnTN+jx7Ib6rBHPsi/AQB9cOPGDQ6HA/cagkHR1tb2+eef4/F4Q0PDQ4cOaTqcgSorKzMyMlq/fn2PN++CIZJbzPsrriY2rZHfIbNh00MDrdwcjSxMnvL5B4dD491NEUJeLsbDEuZ/XtrMSNfMSDdkAlupwipr+fnFbX/F1x27WGZpqvvsJPOZ4VZsU9owR9XV44q53UPWMM296Sz7fu0V5zdtG9Pce5jXnx+xIP8GAACgGbW1tSKRaPz48QQCQdOxDBSfz29padm6dSsk38NDJFFcT64/d72quFJgaU4PnWjl62ZiyBxl33wCHudgbeBgbTAz0qGqXnD/QfOft2qOXSgL8DJ6dZrNM+NN8PhhqhEXCepaa9I5DVnchiyRoP6/xdz+ZB2Dgb/E49bfGZsg/wYAAKBJK1eupNE0ebZvUGRnZ0dHR+vowGLmQ47fLjt9peLM1UqZXOXrbrrq7XG2liOubKMfbCwYNhaMmeEOecWtKZn1a3bcNTWkvv2K44wwSxJx8M8ZYyqloK1YXczdVpshk/DVxdxs5xeeWswNBg7ybwAAGBBHR8f29nZNRwGA9uO3y05eLv/9WhWBgAsLsn5mPFuXpm338OHxOC8XYy8X4xaOKC6tZseR/J/PlS58yWF2pDVxwP1SeirmNtQ3cbX3fZNp7s009cDhIS0cJvCNBgCAAZk6daqmQwBAy2EYuppYu/d4gUKJhU20Cgu0plJGfc3SkxmzaHOnOz8faheXVvPt8YLf/q749B33IJ8+V6tLRa3qpXAGtZgbDBTk3wAAAAAYuYorBdEHcwsr+WETrJ4PtaVQxlDqQtclz4xwmORn8ef1kpXR6VMnWaxZ5MbSf0pliEhQx2nIUjfn7uBU/KeYm+1HpjKHJ3jwBGPoIAYAAADAKIJh6Pd/Kr47WWhjwVj7XoD507qaaCtDA+p7r3nll7Sdv1Y8f3XS1pU+AV5GXSf8t5j7rkzCI5CoDKNxpraTXYJWGFr4Esl6mgoe9AjybwBAH0CtMwBgeHSIFBu/z0q53/z8ZLupz9jgh7hF98jn7mToYD3h9ytFK75KX/iSwzuvWAqa8tXF3NyGbKVCSqGx9E3c7H3fYJp7G5i4j9IFboqy/irK+kvTUQw5yL8BAH0Atc4AgGHA4ctWfHWnuU264k1fB+tBaH6nHXQoxKiX3cfZMk9cLtZr283C3VcXc7s9s5pp7k1n2SE0uj+leEd+iakUmo5iSOibuHV9CPk3AAAAAEaQpjbxsi13JDLsw0XjDQ1GWUvvYRA03oJloHP2Ms/Fad5Xi8PIJO1Z0cbMPkzTIQwT7fmZAQAAAGC0E4kVK6MzFCrcyihIvh/L2Z41/9Xw9AeKrT/maDoW0B+QfwMAxjSJRDLAPZSVlRUUFAxKMACMcRiGvvwxp5UrXTLfi6FH7vd+xGLRIEY1MtmyGYvmuN+4XX/icrmmYwF9BvUnAIAhgWHY1atX5XJ5bGysk5PTsmXLhmiNcaVSWV5enpWVNW7cOG9vb4RQRkbG0aNH169fz2azn7BhUlJSYmJidXX1oUOHBhLAjRs3OBzOunXrBrIT8DjZ2dnJyckJCQkIITc3NyKRKBaLMQwLDg6OiIiAxd61zLnrVQnpTR+86ctk9HMl0StXriQlJrZ3dBw4cKD7s2lpaYcOHfryyy+trKwGFumIMM6ONTvScf9vhRM8DF3s9TUdDugDOP8NABgS586dq6+vnz179rJly0QikUqlGqIXKisru3Xr1tmzZ9va2tQjFAqFwWCQSE+593/SpEkKhUKheOy9PlwudzADBf3i7e29bNkydZ69adOm9evXR0dHz5gx4+TJk9u2bXvCjw+MOgKh/ODvxVMCreyt+59KTps2TSgSPu4PDoVC0dfXJ5H7f2Z9pAmbaGVvrb/j53wM03QooC8g/wYADIkbN24YGxsjhFxcXNauXfvUbLjfxo0bN23atK4jXl5e27dvNzExefKGeDyexWI97lmhUPj9998PTohgYHA4nDr/xv2/A11wcHBQUFBBQUFRUZFGQwOD6difpQihqc/YDGQnBALBkGX4uGd9fX337t1rZmo6kJcYaWZPdcov4SXebdJ0IKAPIP8GAPRBL2ud5XI5n8/HDVe/XiJxkEvpFArFvn37mprg/9lI0f1YMjU1RQg1NzdrIhww+FQq7EpCXUiApc5YWt5yUFib010cmX/F1Wo6ENAHcJQDAPqgN7XOCQkJOTk5CKHU1NTGxkYzM7PQ0NDk5OT4+Ph169YdOHCgvr5++/btKpXqzJkzRkZGra2tAoHg/fffp9Pp6j3cv38/MzOTQCCUlpaGh4dHRET0PkKhUHjnzp2UlJRp06ZNmDBBPaiuUZFIJI2NjeHh4eHh4V2L0Xk83uHDhx88eGBiYrJy5Uo2m52amlpTUyMUCg8dOmRhYfHiiy/2+TsFhlhRUREOh3N0dHzytIKCgt27dwsEgpdffnnevHkIodzc3F27dr344otz5szh8/ndD0Iej9f9cG1ra7t69SqbzS4qKpJKpRs2bBiWdzmGZOa3cfjS8W5PuWzVeyXFJSdPniguKXFyGrd82VJTM7OOjo7bt28nJSW98MILgYGB6mm3b9/Oyckhkck1VVWOjk7z5r1GJJGqq6vj4+Nvp9ze+tXW69evx8bGUqnU95cscXFxOX7817T0O0qF4oMVK/zGj1fvhMfjnTh5wtjIuLWlhS8QrFixksGgI4QqyisuX75sackuKCyUSqVbt2593OAA+bqZ/nG1qEOk0KNBXjc6wPlvAMAgCw0NXbhwIUIoICBgyZIls2bNqqysjImJqa2tvXXr1qRJkwwMDBQKxd69e8Vi8SuvvLJkyZLm5uZjx46pN09MTExMTHznnXcWLVrk7+9/6NChvLy83r86j8erqanJzc3tLABtbW3dvHnzyy+//OGHH1paWh4+fHjdunXHjx9XPyuTyS5durRgwYItW7Y0NzefPHkSIRQSEmJra0un05csWQLJ98hRVVVVWVmZlZW1b9++ysrK995776l30bm6ur766qsIIXt7e/WIm5ubvb39nDlzEEI9HoSPO1wjIiJmzZq1atUqshZVD48cWYVcMyOaMYs2KHtrFwji4mNnzp4997XX8nJzPl27ViqVcrncmurqrKyszj8Oly5funjx4rvvvfvO22+vWr0mKTlpw8aNGIYZGBi0trXV1dedOXMmKCjowIH9dD29fd9///PRo89Ne27/d9+ZW1j8+OOPnS+3Y8cOiUg8b968D1asaGxqOnzksHp8+44dU5999pU5c9Z+9hmJTHrC4AC5jzOSy1X5pbxB2RsYBpB/AwCGnI+Pj7Ozs0qlCgkJmTJlytdff81kMhFCNjYPCz2tra2rq6sRQgKB4OjRo/Pnz1fXG0RGRk6cOFE9uZfYbHbnaW+1a9eu6enpqYvRX3rpJfVuo6Ki1M8SCIQ33njDwsLC2traw8OjvBw6eY1cV69evXTp0u+//56Wlubr69uZUj/ZlClT9PT0kpKS1A+zs7M7z32ing7C7ocrg8FoaGhQHxtEIvGR+w3AoGhqFbMM+tnzpDsCkbh48RK/8eNfmj379QULOBzOjes3rKysJnb50fP5/JMnTj4/bRqRQEQIMRj0V+e+mpeXlxAfz2AwXJydEUIvvjjTwcGBSqUFBgc3NTY+9+xzVlZWOlTqxIkBTY2NAoHg4b5wOFs7O/WXtjY2VRUVCCGFUlFfX1dWWooQIhGJM2a8+LjBgdOjknQoxKZW8aDsDQwDuE4BABgOBAKBQCCYmZl1jmzatAkhJJVKExMTS0tLMQxDCBUWFmIY1nnrJJ1OX716dT9eq+tDDocjk8nUX1tYWNDp9M5OKZ2Bqb/W1dXt6Ojo68s5Ojq2t7f3dSvQD0uXLlV/UV1dvXPnznXr1q1Zs8bPz+/JW5HJ5NDQ0GvXrrW3t9Pp9Nu3by9atEj9VI8HIep2uBIIBC8vr2PHjlVXVy9YsEDd5vKpMAw7dOjQALtbjh00lifd8oVB2xvt3/Po4eHhx48fLy0rRQjh8f/+cSgsLJRIJMZdbtSeMCEAIZSTmxs2ZQoej0cI4fEPbzxQ3wFMID7cXEeHihDi8/kMBgMh9HV0NEJIIpHEx8eXFJeoEIYQIhKIvj4+h48crqyuXBi1aLyv7+MGB4W+HrmVJx2svYGhBvk3AEAzVCrVpUuXGhoaZsyYUVhYWFJSghCqqalRKBQYhg3ivZs+Pj7Jycm5ubmenp5CoVAikfj4+PQ4s38vOnXq1IEFCPrM2tp6wYIFe/bs+fXXX5+afyOEIiMjr1y5kpiYGBYWhsfjdXV11eM9HoQ9+uijj/bt2xcTE5Oenr5q1Sp3d/envigOh4uMjPT09Oz9+xrL/ozlcsTyodgzi8UikymdH8I7NTe3IIS6fnjWZzAoFAqny+fzTrieHnZ+YFOpVOfOn2uoa5g1e7aT84POtjyfrl27c8eOG9dv3ElNW7t2raeX1+MGB04kkTN0h6rNFBh0kH8DADQAw7BvvvmGwWCsWLGi6ziVSpXL5bW1tV3rehUKxUA6nEyePJnL5e7fvz88PJzD4Xz00UfOzs79Dx2MDHZ2dgihxsZGpVL51KWd2Gy2q6trXFwcmUwOCQlRDz7uIOwRhUL54osvkpKSTpw4ER0dvXPnziev7qTm4OAQFBTUi3cD0N2ywoqMoepmg8Mha2vrRwbVXQibGhsfGbe07NvSPCoVtnnzFn0D/dWrVj3yFJlC2bxlS3x8/NGjRzdt2rTvu++srKx6HOzjG3qUQqHqEMlNDQetgAcMNaj/BgBoQGlpaXZ2dudJRKVSqT6T5ODggBA6c+ZM54mlxsbG1NTUgbyWUqns6OjYtWvXa6+9tnTp0keqwx8Hh8MplcqBvC4YRFi3xUXq6+sRQmZmZr1cVzUyMrK6ujoxMdHDw0M98riDsDu5XH7r1i2EUEhISHR0NIZhfbonGPSGgzW9vlkolg7+L11Tc5NSoez83NXJ2cWFRqOlpaV1jrS2tkql0okTA/q0/5KS4vv373n+/7hSKRTqA0khl1+/dg0hFBYWtmvXLgxDubm5PQ4O5N2pldfyMQzZW9EHviswPCD/BgD0gaOjo6ur61OnSSQShJBU+m8xokqlUqlUj2S0CQkJ1dXVcXFxNTU1fD6/qqrKzMzM19c3IyNjy5Yt165dO3ny5IkTJ4KDg5/8cmKxGCHUuXP1hWa5/OG17IsXLz548CAnJyc/P7+srKxrx2iFQtE5Tb1hZxLGZDJ5PF5lZWV+fn7XNwKGH4Zh6h9x5w+ipaVF3atE3VKwNwIDA3V1db28vB6pMup+EPL5/O6Ha1xcnLppBovFotFovbz1E/Re6ARThEM5hYNwChxHwItEIvWPD8Ow38/8Pu/1eZaWlgghmUyK/v/HgcGgL1y48EFBQXZ2tnrDv/76KyI8Ql0Qol5aVfX/Y0C9t84iFvXB8PCvBw4hhGJiYysrq27evFlVXcXj8SoqK7k83s2bNx8eNoYsXV2a+vxCj4MDlJnX5GKvzzYdnO4xYBgQNm/erOkYAACjhoODw1Pz74qKigsXLlRVVXE4HAaDYWRklJaWdv36dbFYLBaLDQ0N9fX1DQ0NeTxeTk5OSUlJQECAh4dHZmZma2trcHBwcHCwUCgsLi7Oz883MzN75513KBTKE16usrLywoULdXV1YrHYxMSEz+dfvHixsbFRIBBYWFgYGRmJxeKbN28mJycnJCTExMRcvXo1LS0tICAgLy/vn3/+EQqFeDzezs7u/v37V69eVX9ycHZ2NjExyczMzMjIGDdunK2t7SB+D0GnpqampKSk2bNnP2F51Ly8vIsXLxYXFyOEMjIyMjMz//nnn5s3b7LZ7KVLl/r2+vY1AoEgEommTp3aeWfe4w5CpVIZExPT9XBVqVTx8fHp6elcLjcpKSksLMzf3/+p7+XixYve3t6QqfcSmYQvKBPklXACfSwGePeHrY1dS0tLzK2beQ/yc7JzfHx8np/2PEKoqKjo3PnzDfX1fL6AzWYbGxs7OTnZ29tfvnSppKS4sLCIQadHLVyIw+GKiov+PP9nW1ubWCy2t7Orb2y48OefLS2tYpHI1tamubn5/PlzLS2tEqnUwc7OxsaWx+Nl3c8qKioMDg728va+m57e0tISHDwpITEh9fZtTltbfEJ8eHjExIkTVSpVTGzMI4MD/NYJRfI/rhbPfd7Gy7kPraKAZuEed7kNAAC0Q1JSEpFIdHFx4fF4EolEIpGUlpYqFIr58+drOrSxLjs7Ozo6+tixY127VYxS3d9LVFTUW2+91afVo8a4kkrBG2uT35zt5uehVevDD7WzV4rySlov7A/TpcJNfaMG/KgAAKPAO++887inli1b9oQOGFVVVb/99tvBgwcRQp19xMeNG5eYmDjoQQJN6ffhAUYUJ1vGzCmWl2NKXexZujRo5dErlXWClKz6De97QfI9usBPCwAwCvz888/927CyspLD4Vy4cGHy5MkGBgZCobCkpCQnJ+f1118frNjKyspkMllvyuLBEOn34QFGmg8WuKRltx47n7d0gU9n723wOIJ22dGzuRM9jaaHPr0bDxhRIP8GAGizkJCQpqama9eunT59WkdHx9LS8tlnn124cOEg9he/ceMGh8NZt27dYO0QgDFLn07es9b/7XW3z/5TNHe6y+D9mmohqVTx87kcOo0Y/ZEvHr5Tow3k3wAAbYbH4+fOnTt37lypVMhQiDAAACAASURBVEomkwcx7QYADAUnW8ZXH/l+vueeQoG9PtMFfmd7JBTJD57OFrRLf/oykA7L7oxC0H8QADAmUCgU+EcOwKgQOsF016f+WQXNR8/lSaUKTYcz4rTxxN8dv6fixHoY3EiJv5SZmSkUCjUdFOgbOP8NAOgDqHUGAAyDYF/j/RsCPtmRuevI3YWveLDN9DQd0UiRVdB85q9CtintnVcjiwtz0tPTL126hMfjbWxsXP6v817zUScqKkrd7F/7LFmypGs3JMi/AQB9ALXOAIDh4ePCOrU7ZP3erD1H784IdwgNsBzjd2SKpcrLt0pSMuvnPGfzcZQbmYSPmDIJIcTn80tLSwsLCwsLC2/evKlQKJhMpouLi7Ozs4uLi52d3ei69Dd16tTORWq1xoEDBx4ZgfwbAAAAACOLUokJJQoKmbBxmdfv/1Seu16Wcq8uMtCGaUBBCMnkKkdbJpVC0HSYwwTDUEZuw18xZTiEtq/2Cw806/qsvr6+n5+fus+mVCqtqKgoKioqLCz8448/RCIRlUp1dHT08vJydnZ2cHB4wlpXI4S9vX1QUJCmoxhk6h64XUH+DQAAAAANuF/A+fbYA5lCJZEqMQx1COUIIbFUKVeouk9ubhWd+rsAIYTH4+ZOdx47yXdJJfdqfHlFreDlqdZL5zsznni3JYVCUZegzJo1S6VS1dXVFRUV5ebm/v3337/99huFQrG1te0sU9HV1R22dwEeAfk3AAAMiKOjY3t7u6ajAGD0cXc0qGsWCTrkvd+EgMNhGFZaxbO31jcz0vL0sbiCcy2xsrSK5+9uuPmbSS72+n3aHI/HW1lZWVlZRUZGIoSampoKCwuLiooyMzMvX76Mw+EsLCzUZSru7u5GRkZD8yZAzyD/BgCAAZk6dWpubm5TU5OpKSyaDUAfkEn4ac+w/7hW2cv5Vma6u9b61TWKfjxTvO3H9HH2zCBfC28XYy2rC1coVPceNCWm11bXt3u5MH/YFDjBw3DguzU1NTU1NQ0NDUX/LRmPj48f7SXjoxHk3wAAMFCnT58uKytzc3MLDw8PDAwc+RWWAIwQL06x7GX+7e3C3PmJP5NBtrekT/IzScxoOnut6tj5PJa+zkQfcz8PU2MWbYiDHVoYhqrqBBm5DXdzmhQq1dQg8y0feHk4GQzFaz2uZPz3338Xi8X6+vqOjo7qdNzR0ZFIhFxx8MH3FAAABio6OjovL+/WrVs//PDDzz//HBwcPHXqVDs7O03HBTQmJiZGIpEwGAxNBzLSudjrO9kwSqoET5723DMWG5d5k0kPFy3B43BhAWZhAWY1jcI/b1Zfia+9Gl9hZa7n42bq62ZixKQOfeCDBsNQdYPgfn5zVkEzhyexsdBb/JrTi2GW+nTy8ATQtWRcqVRWVVWpy1T++uuvwS0Zl8vlcG6iE+TfAIA+gFrnHuFwOE9PT09PTx6Pl5CQEBcXd+vWLT8/v7Vr12o6NKABsbGxP/3005w5cyZMmKDpWEa0irqOK/G1dU2iJ8zB4dC7c5wWzx3X47NWZrofvum64g2XnCJuTGrDjZTav2LKjFlUJ1umsz3LxZ5F1RmheU67UF5axS0u5zwoa+PypWZG1GeDzSKCzH1cWBqMikAg2Nvb29vbT58+Hf23ZFzdZbyzZNzDw8PQsG9VMZs2bZo0adLzzz+Px8Pij5B/AwD6YurUqZoOYUQzMDCYNWvWzJkzCwsLBYKnnNIDWikuLu7QoUNz5sx59dVXNR3LCNUhUty8XX8loTa7kPvkmWQSftNy72cnWTx5Gh6H83Fh+biwPnrL7X4B5052S2p26/HzDQiPbMzp1myGDVvfls3Q7HlxDMMamoQVdYLKWn51vaChRUgm4b2cWQtm2AX7GDvZjsRLJV1Lxnk8XllZmbpkPC4uTqlUmpqaquvFnZ2dLS0tn1wy3t7eXlZWVlZWlpKSsmTJEhsbm+F6EyMU5N8AADDIcDgcLBE6NiUlJR09ehSS7x6pMCwjt+2vuJq4O40y+b8dBo2YFD0aqbKu45H5xiydPWv9+9T0g0DA+XsY+nsYLl+AuAJZRm5rdiE3p5ibcrdOocToNJKFqZ6xIc3cVM+MRTMz0aXrDlWNB4ZhHL6kqVXc2NzR2CZqaumobxZKZUoqhejqoP/cM+bj3Vi+riyd0dNF0cDAoLNkXCKRlJSUqHPxY8eOyWSyp5aMFxUVIYS++uqrU6dOffbZZ88+++zrr79OoVA08E5GBsi/AQBgWF28eNHS0tLX15dAGDX/ekEvHT16dObMmZB8P6K5TfJPUt2FW9VdS03weJy/h+FLkdZhAWbpOa0ffp3edRMnW8aetf5mRv0/Y81kkJ+dZKE+dy6VKQvLBQ/KeOU17WU1HVkPmjtEcoQQiYhn6esY6OsY0CksAx0alaSrQ6RRSTQqiUYlEol4HQoRIYTD4dTtxlUYJpEqEUKYCpNIFXKFSiiRi8QKkVguEis6hDKuQMrjS7gCCbddqlJiCCEjAx07K70AT5ajtY27k4GDFV0LurXo6OioK+4QQl1Lxi9fvtze3t61ZNzV1ZVGoyGECgsLLS0tnZycNm7cGBMTc+LEiXv37i1evFi9kzEI8m8AQP9FRUWJxeLu48ePH6dSe/jHqa3z161b5+3t3X28OwzDCgoKTp8+bWBgEBoaOmXKFHNz895sqMUWLlyo6RAGzezZs+fPn6/pKEYKmVyVeLfpwq3qjNxWDPt33I6t90KY5YtTrFj6D08/B3obmRjqNLdJ1A/DAsy+XOkziCvsUMgEbxemtwuzc6SFK6mqEza2ihtbxU2t4sZWyYPSFkG7vEMk73H1n6fun65LMmCQzYyp490MTI10TA2pFiY0W7Yu/YnL5WiBriXjGIbV1taqz4vfvn370qVL6mddXFzu37/v5uaGEMLhcJGRkX5+fkePHv3qq69CQkKioqLodLqm38dww2FdfycAAKAv0tPTlUpl9/GAgIAeT+5q63wDA4M+FZy0tbUlJyffuHGjpaXF3t4+MjIyJCRkDF6K5fF4BQUFmo5i0NBotF5+DNN6BeX8qwm1/yTV89tlnYN6NOLUYIvpoewebzH88XTR0T9LEUJRsx2Wve6M11z/abFUKeiQCTrkCiXW3iFHCKkwrEOkQAjhcIhOIyGECAQcjUrUIRPouiSGHqmzMQvoisvlFv5fZWXlBx98EBIS0nVCZmbm4cOHlUrlG2+8oa4yj4qKeuuttyIiIjQU8lDp/r4g/wYAAM1QqVTZ2dmxsbF379718fGBZilgtBN0yGPSGs5eryqp/PfmYzwO5+ls8EKo5bQQ9hNOadc1ieZ8GL/mbfdXnh3rd+Zpn/z8/C1btvzwww/dV9kUCoV//PHHtWvXfH1933333dWrV4+R/BvqTwAAQDPweLyvr6+vry+fz+/oePTmMwBGC5UKu5vXduFWdXx6o0L570k9E0Od50PYL0Vas02fvjIO25R2avdkO7beUEYKNKOoqMjQ0LDHJe51dXUXLVoUEBDw008/rV69uscLjFoJ8m8AANAwfX19ff0+NHkAYISorOv4O772r7haDl/aOUgm4Sf7m74UaT3B06hPVSSQfGurwsJCdYWeUqnk8Xitra1cLpfD4XA4HC6X29rayuPx2traZDIZQujSpUtubm5af2MM5N8AADBCYRi2bds2Z2fnsLAwFkuTq3IA0JVQrIhPb7yaWPfIjZWu9vrTQ9nPh7CHbe1GMPKpVKri4mIikbh48WI+n68ue8bhcPr6+kwmk8ViWVlZeXl5GRoaMpnMXbt2TZs2bSiS7+zs7OTk5ISEBISQm5sbkUgUi8UYhgUHB0dERPR4w/2QgvwbAABGKLlcbmFhceXKlT/++MPX1zc8PHz8+PHQtRBoUEE5/8LN6mtJdWLpv3UCDD1SRKD5nOdsxo3IRWSAZnG5XD8/P3WqbWhoaGBgYGRkZGBg0OOfMjweP0R3ont7e3t5eaWnp4vF4k2bNqlXC7p9+/Z3332XkZGxYcOG7j3LhxTk3wAAMEKRyeSoqKjXX3/97t27sbGxu3bt0tfXDw0NDQ8P1/qLs2BEaeFIribWXbxVXfuYBt5EwqjvaQ2GiKGh4YoVKzQdBULqPu5Uqlgs7lyqMzg4OCMjIyUlpaioyN3dfTiDgfwbAABGNBKJFBQUFBQUxOFwkpKSbt68KZPJFi1apOm4gPZTN/C+klCbmtWi7HJjpS1bb0aY5YwwS0ODMdc0E4xquG53JJiamiKEmpubIf8GAADQAxaLNWvWrJkzZ0okEk3HArRceU371cS6SzE1vC4NvHWpxNAJpi+EWvb1xkoARqyioiIcDufo6DjMrwv5NwAAjCbqS6g9PiWXy0kkLV9sDwwpgVAek9pw/kZVUYWg67irvf5LU62f3MAbgNGiqqoKwzAej5eQkFBZWfnee+9ZWVkNcwyQfwMAgDaQSCTLly/38PCYPHmyr68vHg8L8oHeUmHY3dy2C7eqEzKauq6+bszSmT6ZPTvS2rIXDbwBGC2uXr0qk8kaGxsrKyuDgoLs7e2HPwbIvwEAQBvg8fjXX389Li5u+/btpqamYWFhYWFhhoaGmo4LjGjVDcJrSXV/x9c2tIg7B9UNvKdPZgf7mhDgxkqgdZYuXar+orq6eufOnevWrVuzZo2fn99wxgD5NwAAaAMymRwREREREVFTUxMbG3v16tWzZ896e3vPnDlzmO8rAiOfVKZMymy+cKv6kQbedpZ6L4RazoqwMoAG3mAMsLa2XrBgwZ49e3799VfIvwEAAPSflZVVVFTUggULMjIy4uLiGhsbIf8GndQNvK8n14skis5Bhi4pIsj8lWdtnO2ggTcYW+zs7BBCjY2NSqVyOFdXgPwbAAC0EJFIVHct1HQgYERo4UquJtRdiq2paRB2DuJxOH9Pw+mT2ZFB5hQy3FgJtB/W9XIPQgih+vp6hJCZmdkwL20G+TcAAIxF1dXV1tbWmo4CDC25QpWW1XI1sS4uvbFrA29rc93nnrF4cYqVufFwL7sNgKZgGCYWixFCUqlUvcpmS0vLsWPHEELz5s0b5mAg/wYAgDGntrZ2zZo11tbW4eHhISEhdDpd0xGBQVZR23ElofZybA1X8G8DbwqZEOJn8lKkNTTwBmNNXl5eSkqKOv/+/PPPjYyMOjo62tvbLS0tly5d6uLiMszxQP4NAABjjqWl5bZt2xISEs6dO3fy5Elvb+/JkydPnDgRuhaOdu1C+a3UhisJtdmF3K7j6gbezz1jQdOB//tgLPLw8PDw8FiyZImmA3kIfg8BAGAssre3t7e3nz9/fmpqamxs7LfffmtsbLxo0SJ/f39Nhwb6TN3A+0pCbeydRolU2TluzNSZHsqeFW5lZa6rwfAAAI+A/BsAAMYuHR2dKVOmTJkypa6uLjY2Vl9fX9MRgb5pahNfS6o/f6OqawNvEhE/0dvof+zdd0BT59oA8DeDJEAGe4W9QZbKVNnBgVqrttqKWq2r2qG19PZr7dLeDm+tV69aa2tb22qrdRREhgrIHgIiCsreGzIY2ev7I21KFcImoM/vL3hz8p7nnCTnfXLynucsDTYP9TWBAt4ATEOQfwMAAEB0On3Dhg3qjgKMlEgsyyjsGKqA9zNhFrpUKOANwPQF+TcAAABVxGJxVlZWQEAAiURSdyzgrwLe2a08/t8FvCnaGowA08hgupeznhpjAwCMEOTfAAAAVKmtrT19+vSZM2cCAgLCwsIcHR3VHdHTiMkR3sxpvZraXNXQq2xUFvAO9zclEaGANwAzBuTfYHTeeeeduro6dUcxLaxYsSIqKkrdUYzOvdRPmh5eVXcUYBCGFv6+zxxTdxSDc3Jy+vbbb3Nzc2/evPn+++/T6fSQkJCQkJDpM1lcJJa1dvLauvgtnbxOpoDdI+T0iTl9Ik6fWCiS9veLEUISqZwvlCCEiAQcAY9FCGlp4UkEnA6FoEPVoFEIulSCkT7J1FCLbqRpZqQ1TdJZmUxeWMr8I7kx7Xa7ZEABb2N9zcWBZqsiLM2MtNQY3qBOnjx569YtdUcBRmrHjh3h4eHqjuKpA/k3GDUfH58FCxaoOwo1O3funLpDGCMyzcTSIVDdUYB/aK0vRI/dlW1a0dbWZjAYDAajpqYmNTX1ypUrFy5cePPNN318fKY+GLkcNbVzK+t7K+t7K+t6qxv7Oph/XnqoramhSyORtTW0NTWoZC1TIw0CAadJxCOEcFhEIOARQiKxVHEnGoFQIhJLuXwxlyvuYnP7eWw2R9jHEyu60tch2ltSnWyoDtZURyuKNZ2MxU7phYx1Lf3xac1xt5pYPX8X8CZoYIO8jad/AW8rK6tVq1apOwowvBMnTqg7hKcU5N9g1MzMzOCm1jExMeoOYYwIRLIh3VXdUYB/YHVWS2XqDmJk7Ozs7OzsNm7cmJeXN5UTUWQy+cPanrvlrDsPWCUP2T39IiwOY6yvZWZE9vMyM9LX0tfR1NMhaY67uLVQJGFyhEwOv6ub19LZn3q781xcrVQm19bEezrrzXbRne2i72pP08BPVqH0fp7kZk7roAW8I4PpkUHmVLLGJK16Auno6MAwMSN888036g7hKQX5NwAAgNEhEonBwcFTsCIeX5Jb0pVR0JF1p6u3X0TR1rC10AmbZ2VrSaMbkfGTkAQTCXgzI7yZkTb668uFRCpr7+LVNnFqG3vOXas78WuFFgk/b45hsLfxvNlGE5UNy+TyexXshPSWpMwW/oAC3vo6xIh5ps+EWThYUSdkRQCA6QDybwAAABOmq6srISEhLCzMwsJizJ1IpPLsO51xac05xZ1SqdzWnBYaYDnLXt/YQHvqJ13gcVhzE7K5CTnIxxwh1MXiPahmlVV1f3y8BGGQj5vB8lDzEF8TgsYYvwx0MgWJmS1/JDe2dPCUjVgsxttNfyXDMsTXBA8FvAF44kD+DQAAYMJ0dXUVFhbGx8c7ODiEhYXNmzdPU1Nz5E9v7uD9nlifmNHS2y92sNZZs8RxlpMhWXMazbgw1NMK9tUK9jXnC6UPq7sL77d/cOyuFhG/cL7pmsXWdpaUEfajKOAdn96cU9wlk/09+9+GTl4aYr481FyPRpycLQAAqB/k3wAAACaMq6vrsWPHamtrk5OTz5w588MPP3h7ezMYDDc3N4zKc9elVZxfrtam3W7Xo5HmzaX7eZrq0qZ1uXFNIm7OLOM5s4x7+0WF99tz77b9kdzo52G48Vk7Hzd9FU98WNuTkN6cmNna0/f3hZVkLXzEPDMo4A3AUwLybwAAABPM1tZ2+/btUVFRGRkZqampn3zyyQcffODu7j7owpX1vf/7pTz/XpeVGWXjStfZrkaqM/XphkomhAVYhvpbPqhm3spt3LU/z81BZ/dGl0cy6V6uOCW37dL1hsr6fxTwdnfSWRpsvjiQrjk9Kh4CAKYA5N8AAAAmhba29pIlS5YsWVJbW2ttbf34Ap1Mwde/VSRmtFiYUV7b4OVoM4NP/WIwaJaD/iwH/YbW3muptds+yA32MXljg7O5sdagBbyN9ElLAukrGZZ042lXwBsAMNkg/wYAADC5bG1tH2mRy1FsatN/zzzQ1tLYuMp1tqvxjDrlrYqVGfXV9V4PqllxKdUvvJVhZ0Epr+1RPkok4ML8TZaHWsydpYd9YrYZADBKkH8DAACYUt1s4f4TJbfvd4f6WSwNtZ2MMoJq52qv52zrk5LTkJj+5w2DFQW8lwTSaRSCemMDAKgd5N8AAACmTlk1J/pgERaH3bNpjrX5dLmD/WTAYjERC6xd7Q1O/nZXKpa9GuXs52Gg7qAAANMC5N8AAACmyPWs1v1flzhY6by0ym3896qcEegm5I9fn/drXPnuz27v3eS6ZrG1uiMCYFo7derUqVOn1B3FpHsqDn8AAADULimr9aP/3Q3yNV+50H5mVTgZJzweu3Glq6mR9qEfyiQS+bplNuqOCIBp6tVXX5VKpcMvNwPZ2dkN/BfybwAAAJMu7Xb7x8fvhgRYPMuwV3cs6hEx3wqPwx75+QGRgF290Erd4QAwHfn6+qo7hCkC+TcAAIDJVdvU9/7Ru/Nmm60If0qTb4VQfwuRRPqf78tszSmzXWdwsUUAwDg9gVedAwDUiM8XqjsEML2IxLJ9R++aGmqvWuw4Q2edCPj8iepq0QJrd0eDfUeLB9788qnFn7gdCwQCgbpDAKMA+TeYeFKptKqq6uLFiyUlJWPuRC6Xx8fHx8TEvPHGG8eOHXtSJ4RNQ1KptOxB9fc/Xc4vvK9oycgufHbt6/WNLaqfeD05+81/fb52w97Ji00ul5+/mPjLr1fXbHjzwOdfS6XSR1pupeePJNQRbhGYEKcvVbV18jetdsNhZ172nZaW9uGHH21/ZccE9vnichepFB39pXwC+5xxrl+//uGHH+7bt2/QRwsKCnbu3NnSAp/QEcnMzPz00093796t7kDAKED+DSZeTU1NcnLyxYsXmUzmmDu5dOlSa2vrs88+u2vXLh6PJ5PJJjBCoMLD8tqYaynf/3S5s/PPl49EIunqUoiEYYoWR4QGiCVSsVQy1ALdLPY4Y/vh5yuNza0b1j3z/juv9HF5Eqn0kRaChsZIQh3hFoHx4/SJzifUR8y30tMhqTuWUWD/9V4NCgqSSMQyyUR+/9fSxC8LtY1Pb65v6Z/AbmcWBoPB4/HkcvmgjxKJRCqVqqGhMcVRzSxs9p/v0vnz50skEolkyGMvmIYg/wYTz9HRcfHixePs5MaNG4aGhgghZ2fnd955Bw7EU8ZtlsPzKxcNbPGd6/bjN5+ZmhiqfiIWhzUyHHJKa18fd/+nX48ztitXb5oaGyKEPNycvvx3NJFAeKRl/rw5Iwl1hFsExu/c1VqCBnaBD13dgYxCf3//oa++UvyNxWL1DSa+aPccd2MTA+0fr1RPeM+T5/79+0ePHi0sLJyQPA+Hw+npDXm48PDwOHjwoJGR0fhX9KTicrnHjh1T/I3FYlXsTDA9wfWXYFLg8eN6a4nF4p6enqeqQtm0oqExwUcGsUTy0afHW1o7xtOJUCRis3sHvikebwHTzY2cNj9PM4IGTt2BjJRYIjn05Zcd7e2TuhYsBrPAmx6XWrNPLCNozIwTYSKRKDs7OycnR0tLy9/ff8GCBa6urnCUVguJRHL06NGOjnEdUYF6Qf4NpoJcLk9OTq6vr6+rq9PS0tqyZYupqSlCqKen5/z58wYGBt3d3b29va+88gqFQklPT7937x5CKDc3t7293cTEZMWKFSo6H7QTDoeTlZWVlpa2b9++EydOtLa2Hjx4kEwmjzyMqdkz019fHzctsyD5Vu7qZyOC5nsrGh9W1sZcTREIBC0tHcsiQ5dHhuBwfydYTBbnP//9/u69clMTw4/3vWptSU9Ny6+rb+7t6//80HeWlmZRa5aqWKNcLo+JS6mubSyvrKNoa0bvftnc3CThekbhnVKEUGp6flNLhwXdWE9P55GWFcvCHw81J/9udm6xBh5bVl6zfEnIM0vDHt+iQddYWV1/Mzk7NeP2mVOfHf36l+zcO3RTowMfvmFmajRUz5nZRR9/dpzPF+7etWHVsxEaeHxpWdW7H/33+ZULN0Y9OwkvznRX3djX2sl78ZkJOH9cXVWdlJTIFwjb2lsXRiyMiIjA4XBsNjstPT01JfnA/k/+e+S/zc3NR44cpVIpOTk59+7d0yAQmhoa7O0dXnhhLV5Do7j4zoH9nyCE3nvvPS8vz+9On05MTKSb0V997VV3d/eurq6DXxzUN9APCAhobGzs43KPHztGp9NXrlqlCIDNZp84caKsrMzIyCg6OtrCwmKcW+TuZHAxsaKojBngNZN+hzl69OidO3dyc3MPHDigo6Pj7+8fEBDg5OQ05kS8pqbm/Pnz1dXV9vb2W7duNTY25nK5+fn52dnZixcv9vHxUSyWn59fWlpKIBCamppsbW1Xr16toaHR1NSUlZWVl5f3wQcfpKSkpKenk0ikLVu2ODo6/vrrr4pT9Tt27PDy8lJ0MtShvr6+PiEhgU6nV1RUCIXCDz74YKjGYbclOTlZIBC0t7eHhYWFhYXhcLhBByMKhTLoFpWUlHzxxRcIoejoaA8PjzNnzty8edPU1HT79u2zZs3q7u7+73//q6en5+vr29TUxOVyT506ZWZmtnz5ckUAHA7nu+++e/DggZGR0RtvvEGnz6TfnZ42M+NrN5jpYmNjCQTCtm3b/v3vf/P5/I8++kgoFCKEjhw5wufzV69evWPHjs7OzjNnziCEgoODN23ahBDy9fXdsWOH6uR7qE7q6+tTUlKam5uTk5Pnz5+vo6MjkUhGFQZQYLI5dQ1NBUX3ZdI/p+C3dzBf3fPJ5g0r97//upUV/T///X7bqx8e/foXxaNCoejs+bhXt6/7+sgHrW2dJ079ihBaxJhvb2dJo1Lejd6mOvlGCJ39LY5IJLy95+Xvju3n8gU79xwQCESRi4J2v7oRIRQc6PNu9Lb1Lz7zeMvjoSbeyEq6kfXWG5v2vPZSYMCcL746XVRc9vhig65RX0+nsqaxrb3r5OnzUS8sP/DB6w1Nbd+c/l1Fz4Hz5z63chFCyMPDSQOPRwg5OdkYGxs8nck3QqismkMi4i1Mx/tttqur69333n1+7Zq33462MLc4ceJEdHT06e9O19bV3bh+vbGxKTEpMTAwUFdHVyIRx16NjYmJ2bpt65aXX977VnRmVuYHH34ol8tnz56zIHABBoM8PD00CIRXXtlpZGRkZm7m7u6OEDI0NDQ0Mnx58+aQkBBrWxsahfra668rk2+hSHT50uXNmzd9/vkXHR0dP575cby7BiEahWisr1VaxRl/V1NJT08vMjLyk08+OX78eGRkZElJyYcffvjaa6+dO3duDJdL9vb2ZmRkLF26dPXq1WVlZR9++KFQKORwOE1NTffv31de9hMfH3/t2rVNmzZt2LDh9ddfI4AmrQAAIABJREFUz83N/fTTT+VyOY1GYzKZbW1tly5d8vX1/eqrr8hk8jfffPPzzz8zGIwvv/zSxMTk+++/V65uqEP9kSNHwsPDV6xYsXfvXsJfl4UM2qhCd3f3xx9/vGrVqt27d5ubm3/33Xf79u376aefBh2MhtoiT0/PefPmYTAYNzc3DQ2NrVu3GhoampmZzZo1CyFkYGBgYGCwfv36wMBAa2trCoWyY8cOZfItEoliY2OjoqL279/f2dl59uzZ0b4cYCpB/g0mHZvNjo+PDwoKQghhsVh/f38Oh1NUVKR41Mrqz/tQWFpaNjY2jm0Vj3fi5eXl5OQkk8kCAwNDQ0M/++wzhNBkh/FEsrakB87zHthyKeY6jUo2MTZACL0U9SxCaMWysN27NigexeFwr+1YZ2lhamdj6T3HraKiflSr62ayL1xOXBwRiBDC4rChwX5MFicrr2gMoXI4vYePndm5bS0Wi0EIrVgWHhLoq6+v88hiQ61RX0/HxckWIbRjy1obK7rPXHdPD+fyqloVPSOEVq+IwOFwMVdTFJ0XFN5fEDB7VHvgSdLFEuhSidhxT1G4du0ahUw2NjJGCK1Z8zxCaPGixVu3bZ07Z46rq6tMJgsNCYmIiPjq8Fc4HO7sL2eXLF6Mx+ERQlQq5fk1z5eWlqanpSGEFkZEiCWSvLw8hBAWiwnwD7h7p7i/vx8hJBaJZDKpsYnJoAHgsNjNL2+m082tra08PT2rqydm3rYOjdTNnqk14wwNDVesWHHkyJGvvvoqJCQkNzf3zTff3Lt378WLF0deVRCPx2/evNnLy2vZsmVr1qxhs9mpqal0Ol152hv9ddJa8YsHQohCoaxcufLBgwdZWVlUKtXBwQEhFBkZaWNjo6mp6efn19HRER4eTqfTSSSSt7d3R0dHb2+vsrfHD/VSqbStra22tlYRj+LipUEbVUtKSiKTyYrLllauXIkQYjAYL7300uODERaLHWqLEEJhYWESiaSgoAAhhMFgfH19S0pKuFwuQkgsFstkMmNj40EDwOFw69evNzMzs7S0dHNzUwQPpi2YfwImXUVFhVQq/fbbb5Ut4eHhitMJH330EUJIKBRmZGRUV1cPdS28akN1gsPhcDicyV8D6mSH8QQbOLcEIdTdzRII/izybWlhSqOSOzpZykfxeJxyeQpZq6+fO6p13S+tlEikBw+fVrYsjwwljbhQycBQS0or5HKZ8iJLGo3y2f49jy+mYo1YLBYhhMf9eZ5CS1OTzxOo7tnIUD8s2PdGcvaubS/QaJSUtLwtL60eSeS93RXxJ3yGX25GMUXIWn83Qn7j7IfJZApFf77l6HRzKpXS1d2l+FfxMTc1M1P8W15eLhAIDAdct+fj44sQunf/fkhoqJu7u4mx8a3U1ODgYIRQXX29VCbNzspetHhRdk7OvHnzhwoAj8cr3zNkMrl/lO/qoZA1Ne6mfr4meWaXrbCwsLCwsHjuuedKS0t/+OGHixcvIoTIZHJjY6OlpaXq52ppaSn/Dg4O/vXXXxVZ48BPaFVVlVAoNBhwFezcuXMRQqWlpYGBgYoPqXL2C4lEGvh0xb99fX1UKhUNcajH4XCKmR6NjY1RUVGenp5DNarGYrFEoj9rupuZmVEoFGUFsEcGI9Vb5OrqamRklJGRsWDBAoRQQ0ODVCrNzc1lMBh5eXl+fkN+mhRrUfytra2t+GIJpi3Iv8Gka2lpIRKJO3YMUkBXJpPFxsa2tbUtW7asvLy8qqpqDP2PsJPJDuPp4efjdSMlp/BOqfcct/5+nkAg8vcdanAa9YnP+sYWTU3iu9HbxhkkQqi2rkkqkcnlctUzU8ewRtU9r31+6c3U3NhrKS+uXdbT06ecL66aJsVsVvA7I49hRrie3drVrz/+fubOmZOenl5SUuLp6cnlcvkC4Zw5cwddsrOzCyHU19enbKFRqUQikcVkIoQwGExoWNiFCxfYbHZrW5ujowMOh01Nu7Vo8aKcnJzo6LdGEswEXm8oEErMXVY8t3CYJHWaqK2tjY2NfbxdLpdXV1dnZWXl5uZyOBw7OzssFksgEIZNvh+hq6tLIBCUKaxSV1cXQmhgNkmhUIhEorL63kCPfCQV/yrnsQx1qN+zZ8/Ro0dTUlJu3769d+9exWSPQRtV8PLyysrKun//vru7O5fLFQgEynnno9oiDAYTHBx8+fJlDofT3t5ub2+PxWIzMzMZDEZ+fv4bb7yhOoxB9wOYhiD/BpOOQCCwWCwmk6mv//dI3NfXRyaTP//8cyqV+vrrr4+5c7lcPsJOJjWMp8qShQuYTNaBz08uWxLS1c3a/8FrHm6OE9U5kUTs7GJ1djGNDP9+mXp6+mi0Uc8h1tbSEopE9Q0tNtbmykaxRKLxz+I8Y1ij6p5dnWw93Bwvxdy0tDSbHzBnhNFqECmm9owRLjxTaFXXd3Im4NtsaFgYi8U6fPhwREQEk8n619tvu7q6DLqkibExQujx6iXm5n9eLhnOCD9//nx6RkZlReXWrVvu3bt3+PDhe/dKdHV1CQTi+EMdlV6u0NvNKyDAaYrXOzYEAuGR/Lu5uTk3NzcrK6utrc3Q0DA4ODg0NNTMzOzkyZMsFmuoflTAYDCPX9iqqEL4eK2P0V5cqGKwIBKJ7733XmZm5i+//PLpp59++eWXdDp90EYV/QcFBbHZ7OPHj4eFhbFYrD179jg5Df7KDrtFISEhly5dys7Orq6u3rhxY2lp6fHjx0tLSxVfUUa11WDagvnfYNJZWlrK5fJz584pW3p6em7dulVdXV1SUqI8qaC4l+FoOx95J5MaxlNFIpX09HF/Of3F9pef3/evHcpKI6phMFipdPibKNnZWMrl8q+//U3Zwmb3xielI4TQ46+LyldKMXv71Pe/y2R/Ltbc0pGalj+KNY615/UvLO9msv/39dmwEH8V/TzxbOjkPq6I3TPeKc4SqaSvv/9/x46tX79+9+43/P2H3KtOzs5aWlqKGd4K3d3dQqHQz89X8a+xkbGbu3t8XByRSNTT0wsICCCRNA8d+iqCEaF8ChaDlQx9G6mJIhRL27v4Vmbak72iCcdkMhMSEj744IO9e/empqZ6eXkdOHDgxIkTUVFRZn9NBBqDrq4uiUQSEBDwSLujo6OmpqZiPrQyAKFQ6O09oiOP0lCHerFYnJycjBAKDAxUXARZWlo6aKPq/qVSaX9//6FDh9auXbtz586BU9hHu0WGhoaurq6JiYkEAkFXV9fX15dEIv3vf/8LCQlRPgWDwcBtoWc0OP8NJoXi+hvF0cHDw8POzi4rK0ssFvv4+LS3t1dUVOzZs6e9vR0hlJ6ebm9vX1NT09TU1NPT09DQoKOjo/gJUlGcZCQG7UQmk8lkMqlUqpgSN4YwaDTaJO2faY7L/fvlQ3+9ECLxnxnJ2d/iikseOtpb6+vRNLVIOlSKcia0SCwZ+POxSCQSSyWKeRqGBro5+cWV1fX9/TxXZ3sSafCzOL5z3VydbG+k5IhEksD53i2t7ffLqg68/xpCiMcXIoT4gr/7f7xlYKjubo4Bvp4Z2YWvv/Xv0GC/9o7u5ub2Tz/e/chiKtYokUoRQpK/vjYIRULFxHcVPSvMD5hja2NBNzOiUcljewmeDLNd9bU1NUormYHju//O5UuXS++X2tra6OrqaZI0yVSKyV+XoMmk0oEfcyqVsmnTppMnTyomqyCE4uLiwsPC3T08lL1FhIcf/u9/33tvOUKISCQuWDC/srLC3sFeuYCenh6bza6rrevn9js6OkrEYqFYrHxUKBJJJZJh5zUNq6KGJZHK5s+ZYbeY2b9/f3V1NZlMDggIWLdunbOz85j3AxaL5fF4itdOLpdfunTp+eefV5wDVhxGxGIxQohCoaxfv/706dOKqR0IocTExODgYEUmrThMKWeYKP4V//V6Kf4deMOgxw/12trat27dWrhwoeIuNlpaWra2tgihQRtViImJefDggbW1tY6ODolEolAoyvsHPTIYqd4ihdDQ0OPHj0dHRyOEiESiv79/dXW1nZ2dcgFdXV0Oh1NfX8/lcu3t7SUSiXjAu1QkEim+YMBElGkL9/HHH6s7BjCTJCcnGxsbewwYzB5XX1//xx9/tLS08Pl8IyMjIyMjf39/FotVVlZWUlJCpVK3bNlCo9H09fU5HM69e/eqqqp8fX3d3NyKioq6u7tNTEzi4uIaGhpYLBaVSjUwMFBx88uhOpFKpSkpKXw+n8/n6+vr02g0DAYzqjDmzZun4i5CI9kP01BHXYaY32VsoSrsyur6n3+92tDY2s/lm5kaslg9Z8/HNbW0c3r6LM1NjY30uVxBTFzyzZSchOsZV6+l/n45KTU9P3iBd2Fx2cU/rvf387BYjJODTU5+8YXLSXy+ACHk7uZoamKYnXsnI6vI3dXBwd5qqLVjMJiQYN+ubtadkgf5hfd0aJS3dm/S06VVVNb/8ltMdU1jZxdTV4dmYqxfV9/ySEtVdcMjoYYE+vb1c0vLqorvPqCbmUTv3kQkEsseVP9jMWODQddYeKf03IW43j4uny9wdba7lVFw5Woyl8dHCHm5O4cG+z3e88CtaGxuW+A/Z+AEFRWY7RVyOY7uHDnSF3KGwGIxVQ29pZWsgNljPy2KEOLz+IlJSenp6SkpKdevX4+7ejU7OzsgICA/P/9aQjyfz+fxeIaGhoovzA4ODra2tldjY6uqKsvLK6gUykubNg3MQuh0MxaTtXjJnxUtaDSaoaGRooyGgoGhYcHt23l5ec7Ozh0dHXFxcVwuF4vF2tnZFhYWxsbGCgQChJCziwsOO/bfkK+l1proE9cssR5zD1Osra2tqKjIyclp3bp1W7du9fb2NjQ0HDS9Kyws5PP5imJTKlhaWjKZzFu3bj18+LC0tNTDwyMiIgIhVFVVFRMT097e3tvba2ZmZmBgYGdnZ2Njk5CQUFNTU1lZSaFQoqKiMBhMVVXV1atXWSyWQCCwtrZub2+/evUqk8nk8XiWlpZdXV2xsbGKU8vW1taWlpaDHur9/PyysrJu377NZrMzMzNDQkK8vb1lMllaWtojjao3h8/n37x5MysrS/FGTUhIyMvL8/X1LSwsvH79+sDBCCE01BYpezM1NWWxWIodgv58lxoOzL8NDAyKiooKCgocHR27uroSExMV71IbG5vi4uKEhATFu9TJyQmr8l0aExPj6ek57LcLMOEw8FM7GJV33nnHw8MjKipK3YGo2QzdD/dSP+EyH7gHjCvs68nZeBzO09OJ2d0jEAp4fOGDh9ViifSVLWsmKs4nwBvRn335WTRxZJM1K4qvSmUE3xXHJzuqqfewtuel/8va8YKnq8PYL8RMS0vD4fBus2ax2CyhQMATCCorKqQS6YaNGyYw1KnU1NZ36HTBoX95B3kPXktuGuJyuRoaGiOZf6yY/71v374piGr6yMzMxOPxzs7OHA5HIBAIBILq6mqJRPLiiy+qOzRVXnrppY0bN4aHh6s7kKcOzD8BM8CWLVuGemjXrl2Kyk1galTVNHz97W+xvx9HCBno6Soa3V0dEm5kjryTJSsHqUKj8P7bO+bPG+k1i9NWUXGZk6PNCJPvJ5uLLS1wrvG1tFpHW11lJcdRqa+rO3PmjOJWKbp/veVcnJ1TU1InMM6pJJejqyk1LrY6gXNnTPKNENLWnnlT1SeWipEoMjLy5s2b33zzDUJIV/fPd6mjo2NGRsYUBQdmGsi/wQww8AZmQL2qaxq7ulk//xq7OGKBnh6tv49X9rCmoOjeK1tHcY4n8Y9TkxehGt0rrTj41WkbG4va2qaTRz9UdzjTxZ6NLlFvZ11LrX02wn74pR9TW1fHZDIvXrwYGhqqo6vD4/IqyiuKS4pf2vjShIc6NW7lN9Y0sL/7ZB5MzZ1ZVIxE6enpLBbrjz/+CAoK0tHR4XK5VVVV9+7dW7du3VRGCGYQyL8BAKOwKHx+S2vHpSs3vjl9QVOTaG1lvnpFxBu7NiruBPmUo1LJQpG4orLu/Xd2jKFg4pPKwlT7/7a7fXz8rp2VjrujwfBP+KeQkJD29va4a3E///wzSVPT0txiydIlW7dsm6FvufrmnmsptTtecHJz0FF3LGDCBAYGdnR0JCUl/fbbbyQSydzcfOHChZv+eeEBAANB/g0AGAUsDrt103NbNz0nEIiIRA0YXQaytqRfOndE3VFMR5FB9JJy1k+Xy7a/4O5oozeq52Kx2HXr1q1bt04oFBIIhBn9lmtu7z/12z1/L8ONK+BytycKFotds2bNmjVrnoB3KZgaUP8bADAWJBKMMWAU3tnqFuZn/N2F+1V1g9y2cCSIROKMfss1t/d/fbZ4lj3t4FtzsDN5Q4AKM/1dCqYM5N8AAAAmHRaL+fg1r0Bv46/P3c0ualV3OFOt5GHX0TNFLna0r97xJmjAyAvA0w7mnwAAAJgKOBzmk9e9Thpp/hJbXtvIDptnJZXJZVK5WCK1t9J9Uk8aymTypIz665l1qxdaRW+ehcM9odsJABgNyL8BAABMgOSctpS8Nplc3s+TyGXyfp5EKpNz+RKZTM7962/lwgX3OwrudyCENIm4zc+5PanJd2sn97erD9q6ee9ud1/JsFR3OACA6QLybwAAABNAX4eYnNs2qqdgEJrlYGBhSp2kkNRIKJQk5zSm5DS62NEO/1+gpenTXjwbADAQ5N8AAAAmgJeLnqWpdmMbd4TLz7LXWbTA7McrNZ+cyGPMtwzxtcDjn4SJ0TKZPOdOa1JGnUwmf3298wuR1jO0VCIAYPJA/g0AAGACYDDomTCL4+fKR7JwmL/J/te8SETcinCLX2Jrz16tzchvDvI1nz+XrkmaqQOTUCy9fbc9Lb+R0ytcvdBq63P2NArcAxUAMIiZepgDQO2qqqqys7P9/PzwePgcAYAQQstDzb85XyGRylUv9kKk9ZubXBU1+LRI+B1rHVcvtPr1Wu3lGw03shr8vUznzTUzMZhJEzaYHH7enbbsOy0isWx5qPmGZ2zpxlrqDgoAMH1B3gDAGPX19R0/fvynn35iMBgRERG6urrqjggAdepmC+PTmzXwWIlUOtQyOBwm+uVZzy20eqTdQJf4xgaXLc85/HGz8UJifVp+kzWd6utpOmeWsZbm9B2nhELJ3fKu2yXt1Q1sXSpx3TKb5xZZ6VLhnDcAYBjT97gGwDQ3Z86c999/PyMjIzEx8cqVK7Nnz46MjHRzc4ObL4CnikwmLyxl/pHcmHa7XfWZby1N/Odvzpk323CoBbQ18eufsV233OZeBTshvSUupeZSUqWNOXWWg4G7k4HxtDkj3scVP6zpflDFLKtiymRyX0+Dl1fNCfE1wUNtQQDAyED+DcDY6erqrlixYunSpQUFBcnJyZ988gmdTo+IiAgPDycSieqODoDJ1djGvZradC2tmckRKhu1NPFyuZwvePQUuJmR1pH3fGzo5GG7xWIwXs56Xs56eza6ZBZ1ZhR2pOY2Xk2pMTHQsrXUsbfUsbPW0aWSJnhjhtPbL6pp5NQ0cGoaOa2d/UQNnJ+X4TtbZwX7mFDJGlMcDABgpoP8G4DxwuPxAQEBAQEBtbW1ycnJv/322++//z5v3rylS5fS6XR1RwfABBOJZRmFHX8kNxbc75YPON/tYktbGWG5aIHZmT9qfrxSPfApHk66h/7lPdqJGVqa+EULzBYtMJNI5cUPWfklXXcesH671i6WyPR1SHRjspkxxcxYm25MNtDVnNjfnWRyObtH0NrBbenoa+vktnT0dzJ5WCzG0Zoa7GPo5+Hq7aYPt7EEAIwZ5N8ATBhbW9vt27dHRUWlp6fHx8enpKS4ubkxGAw/Pz8sFoZqMOPVNvUlZLTEpDT19ImUjVRtjfAA0+cXWzlY/VnG+5kwizN/VCtT84XzzT561XM82Soeh/Fx0/dx00cICYTS0irOvUp2VX1vWWXnjSyeTCbHYTH6OiRdHU19GlGHRiJrESjaBG0tvLYmgaCB1dTUQAjhsIhIwCOERGKpYp4MXyAWi2VcvpjLE/fzJX1cYU+vkMXhM9kCVo9ALJFhMMjUUMvRmuo9i+7uqOvppDudJ6MDAGYQOJSAUYuNjY2NjVV3FOrn4eExaLu2tnZkZOSSJUtKS0sTEhKOHDliZGTEYDDCw8PJ5OF/fJ9srM7q9Nj96o4CPMrQwk/dIQypnye5mdN65WZjeW2PshGLwXi7669kWAb7GGv8s263ubGW9yz9glImBoNeXmW/Y63TBJ6bJhFx3m763m76in8FQmlNU19TO6+1k9fawWvp4N0v7+X0ivp44lF1q0XC61AJxvqatuZagXMNzIy0LEy0bC0o2pBwj0lJScmaNWvUHQUA0xdGLh+mUBQAA927d4/LHen9NZ5sdDrd0nL4G0q3tbWlpqYmJyeLRKKAgIDly5dbWT1a/GHK9HQ+5PW2qGvtQAWilr6e2Wx1R/EPcjkqqWAlpLckZrYIhH/P5zbSJy0JpK9eaGVqqDnUc5MyWw58fW/fK+5Lg82nJNhHyWRyTp+4p18kEEr7eRK5TC6WyPhCKUKIRMQR8FiEEIWsQdTA0igEGoUAl05OoJqams7OTnVHAUbKzs7OyMhI3VE8dSD/BmAq8Pn87OzsxMTEpqYmW1vbJUuWLFiwAIfDqTsuAAbRxRYkpLfEJDc2d/CUjQQNbJC3cWQQff4co2Fv6CgSy8qqObNd9CY5UgAAmJEg/wZgSpWXlycmJt6+fZtKpQYFBS1ZskRPD3IUMC0oKwneut0uHVBJ0IZOXhpi/kyYBVS2BgCACQH5NwBqwGKxUlJSkpKS+Hy+j48Pg8Fwd3dXd1Dg6aWoJBh3q5nV83clQW1NfLCP8dJgc18PAzXGBgAATx7IvwFQG7FYXFhYGB8fX1lZaWtry2AwAgMDoXA4mDLDVhLUIsHVhwAAMPEg/wZA/RSFw9PT0wkEQlBQ0LJlywwNh7xHIADj97C2JyG9OSGjpbf/7zohikqCa5ZY21tS1BgbAAA88SD/BmC66OnpSUtLu379OpPJdHNzi4yMnDNnDtzNHkygPq44Obft8o2GirpeZaOykiDcQR0AAKYG5N8ATC8ymay4uDghIaG0tNTExCQsLIzBYGhra6s7LjCDyeTyexXssVUSBAAAMOEg/wZgmmppablx40ZqaioWi50/f/6SJUssLCzUHRSYYRSVBP9Ibmx5rJLgSoalj7sB/L4CAABTD/JvAKY1Ho+Xk5MTHx/f0tLi5OQUGRnp6+sLhcOBakNWEjQnLw02XxFuoUOBSoIAAKA2kH8DMAPI5fLS0tLk5OT8/HwdHZ3w8PDFixdTKHCRHHhUQys37lZT3K0mVo9I2aitiV843ywymO7lDMXmAQBA/SD/BmAm6ejoSE5OTklJEQqF3t7eS5cudXR0VHdQQP1UVxJcHEjXJMJvJgAAMF1A/g3AzCMWi3Nycq5du9bQ0KAoHB4cHKyhoaHuuIAaPKzt+eNm4/XsVh5fomzU1yFGzDNdEW4JlQQBAGAagvwbgBmstrY2ISEhOzubTCaHhIQsWrTIwABuVfhUUFQSvHS9obIeKgkCAMAMA/k3ADMem83OyMhITEzkcDizZ8+OjIx0c3ODwuFPJJlcXnifGZ/enJLXLhT9XUnQWF9zcaAZVBIEAIAZAfJvAJ4QEomkoKAgOTn5/v37dDo9IiIiPDwc7mb/xOhiCRIyoJIgAAA8CSD/BuBJU1dXd/PmzczMTBwON2/evKVLl9LpdHUHBcZILJHl3e1KyGiBSoIAAPDEgPwbgCcTl8tNT0+Pj4/v7u52c3NjMBh+fn5YLFbdcYGRqm/pv5bW/EglQbIWPmIeVBIEAICZDfJvAJ5kisLhCQkJd+7cMTIyYjAY4eHhZDJZ3XGBIQlF0syiTqgkCAAATzDIvwF4KrS1taWmpiYnJ4tEooCAgOXLl1tZWak7KPAPQ1USXBZiviLcwsJEW42xAQAAmECQfwPwFOHz+dnZ2YmJiU1NTba2tkuWLFmwYAHczV69ernilNy2i9cbqqCSIAAAPB0g/wbgaVReXp6YmHj79m0qlRoUFLRkyRI9PZhPPKWGqiRoYaq9eIHZM2EWJgZQSRAAAJ5MkH8D8PRis9nJyclJSUl8Pt/Hx4fBYLi7u6s7qCefopLglZuNrZ1QSRAAAJ5GE5N/Hz58OC8vT/nv77//Puhia9asGbR9pi/v7++/d+/eQR96knB7mtLOrlJ3FNOLFtUsdEOsuqMYL7FYXFhYGB8fX1lZaWNjExERERgYqN7C4Zw+UXM7r6WD19LJY7KFPf0iJkfE6RPx+BIuTyKTySUyOV8gQQiRCDgNPBZhEEVbg0TE6VIJejSiDlVDl0o0N9aiG2vRjbX0daZFEXSxRJZe0BGf3pxT3CWTPVpJ8NlwC9q0qSR48uTJW7duqTsKMAqenp779u1TdxQAgJHCT1RHDg4Oy5YtU73Mm2++Oao+Z8Ty165dG1UnM52tazhJCyYqIIRQd9vD/l6muqOYABoaGgEBAQEBAbW1tcnJyT/++OO5c+eCgoKWLVtmaGg4BQFIpfKapr6Kup6Kut7y2t7qxl4uX4IQwmEx+jokKpmopaWhrUWwsyATiThNkgYGg7AYRCTiEUIikUQqQwghnkAsEsm4XFEnW1TXyuvrEzE5AsVjmkS8rQXZ2ZbmZEN1tqHZW1E08FNah7GupT8+rflqahO799FKgqsiLJ1taVMZzAhZWVmtWgXft2eGGzduqDsEAMDoTFj+ra+vHxAQoHqZYReYicvn5uaOqpOZTsfQjqJjqu4opgU+l/Vk5N9Ktra227dvX7t2bVpa2vXr15OSktzc3CIjI+fMmTPhd7OXyeQPa3vuPGAVljKLH7L4AglBA0c31qabUJaFGRnqkfR1NXWpJCx27OuVyeU9vcJuNr+bzW/t6C8p74lPaxGIJEQCzt1R19tNf+4sPTcH3cm7upEYrLQdAAAgAElEQVTHl9y63Z6Q0XL7XvfAdkUlwSWBdNI0riSoo6Mz2iMkUJe7d++yWCx1RwEAGIUJy78BAE8GGo22YsWK5cuXFxcXJyQk/Oc//zExMQkLC2MwGNra4y2BJ5bICu4zb91uT7/dzu4VUckEOyud5WF2tpY6JgZa48m2H4fFYHRpJF0aycFaV9Eik8u7mLzapp7qBs6FxPpvzldQtDQCvY1C/Uz8PQ0nMBv+s5JgVitP8HclQQNdouKOlVBJEAAAnnITk387OjpOSD8AgGkCi8XOnTt37ty5LS0tN27cuHTp0pUrV+bPn79kyRILC4sxdPigmhOT0nQju5UnkFjSqQt8LNwdDUwMpzQTxWIwxgbaxgbaAbPNEEJdLF5pJfN+RVdS5h0NDWyYv8mz4RazXfTHfK7/z0qCSQ1VDQMqCWIx3m76KxmWob4mOKgkCAAAYKLy72FnfgMAZig6nb558+YXXnghOzs7Pj4+OTnZyckpMjLS19d3JIXDRWLZ1VtNl683Vjf2mhppRwRaz3Yx0qWRpiDyYRnqaYX6a4X6W/RxRXfLu27fbUvMyDM30V4VYbkqwlJbc6SHR0UlwT+SG9MLOsQSmbLd0lR70QKzFeEWxvpQSRAAAMDfYP4JAGB4mpqainvXl5aWJicnHz16lEajMRiMxYsXUyiUQZ/C40su32w8e7W2jyue627yDMPB2nw6XmiIEKJoEwLn0gPn0lvb+3OKW7/9verHy9VrI63XRlrrqKxJ0skUJGa2XL7R0NbFVzZCJUEAAACqQf4NABgpDAbj7u7u7u7e0dGRnJycmJgYExPj7e29dOnSgZPQpFL55ZsNpy5UicSy+XPMQgMsqeTpUllPNTMT8nNLHCNDbTNuN11IqD8XV/fSSrv1y22IhH+c6ReJZRmFg1QSdLGlRQbTI4PMqWSNKY8dAADAjAH593jB3HfwFDI2No6KilqzZk1OTs61a9fef/99W1tbBoMRHBxc9IDz1Y8PWjp4wb4WjAVWWqSZd5DRIuEXB9mEBlhm5DeduVITk9y4e4MLY54p+quSYGxKE6fv0UqCqxdaOdlQ1Rc1AACAGWPmDY3TDcx9B08tDQ2N4ODg4ODgsrKy69evf//992fPXyvrifB0Nty4yt1Ad2ZPeiZq4CIWWPt5msWl1uw7Unwjt1UmlacXdCgXwGIwc930V4RZhPqZEDSmtKA4AACAGQ3ybwDAeM2aNQtLMs+sdmT2Mrc87+7pMhV37ZkaVAohaoWLj6fJr7EPBUKpotFQlxQZTH+WYWlurKXe8AAAAMxEkH8DAMYrNa/9g2N3bS30d2xYQCNPi5u9TyxHa91/7fA9F/uwtLLruYVW0S/PmthS5QAAAJ4qE5N/V1VVIYQcHBwmpDcAwAxyNq722C/lC7zpqxc7TPhtMqcPLRJ+21r365n1l27UEom4N9a7PLnbCgAAYHJNTP4dFxeHENq7d++E9AYAmCkuJNb/75eHKxc6hPiN5aY8M86iQGt9Xc1zMQ9wWMxrUc7qDgcAAMCMBPNPAABjlJTVevjHB88w7J+S5FvB280YyeS/xD7UoRDWP2Or7nAAAADMPJB/AwDGorap78DXJSH+FuEBluqOZap5e5j088XHzpa72NHmztJXdzgAAABmmKe3ZpZAIJiQfqqqqhTT3wF4eojEsn1H71qYUFYw7NQdiyoCPn/4hcYkxM/Cy8Xwg//d7eWKJ2kVYJqYqMFCXf0DAKahp/H8d0pKSk5OTmtr68mTJ0tKSrKystLT0xFCrq6ueDyez+fL5fJ58+aFh4drag5fwBjmvs9ccrn8wqUksVgcl3jLzdVh3792YLHYR1pwONzwHT19fo2va27nvbPdZ8wXXMrl8tirVyVi8Y2bN52cnPbs3j3orpZKpdXV1Xfu3HF2dpo9ew5CKC8v79SpUwcOHLCwUDXpJS0tLTX1Vn1D3c8//Ty2CIf13FKng9/kf3uhMvrlWZO0immuoKDghx9+eP/99+l0urpjmRQDBwsVi0ml0tra2rt37zo6Onp6eqIR75nMzMyMjIzGxsZTp05NcOgAgOntaTz/HRoaKhaLpVIpQsjT03PXrl2KPPujjz56//33P/3002XLlp09e/aLL76QSCTqDvZp0c1iT/1Kf/j5SmNz64Z1z7z/zit9XJ5EKn28Zeqjmv74QumvcbXBvub647jDzm+//dbS3Pzcc8/t3r2bx+XKhtjVVVVVSUnXf/31166ubkULkUik0WgahGFuaB8UFCSRiGWSIV9B9rjfcmRNjUWBNleSG7vYT+n5SyKRSKVSNTQ0RrIwm62Gz/g4Yxg4WKhQU1OTnJx88eJFJpOpaBnhnpk/f75EIlEx0EyHnQYAmAxPY/6NxWL19f+esonBYBT5t/JM3rx58wICAh4+fFhRUaGeEJ8yfX3c/Z9+PfXrvXL1pqmxIULIw83py39HEwmEx1umPqrpLzalkS+QjfOay4SEBGNjY4TQLFfXDz74YKh82tnZefnyf9xidvbs2UeOHDExNlbdPxaL1TcwGOrR/v7+Q199NfqoH+XvZaqtqXE+vn78XU0BJpP56aefpqen8ydoWo6Hh8fBgweNjIyGXZLL5R47dmxCVjpmY4jhkcFiKI6OjosXLx7YMsI9g8Vi9fT0hnp0Ouw0AMAkmZj829HR0dHRcUK6UovHf0NXZAadnZ3qCOfpIpZIPvr0eEtrx/CLTiihSMRm9w585R9vAYNKyW33dDXU1hrRWc9BiUWinp6eEe5pPH6Cp8mJJZJDX37Z0d4+/q7weKyvh2lKbtv4u5oCcrm8pKTk66+/3rp16+HDh/Pz88XiqZi8LpFIjh492tEx1Z/xqYxhwt+l02GnAQAmz8QcMpYtWzbsMs3NzZmZmbdv3/7www9Pnz794MEDExOTl19+2cHBgcPhZGVlpaWl7du378SJE62trQcPHiSTycnJyfX19XV1dVpaWlu2bDE1NX348OFXX33V29u7atWqF154ASF0//79Q4cOLV++/LnnnlMdQEFBwZ07d8hkslAoHPZHvYqKCgwGY29vP/KdABTkcnlMXEp1bWN5ZR1FWzN698vm5iZVNQ1Hjv9cXPJw7uxZH+3blZKad/K781teWv3i2sjUtPy6+ubevv7PD31naWkWtWap6v5z8u9m5xZr4LFl5TXLl4Q8szRM0Z6Wcbuo+AGRoFHb0OzkYLN540qChsZQ8SRczyi8U4oQSk3Pb2rpsKAb6+npPNKy/sVnJnlXzUi9XPH9KvbGlWOf8ZySmnL3bglCKCs7u62tzdTUdPVwH16l/v7+nJyczMzMpUuX+vv7Kxqrq6qTkhL5AmFbe+vCiIUREREDp5Kz2ewTJ06UlZUZGRlFR0dbWFhkZ2U1Njb2cbnHjx2j0+krV60a87YghNwc9W9k1Te0cq3MtMfTz5R57733OBxOXl7ekSNHiESit7d3QECAl5fXaC914HK5+fn52dnZixcv9vHxqa+vz8zMzM/PP3jw4JkzZ+7cuWNkZLRnzx5jY+Pc3NympiYul3vq1CkzM7Ply5fL5fLHD++DDgQUCqW4uLioqAiHw1VXV4eFhYWHhyOEBu1BxSgzwhgUmzaqwWLYPaNoVMxREQgE7e3tYWFhYWFhA3c4h8P57rvvHjx4YGRk9MYbb9Dp9McDHm0YAIDpbOrmn2RkZNy4caOtre3q1auRkZGvvPJKZ2fngQMH2Gx2fX19SkpKc3NzcnLy/PnzdXR0JBJJbGwsgUDYtm3bv//9bz6f/9FHHwmFQhcXl+effx4hZGv7Z9ldV1dXW1vbYZPvrKysmJiYl19+OSoq6vnnn29ubn58mYaGhvr6+rt37x49erS+vn7btm2qL/ACgzr7WxyRSHh7z8vfHdvP5Qt27jkgEIgc7Kw+P/CmgZ4ul8vT19URikTvvr19w7pn8Dj8IsZ8eztLGpXybvS2YZPvxBtZSTey3npj057XXgoMmPPFV6eLissQQhcuJf52KWH3a+tf2xn10XuvpqTnvfmvL+Ry+VDxRC4K2v3qRoRQcKDPu9Hb1r/4zOMtk7+rZqSK2h6pVG5vpTvmHsLDwrdt3YYQ8g/wf+3110eefCOE2Gx2U2Pj3bt3ZTKZoqWrq+vd9959fu2at9+OtjC3OHHiRHR09OnvTiseFYpEly9d3rx50+eff9HR0fHjmR8RQiEhIda2NjQK9bXXXx9n8o0QsqJTCRq4smrOOPuZMlpaWsHBwe+888633367fv36jo6O//znP9u3b//222/Ly8sVn5qR4HA4TU1N9+/fV7wWOjo69fX1nZ2dv/7664oVK/bs2dPa2nr+/HmEUGBgoLW1NYVC2bFjhyKPHPTwPuhAkJGRkZGRsWXLls2bN3t7e586daq0tHSoHlSMMiOMAY1ssBjVnkEIdXd3f/zxx6tWrdq9e7e5ufl33323b9++n376SfGoSCSKjY2Niorav39/Z2fn2bNnB91pAIAnydTl3+vWrZs9ezYGg1m/fv2sWbP8/Py2b98uFApv3rzp5eXl5OQkk8kCAwNDQ0M/++wzhFB8fHxQUBBCCIvF+vv7czicoqIihFBoaCiZTM7MzFR0W1JSojwNNhShUPjLL79ERkYqroahUCguLi6PL5aQkBAbG3vhwoW8vLzZs2crU3wwct1M9oXLiYsjAhFCWBw2NNiPyeJk5RUhhKgU8uu71pdX1n3/0+WH5bWLGPNH2zmH03v42Jmd29ZisRiE0Ipl4SGBvvr6Omx276kffn92GQOPwyOEaFTypqhni0seXk/OVhEPGJtutlADjyWPY/LJeFhYWPj98/N+7do1CplsbGSMEFqz5nmE0OJFi7du26p4FIfFbn55M51ubm1t5enpWV1dPeEhYTAYGoXQxZp5l2BSKBQGg/HJJ58cP3589erVNTU1H3744a5du3788cf+/v5hn06n05UndxFCOjo6ih8MX3jhBXNzc3d3dxcXl9ra2sefyGazBz28Pz4Q4HC4H3744cUXX1RMEWQwGH5+frq6ukP1oGKUGWEMIxwsRrVnEEJJSUlkMtnQ0BAhtHLlSsW2vPTSS4pHcTjc+vXrzczMLC0t3dzcBt1pAIAnzJTWHyQSiVgsVvmjm7e3t4aGRmNjI0IIh8PhcDgTExPFQxUVFVKp9Ntvv1U+Nzw8nEAgIIQIBEJwcHBSUlJfXx+FQsnJydm8ebPq9ZaXl7PZbEvLv+8SMuhcvZ07dyr+aGxs/PLLL/ft2xcdHT137lzVnc/oie8T7n5ppUQiPXj4tLJleWQo6a9L6yLCAq7Gp/7w85Vfvv9iDJ2XlFbI5TJTE0PFvzQa5bP9exBCWTlFAoHQxPjvy6Tm+89GCN25+4BI0FARz/iJRdz4Ez7DL/dEwWprfarGWfJY7D+mSTCZTKFIqPibTjenUild3V3KR/F4vPKAQyaT+/u5kxESRVsj8/q38b/WTUbnU8DQ0DAyMjIyMrK+vv7nn39OTExECJFIpLt373p5eal44iNTVrBY7MBGTU3NQS/0VHF4f2QgUJyPV17FSKFQ3nrrLYRQXl7eUD2oGGVGEsMIB4thPbJnWCyWSCRS/G1mZkahUJSVUpRbrfhbW1t7JF9+AAAznTrrf+NwOF1d3UFLO7W0tBCJxB07dgz6RAaDER8fn5GRERISgsVitbWHmXbZ0tKCRnMYtbS0jIqKOnz48M8//zxs/j2Sue9Pj/rGFk1N4rvR24ZaIHJRUFFxWVxC2p5XN46289q6JqlEJpfLH7letq2jGyHU2/f3oEWjUUgkQjeTPWw844THk9xD3p2kzqengjKWIHcalWWcO2dOenp6SUmJp6cnl8vlC4Rz5gz+mZ28rwx8gXSue3jgbMqkrWFi9PX1nT59etCHWlpacnJysrKyFDPyiUQikUhUnXyPmerD+0BNTU0SieTxj/zIexhqlBmqh4SEBDQJF1N6eXllZWXdv3/f3d2dy+UKBIKh9u2YC+oDAGYWNd9/RygUDnp7AgKBwGKxmEzmwNpPihPeCCE6ne7i4nLr1i0CgRAYGDjsWhQH066uLuXlNcOysbFBCLW3t0ulUrgDy8gRScTOLlZnF9PI8O8Xrqenj0ajIIQEAuGNlOxFjPmXYm4sXRzsYGc1qs61tbSEIlF9Q4uNtbmyUSyRmJkYIYRa2h4tVmNlaaY6nvHDYHGm9owJ6Wqm0OvtFAgLhGIpUWNafC5Cw8JYLNbhw4cjIiKYTNa/3n7b1XXUEwbGqadP6OjoEhBgOfyiatXd3f1IC4vFysvLy83Nraio0NXV9ff337lzp5OT0zfffMNisSYpDNWH94E0NTXFYnFzc/PAS3EkEsnIe0BDjDJD9TCGwWIkgoKC2Gz28ePHw8LCWCzWnj17nJycJrB/AMCMo87632w2u7e3d9DZ25aWlnK5/Ny5c8qWnp6eW7duKf9lMBiNjY0ZGRlubm7DrsjKygohlJOTo2yRyWTKK2MQQo9fctTa2ooQMjExgeR7VOxsLOVy+dff/qZsYbN745PSFX9/++PvL65Z9sbODVqapENHf1TudgwGK5XKBunun1ycbBFCp77/XSb784nNLR2paflusxy0tTQzMguVS3Z2MQUC0YKAOariefw6sxFfefY0U1T5aG7rG08ncjRhu1oilfT19//v2LH169fv3v3GsFeDKGAxWIl0Yu6uxWTzeQKJ5QwpfqLA5XLT09MPHjy4a9euixcvGhsbv/POO19//fXmzZudnZ0n4xQsBoNRnoQe9vCuZGdnhxA6f/688ljR3t6em5s78h4GjjIjiWHYwWJspFJpf3//oUOH1q5du3Pnzkdmhw9lYMAAgCfMxJz/rqqqQgg5ODgMu6REImloaFAc465cuRISEqK4ZEdxjFOebPbw8LCzs8vKyhKLxT4+Pu3t7RUVFXv27FH24+/v/8MPP3h4eIxkqHBycpo1a1ZaWpqtrW1wcHBzc3N5eXlvb292dra3tzeBQFBMUhQKhUQiESHU1dV15swZhJCixCEYOd+5bq5OtjdSckQiSeB875bW9vtlVQfefw0h9OBhdUcny3euG0Jo+8trDv/vTExcyspnGAghQwPdnPziyur6/n6eq7M9iTT4/Gx3N8cAX8+M7MLX3/p3aLBfe0d3c3P7px/vxuFwu7a/eOjoj4V3Sr3nuCGEfr9yPXJR0NzZs+Ry+VDx8PhChBBfIFL2/3gLeJyFiba5ifaDapadpc6YOxEKBAgh0ch2NY/HQwgpcyCRSIgQUhauvnzpcun9UltbG11dPU2SJplKUd6aRyIWCwfUtxaKRNK/JjPo6emx2ey62rp+br+jo6Pigz82pVVMLRLew2nIu6hMN99//31DQwMej/f29o6Ojvby8hrzdAvFnGbla6G4j6MyZRSJRIqKIgghXV1dDodTX1/P5XKdnZ2HOrw/MhA4OTnNnj27oKBg//79/v7+3d3dbW1te/fuxWKxKgaIoUaZkcRAoVBUDBYq3ieKQWTgtg/cMzExMQ8ePLC2ttbR0SGRSBQKRTmpXSKRDKzCLhKJpFKp4l06MGB7e/vxvEsBANMN7uOPPx5/Lz/99FNlZWVAQIDqxYqKihobG/F4/K1bt0pKSvT19Tds2IDBYDIzM69fv87n8/l8vr6+Po1Gw2Aw/v7+LBarrKyspKSESqVu2bKFRqP9HTcOx+PxIiIitLS0RhKhn58fh8NJSUm5efMmiUTS1dW1srJycHBgMpkxMTGVlZUIoYKCgqKiosTExJs3b9Lp9J07d86ePXs8u+UJIxb21t+7YGo9l0gacvIGBoMJCfbt6mbdKXmQX3hPh0Z5a/cmPV1aUXHZR/8+4eHq4OvtjsFgmprb0zMLCgrvU6nars52xkb62bl3MrKK3F0dHOxVTUoJCfTt6+eWllUV331ANzOJ3r1JMSa5ONk6OVhfuJz0sLym9EE1jUbete1FDAYzVDwVlfW//BZTXdPY2cXU1aGZGOvX1bc80kIgDFPio4fZyO3tsvF8cWz7c+Zq6+Ll3OkI8jEf24nSmpqai5cu1dfVMZndNBrN0MiIMPRtuutq6y5evNjc3Mzl8UyMjTkczqXLl9taW3t6eul0uqGhIZ/HT0xKSk9PT0lJuX79etzVq9nZ2QEBASUlJXFxcVwuF4vF2tnZFhYWxsbGCgQChJCzi4uxsXHB7dt5eXnOzs6KyWZjFnuzyt1JZ+E8s/F0MjV4PF5SUpKNjc3q1atfeeWVBQsWmJmZKS6afERhYSGfz1eUBxlKVVVVTExMe3t7b2+vmZmZoupff3+/UCi0t7fPz8+/ceOGIit1cXExNDQsKioqKChwdHS0trYe9PD++ECAEPLz8+NyuZWVlWVlZSYmJlu2bCESiSoGiKFGGYSQgYHBsDGgoQcLU1PTod7w9fX1f/zxR0tLC5/PNzIy6unpGbhnDAwM+Hz+zZs3s7KyFG/UhISEvLw8X1/f0tLSxMRExbvUxsamuLg4ISFB8S51cnIyMjIaGLCK12IkrxcAYFrBjLzaqwqHDx9GCO3du1f1YqdOncrIyBj4kx+YQbg9TWlnV80J3k7RmciZkTNXY2VWR/OD0I1X1R3IVGvp4K3enRb1jIu3u4m6Y0FpaWk4HN5t1iwWmyUUCHgCQWVFhVQi3bBxwxSsvbKeffzn4u8+CfByngHnv8VisUAgGHSS9CNOnjzJYrH27dv3/+3dd1zTd/4H8E92IAkJhBX2XjIUBAfixEW11baOTnvnWVuvdv26x6/jOn5ee3f1rsPW69DWah114kBAoVLrAAVUZkgg7BESIHv9/qBHvQrITAi8nn/0IZ98+HzfpFFe+eTz/XysUNXIGpu/ZX766Sc6nR4REaFQKLRarVarraysNBqN9903Mu/e7ff/F8CEZeP7L0fQ+vXr+3po06ZNt93GBMaIpSv73NPgtec3Js+Mt2Yx0CtvD8cls7xP5UonR7rT6SNwD8mDDzzQ10NPPvVUUlJSX49KJZJvvvmme7WYs8uvRwJFRkRkZ2UPv6rbMlssJ85WJca42kX4JoQwGAxG3x81QP+G/Cumurp6165d27ZtI4Q4O//6Kg0LC8vNzR3xIgHAXlg1f2u12p6VbSM++JdffjniYw7EwNe+w0CcOPi5rUuA29u4Juzsxdyj2eKVi0bglf/dUGcrqySStra2ffv2zZs3T+AsUKvUZaVlVwqvrHt43fCruq2zv8hq6jvf3jzok6Rg9Izeb5kh/4qRSqVyufzgwYOzZ88WCAQqlaqioqKoqOj+++8f2QoBwI5YL3/n5OQUFRWZzeadO3cmJyd33xAzDhw9epQMYO0NwHgicnN4fv2ktz8piggWRgbbbPZ37ty5jY2NR48d3blzJ9vBwc/Hd+kdS/+0fkP3CamjStbQmX6m6tE1YWEBTqN9LRigsflbJiUlpamp6eTJk7t372az2T4+PosWLXrkkUew1TfARGa9/D1nzpw5c+ZY7XIAMKrumONzqbjt6/3Xnnhwsp+3bTIolUq9//7777//fp1Ox2QyrRZoWuTqz3cXTol0efjOIOtcEQZibP6WoVKpq1evXr16tZVfpQAwltly/28AsGuvPR47JdL5892F9c2jcq77wHXviWGda8kV2s92Ffp4OH7wQoIVJtph3LDmqxQAxriRyd9hYWFhYWEjMhQA2As6jfLX5xJC/J3++U1+adVoHZc4psjqO//x9WWBE+OfryY6ssfP/esAAGBNI5O/ly1btmzZshEZCgDsCJtF+/j1pNmJHp9/X3jucl1Pu9FoNpnH23miV240/3NnQWQQ/8u/zODzej8lCgAA4LYwfwMAt2cwmjtVxi61oVNl6FQZulTGTrWho8vQpTJ0qo1ms0Xk7rjvRNnhzEoGg6bVGWPCXB9aEUXGy/IMrc544FTFhasNq5cEPPtIFI02Tn4uAACwCeRvAOhTYWn7y38v6FQbtDrTQPrr9Cad3hQe5Pzw3ZNo4yV8XytvO3CyzGw2//3FqSlTPWxdDgAA2D3k7+HCwncYx2LCBSwmtaV9QOG7W2SwoKxK8c8dBXcvDvX3su+9+RpbVYcyKm5UyhfMFL3wx2gXPtacAADACED+Hi4sfIdxjEqh3LPYf+vOkgF1plJe3hC9ItWvXNrx4Vc3/v7l5dgIt9Rkf3tM4Y0tqsy86svXm0J8eV+8NWNKlH2ccAkAAHYB+Xu4LBbLe++9FxMTs2DBAg6HY+tyAEbYXfN9v/ihXHO79SdMBvXtJycvmC4ihIQFOH3x9vTcy01f7q/8278vhwe5zJvmGxniMvY3X7NYSGV1e+7F2uKyVj8vzhub4pakeFHHfNkAAGBfkL+HS6/X+/j4HDhwYP/+/XPnzl26dKlIJLJ1UQAjhsdhLJghOna2tv8+f3th6u8miWdP9Zg91eNiUevXB8Wf7ykUOLGmxXlNnyxyEbBHueSh6OjSXyxs+OVqQ3ObOjpUsOW5+NmJHkjeAAAwGkYmf1dUVBBCQkNDR2Q0+8JisdatW7d69eq8vLxjx46dOnUqOjo6LS0tPj5+7M/2AfRP1qA6nC07e6Gxnz6uzqytryT1dQx7UqxrUqyrrEF14qe6w1m1J3Mlnm6cKVHuUya5e7ra/vOidqW2RCy/Vt5aUtnGZtEWJXvds8g/PND+FswAAIAdGZn8ffToUULIs88+OyKj2SMHB4fU1NT58+dfunTp+PHjW7ZsWbt27d13323rugCGwmy2nCto3ntCerG41dLvLt4+Ho7/en2aj4dj/wP6ijiPrg774z2hvxS2nL3QmHOp7kSOxNPVMdTfOSTAOSTAmcdhjOQP0C+11iiuVpRL2sU1itrGTq4jY1aC+0PL42cluDMZOBIYAABGHdafjCQqlTpt2rRp06aJxWI+n2/rcgAGrUttPHZWtjtdWt+s7ml0dWbFhTtn/fL7WfDoUME/Xk4UDPgkGoxqHPgAACAASURBVDqNMivefVa8+ysbLVdL5eevtFy61rbzUL3ZbPFw5Xh7cn08eT4eXG8Rj+swknFcozXWNXXWNnbVNnTVNXU2NKsIIcF+vNlTXWdMjkyYJGTQEbsBAMB6kL9HRXBwsK1LABicMknHgYzqEz/V3bzVd1yE89q0wHlJnoSQok3ZLXJtz0OJMa4fPp/g6DCUf0OoVEp8lDA+SkgIUWuMBSXy4rL2UklH3qXaVoWWEOLowHB1ZgsFDkJnBz6PyXFgcByZThwmm0VjsehUKoVGISwWnRCiM5hMJovFbNHqjFq9qUul71IbutSGzi59a7tGrtS0yjVdagMhRMBjhgU4LZjuERMmiI8SOnGtN+MOAABwsxHL37/88svq1au7/7x3795e+/R0+B177//uu+8OcO27RqMpKyuLi4uz36XhBTlf2LqEMcSR52XrEobLYDTnXGo6mFlzsai1p9GRTV88y2v10oAQP15P48pUvy/2lnf/eels7//dFEcfiWMgHR3o3ZPi3V/KlbrK6s7aJnVto6quWS2tbW9X6pSdeqNpoKfZU6kUPpfpzGf6ejpGBrr6eDp6ezgG+/LchWPxvs8xq7CwsK9/8WAMiouLs3UJADAIFEv/qzsHpry8vK2trefLGTNm9Nrt/Pnzvbbbe3+hUDjAU3jOnz//0UcfeXl53XHHHbNnz2Yy7ek4D6NB3VL9s62rGFtoDAd3/2RbVzFEbQrdsbO1e09Km9t+m9X29eTctcB3ZarfrdPDbQrd8sezDUbz2rSAZx6JsvLeIF1qY7tS16UxarRGo9FiNFnUWiMhxIFFY9CpVCqF40h3ZNMFPAZ/wOthoC9isbi5udnWVcAgCASCyMhIW1cBAAM1MvkbBq6hoeHkyZNZWVl0On3OnDl33nmnUCi0dVEwsZRUKfekSzLy6nsmlakUytQY4dqlAbMSPPrJ1a9vvdJ9J6WVCgUAABiPkL9tQ6lUZmRkZGRkqFSqmTNnPvjggwKBwNZFwTinN5hP/1y/65ikQtrR08h1pC+b63PfHYFe7rfZw4QQotObWEzaaNYIAAAw/iF/25LBYDh37tzZs2dfeeUVFotl63Jg3KprUh/MrDmUJVN26nsawwOd7lnkvzTFm81CpAYAALAe5G+AcctiIZeKWw9m1mRfaDSbf/2bzqBT5yR6rEz1S4p1tW15AAAAExP2HwQYh1QaY0Ze/e50iaS2q6dRKGAtm+uzaom/h9DBhrUBAABMcMjfY9f27dvlcnlaWlpMTIytawG7UV2v2n9KeiS7tnt7kG6RQfw1aQGLZ3mPyI6BAAAAMBxYfzJ2/fLLL4cPHxaLxaGhocuWLUtKSqLRsE4Xeme2WPLym/eckF666cR4JoOaOkP0wPKgsAAnm1YHAAAAv0H+HuuqqqqOHz+el5fn5OSUmpq6dOlSLpdr66JgDJEr9UfPyA5kVDe0aHoavT0cV6b6rVjgi82wAQAAxhrkb/vQ3Nx84sSJ7OxsX1/fd955x9blwJhQUqU8eLrmeG6dTv/rifEUCkmMcV2Z6jd/mieViqUmAAAAYxHytz3RaDStra2+vr62LgRsSW8w515u2p0uKSpr72nkONAXJXvdd0dgoA8+HgEAABjTkL8B7EZLu/bg6Zr9p6rbO37bxtvfi3PvYv875/s6snE7NQAAgB3AL+xx4syZMwkJCU5OuM1ufLpaKv/huPTMxUbTTSfGz4x3uy8tMDHGtZ8T4wEAAGCswfz3eKBQKJ599lm9Xp+SkpKWloYFKuOGWmM8lVe/94S0sqazp9GFz1w+z/eeRf4iN2zjDQAAYH+Qv8cJg8Hw888/HzlyRCaThYeHr1ixIj4+noJ5Ubsla1AdzpYdPF3ToTL0NEYG8Vcu9Eub7c1iYidKAAAAe4X8Pa5YLJYrV66kp6cXFxf7+Pj84Q9/wNk99sVssVwubtt9XJJX0HzzNt6zp3qsTQuMi3C2aXUAAAAwApC/x6eampr09PTU1NTQ0FBb1wID0qU2Hjsr250urW9W9zS6OrNWpvqtWhLg7IRtvAEAAMYJ5G8AGyuTdBzIqD7xU51WZ+ppjItwXpsWOC/Jk4YT4wEAAMYX7H8y4ZjNZgqFgqXhNmcwmnMuNR3MrLlY1NrT6MimL57ltXppQIgfz4a1AQAAwOhB/p5w8vLy9u7dm5qampqayuFwbF3ORNSm0B07W7v3pLS5TdvT6OvJuWuB78qFfk4chg1rAwAAgNGG9ScTTmNj47Fjx3Jycuh0+oIFC5YsWeLq6mrroiaKkirlnnRJRl698aZtvKfGCNcuDZiV4IHPJAAAACYC5O8JSq1Wnz179tixY21tbfHx8StWrAgPD7d1UeOW3mA+/XP9rmOSCmlHTyPXkb5srs99dwR6uTvasDYAAACwMuTvCc1kMp0/fz49Pb2mpmbbtm08HtYcj7DaJvWhzJpDWTJl528nxocHOt2zyH9pijebhW28AQAAJpzRyt8FJ19qEGeNxsg2JwpeEL/k/2xdxQhrbGz09PS01dXNZkubUtfUqm1t1za2auVKXUeXoaPL0Kn69b96o1mtNnZ3VmmNZrOFEMJgUNkMGiGEQqVwHelMJs2JQ+dxGE5cBs+Rwecx3F3Yri5sT1cHN2cWn2fV/fu6t/E+mFmTfaGxu1pCCINOnZPosTLVLynW7hf8nD59+quvvjKZTLc+tGPHDgeHXg7mXLdunUajGX/9V61atWrVqlvbAQAA+jKK91/ynH18g2eM3vg2IROft3UJo8Ka4btNoauq7aqp75LWqaR1XdK6rpZ2rek/66H5PCaPy+Kw6Ww23YHN8HRzCPSj06gUBzaje3k0k0Gl0aiEEL3B1P1dJpNFpzfqDWaNzqDWGGVNOp1W1aUxKJQ6je7X1M5k0rw9HAO9Of5e3ABvboAXJ8Cb6+gw8q9/lcaYkVe/O10iqe3qaRQKWMvm+qxeEuAuZI/4FW1i4cKFfD6/1/zNZPb+VufPf/7zuOyflJTUa38AAIC+jOL8t1HTEJU43qaFblzaR3cQjb/5776cO3fO2dl50qRJwxlErtTfECtKq5TXK5WlYmWrQksIcXRgeAgd3IUcd1dHoYDNd2I5O7GduEw6jTpCtRNCiE5vbO/QKTt0ik5da5umWa5ublM3t6kNRjOVQvETcSJD+FHB/IggfkQgf5irQarrVftPSY9k16q1xp7GyCD+mrSAxbO86djGGwAAAAgh2H8Q+nf+/PlLly4FBgampaUlJyfT6QN9wSg79QU35JevtV0sbpXWdRFC3F0cvEW8mVO9/UQ8kTuXx7HGghAWk+7pSvd0/a9tFi0WS5tCW9/UJavvrK7vOHe5uVNtYNCpk0IEiTHCqdHC6FBnJmOgbwPMFktefvOeE9JLxa03nxifOkP0wPKgsACnkf2JAAAAwN5h/ntwJtr8NyFEIpGkp6fn5eVxudxFixYtWbKkn9s0JbVdZy82nrnYVFalJBTiK+KG+DmHBroE+Dg5ssfumz25QlslU5RLFZXS9tZ2DZNJS4wWzpvmOXuqRz8Hv8uV+qNnZPtPVTe2/rYs2NvDcWWq34oFvlZecQ4AAAD2Avl7cCZg/u4ml8tPnjyZmZmp1+uXL1++Zs2amx+V1Hal59Rm/9Ioa1Q5cZmTwlyjQ11D/AUOYzhz90Wu1JZVya+Vt5ZVtRtN5tgw5wUzPJekeAtuytMlVcqDp2uO59bp9L8uCKZQSGKM68pUv/nTPKlULDUBAACAPiF/D86Ezd/ddDpdTk4Oi8WaM2cOIUSlMZ7Oqz+cLbtWoRAK2JMj3WPC3QJ8najj4iAZvcFUUikvLmspLms1mswpUz3umu/r4+n42tYrJWJlTzeuI335PN9Vi/19RThMFAAAAG7P/qYnwYZYLNaiRYsIIQ0tmu+PVR3KlJnMlrhI9ycemhwS4Dw+YncPJoMWF+kWF+mmM5iu3mi+UNjw9PsX3V0cOlWG7g7+Xpx7F/vfOd93LC+tAQAAgLEGuQEGp6K6Y+ch8enzDQIeK21e0LQ4kT0uMhkUFoM2LU40LU7UIlfnXqw7d7mWTqMuShY980iUYKIu8haLxXq9PjIy0taF2BieBwAAGIJxnpxgBLW0a7fvrTicLfNy5963PCIh2pM2wRY6u7k43rMk9I55gRcKG7J+rj7z+JkH7wx8ZGXIwDdLGTcyMjLkcvmrr75q60JsDM8DAAAMAfI33J7eYN55WLzjoJjjyHh4ZdSUKI/xtdJkcNgs+pwk3+mTRVk/y3YcrkrPqXtmXeTcJJudHgoAAAD2BfkbbqOypvP1f16tbVAvTAmYN82XTp9wc729YjHpaXMDZ8Z7HcsWv/Bh/uJZ3i+sn8TjMGxdFwAAAIx1yFLQJ4uFfHe06uGXzhEL9cWNiQuT/RG+f0fgxHpwRdTG+yafv9qy9tmfCm602boiAAAAGOsQp6B3RpPl7U8L/7WrdOnswM3rpgidHWxd0dgVFeLy0sZpIg/un9++cOxsra3LAQAAgDEN60+gF2qN8fkP8ovKFBvXxkUGu9i6HDvAcWT88d6Y9DNVb39a2Niq+dO9obauCAAAAMYo5G/4PaPJ8twH+eXSjs3rpviK+jxqHn6HQiHL5gcJBezt+8qYDOrDdwXbuiIAAAAYi5C/4b9YLOTdbUXF5Yon18X7eHJtXY79mRHvZbaQj3eVujmzl872tnU5oyUkJKSzs9PWVdgengcAABiCcZW/TSZTaZnkl0uF0ZPCpk2NsXU5dulwVs3xn+o2ro0bTvg2mUyVlZUFBQUREeFTpsQPbRCLxXL4yBGjwZBx+nR4ePjTTz1Fo9GGXJI1JSd4tbSp/7KtKDpM4Os5Pg+lX7hw4W37mEymqqqqq1evhoWFxcXFDe1CFovl+PHjBoMhOzs7NDR006ZNY+plMJDnAQAA4HfG1f2XJaVVh45lfbnjQHMztqEYCmWn/uNdZfOSfIe55ruiouLkyVPff/99S0vrkAfZvXt3XW3tvffe+9RTT6lVKrPJNJySrOzO1GAPoeOW7ddtXYgticXizMzMffv2tbUN/e/j/v376+vrV6xYsWnTJrVabTabR7BCAAAAmxhX+Tt6UuiqlYttXYUd+2xPOZVGWTInYJjjRERELF++bJiDHD9+3MPDgxAyKSrq9ddfZzDt6aR3KpWyamn4xeKW3MtNtq5lEEwm0xtvvHH69OkRWVMRFha2ZMmSYQ6SkZHh5uZGCImIiHjxxRcZDOywDgAAdm9crT8hhDAY4+0nshqtznQ8t+6OeUEs5gg8h3T6sAYx6PVKpdKuD9kM9OVHhQp/PF0ze6qHrWsZhJKSktLS0q+++iouLi45OTkxMZHNZg95tOG+DAwGpVJJmcinrQIAwHhkf2lVUl13KjMv96dL//zbKx989NXVolJfL49nNj8yKSrE1qXZt7OXmvR6U3z0qIRFi8Vy8uRJiUQirhRzuJzHHnvMy8uLEKJQKL797ls3V7fWlhZlR8fmzU86OfGysrOuXi0khJzLy2toaBCJRPfce28/g/c6SHt7+9mcnOyszLff+ss/PvpHbW3tRx9t5fG4Ay9j+D91Yoznt4duyJU6Fz5r+KNZzZNPPslms3Nzcz/77LNt27bFxsbOnj07MTFxmGGaEGKxWDIzM6VSqUQicXR0XL9+vUgkIoQolco9e/a4urq2trZ2dHQ89thjPB4vJyenqKiIEHL+/PnGxkZPT8+77rqrn8F7HUShUJw7d+7s2bOvvvrqJ598Ul9fv2XLFi6XO/AyhvkjAwAA3Mr+1p+cPP3Tj4czauoavt97bM09S19+bkNdY8vm595plbfbujT7ln+9LdhfwHUYlc/3Dxw4wGQxN23a9MGHH6jV6pdeekmn0xFC/vrXv2rVmrVr1z6xeXNjU9P2f28nhCyYv2DDnzYQQqbPmP7E5s39h+++BqmSSDJOnaqpkZ04eSIlJcVZ4Gw0GgZVxvBFh7kSC7l8zc7uRmAwGAkJCc8888z27dsfffRRQsjWrVs3bNjw8ccf5+fnm4axEP/w4cNMJnPDhg3vvPOORqN54403up//jz76SKPR3HPPPRs3bmxubv7mm28IIXPmzHnkkUcIIUlJSRs3buw/fPc1iFQqzcrKqq2tzczMTE5OFggERqNxUGUAAACMOPvL34//ae3MaZOphLrp0fviJ0fNTUl68Zn1Wq3+0JEsW5dm3xpbNELBqBxyKZfLDx8+PG/ufEIIlUqdlZzc3t5+4eJFQgihUAICA7u7Bfj7V0skQ7lAb4MkxMdHRUWZzeZ5c+cuXLjwb3//GyFkdMu4BZNBc3d1lNZ1jcho1sfhcObMmfPiiy9++umnq1atampq2rJly6ZNm77++uvS0lKLxTKo0drb29PT02fPnk0IoVKp06dPVygU+fn53Y/6+/t3/8HPz6+mpmZoBd86yOTJk8PDw81mc0pKyrx589577z1CyGiXAQAA0D/7W39CCGGxWDQalU77tfiU5AQmgyGuklnn6oqma+mfJFrnWtbkZFxNFd4xGiOXlJSYTMZPP/m4p2XxokUsJpMQ8t677xJCtFrt2bNnK8orzGRwka5bX4PQaDQajSby8rJOGb1ydKCXXD29ev9rtz60atWqVatW3dq+b9++ffv22aT/3XfffWs7IcTFxSUtLS0tLa2urm7Pnj0nTpw4ceKEUCh88MEHk5OTe/2WW5WVlZlMpi+++KKnZcGCBUwmkxDyxhtvEEJ0Ol1ubm5lZeVgk323vgbpfhl4enqORhlisViv10dGRg6hYAAAmLDsMn//Do1GEwoFRrOV9qfj8H0jk5+2zrWsKeM7LUNrGI2RZTIZm8V+YvPmWx8ym837D+xvqGu4a8WK0PAbZWVlQxh/gIOMdhm9MhjMopDY1ct72QTdx8en12+ZMWNGrw/Zqn+3lpaWvLy8vLy86upqoVDI4XDYbPbAwzchpK6ujsVibdy48daHzGbz4cOHGxoali1bVlpaWlFRMfBhBzvIyJaRkZEhl8tfffXVIRQMAAAT1njI34QQnU7v7+tlnWsx2HxRSKp1rmVNTi5X65u1ozEym8VqbWtrbW11dXXtaVR2dPC4vDfffIsv4P/Ps88OeXCz2TLAQUa1jF5ZLKRVrgkJjpwxw2/g3+Xj49N/FB69/reu7e7q6srPz8/Nzb127Zqjo2NCQsLDDz8cHR29bds2uVw+8IsSQphMplwub2trEwqFPY2dnZ1cLvf99993cnLa3NtbowGyWCwDHGRUywAAABgI+1v/fatWebtC2bFgzjRbF2LfwgKcJDKlyTxiSy96+Af4WyyWm+9mUyqVWZmZFRXlV64UxERHdzeajcaeT/wtA14B0s8gwy9jmKS1SrXWGBvuPCKjWZNOpzt//vyWLVs2bNiwfft2Lpf7wgsvbN++/YknnoiJiRnahoB+fn4Wi2XXrl09LUql8syZM5WVlYWFhZMmTepuNJlMQ3j+Bz7IqJYBAAAwEPY6/603GCrE1aHB/oSQb749tHTR7MiIYEKISqUhvU3jwW0tmeX18XelJZVt0WGut+99O2q1mhDSfVrh5MlTQsNCc3JyDAb99GnTGxobS0pKnnv++cbGBkJIVnZ2WFh4RUV5dU21QqGQSKXOAoFeryeE6LX621+JQvoaxGwymc1mk8nUfWL5EMoQCATDeRIuFTcG+vBC/OxsD7v9+/dv3bqVEDJ58uTNmzdPnTqVOdTDjzSa3/4+xsbGBgcHnzt3zmAwJCYmNjY2lpWVPf30042NjYSQnJyckJAQsVgsk8mUSmV1dbXgPy+D7s1JBqLXQcxm880vgyGUwefzh/bjAwAA9Ir25ptvjsa4DZWZZmOXm/ek0Rj83M8FVRIZg0k/eiLnwqVCD3fh5sceoFAo5ZXSnd8fqa6p71JpvERuIk+3Eb90S/0NKoM3LtefcBzoBdfbyqXKpDjRMIeSVEn27dtXW1urUqs9PTw8PDxmzkxua2srKiouKCjg8/mPPfaYs0DgKnRVKBRXr1wtKyudOXNmbFzc5YsXW1pavESiHw8dkkokbW2tfD7fzd2d2feph30NYjKaTmac1Gg0arXazc2Nz+dTKJRBlTFr1qzh7HjdqdLvTS+7/45AO5r/tlgsBw8e9PHxueuuux5//PG5c+f6+vp2x9bfuXz5skaj6d5FpC9SqfTgwYN1dXUajcbd3d3d3X369Olyufz69euFhYVOTk7r16/n8/lCoVChUBQVFVVUVCQlJUVHR+fn57e2tnp6eh49erS6uloulzs5Obm6uvZz+GVfg5hMpqysLI1Go9FohEJh98tgUGXMnDmzn5fBQJ4HAACA36GM0mesBSdfMmoaohJ72X5h+N7/cHtGZt6Zk9+MxuD9u3FpH91BFL/k/6x/aSsoESsfeTnvoZVRCaNzCs+E8u2hGzV1yn1b5ziwesmvY5PFYlEoFM7Ot3/D8Nlnn+G+Q4LnAQAAhsRe15/AaIgM5q9I9T10uiIkQMDnjqEjGx984IG+HnryqaeSkpKsWcxAXK9ou1zc+OELU+0ofBNCKBTKQMK3raxfv76vhzZt2pSQkGDNYgAAAIbMLvO3RqMzmIwWi2Vo94FBP554IKLgunz7nqLND09hMcfKy+O7m+6WG/vqGrt2/Hj9znm+s6eO248RQkJCOjs7rXzRL7/80spXvC2bPA8AAGDv7G//kxMZP13KLzKbzP/a9l1JqdjW5Yw3PA7jn68ldXbpv95/zWDEbayD1iJXf76nMDZM8NKjMbauZRQtXLiwr8N6JhQ8DwAAMARjZYJz4JYuSlm6KMXWVYxnIjeHra8kPvHOxY+/vbphTSzXsc+b3uB3JDLl9h+K/EScvz6fQKfhwxkAAADohf3Nf4MVRAbzv3p3pl5n+Ojr/IZmla3LsQ+Xixs//vZKwiTh529N5zjY3ztbAAAAsA7kb+idvxfnq/eSRa7sD/99Kft8jRlnkfRNrTXuPHj920M3Vi8J+Otz8Wy7uucSAAAArAyzdNAnFz7zi7en7zws/mJvxfWKtlVpYZ6uHFsXNeYUl7XuP1lGo1C2vpI0Y/LIbzkPAAAA4wzyN/SHSqU8sjJkxmT3tz4p/L/PL86c4pU2L4jrgBXhhBBS29h16HRFhbR90SzvF/44yYmLpwUAAABuD/kbbi880Om7D2YdO1P76e6ygmtNc6f7pkz14Uzg+zIbW1Sn86rzi5uiQvhfvjMzJmzs7pkNAAAAYw3yNwwIlUK5c75v6kzRrqOS3emSrJ9rpk8RzZvm5yJg27o0qxLLFFk/11wvb/X34v7lqckLZ3pNzD3oxWKxXq+PjIy0dSE2hucBAACGAPkbBsGRTd+wKvTBO4MOZ1ZcyTt46AeKhjtn5hSvmHBXOm0838ur0Rqv3Gi+VNwgrlZGBPLf+HPc0hRvKnVCRm9CCCEZGRk4d53geQAAgCFB/obB0apaaor3CRt/nOunobitPHaDtuPAdS6HnhDtOSXKw8+bRx1HE8IGo6lU3H75WuO1slY6jbowWfTqo5Ow2gQAAACGA/kbBqqjtbz62v7a0nQ6k+sbtSIgdg2b47bkHtLUpjl6pjb9bN2ZX2QCHis63DU23DUkwNl+Z8TVGuP1itaispYSsdxoMMdGOL/8aPSCGSJHNv6+AAAAwHAhT8BtWCzm5uo8adGeVtlFJ9fQSSnPeYen0eisng4eQoc/3Rv6p3tDq2SdP+U3515u+uz7QgaDFuTLD/ThB/nyg/0FYz+L6wwmqUxZJmmX1Cqksg4LIdFhgs0PhC+YIXJznlhr3AEAAGBUIX9Dn4wGdX35KUnh9ypFjdBn6tQ7/u4RMIuQPpeXBPnygnx561YEN7RoLhS15l9rvVhYfyJHwmbR/b14Pp48Py8nPy+e0NnBmj9FX0xmS0OzqqahU1avlDV01jZ1WcyWQB9eYrTwsdUhiTGuOMMSAAAARgMSBvRCq2qpuX5QWvyDyaAVhaQmLPkr1yVw4N8ucnNYscB3xQJfQoi0rqvghvx6peJGpeLsRZnJZOE4MrzcOG4uDu5Cjruro4erozOfPdoT5DqdsaVd29ymampVN7WqW9vVDc0qg9HswKKHBzrNineNCQ2NnyR04TNHtQwAAAAA5G/4L8qWEknhnvqKU0y2ICBmTUDsGiabP5wBA7y5Ad7cuxf6EUK0OlO5tKNUopTIuqT1qryC2ha5lhBCoRAnLlPAYznxWAInlhOXxXFgOLDpDmyGI5vGZtMZNCqLRe/eb4TFpNGoFEKI3mAymiyEEKPBbDCatHqTVmtU64warUGjNao1RrlS19mlVXTqFUqtWmskhNBpFJGbY4APd1KwW5BvUFQwP8CbO5G3MQEAAADrG8X83VJ/I+fwW6M3vq2IgkW2LmHkdS/yFhfsaG8o5LtFxM5/3Tt0MYU6wi8PNosWG+4cG/7b/iFqjbG6QdXUqmls1Ta3aVradY0tmiqZoqvL0KUxmEyWIVyFwaA6cRg8DsND6BDsy/EQCt2FbDcXtq8nx9vDkU5D2h4ZYWFhvbavW7dOo9Hc2r5jxw4Hh16WHtl1/5CQkPz8/Fs7AwAA9INisQwl4txWe2OxtqtpNEa2OTbXw9kzxtZVjBijXiUrOSop/F7b1eTmPzMw9j5X3yRbF/UrtcbYqTZ0dBmMJkuXytD9UlVpjCazhRDCYlBZTBohhEGnstk0NovGc2Q4cRlMxli/13McEIvFAQEBNBrt1ocuXrxoMplubU9KShqX/cvLy/t6KwIAANCr0crfMPaplbU1Nw5VXztALGafyDuDJt/vwBuHU/sAAAAAYwry90Qkb7gqLfqhUZztwPP0m3S336S7GSyerYsCAAAAmBCQvycQs8nQJMmpurpL0XSN7xYZELfGO3QJhdrLR+oAAAAAMEqQvycEvaZdVnJEWrxXp5Z7Bs0NjLt/PC1hBwAAALAj2H9wnFMpZNLivbIbtNqx6QAACVVJREFUhyhUuk/EsqApDzpwPWxdFAAAAMDEhfnvcUvecFVcsKNZmsfh+/jHrPaLuovGGBMHTwIAAABMZMjf443ZpK+vPF1VsLNTXuUsiguMXesZPJ9CwZZ8AAAAAGMC8vf4oVPLq6/try7eZzSoRCELg6c8xBOG2LooAAAAAPgvyN/jQUdrefW1/bWl6XQm1zdyeUDsGjbHzdZFAQAAAEAvkL/tWPeh8dKiPa2yi07CUP+YVd7haTQ6y9Z1AQAAAECfkL/tktGgri8/JSn8vqu92tU3MSB2rUfALEIotq4LAAAAAG4D+dvO6NSt1dd+lBb/YDJoRSGpIfGPcF0CbV0UAAAAAAwU8rfdULaUSAr31FecYrIFfpPuDohdw2TzbV0UAAAAAAwO8vdY173IW1ywo72hkO8WERC31jt0MYWKg5MAAAAA7BLy99hl1KtkJUclhd9ru5rc/GcGxt7n6ptk66IAAAAAYFgwjToWqTvqaq4frLn+o8Vs8gpbHDT5AY7A39ZFAQAAAMAIwPz32CJvuCot+qFRnO3A8/SbdLffpJUMlpOtiwIAAACAEYP8PSaYTYYmSU7V1V2Kpmt8t8iAuDXeoUsoVJqt6wIAAACAEYb8bWN6Tbus5Ii0eK9OLfcMmhsYd7+zZ4ytiwIAAACA0YL13zajUsikxXtlNw5RqHSfiGVBUx504HrYuigAAAAAGF2Y/7YBecNVccGOZmkeh+/jH7PaL+ouGsPB1kUBAAAAgDUgf1uPxWyUlRyVFO7uape6+iYGxt3v7j8Th8YDAAAATCj/lb8bKjMLTr1sw2ommvjF74tCUm1dBQAAAABYTy/rv6OmrrJ+HROEhVgo/5nwvnF5n22LAQAAAADr6yV/u3lHWb+OieiyrQsAAAAAAKuj2roAAAAAAIAJBPkbAAAAAMB6kL8BAAAAAKwH+RsAAAAAwHqQvwEAAAAArAf5GwAAAADAepC/AQAAAACsB/kbAAAAAMB6kL8BAAAAAKwH+RsAAAAAwHqQvwEAAAAArAf5GwAAAADAepC/AQAAAACsB/kbAAAAAMB6hpK/c/Mur1izWVpTN4I9b2Yyma7fqPxyx4ELl4uHUF43i8WyZ9+Jb78/svqhZ95+/1OTyTTkoQAAAAAARspQ8jebzXZ25rGYzCH0bJW33/a7SkqrDh3L+nLHgebmtiGU1+2rnT/W1NY/dP+dr734WKdKbUT+BgAAAIAxYCj5Oykh+utt74k83Qbbs7NT9da7n972u6Inha5auXgIhd3sxyOnRR5uhJDY6PAP3nluIO8WAAAAAABGm/XWfxuMxjfe/biuvmkgnRkM+nCupdPr29s7KJThjAEAAAAAMPIGHXM7O1Vnf7qUeeb8PSsWzk6eWl4pPZ2Zl5178ZvP39v66bd55wu8Re5v/++TXiL33/XMPntBIq3t6Ox6/8Ptfn5eD6y+Y+AXtVgsh45mVVbVlJZLeByH5576o4+PJyFE3q784qt9Hu4ujU1tSmXny88/ynfiHj+Ve7ngGiEkO+eCrK7J19vjwfvu7GfwXgdpkysysn8+fiL3Hx+8+M77n9XUNnz9+ftOPM7AyxjsEwsAAAAAE8Gg57/b2hWSatml/GKzyUwIEboIysU1DY0tn/17zwNrl7/9+uZqWcO2f++9tefi1OSQYD++E+/l5zYMKnwTQr7bfZTFYj7/9B+3/+stlUb7+NNva7V6Qsj//uVfapXmDw/d/fJzGxoaW7Z+spMQkrZ49lN/fpgQMicl8eXnNvQfvvsapKKy+sixbElN7eGj2anzZzo7CwwGw6DKAAAAAAC41aDzd4Cfd8rMqT1fCl0EkeFBhJCN69cE+nsnJsTExUaUVlTd2nPIWtvafzhwYsnCFEIIlUadN2dam1xx7pd8QgiFQgkJ8evuFhToUymuGcL4vQ4yPSkuNjrMbDIvTp21bOncLz/9CyFkVMsAAAAAgIlgKMusaTTazV9SqVRCCJ32a5R3dHDQqLW99hya4mvlRqNpy9//3dOyPG0em8kkhPzrb68SQrRa3cnT526UVlks5iGM39cgdDqdRqP5eHtYpwwAAAAAmAiGdZujdUhr6hwcWC8/t+HWh8wm83d7jtTUNt63Oq3oWvC1GxVDGH+Ag4x2GQAAAAAwEdhB/maxWc0t8uaWNnc3YU+jUtnJ43H/5+Utzs78/31505AHN5stAxxkVMsAAAAAgAnCqufPUyhUk2nQazOCA/0sFsunX+zuaWlv70g/mVNSKr5wuXhKXFR3o9Fgslj+0+O3P91Gf4MMvwwAAAAAgP82lPlvnU5HCNEbjN1fdh8tafxPsNbpdVqtrteebq7OP1+4Ul4p7epSR0WEsNl9nomjUmkIId2HxiclREeFB2Vk/azXG1OSp9bVNxZfr3j7tSe6txI/fio3KjKopLSqqrpW3q6orKpxcebrdAZCiEarv+3P0r1HeK+DGI0ms9lsMpm6V7EPoQwXZ/7gn10AAAAAGM9ob775Zs8XXfKqBnFWQMTcfr7h+o3K7/YcldU1KpSdfj4iWW3Drh+OdnSqNBptVETwmdxLPx7JVKk1hBA6nf79D8d6enq4Cz3chXnnC3LP5cdEhYaG+Pd1ifJK6c7vj1TX1HepNF4iNy+R+9w5SS2t8oLCGxcuFwn4vP956hEXZ76bm4u8XXkxv+h6SeXclMSE+Ohz5wuamtt8vT127ztWKa5pbmlzFvA9PYRMJqOva/U1iMloPHLsjFqjUak1Hu5CZ4EThUIZVBmpc6fT6f29vakuyxGFpPJcgvrpAwAAAADjDMVy02qJhsrMglMvz7nrDRsWNHHkHH4rfvH7opBUWxcCAAAAANZjs/svl67c2NdDrz2/MXlmvJ1eCwAAAACgHzbL3ycOfj4urwUAAAAA0A+r7n8CAAAAADDBIX8DAAAAAFgP8jcAAAAAgPUgfwMAAAAAWA/yNwAAAACA9SB/AwAAAABYD/I3AAAAAID1IH8DAAAAAFgP8jcAAAAAgPUgfwMAAAAAWA/yNwAAAACA9SB/AwAAAABYD/I3AAAAAID1IH8DAAAAAFgP8jcAAAAAgPXQb23KOfyW9esAAAAAAJgIKBaLpecLbVdze2ORDauZaJw9Y9lcd1tXAQAAAADW81/5GwAAAAAARhXWfwMAAAAAWA/yNwAAAACA9SB/AwAAAABYz/8DpnfTqHHJtBAAAAAASUVORK5CYII=\n", + "image/png": "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\n", "text/plain": [ "" ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "model.visualize(show_variables=True)" + "model.visualize(show_only_variable=('biomass','B'))" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "acoustic-circulation", "metadata": {}, "outputs": [], "source": [ - "ds_in = xs.create_setup(model=model,clocks={'clock':range(100)},output_vars={'biomass__B':'clock'})" + "ds_in = xs.create_setup(model=model,clocks={'clock':range(100)},output_vars={'otherclass__somevar':'clock'})" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "id": "controlling-breakfast", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "_dep_processes: {'leaf_area': set(), 'f_light': {'leaf_area'}, 'halve_f_light': {'f_light'}, 'maxrad': set(), 'growth': {'maxrad', 'halve_f_light'}, 'death': set(), 'biomass': {'growth', 'death'}, 'otherclass': {'biomass'}}\n", + "_dep_processes dict: {'leaf_area': [], 'f_light': ['leaf_area'], 'halve_f_light': ['f_light'], 'maxrad': [], 'growth': ['maxrad', 'halve_f_light'], 'death': [], 'biomass': ['growth', 'death'], 'otherclass': ['biomass']}\n" + ] }, { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" + "ename": "NameError", + "evalue": "name 'sin' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#plot to verify that it works\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mds_in\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxsimlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0motherclass__somevar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/xr_accessor.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, model, batch_dim, check_dims, validate, store, encoding, decoding, hooks, parallel, scheduler, safe_mode)\u001b[0m\n\u001b[1;32m 831\u001b[0m )\n\u001b[1;32m 832\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 833\u001b[0;31m \u001b[0mdriver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 834\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 835\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mdriver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_results\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/drivers.py\u001b[0m in \u001b[0;36mrun_model\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 477\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbatch_dim\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 478\u001b[0;31m _run(\n\u001b[0m\u001b[1;32m 479\u001b[0m \u001b[0mds_in\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 480\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/drivers.py\u001b[0m in \u001b[0;36m_run\u001b[0;34m(dataset, model, store, hooks, validate, batch, batch_size, parallel, scheduler)\u001b[0m\n\u001b[1;32m 353\u001b[0m \u001b[0min_vars\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_input_vars\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds_step\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 354\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate_state\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0min_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_inputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_static\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 355\u001b[0;31m \u001b[0msignal\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"run_step\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrt_context\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mexecute_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 356\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 357\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msignal\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mRuntimeSignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBREAK\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/model.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, stage, runtime_context, hooks, validate, parallel, scheduler)\u001b[0m\n\u001b[1;32m 1050\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1051\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp_obj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_processes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1052\u001b[0;31m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msignal_process\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_execute_process\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mexecute_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1053\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1054\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msignal_process\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mRuntimeSignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBREAK\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/model.py\u001b[0m in \u001b[0;36m_execute_process\u001b[0;34m(self, p_obj, stage, runtime_context, hooks, validate, state)\u001b[0m\n\u001b[1;32m 869\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mp_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msignal_pre\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 870\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 871\u001b[0;31m state_out, signal_out = executor.execute(\n\u001b[0m\u001b[1;32m 872\u001b[0m \u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mruntime_context\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 873\u001b[0m )\n", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/process.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, p_obj, stage, runtime_context, state)\u001b[0m\n\u001b[1;32m 528\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mRuntimeSignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNONE\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 529\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 530\u001b[0;31m \u001b[0msignal_out\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexecutor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mruntime_context\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 531\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 532\u001b[0m \u001b[0mskeys\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__xsimlab_state_keys__\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mout_vars\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/process.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, p_obj, runtime_context, state)\u001b[0m\n\u001b[1;32m 392\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mruntime_context\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 394\u001b[0;31m \u001b[0msignal\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 396\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msignal\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36mrun_step\u001b[0;34m(self, n)\u001b[0m\n\u001b[1;32m 49\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mxs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mruntime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'step'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmaxrad\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0msin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'sin' is not defined" + ] } ], "source": [ "#plot to verify that it works\n", - "ds_in.xsimlab.run(model).biomass__B.plot()" + "ds_in.xsimlab.run(model).otherclass__somevar.plot()" ] } ], diff --git a/xsimlab/dot.py b/xsimlab/dot.py index c71ca04a..72a12f0e 100644 --- a/xsimlab/dot.py +++ b/xsimlab/dot.py @@ -114,7 +114,10 @@ def add_inout_arrows(self): for var_name, var in variables_dict(p_cls).items(): # test if the variable is inout - if var.metadata["intent"] == VarIntent.INOUT: + if ( + var.metadata["intent"] == VarIntent.INOUT + and var.metadata["var_type"] == VarType.VARIABLE + ): target_keys = _get_target_keys(p_obj, var_name) # now again cycle through all processes to see if there is a variable with the same reference @@ -129,7 +132,6 @@ def add_inout_arrows(self): and var2.metadata["intent"] == VarIntent.IN ): edge_ends = p_name, p2_name - print(target_keys, target2_keys, var_name, var2_name) self.g.edge( *edge_ends, weight="200", **INOUT_EDGE_ATTRS ) diff --git a/xsimlab/model.py b/xsimlab/model.py index 135aaf61..0cdd4c93 100644 --- a/xsimlab/model.py +++ b/xsimlab/model.py @@ -14,7 +14,7 @@ RuntimeSignal, SimulationStage, ) -from .utils import AttrMapping, Frozen, variables_dict +from .utils import AttrMapping, Frozen, variables_dict, as_variable_key from .formatting import repr_model @@ -401,11 +401,13 @@ def get_processes_to_validate(self): return {k: list(v) for k, v in processes_to_validate.items()} - def get_process_dependencies(self): + def get_process_dependencies(self, custom_dependencies=None): """Return a dictionary where keys are each process of the model and values are lists of the names of dependent processes (or empty lists for processes that have no dependencies). + inputs: dependencies: a {('p_name','var_name'):'dep_p_name'} dictionary + Process 1 depends on process 2 if the later declares a variable (resp. a foreign variable) with intent='out' that itself (resp. its target variable) is needed in process 1. @@ -414,6 +416,7 @@ def get_process_dependencies(self): self._dep_processes = {k: set() for k in self._processes_obj} d_keys = {} # all state/on-demand keys for each process + skip_deps = {} # dict of dependencies to skip {'p_name':key} for p_name, p_obj in self._processes_obj.items(): d_keys[p_name] = _flatten_keys( @@ -423,6 +426,16 @@ def get_process_dependencies(self): ] ) + if custom_dependencies is not None: + for dep_key in custom_dependencies: + p_name, var_name = as_variable_key(dep_key) + dep_p_name = custom_dependencies[dep_key] + # TODO: fix also for on-demand variables + skip_deps[p_name] = self._processes_obj[p_name].__xsimlab_state_keys__[ + var_name + ] + self._dep_processes[p_name].add(dep_p_name) + for p_name, p_obj in self._processes_obj.items(): for var in filter_variables(p_obj, intent=VarIntent.OUT).values(): if var.metadata["var_type"] == VarType.ON_DEMAND: @@ -430,8 +443,16 @@ def get_process_dependencies(self): else: key = p_obj.__xsimlab_state_keys__[var.name] + # iterate through all processes names out_var->pn for pn in self._processes_obj: + # check if this is a different process and the process key is the same + # -> then we have an out process that is used as input here! + # here also check if the process is not in the dependencies list (how?) if pn != p_name and key in d_keys[pn]: + if pn in skip_deps: + if skip_deps[pn] == key: + # do not add this process, since it is in the dependencies list + continue self._dep_processes[pn].add(p_name) self._dep_processes = {k: list(v) for k, v in self._dep_processes.items()} @@ -534,13 +555,17 @@ class Model(AttrMapping): active = [] - def __init__(self, processes): + def __init__(self, processes, custom_dependencies=None): """ Parameters ---------- processes : dict Dictionnary with process names as keys and classes (decorated with :func:`process`) as values. + custom_dependencies : dict + Dictionary with dependencies of processes wher this is not clear from + the model, in the case of intent='inout' variables. the dictionary should be in the form: + {('process_name','variable_name'):'dependent_process_name'} or {'p_name__var_name':'dep_p_name'} Raises ------ @@ -572,7 +597,8 @@ def __init__(self, processes): self._processes_to_validate = builder.get_processes_to_validate() - self._dep_processes = builder.get_process_dependencies() + self._custom_dependencies = custom_dependencies + self._dep_processes = builder.get_process_dependencies(custom_dependencies) self._processes = builder.get_sorted_processes() super(Model, self).__init__(self._processes) @@ -1035,11 +1061,11 @@ def clone(self): Returns ------- cloned : Model - New Model instance with the same processes. + New Model instance with the same processes. and defined dependencies """ processes_cls = {k: type(obj) for k, obj in self._processes.items()} - return type(self)(processes_cls) + return type(self)(processes_cls, self._custom_dependencies) def update_processes(self, processes): """Add or replace processe(s) in this model. diff --git a/xsimlab/utils.py b/xsimlab/utils.py index bbf2ddd6..a74a7c6f 100644 --- a/xsimlab/utils.py +++ b/xsimlab/utils.py @@ -43,6 +43,33 @@ def __repr__(self): """ +def as_variable_key(key): + """Returns ``key`` as a tuple of the form + ``('process_name', 'var_name')``. + + If ``key`` is given as a string, then process name and variable + name must be separated unambiguously by '__' (double underscore) + and must not be empty. + + """ + key_tuple = None + + if isinstance(key, tuple) and len(key) == 2: + key_tuple = key + + elif isinstance(key, str): + key_split = key.split("__") + if len(key_split) == 2: + p_name, var_name = key_split + if p_name and var_name: + key_tuple = (p_name, var_name) + + if key_tuple is None: + raise ValueError(f"{key!r} is not a valid input variable key") + + return key_tuple + + def variables_dict(process_cls): """Get all xsimlab variables declared in a process. diff --git a/xsimlab/variable.py b/xsimlab/variable.py index d6b642a1..1aedb970 100644 --- a/xsimlab/variable.py +++ b/xsimlab/variable.py @@ -445,8 +445,6 @@ def foreign(other_process_cls, var_name, intent="in"): model. """ - if intent == "inout": - raise ValueError("intent='inout' is not supported for foreign variables") ref_var = attr.fields_dict(other_process_cls)[var_name] diff --git a/xsimlab/xr_accessor.py b/xsimlab/xr_accessor.py index a12343da..8fb9d3fd 100644 --- a/xsimlab/xr_accessor.py +++ b/xsimlab/xr_accessor.py @@ -11,7 +11,7 @@ from .drivers import XarraySimulationDriver from .model import get_model_variables, Model -from .utils import Frozen, variables_dict +from .utils import Frozen, variables_dict, as_variable_key from .variable import VarType @@ -44,33 +44,6 @@ def _maybe_get_model_from_context(model): return model -def as_variable_key(key): - """Returns ``key`` as a tuple of the form - ``('process_name', 'var_name')``. - - If ``key`` is given as a string, then process name and variable - name must be separated unambiguously by '__' (double underscore) - and must not be empty. - - """ - key_tuple = None - - if isinstance(key, tuple) and len(key) == 2: - key_tuple = key - - elif isinstance(key, str): - key_split = key.split("__") - if len(key_split) == 2: - p_name, var_name = key_split - if p_name and var_name: - key_tuple = (p_name, var_name) - - if key_tuple is None: - raise ValueError(f"{key!r} is not a valid input variable key") - - return key_tuple - - def _flatten_inputs(input_vars): """Returns ``input_vars`` as a flat dictionary where keys are tuples in the form ``(process_name, var_name)``. Raises an error if the From e7f76fde02512b8dc9d013b8fd2903b4074f1c08 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Sat, 20 Mar 2021 21:58:36 +0100 Subject: [PATCH 4/9] fixed failing tests, need tests still --- notebooks/cyclic.ipynb | 255 +++++++++++++++++++++++++++++---- xsimlab/tests/test_dot.py | 2 +- xsimlab/tests/test_variable.py | 3 - 3 files changed, 229 insertions(+), 31 deletions(-) diff --git a/notebooks/cyclic.ipynb b/notebooks/cyclic.ipynb index bbb5a4cb..d7dcc2ca 100644 --- a/notebooks/cyclic.ipynb +++ b/notebooks/cyclic.ipynb @@ -14,7 +14,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "thermal-measure", + "id": "absolute-spyware", "metadata": {}, "outputs": [ { @@ -90,7 +90,7 @@ " \n", " @xs.runtime(args='step')\n", " def run_step(self,n):\n", - " self.maxrad = 1+sin(n/math.pi)\n", + " self.maxrad = 1+math.sin(n/math.pi)\n", " \n", " \n", "#this process actually adds some to 'biomass' group\n", @@ -135,7 +135,7 @@ " \n", "@xs.process\n", "class OtherClass:\n", - " biomass = xs.foreign(Biomass,\"out_B\", intent='in')\n", + " biomass = xs.foreign(Biomass,\"B\", intent='in')\n", " somevar = xs.variable(intent='out')\n", " \n", " def initialize(self):\n", @@ -156,8 +156,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "_dep_processes: {'halve_f_light': {'f_light'}, 'f_light': {'leaf_area'}, 'maxrad': set(), 'leaf_area': set(), 'growth': {'maxrad', 'halve_f_light'}, 'death': set(), 'biomass': {'growth', 'death'}, 'otherclass': {'biomass'}}\n", - "_dep_processes dict: {'halve_f_light': ['f_light'], 'f_light': ['leaf_area'], 'maxrad': [], 'leaf_area': [], 'growth': ['maxrad', 'halve_f_light'], 'death': [], 'biomass': ['growth', 'death'], 'otherclass': ['biomass']}\n" + "_dep_processes: {'halve_f_light': {'f_light'}, 'f_light': {'leaf_area'}, 'maxrad': set(), 'leaf_area': set(), 'growth': {'halve_f_light', 'maxrad'}, 'death': set(), 'biomass': {'death', 'growth'}, 'otherclass': {'biomass'}}\n", + "_dep_processes dict: {'halve_f_light': ['f_light'], 'f_light': ['leaf_area'], 'maxrad': [], 'leaf_area': [], 'growth': ['halve_f_light', 'maxrad'], 'death': [], 'biomass': ['death', 'growth'], 'otherclass': ['biomass']}\n" ] } ], @@ -173,7 +173,7 @@ " 'death':BiomassDeath,\n", " 'biomass':Biomass,\n", " 'otherclass':OtherClass\n", - " },custom_dependencies = {'growth__frac_light':'halve_f_light'}\n", + " },custom_dependencies = {'growth__frac_light':'halve_f_light','otherclass__biomass':'biomass'}\n", ")" ] }, @@ -185,7 +185,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "" ] @@ -208,7 +208,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "" ] @@ -242,28 +242,229 @@ "name": "stdout", "output_type": "stream", "text": [ - "_dep_processes: {'leaf_area': set(), 'f_light': {'leaf_area'}, 'halve_f_light': {'f_light'}, 'maxrad': set(), 'growth': {'maxrad', 'halve_f_light'}, 'death': set(), 'biomass': {'growth', 'death'}, 'otherclass': {'biomass'}}\n", - "_dep_processes dict: {'leaf_area': [], 'f_light': ['leaf_area'], 'halve_f_light': ['f_light'], 'maxrad': [], 'growth': ['maxrad', 'halve_f_light'], 'death': [], 'biomass': ['growth', 'death'], 'otherclass': ['biomass']}\n" + "_dep_processes: {'leaf_area': set(), 'f_light': {'leaf_area'}, 'halve_f_light': {'f_light'}, 'maxrad': set(), 'growth': {'halve_f_light', 'maxrad'}, 'death': set(), 'biomass': {'death', 'growth'}, 'otherclass': {'biomass'}}\n", + "_dep_processes dict: {'leaf_area': [], 'f_light': ['leaf_area'], 'halve_f_light': ['f_light'], 'maxrad': [], 'growth': ['halve_f_light', 'maxrad'], 'death': [], 'biomass': ['death', 'growth'], 'otherclass': ['biomass']}\n", + "Step: 0 out_B: 1.011452127744409\n", + "otherclass: 1.011452127744409\n", + "Step: 1 out_B: 1.0266748878158212\n", + "otherclass: 1.0266748878158212\n", + "Step: 2 out_B: 1.045320250903847\n", + "otherclass: 1.045320250903847\n", + "Step: 3 out_B: 1.0667018912498643\n", + "otherclass: 1.0667018912498643\n", + "Step: 4 out_B: 1.0898581900078508\n", + "otherclass: 1.0898581900078508\n", + "Step: 5 out_B: 1.1136427483542828\n", + "otherclass: 1.1136427483542828\n", + "Step: 6 out_B: 1.1368353953079635\n", + "otherclass: 1.1368353953079635\n", + "Step: 7 out_B: 1.158264030820504\n", + "otherclass: 1.158264030820504\n", + "Step: 8 out_B: 1.1769253946250038\n", + "otherclass: 1.1769253946250038\n", + "Step: 9 out_B: 1.1920916442459513\n", + "otherclass: 1.1920916442459513\n", + "Step: 10 out_B: 1.203390082965359\n", + "otherclass: 1.203390082965359\n", + "Step: 11 out_B: 1.2108458376254678\n", + "otherclass: 1.2108458376254678\n", + "Step: 12 out_B: 1.2148816032034735\n", + "otherclass: 1.2148816032034735\n", + "Step: 13 out_B: 1.2162740799126601\n", + "otherclass: 1.2162740799126601\n", + "Step: 14 out_B: 1.2160723937215083\n", + "otherclass: 1.2160723937215083\n", + "Step: 15 out_B: 1.2154885111439815\n", + "otherclass: 1.2154885111439815\n", + "Step: 16 out_B: 1.2157726022848685\n", + "otherclass: 1.2157726022848685\n", + "Step: 17 out_B: 1.2180871427824536\n", + "otherclass: 1.2180871427824536\n", + "Step: 18 out_B: 1.2233924872341286\n", + "otherclass: 1.2233924872341286\n", + "Step: 19 out_B: 1.232354293091122\n", + "otherclass: 1.232354293091122\n", + "Step: 20 out_B: 1.2452802454348688\n", + "otherclass: 1.2452802454348688\n", + "Step: 21 out_B: 1.2620906105164822\n", + "otherclass: 1.2620906105164822\n", + "Step: 22 out_B: 1.2823245125977034\n", + "otherclass: 1.2823245125977034\n", + "Step: 23 out_B: 1.3051814569925106\n", + "otherclass: 1.3051814569925106\n", + "Step: 24 out_B: 1.329595291040203\n", + "otherclass: 1.329595291040203\n", + "Step: 25 out_B: 1.3543352785208522\n", + "otherclass: 1.3543352785208522\n", + "Step: 26 out_B: 1.3781262197578827\n", + "otherclass: 1.3781262197578827\n", + "Step: 27 out_B: 1.399776836262679\n", + "otherclass: 1.399776836262679\n", + "Step: 28 out_B: 1.418303503653965\n", + "otherclass: 1.418303503653965\n", + "Step: 29 out_B: 1.4330355553620175\n", + "otherclass: 1.4330355553620175\n", + "Step: 30 out_B: 1.4436893894770468\n", + "otherclass: 1.4436893894770468\n", + "Step: 31 out_B: 1.4504017276978034\n", + "otherclass: 1.4504017276978034\n", + "Step: 32 out_B: 1.4537173016403393\n", + "otherclass: 1.4537173016403393\n", + "Step: 33 out_B: 1.45453215714713\n", + "otherclass: 1.45453215714713\n", + "Step: 34 out_B: 1.4539995367983658\n", + "otherclass: 1.4539995367983658\n", + "Step: 35 out_B: 1.4534098150821095\n", + "otherclass: 1.4534098150821095\n", + "Step: 36 out_B: 1.4540584711744586\n", + "otherclass: 1.4540584711744586\n", + "Step: 37 out_B: 1.457116399251865\n", + "otherclass: 1.457116399251865\n", + "Step: 38 out_B: 1.463515325079495\n", + "otherclass: 1.463515325079495\n", + "Step: 39 out_B: 1.4738584085305924\n", + "otherclass: 1.4738584085305924\n", + "Step: 40 out_B: 1.4883630032392112\n", + "otherclass: 1.4883630032392112\n", + "Step: 41 out_B: 1.5068395529833731\n", + "otherclass: 1.5068395529833731\n", + "Step: 42 out_B: 1.528707936072495\n", + "otherclass: 1.528707936072495\n", + "Step: 43 out_B: 1.5530501264323313\n", + "otherclass: 1.5530501264323313\n", + "Step: 44 out_B: 1.578695570583507\n", + "otherclass: 1.578695570583507\n", + "Step: 45 out_B: 1.604332980734315\n", + "otherclass: 1.604332980734315\n", + "Step: 46 out_B: 1.62863934636194\n", + "otherclass: 1.62863934636194\n", + "Step: 47 out_B: 1.650414224584772\n", + "otherclass: 1.650414224584772\n", + "Step: 48 out_B: 1.6687054163754926\n", + "otherclass: 1.6687054163754926\n", + "Step: 49 out_B: 1.6829116984591457\n", + "otherclass: 1.6829116984591457\n", + "Step: 50 out_B: 1.6928499093559553\n", + "otherclass: 1.6928499093559553\n", + "Step: 51 out_B: 1.6987774939545737\n", + "otherclass: 1.6987774939545737\n", + "Step: 52 out_B: 1.7013671310297664\n", + "otherclass: 1.7013671310297664\n", + "Step: 53 out_B: 1.701636330311303\n", + "otherclass: 1.701636330311303\n", + "Step: 54 out_B: 1.7008406743215811\n", + "otherclass: 1.7008406743215811\n", + "Step: 55 out_B: 1.700343604398861\n", + "otherclass: 1.700343604398861\n", + "Step: 56 out_B: 1.7014776686583344\n", + "otherclass: 1.7014776686583344\n", + "Step: 57 out_B: 1.7054119201046138\n", + "otherclass: 1.7054119201046138\n", + "Step: 58 out_B: 1.7130381595061577\n", + "otherclass: 1.7130381595061577\n", + "Step: 59 out_B: 1.7248857225717487\n", + "otherclass: 1.7248857225717487\n", + "Step: 60 out_B: 1.7410712523602727\n", + "otherclass: 1.7410712523602727\n", + "Step: 61 out_B: 1.7612868525037795\n", + "otherclass: 1.7612868525037795\n", + "Step: 62 out_B: 1.7848273089388242\n", + "otherclass: 1.7848273089388242\n", + "Step: 63 out_B: 1.8106545346051248\n", + "otherclass: 1.8106545346051248\n", + "Step: 64 out_B: 1.837494761662\n", + "otherclass: 1.837494761662\n", + "Step: 65 out_B: 1.8639611155950397\n", + "otherclass: 1.8639611155950397\n", + "Step: 66 out_B: 1.888691171631072\n", + "otherclass: 1.888691171631072\n", + "Step: 67 out_B: 1.910486373362779\n", + "otherclass: 1.910486373362779\n", + "Step: 68 out_B: 1.9284384969022836\n", + "otherclass: 1.9284384969022836\n", + "Step: 69 out_B: 1.9420284112817348\n", + "otherclass: 1.9420284112817348\n", + "Step: 70 out_B: 1.9511846946801095\n", + "otherclass: 1.9511846946801095\n", + "Step: 71 out_B: 1.9562941819015172\n", + "otherclass: 1.9562941819015172\n", + "Step: 72 out_B: 1.9581626026454593\n", + "otherclass: 1.9581626026454593\n", + "Step: 73 out_B: 1.957930007187579\n", + "otherclass: 1.957930007187579\n", + "Step: 74 out_B: 1.9569513921729538\n", + "otherclass: 1.9569513921729538\n", + "Step: 75 out_B: 1.9566567902871224\n", + "otherclass: 1.9566567902871224\n", + "Step: 76 out_B: 1.9584065613935333\n", + "otherclass: 1.9584065613935333\n", + "Step: 77 out_B: 1.9633568352605735\n", + "otherclass: 1.9633568352605735\n", + "Step: 78 out_B: 1.9723476183476696\n", + "otherclass: 1.9723476183476696\n", + "Step: 79 out_B: 1.9858228089270507\n", + "otherclass: 1.9858228089270507\n", + "Step: 80 out_B: 2.0037879843598074\n", + "otherclass: 2.0037879843598074\n", + "Step: 81 out_B: 2.0258087359205565\n", + "otherclass: 2.0258087359205565\n", + "Step: 82 out_B: 2.051049569305229\n", + "otherclass: 2.051049569305229\n", + "Step: 83 out_B: 2.0783507423323577\n", + "otherclass: 2.0783507423323577\n", + "Step: 84 out_B: 2.106337600149586\n", + "otherclass: 2.106337600149586\n", + "Step: 85 out_B: 2.1335538844137076\n", + "otherclass: 2.1335538844137076\n", + "Step: 86 out_B: 2.1586073508402266\n", + "otherclass: 2.1586073508402266\n", + "Step: 87 out_B: 2.1803133909321692\n", + "otherclass: 2.1803133909321692\n", + "Step: 88 out_B: 2.19782099557389\n", + "otherclass: 2.19782099557389\n", + "Step: 89 out_B: 2.2107060513475547\n", + "otherclass: 2.2107060513475547\n", + "Step: 90 out_B: 2.2190200039847654\n", + "otherclass: 2.2190200039847654\n", + "Step: 91 out_B: 2.2232871567783765\n", + "otherclass: 2.2232871567783765\n", + "Step: 92 out_B: 2.2244504756933354\n", + "otherclass: 2.2244504756933354\n", + "Step: 93 out_B: 2.2237725016207324\n", + "otherclass: 2.2237725016207324\n", + "Step: 94 out_B: 2.2227035178258157\n", + "otherclass: 2.2227035178258157\n", + "Step: 95 out_B: 2.222732518754895\n", + "otherclass: 2.222732518754895\n", + "Step: 96 out_B: 2.2252374118607308\n", + "otherclass: 2.2252374118607308\n", + "Step: 97 out_B: 2.2313495349971983\n", + "otherclass: 2.2313495349971983\n", + "Step: 98 out_B: 2.2418447155784116\n", + "otherclass: 2.2418447155784116\n" ] }, { - "ename": "NameError", - "evalue": "name 'sin' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m#plot to verify that it works\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mds_in\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxsimlab\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0motherclass__somevar\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/xr_accessor.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, model, batch_dim, check_dims, validate, store, encoding, decoding, hooks, parallel, scheduler, safe_mode)\u001b[0m\n\u001b[1;32m 831\u001b[0m )\n\u001b[1;32m 832\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 833\u001b[0;31m \u001b[0mdriver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 834\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 835\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mdriver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_results\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/drivers.py\u001b[0m in \u001b[0;36mrun_model\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 476\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 477\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbatch_dim\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 478\u001b[0;31m _run(\n\u001b[0m\u001b[1;32m 479\u001b[0m \u001b[0mds_in\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 480\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/drivers.py\u001b[0m in \u001b[0;36m_run\u001b[0;34m(dataset, model, store, hooks, validate, batch, batch_size, parallel, scheduler)\u001b[0m\n\u001b[1;32m 353\u001b[0m \u001b[0min_vars\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_input_vars\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds_step\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 354\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate_state\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0min_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_inputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_static\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 355\u001b[0;31m \u001b[0msignal\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"run_step\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrt_context\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mexecute_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 356\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 357\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msignal\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mRuntimeSignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBREAK\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/model.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, stage, runtime_context, hooks, validate, parallel, scheduler)\u001b[0m\n\u001b[1;32m 1050\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1051\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp_obj\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_processes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1052\u001b[0;31m \u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0m_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msignal_process\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_execute_process\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mexecute_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1053\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1054\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msignal_process\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mRuntimeSignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBREAK\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/model.py\u001b[0m in \u001b[0;36m_execute_process\u001b[0;34m(self, p_obj, stage, runtime_context, hooks, validate, state)\u001b[0m\n\u001b[1;32m 869\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mp_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msignal_pre\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 870\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 871\u001b[0;31m state_out, signal_out = executor.execute(\n\u001b[0m\u001b[1;32m 872\u001b[0m \u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mruntime_context\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 873\u001b[0m )\n", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/process.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, p_obj, stage, runtime_context, state)\u001b[0m\n\u001b[1;32m 528\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mRuntimeSignal\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNONE\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 529\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 530\u001b[0;31m \u001b[0msignal_out\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mexecutor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mruntime_context\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 531\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 532\u001b[0m \u001b[0mskeys\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__xsimlab_state_keys__\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mout_vars\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/miniconda3/envs/simlab-dev/lib/python3.9/site-packages/xsimlab/process.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, p_obj, runtime_context, state)\u001b[0m\n\u001b[1;32m 392\u001b[0m \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mruntime_context\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 394\u001b[0;31m \u001b[0msignal\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmeth\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mp_obj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 396\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0msignal\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m\u001b[0m in \u001b[0;36mrun_step\u001b[0;34m(self, n)\u001b[0m\n\u001b[1;32m 49\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mxs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mruntime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'step'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mrun_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 51\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmaxrad\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0msin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 52\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mNameError\u001b[0m: name 'sin' is not defined" - ] + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ diff --git a/xsimlab/tests/test_dot.py b/xsimlab/tests/test_dot.py index ec9fb17b..947ec9c2 100644 --- a/xsimlab/tests/test_dot.py +++ b/xsimlab/tests/test_dot.py @@ -55,7 +55,7 @@ def _ensure_not_exists(filename): def test_to_graphviz(model): - g = to_graphviz(model) + g = to_graphviz(model, show_inout_arrows=False) actual_nodes = _get_graph_nodes(g) actual_edges = _get_graph_edges(g) expected_nodes = list(model) diff --git a/xsimlab/tests/test_variable.py b/xsimlab/tests/test_variable.py index 159edf5d..9efb1c9d 100644 --- a/xsimlab/tests/test_variable.py +++ b/xsimlab/tests/test_variable.py @@ -104,9 +104,6 @@ class Foo: def test_foreign(): - with pytest.raises(ValueError, match="intent='inout' is not supported.*"): - xs.foreign(ExampleProcess, "some_var", intent="inout") - var = attr.fields(ExampleProcess).out_foreign_var ref_var = attr.fields(AnotherProcess).another_var From de9d19e93bdf2dbc2452f0dcc23060e66140d2a4 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Sat, 20 Mar 2021 22:53:07 +0100 Subject: [PATCH 5/9] fixed arrows --- notebooks/cyclic.ipynb | 465 ++++++++++++++++++++--------------------- xsimlab/dot.py | 5 +- xsimlab/model.py | 2 + 3 files changed, 227 insertions(+), 245 deletions(-) diff --git a/notebooks/cyclic.ipynb b/notebooks/cyclic.ipynb index d7dcc2ca..d2fd76a9 100644 --- a/notebooks/cyclic.ipynb +++ b/notebooks/cyclic.ipynb @@ -13,29 +13,7 @@ }, { "cell_type": "code", - "execution_count": 2, - "id": "absolute-spyware", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "10" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a,b = (10,20)\n", - "a" - ] - }, - { - "cell_type": "code", - "execution_count": 3, + "execution_count": 9, "id": "cloudy-viking", "metadata": {}, "outputs": [], @@ -90,7 +68,7 @@ " \n", " @xs.runtime(args='step')\n", " def run_step(self,n):\n", - " self.maxrad = 1+math.sin(n/math.pi)\n", + " self.maxrad = 3\n", " \n", " \n", "#this process actually adds some to 'biomass' group\n", @@ -121,6 +99,13 @@ " \n", " def run_step(self):\n", " self.f_light = self.f_light/2\n", + "\n", + "@xs.process\n", + "class DoubleFLight:\n", + " f_light = xs.foreign(FracInterceptedLight,'intercepted_light',intent='inout')\n", + " \n", + " def run_step(self):\n", + " self.f_light = self.f_light*2\n", " \n", "@xs.process\n", "class BiomassDeath:\n", @@ -148,23 +133,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "id": "positive-physiology", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "_dep_processes: {'halve_f_light': {'f_light'}, 'f_light': {'leaf_area'}, 'maxrad': set(), 'leaf_area': set(), 'growth': {'halve_f_light', 'maxrad'}, 'death': set(), 'biomass': {'death', 'growth'}, 'otherclass': {'biomass'}}\n", - "_dep_processes dict: {'halve_f_light': ['f_light'], 'f_light': ['leaf_area'], 'maxrad': [], 'leaf_area': [], 'growth': ['halve_f_light', 'maxrad'], 'death': [], 'biomass': ['death', 'growth'], 'otherclass': ['biomass']}\n" - ] - } - ], + "outputs": [], "source": [ "model = xs.Model(\n", " {\n", " 'halve_f_light':HalveFLight,\n", + " 'double_f_light':DoubleFLight,\n", " 'f_light':FracInterceptedLight,\n", "# 'initial':InitialBiomass,\n", " 'maxrad':MaxExtraTerrestrialRadiation,\n", @@ -173,24 +150,26 @@ " 'death':BiomassDeath,\n", " 'biomass':Biomass,\n", " 'otherclass':OtherClass\n", - " },custom_dependencies = {'growth__frac_light':'halve_f_light','otherclass__biomass':'biomass'}\n", + " },custom_dependencies = {'growth__frac_light':'halve_f_light',\n", + " 'halve_f_light__f_light':'double_f_light',\n", + " 'otherclass__biomass':'biomass'}\n", ")" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 11, "id": "fresh-helmet", "metadata": {}, "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "" ] }, - "execution_count": 5, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -208,7 +187,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "" ] @@ -234,7 +213,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 12, "id": "controlling-breakfast", "metadata": {}, "outputs": [ @@ -242,221 +221,219 @@ "name": "stdout", "output_type": "stream", "text": [ - "_dep_processes: {'leaf_area': set(), 'f_light': {'leaf_area'}, 'halve_f_light': {'f_light'}, 'maxrad': set(), 'growth': {'halve_f_light', 'maxrad'}, 'death': set(), 'biomass': {'death', 'growth'}, 'otherclass': {'biomass'}}\n", - "_dep_processes dict: {'leaf_area': [], 'f_light': ['leaf_area'], 'halve_f_light': ['f_light'], 'maxrad': [], 'growth': ['halve_f_light', 'maxrad'], 'death': [], 'biomass': ['death', 'growth'], 'otherclass': ['biomass']}\n", - "Step: 0 out_B: 1.011452127744409\n", - "otherclass: 1.011452127744409\n", - "Step: 1 out_B: 1.0266748878158212\n", - "otherclass: 1.0266748878158212\n", - "Step: 2 out_B: 1.045320250903847\n", - "otherclass: 1.045320250903847\n", - "Step: 3 out_B: 1.0667018912498643\n", - "otherclass: 1.0667018912498643\n", - "Step: 4 out_B: 1.0898581900078508\n", - "otherclass: 1.0898581900078508\n", - "Step: 5 out_B: 1.1136427483542828\n", - "otherclass: 1.1136427483542828\n", - "Step: 6 out_B: 1.1368353953079635\n", - "otherclass: 1.1368353953079635\n", - "Step: 7 out_B: 1.158264030820504\n", - "otherclass: 1.158264030820504\n", - "Step: 8 out_B: 1.1769253946250038\n", - "otherclass: 1.1769253946250038\n", - "Step: 9 out_B: 1.1920916442459513\n", - "otherclass: 1.1920916442459513\n", - "Step: 10 out_B: 1.203390082965359\n", - "otherclass: 1.203390082965359\n", - "Step: 11 out_B: 1.2108458376254678\n", - "otherclass: 1.2108458376254678\n", - "Step: 12 out_B: 1.2148816032034735\n", - "otherclass: 1.2148816032034735\n", - "Step: 13 out_B: 1.2162740799126601\n", - "otherclass: 1.2162740799126601\n", - "Step: 14 out_B: 1.2160723937215083\n", - "otherclass: 1.2160723937215083\n", - "Step: 15 out_B: 1.2154885111439815\n", - "otherclass: 1.2154885111439815\n", - "Step: 16 out_B: 1.2157726022848685\n", - "otherclass: 1.2157726022848685\n", - "Step: 17 out_B: 1.2180871427824536\n", - "otherclass: 1.2180871427824536\n", - "Step: 18 out_B: 1.2233924872341286\n", - "otherclass: 1.2233924872341286\n", - "Step: 19 out_B: 1.232354293091122\n", - "otherclass: 1.232354293091122\n", - "Step: 20 out_B: 1.2452802454348688\n", - "otherclass: 1.2452802454348688\n", - "Step: 21 out_B: 1.2620906105164822\n", - "otherclass: 1.2620906105164822\n", - "Step: 22 out_B: 1.2823245125977034\n", - "otherclass: 1.2823245125977034\n", - "Step: 23 out_B: 1.3051814569925106\n", - "otherclass: 1.3051814569925106\n", - "Step: 24 out_B: 1.329595291040203\n", - "otherclass: 1.329595291040203\n", - "Step: 25 out_B: 1.3543352785208522\n", - "otherclass: 1.3543352785208522\n", - "Step: 26 out_B: 1.3781262197578827\n", - "otherclass: 1.3781262197578827\n", - "Step: 27 out_B: 1.399776836262679\n", - "otherclass: 1.399776836262679\n", - "Step: 28 out_B: 1.418303503653965\n", - "otherclass: 1.418303503653965\n", - "Step: 29 out_B: 1.4330355553620175\n", - "otherclass: 1.4330355553620175\n", - "Step: 30 out_B: 1.4436893894770468\n", - "otherclass: 1.4436893894770468\n", - "Step: 31 out_B: 1.4504017276978034\n", - "otherclass: 1.4504017276978034\n", - "Step: 32 out_B: 1.4537173016403393\n", - "otherclass: 1.4537173016403393\n", - "Step: 33 out_B: 1.45453215714713\n", - "otherclass: 1.45453215714713\n", - "Step: 34 out_B: 1.4539995367983658\n", - "otherclass: 1.4539995367983658\n", - "Step: 35 out_B: 1.4534098150821095\n", - "otherclass: 1.4534098150821095\n", - "Step: 36 out_B: 1.4540584711744586\n", - "otherclass: 1.4540584711744586\n", - "Step: 37 out_B: 1.457116399251865\n", - "otherclass: 1.457116399251865\n", - "Step: 38 out_B: 1.463515325079495\n", - "otherclass: 1.463515325079495\n", - "Step: 39 out_B: 1.4738584085305924\n", - "otherclass: 1.4738584085305924\n", - "Step: 40 out_B: 1.4883630032392112\n", - "otherclass: 1.4883630032392112\n", - "Step: 41 out_B: 1.5068395529833731\n", - "otherclass: 1.5068395529833731\n", - "Step: 42 out_B: 1.528707936072495\n", - "otherclass: 1.528707936072495\n", - "Step: 43 out_B: 1.5530501264323313\n", - "otherclass: 1.5530501264323313\n", - "Step: 44 out_B: 1.578695570583507\n", - "otherclass: 1.578695570583507\n", - "Step: 45 out_B: 1.604332980734315\n", - "otherclass: 1.604332980734315\n", - "Step: 46 out_B: 1.62863934636194\n", - "otherclass: 1.62863934636194\n", - "Step: 47 out_B: 1.650414224584772\n", - "otherclass: 1.650414224584772\n", - "Step: 48 out_B: 1.6687054163754926\n", - "otherclass: 1.6687054163754926\n", - "Step: 49 out_B: 1.6829116984591457\n", - "otherclass: 1.6829116984591457\n", - "Step: 50 out_B: 1.6928499093559553\n", - "otherclass: 1.6928499093559553\n", - "Step: 51 out_B: 1.6987774939545737\n", - "otherclass: 1.6987774939545737\n", - "Step: 52 out_B: 1.7013671310297664\n", - "otherclass: 1.7013671310297664\n", - "Step: 53 out_B: 1.701636330311303\n", - "otherclass: 1.701636330311303\n", - "Step: 54 out_B: 1.7008406743215811\n", - "otherclass: 1.7008406743215811\n", - "Step: 55 out_B: 1.700343604398861\n", - "otherclass: 1.700343604398861\n", - "Step: 56 out_B: 1.7014776686583344\n", - "otherclass: 1.7014776686583344\n", - "Step: 57 out_B: 1.7054119201046138\n", - "otherclass: 1.7054119201046138\n", - "Step: 58 out_B: 1.7130381595061577\n", - "otherclass: 1.7130381595061577\n", - "Step: 59 out_B: 1.7248857225717487\n", - "otherclass: 1.7248857225717487\n", - "Step: 60 out_B: 1.7410712523602727\n", - "otherclass: 1.7410712523602727\n", - "Step: 61 out_B: 1.7612868525037795\n", - "otherclass: 1.7612868525037795\n", - "Step: 62 out_B: 1.7848273089388242\n", - "otherclass: 1.7848273089388242\n", - "Step: 63 out_B: 1.8106545346051248\n", - "otherclass: 1.8106545346051248\n", - "Step: 64 out_B: 1.837494761662\n", - "otherclass: 1.837494761662\n", - "Step: 65 out_B: 1.8639611155950397\n", - "otherclass: 1.8639611155950397\n", - "Step: 66 out_B: 1.888691171631072\n", - "otherclass: 1.888691171631072\n", - "Step: 67 out_B: 1.910486373362779\n", - "otherclass: 1.910486373362779\n", - "Step: 68 out_B: 1.9284384969022836\n", - "otherclass: 1.9284384969022836\n", - "Step: 69 out_B: 1.9420284112817348\n", - "otherclass: 1.9420284112817348\n", - "Step: 70 out_B: 1.9511846946801095\n", - "otherclass: 1.9511846946801095\n", - "Step: 71 out_B: 1.9562941819015172\n", - "otherclass: 1.9562941819015172\n", - "Step: 72 out_B: 1.9581626026454593\n", - "otherclass: 1.9581626026454593\n", - "Step: 73 out_B: 1.957930007187579\n", - "otherclass: 1.957930007187579\n", - "Step: 74 out_B: 1.9569513921729538\n", - "otherclass: 1.9569513921729538\n", - "Step: 75 out_B: 1.9566567902871224\n", - "otherclass: 1.9566567902871224\n", - "Step: 76 out_B: 1.9584065613935333\n", - "otherclass: 1.9584065613935333\n", - "Step: 77 out_B: 1.9633568352605735\n", - "otherclass: 1.9633568352605735\n", - "Step: 78 out_B: 1.9723476183476696\n", - "otherclass: 1.9723476183476696\n", - "Step: 79 out_B: 1.9858228089270507\n", - "otherclass: 1.9858228089270507\n", - "Step: 80 out_B: 2.0037879843598074\n", - "otherclass: 2.0037879843598074\n", - "Step: 81 out_B: 2.0258087359205565\n", - "otherclass: 2.0258087359205565\n", - "Step: 82 out_B: 2.051049569305229\n", - "otherclass: 2.051049569305229\n", - "Step: 83 out_B: 2.0783507423323577\n", - "otherclass: 2.0783507423323577\n", - "Step: 84 out_B: 2.106337600149586\n", - "otherclass: 2.106337600149586\n", - "Step: 85 out_B: 2.1335538844137076\n", - "otherclass: 2.1335538844137076\n", - "Step: 86 out_B: 2.1586073508402266\n", - "otherclass: 2.1586073508402266\n", - "Step: 87 out_B: 2.1803133909321692\n", - "otherclass: 2.1803133909321692\n", - "Step: 88 out_B: 2.19782099557389\n", - "otherclass: 2.19782099557389\n", - "Step: 89 out_B: 2.2107060513475547\n", - "otherclass: 2.2107060513475547\n", - "Step: 90 out_B: 2.2190200039847654\n", - "otherclass: 2.2190200039847654\n", - "Step: 91 out_B: 2.2232871567783765\n", - "otherclass: 2.2232871567783765\n", - "Step: 92 out_B: 2.2244504756933354\n", - "otherclass: 2.2244504756933354\n", - "Step: 93 out_B: 2.2237725016207324\n", - "otherclass: 2.2237725016207324\n", - "Step: 94 out_B: 2.2227035178258157\n", - "otherclass: 2.2227035178258157\n", - "Step: 95 out_B: 2.222732518754895\n", - "otherclass: 2.222732518754895\n", - "Step: 96 out_B: 2.2252374118607308\n", - "otherclass: 2.2252374118607308\n", - "Step: 97 out_B: 2.2313495349971983\n", - "otherclass: 2.2313495349971983\n", - "Step: 98 out_B: 2.2418447155784116\n", - "otherclass: 2.2418447155784116\n" + "Step: 0 out_B: 1.0712127664664541\n", + "otherclass: 1.0712127664664541\n", + "Step: 1 out_B: 1.143407161450417\n", + "otherclass: 1.143407161450417\n", + "Step: 2 out_B: 1.216596597852054\n", + "otherclass: 1.216596597852054\n", + "Step: 3 out_B: 1.2907946685606788\n", + "otherclass: 1.2907946685606788\n", + "Step: 4 out_B: 1.3660151487789056\n", + "otherclass: 1.3660151487789056\n", + "Step: 5 out_B: 1.442271998374273\n", + "otherclass: 1.442271998374273\n", + "Step: 6 out_B: 1.5195793642585864\n", + "otherclass: 1.5195793642585864\n", + "Step: 7 out_B: 1.5979515827952393\n", + "otherclass: 1.5979515827952393\n", + "Step: 8 out_B: 1.6774031822347577\n", + "otherclass: 1.6774031822347577\n", + "Step: 9 out_B: 1.7579488851788245\n", + "otherclass: 1.7579488851788245\n", + "Step: 10 out_B: 1.8396036110730372\n", + "otherclass: 1.8396036110730372\n", + "Step: 11 out_B: 1.9223824787286494\n", + "otherclass: 1.9223824787286494\n", + "Step: 12 out_B: 2.0063008088735486\n", + "otherclass: 2.0063008088735486\n", + "Step: 13 out_B: 2.091374126732721\n", + "otherclass: 2.091374126732721\n", + "Step: 14 out_B: 2.1776181646384516\n", + "otherclass: 2.1776181646384516\n", + "Step: 15 out_B: 2.2650488646705216\n", + "otherclass: 2.2650488646705216\n", + "Step: 16 out_B: 2.3536823813266374\n", + "otherclass: 2.3536823813266374\n", + "Step: 17 out_B: 2.443535084223347\n", + "otherclass: 2.443535084223347\n", + "Step: 18 out_B: 2.534623560827699\n", + "otherclass: 2.534623560827699\n", + "Step: 19 out_B: 2.6269646192198715\n", + "otherclass: 2.6269646192198715\n", + "Step: 20 out_B: 2.7205752908870453\n", + "otherclass: 2.7205752908870453\n", + "Step: 21 out_B: 2.8154728335487325\n", + "otherclass: 2.8154728335487325\n", + "Step: 22 out_B: 2.9116747340138294\n", + "otherclass: 2.9116747340138294\n", + "Step: 23 out_B: 3.0091987110696237\n", + "otherclass: 3.0091987110696237\n", + "Step: 24 out_B: 3.1080627184029983\n", + "otherclass: 3.1080627184029983\n", + "Step: 25 out_B: 3.2082849475540653\n", + "otherclass: 3.2082849475540653\n", + "Step: 26 out_B: 3.309883830902471\n", + "otherclass: 3.309883830902471\n", + "Step: 27 out_B: 3.4128780446865994\n", + "otherclass: 3.4128780446865994\n", + "Step: 28 out_B: 3.517286512055915\n", + "otherclass: 3.517286512055915\n", + "Step: 29 out_B: 3.6231284061566607\n", + "otherclass: 3.6231284061566607\n", + "Step: 30 out_B: 3.7304231532511474\n", + "otherclass: 3.7304231532511474\n", + "Step: 31 out_B: 3.8391904358708495\n", + "otherclass: 3.8391904358708495\n", + "Step: 32 out_B: 3.9494501960035326\n", + "otherclass: 3.9494501960035326\n", + "Step: 33 out_B: 4.061222638314629\n", + "otherclass: 4.061222638314629\n", + "Step: 34 out_B: 4.174528233403066\n", + "otherclass: 4.174528233403066\n", + "Step: 35 out_B: 4.289387721091774\n", + "otherclass: 4.289387721091774\n", + "Step: 36 out_B: 4.40582211375306\n", + "otherclass: 4.40582211375306\n", + "Step: 37 out_B: 4.523852699669057\n", + "otherclass: 4.523852699669057\n", + "Step: 38 out_B: 4.643501046427455\n", + "otherclass: 4.643501046427455\n", + "Step: 39 out_B: 4.764789004352694\n", + "otherclass: 4.764789004352694\n", + "Step: 40 out_B: 4.887738709972806\n", + "otherclass: 4.887738709972806\n", + "Step: 41 out_B: 5.0123725895221005\n", + "otherclass: 5.0123725895221005\n", + "Step: 42 out_B: 5.1387133624798675\n", + "otherclass: 5.1387133624798675\n", + "Step: 43 out_B: 5.266784045145261\n", + "otherclass: 5.266784045145261\n", + "Step: 44 out_B: 5.396607954248544\n", + "otherclass: 5.396607954248544\n", + "Step: 45 out_B: 5.528208710598842\n", + "otherclass: 5.528208710598842\n", + "Step: 46 out_B: 5.661610242768576\n", + "otherclass: 5.661610242768576\n", + "Step: 47 out_B: 5.796836790814703\n", + "otherclass: 5.796836790814703\n", + "Step: 48 out_B: 5.933912910036922\n", + "otherclass: 5.933912910036922\n", + "Step: 49 out_B: 6.072863474772972\n", + "otherclass: 6.072863474772972\n", + "Step: 50 out_B: 6.21371368223115\n", + "otherclass: 6.21371368223115\n", + "Step: 51 out_B: 6.35648905636017\n", + "otherclass: 6.35648905636017\n", + "Step: 52 out_B: 6.501215451756462\n", + "otherclass: 6.501215451756462\n", + "Step: 53 out_B: 6.647919057609041\n", + "otherclass: 6.647919057609041\n", + "Step: 54 out_B: 6.796626401682006\n", + "otherclass: 6.796626401682006\n", + "Step: 55 out_B: 6.947364354334778\n", + "otherclass: 6.947364354334778\n", + "Step: 56 out_B: 7.1001601325801476\n", + "otherclass: 7.1001601325801476\n", + "Step: 57 out_B: 7.255041304180187\n", + "otherclass: 7.255041304180187\n", + "Step: 58 out_B: 7.412035791780096\n", + "otherclass: 7.412035791780096\n", + "Step: 59 out_B: 7.571171877080023\n", + "otherclass: 7.571171877080023\n", + "Step: 60 out_B: 7.732478205044891\n", + "otherclass: 7.732478205044891\n", + "Step: 61 out_B: 7.895983788152252\n", + "otherclass: 7.895983788152252\n", + "Step: 62 out_B: 8.06171801067819\n", + "otherclass: 8.06171801067819\n", + "Step: 63 out_B: 8.229710633021263\n", + "otherclass: 8.229710633021263\n", + "Step: 64 out_B: 8.39999179606447\n", + "otherclass: 8.39999179606447\n", + "Step: 65 out_B: 8.57259202557523\n", + "otherclass: 8.57259202557523\n", + "Step: 66 out_B: 8.747542236643312\n", + "otherclass: 8.747542236643312\n", + "Step: 67 out_B: 8.924873738156686\n", + "otherclass: 8.924873738156686\n", + "Step: 68 out_B: 9.104618237315206\n", + "otherclass: 9.104618237315206\n", + "Step: 69 out_B: 9.286807844182063\n", + "otherclass: 9.286807844182063\n", + "Step: 70 out_B: 9.471475076272892\n", + "otherclass: 9.471475076272892\n", + "Step: 71 out_B: 9.658652863182432\n", + "otherclass: 9.658652863182432\n", + "Step: 72 out_B: 9.848374551248606\n", + "otherclass: 9.848374551248606\n", + "Step: 73 out_B: 10.04067390825387\n", + "otherclass: 10.04067390825387\n", + "Step: 74 out_B: 10.235585128163681\n", + "otherclass: 10.235585128163681\n", + "Step: 75 out_B: 10.433142835901874\n", + "otherclass: 10.433142835901874\n", + "Step: 76 out_B: 10.633382092162789\n", + "otherclass: 10.633382092162789\n", + "Step: 77 out_B: 10.836338398259892\n", + "otherclass: 10.836338398259892\n", + "Step: 78 out_B: 11.042047701010675\n", + "otherclass: 11.042047701010675\n", + "Step: 79 out_B: 11.250546397657565\n", + "otherclass: 11.250546397657565\n", + "Step: 80 out_B: 11.461871340824565\n", + "otherclass: 11.461871340824565\n", + "Step: 81 out_B: 11.676059843509334\n", + "otherclass: 11.676059843509334\n", + "Step: 82 out_B: 11.893149684110373\n", + "otherclass: 11.893149684110373\n", + "Step: 83 out_B: 12.113179111488977\n", + "otherclass: 12.113179111488977\n", + "Step: 84 out_B: 12.33618685006559\n", + "otherclass: 12.33618685006559\n", + "Step: 85 out_B: 12.56221210495016\n", + "otherclass: 12.56221210495016\n", + "Step: 86 out_B: 12.79129456710609\n", + "otherclass: 12.79129456710609\n", + "Step: 87 out_B: 13.023474418547337\n", + "otherclass: 13.023474418547337\n", + "Step: 88 out_B: 13.258792337568188\n", + "otherclass: 13.258792337568188\n", + "Step: 89 out_B: 13.497289504005225\n", + "otherclass: 13.497289504005225\n", + "Step: 90 out_B: 13.739007604530963\n", + "otherclass: 13.739007604530963\n", + "Step: 91 out_B: 13.983988837978599\n", + "otherclass: 13.983988837978599\n", + "Step: 92 out_B: 14.232275920697305\n", + "otherclass: 14.232275920697305\n", + "Step: 93 out_B: 14.483912091937452\n", + "otherclass: 14.483912091937452\n", + "Step: 94 out_B: 14.738941119265128\n", + "otherclass: 14.738941119265128\n", + "Step: 95 out_B: 14.997407304005291\n", + "otherclass: 14.997407304005291\n", + "Step: 96 out_B: 15.259355486712835\n", + "otherclass: 15.259355486712835\n", + "Step: 97 out_B: 15.524831052670867\n", + "otherclass: 15.524831052670867\n", + "Step: 98 out_B: 15.793879937415403\n", + "otherclass: 15.793879937415403\n" ] }, { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 8, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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\n", + "image/png": "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\n", "text/plain": [ "
" ] diff --git a/xsimlab/dot.py b/xsimlab/dot.py index 72a12f0e..a26c175b 100644 --- a/xsimlab/dot.py +++ b/xsimlab/dot.py @@ -111,7 +111,6 @@ def _add_var(self, var, p_name): def add_inout_arrows(self): for p_name, p_obj in self.model._processes.items(): p_cls = type(p_obj) - for var_name, var in variables_dict(p_cls).items(): # test if the variable is inout if ( @@ -124,6 +123,10 @@ def add_inout_arrows(self): for p2_name, p2_obj in self.model._processes.items(): p2_cls = type(p2_obj) + # skip this if it is a dependent process + if p_name in self.model.dependent_processes[p2_name]: + continue + for var2_name, var2 in variables_dict(p2_cls).items(): # if the variable is target2_keys = _get_target_keys(p2_obj, var2_name) diff --git a/xsimlab/model.py b/xsimlab/model.py index 0cdd4c93..ac640f7a 100644 --- a/xsimlab/model.py +++ b/xsimlab/model.py @@ -428,12 +428,14 @@ def get_process_dependencies(self, custom_dependencies=None): if custom_dependencies is not None: for dep_key in custom_dependencies: + # this is all just necessary to not add this variable to dependencies. p_name, var_name = as_variable_key(dep_key) dep_p_name = custom_dependencies[dep_key] # TODO: fix also for on-demand variables skip_deps[p_name] = self._processes_obj[p_name].__xsimlab_state_keys__[ var_name ] + # actually add to dependencies self._dep_processes[p_name].add(dep_p_name) for p_name, p_obj in self._processes_obj.items(): From 7ef2a51025e0099d1b49b89ded3959c5ceb034ae Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Tue, 23 Mar 2021 01:13:08 +0100 Subject: [PATCH 6/9] solved checking of inout vars, also transitive reduction --- notebooks/cyclic.ipynb | 474 ----------------------------------------- xsimlab/dot.py | 14 +- xsimlab/model.py | 229 ++++++++++++++++++-- 3 files changed, 214 insertions(+), 503 deletions(-) delete mode 100644 notebooks/cyclic.ipynb diff --git a/notebooks/cyclic.ipynb b/notebooks/cyclic.ipynb deleted file mode 100644 index d2fd76a9..00000000 --- a/notebooks/cyclic.ipynb +++ /dev/null @@ -1,474 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "chronic-survivor", - "metadata": {}, - "outputs": [], - "source": [ - "import xsimlab as xs\n", - "import math\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "cloudy-viking", - "metadata": {}, - "outputs": [], - "source": [ - "@xs.process\n", - "class Biomass:\n", - " B_vars = xs.group('biomass')\n", - " dB = xs.variable(intent='inout',default=0)\n", - " B = xs.variable(intent='inout',default=1)\n", - " out_B = xs.variable(intent='out')\n", - " \n", - " #we can actually safely use run_step because of the cycle ordering?\n", - " @xs.runtime(args='step')\n", - " def run_step(self, n):\n", - "# print(\"Biomass calculating: \")\n", - " self.dB = sum(self.B_vars)\n", - " self.B += self.dB\n", - " self.out_B = self.B\n", - " print(\"Step: \", n,\" out_B: \", self.out_B)\n", - "\n", - "#jsut some processes to have a longer cycle\n", - "@xs.process\n", - "class FracInterceptedLight:\n", - " leaf_area = xs.variable(global_name='leaf_area',intent='in')\n", - " intercepted_light = xs.variable(intent='out')\n", - " ext_coeff = xs.variable(default=0.8)\n", - " \n", - " def run_step(self):\n", - "# print(\"Frac light calculating: \")\n", - " self.intercepted_light = 1-math.exp(-self.ext_coeff*self.leaf_area)\n", - "\n", - "@xs.process\n", - "class LeafAreaAnnual:\n", - " leaf_area = xs.global_ref('leaf_area',intent='out')\n", - " prev_dB = xs.foreign(Biomass, 'dB')\n", - "\n", - " pl = xs.variable(default = 0.002)\n", - " init_leaf_area = xs.variable(default = 0.01)\n", - " \n", - " def initialize(self):\n", - " self.leaf_area = self.init_leaf_area\n", - " \n", - " @xs.runtime(args='step_delta')\n", - " def run_step(self,dt):\n", - "# print(\"leaf area calculating\")\n", - " self.leaf_area += self.pl*self.prev_dB*dt\n", - "\n", - "#the process maxrad also adds to growth\n", - "@xs.process\n", - "class MaxExtraTerrestrialRadiation:\n", - " maxrad = xs.variable(intent='out')\n", - " \n", - " @xs.runtime(args='step')\n", - " def run_step(self,n):\n", - " self.maxrad = 3\n", - " \n", - " \n", - "#this process actually adds some to 'biomass' group\n", - "@xs.process\n", - "class LightLimitedPlantGrowth:\n", - " frac_light = xs.foreign(FracInterceptedLight,\"intercepted_light\")\n", - " maxrad = xs.foreign(MaxExtraTerrestrialRadiation,'maxrad')\n", - " \n", - " light_efficiency = xs.variable(default=3)\n", - " biomass_growth = xs.variable(intent='out',groups='biomass')\n", - " \n", - " @xs.runtime(args='step_delta')\n", - " def run_step(self,dt):\n", - "# print(\"growth calcuating\")\n", - " self.biomass_growth = self.light_efficiency*self.frac_light*self.maxrad\n", - " \n", - "@xs.process\n", - "class InitialBiomass:\n", - " initial = xs.variable(default=1)\n", - " biomass = xs.foreign(Biomass,'B',intent='out')\n", - " \n", - " def initialize(self):\n", - " self.biomass = self.initial\n", - "\n", - "@xs.process\n", - "class HalveFLight:\n", - " f_light = xs.foreign(FracInterceptedLight,'intercepted_light',intent='inout')\n", - " \n", - " def run_step(self):\n", - " self.f_light = self.f_light/2\n", - "\n", - "@xs.process\n", - "class DoubleFLight:\n", - " f_light = xs.foreign(FracInterceptedLight,'intercepted_light',intent='inout')\n", - " \n", - " def run_step(self):\n", - " self.f_light = self.f_light*2\n", - " \n", - "@xs.process\n", - "class BiomassDeath:\n", - " biomass = xs.foreign(Biomass,\"B\")\n", - " death_rate = xs.variable(default=0.0005)\n", - " biomass_death = xs.variable(intent='out',groups='biomass')\n", - " \n", - " @xs.runtime(args='step_delta')\n", - " def run_step(self,dt):\n", - "# print(\"death calcualting\")\n", - " self.biomass_death = -self.biomass*self.death_rate*dt\n", - " \n", - "@xs.process\n", - "class OtherClass:\n", - " biomass = xs.foreign(Biomass,\"B\", intent='in')\n", - " somevar = xs.variable(intent='out')\n", - " \n", - " def initialize(self):\n", - " self.somevar = 1\n", - " \n", - " def run_step(self):\n", - " print('otherclass: ', self.biomass)\n", - " self.somevar += self.biomass" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "positive-physiology", - "metadata": {}, - "outputs": [], - "source": [ - "model = xs.Model(\n", - " {\n", - " 'halve_f_light':HalveFLight,\n", - " 'double_f_light':DoubleFLight,\n", - " 'f_light':FracInterceptedLight,\n", - "# 'initial':InitialBiomass,\n", - " 'maxrad':MaxExtraTerrestrialRadiation,\n", - " 'leaf_area':LeafAreaAnnual,\n", - " 'growth':LightLimitedPlantGrowth,\n", - " 'death':BiomassDeath,\n", - " 'biomass':Biomass,\n", - " 'otherclass':OtherClass\n", - " },custom_dependencies = {'growth__frac_light':'halve_f_light',\n", - " 'halve_f_light__f_light':'double_f_light',\n", - " 'otherclass__biomass':'biomass'}\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "fresh-helmet", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.visualize()\n", - "# model.growth.variables()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "large-correction", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "model.visualize(show_only_variable=('biomass','B'))" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "acoustic-circulation", - "metadata": {}, - "outputs": [], - "source": [ - "ds_in = xs.create_setup(model=model,clocks={'clock':range(100)},output_vars={'otherclass__somevar':'clock'})" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "controlling-breakfast", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Step: 0 out_B: 1.0712127664664541\n", - "otherclass: 1.0712127664664541\n", - "Step: 1 out_B: 1.143407161450417\n", - "otherclass: 1.143407161450417\n", - "Step: 2 out_B: 1.216596597852054\n", - "otherclass: 1.216596597852054\n", - "Step: 3 out_B: 1.2907946685606788\n", - "otherclass: 1.2907946685606788\n", - "Step: 4 out_B: 1.3660151487789056\n", - "otherclass: 1.3660151487789056\n", - "Step: 5 out_B: 1.442271998374273\n", - "otherclass: 1.442271998374273\n", - "Step: 6 out_B: 1.5195793642585864\n", - "otherclass: 1.5195793642585864\n", - "Step: 7 out_B: 1.5979515827952393\n", - "otherclass: 1.5979515827952393\n", - "Step: 8 out_B: 1.6774031822347577\n", - "otherclass: 1.6774031822347577\n", - "Step: 9 out_B: 1.7579488851788245\n", - "otherclass: 1.7579488851788245\n", - "Step: 10 out_B: 1.8396036110730372\n", - "otherclass: 1.8396036110730372\n", - "Step: 11 out_B: 1.9223824787286494\n", - "otherclass: 1.9223824787286494\n", - "Step: 12 out_B: 2.0063008088735486\n", - "otherclass: 2.0063008088735486\n", - "Step: 13 out_B: 2.091374126732721\n", - "otherclass: 2.091374126732721\n", - "Step: 14 out_B: 2.1776181646384516\n", - "otherclass: 2.1776181646384516\n", - "Step: 15 out_B: 2.2650488646705216\n", - "otherclass: 2.2650488646705216\n", - "Step: 16 out_B: 2.3536823813266374\n", - "otherclass: 2.3536823813266374\n", - "Step: 17 out_B: 2.443535084223347\n", - "otherclass: 2.443535084223347\n", - "Step: 18 out_B: 2.534623560827699\n", - "otherclass: 2.534623560827699\n", - "Step: 19 out_B: 2.6269646192198715\n", - "otherclass: 2.6269646192198715\n", - "Step: 20 out_B: 2.7205752908870453\n", - "otherclass: 2.7205752908870453\n", - "Step: 21 out_B: 2.8154728335487325\n", - "otherclass: 2.8154728335487325\n", - "Step: 22 out_B: 2.9116747340138294\n", - "otherclass: 2.9116747340138294\n", - "Step: 23 out_B: 3.0091987110696237\n", - "otherclass: 3.0091987110696237\n", - "Step: 24 out_B: 3.1080627184029983\n", - "otherclass: 3.1080627184029983\n", - "Step: 25 out_B: 3.2082849475540653\n", - "otherclass: 3.2082849475540653\n", - "Step: 26 out_B: 3.309883830902471\n", - "otherclass: 3.309883830902471\n", - "Step: 27 out_B: 3.4128780446865994\n", - "otherclass: 3.4128780446865994\n", - "Step: 28 out_B: 3.517286512055915\n", - "otherclass: 3.517286512055915\n", - "Step: 29 out_B: 3.6231284061566607\n", - "otherclass: 3.6231284061566607\n", - "Step: 30 out_B: 3.7304231532511474\n", - "otherclass: 3.7304231532511474\n", - "Step: 31 out_B: 3.8391904358708495\n", - "otherclass: 3.8391904358708495\n", - "Step: 32 out_B: 3.9494501960035326\n", - "otherclass: 3.9494501960035326\n", - "Step: 33 out_B: 4.061222638314629\n", - "otherclass: 4.061222638314629\n", - "Step: 34 out_B: 4.174528233403066\n", - "otherclass: 4.174528233403066\n", - "Step: 35 out_B: 4.289387721091774\n", - "otherclass: 4.289387721091774\n", - "Step: 36 out_B: 4.40582211375306\n", - "otherclass: 4.40582211375306\n", - "Step: 37 out_B: 4.523852699669057\n", - "otherclass: 4.523852699669057\n", - "Step: 38 out_B: 4.643501046427455\n", - "otherclass: 4.643501046427455\n", - "Step: 39 out_B: 4.764789004352694\n", - "otherclass: 4.764789004352694\n", - "Step: 40 out_B: 4.887738709972806\n", - "otherclass: 4.887738709972806\n", - "Step: 41 out_B: 5.0123725895221005\n", - "otherclass: 5.0123725895221005\n", - "Step: 42 out_B: 5.1387133624798675\n", - "otherclass: 5.1387133624798675\n", - "Step: 43 out_B: 5.266784045145261\n", - "otherclass: 5.266784045145261\n", - "Step: 44 out_B: 5.396607954248544\n", - "otherclass: 5.396607954248544\n", - "Step: 45 out_B: 5.528208710598842\n", - "otherclass: 5.528208710598842\n", - "Step: 46 out_B: 5.661610242768576\n", - "otherclass: 5.661610242768576\n", - "Step: 47 out_B: 5.796836790814703\n", - "otherclass: 5.796836790814703\n", - "Step: 48 out_B: 5.933912910036922\n", - "otherclass: 5.933912910036922\n", - "Step: 49 out_B: 6.072863474772972\n", - "otherclass: 6.072863474772972\n", - "Step: 50 out_B: 6.21371368223115\n", - "otherclass: 6.21371368223115\n", - "Step: 51 out_B: 6.35648905636017\n", - "otherclass: 6.35648905636017\n", - "Step: 52 out_B: 6.501215451756462\n", - "otherclass: 6.501215451756462\n", - "Step: 53 out_B: 6.647919057609041\n", - "otherclass: 6.647919057609041\n", - "Step: 54 out_B: 6.796626401682006\n", - "otherclass: 6.796626401682006\n", - "Step: 55 out_B: 6.947364354334778\n", - "otherclass: 6.947364354334778\n", - "Step: 56 out_B: 7.1001601325801476\n", - "otherclass: 7.1001601325801476\n", - "Step: 57 out_B: 7.255041304180187\n", - "otherclass: 7.255041304180187\n", - "Step: 58 out_B: 7.412035791780096\n", - "otherclass: 7.412035791780096\n", - "Step: 59 out_B: 7.571171877080023\n", - "otherclass: 7.571171877080023\n", - "Step: 60 out_B: 7.732478205044891\n", - "otherclass: 7.732478205044891\n", - "Step: 61 out_B: 7.895983788152252\n", - "otherclass: 7.895983788152252\n", - "Step: 62 out_B: 8.06171801067819\n", - "otherclass: 8.06171801067819\n", - "Step: 63 out_B: 8.229710633021263\n", - "otherclass: 8.229710633021263\n", - "Step: 64 out_B: 8.39999179606447\n", - "otherclass: 8.39999179606447\n", - "Step: 65 out_B: 8.57259202557523\n", - "otherclass: 8.57259202557523\n", - "Step: 66 out_B: 8.747542236643312\n", - "otherclass: 8.747542236643312\n", - "Step: 67 out_B: 8.924873738156686\n", - "otherclass: 8.924873738156686\n", - "Step: 68 out_B: 9.104618237315206\n", - "otherclass: 9.104618237315206\n", - "Step: 69 out_B: 9.286807844182063\n", - "otherclass: 9.286807844182063\n", - "Step: 70 out_B: 9.471475076272892\n", - "otherclass: 9.471475076272892\n", - "Step: 71 out_B: 9.658652863182432\n", - "otherclass: 9.658652863182432\n", - "Step: 72 out_B: 9.848374551248606\n", - "otherclass: 9.848374551248606\n", - "Step: 73 out_B: 10.04067390825387\n", - "otherclass: 10.04067390825387\n", - "Step: 74 out_B: 10.235585128163681\n", - "otherclass: 10.235585128163681\n", - "Step: 75 out_B: 10.433142835901874\n", - "otherclass: 10.433142835901874\n", - "Step: 76 out_B: 10.633382092162789\n", - "otherclass: 10.633382092162789\n", - "Step: 77 out_B: 10.836338398259892\n", - "otherclass: 10.836338398259892\n", - "Step: 78 out_B: 11.042047701010675\n", - "otherclass: 11.042047701010675\n", - "Step: 79 out_B: 11.250546397657565\n", - "otherclass: 11.250546397657565\n", - "Step: 80 out_B: 11.461871340824565\n", - "otherclass: 11.461871340824565\n", - "Step: 81 out_B: 11.676059843509334\n", - "otherclass: 11.676059843509334\n", - "Step: 82 out_B: 11.893149684110373\n", - "otherclass: 11.893149684110373\n", - "Step: 83 out_B: 12.113179111488977\n", - "otherclass: 12.113179111488977\n", - "Step: 84 out_B: 12.33618685006559\n", - "otherclass: 12.33618685006559\n", - "Step: 85 out_B: 12.56221210495016\n", - "otherclass: 12.56221210495016\n", - "Step: 86 out_B: 12.79129456710609\n", - "otherclass: 12.79129456710609\n", - "Step: 87 out_B: 13.023474418547337\n", - "otherclass: 13.023474418547337\n", - "Step: 88 out_B: 13.258792337568188\n", - "otherclass: 13.258792337568188\n", - "Step: 89 out_B: 13.497289504005225\n", - "otherclass: 13.497289504005225\n", - "Step: 90 out_B: 13.739007604530963\n", - "otherclass: 13.739007604530963\n", - "Step: 91 out_B: 13.983988837978599\n", - "otherclass: 13.983988837978599\n", - "Step: 92 out_B: 14.232275920697305\n", - "otherclass: 14.232275920697305\n", - "Step: 93 out_B: 14.483912091937452\n", - "otherclass: 14.483912091937452\n", - "Step: 94 out_B: 14.738941119265128\n", - "otherclass: 14.738941119265128\n", - "Step: 95 out_B: 14.997407304005291\n", - "otherclass: 14.997407304005291\n", - "Step: 96 out_B: 15.259355486712835\n", - "otherclass: 15.259355486712835\n", - "Step: 97 out_B: 15.524831052670867\n", - "otherclass: 15.524831052670867\n", - "Step: 98 out_B: 15.793879937415403\n", - "otherclass: 15.793879937415403\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAEGCAYAAABhMDI9AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAArwklEQVR4nO3dd3yV9fn/8dfF3nuFMMIIW2ZAAXHWgtoKtWpxFZGKWlutbR3Y4be/1lb9Wlvbqi3fKiIOpDjAUSrirAMIe+8AgRASNgEyr98f50YDMnJCTk5yzvv5eORxzv05933O9WGcK/dnmrsjIiJyVJVoByAiIhWLEoOIiBxDiUFERI6hxCAiIsdQYhARkWNUi3YAZ6pZs2aelJQU7TBERCqVBQsWZLt78xO9FtHEYGZdgVeKFXUEfg08H5QnAWnANe6+J7hmAjAOKATudPf/nOozkpKSSE1NLfPYRURimZltPtlrEW1Kcvc17t7X3fsCA4BDwOvA/cAcd08G5gTHmFkPYDTQExgBPGVmVSMZo4iIHKs8+xguBja4+2ZgJDA5KJ8MjAqejwSmunuuu28C1gODyjFGEZG4V56JYTTwcvC8pbtnAASPLYLyRGBrsWvSgzIRESkn5ZIYzKwGcAXwr9OdeoKyr63ZYWbjzSzVzFKzsrLKIkQREQmU1x3DpcBCd88MjjPNLAEgeNwZlKcDbYtd1wbYfvybuftEd09x95TmzU/YqS4iIqVUXonhWr5qRgKYCYwJno8BZhQrH21mNc2sA5AMzCunGEVEhHKYx2BmdYBLgFuLFT8MTDOzccAW4GoAd19hZtOAlUABcIe7F0Y6RhER+UrEE4O7HwKaHle2i9AopROd/xDwUKTjEhGpTNydNxZvY1NWzpdl/do15sJuLU5xVelU+pnPIiLx4K2lGdz9yhIALBimM3ZIByUGEZF4lHUgl1/PWE6fto149bbBVKsa2e5hLaInIlKBuTu/emM5ObmFPHZV74gnBVBiEBGp0N5cmsGsFTu4+5IuJLesXy6fqcQgIlJBZR3I5cGgCemWYR3K7XOVGEREKiB3Z8Jry8jJK+SPV5dPE9JRSgwiIhXQqwu38d6qTO4d3pXOLcqnCekoJQYRkQpm+97D/GbmCgYlNWHs0PJrQjpKiUFEpAJxd+57dSmF7vzv1b2pWuVEa4tGlhKDiEgFMuWLzXyyLpsHLutO+6Z1oxKDEoOISAWxIesgv39nFed3ac71Z7eLWhxKDCIiFUBBYRE/nbaEWtWr8uhVvTEr/yako7QkhohIBfDkBxtYsnUvf7uuHy0b1IpqLLpjEBGJsqXpe/nr++sY1bc13+rdOtrhKDGIiETTobwCfjJ1MS3q1+Q3V/SKdjiAmpJERKLqd2+vYtOuHF78wdk0rFM92uEAumMQEYma91Zm8tLcLYwf1pEhnZpFO5wvKTGIiERB1oFc7nt1Kd0TGvDTb3aJdjjHUFOSiEg5c3fumb6EA7kFvPS9vtSsVjXaIR1DdwwiIuXsuc/S+HBNFr+4rDtdW5XvAnklocQgIlKOVmXs5w/vrOaibi34/uD20Q7nhCKeGMyskZlNN7PVZrbKzAabWRMzm21m64LHxsXOn2Bm681sjZkNj3R8IiLl5Uh+IXe+vIgGtatHfXbzqZTHHcMTwCx37wb0AVYB9wNz3D0ZmBMcY2Y9gNFAT2AE8JSZVazGNxGRUnro7VWs23mQP17Th2b1akY7nJOKaGIwswbAecAzAO6e5+57gZHA5OC0ycCo4PlIYKq757r7JmA9MCiSMYqIlIdZy3cw5YvN3DKsA+d3aR7tcE4p0ncMHYEsYJKZLTKzf5pZXaClu2cABI8tgvMTga3Frk8Pyo5hZuPNLNXMUrOysiJbAxGRM7R972Hue3UpZyU25J7h3aIdzmlFOjFUA/oDT7t7PyCHoNnoJE7U4OZfK3Cf6O4p7p7SvHnFzrwiEt8KCov4ydTFFBQW8Zdr+1GjWsUf8xPpCNOBdHefGxxPJ5QoMs0sASB43Fns/LbFrm8DbI9wjCIiEfPX99czL203vx3Viw7NorPxTrgimhjcfQew1cy6BkUXAyuBmcCYoGwMMCN4PhMYbWY1zawDkAzMi2SMIiKR8tn6bP7y/jqu7J/Ilf3bRDucEiuPmc8/Bl40sxrARmAsoYQ0zczGAVuAqwHcfYWZTSOUPAqAO9y9sBxiFBEpU9kHc7nrlcV0aFaX346sGKumllTEE4O7LwZSTvDSxSc5/yHgoUjGJCISSUVFzt2vLGbf4Xyev3kQdWtWrtWHKn4viIhIJfP3jzfwybpsHvx2D7onNIh2OGFTYhARKUPzNu3mj++u5fLeCVw3qF20wykVJQYRkTKSfTCXH7+8kHZN6vDwlWdV2CUvTkeJQUSkDBztV9hzKJ+/XdeP+rUqxm5spaHEICJSBv72wXo+WZfNb67oSc/WDaMdzhlRYhAROUP/XZfNn95by6i+rRk9sO3pL6jglBhERM5Axr7D3Dl1Eckt6vH7StyvUJwSg4hIKeUVFHHHiwvJzS/k6RsGUKdG5ZqvcDKxUQsRkSj4w79XsXDLXp68rj+dmteLdjhlRncMIiKlMHPJdiZ9msbYoUlc3jsh2uGUKSUGEZEwrdlxgPumL2VgUmMeuKx7tMMpc0oMIiJh2H8kn9teWEC9WtV48rr+VK8ae1+jsVcjEZEIKSpyfjZtCVt3H+Kp6/vTokGtaIcUEUoMIiIl9OQH65m9MpMHLuvOwKQm0Q4nYpQYRERK4P3VmTz+3lq+0y+RsUOToh1ORCkxiIicxqbsHO6aupgeCQ34/XdiYxLbqSgxiIicwsHcAm6dkkq1KsbfbxhA7RpVox1SxGmCm4jISRQVOT99ZTEbsnJ4/uZBtG1SJ9ohlQvdMYiInMRf3l/Huysz+cVl3RnauVm0wyk3JUoMZlbFzK6JdDAiIhXFrOU7+PN76/hu/zYx39l8vBIlBncvAn5Umg8wszQzW2Zmi80sNShrYmazzWxd8Ni42PkTzGy9ma0xs+Gl+UwRkTOxesd+fjZtMX3aNuKh7/SK+c7m44XTlDTbzH5uZm2DL/YmZlbSgbwXuntfd08Jju8H5rh7MjAnOMbMegCjgZ7ACOApM4v9nh4RqTB2HczlB5NTqVerGhNvHECt6vH3FRRO5/PNweMdxcoc6FiKzx0JXBA8nwx8CNwXlE9191xgk5mtBwYBn5fiM0REwpJXUMTtLywk60Au024dTMsYndl8OiVODO7eoZSf4cC7ZubAP9x9ItDS3TOC980wsxbBuYnAF8WuTQ/KjmFm44HxAO3atStlWCIiX3F3Hpy5nHlpu3lidF/6tG0U7ZCiJqzhqmbWC+gBfJlG3f3501w21N23B1/+s81s9ak+4gRl/rWCUHKZCJCSkvK110VEwvXsp2m8PG8rP7ygEyP7fu330bhS4sRgZg8Sav7pAbwDXAr8FzhlYnD37cHjTjN7nVDTUKaZJQR3CwnAzuD0dKD4hqltgO0ljVFEpDQ+WL2Th95eyYierfj5N7tGO5yoC6fz+SrgYmCHu48F+gA1T3WBmdU1s/pHnwPfBJYDM4ExwWljgBnB85nAaDOraWYdgGRgXhgxioiEZc2OA/z45UX0aN2Ax7/XhypV4msE0omE05R02N2LzKzAzBoQ+i3/dB3PLYHXg6Fe1YCX3H2Wmc0HppnZOGALcDWAu68ws2nASqAAuMPdC8OrkohIyWQdyOXm5+ZTp0ZV/vn9gTGzZ/OZCudPIdXMGgH/BywADnKa3+bdfSOhO4vjy3cRuvs40TUPAQ+FEZeISNiO5Bdyy/Op7MoJjUBq1TA+RyCdSDijkn4YPP27mc0CGrj70siEJSISOUVFzk+nLWZJ+l6evn4Avds0inZIFUqJ+xjMbIaZXWdmdd09TUlBRCqr/313De8s28GES7sxoleraIdT4YTT+fw4cC6w0sz+ZWZXmZnuvUSkUnl53hae/nAD1w5qxy3DSjM/N/aF05T0EfBRsETFRcAtwLNAgwjFJiJSpj5cs5NfvrGc87s057cje8bdGkglFe4Et9rAt4HvAf0JLWchIlLhrdi+jzteXEiXlvV58vr+VKuqXQdOJpwJbq8AZwOzgCeBD4NVV0VEKrTtew9z83PzaVC7OpNuGki9mhqWeirh/OlMAq7TvAIRqUz2HcpnzLPzOJRbyLTbNCy1JMK5l/oYmGBmEwHMLNnMvhWZsEREztyR/EJumZJK2q4c/nHjALonqEu0JMJJDJOAPGBIcJwO/K7MIxIRKQNFRc7P/rWEeZt289jVfRgSR1tznqlwEkMnd38UyAdw98OceDVUEZGocnd++/ZK3l6awYRLu8X9aqnhCicx5AWjkhzAzDoBuRGJSkTkDPz9o41M+jSNm4d2YPx5mqsQrnA6nx8kNCKprZm9CAwFbopEUCIipfWv1K08Mms1V/RpzS8v7665CqUQzgS32Wa2EDiHUBPSXe6eHbHIRETC9P7qTO5/bRnDkpvx2NVaQru0wp3hkQhUBWoA55nZlWUfkohI+Oan7eb2FxbSI6EBT98wgBrVNIGttMKZ4PYs0BtYARyd2ObAaxGIS0SkxFZl7Ofm5+aT2Lg2z43VBLYzFc6f3jnu3iNikYiIlMLmXTl8/9l51KtZjSnjzqZpvVNuLCklEM691udmpsQgIhXGjn1HuOGZueQXFjFl3CASG9WOdkgxIZw7hsmEksMOQsNUDXB37x2RyERETmF3Th43PjOXPTn5vHTL2XRuUT/aIcWMcBLDs8CNwDK+6mMQESl3B47kc9OkeWzZfYjJNw/SDmxlLJzEsMXdZ0YsEhGREjicV8i451JZuX0/E78/gHM6No12SDEnnD6G1Wb2kplda2ZXHv0pyYVmVtXMFpnZW8FxEzObbWbrgsfGxc6dYGbrzWyNmQ0Psz4iEsNyCwoZPyWV1M27+dP3+nJRt5bRDikmhZMYahPqW/gmoc16vg2UdHXVu4BVxY7vB+a4ezIwJzgm6NweDfQERgBPBTvGiUicyy8s4o4XF/HJumwe+W5vvt2ndbRDilnhzHweW5oPMLM2wOXAQ8BPg+KRwAXB88nAh8B9QflUd88FNpnZemAQ8HlpPltEYkNBYRF3v7KY91Zl8tuRPbk6pW20Q4ppJb5jMLM2Zva6me00s0wzezX40j+dPwP3cmyHdUt3zwAIHlsE5YnA1mLnpQdlx8cy3sxSzSw1KyurpFUQkUqosMi5d/pS3lqawQOXdePGwUnRDinmhbsfw0ygNaEv6zeDspMKNvLZ6e4LSvgZJ1rYxL9W4D7R3VPcPaV58+YlfGsRqWyKipwHXlvGa4u28fNvdmH8eZ2iHVJcCCcxNHf3Se5eEPw8B5zuW3kocIWZpQFTgYvM7AUg08wSAILHncH56UDxe8Q2wPYwYhSRGOHu/GrGcl5J3cqdF3XmRxclRzukuBFOYsg2sxuCEUZVzewGYNepLnD3Ce7ext2TCHUqv+/uNxC68xgTnDYGmBE8nwmMNrOaZtYBSAbmhRGjiMQAd+fXM1bw4twt3HZ+J+6+pEu0Q4or4SSGm4FrgB3Bz1VBWWk8DFxiZuuAS4Jj3H0FMA1YSWjvhzvcvbCUnyEilZC78z8zVzDli83cel5H7hvRVXsqlDNz/1oTfqWSkpLiqamp0Q5DRMqAu/ObN1fy3Gdp3DKsAw9cpo12IsXMFrh7yoleC2dU0qNm1sDMqpvZHDPLDpqTRETOmLvz4MwVPPdZGj84V0khmsJpSvqmu+8nNKktHegC3BORqEQkrhQVOb98YznPfx5qPvqFtuSMqnDWSqoePF4GvOzuu/UXJyJnqqjI+cUby3h53lZuv6AT9w5Xn0K0hZMY3jSz1cBh4Idm1hw4EpmwRCQeFBY590xfwmsLt3HHhZ34+TeVFCqCEjclufv9wGAgxd3zgUOElrAAwMwuKfvwRCRW5RcW8ZNXFvPawm389JIu3DO8m5JCBRHWbtnuvufo8FF3z3H3HcVefqRMIxORmJVbUMiPXlrIm0u2c/+l3bjzYk1eq0jKcsdspXoROa3DeYXc+sICPl6bxYPf7sHYoR2iHZIcpywTQ+WeECEiEXfgSD7jJqcyP203j363N9cM1CqpFVFZJgYRkZPak5PHTZPmsWL7fp4Y3Y8rtJ9ChVWWiaF9Gb6XiMSQzP1HuPGZuaTtOsTTNwzgkh7aea0iK8vEsKUM30tEYsSWXYe4/pkv2H0wj+fGDmRIp2bRDklOQ30MIhIxqzL2M+bZeeQVFvHSLefQp22jaIckJaA+BhGJiHmbdjNu8nzq1qjGv24dTHLL+tEOSUpIiUFEytx7KzO546WFJDauzZRxZ5PYqHa0Q5IwlGViSCvD9xKRSmra/K1MeH0ZvVo3YNLYQTSpWyPaIUmYwll2+2ozqx88/6WZvWZm/Y++7u5XRiJAEakc3J2/zlnHva8uZUinprx4yzlKCpVUOEti/MrdD5jZucBwYDLwdGTCEpHKpLAotD/zH2ev5cp+iTwzZiD1aqqlurIKJzEc3WLzcuBpd58B6NcBkTh3OK+Q215YwAtfbOHW8zvyx2v6UKNaWMuwSQUTTkrfZmb/AL4BPGJmNQlzET4RiS27DuYybnIqS9L38psrejJmSFK0Q5IyEE5iuAYYATzm7nvNLAHt4CYStzZl5zB20jwy9h3h6esHMKJXq2iHJGUknN/4E4C33X2dmV0AXA3MO9UFZlbLzOaZ2RIzW2FmvwnKm5jZbDNbFzw2LnbNBDNbb2ZrzGx4+FUSkUibn7ab7zz1KfuPFPDSLecoKcSYcBLDq0ChmXUGngE6AC+d5ppc4CJ37wP0BUaY2TnA/cAcd08G5gTHmFkPYDTQk9DdyVNmVjWMGEUkwmYs3sb1/zeXJnVq8PoPhzCgfePTXySVSjiJocjdC4ArgT+7+92E7iJOykMOBofVgx8ntPPb5KB8MjAqeD4SmOruue6+CVgPDAojRhGJEHfnL3PWcdfUxfRt24hXbx9C+6Z1ox2WREA4iSHfzK4Fvg+8FZRVP91FZlbVzBYDO4HZ7j4XaOnuGQDBY4vg9ERga7HL04Oy499zvJmlmllqVlZWGFUQkdI4kl/I3a8s5vHZa/lOv0Sm/GAQjTVHIWaFkxjGEtrz+SF332RmHYAXTneRuxe6e1+gDTDIzHqd4vQT7QL3tcX53H2iu6e4e0rz5s1LFr2IlMqug7nc8M+5vLF4Oz//Zhcev6YPNauphTeWlXhUkruvBO4sdrwJeDiM6/ea2YeE+g4yzSzB3TOC0U07g9PSgeJbOrUBtpf0M0SkbK3esZ9xz6WSfTCXv13Xj2/11uY68SCcJTGSzWy6ma00s41Hf05zTXMzaxQ8r01oDsRqYCYwJjhtDDAjeD4TGG1mNYM7kmROM/JJRCJj9spMvvvUZ+QXFjHt1sFKCnEknHkMk4AHgT8BFxJqWjpR009xCcDkYGRRFWCau79lZp8D08xsHKENfq4GcPcVZjYNWAkUAHe4e+FJ3ltEIsDdeerDDTz27hrOSmzIxBtTaNWwVrTDknJk7iXbX8fMFrj7ADNb5u5nBWWfuPuwiEZ4GikpKZ6amhrNEERixqG8Au6dvpS3lmZwRZ/WPHpVb2pVV39CLAq+01NO9Fo4dwxHzKwKsM7MfgRs46vRRCJSyaXvOcT45xewasd+JlzajfHndcTsdI0CEovCSQw/AeoQ6oD+LXARX/UTiEgl9tn6bO54aSEFRc6zNw3kwq76nS+ehTMqaX7w9CCh/gURqeTcnX9+sok//HsVnZrX4x83DqBj83rRDkui7LSJwcze5ARzCY5y9yvKNCIRKRc5uQXc/9oy3lyynUt7teJ/r+6jPRQEKNkdw2MRj0JEytWGrIPcNmUBG7IOcu+Irtx+fif1J8iXTpsY3P0jADOrCxx296LguCpQM7LhiUhZ+/eyDO6ZvpQa1aowZdzZDO3cLNohSQUTzpIYcwh1Ph9VG3ivbMMRkUjJLyzit2+t5PYXF9K5RT3e+vG5SgpyQuE0KNYqtlIq7n7QzOqc6gIRqRgy9h3mRy8tYsHmPdw0JIkHLuuu7TflpMJJDDlm1t/dFwKY2QDgcGTCEpGy8sGanfz0lcXkFRRpvSMpkXASw13Av8zs6KJ2CcD3yj4kESkL+YVF/PHdtfz9ow10a1WfJ6/vTycNRZUSKFFiCDqahwHdgK6E1kha7e75EYxNREopfc8h7pq6mAWb93Dd2e349bd6aGkLKbESJQZ3LzSzke7+J2B5hGMSkTMwa3kG905fSpHDE6P7MrLv1/a6EjmlcJqSPjWzvwGvADlHC4/2OYhIdB3JL+Sht1cx5YvN9G7TkL9e209bb0qphJMYhgSP/69YmRNaM0lEomhVxn7ufHkR63Ye5JZhHbhneDeNOpJSC2etpAsjGYiIhK+oyJn8eRp/+PdqGtauzvM3D+K8LtruVs5MiRODmbUEfg+0dvdLzawHMNjdn4lYdCJyUpn7j3DP9KV8vDaLi7u14NGretO0nhYjkDMXzr3mc8B/gKODoNcSWopbRMrZrOUZjPjzx8zbtIvfjerFP8ekKClImQmnj6GZu08zswkA7l5gZtp2U6Qc7T+Sz//MXMFrC7fRu01D/vS9vpqbIGUu3JnPTQmW4Dazc4B9EYlKRL7m0/XZ3POvJWQeyOXOi5P58UWdqV5VHcxS9sJJDD8FZgKdzOxToDlwVUSiEpEv5eQW8Mis1Tz/+WY6Nq/La7cPoU/bRtEOS2JYOKOSFprZ+Xw183nN6WY+m1lb4HmgFVAETHT3J8ysCaH5EElAGnCNu+8JrpkAjAMKgTvd/T/hVkokVszduIt7pi9l655D3Dy0A/cM70rtGprBLJEV7nZNgwh9mVcD+psZ7v78Kc4vAH4WJJX6wAIzmw3cBMxx94fN7H7gfuC+YKTTaKAnoU7u98ysi7urL0PiyqG8Ah6dtYbJn6fRtnEdpt5yDmd3bBrtsCROhDNcdQrQCVhM6Ld5CPU3nDQxuHsGkBE8P2Bmq4BEYCRwQXDaZOBD4L6gfKq75wKbzGw9oWT0eUnjFKnsPlufzX2vLWXr7sOMGdyee0d0o6623JRyFM6/thSgh7ufdP/nUzGzJKAfMBdoGSQN3D3DzFoEpyUCXxS7LD0oO/69xgPjAdq1a1eacEQqnH2H83n436t4ed5WkprWYdqtgxnUoUm0w5I4FE5iWE6oryAj3A8xs3rAq8BP3H3/KfaWPdELX0tE7j4RmAiQkpJSqkQlUpHMWr6DX89YTvbBXMaf15G7v9FFfQkSNadNDGb2JqEv5/rASjObB+Qefd3drzjN9dUJJYUX3f21oDjTzBKCu4UEYGdQng60LXZ5G2A7IjFqx74j/M/MFcxasYPuCQ14ZsxAzmrTMNphSZwryR3DY6V9cwvdGjwDrHL3x4u9NBMYAzwcPM4oVv6SmT1OqPM5GZhX2s8XqaiKipwX527mkVlryC8s4t4RXbllWEfNS5AK4bSJwd0/AjCzR9z9vuKvmdkjwEenuHwocCOwzMwWB2UPEEoI08xsHLAFuDr4rBVmNg1YSWhE0x0akSSxZvm2ffzijeUs2bqXYcnN+N2oXloeWyoUK2lfspktdPf+x5UtdffeEYmshFJSUjw1NTWaIYiUyMHcAh5/dy3PfbaJJnVr8IvLuzOqbyKn6HMTiRgzW+DuKSd6rSR9DLcDPyQ043lpsZfqA5+VTYgiscvdmblkOw+9vYqsg7lcN6gd9w7vRsM61aMdmsgJlaSP4SXg38AfCDUBnReU/9fdF0UqMJFYsC7zAL+esYLPN+7irMSG/OPGAfRr1zjaYYmcUkn6GPYB+8zsC+AF4DVCw0onm9n/uftfIxyjSKWz/0g+f569jsmfp1GvZjV+N6oX1w5qR9UqajaSii+ceQzjgHPcPQe+7Hj+HFBiEAkUFjmvLkjn0f+sZldOHqMHtuOe4V1pUrdGtEMTKbFwEoPx1VIYBM/1649IYH7abn7z5gqWb9tP/3aNmHTTIM1JkEopnMQwCZhrZq8Hx6MIzVEQiWtbdx/ikVmreWtpBgkNa/HE6L5c0ae1RhtJpRXOstuPm9mHwLmE7hTGqvNZ4tn+I/k89cEGnv10E1UM7rw4mdvO70idGlrwTiq3sP4Fu/tCYGGEYhGpFPIKinh53haemLOO3Tl5fLd/G34+vAsJDWtHOzSRMqFfbURKyN2ZtXwHj8xaTdquQwzu2JQHLuuufgSJOUoMIiXw2YZsHpm1hiVb95Lcoh7P3pTChV1bqB9BYpISg8gpLN+2j0f/s4aP12aR0LAWj363N1f2T6SaFruTGKbEIHIC63ce5PHZa3hn2Q4a1anOhEu7MWZIErWqa48EiX1KDCLFpGXn8Jf31/HGom3Url6VOy9O5gfDOtCgltY1kvihxCBCaC7C395fz/SF6VSrYow7twO3nd+JpvVqRjs0kXKnxCBxbevuQzz5wXqmL0inihk3ntOeH17QiRYNakU7NJGoUWKQuLQpO4enPljP64u2UcWM689ux+0XdKZVQyUEESUGiStrMw/w5AfreXPJdqpXrcIN57TntvM7KSGIFKPEIHFh0ZY9PPXhBmavzKROjar8YFhHfjCsAy3qKyGIHE+JQWKWu/Ph2iz+8dEGvti4m4a1q/OTbyQzZnASjbUMtshJKTFIzMkrKOLNJdv5v082snrHARIa1uKXl3fn2kHtqFtT/+RFTiei/0vM7FngW8BOd+8VlDUBXgGSgDTgGnffE7w2gdCGQIXAne7+n0jGJ7Fl3+F8Xp63hUmfbiJzfy7JLerx2NV9uKJPa2pU00xlkZKK9K9PzwF/A54vVnY/MMfdHzaz+4Pj+8ysBzAa6Am0Bt4zsy7uXojIKWzKzmHSp5uYviCdQ3mFDO3clIe/25sLujTXWkYipRDRxODuH5tZ0nHFI4ELgueTgQ+B+4Lyqe6eC2wys/XAIELbh4ocw9357/psnvs0jffX7KRaFeOKPomMHZpEr0StdipyJqLR4NrS3TMA3D3DzFoE5YnAF8XOSw/KvsbMxgPjAdq1axfBUKWiOXAkn9cXbeP5zzezfudBmtWrwY8v7MwNg9trhJFIGalIPXEnuuf3E53o7hOBiQApKSknPEdiy5odB5jyRRqvL9xGTl4hvds05PFr+nB57wRqVtPCdiJlKRqJIdPMEoK7hQRgZ1CeDrQtdl4bYHu5RycVxpH8QmYt38GLczczP20PNapV4Vu9E/j+4CT6tm0U7fBEYlY0EsNMYAzwcPA4o1j5S2b2OKHO52RgXhTikyhbv/MAL8/byqsL09l7KJ/2TevwwGXduGpAW5po/oFIxEV6uOrLhDqam5lZOvAgoYQwzczGAVuAqwHcfYWZTQNWAgXAHRqRFD9ycgt4e1kG0+ZvJXXzHqpXNS7p0ZJrB7VjaKdmVKmi0UUi5cXcK3cTfUpKiqempkY7DCkFd2d+2h6mL9jKW0szOJRXSMfmdfleSlu+O6ANzbTktUjEmNkCd0850WsVqfNZ4sTW3Yd4fdE2Xl2YzuZdh6hToyqXn5XA9wa2ZUD7xpp7IBJlSgxSLvYeyuOdZTt4fVE689P2ADC4Y1PuvCiZEb1aaakKkQpE/xslYg7nFfLeqkxmLN7OR2t3kl/odG5Rj3uGd2VUv0QSG9WOdogicgJKDFKmcgsK+XhtNm8u2c57qzI5lFdIywY1GTM4iVH9EunZuoGaikQqOCUGOWNH8gv5ZF027yzL4L2VmRzILaBxneqM6pfIt3oncHaHplTVqCKRSkOJQUolJ7eAj9Zm8e/lO3h/VSY5eYU0rF2dEb1acVnvBM7t3IzqVbWiqUhlpMQgJZZ1IJf3V2fy7opMPlmfTV5BEU3r1uCKvq0Z3rMVQzo10/LWIjFAiUFOyt1Zm3mQOaszeW9lJou27sUdEhvV5oaz23NJj5YMTGpMNd0ZiMQUJQY5xuG8Qj7fmM0Hq7N4f/VOtu09DMBZiQ35ycVd+EaPFvRIUAeySCxTYohz7s76nQf5aG0WH63NYu6m3eQVFFG7elWGdm7Gjy7qzIVdW9CqoZa0FokXSgxxKOtALp9tyObT9dl8si6bjH1HAOjYvC43ntOeC7o2Z2BSE2pV13LWIvFIiSEO7D+Sz7yNu/lswy4+25DN6h0HAGhQqxpDOzfjzoubMyy5GW0a14lypCJSESgxxKB9h/KZn7abuZt28cXG3azYvo8ih5rVqpCS1Jh7hnfl3M7N6JXYUPMLRORrlBhiwLa9h0lN282CzXuYt2k3azIP4A41qlWhX9tG/PiiZM7u2IT+7RqreUhETkuJoZLJLShk5fb9LNyyl4Vb9rBw854v+wjq1KjKgPaNufysBAZ2aELfto2UCEQkbEoMFVhRkbMxO4el6XtZmr6PRVv3smr7fvIKi4DQfIKUpCYMaNeIlKQmdGtVX3MKROSMKTFUEIVFzqbsg6zYvp9l6ftYtm0fK7fv50BuAQC1q1flrDYNGTs0tN9x//aNadlAQ0hFpOwpMUTB/iP5rN1xgFUZ+1m14wArt+9n9Y79HMkP3QnUrFaF7gkNGNUvkbPaNKRPm0Z0blFPHcUiUi6UGCLoUF4BG3bmsDbzAGt3HmDtjgOszTz45WxigIa1q9OtVX2uG9Senq0b0KN1Azq3qKcF6EQkapQYzlBRkZN54Agbs3LYmJ3DxqyDbMjKYcPOYxNAjapV6Ni8LilJjbm+VTu6tqxP94QGJDSspeUlRKRCqXCJwcxGAE8AVYF/uvvDUQ6JvIIitu09zNbdh9i8+1DocVcOadmH2Lw758smIAiNDOrYvC4DkxozunlbOreoR3LL+iQ1raOOYRGpFCpUYjCzqsCTwCVAOjDfzGa6+8pIfaa7s/9IATv2HWH7vsNs3xv62bbnMNuCx4z9R3D/6poa1arQrkkdkprWYVhyM5Ka1aVDs7p0bF6XVg10ByAilVuFSgzAIGC9u28EMLOpwEigzBPDp+uz+dUby9mx/wiH8gqPea1qFaNVg1q0aVybczo1pU3jOrRtXJu2TerQvmkdWtavRRV1BItIjKpoiSER2FrsOB04OxIf1KhOdbonNODCbi1IaFiLlg1q0bpRbVo3qkWL+rU0AkhE4lZFSwwn+jb2r51kNh4YD9CuXbtSfVDP1g158vr+pbpWRCSWVbTe0HSgbbHjNsD2409y94nunuLuKc2bNy+34ERE4kFFSwzzgWQz62BmNYDRwMwoxyQiElcqVFOSuxeY2Y+A/xAarvqsu6+IclgiInGlQiUGAHd/B3gn2nGIiMSritaUJCIiUabEICIix1BiEBGRYygxiIjIMcz9a/PHKhUzywI2l/LyZkB2GYZTWcRjveOxzhCf9Y7HOkP49W7v7iecCFbpE8OZMLNUd0+JdhzlLR7rHY91hvisdzzWGcq23mpKEhGRYygxiIjIMeI9MUyMdgBREo/1jsc6Q3zWOx7rDGVY77juYxARka+L9zsGERE5jhKDiIgcI24Tg5mNMLM1ZrbezO6PdjyRYGZtzewDM1tlZivM7K6gvImZzTazdcFj42jHWtbMrKqZLTKzt4LjeKhzIzObbmarg7/zwXFS77uDf9/LzexlM6sVa/U2s2fNbKeZLS9WdtI6mtmE4LttjZkND/fz4jIxmFlV4EngUqAHcK2Z9YhuVBFRAPzM3bsD5wB3BPW8H5jj7snAnOA41twFrCp2HA91fgKY5e7dgD6E6h/T9TazROBOIMXdexFarn80sVfv54ARx5WdsI7B//HRQM/gmqeC77wSi8vEAAwC1rv7RnfPA6YCI6McU5lz9wx3Xxg8P0DoiyKRUF0nB6dNBkZFJcAIMbM2wOXAP4sVx3qdGwDnAc8AuHueu+8lxusdqAbUNrNqQB1Cuz7GVL3d/WNg93HFJ6vjSGCqu+e6+yZgPaHvvBKL18SQCGwtdpwelMUsM0sC+gFzgZbungGh5AG0iGJokfBn4F6gqFhZrNe5I5AFTAqa0P5pZnWJ8Xq7+zbgMWALkAHsc/d3ifF6B05WxzP+fovXxGAnKIvZcbtmVg94FfiJu++PdjyRZGbfAna6+4Jox1LOqgH9gafdvR+QQ+VvPjmtoF19JNABaA3UNbMbohtV1J3x91u8JoZ0oG2x4zaEbj9jjplVJ5QUXnT314LiTDNLCF5PAHZGK74IGApcYWZphJoILzKzF4jtOkPo33S6u88NjqcTShSxXu9vAJvcPcvd84HXgCHEfr3h5HU84++3eE0M84FkM+tgZjUIddTMjHJMZc7MjFCb8yp3f7zYSzOBMcHzMcCM8o4tUtx9gru3cfckQn+v77v7DcRwnQHcfQew1cy6BkUXAyuJ8XoTakI6x8zqBP/eLybUlxbr9YaT13EmMNrMappZByAZmBfWO7t7XP4AlwFrgQ3AL6IdT4TqeC6hW8ilwOLg5zKgKaFRDOuCxybRjjVC9b8AeCt4HvN1BvoCqcHf9xtA4zip92+A1cByYApQM9bqDbxMqA8ln9AdwbhT1RH4RfDdtga4NNzP05IYIiJyjHhtShIRkZNQYhARkWMoMYiIyDGUGERE5BhKDCIicgwlBpEzYGb/Y2Y/L8V1Fxxd+VWkolFiEBGRYygxiITBzL5vZkvNbImZTTnutb5m9kXw+utH18c3s85m9l5wzUIz63TcdQODhe86lmddRE5GiUGkhMysJ6EZpRe5ex9Cez4U9zxwn7v3BpYBDwblLwJPBtcMITSD9eh7DgH+Dox0940RroJIiSgxiJTcRcB0d88GcPcv18c3s4ZAI3f/KCiaDJxnZvWBRHd/PbjmiLsfCs7pDkwEvu3uW8qrEiKno8QgUnJG+Muzn2gJ5KMygCOE9skQqTCUGERKbg5wjZk1hdCeu0dfcPd9wB4zGxYU3Qh85KH9L9LNbFRwTU0zqxOcs5fQTnO/N7MLyqMCIiVRLdoBiFQW7r7CzB4CPjKzQmARkFbslDHA34Mv/o3A2KD8RuAfZvb/CK2OeXWx98w0s28D/zazm/2r/RREokarq4qIyDHUlCQiIsdQYhARkWMoMYiIyDGUGERE5BhKDCIicgwlBhEROYYSg4iIHOP/A3SUeHY3nnUxAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "#plot to verify that it works\n", - "ds_in.xsimlab.run(model).otherclass__somevar.plot()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/xsimlab/dot.py b/xsimlab/dot.py index a26c175b..55a59304 100644 --- a/xsimlab/dot.py +++ b/xsimlab/dot.py @@ -115,7 +115,7 @@ def add_inout_arrows(self): # test if the variable is inout if ( var.metadata["intent"] == VarIntent.INOUT - and var.metadata["var_type"] == VarType.VARIABLE + and var.metadata["var_type"] != VarType.FOREIGN ): target_keys = _get_target_keys(p_obj, var_name) @@ -123,17 +123,17 @@ def add_inout_arrows(self): for p2_name, p2_obj in self.model._processes.items(): p2_cls = type(p2_obj) - # skip this if it is a dependent process - if p_name in self.model.dependent_processes[p2_name]: + # skip this if it is a dependent process or the process itself + if ( + p_name in self.model.dependent_processes[p2_name] + or p_name == p2_name + ): continue for var2_name, var2 in variables_dict(p2_cls).items(): # if the variable is target2_keys = _get_target_keys(p2_obj, var2_name) - if ( - len(set(target_keys) & set(target2_keys)) - and var2.metadata["intent"] == VarIntent.IN - ): + if len(set(target_keys) & set(target2_keys)): edge_ends = p_name, p2_name self.g.edge( *edge_ends, weight="200", **INOUT_EDGE_ATTRS diff --git a/xsimlab/model.py b/xsimlab/model.py index ac640f7a..fdac512a 100644 --- a/xsimlab/model.py +++ b/xsimlab/model.py @@ -406,7 +406,7 @@ def get_process_dependencies(self, custom_dependencies=None): values are lists of the names of dependent processes (or empty lists for processes that have no dependencies). - inputs: dependencies: a {('p_name','var_name'):'dep_p_name'} dictionary + inputs: dependencies: a {'p_name':['dep_p_name','dep2_p_name']} dictionary Process 1 depends on process 2 if the later declares a variable (resp. a foreign variable) with intent='out' that @@ -416,7 +416,6 @@ def get_process_dependencies(self, custom_dependencies=None): self._dep_processes = {k: set() for k in self._processes_obj} d_keys = {} # all state/on-demand keys for each process - skip_deps = {} # dict of dependencies to skip {'p_name':key} for p_name, p_obj in self._processes_obj.items(): d_keys[p_name] = _flatten_keys( @@ -427,16 +426,14 @@ def get_process_dependencies(self, custom_dependencies=None): ) if custom_dependencies is not None: - for dep_key in custom_dependencies: - # this is all just necessary to not add this variable to dependencies. - p_name, var_name = as_variable_key(dep_key) - dep_p_name = custom_dependencies[dep_key] - # TODO: fix also for on-demand variables - skip_deps[p_name] = self._processes_obj[p_name].__xsimlab_state_keys__[ - var_name - ] + for p_name in custom_dependencies: + deps = custom_dependencies[p_name] + if type(deps) == str: + deps = [deps] + # actually add to dependencies - self._dep_processes[p_name].add(dep_p_name) + for dep_p_name in deps: + self._dep_processes[p_name].add(dep_p_name) for p_name, p_obj in self._processes_obj.items(): for var in filter_variables(p_obj, intent=VarIntent.OUT).values(): @@ -445,22 +442,208 @@ def get_process_dependencies(self, custom_dependencies=None): else: key = p_obj.__xsimlab_state_keys__[var.name] - # iterate through all processes names out_var->pn for pn in self._processes_obj: - # check if this is a different process and the process key is the same - # -> then we have an out process that is used as input here! - # here also check if the process is not in the dependencies list (how?) if pn != p_name and key in d_keys[pn]: - if pn in skip_deps: - if skip_deps[pn] == key: - # do not add this process, since it is in the dependencies list - continue self._dep_processes[pn].add(p_name) self._dep_processes = {k: list(v) for k, v in self._dep_processes.items()} - + self._check_inout_vars() return self._dep_processes + def _check_inout_vars(self): + """ + checks if all inout variables and corresponding in variables are explicitly set in the dependencies + Out variables always come first, since the get_process_dependencies checks for that. + A well-behaved graph looks like: + ``` + inout1->inout2 + ^ \ ^ \ + / \ / \ + in in in + ``` + """ + # create dictionaries with all inout variables and input variables + inout_dict = {} # dict of {key:{p1_name,p2_name}} for inout variables + in_dict = {} + + for p_name, p_obj in self._processes_obj.items(): + # create {key:{p1_name,p2_name}} dicts for in and inout vars. + for var in filter_variables(p_obj, intent=VarIntent.INOUT): + if var in p_obj.__xsimlab_state_keys__: + keys = p_obj.__xsimlab_state_keys__[var] + else: + keys = p_obj.__xsimlab_od_keys__[var] + + for key in keys: + if not key in inout_dict: + inout_dict[key] = {p_name} + else: + inout_dict[key].add(p_name) + + for var in filter_variables(p_obj, intent=VarIntent.IN): + if var in p_obj.__xsimlab_state_keys__: + keys = p_obj.__xsimlab_state_keys__[var] + else: + keys = p_obj.__xsimlab_od_keys__[var] + + for key in keys: + if not key in in_dict: + in_dict[key] = {p_name} + else: + in_dict[key].add(p_name) + + # filter out variables that do not need to be checked: + inout_dict = {k: v for k, v in inout_dict.items() if k in in_dict} + + # get a dict of all dependent processes for easier processing + deps_dict = self.get_dependency_dict() + + for key, inout_ps in inout_dict.items(): + in_ps = in_dict[key] + + verified_ios = [] + + # now we only have to search and verify all inout variables + print("checking ", key, " with io processes ", inout_ps) + for io_p in inout_ps: + io_stack = [io_p] + while io_stack: + cur = io_stack[-1] + if cur in verified_ios: + io_stack.pop() + continue + + child_ios = deps_dict[io_p].intersection(inout_ps - {cur}) + if child_ios: + # TODO: fix this with intersections + # lost_children = child_ios.symetric_difference(set(verified_ios)) + if len(child_ios) == len(verified_ios): + child_ins = in_ps.intersection(deps_dict[cur]) + # verify that all children have the previous io as dependency + for child_in in child_ins: + if not verified_ios[-1] in deps_dict[child_in]: + raise RuntimeError( + f"inout process {verified_ios[-1]} not in {child_in}'s " + + "dependencies, could not establish strict dependency order" + ) + # we can now safely remove these in nodes + in_ps -= child_ins + verified_ios.append(cur) + io_stack.pop() + elif len(child_ios) > len(verified_ios): + # we need to search deeper: add to the stack. + io_stack.extend( + [io for io in child_ios if io not in verified_ios] + ) + else: + raise RuntimeError( + f"inout process {cur} depends on {child_ios}, but should depend on all of {verified_ios}, especially {verified_ios[-1]}" + ) + else: + # we are at the bottom inout process: remove in variables from the set + # this can only happen if we are the first process at the bottom + if verified_ios: + # impor + raise RuntimeError( + f"inout process {cur} has no dependencies with variable {key}, but {verified_ios} should be one", + ) + in_ps -= deps_dict[cur] + verified_ios.append(cur) + io_stack.pop() + # print("finished searching ios, now have: ", in_ps, verified_ios) + for p in in_ps: + if not verified_ios[-1] in deps_dict[p]: + raise RuntimeError( + f"process {verified_ios[-1]} not in depdendencies of {p} while {key} requires so" + ) + + def get_dependency_dict(self): + """ + IMPORTANT: assumes no cycles in the graph -> this is actually for the dependency_dict can be undone + generate a {'p_name':{dep1_p_name,dep2_p_name}} list for all processes, for easier validation + TODO: incorporate this into the other DFS algorithm + """ + # this is to ensure that we do not encounter a cycle + seen = set() + descendants = {p: set() for p in self._dep_processes} + completed_d = set() + for p_name in self._dep_processes: + # create the descendants using DFS only if they are not yet there yet + if p_name not in completed_d: + # implement a DFS algorithm + nodes = [p_name] + while nodes: + cur = nodes[-1] + if cur in completed_d: + nodes.pop() + continue + seen.add(cur) + + next_nodes = [] + for nxt in self._dep_processes[cur]: + if nxt in seen: + # Cycle detected! + cycle = [nxt] + while nodes[-1] != nxt: + cycle.append(nodes.pop()) + cycle.append(nodes.pop()) + cycle.reverse() + cycle = "->".join(cycle) + raise RuntimeError( + f"Cycle detected in process graph: {cycle}" + ) + if nxt in completed_d: + descendants[cur].add(nxt) + descendants[cur].update(descendants[nxt]) + else: + next_nodes.append(nxt) + if next_nodes: + nodes.extend(next_nodes) + else: + # it has no more depndencies, so we can add it to the descendants + completed_d.add(cur) + seen.remove(cur) + nodes.pop() + + return descendants + + def transitive_reduction(self): + """Returns transitive reduction of a directed graph + + The transitive reduction of G = (V,E) is a graph G- = (V,E-) such that + for all v,w in V there is an edge (v,w) in E- if and only if (v,w) is + in E and there is no path from v to w in G with length greater than 1. + + Parameters + ---------- + G : NetworkX DiGraph + A directed acyclic graph (DAG) + + Returns + ------- + NetworkX DiGraph + The transitive reduction of `G` + + Raises + ------ + NetworkXError + If `G` is not a directed acyclic graph (DAG) transitive reduction is + not uniquely defined and a :exc:`NetworkXError` exception is raised. + + References + ---------- + https://en.wikipedia.org/wiki/Transitive_reduction + adapted from networkx: https://networkx.org/documentation/stable/_modules/networkx/algorithms/dag.html#transitive_reduction + + """ + dep_dict = self.get_dependency_dict() + + for p_name in self._dep_processes: + p_nbrs = set(self._dep_processes[p_name]) + for dep_p in self._dep_processes[p_name]: + p_nbrs -= dep_dict[dep_p] + self._dep_processes[p_name] = list(p_nbrs) + def _sort_processes(self): """Sort processes based on their dependencies (return a list of sorted process names). @@ -603,6 +786,8 @@ def __init__(self, processes, custom_dependencies=None): self._dep_processes = builder.get_process_dependencies(custom_dependencies) self._processes = builder.get_sorted_processes() + # builder.get_dependencies_dict() # transitive_reduction() + super(Model, self).__init__(self._processes) self._initialized = True @@ -1086,7 +1271,7 @@ def update_processes(self, processes): """ processes_cls = {k: type(obj) for k, obj in self._processes.items()} processes_cls.update(processes) - return type(self)(processes_cls) + return type(self)(processes_cls, self._custom_dependencies) def drop_processes(self, keys): """Drop processe(s) from this model. @@ -1108,7 +1293,7 @@ def drop_processes(self, keys): processes_cls = { k: type(obj) for k, obj in self._processes.items() if k not in keys } - return type(self)(processes_cls) + return type(self)(processes_cls, self._custom_dependencies) def __eq__(self, other): if not isinstance(other, self.__class__): From 4388932d54ee3cd3d8cf6e3985683a1fcbfcf91a Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Tue, 23 Mar 2021 11:18:08 +0100 Subject: [PATCH 7/9] some refactoring --- xsimlab/model.py | 173 +++++++++++++++++++---------------------------- 1 file changed, 71 insertions(+), 102 deletions(-) diff --git a/xsimlab/model.py b/xsimlab/model.py index fdac512a..180b5047 100644 --- a/xsimlab/model.py +++ b/xsimlab/model.py @@ -401,7 +401,7 @@ def get_processes_to_validate(self): return {k: list(v) for k, v in processes_to_validate.items()} - def get_process_dependencies(self, custom_dependencies=None): + def get_process_dependencies(self, custom_dependencies={}): """Return a dictionary where keys are each process of the model and values are lists of the names of dependent processes (or empty lists for processes that have no dependencies). @@ -425,15 +425,14 @@ def get_process_dependencies(self, custom_dependencies=None): ] ) - if custom_dependencies is not None: - for p_name in custom_dependencies: - deps = custom_dependencies[p_name] - if type(deps) == str: - deps = [deps] + for p_name in custom_dependencies: + deps = custom_dependencies[p_name] + if type(deps) == str: + deps = [deps] - # actually add to dependencies - for dep_p_name in deps: - self._dep_processes[p_name].add(dep_p_name) + # actually add to dependencies + for dep_p_name in deps: + self._dep_processes[p_name].add(dep_p_name) for p_name, p_obj in self._processes_obj.items(): for var in filter_variables(p_obj, intent=VarIntent.OUT).values(): @@ -447,10 +446,9 @@ def get_process_dependencies(self, custom_dependencies=None): self._dep_processes[pn].add(p_name) self._dep_processes = {k: list(v) for k, v in self._dep_processes.items()} - self._check_inout_vars() return self._dep_processes - def _check_inout_vars(self): + def _check_inout_vars(self, deps_dict): """ checks if all inout variables and corresponding in variables are explicitly set in the dependencies Out variables always come first, since the get_process_dependencies checks for that. @@ -466,6 +464,10 @@ def _check_inout_vars(self): inout_dict = {} # dict of {key:{p1_name,p2_name}} for inout variables in_dict = {} + # TODO: improve this: the aim is to create a {key:{p1,p2,p3}} dict, + # where p1,p2,p3 are process names that have the key var as inout, resp. in vars + # some problems are that we can have on_demand and state varibles, + # that key can return a tuple or list, for p_name, p_obj in self._processes_obj.items(): # create {key:{p1_name,p2_name}} dicts for in and inout vars. for var in filter_variables(p_obj, intent=VarIntent.INOUT): @@ -474,6 +476,9 @@ def _check_inout_vars(self): else: keys = p_obj.__xsimlab_od_keys__[var] + if type(keys) == tuple: + keys = [keys] + for key in keys: if not key in inout_dict: inout_dict[key] = {p_name} @@ -486,25 +491,25 @@ def _check_inout_vars(self): else: keys = p_obj.__xsimlab_od_keys__[var] + if type(keys) == tuple: + keys = [keys] + for key in keys: if not key in in_dict: in_dict[key] = {p_name} else: in_dict[key].add(p_name) - # filter out variables that do not need to be checked: + # filter out variables that do not need to be checked (without inputs): inout_dict = {k: v for k, v in inout_dict.items() if k in in_dict} - # get a dict of all dependent processes for easier processing - deps_dict = self.get_dependency_dict() - for key, inout_ps in inout_dict.items(): in_ps = in_dict[key] verified_ios = [] # now we only have to search and verify all inout variables - print("checking ", key, " with io processes ", inout_ps) + # print("checking ", key, " with io processes ", inout_ps) for io_p in inout_ps: io_stack = [io_p] while io_stack: @@ -550,104 +555,42 @@ def _check_inout_vars(self): in_ps -= deps_dict[cur] verified_ios.append(cur) io_stack.pop() - # print("finished searching ios, now have: ", in_ps, verified_ios) + + # we finished all inout, and inputs that are descendants of inout + # vars, so all remaining input vars shoudl depend on the last inout var for p in in_ps: if not verified_ios[-1] in deps_dict[p]: raise RuntimeError( f"process {verified_ios[-1]} not in depdendencies of {p} while {key} requires so" ) - def get_dependency_dict(self): - """ - IMPORTANT: assumes no cycles in the graph -> this is actually for the dependency_dict can be undone - generate a {'p_name':{dep1_p_name,dep2_p_name}} list for all processes, for easier validation - TODO: incorporate this into the other DFS algorithm - """ - # this is to ensure that we do not encounter a cycle - seen = set() - descendants = {p: set() for p in self._dep_processes} - completed_d = set() - for p_name in self._dep_processes: - # create the descendants using DFS only if they are not yet there yet - if p_name not in completed_d: - # implement a DFS algorithm - nodes = [p_name] - while nodes: - cur = nodes[-1] - if cur in completed_d: - nodes.pop() - continue - seen.add(cur) - - next_nodes = [] - for nxt in self._dep_processes[cur]: - if nxt in seen: - # Cycle detected! - cycle = [nxt] - while nodes[-1] != nxt: - cycle.append(nodes.pop()) - cycle.append(nodes.pop()) - cycle.reverse() - cycle = "->".join(cycle) - raise RuntimeError( - f"Cycle detected in process graph: {cycle}" - ) - if nxt in completed_d: - descendants[cur].add(nxt) - descendants[cur].update(descendants[nxt]) - else: - next_nodes.append(nxt) - if next_nodes: - nodes.extend(next_nodes) - else: - # it has no more depndencies, so we can add it to the descendants - completed_d.add(cur) - seen.remove(cur) - nodes.pop() - - return descendants - - def transitive_reduction(self): + def transitive_reduction(self, deps_dict): """Returns transitive reduction of a directed graph The transitive reduction of G = (V,E) is a graph G- = (V,E-) such that for all v,w in V there is an edge (v,w) in E- if and only if (v,w) is in E and there is no path from v to w in G with length greater than 1. - Parameters - ---------- - G : NetworkX DiGraph - A directed acyclic graph (DAG) - - Returns - ------- - NetworkX DiGraph - The transitive reduction of `G` - - Raises - ------ - NetworkXError - If `G` is not a directed acyclic graph (DAG) transitive reduction is - not uniquely defined and a :exc:`NetworkXError` exception is raised. - References ---------- https://en.wikipedia.org/wiki/Transitive_reduction adapted from networkx: https://networkx.org/documentation/stable/_modules/networkx/algorithms/dag.html#transitive_reduction """ - dep_dict = self.get_dependency_dict() for p_name in self._dep_processes: p_nbrs = set(self._dep_processes[p_name]) for dep_p in self._dep_processes[p_name]: - p_nbrs -= dep_dict[dep_p] + p_nbrs -= deps_dict[dep_p] self._dep_processes[p_name] = list(p_nbrs) def _sort_processes(self): """Sort processes based on their dependencies (return a list of sorted process names). + new in 0.6.0: now also returns a dictionary of {'p_name':{des,cen,dants}} + for strict checking and transitive reduction. + Stack-based depth-first search traversal. This is based on Tarjan's method for topological sorting. @@ -661,6 +604,7 @@ def _sort_processes(self): """ ordered = [] + descendants = {p: set() for p in self._dep_processes} # Nodes whose descendents have been completely explored. # These nodes are guaranteed to not be part of a cycle. @@ -690,18 +634,19 @@ def _sort_processes(self): # Add direct descendants of cur to nodes stack next_nodes = [] for nxt in self._dep_processes[cur]: - if nxt not in completed: - if nxt in seen: - # Cycle detected! - cycle = [nxt] - while nodes[-1] != nxt: - cycle.append(nodes.pop()) + if nxt in seen: + # Cycle detected! + cycle = [nxt] + while nodes[-1] != nxt: cycle.append(nodes.pop()) - cycle.reverse() - cycle = "->".join(cycle) - raise RuntimeError( - f"Cycle detected in process graph: {cycle}" - ) + cycle.append(nodes.pop()) + cycle.reverse() + cycle = "->".join(cycle) + raise RuntimeError(f"Cycle detected in process graph: {cycle}") + if nxt in completed: + descendants[cur].add(nxt) + descendants[cur].update(descendants[nxt]) + else: next_nodes.append(nxt) if next_nodes: @@ -713,11 +658,20 @@ def _sort_processes(self): completed.add(cur) seen.remove(cur) nodes.pop() - return ordered + return ordered, descendants + + def get_sorted_processes_check_treduce( + self, strict_check=False, transitive_reduce=False + ): + self._sorted_processes, deps_dict = self._sort_processes() + + if strict_check: + self._check_inout_vars(deps_dict) + if transitive_reduce: + self.transitive_reduction(deps_dict) - def get_sorted_processes(self): self._sorted_processes = OrderedDict( - [(p_name, self._processes_obj[p_name]) for p_name in self._sort_processes()] + [(p_name, self._processes_obj[p_name]) for p_name in self._sorted_processes] ) return self._sorted_processes @@ -740,7 +694,13 @@ class Model(AttrMapping): active = [] - def __init__(self, processes, custom_dependencies=None): + def __init__( + self, + processes, + custom_dependencies={}, + strict_check=False, + transitive_reduce=False, + ): """ Parameters ---------- @@ -784,7 +744,10 @@ def __init__(self, processes, custom_dependencies=None): self._custom_dependencies = custom_dependencies self._dep_processes = builder.get_process_dependencies(custom_dependencies) - self._processes = builder.get_sorted_processes() + + self._processes = builder.get_sorted_processes_check_treduce( + strict_check, transitive_reduce + ) # change here to incorporate # builder.get_dependencies_dict() # transitive_reduction() @@ -1293,6 +1256,12 @@ def drop_processes(self, keys): processes_cls = { k: type(obj) for k, obj in self._processes.items() if k not in keys } + self._custom_dependencies = { + p_name: list(set(deps) - set(keys)) + for p_name, deps in self._custom_dependencies.items() + if p_name not in keys + } + return type(self)(processes_cls, self._custom_dependencies) def __eq__(self, other): From c0571d2418d24d8798ca8bb45ca8d0bccc27c5a9 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Tue, 23 Mar 2021 11:54:07 +0100 Subject: [PATCH 8/9] improved refactoring --- xsimlab/model.py | 53 +++++++++++++++++++++++------------------------- 1 file changed, 25 insertions(+), 28 deletions(-) diff --git a/xsimlab/model.py b/xsimlab/model.py index 180b5047..963a9935 100644 --- a/xsimlab/model.py +++ b/xsimlab/model.py @@ -120,6 +120,7 @@ def __init__(self, processes_cls): self._dep_processes = None self._sorted_processes = None + self._deps_dict = None # a cache for group keys self._group_keys = {} @@ -448,7 +449,7 @@ def get_process_dependencies(self, custom_dependencies={}): self._dep_processes = {k: list(v) for k, v in self._dep_processes.items()} return self._dep_processes - def _check_inout_vars(self, deps_dict): + def _check_inout_vars(self): """ checks if all inout variables and corresponding in variables are explicitly set in the dependencies Out variables always come first, since the get_process_dependencies checks for that. @@ -459,6 +460,7 @@ def _check_inout_vars(self, deps_dict): / \ / \ in in in ``` + needs to be run after _sort_processes """ # create dictionaries with all inout variables and input variables inout_dict = {} # dict of {key:{p1_name,p2_name}} for inout variables @@ -518,15 +520,15 @@ def _check_inout_vars(self, deps_dict): io_stack.pop() continue - child_ios = deps_dict[io_p].intersection(inout_ps - {cur}) + child_ios = self._deps_dict[io_p].intersection(inout_ps - {cur}) if child_ios: # TODO: fix this with intersections # lost_children = child_ios.symetric_difference(set(verified_ios)) if len(child_ios) == len(verified_ios): - child_ins = in_ps.intersection(deps_dict[cur]) + child_ins = in_ps.intersection(self._deps_dict[cur]) # verify that all children have the previous io as dependency for child_in in child_ins: - if not verified_ios[-1] in deps_dict[child_in]: + if not verified_ios[-1] in self._deps_dict[child_in]: raise RuntimeError( f"inout process {verified_ios[-1]} not in {child_in}'s " + "dependencies, could not establish strict dependency order" @@ -542,35 +544,36 @@ def _check_inout_vars(self, deps_dict): ) else: raise RuntimeError( - f"inout process {cur} depends on {child_ios}, but should depend on all of {verified_ios}, especially {verified_ios[-1]}" + f"inout process {cur} depends on {child_ios}, but should\ + depend on all of {verified_ios}, especially {verified_ios[-1]}" ) else: # we are at the bottom inout process: remove in variables from the set # this can only happen if we are the first process at the bottom if verified_ios: - # impor raise RuntimeError( f"inout process {cur} has no dependencies with variable {key}, but {verified_ios} should be one", ) - in_ps -= deps_dict[cur] + in_ps -= self._deps_dict[cur] verified_ios.append(cur) io_stack.pop() # we finished all inout, and inputs that are descendants of inout # vars, so all remaining input vars shoudl depend on the last inout var for p in in_ps: - if not verified_ios[-1] in deps_dict[p]: + if not verified_ios[-1] in self._deps_dict[p]: raise RuntimeError( f"process {verified_ios[-1]} not in depdendencies of {p} while {key} requires so" ) - def transitive_reduction(self, deps_dict): + def transitive_reduction(self): """Returns transitive reduction of a directed graph The transitive reduction of G = (V,E) is a graph G- = (V,E-) such that for all v,w in V there is an edge (v,w) in E- if and only if (v,w) is in E and there is no path from v to w in G with length greater than 1. + needs to be run after _sort_processes References ---------- https://en.wikipedia.org/wiki/Transitive_reduction @@ -581,7 +584,7 @@ def transitive_reduction(self, deps_dict): for p_name in self._dep_processes: p_nbrs = set(self._dep_processes[p_name]) for dep_p in self._dep_processes[p_name]: - p_nbrs -= deps_dict[dep_p] + p_nbrs -= self._deps_dict[dep_p] self._dep_processes[p_name] = list(p_nbrs) def _sort_processes(self): @@ -604,7 +607,7 @@ def _sort_processes(self): """ ordered = [] - descendants = {p: set() for p in self._dep_processes} + self._deps_dict = {p: set() for p in self._dep_processes} # Nodes whose descendents have been completely explored. # These nodes are guaranteed to not be part of a cycle. @@ -644,8 +647,8 @@ def _sort_processes(self): cycle = "->".join(cycle) raise RuntimeError(f"Cycle detected in process graph: {cycle}") if nxt in completed: - descendants[cur].add(nxt) - descendants[cur].update(descendants[nxt]) + self._deps_dict[cur].add(nxt) + self._deps_dict[cur].update(self._deps_dict[nxt]) else: next_nodes.append(nxt) @@ -658,20 +661,12 @@ def _sort_processes(self): completed.add(cur) seen.remove(cur) nodes.pop() - return ordered, descendants + return ordered - def get_sorted_processes_check_treduce( - self, strict_check=False, transitive_reduce=False - ): - self._sorted_processes, deps_dict = self._sort_processes() - - if strict_check: - self._check_inout_vars(deps_dict) - if transitive_reduce: - self.transitive_reduction(deps_dict) + def get_sorted_processes(self, strict_check=False, transitive_reduce=False): self._sorted_processes = OrderedDict( - [(p_name, self._processes_obj[p_name]) for p_name in self._sorted_processes] + [(p_name, self._processes_obj[p_name]) for p_name in self._sort_processes()] ) return self._sorted_processes @@ -745,11 +740,13 @@ def __init__( self._custom_dependencies = custom_dependencies self._dep_processes = builder.get_process_dependencies(custom_dependencies) - self._processes = builder.get_sorted_processes_check_treduce( - strict_check, transitive_reduce - ) # change here to incorporate + self._processes = builder.get_sorted_processes() - # builder.get_dependencies_dict() # transitive_reduction() + # these depend on the deps_dict created in sort_processes: + if strict_check: + builder._check_inout_vars() + if transitive_reduce: + builder.transitive_reduction() super(Model, self).__init__(self._processes) self._initialized = True From 34bb82cab09fc6b37024f93571974f7e6d1b3f89 Mon Sep 17 00:00:00 2001 From: Joeperdefloep Date: Tue, 23 Mar 2021 17:16:13 +0100 Subject: [PATCH 9/9] fixed drop_processes ++DFS YAY! --- xsimlab/model.py | 112 +++++++++++++++++++++++++++++++++++------------ 1 file changed, 85 insertions(+), 27 deletions(-) diff --git a/xsimlab/model.py b/xsimlab/model.py index 963a9935..f88e4e41 100644 --- a/xsimlab/model.py +++ b/xsimlab/model.py @@ -426,14 +426,9 @@ def get_process_dependencies(self, custom_dependencies={}): ] ) - for p_name in custom_dependencies: - deps = custom_dependencies[p_name] - if type(deps) == str: - deps = [deps] - - # actually add to dependencies - for dep_p_name in deps: - self._dep_processes[p_name].add(dep_p_name) + # actually add custom dependencies + for p_name, deps in custom_dependencies.items(): + self._dep_processes[p_name].update(deps) for p_name, p_obj in self._processes_obj.items(): for var in filter_variables(p_obj, intent=VarIntent.OUT).values(): @@ -524,7 +519,7 @@ def _check_inout_vars(self): if child_ios: # TODO: fix this with intersections # lost_children = child_ios.symetric_difference(set(verified_ios)) - if len(child_ios) == len(verified_ios): + if child_ios == set(verified_ios): child_ins = in_ps.intersection(self._deps_dict[cur]) # verify that all children have the previous io as dependency for child_in in child_ins: @@ -537,7 +532,7 @@ def _check_inout_vars(self): in_ps -= child_ins verified_ios.append(cur) io_stack.pop() - elif len(child_ios) > len(verified_ios): + elif child_ios - set(verified_ios): # we need to search deeper: add to the stack. io_stack.extend( [io for io in child_ios if io not in verified_ios] @@ -737,15 +732,26 @@ def __init__( self._processes_to_validate = builder.get_processes_to_validate() - self._custom_dependencies = custom_dependencies - self._dep_processes = builder.get_process_dependencies(custom_dependencies) + # clean custom dependencies + self._custom_dependencies = {} + for p_name, c_deps in custom_dependencies.items(): + c_deps = ( + {c_deps} if isinstance(c_deps, str) else {c_dep for c_dep in c_deps} + ) + self._custom_dependencies[p_name] = c_deps + + self._dep_processes = builder.get_process_dependencies( + self._custom_dependencies + ) self._processes = builder.get_sorted_processes() # these depend on the deps_dict created in sort_processes: - if strict_check: + self._strict_check = strict_check + self._transitive_reduce = transitive_reduce + if self._strict_check: builder._check_inout_vars() - if transitive_reduce: + if self._transitive_reduce: builder.transitive_reduction() super(Model, self).__init__(self._processes) @@ -827,9 +833,13 @@ def dependent_processes(self): return self._dep_processes def visualize( - self, show_only_variable=None, show_inputs=False, show_variables=False + self, + show_only_variable=None, + show_inputs=False, + show_variables=False, + show_inout_arrows=True, ): - """Render the model as a graph using dot (require graphviz). + """Render the model as a graph using dot (requires graphviz). Parameters ---------- @@ -856,6 +866,7 @@ def visualize( show_only_variable=show_only_variable, show_inputs=show_inputs, show_variables=show_variables, + show_inout_arrows=show_inout_arrows, ) @property @@ -1212,7 +1223,12 @@ def clone(self): """ processes_cls = {k: type(obj) for k, obj in self._processes.items()} - return type(self)(processes_cls, self._custom_dependencies) + return type(self)( + processes_cls, + self._custom_dependencies, + self._strict_check, + self._transitive_reduce, + ) def update_processes(self, processes): """Add or replace processe(s) in this model. @@ -1231,14 +1247,19 @@ def update_processes(self, processes): """ processes_cls = {k: type(obj) for k, obj in self._processes.items()} processes_cls.update(processes) - return type(self)(processes_cls, self._custom_dependencies) + return type(self)( + processes_cls, + self._custom_dependencies, + self._strict_check, + self._transitive_reduce, + ) def drop_processes(self, keys): """Drop processe(s) from this model. Parameters ---------- - keys : str or list of str + keys : str or iterable of str Name(s) of the processes to drop. Returns @@ -1247,19 +1268,56 @@ def drop_processes(self, keys): New Model instance with dropped processes. """ - if isinstance(keys, str): - keys = [keys] + keys = {keys} if isinstance(keys, str) else {key for key in keys} processes_cls = { k: type(obj) for k, obj in self._processes.items() if k not in keys } - self._custom_dependencies = { - p_name: list(set(deps) - set(keys)) - for p_name, deps in self._custom_dependencies.items() - if p_name not in keys - } - return type(self)(processes_cls, self._custom_dependencies) + # nooo we also should check for chains of deps e.g. + # a->b->c->d->e where {b,c,d} are removed + # wake me up when the depndencies end... + # here comes the stack again... defining who we are... + # start a DFS only on these keys again... + # actually it is only dfs on custom deps, so not too bad + # let's see if we can do it in-place + completed = set() + for key in self._custom_dependencies: + if key in completed: + continue + key_stack = [key] + while key_stack: + cur = key_stack[-1] + if cur in completed: + key_stack.pop() + continue + + child_keys = keys.intersection(self._custom_dependencies[cur]) + if child_keys.issubset(completed): + # all children are added, so we are safe + self._custom_dependencies[cur].update( + *[ + self._custom_dependencies[child_key] + for child_key in child_keys + ] + ) + self._custom_dependencies[cur] -= child_keys + completed.add(cur) + key_stack.pop() + else: # if child_keys - completed: + # we need to search deeper: add to the stack. + key_stack.extend([k for k in child_keys - completed]) + + # that was actually quite ok.. now also remove keys from custom deps + for key in keys: + del self._custom_dependencies[key] + + return type(self)( + processes_cls, + self._custom_dependencies, + self._strict_check, + self._transitive_reduce, + ) def __eq__(self, other): if not isinstance(other, self.__class__):