Experto en enfermedades (versión en V)
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Sistema experto sobre enfermedades, escrito en V.
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// main.v
//
// This file is part of Experto en enfermedades (Expert on diseases)
// Last modified 20250812T1907+0200.
/*
Copyright (C) 1985, Chris Naylor: Sinclair BASIC code included in his book
"Build Your Own Expert System" (Sigma Press, 1985).
Copyright (C) 1988, 1989, Marcos Cruz (programandala.net): SuperBASIC version
(http:///programandala.net/es.programa.sistema_experto_sobre_enfermedades.html).
Copyright (C) 2023, 2024, Marcos Cruz (programandala.net): Odin version.
Copyright (C) 2024, 2025, Marcos Cruz (programandala.net): SBASIC version.
Copyright (C) 2025, Marcos Cruz (programandala.net): V version.
This program is licensed under a BSD 2-Clause License
(https://opensource.org/license/bsd-2-clause/). See the <LICENSE.txt> file.
*/
// ==========================================================================
import math
import strconv
import term
const title = 'Experto en enfermedades'
// XXX TMP
// debug level
// 0: do not include debug code (this is the default)
// 1: add the test options to the main menu
// 2: also print debugging messages during the main loop
const debug_level = $d('debug_level', 1)
const diseases = 91
const symptoms = 68
const max_answer = 5
const min_answer = -max_answer
enum Mode {
normal_mode
random_demo_mode
value_demo_mode
}
__global mode = Mode.normal_mode
__global demo_value = 0
fn init() {
// Anodino's type package is used by Anodino's par package. When type's
// `max_lines_printed_before_a_pause` is set to zero, no pause is issued
// during the printing of the paragrahps:
// type.max_lines_printed_before_a_pause = 0 // XXX TODO
}
fn consult() {
mut max_prob := [diseases]f64{}
mut min_prob := [diseases]f64{}
mut prob := [diseases]f64{}
mut asked := [symptoms]bool{}
mut symptoms_count := [diseases]int{}
mut symptoms_left := [diseases]int{}
mut value := [symptoms]f64{}
mut answer_value := 0
mut disease_name := ''
mut disease_prob := 0.0
mut hypothesis := 0
mut symptom := 0
mut current_prob := 0.0
mut con_prob := 0.0
mut pro_prob := 0.0
// Find the a priori probability and the rule values
if debug_level > 1 {
println('Find the a priori probability and the rule values')
}
for disease in 0 .. diseases {
disease_name, prob[disease] = disease_data(disease)
current_prob = prob[disease]
if debug_level > 1 {
print("Disease #${disease}: \"${disease_name}\" (current prob: ${current_prob})\n")
}
for disease_symptom := 0; true; disease_symptom += 1 {
symptom, pro_prob, con_prob = symptom_data(disease, disease_symptom) or { break }
symptoms_left[disease] += 1
value[symptom] += math.abs(current_prob * pro_prob / (current_prob * pro_prob +
(1 - current_prob) * con_prob) - current_prob * (1 - pro_prob) / (
current_prob * (1 - pro_prob) + (1 - current_prob) * (1 - con_prob)))
if debug_level > 1 {
print('Symptom #${symptom} (value: ${value[symptom]})\n')
}
}
symptoms_count[disease] = symptoms_left[disease]
}
for {
// Find the most important symptom and ask about it
if debug_level > 1 {
println('Find the most important symptom and ask about it')
}
mut min_value := 0.0
no_symptom := -1
mut symptom_to_ask_for := no_symptom
for s in 0 .. symptoms {
if value[s] > min_value {
symptom_to_ask_for = s
min_value = value[s]
if debug_level > 1 {
print("Symptom to ask for: #${symptom_to_ask_for}, \"${question(symptom_to_ask_for)}\" (value: ${min_value})\n")
}
}
value[s] = 0
}
if symptom_to_ask_for == no_symptom {
println('No hay más preguntas.') // XXX TODO par.whole
return
}
if debug_level == 0 {
if mode == .normal_mode {
term.clear()
}
}
println(question(symptom_to_ask_for)) // XXX TODO par.whole
match mode {
.random_demo_mode {
answer_value = random_answer()
println(answer_value) // XXX TODO par.whole
}
.value_demo_mode {
answer_value = demo_value
println(answer_value) // XXX TODO par.whole
}
.normal_mode {
answer_value = user_answer()
}
}
asked[symptom_to_ask_for] = true
// Update the a priori probabilities
if debug_level > 1 {
println('Update the a priori probabilities')
}
for disease in 0 .. diseases {
disease_name, _ = disease_data(disease)
if debug_level > 1 {
print("Disease #${disease}: \"${disease_name}\"\n")
}
for s in 0 .. symptoms_count[disease] {
symptom, pro_prob, con_prob = symptom_data(disease, s) or { 0, 0.0, 0.0 } // `or` should never happen
if symptom == symptom_to_ask_for && symptoms_left[disease] > 0 {
symptoms_left[disease] = symptoms_left[disease] - 1
current_prob = prob[disease]
mut pe := current_prob * pro_prob + (1 - current_prob) * con_prob
if answer_value > 0 {
prob[disease] = current_prob * (1 +
(pro_prob / pe - 1) * f64(answer_value) / max_answer)
} else {
prob[disease] = current_prob * (1 +
(pro_prob - (1 - pro_prob) * pe / (1 - pe)) * f64(answer_value) / max_answer)
}
if prob[disease] == math.trunc(prob[disease]) {
symptoms_left[disease] = 0
}
}
}
}
// Find new min and max rule values
mut current_min_prob := 0.0
for disease in 0 .. diseases {
current_prob = prob[disease]
mut a1 := 1.0
mut a2 := 1.0
mut a3 := 1.0
mut a4 := 1.0
disease_name, disease_prob = disease_data(disease)
for s in 0 .. symptoms_count[disease] {
symptom, pro_prob, con_prob = symptom_data(disease, s) or { 0, 0.0, 0.0 } // `or` should never happen
if !asked[symptom] && symptoms_left[disease] > 0 {
if con_prob > pro_prob {
pro_prob = 1 - pro_prob
con_prob = 1 - con_prob
}
value[symptom] = value[symptom] +
current_prob * pro_prob / (current_prob * pro_prob +
(1 - current_prob) * con_prob) - current_prob * (1 - pro_prob) / (
current_prob * (1 - pro_prob) + (1 - current_prob) * (1 - con_prob))
a1 = a1 * pro_prob
a2 = a2 * con_prob
a3 = a3 * (1 - pro_prob)
a4 = a4 * (1 - con_prob)
}
}
max_prob[disease] = current_prob * a1 / (current_prob * a1 + (1 - current_prob) * a2)
min_prob[disease] = current_prob * a3 / (current_prob * a3 + (1 - current_prob) * a4)
if max_prob[disease] < disease_prob {
symptoms_left[disease] = 0
}
if min_prob[disease] > current_min_prob {
hypothesis = disease
current_min_prob = min_prob[disease]
if debug_level > 1 {
disease_name_, _ := disease_data(hypothesis)
print('Hipótesis: ${disease_name_} (#${hypothesis}), probabilidad mínima: ${current_min_prob}\n')
}
}
}
// Search for a clearly possible hypothesis
for disease in 0 .. diseases {
if min_prob[hypothesis] <= max_prob[disease] && disease != hypothesis {
current_min_prob = 0
}
}
if current_min_prob != 0 {
break
}
}
disease_name, _ = disease_data(hypothesis)
unsafe {
println(strconv.v_sprintf('El resultado más probable es ${disease_name} con probabilidad ${prob[hypothesis]}.')) // XXX TODO par.whole
}
}
fn print_credits() {
println(title) // XXX TODO par.whole
unsafe {
println(strconv.v_sprintf('Versión ${version}')) // XXX TODO par.whole
}
println('')
println('(C) 1985, Chris Naylor: en Sinclair BASIC.') // XXX TODO par.whole
println('(C) 1988, 1989, Marcos Cruz (programandala.net): en SuperBASIC.') // XXX TODO par.whole
println('(C) 2023, 2024, Marcos Cruz (programandala.net): en Odin.') // XXX TODO par.whole
println('(C) 2025, Marcos Cruz (programandala.net): en V.') // XXX TODO par.whole
println('')
}
fn main() {
init()
for {
term.clear()
print_credits()
if ready() {
consult()
press_enter()
} else {
break
}
}
}
// data.v
//
// This file is part of Experto en enfermedades (Expert on diseases)
// Last modified 20250812T1907+0200.
/*
Copyright (C) 1985, Chris Naylor: Sinclair BASIC code included in his book
"Build Your Own Expert System" (Sigma Press, 1985).
Copyright (C) 1988, 1989, Marcos Cruz (programandala.net): SuperBASIC version
(http:///programandala.net/es.programa.sistema_experto_sobre_enfermedades.html).
Copyright (C) 2023, 2024, Marcos Cruz (programandala.net): Odin version.
Copyright (C) 2024, 2025, Marcos Cruz (programandala.net): SBASIC version.
Copyright (C) 2025, Marcos Cruz (programandala.net): V version.
This program is licensed under a BSD 2-Clause License
(https://opensource.org/license/bsd-2-clause/). See the <LICENSE.txt> file.
*/
// ==========================================================================
// Return name and probability of the given disease.
fn disease_data(disease int) (string, f64) {
match disease {
0 { return 'resfriado común', 0.02 }
1 { return 'rinitis alérgica', 0.01 }
2 { return 'sinusitis', 0.01 }
3 { return 'faringitis', 0.02 }
4 { return 'amigdalitis', 0.001 }
5 { return 'gripe', 0.01 }
6 { return 'laringitis', 0.01 }
7 { return 'tumor de laringe', 0.00004 }
8 { return 'bronquitis aguda', 0.005 }
9 { return 'bronquitis crónica', 0.005 }
10 { return 'asma', 0.02 }
11 { return 'enfisema pulmonar', 0.01 }
12 { return 'neumonía', 0.003 }
13 { return 'pleuresia', 0.001 }
14 { return 'neumotórax', 0.0002 }
15 { return 'bronquiectasia', 0.00001 }
16 { return 'abceso pulmonar', 0.00001 }
17 { return 'neumoconiosis', 0.001 }
18 { return 'cáncer de pulmón', 0.001 }
19 { return 'fibrosis intersticial', 0.00001 }
20 { return 'edema pulmonar', 0.001 }
21 { return 'gastritis', 0.01 }
22 { return 'hernia de hiato', 0.001 }
23 { return 'úlcera duodenal', 0.01 }
24 { return 'úlcera gástrica', 0.01 }
25 { return 'diverticulitis intestinal', 0.001 }
26 { return 'enterocolitis', 0.0001 }
27 { return 'enfermedad de Crohn', 0.0001 }
28 { return 'oclusión intestinal', 0.00001 }
29 { return 'apendicitis', 0.001 }
30 { return 'intoxicación alimentaria', 0.001 }
31 { return 'gastroenteritis', 0.01 }
32 { return 'litiasis renal', 0.001 }
33 { return 'pielonefritis aguda', 0.001 }
34 { return 'litiasis biliar', 0.01 }
35 { return 'colecistitis', 0.001 }
36 { return 'herpes', 0.001 }
37 { return 'trombloflebitis', 0.0005 }
38 { return 'artritis reumatoide', 0.001 }
39 { return 'insuficiencia cardiaca', 0.001 }
40 { return 'ansiedad', 0.01 }
41 { return 'depresión', 0.01 }
42 { return 'trombosis coronaria', 0.01 }
43 { return 'angina de pecho', 0.01 }
44 { return 'embolia pulmonar', 0.0001 }
45 { return 'apoplegía', 0.001 }
46 { return 'ataque isquémico transitorio', 0.001 }
47 { return 'tuberculosis', 0.0001 }
48 { return 'hemorroides', 0.01 }
49 { return 'hipotiroidismo', 0.001 }
50 { return 'colon irritable', 0.0007 }
51 { return 'cáncer intestinal', 0.001 }
52 { return 'colitis ulcerosa', 0.0004 }
53 { return 'enfermedad de Meniere', 0.0005 }
54 { return 'espondilosis cervical', 0.006 }
55 { return 'hemorragia subdural', 0.000001 }
56 { return 'tumor cerebral', 0.000001 }
57 { return 'meningitis', 0.000001 }
58 { return 'hemorragia subaracnoidea', 0.00001 }
59 { return 'glaucoma agudo', 0.01 }
60 { return 'arteritis de la temporal', 0.001 }
61 { return 'dispepsia', .1 }
62 { return 'bloqueo cardiaco', 0.0003 }
63 { return 'anemia perniciosa', 0.0004 }
64 { return 'jaqueca', .1 }
65 { return 'hipertensión esencial', .15 }
66 { return 'eccema', 0.03 }
67 { return 'urticaria', 0.03 }
68 { return 'sarna', 0.001 }
69 { return 'sarampión', 0.02 }
70 { return 'rubeola', 0.01 }
71 { return 'varicela', 0.001 }
72 { return 'psoriasis', 0.02 }
73 { return 'pitiriasis rubra', 0.01 }
74 { return 'acné rosáceo', 0.01 }
75 { return 'tirotoxicosis', 0.001 }
76 { return 'diabetes mellitus', 0.01 }
77 { return 'cáncer de estómago', 0.0003 }
78 { return 'fibrilación auricular', 0.001 }
79 { return 'enfermedad de Hodgkin', 0.0001 }
80 { return 'fiebre glandular', 0.001 }
81 { return 'linfoma', 0.0001 }
82 { return 'paperas', 0.01 }
83 { return 'parálisis facial', 0.0003 }
84 { return 'enfermedad de Parkinson', 0.001 }
85 { return 'artritis reumatoide', 0.01 }
86 { return 'cistitis', 0.01 }
87 { return 'tumor renal', 0.001 }
88 { return 'tumor en la vejiga', 0.0004 }
89 { return 'iritis', 0.0005 }
90 { return 'hepatitis aguda', 0.001 }
else { return '', 0.0 }
}
return '', 0.0
}
// XXX TODO include details of the return values in the documentation:
// Given a disease and an ordinal symptom associated to it, return the global
// identifier of the symptom, and the pro and con probabilities of the given
// disease and symptom; if the list of symptoms of the given disease is
// exhausted, return `none` instead.
//
fn symptom_data(disease int, disease_symptom int) ?(int, f64, f64) {
match disease {
0 {
match disease_symptom {
0 { return 0, 0.9, 0.05 }
1 { return 1, 0.8, 0.02 }
2 { return 2, 0.8, 0.02 }
3 { return 4, 0.6, 0.01 }
4 { return 5, 1.0, 0.01 }
5 { return 6, 0.2, 0.01 }
6 { return 7, 0.5, 0.01 }
7 { return 14, 0.8, 0.01 }
8 { return 33, 0.0, 0.01 }
else {}
}
}
1 {
match disease_symptom {
0 { return 0, 1.0, 0.01 }
1 { return 1, 1.0, 0.01 }
2 { return 5, 0.9, 0.01 }
3 { return 9, 0.7, 0.01 }
4 { return 10, 0.7, 0.01 }
5 { return 11, 0.6, 0.01 }
6 { return 19, 0.9, 0.01 }
else {}
}
}
2 {
match disease_symptom {
0 { return 1, 0.5, 0.01 }
1 { return 5, 0.5, 0.01 }
2 { return 6, 0.8, 0.01 }
3 { return 12, 0.9, 0.01 }
4 { return 13, 0.8, 0.01 }
5 { return 14, 0.8, 0.01 }
6 { return 21, 0.5, 0.01 }
7 { return 62, 0.9, 0.01 }
else {}
}
}
3 {
match disease_symptom {
0 { return 2, 1.0, 0.01 }
1 { return 7, 0.5, 0.01 }
2 { return 10, 0.9, 0.01 }
3 { return 15, 0.9, 0.01 }
4 { return 36, 0.8, 0.3 }
5 { return 63, 0.4, 0.01 }
else {}
}
}
4 {
match disease_symptom {
0 { return 2, 1.0, 0.01 }
1 { return 6, 0.9, 0.01 }
2 { return 7, 0.9, 0.01 }
3 { return 14, 1.0, 0.01 }
4 { return 15, 0.7, 0.01 }
5 { return 18, 0.0, 0.5 }
6 { return 33, 0.0, 0.01 }
7 { return 63, 0.8, 0.01 }
else {}
}
}
5 {
match disease_symptom {
0 { return 0, 0.9, 0.01 }
1 { return 2, 0.9, 0.01 }
2 { return 5, 0.5, 0.01 }
3 { return 6, 0.7, 0.01 }
4 { return 7, 1.0, 0.01 }
5 { return 14, 1.0, 0.01 }
6 { return 16, 0.8, 0.01 }
7 { return 17, 0.6, 0.01 }
8 { return 33, 0.0, 0.01 }
else {}
}
}
6 {
match disease_symptom {
0 { return 3, 1.0, 0.01 }
1 { return 4, 0.9, 0.01 }
2 { return 7, 0.6, 0.01 }
3 { return 14, 0.05, 0.01 }
4 { return 15, 0.7, 0.01 }
5 { return 36, 0.8, 0.3 }
6 { return 20, 0.1, 0.01 }
else {}
}
}
7 {
match disease_symptom {
0 { return 3, 1.0, 0.01 }
1 { return 33, 0.99, 0.01 }
2 { return 36, 0.8, 0.3 }
else {}
}
}
8 {
match disease_symptom {
0 { return 4, 1.0, 0.01 }
1 { return 7, 1.0, 0.01 }
2 { return 11, 1.0, 0.01 }
3 { return 14, 1.0, 0.01 }
4 { return 17, 0.5, 0.01 }
5 { return 20, 1.0, 0.01 }
6 { return 21, 0.9, 0.01 }
7 { return 30, 0.9, 0.01 }
8 { return 33, 0.0, 0.01 }
else {}
}
}
9 {
match disease_symptom {
0 { return 4, 1.0, 0.01 }
1 { return 11, 0.9, 0.01 }
2 { return 13, 0.5, 0.01 }
3 { return 20, 1.0, 0.01 }
4 { return 21, 0.8, 0.01 }
5 { return 33, 1.0, 0.01 }
6 { return 35, 0.9, 0.01 }
7 { return 36, 0.8, 0.3 }
else {}
}
}
10 {
match disease_symptom {
0 { return 11, 0.8, 0.01 }
1 { return 21, 1.0, 0.01 }
2 { return 22, 0.5, 0.01 }
3 { return 23, 0.5, 0.01 }
4 { return 24, 0.5, 0.01 }
5 { return 25, 0.5, 0.01 }
6 { return 30, 0.8, 0.01 }
else {}
}
}
11 {
match disease_symptom {
0 { return 4, 0.6, 0.01 }
1 { return 11, 0.6, 0.01 }
2 { return 20, 0.6, 0.01 }
3 { return 21, 1.0, 0.01 }
4 { return 25, 0.8, 0.01 }
5 { return 36, 0.8, 0.3 }
else {}
}
}
12 {
match disease_symptom {
0 { return 7, 1.0, 0.01 }
1 { return 14, 1.0, 0.01 }
2 { return 16, 0.9, 0.01 }
3 { return 17, 0.8, 0.01 }
4 { return 21, 1.0, 0.01 }
5 { return 22, 0.5, 0.01 }
6 { return 25, 0.5, 0.01 }
7 { return 26, 0.2, 0.01 }
8 { return 27, 0.1, 0.01 }
9 { return 28, 0.02, 0.01 }
10 { return 30, 0.9, 0.01 }
11 { return 31, 0.5, 0.005 }
12 { return 35, 0.1, 0.9 }
else {}
}
}
13 {
match disease_symptom {
0 { return 4, 0.8, 0.01 }
1 { return 7, 0.9, 0.01 }
2 { return 14, 1.0, 0.01 }
3 { return 21, 0.5, 0.01 }
4 { return 30, 0.8, 0.01 }
5 { return 31, 0.8, 0.01 }
6 { return 33, 0.0, 0.01 }
else {}
}
}
14 {
match disease_symptom {
0 { return 17, 0.8, 0.01 }
1 { return 21, 0.8, 0.01 }
2 { return 31, 0.8, 0.005 }
else {}
}
}
15 {
match disease_symptom {
0 { return 4, 1.0, 0.01 }
1 { return 13, 0.5, 0.01 }
2 { return 20, 1.0, 0.01 }
3 { return 26, 0.5, 0.01 }
else {}
}
}
16 {
match disease_symptom {
0 { return 17, 0.5, 0.01 }
1 { return 20, 0.5, 0.01 }
2 { return 26, 0.5, 0.01 }
3 { return 32, 0.9, 0.01 }
else {}
}
}
17 {
match disease_symptom {
0 { return 8, 1.0, 0.01 }
1 { return 20, 0.8, 0.01 }
2 { return 21, 1.0, 0.01 }
3 { return 35, 1.0, 0.01 }
else {}
}
}
18 {
match disease_symptom {
0 { return 4, 1.0, 0.01 }
1 { return 11, 0.5, 0.01 }
2 { return 17, 0.8, 0.01 }
3 { return 20, 0.8, 0.01 }
4 { return 21, 0.5, 0.01 }
5 { return 26, 0.5, 0.01 }
6 { return 36, 0.99, 0.3 }
else {}
}
}
19 {
match disease_symptom {
0 { return 20, 0.6, 0.01 }
1 { return 21, 0.8, 0.01 }
2 { return 34, 0.8, 0.01 }
else {}
}
}
20 {
match disease_symptom {
0 { return 11, 0.8, 0.01 }
1 { return 21, 0.9, 0.01 }
2 { return 24, 0.9, 0.01 }
3 { return 25, 0.5, 0.01 }
4 { return 26, 0.5, 0.01 }
5 { return 29, 0.5, 0.01 }
else {}
}
}
21 {
match disease_symptom {
0 { return 7, 0.4, 0.01 }
1 { return 36, 0.9, 0.5 }
2 { return 40, 0.01, 0.8 }
3 { return 42, 0.8, 0.01 }
4 { return 41, 0.5, 0.01 }
else {}
}
}
22 {
match disease_symptom {
0 { return 15, 0.9, 0.01 }
1 { return 17, 0.9, 0.01 }
2 { return 31, 0.5, 0.005 }
3 { return 40, 0.8, 0.01 }
4 { return 41, 0.8, 0.005 }
5 { return 56, 0.9, 0.01 }
else {}
}
}
23 {
match disease_symptom {
0 { return 36, 0.8, 0.2 }
1 { return 40, 0.8, 0.01 }
2 { return 41, 0.99, 0.005 }
3 { return 56, 0.7, 0.01 }
else {}
}
}
24 {
match disease_symptom {
0 { return 19, 0.8, 0.01 }
1 { return 40, 0.7, 0.01 }
2 { return 41, 0.9, 0.005 }
3 { return 45, 0.5, 0.01 }
4 { return 55, 0.9, 0.01 }
5 { return 61, 0.0001, 0.01 }
else {}
}
}
25 {
match disease_symptom {
0 { return 7, 0.5, 0.01 }
1 { return 40, 0.5, 0.01 }
2 { return 41, 0.6, 0.005 }
3 { return 42, 0.5, 0.01 }
4 { return 55, 0.8, 0.01 }
else {}
}
}
26 {
match disease_symptom {
0 { return 7, 0.3, 0.01 }
1 { return 22, 0.3, 0.01 }
2 { return 40, 0.3, 0.01 }
3 { return 41, 0.9, 0.005 }
4 { return 42, 0.7, 0.01 }
else {}
}
}
27 {
match disease_symptom {
0 { return 7, 0.7, 0.01 }
1 { return 14, 0.9, 0.01 }
2 { return 41, 0.9, 0.005 }
3 { return 42, 0.9, 0.01 }
4 { return 61, 0.00001, 0.01 }
else {}
}
}
28 {
match disease_symptom {
0 { return 40, 0.5, 0.01 }
1 { return 41, 0.9, 0.005 }
2 { return 42, 0.8, 0.01 }
else {}
}
}
29 {
match disease_symptom {
0 { return 7, 0.8, 0.01 }
1 { return 33, 0.1, 0.9 }
2 { return 40, 0.8, 0.01 }
3 { return 41, 0.9, 0.005 }
4 { return 43, 0.0, 0.5 }
else {}
}
}
30 {
match disease_symptom {
0 { return 6, 0.8, 0.01 }
1 { return 40, 0.9, 0.01 }
2 { return 41, 0.5, 0.005 }
3 { return 42, 0.9, 0.01 }
else {}
}
}
31 {
match disease_symptom {
0 { return 7, 0.5, 0.01 }
1 { return 40, 0.8, 0.01 }
2 { return 41, 0.7, 0.005 }
3 { return 42, 0.9, 0.01 }
else {}
}
}
32 {
match disease_symptom {
0 { return 41, 0.7, 0.005 }
else {}
}
}
33 {
match disease_symptom {
0 { return 7, 0.8, 0.01 }
1 { return 40, 0.7, 0.01 }
2 { return 41, 0.9, 0.005 }
3 { return 66, 0.9, 0.01 }
else {}
}
}
34 {
match disease_symptom {
0 { return 40, 0.5, 0.01 }
1 { return 41, 0.5, 0.005 }
2 { return 56, 0.9, 0.01 }
else {}
}
}
35 {
match disease_symptom {
0 { return 7, 0.9, 0.01 }
1 { return 40, 0.8, 0.01 }
2 { return 41, 0.8, 0.005 }
3 { return 44, 0.8, 0.001 }
else {}
}
}
36 {
match disease_symptom {
0 { return 1, 0.6, 0.01 }
1 { return 7, 0.5, 0.01 }
2 { return 13, 0.8, 0.01 }
3 { return 17, 0.5, 0.01 }
4 { return 58, 0.9, 0.01 }
5 { return 59, 0.9, 0.01 }
else {}
}
}
37 {
match disease_symptom {
0 { return 39, 0.8, 0.01 }
else {}
}
}
38 {
match disease_symptom {
0 { return 14, 0.8, 0.01 }
1 { return 16, 0.8, 0.01 }
2 { return 39, 0.5, 0.001 }
else {}
}
}
39 {
match disease_symptom {
0 { return 11, 0.6, 0.01 }
1 { return 17, 0.5, 0.01 }
2 { return 21, 0.9, 0.01 }
3 { return 24, 0.5, 0.001 }
4 { return 25, 0.3, 0.001 }
5 { return 31, 0.3, 0.001 }
6 { return 35, 0.5, 0.01 }
7 { return 38, 0.5, 0.01 }
8 { return 41, 0.5, 0.01 }
9 { return 46, 0.9, 0.01 }
else {}
}
}
40 {
match disease_symptom {
0 { return 6, 0.5, 0.01 }
1 { return 14, 0.5, 0.01 }
2 { return 15, 0.3, 0.01 }
3 { return 21, 0.5, 0.01 }
4 { return 22, 0.6, 0.01 }
5 { return 27, 0.3, 0.01 }
6 { return 37, 0.5, 0.01 }
7 { return 38, 0.8, 0.01 }
8 { return 42, 0.2, 0.01 }
9 { return 45, 0.9, 0.01 }
10 { return 46, 0.6, 0.01 }
11 { return 47, 0.6, 0.01 }
12 { return 49, 0.5, 0.01 }
13 { return 56, 0.5, 0.01 }
14 { return 57, 0.5, 0.01 }
else {}
}
}
41 {
match disease_symptom {
0 { return 6, 0.5, 0.01 }
1 { return 14, 0.5, 0.01 }
2 { return 46, 0.5, 0.01 }
3 { return 48, 0.5, 0.01 }
4 { return 49, 0.5, 0.01 }
5 { return 61, 0.8, 0.01 }
else {}
}
}
42 {
match disease_symptom {
0 { return 14, 0.9, 0.01 }
1 { return 17, 0.5, 0.01 }
2 { return 19, 0.5, 0.01 }
3 { return 21, 0.5, 0.01 }
4 { return 22, 0.5, 0.01 }
5 { return 31, 0.9, 0.001 }
6 { return 35, 0.0, 0.2 }
7 { return 37, 0.5, 0.01 }
8 { return 40, 0.5, 0.01 }
else {}
}
}
43 {
match disease_symptom {
0 { return 17, 0.9, 0.01 }
1 { return 19, 0.9, 0.01 }
2 { return 21, 0.5, 0.01 }
3 { return 22, 0.5, 0.01 }
4 { return 31, 1.0, 0.001 }
5 { return 35, 0.9, 0.01 }
6 { return 36, 0.8, 0.3 }
7 { return 37, 0.5, 0.01 }
else {}
}
}
44 {
match disease_symptom {
0 { return 17, 0.7, 0.01 }
1 { return 20, 0.6, 0.01 }
2 { return 21, 1.0, 0.01 }
3 { return 24, 0.5, 0.001 }
4 { return 25, 0.4, 0.001 }
5 { return 26, 0.5, 0.001 }
else {}
}
}
45 {
match disease_symptom {
0 { return 27, 0.8, 0.01 }
1 { return 37, 0.7, 0.01 }
2 { return 50, 0.8, 0.001 }
3 { return 57, 0.9, 0.01 }
4 { return 60, 0.9, 0.01 }
else {}
}
}
46 {
match disease_symptom {
0 { return 19, 0.5, 0.01 }
1 { return 27, 0.8, 0.01 }
2 { return 33, 0.0, 0.01 }
3 { return 37, 0.7, 0.01 }
4 { return 50, 0.8, 0.001 }
5 { return 57, 0.9, 0.01 }
6 { return 60, 0.9, 0.01 }
else {}
}
}
47 {
match disease_symptom {
0 { return 4, 0.5, 0.01 }
1 { return 6, 0.5, 0.01 }
2 { return 7, 0.5, 0.01 }
3 { return 11, 0.5, 0.01 }
4 { return 14, 0.5, 0.01 }
5 { return 17, 0.5, 0.01 }
6 { return 21, 0.5, 0.01 }
7 { return 22, 0.5, 0.01 }
8 { return 26, 0.5, 0.001 }
9 { return 29, 0.5, 0.01 }
10 { return 61, 0.0001, 0.01 }
else {}
}
}
48 {
match disease_symptom {
0 { return 48, 0.8, 0.01 }
1 { return 51, 0.9, 0.001 }
2 { return 55, 0.9, 0.01 }
3 { return 58, 0.5, 0.01 }
else {}
}
}
49 {
match disease_symptom {
0 { return 3, 0.5, 0.01 }
1 { return 16, 0.5, 0.01 }
2 { return 22, 0.001, 0.01 }
3 { return 23, 0.0, 0.01 }
4 { return 38, 0.001, 0.01 }
5 { return 42, 0.0, 0.01 }
6 { return 45, 0.001, 0.01 }
7 { return 47, 0.001, 0.01 }
8 { return 48, 0.8, 0.01 }
9 { return 61, 0.9, 0.05 }
else {}
}
}
50 {
match disease_symptom {
0 { return 40, 0.3, 0.01 }
1 { return 41, 0.8, 0.001 }
2 { return 42, 0.5, 0.01 }
3 { return 48, 0.5, 0.01 }
4 { return 55, 0.5, 0.01 }
5 { return 56, 0.9, 0.01 }
else {}
}
}
51 {
match disease_symptom {
0 { return 41, 0.5, 0.005 }
1 { return 42, 0.9, 0.01 }
2 { return 48, 0.9, 0.01 }
3 { return 51, 0.5, 0.001 }
4 { return 55, 0.9, 0.01 }
5 { return 61, 0.0001, 0.01 }
else {}
}
}
52 {
match disease_symptom {
0 { return 7, 0.5, 0.01 }
1 { return 22, 0.5, 0.01 }
2 { return 33, 0.4, 0.01 }
3 { return 40, 0.5, 0.01 }
4 { return 41, 0.8, 0.005 }
5 { return 42, 0.8, 0.01 }
6 { return 51, 0.6, 0.001 }
7 { return 55, 0.9, 0.01 }
else {}
}
}
53 {
match disease_symptom {
0 { return 19, 0.9, 0.01 }
1 { return 33, 0.5, 0.01 }
2 { return 37, 0.9, 0.001 }
3 { return 40, 0.8, 0.01 }
else {}
}
}
54 {
match disease_symptom {
0 { return 6, 0.5, 0.01 }
1 { return 37, 0.5, 0.01 }
2 { return 53, 0.9, 0.01 }
3 { return 57, 0.9, 0.01 }
4 { return 60, 0.5, 0.01 }
else {}
}
}
55 {
match disease_symptom {
0 { return 6, 0.9, 0.01 }
1 { return 19, 0.5, 0.01 }
2 { return 27, 0.9, 0.001 }
3 { return 33, 0.5, 0.01 }
4 { return 37, 0.9, 0.01 }
5 { return 40, 0.9, 0.01 }
6 { return 54, 0.99, 0.001 }
else {}
}
}
56 {
match disease_symptom {
0 { return 6, 0.9, 0.01 }
1 { return 33, 0.5, 0.01 }
2 { return 37, 0.8, 0.01 }
3 { return 40, 0.9, 0.01 }
4 { return 49, 0.8, 0.01 }
else {}
}
}
57 {
match disease_symptom {
0 { return 1, 0.9, 0.01 }
1 { return 6, 0.9, 0.01 }
2 { return 7, 0.9, 0.01 }
3 { return 27, 0.7, 0.01 }
4 { return 40, 0.9, 0.01 }
5 { return 53, 0.9, 0.01 }
6 { return 59, 0.5, 0.01 }
else {}
}
}
58 {
match disease_symptom {
0 { return 1, 0.8, 0.01 }
1 { return 6, 0.99, 0.01 }
2 { return 27, 0.7, 0.01 }
3 { return 37, 0.7, 0.01 }
4 { return 40, 0.8, 0.01 }
5 { return 53, 0.9, 0.01 }
else {}
}
}
59 {
match disease_symptom {
0 { return 1, 0.9, 0.01 }
1 { return 6, 0.9, 0.01 }
2 { return 19, 0.8, 0.01 }
3 { return 33, 0.8, 0.01 }
4 { return 40, 0.7, 0.01 }
5 { return 62, 0.9, 0.01 }
6 { return 67, 0.9, 0.01 }
else {}
}
}
60 {
match disease_symptom {
0 { return 6, 0.9, 0.01 }
1 { return 7, 0.7, 0.01 }
2 { return 16, 0.7, 0.01 }
3 { return 22, 0.8, 0.01 }
4 { return 62, 0.99, 0.01 }
else {}
}
}
61 {
match disease_symptom {
0 { return 6, 0.7, 0.01 }
1 { return 19, 0.9, 0.01 }
2 { return 40, 0.7, 0.01 }
3 { return 41, 0.7, 0.01 }
4 { return 56, 0.7, 0.01 }
5 { return 61, 0.001, 0.01 }
else {}
}
}
62 {
match disease_symptom {
0 { return 17, 0.6, 0.01 }
1 { return 21, 0.5, 0.01 }
2 { return 38, 0.6, 0.01 }
3 { return 57, 0.8, 0.01 }
else {}
}
}
63 {
match disease_symptom {
0 { return 21, 0.9, 0.01 }
1 { return 27, 0.4, 0.01 }
2 { return 35, 0.9, 0.01 }
3 { return 38, 0.9, 0.01 }
4 { return 41, 0.5, 0.01 }
5 { return 44, 0.5, 0.01 }
6 { return 49, 0.5, 0.01 }
7 { return 57, 0.9, 0.01 }
else {}
}
}
64 {
match disease_symptom {
0 { return 1, 0.9, 0.01 }
1 { return 6, 1.0, 0.01 }
2 { return 14, 0.9, 0.01 }
3 { return 19, 0.9, 0.01 }
4 { return 33, 0.9, 0.01 }
5 { return 40, 0.9, 0.01 }
6 { return 42, 0.5, 0.01 }
7 { return 62, 0.99, 0.01 }
else {}
}
}
65 {
match disease_symptom {
0 { return 6, 0.5, 0.01 }
1 { return 14, 0.9, 0.01 }
2 { return 33, 0.9, 0.01 }
3 { return 38, 0.5, 0.01 }
else {}
}
}
66 {
match disease_symptom {
0 { return 58, 0.9, 0.01 }
1 { return 59, 0.1, 0.01 }
else {}
}
}
67 {
match disease_symptom {
0 { return 45, 0.5, 0.01 }
1 { return 58, 0.9, 0.01 }
2 { return 59, 1.0, 0.01 }
else {}
}
}
68 {
match disease_symptom {
0 { return 58, 1.0, 0.01 }
1 { return 59, 1.0, 0.01 }
else {}
}
}
69 {
match disease_symptom {
0 { return 1, 0.9, 0.01 }
1 { return 4, 0.9, 0.01 }
2 { return 5, 0.9, 0.01 }
3 { return 6, 0.5, 0.01 }
4 { return 7, 1.0, 0.01 }
5 { return 10, 0.9, 0.01 }
6 { return 14, 1.0, 0.01 }
7 { return 33, 0.0, 0.01 }
8 { return 42, 0.5, 0.01 }
9 { return 59, 1.0, 0.01 }
else {}
}
}
70 {
match disease_symptom {
0 { return 7, 0.5, 0.01 }
1 { return 33, 0.0, 0.01 }
2 { return 53, 0.2, 0.01 }
3 { return 59, 0.9, 0.01 }
4 { return 63, 0.5, 0.01 }
else {}
}
}
71 {
match disease_symptom {
0 { return 6, 0.5, 0.01 }
1 { return 7, 0.8, 0.01 }
2 { return 14, 0.5, 0.01 }
3 { return 33, 0.0, 0.01 }
4 { return 58, 1.0, 0.01 }
5 { return 59, 1.0, 0.01 }
else {}
}
}
72 {
match disease_symptom {
0 { return 2, 0.5, 0.01 }
1 { return 45, 0.6, 0.01 }
2 { return 58, 0.5, 0.01 }
3 { return 59, 0.99, 0.01 }
else {}
}
}
73 {
match disease_symptom {
0 { return 33, 0.5, 0.01 }
1 { return 58, 0.9, 0.01 }
2 { return 59, 1.0, 0.01 }
else {}
}
}
74 {
match disease_symptom {
0 { return 1, 0.5, 0.01 }
1 { return 33, 0.8, 0.01 }
2 { return 59, 0.9, 0.01 }
else {}
}
}
75 {
match disease_symptom {
0 { return 1, 0.5, 0.01 }
1 { return 21, 0.8, 0.01 }
2 { return 22, 0.9, 0.01 }
3 { return 23, 0.9, 0.01 }
4 { return 38, 0.9, 0.01 }
5 { return 42, 0.8, 0.01 }
6 { return 45, 0.9, 0.01 }
7 { return 46, 0.8, 0.01 }
8 { return 47, 0.9, 0.01 }
9 { return 61, 0.00001, 0.01 }
10 { return 63, 0.3, 0.01 }
11 { return 67, 0.3, 0.01 }
else {}
}
}
76 {
match disease_symptom {
0 { return 1, 0.5, 0.01 }
1 { return 60, 0.5, 0.01 }
2 { return 61, 0.0001, 0.01 }
3 { return 65, 0.99, 0.01 }
4 { return 67, 1.0, 0.01 }
else {}
}
}
77 {
match disease_symptom {
0 { return 40, 0.5, 0.01 }
1 { return 41, 0.7, 0.005 }
2 { return 51, 0.6, 0.001 }
3 { return 55, 0.5, 0.01 }
4 { return 61, 0.0001, 0.01 }
else {}
}
}
78 {
match disease_symptom {
0 { return 19, 0.4, 0.01 }
1 { return 37, 0.5, 0.01 }
2 { return 38, 0.8, 0.01 }
3 { return 57, 0.5, 0.01 }
else {}
}
}
79 {
match disease_symptom {
0 { return 22, 0.5, 0.01 }
1 { return 53, 0.8, 0.01 }
2 { return 58, 0.7, 0.01 }
3 { return 62, 0.6, 0.01 }
4 { return 63, 0.99, 0.01 }
else {}
}
}
80 {
match disease_symptom {
0 { return 2, 0.9, 0.01 }
1 { return 6, 0.9, 0.01 }
2 { return 7, 0.9, 0.01 }
3 { return 14, 0.9, 0.01 }
4 { return 44, 0.5, 0.001 }
5 { return 53, 0.8, 0.01 }
6 { return 59, 0.5, 0.01 }
7 { return 63, 0.8, 0.01 }
else {}
}
}
81 {
match disease_symptom {
0 { return 7, 0.8, 0.01 }
1 { return 14, 0.8, 0.01 }
2 { return 22, 0.5, 0.01 }
3 { return 53, 0.8, 0.01 }
4 { return 58, 0.8, 0.01 }
5 { return 61, 0.001, 0.01 }
6 { return 63, 0.9, 0.01 }
else {}
}
}
82 {
match disease_symptom {
0 { return 2, 0.8, 0.01 }
1 { return 7, 0.8, 0.01 }
2 { return 14, 0.9, 0.01 }
3 { return 15, 0.7, 0.01 }
4 { return 53, 0.6, 0.01 }
5 { return 63, 0.99, 0.01 }
else {}
}
}
83 {
match disease_symptom {
0 { return 1, 0.9, 0.01 }
1 { return 50, 0.9, 0.01 }
2 { return 62, 0.5, 0.01 }
else {}
}
}
84 {
match disease_symptom {
0 { return 27, 0.2, 0.01 }
1 { return 33, 1.0, 0.01 }
2 { return 47, 0.9, 0.01 }
3 { return 49, 0.2, 0.01 }
4 { return 50, 0.8, 0.01 }
5 { return 52, 0.8, 0.5 }
else {}
}
}
85 {
match disease_symptom {
0 { return 6, 0.8, 0.01 }
1 { return 7, 0.8, 0.01 }
2 { return 14, 0.8, 0.01 }
3 { return 47, 0.1, 0.01 }
4 { return 58, 0.001, 0.01 }
5 { return 59, 0.5, 0.01 }
6 { return 63, 0.8, 0.01 }
else {}
}
}
86 {
match disease_symptom {
0 { return 7, 0.5, 0.01 }
1 { return 64, 0.9, 0.01 }
2 { return 65, 0.9, 0.01 }
3 { return 66, 0.9, 0.01 }
else {}
}
}
87 {
match disease_symptom {
0 { return 7, 0.6, 0.01 }
1 { return 40, 0.5, 0.01 }
2 { return 41, 0.5, 0.01 }
3 { return 61, 0.0001, 0.01 }
4 { return 64, 0.7, 0.01 }
else {}
}
}
88 {
match disease_symptom {
0 { return 7, 0.3, 0.01 }
1 { return 41, 0.5, 0.01 }
2 { return 64, 0.9, 0.01 }
3 { return 65, 0.5, 0.01 }
4 { return 66, 0.5, 0.01 }
else {}
}
}
89 {
match disease_symptom {
0 { return 1, 0.9, 0.01 }
1 { return 67, 0.9, 0.01 }
else {}
}
}
90 {
match disease_symptom {
0 { return 7, 0.8, 0.01 }
1 { return 14, 0.8, 0.01 }
2 { return 16, 0.5, 0.01 }
3 { return 40, 0.5, 0.01 }
4 { return 41, 0.5, 0.01 }
5 { return 44, 0.5, 0.01 }
else {}
}
}
else {}
}
return none
}
// Return the question about the given symptom.
fn question(symptom int) string {
match symptom {
0 { return '¿Estornudas mucho?' }
1 { return '¿Te duelen los ojos, o lagrimeas mucho?' }
2 { return '¿Te duele la garganta?' }
3 { return '¿Tienes ronquera o afonía?' }
4 { return '¿Toses mucho?' }
5 { return '¿Tienes mucosidad nasal muy fluida?' }
6 { return '¿Te duele la cabeza, o sufres, en general, de dolores de cabeza?' }
7 { return '¿Tienes alta temperatura (superior a 37 grados centígrados)?' }
8 { return '¿Te ves obligado, por tu trabajo, a pasar muchas horas respirando aire viciado o polvoriento?' }
9 { return '¿Te pica la nariz?' }
10 { return '¿Tienes la garganta reseca?' }
11 { return '¿Respiras con dificultad y fatiga?' }
12 { return '¿Tienes la nariz muy taponada?' }
13 { return '¿Has tenido recientemente un resfriado u otra infección similar?' }
14 { return '¿Tienes malestar general?' }
15 { return '¿Tienes dificultad para tragar?' }
16 { return '¿Tienes dolores musculares?' }
17 { return '¿Sientes cualquier tipo de dolor en el pecho?' }
18 { return '¿Te han extirpado las amigdalas?' }
19 { return '¿Tus síntomas tienden a aparecer en ataques, y no a estar presentes continuamente?' }
20 { return '¿Tienes una tos productiva, o sea una tos en la que expulsas algo?' }
21 { return '¿Respiras entrecortadamente?' }
22 { return '¿Sudas mucho? (No ya cuando haces un esfuerzo, sino cuando estás físicamente relajado).' }
23 { return '¿Tienes la frecuencia cardiaca elevada? (Normalmente debe estar entre 60 y 80 pulsaciones por minuto, y algo más rápida para personas de edad superior a 70 o inferior a 20).' }
24 { return '¿Sufres ataques de dificultades respiratorias tan fuertes que llegan a preocuparte?' }
25 { return '¿Tienes cianosis, es decir, se te ha puesto la piel de un color ligeramente azulado?' }
26 { return '¿Cuando toses, presentan sangre los esputos?' }
27 { return '¿Estás aturdido o perplejo sobre cuanto acontece a tu alrededor?' }
28 { return '¿Estás (o está el paciente) en estado delirante, hablando incoherentemente y con mala coordinación muscular?' }
29 { return '¿Tienes una tos seca (no productiva)?' }
30 { return '¿Sientes dolor al respirar o al toser?' }
31 { return '¿Has sentido en estos días un dolor muy fuerte en el pecho?' }
32 { return '¿Tienes sensaciones alternantes de frío y calor?' }
33 { return '¿Hace ya tiempo (seis semanas o más) que presentas alguno de estos síntomas?' }
34 { return '¿Tienes los dedos hipocráticos, o en «palillos de tambor»? (Se llaman así cuando las cutículas casi han desaparecido, y las uñas se abomban excesivamente hacia la punta).' }
35 { return '¿Tienes síntomas que aparecen fundamentalmente al realizar algún esfuerzo?' }
36 { return '¿Fumas? responde con el número que resulta de dividir por cinco el número de cigarrillos diarios. El número máximo para la respuesta es 5. Si no fumas, responde -5.' }
37 { return '¿Tienes sensaciones de vértigo?' }
38 { return '¿Tienes palpitaciones (sensación de que el corazón late más fuerte, o más rápido, o menos regularmente de lo que debiera)?' }
39 { return '¿Tienes algún tobillo excesivamente hinchado?' }
40 { return '¿Tienes vómitos, o fuertes náuseas?' }
41 { return '¿Sufres de algún tipo de dolor abdominal, o dolor localizado entre las costillas inferiores y las ingles?' }
42 { return '¿Padeces diarrea, o sueles tener crisis de diarrea?' }
43 { return '¿Te han extirpado el apéndice?' }
44 { return '¿Tienes ictericia? (La ictericia no es una enfermedad, sino un síntoma. Con frecuencia es más patente en los ojos: la parte blanca se torna amarillenta).' }
45 { return '¿Te sientes tenso o inquieto?' }
46 { return '¿Te cuesta conciliar el sueño, o te desvelas frecuentemente por la noche?' }
47 { return '¿Tienes contracciones involuntarias o temblores?' }
48 { return '¿Sufres de estreñimiento, o sueles tener crisis de estreñimiento?' }
49 { return '¿Te falla la memoria, tienes dificultad para recordar hechos aislados, ya sea ocasional o regularmente?' }
50 { return '¿Sufres afasia, es decir, has perdido capacidad para expresarte con palabras?' }
51 { return '¿Has tenido alguna hemorragia por el recto?' }
52 { return '¿Eres hombre o mujer? Responde con 5 para hombre y -5 para mujer. Una respuesta 0 hace que el diagnóstico sea independiente del sexo.' }
53 { return '¿Tienes rigidez o dolor en el cuello?' }
54 { return '¿Has sufrido algún golpe o herida de cualquier tipo en la cabeza durante las últimas semanas? (Un golpe incluso leve puede ser importante).' }
55 { return '¿Has expulsado recientemente heces de aspecto anormal?' }
56 { return '¿Expulsas muchos gases, por cualquier vía?' }
57 { return '¿Tienes sensaciones repentinas de desmayo, es decir, de sentirte desfallecido y mareado, incluso, quizás con pérdida de consciencia?' }
58 { return '¿Te pica alguna parte del cuerpo, tengas o no erupción en ella?' }
59 { return '¿Tienes alguna erupción o lesión de cualquier tipo en la piel?' }
60 { return '¿Tienes alguna parte del cuerpo entumecida, o con sensación de comezón u hormigueo, como de «agujas y alfileres»?' }
61 { return '¿Es tu peso anormal? Responde con 5 para un peso excesivamente elevado, con -5 si es excesivamente bajo y con 0 si es normal.' }
62 { return '¿Sufres de algún dolor en la cara o en la frente?' }
63 { return '¿Tienes algún bulto, hinchazón o abultamiento, en cualquier parte del cuerpo?' }
64 { return '¿Es anormal el color de tu orina?' }
65 { return '¿Orinas con una frecuencia anormal?' }
66 { return '¿Tienes dolores al orinar?' }
67 { return '¿Tienes alguna anormalidad en la visión, como ver borroso o doble, o luces destelleantes? (No cuentan los defectos que pueden corregirse con gafas).' }
else {}
}
return ''
}
// user_input.v
//
// This file is part of Experto en enfermedades (Expert on diseases)
// Last modified 20250812T1907+0200.
/*
Copyright (C) 1985, Chris Naylor: Sinclair BASIC code included in his book
"Build Your Own Expert System" (Sigma Press, 1985).
Copyright (C) 1988, 1989, Marcos Cruz (programandala.net): SuperBASIC version
(http:///programandala.net/es.programa.sistema_experto_sobre_enfermedades.html).
Copyright (C) 2023, 2024, Marcos Cruz (programandala.net): Odin version.
Copyright (C) 2024, 2025, Marcos Cruz (programandala.net): SBASIC version.
Copyright (C) 2025, Marcos Cruz (programandala.net): V version.
This program is licensed under a BSD 2-Clause License
(https://opensource.org/license/bsd-2-clause/). See the <LICENSE.txt> file.
*/
// ==========================================================================
import os
import rand
import strconv
const prompt = '> '
fn user_input_string() string {
print(prompt)
return os.input('')
}
fn print_menu() {
if debug_level == 0 {
println('Comandos:') // XXX TODO par.whole
} else {
println('Comandos principales:') // XXX TODO par.whole
}
println('- Consultar') // XXX TODO par.whole
println('- Finalizar') // XXX TODO par.whole
if debug_level > 0 {
println('Comandos para depuración:') // XXX TODO par.whole
println('- Probar (modo automático con respuestas aleatorias)') // XXX TODO par.whole
unsafe {
println(strconv.v_sprintf('- Número de ${min_answer} a ${max_answer} (modo automático con respuesta única)')) // XXX TODO par.whole
}
}
}
// Ask the user for permission to start a new consult; return `true` for yes
// and `false` for no.
fn ready() bool {
for {
print_menu()
mut answer := user_input_string().to_lower()
match true {
answer.starts_with('consultar') {
mode = .normal_mode
return true
}
answer.starts_with('finalizar') {
return false
}
answer.starts_with('probar') {
if debug_level > 0 {
mode = .random_demo_mode
return true
}
}
else {
demo_value = valid_answer(answer) or { continue }
mode = .value_demo_mode
return true
}
}
}
return false
}
fn press_enter() {
println('')
println('Pulsa la tecla «intro» para empezar.') // XXX TODO par.whole
user_input_string()
}
// Check the given user answer string; if it is valid, return its numerical
// value; otherwise return an error.
fn valid_answer(answer string) !int {
match answer.len {
1 {
if !'012345'.contains(answer) {
return error('Formato de número incorrecto o no en el rango permitido.')
}
}
2 {
if !'+-'.contains(answer.substr(0, 1)) {
return error('Formato de número incorrecto.')
}
if !'012345'.contains(answer.substr(1, 1)) {
return error('Formato de número incorrecto o no en el rango permitido.')
}
}
else {
return error('Formato de número incorrecto.')
}
}
return strconv.atoi(answer)
}
// Prompt the user for a valid answer, check it and return it.
fn user_answer() int {
mut answer_value := 0
for {
unsafe {
println(strconv.v_sprintf('Responde con un número de ${min_answer} a ${max_answer}:')) // XXX TODO par.whole
println(strconv.v_sprintf('${min_answer} (no, nunca) … 0 … ${max_answer} (sí, siempre)')) // XXX TODO par.whole
}
answer_value = valid_answer(user_input_string()) or {
println(err)
continue
}
break
}
return answer_value
}
// Return a random number in the range `min_answer ... max_answer`.
fn random_answer() int {
return rand.intn(max_answer - min_answer + 1) or { 0 } + min_answer
}
// VERSION.v
//
// This file is part of Experto en enfermedades (Expert on diseases)
// Last modified 20250812T1908+0200.
/*
Copyright (C) 1985, Chris Naylor: Sinclair BASIC code included in his book
"Build Your Own Expert System" (Sigma Press, 1985).
Copyright (C) 1988, 1989, Marcos Cruz (programandala.net): SuperBASIC version
(http:///programandala.net/es.programa.sistema_experto_sobre_enfermedades.html).
Copyright (C) 2023, 2024, Marcos Cruz (programandala.net): Odin version.
Copyright (C) 2024, 2025, Marcos Cruz (programandala.net): SBASIC version.
Copyright (C) 2025, Marcos Cruz (programandala.net): V version.
This program is licensed under a BSD 2-Clause License
(https://opensource.org/license/bsd-2-clause/). See the <LICENSE.txt> file.
*/
// ==========================================================================
const version = '0.1.0-dev.0.28.2+20250626T0104CEST'
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