Add total number of elements

Author: peterfication

CHANGELOG.md

@@ -3,6 +3,7 @@
 ## [Unreleased]
 
 - Add byte size
+- Add total number of elements
 
 ## [0.1.1] - 2025-09-12
 

README.md

@@ -55,7 +55,6 @@ just run-float
 
 - Limit showing unique values to 10 values
   - If there are more than 10 values, show the smallest 10 and the highest 10
-- Total Elements
 - Mean, Standard Deviation, Median
 - Different output formats: text, json, ...
 

src/analyze.rs

@@ -16,11 +16,13 @@ pub struct NpyAnalysis {
 #[derive(Debug)]
 pub enum ValueStats {
     F64 {
+        count: usize,
         unique_values: Vec<f64>,
         min: f64,
         max: f64,
     },
     I64 {
+        count: usize,
         unique_values: Vec<i64>,
         min: i64,
         max: i64,
@@ -48,6 +50,7 @@ pub fn analyze_npy(file_path: &str) -> Result<NpyAnalysis, Box<dyn std::error::E
                     if data.is_empty() {
                         None
                     } else {
+                        let count = data.len();
                         let mut unique_numbers: Vec<_> = HashSet::<OrderedFloat<f64>>::from_iter(
                             data.into_iter().map(OrderedFloat),
                         )
@@ -57,6 +60,7 @@ pub fn analyze_npy(file_path: &str) -> Result<NpyAnalysis, Box<dyn std::error::E
 
                         match (unique_numbers.first(), unique_numbers.last()) {
                             (Some(first), Some(last)) => Some(ValueStats::F64 {
+                                count,
                                 min: first.0,
                                 max: last.0,
                                 unique_values: unique_numbers.into_iter().map(|n| n.0).collect(),
@@ -72,11 +76,13 @@ pub fn analyze_npy(file_path: &str) -> Result<NpyAnalysis, Box<dyn std::error::E
                     if data.is_empty() {
                         None
                     } else {
+                        let count = data.len();
                         let mut unique_numbers: Vec<_> =
                             HashSet::<i64>::from_iter(data).into_iter().collect();
                         unique_numbers.sort_unstable();
 
                         Some(ValueStats::I64 {
+                            count,
                             min: *unique_numbers
                                 .first()
                                 .expect("unique_numbers should not be empty due to is_empty check"),

src/present.rs

@@ -17,30 +17,33 @@ pub fn present_analysis(file_path: &str, analysis: &NpyAnalysis) {
 
     match &analysis.stats {
         Some(ValueStats::F64 {
+            count,
             unique_values,
             min,
             max,
         }) => {
-            print_stats(unique_values, min, max);
+            print_stats(count, unique_values, min, max);
         }
         Some(ValueStats::I64 {
+            count,
             unique_values,
             min,
             max,
         }) => {
-            print_stats(unique_values, min, max);
+            print_stats(count, unique_values, min, max);
         }
         None => {
             println!("Unsupported dtype for unique value calculation");
         }
     }
 }
 
-fn print_stats<T, U>(unique_values: &U, min: &T, max: &T)
+fn print_stats<T, U>(count: &usize, unique_values: &U, min: &T, max: &T)
 where
     T: std::fmt::Debug + std::fmt::Display,
     U: std::fmt::Debug + std::ops::Deref<Target = [T]>,
 {
+    println!("Number of values: {count}");
     println!("Number of unique values: {}", unique_values.len());
     println!("Unique values: {unique_values:?}");
     println!("Min value: {min}");

tests/snapshots/cli__cli_run_float.snap

@@ -9,6 +9,7 @@ Shape: [2, 3]
 Type: Float8
 Bytes: 176 B
 ----------------------------------------
+Number of values: 6
 Number of unique values: 6
 Unique values: [1.1, 3.3, 4.2, 8.4, 12.6, 22.5]
 Min value: 1.1

tests/snapshots/cli__cli_run_int.snap

@@ -9,6 +9,7 @@ Shape: [2, 3]
 Type: Int8
 Bytes: 176 B
 ----------------------------------------
+Number of values: 6
 Number of unique values: 6
 Unique values: [1, 3, 4, 8, 12, 22]
 Min value: 1