ironcalc_base 0.7.1

Open source spreadsheet engine
Documentation 
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

#![allow(clippy::unwrap_used)]

use crate::test::util::new_empty_model;

#[test]
fn test_fn_t_dist_smoke() {
    let mut model = new_empty_model();

    // Valid: cumulative (left-tail CDF)
    model._set("A1", "=T.DIST(2, 10, TRUE)");
    // Valid: probability density function (PDF)
    model._set("B1", "=T.DIST(2, 10, FALSE)");

    // Wrong number of arguments
    model._set("A2", "=T.DIST(2, 10)");
    model._set("A3", "=T.DIST(2, 10, TRUE, FALSE)");

    // Domain error: df < 1 -> #NUM!
    model._set("A4", "=T.DIST(2, 0, TRUE)");
    model._set("A5", "=T.DIST(2, -1, TRUE)");

    model.evaluate();

    assert_eq!(model._get_text("A1"), *"0.963305983");
    assert_eq!(model._get_text("B1"), *"0.061145766");

    assert_eq!(model._get_text("A2"), *"#ERROR!");
    assert_eq!(model._get_text("A3"), *"#ERROR!");
    assert_eq!(model._get_text("A4"), *"#NUM!");
    assert_eq!(model._get_text("A5"), *"#NUM!");
}

#[test]
fn test_fn_t_dist_rt_smoke() {
    let mut model = new_empty_model();

    // Valid: right tail probability
    model._set("A1", "=T.DIST.RT(2, 10)");

    // Wrong number of arguments
    model._set("A2", "=T.DIST.RT(2)");
    model._set("A3", "=T.DIST.RT(2, 10, TRUE)");

    // Domain error: df < 1
    model._set("A4", "=T.DIST.RT(2, 0)");
    model._set("A5", "=T.DIST.RT(2, -1)");

    model.evaluate();

    assert_eq!(model._get_text("A1"), *"0.036694017");

    assert_eq!(model._get_text("A2"), *"#ERROR!");
    assert_eq!(model._get_text("A3"), *"#ERROR!");
    assert_eq!(model._get_text("A4"), *"#NUM!");
    assert_eq!(model._get_text("A5"), *"#NUM!");
}

#[test]
fn test_fn_t_dist_2t_smoke() {
    let mut model = new_empty_model();

    // Valid: two-tailed probability
    model._set("A1", "=T.DIST.2T(2, 10)");

    // In the limit case of x = 0, the two-tailed probability is 1.0
    model._set("A4", "=T.DIST.2T(0, 10)");

    // Wrong number of arguments
    model._set("A2", "=T.DIST.2T(2)");
    model._set("A3", "=T.DIST.2T(2, 10, TRUE)");

    // Domain errors:
    // x < 0 -> #NUM!
    model._set("A5", "=T.DIST.2T(-0.001, 10)");
    // df < 1 -> #NUM!
    model._set("A6", "=T.DIST.2T(2, 0)");

    model.evaluate();

    assert_eq!(model._get_text("A1"), *"0.073388035");
    assert_eq!(model._get_text("A4"), *"1");

    assert_eq!(model._get_text("A2"), *"#ERROR!");
    assert_eq!(model._get_text("A3"), *"#ERROR!");
    assert_eq!(model._get_text("A5"), *"#NUM!");
    assert_eq!(model._get_text("A6"), *"#NUM!");
}

#[test]
fn test_fn_t_inv_smoke() {
    let mut model = new_empty_model();

    // Valid: upper and lower tail
    model._set("A1", "=T.INV(0.95, 10)");
    model._set("A2", "=T.INV(0.05, 10)");
    // limit case:
    model._set("B2", "=T.INV(0.95, 1)");

    // Wrong number of arguments
    model._set("A3", "=T.INV(0.95)");
    model._set("A4", "=T.INV(0.95, 10, 1)");

    // Domain errors:
    // p <= 0 or >= 1
    model._set("A5", "=T.INV(0, 10)");
    model._set("A6", "=T.INV(1, 10)");
    // df < 1
    model._set("A7", "=T.INV(0.95, 0)");

    model.evaluate();

    assert_eq!(model._get_text("A1"), *"1.812461123");
    assert_eq!(model._get_text("A2"), *"-1.812461123");
    assert_eq!(model._get_text("B2"), *"6.313751515");

    assert_eq!(model._get_text("A3"), *"#ERROR!");
    assert_eq!(model._get_text("A4"), *"#ERROR!");
    assert_eq!(model._get_text("A5"), *"#NUM!");
    assert_eq!(model._get_text("A6"), *"#NUM!");
    assert_eq!(model._get_text("A7"), *"#NUM!");
}

#[test]
fn test_fn_t_inv_2t_smoke() {
    let mut model = new_empty_model();

    // Valid: two-tailed critical values
    model._set("A1", "=T.INV.2T(0.1, 10)");
    model._set("A2", "=T.INV.2T(0.05, 10)");

    // p = 1 should give t = 0 (both tails outside are 1.0, so cut at the mean)
    model._set("A3", "=T.INV.2T(1, 10)");

    model._set("A7", "=T.INV.2T(1.5, 10)");

    // Wrong number of arguments
    model._set("A4", "=T.INV.2T(0.1)");
    model._set("A5", "=T.INV.2T(0.1, 10, 1)");

    // Domain errors:
    // p <= 0 or p > 1
    model._set("A6", "=T.INV.2T(0, 10)");
    // df < 1
    model._set("A8", "=T.INV.2T(0.1, 0)");

    model.evaluate();

    assert_eq!(model._get_text("A1"), *"1.812461123");
    assert_eq!(model._get_text("A2"), *"2.228138852");
    assert_eq!(model._get_text("A3"), *"0");

    // NB: Excel returns -0.699812061 for T.INV.2T(1.5, 10)
    // which seems inconsistent with its documented behavior
    assert_eq!(model._get_text("A7"), *"#NUM!");

    assert_eq!(model._get_text("A4"), *"#ERROR!");
    assert_eq!(model._get_text("A5"), *"#ERROR!");
    assert_eq!(model._get_text("A6"), *"#NUM!");
    assert_eq!(model._get_text("A8"), *"#NUM!");
}