Fixing all the warnings.

Author: celsisdurham

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "ta-lib-in-rust"
-version = "1.0.4"
+version = "1.0.5"
 edition = "2021"
 description = "A library of technical indicators for financial analysis, similar to TA-Lib"
 authors = ["Celsis Durham <[email protected]>"]

src/indicators/moving_averages/vwap.rs

@@ -48,7 +48,7 @@ pub fn calculate_vwap(df: &DataFrame, lookback: usize) -> PolarsResult<Series> {
 
     // Calculate price * volume (cumulative money flow)
     let mut price_volume = Vec::with_capacity(df.height());
-    for i in 0..df.height() {
+    for (i, _) in typical_prices.iter().enumerate().take(df.height()) {
         price_volume.push(typical_prices[i] * volume.get(i).unwrap_or(0.0));
     }
 
@@ -60,8 +60,8 @@ pub fn calculate_vwap(df: &DataFrame, lookback: usize) -> PolarsResult<Series> {
         let mut cumulative_pv = 0.0;
         let mut cumulative_volume = 0.0;
 
-        for i in 0..df.height() {
-            cumulative_pv += price_volume[i];
+        for (i, &pv) in price_volume.iter().enumerate().take(df.height()) {
+            cumulative_pv += pv;
             cumulative_volume += volume.get(i).unwrap_or(0.0);
 
             if cumulative_volume > 0.0 {
@@ -78,8 +78,8 @@ pub fn calculate_vwap(df: &DataFrame, lookback: usize) -> PolarsResult<Series> {
             let mut window_pv = 0.0;
             let mut window_volume = 0.0;
 
-            for j in start_idx..=i {
-                window_pv += price_volume[j];
+            for (j, &pv) in price_volume.iter().enumerate().take(i + 1).skip(start_idx) {
+                window_pv += pv;
                 window_volume += volume.get(j).unwrap_or(0.0);
             }
 

src/indicators/oscillators/stochastic.rs

@@ -102,7 +102,7 @@ pub fn calculate_stochastic(
     let mut k_values = Vec::with_capacity(df.height());
 
     // Fill initial values with NaN
-    for i in 0..k_period + slowing - 2 {
+    for _i in 0..k_period + slowing - 2 {
         k_values.push(f64::NAN);
     }
 
@@ -133,7 +133,7 @@ pub fn calculate_stochastic(
     let mut d_values = Vec::with_capacity(df.height());
 
     // Fill initial values with NaN
-    for i in 0..k_period + slowing + d_period - 3 {
+    for _i in 0..k_period + slowing + d_period - 3 {
         d_values.push(f64::NAN);
     }
 

src/indicators/volatility/atr.rs

@@ -51,15 +51,15 @@ pub fn calculate_atr(df: &DataFrame, window: usize) -> PolarsResult<Series> {
 
     // Initialize ATR with simple average of first window TR values
     let mut atr = 0.0;
-    for i in 0..window {
-        atr += tr_values[i];
+    for &tr in tr_values.iter().take(window) {
+        atr += tr;
     }
     atr /= window as f64;
     atr_values.push(atr);
 
     // Apply Wilder's smoothing formula: ATR(t) = ((window-1) * ATR(t-1) + TR(t)) / window
-    for i in window..tr_values.len() {
-        atr = ((window as f64 - 1.0) * atr + tr_values[i]) / window as f64;
+    for &tr in tr_values.iter().skip(window) {
+        atr = ((window as f64 - 1.0) * atr + tr) / window as f64;
         atr_values.push(atr);
     }
 

src/indicators/volume/cmf.rs

@@ -66,7 +66,7 @@ pub fn calculate_cmf(df: &DataFrame, window: usize) -> PolarsResult<Series> {
 
     // Calculate Money Flow Multiplier
     let mut money_flow_multipliers = Vec::with_capacity(df.height());
-    for i in 0..df.height() {
+    for (i, _) in high.iter().enumerate().take(df.height()) {
         let high_val = high.get(i).unwrap_or(f64::NAN);
         let low_val = low.get(i).unwrap_or(f64::NAN);
         let close_val = close.get(i).unwrap_or(f64::NAN);
@@ -113,8 +113,7 @@ pub fn calculate_cmf(df: &DataFrame, window: usize) -> PolarsResult<Series> {
         let mut has_nan = false;
 
         // Sum up money flow volumes and volumes over the window
-        for j in i - window..i {
-            let mfv = money_flow_volumes[j];
+        for (j, &mfv) in money_flow_volumes.iter().enumerate().take(i).skip(i - window) {
             let vol = volume.get(j).unwrap_or(f64::NAN);
 
             if mfv.is_nan() || vol.is_nan() {

src/indicators/volume/mfi.rs

@@ -59,7 +59,7 @@ pub fn calculate_mfi(df: &DataFrame, window: usize) -> PolarsResult<Series> {
 
     // Calculate the typical price: (high + low + close) / 3
     let mut typical_prices = Vec::with_capacity(df.height());
-    for i in 0..df.height() {
+    for (i, _) in high.iter().enumerate().take(df.height()) {
         let high_val = high.get(i).unwrap_or(f64::NAN);
         let low_val = low.get(i).unwrap_or(f64::NAN);
         let close_val = close.get(i).unwrap_or(f64::NAN);

src/strategy/daily/multi_indicator_daily_3.rs

@@ -515,7 +515,7 @@ pub fn calculate_performance(
         let price = close.get(i).unwrap_or(0.0);
         let buy_signal = buy_signals[i];
         let sell_signal = sell_signals[i];
-        let position_size = position_sizes[i].min(1.0).max(0.1); // Ensure position size is between 0.1 and 1.0
+        let position_size = position_sizes[i].clamp(0.1, 1.0); // Ensure position size is between 0.1 and 1.0
 
         if buy_signal == 1 {
             // Use position sizing

src/strategy/minute/multi_indicator_minute_2.rs

@@ -354,7 +354,7 @@ pub fn run_strategy(
             // Smaller position for higher volatility
             let base_position = 1.0 / (params.atr_position_size_factor * atr_val / price);
             // Clamp between 0.1 and 1.0
-            base_position.max(0.1).min(1.0)
+            base_position.clamp(0.1, 1.0)
         } else {
             1.0 // Full position if not using ATR sizing
         };