diff --git a/python-68min-analysis-stdout.txt b/python-68min-analysis-stdout.txt
new file mode 100644
index 0000000..2333eaa
--- /dev/null
+++ b/python-68min-analysis-stdout.txt
@@ -0,0 +1,6009 @@
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+4071.4395051 to_tfame 0.3.72-rc.7 1078 (cursor = 1235952)
+4072.11916399 to_tfame 0.3.72-rc.7 1079 (cursor = 1235980)
+4072.83379316 to_tfame 0.3.72-rc.7 1080 (cursor = 1235982)
+4073.50870109 to_tfame 0.3.72-rc.7 1081 (cursor = 1235995)
+4074.19163704 to_tfame 0.3.72-rc.7 1082 (cursor = 1236011)
+4074.87703609 to_tfame 0.3.72-rc.7 1083 (cursor = 1236086)
+4075.58691907 to_tfame 0.3.72-rc.7 1084 (cursor = 1236154)
+4076.32174015 to_tfame 0.3.72-rc.7 1085 (cursor = 1236177)
+4077.06187916 to_tfame 0.3.72-rc.7 1086 (cursor = 1236190)
+4077.786659 to_tfame 0.3.72-rc.7 1087 (cursor = 1236205)
+4078.52727818 to_tfame 0.3.72-rc.7 1088 (cursor = 1236219)
+4079.27218604 to_tfame 0.3.72-rc.7 1089 (cursor = 1236260)
+4080.03270602 to_tfame 0.3.72-rc.7 1090 (cursor = 1236291)
+4080.80027103 to_tfame 0.3.72-rc.7 1091 (cursor = 1236394)
+4081.54427314 to_tfame 0.3.72-rc.7 1092 (cursor = 1236431)
+4082.26296806 to_tfame 0.3.72-rc.7 1093 (cursor = 1236434)
+4083.00531197 to_tfame 0.3.72-rc.7 1094 (cursor = 1236443)
+4083.80027103 to_tfame 0.3.72-rc.7 1095 (cursor = 1236447)
+4084.54927397 to_tfame 0.3.72-rc.7 1096 (cursor = 1236482)
+4085.27251816 to_tfame 0.3.72-rc.7 1097 (cursor = 1236487)
+4085.98719311 to_tfame 0.3.72-rc.7 1098 (cursor = 1236517)
+4086.77543807 to_tfame 0.3.72-rc.7 1099 (cursor = 1236522)
+4087.52675414 to_tfame 0.3.72-rc.7 1100 (cursor = 1236528)
+4089.26303911 finished
diff --git a/python-68min-analysis-the-function.py b/python-68min-analysis-the-function.py
new file mode 100644
index 0000000..80320ae
--- /dev/null
+++ b/python-68min-analysis-the-function.py
@@ -0,0 +1,55 @@
+
+def to_tframe(version, df, trades, start):
+    d = {'bid': {}, 'ask': {}}
+    cursor = 0
+    n = 0
+    n_periods = 40
+    xs = np.concatenate([periods(n_periods)[:0:-1] * -1, periods(n_periods)]) * 1000000 # mult to convert to nanos
+    mask = df['version'] == version
+    my_trades = sorted(list(zip(df.loc[mask].index.values.astype(np.int64), df.loc[mask, 'side'], df.loc[mask, 'gid'])))
+    idx = trades.index.values.astype(np.int64)
+    amts = trades['amount']
+    totals = trades['total']
+    assert len(idx) == len(amts)
+    assert len(idx) == len(totals)
+    for tm, side, gid in my_trades:
+        print '{} to_tfame {} {} (cursor = {})'.format(time.time() - start, version, n, cursor)
+        min_time = tm + xs[0]
+        max_time = tm + xs[1]
+        if idx[cursor] > min_time:
+            print 'warning: idx[cursor] ({}) > min_time ({})'.format(idx[cursor], min_time)
+            while idx[cursor] > min_time and cursor > 0:
+                cursor -= 1
+        else:
+            while idx[cursor] < min_time and cursor < len(idx) - 1:
+                cursor += 1
+        i = 1
+        j = cursor
+        d[side][gid] = {}
+        while i < len(xs) - 1:
+            wsum = 0.0
+            w = 0.0
+            while idx[j] < max_time:
+                wsum += totals[j]
+                w += amts[j]
+                j += 1
+            if w > 0.0:
+                d[side][gid][xs[i]] = wsum / w
+            else:
+                d[side][gid][xs[i]] = np.nan
+            i += 1
+            min_time = max_time
+            max_time = tm + xs[i]
+        n += 1
+    d['bid'] = sort_cols(pd.DataFrame.from_dict(d['bid'], orient='index'))
+    d['ask'] = sort_cols(pd.DataFrame.from_dict(d['ask'], orient='index'))
+    return d
+
+
+# code used to perform `to_tframe` on all versions:
+
+start = time.time()
+tresults = {}
+for version in version_counts.index:
+    tresults[version] = to_tframe(version, df, trades, start)
+print '{} finished'.format(time.time() - start)
diff --git a/time_explorer_first_pass.rs b/time_explorer_first_pass.rs
new file mode 100644
index 0000000..c1f31c4
--- /dev/null
+++ b/time_explorer_first_pass.rs
@@ -0,0 +1,422 @@
+#![allow(unused_imports)]
+
+#[macro_use] extern crate serde_derive;
+
+//extern crate decimal;
+extern crate clap;
+extern crate serde;
+extern crate csv;
+extern crate itertools_num;
+
+extern crate map;
+
+use std::str::FromStr;
+use std::time::{Instant, Duration};
+use std::{fs, io};
+use std::str::from_utf8;
+use std::error::Error;
+use itertools_num::linspace;
+use map::Map;
+
+const N: usize = 128;
+const LOGSPACE: [i64; 128] =
+    [-2134300000000, -1854700000000, -1611800000000, -1400600000000,
+     -1217200000000, -1057700000000,  -919200000000,  -798800000000,
+      -694100000000,  -603200000000,  -524200000000,  -455500000000,
+      -395800000000,  -344000000000,  -298900000000,  -259700000000,
+      -225700000000,  -196100000000,  -170400000000,  -148100000000,
+      -128700000000,  -111800000000,   -97200000000,   -84400000000,
+       -73400000000,   -63800000000,   -55400000000,   -48100000000,
+       -41800000000,   -36300000000,   -31600000000,   -27400000000,
+       -23800000000,   -20700000000,   -18000000000,   -15600000000,
+       -13600000000,   -11800000000,   -10200000000,    -8900000000,
+        -7700000000,    -6700000000,    -5800000000,    -5000000000,
+        -4400000000,    -3800000000,    -3300000000,    -2900000000,
+        -2500000000,    -2100000000,    -1900000000,    -1600000000,
+        -1400000000,    -1200000000,    -1000000000,     -900000000,
+         -800000000,     -700000000,     -600000000,     -500000000,
+         -400000000,     -300000000,     -200000000,     -100000000,
+          100000000,      200000000,      300000000,      400000000,
+          500000000,      600000000,      700000000,      800000000,
+          900000000,     1000000000,     1200000000,     1400000000,
+         1600000000,     1900000000,     2100000000,     2500000000,
+         2900000000,     3300000000,     3800000000,     4400000000,
+         5000000000,     5800000000,     6700000000,     7700000000,
+         8900000000,    10200000000,    11800000000,    13600000000,
+        15600000000,    18000000000,    20700000000,    23800000000,
+        27400000000,    31600000000,    36300000000,    41800000000,
+        48100000000,    55400000000,    63800000000,    73400000000,
+        84400000000,    97200000000,   111800000000,   128700000000,
+       148100000000,   170400000000,   196100000000,   225700000000,
+       259700000000,   298900000000,   344000000000,   395800000000,
+       455500000000,   524200000000,   603200000000,   694100000000,
+       798800000000,   919200000000,  1057700000000,  1217200000000,
+      1400600000000,  1611800000000,  1854700000000,  2134300000000];
+
+#[derive(Deserialize)]
+struct Trade { //<'a> {
+    pub time: i64,
+    //pub exch: &'a str,
+    pub price: f64,
+    pub amount: f64,
+}
+
+/// Use this to deserialize just the time column on the first pass through
+/// the events file.
+#[derive(Deserialize)]
+struct EventTime {
+    pub time: i64,
+}
+
+struct Event {
+    pub time: i64,
+    //pub meta: Vec<&'a str>,
+    //pub meta: &'a csv::StringRecord,
+    pub data: Vec<f64>,
+}
+
+pub fn seconds(d: Duration) -> f64 {
+    d.as_secs() as f64 + (d.subsec_nanos() as f64 / 1_000_000_000_f64)
+}
+
+fn main() -> Result<(), Box<Error>> {
+    let start = Instant::now();
+    let args: clap::ArgMatches = clap::App::new("time-explorer")
+        .version("0.1")
+        .arg(clap::Arg::with_name("trades")
+             .long("trades-csv")
+             .short("t")
+             .help("Path of csv with time (integer nanoseconds timestamp), \
+                    price (f64), and amount (f64) columns.")
+             .takes_value(true)
+             .required(true))
+        .arg(clap::Arg::with_name("events")
+             .long("events-csv")
+             .short("e")
+             .help("Path of csv file with a time (integer nanoseconds timestamp) as column 0, \
+                    along with any other metadata columns that will be included in results")
+             .takes_value(true)
+             .required(true))
+        .arg(clap::Arg::with_name("output")
+             .long("output-file")
+             .short("o")
+             .help("Path to save results csv to")
+             .takes_value(true)
+             .required(true))
+        .arg(clap::Arg::with_name("verbose")
+             .long("verbose")
+             .short("v"))
+        .arg(clap::Arg::with_name("n-periods")
+             .long("n-periods")
+             .short("n")
+             .help("Controls how many time buckets are evaluated")
+             .takes_value(true)
+             .default_value("50"))
+        .get_matches();
+
+    //assert_eq!(N, LOGSPACE.len());
+
+    let verbose = args.is_present("verbose");
+
+    if verbose { println!("{:>8.2}s reading...", seconds(Instant::now() - start)); }
+
+    let trades_csv = args.value_of("trades").unwrap();
+    let events_csv = args.value_of("events").unwrap();
+    let output = args.value_of("output").unwrap();
+    let n: &str = args.value_of("n-periods").unwrap();
+    let n: usize = usize::from_str(n)?;
+    //println!("{:>8.2s} opening files...", seconds(Instant::now() - start));
+    let trades_csv =
+        fs::OpenOptions::new()
+            .read(true)
+            .open(trades_csv)?;
+
+    let mut trades: Vec<Trade> =
+        csv::Reader::from_reader(trades_csv)
+            .deserialize()
+            .map(|x| x.unwrap())
+            .collect();
+
+    //println!("{:>8.2} sorting trades...", seconds(Instant::now() - start));
+    trades.sort_by_key(|k| k.time);
+
+    // for i in 1..(trades.len() - 1) {
+    //     assert!(trades[i].time >= trades[i-1].time);
+    // }
+
+    //println!("{:>8.2}s arranging in columnar format...", seconds(Instant::now() - start));
+
+    let mut times: Vec<i64> = Vec::with_capacity(trades.len());
+    //let mut prices: Vec<f64> = Vec::with_capacity(trades.len());
+    let mut amounts: Vec<f64> = Vec::with_capacity(trades.len());
+    let mut totals: Vec<f64> = Vec::with_capacity(trades.len());
+
+    for Trade { time, price, amount } in trades {
+        times.push(time);
+        totals.push(price * amount);
+        amounts.push(amount);
+    }
+
+    // let mut headers = csv::ByteRecord::new();
+    // rdr.read_byte_record(&mut headers)?;
+    // assert!(&headers.as_slice()[headers.range(0).unwrap()] == b"time");
+    // let mut record = csv::ByteRecord::new();
+
+    //let headers = rdr.headers()?;
+    //assert_eq!(headers.get(0), Some("time"));
+
+    let mut events: Vec<Event> = {
+        let events_csv =
+            fs::OpenOptions::new()
+                .read(true)
+                .open(events_csv)?;
+
+        csv::Reader::from_reader(events_csv)
+            .deserialize()
+            .map(|t: Result<EventTime, _>| {
+                let EventTime { time } = t.unwrap();
+                //let data = [0.0; N - 1];
+                let data = vec![0.0; n - 1];
+                Event { time, data }
+            }).collect()
+    };
+    //while rdr.read_byte_record(&mut record)? {
+
+    /*
+    for record in rdr.records() {
+        let meta = record?;
+        //let time = i64::from_str(from_utf8(&record[0])?)?;
+        let time = i64::from_str(&meta[0])?;
+        // let meta =
+        //     record.iter()
+        //         .skip(1)
+        //         //.map(|x| x.deserialize().unwrap())
+        //         .collect();
+        let data = [0.0; N - 1];
+        events.push(Event { time, data });
+    }
+    */
+
+    assert!(!events.is_empty());
+
+    // for i in 1..(events.len() - 1) {
+    //     assert!(events[i].time >= events[i-1].time);
+    // }
+
+    events.sort_by_key(|k| k.time);
+    //println!("events[0].time={}, LOGSPACE[0]={}, events[0].time + LOGSPACE[0]={}", 
+    //         events[0].time, LOGSPACE[0], events[0].time + LOGSPACE[0]);
+    let mut cursor: usize = 0;
+    let mut truncate_events = None;
+
+    let buckets: Vec<i64> =
+        linspace(LOGSPACE[0] as f64, LOGSPACE[N - 1] as f64, n)
+            .map(|x| x as i64)
+            .collect();
+    
+    if verbose { println!("{:>8.2}s calculating...", seconds(Instant::now() - start)); }
+
+    'a: for (i, event) in events.iter_mut().enumerate() {
+        //let mut min_time: i64 = event.time + LOGSPACE[0];
+        //let mut max_time: i64 = event.time + LOGSPACE[1];
+
+        let mut min_time: i64 = event.time + buckets[0];
+        let mut max_time: i64 = event.time + buckets[1];
+
+
+        /*
+        let n_nan = event.data.iter().filter(|x| !x.is_finite()).count();
+        println!("{:>8.2} event {:>5} {:>8.2}, {:>8.2}, {:>8.2}, ...  min_time={}, max_time={}, \
+                  cursor={}, j={}, times[cursor]={}, times[j]={}, n_nan={}, max_time-min_time={}", seconds(Instant::now() - start), i,
+                 event.data[0], event.data[10], event.data[100], min_time, max_time, cursor,
+                 "_", times[cursor], "_", n_nan, max_time-min_time);
+
+        println!();
+        */
+
+        // find the beginning if there are gaps
+        'b: while times[cursor] < min_time {
+            if cursor >= times.len() - 1 {
+                truncate_events = Some(i);
+                break 'a
+            } else {
+                cursor += 1
+            }
+        }
+
+        let mut j: usize = cursor;
+
+        'c: for k in 0..(n - 2) {
+            let mut wsum: f64 = 0.0;
+            let mut w: f64 = 0.0;
+
+            'd: while j < times.len() - 1 && times[j] < max_time {
+                wsum += totals[j];
+                w += amounts[j];
+                j += 1;
+            }
+
+            if w > 0.0 {
+                event.data[k] = wsum / w;
+            } else {
+                event.data[k] = ::std::f64::NAN;
+            }
+
+            /*
+            let n_nan = event.data.iter().filter(|x| !x.is_finite()).count();
+            println!("{:>8.2} event {:>5} {:>8.2}, {:>8.2}, {:>8.2}, ...  min_time={}, max_time={}, \
+                      cursor={}, j={}, times[cursor]={}, times[j]={}, n_nan={}, max_time-min_time={} \
+                      wsum={:.3}, w={:.3}", seconds(Instant::now() - start), i,
+                     event.data[0], event.data[10], event.data[100], min_time, max_time, cursor,
+                     j, times[cursor], times[j], n_nan, max_time-min_time, wsum, w);
+            */
+
+            min_time = max_time;
+            max_time = event.time + buckets[k + 2];
+
+            //println!("{:>8.2} event {:>5} {:>8.2}, {:>8.2}, {:>8.2}, ...  min_time={}, max_time={}, \
+            //          cursor={}, j={}, times[cursor]={}, n_nan={}, max_time-min_time={}", seconds(Instant::now() - start), i,
+            //         event.data[0], event.data[10], event.data[100], min_time, max_time, cursor,
+            //         j, times[cursor], n_nan, max_time-min_time);
+
+        }
+
+        /*
+        let n_nan = event.data.iter().filter(|x| !x.is_finite()).count();
+        println!("{:>8.2} event {:>5} {:>8.2}, {:>8.2}, {:>8.2}, ...  min_time={}, max_time={}, \
+                  cursor={}, j={}, times[cursor]={}, times[j]={}, n_nan={}, max_time-min_time={}", seconds(Instant::now() - start), i,
+                 event.data[0], event.data[10], event.data[100], min_time, max_time, cursor,
+                 j, times[cursor], times[j], n_nan, max_time-min_time);
+        println!();
+        */
+
+
+        if i % 100 == 0 {
+            assert!(max_time > min_time);
+            if verbose {
+                //let n_nan = event.data.iter().filter(|x| !x.is_finite()).count();
+                println!("{:>8.2}s     No. {:>5} {:>12.2}, {:>12.2}, {:>12.2}, {:>12.2}, {:>12.2}, {:>12.2}  ...",
+                          //cursor={}, j={}, times[cursor]={}, n_nan={}, max_time-min_time={}",
+                          seconds(Instant::now() - start), i,
+                         event.data[0], event.data[20], event.data[40], event.data[60], event.data[80], event.data[100]);
+                         //min_time, max_time, cursor,
+                         //j, times[cursor], n_nan, max_time-min_time);
+            }
+        }
+    }
+
+    assert!(truncate_events.is_none()); // for now
+
+    if verbose { println!("{:>8.2} writing...", seconds(Instant::now() - start)); }
+
+    // we have to read this again because I could not figure out ownership problems
+    let events_csv =
+        fs::OpenOptions::new()
+            .read(true)
+            .open(events_csv)?;
+
+    let mut events_csv = csv::Reader::from_reader(events_csv);
+
+    let output_csv =
+        fs::OpenOptions::new()
+            .write(true)
+            .create(true)
+            .truncate(true)
+            .open(output)?;
+
+    let mut wtr = csv::Writer::from_writer(output_csv);
+
+    let data_cols: Vec<i64> = {
+        let mut xs = vec![0; n - 1];
+        for i in 0..(n - 1) {
+            //xs[i] = ((LOGSPACE[i] + LOGSPACE[i + 1]) as f64 / 2.0) as i64;
+            xs[i] = (buckets[i] + buckets[i + 1]) / 2;
+        }
+        xs
+    };
+
+    {
+        let headers = events_csv.byte_headers()?;
+        //println!("{:?}", headers);
+        for col in headers.iter() {
+            wtr.write_field(col)?;
+        }
+        for col in data_cols.iter() {
+            wtr.write_field(&format!("{}", col))?;
+        }
+        wtr.write_record(None::<&[u8]>)?;
+    }
+
+    let mut record = csv::ByteRecord::new();
+
+    for event in events {
+        if !events_csv.read_byte_record(&mut record)? { panic!("failed to read from events csv") }
+        for meta in record.iter() {
+            wtr.write_field(meta)?;
+        }
+        for val in event.data.iter() {
+            wtr.write_field(&format!("{}", val))?;
+        }
+        wtr.write_record(None::<&[u8]>)?;
+    }
+
+
+    if verbose { println!("{:>8.2} finished.", seconds(Instant::now() - start)); }
+
+    Ok(())
+}
+
+/*
+def to_tframe(version, df, trades, start):
+    d = {'bid': {}, 'ask': {}}
+    cursor = 0
+    n = 0
+    n_periods = 40
+    xs = np.concatenate([periods(n_periods)[:0:-1] * -1, periods(n_periods)]) * 1000000 # mult to convert to nanos
+    mask = df['version'] == version
+    #my_trades = sorted(list(zip(df.loc[mask].index, df.loc[mask, 'side'], df.loc[mask, 'gid'])))
+    my_trades = sorted(list(zip(df.loc[mask].index.values.astype(np.int64), df.loc[mask, 'side'], df.loc[mask, 'gid'])))
+    #idx = trades.index
+    idx = trades.index.values.astype(np.int64)
+    amts = trades['amount']
+    totals = trades['total']
+    assert len(idx) == len(amts)
+    assert len(idx) == len(totals)
+    for tm, side, gid in my_trades:
+        print '{} to_tfame {} {} (cursor = {})'.format(time.time() - start, version, n, cursor)
+        #min_time = tm + timedelta(milliseconds=xs[0])
+        #max_time = tm + timedelta(milliseconds=xs[1])
+        min_time = tm + xs[0]
+        max_time = tm + xs[1]
+        if idx[cursor] > min_time:
+            print 'warning: idx[cursor] ({}) > min_time ({})'.format(idx[cursor], min_time)
+            while idx[cursor] > min_time and cursor > 0:
+                cursor -= 1
+        else:
+            while idx[cursor] < min_time and cursor < len(idx) - 1:
+                cursor += 1
+        i = 1
+        j = cursor
+        d[side][gid] = {}
+        while i < len(xs) - 1:
+            wsum = 0.0
+            w = 0.0
+            while idx[j] < max_time:
+                wsum += totals[j]
+                w += amts[j]
+                j += 1
+            if w > 0.0:
+                d[side][gid][xs[i]] = wsum / w
+            else:
+                d[side][gid][xs[i]] = np.nan
+            i += 1
+            min_time = max_time
+            #max_time = tm + timedelta(milliseconds=xs[i])
+            max_time = tm + xs[i]
+        n += 1
+    d['bid'] = sort_cols(pd.DataFrame.from_dict(d['bid'], orient='index'))
+    d['ask'] = sort_cols(pd.DataFrame.from_dict(d['ask'], orient='index'))
+    #yield (version, d)
+    return d
+*/
+