Dump and reload example

This notebook illustrates how to dump a cancer simulation to disk, reload it, and continue with changed parameters. This feature allows to model different stages of tumour growth characterized by varying growth parameters (e.g. death_probability and adv_mutant_division_probability).

Import modules

[1]:

# The cancer simulation module.
from casim import casim

[2]:

#  3rd party modules.
import os, shutil
from wand.image import Image as WImage
from glob import glob

[3]:

import pickle
from matplotlib import pyplot

Define some utility functions

[4]:

def unpickle(sim, pkl):

    with open(os.path.join(sim._CancerSimulator__simdir, pkl),'rb') as fp:
        return pickle.load(fp)

[5]:

def clear_outdir(dir):
    if os.path.isdir(dir):
        shutil.rmtree(dir)

Setup parameters

Initially, cells with advantageous mutations divide only seldomly, the tumour is dormant.

[22]:

parameters=casim.CancerSimulatorParameters(
                                matrix_size=200,
                                number_of_generations=50,
                                division_probability=0.6,
                                adv_mutant_division_probability=0.5,
                                death_probability=0.3,
                                adv_mutant_death_probability=0.05,
                                mutation_probability=0.5,
                                adv_mutant_mutation_probability=1.0,
                                number_of_mutations_per_division=10,
                                adv_mutation_wait_time=40,
                                number_of_initial_mutations=2,
                                sampling_fraction=0.9,
                                plot_tumour_growth=True,
                                export_tumour=True
                               )

Setup the simulation engine.

[23]:

outdir = 'out'
clear_outdir(outdir)

[24]:

cancer_sim = casim.CancerSimulator(parameters, seed=1, outdir='out/')

2020-08-19 12:29:15,983 INFO: Running in single tumour mode.
2020-08-19 12:29:15,985 INFO: First cell at (100, 100).

Run the simulation

[25]:

cancer_sim.run()

2020-08-19 12:29:16,398 INFO: Ready to start CancerSim run with these parameters:
2020-08-19 12:29:16,400 INFO: matrix_size = 200
2020-08-19 12:29:16,401 INFO: number_of_generations = 50
2020-08-19 12:29:16,403 INFO: division_probability = 0.6
2020-08-19 12:29:16,404 INFO: adv_mutant_division_probability = 0.5
2020-08-19 12:29:16,405 INFO: death_probability = 0.3
2020-08-19 12:29:16,406 INFO: adv_mutant_death_probability = 0.05
2020-08-19 12:29:16,407 INFO: mutation_probability = 0.5
2020-08-19 12:29:16,409 INFO: adv_mutant_mutation_probability = 1.0
2020-08-19 12:29:16,410 INFO: number_of_mutations_per_division = 10
2020-08-19 12:29:16,411 INFO: adv_mutation_wait_time = 40
2020-08-19 12:29:16,412 INFO: number_of_initial_mutations = 2
2020-08-19 12:29:16,413 INFO: tumour_multiplicity = single
2020-08-19 12:29:16,414 INFO: read_depth = 100
2020-08-19 12:29:16,415 INFO: sampling_fraction = 0.9
2020-08-19 12:29:16,416 INFO: plot_tumour_growth = True
2020-08-19 12:29:16,418 INFO: export_tumour = True
2020-08-19 12:29:16,419 INFO: Tumour growth in progress.
2020-08-19 12:29:16,621 INFO: New beneficial mutation: 2076
2020-08-19 12:29:16,653 INFO: Division of beneficial mutation carrier. Cell index = (108, 110), mutation index = 2076, place_to_divide=(109, 111)
2020-08-19 12:29:16,675 INFO: Division of beneficial mutation carrier. Cell index = (108, 110), mutation index = 2076, place_to_divide=(108, 111)
2020-08-19 12:29:16,688 INFO: Division of beneficial mutation carrier. Cell index = (108, 111), mutation index = 2076, place_to_divide=(109, 110)
2020-08-19 12:29:16,738 INFO: Division of beneficial mutation carrier. Cell index = (109, 111), mutation index = 2076, place_to_divide=(110, 111)
2020-08-19 12:29:16,741 INFO: Division of beneficial mutation carrier. Cell index = (108, 111), mutation index = 2076, place_to_divide=(108, 112)
2020-08-19 12:29:16,757 INFO: Division of beneficial mutation carrier. Cell index = (110, 111), mutation index = 2076, place_to_divide=(110, 112)
2020-08-19 12:29:16,771 INFO: Division of beneficial mutation carrier. Cell index = (108, 111), mutation index = 2076, place_to_divide=(108, 112)
2020-08-19 12:29:16,772 INFO: Mutation  of beneficial mutation carrier. Cell index = (108, 111), mutation index = 2076, place to divide = (108, 112)
2020-08-19 12:29:16,789 INFO: Division of beneficial mutation carrier. Cell index = (110, 111), mutation index = 2076, place_to_divide=(111, 112)
2020-08-19 12:29:16,790 INFO: Mutation  of beneficial mutation carrier. Cell index = (110, 111), mutation index = 2076, place to divide = (111, 112)
2020-08-19 12:29:16,792 INFO: Division of beneficial mutation carrier. Cell index = (110, 112), mutation index = 2076, place_to_divide=(111, 113)
2020-08-19 12:29:16,793 INFO: Mutation  of beneficial mutation carrier. Cell index = (110, 112), mutation index = 2076, place to divide = (111, 113)
2020-08-19 12:29:16,878 INFO: All generations finished. Starting tumour reconstruction.
2020-08-19 12:29:16,884 INFO: Reconstruction done,  get statistics.
2020-08-19 12:29:17,206 INFO: Exporting simulation data
2020-08-19 12:29:17,443 INFO: Growth curve graph written to out/cancer_1/simOutput/growthCurve.pdf.
2020-08-19 12:29:18,021 INFO: CancerSim run has finished.
2020-08-19 12:29:18,023 INFO: Simulation output written to: out/cancer_1/simOutput.
2020-08-19 12:29:18,023 INFO: Log files written to: out/cancer_1/log.
2020-08-19 12:29:18,024 INFO: Consumed Wall time of this run: 1.601802 s.

[25]:

0

Visualize the first stage of the run

[26]:

pdfs = glob(os.path.join(cancer_sim.outdir,'cancer_1', 'simOutput',"*.pdf"))

[27]:

for pdf in pdfs:
    print(pdf)
    display(WImage(filename=pdf))

out/cancer_1/simOutput/sampleHistogram_97_107.pdf
../../_images/include_notebooks_run_dump_reload_continue_17_1.png 
out/cancer_1/simOutput/growthCurve.pdf
../../_images/include_notebooks_run_dump_reload_continue_17_3.png 
out/cancer_1/simOutput/wholeTumourVAFHistogram.pdf
../../_images/include_notebooks_run_dump_reload_continue_17_5.png

Load the mutation matrix

[28]:

mtx=unpickle(cancer_sim,'mtx.p').toarray()

Plot the tumour as a 2D map color coding the mutation ID

[29]:

cmap = pyplot.cm.get_cmap('PRGn', mtx.max()+1)

pyplot.matshow(mtx, cmap=cmap)
pyplot.colorbar()

[29]:

<matplotlib.colorbar.Colorbar at 0x7f3798e37390>
../../_images/include_notebooks_run_dump_reload_continue_21_1.png

Dump the simulation

[30]:

cancer_sim.dump()

Reload the simulation

[31]:

restart_with_mods = casim.load_cancer_simulation(cancer_sim.dumpfile)

Change adv. mutant properties and run for 20 more generations.

[32]:

restart_with_mods.parameters.adv_mutant_division_probability = 1.0
restart_with_mods.parameters.death_probability = 0.5
restart_with_mods.parameters.number_of_generations = 20

[33]:

outdir = 'restart_with_mods'
clear_outdir(outdir)

restart_with_mods.outdir = outdir

[34]:

restart_with_mods.run()

2020-08-19 12:29:32,477 INFO: Ready to start CancerSim run with these parameters:
2020-08-19 12:29:32,479 INFO: matrix_size = 200
2020-08-19 12:29:32,481 INFO: number_of_generations = 20
2020-08-19 12:29:32,482 INFO: division_probability = 0.6
2020-08-19 12:29:32,483 INFO: adv_mutant_division_probability = 1.0
2020-08-19 12:29:32,485 INFO: death_probability = 0.5
2020-08-19 12:29:32,486 INFO: adv_mutant_death_probability = 0.05
2020-08-19 12:29:32,487 INFO: mutation_probability = 0.5
2020-08-19 12:29:32,489 INFO: adv_mutant_mutation_probability = 1.0
2020-08-19 12:29:32,490 INFO: number_of_mutations_per_division = 10
2020-08-19 12:29:32,491 INFO: adv_mutation_wait_time = 40
2020-08-19 12:29:32,492 INFO: number_of_initial_mutations = 2
2020-08-19 12:29:32,494 INFO: tumour_multiplicity = single
2020-08-19 12:29:32,495 INFO: read_depth = 100
2020-08-19 12:29:32,496 INFO: sampling_fraction = 0.9
2020-08-19 12:29:32,497 INFO: plot_tumour_growth = True
2020-08-19 12:29:32,498 INFO: export_tumour = True
2020-08-19 12:29:32,499 INFO: Tumour growth in progress.
2020-08-19 12:29:33,198 INFO: All generations finished. Starting tumour reconstruction.
2020-08-19 12:29:33,209 INFO: Reconstruction done,  get statistics.
2020-08-19 12:29:34,007 INFO: Exporting simulation data
2020-08-19 12:29:34,184 INFO: Growth curve graph written to restart_with_mods/cancer_1/simOutput/growthCurve.pdf.
2020-08-19 12:29:36,200 INFO: CancerSim run has finished.
2020-08-19 12:29:36,202 INFO: Simulation output written to: restart_with_mods/cancer_1/simOutput.
2020-08-19 12:29:36,202 INFO: Log files written to: restart_with_mods/cancer_1/log.
2020-08-19 12:29:36,203 INFO: Consumed Wall time of this run: 3.699930 s.

[34]:

0

Output

[35]:

pdfs = glob(os.path.join(restart_with_mods.outdir,'cancer_1', 'simOutput',"*.pdf"))
for pdf in pdfs:
    print(pdf)
    display(WImage(filename=pdf))

restart_with_mods/cancer_1/simOutput/growthCurve.pdf
../../_images/include_notebooks_run_dump_reload_continue_31_1.png 
restart_with_mods/cancer_1/simOutput/wholeTumourVAFHistogram.pdf
../../_images/include_notebooks_run_dump_reload_continue_31_3.png 
restart_with_mods/cancer_1/simOutput/sampleHistogram_86_78.pdf
../../_images/include_notebooks_run_dump_reload_continue_31_5.png 
[20]:

# Load the mutation matrix
mtx=unpickle(restart_with_mods, 'mtx.p').toarray()

[21]:

# Plot the tumour as a 2D map color coding the mutation ID
cmap = pyplot.cm.get_cmap('PRGn', mtx.max()+1)

pyplot.matshow(mtx, cmap=cmap)
pyplot.colorbar()

[21]:

<matplotlib.colorbar.Colorbar at 0x7f37961dc668>
../../_images/include_notebooks_run_dump_reload_continue_33_1.png 
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