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- import config
- import numpy as np
- from pathlib import Path
- wildcard_constraints:
- source_pop = 'E|I',
- target_pop = 'E|I',
- fraction = '[\d\.]+',
- f = '[\d\.]+',
- N = '\d+',
- epsilon = '[\d\.]+',
- eta = '[\d\.]+',
- mu = '[\d\.]+',
- seed = '\d+',
- seed_a = '\d+',
- seed_b = '\d+',
- sigma_ex = '[\d\.]+',
- sigma_in = '[\d\.]+',
- plot = '[\w\d\-]+',
- matrix = 'weights|correlations',
- measures = 'weights|correlations|ratecorr',
- protocol = '[\w\d\-\.]+',
- syndist = '[a-z\-]+',
- network_specs = '[\w\d\.]+',
- <<<<<<< HEAD
- size = '[\d\.]+',
- length = '\d',
- connectors = '\d+',
- connectors_a = '\d+',
- connectors_b = '\d+',
- =======
- >>>>>>> refs/remotes/origin/synced/master
- rule rewire_and_redraw:
- input:
- expand('simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- <<<<<<< HEAD
- + 'sin{sigma_in}_{syndist}/seed_{seed}/{protocol}/{outfile}', #'{plot}.pdf',
- =======
- + 'sin{sigma_in}_{syndist}/seed_{seed}/{protocol}/{outfile}', #'{plot}.png',
- >>>>>>> refs/remotes/origin/synced/master
- N = config.N,
- f = config.f,
- mu = config.mu,
- epsilon = config.epsilon,
- eta = config.eta,
- sigma_ex = config.sigma_ex,
- sigma_in = config.sigma_in,
- syndist = config.syndist,
- seed = config.seed,
- outfile = 'correlations.npy',
- # plot = ['correlations', 'weights',
- # 'spikes_50000-60000ms', 'spikes_59000-60000ms'],
- protocol = ['original']
- + expand('shuffle_{frac}_{source}-{target}',
- frac=config.shuffle_frac,
- source=config.shuffle_source,
- target=config.shuffle_target)
- + expand('add_{source_frac}{source}-{target_frac}{target}',
- source_frac=config.add_source_frac,
- target_frac=config.add_target_frac,
- source=config.add_source,
- target=config.add_target)
- <<<<<<< HEAD
- + expand('cluster_{num}x{size}{target}_p{epsilon}',
- num=config.cluster_number,
- size=config.cluster_size,
- target=config.cluster_pop,
- epsilon=config.cluster_epsilon))
- =======
- )
- >>>>>>> refs/remotes/origin/synced/master
- rule redraw_comparisons:
- input:
- expand('results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- + 'sin{sigma_in}_{syndist}/redraw_{protocol}/{measure}_{seed_pair}.csv',
- N = config.N,
- f = config.f,
- mu = config.mu,
- epsilon = config.epsilon,
- eta = config.eta,
- sigma_ex = config.sigma_ex,
- sigma_in = config.sigma_in,
- syndist = config.syndist,
- seed_pair = config.seed_pairs[::int(len(config.seed)/2)],
- measure = ['correlations', 'weights', 'ratecorr'],
- <<<<<<< HEAD
- protocol =
- ['original']
- # + expand('cluster_{num}x{size}{target}_p{epsilon}',
- # num=config.cluster_number,
- # size=config.cluster_size,
- # target=config.cluster_pop,
- # epsilon=config.cluster_epsilon)
- # + expand('chain_{num}x{size}{target}_j{strength}_p{epsilon}',
- # num=config.chain_length,
- # size=config.chain_size,
- # target=config.chain_pop,
- # strength=config.chain_strength,
- # epsilon=config.chain_epsilon)
- )
- =======
- protocol = 'original'
- )
- >>>>>>> refs/remotes/origin/synced/master
- rule rewire_comparisons:
- input:
- expand('results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- + 'sin{sigma_in}_{syndist}/{protocol}/{measure}_{seed}.csv',
- N = config.N,
- f = config.f,
- mu = config.mu,
- epsilon = config.epsilon,
- eta = config.eta,
- sigma_ex = config.sigma_ex,
- sigma_in = config.sigma_in,
- syndist = config.syndist,
- seed = config.seed,
- measure = ['correlations', 'weights', 'ratecorr'],
- <<<<<<< HEAD
- protocol =
- # expand('sheffle_{frac}_{source}-{target}',
- # frac=3500, #config.shuffle_frac,
- # source=config.shuffle_source,
- # target=config.shuffle_target)
- # +
- expand('add_{source_frac}{source}-{target_frac}{target}',
- =======
- protocol = expand('shuffle_{frac}_{source}-{target}',
- frac=config.shuffle_frac,
- source=config.shuffle_source,
- target=config.shuffle_target)
- + expand('add_{source_frac}{source}-{target_frac}{target}',
- >>>>>>> refs/remotes/origin/synced/master
- source_frac=config.add_source_frac,
- target_frac=config.add_target_frac,
- source=config.add_source,
- target=config.add_target)
- <<<<<<< HEAD
- # + expand('cluster_{num}x{size}{target}_p{epsilon}',
- # num=config.cluster_number,
- # size=config.cluster_size,
- # target=config.cluster_pop,
- # epsilon=config.cluster_epsilon)
- # expand('chain_{length}_{size}{cpop}_j{strength}_p{epsilon}_c{c_a}-{c_b}',
- # length=config.chain_length,
- # c_a=config.connectors[0],
- # c_b=config.connectors[1],
- # size=config.chain_size,
- # cpop=config.chain_pop,
- # strength=config.chain_strength,
- # epsilon=config.chain_epsilon)
- )
- # rule chain_comparisons:
- # input:
- # expand('results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- # + 'sin{sigma_in}_{syndist}/{protocol}/{measure}_{seed}.csv',
- # N = config.N,
- # f = config.f,
- # mu = config.mu,
- # epsilon = config.epsilon,
- # eta = config.eta,
- # sigma_ex = config.sigma_ex,
- # sigma_in = config.sigma_in,
- # syndist = config.syndist,
- # seed = config.seed,
- # measure = ['correlations', 'weights', 'ratecorr'],
- # protocol = expand('shuffle_{frac}_{source}-{target}',
- # frac=config.shuffle_frac,
- # source=config.shuffle_source,
- # target=config.shuffle_target)
- # )
- =======
- )
- >>>>>>> refs/remotes/origin/synced/master
- # REWIRE EXPERIMENTS
- def id_span(N, f, pop):
- N, f = int(N), float(f)
- N_exc = int(N*f)
- if pop == 'E':
- return (0, N_exc)
- elif pop =='I':
- return (N_exc, N)
- else:
- raise ValueError
- rule shuffle_weights:
- input:
- script = 'scripts/shuffle_weights.py',
- weights = '{root}/N{N}_f{f}_{specs}/original/weights.npy'
- output:
- weights = '{root}/N{N}_f{f}_{specs}/'\
- + 'shuffle_{fraction}_{source_pop}-{target_pop}/weights.npy'
- params:
- source_span = lambda w: id_span(w.N, w.f, w.source_pop),
- target_span = lambda w: id_span(w.N, w.f, w.target_pop),
- shell:
- """
- python {input.script} --input "{input.weights}" \
- --output "{output.weights}" \
- --source_span {params.source_span} \
- --target_span {params.target_span} \
- --fraction {wildcards.fraction}
- """
- <<<<<<< HEAD
- use rule shuffle_weights as sheffle_weights with:
- output:
- weights = '{root}/N{N}_f{f}_{specs}/'\
- + 'sheffle_{fraction}_{source_pop}-{target_pop}/weights.npy'
- =======
- >>>>>>> refs/remotes/origin/synced/master
- rule add_weights:
- input:
- script = 'scripts/add_weights.py',
- weights = '{root}/N{N}_f{f}_{specs}/original/weights.npy'
- output:
- weights = '{root}/N{N}_f{f}_{specs}/'\
- + 'add_{source_frac}{source_pop}-{target_frac}{target_pop}'\
- + '/weights.npy'
- params:
- source_span = lambda w: id_span(w.N, w.f, w.source_pop),
- target_span = lambda w: id_span(w.N, w.f, w.target_pop),
- weight_mean = lambda w: config.J_ex if w.source_pop == 'E' else config.J_in,
- weight_std = lambda w: config.sigma_ex if w.source_pop == 'E' else config.sigma_in,
- syndist = config.syndist
- shell:
- """
- python {input.script} --input "{input.weights}" \
- --output "{output}" \
- --source_span {params.source_span} \
- --target_span {params.target_span} \
- --source_fraction {wildcards.source_frac} \
- --target_fraction {wildcards.target_frac} \
- --weight_mean {params.weight_mean} \
- --weight_std {params.weight_std} \
- --syndist {params.syndist}
- """
- <<<<<<< HEAD
- rule cluster_weights:
- input:
- script = 'scripts/cluster_weights.py',
- weights = '{root}/N{N}_f{f}_{specs}/original/weights.npy'
- output:
- weights = '{root}/N{N}_f{f}_{specs}/'\
- + 'cluster_{num}x{size}{cpop}_p{epsilon}/weights.npy'
- params:
- pop_span = lambda w: id_span(w.N, w.f, w.cpop),
- weight_mean = lambda w: config.J_ex if w.cpop == 'E' else config.J_in,
- weight_std = lambda w: config.sigma_ex if w.cpop == 'E' else config.sigma_in,
- syndist = config.syndist
- shell:
- """
- python {input.script} --input "{input.weights}" \
- --output "{output}" \
- --cluster_number {wildcards.num} \
- --cluster_fraction {wildcards.size} \
- --cluster_prob {wildcards.epsilon} \
- --pop_span {params.pop_span} \
- --weight_mean {params.weight_mean} \
- --weight_std {params.weight_std} \
- --syndist {params.syndist}
- """
- rule hub_weights:
- input:
- script = 'scripts/hub_weights.py',
- weights = '{root}/N{N}_f{f}_{specs}/original/weights.npy'
- output:
- weights = '{root}/N{N}_f{f}_{specs}/' \
- + 'hub_{size}{hpop}_j{strength}_p{epsilon}/weights.npy'
- params:
- pop_span = lambda w: id_span(w.N, w.f, w.hpop),
- shell:
- """
- python {input.script} --input "{input.weights}" \
- --output "{output.weights}" \
- --hub_size {wildcards.size} \
- --hub_prob {wildcards.epsilon} \
- --hub_strength {wildcards.strength} \
- --pop_span {params.pop_span}
- """
- def chain_sections(w):
- min_size = int(w.length)
- sections = list(range(min_size, int(w.length)+min_size))[::-1]
- norm = sum(sections)
- return [i/norm for i in sections]
- rule chain_weights:
- input:
- script = 'scripts/chain_weights.py',
- weights = '{root}/N{N}_f{f}_{network_specs}/seed_{seed}/original/weights.npy'
- output:
- weights = '{root}/N{N}_f{f}_{network_specs}/seed_{seed}/' \
- + 'chain_{length}_{size}{cpop}' \
- + '_j{strength}_p{epsilon}_c{connectors}/weights.npy'
- params:
- pop_span = lambda w: id_span(w.N, w.f, w.cpop),
- chain_sections = chain_sections
- shell:
- """
- python {input.script} --input "{input.weights}" \
- --output "{output.weights}" \
- --chain_size {wildcards.size} \
- --chain_prob {wildcards.epsilon} \
- --chain_strength {wildcards.strength} \
- --pop_span {params.pop_span} \
- --chain_sections "{params.chain_sections}" \
- --connectors {wildcards.connectors} \
- --seed {wildcards.seed}
- """
- =======
- >>>>>>> refs/remotes/origin/synced/master
- # COMPARE NETWORK ACTIVITY AND CONNECTIVITY
- rule compare_redrawn_networks:
- input:
- script = "../scripts/eigenangle_test.py",
- matrix_a = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/seed_{seed_a}/{protocol}/{matrix}.npy',
- matrix_b = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/seed_{seed_b}/{protocol}/{matrix}.npy'
- output:
- temp('results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/redraw_{protocol}/'\
- + '{matrix}_{seed_a}-{seed_b}.json')
- params:
- bin_num = config.bin_num,
- is_connectivity = lambda w: True if ('weights' in w.matrix) else False,
- shuffle_neuron_ids = lambda w, output: 'redraw' in str(output)
- shell:
- """
- python {input.script} --matrix_a {input.matrix_a} \
- --matrix_b {input.matrix_b} \
- --output {output} \
- --N {wildcards.N} \
- --bin_num {params.bin_num} \
- --mu {wildcards.mu} \
- --f {wildcards.f} \
- --epsilon {wildcards.epsilon} \
- --sigma_ex {wildcards.sigma_ex} \
- --sigma_in {wildcards.sigma_in} \
- --is_connectivity {params.is_connectivity} \
- --shuffle_neuron_ids {params.shuffle_neuron_ids}
- """
- use rule compare_redrawn_networks as compare_rewired_network with:
- input:
- script = "../scripts/eigenangle_test.py",
- matrix_a = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/seed_{seed}/original/{matrix}.npy',
- matrix_b = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/seed_{seed}/{protocol}/{matrix}.npy',
- output:
- temp('results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/{protocol}/{matrix}_{seed}.json')
- <<<<<<< HEAD
- use rule compare_redrawn_networks as compare_chain_networks with:
- input:
- script = "../scripts/eigenangle_test.py",
- matrix_a = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/seed_{seed}/chain_{specs}_'\
- + 'c{connectors_a}/{matrix}.npy',
- matrix_b = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/seed_{seed}/chain_{specs}_'\
- + 'c{connectors_b}/{matrix}.npy',
- output:
- 'results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}'\
- + '_sin{sigma_in}_{syndist}/chain_{specs}_'\
- + 'c{connectors_a}-{connectors_b}/{matrix}_{seed}.json'
- #
- # ruleorder: calc_firing_rate_correlation > score_to_dataframe #> compare_chain_networks > compare_rewired_network
- =======
- >>>>>>> refs/remotes/origin/synced/master
- def get_spikes(wildcards):
- network_specs = wildcards.network_specs
- protocol = wildcards.protocol
- seeds = wildcards.seeds
- path = lambda prcl, s: f'simulation_output/{network_specs}/' \
- + f'seed_{s}/{prcl}/spikes.pkl'
- if 'redraw' in protocol:
- protocol = protocol.strip('redraw_')
- return [path(protocol, seed) for seed in seeds.split('-')]
- <<<<<<< HEAD
- elif 'chain' in protocol:
- protocol, connectors = protocol.split('_c')
- connectors = connectors.split('-')
- return [path(f'{protocol}_c{c}', seeds) for c in connectors]
- =======
- >>>>>>> refs/remotes/origin/synced/master
- else:
- return [path(p, seeds) for p in ['original', protocol]]
- rule calc_firing_rate_correlation:
- input:
- script = 'scripts/firing_rate_correlation.py',
- spikes = get_spikes
- params:
- sim_folder = 'simulation_output'
- output:
- 'results/{network_specs}/{protocol}/ratecorr_{seeds}.csv'
- shell:
- """
- python {input.script} --output "{output}" \
- --input "{input.spikes}" \
- --protocol {wildcards.protocol} \
- --seeds {wildcards.seeds}
- """
- # BUILD AND SIMULATE NETWORK
- rule build_network:
- input:
- script = 'scripts/build_network.py',
- config = 'config.py'
- params:
- out_config = lambda w, output: Path(output.weights).parents[1] / 'config.yml'
- output:
- weights = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- + 'sin{sigma_in}_{syndist}/seed_{seed}/original/weights.npy'
- shell:
- """
- python {input.script} --weights_path {output.weights} \
- --out_config {params.out_config} \
- --network_config {input.config} \
- --N {wildcards.N} \
- --f {wildcards.f} \
- --mu {wildcards.mu} \
- --sigma_ex {wildcards.sigma_ex} \
- --sigma_in {wildcards.sigma_in} \
- --epsilon {wildcards.epsilon} \
- --seed {wildcards.seed} \
- --syndist {wildcards.syndist}
- """
- rule simulate_network:
- input:
- script = 'scripts/simulate_network.py',
- weights = 'simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- + 'sin{sigma_in}_{syndist}/seed_{seed}/{protocol}/weights.npy',
- output:
- spikes_ex = temp('simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- + 'sin{sigma_in}_{syndist}/seed_{seed}/{protocol}/spikes_ex.gdf'),
- spikes_in = temp('simulation_output/'\
- + 'N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}_'\
- + 'sin{sigma_in}_{syndist}/seed_{seed}/{protocol}/spikes_in.gdf'),
- params:
- simtime = config.simtime,
- config_path = 'config.py'
- shell:
- """
- python {input.script} --spikes_ex_path {output.spikes_ex} \
- --spikes_in_path {output.spikes_in} \
- --weights_path {input.weights} \
- --network_config {params.config_path} \
- --N {wildcards.N} \
- --f {wildcards.f} \
- --mu {wildcards.mu} \
- --sigma_ex {wildcards.sigma_ex} \
- --sigma_in {wildcards.sigma_in} \
- --epsilon {wildcards.epsilon} \
- --simtime {params.simtime} \
- --seed {wildcards.seed} \
- --eta {wildcards.eta}
- """
- # TRANSFORM RULES
- rule nest_to_neo:
- input:
- script = 'scripts/nest_to_neo.py',
- spikes_ex = 'simulation_output/N{N}_f{f}_{specs}/spikes_ex.gdf',
- spikes_in = 'simulation_output/N{N}_f{f}_{specs}/spikes_in.gdf',
- output:
- 'simulation_output/N{N}_f{f}_{specs}/spikes.pkl'
- params:
- t_start = 0,
- t_stop = config.simtime
- shell:
- """
- python {input.script} --spikes_ex "{input.spikes_ex}" \
- --spikes_in "{input.spikes_in}" \
- --output {output} \
- --t_stop {params.t_stop} \
- --t_start {params.t_start} \
- --N {wildcards.N} \
- --f {wildcards.f}
- """
- rule create_correlation_matrix_from_spikes:
- input:
- script = 'scripts/correlation_matrix_from_spikes.py',
- spikes = '{spikes_dir}/spikes.pkl',
- output:
- correlation = '{spikes_dir}/correlations.npy'
- params:
- t_start = config.cut_inital_time,
- t_stop = config.simtime,
- bin_size = config.bin_size
- shell:
- """
- python {input.script} --spikes "{input.spikes}" \
- --output {output} \
- --t_stop {params.t_stop} \
- --t_start {params.t_start} \
- --bin_size {params.bin_size}
- """
- rule score_to_dataframe:
- input:
- script = '../scripts/score_to_dataframe.py',
- data = 'results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}' \
- + '_sin{sigma_in}_{syndist}/{protocol}/{matrix}_{seeds}.json'
- output:
- 'results/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}_sex{sigma_ex}' \
- + '_sin{sigma_in}_{syndist}/{protocol}/{matrix}_{seeds}.csv'
- params:
- bin_num = config.bin_num,
- simtime = config.simtime
- shell:
- """
- python {input.script} --output "{output}" \
- --input "{input.data}" \
- --params {wildcards} \
- --bin_num {params.bin_num} \
- --simtime {params.simtime}
- """
- rule merge_comparison_results:
- input:
- script = '../scripts/merge_dataframes.py',
- params:
- exclude = ['merged_ratecorr_results', 'merged_comparison_results',
- 'rewiring_results', 'ratecorr']
- output:
- temp('{dir}/merged_comparison_results.csv')
- shell:
- """
- python {input.script} --output "{output}" \
- --exclude "{params.exclude}"
- """
- use rule merge_comparison_results as merge_ratecorr_results with:
- params:
- exclude = ['merged_ratecorr_results', 'merged_comparison_results',
- 'rewiring_results', 'weights', 'correlations']
- output:
- temp('{dir}/merged_ratecorr_results.csv')
- rule process_result_dataframe:
- input:
- script = 'scripts/process_result_dataframe.py',
- comparison_df = '{dir}/merged_comparison_results.csv',
- ratecorr_df = '{dir}/merged_ratecorr_results.csv'
- output:
- '{dir}/rewiring_results.csv'
- shell:
- """
- python {input.script} --output "{output}" \
- --comparison_df "{input.comparison_df}" \
- --ratecorr_df "{input.ratecorr_df}"
- """
- # PLOT SIMULATION OUTPUT
- rule plot_spiketrains:
- input:
- script = '../scripts/plot_spiketrains.py',
- spikes = 'simulation_output/{network_specs}/seed_{seed}/{protocol}/spikes.pkl'
- output:
- <<<<<<< HEAD
- 'images/rasterplot/{network_specs}_seed{seed}_{protocol}_spikes{t_start}-{t_stop}ms.pdf'
- =======
- 'images/rasterplot/{network_specs}_seed{seed}_{protocol}_spikes{t_start}-{t_stop}ms.png'
- >>>>>>> refs/remotes/origin/synced/master
- shell:
- """
- python {input.script} --spikes "{input.spikes}" \
- --output "{output}" \
- --t_start {wildcards.t_start} \
- --t_stop {wildcards.t_stop}
- """
- rule plot_matrix:
- input:
- script = '../scripts/plot_matrix.py',
- matrix = 'simulation_output/{network_specs}/seed_{seed}/{protocol}/{matrix}.npy'
- output:
- <<<<<<< HEAD
- 'images/{matrix}/{network_specs}_seed{seed}_{protocol}.pdf'
- =======
- 'images/{matrix}/{network_specs}_seed{seed}_{protocol}.png'
- >>>>>>> refs/remotes/origin/synced/master
- shell:
- """
- python {input.script} --input "{input.matrix}" \
- --output "{output}"
- """
- rule plot_eigenspectrum:
- input:
- script = 'scripts/plot_eigenspectrum.py',
- files = expand('simulation_output/N{{N}}_f{{f}}_mu{{mu}}_p{{epsilon}}' \
- + '_eta{{eta}}_sex{{sigma_ex}}_sin{{sigma_in}}_{{syndist}}' \
- + '/seed_{seed}/{{protocol}}/weights.npy',
- seed = range(1,9))
- output:
- 'images/eigenspectrum/N{N}_f{f}_mu{mu}_p{epsilon}_eta{eta}' \
- <<<<<<< HEAD
- + '_sex{sigma_ex}_sin{sigma_in}_{syndist}_{protocol}.pdf'
- =======
- + '_sex{sigma_ex}_sin{sigma_in}_{syndist}_{protocol}.png'
- >>>>>>> refs/remotes/origin/synced/master
- shell:
- """
- python {input.script} --input "{input.files}" \
- --output "{output}" \
- --N {wildcards.N} \
- --f {wildcards.f} \
- --mu {wildcards.mu} \
- --sigma_ex {wildcards.sigma_ex} \
- --sigma_in {wildcards.sigma_in} \
- --epsilon {wildcards.epsilon} \
- """
- rule plot_pvalues:
- input:
- script = 'scripts/plot_pvalue_{plot_name}.py',
- dataframe = 'results/{network_specs}/rewiring_results.csv'
- output:
- <<<<<<< HEAD
- 'images/pvalue_{plot_name}/{network_specs}-{protocol}.pdf'
- =======
- 'images/pvalue_{plot_name}/{network_specs}-{protocol}.png'
- >>>>>>> refs/remotes/origin/synced/master
- shell:
- """
- python {input.script} --input "{input.dataframe}" \
- --output "{output}" \
- --protocol {wildcards.protocol}
- """
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