-
Notifications
You must be signed in to change notification settings - Fork 1
/
inputs.f90
342 lines (301 loc) · 14.2 KB
/
inputs.f90
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
MODULE inputs
implicit none
integer, parameter :: clonal = 1, suppressed = 2, full_sexual = 3
integer pop_size, num_generations, num_linkage_subunits, &
bottleneck_generation, bottleneck_pop_size, &
num_bottleneck_generations, fitness_distrib_type, &
max_del_mutn_per_indiv, max_fav_mutn_per_indiv, &
max_neu_mutn_per_indiv, fission_type, &
num_initial_fav_mutn, num_indiv_exchanged, &
random_number_seed, restart_dump_number, &
haploid_chromosome_number, fission_threshold, &
selection_scheme, migration_generations, &
migration_model, num_contrasting_alleles, &
pop_growth_model, plot_allele_gens, verbosity, &
poisson_method, recombination_model, carrying_capacity, &
num_high_impact_alleles, special_feature_code
real reproductive_rate, mutn_rate, &
genome_size, high_impact_mutn_fraction, &
high_impact_mutn_threshold, fraction_recessive, &
dominant_hetero_expression, max_fav_fitness_gain, &
recessive_hetero_expression, frac_fav_mutn, &
heritability, uniform_fitness_effect_del, &
uniform_fitness_effect_fav, multiplicative_weighting, &
fraction_random_death, fraction_self_fertilization, &
initial_alleles_mean_effect, non_scaling_noise, &
partial_truncation_value, se_nonlinked_scaling, &
se_linked_scaling, pop_growth_rate, pop_growth_rate2, &
tc_scaling_factor, group_heritability, fraction_neutral, &
social_bonus_factor, max_total_fitness_increase, &
polygenic_effect, initial_alleles_pop_frac, high_impact_amplitude
real*8 :: tracking_threshold, extinction_threshold
logical :: fitness_dependent_fertility, dynamic_linkage, &
synergistic_epistasis, is_parallel, bottleneck_yes, &
restart_case, write_dump, homogenous_tribes, &
clonal_haploid, write_vcf, &
upload_mutations, altruistic, allow_back_mutn, &
cyclic_bottlenecking, track_neutrals, tribal_competition, &
polygenic_beneficials, fission_tribes, reseed_rng, &
global_allele_analysis
! note: if changing the string length of polygenic_target below,
! need to make corresponding change in polygenic.f90 function poly_match
character case_id*6, data_file_path*80, polygenic_target*40, polygenic_init*40
contains
subroutine read_parameters(nf)
integer nf
namelist /basic/ case_id, mutn_rate, frac_fav_mutn, &
reproductive_rate, pop_size, num_generations
namelist /mutations/ fitness_distrib_type, &
genome_size, high_impact_mutn_fraction, &
high_impact_mutn_threshold, uniform_fitness_effect_del, &
uniform_fitness_effect_fav, &
max_fav_fitness_gain, num_initial_fav_mutn, &
multiplicative_weighting, fraction_recessive, &
recessive_hetero_expression, dominant_hetero_expression, &
upload_mutations, allow_back_mutn, se_nonlinked_scaling, &
se_linked_scaling, synergistic_epistasis
namelist /selection/ fraction_random_death, heritability, &
non_scaling_noise, fitness_dependent_fertility, &
selection_scheme, partial_truncation_value
namelist /population/ recombination_model, clonal_haploid, &
dynamic_linkage, haploid_chromosome_number, &
fraction_self_fertilization, num_linkage_subunits, &
pop_growth_model, pop_growth_rate, pop_growth_rate2, &
bottleneck_yes, bottleneck_generation, bottleneck_pop_size, &
num_bottleneck_generations, carrying_capacity
namelist /substructure/ is_parallel, homogenous_tribes, &
num_indiv_exchanged, migration_model, migration_generations, &
tribal_competition, tc_scaling_factor, group_heritability, &
altruistic, social_bonus_factor, fission_tribes, &
fission_type, fission_threshold
namelist /computation/ tracking_threshold, extinction_threshold, &
max_del_mutn_per_indiv, max_fav_mutn_per_indiv, &
max_neu_mutn_per_indiv, random_number_seed, reseed_rng, &
write_dump, write_vcf, restart_case, &
restart_dump_number, data_file_path, plot_allele_gens, &
global_allele_analysis, verbosity, poisson_method
namelist /special_apps/ num_contrasting_alleles, &
max_total_fitness_increase, initial_alleles_pop_frac, &
num_high_impact_alleles, high_impact_amplitude, &
track_neutrals, fraction_neutral, &
polygenic_effect, polygenic_beneficials, polygenic_target, &
polygenic_init, special_feature_code
read (unit=nf, nml=basic)
read (unit=nf, nml=mutations)
read (unit=nf, nml=selection)
read (unit=nf, nml=population)
read (unit=nf, nml=substructure)
read (unit=nf, nml=computation)
read (unit=nf, nml=special_apps)
end subroutine read_parameters
subroutine write_parameters(nf)
! This routine writes the current parameter values to logical
! unit nf.
integer nf
write(nf,'("&basic")')
write(nf,'(a32,6xa6)') ' case_id = ' , case_id
write(nf,'(a32,e12.3)') ' mutn_rate = ' , mutn_rate
write(nf,'(a32,f12.7)') ' frac_fav_mutn = ' , frac_fav_mutn
write(nf,'(a32,f12.7)') ' reproductive_rate = ' , reproductive_rate
write(nf,'(a32,i12)') ' pop_size = ' , pop_size
write(nf,'(a32,i12)') ' num_generations = ' , num_generations
write(nf,'("/")')
write(nf,'(/"&mutations")')
write(nf,'(a32,i12)') ' fitness_distrib_type = ' , fitness_distrib_type
write(nf,'(a32,f12.7)') ' fraction_neutral = ' , fraction_neutral
write(nf,'(a32,e12.3)') ' genome_size = ' , genome_size
write(nf,'(a32,f12.7)') ' high_impact_mutn_fraction = ', &
high_impact_mutn_fraction
write(nf,'(a32,f12.7)') ' high_impact_mutn_threshold = ', &
high_impact_mutn_threshold
write(nf,'(a32,i12)') ' num_initial_fav_mutn = ' , num_initial_fav_mutn
write(nf,'(a32,f12.7)') ' max_fav_fitness_gain = ' , max_fav_fitness_gain
write(nf,'(a32,f12.7)') ' uniform_fitness_effect_del = ', &
uniform_fitness_effect_del
write(nf,'(a32,f12.7)') ' uniform_fitness_effect_fav = ', &
uniform_fitness_effect_fav
write(nf,'(a32,f12.7)') ' fraction_recessive = ' , fraction_recessive
write(nf,'(a32,f12.7)') ' recessive_hetero_expression = ', &
recessive_hetero_expression
write(nf,'(a32,f12.7)') ' dominant_hetero_expression = ', &
dominant_hetero_expression
write(nf,'(a32,f12.7)') ' multiplicative_weighting = ', &
multiplicative_weighting
write(nf,'(a32,l)') ' synergistic_epistasis = ', &
synergistic_epistasis
write(nf,'(a32,e12.5)') ' se_nonlinked_scaling = ' , se_nonlinked_scaling
write(nf,'(a32,e12.5)') ' se_linked_scaling = ' , se_linked_scaling
write(nf,'(a32,l)') ' upload_mutations = ' , upload_mutations
write(nf,'(a32,l)') ' allow_back_mutn = ' , allow_back_mutn
write(nf,'(a32,l)') ' polygenic_beneficials = ', polygenic_beneficials
write(nf,'(a32,a)') ' polygenic_init = ' , polygenic_init
write(nf,'(a32,a)') ' polygenic_target = ' , polygenic_target
write(nf,'(a32,f12.7)') ' polygenic_effect = ' , polygenic_effect
write(nf,'("/")')
write(nf,'(/"&selection")')
write(nf,'(a32,f12.7)') ' fraction_random_death = ', fraction_random_death
write(nf,'(a32,f12.7)') ' heritability = ' , heritability
write(nf,'(a32,f12.7)') ' non_scaling_noise = ' , non_scaling_noise
write(nf,'(a32,l)') ' fitness_dependent_fertility = ', &
fitness_dependent_fertility
write(nf,'(a32,i12)') ' selection_scheme = ' , selection_scheme
write(nf,'(a32,f12.7)') ' partial_truncation_value = ', &
partial_truncation_value
write(nf,'("/")')
write(nf,'(/"&population")')
write(nf,'(a32,i12)') ' recombination_model = ' , recombination_model
write(nf,'(a32,l)') ' clonal_haploid = ' , clonal_haploid
write(nf,'(a32,f12.7)') ' fraction_self_fertilization = ', &
fraction_self_fertilization
write(nf,'(a32,i12)') ' num_contrasting_alleles = ', &
num_contrasting_alleles
write(nf,'(a32,f12.7)') ' initial_alleles_mean_effect = ', &
initial_alleles_mean_effect
write(nf,'(a32,f12.7)') ' initial_alleles_pop_frac = ', &
initial_alleles_pop_frac
write(nf,'(a32,i12)') ' num_high_impact_alleles = ', &
num_high_impact_alleles
write(nf,'(a32,f12.7)') ' high_impact_amplitude = ', &
high_impact_amplitude
write(nf,'(a32,l)') ' dynamic_linkage = ' , dynamic_linkage
write(nf,'(a32,i12)') ' haploid_chromosome_number = ', &
haploid_chromosome_number
write(nf,'(a32,i12)') ' num_linkage_subunits = ' , num_linkage_subunits
write(nf,'(a32,i12)') ' pop_growth_model = ' , pop_growth_model
write(nf,'(a32,f12.7)') ' pop_growth_rate = ' , pop_growth_rate
write(nf,'(a32,f12.7)') ' pop_growth_rate2 = ' , pop_growth_rate2
write(nf,'(a32,i12)') ' carrying_capacity = ' , carrying_capacity
write(nf,'(a32,l)') ' bottleneck_yes = ' , bottleneck_yes
write(nf,'(a32,i12)') ' bottleneck_generation = ', bottleneck_generation
write(nf,'(a32,i12)') ' bottleneck_pop_size = ' , bottleneck_pop_size
write(nf,'(a32,i12)') ' num_bottleneck_generations = ', &
num_bottleneck_generations
write(nf,'("/")')
write(nf,'(/"&substructure")')
write(nf,'(a32,l)') ' is_parallel = ' , is_parallel
write(nf,'(a32,l)') ' homogenous_tribes = ' , homogenous_tribes
write(nf,'(a32,i12)') ' num_indiv_exchanged = ' , num_indiv_exchanged
write(nf,'(a32,i12)') ' migration_generations = ' , migration_generations
write(nf,'(a32,i12)') ' migration_model = ' , migration_model
write(nf,'(a32,l)') ' tribal_competition = ' , tribal_competition
write(nf,'(a32,f12.7)') ' tc_scaling_factor = ' , tc_scaling_factor
write(nf,'(a32,f12.7)') ' group_heritability = ' , group_heritability
write(nf,'(a32,l)') ' altruistic = ' , altruistic
write(nf,'(a32,f12.7)') ' social_bonus_factor = ' , social_bonus_factor
write(nf,'(a32,l)') ' fission_tribes = ' , fission_tribes
write(nf,'(a32,i12)') ' fission_type = ' , fission_type
write(nf,'(a32,i12)') ' fission_threshold = ' , fission_threshold
write(nf,'("/")')
write(nf,'(/"&computation")')
write(nf,'(a32,1pe12.3)') ' tracking_threshold = ' , tracking_threshold
write(nf,'(a32,f12.7)') ' extinction_threshold = ' , extinction_threshold
write(nf,'(a32,i12)') ' max_del_mutn_per_indiv = ', max_del_mutn_per_indiv
write(nf,'(a32,i12)') ' max_neu_mutn_per_indiv = ', max_neu_mutn_per_indiv
write(nf,'(a32,i12)') ' max_fav_mutn_per_indiv = ', max_fav_mutn_per_indiv
write(nf,'(a32,i12)') ' random_number_seed = ' , random_number_seed
write(nf,'(a32,i12)') ' poisson_method = ' , poisson_method
write(nf,'(a32,l)') ' reseed_rng = ' , reseed_rng
write(nf,'(a32,l)') ' track_neutrals = ' , track_neutrals
write(nf,'(a32,l)') ' write_dump = ' , write_dump
write(nf,'(a32,l)') ' write_vcf = ' , write_vcf
write(nf,'(a32,l)') ' restart_case = ' , restart_case
write(nf,'(a32,i12)') ' restart_dump_number = ' , restart_dump_number
write(nf,'(a32,i12)') ' plot_allele_gens = ' , plot_allele_gens
write(nf,'(a32,i12)') ' verbosity = ' , verbosity
write(nf,'(a20,a,a)') " data_file_path = '", trim(data_file_path),"'"
write(nf,'("/")')
write(nf,'(/"&special_apps")')
write(nf,'("/")')
end subroutine write_parameters
subroutine set_default_parameters()
! basic parameters
case_id = 'test00'
mutn_rate = 10.0
frac_fav_mutn = 0.0
reproductive_rate = 2.0
pop_size = 1000
num_generations = 500
! mutations
fitness_distrib_type = 1 ! exponential_mutation_effect
genome_size = 3.e+8
high_impact_mutn_fraction = 0.001
high_impact_mutn_threshold = 0.001
num_initial_fav_mutn = 0
max_fav_fitness_gain = 0.01
uniform_fitness_effect_del = 0.0
uniform_fitness_effect_fav = 0.0
fraction_recessive = 0.0
recessive_hetero_expression = 0.5
dominant_hetero_expression = 0.5
multiplicative_weighting = 0.0
synergistic_epistasis = .false.
se_nonlinked_scaling = 0
se_linked_scaling = 0
upload_mutations = .false.
allow_back_mutn = .false.
! selection
fraction_random_death = 0.0
heritability = 0.2
non_scaling_noise = 0.05
fitness_dependent_fertility = .false.
selection_scheme = 2
partial_truncation_value = 0.5
! population
recombination_model = full_sexual
clonal_haploid = .false.
fraction_self_fertilization = 0.0
dynamic_linkage = .true.
haploid_chromosome_number = 23
num_linkage_subunits = 989
pop_growth_model = 0 ! fixed_population
pop_growth_rate = 0
pop_growth_rate2 = 0
bottleneck_yes = .false.
bottleneck_generation = 0
bottleneck_pop_size = 0
num_bottleneck_generations = 0
! substructure
is_parallel = .false.
homogenous_tribes = .true.
num_indiv_exchanged = 1
migration_generations = 10
migration_model = 1
tribal_competition = .false.
tc_scaling_factor = 0.1
group_heritability = 0.0
altruistic = .false.
social_bonus_factor = 1.0
tracking_threshold = 0
extinction_threshold = 0
fission_tribes = .false.
fission_type = 2
fission_threshold = 100
! computation
max_del_mutn_per_indiv = 10000
max_neu_mutn_per_indiv = 10000
max_fav_mutn_per_indiv = 10000
random_number_seed = 42
reseed_rng = .false.
poisson_method = 0 ! Numerical Recipes
write_dump = .false.
write_vcf = .false.
restart_case = .false.
restart_dump_number = 0
plot_allele_gens = 100
verbosity = 1
data_file_path = './'
! special applications
num_contrasting_alleles = 0
initial_alleles_mean_effect = 1.0
initial_alleles_pop_frac = 0.5
num_high_impact_alleles = 0
high_impact_amplitude = 0.0
track_neutrals = .false.
fraction_neutral = 0.0
polygenic_beneficials = .false.
polygenic_init = 'AAAAAA'
polygenic_target = 'TCGTCG'
polygenic_effect = 0.001
special_feature_code = 0
end subroutine set_default_parameters
end module inputs