Refactoring v0.15.1

See CHANGELOG.md for a full list of changes

* Removed nxsim
* Refactored `agents.NetworkAgent` and `agents.BaseAgent`
* Refactored exporters
* Added stats to history

CHANGELOG.md

@@ -3,6 +3,29 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.15.1]
+### Added
+* read-only `History`
+### Fixed
+* Serialization problem with the `Environment` on parallel mode.
+* Analysis functions now work as they should in the tutorial
+## [0.15.0]
+### Added
+* Control logging level in CLI and simulation
+* `Stats` to calculate trial and simulation-wide statistics
+* Simulation statistics are stored in a separate table in history (see `History.get_stats` and `History.save_stats`, as well as `soil.stats`)
+* Aliased `NetworkAgent.G` to `NetworkAgent.topology`.
+### Changed
+* Templates in config files can be given as dictionaries in addition to strings
+* Samplers are used more explicitly
+* Removed nxsim dependency. We had already made a lot of changes, and nxsim has not been updated in 5 years.
+* Exporter methods renamed to `trial` and `end`. Added `start`.
+* `Distribution` exporter now a stats class
+* `global_topology` renamed to `topology`
+* Moved topology-related methods to `NetworkAgent`
+### Fixed
+* Temporary files used for history in dry_run mode are not longer left open 
+
 ## [0.14.9]
 ### Changed
 * Seed random before environment initialization

docs/conf.py

@@ -31,7 +31,7 @@
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
-extensions = []
+extensions = ['IPython.sphinxext.ipython_console_highlighting']
 
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
@@ -69,7 +69,7 @@ language = None
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
 # This patterns also effect to html_static_path and html_extra_path
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
+exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', '**.ipynb_checkpoints']
 
 # The name of the Pygments (syntax highlighting) style to use.
 pygments_style = 'sphinx'

docs/configuration.rst

@@ -218,3 +218,24 @@ These agents are programmed in much the same way as network agents, the only dif
 
 You may use environment agents to model events that a normal agent cannot control, such as natural disasters or chance.
 They are also useful to add behavior that has little to do with the network and the interactions within that network.
+
+Templating
+==========
+
+Sometimes, it is useful to parameterize a simulation and run it over a range of values in order to compare each run and measure the effect of those parameters in the simulation.
+For instance, you may want to run a simulation with different agent distributions.
+
+This can be done in Soil using **templates**.
+A template is a configuration where some of the values are specified with a variable.
+e.g.,  ``weight: "{{ var1 }}"`` instead of ``weight: 1``.
+There are two types of variables, depending on how their values are decided:
+
+* Fixed. A list of values is provided, and a new simulation is run for each possible value. If more than a variable is given, a new simulation will be run per combination of values.
+* Bounded/Sampled. The bounds of the variable are provided, along with a sampler method, which will be used to compute all the configuration combinations.
+
+When fixed and bounded variables are mixed, Soil generates a new configuration per combination of fixed values and bounded values.
+
+Here is an example with a single fixed variable and two bounded variable:
+
+.. literalinclude:: ../examples/template.yml
+   :language: yaml

examples/NewsSpread.ipynb

@@ -500,7 +500,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.8.5"
   },
   "toc": {
    "colors": {

examples/Untitled.ipynb

@@ -80800,7 +80800,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.8.6"
   }
  },
  "nbformat": 4,

examples/rabbits/rabbit_agents.py

@@ -1,4 +1,4 @@
-from soil.agents import FSM, state, default_state, BaseAgent
+from soil.agents import FSM, state, default_state, BaseAgent, NetworkAgent
 from enum import Enum
 from random import random, choice
 from itertools import islice
@@ -80,7 +80,7 @@ class RabbitModel(FSM):
                 self.env.add_edge(self['mate'], child.id)
                 # self.add_edge()
                 self.debug('A BABY IS COMING TO LIFE')
-                self.env['rabbits_alive'] = self.env.get('rabbits_alive', self.global_topology.number_of_nodes())+1
+                self.env['rabbits_alive'] = self.env.get('rabbits_alive', self.topology.number_of_nodes())+1
                 self.debug('Rabbits alive: {}'.format(self.env['rabbits_alive']))
                 self['offspring'] += 1
                 self.env.get_agent(self['mate'])['offspring'] += 1
@@ -97,12 +97,14 @@ class RabbitModel(FSM):
         return
 
 
-class RandomAccident(BaseAgent):
+class RandomAccident(NetworkAgent):
 
     level = logging.DEBUG
 
     def step(self):
-        rabbits_total = self.global_topology.number_of_nodes()
+        rabbits_total = self.topology.number_of_nodes()
+        if 'rabbits_alive' not in self.env:
+            self.env['rabbits_alive'] = 0
         rabbits_alive = self.env.get('rabbits_alive', rabbits_total)
         prob_death = self.env.get('prob_death', 1e-100)*math.floor(math.log10(max(1, rabbits_alive)))
         self.debug('Killing some rabbits with prob={}!'.format(prob_death))
@@ -116,5 +118,5 @@ class RandomAccident(BaseAgent):
                 self.log('Rabbits alive: {}'.format(self.env['rabbits_alive']))
                 i.set_state(i.dead)
         self.log('Rabbits alive: {}/{}'.format(rabbits_alive, rabbits_total))
-        if self.count_agents(state_id=RabbitModel.dead.id) == self.global_topology.number_of_nodes():
+        if self.count_agents(state_id=RabbitModel.dead.id) == self.topology.number_of_nodes():
             self.die()

examples/template.yml

@@ -1,13 +1,8 @@
 ---
-vars:
-  bounds:
-    x1: [0, 1]
-    x2: [1, 2]
-  fixed:
-    x3: ["a", "b", "c"]
-sampler: "SALib.sample.morris.sample"
-samples: 10
-template: |
+sampler:
+  method: "SALib.sample.morris.sample"
+  N: 10
+template:
   group: simple
   num_trials: 1
   interval: 1
@@ -19,11 +14,17 @@ template: |
     n: 10
   network_agents:
     - agent_type: CounterModel
-      weight: {{ x1 }}
+      weight: "{{ x1 }}"
       state:
         id: 0
     - agent_type: AggregatedCounter
-      weight: {{ 1 - x1 }}
+      weight: "{{ 1 - x1 }}"
   environment_params:
-    name: {{ x3 }}
+    name: "{{ x3 }}"
   skip_test: true
+vars:
+  bounds:
+    x1: [0, 1]
+    x2: [1, 2]
+  fixed:
+    x3: ["a", "b", "c"]

examples/terrorism/TerroristNetworkModel.py

@@ -195,14 +195,14 @@ class TerroristNetworkModel(TerroristSpreadModel):
                     break
 
     def get_distance(self, target):
-        source_x, source_y = nx.get_node_attributes(self.global_topology, 'pos')[self.id]
-        target_x, target_y = nx.get_node_attributes(self.global_topology, 'pos')[target]
+        source_x, source_y = nx.get_node_attributes(self.topology, 'pos')[self.id]
+        target_x, target_y = nx.get_node_attributes(self.topology, 'pos')[target]
         dx = abs( source_x - target_x )
         dy = abs( source_y - target_y )
         return ( dx ** 2 + dy ** 2 ) ** ( 1 / 2 )
 
     def shortest_path_length(self, target):
         try:
-            return nx.shortest_path_length(self.global_topology, self.id, target)
+            return nx.shortest_path_length(self.topology, self.id, target)
         except nx.NetworkXNoPath:
             return float('inf')

requirements.txt

@@ -1,6 +1,5 @@
-nxsim>=0.1.2
-simpy
-networkx>=2.0,<2.4
+simpy>=4.0
+networkx>=2.5
 numpy
 matplotlib
 pyyaml>=5.1

soil/VERSION

@@ -1 +1 @@
-0.14.9
+0.15.1

soil/__init__.py

@@ -17,12 +17,12 @@ from .environment import Environment
 from .history import History
 from . import serialization
 from . import analysis
+from .utils import logger
 
 def main():
     import argparse
     from . import simulation
 
-    logging.basicConfig(level=logging.INFO)
     logging.info('Running SOIL version: {}'.format(__version__))
 
     parser = argparse.ArgumentParser(description='Run a SOIL simulation')
@@ -40,6 +40,8 @@ def main():
                         help='Dump GEXF graph. Defaults to false.')
     parser.add_argument('--csv', action='store_true',
                         help='Dump history in CSV format. Defaults to false.')
+    parser.add_argument('--level', type=str,
+                        help='Logging level')
     parser.add_argument('--output', '-o', type=str, default="soil_output",
                         help='folder to write results to. It defaults to the current directory.')
     parser.add_argument('--synchronous', action='store_true',
@@ -48,6 +50,7 @@ def main():
                         help='Export environment and/or simulations using this exporter')
 
     args = parser.parse_args()
+    logging.basicConfig(level=getattr(logging, (args.level or 'INFO').upper()))
 
     if os.getcwd() not in sys.path:
         sys.path.append(os.getcwd())

soil/agents/BassModel.py

@@ -9,7 +9,7 @@ class BassModel(BaseAgent):
         imitation_prob
     """
 
-    def __init__(self, environment, agent_id, state):
+    def __init__(self, environment, agent_id, state, **kwargs):
         super().__init__(environment=environment, agent_id=agent_id, state=state)
         env_params = environment.environment_params
         self.state['sentimentCorrelation'] = 0
@@ -19,7 +19,7 @@ class BassModel(BaseAgent):
 
     def behaviour(self):
         # Outside effects
-        if random.random() < self.state_params['innovation_prob']:
+        if random.random() < self['innovation_prob']:
             if self.state['id'] == 0:
                 self.state['id'] = 1
                 self.state['sentimentCorrelation'] = 1
@@ -32,7 +32,7 @@ class BassModel(BaseAgent):
         if self.state['id'] == 0:
             aware_neighbors = self.get_neighboring_agents(state_id=1)
             num_neighbors_aware = len(aware_neighbors)
-            if random.random() < (self.state_params['imitation_prob']*num_neighbors_aware):
+            if random.random() < (self['imitation_prob']*num_neighbors_aware):
                 self.state['id'] = 1
                 self.state['sentimentCorrelation'] = 1
 

soil/agents/CounterModel.py

@@ -1,7 +1,7 @@
-from . import BaseAgent
+from . import NetworkAgent
 
 
-class CounterModel(BaseAgent):
+class CounterModel(NetworkAgent):
     """
     Dummy behaviour. It counts the number of nodes in the network and neighbors
     in each step and adds it to its state.
@@ -9,14 +9,14 @@ class CounterModel(BaseAgent):
 
     def step(self):
         # Outside effects
-        total = len(list(self.get_all_agents()))
+        total = len(list(self.get_agents()))
         neighbors = len(list(self.get_neighboring_agents()))
         self['times'] = self.get('times', 0) + 1
         self['neighbors'] = neighbors
         self['total'] = total
 
 
-class AggregatedCounter(BaseAgent):
+class AggregatedCounter(NetworkAgent):
     """
     Dummy behaviour. It counts the number of nodes in the network and neighbors
     in each step and adds it to its state.
@@ -33,6 +33,6 @@ class AggregatedCounter(BaseAgent):
         self['times'] += 1
         neighbors = len(list(self.get_neighboring_agents()))
         self['neighbors'] += neighbors
-        total = len(list(self.get_all_agents()))
+        total = len(list(self.get_agents()))
         self['total'] += total
         self.debug('Running for step: {}. Total: {}'.format(self.now, total))

soil/agents/__init__.py

@@ -3,19 +3,19 @@
 # for x in range(0, settings.network_params["number_of_nodes"]):
 #     sentimentCorrelationNodeArray.append({'id': x})
 # Initialize agent states. Let's assume everyone is normal.
-    
 
-import nxsim
+
 import logging
 from collections import OrderedDict
 from copy import deepcopy
 from functools import partial
 from scipy.spatial import cKDTree as KDTree
 import json
+import simpy
 
 from functools import wraps
 
-from .. import serialization, history
+from .. import serialization, history, utils
 
 
 def as_node(agent):
@@ -24,7 +24,7 @@ def as_node(agent):
     return agent
 
 
-class BaseAgent(nxsim.BaseAgent):
+class BaseAgent:
     """
     A special simpy BaseAgent that keeps track of its state history.
     """
@@ -32,14 +32,13 @@ class BaseAgent(nxsim.BaseAgent):
     defaults = {}
 
     def __init__(self, environment, agent_id, state=None,
-                 name=None, interval=None, **state_params):
+                 name=None, interval=None):
         # Check for REQUIRED arguments
         assert environment is not None, TypeError('__init__ missing 1 required keyword argument: \'environment\'. '
                                                   'Cannot be NoneType.')
         # Initialize agent parameters
         self.id = agent_id
         self.name = name or '{}[{}]'.format(type(self).__name__, self.id)
-        self.state_params = state_params
 
         # Register agent to environment
         self.env = environment
@@ -51,10 +50,10 @@ class BaseAgent(nxsim.BaseAgent):
         self.state = real_state
         self.interval = interval
 
-        if not hasattr(self, 'level'):
-            self.level = logging.DEBUG
-        self.logger = logging.getLogger(self.env.name)
-        self.logger.setLevel(self.level)
+        self.logger = logging.getLogger(self.env.name).getChild(self.name)
+
+        if hasattr(self, 'level'):
+            self.logger.setLevel(self.level)
 
         # initialize every time an instance of the agent is created
         self.action = self.env.process(self.run())
@@ -75,14 +74,10 @@ class BaseAgent(nxsim.BaseAgent):
         for k, v in value.items():
             self[k] = v
 
-    @property
-    def global_topology(self):
-        return self.env.G
-    
     @property
     def environment_params(self):
         return self.env.environment_params
-    
+
     @environment_params.setter
     def environment_params(self, value):
         self.env.environment_params = value
@@ -135,36 +130,10 @@ class BaseAgent(nxsim.BaseAgent):
     def die(self, remove=False):
         self.alive = False
         if remove:
-            super().die()
+            self.remove_node(self.id)
 
     def step(self):
-        pass
-
-    def count_agents(self, **kwargs):
-        return len(list(self.get_agents(**kwargs)))
-
-    def count_neighboring_agents(self, state_id=None, **kwargs):
-        return len(super().get_neighboring_agents(state_id=state_id, **kwargs))
-
-    def get_neighboring_agents(self, state_id=None, **kwargs):
-        return self.get_agents(limit_neighbors=True, state_id=state_id, **kwargs)
-
-    def get_agents(self, agents=None, limit_neighbors=False, **kwargs):
-        if limit_neighbors:
-            agents = super().get_agents(limit_neighbors=limit_neighbors)
-        else:
-            agents = self.env.get_agents(agents)
-        return select(agents, **kwargs)
-
-    def log(self, message, *args, level=logging.INFO, **kwargs):
-        message = message + " ".join(str(i) for i in args)
-        message = "\t{:10}@{:>5}:\t{}".format(self.name, self.now, message)
-        for k, v in kwargs:
-            message += " {k}={v} ".format(k, v)
-        extra = {}
-        extra['now'] = self.now
-        extra['id'] = self.id
-        return self.logger.log(level, message, extra=extra)
+        return
 
     def debug(self, *args, **kwargs):
         return self.log(*args, level=logging.DEBUG, **kwargs)
@@ -192,24 +161,59 @@ class BaseAgent(nxsim.BaseAgent):
         self._state = state['_state']
         self.env = state['environment']
 
-    def add_edge(self, node1, node2, **attrs):
-        node1 = as_node(node1)
-        node2 = as_node(node2)
+class NetworkAgent(BaseAgent):
 
-        for n in [node1, node2]:
-            if n not in self.global_topology.nodes(data=False):
-                raise ValueError('"{}" not in the graph'.format(n))
-        return self.global_topology.add_edge(node1, node2, **attrs)
+    @property
+    def topology(self):
+        return self.env.G
+
+    @property
+    def G(self):
+        return self.env.G
+
+    def count_agents(self, **kwargs):
+        return len(list(self.get_agents(**kwargs)))
+
+    def count_neighboring_agents(self, state_id=None, **kwargs):
+        return len(self.get_neighboring_agents(state_id=state_id, **kwargs))
+
+    def get_neighboring_agents(self, state_id=None, **kwargs):
+        return self.get_agents(limit_neighbors=True, state_id=state_id, **kwargs)
+
+    def get_agents(self, agents=None, limit_neighbors=False, **kwargs):
+        if limit_neighbors:
+            agents = self.topology.neighbors(self.id)
+
+        agents = self.env.get_agents(agents)
+        return select(agents, **kwargs)
+
+    def log(self, message, *args, level=logging.INFO, **kwargs):
+        message = message + " ".join(str(i) for i in args)
+        message = " @{:>3}: {}".format(self.now, message)
+        for k, v in kwargs:
+            message += " {k}={v} ".format(k, v)
+        extra = {}
+        extra['now'] = self.now
+        extra['agent_id'] = self.id
+        extra['agent_name'] = self.name
+        return self.logger.log(level, message, extra=extra)
 
     def subgraph(self, center=True, **kwargs):
         include = [self] if center else []
-        return self.global_topology.subgraph(n.id for n in self.get_agents(**kwargs)+include)
+        return self.topology.subgraph(n.id for n in self.get_agents(**kwargs)+include)
 
+    def remove_node(self, agent_id):
+        self.topology.remove_node(agent_id)
 
-class NetworkAgent(BaseAgent):
+    def add_edge(self, other, edge_attr_dict=None, *edge_attrs):
+        # return super(NetworkAgent, self).add_edge(node1=self.id, node2=other, **kwargs)
+        if self.id not in self.topology.nodes(data=False):
+            raise ValueError('{} not in list of existing agents in the network'.format(self.id))
+        if other not in self.topology.nodes(data=False):
+            raise ValueError('{} not in list of existing agents in the network'.format(other))
+
+        self.topology.add_edge(self.id, other, edge_attr_dict=edge_attr_dict, *edge_attrs)
 
-    def add_edge(self, other, **kwargs):
-        return super(NetworkAgent, self).add_edge(node1=self.id, node2=other, **kwargs)
 
     def ego_search(self, steps=1, center=False, node=None, **kwargs):
         '''Get a list of nodes in the ego network of *node* of radius *steps*'''
@@ -220,14 +224,14 @@ class NetworkAgent(BaseAgent):
     def degree(self, node, force=False):
         node = as_node(node)
         if force or (not hasattr(self.env, '_degree')) or getattr(self.env, '_last_step', 0) < self.now:
-            self.env._degree = nx.degree_centrality(self.global_topology)
+            self.env._degree = nx.degree_centrality(self.topology)
             self.env._last_step = self.now
         return self.env._degree[node]
 
     def betweenness(self, node, force=False):
         node = as_node(node)
         if force or (not hasattr(self.env, '_betweenness')) or getattr(self.env, '_last_step', 0) < self.now:
-            self.env._betweenness = nx.betweenness_centrality(self.global_topology)
+            self.env._betweenness = nx.betweenness_centrality(self.topology)
             self.env._last_step = self.now
         return self.env._betweenness[node]
 
@@ -292,16 +296,22 @@ class MetaFSM(type):
         cls.states = states
 
 
-class FSM(BaseAgent, metaclass=MetaFSM):
+class FSM(NetworkAgent, metaclass=MetaFSM):
     def __init__(self, *args, **kwargs):
         super(FSM, self).__init__(*args, **kwargs)
         if 'id' not in self.state:
             if not self.default_state:
                 raise ValueError('No default state specified for {}'.format(self.id))
             self['id'] = self.default_state.id
+        self._next_change = simpy.core.Infinity
+        self._next_state = self.state
 
     def step(self):
-        if 'id' in self.state:
+        if self._next_change < self.now:
+            next_state = self._next_state
+            self._next_change = simpy.core.Infinity
+            self['id'] = next_state
+        elif 'id' in self.state:
             next_state = self['id']
         elif self.default_state:
             next_state = self.default_state.id
@@ -311,6 +321,10 @@ class FSM(BaseAgent, metaclass=MetaFSM):
             raise Exception('{} is not a valid id for {}'.format(next_state, self))
         return self.states[next_state](self)
 
+    def next_state(self, state):
+        self._next_change = self.now
+        self._next_state = state
+
     def set_state(self, state):
         if hasattr(state, 'id'):
             state = state.id
@@ -371,14 +385,18 @@ def calculate_distribution(network_agents=None,
     else:
         raise ValueError('Specify a distribution or a default agent type')
 
+    # Fix missing weights and incompatible types
+    for x in network_agents:
+        x['weight'] = float(x.get('weight', 1))
+
     # Calculate the thresholds
-    total = sum(x.get('weight', 1) for x in network_agents)
+    total = sum(x['weight'] for x in network_agents)
     acc = 0
     for v in network_agents:
         if 'ids' in v:
             v['threshold'] = STATIC_THRESHOLD
             continue
-        upper = acc + (v.get('weight', 1)/total)
+        upper = acc + (v['weight']/total)
         v['threshold'] = [acc, upper]
         acc = upper
     return network_agents
@@ -425,7 +443,7 @@ def _validate_states(states, topology):
     states = states or []
     if isinstance(states, dict):
         for x in states:
-            assert x in topology.node
+            assert x in topology.nodes
     else:
         assert len(states) <= len(topology)
     return states

soil/analysis.py

@@ -28,13 +28,13 @@ def _read_data(pattern, *args, from_csv=False, process_args=None, **kwargs):
                 df = read_csv(trial_data, **kwargs)
                 yield config_file, df, config
         else:
-            for trial_data in sorted(glob.glob(join(folder, '*.db.sqlite'))):
+            for trial_data in sorted(glob.glob(join(folder, '*.sqlite'))):
                 df = read_sql(trial_data, **kwargs)
                 yield config_file, df, config
 
 
 def read_sql(db, *args, **kwargs):
-    h = history.History(db_path=db, backup=False)
+    h = history.History(db_path=db, backup=False, readonly=True)
     df = h.read_sql(*args, **kwargs)
     return df
 
@@ -69,6 +69,13 @@ def convert_types_slow(df):
     df = df.apply(convert_row, axis=1)
     return df
 
+
+def split_processed(df):
+    env = df.loc[:, df.columns.get_level_values(1).isin(['env', 'stats'])]
+    agents = df.loc[:, ~df.columns.get_level_values(1).isin(['env', 'stats'])]
+    return env, agents
+
+
 def split_df(df):
     '''
     Split a dataframe in two dataframes: one with the history of agents,
@@ -136,7 +143,7 @@ def get_value(df, *keys, aggfunc='sum'):
     return df.groupby(axis=1, level=0).agg(aggfunc)
 
 
-def plot_all(*args, **kwargs):
+def plot_all(*args, plot_args={}, **kwargs):
     '''
     Read all the trial data and plot the result of applying a function on them.
     '''
@@ -144,14 +151,17 @@ def plot_all(*args, **kwargs):
     ps = []
     for line in dfs:
         f, df, config = line
-        df.plot(title=config['name'])
+        if len(df) < 1:
+            continue
+        df.plot(title=config['name'], **plot_args)
         ps.append(df)
     return ps
 
 def do_all(pattern, func, *keys, include_env=False, **kwargs):
     for config_file, df, config in read_data(pattern, keys=keys):
+        if len(df) < 1:
+            continue
         p = func(df, *keys, **kwargs)
-        p.plot(title=config['name'])
         yield config_file, p, config
 
 

soil/environment.py

@@ -8,11 +8,10 @@ import yaml
 import tempfile
 import pandas as pd
 from copy import deepcopy
-from collections import Counter
 from networkx.readwrite import json_graph
 
 import networkx as nx
-import nxsim
+import simpy
 
 from . import serialization, agents, analysis, history, utils
 
@@ -23,7 +22,7 @@ _CONFIG_PROPS = [ 'name',
                  'interval',
                  ]
 
-class Environment(nxsim.NetworkEnvironment):
+class Environment(simpy.Environment):
     """
     The environment is key in a simulation. It contains the network topology,
     a reference to network and environment agents, as well as the environment
@@ -42,7 +41,10 @@ class Environment(nxsim.NetworkEnvironment):
                  interval=1,
                  seed=None,
                  topology=None,
-                 *args, **kwargs):
+                 initial_time=0,
+                 **environment_params):
+
+
         self.name = name or 'UnnamedEnvironment'
         seed = seed or time.time()
         random.seed(seed)
@@ -52,7 +54,11 @@ class Environment(nxsim.NetworkEnvironment):
         self.default_state = deepcopy(default_state) or {}
         if not topology:
             topology = nx.Graph()
-        super().__init__(*args, topology=topology, **kwargs)
+        self.G = nx.Graph(topology) 
+
+        super().__init__(initial_time=initial_time)
+        self.environment_params = environment_params
+
         self._env_agents = {}
         self.interval = interval
         self._history = history.History(name=self.name,
@@ -151,12 +157,10 @@ class Environment(nxsim.NetworkEnvironment):
         start = start or self.now
         return self.G.add_edge(agent1, agent2, **attrs)
 
-    def run(self, *args, **kwargs):
+    def run(self, until, *args, **kwargs):
         self._save_state()
-        self.log_stats()
-        super().run(*args, **kwargs)
+        super().run(until, *args, **kwargs)
         self._history.flush_cache()
-        self.log_stats()
 
     def _save_state(self, now=None):
         serialization.logger.debug('Saving state @{}'.format(self.now))
@@ -318,25 +322,6 @@ class Environment(nxsim.NetworkEnvironment):
 
         return G
 
-    def stats(self):
-        stats = {}
-        stats['network'] = {}
-        stats['network']['n_nodes'] = self.G.number_of_nodes()
-        stats['network']['n_edges'] = self.G.number_of_edges()
-        c = Counter()
-        c.update(a.__class__.__name__ for a in self.network_agents)
-        stats['agents'] = {}
-        stats['agents']['model_count'] = dict(c)
-        c2 = Counter()
-        c2.update(a['id'] for a in self.network_agents)
-        stats['agents']['state_count'] = dict(c2)
-        stats['params'] = self.environment_params
-        return stats
-
-    def log_stats(self):
-        stats = self.stats()
-        serialization.logger.info('Environment stats: \n{}'.format(yaml.dump(stats, default_flow_style=False)))
-    
     def __getstate__(self):
         state = {}
         for prop in _CONFIG_PROPS:
@@ -344,6 +329,7 @@ class Environment(nxsim.NetworkEnvironment):
         state['G'] = json_graph.node_link_data(self.G)
         state['environment_agents'] = self._env_agents
         state['history'] = self._history
+        state['_now'] = self._now
         return state
 
     def __setstate__(self, state):
@@ -352,6 +338,8 @@ class Environment(nxsim.NetworkEnvironment):
         self._env_agents = state['environment_agents']
         self.G = json_graph.node_link_graph(state['G'])
         self._history = state['history']
+        self._now = state['_now']
+        self._queue = []
 
 
 SoilEnvironment = Environment

soil/exporters.py

@@ -1,10 +1,11 @@
 import os
+import csv as csvlib
 import time
 from io import BytesIO
 
 import matplotlib.pyplot as plt
 import networkx as nx
-import pandas as pd
+
 
 from .serialization import deserialize
 from .utils import open_or_reuse, logger, timer
@@ -49,7 +50,7 @@ class Exporter:
     '''
 
     def __init__(self, simulation, outdir=None, dry_run=None, copy_to=None):
-        self.sim = simulation
+        self.simulation = simulation
         outdir = outdir or os.path.join(os.getcwd(), 'soil_output')
         self.outdir = os.path.join(outdir,
                                    simulation.group or '',
@@ -59,12 +60,15 @@ class Exporter:
 
     def start(self):
         '''Method to call when the simulation starts'''
+        pass
 
-    def end(self):
+    def end(self, stats):
         '''Method to call when the simulation ends'''
+        pass
 
-    def trial_end(self, env):
+    def trial(self, env, stats):
         '''Method to call when a trial ends'''
+        pass
 
     def output(self, f, mode='w', **kwargs):
         if self.dry_run:
@@ -84,13 +88,13 @@ class default(Exporter):
     def start(self):
         if not self.dry_run:
             logger.info('Dumping results to %s', self.outdir)
-            self.sim.dump_yaml(outdir=self.outdir)
+            self.simulation.dump_yaml(outdir=self.outdir)
         else:
             logger.info('NOT dumping results')
 
-    def trial_end(self, env):
+    def trial(self, env, stats):
         if not self.dry_run:
-            with timer('Dumping simulation {} trial {}'.format(self.sim.name,
+            with timer('Dumping simulation {} trial {}'.format(self.simulation.name,
                                                                env.name)):
                 with self.output('{}.sqlite'.format(env.name), mode='wb') as f:
                     env.dump_sqlite(f)
@@ -98,21 +102,27 @@ class default(Exporter):
 
 class csv(Exporter):
     '''Export the state of each environment (and its agents) in a separate CSV file'''
-    def trial_end(self, env):
-        with timer('[CSV] Dumping simulation {} trial {} @ dir {}'.format(self.sim.name,
+    def trial(self, env, stats):
+        with timer('[CSV] Dumping simulation {} trial {} @ dir {}'.format(self.simulation.name,
                                                                           env.name,
                                                                           self.outdir)):
             with self.output('{}.csv'.format(env.name)) as f:
                 env.dump_csv(f)
 
+            with self.output('{}.stats.csv'.format(env.name)) as f:
+                statwriter = csvlib.writer(f, delimiter='\t', quotechar='"', quoting=csvlib.QUOTE_ALL)
+
+                for stat in stats:
+                    statwriter.writerow(stat)
+
 
 class gexf(Exporter):
-    def trial_end(self, env):
+    def trial(self, env, stats):
         if self.dry_run:
             logger.info('Not dumping GEXF in dry_run mode')
             return
 
-        with timer('[GEXF] Dumping simulation {} trial {}'.format(self.sim.name,
+        with timer('[GEXF] Dumping simulation {} trial {}'.format(self.simulation.name,
                                                                   env.name)):
             with self.output('{}.gexf'.format(env.name), mode='wb') as f:
                 env.dump_gexf(f)
@@ -124,56 +134,24 @@ class dummy(Exporter):
         with self.output('dummy', 'w') as f:
             f.write('simulation started @ {}\n'.format(time.time()))
 
-    def trial_end(self, env):
+    def trial(self, env, stats):
         with self.output('dummy', 'w') as f:
             for i in env.history_to_tuples():
                 f.write(','.join(map(str, i)))
                 f.write('\n')
 
-    def end(self):
+    def sim(self, stats):
         with self.output('dummy', 'a') as f:
             f.write('simulation ended @ {}\n'.format(time.time()))
 
 
-class distribution(Exporter):
-    '''
-    Write the distribution of agent states at the end of each trial,
-    the mean value, and its deviation.
-    '''
-
-    def start(self):
-        self.means = []
-        self.counts = []
-
-    def trial_end(self, env):
-        df = env[None, None, None].df()
-        ix = df.index[-1]
-        attrs = df.columns.levels[0]
-        vc = {}
-        stats = {}
-        for a in attrs:
-            t = df.loc[(ix, a)]
-            try:
-                self.means.append(('mean', a, t.mean()))
-            except TypeError:
-                for name, count in t.value_counts().iteritems():
-                    self.counts.append(('count', a, name, count))
-
-    def end(self):
-        dfm = pd.DataFrame(self.means, columns=['metric', 'key', 'value'])
-        dfc = pd.DataFrame(self.counts, columns=['metric', 'key', 'value', 'count'])
-        dfm = dfm.groupby(by=['key']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
-        dfc = dfc.groupby(by=['key', 'value']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
-        with self.output('counts.csv') as f:
-            dfc.to_csv(f)
-        with self.output('metrics.csv') as f:
-            dfm.to_csv(f)
 
 class graphdrawing(Exporter):
 
-    def trial_end(self, env):
+    def trial(self, env, stats):
         # Outside effects
         f = plt.figure()
         nx.draw(env.G, node_size=10, width=0.2, pos=nx.spring_layout(env.G, scale=100), ax=f.add_subplot(111))
         with open('graph-{}.png'.format(env.name)) as f:
             f.savefig(f)
+

soil/history.py

@@ -11,7 +11,7 @@ logger = logging.getLogger(__name__)
 from collections import UserDict, namedtuple
 
 from . import serialization
-from .utils import open_or_reuse
+from .utils import open_or_reuse, unflatten_dict
 
 
 class History:
@@ -19,29 +19,43 @@ class History:
     Store and retrieve values from a sqlite database.
     """
 
-    def __init__(self, name=None, db_path=None, backup=False):
-        self._db = None
+    def __init__(self, name=None, db_path=None, backup=False, readonly=False):
+        if readonly and (not os.path.exists(db_path)):
+            raise Exception('The DB file does not exist. Cannot open in read-only mode')
 
-        if db_path is None:
+        self._db = None
+        self._temp = db_path is None
+        self._stats_columns = None
+        self.readonly = readonly
+
+        if self._temp:
             if not name:
                 name = time.time()
-            _, db_path = tempfile.mkstemp(suffix='{}.sqlite'.format(name))
+            # The file will be deleted as soon as it's closed
+            # Normally, that will be on destruction
+            db_path = tempfile.NamedTemporaryFile(suffix='{}.sqlite'.format(name)).name
+
 
         if backup and os.path.exists(db_path):
-            newname = db_path + '.backup{}.sqlite'.format(time.time())
-            os.rename(db_path, newname)
+                newname = db_path + '.backup{}.sqlite'.format(time.time())
+                os.rename(db_path, newname)
 
         self.db_path = db_path
 
         self.db = db_path
+        self._dtypes = {}
+        self._tups = []
+
+
+        if self.readonly:
+            return
 
         with self.db:
             logger.debug('Creating database {}'.format(self.db_path))
-            self.db.execute('''CREATE TABLE IF NOT EXISTS history (agent_id text, t_step int, key text, value text text)''')
+            self.db.execute('''CREATE TABLE IF NOT EXISTS history (agent_id text, t_step int, key text, value text)''')
             self.db.execute('''CREATE TABLE IF NOT EXISTS value_types (key text, value_type text)''')
+            self.db.execute('''CREATE TABLE IF NOT EXISTS stats (trial_id text)''')
             self.db.execute('''CREATE UNIQUE INDEX IF NOT EXISTS idx_history ON history (agent_id, t_step, key);''')
-        self._dtypes = {}
-        self._tups = []
 
     @property
     def db(self):
@@ -58,6 +72,7 @@ class History:
         if isinstance(db_path, str):
             logger.debug('Connecting to database {}'.format(db_path))
             self._db = sqlite3.connect(db_path)
+            self._db.row_factory = sqlite3.Row
         else:
             self._db = db_path
 
@@ -68,9 +83,56 @@ class History:
         self._db.close()
         self._db = None
 
+    def save_stats(self, stat):
+        if self.readonly:
+            print('DB in readonly mode')
+            return
+        if not stat:
+            return
+        with self.db:
+            if not self._stats_columns:
+                self._stats_columns = list(c['name'] for c in self.db.execute('PRAGMA table_info(stats)'))
+
+            for column, value in stat.items():
+                if column in self._stats_columns:
+                    continue
+                dtype = 'text'
+                if not isinstance(value, str):
+                    try:
+                        float(value)
+                        dtype = 'real'
+                        int(value)
+                        dtype = 'int'
+                    except ValueError:
+                        pass
+                self.db.execute('ALTER TABLE stats ADD "{}" "{}"'.format(column, dtype))
+                self._stats_columns.append(column)
+
+            columns = ", ".join(map(lambda x: '"{}"'.format(x), stat.keys()))
+            values = ", ".join(['"{0}"'.format(col) for col in stat.values()])
+            query = "INSERT INTO stats ({columns}) VALUES ({values})".format(
+                columns=columns,
+                values=values
+            )
+            self.db.execute(query)
+
+    def get_stats(self, unflatten=True):
+        rows = self.db.execute("select * from stats").fetchall()
+        res = []
+        for row in rows:
+            d = {}
+            for k in row.keys():
+                if row[k] is None:
+                    continue
+                d[k] = row[k]
+            if unflatten:
+                d = unflatten_dict(d)
+            res.append(d)
+        return res
+
     @property
     def dtypes(self):
-        self.read_types()
+        self._read_types()
         return {k:v[0] for k, v in self._dtypes.items()}
 
     def save_tuples(self, tuples):
@@ -93,18 +155,10 @@ class History:
         Save a collection of records to the database.
         Database writes are cached.
         '''
-        value = self.convert(key, value)
-        self._tups.append(Record(agent_id=agent_id,
-                                 t_step=t_step,
-                                 key=key,
-                                 value=value))
-        if len(self._tups) > 100:
-            self.flush_cache()
-
-    def convert(self, key, value):
-        """Get the serialized value for a given key."""
+        if self.readonly:
+            raise Exception('DB in readonly mode')
         if key not in self._dtypes:
-            self.read_types()
+            self._read_types()
             if key not in self._dtypes:
                 name = serialization.name(value)
                 serializer = serialization.serializer(name)
@@ -112,21 +166,21 @@ class History:
                 self._dtypes[key] = (name, serializer, deserializer)
                 with self.db:
                     self.db.execute("replace into value_types (key, value_type) values (?, ?)", (key, name))
-        return self._dtypes[key][1](value)
-
-    def recover(self, key, value):
-        """Get the deserialized value for a given key, and the serialized version."""
-        if key not in self._dtypes:
-            self.read_types()
-        if key not in self._dtypes:
-            raise ValueError("Unknown datatype for {} and {}".format(key, value))
-        return self._dtypes[key][2](value)
+        value = self._dtypes[key][1](value)
+        self._tups.append(Record(agent_id=agent_id,
+                                 t_step=t_step,
+                                 key=key,
+                                 value=value))
+        if len(self._tups) > 100:
+            self.flush_cache()
 
     def flush_cache(self):
         '''
         Use a cache to save state changes to avoid opening a session for every change.
         The cache will be flushed at the end of the simulation, and when history is accessed.
         '''
+        if self.readonly:
+            raise Exception('DB in readonly mode')
         logger.debug('Flushing cache {}'.format(self.db_path))
         with self.db:
             for rec in self._tups:
@@ -139,10 +193,14 @@ class History:
             res = self.db.execute("select agent_id, t_step, key, value from history ").fetchall()
         for r in res:
             agent_id, t_step, key, value = r
-            value = self.recover(key, value)
+            if key not in self._dtypes:
+                self._read_types()
+            if key not in self._dtypes:
+                raise ValueError("Unknown datatype for {} and {}".format(key, value))
+            value = self._dtypes[key][2](value)
             yield agent_id, t_step, key, value
 
-    def read_types(self):
+    def _read_types(self):
         with self.db:
             res = self.db.execute("select key, value_type from value_types ").fetchall()
         for k, v in res:
@@ -167,7 +225,7 @@ class History:
 
     def read_sql(self, keys=None, agent_ids=None, t_steps=None, convert_types=False, limit=-1):
 
-        self.read_types()
+        self._read_types()
 
         def escape_and_join(v):
             if v is None:
@@ -181,7 +239,13 @@ class History:
 
         last_df = None
         if t_steps:
-            # Look for the last value before the minimum step in the query
+            # Convert negative indices into positive
+            if any(x<0 for x in t_steps):
+                max_t = int(self.db.execute("select max(t_step) from history").fetchone()[0])
+                t_steps = [t if t>0 else max_t+1+t for t in t_steps]
+
+            # We will be doing ffill interpolation, so we need to look for
+            # the last value before the minimum step in the query
             min_step = min(t_steps)
             last_filters = ['t_step < {}'.format(min_step),]
             last_filters = last_filters + filters
@@ -219,7 +283,11 @@ class History:
         for k, v in self._dtypes.items():
             if k in df_p:
                 dtype, _, deserial = v
-                df_p[k] = df_p[k].fillna(method='ffill').astype(dtype)
+                try:
+                    df_p[k] = df_p[k].fillna(method='ffill').astype(dtype)
+                except (TypeError, ValueError):
+                    # Avoid forward-filling unknown/incompatible types
+                    continue
         if t_steps:
             df_p = df_p.reindex(t_steps, method='ffill')
         return df_p.ffill()
@@ -313,3 +381,5 @@ class Records():
 
 Key = namedtuple('Key', ['agent_id', 't_step', 'key'])
 Record = namedtuple('Record', 'agent_id t_step key value')
+
+Stat = namedtuple('Stat', 'trial_id')

soil/serialization.py

@@ -17,10 +17,10 @@ logger.setLevel(logging.INFO)
 
 
 def load_network(network_params, dir_path=None):
-    if network_params is None:
-        return nx.Graph()
-    path = network_params.get('path', None)
-    if path:
+    G = nx.Graph()
+
+    if 'path' in network_params:
+        path = network_params['path']
         if dir_path and not os.path.isabs(path):
             path = os.path.join(dir_path, path)
         extension = os.path.splitext(path)[1][1:]
@@ -32,21 +32,22 @@ def load_network(network_params, dir_path=None):
             method = getattr(nx.readwrite, 'read_' + extension)
         except AttributeError:
             raise AttributeError('Unknown format')
-        return method(path, **kwargs)
+        G = method(path, **kwargs)
 
-    net_args = network_params.copy()
-    if 'generator' not in net_args:
-        return nx.Graph()
+    elif 'generator' in network_params:
+        net_args = network_params.copy()
+        net_gen = net_args.pop('generator')
 
-    net_gen = net_args.pop('generator')
+        if dir_path not in sys.path:
+            sys.path.append(dir_path)
 
-    if dir_path not in sys.path:
-        sys.path.append(dir_path)
+        method = deserializer(net_gen,
+                              known_modules=['networkx.generators',])
+        G = method(**net_args)
+
+    return G
 
-    method = deserializer(net_gen,
-                          known_modules=['networkx.generators',])
 
-    return method(**net_args)
 
 
 def load_file(infile):
@@ -66,11 +67,32 @@ def expand_template(config):
         raise ValueError(('You must provide a definition of variables'
                           ' for the template.'))
 
-    template = Template(config['template'])
+    template = config['template']
 
-    sampler_name = config.get('sampler', 'SALib.sample.morris.sample')
-    n_samples = int(config.get('samples', 100))
-    sampler = deserializer(sampler_name)
+    if not isinstance(template, str):
+        template = yaml.dump(template)
+
+    template = Template(template)
+
+    params = params_for_template(config)
+
+    blank_str = template.render({k: 0 for k in params[0].keys()})
+    blank = list(load_string(blank_str))
+    if len(blank) > 1:
+        raise ValueError('Templates must not return more than one configuration')
+    if 'name' in blank[0]:
+        raise ValueError('Templates cannot be named, use group instead')
+
+    for ps in params:
+        string = template.render(ps)
+        for c in load_string(string):
+            yield c
+
+
+def params_for_template(config):
+    sampler_config = config.get('sampler', {'N': 100})
+    sampler = sampler_config.pop('method', 'SALib.sample.morris.sample')
+    sampler = deserializer(sampler)
     bounds = config['vars']['bounds']
 
     problem = {
@@ -78,7 +100,7 @@ def expand_template(config):
         'names': list(bounds.keys()),
         'bounds': list(v for v in bounds.values())
     }
-    samples = sampler(problem, n_samples)
+    samples = sampler(problem, **sampler_config)
 
     lists = config['vars'].get('lists', {})
     names = list(lists.keys())
@@ -88,20 +110,7 @@ def expand_template(config):
     allnames = names + problem['names']
     allvalues = [(list(i[0])+list(i[1])) for i in product(combs, samples)]
     params = list(map(lambda x: dict(zip(allnames, x)), allvalues))
-
-
-    blank_str = template.render({k: 0 for k in allnames})
-    blank = list(load_string(blank_str))
-    if len(blank) > 1:
-        raise ValueError('Templates must not return more than one configuration')
-    if 'name' in blank[0]:
-        raise ValueError('Templates cannot be named, use group instead')
-
-    confs = []
-    for ps in params:
-        string = template.render(ps)
-        for c in load_string(string):
-            yield c
+    return params
 
 
 def load_files(*patterns, **kwargs):
@@ -116,7 +125,7 @@ def load_files(*patterns, **kwargs):
 
 def load_config(config):
     if isinstance(config, dict):
-        yield config, None
+        yield config, os.getcwd()
     else:
         yield from load_files(config)
 

soil/simulation.py

@@ -4,6 +4,7 @@ import importlib
 import sys
 import yaml
 import traceback
+import logging
 import networkx as nx
 from networkx.readwrite import json_graph
 from multiprocessing import Pool
@@ -11,17 +12,19 @@ from functools import partial
 
 import pickle
 
-from nxsim import NetworkSimulation
-
 from . import serialization, utils, basestring, agents
 from .environment import Environment
 from .utils import logger
-from .exporters import for_sim as exporters_for_sim
+from .exporters import default, for_sim as exporters_for_sim
+from .stats import defaultStats
+from .history import History
 
 
-class Simulation(NetworkSimulation):
+#TODO: change documentation for simulation
+
+class Simulation:
     """
-    Subclass of nsim.NetworkSimulation with three main differences:
+    Similar to nsim.NetworkSimulation with three main differences:
         1) agent type can be specified by name or by class.
         2) instead of just one type, a network agents distribution can be used.
            The distribution specifies the weight (or probability) of each
@@ -91,11 +94,12 @@ class Simulation(NetworkSimulation):
                  environment_params=None, environment_class=None,
                  **kwargs):
 
-        self.seed = str(seed) or str(time.time())
         self.load_module = load_module
         self.network_params = network_params
-        self.name = name or 'Unnamed_' + time.strftime("%Y-%m-%d_%H.%M.%S")
-        self.group = group or None
+        self.name = name or 'Unnamed'
+        self.seed = str(seed or name)
+        self._id = '{}_{}'.format(self.name, time.strftime("%Y-%m-%d_%H.%M.%S"))
+        self.group = group or ''
         self.num_trials = num_trials
         self.max_time = max_time
         self.default_state = default_state or {}
@@ -128,12 +132,15 @@ class Simulation(NetworkSimulation):
         self.states = agents._validate_states(states,
                                               self.topology)
 
+        self._history = History(name=self.name,
+                               backup=False)
+
     def run_simulation(self, *args, **kwargs):
         return self.run(*args, **kwargs)
 
     def run(self, *args, **kwargs):
         '''Run the simulation and return the list of resulting environments'''
-        return list(self._run_simulation_gen(*args, **kwargs))
+        return list(self.run_gen(*args, **kwargs))
 
     def _run_sync_or_async(self, parallel=False, *args, **kwargs):
         if parallel:
@@ -148,12 +155,16 @@ class Simulation(NetworkSimulation):
                 yield i
         else:
             for i in range(self.num_trials):
-                yield self.run_trial(i,
-                                     *args,
+                yield self.run_trial(*args,
                                      **kwargs)
 
-    def _run_simulation_gen(self, *args, parallel=False, dry_run=False,
-                            exporters=['default', ], outdir=None, exporter_params={}, **kwargs):
+    def run_gen(self, *args, parallel=False, dry_run=False,
+                exporters=[default, ], stats=[defaultStats], outdir=None, exporter_params={},
+                stats_params={}, log_level=None,
+                **kwargs):
+        '''Run the simulation and yield the resulting environments.'''
+        if log_level:
+            logger.setLevel(log_level)
         logger.info('Using exporters: %s', exporters or [])
         logger.info('Output directory: %s', outdir)
         exporters = exporters_for_sim(self,
@@ -161,31 +172,63 @@ class Simulation(NetworkSimulation):
                                       dry_run=dry_run,
                                       outdir=outdir,
                                       **exporter_params)
+        stats = exporters_for_sim(self,
+                                  stats,
+                                  **stats_params)
 
         with utils.timer('simulation {}'.format(self.name)):
+            for stat in stats:
+                stat.start()
+
             for exporter in exporters:
                 exporter.start()
-
-            for env in self._run_sync_or_async(*args, parallel=parallel,
+            for env in self._run_sync_or_async(*args,
+                                               parallel=parallel,
+                                               log_level=log_level,
                                                **kwargs):
+
+                collected = list(stat.trial(env) for stat in stats)
+
+                saved = self.save_stats(collected, t_step=env.now, trial_id=env.name)
+
                 for exporter in exporters:
-                    exporter.trial_end(env)
+                    exporter.trial(env, saved)
+
                 yield env
 
-            for exporter in exporters:
-                exporter.end()
 
-    def get_env(self, trial_id = 0, **kwargs):
+            collected = list(stat.end() for stat in stats)
+            saved = self.save_stats(collected)
+
+            for exporter in exporters:
+                exporter.end(saved)
+
+
+    def save_stats(self, collection, **kwargs):
+        stats = dict(kwargs)
+        for stat in collection:
+            stats.update(stat)
+        self._history.save_stats(utils.flatten_dict(stats))
+        return stats
+
+    def get_stats(self, **kwargs):
+        return self._history.get_stats(**kwargs)
+
+    def log_stats(self, stats):
+        logger.info('Stats: \n{}'.format(yaml.dump(stats, default_flow_style=False)))
+    
+
+    def get_env(self, trial_id=0, **kwargs):
         '''Create an environment for a trial of the simulation'''
         opts = self.environment_params.copy()
-        env_name = '{}_trial_{}'.format(self.name, trial_id)
         opts.update({
-            'name': env_name,
+            'name': trial_id,
             'topology': self.topology.copy(),
-            'seed': self.seed+env_name,
+            'seed': '{}_trial_{}'.format(self.seed, trial_id),
             'initial_time': 0,
             'interval': self.interval,
             'network_agents': self.network_agents,
+            'initial_time': 0,
             'states': self.states,
             'default_state': self.default_state,
             'environment_agents': self.environment_agents,
@@ -194,20 +237,22 @@ class Simulation(NetworkSimulation):
         env = self.environment_class(**opts)
         return env
 
-    def run_trial(self, trial_id=0, until=None, **opts):
-        """Run a single trial of the simulation
-
-        Parameters
-        ----------
-        trial_id : int
+    def run_trial(self, until=None, log_level=logging.INFO, **opts):
         """
+        Run a single trial of the simulation
+
+        """
+        trial_id = '{}_trial_{}'.format(self.name, time.time()).replace('.', '-')
+        if log_level:
+            logger.setLevel(log_level)
         # Set-up trial environment and graph
         until = until or self.max_time
-        env = self.get_env(trial_id = trial_id, **opts)
+        env = self.get_env(trial_id=trial_id, **opts)
         # Set up agents on nodes
         with utils.timer('Simulation {} trial {}'.format(self.name, trial_id)):
             env.run(until)
         return env
+
     def run_trial_exceptions(self, *args, **kwargs):
         '''
         A wrapper for run_trial that catches exceptions and returns them.

soil/stats.py

@@ -0,0 +1,106 @@
+import pandas as pd
+
+from collections import Counter
+
+class Stats:
+    '''
+    Interface for all stats. It is not necessary, but it is useful
+    if you don't plan to implement all the methods.
+    '''
+
+    def __init__(self, simulation):
+        self.simulation = simulation
+
+    def start(self):
+        '''Method to call when the simulation starts'''
+        pass
+
+    def end(self):
+        '''Method to call when the simulation ends'''
+        return {}
+
+    def trial(self, env):
+        '''Method to call when a trial ends'''
+        return {}
+
+
+class distribution(Stats):
+    '''
+    Calculate the distribution of agent states at the end of each trial,
+    the mean value, and its deviation.
+    '''
+
+    def start(self):
+        self.means = []
+        self.counts = []
+
+    def trial(self, env):
+        df = env[None, None, None].df()
+        df = df.drop('SEED', axis=1)
+        ix = df.index[-1]
+        attrs = df.columns.get_level_values(0)
+        vc = {}
+        stats = {
+            'mean': {},
+            'count': {},
+        }
+        for a in attrs:
+            t = df.loc[(ix, a)]
+            try:
+                stats['mean'][a] = t.mean()
+                self.means.append(('mean', a, t.mean()))
+            except TypeError:
+                pass
+
+            for name, count in t.value_counts().iteritems():
+                if a not in stats['count']:
+                    stats['count'][a] = {}
+                stats['count'][a][name] = count
+                self.counts.append(('count', a, name, count))
+
+        return stats
+
+    def end(self):
+        dfm = pd.DataFrame(self.means, columns=['metric', 'key', 'value'])
+        dfc = pd.DataFrame(self.counts, columns=['metric', 'key', 'value', 'count'])
+
+        count = {}
+        mean = {}
+
+        if self.means:
+            res = dfm.groupby(by=['key']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
+            mean = res['value'].to_dict()
+        if self.counts:
+            res = dfc.groupby(by=['key', 'value']).agg(['mean', 'std', 'count', 'median', 'max', 'min'])
+            for k,v in res['count'].to_dict().items():
+                if k not in count:
+                    count[k] = {}
+                for tup, times in v.items():
+                    subkey, subcount = tup
+                    if subkey not in count[k]:
+                        count[k][subkey] = {}
+                    count[k][subkey][subcount] = times
+
+
+        return {'count': count, 'mean': mean}
+
+
+class defaultStats(Stats):
+
+    def trial(self, env):
+        c = Counter()
+        c.update(a.__class__.__name__ for a in env.network_agents)
+
+        c2 = Counter()
+        c2.update(a['id'] for a in env.network_agents)
+
+        return {
+            'network ': {
+                'n_nodes': env.G.number_of_nodes(),
+                'n_edges': env.G.number_of_nodes(),
+            },
+            'agents': {
+                'model_count': dict(c),
+                'state_count': dict(c2),
+            }
+        }

soil/utils.py

@@ -7,6 +7,7 @@ from shutil import copyfile
 from contextlib import contextmanager
 
 logger = logging.getLogger('soil')
+logging.basicConfig()
 logger.setLevel(logging.INFO)
 
 
@@ -31,14 +32,13 @@ def safe_open(path, mode='r', backup=True, **kwargs):
         os.makedirs(outdir)
     if backup and 'w' in mode and os.path.exists(path):
         creation = os.path.getctime(path)
-        stamp = time.strftime('%Y-%m-%d_%H.%M', time.localtime(creation))
+        stamp = time.strftime('%Y-%m-%d_%H.%M.%S', time.localtime(creation))
 
-        backup_dir = os.path.join(outdir, stamp)
+        backup_dir = os.path.join(outdir, 'backup')
         if not os.path.exists(backup_dir):
             os.makedirs(backup_dir)
-        newpath = os.path.join(backup_dir, os.path.basename(path))
-        if os.path.exists(newpath):
-            newpath = '{}@{}'.format(newpath, time.time())
+        newpath = os.path.join(backup_dir, '{}@{}'.format(os.path.basename(path),
+                                                               stamp))
         copyfile(path, newpath)
     return open(path, mode=mode, **kwargs)
 
@@ -48,3 +48,40 @@ def open_or_reuse(f, *args, **kwargs):
         return safe_open(f, *args, **kwargs)
     except (AttributeError, TypeError):
         return f
+
+def flatten_dict(d):
+    if not isinstance(d, dict):
+        return d
+    return dict(_flatten_dict(d))
+
+def _flatten_dict(d, prefix=''):
+    if not isinstance(d, dict):
+        # print('END:', prefix, d)
+        yield prefix, d
+        return
+    if prefix:
+        prefix = prefix + '.'
+    for k, v in d.items():
+        # print(k, v)
+        res = list(_flatten_dict(v, prefix='{}{}'.format(prefix, k)))
+        # print('RES:', res)
+        yield from res
+
+
+def unflatten_dict(d):
+    out = {}
+    for k, v in d.items():
+        target = out
+        if not isinstance(k, str):
+            target[k] = v
+            continue
+        tokens = k.split('.')
+        if len(tokens) < 2:
+            target[k] = v
+            continue
+        for token in tokens[:-1]:
+            if token not in target:
+                target[token] = {}
+            target = target[token]
+        target[tokens[-1]] = v
+    return out

tests/test_analysis.py

@@ -66,8 +66,8 @@ class TestAnalysis(TestCase):
         env = self.env
         df = analysis.read_sql(env._history.db_path)
         res = analysis.get_count(df, 'SEED', 'id')
-        assert res['SEED']['seedanalysis_trial_0'].iloc[0] == 1
-        assert res['SEED']['seedanalysis_trial_0'].iloc[-1] == 1
+        assert res['SEED'][self.env['SEED']].iloc[0] == 1
+        assert res['SEED'][self.env['SEED']].iloc[-1] == 1
         assert res['id']['odd'].iloc[0] == 2
         assert res['id']['even'].iloc[0] == 0
         assert res['id']['odd'].iloc[-1] == 1
@@ -75,7 +75,7 @@ class TestAnalysis(TestCase):
 
     def test_value(self):
         env = self.env
-        df = analysis.read_sql(env._history._db)
+        df = analysis.read_sql(env._history.db_path)
         res_sum = analysis.get_value(df, 'count')
 
         assert res_sum['count'].iloc[0] == 2
@@ -86,4 +86,4 @@ class TestAnalysis(TestCase):
 
         res_total = analysis.get_value(df)
 
-        res_total['SEED'].iloc[0] == 'seedanalysis_trial_0'
+        res_total['SEED'].iloc[0] == self.env['SEED']

tests/test_examples.py

@@ -31,7 +31,7 @@ def make_example_test(path, config):
                 try:
                     n = config['network_params']['n']
                     assert len(list(env.network_agents)) == n
-                    assert env.now > 2  # It has run
+                    assert env.now > 0  # It has run
                     assert env.now <= config['max_time']  # But not further than allowed
                 except KeyError:
                     pass

tests/test_exporters.py

@@ -6,26 +6,32 @@ from time import time
 
 from unittest import TestCase
 from soil import exporters
-from soil.utils import safe_open
 from soil import simulation
 
+from soil.stats import distribution
 
 class Dummy(exporters.Exporter):
     started = False
     trials = 0
     ended = False
     total_time = 0
+    called_start = 0
+    called_trial = 0
+    called_end = 0
 
     def start(self):
+        self.__class__.called_start += 1
         self.__class__.started = True
 
-    def trial_end(self, env):
+    def trial(self, env, stats):
         assert env
         self.__class__.trials += 1
         self.__class__.total_time += env.now
+        self.__class__.called_trial += 1
 
-    def end(self):
+    def end(self, stats):
         self.__class__.ended = True
+        self.__class__.called_end += 1
 
 
 class Exporters(TestCase):
@@ -39,32 +45,17 @@ class Exporters(TestCase):
             'environment_params': {}
         }
         s = simulation.from_config(config)
-        s.run_simulation(exporters=[Dummy], dry_run=True)
+        for env in s.run_simulation(exporters=[Dummy], dry_run=True):
+            assert env.now <= 2
+
         assert Dummy.started
         assert Dummy.ended
+        assert Dummy.called_start == 1
+        assert Dummy.called_end == 1
+        assert Dummy.called_trial == 5
         assert Dummy.trials == 5
         assert Dummy.total_time == 2*5
 
-    def test_distribution(self):
-        '''The distribution exporter should write the number of agents in each state'''
-        config = {
-            'name': 'exporter_sim',
-            'network_params': {
-                'generator': 'complete_graph',
-                'n': 4
-            },
-            'agent_type': 'CounterModel',
-            'max_time': 2,
-            'num_trials': 5,
-            'environment_params': {}
-        }
-        output = io.StringIO()
-        s = simulation.from_config(config)
-        s.run_simulation(exporters=[exporters.distribution], dry_run=True, exporter_params={'copy_to': output})
-        result = output.getvalue()
-        assert 'count' in result
-        assert 'SEED,Noneexporter_sim_trial_3,1,,1,1,1,1' in result
-
     def test_writing(self):
         '''Try to write CSV, GEXF, sqlite and YAML (without dry_run)'''
         n_trials = 5
@@ -86,8 +77,8 @@ class Exporters(TestCase):
             exporters.default,
             exporters.csv,
             exporters.gexf,
-            exporters.distribution,
         ],
+                                stats=[distribution,],
                                 outdir=tmpdir,
                                 exporter_params={'copy_to': output})
         result = output.getvalue()

tests/test_history.py

@@ -5,6 +5,7 @@ import shutil
 from glob import glob
 
 from soil import history
+from soil import utils
 
 
 ROOT = os.path.abspath(os.path.dirname(__file__))
@@ -154,3 +155,49 @@ class TestHistory(TestCase):
         assert recovered
         for i in recovered:
             assert i in tuples
+
+    def test_stats(self):
+        """
+        The data recovered should be equal to the one recorded.
+        """
+        tuples = (
+            ('a_1', 0, 'id', 'v'),
+            ('a_1', 1, 'id', 'a'),
+            ('a_1', 2, 'id', 'l'),
+            ('a_1', 3, 'id', 'u'),
+            ('a_1', 4, 'id', 'e'),
+            ('env', 1, 'prob', 1),
+            ('env', 2, 'prob', 2),
+            ('env', 3, 'prob', 3),
+            ('a_2', 7, 'finished', True),
+        )
+        stat_tuples = [
+            {'num_infected': 5, 'runtime': 0.2},
+            {'num_infected': 5, 'runtime': 0.2},
+            {'new': '40'},
+        ]
+        h = history.History()
+        h.save_tuples(tuples)
+        for stat in stat_tuples:
+            h.save_stats(stat)
+        recovered = h.get_stats()
+        assert recovered
+        assert recovered[0]['num_infected'] == 5
+        assert recovered[1]['runtime'] == 0.2
+        assert recovered[2]['new'] == '40'
+
+    def test_unflatten(self):
+        ex = {'count.neighbors.3': 4,
+              'count.times.2': 4,
+              'count.total.4': 4,
+              'mean.neighbors': 3,
+              'mean.times': 2,
+              'mean.total': 4,
+              't_step': 2,
+              'trial_id': 'exporter_sim_trial_1605817956-4475424'}
+        res = utils.unflatten_dict(ex)
+
+        assert 'count' in res
+        assert 'mean' in res
+        assert 't_step' in res
+        assert 'trial_id' in res

tests/test_main.py

@@ -343,4 +343,16 @@ class TestMain(TestCase):
         configs = serialization.load_file(join(EXAMPLES, 'template.yml'))
         assert len(configs) > 0
 
-
+    def test_until(self):
+        config = {
+            'name': 'exporter_sim',
+            'network_params': {},
+            'agent_type': 'CounterModel',
+            'max_time': 2,
+            'num_trials': 100,
+            'environment_params': {}
+        }
+        s = simulation.from_config(config)
+        runs = list(s.run_simulation(dry_run=True))
+        over = list(x.now for x in runs if x.now>2)
+        assert len(over) == 0

tests/test_stats.py

@@ -0,0 +1,34 @@
+from unittest import TestCase
+
+from soil import simulation, stats
+from soil.utils import unflatten_dict
+
+class Stats(TestCase):
+
+    def test_distribution(self):
+        '''The distribution exporter should write the number of agents in each state'''
+        config = {
+            'name': 'exporter_sim',
+            'network_params': {
+                'generator': 'complete_graph',
+                'n': 4
+            },
+            'agent_type': 'CounterModel',
+            'max_time': 2,
+            'num_trials': 5,
+            'environment_params': {}
+        }
+        s = simulation.from_config(config)
+        for env in s.run_simulation(stats=[stats.distribution]):
+            pass
+            # stats_res = unflatten_dict(dict(env._history['stats', -1, None]))
+        allstats = s.get_stats()
+        for stat in allstats:
+            assert 'count' in stat
+            assert 'mean' in stat
+            if 'trial_id' in stat:
+                assert stat['mean']['neighbors'] == 3
+                assert stat['count']['total']['4'] == 4
+            else:
+                assert stat['count']['count']['neighbors']['3'] == 20
+                assert stat['mean']['min']['neighbors'] == stat['mean']['max']['neighbors']