def __init__(self):
super().__init__()
self.slot = [
State.Slot(Root.size[0] / 2 - 100, Root.size[1] / 2),
]
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y, '', self.go_back)
]
def __init__(self):
super().__init__()
self.slot = [
State.Slot(Root.size[0] / 2 - 100, Root.size[1] / 2),
State.Slot(Root.size[0] / 2 - 100, Root.size[1] / 2 + 30)
]
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y, '시작하기', self.start),
State.Input(self.slot[1].x, self.slot[1].y, '만든 사람들', self.credit)
]
self.pointer = State.Pointer(self.slot[self.place].x, self.slot[self.place].y)
def __init__(self): State().read() self.audio = Audio() audioPatch = AudioPatch() self.audioPatch = audioPatch self.audio.setAudioObject(audioPatch.output()) self.audio.setClock(audioPatch.clock) State().params['patchbay'].setCallback(audioPatch.patchbay)
def frames():
from FigureNumber import FigureNumber
from state.State import State
from state.Model import Model
from state.Reaction import Reaction
from state.Species import Species
from state.SpeciesReference import SpeciesReference
from state.Histogram import Histogram
from state.HistogramFrames import HistogramFrames
# Figure number.
figureNumber = FigureNumber()
# A histogram.
numberOfBins = 4
multiplicity = 2
h = Histogram(numberOfBins, multiplicity)
h.setCurrentToMinimum()
h.accumulate(0, 1)
h.accumulate(1, 2)
h.accumulate(2, 2)
h.accumulate(3, 1)
# Simulation output.
frameTimes = [0, 1]
recordedSpecies = [0, 1, 2]
hf = HistogramFrames(numberOfBins, multiplicity, recordedSpecies)
hf.setFrameTimes(frameTimes)
for i in range(len(frameTimes)):
for j in range(len(recordedSpecies)):
hf.histograms[i][j].merge(h)
# The model.
model = Model()
model.speciesIdentifiers = ['s1', 's2', 's3']
# The state.
state = State()
state.models['model'] = model
state.output[('model', 'method')] = hf
app = wx.PySimpleApp()
TestConfiguration(None, 'Populations.', state, figureNumber).Show()
app.MainLoop()
def average():
from FigureNumber import FigureNumber
from state.State import State
from state.Model import Model
from state.Reaction import Reaction
from state.Species import Species
from state.SpeciesReference import SpeciesReference
from state.Histogram import Histogram
from state.HistogramAverage import HistogramAverage
# Figure number.
figureNumber = FigureNumber()
# A histogram.
numberOfBins = 4
multiplicity = 2
h = Histogram(numberOfBins, multiplicity)
h.setCurrentToMinimum()
h.accumulate(0, 1)
h.accumulate(1, 2)
h.accumulate(2, 2)
h.accumulate(3, 1)
# Simulation output.
recordedSpecies = [0, 1, 2]
output = HistogramAverage(numberOfBins, multiplicity, recordedSpecies)
for x in output.histograms:
x.merge(h)
# The model.
model = Model()
model.speciesIdentifiers = ['s1', 's2', 's3']
# The state.
state = State()
state.models['model'] = model
state.output[('model', 'method')] = output
app = wx.PySimpleApp()
TestConfiguration(None, 'Populations.', state, figureNumber).Show()
app.MainLoop()
def main():
from FigureNumber import FigureNumber
from state.StatisticsFrames import StatisticsFrames
from state.State import State
from state.Model import Model
#from state.Reaction import Reaction
class TestConfiguration(wx.Frame):
"""Test the Configuration panel."""
def __init__(self, parent, title, state, figureNumber):
wx.Frame.__init__(self, parent, -1, title)
panel = Configuration(self, state, figureNumber)
bestSize = self.GetBestSize()
# Add twenty to avoid an unecessary horizontal scroll bar.
size = (bestSize[0] + 80, min(bestSize[1], 700))
self.SetSize(size)
self.Fit()
app = wx.PySimpleApp()
figureNumber = FigureNumber()
s = ['a', 'b', 'c']
t = StatisticsFrames([0, 1, 2])
t.setFrameTimes([0, 1, 2])
t.setStatistics([1, 0.1, 2, 0.2, 3, 0.3] * 3)
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers = s
# Dummy reactions.
#model.reactions = [Reaction(_id, '', [], [], True, '0') for _id in r]
# Store the trajectories.
state.output[(modelId, 'method')] = t
TestConfiguration(None, 'Populations.', state, figureNumber).Show()
app.MainLoop()
def __init__(self):
super().__init__()
self.slot = [
State.Slot(Root.size[0] / 2 - 100, Root.size[1] / 2),
State.Slot(Root.size[0] / 2 - 100, Root.size[1] / 2 + 30),
State.Slot(Root.size[0] / 2 - 100, Root.size[1] / 2 + 60)
]
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y, '다시하기', self.restart),
State.Input(self.slot[1].x, self.slot[1].y, '메인화면으로', self.start_screen),
State.Input(self.slot[2].x, self.slot[2].y, '끝내기', self.end)
]
self.pointer = State.Pointer(self.slot[self.place].x, self.slot[self.place].y)
def show_actions(self, text1, text2, text3, text4):
self.slot = [
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 2),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 3),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 4),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 5)
]
self.place = 0
self.show_action = True
self.pointer = 0
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y, text1,
self.getover_turn),
State.Input(self.slot[1].x, self.slot[1].y, text2,
self.getover_turn),
State.Input(self.slot[2].x, self.slot[2].y, text3,
self.getover_turn),
State.Input(self.slot[3].x, self.slot[3].y, text4,
self.getover_turn),
]
def open_magic_menu(self):
self.place = 0
if Root.turn and not self.player1_choose:
Sp.random_spell(self.player1)
self.player1_choose = True
elif not Root.turn and not self.player2_choose:
Sp.random_spell(self.player2)
self.player2_choose = True
if Root.turn:
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y,
self.player1.spell_list[0].name, self.use_spell),
State.Input(self.slot[1].x, self.slot[1].y,
self.player1.spell_list[1].name, self.use_spell),
State.Input(self.slot[2].x, self.slot[2].y,
self.player1.spell_list[2].name, self.use_spell),
State.Input(self.slot[3].x, self.slot[3].y,
self.player1.spell_list[3].name, self.use_spell),
State.Input(self.slot[4].x, self.slot[4].y, '돌아가기', self.init)
]
else:
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y,
self.player2.spell_list[0].name, self.use_spell),
State.Input(self.slot[1].x, self.slot[1].y,
self.player2.spell_list[1].name, self.use_spell),
State.Input(self.slot[2].x, self.slot[2].y,
self.player2.spell_list[2].name, self.use_spell),
State.Input(self.slot[3].x, self.slot[3].y,
self.player2.spell_list[3].name, self.use_spell),
State.Input(self.slot[4].x, self.slot[4].y, '돌아가기', self.init)
]
self.pointer = State.Pointer(self.slot[self.place].x,
self.slot[self.place].y)
def init(self):
self.place = 0
if not Root.turn:
self.slot = [
State.Slot(Root.size[0] / 16 + Root.size[0] / 2,
Root.size[1] / 2 + 50),
State.Slot(Root.size[0] / 16 + Root.size[0] / 2,
Root.size[1] / 2 + 50 * 2),
State.Slot(Root.size[0] / 16 + Root.size[0] / 2,
Root.size[1] / 2 + 50 * 3),
State.Slot(Root.size[0] / 16 + Root.size[0] / 2,
Root.size[1] / 2 + 50 * 4),
State.Slot(Root.size[0] / 16 + Root.size[0] / 2,
Root.size[1] / 2 + 50 * 5)
]
else:
self.slot = [
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 2),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 3),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 4),
State.Slot(Root.size[0] / 16, Root.size[1] / 2 + 50 * 5)
]
self.menu = [
State.Input(self.slot[0].x, self.slot[0].y, '기본 공격',
self.basic_atk),
State.Input(self.slot[1].x, self.slot[1].y, '스킬',
self.open_magic_menu),
State.Input(self.slot[2].x, self.slot[2].y, '마나 회복',
self.recover_mp)
]
self.pointer = State.Pointer(self.slot[self.place].x,
self.slot[self.place].y)
def checkState(self):
for inppName, value in State().params['patchbay'].items():
for outppName in value:
self.newPcFromPpNames(inppName, outppName)
def main():
from state.TimeSeriesFrames import TimeSeriesFrames
from state.TimeSeriesAllReactions import TimeSeriesAllReactions
from state.State import State
from state.Model import Model
from state.Reaction import Reaction
from state.Species import Species
from state.SpeciesReference import SpeciesReference
app = wx.PySimpleApp()
# Many species.
s = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i',
'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r',
's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
r = ['r1', 'r2', 'r3', 'r4']
t = TimeSeriesFrames()
t.setFrameTimes([0, 1, 2])
t.recordedSpecies = range(len(s))
t.recordedReactions = range(len(r))
t.appendPopulations([1]*len(s) + [2]*len(s) + [3]*len(s))
t.appendReactionCounts([0]*len(r) + [2]*len(r) + [4]*len(r))
t.appendPopulations([2]*len(s) + [3]*len(s) + [5]*len(s))
t.appendReactionCounts([0]*len(r) + [3]*len(r) + [6]*len(r))
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers = s
# Dummy reactions.
model.reactions = [Reaction(_id, '', [], [], True, '0') for _id in r]
# Store the trajectories.
state.output[(modelId, 'method')] = t
Export(None, 'Populations.', state).Show()
s = ['a', 'b', 'c']
r = ['r1', 'r2', 'r3', 'r4']
t = TimeSeriesFrames()
t.setFrameTimes([0, 1, 2])
t.recordedSpecies = range(len(s))
t.recordedReactions = range(len(r))
t.appendPopulations([1]*len(s) + [2]*len(s) + [3]*len(s))
t.appendReactionCounts([0]*len(r) + [2]*len(r) + [4]*len(r))
t.appendPopulations([2]*len(s) + [3]*len(s) + [5]*len(s))
t.appendReactionCounts([0]*len(r) + [3]*len(r) + [6]*len(r))
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers = s
# Dummy reactions.
model.reactions = [Reaction(_id, '', [], [], True, '0') for _id in r]
# Store the trajectories.
state.output[(modelId, 'method')] = t
Export(None, 'Populations.', state).Show()
initialTime = 0.
finalTime = 1.
t = TimeSeriesAllReactions([0, 1], [0, 1], initialTime, finalTime)
t.appendIndices([0])
t.appendTimes([0.5])
t.appendInitialPopulations([13, 17])
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers.append('s1')
model.species['s1'] = Species('C1', 'species 1', '13')
model.speciesIdentifiers.append('s2')
model.species['s2'] = Species('C1', 'species 2', '17')
model.reactions.append(
Reaction('r1', 'reaction 1', [SpeciesReference('s1')],
[SpeciesReference('s2')], True, '1.5'))
model.reactions.append(
Reaction('r2', 'reaction 2',
[SpeciesReference('s1'), SpeciesReference('s2')],
[SpeciesReference('s1', 2)], True, '2.5'))
# Store the trajectories.
state.output[(modelId, 'method')] = t
Export(None, 'Populations.', state).Show()
app.MainLoop()
def close(self): State().save() self.audio.stop()
def main():
import os
from state.TimeSeriesFrames import TimeSeriesFrames
from state.TimeSeriesAllReactions import TimeSeriesAllReactions
from state.State import State
from state.Model import Model
from state.Reaction import Reaction
from state.Species import Species
from state.SpeciesReference import SpeciesReference
class TestConfiguration(wx.Frame):
"""Test the Configuration panel."""
def __init__(self, parent, title, state):
wx.Frame.__init__(self, parent, -1, title)
panel = Configuration(self, state)
bestSize = self.GetBestSize()
# Add twenty to avoid an unecessary horizontal scroll bar.
size = (bestSize[0] + 80, min(bestSize[1], 700))
self.SetSize(size)
self.Fit()
app = wx.PySimpleApp()
# Many species.
s = [
'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n',
'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z'
]
r = ['r1', 'r2', 'r3', 'r4']
t = TimeSeriesFrames()
t.setFrameTimes([0, 1, 2])
t.recordedSpecies = range(len(s))
t.recordedReactions = range(len(r))
t.appendPopulations([1] * len(s) + [2] * len(s) + [3] * len(s))
t.appendReactionCounts([0] * len(r) + [2] * len(r) + [4] * len(r))
t.appendPopulations([2] * len(s) + [3] * len(s) + [5] * len(s))
t.appendReactionCounts([0] * len(r) + [3] * len(r) + [6] * len(r))
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers = s
# Dummy reactions.
model.reactions = [Reaction(_id, '', [], [], True, '0') for _id in r]
# Store the trajectories.
state.output[(modelId, 'method')] = t
TestConfiguration(None, 'Time series frames.', state).Show()
s = ['a', 'b', 'c']
r = ['r1', 'r2', 'r3', 'r4']
t = TimeSeriesFrames()
t.setFrameTimes([0, 1, 2])
t.recordedSpecies = range(len(s))
t.recordedReactions = range(len(r))
t.appendPopulations([1] * len(s) + [2] * len(s) + [3] * len(s))
t.appendReactionCounts([0] * len(r) + [2] * len(r) + [4] * len(r))
t.appendPopulations([2] * len(s) + [3] * len(s) + [5] * len(s))
t.appendReactionCounts([0] * len(r) + [3] * len(r) + [6] * len(r))
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers = s
# Dummy reactions.
model.reactions = [Reaction(_id, '', [], [], True, '0') for _id in r]
# Store the trajectories.
state.output[(modelId, 'method')] = t
TestConfiguration(None, 'Time series frames.', state).Show()
initialTime = 0.
finalTime = 1.
t = TimeSeriesAllReactions([0, 1], [0, 1], initialTime, finalTime)
t.appendIndices([0])
t.appendTimes([0.5])
t.appendInitialPopulations([13, 17])
state = State()
# Set the species identifiers.
modelId = state.insertNewModel()
model = state.models[modelId]
model.id = modelId
model.speciesIdentifiers.append('s1')
model.species['s1'] = Species('C1', 'species 1', '13')
model.speciesIdentifiers.append('s2')
model.species['s2'] = Species('C1', 'species 2', '17')
model.reactions.append(
Reaction('r1', 'reaction 1', [SpeciesReference('s1')],
[SpeciesReference('s2')], True, '1.5'))
model.reactions.append(
Reaction('r2', 'reaction 2',
[SpeciesReference('s1'),
SpeciesReference('s2')], [SpeciesReference('s1', 2)], True,
'2.5'))
# Store the trajectories.
state.output[(modelId, 'method')] = t
TestConfiguration(None, 'Time series all reactions.', state).Show()
app.MainLoop()